system

Abstract

We provide the system. [Solution] A means of entering meal information, A computer including a generative model that automatically generates tableware designs based on input meal information, A means of transmitting and displaying the generated design information on tableware equipped with a display, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, the method 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 as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In order to enrich the dining experience, visual elements are important. However, preparing tableware suitable for various meals in ordinary households and restaurants places a great burden in terms of cost and management. In particular, it is desired to solve the problem that it is difficult to prepare tableware with an appropriate design for each different meal.

Means for Solving the Problems

[0005] This invention solves these problems by providing a means for inputting meal information and constructing a system that automatically generates tableware designs using a generation AI model based on the input meal information. Furthermore, by providing a means for transmitting and displaying the generated design information on tableware equipped with a display, it becomes possible to easily provide tableware that visually harmonizes with the meal. As a result, users can enjoy the optimal tableware design for each different meal, thereby improving their dining experience.

[0006] "Dietary information" refers to data that shows the content and type of meals, as well as related supplementary information.

[0007] "Input methods" refer to devices or interfaces used by users to provide information or data to a system.

[0008] A "generative model" is an algorithm or program that automatically generates tableware designs based on given data.

[0009] An "electronic computer" refers to a computer or its peripheral devices used for data processing and calculations.

[0010] "Design information" refers to information that describes the elements and data that characterize a visual design.

[0011] "Tableware with a display" refers to tableware that has a built-in display device and can express visual designs.

[0012] "Means of display" refers to devices or functions that visually present generated information to the user. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an 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 an emotion engine is combined.

Mode for Carrying Out the Invention

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the language used in the following description will be explained.

[0016] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] 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.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0019] In the following embodiments, the numbered communication I / F (Interface) is an interface that includes a communication processor, an antenna, and the like. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] This invention is a system that automatically generates appropriate tableware designs based on the content of a meal, providing a visually superior dining experience. This system mainly consists of a user terminal, a server, and tableware with a display.

[0035] Users input details of their daily meals into their device via a dedicated app. This includes the name of the dish, ingredients, and beverages. This information is then sent from the device to a server.

[0036] The server analyzes the received meal information and generates tableware designs using a generative AI model. Based on pre-trained data, the AI ​​model proposes designs that take into account color, pattern, and theme. For example, for Italian cuisine, it will generate a design incorporating traditional Italian motifs.

[0037] The generated design is transferred from the server to a terminal and then displayed on tableware equipped with a display. The terminal transmits the latest design information to the tableware via wireless communication, and the tableware displays the design in real time. This ensures that the visual presentation on the table harmonizes with the meal content, providing users with a themed visual experience.

[0038] Furthermore, users can choose to customize the design of the tableware, adjusting design elements according to their preferences. The customized design is also recalculated on the server, and the updated design is reflected on the tableware.

[0039] This invention allows users to easily enjoy a beautiful and unified dining experience every day, thereby improving their satisfaction with meals. For example, if a user selects Japanese cuisine, patterns such as cherry blossoms or ripples can be generated and applied to the entire tableware, enabling a wide variety of designs.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user launches a dedicated app on their device and enters the details of their meals for the day. They list the dish name, ingredients, and corresponding drinks, and then press the submit button.

[0043] Step 2:

[0044] The terminal receives input information from the user, processes the information, and sends it to the server. The information is encrypted using a secure protocol, protecting personal information.

[0045] Step 3:

[0046] The server analyzes the received meal information and inputs it into a generating AI model. Based on the ingredients and type of dish, the model analyzes the colors and patterns to generate tableware designs.

[0047] Step 4:

[0048] The server compiles the generated design as data and sends it to the terminal. The transmitted data is optimized for smaller file sizes, allowing for rapid processing on the terminal.

[0049] Step 5:

[0050] The terminal receives design data sent from the server and delivers it to the tableware with a display. The tableware immediately displays the received design, providing a dynamic visual experience at the dining table.

[0051] Step 6:

[0052] Users can view the tableware designs displayed on the screen and arrange them on the table. They can also customize the designs as needed and resubmit them to the server.

[0053] Step 7:

[0054] The device sends the customized design back to the server, and the new design is reflected on the tableware. This allows users to control a different visual experience for each meal.

[0055] (Example 1)

[0056] 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."

[0057] There are challenges in easily providing an environment that allows for visual enjoyment of meals and reflecting designs on tableware that match the content of each meal. Furthermore, there is a lack of efficient means for automatic design generation and customization. Additionally, security must be ensured when transferring meal information.

[0058] 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.

[0059] In this invention, the server includes a terminal device for receiving meal contents, an information processing device including a generative model for analyzing the received meal contents and generating design idea information, and means for transferring the generated design idea information to tableware equipped with a display function using wireless communication technology and displaying the design. This makes it possible to provide a design suitable for each meal in real time and improve the user's visual satisfaction. Furthermore, by using a secure means for communicating meal information, it is possible to process the information efficiently while maintaining its security.

[0060] "Meal details" refers to information about the name of the dish specified by the user, the ingredients used, and the beverages.

[0061] A "terminal device" is an electronic device used by users to input meal details and send that information to a server.

[0062] A "generative model" is a program equipped with AI technology to create design inspiration information based on meal content.

[0063] An "information processing device" is a computer device used to execute generative models, and its role is to analyze meal content and generate designs.

[0064] "Design inspiration information" refers to concept data for tableware designs based on colors, patterns, and themes proposed by a generative model.

[0065] "Wireless communication technology" refers to communication technology that transfers information from a terminal device to tableware without using cables.

[0066] "Tableware with a display function" refers to tableware that has the ability to display visual information based on received design inspiration information.

[0067] "Secure communication methods" refer to communication protocols and technologies designed to protect data confidentiality when transmitting information about food contents.

[0068] This invention relates to a system for applying displayable tableware with individual designs based on the contents of a meal. The system consists of a user terminal device, a server, a generative AI model, and tableware with a display function equipped with wireless communication technology.

[0069] Users input their daily meal details through a dedicated application using terminal devices such as mobile phones or computers. This meal information includes the dish name, main ingredients, and associated beverages. The entered meal details are securely transmitted from the terminal device to the server.

[0070] The server analyzes the received meal information and uses a generative AI model to create tableware designs. This AI model is trained on a vast amount of visual design pattern data and generates design proposals while considering colors, patterns, and themes appropriate for the meal. For example, if the user selects Italian cuisine, the AI ​​model will suggest a design incorporating traditional Italian patterns and appropriate color tones.

[0071] The generated design concept information is sent back from the server to a terminal device. The terminal device uses wireless communication technology to transfer the design information to tableware equipped with a display function. The tableware displays this design in real time, providing the user with a visual experience that harmonizes with the meal.

[0072] Furthermore, users can customize the design through the app. When a user requests changes to the design's colors or patterns, the changes are sent back to the server and re-analyzed by the generating AI model. The updated design is then quickly reflected on the tableware.

[0073] For example, if a user selects Japanese food, a design featuring cherry blossoms or ripples could be generated and projected onto the tableware. An example of a prompt to the generation AI model would be, "Please suggest a design that matches a menu that includes Japanese food." In this way, the aim is to enrich the daily dining experience and enhance visual satisfaction.

[0074] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0075] Step 1:

[0076] The user launches a dedicated application using a terminal device and enters details of their meal for the day. Specifically, they select the dish name (e.g., carbonara), main ingredients (e.g., pasta, bacon), and beverage (e.g., red wine). This information is entered into the terminal device as digital data.

[0077] Step 2:

[0078] The terminal device packages the meal information entered by the user and transmits it to the server via a secure communication protocol. Here, data encoding is performed to ensure that the meal information is transmitted accurately and safely. The input is digital data of the meal information, and the output is data communication.

[0079] Step 3:

[0080] The server analyzes the meal details received from the terminal device. Based on the analyzed information, a generative AI model constructs prompt sentences and generates tableware designs. These prompt sentences are based on the meal theme, and the AI ​​model selects the optimal design elements from pre-trained data to generate design inspiration information. The input is the meal details based on the prompt sentences, and the output is design inspiration information.

[0081] Step 4:

[0082] The server sends the generated design idea information back to the terminal device. The server converts the data into a format that the terminal device can receive. During this process, the format is adjusted to ensure that the design data is received correctly. The input is the design idea information, and the output is the converted design data.

[0083] Step 5:

[0084] The terminal device analyzes the received design data and transmits it to tableware equipped with a display function using wireless communication technology. The tableware receives this data in real time and displays the new design on its display. This visually provides a design that reflects the contents of the meal. The input is the converted design data, and the output is the design display on the tableware.

[0085] Step 6:

[0086] Users can customize the design of their tableware using the app. For example, if they change the colors or patterns, that information is sent back to the server from the terminal device. The server generates new design inspiration information and displays it on the tableware through the terminal device. The input is the user's customization information, and the output is the updated design inspiration information.

[0087] (Application Example 1)

[0088] 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."

[0089] While the visual experience is increasingly important in the modern food and beverage industry, providing consistent tableware designs based on individual dining information is complex. Traditional methods make it difficult to instantly change designs to meet individual customer needs, resulting in decreased customer satisfaction. Furthermore, there is a lack of systems that are easy for users to operate and provide real-time visualization.

[0090] 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.

[0091] In this invention, the server includes a device for inputting meal information, an information processing device including a generation algorithm that automatically generates tableware designs based on the input information, and a device for transmitting and displaying the generated design information on tableware equipped with a visual output device. This enables restaurants to input meal information using a visualization device and display the corresponding design in real time.

[0092] A "device for inputting meal information" is an electronic input device used by users to input information about meals, such as ingredients and dish names.

[0093] An "information processing device including a generation algorithm" is a computing device that runs a program that automatically generates tableware designs based on input meal information.

[0094] "Tableware with a visual output device" refers to tableware equipped with a display function for displaying generated design information.

[0095] "Means of inputting meal information using visualization devices" refers to methods in which users input meal information while being visually assisted through devices such as smart glasses or head-mounted displays.

[0096] "A means of updating the display in real time" refers to a system that instantly changes design information based on meal information and user requests, and displays the latest design on tableware equipped with a visual output device.

[0097] The system for implementing this invention aims to improve the visual experience in the food and beverage industry, and in particular enables the real-time generation and display of tableware designs based on individual meal information. The detailed method for implementing the invention is described below.

[0098] Users input meal information using visualization devices such as smart glasses or head-mounted displays. This information includes ingredients, dish names, and themes. This information is then transmitted from the device to the server.

[0099] The server runs using Python as part of the information processing unit and executes a generative AI model. The model is built using TENSORFLOW® or PyTorch and generates designs based on input meal information. This algorithm considers design elements related to color, pattern, and theme to construct visually appealing designs.

[0100] Design information generated from the server is transmitted wirelessly to tableware equipped with a visual output device. This tableware utilizes electronic paper technology to display and update the design in real time.

[0101] As a concrete example, let's consider the case where a user orders a Japanese meal called "Sakura Gozen" at a restaurant. In this case, when the user types "Sakura Gozen," the server will suggest a design themed around cherry blossom petals.

[0102] Examples of prompt statements for a generative AI model are shown below.

[0103] "Meal details: Sakura Gozen (cherry blossom set meal), Season: Spring, Features: Generates a design based on flower petals."

[0104] In this way, the present invention can improve the overall dining experience in the food and beverage industry, and in particular enhance customer satisfaction by providing visually harmonious tableware designs.

[0105] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0106] Step 1:

[0107] Users input meal information using smart glasses or head-mounted displays. This information includes dish names, ingredients, and themes. This allows for the generation of designs tailored to user needs, and initial data is collected.

[0108] Step 2:

[0109] The terminal sends the user's entered meal information to the server. The transmitted information arrives at the server via a secure communication protocol. At this stage, the input information is organized as data and prepared for the next analysis process.

[0110] Step 3:

[0111] The server generates a design using a generative AI model based on the received meal information. An example of a prompt is, "Meal details: Sakura Gozen, Season: Spring, Features: Generate a design with a flower petal motif." The AI ​​model takes meal information as input and outputs new design data by combining elements of color, pattern, and theme based on this information.

[0112] Step 4:

[0113] The server returns the generated design information to the terminal, which then wirelessly transmits this information to the tableware equipped with a visual output device. Here, the design information is treated as wireless data and then formatted into a format that can be reflected on the tableware.

[0114] Step 5:

[0115] Tableware equipped with a visual output device applies received design information to an e-paper display, showing the design in real time. At this stage, a design tailored to the theme of the meal is materialized on the tableware, creating a visual effect before the user's eyes.

[0116] 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.

[0117] This invention provides a system that recognizes user emotions and dynamically adjusts the design of tableware based on those emotions in order to improve the dining experience. The system consists of a user terminal, a server, an emotion engine, and tableware with a display.

[0118] The user acquires emotional information using the device's camera and microphone. The device collects facial expressions and tone of voice as the user sits in front of the device and begins to eat. The device processes the collected data in real time to recognize the user's emotions.

[0119] The emotion engine analyzes the collected data and evaluates the user's current emotional state (e.g., happiness, surprise, anxiety). This identifies what emotion the user is experiencing.

[0120] The device sends emotional data along with meal information to the server. A secure communication protocol is used for information transmission, and appropriate encryption is performed to protect privacy.

[0121] The server integrates and analyzes the received meal information and emotional data. The generative AI model takes both datasets as input and generates tableware designs. The generated designs reflect the user's emotions in addition to the characteristics of the ingredients and dishes. For example, if the user is in a happy state, a design with bright and vibrant colors will be selected.

[0122] Ultimately, the terminal receives the design data from the server and sends it to the display-equipped tableware, which displays it instantly. Users can then enjoy their dining experience with tableware featuring visually harmonious designs that match their emotions and the content of their meal.

[0123] For example, when a user is enjoying Japanese food and is in a relaxed emotional state, a design featuring traditional Japanese patterns adorned with gentle blues and greens will be displayed, providing a visually relaxing environment. This system allows users to experience a new dining experience that is in sync with their emotions.

[0124] The following describes the processing flow.

[0125] Step 1:

[0126] The user launches a dedicated app on their device and grants permission to use the camera and microphone. This allows the device to capture the user's facial expressions and voice in real time.

[0127] Step 2:

[0128] The device collects the user's facial video and audio data, and uses this to activate an emotion engine. The emotion engine analyzes facial features and voice tone to infer the user's emotional state.

[0129] Step 3:

[0130] The device combines the emotional data recognized by the emotion engine with the meal information entered by the user into the app, and sends it to the server. Communication is conducted through a secure protocol.

[0131] Step 4:

[0132] The server receives meal information and emotional data and analyzes them. A generative AI model generates the optimal tableware design based on the meal and emotions. For example, if the emotion is "happiness," a bright and refreshing design will be selected.

[0133] Step 5:

[0134] The server generates design data and sends it back to the terminal. This data includes color and pattern information that reflects emotions.

[0135] Step 6:

[0136] The terminal receives design data and sends it to the tableware with a display, which instantly displays the new design. This process allows for a visual presentation at the dining table that harmonizes with the user's emotions.

[0137] Step 7:

[0138] Users enjoy meals with tableware designed to match their emotions. The design can be customized, regenerated, and reapplied as needed.

[0139] (Example 2)

[0140] 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".

[0141] To improve the dining experience, it is necessary to dynamically adjust visual elements according to the emotional state of individual users. However, conventional methods are limited to static design generation based solely on dining information, and have the challenge of not being able to dynamically adjust designs that incorporate user emotions.

[0142] 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.

[0143] In this invention, the server includes means for inputting meal information, an information processing device including a generation model that automatically generates tableware designs based on the input meal information and emotional information, means for transmitting and displaying the generated design information to tableware equipped with an output device, and means for providing an input device for acquiring emotional information. This makes it possible to generate and display dynamic tableware designs that take into account the user's emotional state and meal content.

[0144] "Dietary information" refers to information that includes the type of meal, the theme of the dish, and other related data.

[0145] "Emotional information" refers to data indicating the emotional state of a user, obtained based on their facial expressions and tone of voice.

[0146] A "generative model" is a model that includes an algorithm that automatically generates tableware designs based on input data.

[0147] An "information processing device" refers to an electronic computer that collects, analyzes, and outputs data.

[0148] "Tableware with an output device" refers to tableware equipped with a display device that has the function of displaying the generated design in real time.

[0149] An "input device" is hardware or software used to acquire data from a user.

[0150] A "secure communication protocol" is a protocol that includes security technologies used to protect data transmission.

[0151] This invention is a system designed to enhance the dining experience. The system consists of a terminal, a server, a device for recognizing user emotions, and tableware with an output device.

[0152] The device is equipped with the ability to acquire user emotional information. Specifically, it uses a built-in camera and microphone to capture and record the user's facial expressions and tone of voice in real time. Then, emotion recognition software processes this data to recognize the user's current emotions.

[0153] The emotion engine analyzes data collected by the device to evaluate the user's emotional state in detail. This analysis, along with meal information, is sent to the server using a secure communication protocol.

[0154] The server integrates and analyzes the received emotional and food information. Here, a generative AI model plays a crucial role. The model automatically generates tableware designs based on specified prompt sentences. An example of a prompt sentence might be, "User's emotion is relaxed, food is Japanese." Based on this sentence, a design combining traditional Japanese patterns with soft blues and greens is generated.

[0155] The generated design is pushed to tableware equipped with an output device via a terminal. The generated design is immediately displayed on the tableware's display, allowing the user to enjoy a dining experience that is in harmony with their emotions.

[0156] The above is an overview of the system for carrying out this invention. Depending on the hardware and software used, this system can provide customized designs that respond to a variety of emotional states and eating styles.

[0157] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0158] Step 1:

[0159] The user sits in front of the device and begins eating. The device's camera and microphone capture and record the user's facial expressions and tone of voice. This allows for the acquisition of emotional information. The input consists of the user's real-time video and audio.

[0160] Step 2:

[0161] The device analyzes the acquired video and audio using emotion recognition software to detect the user's emotional state. For example, it uses an AI algorithm to identify emotions such as "happiness" or "relaxation" from eye movements and voice tone. This analysis result is output as emotional information.

[0162] Step 3:

[0163] The terminal combines detected emotion information with pre-entered meal information and sends it to the server via a secure communication protocol. The input consists of emotion information and meal information, and the output is a data package sent to the server.

[0164] Step 4:

[0165] The server integrates and analyzes the received emotion and food information. Using a generative AI model, it processes the data based on prompts to generate tableware designs. For example, the prompt might be "User's emotion is relaxed, food is Japanese." In this case, the output is the generated tableware design.

[0166] Step 5:

[0167] The server sends the generated design to the terminal. The terminal pushes the design data to a tableware unit equipped with an output device, displaying the design on the tableware's screen. This allows the user to enjoy a meal that harmonizes with their emotional state. The input is the generated design data, and the output is the design displayed on the tableware.

[0168] (Application Example 2)

[0169] 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".

[0170] In today's restaurant industry, providing a unique dining experience tailored to each customer's emotional state is challenging. Dynamically changing tableware designs based on customer emotions are a crucial element in achieving a more personalized and satisfying experience. However, conventional systems are static and cannot provide real-time, emotion-responsive designs, thus failing to meet the complex needs of customers.

[0171] 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.

[0172] In this invention, the server includes a device for acquiring emotional information, an analysis mechanism for evaluating the emotional state based on the acquired emotional information, and a computing device including a generative AI model that automatically generates tableware designs based on the emotional state and meal information. This enables the provision of special tableware designs tailored to the customer's emotional state in real time, making a personalized dining experience possible.

[0173] A "device for acquiring emotional information" is a device that collects a user's facial expressions and tone of voice in real time and obtains data on their emotional state at that moment.

[0174] An "emotional state evaluation mechanism" is a mechanism that analyzes acquired emotional information to identify what emotions the user is currently experiencing.

[0175] A "computational device including a generative AI model" is a computational device equipped with algorithms and processing power to generate appropriate designs based on emotional states and dietary information.

[0176] "Tableware with a display" refers to tableware equipped with a display function to visually display the generated design information.

[0177] The system that implements this application example uses the following components.

[0178] First, the user acquires emotional information through the smart glasses. The smart glasses are equipped with a camera and microphone, which can collect the user's facial expressions and tone of voice in real time. This information is used to evaluate the emotional state and is sent to a server in the cloud.

[0179] Next, the server uses an emotion recognition API to analyze emotional information and identify the user's emotional state. Based on this information, a computing unit including a generative AI model automatically generates an appropriate design. By using, for example, GPT-4(registered trademark) as the generative AI model, it is possible to dynamically create designs based on emotional state and meal information.

[0180] The generated design information is transmitted to the tableware with a display via a secure communication protocol. The tableware with a display then visually displays a design that harmonizes with the user's emotions, providing a special dining experience.

[0181] As a concrete example, when a user experiences a special anniversary dinner at a restaurant, the system recognizes the user's feelings of joy and provides high-quality tableware designs in real time. Examples of prompts for the generative AI model in this scenario include the following:

[0182] "The current user emotion is 'joy.' Based on this, please create a luxurious tableware design perfect for a special dinner. The color scheme should be primarily gold and white."

[0183] In this way, a personalized dining experience tailored to the user's emotions can be realized.

[0184] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0185] Step 1:

[0186] The device uses the smart device's camera and microphone to capture the user's facial expressions and tone of voice. This input data is then used to collect basic information about the user's emotions.

[0187] Step 2:

[0188] The collected emotional information is transmitted from the terminal to the server via a secure communication protocol. The input here is emotional information, and the output is encrypted data. The server accurately decrypts this received data and converts it into a format usable for analysis.

[0189] Step 3:

[0190] The server uses an emotion recognition API to analyze the acquired emotion information. The input is the emotion information mentioned earlier, and the output is the emotional state evaluated through the analysis. In this step, the API identifies the emotional state by combining facial recognition technology and voice analysis.

[0191] Step 4:

[0192] The server provides emotional state and pre-acquired meal information as input to a generating AI model, which then generates a design. The input consists of emotional state and meal characteristic information, and the output is the generated tableware design information. Based on these inputs, the generating AI model creates prompt statements and selects appropriate design elements.

[0193] Step 5:

[0194] The server transmits the design information obtained from the generating AI model to the tableware with a display. The input is design information, and the output is the visual design displayed on the tableware. The tableware with a display interprets the design data and provides visual feedback to the user.

[0195] Step 6:

[0196] The user visually experiences the design displayed on the tableware with a display. In this step, the user actually enjoys the displayed design while eating, gaining a new dining experience that matches their emotions.

[0197] 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.

[0198] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0199] 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.

[0200] [Second Embodiment]

[0201] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0202] 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.

[0203] 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).

[0204] 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.

[0205] 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.

[0206] 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).

[0207] 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.

[0208] 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.

[0209] 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.

[0210] 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.

[0211] 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.

[0212] 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".

[0213] This invention is a system that automatically generates appropriate tableware designs based on the content of a meal, providing a visually superior dining experience. This system mainly consists of a user terminal, a server, and tableware with a display.

[0214] Users input details of their daily meals into their device via a dedicated app. This includes the name of the dish, ingredients, and beverages. This information is then sent from the device to a server.

[0215] The server analyzes the received meal information and generates tableware designs using a generative AI model. Based on pre-trained data, the AI ​​model proposes designs that take into account color, pattern, and theme. For example, for Italian cuisine, it will generate a design incorporating traditional Italian motifs.

[0216] The generated design is transferred from the server to a terminal and then displayed on tableware equipped with a display. The terminal transmits the latest design information to the tableware via wireless communication, and the tableware displays the design in real time. This ensures that the visual presentation on the table harmonizes with the meal content, providing users with a themed visual experience.

[0217] Furthermore, users can choose to customize the design of the tableware, adjusting design elements according to their preferences. The customized design is also recalculated on the server, and the updated design is reflected on the tableware.

[0218] This invention allows users to easily enjoy a beautiful and unified dining experience every day, thereby improving their satisfaction with meals. For example, if a user selects Japanese cuisine, patterns such as cherry blossoms or ripples can be generated and applied to the entire tableware, enabling a wide variety of designs.

[0219] The following describes the processing flow.

[0220] Step 1:

[0221] The user launches a dedicated app on their device and enters the details of their meals for the day. They list the dish name, ingredients, and corresponding drinks, and then press the submit button.

[0222] Step 2:

[0223] The terminal receives input information from the user, processes the information, and sends it to the server. The information is encrypted using a secure protocol, protecting personal information.

[0224] Step 3:

[0225] The server analyzes the received meal information and inputs it into a generating AI model. Based on the ingredients and type of dish, the model analyzes the colors and patterns to generate tableware designs.

[0226] Step 4:

[0227] The server compiles the generated design as data and sends it to the terminal. The transmitted data is optimized for smaller file sizes, allowing for rapid processing on the terminal.

[0228] Step 5:

[0229] The terminal receives design data sent from the server and delivers it to the tableware with a display. The tableware immediately displays the received design, providing a dynamic visual experience at the dining table.

[0230] Step 6:

[0231] Users can view the tableware designs displayed on the screen and arrange them on the table. They can also customize the designs as needed and resubmit them to the server.

[0232] Step 7:

[0233] The device sends the customized design back to the server, and the new design is reflected on the tableware. This allows users to control a different visual experience for each meal.

[0234] (Example 1)

[0235] 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."

[0236] There are challenges in easily providing an environment that allows for visual enjoyment of meals and reflecting designs on tableware that match the content of each meal. Furthermore, there is a lack of efficient means for automatic design generation and customization. Additionally, security must be ensured when transferring meal information.

[0237] 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.

[0238] In this invention, the server includes a terminal device for receiving meal contents, an information processing device including a generative model for analyzing the received meal contents and generating design idea information, and means for transferring the generated design idea information to tableware equipped with a display function using wireless communication technology and displaying the design. This makes it possible to provide a design suitable for each meal in real time and improve the user's visual satisfaction. Furthermore, by using a secure means for communicating meal information, it is possible to process the information efficiently while maintaining its security.

[0239] "Meal details" refers to information about the name of the dish specified by the user, the ingredients used, and the beverages.

[0240] A "terminal device" is an electronic device used by users to input meal details and send that information to a server.

[0241] A "generative model" is a program equipped with AI technology to create design inspiration information based on meal content.

[0242] An "information processing device" is a computer device used to execute generative models, and its role is to analyze meal content and generate designs.

[0243] "Design inspiration information" refers to concept data for tableware designs based on colors, patterns, and themes proposed by a generative model.

[0244] "Wireless communication technology" refers to communication technology that transfers information from a terminal device to tableware without using cables.

[0245] "Tableware with a display function" refers to tableware that has the ability to display visual information based on received design inspiration information.

[0246] "Secure communication methods" refer to communication protocols and technologies designed to protect data confidentiality when transmitting information about food contents.

[0247] This invention relates to a system for applying displayable tableware with individual designs based on the contents of a meal. The system consists of a user terminal device, a server, a generative AI model, and tableware with a display function equipped with wireless communication technology.

[0248] Users input their daily meal details through a dedicated application using terminal devices such as mobile phones or computers. This meal information includes the dish name, main ingredients, and associated beverages. The entered meal details are securely transmitted from the terminal device to the server.

[0249] The server analyzes the received meal information and uses a generative AI model to create tableware designs. This AI model is trained on a vast amount of visual design pattern data and generates design proposals while considering colors, patterns, and themes appropriate for the meal. For example, if the user selects Italian cuisine, the AI ​​model will suggest a design incorporating traditional Italian patterns and appropriate color tones.

[0250] The generated design concept information is sent back from the server to a terminal device. The terminal device uses wireless communication technology to transfer the design information to tableware equipped with a display function. The tableware displays this design in real time, providing the user with a visual experience that harmonizes with the meal.

[0251] Furthermore, users can customize the design through the app. When a user requests changes to the design's colors or patterns, the changes are sent back to the server and re-analyzed by the generating AI model. The updated design is then quickly reflected on the tableware.

[0252] For example, if a user selects Japanese food, a design featuring cherry blossoms or ripples could be generated and projected onto the tableware. An example of a prompt to the generation AI model would be, "Please suggest a design that matches a menu that includes Japanese food." In this way, the aim is to enrich the daily dining experience and enhance visual satisfaction.

[0253] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0254] Step 1:

[0255] The user launches a dedicated application using a terminal device and enters details of their meal for the day. Specifically, they select the dish name (e.g., carbonara), main ingredients (e.g., pasta, bacon), and beverage (e.g., red wine). This information is entered into the terminal device as digital data.

[0256] Step 2:

[0257] The terminal device packages the meal information entered by the user and transmits it to the server via a secure communication protocol. Here, data encoding is performed to ensure that the meal information is transmitted accurately and safely. The input is digital data of the meal information, and the output is data communication.

[0258] Step 3:

[0259] The server analyzes the meal details received from the terminal device. Based on the analyzed information, a generative AI model constructs prompt sentences and generates tableware designs. These prompt sentences are based on the meal theme, and the AI ​​model selects the optimal design elements from pre-trained data to generate design inspiration information. The input is the meal details based on the prompt sentences, and the output is design inspiration information.

[0260] Step 4:

[0261] The server sends the generated design idea information back to the terminal device. The server converts the data into a format that the terminal device can receive. During this process, the format is adjusted to ensure that the design data is received correctly. The input is the design idea information, and the output is the converted design data.

[0262] Step 5:

[0263] The terminal device analyzes the received design data and transmits it to tableware equipped with a display function using wireless communication technology. The tableware receives this data in real time and displays the new design on its display. This visually provides a design that reflects the contents of the meal. The input is the converted design data, and the output is the design display on the tableware.

[0264] Step 6:

[0265] Users can customize the design of their tableware using the app. For example, if they change the colors or patterns, that information is sent back to the server from the terminal device. The server generates new design inspiration information and displays it on the tableware through the terminal device. The input is the user's customization information, and the output is the updated design inspiration information.

[0266] (Application Example 1)

[0267] 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."

[0268] While the visual experience is increasingly important in the modern food and beverage industry, providing consistent tableware designs based on individual dining information is complex. Traditional methods make it difficult to instantly change designs to meet individual customer needs, resulting in decreased customer satisfaction. Furthermore, there is a lack of systems that are easy for users to operate and provide real-time visualization.

[0269] 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.

[0270] In this invention, the server includes a device for inputting meal information, an information processing device including a generation algorithm that automatically generates tableware designs based on the input information, and a device for transmitting and displaying the generated design information on tableware equipped with a visual output device. This enables restaurants to input meal information using a visualization device and display the corresponding design in real time.

[0271] A "device for inputting meal information" is an electronic input device used by users to input information about meals, such as ingredients and dish names.

[0272] An "information processing device including a generation algorithm" is a computing device that runs a program that automatically generates tableware designs based on input meal information.

[0273] "Tableware with a visual output device" refers to tableware equipped with a display function for displaying generated design information.

[0274] "Means of inputting meal information using visualization devices" refers to methods in which users input meal information while being visually assisted through devices such as smart glasses or head-mounted displays.

[0275] "A means of updating the display in real time" refers to a system that instantly changes design information based on meal information and user requests, and displays the latest design on tableware equipped with a visual output device.

[0276] The system for implementing this invention aims to improve the visual experience in the food and beverage industry, and in particular enables the real-time generation and display of tableware designs based on individual meal information. The detailed method for implementing the invention is described below.

[0277] Users input meal information using visualization devices such as smart glasses or head-mounted displays. This information includes ingredients, dish names, and themes. This information is then transmitted from the device to the server.

[0278] The server runs using Python as part of the information processing unit and executes a generative AI model. The model is built using TensorFlow or PyTorch and generates designs based on input meal information. This algorithm considers design elements related to color, pattern, and theme to construct visually appealing designs.

[0279] Design information generated from the server is transmitted wirelessly to tableware equipped with a visual output device. This tableware utilizes electronic paper technology to display and update the design in real time.

[0280] As a concrete example, let's consider the case where a user orders a Japanese meal called "Sakura Gozen" at a restaurant. In this case, when the user types "Sakura Gozen," the server will suggest a design themed around cherry blossom petals.

[0281] Examples of prompt statements for a generative AI model are shown below.

[0282] "Meal details: Sakura Gozen (cherry blossom set meal), Season: Spring, Features: Generates a design based on flower petals."

[0283] In this way, the present invention can improve the overall dining experience in the food service industry, and in particular, by providing a visually harmonious tableware design, it enhances customer satisfaction.

[0284] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0285] Step 1:

[0286] The user inputs food information using smart glasses or a head-mounted display. The information to be input includes the name of the dish, ingredients, theme, etc. This enables the generation of a design that meets the user's needs and initial data is collected.

[0287] Step 2:

[0288] The terminal sends the food information input by the user to the server. The information to be sent reaches the server via a secure communication protocol. At this stage, the input information is organized as data in preparation for the next analysis process.

[0289] Step 3:

[0290] Based on the received food information, the server generates a design using the generative AI model. An example of the prompt text is "Meal content: Cherry blossom cuisine, Season: Spring, Feature: Generate a design with flower petals as a motif". The food information is obtained as input, and the AI model combines elements of color, pattern, and theme based on this to output new design data.

[0291] Step 4:

[0292] The server returns the generated design information to the terminal, and the terminal wirelessly transmits this information to the tableware with a visual output device. Here, the design information is treated as wireless data and is formatted into a form for reflection on the tableware next.

[0293] Step 5:

[0294] Tableware equipped with a visual output device applies received design information to an e-paper display, showing the design in real time. At this stage, a design tailored to the theme of the meal is materialized on the tableware, creating a visual effect before the user's eyes.

[0295] 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.

[0296] This invention provides a system that recognizes user emotions and dynamically adjusts the design of tableware based on those emotions in order to improve the dining experience. The system consists of a user terminal, a server, an emotion engine, and tableware with a display.

[0297] The user acquires emotional information using the device's camera and microphone. The device collects facial expressions and tone of voice as the user sits in front of the device and begins to eat. The device processes the collected data in real time to recognize the user's emotions.

[0298] The emotion engine analyzes the collected data and evaluates the user's current emotional state (e.g., happiness, surprise, anxiety). This identifies what emotion the user is experiencing.

[0299] The device sends emotional data along with meal information to the server. A secure communication protocol is used for information transmission, and appropriate encryption is performed to protect privacy.

[0300] The server integrates and analyzes the received food information and emotion data. The generative AI model receives both data sets as inputs and generates the design of tableware. The generated design reflects not only the ingredients and characteristics of the dish but also the user's emotions. For example, when the user is in a happy state, a design with bright and vivid colors is selected.

[0301] Finally, the terminal sends the design data received from the server to the tableware with a display and immediately displays it. The user can enjoy the dining experience with tableware featuring a visually harmonious design that suits their emotions and the content of the meal.

[0302] As a specific example, when the user is in a relaxed emotional state while enjoying Japanese cuisine, a design featuring blue or green, which is gentle on traditional Japanese patterns, is displayed, providing a visually relaxing environment. With this system, the user can obtain a new dining experience that integrates with their emotions.

[0303] The following describes the processing flow.

[0304] Step 1:

[0305] The user launches the dedicated app on the terminal and permits the use of the camera and microphone. This enables the terminal to capture the user's expression and voice in real time.

[0306] Step 2:

[0307] The terminal collects the user's face video and voice data and operates the emotion engine based on these. The emotion engine analyzes the facial features and voice tone to infer the user's emotional state.

[0308] Step 3:

[0309] The terminal consolidates the emotion data recognized by the emotion engine and the food information input by the user into the app and sends it to the server. The communication is carried out through a secure protocol.

[0310] Step 4:

[0311] The server receives meal information and emotional data and analyzes them. A generative AI model generates the optimal tableware design based on the meal and emotions. For example, if the emotion is "happiness," a bright and refreshing design will be selected.

[0312] Step 5:

[0313] The server generates design data and sends it back to the terminal. This data includes color and pattern information that reflects emotions.

[0314] Step 6:

[0315] The terminal receives design data and sends it to the tableware with a display, which instantly displays the new design. This process allows for a visual presentation at the dining table that harmonizes with the user's emotions.

[0316] Step 7:

[0317] Users enjoy meals with tableware designed to match their emotions. The design can be customized, regenerated, and reapplied as needed.

[0318] (Example 2)

[0319] 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".

[0320] To improve the dining experience, it is necessary to dynamically adjust visual elements according to the emotional state of individual users. However, conventional methods are limited to static design generation based solely on dining information, and have the challenge of not being able to dynamically adjust designs that incorporate user emotions.

[0321] 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.

[0322] In this invention, the server includes means for inputting meal information, an information processing device including a generation model that automatically generates tableware designs based on the input meal information and emotional information, means for transmitting and displaying the generated design information to tableware equipped with an output device, and means for providing an input device for acquiring emotional information. This makes it possible to generate and display dynamic tableware designs that take into account the user's emotional state and meal content.

[0323] "Dietary information" refers to information that includes the type of meal, the theme of the dish, and other related data.

[0324] "Emotional information" refers to data indicating the emotional state of a user, obtained based on their facial expressions and tone of voice.

[0325] A "generative model" is a model that includes an algorithm that automatically generates tableware designs based on input data.

[0326] An "information processing device" refers to an electronic computer that collects, analyzes, and outputs data.

[0327] "Tableware with an output device" refers to tableware equipped with a display device that has the function of displaying the generated design in real time.

[0328] An "input device" is hardware or software used to acquire data from a user.

[0329] A "secure communication protocol" is a protocol that includes security technologies used to protect data transmission.

[0330] This invention is a system designed to enhance the dining experience. The system consists of a terminal, a server, a device for recognizing user emotions, and tableware with an output device.

[0331] The device is equipped with the ability to acquire user emotional information. Specifically, it uses a built-in camera and microphone to capture and record the user's facial expressions and tone of voice in real time. Then, emotion recognition software processes this data to recognize the user's current emotions.

[0332] The emotion engine analyzes data collected by the device to evaluate the user's emotional state in detail. This analysis, along with meal information, is sent to the server using a secure communication protocol.

[0333] The server integrates and analyzes the received emotional and food information. Here, a generative AI model plays a crucial role. The model automatically generates tableware designs based on specified prompt sentences. An example of a prompt sentence might be, "User's emotion is relaxed, food is Japanese." Based on this sentence, a design combining traditional Japanese patterns with soft blues and greens is generated.

[0334] The generated design is pushed to tableware equipped with an output device via a terminal. The generated design is immediately displayed on the tableware's display, allowing the user to enjoy a dining experience that is in harmony with their emotions.

[0335] The above is an overview of the system for carrying out this invention. Depending on the hardware and software used, this system can provide customized designs that respond to a variety of emotional states and eating styles.

[0336] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0337] Step 1:

[0338] The user sits in front of the device and begins eating. The device's camera and microphone capture and record the user's facial expressions and tone of voice. This allows for the acquisition of emotional information. The input consists of the user's real-time video and audio.

[0339] Step 2:

[0340] The device analyzes the acquired video and audio using emotion recognition software to detect the user's emotional state. For example, it uses an AI algorithm to identify emotions such as "happiness" or "relaxation" from eye movements and voice tone. This analysis result is output as emotional information.

[0341] Step 3:

[0342] The terminal combines detected emotion information with pre-entered meal information and sends it to the server via a secure communication protocol. The input consists of emotion information and meal information, and the output is a data package sent to the server.

[0343] Step 4:

[0344] The server integrates and analyzes the received emotion and food information. Using a generative AI model, it processes the data based on prompts to generate tableware designs. For example, the prompt might be "User's emotion is relaxed, food is Japanese." In this case, the output is the generated tableware design.

[0345] Step 5:

[0346] The server sends the generated design to the terminal. The terminal pushes the design data to a tableware unit equipped with an output device, displaying the design on the tableware's screen. This allows the user to enjoy a meal that harmonizes with their emotional state. The input is the generated design data, and the output is the design displayed on the tableware.

[0347] (Application Example 2)

[0348] 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."

[0349] In today's restaurant industry, providing a unique dining experience tailored to each customer's emotional state is challenging. Dynamically changing tableware designs based on customer emotions are a crucial element in achieving a more personalized and satisfying experience. However, conventional systems are static and cannot provide real-time, emotion-responsive designs, thus failing to meet the complex needs of customers.

[0350] 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.

[0351] In this invention, the server includes a device for acquiring emotional information, an analysis mechanism for evaluating the emotional state based on the acquired emotional information, and a computing device including a generative AI model that automatically generates tableware designs based on the emotional state and meal information. This enables the provision of special tableware designs tailored to the customer's emotional state in real time, making a personalized dining experience possible.

[0352] A "device for acquiring emotional information" is a device that collects a user's facial expressions and tone of voice in real time and obtains data on their emotional state at that moment.

[0353] An "emotional state evaluation mechanism" is a mechanism that analyzes acquired emotional information to identify what emotions the user is currently experiencing.

[0354] A "computational device including a generative AI model" is a computational device equipped with algorithms and processing power to generate appropriate designs based on emotional states and dietary information.

[0355] "Tableware with a display" refers to tableware equipped with a display function to visually display the generated design information.

[0356] The system that implements this application example uses the following components.

[0357] First, the user acquires emotional information through the smart glasses. The smart glasses are equipped with a camera and microphone, which can collect the user's facial expressions and tone of voice in real time. This information is used to evaluate the emotional state and is sent to a server in the cloud.

[0358] Next, the server uses an emotion recognition API to analyze emotional information and identify the user's emotional state. Based on this information, a computing unit including a generative AI model automatically generates an appropriate design. By using, for example, GPT-4 as the generative AI model, it is possible to dynamically create a design based on emotional state and meal information.

[0359] The generated design information is transmitted to the tableware with a display via a secure communication protocol. The tableware with a display then visually displays a design that harmonizes with the user's emotions, providing a special dining experience.

[0360] As a concrete example, when a user experiences a special anniversary dinner at a restaurant, the system recognizes the user's feelings of joy and provides high-quality tableware designs in real time. Examples of prompts for the generative AI model in this scenario include the following:

[0361] "The current user emotion is 'joy.' Based on this, please create a luxurious tableware design perfect for a special dinner. The color scheme should be primarily gold and white."

[0362] In this way, a personalized dining experience tailored to the user's emotions can be realized.

[0363] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0364] Step 1:

[0365] The device uses the smart device's camera and microphone to capture the user's facial expressions and tone of voice. This input data is then used to collect basic information about the user's emotions.

[0366] Step 2:

[0367] The collected emotional information is transmitted from the terminal to the server via a secure communication protocol. The input here is emotional information, and the output is encrypted data. The server accurately decrypts this received data and converts it into a format usable for analysis.

[0368] Step 3:

[0369] The server uses an emotion recognition API to analyze the acquired emotion information. The input is the emotion information mentioned earlier, and the output is the emotional state evaluated through the analysis. In this step, the API identifies the emotional state by combining facial recognition technology and voice analysis.

[0370] Step 4:

[0371] The server provides emotional state and pre-acquired meal information as input to a generating AI model, which then generates a design. The input consists of emotional state and meal characteristic information, and the output is the generated tableware design information. Based on these inputs, the generating AI model creates prompt statements and selects appropriate design elements.

[0372] Step 5:

[0373] The server transmits the design information obtained from the generative AI model to the tableware with a display. The input is design information, and the output is the visual design displayed on the tableware. The tableware with a display interprets the design data and provides visual feedback to the user.

[0374] Step 6:

[0375] The user visually experiences the design displayed on the tableware with a display. In this step, the user actually enjoys the displayed design while eating, gaining a new dining experience that matches their emotions.

[0376] 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.

[0377] 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.

[0378] 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.

[0379] [Third Embodiment]

[0380] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0381] 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.

[0382] 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).

[0383] 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.

[0384] 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.

[0385] 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).

[0386] 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.

[0387] 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.

[0388] 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.

[0389] 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.

[0390] 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.

[0391] 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".

[0392] This invention is a system that automatically generates appropriate tableware designs based on the content of a meal, providing a visually superior dining experience. This system mainly consists of a user terminal, a server, and tableware with a display.

[0393] Users input details of their daily meals into their device via a dedicated app. This includes the name of the dish, ingredients, and beverages. This information is then sent from the device to a server.

[0394] The server analyzes the received meal information and generates tableware designs using a generative AI model. Based on pre-trained data, the AI ​​model proposes designs that take into account color, pattern, and theme. For example, for Italian cuisine, it will generate a design incorporating traditional Italian motifs.

[0395] The generated design is transferred from the server to a terminal and then displayed on tableware equipped with a display. The terminal transmits the latest design information to the tableware via wireless communication, and the tableware displays the design in real time. This ensures that the visual presentation on the table harmonizes with the meal content, providing users with a themed visual experience.

[0396] Furthermore, users can choose to customize the design of the tableware, adjusting design elements according to their preferences. The customized design is also recalculated on the server, and the updated design is reflected on the tableware.

[0397] This invention allows users to easily enjoy a beautiful and unified dining experience every day, thereby improving their satisfaction with meals. For example, if a user selects Japanese cuisine, patterns such as cherry blossoms or ripples can be generated and applied to the entire tableware, enabling a wide variety of designs.

[0398] The following describes the processing flow.

[0399] Step 1:

[0400] The user launches a dedicated app on their device and enters the details of their meals for the day. They list the dish name, ingredients, and corresponding drinks, and then press the submit button.

[0401] Step 2:

[0402] The terminal receives input information from the user, processes the information, and sends it to the server. The information is encrypted using a secure protocol, protecting personal information.

[0403] Step 3:

[0404] The server analyzes the received meal information and inputs it into a generating AI model. Based on the ingredients and type of dish, the model analyzes the colors and patterns to generate tableware designs.

[0405] Step 4:

[0406] The server compiles the generated design as data and sends it to the terminal. The transmitted data is optimized for smaller file sizes, allowing for rapid processing on the terminal.

[0407] Step 5:

[0408] The terminal receives design data sent from the server and delivers it to the tableware with a display. The tableware immediately displays the received design, providing a dynamic visual experience at the dining table.

[0409] Step 6:

[0410] Users can view the tableware designs displayed on the screen and arrange them on the table. They can also customize the designs as needed and resubmit them to the server.

[0411] Step 7:

[0412] The device sends the customized design back to the server, and the new design is reflected on the tableware. This allows users to control a different visual experience for each meal.

[0413] (Example 1)

[0414] 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."

[0415] There are challenges in easily providing an environment that allows for visual enjoyment of meals and reflecting designs on tableware that match the content of each meal. Furthermore, there is a lack of efficient means for automatic design generation and customization. Additionally, security must be ensured when transferring meal information.

[0416] 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.

[0417] In this invention, the server includes a terminal device for receiving meal contents, an information processing device including a generative model for analyzing the received meal contents and generating design idea information, and means for transferring the generated design idea information to tableware equipped with a display function using wireless communication technology and displaying the design. This makes it possible to provide a design suitable for each meal in real time and improve the user's visual satisfaction. Furthermore, by using a secure means for communicating meal information, it is possible to process the information efficiently while maintaining its security.

[0418] "Meal details" refers to information about the name of the dish specified by the user, the ingredients used, and the beverages.

[0419] A "terminal device" is an electronic device used by users to input meal details and send that information to a server.

[0420] A "generative model" is a program equipped with AI technology to create design inspiration information based on meal content.

[0421] An "information processing device" is a computer device used to execute generative models, and its role is to analyze meal content and generate designs.

[0422] "Design inspiration information" refers to concept data for tableware designs based on colors, patterns, and themes proposed by a generative model.

[0423] "Wireless communication technology" refers to communication technology that transfers information from a terminal device to tableware without using cables.

[0424] "Tableware with a display function" refers to tableware that has the ability to display visual information based on received design inspiration information.

[0425] "Secure communication methods" refer to communication protocols and technologies designed to protect data confidentiality when transmitting information about food contents.

[0426] This invention relates to a system for applying displayable tableware with individual designs based on the contents of a meal. The system consists of a user terminal device, a server, a generative AI model, and tableware with a display function equipped with wireless communication technology.

[0427] Users input their daily meal details through a dedicated application using terminal devices such as mobile phones or computers. This meal information includes the dish name, main ingredients, and associated beverages. The entered meal details are securely transmitted from the terminal device to the server.

[0428] The server analyzes the received meal information and uses a generative AI model to create tableware designs. This AI model is trained on a vast amount of visual design pattern data and generates design proposals while considering colors, patterns, and themes appropriate for the meal. For example, if the user selects Italian cuisine, the AI ​​model will suggest a design incorporating traditional Italian patterns and appropriate color tones.

[0429] The generated design concept information is sent back from the server to a terminal device. The terminal device uses wireless communication technology to transfer the design information to tableware equipped with a display function. The tableware displays this design in real time, providing the user with a visual experience that harmonizes with the meal.

[0430] Furthermore, users can customize the design through the app. When a user requests changes to the design's colors or patterns, the changes are sent back to the server and re-analyzed by the generating AI model. The updated design is then quickly reflected on the tableware.

[0431] For example, if a user selects Japanese food, a design featuring cherry blossoms or ripples could be generated and projected onto the tableware. An example of a prompt to the generation AI model would be, "Please suggest a design that matches a menu that includes Japanese food." In this way, the aim is to enrich the daily dining experience and enhance visual satisfaction.

[0432] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0433] Step 1:

[0434] The user launches a dedicated application using a terminal device and enters details of their meal for the day. Specifically, they select the dish name (e.g., carbonara), main ingredients (e.g., pasta, bacon), and beverage (e.g., red wine). This information is entered into the terminal device as digital data.

[0435] Step 2:

[0436] The terminal device packages the meal information entered by the user and transmits it to the server via a secure communication protocol. Here, data encoding is performed to ensure that the meal information is transmitted accurately and safely. The input is digital data of the meal information, and the output is data communication.

[0437] Step 3:

[0438] The server analyzes the meal details received from the terminal device. Based on the analyzed information, a generative AI model constructs prompt sentences and generates tableware designs. These prompt sentences are based on the meal theme, and the AI ​​model selects the optimal design elements from pre-trained data to generate design inspiration information. The input is the meal details based on the prompt sentences, and the output is design inspiration information.

[0439] Step 4:

[0440] The server sends the generated design idea information back to the terminal device. The server converts the data into a format that the terminal device can receive. During this process, the format is adjusted to ensure that the design data is received correctly. The input is the design idea information, and the output is the converted design data.

[0441] Step 5:

[0442] The terminal device analyzes the received design data and transmits it to tableware equipped with a display function using wireless communication technology. The tableware receives this data in real time and displays the new design on its display. This visually provides a design that reflects the contents of the meal. The input is the converted design data, and the output is the design display on the tableware.

[0443] Step 6:

[0444] Users can customize the design of their tableware using the app. For example, if they change the colors or patterns, that information is sent back to the server from the terminal device. The server generates new design inspiration information and displays it on the tableware through the terminal device. The input is the user's customization information, and the output is the updated design inspiration information.

[0445] (Application Example 1)

[0446] 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."

[0447] While the visual experience is increasingly important in the modern food and beverage industry, providing consistent tableware designs based on individual dining information is complex. Traditional methods make it difficult to instantly change designs to meet individual customer needs, resulting in decreased customer satisfaction. Furthermore, there is a lack of systems that are easy for users to operate and provide real-time visualization.

[0448] 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.

[0449] In this invention, the server includes a device for inputting meal information, an information processing device including a generation algorithm that automatically generates tableware designs based on the input information, and a device for transmitting and displaying the generated design information on tableware equipped with a visual output device. This enables restaurants to input meal information using a visualization device and display the corresponding design in real time.

[0450] A "device for inputting meal information" is an electronic input device used by users to input information about meals, such as ingredients and dish names.

[0451] An "information processing device including a generation algorithm" is a computing device that runs a program that automatically generates tableware designs based on input meal information.

[0452] "Tableware with a visual output device" refers to tableware equipped with a display function for displaying generated design information.

[0453] "Means of inputting meal information using visualization devices" refers to methods in which users input meal information while being visually assisted through devices such as smart glasses or head-mounted displays.

[0454] "A means of updating the display in real time" refers to a system that instantly changes design information based on meal information and user requests, and displays the latest design on tableware equipped with a visual output device.

[0455] The system for implementing this invention aims to improve the visual experience in the food and beverage industry, and in particular enables the real-time generation and display of tableware designs based on individual meal information. The detailed method for implementing the invention is described below.

[0456] Users input meal information using visualization devices such as smart glasses or head-mounted displays. This information includes ingredients, dish names, and themes. This information is then transmitted from the device to the server.

[0457] The server runs using Python as part of the information processing unit and executes a generative AI model. The model is built using TensorFlow or PyTorch and generates designs based on input meal information. This algorithm considers design elements related to color, pattern, and theme to construct visually appealing designs.

[0458] Design information generated from the server is transmitted wirelessly to tableware equipped with a visual output device. This tableware utilizes electronic paper technology to display and update the design in real time.

[0459] As a concrete example, let's consider the case where a user orders a Japanese meal called "Sakura Gozen" at a restaurant. In this case, when the user types "Sakura Gozen," the server will suggest a design themed around cherry blossom petals.

[0460] Examples of prompt statements for a generative AI model are shown below.

[0461] "Meal details: Sakura Gozen (cherry blossom set meal), Season: Spring, Features: Generates a design based on flower petals."

[0462] In this way, the present invention can improve the overall dining experience in the food and beverage industry, and in particular enhance customer satisfaction by providing visually harmonious tableware designs.

[0463] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0464] Step 1:

[0465] Users input meal information using smart glasses or head-mounted displays. This information includes dish names, ingredients, and themes. This allows for the generation of designs tailored to user needs, and initial data is collected.

[0466] Step 2:

[0467] The terminal sends the user's entered meal information to the server. The transmitted information arrives at the server via a secure communication protocol. At this stage, the input information is organized as data and prepared for the next analysis process.

[0468] Step 3:

[0469] The server generates a design using a generative AI model based on the received meal information. An example of a prompt is, "Meal details: Sakura Gozen, Season: Spring, Features: Generate a design with a flower petal motif." The AI ​​model takes meal information as input and outputs new design data by combining elements of color, pattern, and theme based on this information.

[0470] Step 4:

[0471] The server returns the generated design information to the terminal, which then wirelessly transmits this information to the tableware equipped with a visual output device. Here, the design information is treated as wireless data and then formatted into a format that can be reflected on the tableware.

[0472] Step 5:

[0473] Tableware equipped with a visual output device applies received design information to an e-paper display, showing the design in real time. At this stage, a design tailored to the theme of the meal is materialized on the tableware, creating a visual effect before the user's eyes.

[0474] 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.

[0475] This invention provides a system that recognizes user emotions and dynamically adjusts the design of tableware based on those emotions in order to improve the dining experience. The system consists of a user terminal, a server, an emotion engine, and tableware with a display.

[0476] The user acquires emotional information using the device's camera and microphone. The device collects facial expressions and tone of voice as the user sits in front of the device and begins to eat. The device processes the collected data in real time to recognize the user's emotions.

[0477] The emotion engine analyzes the collected data and evaluates the user's current emotional state (e.g., happiness, surprise, anxiety). This identifies what emotion the user is experiencing.

[0478] The device sends emotional data along with meal information to the server. A secure communication protocol is used for information transmission, and appropriate encryption is performed to protect privacy.

[0479] The server integrates and analyzes the received meal information and emotional data. The generative AI model takes both datasets as input and generates tableware designs. The generated designs reflect the user's emotions in addition to the characteristics of the ingredients and dishes. For example, if the user is in a happy state, a design with bright and vibrant colors will be selected.

[0480] Ultimately, the terminal receives the design data from the server and sends it to the display-equipped tableware, which displays it instantly. Users can then enjoy their dining experience with tableware featuring visually harmonious designs that match their emotions and the content of their meal.

[0481] For example, when a user is enjoying Japanese food and is in a relaxed emotional state, a design featuring traditional Japanese patterns adorned with gentle blues and greens will be displayed, providing a visually relaxing environment. This system allows users to experience a new dining experience that is in sync with their emotions.

[0482] The following describes the processing flow.

[0483] Step 1:

[0484] The user launches a dedicated app on their device and grants permission to use the camera and microphone. This allows the device to capture the user's facial expressions and voice in real time.

[0485] Step 2:

[0486] The device collects the user's facial video and audio data, and uses this to activate an emotion engine. The emotion engine analyzes facial features and voice tone to infer the user's emotional state.

[0487] Step 3:

[0488] The device combines the emotional data recognized by the emotion engine with the meal information entered by the user into the app, and sends it to the server. Communication is conducted through a secure protocol.

[0489] Step 4:

[0490] The server receives meal information and emotional data and analyzes them. A generative AI model generates the optimal tableware design based on the meal and emotions. For example, if the emotion is "happiness," a bright and refreshing design will be selected.

[0491] Step 5:

[0492] The server generates design data and sends it back to the terminal. This data includes color and pattern information that reflects emotions.

[0493] Step 6:

[0494] The terminal receives design data and sends it to the tableware with a display, which instantly displays the new design. This process allows for a visual presentation at the dining table that harmonizes with the user's emotions.

[0495] Step 7:

[0496] Users enjoy meals with tableware designed to match their emotions. The design can be customized, regenerated, and reapplied as needed.

[0497] (Example 2)

[0498] 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."

[0499] To improve the dining experience, it is necessary to dynamically adjust visual elements according to the emotional state of individual users. However, conventional methods are limited to static design generation based solely on dining information, and have the challenge of not being able to dynamically adjust designs that incorporate user emotions.

[0500] 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.

[0501] In this invention, the server includes means for inputting meal information, an information processing device including a generation model that automatically generates tableware designs based on the input meal information and emotional information, means for transmitting and displaying the generated design information to tableware equipped with an output device, and means for providing an input device for acquiring emotional information. This makes it possible to generate and display dynamic tableware designs that take into account the user's emotional state and meal content.

[0502] "Dietary information" refers to information that includes the type of meal, the theme of the dish, and other related data.

[0503] "Emotional information" refers to data indicating the emotional state of a user, obtained based on their facial expressions and tone of voice.

[0504] A "generative model" is a model that includes an algorithm that automatically generates tableware designs based on input data.

[0505] An "information processing device" refers to an electronic computer that collects, analyzes, and outputs data.

[0506] "Tableware with an output device" refers to tableware equipped with a display device that has the function of displaying the generated design in real time.

[0507] An "input device" is hardware or software used to acquire data from a user.

[0508] A "secure communication protocol" is a protocol that includes security technologies used to protect data transmission.

[0509] This invention is a system designed to enhance the dining experience. The system consists of a terminal, a server, a device for recognizing user emotions, and tableware with an output device.

[0510] The device is equipped with the ability to acquire user emotional information. Specifically, it uses a built-in camera and microphone to capture and record the user's facial expressions and tone of voice in real time. Then, emotion recognition software processes this data to recognize the user's current emotions.

[0511] The emotion engine analyzes data collected by the device to evaluate the user's emotional state in detail. This analysis, along with meal information, is sent to the server using a secure communication protocol.

[0512] The server integrates and analyzes the received emotional and food information. Here, a generative AI model plays a crucial role. The model automatically generates tableware designs based on specified prompt sentences. An example of a prompt sentence might be, "User's emotion is relaxed, food is Japanese." Based on this sentence, a design combining traditional Japanese patterns with soft blues and greens is generated.

[0513] The generated design is pushed to tableware equipped with an output device via a terminal. The generated design is immediately displayed on the tableware's display, allowing the user to enjoy a dining experience that is in harmony with their emotions.

[0514] The above is an overview of the system for carrying out this invention. Depending on the hardware and software used, this system can provide customized designs that respond to a variety of emotional states and eating styles.

[0515] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0516] Step 1:

[0517] The user sits in front of the device and begins eating. The device's camera and microphone capture and record the user's facial expressions and tone of voice. This allows for the acquisition of emotional information. The input consists of the user's real-time video and audio.

[0518] Step 2:

[0519] The device analyzes the acquired video and audio using emotion recognition software to detect the user's emotional state. For example, it uses an AI algorithm to identify emotions such as "happiness" or "relaxation" from eye movements and voice tone. This analysis result is output as emotional information.

[0520] Step 3:

[0521] The terminal combines detected emotion information with pre-entered meal information and sends it to the server via a secure communication protocol. The input consists of emotion information and meal information, and the output is a data package sent to the server.

[0522] Step 4:

[0523] The server integrates and analyzes the received emotion and food information. Using a generative AI model, it processes the data based on prompts to generate tableware designs. For example, the prompt might be "User's emotion is relaxed, food is Japanese." In this case, the output is the generated tableware design.

[0524] Step 5:

[0525] The server sends the generated design to the terminal. The terminal pushes the design data to a tableware unit equipped with an output device, displaying the design on the tableware's screen. This allows the user to enjoy a meal that harmonizes with their emotional state. The input is the generated design data, and the output is the design displayed on the tableware.

[0526] (Application Example 2)

[0527] 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."

[0528] In today's restaurant industry, providing a unique dining experience tailored to each customer's emotional state is challenging. Dynamically changing tableware designs based on customer emotions are a crucial element in achieving a more personalized and satisfying experience. However, conventional systems are static and cannot provide real-time, emotion-responsive designs, thus failing to meet the complex needs of customers.

[0529] 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.

[0530] In this invention, the server includes a device for acquiring emotional information, an analysis mechanism for evaluating the emotional state based on the acquired emotional information, and a computing device including a generative AI model that automatically generates tableware designs based on the emotional state and meal information. This enables the provision of special tableware designs tailored to the customer's emotional state in real time, making a personalized dining experience possible.

[0531] A "device for acquiring emotional information" is a device that collects a user's facial expressions and tone of voice in real time and obtains data on their emotional state at that moment.

[0532] An "emotional state evaluation mechanism" is a mechanism that analyzes acquired emotional information to identify what emotions the user is currently experiencing.

[0533] A "computational device including a generative AI model" is a computational device equipped with algorithms and processing power to generate appropriate designs based on emotional states and dietary information.

[0534] "Tableware with a display" refers to tableware equipped with a display function to visually display the generated design information.

[0535] The system that implements this application example uses the following components.

[0536] First, the user acquires emotional information through the smart glasses. The smart glasses are equipped with a camera and microphone, which can collect the user's facial expressions and tone of voice in real time. This information is used to evaluate the emotional state and is sent to a server in the cloud.

[0537] Next, the server uses an emotion recognition API to analyze emotional information and identify the user's emotional state. Based on this information, a computing unit including a generative AI model automatically generates an appropriate design. By using, for example, GPT-4 as the generative AI model, it is possible to dynamically create a design based on emotional state and meal information.

[0538] The generated design information is transmitted to the tableware with a display via a secure communication protocol. The tableware with a display then visually displays a design that harmonizes with the user's emotions, providing a special dining experience.

[0539] As a concrete example, when a user experiences a special anniversary dinner at a restaurant, the system recognizes the user's feelings of joy and provides high-quality tableware designs in real time. Examples of prompts for the generative AI model in this scenario include the following:

[0540] "The current user emotion is 'joy.' Based on this, please create a luxurious tableware design perfect for a special dinner. The color scheme should be primarily gold and white."

[0541] In this way, a personalized dining experience tailored to the user's emotions can be realized.

[0542] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0543] Step 1:

[0544] The device uses the smart device's camera and microphone to capture the user's facial expressions and tone of voice. This input data is then used to collect basic information about the user's emotions.

[0545] Step 2:

[0546] The collected emotional information is transmitted from the terminal to the server via a secure communication protocol. The input here is emotional information, and the output is encrypted data. The server accurately decrypts this received data and converts it into a format usable for analysis.

[0547] Step 3:

[0548] The server uses an emotion recognition API to analyze the acquired emotion information. The input is the emotion information mentioned earlier, and the output is the emotional state evaluated through the analysis. In this step, the API identifies the emotional state by combining facial recognition technology and voice analysis.

[0549] Step 4:

[0550] The server provides emotional state and pre-acquired meal information as input to a generating AI model, which then generates a design. The input consists of emotional state and meal characteristic information, and the output is the generated tableware design information. Based on these inputs, the generating AI model creates prompt statements and selects appropriate design elements.

[0551] Step 5:

[0552] The server transmits the design information obtained from the generating AI model to the tableware with a display. The input is design information, and the output is the visual design displayed on the tableware. The tableware with a display interprets the design data and provides visual feedback to the user.

[0553] Step 6:

[0554] The user visually experiences the design displayed on the tableware with a display. In this step, the user actually enjoys the displayed design while eating, gaining a new dining experience that matches their emotions.

[0555] 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.

[0556] 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.

[0557] 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.

[0558] [Fourth Embodiment]

[0559] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0560] 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.

[0561] 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).

[0562] 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.

[0563] 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.

[0564] 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).

[0565] 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.

[0566] 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.

[0567] 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.

[0568] 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.

[0569] 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.

[0570] 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.

[0571] 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".

[0572] This invention is a system that automatically generates appropriate tableware designs based on the content of a meal, providing a visually superior dining experience. This system mainly consists of a user terminal, a server, and tableware with a display.

[0573] Users input details of their daily meals into their device via a dedicated app. This includes the name of the dish, ingredients, and beverages. This information is then sent from the device to a server.

[0574] The server analyzes the received meal information and generates tableware designs using a generative AI model. Based on pre-trained data, the AI ​​model proposes designs that take into account color, pattern, and theme. For example, for Italian cuisine, it will generate a design incorporating traditional Italian motifs.

[0575] The generated design is transferred from the server to a terminal and then displayed on tableware equipped with a display. The terminal transmits the latest design information to the tableware via wireless communication, and the tableware displays the design in real time. This ensures that the visual presentation on the table harmonizes with the meal content, providing users with a themed visual experience.

[0576] Furthermore, users can choose to customize the design of the tableware, adjusting design elements according to their preferences. The customized design is also recalculated on the server, and the updated design is reflected on the tableware.

[0577] This invention allows users to easily enjoy a beautiful and unified dining experience every day, thereby improving their satisfaction with meals. For example, if a user selects Japanese cuisine, patterns such as cherry blossoms or ripples can be generated and applied to the entire tableware, enabling a wide variety of designs.

[0578] The following describes the processing flow.

[0579] Step 1:

[0580] The user launches a dedicated app on their device and enters the details of their meals for the day. They list the dish name, ingredients, and corresponding drinks, and then press the submit button.

[0581] Step 2:

[0582] The terminal receives input information from the user, processes the information, and sends it to the server. The information is encrypted using a secure protocol, protecting personal information.

[0583] Step 3:

[0584] The server analyzes the received meal information and inputs it into a generating AI model. Based on the ingredients and type of dish, the model analyzes the colors and patterns to generate tableware designs.

[0585] Step 4:

[0586] The server compiles the generated design as data and sends it to the terminal. The transmitted data is optimized for smaller file sizes, allowing for rapid processing on the terminal.

[0587] Step 5:

[0588] The terminal receives design data sent from the server and delivers it to the tableware with a display. The tableware immediately displays the received design, providing a dynamic visual experience at the dining table.

[0589] Step 6:

[0590] Users can view the tableware designs displayed on the screen and arrange them on the table. They can also customize the designs as needed and resubmit them to the server.

[0591] Step 7:

[0592] The device sends the customized design back to the server, and the new design is reflected on the tableware. This allows users to control a different visual experience for each meal.

[0593] (Example 1)

[0594] 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".

[0595] There are challenges in easily providing an environment that allows for visual enjoyment of meals and reflecting designs on tableware that match the content of each meal. Furthermore, there is a lack of efficient means for automatic design generation and customization. Additionally, security must be ensured when transferring meal information.

[0596] 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.

[0597] In this invention, the server includes a terminal device for receiving meal contents, an information processing device including a generative model for analyzing the received meal contents and generating design idea information, and means for transferring the generated design idea information to tableware equipped with a display function using wireless communication technology and displaying the design. This makes it possible to provide a design suitable for each meal in real time and improve the user's visual satisfaction. Furthermore, by using a secure means for communicating meal information, it is possible to process the information efficiently while maintaining its security.

[0598] "Meal details" refers to information about the name of the dish specified by the user, the ingredients used, and the beverages.

[0599] A "terminal device" is an electronic device used by users to input meal details and send that information to a server.

[0600] A "generative model" is a program equipped with AI technology to create design inspiration information based on meal content.

[0601] An "information processing device" is a computer device used to execute generative models, and its role is to analyze meal content and generate designs.

[0602] "Design inspiration information" refers to concept data for tableware designs based on colors, patterns, and themes proposed by a generative model.

[0603] "Wireless communication technology" refers to communication technology that transfers information from a terminal device to tableware without using cables.

[0604] "Tableware with a display function" refers to tableware that has the ability to display visual information based on received design inspiration information.

[0605] "Secure communication methods" refer to communication protocols and technologies designed to protect data confidentiality when transmitting information about food contents.

[0606] This invention relates to a system for applying displayable tableware with individual designs based on the contents of a meal. The system consists of a user terminal device, a server, a generative AI model, and tableware with a display function equipped with wireless communication technology.

[0607] Users input their daily meal details through a dedicated application using terminal devices such as mobile phones or computers. This meal information includes the dish name, main ingredients, and associated beverages. The entered meal details are securely transmitted from the terminal device to the server.

[0608] The server analyzes the received meal information and uses a generative AI model to create tableware designs. This AI model is trained on a vast amount of visual design pattern data and generates design proposals while considering colors, patterns, and themes appropriate for the meal. For example, if the user selects Italian cuisine, the AI ​​model will suggest a design incorporating traditional Italian patterns and appropriate color tones.

[0609] The generated design concept information is sent back from the server to a terminal device. The terminal device uses wireless communication technology to transfer the design information to tableware equipped with a display function. The tableware displays this design in real time, providing the user with a visual experience that harmonizes with the meal.

[0610] Furthermore, users can customize the design through the app. When a user requests changes to the design's colors or patterns, the changes are sent back to the server and re-analyzed by the generating AI model. The updated design is then quickly reflected on the tableware.

[0611] For example, if a user selects Japanese food, a design featuring cherry blossoms or ripples could be generated and projected onto the tableware. An example of a prompt to the generation AI model would be, "Please suggest a design that matches a menu that includes Japanese food." In this way, the aim is to enrich the daily dining experience and enhance visual satisfaction.

[0612] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0613] Step 1:

[0614] The user launches a dedicated application using a terminal device and enters details of their meal for the day. Specifically, they select the dish name (e.g., carbonara), main ingredients (e.g., pasta, bacon), and beverage (e.g., red wine). This information is entered into the terminal device as digital data.

[0615] Step 2:

[0616] The terminal device packages the meal information entered by the user and transmits it to the server via a secure communication protocol. Here, data encoding is performed to ensure that the meal information is transmitted accurately and safely. The input is digital data of the meal information, and the output is data communication.

[0617] Step 3:

[0618] The server analyzes the meal details received from the terminal device. Based on the analyzed information, a generative AI model constructs prompt sentences and generates tableware designs. These prompt sentences are based on the meal theme, and the AI ​​model selects the optimal design elements from pre-trained data to generate design inspiration information. The input is the meal details based on the prompt sentences, and the output is design inspiration information.

[0619] Step 4:

[0620] The server sends the generated design idea information back to the terminal device. The server converts the data into a format that the terminal device can receive. During this process, the format is adjusted to ensure that the design data is received correctly. The input is the design idea information, and the output is the converted design data.

[0621] Step 5:

[0622] The terminal device analyzes the received design data and transmits it to tableware equipped with a display function using wireless communication technology. The tableware receives this data in real time and displays the new design on its display. This visually provides a design that reflects the contents of the meal. The input is the converted design data, and the output is the design display on the tableware.

[0623] Step 6:

[0624] Users can customize the design of their tableware using the app. For example, if they change the colors or patterns, that information is sent back to the server from the terminal device. The server generates new design inspiration information and displays it on the tableware through the terminal device. The input is the user's customization information, and the output is the updated design inspiration information.

[0625] (Application Example 1)

[0626] 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".

[0627] While the visual experience is increasingly important in the modern food and beverage industry, providing consistent tableware designs based on individual dining information is complex. Traditional methods make it difficult to instantly change designs to meet individual customer needs, resulting in decreased customer satisfaction. Furthermore, there is a lack of systems that are easy for users to operate and provide real-time visualization.

[0628] 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.

[0629] In this invention, the server includes a device for inputting meal information, an information processing device including a generation algorithm that automatically generates tableware designs based on the input information, and a device for transmitting and displaying the generated design information on tableware equipped with a visual output device. This enables restaurants to input meal information using a visualization device and display the corresponding design in real time.

[0630] A "device for inputting meal information" is an electronic input device used by users to input information about meals, such as ingredients and dish names.

[0631] An "information processing device including a generation algorithm" is a computing device that runs a program that automatically generates tableware designs based on input meal information.

[0632] "Tableware with a visual output device" refers to tableware equipped with a display function for displaying generated design information.

[0633] "Means of inputting meal information using visualization devices" refers to methods in which users input meal information while being visually assisted through devices such as smart glasses or head-mounted displays.

[0634] "A means of updating the display in real time" refers to a system that instantly changes design information based on meal information and user requests, and displays the latest design on tableware equipped with a visual output device.

[0635] The system for implementing this invention aims to improve the visual experience in the food and beverage industry, and in particular enables the real-time generation and display of tableware designs based on individual meal information. The detailed method for implementing the invention is described below.

[0636] Users input meal information using visualization devices such as smart glasses or head-mounted displays. This information includes ingredients, dish names, and themes. This information is then transmitted from the device to the server.

[0637] The server runs using Python as part of the information processing unit and executes a generative AI model. The model is built using TensorFlow or PyTorch and generates designs based on input meal information. This algorithm considers design elements related to color, pattern, and theme to construct visually appealing designs.

[0638] Design information generated from the server is transmitted wirelessly to tableware equipped with a visual output device. This tableware utilizes electronic paper technology to display and update the design in real time.

[0639] As a concrete example, let's consider the case where a user orders a Japanese meal called "Sakura Gozen" at a restaurant. In this case, when the user types "Sakura Gozen," the server will suggest a design themed around cherry blossom petals.

[0640] Examples of prompt statements for a generative AI model are shown below.

[0641] "Meal details: Sakura Gozen (cherry blossom set meal), Season: Spring, Features: Generates a design based on flower petals."

[0642] In this way, the present invention can improve the overall dining experience in the food and beverage industry, and in particular enhance customer satisfaction by providing visually harmonious tableware designs.

[0643] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0644] Step 1:

[0645] Users input meal information using smart glasses or head-mounted displays. This information includes dish names, ingredients, and themes. This allows for the generation of designs tailored to user needs, and initial data is collected.

[0646] Step 2:

[0647] The terminal sends the user's entered meal information to the server. The transmitted information arrives at the server via a secure communication protocol. At this stage, the input information is organized as data and prepared for the next analysis process.

[0648] Step 3:

[0649] The server generates a design using a generative AI model based on the received meal information. An example of a prompt is, "Meal details: Sakura Gozen, Season: Spring, Features: Generate a design with a flower petal motif." The AI ​​model takes meal information as input and outputs new design data by combining elements of color, pattern, and theme based on this information.

[0650] Step 4:

[0651] The server returns the generated design information to the terminal, which then wirelessly transmits this information to the tableware equipped with a visual output device. Here, the design information is treated as wireless data and then formatted into a format that can be reflected on the tableware.

[0652] Step 5:

[0653] Tableware equipped with a visual output device applies received design information to an e-paper display, showing the design in real time. At this stage, a design tailored to the theme of the meal is materialized on the tableware, creating a visual effect before the user's eyes.

[0654] 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.

[0655] This invention provides a system that recognizes user emotions and dynamically adjusts the design of tableware based on those emotions in order to improve the dining experience. The system consists of a user terminal, a server, an emotion engine, and tableware with a display.

[0656] The user acquires emotional information using the device's camera and microphone. The device collects facial expressions and tone of voice as the user sits in front of the device and begins to eat. The device processes the collected data in real time to recognize the user's emotions.

[0657] The emotion engine analyzes the collected data and evaluates the user's current emotional state (e.g., happiness, surprise, anxiety). This identifies what emotion the user is experiencing.

[0658] The device sends emotional data along with meal information to the server. A secure communication protocol is used for information transmission, and appropriate encryption is performed to protect privacy.

[0659] The server integrates and analyzes the received meal information and emotional data. The generative AI model takes both datasets as input and generates tableware designs. The generated designs reflect the user's emotions in addition to the characteristics of the ingredients and dishes. For example, if the user is in a happy state, a design with bright and vibrant colors will be selected.

[0660] Ultimately, the terminal receives the design data from the server and sends it to the display-equipped tableware, which displays it instantly. Users can then enjoy their dining experience with tableware featuring visually harmonious designs that match their emotions and the content of their meal.

[0661] For example, when a user is enjoying Japanese food and is in a relaxed emotional state, a design featuring traditional Japanese patterns adorned with gentle blues and greens will be displayed, providing a visually relaxing environment. This system allows users to experience a new dining experience that is in sync with their emotions.

[0662] The following describes the processing flow.

[0663] Step 1:

[0664] The user launches a dedicated app on their device and grants permission to use the camera and microphone. This allows the device to capture the user's facial expressions and voice in real time.

[0665] Step 2:

[0666] The device collects the user's facial video and audio data, and uses this to activate an emotion engine. The emotion engine analyzes facial features and voice tone to infer the user's emotional state.

[0667] Step 3:

[0668] The device combines the emotional data recognized by the emotion engine with the meal information entered by the user into the app, and sends it to the server. Communication is conducted through a secure protocol.

[0669] Step 4:

[0670] The server receives meal information and emotional data and analyzes them. A generative AI model generates the optimal tableware design based on the meal and emotions. For example, if the emotion is "happiness," a bright and refreshing design will be selected.

[0671] Step 5:

[0672] The server generates design data and sends it back to the terminal. This data includes color and pattern information that reflects emotions.

[0673] Step 6:

[0674] The terminal receives design data and sends it to the tableware with a display, which instantly displays the new design. This process allows for a visual presentation at the dining table that harmonizes with the user's emotions.

[0675] Step 7:

[0676] Users enjoy meals with tableware designed to match their emotions. The design can be customized, regenerated, and reapplied as needed.

[0677] (Example 2)

[0678] 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".

[0679] To improve the dining experience, it is necessary to dynamically adjust visual elements according to the emotional state of individual users. However, conventional methods are limited to static design generation based solely on dining information, and have the challenge of not being able to dynamically adjust designs that incorporate user emotions.

[0680] 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.

[0681] In this invention, the server includes means for inputting meal information, an information processing device including a generation model that automatically generates tableware designs based on the input meal information and emotional information, means for transmitting and displaying the generated design information to tableware equipped with an output device, and means for providing an input device for acquiring emotional information. This makes it possible to generate and display dynamic tableware designs that take into account the user's emotional state and meal content.

[0682] "Dietary information" refers to information that includes the type of meal, the theme of the dish, and other related data.

[0683] "Emotional information" refers to data indicating the emotional state of a user, obtained based on their facial expressions and tone of voice.

[0684] A "generative model" is a model that includes an algorithm that automatically generates tableware designs based on input data.

[0685] An "information processing device" refers to an electronic computer that collects, analyzes, and outputs data.

[0686] "Tableware with an output device" refers to tableware equipped with a display device that has the function of displaying the generated design in real time.

[0687] An "input device" is hardware or software used to acquire data from a user.

[0688] A "secure communication protocol" is a protocol that includes security technologies used to protect data transmission.

[0689] This invention is a system designed to enhance the dining experience. The system consists of a terminal, a server, a device for recognizing user emotions, and tableware with an output device.

[0690] The device is equipped with the ability to acquire user emotional information. Specifically, it uses a built-in camera and microphone to capture and record the user's facial expressions and tone of voice in real time. Then, emotion recognition software processes this data to recognize the user's current emotions.

[0691] The emotion engine analyzes data collected by the device to evaluate the user's emotional state in detail. This analysis, along with meal information, is sent to the server using a secure communication protocol.

[0692] The server integrates and analyzes the received emotional and food information. Here, a generative AI model plays a crucial role. The model automatically generates tableware designs based on specified prompt sentences. An example of a prompt sentence might be, "User's emotion is relaxed, food is Japanese." Based on this sentence, a design combining traditional Japanese patterns with soft blues and greens is generated.

[0693] The generated design is pushed to tableware equipped with an output device via a terminal. The generated design is immediately displayed on the tableware's display, allowing the user to enjoy a dining experience that is in harmony with their emotions.

[0694] The above is an overview of the system for carrying out this invention. Depending on the hardware and software used, this system can provide customized designs that respond to a variety of emotional states and eating styles.

[0695] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0696] Step 1:

[0697] The user sits in front of the device and begins eating. The device's camera and microphone capture and record the user's facial expressions and tone of voice. This allows for the acquisition of emotional information. The input consists of the user's real-time video and audio.

[0698] Step 2:

[0699] The device analyzes the acquired video and audio using emotion recognition software to detect the user's emotional state. For example, it uses an AI algorithm to identify emotions such as "happiness" or "relaxation" from eye movements and voice tone. This analysis result is output as emotional information.

[0700] Step 3:

[0701] The terminal combines detected emotion information with pre-entered meal information and sends it to the server via a secure communication protocol. The input consists of emotion information and meal information, and the output is a data package sent to the server.

[0702] Step 4:

[0703] The server integrates and analyzes the received emotion and food information. Using a generative AI model, it processes the data based on prompts to generate tableware designs. For example, the prompt might be "User's emotion is relaxed, food is Japanese." In this case, the output is the generated tableware design.

[0704] Step 5:

[0705] The server sends the generated design to the terminal. The terminal pushes the design data to a tableware unit equipped with an output device, displaying the design on the tableware's screen. This allows the user to enjoy a meal that harmonizes with their emotional state. The input is the generated design data, and the output is the design displayed on the tableware.

[0706] (Application Example 2)

[0707] 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".

[0708] In today's restaurant industry, providing a unique dining experience tailored to each customer's emotional state is challenging. Dynamically changing tableware designs based on customer emotions are a crucial element in achieving a more personalized and satisfying experience. However, conventional systems are static and cannot provide real-time, emotion-responsive designs, thus failing to meet the complex needs of customers.

[0709] 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.

[0710] In this invention, the server includes a device for acquiring emotional information, an analysis mechanism for evaluating the emotional state based on the acquired emotional information, and a computing device including a generative AI model that automatically generates tableware designs based on the emotional state and meal information. This enables the provision of special tableware designs tailored to the customer's emotional state in real time, making a personalized dining experience possible.

[0711] A "device for acquiring emotional information" is a device that collects a user's facial expressions and tone of voice in real time and obtains data on their emotional state at that moment.

[0712] An "emotional state evaluation mechanism" is a mechanism that analyzes acquired emotional information to identify what emotions the user is currently experiencing.

[0713] A "computational device including a generative AI model" is a computational device equipped with algorithms and processing power to generate appropriate designs based on emotional states and dietary information.

[0714] "Tableware with a display" refers to tableware equipped with a display function to visually display the generated design information.

[0715] The system that implements this application example uses the following components.

[0716] First, the user acquires emotional information through the smart glasses. The smart glasses are equipped with a camera and microphone, which can collect the user's facial expressions and tone of voice in real time. This information is used to evaluate the emotional state and is sent to a server in the cloud.

[0717] Next, the server uses an emotion recognition API to analyze emotional information and identify the user's emotional state. Based on this information, a computing unit including a generative AI model automatically generates an appropriate design. By using, for example, GPT-4 as the generative AI model, it is possible to dynamically create a design based on emotional state and meal information.

[0718] The generated design information is transmitted to the tableware with a display via a secure communication protocol. The tableware with a display then visually displays a design that harmonizes with the user's emotions, providing a special dining experience.

[0719] As a concrete example, when a user experiences a special anniversary dinner at a restaurant, the system recognizes the user's feelings of joy and provides high-quality tableware designs in real time. Examples of prompts for the generative AI model in this scenario include the following:

[0720] "The current user emotion is 'joy.' Based on this, please create a luxurious tableware design perfect for a special dinner. The color scheme should be primarily gold and white."

[0721] In this way, a personalized dining experience tailored to the user's emotions can be realized.

[0722] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0723] Step 1:

[0724] The device uses the smart device's camera and microphone to capture the user's facial expressions and tone of voice. This input data is then used to collect basic information about the user's emotions.

[0725] Step 2:

[0726] The collected emotional information is transmitted from the terminal to the server via a secure communication protocol. The input here is emotional information, and the output is encrypted data. The server accurately decrypts this received data and converts it into a format usable for analysis.

[0727] Step 3:

[0728] The server uses an emotion recognition API to analyze the acquired emotion information. The input is the emotion information mentioned earlier, and the output is the emotional state evaluated through the analysis. In this step, the API identifies the emotional state by combining facial recognition technology and voice analysis.

[0729] Step 4:

[0730] The server provides emotional state and pre-acquired meal information as input to a generating AI model, which then generates a design. The input consists of emotional state and meal characteristic information, and the output is the generated tableware design information. Based on these inputs, the generating AI model creates prompt statements and selects appropriate design elements.

[0731] Step 5:

[0732] The server transmits the design information obtained from the generative AI model to the tableware with a display. The input is design information, and the output is the visual design displayed on the tableware. The tableware with a display interprets the design data and provides visual feedback to the user.

[0733] Step 6:

[0734] The user visually experiences the design displayed on the tableware with a display. In this step, the user actually enjoys the displayed design while eating, gaining a new dining experience that matches their emotions.

[0735] 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.

[0736] 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.

[0737] 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.

[0738] 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.

[0739] 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.

[0740] 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.

[0741] 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.

[0742] 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.

[0743] 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."

[0744] 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.

[0745] 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.

[0746] 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.

[0747] 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.

[0748] 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.

[0749] 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.

[0750] 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.

[0751] 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.

[0752] 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.

[0753] 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.

[0754] 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.

[0755] 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.

[0756] The following is further disclosed regarding the embodiments described above.

[0757] (Claim 1)

[0758] A means of entering meal information,

[0759] A computer including a generative model that automatically generates tableware designs based on input meal information,

[0760] A means of transmitting and displaying the generated design information on tableware equipped with a display,

[0761] A system that includes this.

[0762] (Claim 2)

[0763] The system according to claim 1, wherein the generative model selects design elements related to color, pattern, and theme based on meal information to generate a design.

[0764] (Claim 3)

[0765] The system according to claim 1, comprising means for transmitting meal information using a secure communication protocol.

[0766] "Example 1"

[0767] (Claim 1)

[0768] A terminal device for receiving meal details,

[0769] An information processing device that includes a generative model that analyzes the contents of a received meal and generates design inspiration information,

[0770] A means of transferring generated design concept information to tableware equipped with a display function using wireless communication technology, and displaying the design,

[0771] A system that includes this.

[0772] (Claim 2)

[0773] The system according to claim 1, wherein the generative model determines design elements related to color, pattern, and theme based on the contents of the meal, and generates design inspiration information.

[0774] (Claim 3)

[0775] The system according to claim 1, comprising means for transmitting meal contents to an information processing device using secure communication means.

[0776] "Application Example 1"

[0777] (Claim 1)

[0778] A device for inputting meal information,

[0779] An information processing device including a generation algorithm that automatically generates tableware designs based on input meal information,

[0780] A device that transmits and displays the generated design information on tableware equipped with a visual output device,

[0781] A means for users to input meal information using a visualization device,

[0782] A tableware equipped with a visual output device communicates and receives a design transmitted from an information processing device, and has a means to update the display in real time.

[0783] A system that includes this.

[0784] (Claim 2)

[0785] The system according to claim 1, wherein a generation algorithm selects design elements related to color, pattern, and theme based on meal information to generate a design, and displays it on tableware equipped with a visual output device.

[0786] (Claim 3)

[0787] The system according to claim 1, comprising a device for transmitting meal information to an information processing device using a secure communication means and for transmitting it to tableware equipped with a visual output device.

[0788] "Example 2 of combining an emotion engine"

[0789] (Claim 1)

[0790] A means of entering meal information,

[0791] An information processing device including a generative model that automatically generates tableware designs based on input meal information and emotional information,

[0792] A means for transmitting and displaying the generated design information on tableware equipped with an output device,

[0793] A means equipped with an input device for acquiring emotional information,

[0794] A system that includes this.

[0795] (Claim 2)

[0796] The system according to claim 1, wherein the generative model selects design elements related to color, shape, and theme based on meal information and emotional information to generate a design.

[0797] (Claim 3)

[0798] The system according to claim 1, comprising means for transmitting meal information and emotional information using a secure communication protocol.

[0799] "Application example 2 when combining with an emotional engine"

[0800] (Claim 1)

[0801] A device for acquiring emotional information,

[0802] An analytical mechanism that evaluates emotional states based on acquired emotional information,

[0803] A computing device including a generative AI model that automatically generates tableware designs based on emotional state and meal information,

[0804] A device that transmits and displays the generated design information on tableware with a display,

[0805] A system that includes this.

[0806] (Claim 2)

[0807] The system according to claim 1, wherein a generative AI model selects design elements related to color, pattern, and theme based on emotional state and dietary information to generate a design.

[0808] (Claim 3)

[0809] The system according to claim 1, comprising a device for transmitting emotional information and meal information using a secure communication protocol. [Explanation of Symbols]

[0810] 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 of entering meal information, A computer including a generative model that automatically generates tableware designs based on input meal information, A means of transmitting and displaying the generated design information on tableware equipped with a display, A system that includes this.

2. The system according to claim 1, wherein the generative model selects design elements related to color, pattern, and theme based on meal information to generate a design.

3. The system according to claim 1, comprising means for transmitting meal information using a secure communication protocol.

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