system

Abstract

We provide the system. [Solution] A data collection means for processing biometric data and voice data obtained from users, A data analysis means that analyzes the aforementioned biometric data and voice data to identify the user's psychological state, An aroma blend generation means that generates an appropriate scent according to the psychological state obtained by the data analysis means, An aroma dispenser means for mixing the aforementioned aroma blend in an appropriate proportion and diffusing it into the surroundings, A feedback means for collecting user feedback based on the effects of the aforementioned fragrance and reflecting it in the next fragrance generation, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, many people are troubled by stress and fatigue, and effective means for maintaining and improving physical and mental health are required. However, it is difficult to provide an appropriate relaxation method according to the state of each individual user, and there is a problem that there is a lack of technology for adjusting and providing scents suitable for individual conditions of users, especially in the approach using smell.

Means for Solving the Problems

[0005] To address this challenge, the present invention provides a system that collects user biometric and voice data, analyzes this data to identify the user's psychological state, and then automatically generates an optimal aroma blend based on the analysis results, which is then effectively diffused into the surrounding environment using an aroma dispenser. Furthermore, it employs a means of providing a customized aroma experience tailored to the user's individual psychological and physiological state by collecting user feedback on the effects of the fragrance and utilizing this feedback for future fragrance adjustments.

[0006] A "user" refers to an individual who uses this system and provides their biometric and voice data.

[0007] "Biometric data" refers to information that indicates the user's physical health status, such as heart rate, body temperature, and respiratory rate, which is acquired through sensors.

[0008] "Audio data" refers to information obtained by recording a user's speech and converting it into text data, and includes content based on conversations and speech.

[0009] "Data collection means" refers to equipment and technologies for acquiring biometric and voice data from users, which enables data acquisition.

[0010] "Data analysis means" refers to analytical devices and software that process acquired biometric and audio data to identify the user's psychological state.

[0011] An "aroma blend generation method" is a method for selecting and generating an aroma combination suitable for a specific user based on data analysis.

[0012] An "aroma dispenser" refers to a device or mechanism that appropriately mixes the generated aroma blend and diffuses it around the user.

[0013] A "feedback mechanism" is a means of collecting feedback from users about the effects of fragrances and incorporating that feedback into future fragrance creation and system adjustments. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units 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), and the like.

[0018] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the 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.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, specific processing 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" related to the technology of this 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 processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention is a system that utilizes a user's biometric and voice data to provide the optimal aroma according to their individual psychological state. This system consists of a user, a terminal, a server, various sensors, an aroma dispenser, and other components. The embodiments are described in detail below in natural language.

[0036] Data collection and analysis

[0037] As the device is worn or carried by the user, sensors acquire biometric data in real time. Audio data is recorded by capturing the user's conversation through the device's microphone and converting it to text. The server receives this collected data and analyzes the text data using natural language processing technology to analyze the user's emotional state. Furthermore, the server evaluates the biometric data using machine learning algorithms to assess the user's health status.

[0038] Aroma blend creation and diffusion

[0039] Based on the analysis results, the server determines an aroma blend suitable for the user's psychological and physical state. Based on this determination, the aroma blend generation system constructs an appropriate fragrance combination and sends it to the terminal. The terminal controls the aroma dispenser, blends the specified aroma oils in the appropriate proportions, and diffuses the fragrance through the diffuser. Through this process, the user can obtain a personalized fragrance experience.

[0040] Feedback and Improvement

[0041] Users provide feedback on the effects of the fragrance. This feedback is collected on the device and the results are sent to the server. The server analyzes the feedback as new data and adjusts and optimizes the system for the next aroma blend generation. This feedback loop allows users to continue enjoying a more effective fragrance experience.

[0042] Specific example

[0043] For example, suppose a user is experiencing high stress levels due to prolonged desk work. In this case, the device analyzes the user's heart rate and voice tone to determine that their stress level is elevated. Based on this, the server generates an aroma blend containing lavender and bergamot, which are known to be effective for relaxation, and the device diffuses it. The user relaxes while inhaling the scent, and their work efficiency improves. Furthermore, they provide feedback on their experience using the scent, which is used to select the next aroma blend.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The device collects the user's biometric data. Specifically, it uses sensors to acquire data such as heart rate, body temperature, and respiratory rate in real time.

[0047] Step 2:

[0048] The device collects the user's voice data. It records conversations through the microphone and converts them to text using speech recognition technology.

[0049] Step 3:

[0050] The device encrypts the biometric and voice data it collects and securely transmits it to the server.

[0051] Step 4:

[0052] The server applies natural language processing techniques to the received audio data to analyze the user's emotional state. Keywords and context from the audio are used for the analysis.

[0053] Step 5:

[0054] The server uses machine learning algorithms to analyze biometric data and evaluate the user's health status and stress level.

[0055] Step 6:

[0056] The server determines the optimal aroma blend based on the analysis results. This includes a process of selecting a combination of aromas that suits the user's psychological and physical state.

[0057] Step 7:

[0058] The server selects an aroma blend and instructs the terminal to specify the required types and proportions of essential oils.

[0059] Step 8:

[0060] The device controls the aroma dispenser and mixes the aroma oils in the specified proportions.

[0061] Step 9:

[0062] The device activates an aroma diffuser, diffusing the selected scent around the user.

[0063] Step 10:

[0064] Users provide feedback about the effects of the fragrance they experienced and input it into the device.

[0065] Step 11:

[0066] The device sends feedback received from the user to a server, accumulating data that can be used in future aroma blend generation processes.

[0067] (Example 1)

[0068] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0069] In today's stressful society, there is a need for relaxation methods tailored to the individual psychological and physical states of each user. However, conventional methods struggle to provide individualized treatment that adapts to each user's condition, making it difficult to offer effective relaxation. In particular, the lack of technology to generate optimal scents by fusing biometric and auditory information makes it difficult to optimize the user experience.

[0070] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0071] In this invention, the server includes information gathering means for processing biometric and voice information acquired from the user, information analysis means for analyzing the biometric and voice information to identify the user's psychological state, and fragrance generation means for generating an optimal fragrance according to the psychological state obtained by the information analysis means. This makes it possible to provide an optimized fragrance for each individual user and realize an effective relaxation experience.

[0072] "Information gathering means" refers to devices and systems for acquiring biometric and voice information from users and processing it.

[0073] "Information analysis means" refers to technology that analyzes collected biometric and audio information to identify the user's psychological state and health status.

[0074] "Fragrance generation means" refers to a device or system for generating the optimal fragrance combination based on the analyzed user's condition.

[0075] "Fragrance diffusion device means" refers to a device or system for blending generated fragrances in appropriate proportions and diffusing them into the environment.

[0076] "Feedback analysis means" refers to technology that collects and analyzes user feedback and incorporates the results into the next fragrance generation process to improve the overall system performance.

[0077] To implement this invention, a system is required that includes a user, a terminal, a server, various sensors, and an aroma dispenser. This system is configured to be attached to or carried by the user in a terminal owned by the user. The terminal includes sensors for acquiring biometric information, collecting data such as heart rate, body temperature, and respiratory rate in real time. Voice information is recorded by recording the user's conversation through a microphone mounted on the terminal and converted into text using speech recognition software.

[0078] The biometric and voice information collected by the device is sent to the server. The server receives this information and uses natural language processing technology to analyze the user's emotional state. For example, the server has a built-in generative AI model that determines the user's stress level and psychological tendencies from their voice. An example of a prompt used for voice analysis would be, "Please suggest the most suitable relaxation aroma based on the user's heart rate and voice data."

[0079] Based on the information analyzed by the server, an optimal aroma blend is generated for the user's psychological and health state. The selected aroma blend information is sent to the terminal, which controls the aroma dispenser. The dispenser, following the received instructions, blends the aroma oils in the appropriate proportions and diffuses the scent using a diffuser. This allows the user to receive a customized fragrance experience.

[0080] User feedback is sent to the server via the terminal. This feedback is used to optimize future fragrance generation and the overall system. For example, if a user who has accumulated stress from long hours of desk work shows an increased heart rate or a loud voice, it is possible to generate an aroma blend containing lavender and bergamot, which are suitable for relaxation, and diffuse it through a dispenser to help the user relax.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The device uses sensors to collect biometric information.

[0084] Input: Real-time data such as the user's heart rate, body temperature, and respiratory rate.

[0085] Data processing: Analog signals from sensors are converted into digital data, and smoothing and filtering are performed as needed.

[0086] Output: Formatted biometric data set.

[0087] Specific operation: Biometric data is captured every second, buffered within the device, and prepared for the next processing step at regular intervals.

[0088] Step 2:

[0089] The device records the user's voice through the microphone and converts it to text.

[0090] Input: User's voice signal.

[0091] Data processing: Convert audio signals into text data using speech recognition software.

[0092] Output: Audio data in text format.

[0093] Specific operation: Noise is removed from the audio signal using a feature extraction technique, and the audio is converted to text using a language model.

[0094] Step 3:

[0095] The server receives biometric and voice information transmitted from the terminal and performs analysis.

[0096] Input: Biometric data and text data transmitted from the device.

[0097] Data Processing: We analyze text data using natural language processing techniques to determine the user's emotional state. We also analyze biometric data using machine learning algorithms.

[0098] Output: Data representing the user's psychological and physical state.

[0099] Specific operation: A generative AI model on the server performs sentiment analysis on the speech-to-text data and calculates a health status score based on biometric data.

[0100] Step 4:

[0101] The server determines the optimal aroma blend based on the analysis results.

[0102] Input: Analyzed user psychological and health status data.

[0103] Data processing: Use prompt statements to instruct the generation AI model to create aroma blends.

[0104] Output: Aroma blend recipe information.

[0105] Specific operation: The server selects a combination of aroma oils from several options that is suitable for a specific emotional state and sends the information to the terminal.

[0106] Step 5:

[0107] The device controls the aroma dispenser to diffuse the fragrance.

[0108] Input: Aroma blend recipe information sent from the server.

[0109] Data processing: Generates control signals to blend essential oils in specified proportions.

[0110] Output: A scent of a carefully adjusted aroma blend.

[0111] Specific operation: The aroma dispenser mixes a specified amount of aroma oil and diffuses the scent around the user through the diffuser.

[0112] Step 6:

[0113] We collect feedback from users about their fragrance experience.

[0114] Input: User feedback information.

[0115] Data processing: The feedback data is formatted as reference information for the next aroma blend generation.

[0116] Output: Feedback data for analysis.

[0117] Specific operation: The user fills out an evaluation form on their device, and this information is automatically sent to the server. This data will be used to optimize the system in the future.

[0118] (Application Example 1)

[0119] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0120] In modern brick-and-mortar stores, there are limited ways to understand customers' psychological states and emotions in real time and optimize the store atmosphere accordingly. In particular, it is difficult to instantly provide the appropriate scent when a customer is stressed or seeking relaxation. By solving this problem, we aim to create a more pleasant shopping experience and increase store sales.

[0121] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0122] In this invention, the server includes information gathering means for processing biometric and voice information acquired from the user, information analysis means for analyzing the biometric and voice information to identify the user's emotional state, and fragrance blend generation means for generating an optimal fragrance according to the emotional state obtained by the information analysis means. This makes it possible to automatically select and diffuse an appropriate fragrance according to the customer's emotional state within a physical store.

[0123] "Information gathering means" refers to devices and methods for acquiring and processing biometric and voice information from users.

[0124] "Information analysis means" refers to devices and methods for analyzing acquired biometric and audio information to identify the user's emotional state.

[0125] A "fragrance blend generation method" refers to a device or method for generating the optimal fragrance combination based on the analyzed emotional state of the user.

[0126] A "fragrance diffusion means" refers to a device or method for blending a generated fragrance blend in appropriate proportions and diffusing it into the surrounding environment.

[0127] "Feedback collection means" refers to devices or methods for collecting user feedback based on the effects of fragrances and using that feedback to improve future fragrance creation.

[0128] "Environmental adjustment means" refers to devices or methods for automatically selecting the optimal scent according to the emotional state of customers within a physical store and adjusting the store environment.

[0129] The system implementing this invention will create an optimal purchasing environment by understanding the psychological state of customers in a physical store in real time and automatically providing a corresponding fragrance. Specifically, the following means will be combined.

[0130] The server uses information gathering methods to acquire biometric information from customers' smart devices. For example, data such as heart rate and body temperature are collected through sensors in smartphones and smartwatches. The devices are also equipped with high-quality microphones, which are used to collect audio information of conversations between customers and staff. This data is transmitted to the server via wireless communication technology.

[0131] The server analyzes this data using natural language processing tools (e.g., NLTK and spaCy) and machine learning tools (e.g., TENSORFLOW® and PyTorch) as information analysis tools. It identifies the user's emotional state from biometric and voice information, and the fragrance blend generation mechanism operates based on the analysis results.

[0132] The fragrance blend generation system selects the most suitable fragrance for a given emotional state and distributes the combination from the server to the fragrance diffusion system within the store. Diffusers are placed throughout the store, which then spread the selected fragrance throughout the premises. The diffusers are controlled to blend the fragrances and automatically diffuse them at the appropriate times.

[0133] Furthermore, using a feedback collection system, customers input their impressions and evaluations of the scents they experienced via a terminal, and this feedback is sent to a server so that it can be reflected in future scent selection processes. Through this feedback loop, the system is continuously optimized, and the store's scent environment becomes more tailored to customer needs.

[0134] For example, if the server determines that a customer visiting the store is experiencing stress, the system will select relaxing scents such as lavender or bergamot and diffuse them throughout the store to promote relaxation. An example of a prompt used might be, "Please describe the process of selecting the optimal aroma to reduce stress."

[0135] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0136] Step 1:

[0137] The device acquires biometric information from the customer. Specifically, it measures biometric data such as heart rate and body temperature using a smartphone or smartwatch. This data is transmitted to a server via Bluetooth or Wi-Fi. The input is the customer's biometric information, and the output is the set of biometric data transmitted to the server. The data processing performed in this step is the conversion of analog signals obtained from biosensors into digital data.

[0138] Step 2:

[0139] The terminal records conversations between customers and staff to acquire audio information. It collects audio data using a built-in microphone and converts it into text data. The input is the audio data of the conversation, and the output is the transcribed conversation. The audio data is converted into text by speech recognition software.

[0140] Step 3:

[0141] The server receives biometric data and text data obtained from voice. The server uses natural language processing tools to analyze the emotional state from the text data. The input is text data and biometric data, and the output is the analysis result indicating the customer's emotional state. A generative AI model is used for emotion classification in the data calculations.

[0142] Step 4:

[0143] The server determines the fragrance blend based on the analyzed emotional state. It selects a fragrance combination and sends instructions to the fragrance diffusion system. The input is the result of the emotional analysis, and the output is the fragrance combination. The server uses pre-configured prompt sentences and a generating AI model to select the optimal blend.

[0144] Step 5:

[0145] The terminal controls the diffusers in the store to diffuse the selected fragrance. It adjusts the amount of fragrance released from the diffuser at the appropriate time. The input is information about the fragrance combination, and the output is the actual fragrance that is diffused. The diffuser's operation involves blending and diffusing the fragrance based on the proportions of the selected essential oils.

[0146] Step 6:

[0147] Users input feedback about the scents they experience into a terminal. They input their evaluation of the scent's effects as text and send it to the server. The input is the user's feedback text, and the output is feedback data. The feedback data is used to optimize the future scent selection process.

[0148] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0149] One embodiment of the present invention is an emotion engine that accurately recognizes the user's emotions, and a system that provides an optimal aroma experience based on this engine. This system consists of a user, a terminal, a server, various sensors, an aroma dispenser, and the emotion engine. The embodiments thereof will be described in detail below in natural language.

[0150] Data collection and emotion recognition

[0151] The device connects to the user and acquires biometric data in real time through sensors. This biometric data includes heart rate, body temperature, and respiratory rate. Next, the device collects the user's voice data and records the conversation through a microphone. The voice data is converted into text using natural language processing technology and sent to a server. The server analyzes this text data and biometric data with an emotion engine to comprehensively evaluate the user's emotional state. This engine combines changes in the user's voice tone and biometric indicators to identify a precise emotional state.

[0152] Aroma blend creation and application

[0153] Based on the analysis results from the emotion engine, the server selects the aroma blend best suited to the user's current emotional state. The selected aroma recipe is sent to the terminal, which controls the aroma dispenser to mix the essential oils as instructed. The terminal then diffuses this blended aroma around the user through a diffuser, promoting effects such as relaxation and improved concentration.

[0154] Feedback and adjustments

[0155] Users provide feedback on the effects of the fragrance and input the results into their device. This feedback is collected on the server and, along with analysis by the emotion engine, is used to improve future aroma blend generation. This feedback loop allows the system to continuously improve the fragrance experience delivered to each user, adapting to their individual changes and preferences.

[0156] Specific example

[0157] For example, if a user is feeling nervous before an important presentation, the device detects an increase in heart rate from biometric data and identifies an anxious tone through voice analysis. The emotion engine determines this to be a high-stress state, and the server creates an aroma blend with corresponding relaxation effects. The device diffuses a scent containing lavender and bergamot, allowing the user to feel relaxed. Through this process, the user can approach the presentation in a better state of mind.

[0158] The following describes the processing flow.

[0159] Step 1:

[0160] The device collects biometric data in real time through sensors attached to the user. Specifically, it acquires data such as heart rate, body temperature, and respiratory rate.

[0161] Step 2:

[0162] The device uses its microphone to collect user voice data. It records the user's conversation and converts it to text using speech recognition technology.

[0163] Step 3:

[0164] The biometric and voice data collected by the device are encrypted and sent to the server in a secure manner.

[0165] Step 4:

[0166] The server applies natural language processing to the transmitted audio data and analyzes the user's emotional state from the content of their conversation.

[0167] Step 5:

[0168] The server inputs biometric data into an emotion engine, which analyzes changes in heart rate and body temperature to evaluate the user's stress level and psychological state.

[0169] Step 6:

[0170] Based on the analysis results of the emotion engine, the server determines the optimal aroma blend for the user's current emotional state and sends the recipe to the device.

[0171] Step 7:

[0172] The terminal operates the aroma dispenser, blends the specified aroma oils in the appropriate proportions, and diffuses the scent using a diffuser.

[0173] Step 8:

[0174] Users experience the scent and input feedback about its effects into a device.

[0175] Step 9:

[0176] The device sends user feedback to the server, which is then used as data to adjust the emotion engine's algorithm.

[0177] Step 10:

[0178] The server processes feedback and incorporates it into future aroma blend creation, continuously improving the user experience.

[0179] (Example 2)

[0180] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0181] In recent years, there has been a growing demand for personalized fragrance experiences tailored to the individual user's psychological state. However, conventional systems have struggled to accurately grasp users' emotions and preferences and generate appropriate fragrances. There is a need to solve this problem and provide more precise and individualized fragrance experiences.

[0182] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0183] In this invention, the server includes information acquisition means, information analysis means, and fragrance generation means. This makes it possible to acquire and analyze the user's biometric data and voice data in real time, and to efficiently generate and provide fragrances adapted to the user's emotional state.

[0184] "Information acquisition means" refers to a device or system that provides the function of collecting biometric data and voice data from users in real time.

[0185] "Information analysis means" refers to a device or system that analyzes collected biometric data and voice data and provides a function for evaluating the user's emotional state and psychological state.

[0186] "Fragrance generation means" refers to a device or system for generating an appropriate fragrance based on the user's emotional state obtained through information analysis means.

[0187] A "fragrance diffusion means" is a device or system that provides the function of appropriately blending the generated fragrance and diffusing it into the surroundings.

[0188] "Evaluation means" refers to a device or system that has the function of collecting feedback from users based on the effects of diffused fragrances and reflecting that feedback in the next fragrance generation process.

[0189] The system of the present invention includes information acquisition means, information analysis means, fragrance generation means, fragrance diffusion means, and evaluation means in order to provide a personalized fragrance experience according to the user's psychological state.

[0190] The user connects to various sensors via a terminal, allowing for the real-time collection of biometric data such as heart rate, body temperature, and respiratory rate. The terminal also includes a microphone, collecting the user's voice data. The collected data is transmitted to a server via an information acquisition system. Specific devices used at this stage include standard biosensors and microphones.

[0191] The server processes the acquired biometric and voice data using information analysis tools. It utilizes natural language processing and signal processing technologies to identify the user's emotional state from the data. Specific software examples include voice recognition systems and data analysis algorithms. Based on the analysis results, a fragrance generation tool selects the optimal scent, and the server sends that recipe to the terminal.

[0192] The device controls the fragrance diffusion method based on the received fragrance recipe and diffuses the blended fragrance through the diffuser. The fragrance promotes relaxation and concentration effects that correspond to the user's psychological state.

[0193] Furthermore, users evaluate the effects of the scents they experience and input feedback into their devices. This feedback is collected by the evaluation system and reflected in future scent generation, thereby improving the system's personalization capabilities.

[0194] For example, when a user experiences stress, their heart rate often increases. The device detects this, and the server generates a relaxing blend based on lavender and bergamot. This allows the user to maintain a calmer state.

[0195] An example of input to the generative AI model could be a prompt such as, "Analyze the user's voice data and biometric data to generate the optimal relaxation fragrance blend." Through this prompt, the system can quickly and effectively provide fragrances tailored to the user's specific needs.

[0196] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0197] Step 1:

[0198] The device connects to the user and acquires biometric data in real time through various sensors. Specifically, it collects heart rate, body temperature, and respiratory rate from sensors and processes them as digital signals. This data is then input, and the device sends it to a server for data preparation.

[0199] Step 2:

[0200] The device uses a microphone to record the user's voice data. Speech recognition software is used to convert the recorded data into text, and this converted text data is sent to a server. The input is the user's voice data, and the output is text data. This data serves as preparation data for analyzing the user's linguistic characteristics.

[0201] Step 3:

[0202] The server uses information analysis tools to analyze the received biometric and text data. It employs natural language processing techniques to extract emotional keywords from the text and signal processing techniques to analyze patterns in the biometric data. The input consists of biometric and text data, and the output is an analysis result indicating the user's emotional state. Specifically, the server executes an analysis algorithm to evaluate the psychological state.

[0203] Step 4:

[0204] The server selects an appropriate scent using a fragrance generation system based on the analysis results. Past data and feedback are also considered, so the input consists of the analysis results and existing data such as stress reduction and concentration improvement. The output is the recipe for the selected scent. The server sends this recipe to the terminal.

[0205] Step 5:

[0206] The terminal controls the fragrance diffusion mechanism, operating the aroma dispenser according to the received fragrance recipe to mix the scents. Specifically, the terminal activates the diffuser and diffuses the blended fragrance. The input is the fragrance recipe, and the output is the diffusion of the fragrance.

[0207] Step 6:

[0208] Users input feedback into a terminal based on their fragrance experience. The feedback is analyzed on a server using an evaluation method; therefore, the input is user feedback, and the output is evaluation information that will be reflected in future fragrance creation. Specifically, the terminal sends the feedback to the server in a digital form, where it is recorded in a database.

[0209] (Application Example 2)

[0210] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0211] In today's commercial environment, there is a need for effective methods to respond to the diverse emotional states of customers and promote purchasing activity. Traditional methods have faced challenges in accurately understanding the psychological state of individual customers in real time and providing responsive services accordingly. In particular, while providing experiences using scent has the potential to significantly influence emotions, methods for directly linking them to the customer's state of mind have not been sufficiently developed.

[0212] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0213] In this invention, the server includes information gathering means for processing biometric data and voice data acquired from the user, information analysis means for analyzing the biometric data and voice data to identify the user's emotional state, and fragrance generation means for generating an appropriate fragrance according to the emotional state obtained by the information analysis means. This makes it possible to provide a fragrance experience tailored to the emotional state of each customer visiting a store in a commercial environment, thereby promoting purchasing activity.

[0214] "Information gathering means" refers to a system of devices and software that acquire and process biometric and voice data from users.

[0215] "Information analysis means" refers to technology or software that analyzes collected biometric and audio data to identify the user's emotional state.

[0216] A "fragrance generation means" is a device or system for blending the optimal fragrance according to the emotional state identified by an information analysis means.

[0217] A "fragrance diffusion means" is a mechanism or device that effectively diffuses a blended fragrance into the surrounding space.

[0218] A "feedback collection method" is a system that collects user reactions and evaluations based on the effects of fragrances and uses them to improve future fragrance creation.

[0219] A "commercial environment support device" is a device or system designed to promote purchasing activity by providing an appropriate fragrance experience based on the user's emotional state.

[0220] The system implementing this invention consists of a user, a terminal, a server, various sensors, a fragrance diffusion device, and an information analysis engine. The basic flow is shown below.

[0221] First, the device connects to the user to acquire biometric data. Through sensors, it collects vital data such as heart rate, body temperature, and respiratory rate in real time. Simultaneously, the device uses a microphone to collect the user's voice data, converts this data into text using natural language processing technology, and sends it to the server. The server analyzes the voice data using natural language processing technologies such as Google Cloud Natural Language API and spaCy, and processes the resulting text data and biometric data with an information analysis engine. This analysis identifies the user's emotional state.

[0222] Next, the server determines the most suitable scent for the user's current emotional state based on the results of the information analysis engine. The scent generation device blends the scents based on the identified recipe and sends the instructions to the terminal. The terminal controls the scent diffusion device to appropriately diffuse the required scent into the surrounding space.

[0223] Furthermore, the device collects feedback from users regarding the effects of the fragrance. This feedback is sent to a server and used to adjust the fragrance generation process for the next time. Through this feedback collection mechanism, the system improves its performance to provide the optimal experience for each individual user.

[0224] For example, if a customer is feeling stressed, the device can detect their emotions from their increased heart rate and tone of voice, and then provide a relaxing experience using the scents of lavender and bergamot. This process is expected to increase the customer's willingness to purchase. Examples of prompts include, "What scent would you recommend for relaxation time?" or "How would you describe your mood today in one word?"

[0225] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0226] Step 1:

[0227] The device acquires biometric data (heart rate, body temperature, respiratory rate) from the user through sensors. This data is fundamental information for evaluating the user's emotional state. Data from the sensors is provided as input, and a set of biometric data is stored in the device as output.

[0228] Step 2:

[0229] The device collects the user's voice using a microphone and converts the voice data into text data. This conversion uses the Google Cloud Natural Language API. The input is voice data, and the output is text data. The process involves recognizing the voice and converting it into text.

[0230] Step 3:

[0231] The device sends biometric and text data to the server. This data is received by the server as foundational data for evaluating the user's emotions. The input is a set of biometric and text data, and the output is the transfer of data to the server.

[0232] Step 4:

[0233] The server uses the received biometric and text data to analyze the user's emotional state using an information analysis engine. This analysis also utilizes a generative AI model for data analysis. Biometric and text data are provided as input, and the user's emotional state is identified as output.

[0234] Step 5:

[0235] The server uses a fragrance generation mechanism based on the analysis results to determine the optimal fragrance blend. The results of the data analysis are input into the fragrance generation algorithm, and a fragrance recipe is output. The input is the analyzed emotional state, and the output is the fragrance recipe.

[0236] Step 6:

[0237] The terminal controls the fragrance diffusion device to diffuse the fragrance into the space based on the fragrance recipe received from the server. The fragrance, blended by the fragrance generation means, spreads to the surroundings by the device. The input is the fragrance recipe, and the output is the diffusion of the fragrance.

[0238] Step 7:

[0239] The user inputs feedback on the effects of the fragrance into the terminal. This feedback is sent to the server as data for the next fragrance generation. The input is user feedback information, and the output is data transfer to the server.

[0240] Step 8:

[0241] The server receives feedback from users and incorporates the data into the information analysis engine for the next fragrance generation. This allows the system's fragrance generation method to be improved based on subsequent adjustments. The input is user feedback, and the output is the updated analysis parameters.

[0242] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0243] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0244] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0245] [Second Embodiment]

[0246] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0247] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0248] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0249] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0250] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0251] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0252] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0253] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0254] The specific processing program 56 is an example of a "program" relating to the technology of this 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 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.

[0255] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0256] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0257] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0258] This invention is a system that utilizes a user's biometric and voice data to provide the optimal aroma according to their individual psychological state. This system consists of a user, a terminal, a server, various sensors, an aroma dispenser, and other components. The embodiments are described in detail below in natural language.

[0259] Data collection and analysis

[0260] As the device is worn or carried by the user, sensors acquire biometric data in real time. Audio data is recorded by capturing the user's conversation through the device's microphone and converting it to text. The server receives this collected data and analyzes the text data using natural language processing technology to analyze the user's emotional state. Furthermore, the server evaluates the biometric data using machine learning algorithms to assess the user's health status.

[0261] Aroma blend creation and diffusion

[0262] Based on the analysis results, the server determines an aroma blend suitable for the user's psychological and physical state. Based on this determination, the aroma blend generation system constructs an appropriate fragrance combination and sends it to the terminal. The terminal controls the aroma dispenser, blends the specified aroma oils in the appropriate proportions, and diffuses the fragrance through the diffuser. Through this process, the user can obtain a personalized fragrance experience.

[0263] Feedback and Improvement

[0264] Users provide feedback on the effects of the fragrance. This feedback is collected on the device and the results are sent to the server. The server analyzes the feedback as new data and adjusts and optimizes the system for the next aroma blend generation. This feedback loop allows users to continue enjoying a more effective fragrance experience.

[0265] Specific example

[0266] For example, suppose a user is experiencing high stress levels due to prolonged desk work. In this case, the device analyzes the user's heart rate and voice tone to determine that their stress level is elevated. Based on this, the server generates an aroma blend containing lavender and bergamot, which are known to be effective for relaxation, and the device diffuses it. The user relaxes while inhaling the scent, and their work efficiency improves. Furthermore, they provide feedback on their experience using the scent, which is used to select the next aroma blend.

[0267] The following describes the processing flow.

[0268] Step 1:

[0269] The device collects the user's biometric data. Specifically, it uses sensors to acquire data such as heart rate, body temperature, and respiratory rate in real time.

[0270] Step 2:

[0271] The device collects the user's voice data. It records conversations through the microphone and converts them to text using speech recognition technology.

[0272] Step 3:

[0273] The device encrypts the biometric and voice data it collects and securely transmits it to the server.

[0274] Step 4:

[0275] The server applies natural language processing techniques to the received audio data to analyze the user's emotional state. Keywords and context from the audio are used for the analysis.

[0276] Step 5:

[0277] The server uses machine learning algorithms to analyze biometric data and evaluate the user's health status and stress level.

[0278] Step 6:

[0279] Based on the analysis results, the server determines the optimal aroma blend. This includes the process of selecting an aroma combination suitable for the user's mental state and health condition.

[0280] Step 7:

[0281] The server instructs the terminal about the selected aroma blend and conveys the types and ratios of the required aroma oils.

[0282] Step 8:

[0283] The terminal controls the aroma dispenser and mixes the aroma oils at the instructed ratios.

[0284] Step 9:

[0285] The terminal activates the aroma diffuser and diffuses the selected fragrance around the user.

[0286] Step 10:

[0287] The user provides feedback on the effects of the experienced fragrance and inputs it into the terminal.

[0288] Step 11:

[0289] The terminal transmits the feedback received from the user to the server and accumulates the data for utilization in subsequent aroma blend generation processes.

[0290] (Example 1)

[0291] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0292] In today's stressful society, there is a need for relaxation methods tailored to the individual psychological and physical states of each user. However, conventional methods struggle to provide individualized treatment that adapts to each user's condition, making it difficult to offer effective relaxation. In particular, the lack of technology to generate optimal scents by fusing biometric and auditory information makes it difficult to optimize the user experience.

[0293] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0294] In this invention, the server includes information gathering means for processing biometric and voice information acquired from the user, information analysis means for analyzing the biometric and voice information to identify the user's psychological state, and fragrance generation means for generating an optimal fragrance according to the psychological state obtained by the information analysis means. This makes it possible to provide an optimized fragrance for each individual user and realize an effective relaxation experience.

[0295] "Information gathering means" refers to devices and systems for acquiring biometric and voice information from users and processing it.

[0296] "Information analysis means" refers to technology that analyzes collected biometric and audio information to identify the user's psychological state and health status.

[0297] "Fragrance generation means" refers to a device or system for generating the optimal fragrance combination based on the analyzed user's condition.

[0298] "Fragrance diffusion device means" refers to a device or system for blending generated fragrances in appropriate proportions and diffusing them into the environment.

[0299] "Feedback analysis means" refers to technology that collects and analyzes user feedback and incorporates the results into the next fragrance generation process to improve the overall system performance.

[0300] To implement this invention, a system is required that includes a user, a terminal, a server, various sensors, and an aroma dispenser. This system is configured to be attached to or carried by the user in a terminal owned by the user. The terminal includes sensors for acquiring biometric information, collecting data such as heart rate, body temperature, and respiratory rate in real time. Voice information is recorded by recording the user's conversation through a microphone mounted on the terminal and converted into text using speech recognition software.

[0301] The biometric and voice information collected by the device is sent to the server. The server receives this information and uses natural language processing technology to analyze the user's emotional state. For example, the server has a built-in generative AI model that determines the user's stress level and psychological tendencies from their voice. An example of a prompt used for voice analysis would be, "Please suggest the most suitable relaxation aroma based on the user's heart rate and voice data."

[0302] Based on the information analyzed by the server, an optimal aroma blend is generated for the user's psychological and health state. The selected aroma blend information is sent to the terminal, which controls the aroma dispenser. The dispenser, following the received instructions, blends the aroma oils in the appropriate proportions and diffuses the scent using a diffuser. This allows the user to receive a customized fragrance experience.

[0303] Feedback obtained from the user is transmitted to the server through the terminal. This feedback can be used for subsequent fragrance generation and overall system optimization. As a specific example, when a user who has accumulated stress from long hours of desk work shows an increase in heart rate or a strong-toned voice, it is possible to generate an aroma blend containing lavender and bergamot suitable for relaxation and assist the user's relaxation by diffusing it with a dispenser.

[0304] The flow of the specific process in Example 1 will be described using FIG. 11.

[0305] Step 1:

[0306] The terminal uses a sensor to collect biometric information.

[0307] Input: Real-time data such as the user's heart rate, body temperature, and respiratory rate.

[0308] Data processing: Convert the analog signal from the sensor into digital data, and perform smoothing and filtering as necessary.

[0309] Output: A set of formatted biometric information data.

[0310] Specific operation: Capture biometric data in seconds, buffer it within the terminal, and prepare for the next processing step at regular intervals.

[0311] Step 2:

[0312] The terminal records the user's voice through the microphone and converts it into text.

[0313] Input: The user's voice signal.

[0314] Data processing: Convert the voice signal into text data using voice recognition software.

[0315] Output: Data in text format of the voice.

[0316] Specific operation: Noise is removed from the audio signal using a feature extraction technique, and the audio is converted to text using a language model.

[0317] Step 3:

[0318] The server receives biometric and voice information transmitted from the terminal and performs analysis.

[0319] Input: Biometric data and text data transmitted from the device.

[0320] Data Processing: We analyze text data using natural language processing techniques to determine the user's emotional state. We also analyze biometric data using machine learning algorithms.

[0321] Output: Data representing the user's psychological and physical state.

[0322] Specific operation: A generative AI model on the server performs sentiment analysis on the speech-to-text data and calculates a health status score based on biometric data.

[0323] Step 4:

[0324] The server determines the optimal aroma blend based on the analysis results.

[0325] Input: Analyzed user psychological and health status data.

[0326] Data processing: Use prompt statements to instruct the generation AI model to create aroma blends.

[0327] Output: Aroma blend recipe information.

[0328] Specific operation: The server selects a combination of aroma oils from several options that is suitable for a specific emotional state and sends the information to the terminal.

[0329] Step 5:

[0330] The device controls the aroma dispenser to diffuse the fragrance.

[0331] Input: Aroma blend recipe information sent from the server.

[0332] Data processing: Generates control signals to blend essential oils in specified proportions.

[0333] Output: A scent of a carefully adjusted aroma blend.

[0334] Specific operation: The aroma dispenser mixes a specified amount of aroma oil and diffuses the scent around the user through the diffuser.

[0335] Step 6:

[0336] We collect feedback from users about their fragrance experience.

[0337] Input: User feedback information.

[0338] Data processing: The feedback data is formatted as reference information for the next aroma blend generation.

[0339] Output: Feedback data for analysis.

[0340] Specific operation: The user fills out an evaluation form on their device, and this information is automatically sent to the server. This data will be used to optimize the system in the future.

[0341] (Application Example 1)

[0342] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0343] In modern brick-and-mortar stores, there are limited ways to understand customers' psychological states and emotions in real time and optimize the store atmosphere accordingly. In particular, it is difficult to instantly provide the appropriate scent when a customer is stressed or seeking relaxation. By solving this problem, we aim to create a more pleasant shopping experience and increase store sales.

[0344] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0345] In this invention, the server includes information gathering means for processing biometric and voice information acquired from the user, information analysis means for analyzing the biometric and voice information to identify the user's emotional state, and fragrance blend generation means for generating an optimal fragrance according to the emotional state obtained by the information analysis means. This makes it possible to automatically select and diffuse an appropriate fragrance according to the customer's emotional state within a physical store.

[0346] "Information gathering means" refers to devices and methods for acquiring and processing biometric and voice information from users.

[0347] "Information analysis means" refers to devices and methods for analyzing acquired biometric and audio information to identify the user's emotional state.

[0348] A "fragrance blend generation method" refers to a device or method for generating the optimal fragrance combination based on the analyzed emotional state of the user.

[0349] A "fragrance diffusion means" refers to a device or method for blending a generated fragrance blend in appropriate proportions and diffusing it into the surrounding environment.

[0350] "Feedback collection means" refers to devices or methods for collecting user feedback based on the effects of fragrances and using that feedback to improve future fragrance creation.

[0351] "Environmental adjustment means" refers to devices or methods for automatically selecting the optimal scent according to the emotional state of customers within a physical store and adjusting the store environment.

[0352] The system implementing this invention will create an optimal purchasing environment by understanding the psychological state of customers in a physical store in real time and automatically providing a corresponding fragrance. Specifically, the following means will be combined.

[0353] The server uses information gathering methods to acquire biometric information from customers' smart devices. For example, data such as heart rate and body temperature are collected through sensors in smartphones and smartwatches. The devices are also equipped with high-quality microphones, which are used to collect audio information of conversations between customers and staff. This data is transmitted to the server via wireless communication technology.

[0354] The server analyzes this data using natural language processing tools (e.g., NLTK and spaCy) and machine learning tools (e.g., TensorFlow and PyTorch) as information analysis tools. It identifies the user's emotional state from biometric and voice information, and the fragrance blend generation mechanism operates based on the analysis results.

[0355] The fragrance blend generation system selects the most suitable fragrance for a given emotional state and distributes the combination from the server to the fragrance diffusion system within the store. Diffusers are placed throughout the store, which then spread the selected fragrance throughout the premises. The diffusers are controlled to blend the fragrances and automatically diffuse them at the appropriate times.

[0356] Furthermore, using a feedback collection system, customers input their impressions and evaluations of the scents they experienced via a terminal, and this feedback is sent to a server so that it can be reflected in future scent selection processes. Through this feedback loop, the system is continuously optimized, and the store's scent environment becomes more tailored to customer needs.

[0357] For example, if the server determines that a customer visiting the store is experiencing stress, the system will select relaxing scents such as lavender or bergamot and diffuse them throughout the store to promote relaxation. An example of a prompt used might be, "Please describe the process of selecting the optimal aroma to reduce stress."

[0358] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0359] Step 1:

[0360] The device acquires biometric information from the customer. Specifically, it measures biometric data such as heart rate and body temperature using a smartphone or smartwatch. This data is transmitted to a server via Bluetooth or Wi-Fi. The input is the customer's biometric information, and the output is the set of biometric data transmitted to the server. The data processing performed in this step is the conversion of analog signals obtained from biosensors into digital data.

[0361] Step 2:

[0362] The terminal records conversations between customers and staff to acquire audio information. It collects audio data using a built-in microphone and converts it into text data. The input is the audio data of the conversation, and the output is the transcribed conversation. The audio data is converted into text by speech recognition software.

[0363] Step 3:

[0364] The server receives biometric data and text data obtained from voice. The server uses natural language processing tools to analyze the emotional state from the text data. The input is text data and biometric data, and the output is the analysis result indicating the customer's emotional state. A generative AI model is used for emotion classification in the data calculations.

[0365] Step 4:

[0366] The server determines the fragrance blend based on the analyzed emotional state. It selects a fragrance combination and sends instructions to the fragrance diffusion system. The input is the result of the emotional analysis, and the output is the fragrance combination. The server uses pre-configured prompt sentences and a generating AI model to select the optimal blend.

[0367] Step 5:

[0368] The terminal controls the diffusers in the store to diffuse the selected fragrance. It adjusts the amount of fragrance released from the diffuser at the appropriate time. The input is information about the fragrance combination, and the output is the actual fragrance that is diffused. The diffuser's operation involves blending and diffusing the fragrance based on the proportions of the selected essential oils.

[0369] Step 6:

[0370] Users input feedback about the scents they experience into a terminal. They input their evaluation of the scent's effects as text and send it to the server. The input is the user's feedback text, and the output is feedback data. The feedback data is used to optimize the future scent selection process.

[0371] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0372] One embodiment of the present invention is an emotion engine that accurately recognizes the user's emotions, and a system that provides an optimal aroma experience based on this engine. This system consists of a user, a terminal, a server, various sensors, an aroma dispenser, and the emotion engine. The embodiments thereof will be described in detail below in natural language.

[0373] Data collection and emotion recognition

[0374] The device connects to the user and acquires biometric data in real time through sensors. This biometric data includes heart rate, body temperature, and respiratory rate. Next, the device collects the user's voice data and records the conversation through a microphone. The voice data is converted into text using natural language processing technology and sent to a server. The server analyzes this text data and biometric data with an emotion engine to comprehensively evaluate the user's emotional state. This engine combines changes in the user's voice tone and biometric indicators to identify a precise emotional state.

[0375] Aroma blend creation and application

[0376] Based on the analysis results from the emotion engine, the server selects the aroma blend best suited to the user's current emotional state. The selected aroma recipe is sent to the terminal, which controls the aroma dispenser to mix the essential oils as instructed. The terminal then diffuses this blended aroma around the user through a diffuser, promoting effects such as relaxation and improved concentration.

[0377] Feedback and adjustments

[0378] Users provide feedback on the effects of the fragrance and input the results into their device. This feedback is collected on the server and, along with analysis by the emotion engine, is used to improve future aroma blend generation. This feedback loop allows the system to continuously improve the fragrance experience delivered to each user, adapting to their individual changes and preferences.

[0379] Specific example

[0380] For example, if a user is feeling nervous before an important presentation, the device detects an increase in heart rate from biometric data and identifies an anxious tone through voice analysis. The emotion engine determines this to be a high-stress state, and the server creates an aroma blend with corresponding relaxation effects. The device diffuses a scent containing lavender and bergamot, allowing the user to feel relaxed. Through this process, the user can approach the presentation in a better state of mind.

[0381] The following describes the processing flow.

[0382] Step 1:

[0383] The device collects biometric data in real time through sensors attached to the user. Specifically, it acquires data such as heart rate, body temperature, and respiratory rate.

[0384] Step 2:

[0385] The device uses its microphone to collect user voice data. It records the user's conversation and converts it to text using speech recognition technology.

[0386] Step 3:

[0387] The biometric and voice data collected by the device are encrypted and sent to the server in a secure manner.

[0388] Step 4:

[0389] The server applies natural language processing to the transmitted audio data and analyzes the user's emotional state from the content of their conversation.

[0390] Step 5:

[0391] The server inputs biometric data into an emotion engine, which analyzes changes in heart rate and body temperature to evaluate the user's stress level and psychological state.

[0392] Step 6:

[0393] Based on the analysis results of the emotion engine, the server determines the optimal aroma blend for the user's current emotional state and sends the recipe to the device.

[0394] Step 7:

[0395] The terminal operates the aroma dispenser, blends the specified aroma oils in the appropriate proportions, and diffuses the scent using a diffuser.

[0396] Step 8:

[0397] Users experience the scent and input feedback about its effects into a device.

[0398] Step 9:

[0399] The device sends user feedback to the server, which is then used as data to adjust the emotion engine's algorithm.

[0400] Step 10:

[0401] The server processes feedback and incorporates it into future aroma blend generation, continuously improving the user experience.

[0402] (Example 2)

[0403] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0404] In recent years, there has been a growing demand for personalized fragrance experiences tailored to the individual psychological state of each user. However, conventional systems have struggled to accurately grasp users' emotions and preferences and generate appropriate fragrances. There is a need to solve this problem and provide more precise and individualized fragrance experiences.

[0405] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0406] In this invention, the server includes information acquisition means, information analysis means, and fragrance generation means. This makes it possible to acquire and analyze the user's biometric data and voice data in real time, and to efficiently generate and provide fragrances adapted to the user's emotional state.

[0407] "Information acquisition means" refers to a device or system that provides the function of collecting biometric data and voice data from users in real time.

[0408] "Information analysis means" refers to a device or system that analyzes collected biometric data and voice data and provides a function for evaluating the user's emotional state and psychological state.

[0409] "Fragrance generation means" refers to a device or system for generating an appropriate fragrance based on the user's emotional state obtained through information analysis means.

[0410] A "fragrance diffusion means" is a device or system that provides the function of appropriately blending the generated fragrance and diffusing it into the surroundings.

[0411] "Evaluation means" refers to a device or system that has the function of collecting feedback from users based on the effects of diffused fragrances and reflecting that feedback in the next fragrance generation process.

[0412] The system of the present invention includes information acquisition means, information analysis means, fragrance generation means, fragrance diffusion means, and evaluation means in order to provide a personalized fragrance experience according to the user's psychological state.

[0413] The user connects to various sensors via a terminal, allowing for the real-time collection of biometric data such as heart rate, body temperature, and respiratory rate. The terminal also includes a microphone, collecting the user's voice data. The collected data is transmitted to a server via an information acquisition system. Specific devices used at this stage include standard biosensors and microphones.

[0414] The server processes the acquired biometric and voice data using information analysis tools. It utilizes natural language processing and signal processing technologies to identify the user's emotional state from the data. Specific software examples include voice recognition systems and data analysis algorithms. Based on the analysis results, a fragrance generation tool selects the optimal scent, and the server sends that recipe to the terminal.

[0415] The device controls the fragrance diffusion method based on the received fragrance recipe and diffuses the blended fragrance through the diffuser. The fragrance promotes relaxation and concentration effects that correspond to the user's psychological state.

[0416] Furthermore, users evaluate the effects of the scents they experience and input feedback into their devices. This feedback is collected by the evaluation system and reflected in future scent generation, thereby improving the system's personalization capabilities.

[0417] For example, when a user experiences stress, their heart rate often increases. The device detects this, and the server generates a relaxing blend based on lavender and bergamot. This allows the user to maintain a calmer state.

[0418] An example of input to the generative AI model could be a prompt such as, "Analyze the user's voice data and biometric data to generate the optimal relaxation fragrance blend." Through this prompt, the system can quickly and effectively provide fragrances tailored to the user's specific needs.

[0419] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0420] Step 1:

[0421] The device connects to the user and acquires biometric data in real time through various sensors. Specifically, it collects heart rate, body temperature, and respiratory rate from sensors and processes them as digital signals. This data is then input, and the device sends it to a server for data preparation.

[0422] Step 2:

[0423] The device uses a microphone to record the user's voice data. Speech recognition software is used to convert the recorded data into text, and this converted text data is sent to a server. The input is the user's voice data, and the output is text data. This data serves as preparation data for analyzing the user's linguistic characteristics.

[0424] Step 3:

[0425] The server uses information analysis tools to analyze the received biometric and text data. It employs natural language processing techniques to extract emotional keywords from the text and signal processing techniques to analyze patterns in the biometric data. The input consists of biometric and text data, and the output is an analysis result indicating the user's emotional state. Specifically, the server executes an analysis algorithm to evaluate the psychological state.

[0426] Step 4:

[0427] The server selects an appropriate scent using a fragrance generation system based on the analysis results. Past data and feedback are also considered, so the input consists of the analysis results and existing data such as stress reduction and concentration improvement. The output is the recipe for the selected scent. The server sends this recipe to the terminal.

[0428] Step 5:

[0429] The terminal controls the fragrance diffusion mechanism, operating the aroma dispenser according to the received fragrance recipe to mix the scents. Specifically, the terminal activates the diffuser and diffuses the blended fragrance. The input is the fragrance recipe, and the output is the diffusion of the fragrance.

[0430] Step 6:

[0431] Users input feedback into a terminal based on their fragrance experience. The feedback is analyzed on a server using an evaluation method; therefore, the input is user feedback, and the output is evaluation information that will be reflected in future fragrance creation. Specifically, the terminal sends the feedback to the server in a digital form, where it is recorded in a database.

[0432] (Application Example 2)

[0433] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0434] In today's commercial environment, there is a need for effective methods to respond to the diverse emotional states of customers and promote purchasing activity. Traditional methods have faced challenges in accurately understanding the psychological state of individual customers in real time and providing responsive services accordingly. In particular, while providing experiences using scent has the potential to significantly influence emotions, methods for directly linking them to the customer's state of mind have not been sufficiently developed.

[0435] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0436] In this invention, the server includes information gathering means for processing biometric data and voice data acquired from the user, information analysis means for analyzing the biometric data and voice data to identify the user's emotional state, and fragrance generation means for generating an appropriate fragrance according to the emotional state obtained by the information analysis means. This makes it possible to provide a fragrance experience tailored to the emotional state of each customer visiting a store in a commercial environment, thereby promoting purchasing activity.

[0437] "Information gathering means" refers to a system of devices and software that acquire and process biometric and voice data from users.

[0438] "Information analysis means" refers to technology or software that analyzes collected biometric and audio data to identify the user's emotional state.

[0439] A "fragrance generation means" is a device or system for blending the optimal fragrance according to the emotional state identified by an information analysis means.

[0440] A "fragrance diffusion means" is a mechanism or device that effectively diffuses a blended fragrance into the surrounding space.

[0441] A "feedback collection method" is a system that collects user reactions and evaluations based on the effects of fragrances and uses them to improve future fragrance creation.

[0442] A "commercial environment support device" is a device or system designed to promote purchasing activity by providing an appropriate fragrance experience based on the user's emotional state.

[0443] The system implementing this invention consists of a user, a terminal, a server, various sensors, a fragrance diffusion device, and an information analysis engine. The basic flow is shown below.

[0444] First, the device connects to the user to acquire biometric data. Through sensors, it collects vital data such as heart rate, body temperature, and respiratory rate in real time. Simultaneously, the device uses a microphone to collect the user's voice data, converts this data into text using natural language processing technology, and sends it to the server. The server analyzes the voice data using natural language processing technologies such as Google Cloud Natural Language API and spaCy, and processes the resulting text data and biometric data with an information analysis engine. This analysis identifies the user's emotional state.

[0445] Next, the server determines the most suitable scent for the user's current emotional state based on the results of the information analysis engine. The scent generation device blends the scents based on the identified recipe and sends the instructions to the terminal. The terminal controls the scent diffusion device to appropriately diffuse the required scent into the surrounding space.

[0446] Furthermore, the device collects feedback from users regarding the effects of the fragrance. This feedback is sent to a server and used to adjust the fragrance generation process for the next time. Through this feedback collection mechanism, the system improves its performance to provide the optimal experience for each individual user.

[0447] For example, if a customer is feeling stressed, the device can detect their emotions from their increased heart rate and tone of voice, and then provide a relaxing experience using the scents of lavender and bergamot. This process is expected to increase the customer's willingness to purchase. Examples of prompts include, "What scent would you recommend for relaxation time?" or "How would you describe your mood today in one word?"

[0448] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0449] Step 1:

[0450] The device acquires biometric data (heart rate, body temperature, respiratory rate) from the user through sensors. This data is fundamental information for evaluating the user's emotional state. Data from the sensors is provided as input, and a set of biometric data is stored in the device as output.

[0451] Step 2:

[0452] The device collects the user's voice using a microphone and converts the voice data into text data. This conversion uses the Google Cloud Natural Language API. The input is voice data, and the output is text data. The process involves recognizing the voice and converting it into text.

[0453] Step 3:

[0454] The device sends biometric and text data to the server. This data is received by the server as foundational data for evaluating the user's emotions. The input is a set of biometric and text data, and the output is the transfer of data to the server.

[0455] Step 4:

[0456] The server uses the received biometric and text data to analyze the user's emotional state using an information analysis engine. This analysis also utilizes a generative AI model for data analysis. Biometric and text data are provided as input, and the user's emotional state is identified as output.

[0457] Step 5:

[0458] The server uses a fragrance generation mechanism based on the analysis results to determine the optimal fragrance blend. The results of the data analysis are input into the fragrance generation algorithm, and a fragrance recipe is output. The input is the analyzed emotional state, and the output is the fragrance recipe.

[0459] Step 6:

[0460] The terminal controls the fragrance diffusion device to diffuse the fragrance into the space based on the fragrance recipe received from the server. The fragrance, blended by the fragrance generation means, spreads to the surroundings by the device. The input is the fragrance recipe, and the output is the diffusion of the fragrance.

[0461] Step 7:

[0462] The user inputs feedback on the effects of the fragrance into the terminal. This feedback is sent to the server as data for the next fragrance generation. The input is user feedback information, and the output is data transfer to the server.

[0463] Step 8:

[0464] The server receives feedback from users and incorporates the data into the information analysis engine for the next fragrance generation. This allows the system's fragrance generation method to be improved based on subsequent adjustments. The input is user feedback, and the output is the updated analysis parameters.

[0465] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0466] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0467] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0468] [Third Embodiment]

[0469] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0470] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0471] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0472] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0473] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0474] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0475] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0476] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0477] The specific processing program 56 is an example of a "program" relating to the technology of this 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 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.

[0478] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0479] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0480] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0481] This invention is a system that utilizes a user's biometric and voice data to provide the optimal aroma according to their individual psychological state. This system consists of a user, a terminal, a server, various sensors, an aroma dispenser, and other components. The embodiments are described in detail below in natural language.

[0482] Data collection and analysis

[0483] As the device is worn or carried by the user, sensors acquire biometric data in real time. Audio data is recorded by capturing the user's conversation through the device's microphone and converting it to text. The server receives this collected data and analyzes the text data using natural language processing technology to analyze the user's emotional state. Furthermore, the server evaluates the biometric data using machine learning algorithms to assess the user's health status.

[0484] Aroma blend creation and diffusion

[0485] Based on the analysis results, the server determines an aroma blend suitable for the user's psychological and physical state. Based on this determination, the aroma blend generation system constructs an appropriate fragrance combination and sends it to the terminal. The terminal controls the aroma dispenser, blends the specified aroma oils in the appropriate proportions, and diffuses the fragrance through the diffuser. Through this process, the user can obtain a personalized fragrance experience.

[0486] Feedback and Improvement

[0487] Users provide feedback on the effects of the fragrance. This feedback is collected on the device and the results are sent to the server. The server analyzes the feedback as new data and adjusts and optimizes the system for the next aroma blend generation. This feedback loop allows users to continue enjoying a more effective fragrance experience.

[0488] Specific example

[0489] For example, suppose a user is experiencing high stress levels due to prolonged desk work. In this case, the device analyzes the user's heart rate and voice tone to determine that their stress level is elevated. Based on this, the server generates an aroma blend containing lavender and bergamot, which are known to be effective for relaxation, and the device diffuses it. The user relaxes while inhaling the scent, and their work efficiency improves. Furthermore, they provide feedback on their experience using the scent, which is used to select the next aroma blend.

[0490] The following describes the processing flow.

[0491] Step 1:

[0492] The device collects the user's biometric data. Specifically, it uses sensors to acquire data such as heart rate, body temperature, and respiratory rate in real time.

[0493] Step 2:

[0494] The device collects the user's voice data. It records conversations through the microphone and converts them to text using speech recognition technology.

[0495] Step 3:

[0496] The device encrypts the biometric and voice data it collects and securely transmits it to the server.

[0497] Step 4:

[0498] The server applies natural language processing techniques to the received audio data to analyze the user's emotional state. Keywords and context from the audio are used for the analysis.

[0499] Step 5:

[0500] The server uses machine learning algorithms to analyze biometric data and evaluate the user's health status and stress level.

[0501] Step 6:

[0502] The server determines the optimal aroma blend based on the analysis results. This includes a process of selecting a combination of aromas that suits the user's psychological and physical state.

[0503] Step 7:

[0504] The server selects an aroma blend and instructs the terminal to specify the required types and proportions of essential oils.

[0505] Step 8:

[0506] The device controls the aroma dispenser and mixes the aroma oils in the specified proportions.

[0507] Step 9:

[0508] The device activates an aroma diffuser, diffusing the selected scent around the user.

[0509] Step 10:

[0510] Users provide feedback about the effects of the fragrance they experienced and input it into the device.

[0511] Step 11:

[0512] The device sends feedback received from the user to a server, accumulating data that can be used in future aroma blend generation processes.

[0513] (Example 1)

[0514] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0515] In today's stressful society, there is a need for relaxation methods tailored to the individual psychological and physical states of each user. However, conventional methods struggle to provide individualized treatment that adapts to each user's condition, making it difficult to offer effective relaxation. In particular, the lack of technology to generate optimal scents by fusing biometric and auditory information makes it difficult to optimize the user experience.

[0516] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0517] In this invention, the server includes information gathering means for processing biometric and voice information acquired from the user, information analysis means for analyzing the biometric and voice information to identify the user's psychological state, and fragrance generation means for generating an optimal fragrance according to the psychological state obtained by the information analysis means. This makes it possible to provide an optimized fragrance for each individual user and realize an effective relaxation experience.

[0518] "Information gathering means" refers to devices and systems for acquiring biometric and voice information from users and processing it.

[0519] "Information analysis means" refers to technology that analyzes collected biometric and audio information to identify the user's psychological state and health status.

[0520] "Fragrance generation means" refers to a device or system for generating the optimal fragrance combination based on the analyzed user's condition.

[0521] "Fragrance diffusion device means" refers to a device or system for blending generated fragrances in appropriate proportions and diffusing them into the environment.

[0522] "Feedback analysis means" refers to technology that collects and analyzes user feedback and incorporates the results into the next fragrance generation process to improve the overall system performance.

[0523] To implement this invention, a system is required that includes a user, a terminal, a server, various sensors, and an aroma dispenser. This system is configured to be attached to or carried by the user in a terminal owned by the user. The terminal includes sensors for acquiring biometric information, collecting data such as heart rate, body temperature, and respiratory rate in real time. Voice information is recorded by recording the user's conversation through a microphone mounted on the terminal and converted into text using speech recognition software.

[0524] The biometric and voice information collected by the device is sent to the server. The server receives this information and uses natural language processing technology to analyze the user's emotional state. For example, the server has a built-in generative AI model that determines the user's stress level and psychological tendencies from their voice. An example of a prompt used for voice analysis would be, "Please suggest the most suitable relaxation aroma based on the user's heart rate and voice data."

[0525] Based on the information analyzed by the server, an optimal aroma blend is generated for the user's psychological and health state. The selected aroma blend information is sent to the terminal, which controls the aroma dispenser. The dispenser, following the received instructions, blends the aroma oils in the appropriate proportions and diffuses the scent using a diffuser. This allows the user to receive a customized fragrance experience.

[0526] User feedback is sent to the server via the terminal. This feedback is used to optimize future fragrance generation and the overall system. For example, if a user who has accumulated stress from long hours of desk work shows an increased heart rate or a loud voice, it is possible to generate an aroma blend containing lavender and bergamot, which are suitable for relaxation, and diffuse it through a dispenser to help the user relax.

[0527] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0528] Step 1:

[0529] The device uses sensors to collect biometric information.

[0530] Input: Real-time data such as the user's heart rate, body temperature, and respiratory rate.

[0531] Data processing: Analog signals from sensors are converted into digital data, and smoothing and filtering are performed as needed.

[0532] Output: Formatted biometric data set.

[0533] Specific operation: Biometric data is captured every second, buffered within the device, and prepared for the next processing step at regular intervals.

[0534] Step 2:

[0535] The device records the user's voice through the microphone and converts it to text.

[0536] Input: User's voice signal.

[0537] Data processing: Convert audio signals into text data using speech recognition software.

[0538] Output: Audio data in text format.

[0539] Specific operation: Noise is removed from the audio signal using a feature extraction technique, and the audio is converted to text using a language model.

[0540] Step 3:

[0541] The server receives biometric and voice information transmitted from the terminal and performs analysis.

[0542] Input: Biometric data and text data transmitted from the device.

[0543] Data Processing: We analyze text data using natural language processing techniques to determine the user's emotional state. We also analyze biometric data using machine learning algorithms.

[0544] Output: Data representing the user's psychological and physical state.

[0545] Specific operation: A generative AI model on the server performs sentiment analysis on the speech-to-text data and calculates a health status score based on biometric data.

[0546] Step 4:

[0547] The server determines the optimal aroma blend based on the analysis results.

[0548] Input: Analyzed user psychological and health status data.

[0549] Data processing: Use prompt statements to instruct the generation AI model to create aroma blends.

[0550] Output: Aroma blend recipe information.

[0551] Specific operation: The server selects a combination of aroma oils from several options that is suitable for a specific emotional state and sends the information to the terminal.

[0552] Step 5:

[0553] The device controls the aroma dispenser to diffuse the fragrance.

[0554] Input: Aroma blend recipe information sent from the server.

[0555] Data processing: Generates control signals to blend essential oils in specified proportions.

[0556] Output: A scent of a carefully adjusted aroma blend.

[0557] Specific operation: The aroma dispenser mixes a specified amount of aroma oil and diffuses the scent around the user through the diffuser.

[0558] Step 6:

[0559] We collect feedback from users about their fragrance experience.

[0560] Input: User feedback information.

[0561] Data processing: The feedback data is formatted as reference information for the next aroma blend generation.

[0562] Output: Feedback data for analysis.

[0563] Specific operation: The user fills out an evaluation form on their device, and this information is automatically sent to the server. This data will be used to optimize the system in the future.

[0564] (Application Example 1)

[0565] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0566] In modern brick-and-mortar stores, there are limited ways to understand customers' psychological states and emotions in real time and optimize the store atmosphere accordingly. In particular, it is difficult to instantly provide the appropriate scent when a customer is stressed or seeking relaxation. By solving this problem, we aim to create a more pleasant shopping experience and increase store sales.

[0567] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0568] In this invention, the server includes information gathering means for processing biometric and voice information acquired from the user, information analysis means for analyzing the biometric and voice information to identify the user's emotional state, and fragrance blend generation means for generating an optimal fragrance according to the emotional state obtained by the information analysis means. This makes it possible to automatically select and diffuse an appropriate fragrance according to the customer's emotional state within a physical store.

[0569] "Information gathering means" refers to devices and methods for acquiring and processing biometric and voice information from users.

[0570] "Information analysis means" refers to devices and methods for analyzing acquired biometric and audio information to identify the user's emotional state.

[0571] A "fragrance blend generation method" refers to a device or method for generating the optimal fragrance combination based on the analyzed emotional state of the user.

[0572] A "fragrance diffusion means" refers to a device or method for blending a generated fragrance blend in appropriate proportions and diffusing it into the surrounding environment.

[0573] "Feedback collection means" refers to devices or methods for collecting user feedback based on the effects of fragrances and using that feedback to improve future fragrance creation.

[0574] "Environmental adjustment means" refers to devices or methods for automatically selecting the optimal scent according to the emotional state of customers within a physical store and adjusting the store environment.

[0575] The system implementing this invention will create an optimal purchasing environment by understanding the psychological state of customers in a physical store in real time and automatically providing a corresponding fragrance. Specifically, the following means will be combined.

[0576] The server uses information gathering methods to acquire biometric information from customers' smart devices. For example, data such as heart rate and body temperature are collected through sensors in smartphones and smartwatches. The devices are also equipped with high-quality microphones, which are used to collect audio information of conversations between customers and staff. This data is transmitted to the server via wireless communication technology.

[0577] The server analyzes this data using natural language processing tools (e.g., NLTK and spaCy) and machine learning tools (e.g., TensorFlow and PyTorch) as information analysis tools. It identifies the user's emotional state from biometric and voice information, and the fragrance blend generation mechanism operates based on the analysis results.

[0578] The fragrance blend generation system selects the most suitable fragrance for a given emotional state and distributes the combination from the server to the fragrance diffusion system within the store. Diffusers are placed throughout the store, which then spread the selected fragrance throughout the premises. The diffusers are controlled to blend the fragrances and automatically diffuse them at the appropriate times.

[0579] Furthermore, using a feedback collection system, customers input their impressions and evaluations of the scents they experienced via a terminal, and this feedback is sent to a server so that it can be reflected in future scent selection processes. Through this feedback loop, the system is continuously optimized, and the store's scent environment becomes more tailored to customer needs.

[0580] For example, if the server determines that a customer visiting the store is experiencing stress, the system will select relaxing scents such as lavender or bergamot and diffuse them throughout the store to promote relaxation. An example of a prompt used might be, "Please describe the process of selecting the optimal aroma to reduce stress."

[0581] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0582] Step 1:

[0583] The device acquires biometric information from the customer. Specifically, it measures biometric data such as heart rate and body temperature using a smartphone or smartwatch. This data is transmitted to a server via Bluetooth or Wi-Fi. The input is the customer's biometric information, and the output is the set of biometric data transmitted to the server. The data processing performed in this step is the conversion of analog signals obtained from biosensors into digital data.

[0584] Step 2:

[0585] The terminal records conversations between customers and staff to acquire audio information. It collects audio data using a built-in microphone and converts it into text data. The input is the audio data of the conversation, and the output is the transcribed conversation. The audio data is converted into text by speech recognition software.

[0586] Step 3:

[0587] The server receives biometric data and text data obtained from voice. The server uses natural language processing tools to analyze the emotional state from the text data. The input is text data and biometric data, and the output is the analysis result indicating the customer's emotional state. A generative AI model is used for emotion classification in the data calculations.

[0588] Step 4:

[0589] The server determines the fragrance blend based on the analyzed emotional state. It selects a fragrance combination and sends instructions to the fragrance diffusion system. The input is the result of the emotional analysis, and the output is the fragrance combination. The server uses pre-configured prompt sentences and a generating AI model to select the optimal blend.

[0590] Step 5:

[0591] The terminal controls the diffusers in the store to diffuse the selected fragrance. It adjusts the amount of fragrance released from the diffuser at the appropriate time. The input is information about the fragrance combination, and the output is the actual fragrance that is diffused. The diffuser's operation involves blending and diffusing the fragrance based on the proportions of the selected essential oils.

[0592] Step 6:

[0593] Users input feedback about the scents they experience into a terminal. They input their evaluation of the scent's effects as text and send it to the server. The input is the user's feedback text, and the output is feedback data. The feedback data is used to optimize the future scent selection process.

[0594] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0595] One embodiment of the present invention is an emotion engine that accurately recognizes the user's emotions, and a system that provides an optimal aroma experience based on this engine. This system consists of a user, a terminal, a server, various sensors, an aroma dispenser, and the emotion engine. The embodiments thereof will be described in detail below in natural language.

[0596] Data collection and emotion recognition

[0597] The device connects to the user and acquires biometric data in real time through sensors. This biometric data includes heart rate, body temperature, and respiratory rate. Next, the device collects the user's voice data and records the conversation through a microphone. The voice data is converted into text using natural language processing technology and sent to a server. The server analyzes this text data and biometric data with an emotion engine to comprehensively evaluate the user's emotional state. This engine combines changes in the user's voice tone and biometric indicators to identify a precise emotional state.

[0598] Aroma blend creation and application

[0599] Based on the analysis results from the emotion engine, the server selects the aroma blend best suited to the user's current emotional state. The selected aroma recipe is sent to the terminal, which controls the aroma dispenser to mix the essential oils as instructed. The terminal then diffuses this blended aroma around the user through a diffuser, promoting effects such as relaxation and improved concentration.

[0600] Feedback and adjustments

[0601] Users provide feedback on the effects of the fragrance and input the results into their device. This feedback is collected on the server and, along with analysis by the emotion engine, is used to improve future aroma blend generation. This feedback loop allows the system to continuously improve the fragrance experience delivered to each user, adapting to their individual changes and preferences.

[0602] Specific example

[0603] For example, if a user is feeling nervous before an important presentation, the device detects an increase in heart rate from biometric data and identifies an anxious tone through voice analysis. The emotion engine determines this to be a high-stress state, and the server creates an aroma blend with corresponding relaxation effects. The device diffuses a scent containing lavender and bergamot, allowing the user to feel relaxed. Through this process, the user can approach the presentation in a better state of mind.

[0604] The following describes the processing flow.

[0605] Step 1:

[0606] The device collects biometric data in real time through sensors attached to the user. Specifically, it acquires data such as heart rate, body temperature, and respiratory rate.

[0607] Step 2:

[0608] The device uses its microphone to collect user voice data. It records the user's conversation and converts it to text using speech recognition technology.

[0609] Step 3:

[0610] The biometric and voice data collected by the device are encrypted and sent to the server in a secure manner.

[0611] Step 4:

[0612] The server applies natural language processing to the transmitted audio data and analyzes the user's emotional state from the content of their conversation.

[0613] Step 5:

[0614] The server inputs biometric data into an emotion engine, which analyzes changes in heart rate and body temperature to evaluate the user's stress level and psychological state.

[0615] Step 6:

[0616] Based on the analysis results of the emotion engine, the server determines the optimal aroma blend for the user's current emotional state and sends the recipe to the device.

[0617] Step 7:

[0618] The terminal operates the aroma dispenser, blends the specified aroma oils in the appropriate proportions, and diffuses the scent using a diffuser.

[0619] Step 8:

[0620] Users experience the scent and input feedback about its effects into a device.

[0621] Step 9:

[0622] The device sends user feedback to the server, which is then used as data to adjust the emotion engine's algorithm.

[0623] Step 10:

[0624] The server processes feedback and incorporates it into future aroma blend generation, continuously improving the user experience.

[0625] (Example 2)

[0626] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0627] In recent years, there has been a growing demand for personalized fragrance experiences tailored to the individual psychological state of each user. However, conventional systems have struggled to accurately grasp users' emotions and preferences and generate appropriate fragrances. There is a need to solve this problem and provide more precise and individualized fragrance experiences.

[0628] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0629] In this invention, the server includes information acquisition means, information analysis means, and fragrance generation means. This makes it possible to acquire and analyze the user's biometric data and voice data in real time, and to efficiently generate and provide fragrances adapted to the user's emotional state.

[0630] "Information acquisition means" refers to a device or system that provides the function of collecting biometric data and voice data from users in real time.

[0631] "Information analysis means" refers to a device or system that analyzes collected biometric data and voice data and provides a function for evaluating the user's emotional state and psychological state.

[0632] "Fragrance generation means" refers to a device or system for generating an appropriate fragrance based on the user's emotional state obtained through information analysis means.

[0633] A "fragrance diffusion means" is a device or system that provides the function of appropriately blending the generated fragrance and diffusing it into the surroundings.

[0634] "Evaluation means" refers to a device or system that has the function of collecting feedback from users based on the effects of diffused fragrances and reflecting that feedback in the next fragrance generation process.

[0635] The system of the present invention includes information acquisition means, information analysis means, fragrance generation means, fragrance diffusion means, and evaluation means in order to provide a personalized fragrance experience according to the user's psychological state.

[0636] The user connects to various sensors via a terminal, allowing for the real-time collection of biometric data such as heart rate, body temperature, and respiratory rate. The terminal also includes a microphone, collecting the user's voice data. The collected data is transmitted to a server via an information acquisition system. Specific devices used at this stage include standard biosensors and microphones.

[0637] The server processes the acquired biometric and voice data using information analysis tools. It utilizes natural language processing and signal processing technologies to identify the user's emotional state from the data. Specific software examples include voice recognition systems and data analysis algorithms. Based on the analysis results, a fragrance generation tool selects the optimal scent, and the server sends that recipe to the terminal.

[0638] The device controls the fragrance diffusion method based on the received fragrance recipe and diffuses the blended fragrance through the diffuser. The fragrance promotes relaxation and concentration effects that correspond to the user's psychological state.

[0639] Furthermore, users evaluate the effects of the scents they experience and input feedback into their devices. This feedback is collected by the evaluation system and reflected in future scent generation, thereby improving the system's personalization capabilities.

[0640] For example, when a user experiences stress, their heart rate often increases. The device detects this, and the server generates a relaxing blend based on lavender and bergamot. This allows the user to maintain a calmer state.

[0641] An example of input to the generative AI model could be a prompt such as, "Analyze the user's voice data and biometric data to generate the optimal relaxation fragrance blend." Through this prompt, the system can quickly and effectively provide fragrances tailored to the user's specific needs.

[0642] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0643] Step 1:

[0644] The device connects to the user and acquires biometric data in real time through various sensors. Specifically, it collects heart rate, body temperature, and respiratory rate from sensors and processes them as digital signals. This data is then input, and the device sends it to a server for data preparation.

[0645] Step 2:

[0646] The device uses a microphone to record the user's voice data. Speech recognition software is used to convert the recorded data into text, and this converted text data is sent to a server. The input is the user's voice data, and the output is text data. This data serves as preparation data for analyzing the user's linguistic characteristics.

[0647] Step 3:

[0648] The server uses information analysis tools to analyze the received biometric and text data. It employs natural language processing techniques to extract emotional keywords from the text and signal processing techniques to analyze patterns in the biometric data. The input consists of biometric and text data, and the output is an analysis result indicating the user's emotional state. Specifically, the server executes an analysis algorithm to evaluate the psychological state.

[0649] Step 4:

[0650] The server selects an appropriate scent using a fragrance generation system based on the analysis results. Past data and feedback are also considered, so the input consists of the analysis results and existing data such as stress reduction and concentration improvement. The output is the recipe for the selected scent. The server sends this recipe to the terminal.

[0651] Step 5:

[0652] The terminal controls the fragrance diffusion mechanism, operating the aroma dispenser according to the received fragrance recipe to mix the scents. Specifically, the terminal activates the diffuser and diffuses the blended fragrance. The input is the fragrance recipe, and the output is the diffusion of the fragrance.

[0653] Step 6:

[0654] Users input feedback into a terminal based on their fragrance experience. The feedback is analyzed on a server using an evaluation method; therefore, the input is user feedback, and the output is evaluation information that will be reflected in future fragrance creation. Specifically, the terminal sends the feedback to the server in a digital form, where it is recorded in a database.

[0655] (Application Example 2)

[0656] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0657] In today's commercial environment, there is a need for effective methods to respond to the diverse emotional states of customers and promote purchasing activity. Traditional methods have faced challenges in accurately understanding the psychological state of individual customers in real time and providing responsive services accordingly. In particular, while providing experiences using scent has the potential to significantly influence emotions, methods for directly linking them to the customer's state of mind have not been sufficiently developed.

[0658] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0659] In this invention, the server includes information gathering means for processing biometric data and voice data acquired from the user, information analysis means for analyzing the biometric data and voice data to identify the user's emotional state, and fragrance generation means for generating an appropriate fragrance according to the emotional state obtained by the information analysis means. This makes it possible to provide a fragrance experience tailored to the emotional state of each customer visiting a store in a commercial environment, thereby promoting purchasing activity.

[0660] "Information gathering means" refers to a system of devices and software that acquire and process biometric and voice data from users.

[0661] "Information analysis means" refers to technology or software that analyzes collected biometric and audio data to identify the user's emotional state.

[0662] A "fragrance generation means" is a device or system for blending the optimal fragrance according to the emotional state identified by an information analysis means.

[0663] A "fragrance diffusion means" is a mechanism or device that effectively diffuses a blended fragrance into the surrounding space.

[0664] A "feedback collection method" is a system that collects user reactions and evaluations based on the effects of fragrances and uses them to improve future fragrance creation.

[0665] A "commercial environment support device" is a device or system designed to promote purchasing activity by providing an appropriate fragrance experience based on the user's emotional state.

[0666] The system implementing this invention consists of a user, a terminal, a server, various sensors, a fragrance diffusion device, and an information analysis engine. The basic flow is shown below.

[0667] First, the device connects to the user to acquire biometric data. Through sensors, it collects vital data such as heart rate, body temperature, and respiratory rate in real time. Simultaneously, the device uses a microphone to collect the user's voice data, converts this data into text using natural language processing technology, and sends it to the server. The server analyzes the voice data using natural language processing technologies such as Google Cloud Natural Language API and spaCy, and processes the resulting text data and biometric data with an information analysis engine. This analysis identifies the user's emotional state.

[0668] Next, the server determines the most suitable scent for the user's current emotional state based on the results of the information analysis engine. The scent generation device blends the scents based on the identified recipe and sends the instructions to the terminal. The terminal controls the scent diffusion device to appropriately diffuse the required scent into the surrounding space.

[0669] Furthermore, the device collects feedback from users regarding the effects of the fragrance. This feedback is sent to a server and used to adjust the fragrance generation process for the next time. Through this feedback collection mechanism, the system improves its performance to provide the optimal experience for each individual user.

[0670] For example, if a customer is feeling stressed, the device can detect their emotions from their increased heart rate and tone of voice, and then provide a relaxing experience using the scents of lavender and bergamot. This process is expected to increase the customer's willingness to purchase. Examples of prompts include, "What scent would you recommend for relaxation time?" or "How would you describe your mood today in one word?"

[0671] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0672] Step 1:

[0673] The device acquires biometric data (heart rate, body temperature, respiratory rate) from the user through sensors. This data is fundamental information for evaluating the user's emotional state. Data from the sensors is provided as input, and a set of biometric data is stored in the device as output.

[0674] Step 2:

[0675] The device collects the user's voice using a microphone and converts the voice data into text data. This conversion uses the Google Cloud Natural Language API. The input is voice data, and the output is text data. The process involves recognizing the voice and converting it into text.

[0676] Step 3:

[0677] The device sends biometric and text data to the server. This data is received by the server as foundational data for evaluating the user's emotions. The input is a set of biometric and text data, and the output is the transfer of data to the server.

[0678] Step 4:

[0679] The server uses the received biometric and text data to analyze the user's emotional state using an information analysis engine. This analysis also utilizes a generative AI model for data analysis. Biometric and text data are provided as input, and the user's emotional state is identified as output.

[0680] Step 5:

[0681] The server uses a fragrance generation mechanism based on the analysis results to determine the optimal fragrance blend. The results of the data analysis are input into the fragrance generation algorithm, and a fragrance recipe is output. The input is the analyzed emotional state, and the output is the fragrance recipe.

[0682] Step 6:

[0683] The terminal controls the fragrance diffusion device to diffuse the fragrance into the space based on the fragrance recipe received from the server. The fragrance, blended by the fragrance generation means, spreads to the surroundings by the device. The input is the fragrance recipe, and the output is the diffusion of the fragrance.

[0684] Step 7:

[0685] The user inputs feedback on the effects of the fragrance into the terminal. This feedback is sent to the server as data for the next fragrance generation. The input is user feedback information, and the output is data transfer to the server.

[0686] Step 8:

[0687] The server receives feedback from users and incorporates the data into the information analysis engine for the next fragrance generation. This allows the system's fragrance generation method to be improved based on subsequent adjustments. The input is user feedback, and the output is the updated analysis parameters.

[0688] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0689] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0690] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0691] [Fourth Embodiment]

[0692] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0693] As shown in Figure 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.

[0694] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0695] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0696] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0697] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0698] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0699] The controlled 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0700] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0701] The specific processing program 56 is an example of a "program" relating to the technology of this 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 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.

[0702] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0703] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0704] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0705] This invention is a system that utilizes a user's biometric and voice data to provide the optimal aroma according to their individual psychological state. This system consists of a user, a terminal, a server, various sensors, an aroma dispenser, and other components. The embodiments are described in detail below in natural language.

[0706] Data collection and analysis

[0707] As the device is worn or carried by the user, sensors acquire biometric data in real time. Audio data is recorded by capturing the user's conversation through the device's microphone and converting it to text. The server receives this collected data and analyzes the text data using natural language processing technology to analyze the user's emotional state. Furthermore, the server evaluates the biometric data using machine learning algorithms to assess the user's health status.

[0708] Aroma blend creation and diffusion

[0709] Based on the analysis results, the server determines an aroma blend suitable for the user's psychological and physical state. Based on this determination, the aroma blend generation system constructs an appropriate fragrance combination and sends it to the terminal. The terminal controls the aroma dispenser, blends the specified aroma oils in the appropriate proportions, and diffuses the fragrance through the diffuser. Through this process, the user can obtain a personalized fragrance experience.

[0710] Feedback and Improvement

[0711] Users provide feedback on the effects of the fragrance. This feedback is collected on the device and the results are sent to the server. The server analyzes the feedback as new data and adjusts and optimizes the system for the next aroma blend generation. This feedback loop allows users to continue enjoying a more effective fragrance experience.

[0712] Specific example

[0713] For example, suppose a user is experiencing high stress levels due to prolonged desk work. In this case, the device analyzes the user's heart rate and voice tone to determine that their stress level is elevated. Based on this, the server generates an aroma blend containing lavender and bergamot, which are known to be effective for relaxation, and the device diffuses it. The user relaxes while inhaling the scent, and their work efficiency improves. Furthermore, they provide feedback on their experience using the scent, which is used to select the next aroma blend.

[0714] The following describes the processing flow.

[0715] Step 1:

[0716] The device collects the user's biometric data. Specifically, it uses sensors to acquire data such as heart rate, body temperature, and respiratory rate in real time.

[0717] Step 2:

[0718] The device collects the user's voice data. It records conversations through the microphone and converts them to text using speech recognition technology.

[0719] Step 3:

[0720] The device encrypts the biometric and voice data it collects and securely transmits it to the server.

[0721] Step 4:

[0722] The server applies natural language processing techniques to the received audio data to analyze the user's emotional state. Keywords and context from the audio are used for the analysis.

[0723] Step 5:

[0724] The server uses machine learning algorithms to analyze biometric data and evaluate the user's health status and stress level.

[0725] Step 6:

[0726] The server determines the optimal aroma blend based on the analysis results. This includes a process of selecting a combination of aromas that suits the user's psychological and physical state.

[0727] Step 7:

[0728] The server selects an aroma blend and instructs the terminal to specify the required types and proportions of essential oils.

[0729] Step 8:

[0730] The device controls the aroma dispenser and mixes the aroma oils in the specified proportions.

[0731] Step 9:

[0732] The device activates an aroma diffuser, diffusing the selected scent around the user.

[0733] Step 10:

[0734] Users provide feedback about the effects of the fragrance they experienced and input it into the device.

[0735] Step 11:

[0736] The device sends feedback received from the user to a server, accumulating data that can be used in future aroma blend generation processes.

[0737] (Example 1)

[0738] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0739] In today's stressful society, there is a need for relaxation methods tailored to the individual psychological and physical states of each user. However, conventional methods struggle to provide individualized treatment that adapts to each user's condition, making it difficult to offer effective relaxation. In particular, the lack of technology to generate optimal scents by fusing biometric and auditory information makes it difficult to optimize the user experience.

[0740] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0741] In this invention, the server includes information gathering means for processing biometric and voice information acquired from the user, information analysis means for analyzing the biometric and voice information to identify the user's psychological state, and fragrance generation means for generating an optimal fragrance according to the psychological state obtained by the information analysis means. This makes it possible to provide an optimized fragrance for each individual user and realize an effective relaxation experience.

[0742] "Information gathering means" refers to devices and systems for acquiring biometric and voice information from users and processing it.

[0743] "Information analysis means" refers to technology that analyzes collected biometric and audio information to identify the user's psychological state and health status.

[0744] "Fragrance generation means" refers to a device or system for generating the optimal fragrance combination based on the analyzed user's condition.

[0745] "Fragrance diffusion device means" refers to a device or system for blending generated fragrances in appropriate proportions and diffusing them into the environment.

[0746] "Feedback analysis means" refers to technology that collects and analyzes user feedback and incorporates the results into the next fragrance generation process to improve the overall system performance.

[0747] To implement this invention, a system is required that includes a user, a terminal, a server, various sensors, and an aroma dispenser. This system is configured to be attached to or carried by the user in a terminal owned by the user. The terminal includes sensors for acquiring biometric information, collecting data such as heart rate, body temperature, and respiratory rate in real time. Voice information is recorded by recording the user's conversation through a microphone mounted on the terminal and converted into text using speech recognition software.

[0748] The biometric and voice information collected by the device is sent to the server. The server receives this information and uses natural language processing technology to analyze the user's emotional state. For example, the server has a built-in generative AI model that determines the user's stress level and psychological tendencies from their voice. An example of a prompt used for voice analysis would be, "Please suggest the most suitable relaxation aroma based on the user's heart rate and voice data."

[0749] Based on the information analyzed by the server, an optimal aroma blend is generated for the user's psychological and health state. The selected aroma blend information is sent to the terminal, which controls the aroma dispenser. The dispenser, following the received instructions, blends the aroma oils in the appropriate proportions and diffuses the scent using a diffuser. This allows the user to receive a customized fragrance experience.

[0750] User feedback is sent to the server via the terminal. This feedback is used to optimize future fragrance generation and the overall system. For example, if a user who has accumulated stress from long hours of desk work shows an increased heart rate or a loud voice, it is possible to generate an aroma blend containing lavender and bergamot, which are suitable for relaxation, and diffuse it through a dispenser to help the user relax.

[0751] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0752] Step 1:

[0753] The device uses sensors to collect biometric information.

[0754] Input: Real-time data such as the user's heart rate, body temperature, and respiratory rate.

[0755] Data processing: Analog signals from sensors are converted into digital data, and smoothing and filtering are performed as needed.

[0756] Output: Formatted biometric data set.

[0757] Specific operation: Biometric data is captured every second, buffered within the device, and prepared for the next processing step at regular intervals.

[0758] Step 2:

[0759] The device records the user's voice through the microphone and converts it to text.

[0760] Input: User's voice signal.

[0761] Data processing: Convert audio signals into text data using speech recognition software.

[0762] Output: Audio data in text format.

[0763] Specific operation: Noise is removed from the audio signal using a feature extraction technique, and the audio is converted to text using a language model.

[0764] Step 3:

[0765] The server receives biometric and voice information transmitted from the terminal and performs analysis.

[0766] Input: Biometric data and text data transmitted from the device.

[0767] Data Processing: We analyze text data using natural language processing techniques to determine the user's emotional state. We also analyze biometric data using machine learning algorithms.

[0768] Output: Data representing the user's psychological and physical state.

[0769] Specific operation: A generative AI model on the server performs sentiment analysis on the speech-to-text data and calculates a health status score based on biometric data.

[0770] Step 4:

[0771] The server determines the optimal aroma blend based on the analysis results.

[0772] Input: Analyzed user psychological and health status data.

[0773] Data processing: Use prompt statements to instruct the generation AI model to create aroma blends.

[0774] Output: Aroma blend recipe information.

[0775] Specific operation: The server selects a combination of aroma oils from several options that is suitable for a specific emotional state and sends the information to the terminal.

[0776] Step 5:

[0777] The device controls the aroma dispenser to diffuse the fragrance.

[0778] Input: Aroma blend recipe information sent from the server.

[0779] Data processing: Generates control signals to blend essential oils in specified proportions.

[0780] Output: A scent of a carefully adjusted aroma blend.

[0781] Specific operation: The aroma dispenser mixes a specified amount of aroma oil and diffuses the scent around the user through the diffuser.

[0782] Step 6:

[0783] We collect feedback from users about their fragrance experience.

[0784] Input: User feedback information.

[0785] Data processing: The feedback data is formatted as reference information for the next aroma blend generation.

[0786] Output: Feedback data for analysis.

[0787] Specific operation: The user fills out an evaluation form on their device, and this information is automatically sent to the server. This data will be used to optimize the system in the future.

[0788] (Application Example 1)

[0789] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0790] In modern brick-and-mortar stores, there are limited ways to understand customers' psychological states and emotions in real time and optimize the store atmosphere accordingly. In particular, it is difficult to instantly provide the appropriate scent when a customer is stressed or seeking relaxation. By solving this problem, we aim to create a more pleasant shopping experience and increase store sales.

[0791] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0792] In this invention, the server includes information gathering means for processing biometric and voice information acquired from the user, information analysis means for analyzing the biometric and voice information to identify the user's emotional state, and fragrance blend generation means for generating an optimal fragrance according to the emotional state obtained by the information analysis means. This makes it possible to automatically select and diffuse an appropriate fragrance according to the customer's emotional state within a physical store.

[0793] "Information gathering means" refers to devices and methods for acquiring and processing biometric and voice information from users.

[0794] "Information analysis means" refers to devices and methods for analyzing acquired biometric and audio information to identify the user's emotional state.

[0795] A "fragrance blend generation method" refers to a device or method for generating the optimal fragrance combination based on the analyzed emotional state of the user.

[0796] A "fragrance diffusion means" refers to a device or method for blending a generated fragrance blend in appropriate proportions and diffusing it into the surrounding environment.

[0797] "Feedback collection means" refers to devices or methods for collecting user feedback based on the effects of fragrances and using that feedback to improve future fragrance creation.

[0798] "Environmental adjustment means" refers to devices or methods for automatically selecting the optimal scent according to the emotional state of customers within a physical store and adjusting the store environment.

[0799] The system implementing this invention will create an optimal purchasing environment by understanding the psychological state of customers in a physical store in real time and automatically providing a corresponding fragrance. Specifically, the following means will be combined.

[0800] The server uses information gathering methods to acquire biometric information from customers' smart devices. For example, data such as heart rate and body temperature are collected through sensors in smartphones and smartwatches. The devices are also equipped with high-quality microphones, which are used to collect audio information of conversations between customers and staff. This data is transmitted to the server via wireless communication technology.

[0801] The server analyzes this data using natural language processing tools (e.g., NLTK and spaCy) and machine learning tools (e.g., TensorFlow and PyTorch) as information analysis tools. It identifies the user's emotional state from biometric and voice information, and the fragrance blend generation mechanism operates based on the analysis results.

[0802] The fragrance blend generation system selects the most suitable fragrance for a given emotional state and distributes the combination from the server to the fragrance diffusion system within the store. Diffusers are placed throughout the store, which then spread the selected fragrance throughout the premises. The diffusers are controlled to blend the fragrances and automatically diffuse them at the appropriate times.

[0803] Furthermore, using a feedback collection system, customers input their impressions and evaluations of the scents they experienced via a terminal, and this feedback is sent to a server so that it can be reflected in future scent selection processes. Through this feedback loop, the system is continuously optimized, and the store's scent environment becomes more tailored to customer needs.

[0804] For example, if the server determines that a customer visiting the store is experiencing stress, the system will select relaxing scents such as lavender or bergamot and diffuse them throughout the store to promote relaxation. An example of a prompt used might be, "Please describe the process of selecting the optimal aroma to reduce stress."

[0805] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0806] Step 1:

[0807] The device acquires biometric information from the customer. Specifically, it measures biometric data such as heart rate and body temperature using a smartphone or smartwatch. This data is transmitted to a server via Bluetooth or Wi-Fi. The input is the customer's biometric information, and the output is the set of biometric data transmitted to the server. The data processing performed in this step is the conversion of analog signals obtained from biosensors into digital data.

[0808] Step 2:

[0809] The terminal records conversations between customers and staff to acquire audio information. It collects audio data using a built-in microphone and converts it into text data. The input is the audio data of the conversation, and the output is the transcribed conversation. The audio data is converted into text by speech recognition software.

[0810] Step 3:

[0811] The server receives biometric data and text data obtained from voice. The server uses natural language processing tools to analyze the emotional state from the text data. The input is text data and biometric data, and the output is the analysis result indicating the customer's emotional state. A generative AI model is used for emotion classification in the data calculations.

[0812] Step 4:

[0813] The server determines the fragrance blend based on the analyzed emotional state. It selects a fragrance combination and sends instructions to the fragrance diffusion system. The input is the result of the emotional analysis, and the output is the fragrance combination. The server uses pre-configured prompt sentences and a generating AI model to select the optimal blend.

[0814] Step 5:

[0815] The terminal controls the diffusers in the store to diffuse the selected fragrance. It adjusts the amount of fragrance released from the diffuser at the appropriate time. The input is information about the fragrance combination, and the output is the actual fragrance that is diffused. The diffuser's operation involves blending and diffusing the fragrance based on the proportions of the selected essential oils.

[0816] Step 6:

[0817] Users input feedback about the scents they experience into a terminal. They input their evaluation of the scent's effects as text and send it to the server. The input is the user's feedback text, and the output is feedback data. The feedback data is used to optimize the future scent selection process.

[0818] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0819] One embodiment of the present invention is an emotion engine that accurately recognizes the user's emotions, and a system that provides an optimal aroma experience based on this engine. This system consists of a user, a terminal, a server, various sensors, an aroma dispenser, and the emotion engine. The embodiments thereof will be described in detail below in natural language.

[0820] Data collection and emotion recognition

[0821] The device connects to the user and acquires biometric data in real time through sensors. This biometric data includes heart rate, body temperature, and respiratory rate. Next, the device collects the user's voice data and records the conversation through a microphone. The voice data is converted into text using natural language processing technology and sent to a server. The server analyzes this text data and biometric data with an emotion engine to comprehensively evaluate the user's emotional state. This engine combines changes in the user's voice tone and biometric indicators to identify a precise emotional state.

[0822] Aroma blend creation and application

[0823] Based on the analysis results from the emotion engine, the server selects the aroma blend best suited to the user's current emotional state. The selected aroma recipe is sent to the terminal, which controls the aroma dispenser to mix the essential oils as instructed. The terminal then diffuses this blended aroma around the user through a diffuser, promoting effects such as relaxation and improved concentration.

[0824] Feedback and adjustments

[0825] Users provide feedback on the effects of the fragrance and input the results into their device. This feedback is collected on the server and, along with analysis by the emotion engine, is used to improve future aroma blend generation. This feedback loop allows the system to continuously improve the fragrance experience delivered to each user, adapting to their individual changes and preferences.

[0826] Specific example

[0827] For example, if a user is feeling nervous before an important presentation, the device detects an increase in heart rate from biometric data and identifies an anxious tone through voice analysis. The emotion engine determines this to be a high-stress state, and the server creates an aroma blend with corresponding relaxation effects. The device diffuses a scent containing lavender and bergamot, allowing the user to feel relaxed. Through this process, the user can approach the presentation in a better state of mind.

[0828] The following describes the processing flow.

[0829] Step 1:

[0830] The device collects biometric data in real time through sensors attached to the user. Specifically, it acquires data such as heart rate, body temperature, and respiratory rate.

[0831] Step 2:

[0832] The device uses its microphone to collect user voice data. It records the user's conversation and converts it to text using speech recognition technology.

[0833] Step 3:

[0834] The biometric and voice data collected by the device are encrypted and sent to the server in a secure manner.

[0835] Step 4:

[0836] The server applies natural language processing to the transmitted audio data and analyzes the user's emotional state from the content of their conversation.

[0837] Step 5:

[0838] The server inputs biometric data into an emotion engine, which analyzes changes in heart rate and body temperature to evaluate the user's stress level and psychological state.

[0839] Step 6:

[0840] Based on the analysis results of the emotion engine, the server determines the optimal aroma blend for the user's current emotional state and sends the recipe to the device.

[0841] Step 7:

[0842] The terminal operates the aroma dispenser, blends the specified aroma oils in the appropriate proportions, and diffuses the scent using a diffuser.

[0843] Step 8:

[0844] Users experience the scent and input feedback about its effects into a device.

[0845] Step 9:

[0846] The device sends user feedback to the server, which is then used as data to adjust the emotion engine's algorithm.

[0847] Step 10:

[0848] The server processes feedback and incorporates it into future aroma blend generation, continuously improving the user experience.

[0849] (Example 2)

[0850] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0851] In recent years, there has been a growing demand for personalized fragrance experiences tailored to the individual psychological state of each user. However, conventional systems have struggled to accurately grasp users' emotions and preferences and generate appropriate fragrances. There is a need to solve this problem and provide more precise and individualized fragrance experiences.

[0852] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0853] In this invention, the server includes information acquisition means, information analysis means, and fragrance generation means. This makes it possible to acquire and analyze the user's biometric data and voice data in real time, and to efficiently generate and provide fragrances adapted to the user's emotional state.

[0854] "Information acquisition means" refers to a device or system that provides the function of collecting biometric data and voice data from users in real time.

[0855] "Information analysis means" refers to a device or system that analyzes collected biometric data and voice data and provides a function for evaluating the user's emotional state and psychological state.

[0856] "Fragrance generation means" refers to a device or system for generating an appropriate fragrance based on the user's emotional state obtained through information analysis means.

[0857] A "fragrance diffusion means" is a device or system that provides the function of appropriately blending the generated fragrance and diffusing it into the surroundings.

[0858] "Evaluation means" refers to a device or system that has the function of collecting feedback from users based on the effects of diffused fragrances and reflecting that feedback in the next fragrance generation process.

[0859] The system of the present invention includes information acquisition means, information analysis means, fragrance generation means, fragrance diffusion means, and evaluation means in order to provide a personalized fragrance experience according to the user's psychological state.

[0860] The user connects to various sensors via a terminal, allowing for the real-time collection of biometric data such as heart rate, body temperature, and respiratory rate. The terminal also includes a microphone, collecting the user's voice data. The collected data is transmitted to a server via an information acquisition system. Specific devices used at this stage include standard biosensors and microphones.

[0861] The server processes the acquired biometric and voice data using information analysis tools. It utilizes natural language processing and signal processing technologies to identify the user's emotional state from the data. Specific software examples include voice recognition systems and data analysis algorithms. Based on the analysis results, a fragrance generation tool selects the optimal scent, and the server sends that recipe to the terminal.

[0862] The device controls the fragrance diffusion method based on the received fragrance recipe and diffuses the blended fragrance through the diffuser. The fragrance promotes relaxation and concentration effects that correspond to the user's psychological state.

[0863] Furthermore, users evaluate the effects of the scents they experience and input feedback into their devices. This feedback is collected by the evaluation system and reflected in future scent generation, thereby improving the system's personalization capabilities.

[0864] For example, when a user experiences stress, their heart rate often increases. The device detects this, and the server generates a relaxing blend based on lavender and bergamot. This allows the user to maintain a calmer state.

[0865] An example of input to the generative AI model could be a prompt such as, "Analyze the user's voice data and biometric data to generate the optimal relaxation fragrance blend." Through this prompt, the system can quickly and effectively provide fragrances tailored to the user's specific needs.

[0866] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0867] Step 1:

[0868] The device connects to the user and acquires biometric data in real time through various sensors. Specifically, it collects heart rate, body temperature, and respiratory rate from sensors and processes them as digital signals. This data is then input, and the device sends it to a server for data preparation.

[0869] Step 2:

[0870] The device uses a microphone to record the user's voice data. Speech recognition software is used to convert the recorded data into text, and this converted text data is sent to a server. The input is the user's voice data, and the output is text data. This data serves as preparation data for analyzing the user's linguistic characteristics.

[0871] Step 3:

[0872] The server uses information analysis tools to analyze the received biometric and text data. It employs natural language processing techniques to extract emotional keywords from the text and signal processing techniques to analyze patterns in the biometric data. The input consists of biometric and text data, and the output is an analysis result indicating the user's emotional state. Specifically, the server executes an analysis algorithm to evaluate the psychological state.

[0873] Step 4:

[0874] The server selects an appropriate scent using a fragrance generation system based on the analysis results. Past data and feedback are also considered, so the input consists of the analysis results and existing data such as stress reduction and concentration improvement. The output is the recipe for the selected scent. The server sends this recipe to the terminal.

[0875] Step 5:

[0876] The terminal controls the fragrance diffusion mechanism, operating the aroma dispenser according to the received fragrance recipe to mix the scents. Specifically, the terminal activates the diffuser and diffuses the blended fragrance. The input is the fragrance recipe, and the output is the diffusion of the fragrance.

[0877] Step 6:

[0878] Users input feedback into a terminal based on their fragrance experience. The feedback is analyzed on a server using an evaluation method; therefore, the input is user feedback, and the output is evaluation information that will be reflected in future fragrance creation. Specifically, the terminal sends the feedback to the server in a digital form, where it is recorded in a database.

[0879] (Application Example 2)

[0880] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0881] In today's commercial environment, there is a need for effective methods to respond to the diverse emotional states of customers and promote purchasing activity. Traditional methods have faced challenges in accurately understanding the psychological state of individual customers in real time and providing responsive services accordingly. In particular, while providing experiences using scent has the potential to significantly influence emotions, methods for directly linking them to the customer's state of mind have not been sufficiently developed.

[0882] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0883] In this invention, the server includes information gathering means for processing biometric data and voice data acquired from the user, information analysis means for analyzing the biometric data and voice data to identify the user's emotional state, and fragrance generation means for generating an appropriate fragrance according to the emotional state obtained by the information analysis means. This makes it possible to provide a fragrance experience tailored to the emotional state of each customer visiting a store in a commercial environment, thereby promoting purchasing activity.

[0884] "Information gathering means" refers to a system of devices and software that acquire and process biometric and voice data from users.

[0885] "Information analysis means" refers to technology or software that analyzes collected biometric and audio data to identify the user's emotional state.

[0886] A "fragrance generation means" is a device or system for blending the optimal fragrance according to the emotional state identified by an information analysis means.

[0887] A "fragrance diffusion means" is a mechanism or device that effectively diffuses a blended fragrance into the surrounding space.

[0888] A "feedback collection method" is a system that collects user reactions and evaluations based on the effects of fragrances and uses them to improve future fragrance creation.

[0889] A "commercial environment support device" is a device or system designed to promote purchasing activity by providing an appropriate fragrance experience based on the user's emotional state.

[0890] The system implementing this invention consists of a user, a terminal, a server, various sensors, a fragrance diffusion device, and an information analysis engine. The basic flow is shown below.

[0891] First, the device connects to the user to acquire biometric data. Through sensors, it collects vital data such as heart rate, body temperature, and respiratory rate in real time. Simultaneously, the device uses a microphone to collect the user's voice data, converts this data into text using natural language processing technology, and sends it to the server. The server analyzes the voice data using natural language processing technologies such as Google Cloud Natural Language API and spaCy, and processes the resulting text data and biometric data with an information analysis engine. This analysis identifies the user's emotional state.

[0892] Next, the server determines the most suitable scent for the user's current emotional state based on the results of the information analysis engine. The scent generation device blends the scents based on the identified recipe and sends the instructions to the terminal. The terminal controls the scent diffusion device to appropriately diffuse the required scent into the surrounding space.

[0893] Furthermore, the device collects feedback from users regarding the effects of the fragrance. This feedback is sent to a server and used to adjust the fragrance generation process for the next time. Through this feedback collection mechanism, the system improves its performance to provide the optimal experience for each individual user.

[0894] For example, if a customer is feeling stressed, the device can detect their emotions from their increased heart rate and tone of voice, and then provide a relaxing experience using the scents of lavender and bergamot. This process is expected to increase the customer's willingness to purchase. Examples of prompts include, "What scent would you recommend for relaxation time?" or "How would you describe your mood today in one word?"

[0895] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0896] Step 1:

[0897] The device acquires biometric data (heart rate, body temperature, respiratory rate) from the user through sensors. This data is fundamental information for evaluating the user's emotional state. Data from the sensors is provided as input, and a set of biometric data is stored in the device as output.

[0898] Step 2:

[0899] The device collects the user's voice using a microphone and converts the voice data into text data. This conversion uses the Google Cloud Natural Language API. The input is voice data, and the output is text data. The process involves recognizing the voice and converting it into text.

[0900] Step 3:

[0901] The device sends biometric and text data to the server. This data is received by the server as foundational data for evaluating the user's emotions. The input is a set of biometric and text data, and the output is the transfer of data to the server.

[0902] Step 4:

[0903] The server uses the received biometric and text data to analyze the user's emotional state using an information analysis engine. This analysis also utilizes a generative AI model for data analysis. Biometric and text data are provided as input, and the user's emotional state is identified as output.

[0904] Step 5:

[0905] The server uses a fragrance generation mechanism based on the analysis results to determine the optimal fragrance blend. The results of the data analysis are input into the fragrance generation algorithm, and a fragrance recipe is output. The input is the analyzed emotional state, and the output is the fragrance recipe.

[0906] Step 6:

[0907] The terminal controls the fragrance diffusion device to diffuse the fragrance into the space based on the fragrance recipe received from the server. The fragrance, blended by the fragrance generation means, spreads to the surroundings by the device. The input is the fragrance recipe, and the output is the diffusion of the fragrance.

[0908] Step 7:

[0909] The user inputs feedback on the effects of the fragrance into the terminal. This feedback is sent to the server as data for the next fragrance generation. The input is user feedback information, and the output is data transfer to the server.

[0910] Step 8:

[0911] The server receives feedback from users and incorporates the data into the information analysis engine for the next fragrance generation. This allows the system's fragrance generation method to be improved based on subsequent adjustments. The input is user feedback, and the output is the updated analysis parameters.

[0912] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0913] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0914] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0915] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0916] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0917] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0918] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0919] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0920] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0921] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0922] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0923] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0924] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0925] 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.

[0926] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0927] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0928] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0929] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0930] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0931] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0932] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0933] The following is further disclosed regarding the embodiments described above.

[0934] (Claim 1)

[0935] A data collection means for processing biometric data and voice data obtained from users,

[0936] A data analysis means that analyzes the aforementioned biometric data and voice data to identify the user's psychological state,

[0937] An aroma blend generation means that generates an appropriate scent according to the psychological state obtained by the data analysis means,

[0938] An aroma dispenser means for mixing the aforementioned aroma blend in an appropriate proportion and diffusing it into the surroundings,

[0939] A feedback means for collecting user feedback based on the effects of the aforementioned fragrance and reflecting it in the next fragrance generation,

[0940] A system that includes this.

[0941] (Claim 2)

[0942] The data analysis means determines the user's emotional state from voice data using natural language processing technology, according to claim 1.

[0943] (Claim 3)

[0944] The system according to claim 1, wherein the biometric data includes heart rate, body temperature, or respiratory rate.

[0945] "Example 1"

[0946] (Claim 1)

[0947] Information collection means for processing biometric and voice information obtained from users,

[0948] Information analysis means for analyzing the aforementioned biometric and voice information to identify the user's psychological state,

[0949] A fragrance generation means that generates an optimal fragrance according to the psychological state obtained by the information analysis means,

[0950] A fragrance diffusion device means for blending the fragrance determined by the fragrance generating means in an appropriate proportion and diffusing it into the environment,

[0951] A feedback analysis means for collecting user feedback based on the effects of the aforementioned fragrance and reflecting it in the next fragrance generation,

[0952] A system that includes this.

[0953] (Claim 2)

[0954] The information analysis means determines the user's emotional state from voice information using natural language processing, according to claim 1.

[0955] (Claim 3)

[0956] The system according to claim 1, wherein the biological information includes heart rate, body temperature, or respiratory rate.

[0957] "Application Example 1"

[0958] (Claim 1)

[0959] Information collection means for processing biometric and voice information obtained from users,

[0960] Information analysis means for analyzing the aforementioned biometric and voice information to identify the user's emotional state,

[0961] A fragrance blend generation means that generates an optimal fragrance according to the emotional state obtained by the information analysis means,

[0962] A fragrance diffusion means for mixing the aforementioned fragrance blend in an appropriate proportion and diffusing it into the surroundings,

[0963] A feedback collection means for collecting user feedback based on the effects of the aforementioned fragrance and reflecting it in the next fragrance generation,

[0964] An environmental adjustment mechanism for automatically selecting and diffusing the optimal scent according to the customer's emotional state within a physical store,

[0965] A system that includes this.

[0966] (Claim 2)

[0967] The information analysis means determines the user's emotional state from voice information using natural language processing technology, according to claim 1.

[0968] (Claim 3)

[0969] The system according to claim 1, wherein the biological information includes heart rate, body temperature, or respiratory rate.

[0970] "Example 2 of combining an emotion engine"

[0971] (Claim 1)

[0972] Information acquisition means for processing biometric data and voice data obtained from users,

[0973] Information analysis means for analyzing the aforementioned biometric data and voice data to identify the user's psychological state,

[0974] A fragrance generating means that generates an appropriate fragrance according to the psychological state obtained by the information analysis means,

[0975] A fragrance diffusion means for blending the fragrance produced by the fragrance generating means in an appropriate proportion and diffusing it into the surroundings,

[0976] An evaluation means for collecting user feedback based on the effects of the aforementioned fragrance and reflecting it in the next fragrance creation,

[0977] A system that includes this.

[0978] (Claim 2)

[0979] The information analysis means determines the user's emotional state from voice data using natural language processing technology, according to claim 1.

[0980] (Claim 3)

[0981] The system according to claim 1, wherein the biometric data includes heart rate, body temperature, or respiratory rate.

[0982] "Application example 2 of combining emotional engines"

[0983] (Claim 1)

[0984] Information gathering means for processing biometric data and voice data obtained from users,

[0985] Information analysis means for analyzing the aforementioned biometric data and voice data to identify the user's emotional state,

[0986] A fragrance generation means that generates an appropriate fragrance according to the emotional state obtained by the information analysis means,

[0987] A fragrance diffusion means for blending the aforementioned fragrance in an appropriate proportion and diffusing it into the space,

[0988] A feedback collection means for collecting user feedback based on the effects of the aforementioned fragrance and reflecting it in the next fragrance generation,

[0989] By providing a fragrance experience suitable to the emotional state of the user, this is a means of supporting a commercial environment that promotes purchasing activity.

[0990] A system that includes this.

[0991] (Claim 2)

[0992] The information analysis means determines the user's emotional state from voice data using natural language processing technology, according to claim 1.

[0993] (Claim 3)

[0994] The system according to claim 1, wherein the biometric data includes heart rate, body temperature, or respiratory rate, and provides a fragrance experience tailored to the emotional state of a customer in a commercial environment. [Explanation of Symbols]

[0995] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A data collection means for processing biometric data and voice data obtained from users, A data analysis means that analyzes the aforementioned biometric data and voice data to identify the user's psychological state, An aroma blend generation means that generates an appropriate scent according to the psychological state obtained by the data analysis means, An aroma dispenser means for mixing the aforementioned aroma blend in an appropriate proportion and diffusing it into the surroundings, A feedback means for collecting user feedback based on the effects of the aforementioned fragrance and reflecting it in the next fragrance generation, A system that includes this.

2. The data analysis means determines the user's emotional state from voice data using natural language processing technology, according to claim 1.

3. The system according to claim 1, wherein the biometric data includes heart rate, body temperature, or respiratory rate.

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