system

Abstract

We provide a system that helps users get quality sleep. [Solution] A system comprising: means for the user to input the elements of a dream they desire; means for sending the input dream elements to a server; means for receiving and analyzing the transmitted data; means for generating a specific dream scenario using a generation AI based on the analyzed data; means for converting the generated scenario into electroencephalogram (EEG) data; means for sending the converted EEG data to the user's terminal; and means for the terminal to send the EEG data to the user's brain in conjunction with REM sleep.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Many people have experienced having nightmares and being unable to fall asleep when they were children, and it has been reported that nightmares reduce the quality of sleep and have accompanying negative impacts on daily life. Also, in many cases, high-quality sleep cannot be obtained due to stress and anxiety. It is an object of the present invention to solve these problems and provide a method for a user to obtain high-quality sleep.

Means for Solving the Problems

[0005] The system provides a means for the user to input desired dream elements, a means for transmitting the input dream elements to a server, a means for receiving and analyzing the transmitted data, a means for generating a specific dream scenario using a generative AI based on the analyzed data, a means for converting the generated scenario into electroencephalogram (EEG) data, a means for transmitting the converted EEG data to the user's terminal, and a means for the terminal to transmit the EEG data to the user's brain in conjunction with REM sleep. This allows the user to have the dreams they desire, achieve quality sleep, and wake up feeling positive.

[0006] A "user" is an individual or entity that uses this system, inputting dream elements and experiencing the dream generated by the system.

[0007] "Dream elements" refer to the specific content of the dream that the user wants to see, including information such as the scenario, characters, location, and events.

[0008] A "server" is a device or system that receives data sent by a user, generates dream scenarios using analysis and generation AI, converts them into brainwave data, and transmits them to the user's terminal.

[0009] "Generative AI" is artificial intelligence that generates specific dream scenarios based on dream elements entered by the user, and it is a technology that uses automated natural language processing and generative models.

[0010] A "dream scenario" is the specific content and development of a dream generated by the AI ​​based on the dream elements specified by the user.

[0011] "Electroencephalogram (EEG) data" refers to electrical signals that have been converted to appropriately convey the generated dream scenario to the user's brain.

[0012] A "terminal" is a device used by a user that transmits user input data to a server, receives brainwave data transmitted from the server, and transmits it to the brain during REM sleep.

[0013] REM sleep is a type of sleep in which the brain is active and dreams are common. By inputting brainwave data during this time, it becomes possible to control dreams. [Brief explanation of the drawing]

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

[0015] 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.

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

[0017] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, 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.

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

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

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

[0022] [First Embodiment]

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

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

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

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

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

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

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

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

[0031] As shown in Figure 2, in the data processing device 12, 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.

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

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

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

[0035] System Overview

[0036] This invention is a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system consists of a user terminal, a server, a generating AI, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[0037] User input processing

[0038] Users input the elements of their dreams using a dedicated application. The application's interface is intuitive, making it easy to select scenarios and enter custom information. For example, users can input specific elements such as "underwater city," "dolphins," or "treasure hunt."

[0039] Sending and receiving data

[0040] The terminal sends the input dream elements to the server. The data is converted to JSON format and transmitted using the secure HTTPS protocol. The server, in turn, analyzes the received data and passes it to a generative AI. This AI uses a natural language processing model to generate a specific dream scenario based on the user's wishes.

[0041] Generating a dream scenario

[0042] The server's generation AI generates stories based on elements entered by the user. For example, it might generate a dream scenario such as "exploring hidden treasure at the bottom of the ocean with the help of dolphins." This scenario is presented as a series of stories, designed to be experienced naturally by the user within the dream.

[0043] Scenario conversion and transmission

[0044] (The server converts the generated dream scenario into electroencephalogram (EEG) data. The algorithm used here maps each element of the generated scenario to a corresponding EEG pattern. This converted EEG data is transmitted to the terminal via a secure communication channel.)

[0045] Receiving brainwave data and experiencing dreams

[0046] The device analyzes and stores brainwave data received from the server. Furthermore, it is equipped with a sensor that monitors the timing of REM sleep. When it detects that the user has entered REM sleep, it transmits brainwave data to the brain. This allows the user to experience their desired dreams.

[0047] Feedback function

[0048] Users provide feedback on their dreams after waking up through a dedicated application. This feedback is used as data to generate higher-quality dream scenarios in the future.

[0049] Specific example

[0050] 1. Let's say the user dreams of an "underwater adventure." They open the dedicated application and input elements such as "underwater city," "dolphins," and "treasure hunt."

[0051] 2. The device sends this data to the server.

[0052] 3. The server analyzes the received data, and the generating AI creates a dream scenario. For example, a scenario where "you encounter dolphins while exploring an underwater city and search for treasure together."

[0053] 4. The server converts this scenario into electroencephalogram (EEG) data and sends it to the terminal.

[0054] 5. The device monitors the timing of REM sleep and transmits brainwave data to the user's brain at the appropriate time.

[0055] 6. Users experience the dreams they desire, waking up with restful sleep and a positive mood.

[0056] The system of this invention aims to control dreams according to the user's wishes and provide high-quality sleep. This makes it possible to improve sleep quality, reduce stress, and wake up feeling positive.

[0057] The following describes the processing flow.

[0058] Detailed program processing flow

[0059] Step 1:

[0060] The user opens a dedicated application and enters the elements of the dream they want to see. The application's interface displays scenario options and custom input boxes, allowing the user to enter specific elements such as "underwater city," "dolphins," or "treasure hunt." Then they press the "Submit" button.

[0061] Step 2:

[0062] The terminal sends the entered dream elements to the server. This process converts the user-entered data into JSON format and sends it to the server in an encrypted format using the HTTPS protocol.

[0063] Step 3:

[0064] The server receives data transmitted via the data reception API. At this stage, it verifies the integrity and format of the data and passes it to the generating AI module for analysis.

[0065] Step 4:

[0066] The server's generation AI module generates dream scenarios based on input data. For example, using topic modeling and sequence generation models, it generates a story like "Meeting dolphins while exploring an underwater city and searching for treasure together."

[0067] Step 5:

[0068] The server converts the generated dream scenario into electroencephalogram (EEG) data. This conversion is performed using a highly specialized algorithm that maps each element of the generated story (e.g., scenes and events) to a corresponding EEG pattern.

[0069] Step 6:

[0070] The server transmits the converted EEG data to the terminal. The transmission uses an encrypted communication channel via a security protocol, ensuring secure and rapid data transfer.

[0071] Step 7:

[0072] The device analyzes the brainwave data received from the server and stores it locally. Furthermore, it uses a sensor to monitor the timing of REM sleep, and when it detects that the user has entered REM sleep, it prepares to transmit the stored brainwave data.

[0073] Step 8:

[0074] The device triggers the transmission of brainwave data to the user's brain when REM sleep is detected. This transmission occurs through a device connected to the user's brain, and dream elements are transmitted to the brain as electrical signals.

[0075] Step 9:

[0076] The user experiences a desired dream based on the electrical signals they input. After waking, they open a dedicated application to provide feedback on the dream they had. This feedback is used to improve the quality of future dream generation.

[0077] The above is the specific processing flow of the "Wake Up Refreshed! Dream Palette" system. This allows users to experience their desired dreams, achieve quality sleep, and wake up feeling refreshed.

[0078] (Example 1)

[0079] 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."

[0080] In modern society, ensuring quality sleep is a crucial issue for users. In particular, many users experience stress and anxiety, leading to an increasing number of cases where they cannot get satisfactory sleep. If users could experience dreams they desire, it would lead to mental refreshment and stress reduction, thus providing quality sleep. However, because there is no concrete system to induce such dream experiences, users are unable to freely experience the dreams they want.

[0081] 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.

[0082] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the input dream elements to a digital device, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to a digital device, means for the digital device to transmit the EEG data to the user's brain in conjunction with REM sleep, means for providing feedback on the dream the user experienced, and sensors for monitoring the timing of REM sleep. This enables the user to experience their desired dream and obtain quality sleep.

[0083] "A means of inputting the dream elements desired by the user" refers to providing an interface for users to input the dream elements they wish to experience, and a means of incorporating that input data into the system.

[0084] "Means for transmitting input dream elements to a digital device" refers to a means for converting the dream elements entered by the user into a data format and securely transmitting them to a digital device.

[0085] "Means for receiving and analyzing transmitted data" refers to a method of receiving data from a transmitted digital device, analyzing its contents, and extracting elements of dreams.

[0086] "A method for generating specific dream scenarios using generative AI" refers to a method of creating specific dream scenarios that users will experience, based on the elements of the dreams they have received, using generative AI (artificial intelligence).

[0087] "Methods for converting generated scenarios into brainwave data" refers to methods for converting generated dream scenarios into corresponding brainwave patterns so that users can actually experience the dream.

[0088] "Means for transmitting converted brainwave data to a digital device" refers to means for securely transmitting converted brainwave data to a digital device.

[0089] "A method by which a digital device transmits brainwave data to a user's brain in conjunction with REM sleep" refers to a method in which a digital device detects the user's REM sleep and sends brainwave data to the user's brain at that time.

[0090] "A means of providing feedback on dreams experienced by users" refers to a method for users to provide feedback to the system regarding their thoughts and opinions about the dreams they have experienced.

[0091] A "sensor that monitors the timing of REM sleep" is a sensor that monitors the user's sleep state and detects when the user enters REM sleep.

[0092] This invention is a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system consists of a user terminal, a server, a generating AI, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[0093] User input processing

[0094] The user launches a dedicated application and enters the elements of the dream they want to see. This application features an intuitive interface, allowing users to input their desired dream elements through text input or by selecting options. For example, they can enter "underwater city," "dolphins," or "treasure hunt."

[0095] Sending and receiving data

[0096] The terminal converts the dream elements entered by the user into JSON data and sends it to the server using the HTTPS protocol. The terminal encrypts the data using SSL / TLS to ensure its security. The server receives and analyzes the data sent from the terminal. This analysis includes data extraction and the generation of prompts for the generative AI model.

[0097] Generating dream scenarios using AI

[0098] The generation AI installed on the server generates a specific dream scenario that includes elements desired by the user, based on the received prompt text. The generation AI model uses natural language processing technology to create a story based on the elements input by the user. For example, it can generate a scenario such as "searching for treasure with dolphins in an underwater city."

[0099] Scenario conversion and transmission

[0100] The server converts the generated dream scenario into brainwave data. A specialized algorithm is used for this conversion, mapping each element of the scenario to a corresponding brainwave pattern. The brainwave data is encrypted to ensure security and transmitted to a digital device.

[0101] Receiving brainwave data and experiencing dreams

[0102] The device receives transmitted brainwave data and stores it in local storage. Furthermore, the device is equipped with a sensor that monitors the timing of REM sleep, monitoring the user's sleep state in real time. When the sensor detects the user's REM sleep, the device transmits the stored brainwave data to the user's brain. This allows the user to experience their desired dreams.

[0103] Feedback function

[0104] After waking up, users provide feedback about their dreams through a dedicated application. This feedback is used as training data for the generating AI and is reflected in the creation of future dream scenarios. This allows users to experience dreams that are more faithful to their preferences and of higher quality.

[0105] Specific example

[0106] The following are some specific examples.

[0107] 1. The user expresses a desire to experience an "underwater adventure" and opens the dedicated application.

[0108] 2. Enter specific elements such as "underwater city," "dolphins," and "treasure hunt."

[0109] 3. The device converts this data into JSON format and sends it to the server using HTTPS.

[0110] 4. The server receives and analyzes the data to generate a prompt message, which is then passed to the generating AI. The generating AI then creates a dream scenario: "While exploring an underwater city, you encounter dolphins and search for treasure together."

[0111] 5. Convert the scenario into electroencephalogram (EEG) data and transmit it to the terminal via a secure channel.

[0112] 6. The device stores brainwave data and detects the user's REM sleep, transmitting the data to the brain.

[0113] 7. Users experience the dreams they desire and provide feedback about the dreams they had.

[0114] Examples of prompts to input into a generative AI model

[0115] The following are specific examples of prompt statements to be input to a generative AI model.

[0116] "The user wants to dream about an 'underwater city,' 'dolphins,' and 'treasure hunting.' Please generate a specific dream scenario that includes these elements."

[0117] This system allows users to experience their desired dreams and get quality sleep.

[0118] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0119] Step 1:

[0120] The user launches a dedicated application and inputs the elements of the dream they want to see. This input is done through text boxes or selection lists, such as "underwater city," "dolphins," or "treasure hunt." The input data (e.g., underwater city, dolphins, treasure hunt) is then taken into the system.

[0121] Step 2:

[0122] The terminal converts the dream elements entered by the user into JSON format and sends them to the server using the HTTPS protocol. Specifically, it transforms the input data (e.g., underwater city, dolphins, treasure hunt) into a JSON structure and sends it as SSL / TLS encrypted data. The JSON formatted data is output and sent to the server via a secure communication channel.

[0123] Step 3:

[0124] The server receives JSON data sent from the terminal. It parses the received data and extracts the dream elements. Specifically, it parses the received data (e.g., {"elements":["Underwater city", "Dolphin", "Treasure hunt"]}) and extracts a list of elements. The extracted list of elements is output.

[0125] Step 4:

[0126] The server generates a prompt message for the generating AI based on the element list and passes it to the AI. The generated prompt message (e.g., "The user wants to have a dream that includes 'underwater city,' 'dolphins,' and 'treasure hunt.' Please generate a specific dream scenario that includes these elements.") is input into the generating AI model. The prompt message is output and passed to the generating AI model.

[0127] Step 5:

[0128] The generative AI generates a specific dream scenario that includes elements desired by the user, based on the given prompt text. Specifically, the generative AI model receives the prompt text as input and performs natural language processing to generate a scenario such as "Meeting a dolphin while exploring an underwater city and searching for treasure together." The generated scenario is then output.

[0129] Step 6:

[0130] The server converts the generated dream scenario into brainwave data. It uses a conversion algorithm that maps each scene and element of the scenario to the corresponding brainwave pattern. The scenario received as input (e.g., "While exploring an underwater city, I meet a dolphin and we search for treasure together") is converted into a brainwave pattern, and the brainwave data is output.

[0131] Step 7:

[0132] The server transmits the converted EEG data to the terminal via a secure communication channel. Data security is ensured by sending the EEG data to the terminal using encrypted communication. As output, encrypted EEG data is sent to the terminal.

[0133] Step 8:

[0134] The device saves the received brainwave data to local storage. Furthermore, the device is equipped with a sensor that monitors the timing of REM sleep. This sensor analyzes the user's brainwaves in real time and detects when the user enters REM sleep. Upon detecting REM sleep, the stored brainwave data is output and transmitted to the user's brain.

[0135] Step 9:

[0136] The user receives brainwave data transmitted from the device during REM sleep. This allows them to experience a dream where they "encounter dolphins while exploring an underwater city and search for treasure together." Because the user's brain shapes the dream according to the received brainwave data, the user can experience the dream they desire.

[0137] Step 10:

[0138] After waking up, users provide feedback about their dreams through a dedicated application. This feedback includes details and impressions of the dream. This feedback data is sent to the server as learning data to be used in future scenario generation. This allows the system to provide higher-quality dreams.

[0139] (Application Example 1)

[0140] 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."

[0141] Conventional dream induction systems were designed for individual users to use at home, and therefore did not consider use in physical establishments such as relaxation facilities and spas. As a result, there was a lack of means to significantly improve the customer experience in these physical locations. Furthermore, there was no system that allowed customers in relaxation facilities to easily input their desired dreams and experience them as actual dreams. In addition, there were no means to efficiently induce dreams for multiple customers, resulting in a limited quality of customer experience.

[0142] 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.

[0143] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the inputted dream elements to the server, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI based on the analyzed data, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to the user's terminal, means for the terminal to transmit the EEG data to the user's brain in conjunction with REM sleep, means for the customer to input dream elements using an input device in the store, means for the input device to transmit the dream elements to the server, means for the server to convert the data into EEG data based on the dream scenario and transmit it to a relaxation device, and means for the relaxation device to transmit the EEG data to the user's brain during REM sleep. This makes it possible to allow users to experience dreams based on their individual preferences in a physical store, significantly improving the quality of the customer experience at relaxation facilities. It also makes it possible to efficiently and effectively induce dreams for multiple customers.

[0144] A "user" refers to an individual who uses the system to experience their dreams.

[0145] "Dream elements" are the elements that make up the specific scenarios and situations that users input in their dreams that they want to experience.

[0146] A "server" refers to a computer system that receives data sent by users and uses AI for analysis and generation to create dream scenarios.

[0147] "Generative AI" refers to an artificial intelligence model that generates specific dream scenarios based on the elements of a dream that are input.

[0148] A "scenario" refers to a series of events that form the specific story or scenes that a user experiences in their dreams.

[0149] "Electrical wave data" refers to the brainwave patterns that have been converted to allow the user to experience the generated dream scenario.

[0150] A "terminal" refers to a device used by a user that has the function of receiving brainwave data transmitted from a server and transmitting it to the user's brain.

[0151] "REM sleep" refers to the primary sleep stage in which users dream, and it is possible to induce dreams by transmitting brainwave data during this time.

[0152] An "input device" refers to a device used by users to input elements of their dreams, and is typically installed in physical stores or other similar locations.

[0153] A "relaxation device" refers to a device that has the function of appropriately transmitting brainwave data to the user and providing a dream-like experience.

[0154] This invention is a system that allows users to experience their desired dreams during REM sleep. This system works by having the user input elements of their dream, and then a generating AI uses that information to create a specific dream scenario, which is then transmitted to the user as brainwave data.

[0155] System Configuration

[0156] 1. Processing user input

[0157] Users input the elements of their desired dream using a dedicated input device. The input device is installed in physical relaxation facilities, and its user interface is intuitive, making it easy to select scenarios and customize inputs. For example, users can input specific elements such as "beach," "exotic forest," or "quiet mountain lake."

[0158] 2. Sending and receiving data

[0159] The input device sends the input dream elements to the server. The data is converted to JSON format and transmitted using the secure HTTPS protocol. The server analyzes the received data and passes it to a generative AI. This AI uses a natural language processing model to generate a specific dream scenario based on the user's wishes.

[0160] 3. Generating a dream scenario

[0161] The server's generation AI creates stories based on the elements entered by the user. For example, it might generate a dream scenario such as "You standing by a quiet mountain lake." This scenario is presented in a narrative format and is designed to be experienced naturally by the user within the dream.

[0162] 4. Scenario conversion and transmission

[0163] The server converts the generated dream scenario into electroencephalogram (EEG) data. The generative AI model used here maps each element of the generated scenario to a corresponding EEG pattern. This converted EEG data is transmitted to the relaxation device via a secure communication channel.

[0164] 5. Receiving EEG data and experiencing dreams

[0165] The relaxation device analyzes and stores brainwave data received from a server. Furthermore, it is equipped with a sensor that monitors the timing of REM sleep. When it detects that the user has entered REM sleep, it transmits brainwave data to the brain. This allows the user to experience their desired dreams.

[0166] Hardware and software to be used

[0167] Input device: A device for customers to input elements of their dreams. It is installed in physical stores.

[0168] Server: A computer system that receives dream elements, analyzes them, and generates dream scenarios using a generative AI.

[0169] Generative AI: A natural language processing model that creates dream scenarios based on dream elements entered by the user.

[0170] Relaxation device: A device that monitors the timing of REM sleep and transmits brainwave data.

[0171] Specific example

[0172] The customer inputs elements of their desired dream, such as "I want to relax by a quiet mountain lake," into an input device at the relaxation facility. The input device sends this data to a server, which generates a scenario of "themselves standing by a quiet mountain lake." The generated scenario is converted into brainwave data and sent to the relaxation device. The relaxation device monitors the customer's REM sleep and sends brainwave data at the appropriate time.

[0173] Example of a prompt

[0174] The user entered "I want to relax by a quiet mountain lake." Based on this, generate a dream scenario that will help the user relax.

[0175] This format allows users to significantly enhance their experience at relaxation facilities and provides dream experiences tailored to their individual preferences.

[0176] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0177] Step 1: The user enters the elements of their dream.

[0178] Users access an input device installed in a physical store and input elements of their dream experience (e.g., "beach," "exotic forest," "quiet mountain lake"). The input device interface is intuitive, allowing users to easily select or customize their desired elements. The input data is in text format.

[0179] Step 2: Submit the input data

[0180] The input device sends the dream elements entered by the user to the server. The input data is converted to JSON format and sent to the server using the secure HTTPS protocol. An example of input data is {"dream_elements": ["beach", "exotic forest", "quiet mountain lake"]}.

[0181] Step 3: Data reception and analysis

[0182] The server receives data transmitted from the input device. The received data is analyzed and used as material to generate specific dream scenarios based on the user's wishes. This analysis involves examining the structure of the received data and extracting its elements.

[0183] Step 4: Generating dream scenarios using a generative AI

[0184] The server passes the analyzed data to the generative AI. The generative AI model uses natural language processing to generate specific dream scenarios based on the input data. For example, if the user input is "I want to relax by a quiet mountain lake," the generated scenario might be something like "I am standing by a quiet mountain lake."

[0185] Step 5: Converting the scenario's EEG data

[0186] The server converts the generated dream scenario into brainwave data. The generating AI model maps each element of the output scenario to the corresponding brainwave pattern, generating brainwave data that the user can experience as a dream. This converted data is in binary format.

[0187] Step 6: Sending EEG data

[0188] The server transmits the converted EEG data to the relaxation device. The EEG data is sent to the relaxation device using a secure communication channel. The transmitted data is stored in the device's memory.

[0189] Step 7: Monitoring REM sleep

[0190] The relaxation device monitors the user's REM sleep timing using built-in sensors. The sensors analyze brainwave patterns in real time to detect when the user enters REM sleep. Electrodes-based electroencephalogram (EEG) measurement devices and heart rate monitors are used to determine REM sleep.

[0191] Step 8: Sending EEG data and inducing dreams

[0192] After the relaxation device detects the timing of REM sleep, it transmits the received brainwave data to the user's brain. This allows the user to experience the dream they desire. The data transmission is performed using a dedicated brainwave transmission function.

[0193] This series of processes allows users to experience customized dreams at relaxation facilities, providing them with high-quality relaxation.

[0194] 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.

[0195] System Overview

[0196] This invention incorporates an emotion engine into a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system recognizes the user's emotional state and selects and adjusts dreams based on that state. The system consists of a user terminal, a server, a generation AI, an emotion engine, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[0197] User input processing

[0198] Users input the elements of their desired dream using a dedicated application. The application interface displays scenario options and custom input boxes, allowing users to enter specific elements such as "underwater city," "dolphins," and "treasure hunt." Furthermore, an emotion engine analyzes the user's emotional state, and suggests dream elements based on the results.

[0199] How the emotion engine works

[0200] The device collects emotion analysis data to recognize the user's emotional state. This data is obtained, for example, through voice analysis, facial expression analysis, and biometric data analysis from wearable devices. The collected emotion data is sent from the device to a server and analyzed by an emotion engine.

[0201] Analysis and proposals regarding emotional data

[0202] The server's emotion engine analyzes the received emotion data to identify the user's current emotional state. Based on the analyzed emotional state, it suggests the most suitable dream elements. These suggestions are returned to the user's device and displayed in the application. The user then decides whether to accept the suggested elements or enter custom elements.

[0203] Sending and receiving data

[0204] The device sends the elements of the dream that the user has finally decided on to the server. The data is converted to JSON format and transmitted in an encrypted format using the secure HTTPS protocol. Meanwhile, the server analyzes the received data and passes it to a generative AI. This generative AI uses a natural language processing model to generate a specific dream scenario based on the user's wishes.

[0205] Generating a dream scenario

[0206] The server's AI generates dream scenarios based on user input and emotional data. For example, it might generate a dream scenario such as "encountering dolphins while exploring an underwater city and searching for treasure together." This scenario can be customized to match the user's emotional state.

[0207] Scenario conversion and transmission

[0208] The server converts the generated dream scenario into electroencephalogram (EEG) data. This conversion is performed using a specialized algorithm that maps each element of the generated scenario (e.g., scenes and events) to the corresponding EEG pattern. The converted EEG data is then transmitted to the terminal via a secure communication channel.

[0209] Receiving brainwave data and experiencing dreams

[0210] The device analyzes and stores brainwave data received from the server. It also uses a sensor to monitor the timing of REM sleep, and when it detects that the user has entered REM sleep, it transmits the stored brainwave data to the brain.

[0211] Feedback function

[0212] Users provide feedback on their dreams after waking up through a dedicated application. This feedback data is used to improve the accuracy of the dream generation algorithm and emotion engine for future use.

[0213] Specific example

[0214] 1. The user expresses a desire for an "underwater adventure," opens the application, and inputs elements such as "underwater city," "dolphins," and "treasure hunt." Suggestions from the emotion engine are also considered.

[0215] 2. The device sends this data and sentiment data to the server.

[0216] 3. The server analyzes the received data, and the generating AI creates a dream scenario. For example, a scenario where "you encounter dolphins while exploring an underwater city and search for treasure together."

[0217] 4. The server converts this scenario into electroencephalogram (EEG) data and sends it to the terminal.

[0218] 5. The device monitors the timing of REM sleep and transmits brainwave data to the user's brain at the appropriate time.

[0219] 6. Users can have the dreams they desire and enjoy restful sleep.

[0220] The system of this invention aims to control dreams according to the user's wishes and provide high-quality sleep. Furthermore, by utilizing an emotion engine, it is possible to provide an optimal dream experience tailored to the user's emotional state.

[0221] The following describes the processing flow.

[0222] Specific processing flow of the program

[0223] Step 1:

[0224] The user opens a dedicated application and enters the elements of the dream they want to see. The application interface displays scenario options and custom input boxes, allowing the user to enter specific elements such as "underwater city," "dolphins," or "treasure hunt," and then press the "Submit" button.

[0225] Step 2:

[0226] The device collects the user's emotional state using voice input, facial recognition, or biometric data acquired from wearable devices. The collected data is sent to the emotion engine in real time.

[0227] Step 3:

[0228] The device converts the user's emotional data and dream elements into JSON format and sends them to the server using the secure HTTPS protocol.

[0229] Step 4:

[0230] The server receives data sent via the data reception API. It verifies the integrity and format of the data and passes it to the emotion engine. The emotion engine analyzes the user's emotional state and suggests the most suitable dream elements based on the results. This suggestion is returned to the user's device.

[0231] Step 5:

[0232] The user reviews and modifies dream elements based on suggestions from the emotion engine. For example, if the emotion engine suggests "relaxing underwater exploration," the user can add "treasure hunting."

[0233] Step 6:

[0234] The device then sends the finalized dream elements back to the server. This data is converted to JSON format and transmitted using a secure communication channel.

[0235] Step 7:

[0236] The server analyzes the received dream element data and passes it to the generating AI. The generating AI then generates a specific dream scenario based on this data. For example, it might generate a scenario such as, "While exploring an underwater city, you encounter a dolphin and search for treasure together."

[0237] Step 8:

[0238] The server converts the generated scenario into electroencephalogram (EEG) data. This conversion is performed using a specialized algorithm that maps each element of the generated scenario (e.g., scenes and events) to the corresponding EEG pattern. The converted EEG data is transmitted to the terminal via a secure communication channel.

[0239] Step 9:

[0240] The device analyzes and stores brainwave data received from the server. Furthermore, it is equipped with a sensor that monitors the timing of REM sleep. When it detects that the user has entered REM sleep, it prepares to transmit the stored brainwave data to the brain.

[0241] Step 10:

[0242] The device triggers the transmission of brainwave data to the user's brain when REM sleep is detected. This transmission occurs through a device connected to the user's brain, and dream elements are transmitted to the brain as electrical signals.

[0243] Step 11:

[0244] The user experiences a desired dream based on the electrical signals they input. For example, they might dream of "searching for treasure with dolphins in an underwater city." After waking, they open a dedicated application to provide feedback on their dream. This feedback is used to improve the accuracy of the dream generation algorithm and emotion engine for future sessions.

[0245] (Example 2)

[0246] 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".

[0247] To improve sleep quality, there is a need for a system that allows users to experience dreams of their choice. However, conventional technology has been unable to adjust dream content based on the user's emotional state, making it difficult to provide dreams optimized for the user's psychological state. Furthermore, there was a lack of mechanisms to collect feedback on the dreams users experienced and use that feedback to improve the system's accuracy. In addition, the lack of a means to accurately detect the timing of REM sleep made it difficult to provide an effective dream experience.

[0248] 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.

[0249] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the input dream elements to the server, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI based on the analyzed data, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to the user's terminal, means for the terminal to transmit the EEG data to the user's brain in conjunction with REM sleep, means for collecting and analyzing the user's emotional data, and means for suggesting dream elements based on the analyzed emotional data. This makes it possible to allow the user to experience the content of their desired dream and to provide a dream optimized for their emotional state at the time. Furthermore, feedback on the dreams seen can be collected and used to improve the accuracy of the system. In addition, by accurately detecting the timing of REM sleep, a more effective dream experience can be provided to the user.

[0250] A "user" is the individual who uses the system to input the content of their desired dream and then experiences that dream.

[0251] "Dream elements" refer to specific scenarios, scenes, characters, themes, etc., that users want to experience.

[0252] The "server" is a central processing unit that analyzes data sent by users, generates dream scenarios using a generative AI and emotion engine, and converts those scenarios into brainwave data for transmission.

[0253] A "terminal" is a device that the user directly operates, and it is a device that inputs dream elements, collects emotional data, monitors REM sleep, and transmits brainwave data.

[0254] "Emotional data" refers to data that indicates a user's current emotional state, and includes information collected through voice analysis, facial expression analysis, and biometric data analysis from wearable devices.

[0255] The "emotion engine" is a software component that analyzes collected emotional data and, based on the results, suggests the most suitable dream elements to the user.

[0256] "Generative AI" is an artificial intelligence model that generates specific dream scenarios based on received data and analyzed emotional data.

[0257] "Electroencephalogram (EEG) data" refers to data that has been converted to transmit the generated dream scenario to the user's brain, and is expressed as an EEG pattern.

[0258] "REM sleep" is a deep stage of sleep in which users are more likely to dream, and brainwave data is transmitted during this time to induce the desired dream.

[0259] "Feedback" refers to information provided by users through a dedicated application, detailing the content and their impressions of their dreams. This information helps improve the accuracy of future dream generation.

[0260] A "sensor" is a device used to monitor the timing of a user's REM sleep.

[0261] Modes for carrying out the invention

[0262] System Configuration

[0263] This invention incorporates an emotion engine into a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system recognizes the user's emotional state and selects and adjusts dreams based on that state. The system consists of a user terminal, a server, a generation AI, an emotion engine, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[0264] User input processing

[0265] The user launches a dedicated application and enters the elements of the dream they want to see into the interface. Fields are provided for entering specific elements such as "underwater city," "dolphins," and "treasure hunt." Once the user has finished entering the information, the device collects this data.

[0266] How the emotion engine works

[0267] The device simultaneously collects emotional data. For this data collection, the device is equipped with voice analysis, facial expression analysis, and biometric data analysis functions for wearable devices. The collected emotional data is transmitted from the device to a server.

[0268] Analysis and proposals regarding emotional data

[0269] The server's emotion engine analyzes the received emotion data to identify the user's current emotional state. Based on the analysis, it suggests the most suitable dream elements. These suggestions are sent back from the server to the terminal and displayed in the application for the user to review. The user then decides whether to accept the suggested elements or enter new custom elements.

[0270] Generating a dream scenario

[0271] The device sends the elements of the dream that the user has finally decided on to the server. This transmission is converted to JSON format and performed using the secure HTTPS protocol. The server parses the received data and passes it on to the generative AI. The generative AI uses a natural language processing model to generate a specific dream scenario.

[0272] For example, it can generate a specific scenario such as, "While exploring an underwater city, you encounter dolphins and search for treasure together."

[0273] Scenario conversion and transmission

[0274] The server converts the generated dream scenario into electroencephalogram (EEG) data. This conversion process uses a specialized algorithm that maps each element of the generated scenario (e.g., scenes and events) to a corresponding EEG pattern. The converted EEG data is then transmitted to the terminal via a secure communication channel.

[0275] Dream experience

[0276] The device analyzes and stores brainwave data received from the server. It also uses a sensor to monitor the timing of REM sleep, and when it detects that the user has entered REM sleep, it transmits the stored brainwave data to the brain. As a result, the user experiences the dream they desired.

[0277] Feedback function

[0278] Users provide feedback on their dreams after waking up through a dedicated application. This feedback data is used to improve the accuracy of the dream generation algorithm and emotion engine for future use.

[0279] Examples of specific cases and prompt statements

[0280] Specifically, a user might express a desire for an "underwater adventure" and use the application to input elements such as "underwater city," "dolphins," and "treasure hunt." The device sends this data, along with emotional data, to a server, which analyzes it, and a generating AI creates a dream scenario. For example, a scenario might be generated where the user "encounters dolphins while exploring an underwater city and searches for treasure together." The server converts this scenario into brainwave data and sends it to the device. The device monitors the timing of REM sleep and sends the brainwave data to the user's brain at the appropriate time. The user then experiences the dream they desired and enjoys a fulfilling sleep.

[0281] An example of a prompt message is as follows:

[0282] Enter dream elements such as "Underwater City", "Dolphin", and "Treasure Hunt". Also check the elements proposed by the emotion engine.

[0283] By using such a system, it is possible to provide a dream according to the user's wishes and support good-quality sleep. Furthermore, by utilizing the emotion engine, it is possible to obtain a dream experience optimized for the user's emotional state.

[0284] The flow of the specific process in Example 2 will be described using FIG. 13.

[0285] Step 1: Input of user's desired elements

[0286] The user launches the dedicated application and enters the elements of the dream they want to see into the interface. There are fields provided where specific elements such as "Underwater City", "Dolphin", and "Treasure Hunt" can be entered.

[0287] Input: The elements of the dream entered by the user into the dedicated application.

[0288] Output: The dream element data held in the terminal.

[0289] Operation: The user enters specific dream elements in text form into the input field of the application and presses the send button.

[0290] Step 2: Collection of emotion data

[0291] The terminal performs voice analysis, facial expression analysis, and biometric data analysis of the wearable device in order to recognize the user's emotional state.

[0292] Input: The user's voice, facial expressions, and biometric data from the wearable device.

[0293] Output: The analyzed emotion data.

[0294] Action: Collect the user's emotional data using the built-in camera, microphone, and wearable sensors of the terminal. Temporarily store the data.

[0295] Step 3: Sending Emotional Data

[0296] The terminal sends the collected emotional data to the server. This transmission uses the secure HTTPS protocol, and the data is encrypted.

[0297] <000,0938>Input: Collected emotional data.

[0298] Output: Emotional data sent to the server.

[0299] Action: The terminal encrypts the emotional data using the HTTPS protocol and sends it to the server.

[0300] Step 4: Analysis of Emotional Data

[0301] The server passes the received emotional data to the emotion engine for analysis. The emotion engine uses natural language processing and machine learning algorithms to identify the user's emotional state.

[0302] Input: Received emotional data.

[0303] Output: Analyzed emotional state.

[0304] Action: The emotion engine uses algorithms to analyze the user's emotional data item by item and identify the current emotional state.

[0305] Step 5: Proposal of Dream Elements

[0306] The emotion engine of the server proposes the optimal dream elements based on the analysis results. The proposed content is converted into JSON format and sent to the terminal through a secure channel.

[0307] Input: Analyzed emotional state.

[0308] Output: Dream element proposal data.

[0309] Operation: The emotion engine selects the most suitable dream elements for the user based on the analysis results, converts them into JSON format, and sends them to the device.

[0310] Step 6: View and select suggestions

[0311] The device displays the received suggestions to the user. The user then decides whether to accept the suggested elements or enter custom elements.

[0312] Input: Data on the elements of the proposed dream.

[0313] Output: User's final selection data.

[0314] Operation: The device displays the received suggestions in the application interface, and the user confirms and selects them.

[0315] Step 7: Submit selected elements

[0316] The terminal sends the finalized dream elements to the server. This transmission also uses the secure HTTPS protocol.

[0317] Input: User's last selected data.

[0318] Output: Dream element data sent to the server.

[0319] Operation: Converts the dream elements selected by the user into JSON format and sends them to the server using the HTTPS protocol.

[0320] Step 8: Generating dream scenarios using a generative AI

[0321] The server analyzes the received dream elements and passes them to the generative AI. The generative AI uses a natural language processing model to generate a specific dream scenario.

[0322] Input: User's dream element data.

[0323] Output: The generated dream scenario.

[0324] Operation: The generating AI applies a specific algorithm based on the received data to generate dream scenarios such as "Meeting dolphins while exploring an underwater city and searching for treasure together."

[0325] Step 9: Converting the scenario into EEG data

[0326] The server converts the generated dream scenario into brainwave data. Using specialized algorithms, it maps each scene and event to a brainwave pattern.

[0327] Input: The generated dream scenario.

[0328] Output: Converted electroencephalogram (EEG) data.

[0329] Operation: Analyze the generated scenario and apply an algorithm to convert it into electroencephalogram (EEG) data.

[0330] Step 10: Sending EEG data

[0331] The server transmits the converted EEG data to the terminal. This transmission also uses a secure communication channel.

[0332] Input: Converted electroencephalogram (EEG) data.

[0333] Output: EEG data transmitted to the terminal.

[0334] Operation: Transmits EEG data to the terminal via a secure channel.

[0335] Step 11: Monitoring REM sleep

[0336] The device uses sensors to monitor the timing of REM sleep.

[0337] Input: User's sleep status data.

[0338] Output: REM sleep timing detection information.

[0339] Operation: The device continuously monitors the user's sleep state using a REM sleep monitoring sensor.

[0340] Step 12: Sending EEG data

[0341] When the device detects that the user has entered REM sleep, it transmits the stored brainwave data to the user's brain.

[0342] Input: REM sleep timing detection information and stored electroencephalogram (EEG) data.

[0343] Output: Brainwave data transmitted to the user's brain.

[0344] Operation: When REM sleep is detected, the stored electroencephalogram (EEG) data is transmitted to the user's brain.

[0345] Step 13: Provide feedback on your dream

[0346] Users provide feedback about their dreams after waking up through a dedicated application. This feedback data is used to improve the accuracy of the system.

[0347] Input: User feedback information.

[0348] Output: Collected feedback data.

[0349] Operation: Users input their thoughts and evaluations about the content of their dreams using a dedicated application, and this information is sent to the server.

[0350] (Application Example 2)

[0351] 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".

[0352] Conventional systems have found it difficult to individually customize users' dream experiences and lacked sufficient functionality to adjust dream elements based on emotional states. Furthermore, providing feedback based on actual experience was challenging in employee customer service and negotiation skills training. This invention proposes a system that solves these problems and provides optimal dream experiences and training based on the user's emotional state.

[0353] 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.

[0354] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the input dream elements to the server, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI based on the analyzed data, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to the user's terminal, means for the terminal to transmit the EEG data to the user's brain in accordance with REM sleep, means for recognizing and analyzing the user's emotional state, and means for adjusting the dream scenario based on the analyzed emotional data. This makes it possible to adjust the dream experience and training scenario based on the user's emotional state.

[0355] A "user" refers to someone who uses this system to customize their dream experiences and training scenarios.

[0356] "Dream elements" refer to specific items or situations that users want to include in their desired dreams or training scenarios.

[0357] A "server" refers to a central system that receives, analyzes, and processes data sent by users.

[0358] "Means of input" refers to the interface or device that allows the user to input elements of their dreams into the system.

[0359] "Means of transmission" refers to the means of communication used to send the input dream elements to the server.

[0360] "Means for receiving and analyzing" refers to the software and hardware used by the server to receive transmitted data and analyze it.

[0361] "Generative AI" refers to artificial intelligence that uses natural language processing models to generate specific dream scenarios.

[0362] "Means of conversion" refers to algorithms and systems for converting the generated dream scenarios into brainwave data.

[0363] A "terminal" refers to a device used by a user, specifically equipment that receives and transmits electroencephalogram (EEG) data.

[0364] "REM sleep" refers to the period of time when a user enters a deep sleep state, a time when they are more likely to dream.

[0365] "Emotional state" refers to the user's current emotional state and is analyzed from voice, facial expressions, biometric data, and other sources.

[0366] "Means of recognition and analysis" refers to software and hardware for identifying and analyzing a user's emotional state.

[0367] "Means of adjustment" refers to a system for optimizing dream scenarios and training scenarios based on analyzed emotional data.

[0368] This invention provides a system that allows users to input desired dream elements and experience them during REM sleep, as well as a function to recognize emotional states and adjust training scenarios. The system consists of a user terminal, a server, a generative AI, an emotion engine, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[0369] Users access a dedicated application using smart glasses and input elements of the dream or training scenario they wish to experience. For example, for a customer service skills training scenario, they might input specific elements such as "handling complaints" and "product description." The emotion engine analyzes the user's emotional state and displays suggestions for the most suitable training scenario based on the results.

[0370] Smart glasses collect the user's voice, facial expressions, and biometric data and send it to an emotion engine. The emotion engine uses Azure Cognitive Services' emotion recognition API to analyze this data and identify the user's current emotional state. The collected emotional data and user preferences are sent to a server, where a generative AI (e.g., OpenAI's GPT-3) generates specific scenarios based on prompts.

[0371] The server converts the generated scenario into electroencephalogram (EEG) data and sends it to the user's terminal using a secure communication channel (HTTPS). The terminal uses sensors to monitor the timing of REM sleep and transmits EEG data when the user enters REM sleep.

[0372] Furthermore, in training scenarios, the received scenario is overlaid on the smart glasses. The smart glasses monitor the user's emotional state in real time and provide appropriate advice and feedback as the scenario progresses.

[0373] As a concrete example, consider a case where a user requests a training scenario for "handling customer complaints." In this case, the user opens the application and types "handling complaints." Emotional data obtained from voice and facial expressions is sent to the server, and the generating AI creates a "customer complaint dialogue scenario." For example, a scenario is generated in which "a customer complains about a product defect, and the user learns specific ways to handle it," and this is converted into brainwave data. Furthermore, the progress of the training is adjusted and appropriate feedback is provided based on the emotional data collected in real time.

[0374] The following are specific examples of prompt statements for generative AI models:

[0375] "The user's desired scenario is 'handling a complaint,' and their emotional state is 'feeling stressed.' Please generate an appropriate training scenario."

[0376] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0377] Step 1:

[0378] Users input elements of their desired dreams or training scenarios through a dedicated application for smart glasses. For example, they might input specific elements such as "handling customer complaints" or "product description." The input data includes elements specified in text format.

[0379] Step 2:

[0380] The terminal sends the data entered by the user to the server. The data sent includes the elements requested by the user and is sent to the server in JSON format.

[0381] Step 3:

[0382] The server receives the transmitted data and performs analysis. This analysis includes emotion recognition, which is performed using the user's voice and facial expression data. Specifically, it calls the Azure Cognitive Services emotion recognition API to generate emotion data as an analysis result. The input data is voice and image data, and the output is a tag or score indicating the emotional state.

[0383] Step 4:

[0384] The server uses a generative AI model to generate specific scenarios based on the analyzed emotional data and the user's desired elements. In this process, it uses OpenAI's GPT-3 to create prompts such as: "The user's desired scenario is 'Handling a complaint,' and their emotional state is 'Feeling stressed.' Please generate an appropriate training scenario." The output data generated by the generative AI is the specific scenario text.

[0385] Step 5:

[0386] The server converts the generated scenario into electroencephalogram (EEG) data. This conversion uses a specialized algorithm that maps each element of the generated scenario to a corresponding EEG pattern. The input data is the scenario text, and the output is EEG data.

[0387] Step 6:

[0388] The server transmits the converted EEG data to the terminal. The terminal receives and stores the data. Communication is conducted via the secure HTTPS protocol. The input data is EEG data, and the output is data storage on the terminal.

[0389] Step 7:

[0390] The device uses sensors that monitor the timing of REM sleep to detect when the user enters REM sleep. When REM sleep is detected, it transmits stored brainwave data to the user's brain. The input data is biometric information from the sensors, and the output is the transmission of brainwave data.

[0391] Step 8:

[0392] The user's smart glasses overlay the received training scenario and monitor their emotional state in real time. The emotion engine provides feedback and advice at appropriate times. The input data is the user's emotional state, and the output is feedback corresponding to the progress of the scenario.

[0393] Step 9:

[0394] Users provide feedback after training or dream experiences. This feedback data is used to improve the accuracy of future scenario generation and the emotion engine. The input data is the user's feedback text, and the output is the application of that feedback to the system's algorithm.

[0395] 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.

[0396] 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.

[0397] 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.

[0398] [Second Embodiment]

[0399] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0400] 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.

[0401] 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).

[0402] 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.

[0403] 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.

[0404] 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).

[0405] 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.

[0406] 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.

[0407] 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.

[0408] 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.

[0409] 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.

[0410] 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".

[0411] System Overview

[0412] This invention is a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system consists of a user terminal, a server, a generating AI, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[0413] User input processing

[0414] Users input the elements of their dreams using a dedicated application. The application's interface is intuitive, making it easy to select scenarios and enter custom information. For example, users can input specific elements such as "underwater city," "dolphins," or "treasure hunt."

[0415] Sending and receiving data

[0416] The terminal sends the input dream elements to the server. The data is converted to JSON format and transmitted using the secure HTTPS protocol. The server, in turn, analyzes the received data and passes it to a generative AI. This AI uses a natural language processing model to generate a specific dream scenario based on the user's wishes.

[0417] Generating a dream scenario

[0418] The server's generation AI generates stories based on elements entered by the user. For example, it might generate a dream scenario such as "exploring hidden treasure at the bottom of the ocean with the help of dolphins." This scenario is presented as a series of stories, designed to be experienced naturally by the user within the dream.

[0419] Scenario conversion and transmission

[0420] (The server converts the generated dream scenario into electroencephalogram (EEG) data. The algorithm used here maps each element of the generated scenario to a corresponding EEG pattern. This converted EEG data is transmitted to the terminal via a secure communication channel.)

[0421] Receiving brainwave data and experiencing dreams

[0422] The device analyzes and stores brainwave data received from the server. Furthermore, it is equipped with a sensor that monitors the timing of REM sleep. When it detects that the user has entered REM sleep, it transmits brainwave data to the brain. This allows the user to experience their desired dreams.

[0423] Feedback function

[0424] Users provide feedback on their dreams after waking up through a dedicated application. This feedback is used as data to generate higher-quality dream scenarios in the future.

[0425] Specific example

[0426] 1. Let's say the user dreams of an "underwater adventure." They open the dedicated application and input elements such as "underwater city," "dolphins," and "treasure hunt."

[0427] 2. The device sends this data to the server.

[0428] 3. The server analyzes the received data, and the generating AI creates a dream scenario. For example, a scenario where "you encounter dolphins while exploring an underwater city and search for treasure together."

[0429] 4. The server converts this scenario into electroencephalogram (EEG) data and sends it to the terminal.

[0430] 5. The device monitors the timing of REM sleep and transmits brainwave data to the user's brain at the appropriate time.

[0431] 6. Users experience the dreams they desire, waking up with restful sleep and a positive mood.

[0432] The system of this invention aims to control dreams according to the user's wishes and provide high-quality sleep. This makes it possible to improve sleep quality, reduce stress, and wake up feeling positive.

[0433] The following describes the processing flow.

[0434] Detailed program processing flow

[0435] Step 1:

[0436] The user opens a dedicated application and enters the elements of the dream they want to see. The application's interface displays scenario options and custom input boxes, allowing the user to enter specific elements such as "underwater city," "dolphins," or "treasure hunt." Then they press the "Submit" button.

[0437] Step 2:

[0438] The terminal sends the entered dream elements to the server. This process converts the user-entered data into JSON format and sends it to the server in an encrypted format using the HTTPS protocol.

[0439] Step 3:

[0440] The server receives data transmitted via the data reception API. At this stage, it verifies the integrity and format of the data and passes it to the generating AI module for analysis.

[0441] Step 4:

[0442] The server's generation AI module generates dream scenarios based on input data. For example, using topic modeling and sequence generation models, it generates a story like "Meeting dolphins while exploring an underwater city and searching for treasure together."

[0443] Step 5:

[0444] The server converts the generated dream scenario into electroencephalogram (EEG) data. This conversion is performed using a highly specialized algorithm that maps each element of the generated story (e.g., scenes and events) to a corresponding EEG pattern.

[0445] Step 6:

[0446] The server transmits the converted EEG data to the terminal. The transmission uses an encrypted communication channel via a security protocol, ensuring secure and rapid data transfer.

[0447] Step 7:

[0448] The device analyzes the brainwave data received from the server and stores it locally. Furthermore, it uses a sensor to monitor the timing of REM sleep, and when it detects that the user has entered REM sleep, it prepares to transmit the stored brainwave data.

[0449] Step 8:

[0450] The device triggers the transmission of brainwave data to the user's brain when REM sleep is detected. This transmission occurs through a device connected to the user's brain, and dream elements are transmitted to the brain as electrical signals.

[0451] Step 9:

[0452] The user experiences a desired dream based on the electrical signals they input. After waking, they open a dedicated application to provide feedback on the dream they had. This feedback is used to improve the quality of future dream generation.

[0453] The above is the specific processing flow of the "Wake Up Refreshed! Dream Palette" system. This allows users to experience their desired dreams, achieve quality sleep, and wake up feeling refreshed.

[0454] (Example 1)

[0455] 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".

[0456] In modern society, ensuring quality sleep is a crucial issue for users. In particular, many users experience stress and anxiety, leading to an increasing number of cases where they cannot get satisfactory sleep. If users could experience dreams they desire, it would lead to mental refreshment and stress reduction, thus providing quality sleep. However, because there is no concrete system to induce such dream experiences, users are unable to freely experience the dreams they want.

[0457] 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.

[0458] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the input dream elements to a digital device, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to a digital device, means for the digital device to transmit the EEG data to the user's brain in conjunction with REM sleep, means for providing feedback on the dream the user experienced, and sensors for monitoring the timing of REM sleep. This enables the user to experience their desired dream and obtain quality sleep.

[0459] "A means of inputting the dream elements desired by the user" refers to providing an interface for users to input the dream elements they wish to experience, and a means of incorporating that input data into the system.

[0460] "Means for transmitting input dream elements to a digital device" refers to a means for converting the dream elements entered by the user into a data format and securely transmitting them to a digital device.

[0461] "Means for receiving and analyzing transmitted data" refers to a method of receiving data from a transmitted digital device, analyzing its contents, and extracting elements of dreams.

[0462] "A method for generating specific dream scenarios using generative AI" refers to a method of creating specific dream scenarios that users will experience, based on the elements of the dreams they have received, using generative AI (artificial intelligence).

[0463] "Methods for converting generated scenarios into brainwave data" refers to methods for converting generated dream scenarios into corresponding brainwave patterns so that users can actually experience the dream.

[0464] "Means for transmitting converted brainwave data to a digital device" refers to means for securely transmitting converted brainwave data to a digital device.

[0465] "A method by which a digital device transmits brainwave data to a user's brain in conjunction with REM sleep" refers to a method in which a digital device detects the user's REM sleep and sends brainwave data to the user's brain at that time.

[0466] "A means of providing feedback on dreams experienced by users" refers to a method for users to provide feedback to the system regarding their thoughts and opinions about the dreams they have experienced.

[0467] A "sensor that monitors the timing of REM sleep" is a sensor that monitors the user's sleep state and detects when the user enters REM sleep.

[0468] This invention is a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system consists of a user terminal, a server, a generating AI, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[0469] User input processing

[0470] The user launches a dedicated application and enters the elements of the dream they want to see. This application features an intuitive interface, allowing users to input their desired dream elements through text input or by selecting options. For example, they can enter "underwater city," "dolphins," or "treasure hunt."

[0471] Sending and receiving data

[0472] The terminal converts the dream elements entered by the user into JSON data and sends it to the server using the HTTPS protocol. The terminal encrypts the data using SSL / TLS to ensure its security. The server receives and analyzes the data sent from the terminal. This analysis includes data extraction and the generation of prompts for the generative AI model.

[0473] Generating dream scenarios using AI

[0474] The generation AI installed on the server generates a specific dream scenario that includes elements desired by the user, based on the received prompt text. The generation AI model uses natural language processing technology to create a story based on the elements input by the user. For example, it can generate a scenario such as "searching for treasure with dolphins in an underwater city."

[0475] Scenario conversion and transmission

[0476] The server converts the generated dream scenario into brainwave data. A specialized algorithm is used for this conversion, mapping each element of the scenario to a corresponding brainwave pattern. The brainwave data is encrypted to ensure security and transmitted to a digital device.

[0477] Receiving brainwave data and experiencing dreams

[0478] The device receives transmitted brainwave data and stores it in local storage. Furthermore, the device is equipped with a sensor that monitors the timing of REM sleep, monitoring the user's sleep state in real time. When the sensor detects the user's REM sleep, the device transmits the stored brainwave data to the user's brain. This allows the user to experience their desired dreams.

[0479] Feedback function

[0480] After waking up, users provide feedback about their dreams through a dedicated application. This feedback is used as training data for the generating AI and is reflected in the creation of future dream scenarios. This allows users to experience dreams that are more faithful to their preferences and of higher quality.

[0481] Specific example

[0482] The following are some specific examples.

[0483] 1. The user expresses a desire to experience an "underwater adventure" and opens the dedicated application.

[0484] 2. Enter specific elements such as "underwater city," "dolphins," and "treasure hunt."

[0485] 3. The device converts this data into JSON format and sends it to the server using HTTPS.

[0486] 4. The server receives and analyzes the data to generate a prompt message, which is then passed to the generating AI. The generating AI then creates a dream scenario: "While exploring an underwater city, you encounter dolphins and search for treasure together."

[0487] 5. Convert the scenario into electroencephalogram (EEG) data and transmit it to the terminal via a secure channel.

[0488] 6. The device stores brainwave data and detects the user's REM sleep, transmitting the data to the brain.

[0489] 7. Users experience the dreams they desire and provide feedback about the dreams they had.

[0490] Examples of prompts to input into a generative AI model

[0491] The following are specific examples of prompt statements to be input to a generative AI model.

[0492] "The user wants to dream about an 'underwater city,' 'dolphins,' and 'treasure hunting.' Please generate a specific dream scenario that includes these elements."

[0493] This system allows users to experience their desired dreams and get quality sleep.

[0494] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0495] Step 1:

[0496] The user launches a dedicated application and inputs the elements of the dream they want to see. This input is done through text boxes or selection lists, such as "underwater city," "dolphins," or "treasure hunt." The input data (e.g., underwater city, dolphins, treasure hunt) is then taken into the system.

[0497] Step 2:

[0498] The terminal converts the dream elements entered by the user into JSON format and sends them to the server using the HTTPS protocol. Specifically, it transforms the input data (e.g., underwater city, dolphins, treasure hunt) into a JSON structure and sends it as SSL / TLS encrypted data. The JSON formatted data is output and sent to the server via a secure communication channel.

[0499] Step 3:

[0500] The server receives JSON data sent from the terminal. It parses the received data and extracts the dream elements. Specifically, it parses the received data (e.g., {"elements":["Underwater city", "Dolphin", "Treasure hunt"]}) and extracts a list of elements. The extracted list of elements is output.

[0501] Step 4:

[0502] The server generates a prompt message for the generating AI based on the element list and passes it to the AI. The generated prompt message (e.g., "The user wants to have a dream that includes 'underwater city,' 'dolphins,' and 'treasure hunt.' Please generate a specific dream scenario that includes these elements.") is input into the generating AI model. The prompt message is output and passed to the generating AI model.

[0503] Step 5:

[0504] The generative AI generates a specific dream scenario that includes elements desired by the user, based on the given prompt text. Specifically, the generative AI model receives the prompt text as input and performs natural language processing to generate a scenario such as "Meeting a dolphin while exploring an underwater city and searching for treasure together." The generated scenario is then output.

[0505] Step 6:

[0506] The server converts the generated dream scenario into brainwave data. It uses a conversion algorithm that maps each scene and element of the scenario to the corresponding brainwave pattern. The scenario received as input (e.g., "While exploring an underwater city, I meet a dolphin and we search for treasure together") is converted into a brainwave pattern, and the brainwave data is output.

[0507] Step 7:

[0508] The server transmits the converted EEG data to the terminal via a secure communication channel. Data security is ensured by sending the EEG data to the terminal using encrypted communication. As output, encrypted EEG data is sent to the terminal.

[0509] Step 8:

[0510] The device saves the received brainwave data to local storage. Furthermore, the device is equipped with a sensor that monitors the timing of REM sleep. This sensor analyzes the user's brainwaves in real time and detects when the user enters REM sleep. Upon detecting REM sleep, the stored brainwave data is output and transmitted to the user's brain.

[0511] Step 9:

[0512] The user receives brainwave data transmitted from the device during REM sleep. This allows them to experience a dream where they "encounter dolphins while exploring an underwater city and search for treasure together." Because the user's brain shapes the dream according to the received brainwave data, the user can experience the dream they desire.

[0513] Step 10:

[0514] After waking up, users provide feedback about their dreams through a dedicated application. This feedback includes details and impressions of the dream. This feedback data is sent to the server as learning data to be used in future scenario generation. This allows the system to provide higher-quality dreams.

[0515] (Application Example 1)

[0516] 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."

[0517] Conventional dream induction systems were designed for individual users to use at home, and therefore did not consider use in physical establishments such as relaxation facilities and spas. As a result, there was a lack of means to significantly improve the customer experience in these physical locations. Furthermore, there was no system that allowed customers in relaxation facilities to easily input their desired dreams and experience them as actual dreams. In addition, there were no means to efficiently induce dreams for multiple customers, resulting in a limited quality of customer experience.

[0518] 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.

[0519] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the inputted dream elements to the server, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI based on the analyzed data, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to the user's terminal, means for the terminal to transmit the EEG data to the user's brain in conjunction with REM sleep, means for the customer to input dream elements using an input device in the store, means for the input device to transmit the dream elements to the server, means for the server to convert the data into EEG data based on the dream scenario and transmit it to a relaxation device, and means for the relaxation device to transmit the EEG data to the user's brain during REM sleep. This makes it possible to allow users to experience dreams based on their individual preferences in a physical store, significantly improving the quality of the customer experience at relaxation facilities. It also makes it possible to efficiently and effectively induce dreams for multiple customers.

[0520] A "user" refers to an individual who uses the system to experience their dreams.

[0521] "Dream elements" are the elements that make up the specific scenarios and situations that users input in their dreams that they want to experience.

[0522] A "server" refers to a computer system that receives data sent by users and uses AI for analysis and generation to create dream scenarios.

[0523] "Generative AI" refers to an artificial intelligence model that generates specific dream scenarios based on the elements of a dream that are input.

[0524] A "scenario" refers to a series of events that form the specific story or scenes that a user experiences in their dreams.

[0525] "Electrical wave data" refers to the brainwave patterns that have been converted to allow the user to experience the generated dream scenario.

[0526] A "terminal" refers to a device used by a user that has the function of receiving brainwave data transmitted from a server and transmitting it to the user's brain.

[0527] "REM sleep" refers to the primary sleep stage in which users dream, and it is possible to induce dreams by transmitting brainwave data during this time.

[0528] An "input device" refers to a device used by users to input elements of their dreams, and is typically installed in physical stores or other similar locations.

[0529] A "relaxation device" refers to a device that has the function of appropriately transmitting brainwave data to the user and providing a dream-like experience.

[0530] This invention is a system that allows users to experience their desired dreams during REM sleep. This system works by having the user input elements of their dream, and then a generating AI uses that information to create a specific dream scenario, which is then transmitted to the user as brainwave data.

[0531] System Configuration

[0532] 1. Processing user input

[0533] Users input the elements of their desired dream using a dedicated input device. The input device is installed in physical relaxation facilities, and its user interface is intuitive, making it easy to select scenarios and customize inputs. For example, users can input specific elements such as "beach," "exotic forest," or "quiet mountain lake."

[0534] 2. Sending and receiving data

[0535] The input device sends the input dream elements to the server. The data is converted to JSON format and transmitted using the secure HTTPS protocol. The server analyzes the received data and passes it to a generative AI. This AI uses a natural language processing model to generate a specific dream scenario based on the user's wishes.

[0536] 3. Generating a dream scenario

[0537] The server's generation AI creates stories based on the elements entered by the user. For example, it might generate a dream scenario such as "You standing by a quiet mountain lake." This scenario is presented in a narrative format and is designed to be experienced naturally by the user within the dream.

[0538] 4. Scenario conversion and transmission

[0539] The server converts the generated dream scenario into electroencephalogram (EEG) data. The generative AI model used here maps each element of the generated scenario to a corresponding EEG pattern. This converted EEG data is transmitted to the relaxation device via a secure communication channel.

[0540] 5. Receiving EEG data and experiencing dreams

[0541] The relaxation device analyzes and stores brainwave data received from a server. Furthermore, it is equipped with a sensor that monitors the timing of REM sleep. When it detects that the user has entered REM sleep, it transmits brainwave data to the brain. This allows the user to experience their desired dreams.

[0542] Hardware and software to be used

[0543] Input device: A device for customers to input elements of their dreams. It is installed in physical stores.

[0544] Server: A computer system that receives dream elements, analyzes them, and generates dream scenarios using a generative AI.

[0545] Generative AI: A natural language processing model that creates dream scenarios based on dream elements entered by the user.

[0546] Relaxation device: A device that monitors the timing of REM sleep and transmits brainwave data.

[0547] Specific example

[0548] The customer inputs elements of their desired dream, such as "I want to relax by a quiet mountain lake," into an input device at the relaxation facility. The input device sends this data to a server, which generates a scenario of "themselves standing by a quiet mountain lake." The generated scenario is converted into brainwave data and sent to the relaxation device. The relaxation device monitors the customer's REM sleep and sends brainwave data at the appropriate time.

[0549] Example of a prompt

[0550] The user entered "I want to relax by a quiet mountain lake." Based on this, generate a dream scenario that will help the user relax.

[0551] This format allows users to significantly enhance their experience at relaxation facilities and provides dream experiences tailored to their individual preferences.

[0552] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0553] Step 1: The user enters the elements of their dream.

[0554] Users access an input device installed in a physical store and input elements of their dream experience (e.g., "beach," "exotic forest," "quiet mountain lake"). The input device interface is intuitive, allowing users to easily select or customize their desired elements. The input data is in text format.

[0555] Step 2: Submit the input data

[0556] The input device sends the dream elements entered by the user to the server. The input data is converted to JSON format and sent to the server using the secure HTTPS protocol. An example of input data is {"dream_elements": ["beach", "exotic forest", "quiet mountain lake"]}.

[0557] Step 3: Data reception and analysis

[0558] The server receives data transmitted from the input device. The received data is analyzed and used as material to generate specific dream scenarios based on the user's wishes. This analysis involves examining the structure of the received data and extracting its elements.

[0559] Step 4: Generating dream scenarios using a generative AI

[0560] The server passes the analyzed data to the generative AI. The generative AI model uses natural language processing to generate specific dream scenarios based on the input data. For example, if the user input is "I want to relax by a quiet mountain lake," the generated scenario might be something like "I am standing by a quiet mountain lake."

[0561] Step 5: Converting the scenario's EEG data

[0562] The server converts the generated dream scenario into brainwave data. The generating AI model maps each element of the output scenario to the corresponding brainwave pattern, generating brainwave data that the user can experience as a dream. This converted data is in binary format.

[0563] Step 6: Sending EEG data

[0564] The server transmits the converted EEG data to the relaxation device. The EEG data is sent to the relaxation device using a secure communication channel. The transmitted data is stored in the device's memory.

[0565] Step 7: Monitoring REM sleep

[0566] The relaxation device monitors the user's REM sleep timing using built-in sensors. The sensors analyze brainwave patterns in real time to detect when the user enters REM sleep. Electrodes-based electroencephalogram (EEG) measurement devices and heart rate monitors are used to determine REM sleep.

[0567] Step 8: Sending EEG data and inducing dreams

[0568] After the relaxation device detects the timing of REM sleep, it transmits the received brainwave data to the user's brain. This allows the user to experience the dream they desire. The data transmission is performed using a dedicated brainwave transmission function.

[0569] This series of processes allows users to experience customized dreams at relaxation facilities, providing them with high-quality relaxation.

[0570] 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.

[0571] System Overview

[0572] This invention incorporates an emotion engine into a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system recognizes the user's emotional state and selects and adjusts dreams based on that state. The system consists of a user terminal, a server, a generation AI, an emotion engine, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[0573] User input processing

[0574] Users input the elements of their desired dream using a dedicated application. The application interface displays scenario options and custom input boxes, allowing users to enter specific elements such as "underwater city," "dolphins," and "treasure hunt." Furthermore, an emotion engine analyzes the user's emotional state, and suggests dream elements based on the results.

[0575] How the emotion engine works

[0576] The device collects emotion analysis data to recognize the user's emotional state. This data is obtained, for example, through voice analysis, facial expression analysis, and biometric data analysis from wearable devices. The collected emotion data is sent from the device to a server and analyzed by an emotion engine.

[0577] Analysis and proposals regarding emotional data

[0578] The server's emotion engine analyzes the received emotion data to identify the user's current emotional state. Based on the analyzed emotional state, it suggests the most suitable dream elements. These suggestions are returned to the user's device and displayed in the application. The user then decides whether to accept the suggested elements or enter custom elements.

[0579] Sending and receiving data

[0580] The device sends the elements of the dream that the user has finally decided on to the server. The data is converted to JSON format and transmitted in an encrypted format using the secure HTTPS protocol. Meanwhile, the server analyzes the received data and passes it to a generative AI. This generative AI uses a natural language processing model to generate a specific dream scenario based on the user's wishes.

[0581] Generating a dream scenario

[0582] The server's AI generates dream scenarios based on user input and emotional data. For example, it might generate a dream scenario such as "encountering dolphins while exploring an underwater city and searching for treasure together." This scenario can be customized to match the user's emotional state.

[0583] Scenario conversion and transmission

[0584] The server converts the generated dream scenario into electroencephalogram (EEG) data. This conversion is performed using a specialized algorithm that maps each element of the generated scenario (e.g., scenes and events) to the corresponding EEG pattern. The converted EEG data is then transmitted to the terminal via a secure communication channel.

[0585] Receiving brainwave data and experiencing dreams

[0586] The device analyzes and stores brainwave data received from the server. It also uses a sensor to monitor the timing of REM sleep, and when it detects that the user has entered REM sleep, it transmits the stored brainwave data to the brain.

[0587] Feedback function

[0588] Users provide feedback on their dreams after waking up through a dedicated application. This feedback data is used to improve the accuracy of the dream generation algorithm and emotion engine for future use.

[0589] Specific example

[0590] 1. The user expresses a desire for an "underwater adventure," opens the application, and inputs elements such as "underwater city," "dolphins," and "treasure hunt." Suggestions from the emotion engine are also considered.

[0591] 2. The device sends this data and sentiment data to the server.

[0592] 3. The server analyzes the received data, and the generating AI creates a dream scenario. For example, a scenario where "you encounter dolphins while exploring an underwater city and search for treasure together."

[0593] 4. The server converts this scenario into electroencephalogram (EEG) data and sends it to the terminal.

[0594] 5. The device monitors the timing of REM sleep and transmits brainwave data to the user's brain at the appropriate time.

[0595] 6. Users can have the dreams they desire and enjoy restful sleep.

[0596] The system of this invention aims to control dreams according to the user's wishes and provide high-quality sleep. Furthermore, by utilizing an emotion engine, it is possible to provide an optimal dream experience tailored to the user's emotional state.

[0597] The following describes the processing flow.

[0598] Specific processing flow of the program

[0599] Step 1:

[0600] The user opens a dedicated application and enters the elements of the dream they want to see. The application interface displays scenario options and custom input boxes, allowing the user to enter specific elements such as "underwater city," "dolphins," or "treasure hunt," and then press the "Submit" button.

[0601] Step 2:

[0602] The device collects the user's emotional state using voice input, facial recognition, or biometric data acquired from wearable devices. The collected data is sent to the emotion engine in real time.

[0603] Step 3:

[0604] The device converts the user's emotional data and dream elements into JSON format and sends them to the server using the secure HTTPS protocol.

[0605] Step 4:

[0606] The server receives data sent via the data reception API. It verifies the integrity and format of the data and passes it to the emotion engine. The emotion engine analyzes the user's emotional state and suggests the most suitable dream elements based on the results. This suggestion is returned to the user's device.

[0607] Step 5:

[0608] The user reviews and modifies dream elements based on suggestions from the emotion engine. For example, if the emotion engine suggests "relaxing underwater exploration," the user can add "treasure hunting."

[0609] Step 6:

[0610] The device then sends the finalized dream elements back to the server. This data is converted to JSON format and transmitted using a secure communication channel.

[0611] Step 7:

[0612] The server analyzes the received dream element data and passes it to the generating AI. The generating AI then generates a specific dream scenario based on this data. For example, it might generate a scenario such as, "While exploring an underwater city, you encounter a dolphin and search for treasure together."

[0613] Step 8:

[0614] The server converts the generated scenario into electroencephalogram (EEG) data. This conversion is performed using a specialized algorithm that maps each element of the generated scenario (e.g., scenes and events) to the corresponding EEG pattern. The converted EEG data is transmitted to the terminal via a secure communication channel.

[0615] Step 9:

[0616] The device analyzes and stores brainwave data received from the server. Furthermore, it is equipped with a sensor that monitors the timing of REM sleep. When it detects that the user has entered REM sleep, it prepares to transmit the stored brainwave data to the brain.

[0617] Step 10:

[0618] The device triggers the transmission of brainwave data to the user's brain when REM sleep is detected. This transmission occurs through a device connected to the user's brain, and dream elements are transmitted to the brain as electrical signals.

[0619] Step 11:

[0620] The user experiences a desired dream based on the electrical signals they input. For example, they might dream of "searching for treasure with dolphins in an underwater city." After waking, they open a dedicated application to provide feedback on their dream. This feedback is used to improve the accuracy of the dream generation algorithm and emotion engine for future sessions.

[0621] (Example 2)

[0622] 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".

[0623] To improve sleep quality, there is a need for a system that allows users to experience dreams of their choice. However, conventional technology has been unable to adjust dream content based on the user's emotional state, making it difficult to provide dreams optimized for the user's psychological state. Furthermore, there was a lack of mechanisms to collect feedback on the dreams users experienced and use that feedback to improve the system's accuracy. In addition, the lack of a means to accurately detect the timing of REM sleep made it difficult to provide an effective dream experience.

[0624] 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.

[0625] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the input dream elements to the server, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI based on the analyzed data, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to the user's terminal, means for the terminal to transmit the EEG data to the user's brain in conjunction with REM sleep, means for collecting and analyzing the user's emotional data, and means for suggesting dream elements based on the analyzed emotional data. This makes it possible to allow the user to experience the content of their desired dream and to provide a dream optimized for their emotional state at the time. Furthermore, feedback on the dreams seen can be collected and used to improve the accuracy of the system. In addition, by accurately detecting the timing of REM sleep, a more effective dream experience can be provided to the user.

[0626] A "user" is the individual who uses the system to input the content of their desired dream and then experiences that dream.

[0627] "Dream elements" refer to specific scenarios, scenes, characters, themes, etc., that users want to experience.

[0628] The "server" is a central processing unit that analyzes data sent by users, generates dream scenarios using a generative AI and emotion engine, and converts those scenarios into brainwave data for transmission.

[0629] A "terminal" is a device that the user directly operates, and it is a device that inputs dream elements, collects emotional data, monitors REM sleep, and transmits brainwave data.

[0630] "Emotional data" refers to data that indicates a user's current emotional state, and includes information collected through voice analysis, facial expression analysis, and biometric data analysis from wearable devices.

[0631] The "emotion engine" is a software component that analyzes collected emotional data and, based on the results, suggests the most suitable dream elements to the user.

[0632] "Generative AI" is an artificial intelligence model that generates specific dream scenarios based on received data and analyzed emotional data.

[0633] "Electroencephalogram (EEG) data" refers to data that has been converted to transmit the generated dream scenario to the user's brain, and is expressed as an EEG pattern.

[0634] "REM sleep" is a deep stage of sleep in which users are more likely to dream, and brainwave data is transmitted during this time to induce the desired dream.

[0635] "Feedback" refers to information provided by users through a dedicated application, detailing the content and their impressions of their dreams. This information helps improve the accuracy of future dream generation.

[0636] A "sensor" is a device used to monitor the timing of a user's REM sleep.

[0637] Modes for carrying out the invention

[0638] System Configuration

[0639] This invention incorporates an emotion engine into a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system recognizes the user's emotional state and selects and adjusts dreams based on that state. The system consists of a user terminal, a server, a generation AI, an emotion engine, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[0640] User input processing

[0641] The user launches a dedicated application and enters the elements of the dream they want to see into the interface. Fields are provided for entering specific elements such as "underwater city," "dolphins," and "treasure hunt." Once the user has finished entering the information, the device collects this data.

[0642] How the emotion engine works

[0643] The device simultaneously collects emotional data. For this data collection, the device is equipped with voice analysis, facial expression analysis, and biometric data analysis functions for wearable devices. The collected emotional data is transmitted from the device to a server.

[0644] Analysis and proposals regarding emotional data

[0645] The server's emotion engine analyzes the received emotion data to identify the user's current emotional state. Based on the analysis, it suggests the most suitable dream elements. These suggestions are sent back from the server to the terminal and displayed in the application for the user to review. The user then decides whether to accept the suggested elements or enter new custom elements.

[0646] Generating a dream scenario

[0647] The device sends the elements of the dream that the user has finally decided on to the server. This transmission is converted to JSON format and performed using the secure HTTPS protocol. The server parses the received data and passes it on to the generative AI. The generative AI uses a natural language processing model to generate a specific dream scenario.

[0648] For example, it can generate a specific scenario such as, "While exploring an underwater city, you encounter dolphins and search for treasure together."

[0649] Scenario conversion and transmission

[0650] The server converts the generated dream scenario into electroencephalogram (EEG) data. This conversion process uses a specialized algorithm that maps each element of the generated scenario (e.g., scenes and events) to a corresponding EEG pattern. The converted EEG data is then transmitted to the terminal via a secure communication channel.

[0651] Dream experience

[0652] The device analyzes and stores brainwave data received from the server. It also uses a sensor to monitor the timing of REM sleep, and when it detects that the user has entered REM sleep, it transmits the stored brainwave data to the brain. As a result, the user experiences the dream they desired.

[0653] Feedback function

[0654] Users provide feedback on their dreams after waking up through a dedicated application. This feedback data is used to improve the accuracy of the dream generation algorithm and emotion engine for future use.

[0655] Examples of specific cases and prompt statements

[0656] Specifically, a user might express a desire for an "underwater adventure" and use the application to input elements such as "underwater city," "dolphins," and "treasure hunt." The device sends this data, along with emotional data, to a server, which analyzes it, and a generating AI creates a dream scenario. For example, a scenario might be generated where the user "encounters dolphins while exploring an underwater city and searches for treasure together." The server converts this scenario into brainwave data and sends it to the device. The device monitors the timing of REM sleep and sends the brainwave data to the user's brain at the appropriate time. The user then experiences the dream they desired and enjoys a fulfilling sleep.

[0657] An example of a prompt message is as follows:

[0658] Enter dream elements such as "underwater city," "dolphins," and "treasure hunt." Also, check the elements suggested by the emotion engine.

[0659] By using such a system, it is possible to provide dreams tailored to the user's preferences and support quality sleep. Furthermore, by utilizing an emotion engine, users can obtain a dream experience optimized for their emotional state.

[0660] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0661] Step 1: Enter the user's desired elements.

[0662] The user launches a dedicated application and enters the elements of the dream they want to see into the interface. Fields are provided for entering specific elements such as "underwater city," "dolphins," and "treasure hunt."

[0663] Input: Elements of the dream entered by the user into a dedicated application.

[0664] Output: Dream element data held on the device.

[0665] Operation: The user enters specific dream elements in text format into the application's input field and presses the submit button.

[0666] Step 2: Collecting emotional data

[0667] The device performs voice analysis, facial expression analysis, and biometric data analysis from wearable devices to recognize the user's emotional state.

[0668] Input: User's voice, facial expressions, and biometric data from wearable devices.

[0669] Output: Analyzed sentiment data.

[0670] Operation: Collects user emotion data using the device's built-in camera, microphone, and wearable sensors. This data is then temporarily stored.

[0671] Step 3: Sending emotional data

[0672] The device sends the collected emotional data to the server. This transmission uses the secure HTTPS protocol, and the data is encrypted.

[0673] Input: Collected sentiment data.

[0674] Output: Sentiment data sent to the server.

[0675] Operation: The device encrypts the emotional data using the HTTPS protocol and sends it to the server.

[0676] Step 4: Analysis of emotional data

[0677] The server passes the received emotional data to the emotion engine for analysis. The emotion engine uses natural language processing and machine learning algorithms to identify the user's emotional state.

[0678] Input: Received emotion data.

[0679] Output: Analyzed emotional state.

[0680] Operation: The emotion engine uses algorithms to analyze the user's emotional data item by item and identify their current emotional state.

[0681] Step 5: Propose elements of the dream

[0682] The server's emotion engine suggests the most suitable dream elements based on the analysis results. This suggestion is converted to JSON format and sent to the terminal via a secure channel.

[0683] Input: Analyzed emotional state.

[0684] Output: Dream element proposal data.

[0685] Operation: The emotion engine selects the most suitable dream elements for the user based on the analysis results, converts them into JSON format, and sends them to the device.

[0686] Step 6: View and select suggestions

[0687] The device displays the received suggestions to the user. The user then decides whether to accept the suggested elements or enter custom elements.

[0688] Input: Data on the elements of the proposed dream.

[0689] Output: User's final selection data.

[0690] Operation: The device displays the received suggestions in the application interface, and the user confirms and selects them.

[0691] Step 7: Submit selected elements

[0692] The terminal sends the finalized dream elements to the server. This transmission also uses the secure HTTPS protocol.

[0693] Input: User's last selected data.

[0694] Output: Dream element data sent to the server.

[0695] Operation: Converts the dream elements selected by the user into JSON format and sends them to the server using the HTTPS protocol.

[0696] Step 8: Generating dream scenarios using a generative AI

[0697] The server analyzes the received dream elements and passes them to the generative AI. The generative AI uses a natural language processing model to generate a specific dream scenario.

[0698] Input: User's dream element data.

[0699] Output: The generated dream scenario.

[0700] Operation: The generating AI applies a specific algorithm based on the received data to generate dream scenarios such as "Meeting dolphins while exploring an underwater city and searching for treasure together."

[0701] Step 9: Converting the scenario into EEG data

[0702] The server converts the generated dream scenario into brainwave data. Using specialized algorithms, it maps each scene and event to a brainwave pattern.

[0703] Input: The generated dream scenario.

[0704] Output: Converted electroencephalogram (EEG) data.

[0705] Operation: Analyze the generated scenario and apply an algorithm to convert it into electroencephalogram (EEG) data.

[0706] Step 10: Sending EEG data

[0707] The server transmits the converted EEG data to the terminal. This transmission also uses a secure communication channel.

[0708] Input: Converted electroencephalogram (EEG) data.

[0709] Output: EEG data transmitted to the terminal.

[0710] Operation: Transmits EEG data to the terminal via a secure channel.

[0711] Step 11: Monitoring REM sleep

[0712] The device uses sensors to monitor the timing of REM sleep.

[0713] Input: User's sleep status data.

[0714] Output: REM sleep timing detection information.

[0715] Operation: The device continuously monitors the user's sleep state using a REM sleep monitoring sensor.

[0716] Step 12: Sending EEG data

[0717] When the device detects that the user has entered REM sleep, it transmits the stored brainwave data to the user's brain.

[0718] Input: REM sleep timing detection information and stored electroencephalogram (EEG) data.

[0719] Output: Brainwave data transmitted to the user's brain.

[0720] Operation: When REM sleep is detected, the stored electroencephalogram (EEG) data is transmitted to the user's brain.

[0721] Step 13: Provide feedback on your dream

[0722] Users provide feedback about their dreams after waking up through a dedicated application. This feedback data is used to improve the accuracy of the system.

[0723] Input: User feedback information.

[0724] Output: Collected feedback data.

[0725] Operation: Users input their thoughts and evaluations about the content of their dreams using a dedicated application, and this information is sent to the server.

[0726] (Application Example 2)

[0727] 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."

[0728] Conventional systems have found it difficult to individually customize users' dream experiences and lacked sufficient functionality to adjust dream elements based on emotional states. Furthermore, providing feedback based on actual experience was challenging in employee customer service and negotiation skills training. This invention proposes a system that solves these problems and provides optimal dream experiences and training based on the user's emotional state.

[0729] 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.

[0730] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the input dream elements to the server, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI based on the analyzed data, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to the user's terminal, means for the terminal to transmit the EEG data to the user's brain in accordance with REM sleep, means for recognizing and analyzing the user's emotional state, and means for adjusting the dream scenario based on the analyzed emotional data. This makes it possible to adjust the dream experience and training scenario based on the user's emotional state.

[0731] A "user" refers to someone who uses this system to customize their dream experiences and training scenarios.

[0732] "Dream elements" refer to specific items or situations that users want to include in their desired dreams or training scenarios.

[0733] A "server" refers to a central system that receives, analyzes, and processes data sent by users.

[0734] "Means of input" refers to the interface or device that allows the user to input elements of their dreams into the system.

[0735] "Means of transmission" refers to the means of communication used to send the input dream elements to the server.

[0736] "Means for receiving and analyzing" refers to the software and hardware used by the server to receive transmitted data and analyze it.

[0737] "Generative AI" refers to artificial intelligence that uses natural language processing models to generate specific dream scenarios.

[0738] "Means of conversion" refers to algorithms and systems for converting the generated dream scenarios into brainwave data.

[0739] A "terminal" refers to a device used by a user, specifically equipment that receives and transmits electroencephalogram (EEG) data.

[0740] "REM sleep" refers to the period of time when a user enters a deep sleep state, a time when they are more likely to dream.

[0741] "Emotional state" refers to the user's current emotional state and is analyzed from voice, facial expressions, biometric data, and other sources.

[0742] "Means of recognition and analysis" refers to software and hardware for identifying and analyzing a user's emotional state.

[0743] "Means of adjustment" refers to a system for optimizing dream scenarios and training scenarios based on analyzed emotional data.

[0744] This invention provides a system that allows users to input desired dream elements and experience them during REM sleep, as well as a function to recognize emotional states and adjust training scenarios. The system consists of a user terminal, a server, a generative AI, an emotion engine, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[0745] Users access a dedicated application using smart glasses and input elements of the dream or training scenario they wish to experience. For example, for a customer service skills training scenario, they might input specific elements such as "handling complaints" and "product description." The emotion engine analyzes the user's emotional state and displays suggestions for the most suitable training scenario based on the results.

[0746] Smart glasses collect the user's voice, facial expressions, and biometric data and send it to an emotion engine. The emotion engine uses Azure Cognitive Services' emotion recognition API to analyze this data and identify the user's current emotional state. The collected emotional data and user preferences are sent to a server, where a generative AI (e.g., OpenAI's GPT-3) generates specific scenarios based on prompts.

[0747] The server converts the generated scenario into electroencephalogram (EEG) data and sends it to the user's terminal using a secure communication channel (HTTPS). The terminal uses sensors to monitor the timing of REM sleep and transmits EEG data when the user enters REM sleep.

[0748] Furthermore, in training scenarios, the received scenario is overlaid on the smart glasses. The smart glasses monitor the user's emotional state in real time and provide appropriate advice and feedback as the scenario progresses.

[0749] As a concrete example, consider a case where a user requests a training scenario for "handling customer complaints." In this case, the user opens the application and types "handling complaints." Emotional data obtained from voice and facial expressions is sent to the server, and the generating AI creates a "customer complaint dialogue scenario." For example, a scenario is generated in which "a customer complains about a product defect, and the user learns specific ways to handle it," and this is converted into brainwave data. Furthermore, the progress of the training is adjusted and appropriate feedback is provided based on the emotional data collected in real time.

[0750] The following are specific examples of prompt statements for generative AI models:

[0751] "The user's desired scenario is 'handling a complaint,' and their emotional state is 'feeling stressed.' Please generate an appropriate training scenario."

[0752] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0753] Step 1:

[0754] Users input elements of their desired dreams or training scenarios through a dedicated application for smart glasses. For example, they might input specific elements such as "handling customer complaints" or "product description." The input data includes elements specified in text format.

[0755] Step 2:

[0756] The terminal sends the data entered by the user to the server. The data sent includes the elements requested by the user and is sent to the server in JSON format.

[0757] Step 3:

[0758] The server receives the transmitted data and performs analysis. This analysis includes emotion recognition, which is performed using the user's voice and facial expression data. Specifically, it calls the Azure Cognitive Services emotion recognition API to generate emotion data as an analysis result. The input data is voice and image data, and the output is a tag or score indicating the emotional state.

[0759] Step 4:

[0760] The server uses a generative AI model to generate specific scenarios based on the analyzed emotional data and the user's desired elements. In this process, it uses OpenAI's GPT-3 to create prompts such as: "The user's desired scenario is 'Handling a complaint,' and their emotional state is 'Feeling stressed.' Please generate an appropriate training scenario." The output data generated by the generative AI is the specific scenario text.

[0761] Step 5:

[0762] The server converts the generated scenario into electroencephalogram (EEG) data. This conversion uses a specialized algorithm that maps each element of the generated scenario to a corresponding EEG pattern. The input data is the scenario text, and the output is EEG data.

[0763] Step 6:

[0764] The server transmits the converted EEG data to the terminal. The terminal receives and stores the data. Communication is conducted via the secure HTTPS protocol. The input data is EEG data, and the output is data storage on the terminal.

[0765] Step 7:

[0766] The device uses sensors that monitor the timing of REM sleep to detect when the user enters REM sleep. When REM sleep is detected, it transmits stored brainwave data to the user's brain. The input data is biometric information from the sensors, and the output is the transmission of brainwave data.

[0767] Step 8:

[0768] The user's smart glasses overlay the received training scenario and monitor their emotional state in real time. The emotion engine provides feedback and advice at appropriate times. The input data is the user's emotional state, and the output is feedback corresponding to the progress of the scenario.

[0769] Step 9:

[0770] Users provide feedback after training or dream experiences. This feedback data is used to improve the accuracy of future scenario generation and the emotion engine. The input data is the user's feedback text, and the output is the application of that feedback to the system's algorithm.

[0771] 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.

[0772] 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.

[0773] 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.

[0774] [Third Embodiment]

[0775] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0776] 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.

[0777] 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).

[0778] 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.

[0779] 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.

[0780] 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).

[0781] 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.

[0782] 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.

[0783] 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.

[0784] 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.

[0785] 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.

[0786] 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".

[0787] System Overview

[0788] This invention is a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system consists of a user terminal, a server, a generating AI, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[0789] User input processing

[0790] Users input the elements of their dreams using a dedicated application. The application's interface is intuitive, making it easy to select scenarios and enter custom information. For example, users can input specific elements such as "underwater city," "dolphins," or "treasure hunt."

[0791] Sending and receiving data

[0792] The terminal sends the input dream elements to the server. The data is converted to JSON format and transmitted using the secure HTTPS protocol. The server, in turn, analyzes the received data and passes it to a generative AI. This AI uses a natural language processing model to generate a specific dream scenario based on the user's wishes.

[0793] Generating a dream scenario

[0794] The server's generation AI generates stories based on elements entered by the user. For example, it might generate a dream scenario such as "exploring hidden treasure at the bottom of the ocean with the help of dolphins." This scenario is presented as a series of stories, designed to be experienced naturally by the user within the dream.

[0795] Scenario conversion and transmission

[0796] (The server converts the generated dream scenario into electroencephalogram (EEG) data. The algorithm used here maps each element of the generated scenario to a corresponding EEG pattern. This converted EEG data is transmitted to the terminal via a secure communication channel.)

[0797] Receiving brainwave data and experiencing dreams

[0798] The device analyzes and stores brainwave data received from the server. Furthermore, it is equipped with a sensor that monitors the timing of REM sleep. When it detects that the user has entered REM sleep, it transmits brainwave data to the brain. This allows the user to experience their desired dreams.

[0799] Feedback function

[0800] Users provide feedback on their dreams after waking up through a dedicated application. This feedback is used as data to generate higher-quality dream scenarios in the future.

[0801] Specific example

[0802] 1. Let's say the user dreams of an "underwater adventure." They open the dedicated application and input elements such as "underwater city," "dolphins," and "treasure hunt."

[0803] 2. The device sends this data to the server.

[0804] 3. The server analyzes the received data, and the generating AI creates a dream scenario. For example, a scenario where "you encounter dolphins while exploring an underwater city and search for treasure together."

[0805] 4. The server converts this scenario into electroencephalogram (EEG) data and sends it to the terminal.

[0806] 5. The device monitors the timing of REM sleep and transmits brainwave data to the user's brain at the appropriate time.

[0807] 6. Users experience the dreams they desire, waking up with restful sleep and a positive mood.

[0808] The system of this invention aims to control dreams according to the user's wishes and provide high-quality sleep. This makes it possible to improve sleep quality, reduce stress, and wake up feeling positive.

[0809] The following describes the processing flow.

[0810] Detailed program processing flow

[0811] Step 1:

[0812] The user opens a dedicated application and enters the elements of the dream they want to see. The application's interface displays scenario options and custom input boxes, allowing the user to enter specific elements such as "underwater city," "dolphins," or "treasure hunt." Then they press the "Submit" button.

[0813] Step 2:

[0814] The terminal sends the entered dream elements to the server. This process converts the user-entered data into JSON format and sends it to the server in an encrypted format using the HTTPS protocol.

[0815] Step 3:

[0816] The server receives data transmitted via the data reception API. At this stage, it verifies the integrity and format of the data and passes it to the generating AI module for analysis.

[0817] Step 4:

[0818] The server's generation AI module generates dream scenarios based on input data. For example, using topic modeling and sequence generation models, it generates a story like "Meeting dolphins while exploring an underwater city and searching for treasure together."

[0819] Step 5:

[0820] The server converts the generated dream scenario into electroencephalogram (EEG) data. This conversion is performed using a highly specialized algorithm that maps each element of the generated story (e.g., scenes and events) to a corresponding EEG pattern.

[0821] Step 6:

[0822] The server transmits the converted EEG data to the terminal. The transmission uses an encrypted communication channel via a security protocol, ensuring secure and rapid data transfer.

[0823] Step 7:

[0824] The device analyzes the brainwave data received from the server and stores it locally. Furthermore, it uses a sensor to monitor the timing of REM sleep, and when it detects that the user has entered REM sleep, it prepares to transmit the stored brainwave data.

[0825] Step 8:

[0826] The device triggers the transmission of brainwave data to the user's brain when REM sleep is detected. This transmission occurs through a device connected to the user's brain, and dream elements are transmitted to the brain as electrical signals.

[0827] Step 9:

[0828] The user experiences a desired dream based on the electrical signals they input. After waking, they open a dedicated application to provide feedback on the dream they had. This feedback is used to improve the quality of future dream generation.

[0829] The above is the specific processing flow of the "Wake Up Refreshed! Dream Palette" system. This allows users to experience their desired dreams, achieve quality sleep, and wake up feeling refreshed.

[0830] (Example 1)

[0831] 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."

[0832] In modern society, ensuring quality sleep is a crucial issue for users. In particular, many users experience stress and anxiety, leading to an increasing number of cases where they cannot get satisfactory sleep. If users could experience dreams they desire, it would lead to mental refreshment and stress reduction, thus providing quality sleep. However, because there is no concrete system to induce such dream experiences, users are unable to freely experience the dreams they want.

[0833] 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.

[0834] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the input dream elements to a digital device, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to a digital device, means for the digital device to transmit the EEG data to the user's brain in conjunction with REM sleep, means for providing feedback on the dream the user experienced, and sensors for monitoring the timing of REM sleep. This enables the user to experience their desired dream and obtain quality sleep.

[0835] "A means of inputting the dream elements desired by the user" refers to providing an interface for users to input the dream elements they wish to experience, and a means of incorporating that input data into the system.

[0836] "Means for transmitting input dream elements to a digital device" refers to a means for converting the dream elements entered by the user into a data format and securely transmitting them to a digital device.

[0837] "Means for receiving and analyzing transmitted data" refers to a method of receiving data from a transmitted digital device, analyzing its contents, and extracting elements of dreams.

[0838] "A method for generating specific dream scenarios using generative AI" refers to a method of creating specific dream scenarios that users will experience, based on the elements of the dreams they have received, using generative AI (artificial intelligence).

[0839] "Methods for converting generated scenarios into brainwave data" refers to methods for converting generated dream scenarios into corresponding brainwave patterns so that users can actually experience the dream.

[0840] "Means for transmitting converted brainwave data to a digital device" refers to means for securely transmitting converted brainwave data to a digital device.

[0841] "A method by which a digital device transmits brainwave data to a user's brain in conjunction with REM sleep" refers to a method in which a digital device detects the user's REM sleep and sends brainwave data to the user's brain at that time.

[0842] "A means of providing feedback on dreams experienced by users" refers to a method for users to provide feedback to the system regarding their thoughts and opinions about the dreams they have experienced.

[0843] A "sensor that monitors the timing of REM sleep" is a sensor that monitors the user's sleep state and detects when the user enters REM sleep.

[0844] This invention is a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system consists of a user terminal, a server, a generating AI, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[0845] User input processing

[0846] The user launches a dedicated application and enters the elements of the dream they want to see. This application features an intuitive interface, allowing users to input their desired dream elements through text input or by selecting options. For example, they can enter "underwater city," "dolphins," or "treasure hunt."

[0847] Sending and receiving data

[0848] The terminal converts the dream elements entered by the user into JSON data and sends it to the server using the HTTPS protocol. The terminal encrypts the data using SSL / TLS to ensure its security. The server receives and analyzes the data sent from the terminal. This analysis includes data extraction and the generation of prompts for the generative AI model.

[0849] Generating dream scenarios using AI

[0850] The generation AI installed on the server generates a specific dream scenario that includes elements desired by the user, based on the received prompt text. The generation AI model uses natural language processing technology to create a story based on the elements input by the user. For example, it can generate a scenario such as "searching for treasure with dolphins in an underwater city."

[0851] Scenario conversion and transmission

[0852] The server converts the generated dream scenario into brainwave data. A specialized algorithm is used for this conversion, mapping each element of the scenario to a corresponding brainwave pattern. The brainwave data is encrypted to ensure security and transmitted to a digital device.

[0853] Receiving brainwave data and experiencing dreams

[0854] The device receives transmitted brainwave data and stores it in local storage. Furthermore, the device is equipped with a sensor that monitors the timing of REM sleep, monitoring the user's sleep state in real time. When the sensor detects the user's REM sleep, the device transmits the stored brainwave data to the user's brain. This allows the user to experience their desired dreams.

[0855] Feedback function

[0856] After waking up, users provide feedback about their dreams through a dedicated application. This feedback is used as training data for the generating AI and is reflected in the creation of future dream scenarios. This allows users to experience dreams that are more faithful to their preferences and of higher quality.

[0857] Specific example

[0858] The following are some specific examples.

[0859] 1. The user expresses a desire to experience an "underwater adventure" and opens the dedicated application.

[0860] 2. Enter specific elements such as "underwater city," "dolphins," and "treasure hunt."

[0861] 3. The device converts this data into JSON format and sends it to the server using HTTPS.

[0862] 4. The server receives and analyzes the data to generate a prompt message, which is then passed to the generating AI. The generating AI then creates a dream scenario: "While exploring an underwater city, you encounter dolphins and search for treasure together."

[0863] 5. Convert the scenario into electroencephalogram (EEG) data and transmit it to the terminal via a secure channel.

[0864] 6. The device stores brainwave data and detects the user's REM sleep, transmitting the data to the brain.

[0865] 7. Users experience the dreams they desire and provide feedback about the dreams they had.

[0866] Examples of prompts to input into a generative AI model

[0867] The following are specific examples of prompt statements to be input to a generative AI model.

[0868] "The user wants to dream about an 'underwater city,' 'dolphins,' and 'treasure hunting.' Please generate a specific dream scenario that includes these elements."

[0869] This system allows users to experience their desired dreams and get quality sleep.

[0870] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0871] Step 1:

[0872] The user launches a dedicated application and inputs the elements of the dream they want to see. This input is done through text boxes or selection lists, such as "underwater city," "dolphins," or "treasure hunt." The input data (e.g., underwater city, dolphins, treasure hunt) is then taken into the system.

[0873] Step 2:

[0874] The terminal converts the dream elements entered by the user into JSON format and sends them to the server using the HTTPS protocol. Specifically, it transforms the input data (e.g., underwater city, dolphins, treasure hunt) into a JSON structure and sends it as SSL / TLS encrypted data. The JSON formatted data is output and sent to the server via a secure communication channel.

[0875] Step 3:

[0876] The server receives JSON data sent from the terminal. It parses the received data and extracts the dream elements. Specifically, it parses the received data (e.g., {"elements":["Underwater city", "Dolphin", "Treasure hunt"]}) and extracts a list of elements. The extracted list of elements is output.

[0877] Step 4:

[0878] The server generates a prompt message for the generating AI based on the element list and passes it to the AI. The generated prompt message (e.g., "The user wants to have a dream that includes 'underwater city,' 'dolphins,' and 'treasure hunt.' Please generate a specific dream scenario that includes these elements.") is input into the generating AI model. The prompt message is output and passed to the generating AI model.

[0879] Step 5:

[0880] The generative AI generates a specific dream scenario that includes elements desired by the user, based on the given prompt text. Specifically, the generative AI model receives the prompt text as input and performs natural language processing to generate a scenario such as "Meeting a dolphin while exploring an underwater city and searching for treasure together." The generated scenario is then output.

[0881] Step 6:

[0882] The server converts the generated dream scenario into brainwave data. It uses a conversion algorithm that maps each scene and element of the scenario to the corresponding brainwave pattern. The scenario received as input (e.g., "While exploring an underwater city, I meet a dolphin and we search for treasure together") is converted into a brainwave pattern, and the brainwave data is output.

[0883] Step 7:

[0884] The server transmits the converted EEG data to the terminal via a secure communication channel. Data security is ensured by sending the EEG data to the terminal using encrypted communication. As output, encrypted EEG data is sent to the terminal.

[0885] Step 8:

[0886] The device saves the received brainwave data to local storage. Furthermore, the device is equipped with a sensor that monitors the timing of REM sleep. This sensor analyzes the user's brainwaves in real time and detects when the user enters REM sleep. Upon detecting REM sleep, the stored brainwave data is output and transmitted to the user's brain.

[0887] Step 9:

[0888] The user receives brainwave data transmitted from the device during REM sleep. This allows them to experience a dream where they "encounter dolphins while exploring an underwater city and search for treasure together." Because the user's brain shapes the dream according to the received brainwave data, the user can experience the dream they desire.

[0889] Step 10:

[0890] After waking up, users provide feedback about their dreams through a dedicated application. This feedback includes details and impressions of the dream. This feedback data is sent to the server as learning data to be used in future scenario generation. This allows the system to provide higher-quality dreams.

[0891] (Application Example 1)

[0892] 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."

[0893] Conventional dream induction systems were designed for individual users to use at home, and therefore did not consider use in physical establishments such as relaxation facilities and spas. As a result, there was a lack of means to significantly improve the customer experience in these physical locations. Furthermore, there was no system that allowed customers in relaxation facilities to easily input their desired dreams and experience them as actual dreams. In addition, there were no means to efficiently induce dreams for multiple customers, resulting in a limited quality of customer experience.

[0894] 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.

[0895] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the inputted dream elements to the server, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI based on the analyzed data, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to the user's terminal, means for the terminal to transmit the EEG data to the user's brain in conjunction with REM sleep, means for the customer to input dream elements using an input device in the store, means for the input device to transmit the dream elements to the server, means for the server to convert the data into EEG data based on the dream scenario and transmit it to a relaxation device, and means for the relaxation device to transmit the EEG data to the user's brain during REM sleep. This makes it possible to allow users to experience dreams based on their individual preferences in a physical store, significantly improving the quality of the customer experience at relaxation facilities. It also makes it possible to efficiently and effectively induce dreams for multiple customers.

[0896] A "user" refers to an individual who uses the system to experience their dreams.

[0897] "Dream elements" are the elements that make up the specific scenarios and situations that users input in their dreams that they want to experience.

[0898] A "server" refers to a computer system that receives data sent by users and uses AI for analysis and generation to create dream scenarios.

[0899] "Generative AI" refers to an artificial intelligence model that generates specific dream scenarios based on the elements of a dream that are input.

[0900] A "scenario" refers to a series of events that form the specific story or scenes that a user experiences in their dreams.

[0901] "Electrical wave data" refers to the brainwave patterns that have been converted to allow the user to experience the generated dream scenario.

[0902] A "terminal" refers to a device used by a user that has the function of receiving brainwave data transmitted from a server and transmitting it to the user's brain.

[0903] "REM sleep" refers to the primary sleep stage in which users dream, and it is possible to induce dreams by transmitting brainwave data during this time.

[0904] An "input device" refers to a device used by users to input elements of their dreams, and is typically installed in physical stores or other similar locations.

[0905] A "relaxation device" refers to a device that has the function of appropriately transmitting brainwave data to the user and providing a dream-like experience.

[0906] This invention is a system that allows users to experience their desired dreams during REM sleep. This system works by having the user input elements of their dream, and then a generating AI uses that information to create a specific dream scenario, which is then transmitted to the user as brainwave data.

[0907] System Configuration

[0908] 1. Processing user input

[0909] Users input the elements of their desired dream using a dedicated input device. The input device is installed in physical relaxation facilities, and its user interface is intuitive, making it easy to select scenarios and customize inputs. For example, users can input specific elements such as "beach," "exotic forest," or "quiet mountain lake."

[0910] 2. Sending and receiving data

[0911] The input device sends the input dream elements to the server. The data is converted to JSON format and transmitted using the secure HTTPS protocol. The server analyzes the received data and passes it to a generative AI. This AI uses a natural language processing model to generate a specific dream scenario based on the user's wishes.

[0912] 3. Generating a dream scenario

[0913] The server's generation AI creates stories based on the elements entered by the user. For example, it might generate a dream scenario such as "You standing by a quiet mountain lake." This scenario is presented in a narrative format and is designed to be experienced naturally by the user within the dream.

[0914] 4. Scenario conversion and transmission

[0915] The server converts the generated dream scenario into electroencephalogram (EEG) data. The generative AI model used here maps each element of the generated scenario to a corresponding EEG pattern. This converted EEG data is transmitted to the relaxation device via a secure communication channel.

[0916] 5. Receiving EEG data and experiencing dreams

[0917] The relaxation device analyzes and stores brainwave data received from a server. Furthermore, it is equipped with a sensor that monitors the timing of REM sleep. When it detects that the user has entered REM sleep, it transmits brainwave data to the brain. This allows the user to experience their desired dreams.

[0918] Hardware and software to be used

[0919] Input device: A device for customers to input elements of their dreams. It is installed in physical stores.

[0920] Server: A computer system that receives dream elements, analyzes them, and generates dream scenarios using a generative AI.

[0921] Generative AI: A natural language processing model that creates dream scenarios based on dream elements entered by the user.

[0922] Relaxation device: A device that monitors the timing of REM sleep and transmits brainwave data.

[0923] Specific example

[0924] The customer inputs elements of their desired dream, such as "I want to relax by a quiet mountain lake," into an input device at the relaxation facility. The input device sends this data to a server, which generates a scenario of "themselves standing by a quiet mountain lake." The generated scenario is converted into brainwave data and sent to the relaxation device. The relaxation device monitors the customer's REM sleep and sends brainwave data at the appropriate time.

[0925] Example of a prompt

[0926] The user entered "I want to relax by a quiet mountain lake." Based on this, generate a dream scenario that will help the user relax.

[0927] This format allows users to significantly enhance their experience at relaxation facilities and provides dream experiences tailored to their individual preferences.

[0928] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0929] Step 1: The user enters the elements of their dream.

[0930] Users access an input device installed in a physical store and input elements of their dream experience (e.g., "beach," "exotic forest," "quiet mountain lake"). The input device interface is intuitive, allowing users to easily select or customize their desired elements. The input data is in text format.

[0931] Step 2: Submit the input data

[0932] The input device sends the dream elements entered by the user to the server. The input data is converted to JSON format and sent to the server using the secure HTTPS protocol. An example of input data is {"dream_elements": ["beach", "exotic forest", "quiet mountain lake"]}.

[0933] Step 3: Data reception and analysis

[0934] The server receives data transmitted from the input device. The received data is analyzed and used as material to generate specific dream scenarios based on the user's wishes. This analysis involves examining the structure of the received data and extracting its elements.

[0935] Step 4: Generating dream scenarios using a generative AI

[0936] The server passes the analyzed data to the generative AI. The generative AI model uses natural language processing to generate specific dream scenarios based on the input data. For example, if the user input is "I want to relax by a quiet mountain lake," the generated scenario might be something like "I am standing by a quiet mountain lake."

[0937] Step 5: Converting the scenario's EEG data

[0938] The server converts the generated dream scenario into brainwave data. The generating AI model maps each element of the output scenario to the corresponding brainwave pattern, generating brainwave data that the user can experience as a dream. This converted data is in binary format.

[0939] Step 6: Sending EEG data

[0940] The server transmits the converted EEG data to the relaxation device. The EEG data is sent to the relaxation device using a secure communication channel. The transmitted data is stored in the device's memory.

[0941] Step 7: Monitoring REM sleep

[0942] The relaxation device monitors the user's REM sleep timing using built-in sensors. The sensors analyze brainwave patterns in real time to detect when the user enters REM sleep. Electrodes-based electroencephalogram (EEG) measurement devices and heart rate monitors are used to determine REM sleep.

[0943] Step 8: Sending EEG data and inducing dreams

[0944] After the relaxation device detects the timing of REM sleep, it transmits the received brainwave data to the user's brain. This allows the user to experience the dream they desire. The data transmission is performed using a dedicated brainwave transmission function.

[0945] This series of processes allows users to experience customized dreams at relaxation facilities, providing them with high-quality relaxation.

[0946] 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.

[0947] System Overview

[0948] This invention incorporates an emotion engine into a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system recognizes the user's emotional state and selects and adjusts dreams based on that state. The system consists of a user terminal, a server, a generation AI, an emotion engine, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[0949] User input processing

[0950] Users input the elements of their desired dream using a dedicated application. The application interface displays scenario options and custom input boxes, allowing users to enter specific elements such as "underwater city," "dolphins," and "treasure hunt." Furthermore, an emotion engine analyzes the user's emotional state, and suggests dream elements based on the results.

[0951] How the emotion engine works

[0952] The device collects emotion analysis data to recognize the user's emotional state. This data is obtained, for example, through voice analysis, facial expression analysis, and biometric data analysis from wearable devices. The collected emotion data is sent from the device to a server and analyzed by an emotion engine.

[0953] Analysis and proposals regarding emotional data

[0954] The server's emotion engine analyzes the received emotion data to identify the user's current emotional state. Based on the analyzed emotional state, it suggests the most suitable dream elements. These suggestions are returned to the user's device and displayed in the application. The user then decides whether to accept the suggested elements or enter custom elements.

[0955] Sending and receiving data

[0956] The device sends the elements of the dream that the user has finally decided on to the server. The data is converted to JSON format and transmitted in an encrypted format using the secure HTTPS protocol. Meanwhile, the server analyzes the received data and passes it to a generative AI. This generative AI uses a natural language processing model to generate a specific dream scenario based on the user's wishes.

[0957] Generating a dream scenario

[0958] The server's AI generates dream scenarios based on user input and emotional data. For example, it might generate a dream scenario such as "encountering dolphins while exploring an underwater city and searching for treasure together." This scenario can be customized to match the user's emotional state.

[0959] Scenario conversion and transmission

[0960] The server converts the generated dream scenario into electroencephalogram (EEG) data. This conversion is performed using a specialized algorithm that maps each element of the generated scenario (e.g., scenes and events) to the corresponding EEG pattern. The converted EEG data is then transmitted to the terminal via a secure communication channel.

[0961] Receiving brainwave data and experiencing dreams

[0962] The device analyzes and stores brainwave data received from the server. It also uses a sensor to monitor the timing of REM sleep, and when it detects that the user has entered REM sleep, it transmits the stored brainwave data to the brain.

[0963] Feedback function

[0964] Users provide feedback on their dreams after waking up through a dedicated application. This feedback data is used to improve the accuracy of the dream generation algorithm and emotion engine for future use.

[0965] Specific example

[0966] 1. The user expresses a desire for an "underwater adventure," opens the application, and inputs elements such as "underwater city," "dolphins," and "treasure hunt." Suggestions from the emotion engine are also considered.

[0967] 2. The device sends this data and sentiment data to the server.

[0968] 3. The server analyzes the received data, and the generating AI creates a dream scenario. For example, a scenario where "you encounter dolphins while exploring an underwater city and search for treasure together."

[0969] 4. The server converts this scenario into electroencephalogram (EEG) data and sends it to the terminal.

[0970] 5. The device monitors the timing of REM sleep and transmits brainwave data to the user's brain at the appropriate time.

[0971] 6. Users can have the dreams they desire and enjoy restful sleep.

[0972] The system of this invention aims to control dreams according to the user's wishes and provide high-quality sleep. Furthermore, by utilizing an emotion engine, it is possible to provide an optimal dream experience tailored to the user's emotional state.

[0973] The following describes the processing flow.

[0974] Specific processing flow of the program

[0975] Step 1:

[0976] The user opens a dedicated application and enters the elements of the dream they want to see. The application interface displays scenario options and custom input boxes, allowing the user to enter specific elements such as "underwater city," "dolphins," or "treasure hunt," and then press the "Submit" button.

[0977] Step 2:

[0978] The device collects the user's emotional state using voice input, facial recognition, or biometric data acquired from wearable devices. The collected data is sent to the emotion engine in real time.

[0979] Step 3:

[0980] The device converts the user's emotional data and dream elements into JSON format and sends them to the server using the secure HTTPS protocol.

[0981] Step 4:

[0982] The server receives data sent via the data reception API. It verifies the integrity and format of the data and passes it to the emotion engine. The emotion engine analyzes the user's emotional state and suggests the most suitable dream elements based on the results. This suggestion is returned to the user's device.

[0983] Step 5:

[0984] The user reviews and modifies dream elements based on suggestions from the emotion engine. For example, if the emotion engine suggests "relaxing underwater exploration," the user can add "treasure hunting."

[0985] Step 6:

[0986] The device then sends the finalized dream elements back to the server. This data is converted to JSON format and transmitted using a secure communication channel.

[0987] Step 7:

[0988] The server analyzes the received dream element data and passes it to the generating AI. The generating AI then generates a specific dream scenario based on this data. For example, it might generate a scenario such as, "While exploring an underwater city, you encounter a dolphin and search for treasure together."

[0989] Step 8:

[0990] The server converts the generated scenario into electroencephalogram (EEG) data. This conversion is performed using a specialized algorithm that maps each element of the generated scenario (e.g., scenes and events) to the corresponding EEG pattern. The converted EEG data is transmitted to the terminal via a secure communication channel.

[0991] Step 9:

[0992] The device analyzes and stores brainwave data received from the server. Furthermore, it is equipped with a sensor that monitors the timing of REM sleep. When it detects that the user has entered REM sleep, it prepares to transmit the stored brainwave data to the brain.

[0993] Step 10:

[0994] The device triggers the transmission of brainwave data to the user's brain when REM sleep is detected. This transmission occurs through a device connected to the user's brain, and dream elements are transmitted to the brain as electrical signals.

[0995] Step 11:

[0996] The user experiences a desired dream based on the electrical signals they input. For example, they might dream of "searching for treasure with dolphins in an underwater city." After waking, they open a dedicated application to provide feedback on their dream. This feedback is used to improve the accuracy of the dream generation algorithm and emotion engine for future sessions.

[0997] (Example 2)

[0998] 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."

[0999] To improve sleep quality, there is a need for a system that allows users to experience dreams of their choice. However, conventional technology has been unable to adjust dream content based on the user's emotional state, making it difficult to provide dreams optimized for the user's psychological state. Furthermore, there was a lack of mechanisms to collect feedback on the dreams users experienced and use that feedback to improve the system's accuracy. In addition, the lack of a means to accurately detect the timing of REM sleep made it difficult to provide an effective dream experience.

[1000] 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.

[1001] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the input dream elements to the server, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI based on the analyzed data, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to the user's terminal, means for the terminal to transmit the EEG data to the user's brain in conjunction with REM sleep, means for collecting and analyzing the user's emotional data, and means for suggesting dream elements based on the analyzed emotional data. This makes it possible to allow the user to experience the content of their desired dream and to provide a dream optimized for their emotional state at the time. Furthermore, feedback on the dreams seen can be collected and used to improve the accuracy of the system. In addition, by accurately detecting the timing of REM sleep, a more effective dream experience can be provided to the user.

[1002] A "user" is the individual who uses the system to input the content of their desired dream and then experiences that dream.

[1003] "Dream elements" refer to specific scenarios, scenes, characters, themes, etc., that users want to experience.

[1004] The "server" is a central processing unit that analyzes data sent by users, generates dream scenarios using a generative AI and emotion engine, and converts those scenarios into brainwave data for transmission.

[1005] A "terminal" is a device that the user directly operates, and it is a device that inputs dream elements, collects emotional data, monitors REM sleep, and transmits brainwave data.

[1006] "Emotional data" refers to data that indicates a user's current emotional state, and includes information collected through voice analysis, facial expression analysis, and biometric data analysis from wearable devices.

[1007] The "emotion engine" is a software component that analyzes collected emotional data and, based on the results, suggests the most suitable dream elements to the user.

[1008] "Generative AI" is an artificial intelligence model that generates specific dream scenarios based on received data and analyzed emotional data.

[1009] "Electroencephalogram (EEG) data" refers to data that has been converted to transmit the generated dream scenario to the user's brain, and is expressed as an EEG pattern.

[1010] "REM sleep" is a deep stage of sleep in which users are more likely to dream, and brainwave data is transmitted during this time to induce the desired dream.

[1011] "Feedback" refers to information provided by users through a dedicated application, detailing the content and their impressions of their dreams. This information helps improve the accuracy of future dream generation.

[1012] A "sensor" is a device used to monitor the timing of a user's REM sleep.

[1013] Modes for carrying out the invention

[1014] System Configuration

[1015] This invention incorporates an emotion engine into a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system recognizes the user's emotional state and selects and adjusts dreams based on that state. The system consists of a user terminal, a server, a generation AI, an emotion engine, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[1016] User input processing

[1017] The user launches a dedicated application and enters the elements of the dream they want to see into the interface. Fields are provided for entering specific elements such as "underwater city," "dolphins," and "treasure hunt." Once the user has finished entering the information, the device collects this data.

[1018] How the emotion engine works

[1019] The device simultaneously collects emotional data. For this data collection, the device is equipped with voice analysis, facial expression analysis, and biometric data analysis functions for wearable devices. The collected emotional data is transmitted from the device to a server.

[1020] Analysis and proposals regarding emotional data

[1021] The server's emotion engine analyzes the received emotion data to identify the user's current emotional state. Based on the analysis, it suggests the most suitable dream elements. These suggestions are sent back from the server to the terminal and displayed in the application for the user to review. The user then decides whether to accept the suggested elements or enter new custom elements.

[1022] Generating a dream scenario

[1023] The device sends the elements of the dream that the user has finally decided on to the server. This transmission is converted to JSON format and performed using the secure HTTPS protocol. The server parses the received data and passes it on to the generative AI. The generative AI uses a natural language processing model to generate a specific dream scenario.

[1024] For example, it can generate a specific scenario such as, "While exploring an underwater city, you encounter dolphins and search for treasure together."

[1025] Scenario conversion and transmission

[1026] The server converts the generated dream scenario into electroencephalogram (EEG) data. This conversion process uses a specialized algorithm that maps each element of the generated scenario (e.g., scenes and events) to a corresponding EEG pattern. The converted EEG data is then transmitted to the terminal via a secure communication channel.

[1027] Dream experience

[1028] The device analyzes and stores brainwave data received from the server. It also uses a sensor to monitor the timing of REM sleep, and when it detects that the user has entered REM sleep, it transmits the stored brainwave data to the brain. As a result, the user experiences the dream they desired.

[1029] Feedback function

[1030] Users provide feedback on their dreams after waking up through a dedicated application. This feedback data is used to improve the accuracy of the dream generation algorithm and emotion engine for future use.

[1031] Examples of specific cases and prompt statements

[1032] Specifically, a user might express a desire for an "underwater adventure" and use the application to input elements such as "underwater city," "dolphins," and "treasure hunt." The device sends this data, along with emotional data, to a server, which analyzes it, and a generating AI creates a dream scenario. For example, a scenario might be generated where the user "encounters dolphins while exploring an underwater city and searches for treasure together." The server converts this scenario into brainwave data and sends it to the device. The device monitors the timing of REM sleep and sends the brainwave data to the user's brain at the appropriate time. The user then experiences the dream they desired and enjoys a fulfilling sleep.

[1033] An example of a prompt message is as follows:

[1034] Enter dream elements such as "underwater city," "dolphins," and "treasure hunt." Also, check the elements suggested by the emotion engine.

[1035] By using such a system, it is possible to provide dreams tailored to the user's preferences and support quality sleep. Furthermore, by utilizing an emotion engine, users can obtain a dream experience optimized for their emotional state.

[1036] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1037] Step 1: Enter the user's desired elements.

[1038] The user launches a dedicated application and enters the elements of the dream they want to see into the interface. Fields are provided for entering specific elements such as "underwater city," "dolphins," and "treasure hunt."

[1039] Input: Elements of the dream entered by the user into a dedicated application.

[1040] Output: Dream element data held on the device.

[1041] Operation: The user enters specific dream elements in text format into the application's input field and presses the submit button.

[1042] Step 2: Collecting emotional data

[1043] The device performs voice analysis, facial expression analysis, and biometric data analysis from wearable devices to recognize the user's emotional state.

[1044] Input: User's voice, facial expressions, and biometric data from wearable devices.

[1045] Output: Analyzed sentiment data.

[1046] Operation: Collects user emotion data using the device's built-in camera, microphone, and wearable sensors. This data is then temporarily stored.

[1047] Step 3: Sending emotional data

[1048] The device sends the collected emotional data to the server. This transmission uses the secure HTTPS protocol, and the data is encrypted.

[1049] Input: Collected sentiment data.

[1050] Output: Sentiment data sent to the server.

[1051] Operation: The device encrypts the emotional data using the HTTPS protocol and sends it to the server.

[1052] Step 4: Analysis of emotional data

[1053] The server passes the received emotional data to the emotion engine for analysis. The emotion engine uses natural language processing and machine learning algorithms to identify the user's emotional state.

[1054] Input: Received emotion data.

[1055] Output: Analyzed emotional state.

[1056] Operation: The emotion engine uses algorithms to analyze the user's emotional data item by item and identify their current emotional state.

[1057] Step 5: Propose elements of the dream

[1058] The server's emotion engine suggests the most suitable dream elements based on the analysis results. This suggestion is converted to JSON format and sent to the terminal via a secure channel.

[1059] Input: Analyzed emotional state.

[1060] Output: Dream element proposal data.

[1061] Operation: The emotion engine selects the most suitable dream elements for the user based on the analysis results, converts them into JSON format, and sends them to the device.

[1062] Step 6: View and select suggestions

[1063] The device displays the received suggestions to the user. The user then decides whether to accept the suggested elements or enter custom elements.

[1064] Input: Data on the elements of the proposed dream.

[1065] Output: User's final selection data.

[1066] Operation: The device displays the received suggestions in the application interface, and the user confirms and selects them.

[1067] Step 7: Submit selected elements

[1068] The terminal sends the finalized dream elements to the server. This transmission also uses the secure HTTPS protocol.

[1069] Input: User's last selected data.

[1070] Output: Dream element data sent to the server.

[1071] Operation: Converts the dream elements selected by the user into JSON format and sends them to the server using the HTTPS protocol.

[1072] Step 8: Generating dream scenarios using a generative AI

[1073] The server analyzes the received dream elements and passes them to the generative AI. The generative AI uses a natural language processing model to generate a specific dream scenario.

[1074] Input: User's dream element data.

[1075] Output: The generated dream scenario.

[1076] Operation: The generating AI applies a specific algorithm based on the received data to generate dream scenarios such as "Meeting dolphins while exploring an underwater city and searching for treasure together."

[1077] Step 9: Converting the scenario into EEG data

[1078] The server converts the generated dream scenario into brainwave data. Using specialized algorithms, it maps each scene and event to a brainwave pattern.

[1079] Input: The generated dream scenario.

[1080] Output: Converted electroencephalogram (EEG) data.

[1081] Operation: Analyze the generated scenario and apply an algorithm to convert it into electroencephalogram (EEG) data.

[1082] Step 10: Sending EEG data

[1083] The server transmits the converted EEG data to the terminal. This transmission also uses a secure communication channel.

[1084] Input: Converted electroencephalogram (EEG) data.

[1085] Output: EEG data transmitted to the terminal.

[1086] Operation: Transmits EEG data to the terminal via a secure channel.

[1087] Step 11: Monitoring REM sleep

[1088] The device uses sensors to monitor the timing of REM sleep.

[1089] Input: User's sleep status data.

[1090] Output: REM sleep timing detection information.

[1091] Operation: The device continuously monitors the user's sleep state using a REM sleep monitoring sensor.

[1092] Step 12: Sending EEG data

[1093] When the device detects that the user has entered REM sleep, it transmits the stored brainwave data to the user's brain.

[1094] Input: REM sleep timing detection information and stored electroencephalogram (EEG) data.

[1095] Output: Brainwave data transmitted to the user's brain.

[1096] Operation: When REM sleep is detected, the stored electroencephalogram (EEG) data is transmitted to the user's brain.

[1097] Step 13: Provide feedback on your dream

[1098] Users provide feedback about their dreams after waking up through a dedicated application. This feedback data is used to improve the accuracy of the system.

[1099] Input: User feedback information.

[1100] Output: Collected feedback data.

[1101] Operation: Users input their thoughts and evaluations about the content of their dreams using a dedicated application, and this information is sent to the server.

[1102] (Application Example 2)

[1103] 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."

[1104] Conventional systems have found it difficult to individually customize users' dream experiences and lacked sufficient functionality to adjust dream elements based on emotional states. Furthermore, providing feedback based on actual experience was challenging in employee customer service and negotiation skills training. This invention proposes a system that solves these problems and provides optimal dream experiences and training based on the user's emotional state.

[1105] 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.

[1106] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the input dream elements to the server, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI based on the analyzed data, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to the user's terminal, means for the terminal to transmit the EEG data to the user's brain in accordance with REM sleep, means for recognizing and analyzing the user's emotional state, and means for adjusting the dream scenario based on the analyzed emotional data. This makes it possible to adjust the dream experience and training scenario based on the user's emotional state.

[1107] A "user" refers to someone who uses this system to customize their dream experiences and training scenarios.

[1108] "Dream elements" refer to specific items or situations that users want to include in their desired dreams or training scenarios.

[1109] A "server" refers to a central system that receives, analyzes, and processes data sent by users.

[1110] "Means of input" refers to the interface or device that allows the user to input elements of their dreams into the system.

[1111] "Means of transmission" refers to the means of communication used to send the input dream elements to the server.

[1112] "Means for receiving and analyzing" refers to the software and hardware used by the server to receive transmitted data and analyze it.

[1113] "Generative AI" refers to artificial intelligence that uses natural language processing models to generate specific dream scenarios.

[1114] "Means of conversion" refers to algorithms and systems for converting the generated dream scenarios into brainwave data.

[1115] A "terminal" refers to a device used by a user, specifically equipment that receives and transmits electroencephalogram (EEG) data.

[1116] "REM sleep" refers to the period of time when a user enters a deep sleep state, a time when they are more likely to dream.

[1117] "Emotional state" refers to the user's current emotional state and is analyzed from voice, facial expressions, biometric data, and other sources.

[1118] "Means of recognition and analysis" refers to software and hardware for identifying and analyzing a user's emotional state.

[1119] "Means of adjustment" refers to a system for optimizing dream scenarios and training scenarios based on analyzed emotional data.

[1120] This invention provides a system that allows users to input desired dream elements and experience them during REM sleep, as well as a function to recognize emotional states and adjust training scenarios. The system consists of a user terminal, a server, a generative AI, an emotion engine, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[1121] Users access a dedicated application using smart glasses and input elements of the dream or training scenario they wish to experience. For example, for a customer service skills training scenario, they might input specific elements such as "handling complaints" and "product description." The emotion engine analyzes the user's emotional state and displays suggestions for the most suitable training scenario based on the results.

[1122] Smart glasses collect the user's voice, facial expressions, and biometric data and send it to an emotion engine. The emotion engine uses Azure Cognitive Services' emotion recognition API to analyze this data and identify the user's current emotional state. The collected emotional data and user preferences are sent to a server, where a generative AI (e.g., OpenAI's GPT-3) generates specific scenarios based on prompts.

[1123] The server converts the generated scenario into electroencephalogram (EEG) data and sends it to the user's terminal using a secure communication channel (HTTPS). The terminal uses sensors to monitor the timing of REM sleep and transmits EEG data when the user enters REM sleep.

[1124] Furthermore, in training scenarios, the received scenario is overlaid on the smart glasses. The smart glasses monitor the user's emotional state in real time and provide appropriate advice and feedback as the scenario progresses.

[1125] As a concrete example, consider a case where a user requests a training scenario for "handling customer complaints." In this case, the user opens the application and types "handling complaints." Emotional data obtained from voice and facial expressions is sent to the server, and the generating AI creates a "customer complaint dialogue scenario." For example, a scenario is generated in which "a customer complains about a product defect, and the user learns specific ways to handle it," and this is converted into brainwave data. Furthermore, the progress of the training is adjusted and appropriate feedback is provided based on the emotional data collected in real time.

[1126] The following are specific examples of prompt statements for generative AI models:

[1127] "The user's desired scenario is 'handling a complaint,' and their emotional state is 'feeling stressed.' Please generate an appropriate training scenario."

[1128] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1129] Step 1:

[1130] Users input elements of their desired dreams or training scenarios through a dedicated application for smart glasses. For example, they might input specific elements such as "handling customer complaints" or "product description." The input data includes elements specified in text format.

[1131] Step 2:

[1132] The terminal sends the data entered by the user to the server. The data sent includes the elements requested by the user and is sent to the server in JSON format.

[1133] Step 3:

[1134] The server receives the transmitted data and performs analysis. This analysis includes emotion recognition, which is performed using the user's voice and facial expression data. Specifically, it calls the Azure Cognitive Services emotion recognition API to generate emotion data as an analysis result. The input data is voice and image data, and the output is a tag or score indicating the emotional state.

[1135] Step 4:

[1136] The server uses a generative AI model to generate specific scenarios based on the analyzed emotional data and the user's desired elements. In this process, it uses OpenAI's GPT-3 to create prompts such as: "The user's desired scenario is 'Handling a complaint,' and their emotional state is 'Feeling stressed.' Please generate an appropriate training scenario." The output data generated by the generative AI is the specific scenario text.

[1137] Step 5:

[1138] The server converts the generated scenario into electroencephalogram (EEG) data. This conversion uses a specialized algorithm that maps each element of the generated scenario to a corresponding EEG pattern. The input data is the scenario text, and the output is EEG data.

[1139] Step 6:

[1140] The server transmits the converted EEG data to the terminal. The terminal receives and stores the data. Communication is conducted via the secure HTTPS protocol. The input data is EEG data, and the output is data storage on the terminal.

[1141] Step 7:

[1142] The device uses sensors that monitor the timing of REM sleep to detect when the user enters REM sleep. When REM sleep is detected, it transmits stored brainwave data to the user's brain. The input data is biometric information from the sensors, and the output is the transmission of brainwave data.

[1143] Step 8:

[1144] The user's smart glasses overlay the received training scenario and monitor their emotional state in real time. The emotion engine provides feedback and advice at appropriate times. The input data is the user's emotional state, and the output is feedback corresponding to the progress of the scenario.

[1145] Step 9:

[1146] Users provide feedback after training or dream experiences. This feedback data is used to improve the accuracy of future scenario generation and the emotion engine. The input data is the user's feedback text, and the output is the application of that feedback to the system's algorithm.

[1147] 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.

[1148] 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.

[1149] 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.

[1150] [Fourth Embodiment]

[1151] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1152] 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.

[1153] 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).

[1154] 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.

[1155] 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.

[1156] 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).

[1157] 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.

[1158] 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.

[1159] 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.

[1160] 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.

[1161] 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.

[1162] 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.

[1163] 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".

[1164] System Overview

[1165] This invention is a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system consists of a user terminal, a server, a generating AI, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[1166] User input processing

[1167] Users input the elements of their dreams using a dedicated application. The application's interface is intuitive, making it easy to select scenarios and enter custom information. For example, users can input specific elements such as "underwater city," "dolphins," or "treasure hunt."

[1168] Sending and receiving data

[1169] The terminal sends the input dream elements to the server. The data is converted to JSON format and transmitted using the secure HTTPS protocol. The server, in turn, analyzes the received data and passes it to a generative AI. This AI uses a natural language processing model to generate a specific dream scenario based on the user's wishes.

[1170] Generating a dream scenario

[1171] The server's generation AI generates stories based on elements entered by the user. For example, it might generate a dream scenario such as "exploring hidden treasure at the bottom of the ocean with the help of dolphins." This scenario is presented as a series of stories, designed to be experienced naturally by the user within the dream.

[1172] Scenario conversion and transmission

[1173] (The server converts the generated dream scenario into electroencephalogram (EEG) data. The algorithm used here maps each element of the generated scenario to a corresponding EEG pattern. This converted EEG data is transmitted to the terminal via a secure communication channel.)

[1174] Receiving brainwave data and experiencing dreams

[1175] The device analyzes and stores brainwave data received from the server. Furthermore, it is equipped with a sensor that monitors the timing of REM sleep. When it detects that the user has entered REM sleep, it transmits brainwave data to the brain. This allows the user to experience their desired dreams.

[1176] Feedback function

[1177] Users provide feedback on their dreams after waking up through a dedicated application. This feedback is used as data to generate higher-quality dream scenarios in the future.

[1178] Specific example

[1179] 1. Let's say the user dreams of an "underwater adventure." They open the dedicated application and input elements such as "underwater city," "dolphins," and "treasure hunt."

[1180] 2. The device sends this data to the server.

[1181] 3. The server analyzes the received data, and the generating AI creates a dream scenario. For example, a scenario where "you encounter dolphins while exploring an underwater city and search for treasure together."

[1182] 4. The server converts this scenario into electroencephalogram (EEG) data and sends it to the terminal.

[1183] 5. The device monitors the timing of REM sleep and transmits brainwave data to the user's brain at the appropriate time.

[1184] 6. Users experience the dreams they desire, waking up with restful sleep and a positive mood.

[1185] The system of this invention aims to control dreams according to the user's wishes and provide high-quality sleep. This makes it possible to improve sleep quality, reduce stress, and wake up feeling positive.

[1186] The following describes the processing flow.

[1187] Detailed program processing flow

[1188] Step 1:

[1189] The user opens a dedicated application and enters the elements of the dream they want to see. The application's interface displays scenario options and custom input boxes, allowing the user to enter specific elements such as "underwater city," "dolphins," or "treasure hunt." Then they press the "Submit" button.

[1190] Step 2:

[1191] The terminal sends the entered dream elements to the server. This process converts the user-entered data into JSON format and sends it to the server in an encrypted format using the HTTPS protocol.

[1192] Step 3:

[1193] The server receives data transmitted via the data reception API. At this stage, it verifies the integrity and format of the data and passes it to the generating AI module for analysis.

[1194] Step 4:

[1195] The server's generation AI module generates dream scenarios based on input data. For example, using topic modeling and sequence generation models, it generates a story like "Meeting dolphins while exploring an underwater city and searching for treasure together."

[1196] Step 5:

[1197] The server converts the generated dream scenario into electroencephalogram (EEG) data. This conversion is performed using a highly specialized algorithm that maps each element of the generated story (e.g., scenes and events) to a corresponding EEG pattern.

[1198] Step 6:

[1199] The server transmits the converted EEG data to the terminal. The transmission uses an encrypted communication channel via a security protocol, ensuring secure and rapid data transfer.

[1200] Step 7:

[1201] The device analyzes the brainwave data received from the server and stores it locally. Furthermore, it uses a sensor to monitor the timing of REM sleep, and when it detects that the user has entered REM sleep, it prepares to transmit the stored brainwave data.

[1202] Step 8:

[1203] The device triggers the transmission of brainwave data to the user's brain when REM sleep is detected. This transmission occurs through a device connected to the user's brain, and dream elements are transmitted to the brain as electrical signals.

[1204] Step 9:

[1205] The user experiences a desired dream based on the electrical signals they input. After waking, they open a dedicated application to provide feedback on the dream they had. This feedback is used to improve the quality of future dream generation.

[1206] The above is the specific processing flow of the "Wake Up Refreshed! Dream Palette" system. This allows users to experience their desired dreams, achieve quality sleep, and wake up feeling refreshed.

[1207] (Example 1)

[1208] 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".

[1209] In modern society, ensuring quality sleep is a crucial issue for users. In particular, many users experience stress and anxiety, leading to an increasing number of cases where they cannot get satisfactory sleep. If users could experience dreams they desire, it would lead to mental refreshment and stress reduction, thus providing quality sleep. However, because there is no concrete system to induce such dream experiences, users are unable to freely experience the dreams they want.

[1210] 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.

[1211] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the input dream elements to a digital device, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to a digital device, means for the digital device to transmit the EEG data to the user's brain in conjunction with REM sleep, means for providing feedback on the dream the user experienced, and sensors for monitoring the timing of REM sleep. This enables the user to experience their desired dream and obtain quality sleep.

[1212] "A means of inputting the dream elements desired by the user" refers to providing an interface for users to input the dream elements they wish to experience, and a means of incorporating that input data into the system.

[1213] "Means for transmitting input dream elements to a digital device" refers to a means for converting the dream elements entered by the user into a data format and securely transmitting them to a digital device.

[1214] "Means for receiving and analyzing transmitted data" refers to a method of receiving data from a transmitted digital device, analyzing its contents, and extracting elements of dreams.

[1215] "A method for generating specific dream scenarios using generative AI" refers to a method of creating specific dream scenarios that users will experience, based on the elements of the dreams they have received, using generative AI (artificial intelligence).

[1216] "Methods for converting generated scenarios into brainwave data" refers to methods for converting generated dream scenarios into corresponding brainwave patterns so that users can actually experience the dream.

[1217] "Means for transmitting converted brainwave data to a digital device" refers to means for securely transmitting converted brainwave data to a digital device.

[1218] "A method by which a digital device transmits brainwave data to a user's brain in conjunction with REM sleep" refers to a method in which a digital device detects the user's REM sleep and sends brainwave data to the user's brain at that time.

[1219] "A means of providing feedback on dreams experienced by users" refers to a method for users to provide feedback to the system regarding their thoughts and opinions about the dreams they have experienced.

[1220] A "sensor that monitors the timing of REM sleep" is a sensor that monitors the user's sleep state and detects when the user enters REM sleep.

[1221] This invention is a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system consists of a user terminal, a server, a generating AI, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[1222] User input processing

[1223] The user launches a dedicated application and enters the elements of the dream they want to see. This application features an intuitive interface, allowing users to input their desired dream elements through text input or by selecting options. For example, they can enter "underwater city," "dolphins," or "treasure hunt."

[1224] Sending and receiving data

[1225] The terminal converts the dream elements entered by the user into JSON data and sends it to the server using the HTTPS protocol. The terminal encrypts the data using SSL / TLS to ensure its security. The server receives and analyzes the data sent from the terminal. This analysis includes data extraction and the generation of prompts for the generative AI model.

[1226] Generating dream scenarios using AI

[1227] The generation AI installed on the server generates a specific dream scenario that includes elements desired by the user, based on the received prompt text. The generation AI model uses natural language processing technology to create a story based on the elements input by the user. For example, it can generate a scenario such as "searching for treasure with dolphins in an underwater city."

[1228] Scenario conversion and transmission

[1229] The server converts the generated dream scenario into brainwave data. A specialized algorithm is used for this conversion, mapping each element of the scenario to a corresponding brainwave pattern. The brainwave data is encrypted to ensure security and transmitted to a digital device.

[1230] Receiving brainwave data and experiencing dreams

[1231] The device receives transmitted brainwave data and stores it in local storage. Furthermore, the device is equipped with a sensor that monitors the timing of REM sleep, monitoring the user's sleep state in real time. When the sensor detects the user's REM sleep, the device transmits the stored brainwave data to the user's brain. This allows the user to experience their desired dreams.

[1232] Feedback function

[1233] After waking up, users provide feedback about their dreams through a dedicated application. This feedback is used as training data for the generating AI and is reflected in the creation of future dream scenarios. This allows users to experience dreams that are more faithful to their preferences and of higher quality.

[1234] Specific example

[1235] The following are some specific examples.

[1236] 1. The user expresses a desire to experience an "underwater adventure" and opens the dedicated application.

[1237] 2. Enter specific elements such as "underwater city," "dolphins," and "treasure hunt."

[1238] 3. The device converts this data into JSON format and sends it to the server using HTTPS.

[1239] 4. The server receives and analyzes the data to generate a prompt message, which is then passed to the generating AI. The generating AI then creates a dream scenario: "While exploring an underwater city, you encounter dolphins and search for treasure together."

[1240] 5. Convert the scenario into electroencephalogram (EEG) data and transmit it to the terminal via a secure channel.

[1241] 6. The device stores brainwave data and detects the user's REM sleep, transmitting the data to the brain.

[1242] 7. Users experience the dreams they desire and provide feedback about the dreams they had.

[1243] Examples of prompts to input into a generative AI model

[1244] The following are specific examples of prompt statements to be input to a generative AI model.

[1245] "The user wants to dream about an 'underwater city,' 'dolphins,' and 'treasure hunting.' Please generate a specific dream scenario that includes these elements."

[1246] This system allows users to experience their desired dreams and get quality sleep.

[1247] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1248] Step 1:

[1249] The user launches a dedicated application and inputs the elements of the dream they want to see. This input is done through text boxes or selection lists, such as "underwater city," "dolphins," or "treasure hunt." The input data (e.g., underwater city, dolphins, treasure hunt) is then taken into the system.

[1250] Step 2:

[1251] The terminal converts the dream elements entered by the user into JSON format and sends them to the server using the HTTPS protocol. Specifically, it transforms the input data (e.g., underwater city, dolphins, treasure hunt) into a JSON structure and sends it as SSL / TLS encrypted data. The JSON formatted data is output and sent to the server via a secure communication channel.

[1252] Step 3:

[1253] The server receives JSON data sent from the terminal. It parses the received data and extracts the dream elements. Specifically, it parses the received data (e.g., {"elements":["Underwater city", "Dolphin", "Treasure hunt"]}) and extracts a list of elements. The extracted list of elements is output.

[1254] Step 4:

[1255] The server generates a prompt message for the generating AI based on the element list and passes it to the AI. The generated prompt message (e.g., "The user wants to have a dream that includes 'underwater city,' 'dolphins,' and 'treasure hunt.' Please generate a specific dream scenario that includes these elements.") is input into the generating AI model. The prompt message is output and passed to the generating AI model.

[1256] Step 5:

[1257] The generative AI generates a specific dream scenario that includes elements desired by the user, based on the given prompt text. Specifically, the generative AI model receives the prompt text as input and performs natural language processing to generate a scenario such as "Meeting a dolphin while exploring an underwater city and searching for treasure together." The generated scenario is then output.

[1258] Step 6:

[1259] The server converts the generated dream scenario into brainwave data. It uses a conversion algorithm that maps each scene and element of the scenario to the corresponding brainwave pattern. The scenario received as input (e.g., "While exploring an underwater city, I meet a dolphin and we search for treasure together") is converted into a brainwave pattern, and the brainwave data is output.

[1260] Step 7:

[1261] The server transmits the converted EEG data to the terminal via a secure communication channel. Data security is ensured by sending the EEG data to the terminal using encrypted communication. As output, encrypted EEG data is sent to the terminal.

[1262] Step 8:

[1263] The device saves the received brainwave data to local storage. Furthermore, the device is equipped with a sensor that monitors the timing of REM sleep. This sensor analyzes the user's brainwaves in real time and detects when the user enters REM sleep. Upon detecting REM sleep, the stored brainwave data is output and transmitted to the user's brain.

[1264] Step 9:

[1265] The user receives brainwave data transmitted from the device during REM sleep. This allows them to experience a dream where they "encounter dolphins while exploring an underwater city and search for treasure together." Because the user's brain shapes the dream according to the received brainwave data, the user can experience the dream they desire.

[1266] Step 10:

[1267] After waking up, users provide feedback about their dreams through a dedicated application. This feedback includes details and impressions of the dream. This feedback data is sent to the server as learning data to be used in future scenario generation. This allows the system to provide higher-quality dreams.

[1268] (Application Example 1)

[1269] 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".

[1270] Conventional dream induction systems were designed for individual users to use at home, and therefore did not consider use in physical establishments such as relaxation facilities and spas. As a result, there was a lack of means to significantly improve the customer experience in these physical locations. Furthermore, there was no system that allowed customers in relaxation facilities to easily input their desired dreams and experience them as actual dreams. In addition, there were no means to efficiently induce dreams for multiple customers, resulting in a limited quality of customer experience.

[1271] 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.

[1272] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the inputted dream elements to the server, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI based on the analyzed data, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to the user's terminal, means for the terminal to transmit the EEG data to the user's brain in conjunction with REM sleep, means for the customer to input dream elements using an input device in the store, means for the input device to transmit the dream elements to the server, means for the server to convert the data into EEG data based on the dream scenario and transmit it to a relaxation device, and means for the relaxation device to transmit the EEG data to the user's brain during REM sleep. This makes it possible to allow users to experience dreams based on their individual preferences in a physical store, significantly improving the quality of the customer experience at relaxation facilities. It also makes it possible to efficiently and effectively induce dreams for multiple customers.

[1273] A "user" refers to an individual who uses the system to experience their dreams.

[1274] "Dream elements" are the elements that make up the specific scenarios and situations that users input in their dreams that they want to experience.

[1275] A "server" refers to a computer system that receives data sent by users and uses AI for analysis and generation to create dream scenarios.

[1276] "Generative AI" refers to an artificial intelligence model that generates specific dream scenarios based on the elements of a dream that are input.

[1277] A "scenario" refers to a series of events that form the specific story or scenes that a user experiences in their dreams.

[1278] "Electrical wave data" refers to the brainwave patterns that have been converted to allow the user to experience the generated dream scenario.

[1279] A "terminal" refers to a device used by a user that has the function of receiving brainwave data transmitted from a server and transmitting it to the user's brain.

[1280] "REM sleep" refers to the primary sleep stage in which users dream, and it is possible to induce dreams by transmitting brainwave data during this time.

[1281] An "input device" refers to a device used by users to input elements of their dreams, and is typically installed in physical stores or other similar locations.

[1282] A "relaxation device" refers to a device that has the function of appropriately transmitting brainwave data to the user and providing a dream-like experience.

[1283] This invention is a system that allows users to experience their desired dreams during REM sleep. This system works by having the user input elements of their dream, and then a generating AI uses that information to create a specific dream scenario, which is then transmitted to the user as brainwave data.

[1284] System Configuration

[1285] 1. Processing user input

[1286] Users input the elements of their desired dream using a dedicated input device. The input device is installed in physical relaxation facilities, and its user interface is intuitive, making it easy to select scenarios and customize inputs. For example, users can input specific elements such as "beach," "exotic forest," or "quiet mountain lake."

[1287] 2. Sending and receiving data

[1288] The input device sends the input dream elements to the server. The data is converted to JSON format and transmitted using the secure HTTPS protocol. The server analyzes the received data and passes it to a generative AI. This AI uses a natural language processing model to generate a specific dream scenario based on the user's wishes.

[1289] 3. Generating a dream scenario

[1290] The server's generation AI creates stories based on the elements entered by the user. For example, it might generate a dream scenario such as "You standing by a quiet mountain lake." This scenario is presented in a narrative format and is designed to be experienced naturally by the user within the dream.

[1291] 4. Scenario conversion and transmission

[1292] The server converts the generated dream scenario into electroencephalogram (EEG) data. The generative AI model used here maps each element of the generated scenario to a corresponding EEG pattern. This converted EEG data is transmitted to the relaxation device via a secure communication channel.

[1293] 5. Receiving EEG data and experiencing dreams

[1294] The relaxation device analyzes and stores brainwave data received from a server. Furthermore, it is equipped with a sensor that monitors the timing of REM sleep. When it detects that the user has entered REM sleep, it transmits brainwave data to the brain. This allows the user to experience their desired dreams.

[1295] Hardware and software to be used

[1296] Input device: A device for customers to input elements of their dreams. It is installed in physical stores.

[1297] Server: A computer system that receives dream elements, analyzes them, and generates dream scenarios using a generative AI.

[1298] Generative AI: A natural language processing model that creates dream scenarios based on dream elements entered by the user.

[1299] Relaxation device: A device that monitors the timing of REM sleep and transmits brainwave data.

[1300] Specific example

[1301] The customer inputs elements of their desired dream, such as "I want to relax by a quiet mountain lake," into an input device at the relaxation facility. The input device sends this data to a server, which generates a scenario of "themselves standing by a quiet mountain lake." The generated scenario is converted into brainwave data and sent to the relaxation device. The relaxation device monitors the customer's REM sleep and sends brainwave data at the appropriate time.

[1302] Example of a prompt

[1303] The user entered "I want to relax by a quiet mountain lake." Based on this, generate a dream scenario that will help the user relax.

[1304] This format allows users to significantly enhance their experience at relaxation facilities and provides dream experiences tailored to their individual preferences.

[1305] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1306] Step 1: The user enters the elements of their dream.

[1307] Users access an input device installed in a physical store and input elements of their dream experience (e.g., "beach," "exotic forest," "quiet mountain lake"). The input device interface is intuitive, allowing users to easily select or customize their desired elements. The input data is in text format.

[1308] Step 2: Submit the input data

[1309] The input device sends the dream elements entered by the user to the server. The input data is converted to JSON format and sent to the server using the secure HTTPS protocol. An example of input data is {"dream_elements": ["beach", "exotic forest", "quiet mountain lake"]}.

[1310] Step 3: Data reception and analysis

[1311] The server receives data transmitted from the input device. The received data is analyzed and used as material to generate specific dream scenarios based on the user's wishes. This analysis involves examining the structure of the received data and extracting its elements.

[1312] Step 4: Generating dream scenarios using a generative AI

[1313] The server passes the analyzed data to the generative AI. The generative AI model uses natural language processing to generate specific dream scenarios based on the input data. For example, if the user input is "I want to relax by a quiet mountain lake," the generated scenario might be something like "I am standing by a quiet mountain lake."

[1314] Step 5: Converting the scenario's EEG data

[1315] The server converts the generated dream scenario into brainwave data. The generating AI model maps each element of the output scenario to the corresponding brainwave pattern, generating brainwave data that the user can experience as a dream. This converted data is in binary format.

[1316] Step 6: Sending EEG data

[1317] The server transmits the converted EEG data to the relaxation device. The EEG data is sent to the relaxation device using a secure communication channel. The transmitted data is stored in the device's memory.

[1318] Step 7: Monitoring REM sleep

[1319] The relaxation device monitors the user's REM sleep timing using built-in sensors. The sensors analyze brainwave patterns in real time to detect when the user enters REM sleep. Electrodes-based electroencephalogram (EEG) measurement devices and heart rate monitors are used to determine REM sleep.

[1320] Step 8: Sending EEG data and inducing dreams

[1321] After the relaxation device detects the timing of REM sleep, it transmits the received brainwave data to the user's brain. This allows the user to experience the dream they desire. The data transmission is performed using a dedicated brainwave transmission function.

[1322] This series of processes allows users to experience customized dreams at relaxation facilities, providing them with high-quality relaxation.

[1323] 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.

[1324] System Overview

[1325] This invention incorporates an emotion engine into a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system recognizes the user's emotional state and selects and adjusts dreams based on that state. The system consists of a user terminal, a server, a generation AI, an emotion engine, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[1326] User input processing

[1327] Users input the elements of their desired dream using a dedicated application. The application interface displays scenario options and custom input boxes, allowing users to enter specific elements such as "underwater city," "dolphins," and "treasure hunt." Furthermore, an emotion engine analyzes the user's emotional state, and suggests dream elements based on the results.

[1328] How the emotion engine works

[1329] The device collects emotion analysis data to recognize the user's emotional state. This data is obtained, for example, through voice analysis, facial expression analysis, and biometric data analysis from wearable devices. The collected emotion data is sent from the device to a server and analyzed by an emotion engine.

[1330] Analysis and proposals regarding emotional data

[1331] The server's emotion engine analyzes the received emotion data to identify the user's current emotional state. Based on the analyzed emotional state, it suggests the most suitable dream elements. These suggestions are returned to the user's device and displayed in the application. The user then decides whether to accept the suggested elements or enter custom elements.

[1332] Sending and receiving data

[1333] The device sends the elements of the dream that the user has finally decided on to the server. The data is converted to JSON format and transmitted in an encrypted format using the secure HTTPS protocol. Meanwhile, the server analyzes the received data and passes it to a generative AI. This generative AI uses a natural language processing model to generate a specific dream scenario based on the user's wishes.

[1334] Generating a dream scenario

[1335] The server's AI generates dream scenarios based on user input and emotional data. For example, it might generate a dream scenario such as "encountering dolphins while exploring an underwater city and searching for treasure together." This scenario can be customized to match the user's emotional state.

[1336] Scenario conversion and transmission

[1337] The server converts the generated dream scenario into electroencephalogram (EEG) data. This conversion is performed using a specialized algorithm that maps each element of the generated scenario (e.g., scenes and events) to the corresponding EEG pattern. The converted EEG data is then transmitted to the terminal via a secure communication channel.

[1338] Receiving brainwave data and experiencing dreams

[1339] The device analyzes and stores brainwave data received from the server. It also uses a sensor to monitor the timing of REM sleep, and when it detects that the user has entered REM sleep, it transmits the stored brainwave data to the brain.

[1340] Feedback function

[1341] Users provide feedback on their dreams after waking up through a dedicated application. This feedback data is used to improve the accuracy of the dream generation algorithm and emotion engine for future use.

[1342] Specific example

[1343] 1. The user expresses a desire for an "underwater adventure," opens the application, and inputs elements such as "underwater city," "dolphins," and "treasure hunt." Suggestions from the emotion engine are also considered.

[1344] 2. The device sends this data and sentiment data to the server.

[1345] 3. The server analyzes the received data, and the generating AI creates a dream scenario. For example, a scenario where "you encounter dolphins while exploring an underwater city and search for treasure together."

[1346] 4. The server converts this scenario into electroencephalogram (EEG) data and sends it to the terminal.

[1347] 5. The device monitors the timing of REM sleep and transmits brainwave data to the user's brain at the appropriate time.

[1348] 6. Users can have the dreams they desire and enjoy restful sleep.

[1349] The system of this invention aims to control dreams according to the user's wishes and provide high-quality sleep. Furthermore, by utilizing an emotion engine, it is possible to provide an optimal dream experience tailored to the user's emotional state.

[1350] The following describes the processing flow.

[1351] Specific processing flow of the program

[1352] Step 1:

[1353] The user opens a dedicated application and enters the elements of the dream they want to see. The application interface displays scenario options and custom input boxes, allowing the user to enter specific elements such as "underwater city," "dolphins," or "treasure hunt," and then press the "Submit" button.

[1354] Step 2:

[1355] The device collects the user's emotional state using voice input, facial recognition, or biometric data acquired from wearable devices. The collected data is sent to the emotion engine in real time.

[1356] Step 3:

[1357] The device converts the user's emotional data and dream elements into JSON format and sends them to the server using the secure HTTPS protocol.

[1358] Step 4:

[1359] The server receives data sent via the data reception API. It verifies the integrity and format of the data and passes it to the emotion engine. The emotion engine analyzes the user's emotional state and suggests the most suitable dream elements based on the results. This suggestion is returned to the user's device.

[1360] Step 5:

[1361] The user reviews and modifies dream elements based on suggestions from the emotion engine. For example, if the emotion engine suggests "relaxing underwater exploration," the user can add "treasure hunting."

[1362] Step 6:

[1363] The device then sends the finalized dream elements back to the server. This data is converted to JSON format and transmitted using a secure communication channel.

[1364] Step 7:

[1365] The server analyzes the received dream element data and passes it to the generating AI. The generating AI then generates a specific dream scenario based on this data. For example, it might generate a scenario such as, "While exploring an underwater city, you encounter a dolphin and search for treasure together."

[1366] Step 8:

[1367] The server converts the generated scenario into electroencephalogram (EEG) data. This conversion is performed using a specialized algorithm that maps each element of the generated scenario (e.g., scenes and events) to the corresponding EEG pattern. The converted EEG data is transmitted to the terminal via a secure communication channel.

[1368] Step 9:

[1369] The device analyzes and stores brainwave data received from the server. Furthermore, it is equipped with a sensor that monitors the timing of REM sleep. When it detects that the user has entered REM sleep, it prepares to transmit the stored brainwave data to the brain.

[1370] Step 10:

[1371] The device triggers the transmission of brainwave data to the user's brain when REM sleep is detected. This transmission occurs through a device connected to the user's brain, and dream elements are transmitted to the brain as electrical signals.

[1372] Step 11:

[1373] The user experiences a desired dream based on the electrical signals they input. For example, they might dream of "searching for treasure with dolphins in an underwater city." After waking, they open a dedicated application to provide feedback on their dream. This feedback is used to improve the accuracy of the dream generation algorithm and emotion engine for future sessions.

[1374] (Example 2)

[1375] 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".

[1376] To improve sleep quality, there is a need for a system that allows users to experience dreams of their choice. However, conventional technology has been unable to adjust dream content based on the user's emotional state, making it difficult to provide dreams optimized for the user's psychological state. Furthermore, there was a lack of mechanisms to collect feedback on the dreams users experienced and use that feedback to improve the system's accuracy. In addition, the lack of a means to accurately detect the timing of REM sleep made it difficult to provide an effective dream experience.

[1377] 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.

[1378] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the input dream elements to the server, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI based on the analyzed data, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to the user's terminal, means for the terminal to transmit the EEG data to the user's brain in conjunction with REM sleep, means for collecting and analyzing the user's emotional data, and means for suggesting dream elements based on the analyzed emotional data. This makes it possible to allow the user to experience the content of their desired dream and to provide a dream optimized for their emotional state at the time. Furthermore, feedback on the dreams seen can be collected and used to improve the accuracy of the system. In addition, by accurately detecting the timing of REM sleep, a more effective dream experience can be provided to the user.

[1379] A "user" is the individual who uses the system to input the content of their desired dream and then experiences that dream.

[1380] "Dream elements" refer to specific scenarios, scenes, characters, themes, etc., that users want to experience.

[1381] The "server" is a central processing unit that analyzes data sent by users, generates dream scenarios using a generative AI and emotion engine, and converts those scenarios into brainwave data for transmission.

[1382] A "terminal" is a device that the user directly operates, and it is a device that inputs dream elements, collects emotional data, monitors REM sleep, and transmits brainwave data.

[1383] "Emotional data" refers to data that indicates a user's current emotional state, and includes information collected through voice analysis, facial expression analysis, and biometric data analysis from wearable devices.

[1384] The "emotion engine" is a software component that analyzes collected emotional data and, based on the results, suggests the most suitable dream elements to the user.

[1385] "Generative AI" is an artificial intelligence model that generates specific dream scenarios based on received data and analyzed emotional data.

[1386] "Electroencephalogram (EEG) data" refers to data that has been converted to transmit the generated dream scenario to the user's brain, and is expressed as an EEG pattern.

[1387] "REM sleep" is a deep stage of sleep in which users are more likely to dream, and brainwave data is transmitted during this time to induce the desired dream.

[1388] "Feedback" refers to information provided by users through a dedicated application, detailing the content and their impressions of their dreams. This information helps improve the accuracy of future dream generation.

[1389] A "sensor" is a device used to monitor the timing of a user's REM sleep.

[1390] Modes for carrying out the invention

[1391] System Configuration

[1392] This invention incorporates an emotion engine into a system that allows users to input desired dream elements and experience those dreams during REM sleep. The system recognizes the user's emotional state and selects and adjusts dreams based on that state. The system consists of a user terminal, a server, a generation AI, an emotion engine, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[1393] User input processing

[1394] The user launches a dedicated application and enters the elements of the dream they want to see into the interface. Fields are provided for entering specific elements such as "underwater city," "dolphins," and "treasure hunt." Once the user has finished entering the information, the device collects this data.

[1395] How the emotion engine works

[1396] The device simultaneously collects emotional data. For this data collection, the device is equipped with voice analysis, facial expression analysis, and biometric data analysis functions for wearable devices. The collected emotional data is transmitted from the device to a server.

[1397] Analysis and proposals regarding emotional data

[1398] The server's emotion engine analyzes the received emotion data to identify the user's current emotional state. Based on the analysis, it suggests the most suitable dream elements. These suggestions are sent back from the server to the terminal and displayed in the application for the user to review. The user then decides whether to accept the suggested elements or enter new custom elements.

[1399] Generating a dream scenario

[1400] The device sends the elements of the dream that the user has finally decided on to the server. This transmission is converted to JSON format and performed using the secure HTTPS protocol. The server parses the received data and passes it on to the generative AI. The generative AI uses a natural language processing model to generate a specific dream scenario.

[1401] For example, it can generate a specific scenario such as, "While exploring an underwater city, you encounter dolphins and search for treasure together."

[1402] Scenario conversion and transmission

[1403] The server converts the generated dream scenario into electroencephalogram (EEG) data. This conversion process uses a specialized algorithm that maps each element of the generated scenario (e.g., scenes and events) to a corresponding EEG pattern. The converted EEG data is then transmitted to the terminal via a secure communication channel.

[1404] Dream experience

[1405] The device analyzes and stores brainwave data received from the server. It also uses a sensor to monitor the timing of REM sleep, and when it detects that the user has entered REM sleep, it transmits the stored brainwave data to the brain. As a result, the user experiences the dream they desired.

[1406] Feedback function

[1407] Users provide feedback on their dreams after waking up through a dedicated application. This feedback data is used to improve the accuracy of the dream generation algorithm and emotion engine for future use.

[1408] Examples of specific cases and prompt statements

[1409] Specifically, a user might express a desire for an "underwater adventure" and use the application to input elements such as "underwater city," "dolphins," and "treasure hunt." The device sends this data, along with emotional data, to a server, which analyzes it, and a generating AI creates a dream scenario. For example, a scenario might be generated where the user "encounters dolphins while exploring an underwater city and searches for treasure together." The server converts this scenario into brainwave data and sends it to the device. The device monitors the timing of REM sleep and sends the brainwave data to the user's brain at the appropriate time. The user then experiences the dream they desired and enjoys a fulfilling sleep.

[1410] An example of a prompt message is as follows:

[1411] Enter dream elements such as "underwater city," "dolphins," and "treasure hunt." Also, check the elements suggested by the emotion engine.

[1412] By using such a system, it is possible to provide dreams tailored to the user's preferences and support quality sleep. Furthermore, by utilizing an emotion engine, users can obtain a dream experience optimized for their emotional state.

[1413] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1414] Step 1: Enter the user's desired elements.

[1415] The user launches a dedicated application and enters the elements of the dream they want to see into the interface. Fields are provided for entering specific elements such as "underwater city," "dolphins," and "treasure hunt."

[1416] Input: Elements of the dream entered by the user into a dedicated application.

[1417] Output: Dream element data held on the device.

[1418] Operation: The user enters specific dream elements in text format into the application's input field and presses the submit button.

[1419] Step 2: Collecting emotional data

[1420] The device performs voice analysis, facial expression analysis, and biometric data analysis from wearable devices to recognize the user's emotional state.

[1421] Input: User's voice, facial expressions, and biometric data from wearable devices.

[1422] Output: Analyzed sentiment data.

[1423] Operation: Collects user emotion data using the device's built-in camera, microphone, and wearable sensors. This data is then temporarily stored.

[1424] Step 3: Sending emotional data

[1425] The device sends the collected emotional data to the server. This transmission uses the secure HTTPS protocol, and the data is encrypted.

[1426] Input: Collected sentiment data.

[1427] Output: Sentiment data sent to the server.

[1428] Operation: The device encrypts the emotional data using the HTTPS protocol and sends it to the server.

[1429] Step 4: Analysis of emotional data

[1430] The server passes the received emotional data to the emotion engine for analysis. The emotion engine uses natural language processing and machine learning algorithms to identify the user's emotional state.

[1431] Input: Received emotion data.

[1432] Output: Analyzed emotional state.

[1433] Operation: The emotion engine uses algorithms to analyze the user's emotional data item by item and identify their current emotional state.

[1434] Step 5: Propose elements of the dream

[1435] The server's emotion engine suggests the most suitable dream elements based on the analysis results. This suggestion is converted to JSON format and sent to the terminal via a secure channel.

[1436] Input: Analyzed emotional state.

[1437] Output: Dream element proposal data.

[1438] Operation: The emotion engine selects the most suitable dream elements for the user based on the analysis results, converts them into JSON format, and sends them to the device.

[1439] Step 6: View and select suggestions

[1440] The device displays the received suggestions to the user. The user then decides whether to accept the suggested elements or enter custom elements.

[1441] Input: Data on the elements of the proposed dream.

[1442] Output: User's final selection data.

[1443] Operation: The device displays the received suggestions in the application interface, and the user confirms and selects them.

[1444] Step 7: Submit selected elements

[1445] The terminal sends the finalized dream elements to the server. This transmission also uses the secure HTTPS protocol.

[1446] Input: User's last selected data.

[1447] Output: Dream element data sent to the server.

[1448] Operation: Converts the dream elements selected by the user into JSON format and sends them to the server using the HTTPS protocol.

[1449] Step 8: Generating dream scenarios using a generative AI

[1450] The server analyzes the received dream elements and passes them to the generative AI. The generative AI uses a natural language processing model to generate a specific dream scenario.

[1451] Input: User's dream element data.

[1452] Output: The generated dream scenario.

[1453] Operation: The generating AI applies a specific algorithm based on the received data to generate dream scenarios such as "Meeting dolphins while exploring an underwater city and searching for treasure together."

[1454] Step 9: Converting the scenario into EEG data

[1455] The server converts the generated dream scenario into brainwave data. Using specialized algorithms, it maps each scene and event to a brainwave pattern.

[1456] Input: The generated dream scenario.

[1457] Output: Converted electroencephalogram (EEG) data.

[1458] Operation: Analyze the generated scenario and apply an algorithm to convert it into electroencephalogram (EEG) data.

[1459] Step 10: Sending EEG data

[1460] The server transmits the converted EEG data to the terminal. This transmission also uses a secure communication channel.

[1461] Input: Converted electroencephalogram (EEG) data.

[1462] Output: EEG data transmitted to the terminal.

[1463] Operation: Transmits EEG data to the terminal via a secure channel.

[1464] Step 11: Monitoring REM sleep

[1465] The device uses sensors to monitor the timing of REM sleep.

[1466] Input: User's sleep status data.

[1467] Output: REM sleep timing detection information.

[1468] Operation: The device continuously monitors the user's sleep state using a REM sleep monitoring sensor.

[1469] Step 12: Sending EEG data

[1470] When the device detects that the user has entered REM sleep, it transmits the stored brainwave data to the user's brain.

[1471] Input: REM sleep timing detection information and stored electroencephalogram (EEG) data.

[1472] Output: Brainwave data transmitted to the user's brain.

[1473] Operation: When REM sleep is detected, the stored electroencephalogram (EEG) data is transmitted to the user's brain.

[1474] Step 13: Provide feedback on your dream

[1475] Users provide feedback about their dreams after waking up through a dedicated application. This feedback data is used to improve the accuracy of the system.

[1476] Input: User feedback information.

[1477] Output: Collected feedback data.

[1478] Operation: Users input their thoughts and evaluations about the content of their dreams using a dedicated application, and this information is sent to the server.

[1479] (Application Example 2)

[1480] 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".

[1481] Conventional systems have found it difficult to individually customize users' dream experiences and lacked sufficient functionality to adjust dream elements based on emotional states. Furthermore, providing feedback based on actual experience was challenging in employee customer service and negotiation skills training. This invention proposes a system that solves these problems and provides optimal dream experiences and training based on the user's emotional state.

[1482] 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.

[1483] In this invention, the server includes means for inputting dream elements desired by the user, means for transmitting the input dream elements to the server, means for receiving and analyzing the transmitted data, means for generating a specific dream scenario using a generative AI based on the analyzed data, means for converting the generated scenario into electroencephalogram (EEG) data, means for transmitting the converted EEG data to the user's terminal, means for the terminal to transmit the EEG data to the user's brain in accordance with REM sleep, means for recognizing and analyzing the user's emotional state, and means for adjusting the dream scenario based on the analyzed emotional data. This makes it possible to adjust the dream experience and training scenario based on the user's emotional state.

[1484] A "user" refers to someone who uses this system to customize their dream experiences and training scenarios.

[1485] "Dream elements" refer to specific items or situations that users want to include in their desired dreams or training scenarios.

[1486] A "server" refers to a central system that receives, analyzes, and processes data sent by users.

[1487] "Means of input" refers to the interface or device that allows the user to input elements of their dreams into the system.

[1488] "Means of transmission" refers to the means of communication used to send the input dream elements to the server.

[1489] "Means for receiving and analyzing" refers to the software and hardware used by the server to receive transmitted data and analyze it.

[1490] "Generative AI" refers to artificial intelligence that uses natural language processing models to generate specific dream scenarios.

[1491] "Means of conversion" refers to algorithms and systems for converting the generated dream scenarios into brainwave data.

[1492] A "terminal" refers to a device used by a user, specifically equipment that receives and transmits electroencephalogram (EEG) data.

[1493] "REM sleep" refers to the period of time when a user enters a deep sleep state, a time when they are more likely to dream.

[1494] "Emotional state" refers to the user's current emotional state and is analyzed from voice, facial expressions, biometric data, and other sources.

[1495] "Means of recognition and analysis" refers to software and hardware for identifying and analyzing a user's emotional state.

[1496] "Means of adjustment" refers to a system for optimizing dream scenarios and training scenarios based on analyzed emotional data.

[1497] This invention provides a system that allows users to input desired dream elements and experience them during REM sleep, as well as a function to recognize emotional states and adjust training scenarios. The system consists of a user terminal, a server, a generative AI, an emotion engine, an electroencephalogram (EEG) data conversion device, and a REM sleep monitoring sensor.

[1498] Users access a dedicated application using smart glasses and input elements of the dream or training scenario they wish to experience. For example, for a customer service skills training scenario, they might input specific elements such as "handling complaints" and "product description." The emotion engine analyzes the user's emotional state and displays suggestions for the most suitable training scenario based on the results.

[1499] Smart glasses collect the user's voice, facial expressions, and biometric data and send it to an emotion engine. The emotion engine uses Azure Cognitive Services' emotion recognition API to analyze this data and identify the user's current emotional state. The collected emotional data and user preferences are sent to a server, where a generative AI (e.g., OpenAI's GPT-3) generates specific scenarios based on prompts.

[1500] The server converts the generated scenario into electroencephalogram (EEG) data and sends it to the user's terminal using a secure communication channel (HTTPS). The terminal uses sensors to monitor the timing of REM sleep and transmits EEG data when the user enters REM sleep.

[1501] Furthermore, in training scenarios, the received scenario is overlaid on the smart glasses. The smart glasses monitor the user's emotional state in real time and provide appropriate advice and feedback as the scenario progresses.

[1502] As a concrete example, consider a case where a user requests a training scenario for "handling customer complaints." In this case, the user opens the application and types "handling complaints." Emotional data obtained from voice and facial expressions is sent to the server, and the generating AI creates a "customer complaint dialogue scenario." For example, a scenario is generated in which "a customer complains about a product defect, and the user learns specific ways to handle it," and this is converted into brainwave data. Furthermore, the progress of the training is adjusted and appropriate feedback is provided based on the emotional data collected in real time.

[1503] The following are specific examples of prompt statements for generative AI models:

[1504] "The user's desired scenario is 'handling a complaint,' and their emotional state is 'feeling stressed.' Please generate an appropriate training scenario."

[1505] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1506] Step 1:

[1507] Users input elements of their desired dreams or training scenarios through a dedicated application for smart glasses. For example, they might input specific elements such as "handling customer complaints" or "product description." The input data includes elements specified in text format.

[1508] Step 2:

[1509] The terminal sends the data entered by the user to the server. The data sent includes the elements requested by the user and is sent to the server in JSON format.

[1510] Step 3:

[1511] The server receives the transmitted data and performs analysis. This analysis includes emotion recognition, which is performed using the user's voice and facial expression data. Specifically, it calls the Azure Cognitive Services emotion recognition API to generate emotion data as an analysis result. The input data is voice and image data, and the output is a tag or score indicating the emotional state.

[1512] Step 4:

[1513] The server uses a generative AI model to generate specific scenarios based on the analyzed emotional data and the user's desired elements. In this process, it uses OpenAI's GPT-3 to create prompts such as: "The user's desired scenario is 'Handling a complaint,' and their emotional state is 'Feeling stressed.' Please generate an appropriate training scenario." The output data generated by the generative AI is the specific scenario text.

[1514] Step 5:

[1515] The server converts the generated scenario into electroencephalogram (EEG) data. This conversion uses a specialized algorithm that maps each element of the generated scenario to a corresponding EEG pattern. The input data is the scenario text, and the output is EEG data.

[1516] Step 6:

[1517] The server transmits the converted EEG data to the terminal. The terminal receives and stores the data. Communication is conducted via the secure HTTPS protocol. The input data is EEG data, and the output is data storage on the terminal.

[1518] Step 7:

[1519] The device uses sensors that monitor the timing of REM sleep to detect when the user enters REM sleep. When REM sleep is detected, it transmits stored brainwave data to the user's brain. The input data is biometric information from the sensors, and the output is the transmission of brainwave data.

[1520] Step 8:

[1521] The user's smart glasses overlay the received training scenario and monitor their emotional state in real time. The emotion engine provides feedback and advice at appropriate times. The input data is the user's emotional state, and the output is feedback corresponding to the progress of the scenario.

[1522] Step 9:

[1523] Users provide feedback after training or dream experiences. This feedback data is used to improve the accuracy of future scenario generation and the emotion engine. The input data is the user's feedback text, and the output is the application of that feedback to the system's algorithm.

[1524] 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.

[1525] 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.

[1526] 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.

[1527] 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.

[1528] 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.

[1529] 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.

[1530] 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.

[1531] 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.

[1532] 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."

[1533] 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.

[1534] 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.

[1535] 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.

[1536] 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.

[1537] 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.

[1538] 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.

[1539] 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.

[1540] 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.

[1541] 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.

[1542] 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.

[1543] 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.

[1544] 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.

[1545] The following is further disclosed regarding the embodiments described above.

[1546] (Claim 1)

[1547] A means for users to input the elements of their desired dream,

[1548] A means of sending the input dream elements to the server,

[1549] A means for receiving and analyzing transmitted data,

[1550] A means of generating specific dream scenarios using a generative AI based on analyzed data,

[1551] A means of converting the generated scenario into electroencephalogram data,

[1552] A means of transmitting the converted brainwave data to the user's terminal,

[1553] A means by which the device transmits brainwave data to the user's brain in accordance with REM sleep,

[1554] A system that includes this.

[1555] (Claim 2)

[1556] The system according to claim 1, comprising means for providing feedback about the dreams the user has had.

[1557] (Claim 3)

[1558] The system according to claim 1, comprising a sensor that monitors the timing of REM sleep.

[1559] "Example 1"

[1560] (Claim 1)

[1561] A means for users to input the elements of their desired dream,

[1562] A means of transmitting the input dream elements to a digital device,

[1563] A means for receiving and analyzing transmitted data,

[1564] A means of generating specific dream scenarios using a generative AI based on analyzed data,

[1565] A means of converting the generated scenario into electroencephalogram data,

[1566] A means for transmitting the converted brainwave data to a digital device,

[1567] A means by which a digital device transmits brainwave data to the user's brain in accordance with REM sleep,

[1568] A system that includes this.

[1569] (Claim 2)

[1570] The system according to claim 1, comprising means for providing feedback about the dreams the user has had.

[1571] (Claim 3)

[1572] The system according to claim 1, comprising a sensor that monitors the timing of REM sleep.

[1573] "Application Example 1"

[1574] (Claim 1)

[1575] A means for users to input the elements of their desired dream,

[1576] A means of sending the input dream elements to the server,

[1577] A means for receiving and analyzing transmitted data,

[1578] A means of generating specific dream scenarios using a generative AI based on analyzed data,

[1579] A means of converting the generated scenario into electroencephalogram data,

[1580] A means of transmitting the converted brainwave data to the user's terminal,

[1581] A means by which the device transmits brainwave data to the user's brain in accordance with REM sleep,

[1582] A means by which customers input elements of their dreams using an input device in the store,

[1583] The input device includes means for transmitting the dream elements to the server,

[1584] A server converts the aforementioned data into electroencephalogram (EEG) data based on a dream scenario and transmits it to a relaxation device.

[1585] A relaxation device provides a means for transmitting brainwave data to the user's brain during REM sleep,

[1586] A system that includes this.

[1587] (Claim 2)

[1588] The system according to claim 1, comprising means for providing feedback about the dreams the user has had.

[1589] (Claim 3)

[1590] The system according to claim 1, comprising a sensor that monitors the timing of REM sleep.

[1591] "Example 2 of combining an emotion engine"

[1592] (Claim 1)

[1593] A means for users to input the elements of their desired dream,

[1594] A means of sending the input dream elements to the server,

[1595] A means for receiving and analyzing transmitted data,

[1596] A means of generating specific dream scenarios using a generative AI based on analyzed data,

[1597] A means of converting the generated scenario into electroencephalogram data,

[1598] A means of transmitting the converted brainwave data to the user's terminal,

[1599] A means by which the device transmits brainwave data to the user's brain in accordance with REM sleep,

[1600] A means for collecting and analyzing user sentiment data,

[1601] A method for proposing dream elements based on analyzed emotional data,

[1602] A system that includes this.

[1603] (Claim 2)

[1604] The system according to claim 1, comprising means for providing feedback about the dreams the user has had.

[1605] (Claim 3)

[1606] The system according to claim 1, comprising a sensor that monitors the timing of REM sleep.

[1607] "Application example 2 when combining with an emotional engine"

[1608] (Claim 1)

[1609] A means for users to input the elements of their desired dream,

[1610] A means of sending the input dream elements to the server,

[1611] A means for receiving and analyzing transmitted data,

[1612] A means of generating specific dream scenarios using a generative AI based on analyzed data,

[1613] A means of converting the generated scenario into electroencephalogram data,

[1614] A means of transmitting the converted brainwave data to the user's terminal,

[1615] A means by which the device transmits brainwave data to the user's brain in accordance with REM sleep,

[1616] A means of recognizing and analyzing the emotional state of users,

[1617] A means of adjusting dream scenarios based on analyzed emotional data,

[1618] A system that includes this.

[1619] (Claim 2)

[1620] The system according to claim 1, comprising means for providing feedback about the dreams the user has had.

[1621] (Claim 3)

[1622] The system according to claim 1, comprising a sensor that monitors the timing of REM sleep.

[1623] (Claim 4)

[1624] The system according to claim 1, comprising means for supporting customer service and negotiation skills training based on the emotional state of the user. [Explanation of symbols]

[1625] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to input the elements of their desired dream, A means of sending the input dream elements to the server, A means for receiving and analyzing transmitted data, A means of generating specific dream scenarios using a generative AI based on analyzed data, A means of converting the generated scenario into electroencephalogram data, A means of transmitting the converted brainwave data to the user's terminal, A means by which the device transmits brainwave data to the user's brain in accordance with REM sleep, A system that includes this.

2. The system according to claim 1, comprising means for providing feedback about the dreams the user has had.

3. The system according to claim 1, comprising a sensor that monitors the timing of REM sleep.

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