system

Abstract

We provide the system. [Solution] Equipment for collecting visitor biometric information, An inference device for estimating an emotional state using the aforementioned biological information, A generating device that generates visual and auditory content based on the estimated emotional state, A system including a terminal for displaying the generated content.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is 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 character of the chatbot, 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 information overload and are emotionally exhausted. Especially among the young to middle-aged people living in urban areas, there is a lack of entertainment experiences according to their own emotions and hobbies, which has an adverse impact on physical and mental health. Therefore, there is a need to provide entertainment and relaxation experiences customized according to individual emotional states.

Means for Solving the Problems

[0005] This invention first provides a means for collecting biometric information from visitors. Next, it uses an inference device to estimate the emotional state based on that biometric information. Then, it uses a generation device to generate visual and auditory content according to the estimated emotional state. The generated content is easily displayed on a terminal. Furthermore, it provides a system that can receive feedback from visitors and continuously personalize the content generated based on that feedback.

[0006] A "visitor" is an individual whose biometric information is collected, whose emotional state is estimated, and who is subject to the provision of content.

[0007] "Biometric information" is a general term for data that indicates a visitor's physical condition, such as heart rate, body temperature, activity level, and facial expression data.

[0008] "Devices" is a general term for devices and equipment used to collect biological information.

[0009] An "inference device" refers to a computing device or algorithm used to estimate emotional states based on collected biometric information.

[0010] "Emotional state" is a concept that represents information indicating a visitor's psychological or emotional state.

[0011] A "generating device" refers to a device or software that generates visual or auditory content based on an estimated emotional state.

[0012] "Visual and auditory content" refers to media content such as music and images that can be seen with the eyes and heard with the ears.

[0013] "Terminal" refers to a device used to display generated content to visitors.

[0014] "Feedback" refers to the evaluation and opinions of the content provided by visitors, which is information used for content personalization.

[0015] "Personalization" refers to the process of optimizing the content provided according to the individual preferences and states of visitors.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the language used in the following description will be explained.

[0019] In the following embodiments, the 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.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the 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.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention is a system that collects visitors' biometric information and provides visual and auditory content based on that information. An embodiment of this system is described in detail below.

[0038] First, the device acquires biometric information from the visitor. Wearable devices such as smartwatches and smartphones are used for this purpose. Such devices can collect information such as heart rate, body temperature, activity level, and facial expression data in real time. For example, if a user is wearing a smartwatch, the device will continuously record the user's heart rate and step count.

[0039] Biometric information transmitted from the device is received and stored by the server. Based on the received data, the server uses an AI model to estimate the visitor's emotional state. This estimation is performed in real time; for example, by analyzing facial expression data, the server determines emotions such as "happy" if the user is smiling or "stressed" if they have a grim expression.

[0040] Based on the estimated emotional state, the server generates visual and auditory content. This generated content is optimized for the visitor's emotions, such as relaxing music or images of natural landscapes. This is done by a generative AI model, aiming to provide the visitor with the desired experience.

[0041] The generated content is sent to the device and displayed there visually or audibly. Users can experience the displayed content through their device; for example, they might listen to jazz music or view calming ocean images to relax after returning home. Users can rate this experience and provide feedback through the app.

[0042] User feedback is collected and analyzed on the server. Based on this analysis, content personalization for each visitor is continuously improved. The server uses this feedback to adjust the generation algorithm and provide even more optimized content on subsequent visits.

[0043] This system aims to provide users with personalized experiences tailored to their individual needs, offering entertainment and relaxation that responds to their emotions on a daily basis.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The device collects biometric information from the user's smartwatch or smartphone. This includes heart rate, body temperature, and facial expression data. The device acquires this data in real time and prepares it for transmission to a server.

[0047] Step 2:

[0048] The server receives biometric information transmitted from the terminal. The received data is processed immediately and stored in the database. The server then prepares this data for the next processing stage.

[0049] Step 3:

[0050] The server uses an AI model based on biometric information to estimate the user's emotional state. The AI ​​model determines the user's emotional state in real time from various collected data. Based on this result, it determines the content to be generated.

[0051] Step 4:

[0052] The server generates visual and auditory content using a generative AI model based on the user's emotional state. The generated content, such as relaxing music and nature images, is optimized for the user's current emotional state.

[0053] Step 5:

[0054] The server sends the generated visual and auditory content to the device. The content is then ready to be displayed on the user's device, such as a smartphone or AR glasses.

[0055] Step 6:

[0056] The device displays generated content to the user. Visual content is displayed on the screen, while auditory content is played through speakers or headphones. The user experiences relaxation or entertainment based on the displayed content.

[0057] Step 7:

[0058] Users provide feedback on the content they experience through their device. This feedback is provided based on the user's preferences and the quality of their experience, and is used to improve personalization for future experiences.

[0059] Step 8:

[0060] The device sends user feedback to the server. The server receives this feedback, stores it in a database, and prepares it for analysis.

[0061] Step 9:

[0062] The server analyzes user feedback and uses it to refine the generated AI model. This allows the content provided on subsequent visits to evolve to better suit the user's preferences.

[0063] (Example 1)

[0064] 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."

[0065] In modern society, there is a demand for entertainment and relaxation tailored to the psychological state of individuals. However, with conventional technology, it has been difficult to provide customized visual and auditory content that matches the visitor's mental state at any given time, making it challenging to improve visitor satisfaction.

[0066] 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.

[0067] In this invention, the server includes a device means for acquiring the visitor's biometric characteristics, an algorithm means for estimating the visitor's psychological state using the biometric characteristics, and a process means for generating visual and auditory outputs based on the estimated psychological state. This makes it possible to provide optimal content in real time that is tailored to the visitor's individual psychological state.

[0068] A "visitor" is an individual whose biometric characteristics are acquired by the system and who is the target of content provision.

[0069] "Biological characteristics" refer to physical or physiological information about a visitor, such as heart rate, body temperature, activity level, and facial expression.

[0070] "Device means" refers to hardware equipment used to acquire the visitor's biometric characteristics, and includes, for example, smartwatches and smartphones.

[0071] "Psychological state" refers to the visitor's emotional state, stress level, happiness level, and other mental conditions.

[0072] "Algorithmic methods" refer to computational methods and programs for estimating psychological states based on biological characteristics.

[0073] "Process means" refers to a series of processes that generate visual and auditory outputs based on an estimated psychological state.

[0074] "Output" refers to content delivered through visual or auditory means that is adapted to the estimated psychological state.

[0075] "Display device means" refers to a device for showing the generated output to visitors, and includes displays and speakers.

[0076] "Feedback" refers to the evaluations and opinions that visitors give to the content provided.

[0077] "Analysis methods" refer to the process of analyzing feedback collected from visitors and using that information to create future content.

[0078] This invention is a system that acquires the biometric characteristics of visitors, estimates their emotional state based on that information, and provides appropriate visual and auditory content. The system mainly consists of three entities: a terminal, a server, and a user.

[0079] First, the device acquires biometric characteristics from the visitor. The hardware used here includes wearable devices such as smartwatches and smartphones. These devices have the ability to collect heart rate, body temperature, activity level, and facial expression data in real time. This allows for a detailed understanding of the visitor's current physical and mental state.

[0080] Next, the biometric characteristics collected by the device are sent to the server. The server receives and stores this information. The server also uses an AI model based on the received data to estimate the visitor's psychological state. Specifically, it analyzes the data using algorithms such as neural networks to determine emotions such as "happiness" and "stress." This analysis is performed in real time, and an evaluation is made that is appropriate to the visitor's instantaneous state.

[0081] Based on the psychological state estimated by the server, a generative AI model is used to generate visual and auditory outputs. In this process, the server sets prompts to generate jazz music or calming nature images if it detects a psychological state such as "relaxed." A specific example of a prompt might be, "Generate relaxing music to reduce the user's current stress level."

[0082] Finally, the generated output is sent to the device. The device presents this content to the visitor, providing a visual and auditory experience. Users can experience the displayed content through the device and provide feedback on their results. This feedback is collected on the server and used as data to improve the quality of future output.

[0083] This system allows users to enjoy personalized entertainment tailored to their emotional state at any given time.

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] The terminal acquires the visitor's biometric characteristics. The input here is information obtained from wearable devices worn or carried by the visitor. Specifically, the terminal reads heart rate and activity level information from the smartwatch's sensors and captures facial expression data with the smartphone's camera. This results in output data that quantifies the visitor's physical state in real time.

[0087] Step 2:

[0088] The device collects biometric data and transmits it to the server. The input is biometric data acquired by the device, and the output is encrypted digital data sent to the server. The specific operation includes organizing the data on the device, packetizing the data according to security protocols, and transmitting it to the server via the internet.

[0089] Step 3:

[0090] The server receives and stores biometric data. The input is biometric information data transmitted from the terminal, and the output is biometric data stored in the database. The server converts the data into a parseable format and stores it in the database with a timestamp.

[0091] Step 4:

[0092] The server estimates the visitor's psychological state based on biometric data. The input is stored biometric data, and the output is the determined psychological state. The server uses an AI model to analyze the data and performs specific actions such as classifying emotions by evaluating changes in heart rate and facial expression data using a neural network.

[0093] Step 5:

[0094] The server generates visual and auditory outputs corresponding to the estimated psychological state. The input is the psychological state determination result, and the output is the generated visual and auditory content. Using a generative AI model, it creates content based on prompts and performs specific actions such as selecting music and video materials.

[0095] Step 6:

[0096] The server sends the generated content to the terminal. The input is the generated content data, and the output is the playable content sent to the terminal. The server compresses the content data before transfer and performs specific actions to ensure smooth playback on the terminal.

[0097] Step 7:

[0098] The user experiences content presented through the device. The input is the content received by the device, and the output is the user's experience and feedback. The user performs specific actions such as viewing visual images on the display or listening to auditory content through speakers.

[0099] Step 8:

[0100] Users provide feedback on the content. The input is an evaluation based on the user's experience, and the output is feedback data. Users use an app on their device to input their evaluation on the interface and send the feedback to the server.

[0101] Step 9:

[0102] The server analyzes the feedback and uses it to generate content for the next time. The input is user feedback data, and the output is the improved algorithm settings. The server aggregates the feedback and adjusts the generation algorithm to generate more personalized content for the next visit.

[0103] (Application Example 1)

[0104] 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."

[0105] Traditional stores face the challenge of providing timely and appropriate product information and promotions based on visitors' emotions and circumstances. This can result in visitors not receiving the information they need, thus failing to stimulate their purchasing intent.

[0106] 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.

[0107] In this invention, the server includes means for using a device for collecting visitor biometric information, means for using an inference device for estimating an emotional state using the biometric information, and means for utilizing a generation device for generating visual and auditory content based on the estimated emotional state and displaying it in the store. This makes it possible to provide optimal product information and promotions in real time based on the visitor's emotions.

[0108] A "visitor" refers to an individual who comes to a store or facility, and whose biometric information is subject to measurement and collection.

[0109] "Biometric information" refers to data that indicates an individual's current physical state, such as heart rate, body temperature, activity level, and facial expression data.

[0110] "Device" refers to hardware used to collect or display visitors' biometric information, including smartwatches and smartphones.

[0111] An "inference device" refers to a computing device used to estimate a visitor's emotional state based on collected biometric information.

[0112] "Emotional state" represents the visitor's current psychological condition and, as an estimated result, indicates specific emotions such as "happiness" or "stress."

[0113] A "generation device" refers to a system for generating visual and auditory content based on an estimated emotional state.

[0114] "Content" refers to visual or auditory information provided to visitors, including relaxing music and images of natural landscapes.

[0115] A "display device" refers to a device used to provide generated content to visitors visually or audibly.

[0116] "Feedback" refers to the evaluations and opinions that visitors provide after experiencing content, and this data is used to optimize future content.

[0117] A "store" refers to a physical location or commercial facility that visitors go to, where biometric information is collected and content is displayed.

[0118] The system for carrying out this invention aims to collect visitor biometric information and use it to provide personalized visual and auditory content. The hardware used includes smartwatches, smartphones, smart glasses, and in-store displays. The software uses AI models developed in Python (e.g., TENSORFLOW®), smartphone applications (iOS / ANDROID®), and generative AI models (e.g., OpenAI® GPT).

[0119] The terminal collects biometric information in real time via wearable devices such as smartwatches and smartphones. This includes heart rate, body temperature, activity level, and facial expression data. The terminal transmits the data to a server via Bluetooth or other means. The server-side AI model estimates the visitor's emotional state based on the received data.

[0120] By utilizing a generative AI model, visual and auditory content optimized for the estimated emotional state is generated. This generated content is displayed to visitors through in-store displays and smart glasses. This allows visitors to receive product information and promotions tailored to their current emotional state.

[0121] For example, if a visitor is relaxed, the display will show clothing in calming colors, while if they are active, promotions for new, colorful clothing will be shown. Feedback on the content the user experiences is sent to the server via the smartphone app and used to generate even more optimized content for their next visit.

[0122] An example of a prompt to a generative AI model is, "Generate a promotional video that allows the user to enjoy the purchase in a relaxed and elegant atmosphere." In this way, the visitor experience is tailored to individual needs through the use of biometric information and AI technology.

[0123] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0124] Step 1:

[0125] The device collects visitor biometric information via a smartwatch or smartphone. This includes acquiring heart rate, body temperature, activity level, and facial expression data. The data is stored on the device in real time and transmitted to a server via Bluetooth.

[0126] Step 2:

[0127] The server receives biometric information and stores it in a database. The input here is biometric information from the terminal, and the output is the stored data. This data forms the basis for subsequent emotion estimation.

[0128] Step 3:

[0129] The server uses an AI model (such as TensorFlow) to estimate the visitor's emotional state from biometric data. Specifically, it feeds the model with stored biometric data as input and performs analysis using facial recognition technology. The output is an emotional state such as "happy" or "stressed."

[0130] Step 4:

[0131] The server uses a generative AI model (such as OpenAI GPT) to generate visual and auditory content based on the estimated emotional state. The input is the emotional state, and the generated content is the output. The prompt is "Generate a promotional video that allows the user to enjoy a purchase in a relaxed and elegant atmosphere."

[0132] Step 5:

[0133] The server transmits the generated content to in-store displays and users' smart glasses for display. The input here is the generated content, and the output is product information and promotional videos that visitors see. Users can receive relevant information through the displays.

[0134] Step 6:

[0135] Users submit feedback via a smartphone app after experiencing the provided content. Visitors' comments and ratings are entered into the app as input and sent to the server.

[0136] Step 7:

[0137] The server analyzes user feedback data and adjusts the AI ​​model and generation algorithm based on the results. The input here is the feedback data, and the output is optimized model parameters for future content generation. This results in more personalized content on subsequent visits.

[0138] 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.

[0139] This invention is a system that collects visitor biometric information, combines it with an emotion engine that recognizes the user's emotions based on that information, and provides visual and auditory content. This embodiment is as follows:

[0140] First, the terminal acquires the visitor's biometric information. Smartwatches and smartphones are used as the necessary devices for this. These devices sense heart rate, body temperature, activity level, facial expression data, etc., in real time and prepare to send the data to the server. If the user is wearing a smartwatch, the device continuously records steps and heart rate and sends them to the terminal.

[0141] Next, the server receives biometric information transmitted from the terminal. The data collected by the server is recorded in a database and prepared for analysis by the emotion engine. The emotion engine integrates multiple received data points and has the function of estimating the user's emotional state with high accuracy. For example, it analyzes changes in facial expression and increases in heart rate in combination to determine the state of stress.

[0142] Based on the estimated emotional state, the server uses a generative AI model to generate visual and auditory content. This content is tailored to the user's emotions, such as relaxing music or natural scenery. The generated content is optimized to maximize the user experience and continuously updates as needed, adapting to real-time changes in emotions.

[0143] The generated content is sent to the device. The device then displays the content on the smartphone's screen or AR glasses and provides it to the user. For example, if the user is feeling stressed, the device might create a calming environment by displaying relaxing music and images of a tranquil ocean.

[0144] Furthermore, users can provide feedback on the content provided. Users input their opinions and preferences regarding the experience through their device, and this feedback is sent to the server. The server analyzes this feedback and uses it to train and refine the generative AI model. This allows for further personalized content to be generated in the future, providing users with the best possible experience.

[0145] Thus, this system, which includes an emotion engine, provides entertainment and relaxation tailored to the user's emotions in their daily life, creating experiences that are unique to each individual user.

[0146] The following describes the processing flow.

[0147] Step 1:

[0148] The device collects biometric information from the user's smartwatch or smartphone. This includes heart rate, body temperature, activity level, and facial expression data, all of which are obtained in real time.

[0149] Step 2:

[0150] The device transmits the collected biometric information to the server. The data is transmitted using a secure communication protocol, and the server prepares to process the received data in real time.

[0151] Step 3:

[0152] The server stores the biometric information received from the terminal into a database. At this stage, the data is organized for analysis and prepared as a dataset to be used in the next step.

[0153] Step 4:

[0154] The server uses an emotion engine to estimate the user's overall emotional state based on biometric information. Here, the user's emotions are evaluated in detail through facial recognition and analysis of physiological data. Based on these results, guidelines for the next content to be generated are determined.

[0155] Step 5:

[0156] The server generates visual and auditory content using a generative AI model based on the estimated emotional state. For example, if the server determines that the user is stressed, it will generate relaxation music or calming nature images. This content is designed to meet the user's experience needs.

[0157] Step 6:

[0158] The server sends the generated content to the device. The content is provided in a format suitable for the user's device (for example, a video format for smartphones).

[0159] Step 7:

[0160] The device presents the acquired content to the user. The device provides visual and auditory stimuli through the screen display and speakers. The user can enjoy relaxation and entertainment through this content.

[0161] Step 8:

[0162] Users provide feedback on the content they experience via their devices. This feedback concerns the quality and satisfaction level of the content, as well as their preferences.

[0163] Step 9:

[0164] The device sends user feedback to the server. The server receives this feedback and uses it to improve the personalization of subsequent content generation processes.

[0165] Step 10:

[0166] The server adjusts the personalization algorithm of the generated AI model based on the feedback. This ensures that the content provided on subsequent visits is more tailored to the user's emotions and preferences.

[0167] (Example 2)

[0168] 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".

[0169] Traditional systems struggled to provide content that responded to visitors' instantaneous emotional changes, making it difficult to offer user-optimized entertainment and relaxation. Furthermore, there were problems with the accuracy of emotion estimation and the resulting real-time content generation.

[0170] 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.

[0171] In this invention, the server includes information acquisition means, communication means for transmitting biometric information to the server, analysis means for analyzing the received biometric information and estimating the emotional state, presentation means for transmitting and displaying the generated content on an operating terminal, and adaptive means for collecting user feedback and adjusting the generation means. This makes it possible to provide personalized content that responds to the visitor's instantaneous emotional changes.

[0172] "Information acquisition means" refers to devices or methods for collecting visitors' biometric information, and has the function of detecting heart rate, body temperature, facial expression data, etc.

[0173] "Communication means" refers to technologies and devices for transmitting acquired biometric information to a server, enabling highly secure and real-time data transmission.

[0174] "Analysis means" refers to processes and algorithms for analyzing biometric information received on a server and estimating the emotional state of visitors.

[0175] "Generation means" refers to methods or devices for creating visual and auditory content based on estimated emotional states, thereby generating content that is adapted to the user's emotions.

[0176] "Presentation means" refers to display devices and technologies for transmitting content generated on a server to an operating terminal and presenting it to the user.

[0177] "Adaptive measures" refer to methods and devices for adjusting the generation process based on user feedback and utilizing that feedback for future content generation.

[0178] This invention relates to a system that reads a user's emotional state based on a visitor's biometric information and provides corresponding visual and auditory content. This system includes information acquisition means, communication means, analysis means, generation means, presentation means, and adaptation means.

[0179] First, the terminal uses information acquisition methods to obtain biometric information from devices such as smartwatches and smartphones. This includes heart rate, body temperature, and facial expression data. A smartwatch, for example, can sense steps and heart rate in real time and immediately prepare the data for the next process.

[0180] The device uses communication methods to securely transmit acquired biometric information to a server. Wi-Fi or mobile networks are used for communication. This data is recorded in a database for subsequent analysis.

[0181] Next, the server utilizes analytical tools to process the recorded biometric information. The emotion engine, based on machine learning algorithms, combines data points to estimate the user's emotions. This allows for determinations such as whether the user is experiencing stress.

[0182] Subsequently, the server uses a generation mechanism to utilize a generative AI model to generate visual and auditory content that matches the estimated emotions. At this stage, the generative AI model is given prompts such as "Generate relaxing music and images of a forest for the user."

[0183] The generated content is transmitted to the user's device using a presentation device and displayed on the screen of a smartphone or AR glasses. For example, if the user is feeling tired, the device may display relaxing music and images of nature, providing the user with a calming environment.

[0184] Finally, users submit feedback on the provided content via their device. This feedback is sent to the server via adaptive means and used to adjust and improve the generated AI model. This is to provide users with even more optimized content in the future.

[0185] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0186] Step 1:

[0187] The device collects visitors' biometric information. This process utilizes smartwatches and smartphones to acquire heart rate, body temperature, activity levels, and facial expression data. Specifically, the smartwatch senses wrist movements and uses internal sensors to measure heart rate. The input is biometric information, which is detected in real time and output as a digital signal.

[0188] Step 2:

[0189] The device transmits collected biometric information to a server. Wi-Fi or mobile data networks are used to ensure the data reaches the server reliably. The device incorporates error checking functions and retransmits data as needed to maintain data integrity. The input is biometric information processed as a digital signal by the device, and the output is secure data transmission to the server.

[0190] Step 3:

[0191] The server records the received biometric information in a database. The information stored in the database is organized as a series of biometric data for the user. This makes the information efficiently accessible for subsequent processing. The input is biometric information sent from the terminal, and the output is the information recorded in the database in a structured form.

[0192] Step 4:

[0193] The server uses information to estimate the user's emotional state using an emotion engine. It analyzes biometric data such as heart rate variability and uses a predictive algorithm to estimate emotional states like stress and relaxation. Specifically, the server applies a machine learning model to map biometric information to different emotional states. The input is structured data stored in a database, and the output is the estimated emotional state.

[0194] Step 5:

[0195] The server uses a generative AI model to create appropriate visual and auditory content based on the estimated emotional state. The model receives prompts, which then generate music and images. An example of a generated prompt might be, "Generate music that will help the user relax." The input is the estimated emotional state and the prompt, while the output is the generated content.

[0196] Step 6:

[0197] The server sends the generated content to the device. The content is provided in a format that can be displayed on the user's smartphone or AR device. Specifically, the server streams generated music and image data to the device, which then immediately displays the content to the user. The input is the generated visual and auditory content, and the output is the transmission of data to the device.

[0198] Step 7:

[0199] Users submit feedback on the provided content via their devices. This feedback is recorded regarding the quality of the content and their personal impressions. The input is feedback based on the user's opinions and experiences, and the output is feedback data provided to the server.

[0200] Step 8:

[0201] The server receives feedback and uses it to refine the generative AI model. The feedback data is analyzed to help modify the model's parameters for future content generation processes. The input is user feedback, and the output is the improved parameters of the generative AI model.

[0202] (Application Example 2)

[0203] 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".

[0204] Traditionally, the customer experience in physical stores has been uniform, making it difficult to personalize it according to the emotions and psychological state of individual visitors. Furthermore, while there is a demand to increase customer satisfaction by providing appropriate content based on the visitor's real-time emotional state, a system to achieve this has not existed.

[0205] 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.

[0206] In this invention, the server includes a device for measuring the visitor's biometric data, a processing unit for analyzing the emotional state based on the biometric data, and a generation unit for generating visual and auditory media according to the analyzed emotional state. This makes it possible to provide customized content that is tailored to the individual physiological and psychological state of each visitor.

[0207] "Biometric data" refers to a collection of information that indicates an individual's physiological and psychological state, such as a visitor's heart rate, body temperature, activity level, and facial expression data.

[0208] A "processing unit" is a device or program that takes biometric data acquired from visitors as input, analyzes it, and has the function of estimating their emotional state.

[0209] A "generation unit" is a device or program that generates visual or auditory media content based on an analyzed emotional state.

[0210] A "terminal" is a device used to display generated media, and includes smartphones, tablets, digital signage, and other similar devices.

[0211] "Optimized media for enhancing customer experience" refers to content designed to meet the individual needs and emotions of each visitor, based on their individual physiological and psychological state.

[0212] The system for implementing this invention consists of a device for measuring visitors' biometric data, a processing unit for analyzing their emotional state, a generation unit for generating visual and auditory media, and a terminal for presenting the generated media. Details are described below.

[0213] The server collects biometric data in real time through smartwatches and smartphones worn by visitors. This includes information such as heart rate, body temperature, and facial expression data, which is transferred from the device to the server using Bluetooth technology. On the server, this data is stored in an SQL database to prepare for the next processing step.

[0214] The server's processing unit uses machine learning libraries such as TensorFlow to analyze biometric data and estimate the visitor's emotional state. Based on the estimated emotional state, a generative AI model is used to generate content using prompt text as input. Examples of these prompt texts include, "We want to estimate the visitor's emotional state based on their biometric information and generate visual content that helps the user relax," and "Please write a program that generates music and videos that respond to the customer's emotions to provide a personalized store experience."

[0215] The generation unit utilizes a generative AI model to create media content tailored to the user. For example, if a visitor is feeling stressed, it might create relaxing music and calming landscape images. The generated media is then sent to devices such as smart displays and tablets and presented at the appropriate time.

[0216] Users can provide feedback on the media presented, and this feedback is sent back to the server. The server analyzes this feedback and incorporates it into future media creation, enabling the provision of a more personalized experience. In this way, the present invention revolutionizes the customer experience in physical stores by providing media content optimized for the visitor's emotional state in real time.

[0217] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0218] Step 1:

[0219] The server receives biometric data via Bluetooth from a smart device worn by the visitor. This data includes heart rate, body temperature, and facial expression data. The server stores this received data in an SQL database. The input to this step is biometric data, and the output is saving the data to the SQL database.

[0220] Step 2:

[0221] The server retrieves stored biometric data and performs data analysis using machine learning libraries such as TensorFlow. Specifically, it analyzes heart rate variability and facial expression patterns to estimate emotional states. The input for this step is biometric data retrieved from an SQL database, and the output is the estimated emotional state.

[0222] Step 3:

[0223] The server creates and inputs an appropriate prompt message to the generative AI model based on the estimated emotional state. For example, a prompt message might be, "We want to generate relaxing content based on the visitor's biometric information." The input for this step is the estimated emotional state, and the output is the prompt message passed to the generative AI model.

[0224] Step 4:

[0225] The generative AI model generates visual and auditory media based on the received prompt text. Specifically, it generates relaxing music and nature scenery videos. The input for this step is the prompt text, and the output is the generated media content.

[0226] Step 5:

[0227] The server sends the generated media content to the device. The device displays the received content on a smart display or tablet. This provides visitors with customized content. The input for this step is the generated media content, and the output is the display of the content on the device.

[0228] Step 6:

[0229] The user provides feedback on the provided media. The terminal sends this feedback to the server, which analyzes the feedback data and uses it to improve future media generation. The input for this step is user feedback, and the output is information for improving the content to be generated next time.

[0230] 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.

[0231] 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.

[0232] 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.

[0233] [Second Embodiment]

[0234] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0235] 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.

[0236] 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).

[0237] 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.

[0238] 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.

[0239] 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).

[0240] 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.

[0241] 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.

[0242] 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.

[0243] 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.

[0244] 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.

[0245] 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".

[0246] This invention is a system that collects visitors' biometric information and provides visual and auditory content based on that information. An embodiment of this system is described in detail below.

[0247] First, the device acquires biometric information from the visitor. Wearable devices such as smartwatches and smartphones are used for this purpose. Such devices can collect information such as heart rate, body temperature, activity level, and facial expression data in real time. For example, if a user is wearing a smartwatch, the device will continuously record the user's heart rate and step count.

[0248] Biometric information transmitted from the device is received and stored by the server. Based on the received data, the server uses an AI model to estimate the visitor's emotional state. This estimation is performed in real time; for example, by analyzing facial expression data, the server determines emotions such as "happy" if the user is smiling or "stressed" if they have a grim expression.

[0249] Based on the estimated emotional state, the server generates visual and auditory content. This generated content is optimized for the visitor's emotions, such as relaxing music or images of natural landscapes. This is done by a generative AI model, aiming to provide the visitor with the desired experience.

[0250] The generated content is sent to the device and displayed there visually or audibly. Users can experience the displayed content through their device; for example, they might listen to jazz music or view calming ocean images to relax after returning home. Users can rate this experience and provide feedback through the app.

[0251] User feedback is collected and analyzed on the server. Based on this analysis, content personalization for each visitor is continuously improved. The server uses this feedback to adjust the generation algorithm and provide even more optimized content on subsequent visits.

[0252] This system aims to provide users with personalized experiences tailored to their individual needs, offering entertainment and relaxation that responds to their emotions on a daily basis.

[0253] The following describes the processing flow.

[0254] Step 1:

[0255] The device collects biometric information from the user's smartwatch or smartphone. This includes heart rate, body temperature, and facial expression data. The device acquires this data in real time and prepares it for transmission to a server.

[0256] Step 2:

[0257] The server receives biometric information transmitted from the terminal. The received data is processed immediately and stored in the database. The server then prepares this data for the next processing stage.

[0258] Step 3:

[0259] The server uses an AI model based on biometric information to estimate the user's emotional state. The AI ​​model determines the user's emotional state in real time from various collected data. Based on this result, it determines the content to be generated.

[0260] Step 4:

[0261] The server generates visual and auditory content using a generative AI model based on the user's emotional state. The generated content, such as relaxing music and nature images, is optimized for the user's current emotional state.

[0262] Step 5:

[0263] The server sends the generated visual and auditory content to the device. The content is then ready to be displayed on the user's device, such as a smartphone or AR glasses.

[0264] Step 6:

[0265] The device displays generated content to the user. Visual content is displayed on the screen, while auditory content is played through speakers or headphones. The user experiences relaxation or entertainment based on the displayed content.

[0266] Step 7:

[0267] Users provide feedback on the content they experience through their device. This feedback is provided based on the user's preferences and the quality of their experience, and is used to improve personalization for future experiences.

[0268] Step 8:

[0269] The device sends user feedback to the server. The server receives this feedback, stores it in a database, and prepares it for analysis.

[0270] Step 9:

[0271] The server analyzes user feedback and uses it to refine the generated AI model. This allows the content provided on subsequent visits to evolve to better suit the user's preferences.

[0272] (Example 1)

[0273] 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 glasses 214 will be referred to as the "terminal."

[0274] In modern society, there is a demand for entertainment and relaxation tailored to the psychological state of individuals. However, with conventional technology, it has been difficult to provide customized visual and auditory content that matches the visitor's mental state at any given time, making it challenging to improve visitor satisfaction.

[0275] 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.

[0276] In this invention, the server includes device means for acquiring the biometric characteristics of a visitor, algorithm means for estimating a psychological state using the biometric characteristics, and process means for generating visual and auditory outputs based on the estimated psychological state. As a result, it becomes possible to provide optimal content in real-time according to the individual psychological state of the visitor.

[0277] A "visitor" is an individual for whom the system acquires biometric characteristics and provides content.

[0278] "Biometric characteristics" refers to physical or physiological information of the visitor, such as heart rate, body temperature, activity level, and facial expression.

[0279] "Device means" refers to hardware devices used to acquire the biometric characteristics of the visitor, and includes, for example, smartwatches and smartphones.

[0280] "Psychological state" refers to mental situations such as the emotional state, stress level, and happiness level of the visitor.

[0281] "Algorithm means" refers to calculation methods or programs for estimating a psychological state based on biometric characteristics.

[0282] "Process means" refers to a series of processes for generating visual and auditory outputs based on the estimated psychological state.

[0283] "Output" refers to content provided through vision or audition adapted to the estimated psychological state.

[0284] "Display device means" refers to a device for showing the generated output to the visitor, and includes displays and speakers.

[0285] "Feedback" refers to evaluations and opinions made by the visitor regarding the content provided.

[0286] The "analysis means" refers to the process of analyzing the feedback collected from visitors and applying it to the generation of content in subsequent times.

[0287] This invention is a system that acquires the biometric characteristics of visitors, estimates their emotional state based on that information, and provides appropriate visual and auditory content. The system is mainly composed of three entities: a terminal, a server, and a user.

[0288] First, the terminal acquires the biometric characteristics from the visitor. The hardware used here includes wearable devices such as smartwatches and smartphones. These devices have the function of collecting heart rate, body temperature, activity level, and facial expression data in real time. Thus, the current physical and mental state of the visitor can be grasped in detail.

[0289] Next, the biometric characteristics collected by the terminal are transmitted to the server. The server receives and stores this information. Also, the server uses an AI model based on the received data to estimate the psychological state of the visitor. Specifically, algorithms such as neural networks are used to analyze the data and judge emotions such as "happy" and "stress". This analysis is performed in real time, and an evaluation corresponding to the instantaneous state of the visitor is made.

[0290] [[ID=1,6]]Based on the psychological state estimated by the server, a generative AI model is used to generate visual and auditory outputs. In this process, when the server detects a psychological state such as "relaxed", for example, it sets a prompt to generate jazz music or videos of gentle natural scenery. As a specific example of the prompt, an instruction such as "Please generate relaxing music to reduce the stress level that the user is currently experiencing." can be considered.

[0291] Finally, the generated output is sent to the device. The device presents this content to the visitor, providing a visual and auditory experience. Users can experience the displayed content through the device and provide feedback on their results. This feedback is collected on the server and used as data to improve the quality of future output.

[0292] This system allows users to enjoy personalized entertainment tailored to their emotional state at any given time.

[0293] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0294] Step 1:

[0295] The terminal acquires the visitor's biometric characteristics. The input here is information obtained from wearable devices worn or carried by the visitor. Specifically, the terminal reads heart rate and activity level information from the smartwatch's sensors and captures facial expression data with the smartphone's camera. This results in output data that quantifies the visitor's physical state in real time.

[0296] Step 2:

[0297] The device collects biometric data and transmits it to the server. The input is biometric data acquired by the device, and the output is encrypted digital data sent to the server. The specific operation includes organizing the data on the device, packetizing the data according to security protocols, and transmitting it to the server via the internet.

[0298] Step 3:

[0299] The server receives and stores biometric data. The input is biometric information data transmitted from the terminal, and the output is the biometric data stored in the database. The server performs specific operations of converting the data into an analyzable format and storing it in the database with a timestamp.

[0300] Step 4:

[0301] The server estimates the psychological state of the visitor based on the biometric data. The input is the stored biometric data, and the output is the determined psychological state. The server performs specific operations of analyzing the data using an AI model and evaluating changes in heart rate and expression data with a neural network to classify emotions.

[0302] Step 5:

[0303] The server generates visual and auditory outputs corresponding to the estimated psychological state. The input is the determination result of the psychological state, and the output is the generated visual and auditory content. The server performs specific operations of creating content based on a prompt using a generation AI model and selecting music and video materials.

[0304] Step 6:

[0305] The server transmits the generated content to the terminal. The input is the generated content data, and the output is the reproducible content transmitted to the terminal. The server performs specific operations of compressing and transferring the content data so that it can be smoothly played on the terminal side.

[0306] Step 7:

[0307] The user experiences the content presented via the terminal. The input is the content received by the terminal, and the output is the user's experience and feedback. The user performs specific operations such as viewing visual images on a display or listening to auditory content through a speaker. <舍

[0308] Step 8:

[0309] Users provide feedback on the content. The input is an evaluation based on the user's experience, and the output is feedback data. Users use an app on their device to input their evaluation on the interface and send the feedback to the server.

[0310] Step 9:

[0311] The server analyzes the feedback and uses it to generate content for the next time. The input is user feedback data, and the output is the improved algorithm settings. The server aggregates the feedback and adjusts the generation algorithm to generate more personalized content for the next visit.

[0312] (Application Example 1)

[0313] 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."

[0314] Traditional stores face the challenge of providing timely and appropriate product information and promotions based on visitors' emotions and circumstances. This can result in visitors not receiving the information they need, thus failing to stimulate their purchasing intent.

[0315] 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.

[0316] In this invention, the server includes means for using a device for collecting visitor biometric information, means for using an inference device for estimating an emotional state using the biometric information, and means for utilizing a generation device for generating visual and auditory content based on the estimated emotional state and displaying it in the store. This makes it possible to provide optimal product information and promotions in real time based on the visitor's emotions.

[0317] A "visitor" refers to an individual who comes to a store or facility, and whose biometric information is subject to measurement and collection.

[0318] "Biometric information" refers to data that indicates an individual's current physical state, such as heart rate, body temperature, activity level, and facial expression data.

[0319] "Device" refers to hardware used to collect or display visitors' biometric information, including smartwatches and smartphones.

[0320] An "inference device" refers to a computing device used to estimate a visitor's emotional state based on collected biometric information.

[0321] "Emotional state" represents the visitor's current psychological condition and, as an estimated result, indicates specific emotions such as "happiness" or "stress."

[0322] A "generation device" refers to a system for generating visual and auditory content based on an estimated emotional state.

[0323] "Content" refers to visual or auditory information provided to visitors, including relaxing music and images of natural landscapes.

[0324] A "display device" refers to a device used to provide generated content to visitors visually or audibly.

[0325] "Feedback" refers to the evaluations and opinions that visitors provide after experiencing content, and this data is used to optimize future content.

[0326] A "store" refers to a physical location or commercial facility that visitors go to, where biometric information is collected and content is displayed.

[0327] The system for carrying out this invention aims to collect visitor biometric information and use it to provide personalized visual and auditory content. The hardware used includes smartwatches, smartphones, smart glasses, and in-store displays. The software uses AI models developed in Python (e.g., TensorFlow), smartphone applications (iOS / Android), and generative AI models (e.g., OpenAI GPT).

[0328] The terminal collects biometric information in real time via wearable devices such as smartwatches and smartphones. This includes heart rate, body temperature, activity level, and facial expression data. The terminal transmits the data to a server via Bluetooth or other means. The server-side AI model estimates the visitor's emotional state based on the received data.

[0329] By utilizing a generative AI model, visual and auditory content optimized for the estimated emotional state is generated. This generated content is displayed to visitors through in-store displays and smart glasses. This allows visitors to receive product information and promotions tailored to their current emotional state.

[0330] For example, if a visitor is relaxed, the display will show clothing in calming colors, while if they are active, promotions for new, colorful clothing will be shown. Feedback on the content the user experiences is sent to the server via the smartphone app and used to generate even more optimized content for their next visit.

[0331] An example of a prompt to a generative AI model is, "Generate a promotional video that allows the user to enjoy the purchase in a relaxed and elegant atmosphere." In this way, the visitor experience is tailored to individual needs through the use of biometric information and AI technology.

[0332] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0333] Step 1:

[0334] The device collects visitor biometric information via a smartwatch or smartphone. This includes acquiring heart rate, body temperature, activity level, and facial expression data. The data is stored on the device in real time and transmitted to a server via Bluetooth.

[0335] Step 2:

[0336] The server receives biometric information and stores it in a database. The input here is biometric information from the terminal, and the output is the stored data. This data forms the basis for subsequent emotion estimation.

[0337] Step 3:

[0338] The server uses an AI model (such as TensorFlow) to estimate the visitor's emotional state from biometric data. Specifically, it feeds the model with stored biometric data as input and performs analysis using facial recognition technology. The output is an emotional state such as "happy" or "stressed."

[0339] Step 4:

[0340] The server uses a generative AI model (such as OpenAI GPT) to generate visual and auditory content based on the estimated emotional state. The input is the emotional state, and the generated content is the output. The prompt is "Generate a promotional video that allows the user to enjoy a purchase in a relaxed and elegant atmosphere."

[0341] Step 5:

[0342] The server transmits the generated content to in-store displays and users' smart glasses for display. The input here is the generated content, and the output is product information and promotional videos that visitors see. Users can receive relevant information through the displays.

[0343] Step 6:

[0344] Users submit feedback via a smartphone app after experiencing the provided content. Visitors' comments and ratings are entered into the app as input and sent to the server.

[0345] Step 7:

[0346] The server analyzes user feedback data and adjusts the AI ​​model and generation algorithm based on the results. The input here is the feedback data, and the output is optimized model parameters for future content generation. This results in more personalized content on subsequent visits.

[0347] 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.

[0348] This invention is a system that collects visitor biometric information, combines it with an emotion engine that recognizes the user's emotions based on that information, and provides visual and auditory content. This embodiment is as follows:

[0349] First, the terminal acquires the visitor's biometric information. Smartwatches and smartphones are used as the necessary devices for this. These devices sense heart rate, body temperature, activity level, facial expression data, etc., in real time and prepare to send the data to the server. If the user is wearing a smartwatch, the device continuously records steps and heart rate and sends them to the terminal.

[0350] Next, the server receives biometric information transmitted from the terminal. The data collected by the server is recorded in a database and prepared for analysis by the emotion engine. The emotion engine integrates multiple received data points and has the function of estimating the user's emotional state with high accuracy. For example, it analyzes changes in facial expression and increases in heart rate in combination to determine the state of stress.

[0351] Based on the estimated emotional state, the server uses a generative AI model to generate visual and auditory content. This content is tailored to the user's emotions, such as relaxing music or natural scenery. The generated content is optimized to maximize the user experience and continuously updates as needed, adapting to real-time changes in emotions.

[0352] The generated content is sent to the device. The device then displays the content on the smartphone's screen or AR glasses and provides it to the user. For example, if the user is feeling stressed, the device might create a calming environment by displaying relaxing music and images of a tranquil ocean.

[0353] Furthermore, users can provide feedback on the content provided. Users input their opinions and preferences regarding the experience through their device, and this feedback is sent to the server. The server analyzes this feedback and uses it to train and refine the generative AI model. This allows for further personalized content to be generated in the future, providing users with the best possible experience.

[0354] Thus, this system, which includes an emotion engine, provides entertainment and relaxation tailored to the user's emotions in their daily life, creating experiences that are unique to each individual user.

[0355] The following describes the processing flow.

[0356] Step 1:

[0357] The device collects biometric information from the user's smartwatch or smartphone. This includes heart rate, body temperature, activity level, and facial expression data, all of which are obtained in real time.

[0358] Step 2:

[0359] The device transmits the collected biometric information to the server. The data is transmitted using a secure communication protocol, and the server prepares to process the received data in real time.

[0360] Step 3:

[0361] The server stores the biometric information received from the terminal into a database. At this stage, the data is organized for analysis and prepared as a dataset to be used in the next step.

[0362] Step 4:

[0363] The server uses an emotion engine to estimate the user's overall emotional state based on biometric information. Here, the user's emotions are evaluated in detail through facial recognition and analysis of physiological data. Based on these results, guidelines for the next content to be generated are determined.

[0364] Step 5:

[0365] The server generates visual and auditory content using a generative AI model based on the estimated emotional state. For example, if the server determines that the user is stressed, it will generate relaxation music or calming nature images. This content is designed to meet the user's experience needs.

[0366] Step 6:

[0367] The server sends the generated content to the device. The content is provided in a format suitable for the user's device (for example, a video format for smartphones).

[0368] Step 7:

[0369] The device presents the acquired content to the user. The device provides visual and auditory stimuli through the screen display and speakers. The user can enjoy relaxation and entertainment through this content.

[0370] Step 8:

[0371] Users provide feedback on the content they experience via their devices. This feedback concerns the quality and satisfaction level of the content, as well as their preferences.

[0372] Step 9:

[0373] The device sends user feedback to the server. The server receives this feedback and uses it to improve the personalization of subsequent content generation processes.

[0374] Step 10:

[0375] The server adjusts the personalization algorithm of the generated AI model based on the feedback. This ensures that the content provided on subsequent visits is more tailored to the user's emotions and preferences.

[0376] (Example 2)

[0377] 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".

[0378] Traditional systems struggled to provide content that responded to visitors' instantaneous emotional changes, making it difficult to offer user-optimized entertainment and relaxation. Furthermore, there were problems with the accuracy of emotion estimation and the resulting real-time content generation.

[0379] 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.

[0380] In this invention, the server includes information acquisition means, communication means for transmitting biometric information to the server, analysis means for analyzing the received biometric information and estimating the emotional state, presentation means for transmitting and displaying the generated content on an operating terminal, and adaptive means for collecting user feedback and adjusting the generation means. This makes it possible to provide personalized content that responds to the visitor's instantaneous emotional changes.

[0381] "Information acquisition means" refers to devices or methods for collecting visitors' biometric information, and has the function of detecting heart rate, body temperature, facial expression data, etc.

[0382] "Communication means" refers to technologies and devices for transmitting acquired biometric information to a server, enabling highly secure and real-time data transmission.

[0383] "Analysis means" refers to processes and algorithms for analyzing biometric information received on a server and estimating the emotional state of visitors.

[0384] "Generation means" refers to methods or devices for creating visual and auditory content based on estimated emotional states, thereby generating content that is adapted to the user's emotions.

[0385] "Presentation means" refers to display devices and technologies for transmitting content generated on a server to an operating terminal and presenting it to the user.

[0386] "Adaptive measures" refer to methods and devices for adjusting the generation process based on user feedback and utilizing that feedback for future content generation.

[0387] This invention relates to a system that reads a user's emotional state based on a visitor's biometric information and provides corresponding visual and auditory content. This system includes information acquisition means, communication means, analysis means, generation means, presentation means, and adaptation means.

[0388] First, the terminal uses information acquisition methods to obtain biometric information from devices such as smartwatches and smartphones. This includes heart rate, body temperature, and facial expression data. A smartwatch, for example, can sense steps and heart rate in real time and immediately prepare the data for the next process.

[0389] The device uses communication methods to securely transmit acquired biometric information to a server. Wi-Fi or mobile networks are used for communication. This data is recorded in a database for subsequent analysis.

[0390] Next, the server utilizes analytical tools to process the recorded biometric information. The emotion engine, based on machine learning algorithms, combines data points to estimate the user's emotions. This allows for determinations such as whether the user is experiencing stress.

[0391] Subsequently, the server uses a generation mechanism to utilize a generative AI model to generate visual and auditory content that matches the estimated emotions. At this stage, the generative AI model is given prompts such as "Generate relaxing music and images of a forest for the user."

[0392] The generated content is transmitted to the user's device using a presentation device and displayed on the screen of a smartphone or AR glasses. For example, if the user is feeling tired, the device may display relaxing music and images of nature, providing the user with a calming environment.

[0393] Finally, users submit feedback on the provided content via their device. This feedback is sent to the server via adaptive means and used to adjust and improve the generated AI model. This is to provide users with even more optimized content in the future.

[0394] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0395] Step 1:

[0396] The device collects visitors' biometric information. This process utilizes smartwatches and smartphones to acquire heart rate, body temperature, activity levels, and facial expression data. Specifically, the smartwatch senses wrist movements and uses internal sensors to measure heart rate. The input is biometric information, which is detected in real time and output as a digital signal.

[0397] Step 2:

[0398] The device transmits collected biometric information to a server. Wi-Fi or mobile data networks are used to ensure the data reaches the server reliably. The device incorporates error checking functions and retransmits data as needed to maintain data integrity. The input is biometric information processed as a digital signal by the device, and the output is secure data transmission to the server.

[0399] Step 3:

[0400] The server records the received biometric information in a database. The information stored in the database is organized as a series of biometric data for the user. This makes the information efficiently accessible for subsequent processing. The input is biometric information sent from the terminal, and the output is the information recorded in the database in a structured form.

[0401] Step 4:

[0402] The server uses information to estimate the user's emotional state using an emotion engine. It analyzes biometric data such as heart rate variability and uses a predictive algorithm to estimate emotional states like stress and relaxation. Specifically, the server applies a machine learning model to map biometric information to different emotional states. The input is structured data stored in a database, and the output is the estimated emotional state.

[0403] Step 5:

[0404] The server uses a generative AI model to create appropriate visual and auditory content based on the estimated emotional state. The model receives prompts, which then generate music and images. An example of a generated prompt might be, "Generate music that will help the user relax." The input is the estimated emotional state and the prompt, while the output is the generated content.

[0405] Step 6:

[0406] The server sends the generated content to the device. The content is provided in a format that can be displayed on the user's smartphone or AR device. Specifically, the server streams generated music and image data to the device, which then immediately displays the content to the user. The input is the generated visual and auditory content, and the output is the transmission of data to the device.

[0407] Step 7:

[0408] Users submit feedback on the provided content via their devices. This feedback is recorded regarding the quality of the content and their personal impressions. The input is feedback based on the user's opinions and experiences, and the output is feedback data provided to the server.

[0409] Step 8:

[0410] The server receives feedback and uses it to refine the generative AI model. The feedback data is analyzed to help modify the model's parameters for future content generation processes. The input is user feedback, and the output is the improved parameters of the generative AI model.

[0411] (Application Example 2)

[0412] 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."

[0413] Traditionally, the customer experience in physical stores has been uniform, making it difficult to personalize it according to the emotions and psychological state of individual visitors. Furthermore, while there is a demand to increase customer satisfaction by providing appropriate content based on the visitor's real-time emotional state, a system to achieve this did not exist.

[0414] 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.

[0415] In this invention, the server includes a device for measuring the visitor's biometric data, a processing unit for analyzing the emotional state based on the biometric data, and a generation unit for generating visual and auditory media according to the analyzed emotional state. This makes it possible to provide customized content that is tailored to the individual physiological and psychological state of each visitor.

[0416] "Biometric data" refers to a collection of information that indicates an individual's physiological and psychological state, such as a visitor's heart rate, body temperature, activity level, and facial expression data.

[0417] A "processing unit" is a device or program that takes biometric data acquired from visitors as input, analyzes it, and has the function of estimating their emotional state.

[0418] A "generation unit" is a device or program that generates visual or auditory media content based on an analyzed emotional state.

[0419] A "terminal" is a device used to display generated media, and includes smartphones, tablets, digital signage, and other similar devices.

[0420] "Optimized media for enhancing customer experience" refers to content designed to meet the individual needs and emotions of each visitor, based on their individual physiological and psychological state.

[0421] The system for implementing this invention consists of a device for measuring visitors' biometric data, a processing unit for analyzing their emotional state, a generation unit for generating visual and auditory media, and a terminal for presenting the generated media. Details are described below.

[0422] The server collects biometric data in real time through smartwatches and smartphones worn by visitors. This includes information such as heart rate, body temperature, and facial expression data, which is transferred from the device to the server using Bluetooth technology. On the server, this data is stored in an SQL database to prepare for the next processing step.

[0423] The server's processing unit uses machine learning libraries such as TensorFlow to analyze biometric data and estimate the visitor's emotional state. Based on the estimated emotional state, a generative AI model is used to generate content using prompt text as input. Examples of these prompt texts include, "We want to estimate the visitor's emotional state based on their biometric information and generate visual content that helps the user relax," and "Please write a program that generates music and videos that respond to the customer's emotions to provide a personalized store experience."

[0424] The generation unit utilizes a generative AI model to create media content tailored to the user. For example, if a visitor is feeling stressed, it might create relaxing music and calming landscape images. The generated media is then sent to devices such as smart displays and tablets and presented at the appropriate time.

[0425] Users can provide feedback on the media presented, and this feedback is sent back to the server. The server analyzes this feedback and incorporates it into future media creation, enabling the provision of a more personalized experience. In this way, the present invention revolutionizes the customer experience in physical stores by providing media content optimized for the visitor's emotional state in real time.

[0426] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0427] Step 1:

[0428] The server receives biometric data via Bluetooth from a smart device worn by the visitor. This data includes heart rate, body temperature, and facial expression data. The server stores this received data in an SQL database. The input to this step is biometric data, and the output is saving the data to the SQL database.

[0429] Step 2:

[0430] The server retrieves stored biometric data and performs data analysis using machine learning libraries such as TensorFlow. Specifically, it analyzes heart rate variability and facial expression patterns to estimate emotional states. The input for this step is biometric data retrieved from an SQL database, and the output is the estimated emotional state.

[0431] Step 3:

[0432] The server creates and inputs an appropriate prompt message to the generative AI model based on the estimated emotional state. For example, a prompt message might be, "We want to generate relaxing content based on the visitor's biometric information." The input for this step is the estimated emotional state, and the output is the prompt message passed to the generative AI model.

[0433] Step 4:

[0434] The generative AI model generates visual and auditory media based on the received prompt text. Specifically, it generates relaxing music and nature scenery videos. The input for this step is the prompt text, and the output is the generated media content.

[0435] Step 5:

[0436] The server sends the generated media content to the device. The device displays the received content on a smart display or tablet. This provides visitors with customized content. The input for this step is the generated media content, and the output is the display of the content on the device.

[0437] Step 6:

[0438] The user provides feedback on the provided media. The terminal sends this feedback to the server, which analyzes the feedback data and uses it to improve future media generation. The input for this step is user feedback, and the output is information for improving the content to be generated next time.

[0439] 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.

[0440] 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.

[0441] 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.

[0442] [Third Embodiment]

[0443] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0444] 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.

[0445] 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).

[0446] 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.

[0447] 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.

[0448] 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).

[0449] 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.

[0450] 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.

[0451] 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.

[0452] 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.

[0453] 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.

[0454] 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".

[0455] This invention is a system that collects visitors' biometric information and provides visual and auditory content based on that information. An embodiment of this system is described in detail below.

[0456] First, the device acquires biometric information from the visitor. Wearable devices such as smartwatches and smartphones are used for this purpose. Such devices can collect information such as heart rate, body temperature, activity level, and facial expression data in real time. For example, if a user is wearing a smartwatch, the device will continuously record the user's heart rate and step count.

[0457] Biometric information transmitted from the device is received and stored by the server. Based on the received data, the server uses an AI model to estimate the visitor's emotional state. This estimation is performed in real time; for example, by analyzing facial expression data, the server determines emotions such as "happy" if the user is smiling or "stressed" if they have a grim expression.

[0458] Based on the estimated emotional state, the server generates visual and auditory content. This generated content is optimized for the visitor's emotions, such as relaxing music or images of natural landscapes. This is done by a generative AI model, aiming to provide the visitor with the desired experience.

[0459] The generated content is sent to the device and displayed there visually or audibly. Users can experience the displayed content through their device; for example, they might listen to jazz music or view calming ocean images to relax after returning home. Users can rate this experience and provide feedback through the app.

[0460] User feedback is collected and analyzed on the server. Based on this analysis, content personalization for each visitor is continuously improved. The server uses this feedback to adjust the generation algorithm and provide even more optimized content on subsequent visits.

[0461] This system aims to provide users with personalized experiences tailored to their individual needs, offering entertainment and relaxation that responds to their emotions on a daily basis.

[0462] The following describes the processing flow.

[0463] Step 1:

[0464] The device collects biometric information from the user's smartwatch or smartphone. This includes heart rate, body temperature, and facial expression data. The device acquires this data in real time and prepares it for transmission to a server.

[0465] Step 2:

[0466] The server receives biometric information transmitted from the terminal. The received data is processed immediately and stored in the database. The server then prepares this data for the next processing stage.

[0467] Step 3:

[0468] The server uses an AI model based on biometric information to estimate the user's emotional state. The AI ​​model determines the user's emotional state in real time from various collected data. Based on this result, it determines the content to be generated.

[0469] Step 4:

[0470] The server generates visual and auditory content using a generative AI model based on the user's emotional state. The generated content, such as relaxing music and nature images, is optimized for the user's current emotional state.

[0471] Step 5:

[0472] The server sends the generated visual and auditory content to the device. The content is then ready to be displayed on the user's device, such as a smartphone or AR glasses.

[0473] Step 6:

[0474] The device displays generated content to the user. Visual content is displayed on the screen, while auditory content is played through speakers or headphones. The user experiences relaxation or entertainment based on the displayed content.

[0475] Step 7:

[0476] Users provide feedback on the content they experience through their device. This feedback is provided based on the user's preferences and the quality of their experience, and is used to improve personalization for future experiences.

[0477] Step 8:

[0478] The device sends user feedback to the server. The server receives this feedback, stores it in a database, and prepares it for analysis.

[0479] Step 9:

[0480] The server analyzes user feedback and uses it to refine the generated AI model. This allows the content provided on subsequent visits to evolve to better suit the user's preferences.

[0481] (Example 1)

[0482] 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."

[0483] In modern society, there is a demand for entertainment and relaxation tailored to the psychological state of individuals. However, with conventional technology, it has been difficult to provide customized visual and auditory content that matches the visitor's mental state at any given time, making it challenging to improve visitor satisfaction.

[0484] 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.

[0485] In this invention, the server includes a device means for acquiring the visitor's biometric characteristics, an algorithm means for estimating the visitor's psychological state using the biometric characteristics, and a process means for generating visual and auditory outputs based on the estimated psychological state. This makes it possible to provide optimal content in real time that is tailored to the visitor's individual psychological state.

[0486] A "visitor" is an individual whose biometric characteristics are acquired by the system and who is the target of content provision.

[0487] "Biological characteristics" refer to physical or physiological information about a visitor, such as heart rate, body temperature, activity level, and facial expression.

[0488] "Device means" refers to hardware equipment used to acquire the visitor's biometric characteristics, and includes, for example, smartwatches and smartphones.

[0489] "Psychological state" refers to the visitor's emotional state, stress level, happiness level, and other mental conditions.

[0490] "Algorithmic methods" refer to computational methods and programs for estimating psychological states based on biological characteristics.

[0491] "Process means" refers to a series of processes that generate visual and auditory outputs based on an estimated psychological state.

[0492] "Output" refers to content delivered through visual or auditory means that is adapted to the estimated psychological state.

[0493] "Display device means" refers to a device for showing the generated output to visitors, and includes displays and speakers.

[0494] "Feedback" refers to the evaluations and opinions that visitors give to the content provided.

[0495] "Analysis methods" refer to the process of analyzing feedback collected from visitors and using that information to create future content.

[0496] This invention is a system that acquires the biometric characteristics of visitors, estimates their emotional state based on that information, and provides appropriate visual and auditory content. The system mainly consists of three entities: a terminal, a server, and a user.

[0497] First, the device acquires biometric characteristics from the visitor. The hardware used here includes wearable devices such as smartwatches and smartphones. These devices have the ability to collect heart rate, body temperature, activity level, and facial expression data in real time. This allows for a detailed understanding of the visitor's current physical and mental state.

[0498] Next, the biometric characteristics collected by the device are sent to the server. The server receives and stores this information. The server also uses an AI model based on the received data to estimate the visitor's psychological state. Specifically, it analyzes the data using algorithms such as neural networks to determine emotions such as "happiness" and "stress." This analysis is performed in real time, and an evaluation is made that is appropriate to the visitor's instantaneous state.

[0499] Based on the psychological state estimated by the server, a generative AI model is used to generate visual and auditory outputs. In this process, the server sets prompts to generate jazz music or calming nature images if it detects a psychological state such as "relaxed." A specific example of a prompt might be, "Generate relaxing music to reduce the user's current stress level."

[0500] Finally, the generated output is sent to the device. The device presents this content to the visitor, providing a visual and auditory experience. Users can experience the displayed content through the device and provide feedback on their results. This feedback is collected on the server and used as data to improve the quality of future output.

[0501] This system allows users to enjoy personalized entertainment tailored to their emotional state at any given time.

[0502] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0503] Step 1:

[0504] The terminal acquires the visitor's biometric characteristics. The input here is information obtained from wearable devices worn or carried by the visitor. Specifically, the terminal reads heart rate and activity level information from the smartwatch's sensors and captures facial expression data with the smartphone's camera. This results in output data that quantifies the visitor's physical state in real time.

[0505] Step 2:

[0506] The device collects biometric data and transmits it to the server. The input is biometric data acquired by the device, and the output is encrypted digital data sent to the server. The specific operation includes organizing the data on the device, packetizing the data according to security protocols, and transmitting it to the server via the internet.

[0507] Step 3:

[0508] The server receives and stores biometric data. The input is biometric information data transmitted from the terminal, and the output is biometric data stored in the database. The server converts the data into a parseable format and stores it in the database with a timestamp.

[0509] Step 4:

[0510] The server estimates the visitor's psychological state based on biometric data. The input is stored biometric data, and the output is the determined psychological state. The server uses an AI model to analyze the data and performs specific actions such as classifying emotions by evaluating changes in heart rate and facial expression data using a neural network.

[0511] Step 5:

[0512] The server generates visual and auditory outputs corresponding to the estimated psychological state. The input is the psychological state determination result, and the output is the generated visual and auditory content. Using a generative AI model, it creates content based on prompts and performs specific actions such as selecting music and video materials.

[0513] Step 6:

[0514] The server sends the generated content to the terminal. The input is the generated content data, and the output is the playable content sent to the terminal. The server compresses the content data before transfer and performs specific actions to ensure smooth playback on the terminal.

[0515] Step 7:

[0516] The user experiences content presented through the device. The input is the content received by the device, and the output is the user's experience and feedback. The user performs specific actions such as viewing visual images on the display or listening to auditory content through speakers.

[0517] Step 8:

[0518] Users provide feedback on the content. The input is an evaluation based on the user's experience, and the output is feedback data. Users use an app on their device to input their evaluation on the interface and send the feedback to the server.

[0519] Step 9:

[0520] The server analyzes the feedback and uses it to generate content for the next time. The input is user feedback data, and the output is the improved algorithm settings. The server aggregates the feedback and adjusts the generation algorithm to generate more personalized content for the next visit.

[0521] (Application Example 1)

[0522] 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."

[0523] Traditional stores face the challenge of providing timely and appropriate product information and promotions based on visitors' emotions and circumstances. This can result in visitors not receiving the information they need, thus failing to stimulate their purchasing intent.

[0524] 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.

[0525] In this invention, the server includes means for using a device for collecting visitor biometric information, means for using an inference device for estimating an emotional state using the biometric information, and means for utilizing a generation device for generating visual and auditory content based on the estimated emotional state and displaying it in the store. This makes it possible to provide optimal product information and promotions in real time based on the visitor's emotions.

[0526] A "visitor" refers to an individual who comes to a store or facility, and whose biometric information is subject to measurement and collection.

[0527] "Biometric information" refers to data that indicates an individual's current physical state, such as heart rate, body temperature, activity level, and facial expression data.

[0528] "Device" refers to hardware used to collect or display visitors' biometric information, including smartwatches and smartphones.

[0529] An "inference device" refers to a computing device used to estimate a visitor's emotional state based on collected biometric information.

[0530] "Emotional state" represents the visitor's current psychological condition and, as an estimated result, indicates specific emotions such as "happiness" or "stress."

[0531] A "generation device" refers to a system for generating visual and auditory content based on an estimated emotional state.

[0532] "Content" refers to visual or auditory information provided to visitors, including relaxing music and images of natural landscapes.

[0533] A "display device" refers to a device used to provide generated content to visitors visually or audibly.

[0534] "Feedback" refers to the evaluations and opinions that visitors provide after experiencing content, and this data is used to optimize future content.

[0535] A "store" refers to a physical location or commercial facility that visitors go to, where biometric information is collected and content is displayed.

[0536] The system for carrying out this invention aims to collect visitor biometric information and use it to provide personalized visual and auditory content. The hardware used includes smartwatches, smartphones, smart glasses, and in-store displays. The software uses AI models developed in Python (e.g., TensorFlow), smartphone applications (iOS / Android), and generative AI models (e.g., OpenAI GPT).

[0537] The terminal collects biometric information in real time via wearable devices such as smartwatches and smartphones. This includes heart rate, body temperature, activity level, and facial expression data. The terminal transmits the data to a server via Bluetooth or other means. The server-side AI model estimates the visitor's emotional state based on the received data.

[0538] By utilizing a generative AI model, visual and auditory content optimized for the estimated emotional state is generated. This generated content is displayed to visitors through in-store displays and smart glasses. This allows visitors to receive product information and promotions tailored to their current emotional state.

[0539] For example, if a visitor is relaxed, the display will show clothing in calming colors, while if they are active, promotions for new, colorful clothing will be shown. Feedback on the content the user experiences is sent to the server via the smartphone app and used to generate even more optimized content for their next visit.

[0540] An example of a prompt to a generative AI model is, "Generate a promotional video that allows the user to enjoy the purchase in a relaxed and elegant atmosphere." In this way, the visitor experience is tailored to individual needs through the use of biometric information and AI technology.

[0541] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0542] Step 1:

[0543] The device collects visitor biometric information via a smartwatch or smartphone. This includes acquiring heart rate, body temperature, activity level, and facial expression data. The data is stored on the device in real time and transmitted to a server via Bluetooth.

[0544] Step 2:

[0545] The server receives biometric information and stores it in a database. The input here is biometric information from the terminal, and the output is the stored data. This data forms the basis for subsequent emotion estimation.

[0546] Step 3:

[0547] The server uses an AI model (such as TensorFlow) to estimate the visitor's emotional state from biometric data. Specifically, it feeds the model with stored biometric data as input and performs analysis using facial recognition technology. The output is an emotional state such as "happy" or "stressed."

[0548] Step 4:

[0549] The server uses a generative AI model (such as OpenAI GPT) to generate visual and auditory content based on the estimated emotional state. The input is the emotional state, and the generated content is the output. The prompt is "Generate a promotional video that allows the user to enjoy a purchase in a relaxed and elegant atmosphere."

[0550] Step 5:

[0551] The server transmits the generated content to in-store displays and users' smart glasses for display. The input here is the generated content, and the output is product information and promotional videos that visitors see. Users can receive relevant information through the displays.

[0552] Step 6:

[0553] Users submit feedback via a smartphone app after experiencing the provided content. Visitors' comments and ratings are entered into the app as input and sent to the server.

[0554] Step 7:

[0555] The server analyzes user feedback data and adjusts the AI ​​model and generation algorithm based on the results. The input here is the feedback data, and the output is optimized model parameters for future content generation. This results in more personalized content on subsequent visits.

[0556] 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.

[0557] This invention is a system that collects visitor biometric information, combines it with an emotion engine that recognizes the user's emotions based on that information, and provides visual and auditory content. This embodiment is as follows:

[0558] First, the terminal acquires the visitor's biometric information. Smartwatches and smartphones are used as the necessary devices for this. These devices sense heart rate, body temperature, activity level, facial expression data, etc., in real time and prepare to send the data to the server. If the user is wearing a smartwatch, the device continuously records steps and heart rate and sends them to the terminal.

[0559] Next, the server receives biometric information transmitted from the terminal. The data collected by the server is recorded in a database and prepared for analysis by the emotion engine. The emotion engine integrates multiple received data points and has the function of estimating the user's emotional state with high accuracy. For example, it analyzes changes in facial expression and increases in heart rate in combination to determine the state of stress.

[0560] Based on the estimated emotional state, the server uses a generative AI model to generate visual and auditory content. This content is tailored to the user's emotions, such as relaxing music or natural scenery. The generated content is optimized to maximize the user experience and continuously updates as needed, adapting to real-time changes in emotions.

[0561] The generated content is sent to the device. The device then displays the content on the smartphone's screen or AR glasses and provides it to the user. For example, if the user is feeling stressed, the device might create a calming environment by displaying relaxing music and images of a tranquil ocean.

[0562] Furthermore, users can provide feedback on the content provided. Users input their opinions and preferences regarding the experience through their device, and this feedback is sent to the server. The server analyzes this feedback and uses it to train and refine the generative AI model. This allows for further personalized content to be generated in the future, providing users with the best possible experience.

[0563] Thus, this system, which includes an emotion engine, provides entertainment and relaxation tailored to the user's emotions in their daily life, creating experiences that are unique to each individual user.

[0564] The following describes the processing flow.

[0565] Step 1:

[0566] The device collects biometric information from the user's smartwatch or smartphone. This includes heart rate, body temperature, activity level, and facial expression data, all of which are obtained in real time.

[0567] Step 2:

[0568] The device transmits the collected biometric information to the server. The data is transmitted using a secure communication protocol, and the server prepares to process the received data in real time.

[0569] Step 3:

[0570] The server stores the biometric information received from the terminal into a database. At this stage, the data is organized for analysis and prepared as a dataset to be used in the next step.

[0571] Step 4:

[0572] The server uses an emotion engine to estimate the user's overall emotional state based on biometric information. Here, the user's emotions are evaluated in detail through facial recognition and analysis of physiological data. Based on these results, guidelines for the next content to be generated are determined.

[0573] Step 5:

[0574] The server generates visual and auditory content using a generative AI model based on the estimated emotional state. For example, if the server determines that the user is stressed, it will generate relaxation music or calming nature images. This content is designed to meet the user's experience needs.

[0575] Step 6:

[0576] The server sends the generated content to the device. The content is provided in a format suitable for the user's device (for example, a video format for smartphones).

[0577] Step 7:

[0578] The device presents the acquired content to the user. The device provides visual and auditory stimuli through the screen display and speakers. The user can enjoy relaxation and entertainment through this content.

[0579] Step 8:

[0580] Users provide feedback on the content they experience via their devices. This feedback concerns the quality and satisfaction level of the content, as well as their preferences.

[0581] Step 9:

[0582] The device sends user feedback to the server. The server receives this feedback and uses it to improve the personalization of subsequent content generation processes.

[0583] Step 10:

[0584] The server adjusts the personalization algorithm of the generated AI model based on the feedback. This ensures that the content provided on subsequent visits is more tailored to the user's emotions and preferences.

[0585] (Example 2)

[0586] 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."

[0587] Traditional systems struggled to provide content that responded to visitors' instantaneous emotional changes, making it difficult to offer user-optimized entertainment and relaxation. Furthermore, there were problems with the accuracy of emotion estimation and the resulting real-time content generation.

[0588] 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.

[0589] In this invention, the server includes information acquisition means, communication means for transmitting biometric information to the server, analysis means for analyzing the received biometric information and estimating the emotional state, presentation means for transmitting and displaying the generated content on an operating terminal, and adaptive means for collecting user feedback and adjusting the generation means. This makes it possible to provide personalized content that responds to the visitor's instantaneous emotional changes.

[0590] "Information acquisition means" refers to devices or methods for collecting visitors' biometric information, and has the function of detecting heart rate, body temperature, facial expression data, etc.

[0591] "Communication means" refers to technologies and devices for transmitting acquired biometric information to a server, enabling highly secure and real-time data transmission.

[0592] "Analysis means" refers to processes and algorithms for analyzing biometric information received on a server and estimating the emotional state of visitors.

[0593] "Generation means" refers to methods or devices for creating visual and auditory content based on estimated emotional states, thereby generating content that is adapted to the user's emotions.

[0594] "Presentation means" refers to display devices and technologies for transmitting content generated on a server to an operating terminal and presenting it to the user.

[0595] "Adaptive measures" refer to methods and devices for adjusting the generation process based on user feedback and utilizing that feedback for future content generation.

[0596] This invention relates to a system that reads a user's emotional state based on a visitor's biometric information and provides corresponding visual and auditory content. This system includes information acquisition means, communication means, analysis means, generation means, presentation means, and adaptation means.

[0597] First, the terminal uses information acquisition methods to obtain biometric information from devices such as smartwatches and smartphones. This includes heart rate, body temperature, and facial expression data. A smartwatch, for example, can sense steps and heart rate in real time and immediately prepare the data for the next process.

[0598] The device uses communication methods to securely transmit acquired biometric information to a server. Wi-Fi or mobile networks are used for communication. This data is recorded in a database for subsequent analysis.

[0599] Next, the server utilizes analytical tools to process the recorded biometric information. The emotion engine, based on machine learning algorithms, combines data points to estimate the user's emotions. This allows for determinations such as whether the user is experiencing stress.

[0600] Subsequently, the server uses a generation mechanism to utilize a generative AI model to generate visual and auditory content that matches the estimated emotions. At this stage, the generative AI model is given prompts such as "Generate relaxing music and images of a forest for the user."

[0601] The generated content is transmitted to the user's device using a presentation device and displayed on the screen of a smartphone or AR glasses. For example, if the user is feeling tired, the device may display relaxing music and images of nature, providing the user with a calming environment.

[0602] Finally, users submit feedback on the provided content via their device. This feedback is sent to the server via adaptive means and used to adjust and improve the generated AI model. This is to provide users with even more optimized content in the future.

[0603] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0604] Step 1:

[0605] The device collects visitors' biometric information. This process utilizes smartwatches and smartphones to acquire heart rate, body temperature, activity levels, and facial expression data. Specifically, the smartwatch senses wrist movements and uses internal sensors to measure heart rate. The input is biometric information, which is detected in real time and output as a digital signal.

[0606] Step 2:

[0607] The device transmits collected biometric information to a server. Wi-Fi or mobile data networks are used to ensure the data reaches the server reliably. The device incorporates error checking functions and retransmits data as needed to maintain data integrity. The input is biometric information processed as a digital signal by the device, and the output is secure data transmission to the server.

[0608] Step 3:

[0609] The server records the received biometric information in a database. The information stored in the database is organized as a series of biometric data for the user. This makes the information efficiently accessible for subsequent processing. The input is biometric information sent from the terminal, and the output is the information recorded in the database in a structured form.

[0610] Step 4:

[0611] The server uses information to estimate the user's emotional state using an emotion engine. It analyzes biometric data such as heart rate variability and uses a predictive algorithm to estimate emotional states like stress and relaxation. Specifically, the server applies a machine learning model to map biometric information to different emotional states. The input is structured data stored in a database, and the output is the estimated emotional state.

[0612] Step 5:

[0613] The server uses a generative AI model to create appropriate visual and auditory content based on the estimated emotional state. The model receives prompts, which then generate music and images. An example of a generated prompt might be, "Generate music that will help the user relax." The input is the estimated emotional state and the prompt, while the output is the generated content.

[0614] Step 6:

[0615] The server sends the generated content to the device. The content is provided in a format that can be displayed on the user's smartphone or AR device. Specifically, the server streams generated music and image data to the device, which then immediately displays the content to the user. The input is the generated visual and auditory content, and the output is the transmission of data to the device.

[0616] Step 7:

[0617] Users submit feedback on the provided content via their devices. This feedback is recorded regarding the quality of the content and their personal impressions. The input is feedback based on the user's opinions and experiences, and the output is feedback data provided to the server.

[0618] Step 8:

[0619] The server receives feedback and uses it to refine the generative AI model. The feedback data is analyzed to help modify the model's parameters for future content generation processes. The input is user feedback, and the output is the improved parameters of the generative AI model.

[0620] (Application Example 2)

[0621] 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."

[0622] Traditionally, the customer experience in physical stores has been uniform, making it difficult to personalize it according to the emotions and psychological state of individual visitors. Furthermore, while there is a demand to increase customer satisfaction by providing appropriate content based on the visitor's real-time emotional state, a system to achieve this did not exist.

[0623] 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.

[0624] In this invention, the server includes a device for measuring the visitor's biometric data, a processing unit for analyzing the emotional state based on the biometric data, and a generation unit for generating visual and auditory media according to the analyzed emotional state. This makes it possible to provide customized content that is tailored to the individual physiological and psychological state of each visitor.

[0625] "Biometric data" refers to a collection of information that indicates an individual's physiological and psychological state, such as a visitor's heart rate, body temperature, activity level, and facial expression data.

[0626] A "processing unit" is a device or program that takes biometric data acquired from visitors as input, analyzes it, and has the function of estimating their emotional state.

[0627] A "generation unit" is a device or program that generates visual or auditory media content based on an analyzed emotional state.

[0628] A "terminal" is a device used to display generated media, and includes smartphones, tablets, digital signage, and other similar devices.

[0629] "Optimized media for enhancing customer experience" refers to content designed to meet the individual needs and emotions of each visitor, based on their individual physiological and psychological state.

[0630] The system for implementing this invention consists of a device for measuring visitors' biometric data, a processing unit for analyzing their emotional state, a generation unit for generating visual and auditory media, and a terminal for presenting the generated media. Details are described below.

[0631] The server collects biometric data in real time through smartwatches and smartphones worn by visitors. This includes information such as heart rate, body temperature, and facial expression data, which is transferred from the device to the server using Bluetooth technology. On the server, this data is stored in an SQL database to prepare for the next processing step.

[0632] The server's processing unit uses machine learning libraries such as TensorFlow to analyze biometric data and estimate the visitor's emotional state. Based on the estimated emotional state, a generative AI model is used to generate content using prompt text as input. Examples of these prompt texts include, "We want to estimate the visitor's emotional state based on their biometric information and generate visual content that helps the user relax," and "Please write a program that generates music and videos that respond to the customer's emotions to provide a personalized store experience."

[0633] The generation unit utilizes a generative AI model to create media content tailored to the user. For example, if a visitor is feeling stressed, it might create relaxing music and calming landscape images. The generated media is then sent to devices such as smart displays and tablets and presented at the appropriate time.

[0634] Users can provide feedback on the media presented, and this feedback is sent back to the server. The server analyzes this feedback and incorporates it into future media creation, enabling the provision of a more personalized experience. In this way, the present invention revolutionizes the customer experience in physical stores by providing media content optimized for the visitor's emotional state in real time.

[0635] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0636] Step 1:

[0637] The server receives biometric data via Bluetooth from a smart device worn by the visitor. This data includes heart rate, body temperature, and facial expression data. The server stores this received data in an SQL database. The input to this step is biometric data, and the output is saving the data to the SQL database.

[0638] Step 2:

[0639] The server retrieves stored biometric data and performs data analysis using machine learning libraries such as TensorFlow. Specifically, it analyzes heart rate variability and facial expression patterns to estimate emotional states. The input for this step is biometric data retrieved from an SQL database, and the output is the estimated emotional state.

[0640] Step 3:

[0641] The server creates and inputs an appropriate prompt message to the generative AI model based on the estimated emotional state. For example, a prompt message might be, "We want to generate relaxing content based on the visitor's biometric information." The input for this step is the estimated emotional state, and the output is the prompt message passed to the generative AI model.

[0642] Step 4:

[0643] The generative AI model generates visual and auditory media based on the received prompt text. Specifically, it generates relaxing music and nature scenery videos. The input for this step is the prompt text, and the output is the generated media content.

[0644] Step 5:

[0645] The server sends the generated media content to the device. The device displays the received content on a smart display or tablet. This provides visitors with customized content. The input for this step is the generated media content, and the output is the display of the content on the device.

[0646] Step 6:

[0647] The user provides feedback on the provided media. The terminal sends this feedback to the server, which analyzes the feedback data and uses it to improve future media generation. The input for this step is user feedback, and the output is information for improving the content to be generated next time.

[0648] 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.

[0649] 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.

[0650] 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.

[0651] [Fourth Embodiment]

[0652] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0653] 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.

[0654] 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).

[0655] 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.

[0656] 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.

[0657] 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).

[0658] 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.

[0659] 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.

[0660] 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.

[0661] 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.

[0662] 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.

[0663] 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.

[0664] 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".

[0665] This invention is a system that collects visitors' biometric information and provides visual and auditory content based on that information. An embodiment of this system is described in detail below.

[0666] First, the device acquires biometric information from the visitor. Wearable devices such as smartwatches and smartphones are used for this purpose. Such devices can collect information such as heart rate, body temperature, activity level, and facial expression data in real time. For example, if a user is wearing a smartwatch, the device will continuously record the user's heart rate and step count.

[0667] Biometric information transmitted from the device is received and stored by the server. Based on the received data, the server uses an AI model to estimate the visitor's emotional state. This estimation is performed in real time; for example, by analyzing facial expression data, the server determines emotions such as "happy" if the user is smiling or "stressed" if they have a grim expression.

[0668] Based on the estimated emotional state, the server generates visual and auditory content. This generated content is optimized for the visitor's emotions, such as relaxing music or images of natural landscapes. This is done by a generative AI model, aiming to provide the visitor with the desired experience.

[0669] The generated content is sent to the device and displayed there visually or audibly. Users can experience the displayed content through their device; for example, they might listen to jazz music or view calming ocean images to relax after returning home. Users can rate this experience and provide feedback through the app.

[0670] User feedback is collected and analyzed on the server. Based on this analysis, content personalization for each visitor is continuously improved. The server uses this feedback to adjust the generation algorithm and provide even more optimized content on subsequent visits.

[0671] This system aims to provide users with personalized experiences tailored to their individual needs, offering entertainment and relaxation that responds to their emotions on a daily basis.

[0672] The following describes the processing flow.

[0673] Step 1:

[0674] The device collects biometric information from the user's smartwatch or smartphone. This includes heart rate, body temperature, and facial expression data. The device acquires this data in real time and prepares it for transmission to a server.

[0675] Step 2:

[0676] The server receives biometric information transmitted from the terminal. The received data is processed immediately and stored in the database. The server then prepares this data for the next processing stage.

[0677] Step 3:

[0678] The server uses an AI model based on biometric information to estimate the user's emotional state. The AI ​​model determines the user's emotional state in real time from various collected data. Based on this result, it determines the content to be generated.

[0679] Step 4:

[0680] The server generates visual and auditory content using a generative AI model based on the user's emotional state. The generated content, such as relaxing music and nature images, is optimized for the user's current emotional state.

[0681] Step 5:

[0682] The server sends the generated visual and auditory content to the device. The content is then ready to be displayed on the user's device, such as a smartphone or AR glasses.

[0683] Step 6:

[0684] The device displays generated content to the user. Visual content is displayed on the screen, while auditory content is played through speakers or headphones. The user experiences relaxation or entertainment based on the displayed content.

[0685] Step 7:

[0686] Users provide feedback on the content they experience through their device. This feedback is provided based on the user's preferences and the quality of their experience, and is used to improve personalization for future experiences.

[0687] Step 8:

[0688] The device sends user feedback to the server. The server receives this feedback, stores it in a database, and prepares it for analysis.

[0689] Step 9:

[0690] The server analyzes user feedback and uses it to refine the generated AI model. This allows the content provided on subsequent visits to evolve to better suit the user's preferences.

[0691] (Example 1)

[0692] 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".

[0693] In modern society, there is a demand for entertainment and relaxation tailored to the psychological state of individuals. However, with conventional technology, it has been difficult to provide customized visual and auditory content that matches the visitor's mental state at any given time, making it challenging to improve visitor satisfaction.

[0694] 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.

[0695] In this invention, the server includes a device means for acquiring the visitor's biometric characteristics, an algorithm means for estimating the visitor's psychological state using the biometric characteristics, and a process means for generating visual and auditory outputs based on the estimated psychological state. This makes it possible to provide optimal content in real time that is tailored to the visitor's individual psychological state.

[0696] A "visitor" is an individual whose biometric characteristics are acquired by the system and who is the target of content provision.

[0697] "Biological characteristics" refer to physical or physiological information about a visitor, such as heart rate, body temperature, activity level, and facial expression.

[0698] "Device means" refers to hardware equipment used to acquire the visitor's biometric characteristics, and includes, for example, smartwatches and smartphones.

[0699] "Psychological state" refers to the visitor's emotional state, stress level, happiness level, and other mental conditions.

[0700] "Algorithmic methods" refer to computational methods and programs for estimating psychological states based on biological characteristics.

[0701] "Process means" refers to a series of processes that generate visual and auditory outputs based on an estimated psychological state.

[0702] "Output" refers to content delivered through visual or auditory means that is adapted to the estimated psychological state.

[0703] "Display device means" refers to a device for showing the generated output to visitors, and includes displays and speakers.

[0704] "Feedback" refers to the evaluations and opinions that visitors give to the content provided.

[0705] "Analysis methods" refer to the process of analyzing feedback collected from visitors and using that information to create future content.

[0706] This invention is a system that acquires the biometric characteristics of visitors, estimates their emotional state based on that information, and provides appropriate visual and auditory content. The system mainly consists of three entities: a terminal, a server, and a user.

[0707] First, the device acquires biometric characteristics from the visitor. The hardware used here includes wearable devices such as smartwatches and smartphones. These devices have the ability to collect heart rate, body temperature, activity level, and facial expression data in real time. This allows for a detailed understanding of the visitor's current physical and mental state.

[0708] Next, the biometric characteristics collected by the device are sent to the server. The server receives and stores this information. The server also uses an AI model based on the received data to estimate the visitor's psychological state. Specifically, it analyzes the data using algorithms such as neural networks to determine emotions such as "happiness" and "stress." This analysis is performed in real time, and an evaluation is made that is appropriate to the visitor's instantaneous state.

[0709] Based on the psychological state estimated by the server, a generative AI model is used to generate visual and auditory outputs. In this process, the server sets prompts to generate jazz music or calming nature images if it detects a psychological state such as "relaxed." A specific example of a prompt might be, "Generate relaxing music to reduce the user's current stress level."

[0710] Finally, the generated output is sent to the device. The device presents this content to the visitor, providing a visual and auditory experience. Users can experience the displayed content through the device and provide feedback on their results. This feedback is collected on the server and used as data to improve the quality of future output.

[0711] This system allows users to enjoy personalized entertainment tailored to their emotional state at any given time.

[0712] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0713] Step 1:

[0714] The terminal acquires the visitor's biometric characteristics. The input here is information obtained from wearable devices worn or carried by the visitor. Specifically, the terminal reads heart rate and activity level information from the smartwatch's sensors and captures facial expression data with the smartphone's camera. This results in output data that quantifies the visitor's physical state in real time.

[0715] Step 2:

[0716] The device collects biometric data and transmits it to the server. The input is biometric data acquired by the device, and the output is encrypted digital data sent to the server. The specific operation includes organizing the data on the device, packetizing the data according to security protocols, and transmitting it to the server via the internet.

[0717] Step 3:

[0718] The server receives and stores biometric data. The input is biometric information data transmitted from the terminal, and the output is biometric data stored in the database. The server converts the data into a parseable format and stores it in the database with a timestamp.

[0719] Step 4:

[0720] The server estimates the visitor's psychological state based on biometric data. The input is stored biometric data, and the output is the determined psychological state. The server uses an AI model to analyze the data and performs specific actions such as classifying emotions by evaluating changes in heart rate and facial expression data using a neural network.

[0721] Step 5:

[0722] The server generates visual and auditory outputs corresponding to the estimated psychological state. The input is the psychological state determination result, and the output is the generated visual and auditory content. Using a generative AI model, it creates content based on prompts and performs specific actions such as selecting music and video materials.

[0723] Step 6:

[0724] The server sends the generated content to the terminal. The input is the generated content data, and the output is the playable content sent to the terminal. The server compresses the content data before transfer and performs specific actions to ensure smooth playback on the terminal.

[0725] Step 7:

[0726] The user experiences content presented through the device. The input is the content received by the device, and the output is the user's experience and feedback. The user performs specific actions such as viewing visual images on the display or listening to auditory content through speakers.

[0727] Step 8:

[0728] Users provide feedback on the content. The input is an evaluation based on the user's experience, and the output is feedback data. Users use an app on their device to input their evaluation on the interface and send the feedback to the server.

[0729] Step 9:

[0730] The server analyzes the feedback and uses it to generate content for the next time. The input is user feedback data, and the output is the improved algorithm settings. The server aggregates the feedback and adjusts the generation algorithm to generate more personalized content for the next visit.

[0731] (Application Example 1)

[0732] 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".

[0733] Traditional stores face the challenge of providing timely and appropriate product information and promotions based on visitors' emotions and circumstances. This can result in visitors not receiving the information they need, thus failing to stimulate their purchasing intent.

[0734] 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.

[0735] In this invention, the server includes means for using a device for collecting visitor biometric information, means for using an inference device for estimating an emotional state using the biometric information, and means for utilizing a generation device for generating visual and auditory content based on the estimated emotional state and displaying it in the store. This makes it possible to provide optimal product information and promotions in real time based on the visitor's emotions.

[0736] A "visitor" refers to an individual who comes to a store or facility, and whose biometric information is subject to measurement and collection.

[0737] "Biometric information" refers to data that indicates an individual's current physical state, such as heart rate, body temperature, activity level, and facial expression data.

[0738] "Device" refers to hardware used to collect or display visitors' biometric information, including smartwatches and smartphones.

[0739] An "inference device" refers to a computing device used to estimate a visitor's emotional state based on collected biometric information.

[0740] "Emotional state" represents the visitor's current psychological condition and, as an estimated result, indicates specific emotions such as "happiness" or "stress."

[0741] A "generation device" refers to a system for generating visual and auditory content based on an estimated emotional state.

[0742] "Content" refers to visual or auditory information provided to visitors, including relaxing music and images of natural landscapes.

[0743] A "display device" refers to a device used to provide generated content to visitors visually or audibly.

[0744] "Feedback" refers to the evaluations and opinions that visitors provide after experiencing content, and this data is used to optimize future content.

[0745] A "store" refers to a physical location or commercial facility that visitors go to, where biometric information is collected and content is displayed.

[0746] The system for carrying out this invention aims to collect visitor biometric information and use it to provide personalized visual and auditory content. The hardware used includes smartwatches, smartphones, smart glasses, and in-store displays. The software uses AI models developed in Python (e.g., TensorFlow), smartphone applications (iOS / Android), and generative AI models (e.g., OpenAI GPT).

[0747] The terminal collects biometric information in real time via wearable devices such as smartwatches and smartphones. This includes heart rate, body temperature, activity level, and facial expression data. The terminal transmits the data to a server via Bluetooth or other means. The server-side AI model estimates the visitor's emotional state based on the received data.

[0748] By utilizing a generative AI model, visual and auditory content optimized for the estimated emotional state is generated. This generated content is displayed to visitors through in-store displays and smart glasses. This allows visitors to receive product information and promotions tailored to their current emotional state.

[0749] For example, if a visitor is relaxed, the display will show clothing in calming colors, while if they are active, promotions for new, colorful clothing will be shown. Feedback on the content the user experiences is sent to the server via the smartphone app and used to generate even more optimized content for their next visit.

[0750] An example of a prompt to a generative AI model is, "Generate a promotional video that allows the user to enjoy the purchase in a relaxed and elegant atmosphere." In this way, the visitor experience is tailored to individual needs through the use of biometric information and AI technology.

[0751] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0752] Step 1:

[0753] The device collects visitor biometric information via a smartwatch or smartphone. This includes acquiring heart rate, body temperature, activity level, and facial expression data. The data is stored on the device in real time and transmitted to a server via Bluetooth.

[0754] Step 2:

[0755] The server receives biometric information and stores it in a database. The input here is biometric information from the terminal, and the output is the stored data. This data forms the basis for subsequent emotion estimation.

[0756] Step 3:

[0757] The server uses an AI model (such as TensorFlow) to estimate the visitor's emotional state from biometric data. Specifically, it feeds the model with stored biometric data as input and performs analysis using facial recognition technology. The output is an emotional state such as "happy" or "stressed."

[0758] Step 4:

[0759] The server uses a generative AI model (such as OpenAI GPT) to generate visual and auditory content based on the estimated emotional state. The input is the emotional state, and the generated content is the output. The prompt is "Generate a promotional video that allows the user to enjoy a purchase in a relaxed and elegant atmosphere."

[0760] Step 5:

[0761] The server transmits the generated content to in-store displays and users' smart glasses for display. The input here is the generated content, and the output is product information and promotional videos that visitors see. Users can receive relevant information through the displays.

[0762] Step 6:

[0763] Users submit feedback via a smartphone app after experiencing the provided content. Visitors' comments and ratings are entered into the app as input and sent to the server.

[0764] Step 7:

[0765] The server analyzes user feedback data and adjusts the AI ​​model and generation algorithm based on the results. The input here is the feedback data, and the output is optimized model parameters for future content generation. This results in more personalized content on subsequent visits.

[0766] 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.

[0767] This invention is a system that collects visitor biometric information, combines it with an emotion engine that recognizes the user's emotions based on that information, and provides visual and auditory content. This embodiment is as follows:

[0768] First, the terminal acquires the visitor's biometric information. Smartwatches and smartphones are used as the necessary devices for this. These devices sense heart rate, body temperature, activity level, facial expression data, etc., in real time and prepare to send the data to the server. If the user is wearing a smartwatch, the device continuously records steps and heart rate and sends them to the terminal.

[0769] Next, the server receives biometric information transmitted from the terminal. The data collected by the server is recorded in a database and prepared for analysis by the emotion engine. The emotion engine integrates multiple received data points and has the function of estimating the user's emotional state with high accuracy. For example, it analyzes changes in facial expression and increases in heart rate in combination to determine the state of stress.

[0770] Based on the estimated emotional state, the server uses a generative AI model to generate visual and auditory content. This content is tailored to the user's emotions, such as relaxing music or natural scenery. The generated content is optimized to maximize the user experience and continuously updates as needed, adapting to real-time changes in emotions.

[0771] The generated content is sent to the device. The device then displays the content on the smartphone's screen or AR glasses and provides it to the user. For example, if the user is feeling stressed, the device might create a calming environment by displaying relaxing music and images of a tranquil ocean.

[0772] Furthermore, users can provide feedback on the content provided. Users input their opinions and preferences regarding the experience through their device, and this feedback is sent to the server. The server analyzes this feedback and uses it to train and refine the generative AI model. This allows for further personalized content to be generated in the future, providing users with the best possible experience.

[0773] Thus, this system, which includes an emotion engine, provides entertainment and relaxation tailored to the user's emotions in their daily life, creating experiences that are unique to each individual user.

[0774] The following describes the processing flow.

[0775] Step 1:

[0776] The device collects biometric information from the user's smartwatch or smartphone. This includes heart rate, body temperature, activity level, and facial expression data, all of which are obtained in real time.

[0777] Step 2:

[0778] The device transmits the collected biometric information to the server. The data is transmitted using a secure communication protocol, and the server prepares to process the received data in real time.

[0779] Step 3:

[0780] The server stores the biometric information received from the terminal into a database. At this stage, the data is organized for analysis and prepared as a dataset to be used in the next step.

[0781] Step 4:

[0782] The server uses an emotion engine to estimate the user's overall emotional state based on biometric information. Here, the user's emotions are evaluated in detail through facial recognition and analysis of physiological data. Based on these results, guidelines for the next content to be generated are determined.

[0783] Step 5:

[0784] The server generates visual and auditory content using a generative AI model based on the estimated emotional state. For example, if the server determines that the user is stressed, it will generate relaxation music or calming nature images. This content is designed to meet the user's experience needs.

[0785] Step 6:

[0786] The server sends the generated content to the device. The content is provided in a format suitable for the user's device (for example, a video format for smartphones).

[0787] Step 7:

[0788] The device presents the acquired content to the user. The device provides visual and auditory stimuli through the screen display and speakers. The user can enjoy relaxation and entertainment through this content.

[0789] Step 8:

[0790] Users provide feedback on the content they experience via their devices. This feedback concerns the quality and satisfaction level of the content, as well as their preferences.

[0791] Step 9:

[0792] The device sends user feedback to the server. The server receives this feedback and uses it to improve the personalization of subsequent content generation processes.

[0793] Step 10:

[0794] The server adjusts the personalization algorithm of the generated AI model based on the feedback. This ensures that the content provided on subsequent visits is more tailored to the user's emotions and preferences.

[0795] (Example 2)

[0796] 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".

[0797] Traditional systems struggled to provide content that responded to visitors' instantaneous emotional changes, making it difficult to offer user-optimized entertainment and relaxation. Furthermore, there were problems with the accuracy of emotion estimation and the resulting real-time content generation.

[0798] 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.

[0799] In this invention, the server includes information acquisition means, communication means for transmitting biometric information to the server, analysis means for analyzing the received biometric information and estimating the emotional state, presentation means for transmitting and displaying the generated content on an operating terminal, and adaptive means for collecting user feedback and adjusting the generation means. This makes it possible to provide personalized content that responds to the visitor's instantaneous emotional changes.

[0800] "Information acquisition means" refers to devices or methods for collecting visitors' biometric information, and has the function of detecting heart rate, body temperature, facial expression data, etc.

[0801] "Communication means" refers to technologies and devices for transmitting acquired biometric information to a server, enabling highly secure and real-time data transmission.

[0802] "Analysis means" refers to processes and algorithms for analyzing biometric information received on a server and estimating the emotional state of visitors.

[0803] "Generation means" refers to methods or devices for creating visual and auditory content based on estimated emotional states, thereby generating content that is adapted to the user's emotions.

[0804] "Presentation means" refers to display devices and technologies for transmitting content generated on a server to an operating terminal and presenting it to the user.

[0805] "Adaptive measures" refer to methods and devices for adjusting the generation process based on user feedback and utilizing that feedback for future content generation.

[0806] This invention relates to a system that reads a user's emotional state based on a visitor's biometric information and provides corresponding visual and auditory content. This system includes information acquisition means, communication means, analysis means, generation means, presentation means, and adaptation means.

[0807] First, the terminal uses information acquisition methods to obtain biometric information from devices such as smartwatches and smartphones. This includes heart rate, body temperature, and facial expression data. A smartwatch, for example, can sense steps and heart rate in real time and immediately prepare the data for the next process.

[0808] The device uses communication methods to securely transmit acquired biometric information to a server. Wi-Fi or mobile networks are used for communication. This data is recorded in a database for subsequent analysis.

[0809] Next, the server utilizes analytical tools to process the recorded biometric information. The emotion engine, based on machine learning algorithms, combines data points to estimate the user's emotions. This allows for determinations such as whether the user is experiencing stress.

[0810] Subsequently, the server uses a generation mechanism to utilize a generative AI model to generate visual and auditory content that matches the estimated emotions. At this stage, the generative AI model is given prompts such as "Generate relaxing music and images of a forest for the user."

[0811] The generated content is transmitted to the user's device using a presentation device and displayed on the screen of a smartphone or AR glasses. For example, if the user is feeling tired, the device may display relaxing music and images of nature, providing the user with a calming environment.

[0812] Finally, users submit feedback on the provided content via their device. This feedback is sent to the server via adaptive means and used to adjust and improve the generated AI model. This is to provide users with even more optimized content in the future.

[0813] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0814] Step 1:

[0815] The device collects visitors' biometric information. This process utilizes smartwatches and smartphones to acquire heart rate, body temperature, activity levels, and facial expression data. Specifically, the smartwatch senses wrist movements and uses internal sensors to measure heart rate. The input is biometric information, which is detected in real time and output as a digital signal.

[0816] Step 2:

[0817] The device transmits collected biometric information to a server. Wi-Fi or mobile data networks are used to ensure the data reaches the server reliably. The device incorporates error checking functions and retransmits data as needed to maintain data integrity. The input is biometric information processed as a digital signal by the device, and the output is secure data transmission to the server.

[0818] Step 3:

[0819] The server records the received biometric information in a database. The information stored in the database is organized as a series of biometric data for the user. This makes the information efficiently accessible for subsequent processing. The input is biometric information sent from the terminal, and the output is the information recorded in the database in a structured form.

[0820] Step 4:

[0821] The server uses information to estimate the user's emotional state using an emotion engine. It analyzes biometric data such as heart rate variability and uses a predictive algorithm to estimate emotional states like stress and relaxation. Specifically, the server applies a machine learning model to map biometric information to different emotional states. The input is structured data stored in a database, and the output is the estimated emotional state.

[0822] Step 5:

[0823] The server uses a generative AI model to create appropriate visual and auditory content based on the estimated emotional state. The model receives prompts, which then generate music and images. An example of a generated prompt might be, "Generate music that will help the user relax." The input is the estimated emotional state and the prompt, while the output is the generated content.

[0824] Step 6:

[0825] The server sends the generated content to the device. The content is provided in a format that can be displayed on the user's smartphone or AR device. Specifically, the server streams generated music and image data to the device, which then immediately displays the content to the user. The input is the generated visual and auditory content, and the output is the transmission of data to the device.

[0826] Step 7:

[0827] Users submit feedback on the provided content via their devices. This feedback is recorded regarding the quality of the content and their personal impressions. The input is feedback based on the user's opinions and experiences, and the output is feedback data provided to the server.

[0828] Step 8:

[0829] The server receives feedback and uses it to refine the generative AI model. The feedback data is analyzed to help modify the model's parameters for future content generation processes. The input is user feedback, and the output is the improved parameters of the generative AI model.

[0830] (Application Example 2)

[0831] 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".

[0832] Traditionally, the customer experience in physical stores has been uniform, making it difficult to personalize it according to the emotions and psychological state of individual visitors. Furthermore, while there is a demand to increase customer satisfaction by providing appropriate content based on the visitor's real-time emotional state, a system to achieve this did not exist.

[0833] 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.

[0834] In this invention, the server includes a device for measuring the visitor's biometric data, a processing unit for analyzing the emotional state based on the biometric data, and a generation unit for generating visual and auditory media according to the analyzed emotional state. This makes it possible to provide customized content that is tailored to the individual physiological and psychological state of each visitor.

[0835] "Biometric data" refers to a collection of information that indicates an individual's physiological and psychological state, such as a visitor's heart rate, body temperature, activity level, and facial expression data.

[0836] A "processing unit" is a device or program that takes biometric data acquired from visitors as input, analyzes it, and has the function of estimating their emotional state.

[0837] A "generation unit" is a device or program that generates visual or auditory media content based on an analyzed emotional state.

[0838] A "terminal" is a device used to display generated media, and includes smartphones, tablets, digital signage, and other similar devices.

[0839] "Optimized media for enhancing customer experience" refers to content designed to meet the individual needs and emotions of each visitor, based on their individual physiological and psychological state.

[0840] The system for implementing this invention consists of a device for measuring visitors' biometric data, a processing unit for analyzing their emotional state, a generation unit for generating visual and auditory media, and a terminal for presenting the generated media. Details are described below.

[0841] The server collects biometric data in real time through smartwatches and smartphones worn by visitors. This includes information such as heart rate, body temperature, and facial expression data, which is transferred from the device to the server using Bluetooth technology. On the server, this data is stored in an SQL database to prepare for the next processing step.

[0842] The server's processing unit uses machine learning libraries such as TensorFlow to analyze biometric data and estimate the visitor's emotional state. Based on the estimated emotional state, a generative AI model is used to generate content using prompt text as input. Examples of these prompt texts include, "We want to estimate the visitor's emotional state based on their biometric information and generate visual content that helps the user relax," and "Please write a program that generates music and videos that respond to the customer's emotions to provide a personalized store experience."

[0843] The generation unit utilizes a generative AI model to create media content tailored to the user. For example, if a visitor is feeling stressed, it might create relaxing music and calming landscape images. The generated media is then sent to devices such as smart displays and tablets and presented at the appropriate time.

[0844] Users can provide feedback on the media presented, and this feedback is sent back to the server. The server analyzes this feedback and incorporates it into future media creation, enabling the provision of a more personalized experience. In this way, the present invention revolutionizes the customer experience in physical stores by providing media content optimized for the visitor's emotional state in real time.

[0845] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0846] Step 1:

[0847] The server receives biometric data via Bluetooth from a smart device worn by the visitor. This data includes heart rate, body temperature, and facial expression data. The server stores this received data in an SQL database. The input to this step is biometric data, and the output is saving the data to the SQL database.

[0848] Step 2:

[0849] The server retrieves stored biometric data and performs data analysis using machine learning libraries such as TensorFlow. Specifically, it analyzes heart rate variability and facial expression patterns to estimate emotional states. The input for this step is biometric data retrieved from an SQL database, and the output is the estimated emotional state.

[0850] Step 3:

[0851] The server creates and inputs an appropriate prompt message to the generative AI model based on the estimated emotional state. For example, a prompt message might be, "We want to generate relaxing content based on the visitor's biometric information." The input for this step is the estimated emotional state, and the output is the prompt message passed to the generative AI model.

[0852] Step 4:

[0853] The generative AI model generates visual and auditory media based on the received prompt text. Specifically, it generates relaxing music and nature scenery videos. The input for this step is the prompt text, and the output is the generated media content.

[0854] Step 5:

[0855] The server sends the generated media content to the device. The device displays the received content on a smart display or tablet. This provides visitors with customized content. The input for this step is the generated media content, and the output is the display of the content on the device.

[0856] Step 6:

[0857] The user provides feedback on the provided media. The terminal sends this feedback to the server, which analyzes the feedback data and uses it to improve future media generation. The input for this step is user feedback, and the output is information for improving the content to be generated next time.

[0858] 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.

[0859] 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.

[0860] In the above embodiment, an example was given in which the 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.

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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."

[0867] 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.

[0868] 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.

[0869] 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.

[0870] 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.

[0871] 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.

[0872] 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.

[0873] 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.

[0874] 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.

[0875] 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.

[0876] 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.

[0877] 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.

[0878] 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 to be incorporated by reference.

[0879] The following is further disclosed regarding the embodiments described above.

[0880] (Claim 1)

[0881] Equipment for collecting visitor biometric information,

[0882] An inference device for estimating an emotional state using the aforementioned biological information,

[0883] A generating device that generates visual and auditory content based on the estimated emotional state,

[0884] A system including a terminal for displaying the generated content.

[0885] (Claim 2)

[0886] The system according to claim 1, wherein the inference device analyzes the emotions of a visitor using facial recognition technology.

[0887] (Claim 3)

[0888] The system according to claim 1, wherein the content generated by the generation device is personalized based on feedback from visitors.

[0889] "Example 1"

[0890] (Claim 1)

[0891] A device for acquiring the biometric characteristics of visitors,

[0892] An algorithm for estimating a psychological state using the aforementioned biological characteristics,

[0893] A process means for generating visual and auditory outputs based on the estimated psychological state,

[0894] A display device means for presenting the generated output,

[0895] An analysis means for collecting feedback on the displayed output and reflecting it in the next generation process,

[0896] A system that includes this.

[0897] (Claim 2)

[0898] The system according to claim 1, wherein the algorithm means calculates the psychological state of a visitor using a facial recognition method.

[0899] (Claim 3)

[0900] The system according to claim 1, wherein the output generated by the generation process means is personalized based on evaluations from visitors.

[0901] "Application Example 1"

[0902] (Claim 1)

[0903] A device for collecting visitors' biometric information,

[0904] An inference device for estimating an emotional state using the aforementioned biological information,

[0905] A generating device that generates visual and auditory content based on the estimated emotional state,

[0906] A display device for displaying the generated content,

[0907] A system that includes a device that displays product information and promotions in a store based on the visitor's emotions.

[0908] (Claim 2)

[0909] The system according to claim 1, wherein the inference device analyzes the emotions of visitors using facial recognition technology and provides information based on the visitors' purchasing intent within the store.

[0910] (Claim 3)

[0911] The system according to claim 1, wherein the content generated by the generation device is personalized based on feedback from visitors, and optimized product information is provided for the next visit.

[0912] "Example 2 of combining an emotion engine"

[0913] (Claim 1)

[0914] A means of acquiring information to obtain the biometric information of visitors,

[0915] A communication means for transmitting the aforementioned biometric information to a server,

[0916] An analytical means for analyzing received biometric information and estimating emotional state,

[0917] A generation means for generating visual and auditory content based on the estimated emotional state,

[0918] A presentation means for transmitting and displaying the generated content on a device,

[0919] Adaptive means for collecting user feedback and adjusting the generation means,

[0920] Includes system.

[0921] (Claim 2)

[0922] The system according to claim 1, wherein the analysis means combines facial recognition technology and heart rate analysis to analyze the visitor's emotions with high accuracy.

[0923] (Claim 3)

[0924] The system according to claim 1, wherein the generated content is updated in real time and adapts to changes in the visitor's emotions.

[0925] "Application example 2 when combining with an emotional engine"

[0926] (Claim 1)

[0927] A device for measuring visitors' biometric data,

[0928] A processing unit for analyzing emotional states based on the aforementioned biometric data,

[0929] A generation unit that generates visual and auditory media according to the analyzed emotional state,

[0930] A terminal for presenting the generated media,

[0931] A system that includes means of providing media optimized to enhance the customer experience in real-world environments, based on the customer's physical and psychological information.

[0932] (Claim 2)

[0933] The system according to claim 1, wherein the processing unit performing the analysis uses facial recognition technology to analyze the emotions of the visitor.

[0934] (Claim 3)

[0935] The system according to claim 1, wherein the media generated by the generation unit is adapted based on feedback from visitors. [Explanation of Symbols]

[0936] 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. Equipment for collecting visitor biometric information, An inference device for estimating an emotional state using the aforementioned biological information, A generating device that generates visual and auditory content based on the estimated emotional state, A system including a terminal for displaying the generated content.

2. The system according to claim 1, wherein the inference device analyzes the emotions of a visitor using facial recognition technology.

3. The system according to claim 1, wherein the content generated by the generation device is personalized based on feedback from visitors.

Images