System

Abstract

An object of a system according to an embodiment is to provide a comfortable work-from-home environment by selecting an optimal aromatic oil based on the work contents and psychological state of a user.SOLUTION: A system includes an interaction part, a selection part, a diffusion part, and a replenishment part. The dialogue unit grasps the work content and psychological state of the user. The selection unit selects an aroma oil based on the work content and the psychological state grasped by the dialogue unit. The diffusion part diffuses the aromatic oil selected by the selection part. The replenishment part periodically replenishes aromatic oil.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] With conventional technology, selecting and managing aromatic oils to improve the comfort of working from home was time-consuming, making it difficult to provide an optimal environment tailored to individual needs.

[0005] The system according to the embodiment aims to provide a comfortable working-from-home environment by selecting the most suitable aroma oil based on the user's work content and psychological state. [Means for solving the problem]

[0006] The system according to the embodiment includes a dialogue unit, a selection unit, a diffusion unit, and a refill unit. The dialogue unit grasps the user's work content and psychological state. The selection unit selects an aroma oil based on the work content and psychological state grasped by the dialogue unit. The diffusion unit diffuses the aroma oil selected by the selection unit. The refill unit periodically replenishes the aroma oil. [Effects of the Invention]

[0007] The system according to the embodiment can select the most suitable aroma oil based on the user's work content and psychological state, providing a comfortable working-from-home environment. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The AI ​​interactive aroma system according to the embodiment of the present invention is a system in which AI understands the user's work content and psychological state through dialogue, selects aroma oils according to the user's needs, and the diffuser automatically produces the optimal scent. This allows the AI ​​interactive aroma system to support work efficiency and wellness.

[0029] An AI interactive aroma system according to an embodiment includes a dialogue unit, a selection unit, a diffusion unit, and a refill unit. The dialogue unit grasps the user's work content and psychological state. For example, if the user says, "I want to concentrate on work today," the dialogue unit understands the user's needs based on that information. Furthermore, if the user wants to relax, the dialogue unit selects an aromatic oil with a relaxing effect based on that information. The selection unit selects an aromatic oil based on the work content and psychological state grasped by the dialogue unit. For example, the selection unit selects an aromatic oil such as rosemary or peppermint if the user wants to improve concentration. Furthermore, the selection unit selects an aromatic oil such as lavender or chamomile, which has a relaxing effect. The diffusion unit diffuses the aromatic oil selected by the selection unit. For example, the diffusion unit uses a diffuser to diffuse the selected aromatic oil in an appropriate amount to optimize the user's work environment. The diffusion unit can also release fragrance at appropriate times. The refill unit periodically replenishes the aromatic oil. For example, the refill unit periodically replenishes aroma oils through a subscription service. The refill unit also delivers aroma oils at optimal times according to the user's usage and needs. This allows the AI ​​interactive aroma system according to the embodiment to support the user's work efficiency and wellness. For example, if a user wants to improve their concentration, the system selects an appropriate aroma oil and the diffuser automatically creates a fragrance, thereby improving work efficiency. Also, if a user wants to relax, the system selects an aroma oil with a relaxing effect and the diffuser diffuses the fragrance, thereby supporting the user's wellness.

[0030] The dialogue unit can analyze the user's past dialogue history and track long-term changes in psychological state. For example, the dialogue unit stores the user's past dialogue history in a database and analyzes long-term changes in psychological state. For example, it tracks increases or decreases in stress from the content of past dialogues and suggests appropriate aroma oils. The dialogue unit can also grasp trends in the user's psychological state based on the past dialogue history. For example, it can identify times when the user wants to relax or concentrate from the past dialogue history and suggest aroma oils that correspond to those times. This makes it possible to grasp long-term changes in the user's psychological state.

[0031] The dialogue unit can analyze the user's facial expression using a camera and grasp the user's psychological state from the visual information. The dialogue unit, for example, uses a camera to analyze the user's facial expression in real time and grasp the user's psychological state from the visual information. For example, if the user is smiling, it can determine that the user is in a positive psychological state and suggest an aroma oil with a refreshing effect. The dialogue unit can also analyze changes in facial expression to grasp the user's psychological state. For example, if the user is frowning, it can determine that the user is feeling stressed and suggest an aroma oil with a relaxing effect. This makes it possible to grasp the user's psychological state with high accuracy from the user's facial expression.

[0032] The dialogue unit can use sensors to acquire the user's heart rate and galvanic skin response and evaluate the user's psychological state from multiple angles. The dialogue unit, for example, uses sensors to acquire the user's heart rate and galvanic skin response in real time and evaluates the user's psychological state from multiple angles. For example, if the heart rate is high, it may determine that stress is high and suggest an aroma oil with a relaxing effect. The dialogue unit can also evaluate the user's psychological state by integrating multiple pieces of biometric information. For example, it may analyze changes in the heart rate and galvanic skin response to comprehensively grasp the user's psychological state. This allows the user's psychological state to be evaluated from multiple angles based on the user's biometric information.

[0033] The selection unit can learn the user's past preference data and select a more personalized aroma oil. The selection unit, for example, learns the user's past aroma oil preference data and selects a more personalized aroma oil. For example, the next selection is made based on the aroma oil that the user has used favorably in the past. The selection unit can also suggest the aroma oil that is best suited to each individual user based on the user's preference data. For example, if the user likes aroma oils that have a relaxing effect, the selection unit will suggest an aroma oil that also has a relaxing effect next time. This allows the aroma oil to be personalized based on the user's past preferences.

[0034] The selection unit can select an aroma oil according to the season and weather. The selection unit selects the optimal aroma oil based on, for example, season and weather data. For example, it can suggest a refreshing scent in summer and a warm scent in winter. The selection unit can also select an aroma oil according to the weather. For example, it can suggest an aroma oil with a refreshing effect on a rainy day. This makes it possible to select an aroma oil according to the season and weather.

[0035] The selection unit can select aroma oils that support overall wellness by taking into account the user's food and drink preferences. The selection unit selects aroma oils that support overall wellness based on, for example, the user's food and drink preference data. For example, the selection unit can suggest aromas that go well with specific ingredients or drinks. The selection unit can also select aroma oils by taking into account the user's food and drink preferences. For example, if the user likes coffee, the selection unit can suggest aroma oils that go well with the aroma of coffee. This makes it possible to select aroma oils that take into account the user's food and drink preferences.

[0036] The selection unit can select an appropriate aroma oil taking into account the user's activity level. For example, the selection unit monitors the user's activity level with a sensor and selects an aroma oil according to the amount of exercise. For example, the selection unit can suggest peppermint, which has a refreshing effect after exercise. The selection unit can also select an aroma oil taking into account the user's activity level. For example, if the user is doing desk work, the selection unit can suggest an aroma oil that improves concentration. This makes it possible to select an aroma oil according to the user's activity level.

[0037] The diffusion unit can adjust the diffusion pattern in accordance with the user's breathing rhythm. For example, the diffusion unit monitors the user's breathing rhythm with a sensor and adjusts the diffusion pattern of the diffuser in real time. For example, it can intensify the fragrance in accordance with deep breathing. The diffusion unit can also adjust the diffusion pattern in accordance with the user's breathing rhythm. For example, it can weaken the diffusion if the breathing is fast and strengthen the diffusion if the breathing is slow. This makes it possible to adjust the diffusion pattern in accordance with the user's breathing rhythm.

[0038] The diffusion unit can optimize the diffusion range according to the layout of the room. For example, the diffusion unit analyzes the layout of the room using a camera and optimizes the diffusion range of the diffuser. For example, the diffusion range is widened in a large room. The diffusion unit can also adjust the diffusion range according to the layout of the room. For example, the diffusion range is changed according to the arrangement of furniture. This makes it possible to optimize the diffusion range according to the layout of the room.

[0039] The diffusion unit can be equipped with a humidifying function to allow the device to be used comfortably even in dry environments. For example, the diffusion unit can be equipped with a humidifying function to allow the device to be used comfortably even in dry environments. For example, it can provide a humidifying effect in a dry room during winter. The diffusion unit can also be equipped with a humidifying function to allow the device to be used comfortably even in dry environments. For example, it can humidify the air to maintain a constant humidity level. This allows the device to be used comfortably even in dry environments.

[0040] The diffusion unit can be equipped with a lighting function to provide a visually relaxing effect along with the fragrance. For example, the diffusion unit can be equipped with a lighting function to provide a visually relaxing effect along with the fragrance. For example, it can be equipped with an LED light that emits soft light. The diffusion unit can also use the lighting function to provide a visually relaxing effect along with the fragrance. For example, the color temperature can be adjusted to enhance the relaxing effect. This allows a visually relaxing effect to be provided along with the fragrance.

[0041] The refilling unit can learn the frequency of use by the user and develop an algorithm that predicts the optimal timing for refilling. The refilling unit can, for example, learn the frequency of use by the user of aroma oils and develop an algorithm that predicts the optimal timing for refilling. For example, it can suggest that a user who uses a lot should refill earlier. The refilling unit can also predict the optimal timing for refilling based on the frequency of use by the user. For example, it can suggest that a user who uses less frequently should refill later. This makes it possible to predict the optimal timing for refilling based on the frequency of use by the user.

[0042] The refill unit can customize the type of refill oil to suit the user's seasonal needs. For example, the refill unit analyzes the user's seasonal needs and customizes the type of refill oil. For example, it may suggest a refreshing scent in summer and a warm scent in winter. The refill unit can also customize the type of refill oil according to the user's seasonal needs. For example, it may suggest a floral scent in spring and a woody scent in autumn. This makes it possible to customize the refill oil according to the user's seasonal needs.

[0043] The refilling unit can add wellness products other than aromatic oils to the subscription service. For example, the refilling unit can add wellness products other than aromatic oils to the subscription service to support overall wellness. For example, the refilling unit can provide herbal teas and skin care products. The refilling unit can also add wellness products other than aromatic oils to the subscription service. For example, the refilling unit can suggest herbal teas and skin care products that have a relaxing effect. This makes it possible to provide wellness products other than aromatic oils.

[0044] The replenishing unit can suggest personalized recipes based on user feedback. The replenishing unit, for example, suggests personalized recipes based on user feedback. For example, it provides an aroma oil blend recipe that matches the user's preferences. The replenishing unit can also suggest personalized recipes based on user feedback. For example, if the user likes recipes that have a relaxing effect, it will suggest a recipe with a relaxing effect next time. This makes it possible to suggest personalized recipes based on user feedback.

[0045] The dialogue unit collects user feedback in real time, allowing the generation AI to select aroma oils and adjust the strength of the fragrance on the spot. The dialogue unit, for example, collects user feedback in real time, allowing the generation AI to select aroma oils and adjust the strength of the fragrance on the spot. For example, if the user provides feedback that the scent is "too strong," the strength of the scent is immediately adjusted. The dialogue unit also allows the generation AI to select aroma oils based on user feedback. For example, if the user prefers aroma oils with a relaxing effect, the generation AI will select an aroma oil with a relaxing effect next time as well. This makes it possible to make real-time adjustments based on user feedback.

[0046] The dialogue unit can analyze the user's long-term usage data and propose the optimal telecommuting environment. The dialogue unit, for example, analyzes the user's long-term usage data and proposes the optimal telecommuting environment. For example, it selects the optimal aroma oil based on past data. The dialogue unit can also propose a telecommuting environment based on the user's long-term usage data. For example, it can propose desk placement and lighting adjustments. This makes it possible to propose the optimal telecommuting environment based on the user's long-term usage data.

[0047] The dialogue unit can make suggestions for furniture arrangement and design when personalizing the telecommuting environment. The dialogue unit, for example, makes suggestions for furniture arrangement and design when personalizing the telecommuting environment. For example, it optimizes the arrangement of desks and chairs. The dialogue unit can also make suggestions for furniture arrangement and design. For example, it can suggest color selection and interior style. This makes it possible to make suggestions for furniture arrangement and design.

[0048] The dialogue unit can make comprehensive suggestions that include adjusting music and lighting when personalizing the telecommuting environment. For example, the dialogue unit can make comprehensive suggestions that include adjusting music and lighting when personalizing the telecommuting environment. For example, it can suggest music and lighting that have a relaxing effect. The dialogue unit can also make comprehensive suggestions that include adjusting music and lighting. For example, it can suggest music that improves concentration and bright lighting. This makes it possible to make comprehensive suggestions that include adjusting music and lighting.

[0049] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0050] The selection unit can learn the user's past preference data and select a more personalized aroma oil. For example, the selection unit can learn the user's past aroma oil preference data and select a more personalized aroma oil. The next selection is made based on the aroma oil that the user has used favorably in the past. The selection unit can also suggest the most suitable aroma oil for each individual user based on the user's preference data. If the user likes aroma oils with a relaxing effect, the selection unit will suggest an aroma oil with a relaxing effect next time as well. This allows the aroma oil to be personalized based on the user's past preferences.

[0051] The selection unit can select aroma oils according to the season and weather. For example, it can select the most suitable aroma oil based on season and weather data. It can suggest a refreshing scent in summer and a warm scent in winter. It can also select aroma oils according to the weather. For example, it can suggest an aroma oil with a refreshing effect on a rainy day. This makes it possible to select aroma oils according to the season and weather.

[0052] The selection unit can select aroma oils that support overall wellness by taking into account the user's food and drink preferences. For example, aroma oils that support overall wellness are selected based on the user's food and drink preference data. Scents that go well with specific ingredients or drinks are suggested. Aroma oils can also be selected by taking into account the user's food and drink preferences. If the user likes coffee, aroma oils that go well with the aroma of coffee are suggested. This makes it possible to select aroma oils that take into account the user's food and drink preferences.

[0053] The diffusion unit can adjust the diffusion pattern to match the user's breathing rhythm. For example, the sensor can monitor the user's breathing rhythm and adjust the diffuser's diffusion pattern in real time. The fragrance can be intensified in response to deep breathing. The diffusion pattern can also be adjusted according to the user's breathing rhythm. If breathing is fast, the diffusion is weakened, and if breathing is slow, the diffusion is strengthened. This makes it possible to adjust the diffusion pattern to match the user's breathing rhythm.

[0054] The diffusion unit can optimize the diffusion range according to the room layout. For example, the room layout can be analyzed using a camera to optimize the diffusion range of the diffuser. The diffusion range can be widened in larger rooms. The diffusion range can also be adjusted according to the room layout. The diffusion range can be changed according to the furniture arrangement. This makes it possible to optimize the diffusion range according to the room layout.

[0055] The processing flow of the first embodiment will be briefly explained below.

[0056] Step 1: The dialogue unit understands the user's work content and psychological state. For example, if the user says, "I want to concentrate on my work today," the dialogue unit understands the user's needs based on that information. Also, if the user wants to relax, the dialogue unit selects an aroma oil with a relaxing effect based on that information. Step 2: The selection unit selects an aroma oil based on the task content and psychological state grasped by the dialogue unit. For example, if you want to improve concentration, you can select aroma oils such as rosemary or peppermint, or aroma oils such as lavender or chamomile that have a relaxing effect. Step 3: The diffusion unit diffuses the aroma oil selected by the selection unit. For example, a diffuser can be used to diffuse the selected aroma oil in the appropriate amount to optimize the user's working environment. It can also release the scent at the appropriate time. Step 4: The refilling unit periodically replenishes the aroma oil. For example, this can be done through a subscription service. The unit also delivers the aroma oil at the optimal time based on the user's usage and needs.

[0057] (Example 2) The AI ​​interactive aroma system according to the embodiment of the present invention is a system in which AI understands the user's work content and psychological state through dialogue, selects aroma oils according to the user's needs, and the diffuser automatically produces the optimal scent. This allows the AI ​​interactive aroma system to support work efficiency and wellness.

[0058] An AI interactive aroma system according to an embodiment includes a dialogue unit, a selection unit, a diffusion unit, and a refill unit. The dialogue unit grasps the user's work content and psychological state. For example, if the user says, "I want to concentrate on work today," the dialogue unit understands the user's needs based on that information. Furthermore, if the user wants to relax, the dialogue unit selects an aromatic oil with a relaxing effect based on that information. The selection unit selects an aromatic oil based on the work content and psychological state grasped by the dialogue unit. For example, the selection unit selects an aromatic oil such as rosemary or peppermint if the user wants to improve concentration. Furthermore, the selection unit selects an aromatic oil such as lavender or chamomile, which has a relaxing effect. The diffusion unit diffuses the aromatic oil selected by the selection unit. For example, the diffusion unit uses a diffuser to diffuse the selected aromatic oil in an appropriate amount to optimize the user's work environment. The diffusion unit can also release fragrance at appropriate times. The refill unit periodically replenishes the aromatic oil. For example, the refill unit periodically replenishes aroma oils through a subscription service. The refill unit also delivers aroma oils at optimal times according to the user's usage and needs. This allows the AI ​​interactive aroma system according to the embodiment to support the user's work efficiency and wellness. For example, if a user wants to improve their concentration, the system selects an appropriate aroma oil and the diffuser automatically creates a fragrance, thereby improving work efficiency. Also, if a user wants to relax, the system selects an aroma oil with a relaxing effect and the diffuser diffuses the fragrance, thereby supporting the user's wellness.

[0059] The dialogue unit can analyze the user's voice tone and speaking speed to estimate the stress level and fatigue level. For example, the dialogue unit can analyze the user's voice tone and speaking speed in real time to estimate the stress level and fatigue level. For example, if the user's voice is high-pitched and fast, it can determine that the user is stressed and suggest an aroma oil that has a relaxing effect. The dialogue unit can also analyze changes in the voice tone and speaking speed to grasp the user's psychological state. For example, if the voice tone is low and slow, it can determine that the user is relaxed and suggest an aroma oil that improves concentration. This makes it possible to grasp the user's stress level and fatigue level with high accuracy.

[0060] The dialogue unit can analyze the user's past dialogue history and track long-term changes in psychological state. For example, the dialogue unit stores the user's past dialogue history in a database and analyzes long-term changes in psychological state. For example, it tracks increases or decreases in stress from the content of past dialogues and suggests appropriate aroma oils. The dialogue unit can also grasp trends in the user's psychological state based on the past dialogue history. For example, it can identify times when the user wants to relax or concentrate from the past dialogue history and suggest aroma oils that correspond to those times. This makes it possible to grasp long-term changes in the user's psychological state.

[0061] The dialogue unit can use the emotion estimation function to analyze the user's emotions in real time and select an aroma oil according to changes in emotions. For example, the dialogue unit can use the emotion estimation function to analyze emotions in real time from the user's facial expressions and voice and select an aroma oil according to changes in emotions. For example, if the user looks sad, the dialogue unit can suggest an aroma oil with a relaxing effect. The dialogue unit can also use the emotion estimation function to grasp changes in the user's emotions in real time. For example, if the user is feeling stressed, the dialogue unit can suggest an aroma oil with a stress-reducing effect. This makes it possible to select an aroma oil according to the user's emotions.

[0062] The dialogue unit can analyze the user's facial expression using a camera and grasp the user's psychological state from the visual information. The dialogue unit, for example, uses a camera to analyze the user's facial expression in real time and grasp the user's psychological state from the visual information. For example, if the user is smiling, it can determine that the user is in a positive psychological state and suggest an aroma oil with a refreshing effect. The dialogue unit can also analyze changes in facial expression to grasp the user's psychological state. For example, if the user is frowning, it can determine that the user is feeling stressed and suggest an aroma oil with a relaxing effect. This makes it possible to grasp the user's psychological state with high accuracy from the user's facial expression.

[0063] The dialogue unit can use sensors to acquire the user's heart rate and galvanic skin response and evaluate the user's psychological state from multiple angles. The dialogue unit, for example, uses sensors to acquire the user's heart rate and galvanic skin response in real time and evaluates the user's psychological state from multiple angles. For example, if the heart rate is high, it may determine that stress is high and suggest an aroma oil with a relaxing effect. The dialogue unit can also evaluate the user's psychological state by integrating multiple pieces of biometric information. For example, it may analyze changes in the heart rate and galvanic skin response to comprehensively grasp the user's psychological state. This allows the user's psychological state to be evaluated from multiple angles based on the user's biometric information.

[0064] The dialogue unit uses the emotion estimation function to adjust music and lighting based on the user's emotions, thereby improving overall comfort. The dialogue unit, for example, uses the emotion estimation function to adjust music and lighting based on the user's emotions. For example, if the user wants to relax, it provides calm music and soft lighting. The dialogue unit can also use the emotion estimation function to adjust the environment according to the user's emotions. For example, if the user wants to concentrate, it provides music that enhances concentration and bright lighting. This makes it possible to adjust music and lighting according to the user's emotions.

[0065] The selection unit can learn the user's past preference data and select a more personalized aroma oil. The selection unit, for example, learns the user's past aroma oil preference data and selects a more personalized aroma oil. For example, the next selection is made based on the aroma oil that the user has used favorably in the past. The selection unit can also suggest the aroma oil that is best suited to each individual user based on the user's preference data. For example, if the user likes aroma oils that have a relaxing effect, the selection unit will suggest an aroma oil that also has a relaxing effect next time. This allows the aroma oil to be personalized based on the user's past preferences.

[0066] The selection unit can select an aroma oil according to the season and weather. The selection unit selects the optimal aroma oil based on, for example, season and weather data. For example, it can suggest a refreshing scent in summer and a warm scent in winter. The selection unit can also select an aroma oil according to the weather. For example, it can suggest an aroma oil with a refreshing effect on a rainy day. This makes it possible to select an aroma oil according to the season and weather.

[0067] The selection unit can use the emotion estimation function to suggest an aroma oil blend based on the user's emotion. The selection unit, for example, uses the emotion estimation function to suggest an aroma oil blend based on the user's emotion. For example, a blend of lavender and chamomile, which have a relaxing effect. The selection unit can also use the emotion estimation function to suggest an aroma oil blend according to the user's emotion. For example, if the user is feeling stressed, the selection unit can suggest an aroma oil blend that has a stress-reducing effect. This makes it possible to blend aroma oils based on the user's emotion.

[0068] The selection unit can select aroma oils that support overall wellness by taking into account the user's food and drink preferences. The selection unit selects aroma oils that support overall wellness based on, for example, the user's food and drink preference data. For example, the selection unit can suggest aromas that go well with specific ingredients or drinks. The selection unit can also select aroma oils by taking into account the user's food and drink preferences. For example, if the user likes coffee, the selection unit can suggest aroma oils that go well with the aroma of coffee. This makes it possible to select aroma oils that take into account the user's food and drink preferences.

[0069] The selection unit can select an appropriate aroma oil taking into account the user's activity level. For example, the selection unit monitors the user's activity level with a sensor and selects an aroma oil according to the amount of exercise. For example, the selection unit can suggest peppermint, which has a refreshing effect after exercise. The selection unit can also select an aroma oil taking into account the user's activity level. For example, if the user is doing desk work, the selection unit can suggest an aroma oil that improves concentration. This makes it possible to select an aroma oil according to the user's activity level.

[0070] The selection unit can use the emotion estimation function to select aroma candles and bath salts based on the user's emotion. For example, the selection unit uses the emotion estimation function to select aroma candles based on the user's emotion. For example, the selection unit can suggest a lavender candle that has a relaxing effect. The selection unit can also use the emotion estimation function to select bath salts based on the user's emotion. For example, the selection unit can suggest bath salts that have a stress-reducing effect. This makes it possible to select aroma candles and bath salts based on the user's emotion.

[0071] The diffusion unit can adjust the diffusion pattern in accordance with the user's breathing rhythm. For example, the diffusion unit monitors the user's breathing rhythm with a sensor and adjusts the diffusion pattern of the diffuser in real time. For example, it can intensify the fragrance in accordance with deep breathing. The diffusion unit can also adjust the diffusion pattern in accordance with the user's breathing rhythm. For example, it can weaken the diffusion if the breathing is fast and strengthen the diffusion if the breathing is slow. This makes it possible to adjust the diffusion pattern in accordance with the user's breathing rhythm.

[0072] The diffusion unit can optimize the diffusion range according to the layout of the room. For example, the diffusion unit analyzes the layout of the room using a camera and optimizes the diffusion range of the diffuser. For example, the diffusion range is widened in a large room. The diffusion unit can also adjust the diffusion range according to the layout of the room. For example, the diffusion range is changed according to the arrangement of furniture. This makes it possible to optimize the diffusion range according to the layout of the room.

[0073] The diffusion unit can use the emotion estimation function to adjust the diffusion intensity according to the user's emotion. The diffusion unit, for example, uses the emotion estimation function to adjust the diffusion intensity according to the user's emotion. For example, if the user wants to relax, the diffusion intensity is increased. The diffusion unit can also use the emotion estimation function to adjust the diffusion intensity according to the user's emotion. For example, if the user is feeling stressed, the diffusion intensity is decreased. This makes it possible to adjust the diffusion intensity according to the user's emotion.

[0074] The diffusion unit can be equipped with a humidifying function to allow the device to be used comfortably even in dry environments. For example, the diffusion unit can be equipped with a humidifying function to allow the device to be used comfortably even in dry environments. For example, it can provide a humidifying effect in a dry room during winter. The diffusion unit can also be equipped with a humidifying function to allow the device to be used comfortably even in dry environments. For example, it can humidify the air to maintain a constant humidity level. This allows the device to be used comfortably even in dry environments.

[0075] The diffusion unit can be equipped with a lighting function to provide a visually relaxing effect along with the fragrance. For example, the diffusion unit can be equipped with a lighting function to provide a visually relaxing effect along with the fragrance. For example, it can be equipped with an LED light that emits soft light. The diffusion unit can also use the lighting function to provide a visually relaxing effect along with the fragrance. For example, the color temperature can be adjusted to enhance the relaxing effect. This allows a visually relaxing effect to be provided along with the fragrance.

[0076] The diffusion unit can use the emotion estimation function to add a music playback function based on the user's emotions. For example, the diffusion unit can use the emotion estimation function to develop a diffuser with a music playback function based on the user's emotions. For example, if the user wants to relax, calm music can be played. The diffusion unit can also use the emotion estimation function to add a music playback function based on the user's emotions. For example, if the user wants to concentrate, music that helps improve concentration can be played. This makes it possible to play music based on the user's emotions.

[0077] The refilling unit can learn the frequency of use by the user and develop an algorithm that predicts the optimal timing for refilling. The refilling unit can, for example, learn the frequency of use by the user of aroma oils and develop an algorithm that predicts the optimal timing for refilling. For example, it can suggest that a user who uses a lot should refill earlier. The refilling unit can also predict the optimal timing for refilling based on the frequency of use by the user. For example, it can suggest that a user who uses less frequently should refill later. This makes it possible to predict the optimal timing for refilling based on the frequency of use by the user.

[0078] The refill unit can customize the type of refill oil to suit the user's seasonal needs. For example, the refill unit analyzes the user's seasonal needs and customizes the type of refill oil. For example, it may suggest a refreshing scent in summer and a warm scent in winter. The refill unit can also customize the type of refill oil according to the user's seasonal needs. For example, it may suggest a floral scent in spring and a woody scent in autumn. This makes it possible to customize the refill oil according to the user's seasonal needs.

[0079] The replenishment unit can use the emotion estimation function to suggest oils based on the user's emotions and adjust the subscription content. The replenishment unit, for example, uses the emotion estimation function to suggest oils based on the user's emotions. For example, it suggests oils that have a relaxing effect. The replenishment unit can also use the emotion estimation function to adjust the subscription content based on the user's emotions. For example, if the user is feeling stressed, it suggests oils that have a stress-reducing effect. This makes it possible to suggest oils and adjust the subscription content based on the user's emotions.

[0080] The refilling unit can add wellness products other than aromatic oils to the subscription service. For example, the refilling unit can add wellness products other than aromatic oils to the subscription service to support overall wellness. For example, the refilling unit can provide herbal teas and skin care products. The refilling unit can also add wellness products other than aromatic oils to the subscription service. For example, the refilling unit can suggest herbal teas and skin care products that have a relaxing effect. This makes it possible to provide wellness products other than aromatic oils.

[0081] The replenishing unit can suggest personalized recipes based on user feedback. The replenishing unit, for example, suggests personalized recipes based on user feedback. For example, it provides an aroma oil blend recipe that matches the user's preferences. The replenishing unit can also suggest personalized recipes based on user feedback. For example, if the user likes recipes that have a relaxing effect, it will suggest a recipe with a relaxing effect next time. This makes it possible to suggest personalized recipes based on user feedback.

[0082] The replenishment unit can use the emotion estimation function to suggest a surprise gift based on the user's emotion. The replenishment unit, for example, uses the emotion estimation function to suggest a surprise gift based on the user's emotion. For example, if the user is feeling stressed, a gift with a relaxing effect is suggested. The replenishment unit can also use the emotion estimation function to suggest a surprise gift based on the user's emotion. For example, if the user wants to relax, a gift with a relaxing effect is suggested. This makes it possible to suggest a surprise gift based on the user's emotion.

[0083] The dialogue unit collects user feedback in real time, allowing the generation AI to select aroma oils and adjust the strength of the fragrance on the spot. The dialogue unit, for example, collects user feedback in real time, allowing the generation AI to select aroma oils and adjust the strength of the fragrance on the spot. For example, if the user provides feedback that the scent is "too strong," the strength of the scent is immediately adjusted. The dialogue unit also allows the generation AI to select aroma oils based on user feedback. For example, if the user prefers aroma oils with a relaxing effect, the generation AI will select an aroma oil with a relaxing effect next time as well. This makes it possible to make real-time adjustments based on user feedback.

[0084] The dialogue unit can analyze the user's long-term usage data and propose the optimal telecommuting environment. The dialogue unit, for example, analyzes the user's long-term usage data and proposes the optimal telecommuting environment. For example, it selects the optimal aroma oil based on past data. The dialogue unit can also propose a telecommuting environment based on the user's long-term usage data. For example, it can propose desk placement and lighting adjustments. This makes it possible to propose the optimal telecommuting environment based on the user's long-term usage data.

[0085] The dialogue unit can use the emotion estimation function to make comprehensive adjustments to the telecommuting environment based on the user's emotions. The dialogue unit, for example, uses the emotion estimation function to make comprehensive adjustments to the telecommuting environment based on the user's emotions. For example, if the user wants to relax, the dialogue unit can adjust the fragrance and lighting. The dialogue unit can also use the emotion estimation function to adjust the telecommuting environment according to the user's emotions. For example, if the user wants to concentrate, the dialogue unit can provide music and fragrance that will help the user concentrate. This makes it possible to make comprehensive adjustments to the telecommuting environment based on the user's emotions.

[0086] The dialogue unit can make suggestions for furniture arrangement and design when personalizing the telecommuting environment. The dialogue unit, for example, makes suggestions for furniture arrangement and design when personalizing the telecommuting environment. For example, it optimizes the arrangement of desks and chairs. The dialogue unit can also make suggestions for furniture arrangement and design. For example, it can suggest color selection and interior style. This makes it possible to make suggestions for furniture arrangement and design.

[0087] The dialogue unit can make comprehensive suggestions that include adjusting music and lighting when personalizing the telecommuting environment. For example, the dialogue unit can make comprehensive suggestions that include adjusting music and lighting when personalizing the telecommuting environment. For example, it can suggest music and lighting that have a relaxing effect. The dialogue unit can also make comprehensive suggestions that include adjusting music and lighting. For example, it can suggest music that improves concentration and bright lighting. This makes it possible to make comprehensive suggestions that include adjusting music and lighting.

[0088] The dialogue unit can use the emotion estimation function to suggest relaxation exercises based on the user's emotions. The dialogue unit, for example, uses the emotion estimation function to suggest relaxation exercises based on the user's emotions. For example, if the user is feeling stressed, yoga or deep breathing exercises can be suggested. The dialogue unit can also use the emotion estimation function to suggest exercises based on the user's emotions. For example, if the user wants to relax, exercises that have a relaxing effect can be suggested. This makes it possible to suggest relaxation exercises based on the user's emotions.

[0089] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0090] The dialogue unit can analyze the user's voice tone and speaking speed to estimate stress levels and fatigue levels. For example, it can analyze the tone and speaking speed of the user's voice in real time to estimate stress levels and fatigue levels. If the user's voice is high-pitched and fast, it can determine that stress is high and suggest aroma oils that have a relaxing effect. It can also analyze changes in voice tone and speed to grasp the user's psychological state. If the voice tone is low and slow, it can determine that the user is relaxed and suggest aroma oils that will help improve concentration. This allows the user's stress levels and fatigue levels to be grasped with high accuracy.

[0091] The dialogue unit can analyze the user's past dialogue history and track long-term changes in their psychological state. For example, it can store the user's past dialogue history in a database and analyze long-term changes in their psychological state. It can track increases or decreases in stress from the content of past dialogues and suggest appropriate aroma oils. It can also grasp trends in the user's psychological state based on the past dialogue history. It can identify times when the user wants to relax or concentrate from the past dialogue history and suggest aroma oils that correspond to those times. This makes it possible to grasp long-term changes in the user's psychological state.

[0092] The dialogue unit can use the emotion estimation function to analyze the user's emotions in real time and select an aroma oil according to changes in emotion. For example, the emotion estimation function can be used to analyze emotions in real time from the user's facial expressions and voice, and an aroma oil according to changes in emotion can be selected. If the user looks sad, an aroma oil with a relaxing effect can be suggested. The emotion estimation function can also be used to grasp changes in the user's emotions in real time. If the user is feeling stressed, an aroma oil with a stress-reducing effect can be suggested. This makes it possible to select an aroma oil according to the user's emotions.

[0093] The dialogue unit can analyze the user's facial expression using a camera and grasp the user's psychological state from the visual information. For example, the camera can be used to analyze the user's facial expression in real time and grasp the user's psychological state from the visual information. If the user is smiling, it can be determined that the user is in a positive psychological state and an aroma oil with a refreshing effect can be suggested. It can also analyze changes in facial expression to grasp the user's psychological state. If the user is frowning, it can be determined that the user is feeling stressed and an aroma oil with a relaxing effect can be suggested. This makes it possible to grasp the user's psychological state from the user's facial expression with high accuracy.

[0094] The dialogue unit can use sensors to acquire the user's heart rate and galvanic skin response and evaluate the psychological state from multiple angles. For example, the sensor can be used to acquire the user's heart rate and galvanic skin response in real time to evaluate the psychological state from multiple angles. If the heart rate is high, it can be determined that stress is high and an aroma oil with a relaxing effect can be suggested. The dialogue unit can also integrate multiple pieces of biometric information to evaluate the psychological state. Changes in the heart rate and galvanic skin response can be analyzed to comprehensively grasp the user's psychological state. This allows the psychological state to be evaluated from multiple angles based on the user's biometric information.

[0095] The selection unit can learn the user's past preference data and select a more personalized aroma oil. For example, the selection unit can learn the user's past aroma oil preference data and select a more personalized aroma oil. The next selection is made based on the aroma oil that the user has used favorably in the past. The selection unit can also suggest the most suitable aroma oil for each individual user based on the user's preference data. If the user likes aroma oils with a relaxing effect, the selection unit will suggest an aroma oil with a relaxing effect next time as well. This allows the aroma oil to be personalized based on the user's past preferences.

[0096] The selection unit can select aroma oils according to the season and weather. For example, it can select the most suitable aroma oil based on season and weather data. It can suggest a refreshing scent in summer and a warm scent in winter. It can also select aroma oils according to the weather. For example, it can suggest an aroma oil with a refreshing effect on a rainy day. This makes it possible to select aroma oils according to the season and weather.

[0097] The selection unit can select aroma oils that support overall wellness by taking into account the user's food and drink preferences. For example, aroma oils that support overall wellness are selected based on the user's food and drink preference data. Scents that go well with specific ingredients or drinks are suggested. Aroma oils can also be selected by taking into account the user's food and drink preferences. If the user likes coffee, aroma oils that go well with the aroma of coffee are suggested. This makes it possible to select aroma oils that take into account the user's food and drink preferences.

[0098] The diffusion unit can adjust the diffusion pattern to match the user's breathing rhythm. For example, the sensor can monitor the user's breathing rhythm and adjust the diffuser's diffusion pattern in real time. The fragrance can be intensified in response to deep breathing. The diffusion pattern can also be adjusted according to the user's breathing rhythm. If breathing is fast, the diffusion is weakened, and if breathing is slow, the diffusion is strengthened. This makes it possible to adjust the diffusion pattern to match the user's breathing rhythm.

[0099] The diffusion unit can optimize the diffusion range according to the room layout. For example, the room layout can be analyzed using a camera to optimize the diffusion range of the diffuser. The diffusion range can be widened in larger rooms. The diffusion range can also be adjusted according to the room layout. The diffusion range can be changed according to the furniture arrangement. This makes it possible to optimize the diffusion range according to the room layout.

[0100] The processing flow of the second embodiment will be briefly explained below.

[0101] Step 1: The dialogue unit understands the user's work content and psychological state. For example, if the user says, "I want to concentrate on my work today," the dialogue unit understands the user's needs based on that information. Also, if the user wants to relax, the dialogue unit selects an aroma oil with a relaxing effect based on that information. Step 2: The selection unit selects an aroma oil based on the task content and psychological state grasped by the dialogue unit. For example, if you want to improve concentration, you can select aroma oils such as rosemary or peppermint, or aroma oils such as lavender or chamomile that have a relaxing effect. Step 3: The diffusion unit diffuses the aroma oil selected by the selection unit. For example, a diffuser can be used to diffuse the selected aroma oil in the appropriate amount to optimize the user's working environment. It can also release the scent at the appropriate time. Step 4: The refilling unit periodically replenishes the aroma oil. For example, this can be done through a subscription service. The unit also delivers the aroma oil at the optimal time based on the user's usage and needs.

[0102] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0103] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0104] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0105] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0106] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0107] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0108] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0109] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0110] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0111] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0112] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0113] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0114] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0115] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0116] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0117] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0118] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0119] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0120] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0121] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0122] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0123] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0124] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0125] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0126] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0127] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0128] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0129] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0130] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0131] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0132] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0133] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0134] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0135] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0136] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0137] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0138] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0139] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0140] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0141] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0142] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0143] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0144] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0145] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0146] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0147] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0148] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0149] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0150] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0151] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0152] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0153] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0154] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0155] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0156] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0157] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0158] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0159] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0160] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0161] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0162] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0163] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0164] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0165] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0166] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0167] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, in order to avoid confusion and to facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0168] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0169] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a dialogue unit that grasps the user's work content and psychological state; a selection unit that selects an aroma oil based on the work content and the psychological state grasped by the dialogue unit; a diffusion unit that diffuses the aroma oil selected by the selection unit; and a refilling unit that periodically replenishes the aroma oil. A system characterized by:

2. The dialogue unit Analyzing the user's emotions in real time and selecting the aroma oil according to the change in the emotions.

2. The system of claim 1.

3. The dialogue unit Using sensors, the user's heart rate and skin electrical response are acquired, and the psychological state is evaluated from multiple angles.

2. The system of claim 1.

4. The selection unit Suggesting a blend of the aroma oils based on the user's emotions 2. The system of claim 1.

5. The diffusion section is The diffusion strength is adjusted according to the user's emotion.

2. The system of claim 1.

6. The replenishing section Providing oil recommendations based on the user's emotions and adjusting subscription content 2. The system of claim 1.

7. The diffusion section is Add a music playback function based on the user's emotions 2. The system of claim 1.

8. The dialogue unit Suggesting relaxation exercises based on the user's emotions 2. The system of claim 1.

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