system

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving ingredient information, a recipe, calorie restriction, and allergy information of a new menu input by a restaurant or a food-related company; means for verifying a format of the input information; means for analyzing the received information using a generation AI and virtually providing ingredient information, calorie calculation, halal adaptive information, and allergy information; and means for generating virtual serving images using VR and modeling technology.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional new menu development requires actual ingredients and cooking, which takes a great deal of time and money. It is also difficult to quickly provide new menu items that meet customer needs, placing a heavy burden on small and medium-sized restaurants in particular. Furthermore, food waste and food waste have become problems, calling for efficient resource utilization. It is necessary to solve these problems and promote the growth of a sustainable food industry. [Means for solving the problem]

[0005] The present invention provides a means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related businesses and validating the format of the input data. It also includes a means for virtually providing ingredient data, calorie calculations, halal compliance information, and allergy information using generative AI. Furthermore, the system utilizes VR and modeling technology to generate virtual presentation images and provides a means for transmitting the analysis results and virtual presentation images to a terminal, thereby enabling the efficient evaluation and development of new menu items without the need for actual cooking or ingredients. It also includes a means for accepting feedback from users and reanalyzing the results based on that feedback. It also includes a method for generating reports for evaluating new menu items and providing virtual presentation images from all angles using 3D modeling technology. This streamlines the new menu development process and reduces waste and food loss.

[0006] "Means for verifying whether the format of input data is correct" refers to a means that has the function of checking whether the data entered by the user, such as ingredient information, cooking methods, and restrictions (calories, allergy information, etc.), is in the correct format.

[0007] "Means for analyzing received information using generative AI" refers to means that utilizes artificial intelligence technology to analyze received input data and generate food ingredient data, calorie calculations, halal compliance information, allergy information, etc.

[0008] "Ingredient component data" is detailed information such as the nutritional components and calories contained in each ingredient.

[0009] "Calculating calories" is the process of calculating the total calories when multiple ingredients are used.

[0010] "Halal compliance information" refers to information on whether ingredients and cooking methods comply with Islamic law.

[0011] "Allergy information" is information about allergens contained in the input ingredients and cooking methods.

[0012] "Virtual provision means" refers to means that have the function of providing information digitally without using actual cooking or ingredients.

[0013] "Means for generating using VR and modeling technology" refers to means that have the function of generating virtual presentation images of ingredients and dishes using virtual reality and 3D modeling technology.

[0014] A "virtual presentation image" is an image or model that virtually reproduces the appearance and presentation of ingredients or dishes.

[0015] The "means for transmitting the analysis results and the virtual presentation image to the terminal" is a means having the function of transferring the analyzed data and the generated virtual presentation image to the terminal used by the user.

[0016] "Means for receiving feedback" refers to means that has a function for receiving opinions and correction requests from users.

[0017] A "means for reanalysis" is a means that has the function of performing a new analysis based on the received feedback.

[0018] The "means for generating a report" is a means having a function for creating a report summarizing the evaluation results and analysis data of a new menu.

[0019] "Virtual presentation image from all directions using 3D modeling technology" is a virtual presentation image of ingredients and dishes that can be viewed from all directions using 3D modeling technology. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0021] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0022] First, the terms used in the following description will be explained.

[0023] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0024] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0025] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0026] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0027] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0031] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0032] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0033] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0034] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0035] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0038] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0039] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0040] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0041] The virtual food testing system of the present invention supports the rapid and efficient development of new menu items through the cooperation of users, terminals, and servers. This system allows restaurants and food-related businesses to input information about ingredients, cooking methods, and restrictions for new menu items, and then analyzes the information to provide a virtual evaluation and image. The specific operation of the system is described below.

[0042] System Objectives

[0043] The main purpose of this system is to streamline the process of new menu development and reduce costs and time by conducting virtual evaluations without using actual ingredients or cooking. Furthermore, it will reduce food waste and promote the growth of a sustainable food industry.

[0044] System configuration

[0045] The main components of the system are:

[0046] User device: A computer, tablet, or other input device used by a restaurant or food-related business.

[0047] Server: A central computer that performs analytical processing and generates various data using generative AI.

[0048] Generative AI: Artificial intelligence techniques for performing data analysis.

[0049] VR and 3D modeling technology: Technology for creating virtual presentation images.

[0050] Processing Details

[0051] Below, we will explain how each component works together and its specific operation using concrete examples.

[0052] User: Create and submit input data

[0053] The user uses the terminal to input the cooking method, ingredient information, calorie restrictions, allergy information, etc. of the new menu item. For example, if you want to develop a "low-calorie pasta," you would input the following information:

[0054] Ingredients: Pasta, tomatoes, olive oil, basil

[0055] Cooking method: boiling, frying

[0056] Calorie restriction: 500 kcal or less

[0057] Allergy Information: Gluten Free

[0058] After completing the input, the user presses a button to transmit the data.

[0059] Terminal: Data transmission and validation

[0060] The terminal temporarily stores the data entered by the user and checks whether the format is correct (validation). For example, it checks whether all required fields have been entered, whether the numerical range is correct, etc. If there are no problems, it sends the data to the server.

[0061] Server: Receives and analyzes data

[0062] The server receives the data sent from the device and begins analysis using the AI. Specifically, it retrieves the nutritional information of each ingredient from the ingredient database and calculates the total calories, allergy information, halal compliance information, etc. For example, it retrieves the nutritional information for pasta, tomato, olive oil, and basil, and calculates the total calories as 480 kcal.

[0063] Server: Generate virtual presentation images

[0064] The server then uses VR and 3D modeling technology to generate a virtual presentation of the new menu item, which is then presented as a 3D model that can be viewed from all angles.

[0065] Server: Sending analysis results

[0066] The analysis results and virtual presentation images are sent from the server to the device, including the following information:

[0067] Total calories: 480 kcal

[0068] Nutritional Information: High in Vitamin C and Iron

[0069] Allergy Information: Gluten Free

[0070] Halal compatibility: Considered

[0071] Presentation image: 3D model (all-directional view)

[0072] Terminal: Display of analysis results

[0073] The terminal displays the information received from the server to the user, allowing the user to check the final image of the new menu, as well as information on ingredients and allergies.

[0074] Users: Send feedback and refine

[0075] Users can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the device, and a new analysis is performed.

[0076] In this way, the virtual food testing system enables the new menu development process to proceed efficiently, reducing costs and food waste.

[0077] The processing flow will be explained below.

[0078] Step 1:

[0079] Users input information about ingredients, cooking methods, calorie restrictions, and allergies into the terminal to develop new menu items. Once input is complete, the data is sent by pressing the send button.

[0080] Step 2:

[0081] The terminal temporarily stores the data entered by the user. Then it validates whether the data format is correct, whether all required fields have been entered, whether the numerical range is correct, etc. If the data is valid, the terminal sends the data to the server.

[0082] Step 3:

[0083] The server receives the data sent from the device, stores it, and then converts it into the format required for analysis.

[0084] Step 4:

[0085] The server uses AI to analyze the received data. Here, it retrieves nutritional information for each ingredient from the ingredient database and generates calorie calculations, halal compliance information, and allergy information. For example, in the case of "low-calorie pasta," the ingredient data for pasta, tomato, olive oil, and basil are retrieved, and the total calories are calculated as 480 kcal.

[0086] Step 5:

[0087] The server uses VR and 3D modeling technology to generate a virtual presentation image based on the analysis results, and the generated image is provided as a 3D model that can be viewed from all angles.

[0088] Step 6:

[0089] The server sends the analysis results and virtual presentation images to the device, including data such as total calories, nutritional information, allergy information, halal compliance information, and 3D presentation images.

[0090] Step 7:

[0091] The terminal displays the analysis results received from the server and a virtual presentation image to the user, who can then check the finished image of the new menu, as well as ingredient and allergy information.

[0092] Step 8:

[0093] The user can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the terminal.

[0094] Step 9:

[0095] The server receives feedback from the user, performs a new analysis with necessary adjustments, and then generates the reanalysis results and a new virtual presentation image, which are then sent to the terminal again.

[0096] Through this series of processes, users can efficiently develop and evaluate new menu items, saving time and money, and is also expected to reduce food waste and food waste.

[0097] Example 1

[0098] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0099] The traditional new menu development process requires repeated trial production using actual ingredients, which is costly and time-consuming. Furthermore, failures and readjustments during the trial production stage result in food waste and food waste, which does not contribute to the development of a sustainable food industry. Furthermore, managing ingredient and allergy information is cumbersome and prone to errors.

[0100] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0101] In this invention, the server includes means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related companies, means for verifying that the format of the entered information is correct, means for analyzing the received information using a generative AI model and virtually providing ingredient data, calorie calculations, halal compliance information, and allergy information, means for generating a virtual presentation image using 3D representation technology, and means for transmitting the analysis results and the virtual presentation image to a terminal for displaying them. This allows new menu items to be virtually evaluated and improved without using actual ingredients, thereby reducing costs and food waste and making new menu development more efficient.

[0102] A "restaurant or food-related business" is a business that serves meals or is engaged in the manufacture and sale of food.

[0103] "New menu" refers to the content and combination of newly developed dishes that will be added to the existing menu.

[0104] "Ingredient information" is detailed information such as the names, types, and quantities of ingredients used in the new menu.

[0105] "Cooking method" refers to the specific techniques and processes used to cook ingredients.

[0106] "Calorie restriction" is the upper limit on the total calorie content of a diet set for health and nutritional management.

[0107] "Allergy information" refers to information on whether a consumer may have an allergic reaction to a particular food ingredient.

[0108] "Means for receiving" refers to a method or system for taking in data or information from the outside.

[0109] A "verification means" is a method or system for checking the accuracy and format of the information entered.

[0110] A "generative AI model" is an artificial intelligence algorithm or program that is trained to analyze data and generate new information.

[0111] "Means for analysis" refers to a system or method that examines the received data in detail and extracts and calculates the necessary information.

[0112] "Food ingredient data" is detailed information about the nutritional content and chemical composition of food.

[0113] "Halal compliance information" is information about ingredients and cooking methods that are permitted according to specific religious regulations.

[0114] "Means for providing" refers to a system or method for displaying or transmitting the analyzed or generated information to the user.

[0115] "Three-dimensional representation technology" refers to techniques and methods for visually representing objects and landscapes in three-dimensional space.

[0116] A "terminal" is a device, such as a computer or tablet, that a user uses to enter data or view results.

[0117] "Feedback" refers to opinions and requests for improvement from users regarding analysis results and provided information.

[0118] "Reanalysis" refers to the process of reanalyzing data based on feedback and making corrections or improvements.

[0119] A "report" is a document or electronic file that summarizes analysis results and evaluation information.

[0120] "Omnidirectional viewing" refers to a display method that allows objects in three-dimensional space to be viewed from all angles.

[0121] The virtual food testing system of the present invention supports the rapid and efficient development of new menu items through the cooperation of users, terminals, and servers. This system allows restaurants and food-related businesses to input information on ingredients, cooking methods, calorie restrictions, and allergy information for new menu items, and performs analysis based on this information to provide virtual evaluations and images.

[0122] System configuration

[0123] The main components of the system are:

[0124] User device: An input device such as a computer or tablet used by food-related companies.

[0125] Server: A central computer that performs analytical processing and generates data using generative AI.

[0126] Generative AI: Artificial intelligence technology for data analysis (specifically, using TENSORFLOW (registered trademark) and PyTorch).

[0127] 3D representation technology: Technology for creating virtual presentation images (using Blender and Unity).

[0128] System Operation

[0129] User: Create and submit input data

[0130] The user uses the terminal to input the cooking method, ingredient information, calorie restrictions, allergy information, etc. of the new menu item. For example, if you want to develop a "low-calorie pasta," you would input the following information:

[0131] Ingredients: Pasta, tomatoes, olive oil, basil

[0132] Cooking method: boiling, frying

[0133] Calorie restriction: 500 kcal or less

[0134] Allergy Information: Gluten Free

[0135] After completing the input, the user presses a button to transmit the data.

[0136] Terminal: Data transmission and validation

[0137] The device temporarily stores the data entered by the user and checks whether the format is correct. First, it checks whether all required fields have been entered, and then it checks whether the calorie value and allergy information are within the appropriate range. After checking, the data is sent to the server.

[0138] Server: Receives and analyzes data

[0139] The server receives the data sent from the device and analyzes it using a generative AI model. First, it obtains the nutritional information for each ingredient from the ingredient database. It then calculates the total calories, allergy information, and halal compliance information. For example, based on the ingredient information for pasta, tomato, olive oil, and basil, it calculates the total calories as 480 kcal.

[0140] Server: Generate virtual presentation images

[0141] The server uses 3D rendering technology to generate a virtual presentation of the new menu item, which is then presented as a 3D model that users can view from all angles.

[0142] Server: Sending analysis results

[0143] The analysis results and virtual presentation images are sent from the server to the device, including the following information:

[0144] Total calories: 480 kcal

[0145] Nutritional Information: High in Vitamin C and Iron

[0146] Allergy Information: Gluten Free

[0147] Halal compatibility: Considered

[0148] Presentation image: 3D model (all-directional view)

[0149] Terminal: Display of analysis results

[0150] The terminal displays the information received from the server to the user, allowing the user to check the final image of the new menu, as well as information on ingredients and allergies.

[0151] Users: Send feedback and refine

[0152] The user can input feedback based on the analysis results, such as if the calorie content is too high or if they would like to change the combination of ingredients, and the feedback is sent from the device to the server.

[0153] The server performs a new analysis and sends the retuned data back to the device, allowing the user to easily make further adjustments.

[0154] In this way, the virtual food testing system streamlines the process of new menu development, reducing costs and food waste and promoting the growth of a sustainable food industry.

[0155] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0156] Step 1: Data entry

[0157] The user uses the terminal to input information about the new menu item. Specifically, they enter information about ingredients, cooking methods, calorie restrictions, allergy information, etc. into a form. For example, if you want to develop a "low-calorie pasta," you would enter the following information:

[0158] Ingredients: Pasta, tomatoes, olive oil, basil

[0159] Cooking method: boiling, frying

[0160] Calorie restriction: 500 kcal or less

[0161] Allergy Information: Gluten Free

[0162] Input: Ingredient information, cooking method, calorie restrictions, allergy information

[0163] Output: Save to device

[0164] Step 2: Submit and validate data

[0165] The terminal temporarily stores the data entered by the user. It then validates that the data format is correct. It checks that all required fields have been entered and that calorie values ​​and allergy information are within the range. If validation is successful, it sends the data to the server.

[0166] Input: Data entered by the user

[0167] Data manipulation: format and range checks

[0168] Output: Send data to the server

[0169] Specific behavior:

[0170] 1. Check the required fields

[0171] 2. Check the range of calorie values ​​and allergy information

[0172] 3. Sending data to the server

[0173] Step 3: Receiving and analyzing data

[0174] The server receives the data sent from the device. It then begins analyzing the data using a generative AI model. It obtains nutritional information for each ingredient from the ingredient database and calculates total calories, allergy information, and halal compliance information. For example, based on the ingredient information for pasta, tomato, olive oil, and basil, it calculates the total calories to be 480 kcal.

[0175] Input: Data sent from the terminal

[0176] Data processing: Obtaining nutritional information using a generative AI model and calculating total calories, allergy information, and halal compliance information

[0177] Output: Analysis results

[0178] Specific behavior:

[0179] 1. Obtain information from a food ingredient database

[0180] 2. Calculate total calories and other nutritional information

[0181] Step 4: Generate a virtual presentation image

[0182] The server uses 3D rendering technology to generate a virtual presentation image of the new menu item, which is then presented as a 3D model that users can view from any angle.

[0183] Input: Analysis results

[0184] Data processing: Image generation using 3D expression technology (Blender or Unity)

[0185] Output: Virtual presentation image of 3D model

[0186] Specific behavior:

[0187] 1. 3D modeling of a virtual presentation image

[0188] 2. Provide a format that can be viewed from all angles

[0189] Step 5: Submitting the analysis results

[0190] The server sends the analysis results and the virtual presentation image to the device. The analysis results include the following information:

[0191] Total calories: 480 kcal

[0192] Nutritional Information: High in Vitamin C and Iron

[0193] Allergy Information: Gluten Free

[0194] Halal compatibility: Considered

[0195] Presentation image: 3D model (all-directional view)

[0196] Input: Analysis results, virtual arrangement image of 3D model

[0197] Output: Send to terminal

[0198] Step 6: Viewing the analysis results

[0199] The terminal displays the information received from the server to the user, who can check the finished image of the new menu, as well as information on ingredients and allergies.

[0200] Input: Analysis results and 3D model from the server

[0201] Output: What is displayed to the user

[0202] Specific behavior:

[0203] 1. Display analysis results and 3D models on your device

[0204] Step 7: Provide feedback and refine

[0205] The user inputs feedback based on the analysis results and sends it from the device to the server. The server receives the user's feedback, performs re-analysis using the generative AI model, and then sends the corrected data back to the device.

[0206] Input: User feedback

[0207] Data processing: Reanalysis using generative AI models

[0208] Output: Re-send the corrected analysis results to the terminal

[0209] Specific behavior:

[0210] 1. Receiving Feedback

[0211] 2. Perform reanalysis

[0212] 3. Sending the reanalysis results to the device

[0213] Through these steps, the virtual food testing system streamlines the new menu development process, reducing costs and food waste.

[0214] (Application example 1)

[0215] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0216] The traditional new menu development process required the use of actual ingredients and cooking, which was time-consuming and costly, and required a large number of resources to evaluate new menu items. Furthermore, the food delivery industry is required to quickly provide new menu items in a short amount of time, but there was no efficient way to achieve this. Furthermore, there was a lack of a system for virtually evaluating menu items without actual tasting, thereby improving customer satisfaction.

[0217] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0218] In this invention, the server includes: means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related companies; means for verifying the correct format of the entered information; means for analyzing the received information using generation AI and virtually providing ingredient data, calorie calculations, halal compliance information, and allergy information; means for generating virtual presentation images using VR and modeling technology; means for transmitting the analysis results and the virtual presentation images to a terminal for displaying them; and means for, as a virtual food delivery development support app, allowing users to enter feedback, reanalyze the results, and support the evaluation of new menu items, including readjustments. This allows for an efficient process for new menu development, reducing costs and food waste.

[0219] "Restaurants or food-related businesses" refers to establishments that serve food and beverages, and businesses that manufacture and sell food in general.

[0220] "Ingredient information" refers to detailed information such as the names, types, nutritional components, and origins of the ingredients that make up the new menu.

[0221] "Cooking method" refers to the specific steps or methods for cooking ingredients.

[0222] "Calorie restriction" refers to restricting the total calories of a particular menu item to within a certain range.

[0223] "Allergy information" refers to information that may cause an allergic reaction to a particular food ingredient or component.

[0224] "Means for receiving" refers to hardware or software for receiving and processing data sent from an external source.

[0225] "Verification means" refers to the processes and techniques used to verify the accuracy and integrity of input data.

[0226] "Generative AI" refers to artificial intelligence technology that generates new information based on large amounts of data.

[0227] "Means for analyzing and providing" refers to the technology used to analyze received data and generate and provide useful information or results.

[0228] "VR and modeling technology" refers to virtual reality technology and technology for creating 3D models.

[0229] "Display terminal" refers to a device that visually presents analysis results and virtual images to users.

[0230] A "virtual food delivery development support app" refers to an application designed to streamline the development of new menu items for the food delivery industry.

[0231] "Reanalysis" refers to the process of re-analyzing data based on new information, such as feedback.

[0232] "Means of providing omnidirectional viewpoints" refers to technology that allows 3D models and VR content to be viewed from various viewpoints.

[0233] "Means for generating reports" refers to the technology for compiling analysis results, evaluations, etc. in document format.

[0234] The virtual food delivery development support system of this invention operates in cooperation with three parties: the user, the terminal, and the server. This system provides virtual evaluations and images by allowing the user to input information on ingredients, cooking methods, calorie restrictions, and allergy information for a new menu item and send it to the server via the terminal.

[0235] Specific components of the system include:

[0236] 1. User Device:

[0237] A user terminal is a device such as a computer or tablet used by a restaurant or food-related business. A user uses this terminal to input information about new menu items. For example, a user can input information about a new menu item as follows:

[0238] Ingredients: Pasta, tomatoes, olive oil, basil

[0239] Cooking method: boiling, frying

[0240] Calorie restriction: 500 kcal or less

[0241] Allergy Information: Gluten Free

[0242] 2. Data transmission:

[0243] Once the information has been entered, it is sent from the terminal to the server. At that time, the terminal checks whether the format is correct (validation). For example, it checks whether all required fields have been entered, whether the range of values ​​is correct, etc. If there are no problems, the data is sent to the server.

[0244] 3. Server:

[0245] The server is the hub of the analysis process, using generative AI to analyze the received data and provide ingredient data, calorie calculations, halal compliance information, and allergy information.

[0246] Additionally, VR and 3D modeling technology is used to generate virtual presentation images, which are then presented in a format that can be viewed from all angles.

[0247] 4. Sending analysis results and virtual images:

[0248] The server sends the analysis results and a virtual presentation image to the device, including the following information:

[0249] Total calories: 480 kcal

[0250] Nutritional information: High in vitamin C and iron

[0251] Allergy Information: Gluten Free

[0252] Halal compatibility information: Considered

[0253] Arrangement image: 3D model (all-directional view)

[0254] 5. Display on user terminal:

[0255] The analysis results and virtual images are displayed on the user's terminal, allowing the user to check the finished image of the new menu and ingredient information. Furthermore, by entering feedback, the user can request further improvements and corrections from the server.

[0256] Specifically, the following text prompt can be sent to the server:

[0257] Ingredients: pasta, tomatoes, olive oil, basil

[0258] Cooking method: boiling, frying

[0259] Calorie restriction: 500 kcal or less

[0260] Allergy Information: Gluten Free

[0261] Based on this prompt, the server uses a generative AI model to analyze the new menu and provide a virtual evaluation and image, allowing users to develop new menu items more quickly and efficiently.

[0262] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0263] Step 1:

[0264] The user uses the device to input information about the new menu item, including information about ingredients, cooking methods, calorie restrictions, and allergy information, and then presses a button to send the data after completing the input. This temporarily saves the input data in the device.

[0265] input:

[0266] Ingredients: Pasta, tomatoes, olive oil, basil

[0267] Cooking method: boiling, frying

[0268] Calorie restriction: 500 kcal or less

[0269] Allergy Information: Gluten Free

[0270] output:

[0271] Saved Input Data

[0272] Step 2:

[0273] The terminal checks whether the format of the saved input data is correct (validation). At this stage, it checks whether all required fields have been entered, whether the range of values ​​is correct, etc. If there are no problems, it sends the data to the server.

[0274] input:

[0275] Saved Input Data

[0276] output:

[0277] Validated data

[0278] Step 3:

[0279] The server receives the validated data sent from the device. It analyzes this data using a generation AI and provides ingredient data, calorie calculations, halal compliance information, and allergy information. During the analysis process, it extracts nutritional information for ingredients from the database and calculates total calories and ingredient information.

[0280] input:

[0281] Validated data

[0282] output:

[0283] Ingredient data, calorie calculation results, halal compliance information, allergy information

[0284] Step 4:

[0285] Using VR and 3D modeling technology, the server generates a virtual presentation of the new menu items, which can be viewed in 3D format from any angle.

[0286] input:

[0287] Ingredient data, cooking method data

[0288] output:

[0289] Virtual presentation image (3D model)

[0290] Step 5:

[0291] The server then sends the analysis results and a virtual presentation image to the device, including total calories, nutritional information, and allergy information.

[0292] input:

[0293] Analysis results and virtual presentation image

[0294] output:

[0295] Transmission data (analysis results + virtual image)

[0296] Step 6:

[0297] The terminal displays the received analysis results and virtual images to the user, allowing the user to check the finished image of the new menu, as well as information on ingredients, calories, and allergies.

[0298] input:

[0299] Transmission data (analysis results + virtual image)

[0300] output:

[0301] User Display Data

[0302] Step 7:

[0303] The user checks the analysis results and inputs feedback, which is sent to the server via the terminal, allowing the user to request reanalysis. This feedback can include adjustments to the taste or improvements to the appearance.

[0304] input:

[0305] Feedback Information

[0306] output:

[0307] Reanalysis Request

[0308] Step 8:

[0309] The server then performs a re-analysis based on user feedback, using a re-generative AI to perform a virtual evaluation based on updated data and new conditions, and generate new results.

[0310] input:

[0311] Reanalysis Request

[0312] output:

[0313] Reanalysis results + updated virtual image

[0314] Each processing step works together to make the new menu development process quick and efficient.

[0315] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0316] This invention is a system that supports the rapid and efficient development of new menu items by linking users, terminals, a server, and an emotion engine. This system accepts input of information on ingredients, cooking methods, calorie restrictions, and allergies for new menu items, performs analysis based on the information, and provides a virtual evaluation and image. Furthermore, by recognizing the user's emotions and providing feedback and suggestions based on those emotions, the system achieves more accurate new menu development.

[0317] System Objectives

[0318] The main purpose of this system is to streamline the new menu development process and reduce costs and time by conducting virtual evaluations without using actual ingredients or cooking. Furthermore, it will reduce food waste and promote the growth of a sustainable food industry. Furthermore, by taking user emotions into consideration, it will support the development of menus that provide greater satisfaction.

[0319] System configuration

[0320] The main components of the system are:

[0321] User device: A computer, tablet, or other input device used by a restaurant or food-related business.

[0322] Server: A central computer that performs analytical processing and generates various data using generative AI and an emotion engine.

[0323] Generative AI: Artificial intelligence techniques for performing data analysis.

[0324] Emotion engine: Technology that recognizes and analyzes user emotions.

[0325] VR and 3D modeling technology: Technology for creating virtual presentation images.

[0326] Processing Details

[0327] Below, we will explain how each component works together and its specific operation using concrete examples.

[0328] User: Create and submit input data

[0329] The user uses the terminal to input the cooking method, ingredient information, calorie restrictions, allergy information, etc. of the new menu item. For example, if you want to develop a "low-calorie pasta," you would input the following information:

[0330] Ingredients: Pasta, tomatoes, olive oil, basil

[0331] Cooking method: boiling, frying

[0332] Calorie restriction: 500 kcal or less

[0333] Allergy Information: Gluten Free

[0334] After completing the input, the user presses a button to transmit the data.

[0335] Terminal: Data transmission and validation

[0336] The terminal temporarily stores the data entered by the user and checks whether the format is correct (validation). For example, it checks whether all required fields have been entered, whether the numerical range is correct, etc. If there are no problems, it sends the data to the server.

[0337] Server: Receives and analyzes data

[0338] The server receives and stores the data sent from the device, then uses the generation AI to obtain nutritional information for each ingredient from the ingredient database and calculate total calories, allergy information, and halal compliance information.

[0339] Server: Generate virtual presentation images

[0340] The server then uses VR and 3D modeling technology to generate a virtual presentation of the new menu item, which is then presented as a 3D model that can be viewed from all angles.

[0341] Server: Sending analysis results

[0342] The analysis results and virtual presentation images are sent from the server to the device, including the following information:

[0343] Total calories: 480 kcal

[0344] Nutritional Information: High in Vitamin C and Iron

[0345] Allergy Information: Gluten Free

[0346] Halal compatibility: Considered

[0347] Presentation image: 3D model (all-directional view)

[0348] Terminal: Display of analysis results

[0349] The terminal displays the information received from the server to the user, allowing the user to check the final image of the new menu, as well as information on ingredients and allergies.

[0350] Users: Send feedback and refine

[0351] The user can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the terminal.

[0352] Emotion Engine: User Emotion Recognition and Analysis

[0353] The emotion engine recognizes emotions from user feedback, facial expressions during operation, tone of voice, etc. For example, if the user shows positive emotions, it determines that the proposed menu will be well-received.

[0354] Emotion-based feedback and readjustment

[0355] The emotion data recognized by the emotion engine is taken into account when the server re-analyzes the data. For example, if a user expresses negative emotions in response to a new menu suggestion, the server will suggest different ingredients or cooking methods.

[0356] Generate and display new analysis results

[0357] The reanalyzed data and the virtual presentation image are sent back to the terminal and displayed to the user, who can then provide feedback and make further adjustments as necessary.

[0358] Through this process, users can efficiently develop and evaluate new menu items. Furthermore, feedback that takes user emotions into consideration will enable the development of new menu items that will provide greater satisfaction.

[0359] The processing flow will be explained below.

[0360] Step 1:

[0361] Users input information about ingredients, cooking methods, calorie restrictions, and allergies into the terminal to develop new menu items. For example, if you want to develop a "low-calorie pasta," you would enter the following information:

[0362] Ingredients: Pasta, tomatoes, olive oil, basil

[0363] Cooking method: boiling, frying

[0364] Calorie restriction: 500 kcal or less

[0365] Allergy Information: Gluten Free

[0366] Once you have completed the input, click the send button to send the data.

[0367] Step 2:

[0368] The terminal temporarily stores the data entered by the user. Then it validates whether the data format is correct, whether all required fields have been entered, whether the numerical range is correct, etc. If the data is valid, the terminal sends the data to the server.

[0369] Step 3:

[0370] The server receives the data sent from the device, stores it, and then converts it into the format required for analysis.

[0371] Step 4:

[0372] The server uses AI to analyze the received data. Here, it obtains nutritional information for each ingredient from the ingredient database and generates calorie calculations, halal compliance information, and allergy information. For example, it obtains ingredient data for pasta, tomato, olive oil, and basil and calculates the total calories as 480 kcal.

[0373] Step 5:

[0374] The server uses VR and 3D modeling technology to generate a virtual presentation image based on the analysis results, and the generated image is provided as a 3D model that can be viewed from all angles.

[0375] Step 6:

[0376] The server sends the analysis results and virtual presentation images to the device, including data such as total calories, nutritional information, allergy information, halal compliance information, and 3D presentation images.

[0377] Step 7:

[0378] The terminal displays the analysis results received from the server and a virtual presentation image to the user, who can then check the finished image of the new menu, as well as ingredient and allergy information.

[0379] Step 8:

[0380] The user can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the terminal.

[0381] Step 9:

[0382] The server receives feedback from the user, performs a new analysis with necessary adjustments, and then generates the reanalysis results and a new virtual presentation image, which are then sent to the terminal again.

[0383] Step 10:

[0384] The server runs an emotion engine that recognizes emotions from the user's feedback, facial expressions during operation, tone of voice, etc. The emotion engine analyzes whether the user is expressing positive or negative emotions.

[0385] Step 11:

[0386] The user's emotion data recognized by the emotion engine is used for reanalysis by the server. For example, if the user expresses negative emotion in response to a new menu suggestion, different ingredients or cooking methods will be suggested. Conversely, if a positive emotion is recognized, the suggestion will be saved with high accuracy.

[0387] Step 12:

[0388] The results of the reanalysis using the emotion engine's emotion data analysis and the new virtual presentation image are sent to the device again and displayed to the user. The user can then provide feedback and make further adjustments as necessary.

[0389] Through this process, users can efficiently develop and evaluate new menu items. Furthermore, feedback that takes user emotions into consideration will enable the development of new menu items that will provide greater satisfaction.

[0390] Example 2

[0391] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0392] The traditional new menu development process had the problem of being extremely costly and time-consuming because it was impossible to evaluate the results without using actual ingredients and cooking. Furthermore, it was difficult to provide feedback that took user emotions into consideration, preventing the development of menus that would provide high levels of satisfaction. As a result, food waste and food waste increased, and this did not contribute to the growth of a sustainable food industry.

[0393] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for a new menu item entered by a restaurant or food-related company; means for verifying the correct format of the entered information; means for analyzing the received information using a generative AI and virtually providing ingredient data, calorie calculations, religious compliance information, and allergy information; means for generating a virtual presentation image using virtual reality and modeling technology; means for transmitting the analysis results and the virtual presentation image to a terminal for displaying them; and means for analyzing the user's emotions and providing feedback based on the generative AI model. This enables the rapid and efficient development of new menu items, reduces food waste and ingredient waste, and contributes to the sustainable growth of the food industry. Furthermore, feedback based on user emotions can lead to the development of menu items with higher satisfaction.

[0394] "Ingredient information" refers to information such as the names, amounts, and components of ingredients used in developing new menu items.

[0395] "Recipe" is information that indicates the steps and methods for cooking ingredients.

[0396] "Calorie restriction" is a standard value for limiting the total calories contained in one meal.

[0397] "Allergy information" is information about foods that contain specific allergens.

[0398] "Generative AI" is a system that uses artificial intelligence technology to analyze data and generate information.

[0399] "Ingredient component data" is information on the nutritional and chemical components contained in each ingredient.

[0400] "Religious accommodation information" is food information to meet specific religious restrictions.

[0401] A "virtual presentation image" is a virtual presentation image of a new menu item created using virtual reality and 3D modeling technology.

[0402] A "terminal" is an input and display device, such as a computer or tablet, that a user uses to operate the system.

[0403] The "emotion engine" is a technology that recognizes and analyzes emotions from the user's facial expressions, tone of voice, etc.

[0404] "Feedback" refers to information about opinions and impressions that users input regarding analysis results and suggestions.

[0405] "Reanalysis" is the process in which the generative AI reanalyzes the data and derives new results based on the feedback and sentiment analysis results it receives.

[0406] "Virtual reality" is a technology that uses computer technology to virtually create experiences that are similar to reality.

[0407] "3D modeling technology" is a technology for digitally generating objects in three-dimensional space.

[0408] This invention is a system that supports the rapid and efficient development of new menu items by linking users, terminals, servers, and an emotion engine. Specifically, the system analyzes the data entered by users to input information about ingredients, cooking methods, calorie restrictions, and allergies for new menu items, and provides virtual evaluations and images. It also recognizes the user's emotions and provides feedback and suggestions based on them, enabling more accurate new menu development.

[0409] Hardware and Software

[0410] This system consists of the following components:

[0411] User Device: An input and display device such as a computer or tablet used by a restaurant or food-related business.

[0412] Server: A central computer that performs analytical processing and generates various data using generative AI and an emotion engine.

[0413] Generative AI: Artificial intelligence techniques for performing data analysis.

[0414] Emotion engine: Technology that recognizes and analyzes user emotions.

[0415] VR and 3D modeling technology: Technology for creating virtual presentation images.

[0416] Data processing and calculation

[0417] The user uses the terminal to input information about ingredients, cooking methods, calorie restrictions, and allergy information for the new menu item. For example, if you want to develop a "low-calorie pasta," you would enter the following information:

[0418] Ingredients: Pasta, tomatoes, olive oil, basil

[0419] Cooking method: boiling, frying

[0420] Calorie restriction: 500 kcal or less

[0421] Allergy Information: Gluten Free

[0422] The entered information is first saved on the device and validated for correct format. The data is then sent to the server, where it uses generative AI to retrieve nutritional information for each ingredient from a food ingredient database and calculate total calories, allergy information, and religious compliance information. At the same time, VR and 3D modeling technology is used to generate a virtual presentation of the new menu item.

[0423] The generated analysis results and virtual presentation image are sent to the device and displayed to the user. The user can input feedback based on this information and request readjustments if necessary. The readjustment feedback is sent back to the server, and the emotion engine analyzes the user's emotions. Data analysis is performed based on the user's emotions, and any necessary corrections or improvements are made.

[0424] Prompt Sentence Examples

[0425] An example of a prompt sentence to input to the generative AI model is as follows:

[0426] I'd like you to generate new menu ideas. Please provide the following information:

[0427] Ingredients: Pasta, tomatoes, olive oil, basil

[0428] Cooking method: Boiling, frying

[0429] Calorie restriction: 500 kcal or less

[0430] Allergy Information: Gluten Free

[0431] Through this system, users can quickly and efficiently develop new menu items, reducing food waste and food loss and promoting the growth of a sustainable food industry. Feedback that takes user emotions into consideration also enables the development of menu items that offer greater satisfaction.

[0432] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0433] Step 1:

[0434] The user uses the terminal to input information about ingredients, cooking methods, calorie restrictions, and allergy information for a new menu item. For example, if developing a "low-calorie pasta," the user enters the following information:

[0435] input:

[0436] Ingredients: Pasta, tomatoes, olive oil, basil

[0437] Cooking method: Boiling, frying

[0438] Calorie restriction: 500 kcal or less

[0439] Allergy Information: Gluten Free

[0440] The user presses a button to transmit data to the terminal.

[0441] Step 2:

[0442] The terminal temporarily stores the data entered by the user. Then it validates the data to ensure that it is in the correct format. For example, it checks whether all required fields have been entered and whether the numeric range is correct.

[0443] Input: Data submitted by the user

[0444] Data processing: format check, required field input check, numerical range check

[0445] Output: Validated data

[0446] If the validation is successful, the terminal transmits the data to the server.

[0447] Step 3:

[0448] The server receives the data sent from the device and stores it in a database.

[0449] Input: Validated data sent from the terminal

[0450] Data processing: Saving to database

[0451] Output: Saved data

[0452] Step 4:

[0453] The server uses generative AI to obtain nutritional information for each ingredient from a food ingredient database, such as the calories in pasta or the vitamin C content of tomatoes, and then calculates the total calories, allergy information, and religious compatibility information.

[0454] Input: Saved data

[0455] Data processing: Obtaining nutritional information from the food ingredient database, calculating total calories, and calculating allergy and religious information.

[0456] Output: Analysis results

[0457] Step 5:

[0458] The server uses VR and 3D modeling technology to generate a virtual presentation of the new menu items, which are then presented as 3D models that can be viewed from all angles.

[0459] Input: Analysis results

[0460] Data processing: Creating virtual presentation images using VR and 3D modeling technology

[0461] Output: Virtual presentation image

[0462] Step 6:

[0463] The server sends the analysis results and the generated virtual presentation image to the terminal.

[0464] Input: Analysis results, virtual presentation image

[0465] Data processing: Data integration

[0466] Output: Analysis results and virtual presentation images sent to the device

[0467] Step 7:

[0468] The terminal displays the information received from the server to the user, who can check the finished image of the new menu, as well as information on ingredients and allergies.

[0469] Input: Analysis results and virtual presentation images sent from the server

[0470] Data processing: Conversion to display format

[0471] Output: Displayed information

[0472] Step 8:

[0473] The user inputs feedback based on the analysis results. For example, they can enter comments such as "I'd like to reduce the amount of tomatoes" or "I'd like to change the cooking method." The feedback is sent to the server via the device.

[0474] Input: Analysis results and feedback opinions

[0475] Data processing: Adding feedback

[0476] Output: Feedback sent to the server

[0477] Step 9:

[0478] The server receives feedback from the user. At the same time, it uses an emotion engine to analyze the user's emotions based on their feedback, facial expressions, tone of voice, etc. It determines whether the user is expressing positive or negative emotions.

[0479] Input: Feedback and user emotional data (facial expressions, tone of voice, etc.)

[0480] Data processing: Sentiment analysis

[0481] Output: Emotion analysis results

[0482] Step 10:

[0483] The server reanalyzes the emotion data obtained from the emotion engine, and if the user gives negative feedback, it suggests alternative ingredients and cooking methods.

[0484] Input: Sentiment analysis results and feedback content

[0485] Data processing: reanalysis, generation of proposals

[0486] Output: Reanalysis results and recommendations

[0487] Step 11:

[0488] The server sends the reanalyzed data and the new virtual presentation image to the terminal, which provides new analysis results.

[0489] Input: Reanalysis results and new proposals

[0490] Data processing: Data integration

[0491] Output: Reanalysis results and virtual presentation image sent to the device

[0492] Step 12:

[0493] The device displays the reanalysis results to the user, who then provides feedback based on the new information. This process is repeated until the user is satisfied.

[0494] Input: Reanalysis results and virtual serving image sent from the server

[0495] Data processing: Conversion to display format

[0496] Output: Displayed reanalysis results and virtual presentation image

[0497] This series of processing steps allows users to efficiently develop and evaluate new menus, and feedback that takes user emotions into consideration makes it possible to develop menus that will provide high levels of satisfaction.

[0498] (Application example 2)

[0499] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0500] The traditional new menu development process was cost-inefficient, resulting in a lot of wasted ingredients and time, and requiring multiple prototypes. Furthermore, there was no way to provide feedback or suggestions that directly reflected user sentiment, resulting in low satisfaction with the final menu. To solve these problems, a system is needed that can efficiently and quickly develop new menus and make accurate suggestions based on user sentiment.

[0501] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0502] In this invention, the server includes means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related companies, means for verifying that the format of the entered information is correct, means for analyzing the received information using a generation AI and virtually providing ingredient data, calorie calculations, halal compliance information, and allergy information, means for generating virtual presentation images using virtual reality and 3D modeling technology, means for transmitting the analysis results and the virtual presentation images to a terminal for displaying them, means for providing an emotion engine for recognizing and analyzing user emotions, and means for providing feedback and suggestions based on the user emotions. This enables more efficient new menu development and more accurate suggestions based on user emotions.

[0503] "Restaurants or food-related companies" refers to businesses that develop and offer new menu items.

[0504] A "new menu" is a new dish or food that has never been offered before.

[0505] "Ingredient information" refers to detailed information about the types, quantities, origins, etc. of the various ingredients used in the new menu.

[0506] "Cooking method" refers to the specific cooking steps and methods used with ingredients.

[0507] "Calorie restriction" refers to a standard or requirement for keeping the total calories per meal within a specific range.

[0508] "Allergy information" refers to information about the possibility of an allergic reaction to a particular food ingredient.

[0509] "Means for receiving" refers to the method or technology for receiving information from a user.

[0510] "Verification means" refers to methods or techniques used to verify that received information conforms to its format and content.

[0511] "Generative AI" refers to artificial intelligence techniques used to analyze input data and generate the necessary information.

[0512] "Food ingredient data" refers to data on the nutrients and characteristics contained in each food ingredient.

[0513] "Calculating calories" refers to the process of calculating total calories based on ingredient information.

[0514] "Halal compatibility information" refers to information that indicates whether or not a food is suitable for consumption by Muslims.

[0515] "Virtual provision means" refers to methods and technologies for providing information or images that do not physically exist in a virtual space.

[0516] "Virtual reality" is a technology that provides a realistic experience within a computer-generated virtual environment.

[0517] "3D modeling technology" refers to the techniques and tools used to construct 3D virtual objects.

[0518] "Generative means" refers to methods and techniques for producing new information and images.

[0519] A "display terminal" is a device that allows a user to visually confirm information or images.

[0520] An "emotion engine" is a technology that recognizes and analyzes emotions from a user's facial expressions, tone of voice, etc.

[0521] "Means of providing" refers to methods or means for incorporating specific functions or technologies into a system.

[0522] "Feedback and suggestion means" refers to methods and technologies for providing advice and new suggestions based on analysis results and user sentiment.

[0523] "Means for reanalysis" refers to methods and techniques for re-analyzing data based on feedback or new data.

[0524] This invention is a system that supports the rapid and efficient development of new menus by linking user terminals, servers, generation AI, and emotion engines. This system collects input data, validates and analyzes data, generates virtual images, analyzes emotions, and receives and reanalyzes feedback. Specific implementation methods for the system are described below.

[0525] Hardware and software used

[0526] 1. User device: Uses input devices such as computers and tablets.

[0527] 2. Server: Serves as the central computer that performs analytical processing. Specific software uses generative AI technology.

[0528] 3. Generative AI: Artificial intelligence techniques used for data analysis and virtual presentation image generation.

[0529] 4. Emotion Engine: Technology that analyzes the user's facial expressions and tone of voice to recognize emotions. Uses "some_emotion_recognition_library" as the specific library.

[0530] 5. VR and 3D modeling technology: Technology used to generate virtual presentation images. For specific software, use "some_vr_library".

[0531] Data processing and calculation

[0532] The user terminal collects data such as ingredients, cooking methods, calorie restrictions, and allergy information for new menu items, and verifies that the entered information is in the correct format.

[0533] For example: "Ingredients: pasta, tomato, olive oil, basil", "Cooking method: boiling, frying", "Calorie limit: 500 kcal or less", "Allergy information: gluten-free"

[0534] The server receives data sent from the device and uses AI to analyze ingredient data, calorie calculations, halal compliance information, and allergy information, while also using VR and 3D modeling technology to generate virtual presentation images.

[0535] Example: "The generated virtual presentation image is provided in a format that can be viewed from all directions."

[0536] The emotion engine analyzes feedback from the user, facial expressions during operation, tone of voice, and other factors to recognize the user's emotions.

[0537] For example: "If the user expresses positive emotions, it will be considered positive and other cooking suggestions will be made."

[0538] Specific examples

[0539] For example, if a chef wants to develop a new "low-calorie pasta menu," he or she can use the system as follows:

[0540] 1. Enter ingredient information, cooking method, calorie restrictions, and allergy information into the user terminal.

[0541] 2. The server analyzes the data and generates a virtual presentation image.

[0542] 3. The user checks the analysis results and the virtual presentation image and provides feedback.

[0543] 4. The emotion engine analyzes the feedback and re-suggests the menu if necessary.

[0544] Prompt Sentence Examples

[0545] "This pasta dish uses five ingredients and aims to be under 500 kcal. Basil and tomato are the main ingredients. It is cooked both boiled and sautéed. It is gluten-free. Please generate detailed ingredient information and a virtual serving image for this dish."

[0546] As described above, using this system will make the new menu development process more efficient and enable proposals that will provide high levels of satisfaction based on user emotions.

[0547] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0548] Step 1:

[0549] The user inputs information about ingredients, cooking methods, calorie restrictions, and allergy information for a new menu item into the user terminal. Examples of input data include "Ingredients: pasta, tomato, olive oil, basil," "Cooking method: boiling, stir-frying," "Calorie restrictions: under 500 kcal," and "Allergy information: gluten-free." After input, the user terminal temporarily stores this information.

[0550] Step 2:

[0551] The terminal verifies that the format of the temporarily saved data is correct. For example, it checks whether all required fields have been entered and whether the numeric range is appropriate. If the format is correct, the terminal sends the data to the server. The input here is the menu information entered by the user, and the output is the verified data.

[0552] Step 3:

[0553] The server receives the data sent from the device and stores it. Next, it uses generative AI to obtain nutritional information for each ingredient from the ingredient database and calculates total calories, allergy information, and halal compliance information. For example, it obtains the calorie and nutritional information for "pasta" based on the received ingredient information. The input is verified menu information, and the output is the analysis results.

[0554] Step 4:

[0555] The server uses VR and 3D modeling technology to generate a virtual presentation image based on the analysis results. For example, it generates a 3D model of the appearance of low-calorie pasta. This allows users to check the appearance of the menu from all angles. The input is the analysis results, and the output is a 3D model of the presentation image.

[0556] Step 5:

[0557] The server sends the analysis results and a virtual presentation image to the terminal. The user terminal receives this and displays it to the user. For example, the analysis results may be displayed as "Calories: 480 kcal" or "Nutritional information: High in vitamin C, rich in iron." The input is the analysis results and a 3D image, and the output is visualized data that the user can view.

[0558] Step 6:

[0559] The user checks the displayed analysis results and the virtual presentation image and inputs feedback. The user's device sends this feedback to the server. For example, the user sends a specific request such as "I'd like more tomatoes." The input is the user's feedback, and the output is the feedback data.

[0560] Step 7:

[0561] The server receives the feedback and analyzes the user's emotions using an emotion engine. For example, the analysis result may be, "There are many positive opinions, but they would like to increase the amount of tomatoes." The input is the user's feedback, and the output is the emotion analysis result.

[0562] Step 8:

[0563] The server then uses the generative AI again to perform a new analysis based on the results of the emotion analysis. For example, it recalculates the nutritional content and calories if the amount of tomato is increased, and generates a new virtual presentation image. The input is the emotion analysis result and the reconfigured menu information, and the output is the reanalysis result and the new virtual presentation image.

[0564] Step 9:

[0565] The server sends the reanalysis results and a new virtual presentation image to the terminal and displays them to the user. The user then provides feedback and makes further adjustments as necessary. Ultimately, a new menu that satisfies the user is finalized. The input is the reanalysis results and a new 3D image, and the output is final confirmation data and the completion of the continuous feedback cycle.

[0566] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0567] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0568] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0569] [Second embodiment]

[0570] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0571] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0572] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0573] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0574] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0575] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0576] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0577] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0578] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[0579] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0580] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0581] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0582] The virtual food testing system of the present invention supports the rapid and efficient development of new menu items through the cooperation of users, terminals, and servers. This system allows restaurants and food-related businesses to input information about ingredients, cooking methods, and restrictions for new menu items, and then analyzes the information to provide a virtual evaluation and image. The specific operation of the system is described below.

[0583] System Objectives

[0584] The main purpose of this system is to streamline the process of new menu development and reduce costs and time by conducting virtual evaluations without using actual ingredients or cooking. Furthermore, it will reduce food waste and promote the growth of a sustainable food industry.

[0585] System configuration

[0586] The main components of the system are:

[0587] User device: A computer, tablet, or other input device used by a restaurant or food-related business.

[0588] Server: A central computer that performs analytical processing and generates various data using generative AI.

[0589] Generative AI: Artificial intelligence techniques for performing data analysis.

[0590] VR and 3D modeling technology: Technology for creating virtual presentation images.

[0591] Processing Details

[0592] Below, we will explain how each component works together and its specific operation using concrete examples.

[0593] User: Create and submit input data

[0594] The user uses the terminal to input the cooking method, ingredient information, calorie restrictions, allergy information, etc. of the new menu item. For example, if you want to develop a "low-calorie pasta," you would input the following information:

[0595] Ingredients: Pasta, tomatoes, olive oil, basil

[0596] Cooking method: boiling, frying

[0597] Calorie restriction: 500 kcal or less

[0598] Allergy Information: Gluten Free

[0599] After completing the input, the user presses a button to transmit the data.

[0600] Terminal: Data transmission and validation

[0601] The terminal temporarily stores the data entered by the user and checks whether the format is correct (validation). For example, it checks whether all required fields have been entered, whether the numerical range is correct, etc. If there are no problems, it sends the data to the server.

[0602] Server: Receives and analyzes data

[0603] The server receives the data sent from the device and begins analysis using the AI. Specifically, it retrieves the nutritional information of each ingredient from the ingredient database and calculates the total calories, allergy information, halal compliance information, etc. For example, it retrieves the nutritional information for pasta, tomato, olive oil, and basil, and calculates the total calories as 480 kcal.

[0604] Server: Generate virtual presentation images

[0605] The server then uses VR and 3D modeling technology to generate a virtual presentation of the new menu item, which is then presented as a 3D model that can be viewed from all angles.

[0606] Server: Sending analysis results

[0607] The analysis results and virtual presentation images are sent from the server to the device, including the following information:

[0608] Total calories: 480 kcal

[0609] Nutritional Information: High in Vitamin C and Iron

[0610] Allergy Information: Gluten Free

[0611] Halal compatibility: Considered

[0612] Presentation image: 3D model (all-directional view)

[0613] Terminal: Display of analysis results

[0614] The terminal displays the information received from the server to the user, allowing the user to check the final image of the new menu, as well as information on ingredients and allergies.

[0615] Users: Send feedback and refine

[0616] Users can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the device, and a new analysis is performed.

[0617] In this way, the virtual food testing system enables the new menu development process to proceed efficiently, reducing costs and food waste.

[0618] The processing flow will be explained below.

[0619] Step 1:

[0620] Users input information about ingredients, cooking methods, calorie restrictions, and allergies into the terminal to develop new menu items. Once input is complete, the data is sent by pressing the send button.

[0621] Step 2:

[0622] The terminal temporarily stores the data entered by the user. Then it validates whether the data format is correct, whether all required fields have been entered, whether the numerical range is correct, etc. If the data is valid, the terminal sends the data to the server.

[0623] Step 3:

[0624] The server receives the data sent from the device, stores it, and then converts it into the format required for analysis.

[0625] Step 4:

[0626] The server uses AI to analyze the received data. Here, it retrieves nutritional information for each ingredient from the ingredient database and generates calorie calculations, halal compliance information, and allergy information. For example, in the case of "low-calorie pasta," the ingredient data for pasta, tomato, olive oil, and basil are retrieved, and the total calories are calculated as 480 kcal.

[0627] Step 5:

[0628] The server uses VR and 3D modeling technology to generate a virtual presentation image based on the analysis results, and the generated image is provided as a 3D model that can be viewed from all angles.

[0629] Step 6:

[0630] The server sends the analysis results and virtual presentation images to the device, including data such as total calories, nutritional information, allergy information, halal compliance information, and 3D presentation images.

[0631] Step 7:

[0632] The terminal displays the analysis results received from the server and a virtual presentation image to the user, who can then check the finished image of the new menu, as well as ingredient and allergy information.

[0633] Step 8:

[0634] The user can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the terminal.

[0635] Step 9:

[0636] The server receives feedback from the user, performs a new analysis with necessary adjustments, and then generates the reanalysis results and a new virtual presentation image, which are then sent to the terminal again.

[0637] Through this series of processes, users can efficiently develop and evaluate new menu items, saving time and money, and is also expected to reduce food waste and food waste.

[0638] Example 1

[0639] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0640] The traditional new menu development process requires repeated trial production using actual ingredients, which is costly and time-consuming. Furthermore, failures and readjustments during the trial production stage result in food waste and food waste, which does not contribute to the development of a sustainable food industry. Furthermore, managing ingredient and allergy information is cumbersome and prone to errors.

[0641] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0642] In this invention, the server includes means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related companies, means for verifying that the format of the entered information is correct, means for analyzing the received information using a generative AI model and virtually providing ingredient data, calorie calculations, halal compliance information, and allergy information, means for generating a virtual presentation image using 3D representation technology, and means for transmitting the analysis results and the virtual presentation image to a terminal for displaying them. This allows new menu items to be virtually evaluated and improved without using actual ingredients, thereby reducing costs and food waste and making new menu development more efficient.

[0643] A "restaurant or food-related business" is a business that serves meals or is engaged in the manufacture and sale of food.

[0644] "New menu" refers to the content and combination of newly developed dishes that will be added to the existing menu.

[0645] "Ingredient information" is detailed information such as the names, types, and quantities of ingredients used in the new menu.

[0646] "Cooking method" refers to the specific techniques and processes used to cook ingredients.

[0647] "Calorie restriction" is the upper limit on the total calorie content of a diet set for health and nutritional management.

[0648] "Allergy information" refers to information on whether a consumer may have an allergic reaction to a particular food ingredient.

[0649] "Means for receiving" refers to a method or system for taking in data or information from the outside.

[0650] A "verification means" is a method or system for checking the accuracy and format of the information entered.

[0651] A "generative AI model" is an artificial intelligence algorithm or program that is trained to analyze data and generate new information.

[0652] "Means for analysis" refers to a system or method that examines the received data in detail and extracts and calculates the necessary information.

[0653] "Food ingredient data" is detailed information about the nutritional content and chemical composition of food.

[0654] "Halal compliance information" is information about ingredients and cooking methods that are permitted according to specific religious regulations.

[0655] "Means for providing" refers to a system or method for displaying or transmitting the analyzed or generated information to the user.

[0656] "Three-dimensional representation technology" refers to techniques and methods for visually representing objects and landscapes in three-dimensional space.

[0657] A "terminal" is a device, such as a computer or tablet, that a user uses to enter data or view results.

[0658] "Feedback" refers to opinions and requests for improvement from users regarding analysis results and provided information.

[0659] "Reanalysis" refers to the process of reanalyzing data based on feedback and making corrections or improvements.

[0660] A "report" is a document or electronic file that summarizes analysis results and evaluation information.

[0661] "Omnidirectional viewing" refers to a display method that allows objects in three-dimensional space to be viewed from all angles.

[0662] The virtual food testing system of the present invention supports the rapid and efficient development of new menu items through the cooperation of users, terminals, and servers. This system allows restaurants and food-related businesses to input information on ingredients, cooking methods, calorie restrictions, and allergy information for new menu items, and performs analysis based on this information to provide virtual evaluations and images.

[0663] System configuration

[0664] The main components of the system are:

[0665] User device: An input device such as a computer or tablet used by food-related companies.

[0666] Server: A central computer that performs analytical processing and generates data using generative AI.

[0667] Generative AI: Artificial intelligence techniques for performing data analysis (specifically using TensorFlow and PyTorch).

[0668] 3D representation technology: Technology for creating virtual presentation images (using Blender and Unity).

[0669] System Operation

[0670] User: Create and submit input data

[0671] The user uses the terminal to input the cooking method, ingredient information, calorie restrictions, allergy information, etc. of the new menu item. For example, if you want to develop a "low-calorie pasta," you would input the following information:

[0672] Ingredients: Pasta, tomatoes, olive oil, basil

[0673] Cooking method: boiling, frying

[0674] Calorie restriction: 500 kcal or less

[0675] Allergy Information: Gluten Free

[0676] After completing the input, the user presses a button to transmit the data.

[0677] Terminal: Data transmission and validation

[0678] The device temporarily stores the data entered by the user and checks whether the format is correct. First, it checks whether all required fields have been entered, and then it checks whether the calorie value and allergy information are within the appropriate range. After checking, the data is sent to the server.

[0679] Server: Receives and analyzes data

[0680] The server receives the data sent from the device and analyzes it using a generative AI model. First, it obtains the nutritional information for each ingredient from the ingredient database. It then calculates the total calories, allergy information, and halal compliance information. For example, based on the ingredient information for pasta, tomato, olive oil, and basil, it calculates the total calories as 480 kcal.

[0681] Server: Generate virtual presentation images

[0682] The server uses 3D rendering technology to generate a virtual presentation of the new menu item, which is then presented as a 3D model that users can view from all angles.

[0683] Server: Sending analysis results

[0684] The analysis results and virtual presentation images are sent from the server to the device, including the following information:

[0685] Total calories: 480 kcal

[0686] Nutritional Information: High in Vitamin C and Iron

[0687] Allergy Information: Gluten Free

[0688] Halal compatibility: Considered

[0689] Presentation image: 3D model (all-directional view)

[0690] Terminal: Display of analysis results

[0691] The terminal displays the information received from the server to the user, allowing the user to check the final image of the new menu, as well as information on ingredients and allergies.

[0692] Users: Send feedback and refine

[0693] The user can input feedback based on the analysis results, such as if the calorie content is too high or if they would like to change the combination of ingredients, and the feedback is sent from the device to the server.

[0694] The server performs a new analysis and sends the retuned data back to the device, allowing the user to easily make further adjustments.

[0695] In this way, the virtual food testing system streamlines the process of new menu development, reducing costs and food waste and promoting the growth of a sustainable food industry.

[0696] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0697] Step 1: Data entry

[0698] The user uses the terminal to input information about the new menu item. Specifically, they enter information about ingredients, cooking methods, calorie restrictions, allergy information, etc. into a form. For example, if you want to develop a "low-calorie pasta," you would enter the following information:

[0699] Ingredients: Pasta, tomatoes, olive oil, basil

[0700] Cooking method: boiling, frying

[0701] Calorie restriction: 500 kcal or less

[0702] Allergy Information: Gluten Free

[0703] Input: Ingredient information, cooking method, calorie restrictions, allergy information

[0704] Output: Save to device

[0705] Step 2: Submit and validate data

[0706] The terminal temporarily stores the data entered by the user. It then validates that the data format is correct. It checks that all required fields have been entered and that calorie values ​​and allergy information are within the range. If validation is successful, it sends the data to the server.

[0707] Input: Data entered by the user

[0708] Data manipulation: format and range checks

[0709] Output: Send data to the server

[0710] Specific behavior:

[0711] 1. Check the required fields

[0712] 2. Check the range of calorie values ​​and allergy information

[0713] 3. Sending data to the server

[0714] Step 3: Receiving and analyzing data

[0715] The server receives the data sent from the device. It then begins analyzing the data using a generative AI model. It obtains nutritional information for each ingredient from the ingredient database and calculates total calories, allergy information, and halal compliance information. For example, based on the ingredient information for pasta, tomato, olive oil, and basil, it calculates the total calories to be 480 kcal.

[0716] Input: Data sent from the terminal

[0717] Data processing: Obtaining nutritional information using a generative AI model and calculating total calories, allergy information, and halal compliance information

[0718] Output: Analysis results

[0719] Specific behavior:

[0720] 1. Obtain information from a food ingredient database

[0721] 2. Calculate total calories and other nutritional information

[0722] Step 4: Generate a virtual presentation image

[0723] The server uses 3D rendering technology to generate a virtual presentation image of the new menu item, which is then presented as a 3D model that users can view from any angle.

[0724] Input: Analysis results

[0725] Data processing: Image generation using 3D expression technology (Blender or Unity)

[0726] Output: Virtual presentation image of 3D model

[0727] Specific behavior:

[0728] 1. 3D modeling of a virtual presentation image

[0729] 2. Provide a format that can be viewed from all angles

[0730] Step 5: Submitting the analysis results

[0731] The server sends the analysis results and the virtual presentation image to the device. The analysis results include the following information:

[0732] Total calories: 480 kcal

[0733] Nutritional Information: High in Vitamin C and Iron

[0734] Allergy Information: Gluten Free

[0735] Halal compatibility: Considered

[0736] Presentation image: 3D model (all-directional view)

[0737] Input: Analysis results, virtual arrangement image of 3D model

[0738] Output: Send to terminal

[0739] Step 6: Viewing the analysis results

[0740] The terminal displays the information received from the server to the user, who can check the finished image of the new menu, as well as information on ingredients and allergies.

[0741] Input: Analysis results and 3D model from the server

[0742] Output: What is displayed to the user

[0743] Specific behavior:

[0744] 1. Display analysis results and 3D models on your device

[0745] Step 7: Provide feedback and refine

[0746] The user inputs feedback based on the analysis results and sends it from the device to the server. The server receives the user's feedback, performs re-analysis using the generative AI model, and then sends the corrected data back to the device.

[0747] Input: User feedback

[0748] Data processing: Reanalysis using generative AI models

[0749] Output: Re-send the corrected analysis results to the terminal

[0750] Specific behavior:

[0751] 1. Receiving Feedback

[0752] 2. Perform reanalysis

[0753] 3. Sending the reanalysis results to the device

[0754] Through these steps, the virtual food testing system streamlines the new menu development process, reducing costs and food waste.

[0755] (Application example 1)

[0756] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0757] The traditional new menu development process required the use of actual ingredients and cooking, which was time-consuming and costly, and required a large number of resources to evaluate new menu items. Furthermore, the food delivery industry is required to quickly provide new menu items in a short amount of time, but there was no efficient way to achieve this. Furthermore, there was a lack of a system for virtually evaluating menu items without actual tasting, thereby improving customer satisfaction.

[0758] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0759] In this invention, the server includes: means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related companies; means for verifying the correct format of the entered information; means for analyzing the received information using generation AI and virtually providing ingredient data, calorie calculations, halal compliance information, and allergy information; means for generating virtual presentation images using VR and modeling technology; means for transmitting the analysis results and the virtual presentation images to a terminal for displaying them; and means for, as a virtual food delivery development support app, allowing users to enter feedback, reanalyze the results, and support the evaluation of new menu items, including readjustments. This allows for an efficient process for new menu development, reducing costs and food waste.

[0760] "Restaurants or food-related businesses" refers to establishments that serve food and beverages, and businesses that manufacture and sell food in general.

[0761] "Ingredient information" refers to detailed information such as the names, types, nutritional components, and origins of the ingredients that make up the new menu.

[0762] "Cooking method" refers to the specific steps or methods for cooking ingredients.

[0763] "Calorie restriction" refers to restricting the total calories of a particular menu item to within a certain range.

[0764] "Allergy information" refers to information that may cause an allergic reaction to a particular food ingredient or component.

[0765] "Means for receiving" refers to hardware or software for receiving and processing data sent from an external source.

[0766] "Verification means" refers to the processes and techniques used to verify the accuracy and integrity of input data.

[0767] "Generative AI" refers to artificial intelligence technology that generates new information based on large amounts of data.

[0768] "Means for analyzing and providing" refers to the technology used to analyze received data and generate and provide useful information or results.

[0769] "VR and modeling technology" refers to virtual reality technology and technology for creating 3D models.

[0770] "Display terminal" refers to a device that visually presents analysis results and virtual images to users.

[0771] A "virtual food delivery development support app" refers to an application designed to streamline the development of new menu items for the food delivery industry.

[0772] "Reanalysis" refers to the process of re-analyzing data based on new information, such as feedback.

[0773] "Means of providing omnidirectional viewpoints" refers to technology that allows 3D models and VR content to be viewed from various viewpoints.

[0774] "Means for generating reports" refers to the technology for compiling analysis results, evaluations, etc. in document format.

[0775] The virtual food delivery development support system of this invention operates in cooperation with three parties: the user, the terminal, and the server. This system provides virtual evaluations and images by allowing the user to input information on ingredients, cooking methods, calorie restrictions, and allergy information for a new menu item and send it to the server via the terminal.

[0776] Specific components of the system include:

[0777] 1. User Device:

[0778] A user terminal is a device such as a computer or tablet used by a restaurant or food-related business. A user uses this terminal to input information about new menu items. For example, a user can input information about a new menu item as follows:

[0779] Ingredients: Pasta, tomatoes, olive oil, basil

[0780] Cooking method: boiling, frying

[0781] Calorie restriction: 500 kcal or less

[0782] Allergy Information: Gluten Free

[0783] 2. Data transmission:

[0784] Once the information has been entered, it is sent from the terminal to the server. At that time, the terminal checks whether the format is correct (validation). For example, it checks whether all required fields have been entered, whether the range of values ​​is correct, etc. If there are no problems, the data is sent to the server.

[0785] 3. Server:

[0786] The server is the hub of the analysis process, using generative AI to analyze the received data and provide ingredient data, calorie calculations, halal compliance information, and allergy information.

[0787] Additionally, VR and 3D modeling technology is used to generate virtual presentation images, which are then presented in a format that can be viewed from all angles.

[0788] 4. Sending analysis results and virtual images:

[0789] The server sends the analysis results and a virtual presentation image to the device, including the following information:

[0790] Total calories: 480 kcal

[0791] Nutritional information: High in vitamin C and iron

[0792] Allergy Information: Gluten Free

[0793] Halal compatibility information: Considered

[0794] Arrangement image: 3D model (all-directional view)

[0795] 5. Display on user terminal:

[0796] The analysis results and virtual images are displayed on the user's terminal, allowing the user to check the finished image of the new menu and ingredient information. Furthermore, by entering feedback, the user can request further improvements and corrections from the server.

[0797] Specifically, the following text prompt can be sent to the server:

[0798] Ingredients: pasta, tomatoes, olive oil, basil

[0799] Cooking method: boiling, frying

[0800] Calorie restriction: 500 kcal or less

[0801] Allergy Information: Gluten Free

[0802] Based on this prompt, the server uses a generative AI model to analyze the new menu and provide a virtual evaluation and image, allowing users to develop new menu items more quickly and efficiently.

[0803] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0804] Step 1:

[0805] The user uses the device to input information about the new menu item, including information about ingredients, cooking methods, calorie restrictions, and allergy information, and then presses a button to send the data after completing the input. This temporarily saves the input data in the device.

[0806] input:

[0807] Ingredients: Pasta, tomatoes, olive oil, basil

[0808] Cooking method: boiling, frying

[0809] Calorie restriction: 500 kcal or less

[0810] Allergy Information: Gluten Free

[0811] output:

[0812] Saved Input Data

[0813] Step 2:

[0814] The terminal checks whether the format of the saved input data is correct (validation). At this stage, it checks whether all required fields have been entered, whether the range of values ​​is correct, etc. If there are no problems, it sends the data to the server.

[0815] input:

[0816] Saved Input Data

[0817] output:

[0818] Validated data

[0819] Step 3:

[0820] The server receives the validated data sent from the device. It analyzes this data using a generation AI and provides ingredient data, calorie calculations, halal compliance information, and allergy information. During the analysis process, it extracts nutritional information for ingredients from the database and calculates total calories and ingredient information.

[0821] input:

[0822] Validated data

[0823] output:

[0824] Ingredient data, calorie calculation results, halal compliance information, allergy information

[0825] Step 4:

[0826] Using VR and 3D modeling technology, the server generates a virtual presentation of the new menu items, which can be viewed in 3D format from any angle.

[0827] input:

[0828] Ingredient data, cooking method data

[0829] output:

[0830] Virtual presentation image (3D model)

[0831] Step 5:

[0832] The server then sends the analysis results and a virtual presentation image to the device, including total calories, nutritional information, and allergy information.

[0833] input:

[0834] Analysis results and virtual presentation image

[0835] output:

[0836] Transmission data (analysis results + virtual image)

[0837] Step 6:

[0838] The terminal displays the received analysis results and virtual images to the user, allowing the user to check the finished image of the new menu, as well as information on ingredients, calories, and allergies.

[0839] input:

[0840] Transmission data (analysis results + virtual image)

[0841] output:

[0842] User Display Data

[0843] Step 7:

[0844] The user checks the analysis results and inputs feedback, which is sent to the server via the terminal, allowing the user to request reanalysis. This feedback can include adjustments to the taste or improvements to the appearance.

[0845] input:

[0846] Feedback Information

[0847] output:

[0848] Reanalysis Request

[0849] Step 8:

[0850] The server then performs a re-analysis based on user feedback, using a re-generative AI to perform a virtual evaluation based on updated data and new conditions, and generate new results.

[0851] input:

[0852] Reanalysis Request

[0853] output:

[0854] Reanalysis results + updated virtual image

[0855] Each processing step works together to make the new menu development process quick and efficient.

[0856] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0857] This invention is a system that supports the rapid and efficient development of new menu items by linking users, terminals, a server, and an emotion engine. This system accepts input of information on ingredients, cooking methods, calorie restrictions, and allergies for new menu items, performs analysis based on the information, and provides a virtual evaluation and image. Furthermore, by recognizing the user's emotions and providing feedback and suggestions based on those emotions, the system achieves more accurate new menu development.

[0858] System Objectives

[0859] The main purpose of this system is to streamline the new menu development process and reduce costs and time by conducting virtual evaluations without using actual ingredients or cooking. Furthermore, it will reduce food waste and promote the growth of a sustainable food industry. Furthermore, by taking user emotions into consideration, it will support the development of menus that provide greater satisfaction.

[0860] System configuration

[0861] The main components of the system are:

[0862] User device: A computer, tablet, or other input device used by a restaurant or food-related business.

[0863] Server: A central computer that performs analytical processing and generates various data using generative AI and an emotion engine.

[0864] Generative AI: Artificial intelligence techniques for performing data analysis.

[0865] Emotion engine: Technology that recognizes and analyzes user emotions.

[0866] VR and 3D modeling technology: Technology for creating virtual presentation images.

[0867] Processing Details

[0868] Below, we will explain how each component works together and its specific operation using concrete examples.

[0869] User: Create and submit input data

[0870] The user uses the terminal to input the cooking method, ingredient information, calorie restrictions, allergy information, etc. of the new menu item. For example, if you want to develop a "low-calorie pasta," you would input the following information:

[0871] Ingredients: Pasta, tomatoes, olive oil, basil

[0872] Cooking method: boiling, frying

[0873] Calorie restriction: 500 kcal or less

[0874] Allergy Information: Gluten Free

[0875] After completing the input, the user presses a button to transmit the data.

[0876] Terminal: Data transmission and validation

[0877] The terminal temporarily stores the data entered by the user and checks whether the format is correct (validation). For example, it checks whether all required fields have been entered, whether the numerical range is correct, etc. If there are no problems, it sends the data to the server.

[0878] Server: Receives and analyzes data

[0879] The server receives and stores the data sent from the device, then uses the generation AI to obtain nutritional information for each ingredient from the ingredient database and calculate total calories, allergy information, and halal compliance information.

[0880] Server: Generate virtual presentation images

[0881] The server then uses VR and 3D modeling technology to generate a virtual presentation of the new menu item, which is then presented as a 3D model that can be viewed from all angles.

[0882] Server: Sending analysis results

[0883] The analysis results and virtual presentation images are sent from the server to the device, including the following information:

[0884] Total calories: 480 kcal

[0885] Nutritional Information: High in Vitamin C and Iron

[0886] Allergy Information: Gluten Free

[0887] Halal compatibility: Considered

[0888] Presentation image: 3D model (all-directional view)

[0889] Terminal: Display of analysis results

[0890] The terminal displays the information received from the server to the user, allowing the user to check the final image of the new menu, as well as information on ingredients and allergies.

[0891] Users: Send feedback and refine

[0892] The user can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the terminal.

[0893] Emotion Engine: User Emotion Recognition and Analysis

[0894] The emotion engine recognizes emotions from user feedback, facial expressions during operation, tone of voice, etc. For example, if the user shows positive emotions, it determines that the proposed menu will be well-received.

[0895] Emotion-based feedback and readjustment

[0896] The emotion data recognized by the emotion engine is taken into account when the server re-analyzes the data. For example, if a user expresses negative emotions in response to a new menu suggestion, the server will suggest different ingredients or cooking methods.

[0897] Generate and display new analysis results

[0898] The reanalyzed data and the virtual presentation image are sent back to the terminal and displayed to the user, who can then provide feedback and make further adjustments as necessary.

[0899] Through this process, users can efficiently develop and evaluate new menu items. Furthermore, feedback that takes user emotions into consideration will enable the development of new menu items that will provide greater satisfaction.

[0900] The processing flow will be explained below.

[0901] Step 1:

[0902] Users input information about ingredients, cooking methods, calorie restrictions, and allergies into the terminal to develop new menu items. For example, if you want to develop a "low-calorie pasta," you would enter the following information:

[0903] Ingredients: Pasta, tomatoes, olive oil, basil

[0904] Cooking method: boiling, frying

[0905] Calorie restriction: 500 kcal or less

[0906] Allergy Information: Gluten Free

[0907] Once you have completed the input, click the send button to send the data.

[0908] Step 2:

[0909] The terminal temporarily stores the data entered by the user. Then it validates whether the data format is correct, whether all required fields have been entered, whether the numerical range is correct, etc. If the data is valid, the terminal sends the data to the server.

[0910] Step 3:

[0911] The server receives the data sent from the device, stores it, and then converts it into the format required for analysis.

[0912] Step 4:

[0913] The server uses AI to analyze the received data. Here, it obtains nutritional information for each ingredient from the ingredient database and generates calorie calculations, halal compliance information, and allergy information. For example, it obtains ingredient data for pasta, tomato, olive oil, and basil and calculates the total calories as 480 kcal.

[0914] Step 5:

[0915] The server uses VR and 3D modeling technology to generate a virtual presentation image based on the analysis results, and the generated image is provided as a 3D model that can be viewed from all angles.

[0916] Step 6:

[0917] The server sends the analysis results and virtual presentation images to the device, including data such as total calories, nutritional information, allergy information, halal compliance information, and 3D presentation images.

[0918] Step 7:

[0919] The terminal displays the analysis results received from the server and a virtual presentation image to the user, who can then check the finished image of the new menu, as well as ingredient and allergy information.

[0920] Step 8:

[0921] The user can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the terminal.

[0922] Step 9:

[0923] The server receives feedback from the user, performs a new analysis with necessary adjustments, and then generates the reanalysis results and a new virtual presentation image, which are then sent to the terminal again.

[0924] Step 10:

[0925] The server runs an emotion engine that recognizes emotions from the user's feedback, facial expressions during operation, tone of voice, etc. The emotion engine analyzes whether the user is expressing positive or negative emotions.

[0926] Step 11:

[0927] The user's emotion data recognized by the emotion engine is used for reanalysis by the server. For example, if the user expresses negative emotion in response to a new menu suggestion, different ingredients or cooking methods will be suggested. Conversely, if a positive emotion is recognized, the suggestion will be saved with high accuracy.

[0928] Step 12:

[0929] The results of the reanalysis using the emotion engine's emotion data analysis and the new virtual presentation image are sent to the device again and displayed to the user. The user can then provide feedback and make further adjustments as necessary.

[0930] Through this process, users can efficiently develop and evaluate new menu items. Furthermore, feedback that takes user emotions into consideration will enable the development of new menu items that will provide greater satisfaction.

[0931] Example 2

[0932] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0933] The traditional new menu development process had the problem of being extremely costly and time-consuming because it was impossible to evaluate the results without using actual ingredients and cooking. Furthermore, it was difficult to provide feedback that took user emotions into consideration, preventing the development of menus that would provide high levels of satisfaction. As a result, food waste and food waste increased, and this did not contribute to the growth of a sustainable food industry.

[0934] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for a new menu item entered by a restaurant or food-related company; means for verifying the correct format of the entered information; means for analyzing the received information using a generative AI and virtually providing ingredient data, calorie calculations, religious compliance information, and allergy information; means for generating a virtual presentation image using virtual reality and modeling technology; means for transmitting the analysis results and the virtual presentation image to a terminal for displaying them; and means for analyzing the user's emotions and providing feedback based on the generative AI model. This enables the rapid and efficient development of new menu items, reduces food waste and ingredient waste, and contributes to the sustainable growth of the food industry. Furthermore, feedback based on user emotions can lead to the development of menu items with higher satisfaction.

[0935] "Ingredient information" refers to information such as the names, amounts, and components of ingredients used in developing new menu items.

[0936] "Recipe" is information that indicates the steps and methods for cooking ingredients.

[0937] "Calorie restriction" is a standard value for limiting the total calories contained in one meal.

[0938] "Allergy information" is information about foods that contain specific allergens.

[0939] "Generative AI" is a system that uses artificial intelligence technology to analyze data and generate information.

[0940] "Ingredient component data" is information on the nutritional and chemical components contained in each ingredient.

[0941] "Religious accommodation information" is food information to meet specific religious restrictions.

[0942] A "virtual presentation image" is a virtual presentation image of a new menu item created using virtual reality and 3D modeling technology.

[0943] A "terminal" is an input and display device, such as a computer or tablet, that a user uses to operate the system.

[0944] The "emotion engine" is a technology that recognizes and analyzes emotions from the user's facial expressions, tone of voice, etc.

[0945] "Feedback" refers to information about opinions and impressions that users input regarding analysis results and suggestions.

[0946] "Reanalysis" is the process in which the generative AI reanalyzes the data and derives new results based on the feedback and sentiment analysis results it receives.

[0947] "Virtual reality" is a technology that uses computer technology to virtually create experiences that are similar to reality.

[0948] "3D modeling technology" is a technology for digitally generating objects in three-dimensional space.

[0949] This invention is a system that supports the rapid and efficient development of new menu items by linking users, terminals, servers, and an emotion engine. Specifically, the system analyzes the data entered by users to input information about ingredients, cooking methods, calorie restrictions, and allergies for new menu items, and provides virtual evaluations and images. It also recognizes the user's emotions and provides feedback and suggestions based on them, enabling more accurate new menu development.

[0950] Hardware and Software

[0951] This system consists of the following components:

[0952] User Device: An input and display device such as a computer or tablet used by a restaurant or food-related business.

[0953] Server: A central computer that performs analytical processing and generates various data using generative AI and an emotion engine.

[0954] Generative AI: Artificial intelligence techniques for performing data analysis.

[0955] Emotion engine: Technology that recognizes and analyzes user emotions.

[0956] VR and 3D modeling technology: Technology for creating virtual presentation images.

[0957] Data processing and calculation

[0958] The user uses the terminal to input information about ingredients, cooking methods, calorie restrictions, and allergy information for the new menu item. For example, if you want to develop a "low-calorie pasta," you would enter the following information:

[0959] Ingredients: Pasta, tomatoes, olive oil, basil

[0960] Cooking method: boiling, frying

[0961] Calorie restriction: 500 kcal or less

[0962] Allergy Information: Gluten Free

[0963] The entered information is first saved on the device and validated for correct format. The data is then sent to the server, where it uses generative AI to retrieve nutritional information for each ingredient from a food ingredient database and calculate total calories, allergy information, and religious compliance information. At the same time, VR and 3D modeling technology is used to generate a virtual presentation of the new menu item.

[0964] The generated analysis results and virtual presentation image are sent to the device and displayed to the user. The user can input feedback based on this information and request readjustments if necessary. The readjustment feedback is sent back to the server, and the emotion engine analyzes the user's emotions. Data analysis is performed based on the user's emotions, and any necessary corrections or improvements are made.

[0965] Prompt Sentence Examples

[0966] An example of a prompt sentence to input to the generative AI model is as follows:

[0967] I'd like you to generate new menu ideas. Please provide the following information:

[0968] Ingredients: Pasta, tomatoes, olive oil, basil

[0969] Cooking method: Boiling, frying

[0970] Calorie restriction: 500 kcal or less

[0971] Allergy Information: Gluten Free

[0972] Through this system, users can quickly and efficiently develop new menu items, reducing food waste and food loss and promoting the growth of a sustainable food industry. Feedback that takes user emotions into consideration also enables the development of menu items that offer greater satisfaction.

[0973] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0974] Step 1:

[0975] The user uses the terminal to input information about ingredients, cooking methods, calorie restrictions, and allergy information for a new menu item. For example, if developing a "low-calorie pasta," the user enters the following information:

[0976] input:

[0977] Ingredients: Pasta, tomatoes, olive oil, basil

[0978] Cooking method: Boiling, frying

[0979] Calorie restriction: 500 kcal or less

[0980] Allergy Information: Gluten Free

[0981] The user presses a button to transmit data to the terminal.

[0982] Step 2:

[0983] The terminal temporarily stores the data entered by the user. Then it validates the data to ensure that it is in the correct format. For example, it checks whether all required fields have been entered and whether the numeric range is correct.

[0984] Input: Data submitted by the user

[0985] Data processing: format check, required field input check, numerical range check

[0986] Output: Validated data

[0987] If the validation is successful, the terminal transmits the data to the server.

[0988] Step 3:

[0989] The server receives the data sent from the device and stores it in a database.

[0990] Input: Validated data sent from the terminal

[0991] Data processing: Saving to database

[0992] Output: Saved data

[0993] Step 4:

[0994] The server uses generative AI to obtain nutritional information for each ingredient from a food ingredient database, such as the calories in pasta or the vitamin C content of tomatoes, and then calculates the total calories, allergy information, and religious compatibility information.

[0995] Input: Saved data

[0996] Data processing: Obtaining nutritional information from the food ingredient database, calculating total calories, and calculating allergy and religious information.

[0997] Output: Analysis results

[0998] Step 5:

[0999] The server uses VR and 3D modeling technology to generate a virtual presentation of the new menu items, which are then presented as 3D models that can be viewed from all angles.

[1000] Input: Analysis results

[1001] Data processing: Creating virtual presentation images using VR and 3D modeling technology

[1002] Output: Virtual presentation image

[1003] Step 6:

[1004] The server sends the analysis results and the generated virtual presentation image to the terminal.

[1005] Input: Analysis results, virtual presentation image

[1006] Data processing: Data integration

[1007] Output: Analysis results and virtual presentation images sent to the device

[1008] Step 7:

[1009] The terminal displays the information received from the server to the user, who can check the finished image of the new menu, as well as information on ingredients and allergies.

[1010] Input: Analysis results and virtual presentation images sent from the server

[1011] Data processing: Conversion to display format

[1012] Output: Displayed information

[1013] Step 8:

[1014] The user inputs feedback based on the analysis results. For example, they can enter comments such as "I'd like to reduce the amount of tomatoes" or "I'd like to change the cooking method." The feedback is sent to the server via the device.

[1015] Input: Analysis results and feedback opinions

[1016] Data processing: Adding feedback

[1017] Output: Feedback sent to the server

[1018] Step 9:

[1019] The server receives feedback from the user. At the same time, it uses an emotion engine to analyze the user's emotions based on their feedback, facial expressions, tone of voice, etc. It determines whether the user is expressing positive or negative emotions.

[1020] Input: Feedback and user emotional data (facial expressions, tone of voice, etc.)

[1021] Data processing: Sentiment analysis

[1022] Output: Emotion analysis results

[1023] Step 10:

[1024] The server reanalyzes the emotion data obtained from the emotion engine, and if the user gives negative feedback, it suggests alternative ingredients and cooking methods.

[1025] Input: Sentiment analysis results and feedback content

[1026] Data processing: reanalysis, generation of proposals

[1027] Output: Reanalysis results and recommendations

[1028] Step 11:

[1029] The server sends the reanalyzed data and the new virtual presentation image to the terminal, which provides new analysis results.

[1030] Input: Reanalysis results and new proposals

[1031] Data processing: Data integration

[1032] Output: Reanalysis results and virtual presentation image sent to the device

[1033] Step 12:

[1034] The device displays the reanalysis results to the user, who then provides feedback based on the new information. This process is repeated until the user is satisfied.

[1035] Input: Reanalysis results and virtual serving image sent from the server

[1036] Data processing: Conversion to display format

[1037] Output: Displayed reanalysis results and virtual presentation image

[1038] This series of processing steps allows users to efficiently develop and evaluate new menus, and feedback that takes user emotions into consideration makes it possible to develop menus that will provide high levels of satisfaction.

[1039] (Application example 2)

[1040] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1041] The traditional new menu development process was cost-inefficient, resulting in a lot of wasted ingredients and time, and requiring multiple prototypes. Furthermore, there was no way to provide feedback or suggestions that directly reflected user sentiment, resulting in low satisfaction with the final menu. To solve these problems, a system is needed that can efficiently and quickly develop new menus and make accurate suggestions based on user sentiment.

[1042] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1043] In this invention, the server includes means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related companies, means for verifying that the format of the entered information is correct, means for analyzing the received information using a generation AI and virtually providing ingredient data, calorie calculations, halal compliance information, and allergy information, means for generating virtual presentation images using virtual reality and 3D modeling technology, means for transmitting the analysis results and the virtual presentation images to a terminal for displaying them, means for providing an emotion engine for recognizing and analyzing user emotions, and means for providing feedback and suggestions based on the user emotions. This enables more efficient new menu development and more accurate suggestions based on user emotions.

[1044] "Restaurants or food-related companies" refers to businesses that develop and offer new menu items.

[1045] A "new menu" is a new dish or food that has never been offered before.

[1046] "Ingredient information" refers to detailed information about the types, quantities, origins, etc. of the various ingredients used in the new menu.

[1047] "Cooking method" refers to the specific cooking steps and methods used with ingredients.

[1048] "Calorie restriction" refers to a standard or requirement for keeping the total calories per meal within a specific range.

[1049] "Allergy information" refers to information about the possibility of an allergic reaction to a particular food ingredient.

[1050] "Means for receiving" refers to the method or technology for receiving information from a user.

[1051] "Verification means" refers to methods or techniques used to verify that received information conforms to its format and content.

[1052] "Generative AI" refers to artificial intelligence techniques used to analyze input data and generate the necessary information.

[1053] "Food ingredient data" refers to data on the nutrients and characteristics contained in each food ingredient.

[1054] "Calculating calories" refers to the process of calculating total calories based on ingredient information.

[1055] "Halal compatibility information" refers to information that indicates whether or not a food is suitable for consumption by Muslims.

[1056] "Virtual provision means" refers to methods and technologies for providing information or images that do not physically exist in a virtual space.

[1057] "Virtual reality" is a technology that provides a realistic experience within a computer-generated virtual environment.

[1058] "3D modeling technology" refers to the techniques and tools used to construct 3D virtual objects.

[1059] "Generative means" refers to methods and techniques for producing new information and images.

[1060] A "display terminal" is a device that allows a user to visually confirm information or images.

[1061] An "emotion engine" is a technology that recognizes and analyzes emotions from a user's facial expressions, tone of voice, etc.

[1062] "Means of providing" refers to methods or means for incorporating specific functions or technologies into a system.

[1063] "Feedback and suggestion means" refers to methods and technologies for providing advice and new suggestions based on analysis results and user sentiment.

[1064] "Means for reanalysis" refers to methods and techniques for re-analyzing data based on feedback or new data.

[1065] This invention is a system that supports the rapid and efficient development of new menus by linking user terminals, servers, generation AI, and emotion engines. This system collects input data, validates and analyzes data, generates virtual images, analyzes emotions, and receives and reanalyzes feedback. Specific implementation methods for the system are described below.

[1066] Hardware and software used

[1067] 1. User device: Uses input devices such as computers and tablets.

[1068] 2. Server: Serves as the central computer that performs analytical processing. Specific software uses generative AI technology.

[1069] 3. Generative AI: Artificial intelligence techniques used for data analysis and virtual presentation image generation.

[1070] 4. Emotion Engine: Technology that analyzes the user's facial expressions and tone of voice to recognize emotions. Uses "some_emotion_recognition_library" as the specific library.

[1071] 5. VR and 3D modeling technology: Technology used to generate virtual presentation images. For specific software, use "some_vr_library".

[1072] Data processing and calculation

[1073] The user terminal collects data such as ingredients, cooking methods, calorie restrictions, and allergy information for new menu items, and verifies that the entered information is in the correct format.

[1074] For example: "Ingredients: pasta, tomato, olive oil, basil", "Cooking method: boiling, frying", "Calorie limit: 500 kcal or less", "Allergy information: gluten-free"

[1075] The server receives data sent from the device and uses AI to analyze ingredient data, calorie calculations, halal compliance information, and allergy information, while also using VR and 3D modeling technology to generate virtual presentation images.

[1076] Example: "The generated virtual presentation image is provided in a format that can be viewed from all directions."

[1077] The emotion engine analyzes feedback from the user, facial expressions during operation, tone of voice, and other factors to recognize the user's emotions.

[1078] For example: "If the user expresses positive emotions, it will be considered positive and other cooking suggestions will be made."

[1079] Specific examples

[1080] For example, if a chef wants to develop a new "low-calorie pasta menu," he or she can use the system as follows:

[1081] 1. Enter ingredient information, cooking method, calorie restrictions, and allergy information into the user terminal.

[1082] 2. The server analyzes the data and generates a virtual presentation image.

[1083] 3. The user checks the analysis results and the virtual presentation image and provides feedback.

[1084] 4. The emotion engine analyzes the feedback and re-suggests the menu if necessary.

[1085] Prompt Sentence Examples

[1086] "This pasta dish uses five ingredients and aims to be under 500 kcal. Basil and tomato are the main ingredients. It is cooked both boiled and sautéed. It is gluten-free. Please generate detailed ingredient information and a virtual serving image for this dish."

[1087] As described above, using this system will make the new menu development process more efficient and enable proposals that will provide high levels of satisfaction based on user emotions.

[1088] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1089] Step 1:

[1090] The user inputs information about ingredients, cooking methods, calorie restrictions, and allergy information for a new menu item into the user terminal. Examples of input data include "Ingredients: pasta, tomato, olive oil, basil," "Cooking method: boiling, stir-frying," "Calorie restrictions: under 500 kcal," and "Allergy information: gluten-free." After input, the user terminal temporarily stores this information.

[1091] Step 2:

[1092] The terminal verifies that the format of the temporarily saved data is correct. For example, it checks whether all required fields have been entered and whether the numeric range is appropriate. If the format is correct, the terminal sends the data to the server. The input here is the menu information entered by the user, and the output is the verified data.

[1093] Step 3:

[1094] The server receives the data sent from the device and stores it. Next, it uses generative AI to obtain nutritional information for each ingredient from the ingredient database and calculates total calories, allergy information, and halal compliance information. For example, it obtains the calorie and nutritional information for "pasta" based on the received ingredient information. The input is verified menu information, and the output is the analysis results.

[1095] Step 4:

[1096] The server uses VR and 3D modeling technology to generate a virtual presentation image based on the analysis results. For example, it generates a 3D model of the appearance of low-calorie pasta. This allows users to check the appearance of the menu from all angles. The input is the analysis results, and the output is a 3D model of the presentation image.

[1097] Step 5:

[1098] The server sends the analysis results and a virtual presentation image to the terminal. The user terminal receives this and displays it to the user. For example, the analysis results may be displayed as "Calories: 480 kcal" or "Nutritional information: High in vitamin C, rich in iron." The input is the analysis results and a 3D image, and the output is visualized data that the user can view.

[1099] Step 6:

[1100] The user checks the displayed analysis results and the virtual presentation image and inputs feedback. The user's device sends this feedback to the server. For example, the user sends a specific request such as "I'd like more tomatoes." The input is the user's feedback, and the output is the feedback data.

[1101] Step 7:

[1102] The server receives the feedback and analyzes the user's emotions using an emotion engine. For example, the analysis result may be, "There are many positive opinions, but they would like to increase the amount of tomatoes." The input is the user's feedback, and the output is the emotion analysis result.

[1103] Step 8:

[1104] The server then uses the generative AI again to perform a new analysis based on the results of the emotion analysis. For example, it recalculates the nutritional content and calories if the amount of tomato is increased, and generates a new virtual presentation image. The input is the emotion analysis result and the reconfigured menu information, and the output is the reanalysis result and the new virtual presentation image.

[1105] Step 9:

[1106] The server sends the reanalysis results and a new virtual presentation image to the terminal and displays them to the user. The user then provides feedback and makes further adjustments as necessary. Ultimately, a new menu that satisfies the user is finalized. The input is the reanalysis results and a new 3D image, and the output is final confirmation data and the completion of the continuous feedback cycle.

[1107] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1108] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1109] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1110] [Third embodiment]

[1111] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1112] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1113] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1114] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1115] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1116] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1117] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1118] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1119] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[1120] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1121] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1122] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[1123] The virtual food testing system of the present invention supports the rapid and efficient development of new menu items through the cooperation of users, terminals, and servers. This system allows restaurants and food-related businesses to input information about ingredients, cooking methods, and restrictions for new menu items, and then analyzes the information to provide a virtual evaluation and image. The specific operation of the system is described below.

[1124] System Objectives

[1125] The main purpose of this system is to streamline the process of new menu development and reduce costs and time by conducting virtual evaluations without using actual ingredients or cooking. Furthermore, it will reduce food waste and promote the growth of a sustainable food industry.

[1126] System configuration

[1127] The main components of the system are:

[1128] User device: A computer, tablet, or other input device used by a restaurant or food-related business.

[1129] Server: A central computer that performs analytical processing and generates various data using generative AI.

[1130] Generative AI: Artificial intelligence techniques for performing data analysis.

[1131] VR and 3D modeling technology: Technology for creating virtual presentation images.

[1132] Processing Details

[1133] Below, we will explain how each component works together and its specific operation using concrete examples.

[1134] User: Create and submit input data

[1135] The user uses the terminal to input the cooking method, ingredient information, calorie restrictions, allergy information, etc. of the new menu item. For example, if you want to develop a "low-calorie pasta," you would input the following information:

[1136] Ingredients: Pasta, tomatoes, olive oil, basil

[1137] Cooking method: boiling, frying

[1138] Calorie restriction: 500 kcal or less

[1139] Allergy Information: Gluten Free

[1140] After completing the input, the user presses a button to transmit the data.

[1141] Terminal: Data transmission and validation

[1142] The terminal temporarily stores the data entered by the user and checks whether the format is correct (validation). For example, it checks whether all required fields have been entered, whether the numerical range is correct, etc. If there are no problems, it sends the data to the server.

[1143] Server: Receives and analyzes data

[1144] The server receives the data sent from the device and begins analysis using the AI. Specifically, it retrieves the nutritional information of each ingredient from the ingredient database and calculates the total calories, allergy information, halal compliance information, etc. For example, it retrieves the nutritional information for pasta, tomato, olive oil, and basil, and calculates the total calories as 480 kcal.

[1145] Server: Generate virtual presentation images

[1146] The server then uses VR and 3D modeling technology to generate a virtual presentation of the new menu item, which is then presented as a 3D model that can be viewed from all angles.

[1147] Server: Sending analysis results

[1148] The analysis results and virtual presentation images are sent from the server to the device, including the following information:

[1149] Total calories: 480 kcal

[1150] Nutritional Information: High in Vitamin C and Iron

[1151] Allergy Information: Gluten Free

[1152] Halal compatibility: Considered

[1153] Presentation image: 3D model (all-directional view)

[1154] Terminal: Display of analysis results

[1155] The terminal displays the information received from the server to the user, allowing the user to check the final image of the new menu, as well as information on ingredients and allergies.

[1156] Users: Send feedback and refine

[1157] Users can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the device, and a new analysis is performed.

[1158] In this way, the virtual food testing system enables the new menu development process to proceed efficiently, reducing costs and food waste.

[1159] The processing flow will be explained below.

[1160] Step 1:

[1161] Users input information about ingredients, cooking methods, calorie restrictions, and allergies into the terminal to develop new menu items. Once input is complete, the data is sent by pressing the send button.

[1162] Step 2:

[1163] The terminal temporarily stores the data entered by the user. Then it validates whether the data format is correct, whether all required fields have been entered, whether the numerical range is correct, etc. If the data is valid, the terminal sends the data to the server.

[1164] Step 3:

[1165] The server receives the data sent from the device, stores it, and then converts it into the format required for analysis.

[1166] Step 4:

[1167] The server uses AI to analyze the received data. Here, it retrieves nutritional information for each ingredient from the ingredient database and generates calorie calculations, halal compliance information, and allergy information. For example, in the case of "low-calorie pasta," the ingredient data for pasta, tomato, olive oil, and basil are retrieved, and the total calories are calculated as 480 kcal.

[1168] Step 5:

[1169] The server uses VR and 3D modeling technology to generate a virtual presentation image based on the analysis results, and the generated image is provided as a 3D model that can be viewed from all angles.

[1170] Step 6:

[1171] The server sends the analysis results and virtual presentation images to the device, including data such as total calories, nutritional information, allergy information, halal compliance information, and 3D presentation images.

[1172] Step 7:

[1173] The terminal displays the analysis results received from the server and a virtual presentation image to the user, who can then check the finished image of the new menu, as well as ingredient and allergy information.

[1174] Step 8:

[1175] The user can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the terminal.

[1176] Step 9:

[1177] The server receives feedback from the user, performs a new analysis with necessary adjustments, and then generates the reanalysis results and a new virtual presentation image, which are then sent to the terminal again.

[1178] Through this series of processes, users can efficiently develop and evaluate new menu items, saving time and money, and is also expected to reduce food waste and food waste.

[1179] Example 1

[1180] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1181] The traditional new menu development process requires repeated trial production using actual ingredients, which is costly and time-consuming. Furthermore, failures and readjustments during the trial production stage result in food waste and food waste, which does not contribute to the development of a sustainable food industry. Furthermore, managing ingredient and allergy information is cumbersome and prone to errors.

[1182] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1183] In this invention, the server includes means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related companies, means for verifying that the format of the entered information is correct, means for analyzing the received information using a generative AI model and virtually providing ingredient data, calorie calculations, halal compliance information, and allergy information, means for generating a virtual presentation image using 3D representation technology, and means for transmitting the analysis results and the virtual presentation image to a terminal for displaying them. This allows new menu items to be virtually evaluated and improved without using actual ingredients, thereby reducing costs and food waste and making new menu development more efficient.

[1184] A "restaurant or food-related business" is a business that serves meals or is engaged in the manufacture and sale of food.

[1185] "New menu" refers to the content and combination of newly developed dishes that will be added to the existing menu.

[1186] "Ingredient information" is detailed information such as the names, types, and quantities of ingredients used in the new menu.

[1187] "Cooking method" refers to the specific techniques and processes used to cook ingredients.

[1188] "Calorie restriction" is the upper limit on the total calorie content of a diet set for health and nutritional management.

[1189] "Allergy information" refers to information on whether a consumer may have an allergic reaction to a particular food ingredient.

[1190] "Means for receiving" refers to a method or system for taking in data or information from the outside.

[1191] A "verification means" is a method or system for checking the accuracy and format of the information entered.

[1192] A "generative AI model" is an artificial intelligence algorithm or program that is trained to analyze data and generate new information.

[1193] "Means for analysis" refers to a system or method that examines the received data in detail and extracts and calculates the necessary information.

[1194] "Food ingredient data" is detailed information about the nutritional content and chemical composition of food.

[1195] "Halal compliance information" is information about ingredients and cooking methods that are permitted according to specific religious regulations.

[1196] "Means for providing" refers to a system or method for displaying or transmitting the analyzed or generated information to the user.

[1197] "Three-dimensional representation technology" refers to techniques and methods for visually representing objects and landscapes in three-dimensional space.

[1198] A "terminal" is a device, such as a computer or tablet, that a user uses to enter data or view results.

[1199] "Feedback" refers to opinions and requests for improvement from users regarding analysis results and provided information.

[1200] "Reanalysis" refers to the process of reanalyzing data based on feedback and making corrections or improvements.

[1201] A "report" is a document or electronic file that summarizes analysis results and evaluation information.

[1202] "Omnidirectional viewing" refers to a display method that allows objects in three-dimensional space to be viewed from all angles.

[1203] The virtual food testing system of the present invention supports the rapid and efficient development of new menu items through the cooperation of users, terminals, and servers. This system allows restaurants and food-related businesses to input information on ingredients, cooking methods, calorie restrictions, and allergy information for new menu items, and performs analysis based on this information to provide virtual evaluations and images.

[1204] System configuration

[1205] The main components of the system are:

[1206] User device: An input device such as a computer or tablet used by food-related companies.

[1207] Server: A central computer that performs analytical processing and generates data using generative AI.

[1208] Generative AI: Artificial intelligence techniques for performing data analysis (specifically using TensorFlow and PyTorch).

[1209] 3D representation technology: Technology for creating virtual presentation images (using Blender and Unity).

[1210] System Operation

[1211] User: Create and submit input data

[1212] The user uses the terminal to input the cooking method, ingredient information, calorie restrictions, allergy information, etc. of the new menu item. For example, if you want to develop a "low-calorie pasta," you would input the following information:

[1213] Ingredients: Pasta, tomatoes, olive oil, basil

[1214] Cooking method: boiling, frying

[1215] Calorie restriction: 500 kcal or less

[1216] Allergy Information: Gluten Free

[1217] After completing the input, the user presses a button to transmit the data.

[1218] Terminal: Data transmission and validation

[1219] The device temporarily stores the data entered by the user and checks whether the format is correct. First, it checks whether all required fields have been entered, and then it checks whether the calorie value and allergy information are within the appropriate range. After checking, the data is sent to the server.

[1220] Server: Receives and analyzes data

[1221] The server receives the data sent from the device and analyzes it using a generative AI model. First, it obtains the nutritional information for each ingredient from the ingredient database. It then calculates the total calories, allergy information, and halal compliance information. For example, based on the ingredient information for pasta, tomato, olive oil, and basil, it calculates the total calories as 480 kcal.

[1222] Server: Generate virtual presentation images

[1223] The server uses 3D rendering technology to generate a virtual presentation of the new menu item, which is then presented as a 3D model that users can view from all angles.

[1224] Server: Sending analysis results

[1225] The analysis results and virtual presentation images are sent from the server to the device, including the following information:

[1226] Total calories: 480 kcal

[1227] Nutritional Information: High in Vitamin C and Iron

[1228] Allergy Information: Gluten Free

[1229] Halal compatibility: Considered

[1230] Presentation image: 3D model (all-directional view)

[1231] Terminal: Display of analysis results

[1232] The terminal displays the information received from the server to the user, allowing the user to check the final image of the new menu, as well as information on ingredients and allergies.

[1233] Users: Send feedback and refine

[1234] The user can input feedback based on the analysis results, such as if the calorie content is too high or if they would like to change the combination of ingredients, and the feedback is sent from the device to the server.

[1235] The server performs a new analysis and sends the retuned data back to the device, allowing the user to easily make further adjustments.

[1236] In this way, the virtual food testing system streamlines the process of new menu development, reducing costs and food waste and promoting the growth of a sustainable food industry.

[1237] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1238] Step 1: Data entry

[1239] The user uses the terminal to input information about the new menu item. Specifically, they enter information about ingredients, cooking methods, calorie restrictions, allergy information, etc. into a form. For example, if you want to develop a "low-calorie pasta," you would enter the following information:

[1240] Ingredients: Pasta, tomatoes, olive oil, basil

[1241] Cooking method: boiling, frying

[1242] Calorie restriction: 500 kcal or less

[1243] Allergy Information: Gluten Free

[1244] Input: Ingredient information, cooking method, calorie restrictions, allergy information

[1245] Output: Save to device

[1246] Step 2: Submit and validate data

[1247] The terminal temporarily stores the data entered by the user. It then validates that the data format is correct. It checks that all required fields have been entered and that calorie values ​​and allergy information are within the range. If validation is successful, it sends the data to the server.

[1248] Input: Data entered by the user

[1249] Data manipulation: format and range checks

[1250] Output: Send data to the server

[1251] Specific behavior:

[1252] 1. Check the required fields

[1253] 2. Check the range of calorie values ​​and allergy information

[1254] 3. Sending data to the server

[1255] Step 3: Receiving and analyzing data

[1256] The server receives the data sent from the device. It then begins analyzing the data using a generative AI model. It obtains nutritional information for each ingredient from the ingredient database and calculates total calories, allergy information, and halal compliance information. For example, based on the ingredient information for pasta, tomato, olive oil, and basil, it calculates the total calories to be 480 kcal.

[1257] Input: Data sent from the terminal

[1258] Data processing: Obtaining nutritional information using a generative AI model and calculating total calories, allergy information, and halal compliance information

[1259] Output: Analysis results

[1260] Specific behavior:

[1261] 1. Obtain information from a food ingredient database

[1262] 2. Calculate total calories and other nutritional information

[1263] Step 4: Generate a virtual presentation image

[1264] The server uses 3D rendering technology to generate a virtual presentation image of the new menu item, which is then presented as a 3D model that users can view from any angle.

[1265] Input: Analysis results

[1266] Data processing: Image generation using 3D expression technology (Blender or Unity)

[1267] Output: Virtual presentation image of 3D model

[1268] Specific behavior:

[1269] 1. 3D modeling of a virtual presentation image

[1270] 2. Provide a format that can be viewed from all angles

[1271] Step 5: Submitting the analysis results

[1272] The server sends the analysis results and the virtual presentation image to the device. The analysis results include the following information:

[1273] Total calories: 480 kcal

[1274] Nutritional Information: High in Vitamin C and Iron

[1275] Allergy Information: Gluten Free

[1276] Halal compatibility: Considered

[1277] Presentation image: 3D model (all-directional view)

[1278] Input: Analysis results, virtual arrangement image of 3D model

[1279] Output: Send to terminal

[1280] Step 6: Viewing the analysis results

[1281] The terminal displays the information received from the server to the user, who can check the finished image of the new menu, as well as information on ingredients and allergies.

[1282] Input: Analysis results and 3D model from the server

[1283] Output: What is displayed to the user

[1284] Specific behavior:

[1285] 1. Display analysis results and 3D models on your device

[1286] Step 7: Provide feedback and refine

[1287] The user inputs feedback based on the analysis results and sends it from the device to the server. The server receives the user's feedback, performs re-analysis using the generative AI model, and then sends the corrected data back to the device.

[1288] Input: User feedback

[1289] Data processing: Reanalysis using generative AI models

[1290] Output: Re-send the corrected analysis results to the terminal

[1291] Specific behavior:

[1292] 1. Receiving Feedback

[1293] 2. Perform reanalysis

[1294] 3. Sending the reanalysis results to the device

[1295] Through these steps, the virtual food testing system streamlines the new menu development process, reducing costs and food waste.

[1296] (Application example 1)

[1297] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1298] The traditional new menu development process required the use of actual ingredients and cooking, which was time-consuming and costly, and required a large number of resources to evaluate new menu items. Furthermore, the food delivery industry is required to quickly provide new menu items in a short amount of time, but there was no efficient way to achieve this. Furthermore, there was a lack of a system for virtually evaluating menu items without actual tasting, thereby improving customer satisfaction.

[1299] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1300] In this invention, the server includes: means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related companies; means for verifying the correct format of the entered information; means for analyzing the received information using generation AI and virtually providing ingredient data, calorie calculations, halal compliance information, and allergy information; means for generating virtual presentation images using VR and modeling technology; means for transmitting the analysis results and the virtual presentation images to a terminal for displaying them; and means for, as a virtual food delivery development support app, allowing users to enter feedback, reanalyze the results, and support the evaluation of new menu items, including readjustments. This allows for an efficient process for new menu development, reducing costs and food waste.

[1301] "Restaurants or food-related businesses" refers to establishments that serve food and beverages, and businesses that manufacture and sell food in general.

[1302] "Ingredient information" refers to detailed information such as the names, types, nutritional components, and origins of the ingredients that make up the new menu.

[1303] "Cooking method" refers to the specific steps or methods for cooking ingredients.

[1304] "Calorie restriction" refers to restricting the total calories of a particular menu item to within a certain range.

[1305] "Allergy information" refers to information that may cause an allergic reaction to a particular food ingredient or component.

[1306] "Means for receiving" refers to hardware or software for receiving and processing data sent from an external source.

[1307] "Verification means" refers to the processes and techniques used to verify the accuracy and integrity of input data.

[1308] "Generative AI" refers to artificial intelligence technology that generates new information based on large amounts of data.

[1309] "Means for analyzing and providing" refers to the technology used to analyze received data and generate and provide useful information or results.

[1310] "VR and modeling technology" refers to virtual reality technology and technology for creating 3D models.

[1311] "Display terminal" refers to a device that visually presents analysis results and virtual images to users.

[1312] A "virtual food delivery development support app" refers to an application designed to streamline the development of new menu items for the food delivery industry.

[1313] "Reanalysis" refers to the process of re-analyzing data based on new information, such as feedback.

[1314] "Means of providing omnidirectional viewpoints" refers to technology that allows 3D models and VR content to be viewed from various viewpoints.

[1315] "Means for generating reports" refers to the technology for compiling analysis results, evaluations, etc. in document format.

[1316] The virtual food delivery development support system of this invention operates in cooperation with three parties: the user, the terminal, and the server. This system provides virtual evaluations and images by allowing the user to input information on ingredients, cooking methods, calorie restrictions, and allergy information for a new menu item and send it to the server via the terminal.

[1317] Specific components of the system include:

[1318] 1. User Device:

[1319] A user terminal is a device such as a computer or tablet used by a restaurant or food-related business. A user uses this terminal to input information about new menu items. For example, a user can input information about a new menu item as follows:

[1320] Ingredients: Pasta, tomatoes, olive oil, basil

[1321] Cooking method: boiling, frying

[1322] Calorie restriction: 500 kcal or less

[1323] Allergy Information: Gluten Free

[1324] 2. Data transmission:

[1325] Once the information has been entered, it is sent from the terminal to the server. At that time, the terminal checks whether the format is correct (validation). For example, it checks whether all required fields have been entered, whether the range of values ​​is correct, etc. If there are no problems, the data is sent to the server.

[1326] 3. Server:

[1327] The server is the hub of the analysis process, using generative AI to analyze the received data and provide ingredient data, calorie calculations, halal compliance information, and allergy information.

[1328] Additionally, VR and 3D modeling technology is used to generate virtual presentation images, which are then presented in a format that can be viewed from all angles.

[1329] 4. Sending analysis results and virtual images:

[1330] The server sends the analysis results and a virtual presentation image to the device, including the following information:

[1331] Total calories: 480 kcal

[1332] Nutritional information: High in vitamin C and iron

[1333] Allergy Information: Gluten Free

[1334] Halal compatibility information: Considered

[1335] Arrangement image: 3D model (all-directional view)

[1336] 5. Display on user terminal:

[1337] The analysis results and virtual images are displayed on the user's terminal, allowing the user to check the finished image of the new menu and ingredient information. Furthermore, by entering feedback, the user can request further improvements and corrections from the server.

[1338] Specifically, the following text prompt can be sent to the server:

[1339] Ingredients: pasta, tomatoes, olive oil, basil

[1340] Cooking method: boiling, frying

[1341] Calorie restriction: 500 kcal or less

[1342] Allergy Information: Gluten Free

[1343] Based on this prompt, the server uses a generative AI model to analyze the new menu and provide a virtual evaluation and image, allowing users to develop new menu items more quickly and efficiently.

[1344] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1345] Step 1:

[1346] The user uses the device to input information about the new menu item, including information about ingredients, cooking methods, calorie restrictions, and allergy information, and then presses a button to send the data after completing the input. This temporarily saves the input data in the device.

[1347] input:

[1348] Ingredients: Pasta, tomatoes, olive oil, basil

[1349] Cooking method: boiling, frying

[1350] Calorie restriction: 500 kcal or less

[1351] Allergy Information: Gluten Free

[1352] output:

[1353] Saved Input Data

[1354] Step 2:

[1355] The terminal checks whether the format of the saved input data is correct (validation). At this stage, it checks whether all required fields have been entered, whether the range of values ​​is correct, etc. If there are no problems, it sends the data to the server.

[1356] input:

[1357] Saved Input Data

[1358] output:

[1359] Validated data

[1360] Step 3:

[1361] The server receives the validated data sent from the device. It analyzes this data using a generation AI and provides ingredient data, calorie calculations, halal compliance information, and allergy information. During the analysis process, it extracts nutritional information for ingredients from the database and calculates total calories and ingredient information.

[1362] input:

[1363] Validated data

[1364] output:

[1365] Ingredient data, calorie calculation results, halal compliance information, allergy information

[1366] Step 4:

[1367] Using VR and 3D modeling technology, the server generates a virtual presentation of the new menu items, which can be viewed in 3D format from any angle.

[1368] input:

[1369] Ingredient data, cooking method data

[1370] output:

[1371] Virtual presentation image (3D model)

[1372] Step 5:

[1373] The server then sends the analysis results and a virtual presentation image to the device, including total calories, nutritional information, and allergy information.

[1374] input:

[1375] Analysis results and virtual presentation image

[1376] output:

[1377] Transmission data (analysis results + virtual image)

[1378] Step 6:

[1379] The terminal displays the received analysis results and virtual images to the user, allowing the user to check the finished image of the new menu, as well as information on ingredients, calories, and allergies.

[1380] input:

[1381] Transmission data (analysis results + virtual image)

[1382] output:

[1383] User Display Data

[1384] Step 7:

[1385] The user checks the analysis results and inputs feedback, which is sent to the server via the terminal, allowing the user to request reanalysis. This feedback can include adjustments to the taste or improvements to the appearance.

[1386] input:

[1387] Feedback Information

[1388] output:

[1389] Reanalysis Request

[1390] Step 8:

[1391] The server then performs a re-analysis based on user feedback, using a re-generative AI to perform a virtual evaluation based on updated data and new conditions, and generate new results.

[1392] input:

[1393] Reanalysis Request

[1394] output:

[1395] Reanalysis results + updated virtual image

[1396] Each processing step works together to make the new menu development process quick and efficient.

[1397] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1398] This invention is a system that supports the rapid and efficient development of new menu items by linking users, terminals, a server, and an emotion engine. This system accepts input of information on ingredients, cooking methods, calorie restrictions, and allergies for new menu items, performs analysis based on the information, and provides a virtual evaluation and image. Furthermore, by recognizing the user's emotions and providing feedback and suggestions based on those emotions, the system achieves more accurate new menu development.

[1399] System Objectives

[1400] The main purpose of this system is to streamline the new menu development process and reduce costs and time by conducting virtual evaluations without using actual ingredients or cooking. Furthermore, it will reduce food waste and promote the growth of a sustainable food industry. Furthermore, by taking user emotions into consideration, it will support the development of menus that provide greater satisfaction.

[1401] System configuration

[1402] The main components of the system are:

[1403] User device: A computer, tablet, or other input device used by a restaurant or food-related business.

[1404] Server: A central computer that performs analytical processing and generates various data using generative AI and an emotion engine.

[1405] Generative AI: Artificial intelligence techniques for performing data analysis.

[1406] Emotion engine: Technology that recognizes and analyzes user emotions.

[1407] VR and 3D modeling technology: Technology for creating virtual presentation images.

[1408] Processing Details

[1409] Below, we will explain how each component works together and its specific operation using concrete examples.

[1410] User: Create and submit input data

[1411] The user uses the terminal to input the cooking method, ingredient information, calorie restrictions, allergy information, etc. of the new menu item. For example, if you want to develop a "low-calorie pasta," you would input the following information:

[1412] Ingredients: Pasta, tomatoes, olive oil, basil

[1413] Cooking method: boiling, frying

[1414] Calorie restriction: 500 kcal or less

[1415] Allergy Information: Gluten Free

[1416] After completing the input, the user presses a button to transmit the data.

[1417] Terminal: Data transmission and validation

[1418] The terminal temporarily stores the data entered by the user and checks whether the format is correct (validation). For example, it checks whether all required fields have been entered, whether the numerical range is correct, etc. If there are no problems, it sends the data to the server.

[1419] Server: Receives and analyzes data

[1420] The server receives and stores the data sent from the device, then uses the generation AI to obtain nutritional information for each ingredient from the ingredient database and calculate total calories, allergy information, and halal compliance information.

[1421] Server: Generate virtual presentation images

[1422] The server then uses VR and 3D modeling technology to generate a virtual presentation of the new menu item, which is then presented as a 3D model that can be viewed from all angles.

[1423] Server: Sending analysis results

[1424] The analysis results and virtual presentation images are sent from the server to the device, including the following information:

[1425] Total calories: 480 kcal

[1426] Nutritional Information: High in Vitamin C and Iron

[1427] Allergy Information: Gluten Free

[1428] Halal compatibility: Considered

[1429] Presentation image: 3D model (all-directional view)

[1430] Terminal: Display of analysis results

[1431] The terminal displays the information received from the server to the user, allowing the user to check the final image of the new menu, as well as information on ingredients and allergies.

[1432] Users: Send feedback and refine

[1433] The user can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the terminal.

[1434] Emotion Engine: User Emotion Recognition and Analysis

[1435] The emotion engine recognizes emotions from user feedback, facial expressions during operation, tone of voice, etc. For example, if the user shows positive emotions, it determines that the proposed menu will be well-received.

[1436] Emotion-based feedback and readjustment

[1437] The emotion data recognized by the emotion engine is taken into account when the server re-analyzes the data. For example, if a user expresses negative emotions in response to a new menu suggestion, the server will suggest different ingredients or cooking methods.

[1438] Generate and display new analysis results

[1439] The reanalyzed data and the virtual presentation image are sent back to the terminal and displayed to the user, who can then provide feedback and make further adjustments as necessary.

[1440] Through this process, users can efficiently develop and evaluate new menu items. Furthermore, feedback that takes user emotions into consideration will enable the development of new menu items that will provide greater satisfaction.

[1441] The processing flow will be explained below.

[1442] Step 1:

[1443] Users input information about ingredients, cooking methods, calorie restrictions, and allergies into the terminal to develop new menu items. For example, if you want to develop a "low-calorie pasta," you would enter the following information:

[1444] Ingredients: Pasta, tomatoes, olive oil, basil

[1445] Cooking method: boiling, frying

[1446] Calorie restriction: 500 kcal or less

[1447] Allergy Information: Gluten Free

[1448] Once you have completed the input, click the send button to send the data.

[1449] Step 2:

[1450] The terminal temporarily stores the data entered by the user. Then it validates whether the data format is correct, whether all required fields have been entered, whether the numerical range is correct, etc. If the data is valid, the terminal sends the data to the server.

[1451] Step 3:

[1452] The server receives the data sent from the device, stores it, and then converts it into the format required for analysis.

[1453] Step 4:

[1454] The server uses AI to analyze the received data. Here, it obtains nutritional information for each ingredient from the ingredient database and generates calorie calculations, halal compliance information, and allergy information. For example, it obtains ingredient data for pasta, tomato, olive oil, and basil and calculates the total calories as 480 kcal.

[1455] Step 5:

[1456] The server uses VR and 3D modeling technology to generate a virtual presentation image based on the analysis results, and the generated image is provided as a 3D model that can be viewed from all angles.

[1457] Step 6:

[1458] The server sends the analysis results and virtual presentation images to the device, including data such as total calories, nutritional information, allergy information, halal compliance information, and 3D presentation images.

[1459] Step 7:

[1460] The terminal displays the analysis results received from the server and a virtual presentation image to the user, who can then check the finished image of the new menu, as well as ingredient and allergy information.

[1461] Step 8:

[1462] The user can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the terminal.

[1463] Step 9:

[1464] The server receives feedback from the user, performs a new analysis with necessary adjustments, and then generates the reanalysis results and a new virtual presentation image, which are then sent to the terminal again.

[1465] Step 10:

[1466] The server runs an emotion engine that recognizes emotions from the user's feedback, facial expressions during operation, tone of voice, etc. The emotion engine analyzes whether the user is expressing positive or negative emotions.

[1467] Step 11:

[1468] The user's emotion data recognized by the emotion engine is used for reanalysis by the server. For example, if the user expresses negative emotion in response to a new menu suggestion, different ingredients or cooking methods will be suggested. Conversely, if a positive emotion is recognized, the suggestion will be saved with high accuracy.

[1469] Step 12:

[1470] The results of the reanalysis using the emotion engine's emotion data analysis and the new virtual presentation image are sent to the device again and displayed to the user. The user can then provide feedback and make further adjustments as necessary.

[1471] Through this process, users can efficiently develop and evaluate new menu items. Furthermore, feedback that takes user emotions into consideration will enable the development of new menu items that will provide greater satisfaction.

[1472] Example 2

[1473] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1474] The traditional new menu development process had the problem of being extremely costly and time-consuming because it was impossible to evaluate the results without using actual ingredients and cooking. Furthermore, it was difficult to provide feedback that took user emotions into consideration, preventing the development of menus that would provide high levels of satisfaction. As a result, food waste and food waste increased, and this did not contribute to the growth of a sustainable food industry.

[1475] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for a new menu item entered by a restaurant or food-related company; means for verifying the correct format of the entered information; means for analyzing the received information using a generative AI and virtually providing ingredient data, calorie calculations, religious compliance information, and allergy information; means for generating a virtual presentation image using virtual reality and modeling technology; means for transmitting the analysis results and the virtual presentation image to a terminal for displaying them; and means for analyzing the user's emotions and providing feedback based on the generative AI model. This enables the rapid and efficient development of new menu items, reduces food waste and ingredient waste, and contributes to the sustainable growth of the food industry. Furthermore, feedback based on user emotions can lead to the development of menu items with higher satisfaction.

[1476] "Ingredient information" refers to information such as the names, amounts, and components of ingredients used in developing new menu items.

[1477] "Recipe" is information that indicates the steps and methods for cooking ingredients.

[1478] "Calorie restriction" is a standard value for limiting the total calories contained in one meal.

[1479] "Allergy information" is information about foods that contain specific allergens.

[1480] "Generative AI" is a system that uses artificial intelligence technology to analyze data and generate information.

[1481] "Ingredient component data" is information on the nutritional and chemical components contained in each ingredient.

[1482] "Religious accommodation information" is food information to meet specific religious restrictions.

[1483] A "virtual presentation image" is a virtual presentation image of a new menu item created using virtual reality and 3D modeling technology.

[1484] A "terminal" is an input and display device, such as a computer or tablet, that a user uses to operate the system.

[1485] The "emotion engine" is a technology that recognizes and analyzes emotions from the user's facial expressions, tone of voice, etc.

[1486] "Feedback" refers to information about opinions and impressions that users input regarding analysis results and suggestions.

[1487] "Reanalysis" is the process in which the generative AI reanalyzes the data and derives new results based on the feedback and sentiment analysis results it receives.

[1488] "Virtual reality" is a technology that uses computer technology to virtually create experiences that are similar to reality.

[1489] "3D modeling technology" is a technology for digitally generating objects in three-dimensional space.

[1490] This invention is a system that supports the rapid and efficient development of new menu items by linking users, terminals, servers, and an emotion engine. Specifically, the system analyzes the data entered by users to input information about ingredients, cooking methods, calorie restrictions, and allergies for new menu items, and provides virtual evaluations and images. It also recognizes the user's emotions and provides feedback and suggestions based on them, enabling more accurate new menu development.

[1491] Hardware and Software

[1492] This system consists of the following components:

[1493] User Device: An input and display device such as a computer or tablet used by a restaurant or food-related business.

[1494] Server: A central computer that performs analytical processing and generates various data using generative AI and an emotion engine.

[1495] Generative AI: Artificial intelligence techniques for performing data analysis.

[1496] Emotion engine: Technology that recognizes and analyzes user emotions.

[1497] VR and 3D modeling technology: Technology for creating virtual presentation images.

[1498] Data processing and calculation

[1499] The user uses the terminal to input information about ingredients, cooking methods, calorie restrictions, and allergy information for the new menu item. For example, if you want to develop a "low-calorie pasta," you would enter the following information:

[1500] Ingredients: Pasta, tomatoes, olive oil, basil

[1501] Cooking method: boiling, frying

[1502] Calorie restriction: 500 kcal or less

[1503] Allergy Information: Gluten Free

[1504] The entered information is first saved on the device and validated for correct format. The data is then sent to the server, where it uses generative AI to retrieve nutritional information for each ingredient from a food ingredient database and calculate total calories, allergy information, and religious compliance information. At the same time, VR and 3D modeling technology is used to generate a virtual presentation of the new menu item.

[1505] The generated analysis results and virtual presentation image are sent to the device and displayed to the user. The user can input feedback based on this information and request readjustments if necessary. The readjustment feedback is sent back to the server, and the emotion engine analyzes the user's emotions. Data analysis is performed based on the user's emotions, and any necessary corrections or improvements are made.

[1506] Prompt Sentence Examples

[1507] An example of a prompt sentence to input to the generative AI model is as follows:

[1508] I'd like you to generate new menu ideas. Please provide the following information:

[1509] Ingredients: Pasta, tomatoes, olive oil, basil

[1510] Cooking method: Boiling, frying

[1511] Calorie restriction: 500 kcal or less

[1512] Allergy Information: Gluten Free

[1513] Through this system, users can quickly and efficiently develop new menu items, reducing food waste and food loss and promoting the growth of a sustainable food industry. Feedback that takes user emotions into consideration also enables the development of menu items that offer greater satisfaction.

[1514] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1515] Step 1:

[1516] The user uses the terminal to input information about ingredients, cooking methods, calorie restrictions, and allergy information for a new menu item. For example, if developing a "low-calorie pasta," the user enters the following information:

[1517] input:

[1518] Ingredients: Pasta, tomatoes, olive oil, basil

[1519] Cooking method: Boiling, frying

[1520] Calorie restriction: 500 kcal or less

[1521] Allergy Information: Gluten Free

[1522] The user presses a button to transmit data to the terminal.

[1523] Step 2:

[1524] The terminal temporarily stores the data entered by the user. Then it validates the data to ensure that it is in the correct format. For example, it checks whether all required fields have been entered and whether the numeric range is correct.

[1525] Input: Data submitted by the user

[1526] Data processing: format check, required field input check, numerical range check

[1527] Output: Validated data

[1528] If the validation is successful, the terminal transmits the data to the server.

[1529] Step 3:

[1530] The server receives the data sent from the device and stores it in a database.

[1531] Input: Validated data sent from the terminal

[1532] Data processing: Saving to database

[1533] Output: Saved data

[1534] Step 4:

[1535] The server uses generative AI to obtain nutritional information for each ingredient from a food ingredient database, such as the calories in pasta or the vitamin C content of tomatoes, and then calculates the total calories, allergy information, and religious compatibility information.

[1536] Input: Saved data

[1537] Data processing: Obtaining nutritional information from the food ingredient database, calculating total calories, and calculating allergy and religious information.

[1538] Output: Analysis results

[1539] Step 5:

[1540] The server uses VR and 3D modeling technology to generate a virtual presentation of the new menu items, which are then presented as 3D models that can be viewed from all angles.

[1541] Input: Analysis results

[1542] Data processing: Creating virtual presentation images using VR and 3D modeling technology

[1543] Output: Virtual presentation image

[1544] Step 6:

[1545] The server sends the analysis results and the generated virtual presentation image to the terminal.

[1546] Input: Analysis results, virtual presentation image

[1547] Data processing: Data integration

[1548] Output: Analysis results and virtual presentation images sent to the device

[1549] Step 7:

[1550] The terminal displays the information received from the server to the user, who can check the finished image of the new menu, as well as information on ingredients and allergies.

[1551] Input: Analysis results and virtual presentation images sent from the server

[1552] Data processing: Conversion to display format

[1553] Output: Displayed information

[1554] Step 8:

[1555] The user inputs feedback based on the analysis results. For example, they can enter comments such as "I'd like to reduce the amount of tomatoes" or "I'd like to change the cooking method." The feedback is sent to the server via the device.

[1556] Input: Analysis results and feedback opinions

[1557] Data processing: Adding feedback

[1558] Output: Feedback sent to the server

[1559] Step 9:

[1560] The server receives feedback from the user. At the same time, it uses an emotion engine to analyze the user's emotions based on their feedback, facial expressions, tone of voice, etc. It determines whether the user is expressing positive or negative emotions.

[1561] Input: Feedback and user emotional data (facial expressions, tone of voice, etc.)

[1562] Data processing: Sentiment analysis

[1563] Output: Emotion analysis results

[1564] Step 10:

[1565] The server reanalyzes the emotion data obtained from the emotion engine, and if the user gives negative feedback, it suggests alternative ingredients and cooking methods.

[1566] Input: Sentiment analysis results and feedback content

[1567] Data processing: reanalysis, generation of proposals

[1568] Output: Reanalysis results and recommendations

[1569] Step 11:

[1570] The server sends the reanalyzed data and the new virtual presentation image to the terminal, which provides new analysis results.

[1571] Input: Reanalysis results and new proposals

[1572] Data processing: Data integration

[1573] Output: Reanalysis results and virtual presentation image sent to the device

[1574] Step 12:

[1575] The device displays the reanalysis results to the user, who then provides feedback based on the new information. This process is repeated until the user is satisfied.

[1576] Input: Reanalysis results and virtual serving image sent from the server

[1577] Data processing: Conversion to display format

[1578] Output: Displayed reanalysis results and virtual presentation image

[1579] This series of processing steps allows users to efficiently develop and evaluate new menus, and feedback that takes user emotions into consideration makes it possible to develop menus that will provide high levels of satisfaction.

[1580] (Application example 2)

[1581] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1582] The traditional new menu development process was cost-inefficient, resulting in a lot of wasted ingredients and time, and requiring multiple prototypes. Furthermore, there was no way to provide feedback or suggestions that directly reflected user sentiment, resulting in low satisfaction with the final menu. To solve these problems, a system is needed that can efficiently and quickly develop new menus and make accurate suggestions based on user sentiment.

[1583] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1584] In this invention, the server includes means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related companies, means for verifying that the format of the entered information is correct, means for analyzing the received information using a generation AI and virtually providing ingredient data, calorie calculations, halal compliance information, and allergy information, means for generating virtual presentation images using virtual reality and 3D modeling technology, means for transmitting the analysis results and the virtual presentation images to a terminal for displaying them, means for providing an emotion engine for recognizing and analyzing user emotions, and means for providing feedback and suggestions based on the user emotions. This enables more efficient new menu development and more accurate suggestions based on user emotions.

[1585] "Restaurants or food-related companies" refers to businesses that develop and offer new menu items.

[1586] A "new menu" is a new dish or food that has never been offered before.

[1587] "Ingredient information" refers to detailed information about the types, quantities, origins, etc. of the various ingredients used in the new menu.

[1588] "Cooking method" refers to the specific cooking steps and methods used with ingredients.

[1589] "Calorie restriction" refers to a standard or requirement for keeping the total calories per meal within a specific range.

[1590] "Allergy information" refers to information about the possibility of an allergic reaction to a particular food ingredient.

[1591] "Means for receiving" refers to the method or technology for receiving information from a user.

[1592] "Verification means" refers to methods or techniques used to verify that received information conforms to its format and content.

[1593] "Generative AI" refers to artificial intelligence techniques used to analyze input data and generate the necessary information.

[1594] "Food ingredient data" refers to data on the nutrients and characteristics contained in each food ingredient.

[1595] "Calculating calories" refers to the process of calculating total calories based on ingredient information.

[1596] "Halal compatibility information" refers to information that indicates whether or not a food is suitable for consumption by Muslims.

[1597] "Virtual provision means" refers to methods and technologies for providing information or images that do not physically exist in a virtual space.

[1598] "Virtual reality" is a technology that provides a realistic experience within a computer-generated virtual environment.

[1599] "3D modeling technology" refers to the techniques and tools used to construct 3D virtual objects.

[1600] "Generative means" refers to methods and techniques for producing new information and images.

[1601] A "display terminal" is a device that allows a user to visually confirm information or images.

[1602] An "emotion engine" is a technology that recognizes and analyzes emotions from a user's facial expressions, tone of voice, etc.

[1603] "Means of providing" refers to methods or means for incorporating specific functions or technologies into a system.

[1604] "Feedback and suggestion means" refers to methods and technologies for providing advice and new suggestions based on analysis results and user sentiment.

[1605] "Means for reanalysis" refers to methods and techniques for re-analyzing data based on feedback or new data.

[1606] This invention is a system that supports the rapid and efficient development of new menus by linking user terminals, servers, generation AI, and emotion engines. This system collects input data, validates and analyzes data, generates virtual images, analyzes emotions, and receives and reanalyzes feedback. Specific implementation methods for the system are described below.

[1607] Hardware and software used

[1608] 1. User device: Uses input devices such as computers and tablets.

[1609] 2. Server: Serves as the central computer that performs analytical processing. Specific software uses generative AI technology.

[1610] 3. Generative AI: Artificial intelligence techniques used for data analysis and virtual presentation image generation.

[1611] 4. Emotion Engine: Technology that analyzes the user's facial expressions and tone of voice to recognize emotions. Uses "some_emotion_recognition_library" as the specific library.

[1612] 5. VR and 3D modeling technology: Technology used to generate virtual presentation images. For specific software, use "some_vr_library".

[1613] Data processing and calculation

[1614] The user terminal collects data such as ingredients, cooking methods, calorie restrictions, and allergy information for new menu items, and verifies that the entered information is in the correct format.

[1615] For example: "Ingredients: pasta, tomato, olive oil, basil", "Cooking method: boiling, frying", "Calorie limit: 500 kcal or less", "Allergy information: gluten-free"

[1616] The server receives data sent from the device and uses AI to analyze ingredient data, calorie calculations, halal compliance information, and allergy information, while also using VR and 3D modeling technology to generate virtual presentation images.

[1617] Example: "The generated virtual presentation image is provided in a format that can be viewed from all directions."

[1618] The emotion engine analyzes feedback from the user, facial expressions during operation, tone of voice, and other factors to recognize the user's emotions.

[1619] For example: "If the user expresses positive emotions, it will be considered positive and other cooking suggestions will be made."

[1620] Specific examples

[1621] For example, if a chef wants to develop a new "low-calorie pasta menu," he or she can use the system as follows:

[1622] 1. Enter ingredient information, cooking method, calorie restrictions, and allergy information into the user terminal.

[1623] 2. The server analyzes the data and generates a virtual presentation image.

[1624] 3. The user checks the analysis results and the virtual presentation image and provides feedback.

[1625] 4. The emotion engine analyzes the feedback and re-suggests the menu if necessary.

[1626] Prompt Sentence Examples

[1627] "This pasta dish uses five ingredients and aims to be under 500 kcal. Basil and tomato are the main ingredients. It is cooked both boiled and sautéed. It is gluten-free. Please generate detailed ingredient information and a virtual serving image for this dish."

[1628] As described above, using this system will make the new menu development process more efficient and enable proposals that will provide high levels of satisfaction based on user emotions.

[1629] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1630] Step 1:

[1631] The user inputs information about ingredients, cooking methods, calorie restrictions, and allergy information for a new menu item into the user terminal. Examples of input data include "Ingredients: pasta, tomato, olive oil, basil," "Cooking method: boiling, stir-frying," "Calorie restrictions: under 500 kcal," and "Allergy information: gluten-free." After input, the user terminal temporarily stores this information.

[1632] Step 2:

[1633] The terminal verifies that the format of the temporarily saved data is correct. For example, it checks whether all required fields have been entered and whether the numeric range is appropriate. If the format is correct, the terminal sends the data to the server. The input here is the menu information entered by the user, and the output is the verified data.

[1634] Step 3:

[1635] The server receives the data sent from the device and stores it. Next, it uses generative AI to obtain nutritional information for each ingredient from the ingredient database and calculates total calories, allergy information, and halal compliance information. For example, it obtains the calorie and nutritional information for "pasta" based on the received ingredient information. The input is verified menu information, and the output is the analysis results.

[1636] Step 4:

[1637] The server uses VR and 3D modeling technology to generate a virtual presentation image based on the analysis results. For example, it generates a 3D model of the appearance of low-calorie pasta. This allows users to check the appearance of the menu from all angles. The input is the analysis results, and the output is a 3D model of the presentation image.

[1638] Step 5:

[1639] The server sends the analysis results and a virtual presentation image to the terminal. The user terminal receives this and displays it to the user. For example, the analysis results may be displayed as "Calories: 480 kcal" or "Nutritional information: High in vitamin C, rich in iron." The input is the analysis results and a 3D image, and the output is visualized data that the user can view.

[1640] Step 6:

[1641] The user checks the displayed analysis results and the virtual presentation image and inputs feedback. The user's device sends this feedback to the server. For example, the user sends a specific request such as "I'd like more tomatoes." The input is the user's feedback, and the output is the feedback data.

[1642] Step 7:

[1643] The server receives the feedback and analyzes the user's emotions using an emotion engine. For example, the analysis result may be, "There are many positive opinions, but they would like to increase the amount of tomatoes." The input is the user's feedback, and the output is the emotion analysis result.

[1644] Step 8:

[1645] The server then uses the generative AI again to perform a new analysis based on the results of the emotion analysis. For example, it recalculates the nutritional content and calories if the amount of tomato is increased, and generates a new virtual presentation image. The input is the emotion analysis result and the reconfigured menu information, and the output is the reanalysis result and the new virtual presentation image.

[1646] Step 9:

[1647] The server sends the reanalysis results and a new virtual presentation image to the terminal and displays them to the user. The user then provides feedback and makes further adjustments as necessary. Ultimately, a new menu that satisfies the user is finalized. The input is the reanalysis results and a new 3D image, and the output is final confirmation data and the completion of the continuous feedback cycle.

[1648] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1649] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1650] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1651] [Fourth embodiment]

[1652] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1653] 7, a 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.

[1654] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1655] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1656] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1657] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1658] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1659] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1660] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1661] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[1662] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1663] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1664] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1665] The virtual food testing system of the present invention supports the rapid and efficient development of new menu items through the cooperation of users, terminals, and servers. This system allows restaurants and food-related businesses to input information about ingredients, cooking methods, and restrictions for new menu items, and then analyzes the information to provide a virtual evaluation and image. The specific operation of the system is described below.

[1666] System Objectives

[1667] The main purpose of this system is to streamline the process of new menu development and reduce costs and time by conducting virtual evaluations without using actual ingredients or cooking. Furthermore, it will reduce food waste and promote the growth of a sustainable food industry.

[1668] System configuration

[1669] The main components of the system are:

[1670] User device: A computer, tablet, or other input device used by a restaurant or food-related business.

[1671] Server: A central computer that performs analytical processing and generates various data using generative AI.

[1672] Generative AI: Artificial intelligence techniques for performing data analysis.

[1673] VR and 3D modeling technology: Technology for creating virtual presentation images.

[1674] Processing Details

[1675] Below, we will explain how each component works together and its specific operation using concrete examples.

[1676] User: Create and submit input data

[1677] The user uses the terminal to input the cooking method, ingredient information, calorie restrictions, allergy information, etc. of the new menu item. For example, if you want to develop a "low-calorie pasta," you would input the following information:

[1678] Ingredients: Pasta, tomatoes, olive oil, basil

[1679] Cooking method: boiling, frying

[1680] Calorie restriction: 500 kcal or less

[1681] Allergy Information: Gluten Free

[1682] After completing the input, the user presses a button to transmit the data.

[1683] Terminal: Data transmission and validation

[1684] The terminal temporarily stores the data entered by the user and checks whether the format is correct (validation). For example, it checks whether all required fields have been entered, whether the numerical range is correct, etc. If there are no problems, it sends the data to the server.

[1685] Server: Receives and analyzes data

[1686] The server receives the data sent from the device and begins analysis using the AI. Specifically, it retrieves the nutritional information of each ingredient from the ingredient database and calculates the total calories, allergy information, halal compliance information, etc. For example, it retrieves the nutritional information for pasta, tomato, olive oil, and basil, and calculates the total calories as 480 kcal.

[1687] Server: Generate virtual presentation images

[1688] The server then uses VR and 3D modeling technology to generate a virtual presentation of the new menu item, which is then presented as a 3D model that can be viewed from all angles.

[1689] Server: Sending analysis results

[1690] The analysis results and virtual presentation images are sent from the server to the device, including the following information:

[1691] Total calories: 480 kcal

[1692] Nutritional Information: High in Vitamin C and Iron

[1693] Allergy Information: Gluten Free

[1694] Halal compatibility: Considered

[1695] Presentation image: 3D model (all-directional view)

[1696] Terminal: Display of analysis results

[1697] The terminal displays the information received from the server to the user, allowing the user to check the final image of the new menu, as well as information on ingredients and allergies.

[1698] Users: Send feedback and refine

[1699] Users can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the device, and a new analysis is performed.

[1700] In this way, the virtual food testing system enables the new menu development process to proceed efficiently, reducing costs and food waste.

[1701] The processing flow will be explained below.

[1702] Step 1:

[1703] Users input information about ingredients, cooking methods, calorie restrictions, and allergies into the terminal to develop new menu items. Once input is complete, the data is sent by pressing the send button.

[1704] Step 2:

[1705] The terminal temporarily stores the data entered by the user. Then it validates whether the data format is correct, whether all required fields have been entered, whether the numerical range is correct, etc. If the data is valid, the terminal sends the data to the server.

[1706] Step 3:

[1707] The server receives the data sent from the device, stores it, and then converts it into the format required for analysis.

[1708] Step 4:

[1709] The server uses AI to analyze the received data. Here, it retrieves nutritional information for each ingredient from the ingredient database and generates calorie calculations, halal compliance information, and allergy information. For example, in the case of "low-calorie pasta," the ingredient data for pasta, tomato, olive oil, and basil are retrieved, and the total calories are calculated as 480 kcal.

[1710] Step 5:

[1711] The server uses VR and 3D modeling technology to generate a virtual presentation image based on the analysis results, and the generated image is provided as a 3D model that can be viewed from all angles.

[1712] Step 6:

[1713] The server sends the analysis results and virtual presentation images to the device, including data such as total calories, nutritional information, allergy information, halal compliance information, and 3D presentation images.

[1714] Step 7:

[1715] The terminal displays the analysis results received from the server and a virtual presentation image to the user, who can then check the finished image of the new menu, as well as ingredient and allergy information.

[1716] Step 8:

[1717] The user can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the terminal.

[1718] Step 9:

[1719] The server receives feedback from the user, performs a new analysis with necessary adjustments, and then generates the reanalysis results and a new virtual presentation image, which are then sent to the terminal again.

[1720] Through this series of processes, users can efficiently develop and evaluate new menu items, saving time and money, and is also expected to reduce food waste and food waste.

[1721] Example 1

[1722] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1723] The traditional new menu development process requires repeated trial production using actual ingredients, which is costly and time-consuming. Furthermore, failures and readjustments during the trial production stage result in food waste and food waste, which does not contribute to the development of a sustainable food industry. Furthermore, managing ingredient and allergy information is cumbersome and prone to errors.

[1724] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1725] In this invention, the server includes means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related companies, means for verifying that the format of the entered information is correct, means for analyzing the received information using a generative AI model and virtually providing ingredient data, calorie calculations, halal compliance information, and allergy information, means for generating a virtual presentation image using 3D representation technology, and means for transmitting the analysis results and the virtual presentation image to a terminal for displaying them. This allows new menu items to be virtually evaluated and improved without using actual ingredients, thereby reducing costs and food waste and making new menu development more efficient.

[1726] A "restaurant or food-related business" is a business that serves meals or is engaged in the manufacture and sale of food.

[1727] "New menu" refers to the content and combination of newly developed dishes that will be added to the existing menu.

[1728] "Ingredient information" is detailed information such as the names, types, and quantities of ingredients used in the new menu.

[1729] "Cooking method" refers to the specific techniques and processes used to cook ingredients.

[1730] "Calorie restriction" is the upper limit on the total calorie content of a diet set for health and nutritional management.

[1731] "Allergy information" refers to information on whether a consumer may have an allergic reaction to a particular food ingredient.

[1732] "Means for receiving" refers to a method or system for taking in data or information from the outside.

[1733] A "verification means" is a method or system for checking the accuracy and format of the information entered.

[1734] A "generative AI model" is an artificial intelligence algorithm or program that is trained to analyze data and generate new information.

[1735] "Means for analysis" refers to a system or method that examines the received data in detail and extracts and calculates the necessary information.

[1736] "Food ingredient data" is detailed information about the nutritional content and chemical composition of food.

[1737] "Halal compliance information" is information about ingredients and cooking methods that are permitted according to specific religious regulations.

[1738] "Means for providing" refers to a system or method for displaying or transmitting the analyzed or generated information to the user.

[1739] "Three-dimensional representation technology" refers to techniques and methods for visually representing objects and landscapes in three-dimensional space.

[1740] A "terminal" is a device, such as a computer or tablet, that a user uses to enter data or view results.

[1741] "Feedback" refers to opinions and requests for improvement from users regarding analysis results and provided information.

[1742] "Reanalysis" refers to the process of reanalyzing data based on feedback and making corrections or improvements.

[1743] A "report" is a document or electronic file that summarizes analysis results and evaluation information.

[1744] "Omnidirectional viewing" refers to a display method that allows objects in three-dimensional space to be viewed from all angles.

[1745] The virtual food testing system of the present invention supports the rapid and efficient development of new menu items through the cooperation of users, terminals, and servers. This system allows restaurants and food-related businesses to input information on ingredients, cooking methods, calorie restrictions, and allergy information for new menu items, and performs analysis based on this information to provide virtual evaluations and images.

[1746] System configuration

[1747] The main components of the system are:

[1748] User device: An input device such as a computer or tablet used by food-related companies.

[1749] Server: A central computer that performs analytical processing and generates data using generative AI.

[1750] Generative AI: Artificial intelligence techniques for performing data analysis (specifically using TensorFlow and PyTorch).

[1751] 3D representation technology: Technology for creating virtual presentation images (using Blender and Unity).

[1752] System Operation

[1753] User: Create and submit input data

[1754] The user uses the terminal to input the cooking method, ingredient information, calorie restrictions, allergy information, etc. of the new menu item. For example, if you want to develop a "low-calorie pasta," you would input the following information:

[1755] Ingredients: Pasta, tomatoes, olive oil, basil

[1756] Cooking method: boiling, frying

[1757] Calorie restriction: 500 kcal or less

[1758] Allergy Information: Gluten Free

[1759] After completing the input, the user presses a button to transmit the data.

[1760] Terminal: Data transmission and validation

[1761] The device temporarily stores the data entered by the user and checks whether the format is correct. First, it checks whether all required fields have been entered, and then it checks whether the calorie value and allergy information are within the appropriate range. After checking, the data is sent to the server.

[1762] Server: Receives and analyzes data

[1763] The server receives the data sent from the device and analyzes it using a generative AI model. First, it obtains the nutritional information for each ingredient from the ingredient database. It then calculates the total calories, allergy information, and halal compliance information. For example, based on the ingredient information for pasta, tomato, olive oil, and basil, it calculates the total calories as 480 kcal.

[1764] Server: Generate virtual presentation images

[1765] The server uses 3D rendering technology to generate a virtual presentation of the new menu item, which is then presented as a 3D model that users can view from all angles.

[1766] Server: Sending analysis results

[1767] The analysis results and virtual presentation images are sent from the server to the device, including the following information:

[1768] Total calories: 480 kcal

[1769] Nutritional Information: High in Vitamin C and Iron

[1770] Allergy Information: Gluten Free

[1771] Halal compatibility: Considered

[1772] Presentation image: 3D model (all-directional view)

[1773] Terminal: Display of analysis results

[1774] The terminal displays the information received from the server to the user, allowing the user to check the final image of the new menu, as well as information on ingredients and allergies.

[1775] Users: Send feedback and refine

[1776] The user can input feedback based on the analysis results, such as if the calorie content is too high or if they would like to change the combination of ingredients, and the feedback is sent from the device to the server.

[1777] The server performs a new analysis and sends the retuned data back to the device, allowing the user to easily make further adjustments.

[1778] In this way, the virtual food testing system streamlines the process of new menu development, reducing costs and food waste and promoting the growth of a sustainable food industry.

[1779] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1780] Step 1: Data entry

[1781] The user uses the terminal to input information about the new menu item. Specifically, they enter information about ingredients, cooking methods, calorie restrictions, allergy information, etc. into a form. For example, if you want to develop a "low-calorie pasta," you would enter the following information:

[1782] Ingredients: Pasta, tomatoes, olive oil, basil

[1783] Cooking method: boiling, frying

[1784] Calorie restriction: 500 kcal or less

[1785] Allergy Information: Gluten Free

[1786] Input: Ingredient information, cooking method, calorie restrictions, allergy information

[1787] Output: Save to device

[1788] Step 2: Submit and validate data

[1789] The terminal temporarily stores the data entered by the user. It then validates that the data format is correct. It checks that all required fields have been entered and that calorie values ​​and allergy information are within the range. If validation is successful, it sends the data to the server.

[1790] Input: Data entered by the user

[1791] Data manipulation: format and range checks

[1792] Output: Send data to the server

[1793] Specific behavior:

[1794] 1. Check the required fields

[1795] 2. Check the range of calorie values ​​and allergy information

[1796] 3. Sending data to the server

[1797] Step 3: Receiving and analyzing data

[1798] The server receives the data sent from the device. It then begins analyzing the data using a generative AI model. It obtains nutritional information for each ingredient from the ingredient database and calculates total calories, allergy information, and halal compliance information. For example, based on the ingredient information for pasta, tomato, olive oil, and basil, it calculates the total calories to be 480 kcal.

[1799] Input: Data sent from the terminal

[1800] Data processing: Obtaining nutritional information using a generative AI model and calculating total calories, allergy information, and halal compliance information

[1801] Output: Analysis results

[1802] Specific behavior:

[1803] 1. Obtain information from a food ingredient database

[1804] 2. Calculate total calories and other nutritional information

[1805] Step 4: Generate a virtual presentation image

[1806] The server uses 3D rendering technology to generate a virtual presentation image of the new menu item, which is then presented as a 3D model that users can view from any angle.

[1807] Input: Analysis results

[1808] Data processing: Image generation using 3D expression technology (Blender or Unity)

[1809] Output: Virtual presentation image of 3D model

[1810] Specific behavior:

[1811] 1. 3D modeling of a virtual presentation image

[1812] 2. Provide a format that can be viewed from all angles

[1813] Step 5: Submitting the analysis results

[1814] The server sends the analysis results and the virtual presentation image to the device. The analysis results include the following information:

[1815] Total calories: 480 kcal

[1816] Nutritional Information: High in Vitamin C and Iron

[1817] Allergy Information: Gluten Free

[1818] Halal compatibility: Considered

[1819] Presentation image: 3D model (all-directional view)

[1820] Input: Analysis results, virtual arrangement image of 3D model

[1821] Output: Send to terminal

[1822] Step 6: Viewing the analysis results

[1823] The terminal displays the information received from the server to the user, who can check the finished image of the new menu, as well as information on ingredients and allergies.

[1824] Input: Analysis results and 3D model from the server

[1825] Output: What is displayed to the user

[1826] Specific behavior:

[1827] 1. Display analysis results and 3D models on your device

[1828] Step 7: Provide feedback and refine

[1829] The user inputs feedback based on the analysis results and sends it from the device to the server. The server receives the user's feedback, performs re-analysis using the generative AI model, and then sends the corrected data back to the device.

[1830] Input: User feedback

[1831] Data processing: Reanalysis using generative AI models

[1832] Output: Re-send the corrected analysis results to the terminal

[1833] Specific behavior:

[1834] 1. Receiving Feedback

[1835] 2. Perform reanalysis

[1836] 3. Sending the reanalysis results to the device

[1837] Through these steps, the virtual food testing system streamlines the new menu development process, reducing costs and food waste.

[1838] (Application example 1)

[1839] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1840] The traditional new menu development process required the use of actual ingredients and cooking, which was time-consuming and costly, and required a large number of resources to evaluate new menu items. Furthermore, the food delivery industry is required to quickly provide new menu items in a short amount of time, but there was no efficient way to achieve this. Furthermore, there was a lack of a system for virtually evaluating menu items without actual tasting, thereby improving customer satisfaction.

[1841] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1842] In this invention, the server includes: means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related companies; means for verifying the correct format of the entered information; means for analyzing the received information using generation AI and virtually providing ingredient data, calorie calculations, halal compliance information, and allergy information; means for generating virtual presentation images using VR and modeling technology; means for transmitting the analysis results and the virtual presentation images to a terminal for displaying them; and means for, as a virtual food delivery development support app, allowing users to enter feedback, reanalyze the results, and support the evaluation of new menu items, including readjustments. This allows for an efficient process for new menu development, reducing costs and food waste.

[1843] "Restaurants or food-related businesses" refers to establishments that serve food and beverages, and businesses that manufacture and sell food in general.

[1844] "Ingredient information" refers to detailed information such as the names, types, nutritional components, and origins of the ingredients that make up the new menu.

[1845] "Cooking method" refers to the specific steps or methods for cooking ingredients.

[1846] "Calorie restriction" refers to restricting the total calories of a particular menu item to within a certain range.

[1847] "Allergy information" refers to information that may cause an allergic reaction to a particular food ingredient or component.

[1848] "Means for receiving" refers to hardware or software for receiving and processing data sent from an external source.

[1849] "Verification means" refers to the processes and techniques used to verify the accuracy and integrity of input data.

[1850] "Generative AI" refers to artificial intelligence technology that generates new information based on large amounts of data.

[1851] "Means for analyzing and providing" refers to the technology used to analyze received data and generate and provide useful information or results.

[1852] "VR and modeling technology" refers to virtual reality technology and technology for creating 3D models.

[1853] "Display terminal" refers to a device that visually presents analysis results and virtual images to users.

[1854] A "virtual food delivery development support app" refers to an application designed to streamline the development of new menu items for the food delivery industry.

[1855] "Reanalysis" refers to the process of re-analyzing data based on new information, such as feedback.

[1856] "Means of providing omnidirectional viewpoints" refers to technology that allows 3D models and VR content to be viewed from various viewpoints.

[1857] "Means for generating reports" refers to the technology for compiling analysis results, evaluations, etc. in document format.

[1858] The virtual food delivery development support system of this invention operates in cooperation with three parties: the user, the terminal, and the server. This system provides virtual evaluations and images by allowing the user to input information on ingredients, cooking methods, calorie restrictions, and allergy information for a new menu item and send it to the server via the terminal.

[1859] Specific components of the system include:

[1860] 1. User Device:

[1861] A user terminal is a device such as a computer or tablet used by a restaurant or food-related business. A user uses this terminal to input information about new menu items. For example, a user can input information about a new menu item as follows:

[1862] Ingredients: Pasta, tomatoes, olive oil, basil

[1863] Cooking method: boiling, frying

[1864] Calorie restriction: 500 kcal or less

[1865] Allergy Information: Gluten Free

[1866] 2. Data transmission:

[1867] Once the information has been entered, it is sent from the terminal to the server. At that time, the terminal checks whether the format is correct (validation). For example, it checks whether all required fields have been entered, whether the range of values ​​is correct, etc. If there are no problems, the data is sent to the server.

[1868] 3. Server:

[1869] The server is the hub of the analysis process, using generative AI to analyze the received data and provide ingredient data, calorie calculations, halal compliance information, and allergy information.

[1870] Additionally, VR and 3D modeling technology is used to generate virtual presentation images, which are then presented in a format that can be viewed from all angles.

[1871] 4. Sending analysis results and virtual images:

[1872] The server sends the analysis results and a virtual presentation image to the device, including the following information:

[1873] Total calories: 480 kcal

[1874] Nutritional information: High in vitamin C and iron

[1875] Allergy Information: Gluten Free

[1876] Halal compatibility information: Considered

[1877] Arrangement image: 3D model (all-directional view)

[1878] 5. Display on user terminal:

[1879] The analysis results and virtual images are displayed on the user's terminal, allowing the user to check the finished image of the new menu and ingredient information. Furthermore, by entering feedback, the user can request further improvements and corrections from the server.

[1880] Specifically, the following text prompt can be sent to the server:

[1881] Ingredients: pasta, tomatoes, olive oil, basil

[1882] Cooking method: boiling, frying

[1883] Calorie restriction: 500 kcal or less

[1884] Allergy Information: Gluten Free

[1885] Based on this prompt, the server uses a generative AI model to analyze the new menu and provide a virtual evaluation and image, allowing users to develop new menu items more quickly and efficiently.

[1886] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1887] Step 1:

[1888] The user uses the device to input information about the new menu item, including information about ingredients, cooking methods, calorie restrictions, and allergy information, and then presses a button to send the data after completing the input. This temporarily saves the input data in the device.

[1889] input:

[1890] Ingredients: Pasta, tomatoes, olive oil, basil

[1891] Cooking method: boiling, frying

[1892] Calorie restriction: 500 kcal or less

[1893] Allergy Information: Gluten Free

[1894] output:

[1895] Saved Input Data

[1896] Step 2:

[1897] The terminal checks whether the format of the saved input data is correct (validation). At this stage, it checks whether all required fields have been entered, whether the range of values ​​is correct, etc. If there are no problems, it sends the data to the server.

[1898] input:

[1899] Saved Input Data

[1900] output:

[1901] Validated data

[1902] Step 3:

[1903] The server receives the validated data sent from the device. It analyzes this data using a generation AI and provides ingredient data, calorie calculations, halal compliance information, and allergy information. During the analysis process, it extracts nutritional information for ingredients from the database and calculates total calories and ingredient information.

[1904] input:

[1905] Validated data

[1906] output:

[1907] Ingredient data, calorie calculation results, halal compliance information, allergy information

[1908] Step 4:

[1909] Using VR and 3D modeling technology, the server generates a virtual presentation of the new menu items, which can be viewed in 3D format from any angle.

[1910] input:

[1911] Ingredient data, cooking method data

[1912] output:

[1913] Virtual presentation image (3D model)

[1914] Step 5:

[1915] The server then sends the analysis results and a virtual presentation image to the device, including total calories, nutritional information, and allergy information.

[1916] input:

[1917] Analysis results and virtual presentation image

[1918] output:

[1919] Transmission data (analysis results + virtual image)

[1920] Step 6:

[1921] The terminal displays the received analysis results and virtual images to the user, allowing the user to check the finished image of the new menu, as well as information on ingredients, calories, and allergies.

[1922] input:

[1923] Transmission data (analysis results + virtual image)

[1924] output:

[1925] User Display Data

[1926] Step 7:

[1927] The user checks the analysis results and inputs feedback, which is sent to the server via the terminal, allowing the user to request reanalysis. This feedback can include adjustments to the taste or improvements to the appearance.

[1928] input:

[1929] Feedback Information

[1930] output:

[1931] Reanalysis Request

[1932] Step 8:

[1933] The server then performs a re-analysis based on user feedback, using a re-generative AI to perform a virtual evaluation based on updated data and new conditions, and generate new results.

[1934] input:

[1935] Reanalysis Request

[1936] output:

[1937] Reanalysis results + updated virtual image

[1938] Each processing step works together to make the new menu development process quick and efficient.

[1939] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1940] This invention is a system that supports the rapid and efficient development of new menu items by linking users, terminals, a server, and an emotion engine. This system accepts input of information on ingredients, cooking methods, calorie restrictions, and allergies for new menu items, performs analysis based on the information, and provides a virtual evaluation and image. Furthermore, by recognizing the user's emotions and providing feedback and suggestions based on those emotions, the system achieves more accurate new menu development.

[1941] System Objectives

[1942] The main purpose of this system is to streamline the new menu development process and reduce costs and time by conducting virtual evaluations without using actual ingredients or cooking. Furthermore, it will reduce food waste and promote the growth of a sustainable food industry. Furthermore, by taking user emotions into consideration, it will support the development of menus that provide greater satisfaction.

[1943] System configuration

[1944] The main components of the system are:

[1945] User device: A computer, tablet, or other input device used by a restaurant or food-related business.

[1946] Server: A central computer that performs analytical processing and generates various data using generative AI and an emotion engine.

[1947] Generative AI: Artificial intelligence techniques for performing data analysis.

[1948] Emotion engine: Technology that recognizes and analyzes user emotions.

[1949] VR and 3D modeling technology: Technology for creating virtual presentation images.

[1950] Processing Details

[1951] Below, we will explain how each component works together and its specific operation using concrete examples.

[1952] User: Create and submit input data

[1953] The user uses the terminal to input the cooking method, ingredient information, calorie restrictions, allergy information, etc. of the new menu item. For example, if you want to develop a "low-calorie pasta," you would input the following information:

[1954] Ingredients: Pasta, tomatoes, olive oil, basil

[1955] Cooking method: boiling, frying

[1956] Calorie restriction: 500 kcal or less

[1957] Allergy Information: Gluten Free

[1958] After completing the input, the user presses a button to transmit the data.

[1959] Terminal: Data transmission and validation

[1960] The terminal temporarily stores the data entered by the user and checks whether the format is correct (validation). For example, it checks whether all required fields have been entered, whether the numerical range is correct, etc. If there are no problems, it sends the data to the server.

[1961] Server: Receives and analyzes data

[1962] The server receives and stores the data sent from the device, then uses the generation AI to obtain nutritional information for each ingredient from the ingredient database and calculate total calories, allergy information, and halal compliance information.

[1963] Server: Generate virtual presentation images

[1964] The server then uses VR and 3D modeling technology to generate a virtual presentation of the new menu item, which is then presented as a 3D model that can be viewed from all angles.

[1965] Server: Sending analysis results

[1966] The analysis results and virtual presentation images are sent from the server to the device, including the following information:

[1967] Total calories: 480 kcal

[1968] Nutritional Information: High in Vitamin C and Iron

[1969] Allergy Information: Gluten Free

[1970] Halal compatibility: Considered

[1971] Presentation image: 3D model (all-directional view)

[1972] Terminal: Display of analysis results

[1973] The terminal displays the information received from the server to the user, allowing the user to check the final image of the new menu, as well as information on ingredients and allergies.

[1974] Users: Send feedback and refine

[1975] The user can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the terminal.

[1976] Emotion Engine: User Emotion Recognition and Analysis

[1977] The emotion engine recognizes emotions from user feedback, facial expressions during operation, tone of voice, etc. For example, if the user shows positive emotions, it determines that the proposed menu will be well-received.

[1978] Emotion-based feedback and readjustment

[1979] The emotion data recognized by the emotion engine is taken into account when the server re-analyzes the data. For example, if a user expresses negative emotions in response to a new menu suggestion, the server will suggest different ingredients or cooking methods.

[1980] Generate and display new analysis results

[1981] The reanalyzed data and the virtual presentation image are sent back to the terminal and displayed to the user, who can then provide feedback and make further adjustments as necessary.

[1982] Through this process, users can efficiently develop and evaluate new menu items. Furthermore, feedback that takes user emotions into consideration will enable the development of new menu items that will provide greater satisfaction.

[1983] The processing flow will be explained below.

[1984] Step 1:

[1985] Users input information about ingredients, cooking methods, calorie restrictions, and allergies into the terminal to develop new menu items. For example, if you want to develop a "low-calorie pasta," you would enter the following information:

[1986] Ingredients: Pasta, tomatoes, olive oil, basil

[1987] Cooking method: boiling, frying

[1988] Calorie restriction: 500 kcal or less

[1989] Allergy Information: Gluten Free

[1990] Once you have completed the input, click the send button to send the data.

[1991] Step 2:

[1992] The terminal temporarily stores the data entered by the user. Then it validates whether the data format is correct, whether all required fields have been entered, whether the numerical range is correct, etc. If the data is valid, the terminal sends the data to the server.

[1993] Step 3:

[1994] The server receives the data sent from the device, stores it, and then converts it into the format required for analysis.

[1995] Step 4:

[1996] The server uses AI to analyze the received data. Here, it obtains nutritional information for each ingredient from the ingredient database and generates calorie calculations, halal compliance information, and allergy information. For example, it obtains ingredient data for pasta, tomato, olive oil, and basil and calculates the total calories as 480 kcal.

[1997] Step 5:

[1998] The server uses VR and 3D modeling technology to generate a virtual presentation image based on the analysis results, and the generated image is provided as a 3D model that can be viewed from all angles.

[1999] Step 6:

[2000] The server sends the analysis results and virtual presentation images to the device, including data such as total calories, nutritional information, allergy information, halal compliance information, and 3D presentation images.

[2001] Step 7:

[2002] The terminal displays the analysis results received from the server and a virtual presentation image to the user, who can then check the finished image of the new menu, as well as ingredient and allergy information.

[2003] Step 8:

[2004] The user can input feedback based on the analysis results and request readjustment if further improvements or corrections are needed. The feedback is sent to the server via the terminal.

[2005] Step 9:

[2006] The server receives feedback from the user, performs a new analysis with necessary adjustments, and then generates the reanalysis results and a new virtual presentation image, which are then sent to the terminal again.

[2007] Step 10:

[2008] The server runs an emotion engine that recognizes emotions from the user's feedback, facial expressions during operation, tone of voice, etc. The emotion engine analyzes whether the user is expressing positive or negative emotions.

[2009] Step 11:

[2010] The user's emotion data recognized by the emotion engine is used for reanalysis by the server. For example, if the user expresses negative emotion in response to a new menu suggestion, different ingredients or cooking methods will be suggested. Conversely, if a positive emotion is recognized, the suggestion will be saved with high accuracy.

[2011] Step 12:

[2012] The results of the reanalysis using the emotion engine's emotion data analysis and the new virtual presentation image are sent to the device again and displayed to the user. The user can then provide feedback and make further adjustments as necessary.

[2013] Through this process, users can efficiently develop and evaluate new menu items. Furthermore, feedback that takes user emotions into consideration will enable the development of new menu items that will provide greater satisfaction.

[2014] Example 2

[2015] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2016] The traditional new menu development process had the problem of being extremely costly and time-consuming because it was impossible to evaluate the results without using actual ingredients and cooking. Furthermore, it was difficult to provide feedback that took user emotions into consideration, preventing the development of menus that would provide high levels of satisfaction. As a result, food waste and food waste increased, and this did not contribute to the growth of a sustainable food industry.

[2017] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for a new menu item entered by a restaurant or food-related company; means for verifying the correct format of the entered information; means for analyzing the received information using a generative AI and virtually providing ingredient data, calorie calculations, religious compliance information, and allergy information; means for generating a virtual presentation image using virtual reality and modeling technology; means for transmitting the analysis results and the virtual presentation image to a terminal for displaying them; and means for analyzing the user's emotions and providing feedback based on the generative AI model. This enables the rapid and efficient development of new menu items, reduces food waste and ingredient waste, and contributes to the sustainable growth of the food industry. Furthermore, feedback based on user emotions can lead to the development of menu items with higher satisfaction.

[2018] "Ingredient information" refers to information such as the names, amounts, and components of ingredients used in developing new menu items.

[2019] "Recipe" is information that indicates the steps and methods for cooking ingredients.

[2020] "Calorie restriction" is a standard value for limiting the total calories contained in one meal.

[2021] "Allergy information" is information about foods that contain specific allergens.

[2022] "Generative AI" is a system that uses artificial intelligence technology to analyze data and generate information.

[2023] "Ingredient component data" is information on the nutritional and chemical components contained in each ingredient.

[2024] "Religious accommodation information" is food information to meet specific religious restrictions.

[2025] A "virtual presentation image" is a virtual presentation image of a new menu item created using virtual reality and 3D modeling technology.

[2026] A "terminal" is an input and display device, such as a computer or tablet, that a user uses to operate the system.

[2027] The "emotion engine" is a technology that recognizes and analyzes emotions from the user's facial expressions, tone of voice, etc.

[2028] "Feedback" refers to information about opinions and impressions that users input regarding analysis results and suggestions.

[2029] "Reanalysis" is the process in which the generative AI reanalyzes the data and derives new results based on the feedback and sentiment analysis results it receives.

[2030] "Virtual reality" is a technology that uses computer technology to virtually create experiences that are similar to reality.

[2031] "3D modeling technology" is a technology for digitally generating objects in three-dimensional space.

[2032] This invention is a system that supports the rapid and efficient development of new menu items by linking users, terminals, servers, and an emotion engine. Specifically, the system analyzes the data entered by users to input information about ingredients, cooking methods, calorie restrictions, and allergies for new menu items, and provides virtual evaluations and images. It also recognizes the user's emotions and provides feedback and suggestions based on them, enabling more accurate new menu development.

[2033] Hardware and Software

[2034] This system consists of the following components:

[2035] User Device: An input and display device such as a computer or tablet used by a restaurant or food-related business.

[2036] Server: A central computer that performs analytical processing and generates various data using generative AI and an emotion engine.

[2037] Generative AI: Artificial intelligence techniques for performing data analysis.

[2038] Emotion engine: Technology that recognizes and analyzes user emotions.

[2039] VR and 3D modeling technology: Technology for creating virtual presentation images.

[2040] Data processing and calculation

[2041] The user uses the terminal to input information about ingredients, cooking methods, calorie restrictions, and allergy information for the new menu item. For example, if you want to develop a "low-calorie pasta," you would enter the following information:

[2042] Ingredients: Pasta, tomatoes, olive oil, basil

[2043] Cooking method: boiling, frying

[2044] Calorie restriction: 500 kcal or less

[2045] Allergy Information: Gluten Free

[2046] The entered information is first saved on the device and validated for correct format. The data is then sent to the server, where it uses generative AI to retrieve nutritional information for each ingredient from a food ingredient database and calculate total calories, allergy information, and religious compliance information. At the same time, VR and 3D modeling technology is used to generate a virtual presentation of the new menu item.

[2047] The generated analysis results and virtual presentation image are sent to the device and displayed to the user. The user can input feedback based on this information and request readjustments if necessary. The readjustment feedback is sent back to the server, and the emotion engine analyzes the user's emotions. Data analysis is performed based on the user's emotions, and any necessary corrections or improvements are made.

[2048] Prompt Sentence Examples

[2049] An example of a prompt sentence to input to the generative AI model is as follows:

[2050] I'd like you to generate new menu ideas. Please provide the following information:

[2051] Ingredients: Pasta, tomatoes, olive oil, basil

[2052] Cooking method: Boiling, frying

[2053] Calorie restriction: 500 kcal or less

[2054] Allergy Information: Gluten Free

[2055] Through this system, users can quickly and efficiently develop new menu items, reducing food waste and food loss and promoting the growth of a sustainable food industry. Feedback that takes user emotions into consideration also enables the development of menu items that offer greater satisfaction.

[2056] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2057] Step 1:

[2058] The user uses the terminal to input information about ingredients, cooking methods, calorie restrictions, and allergy information for a new menu item. For example, if developing a "low-calorie pasta," the user enters the following information:

[2059] input:

[2060] Ingredients: Pasta, tomatoes, olive oil, basil

[2061] Cooking method: Boiling, frying

[2062] Calorie restriction: 500 kcal or less

[2063] Allergy Information: Gluten Free

[2064] The user presses a button to transmit data to the terminal.

[2065] Step 2:

[2066] The terminal temporarily stores the data entered by the user. Then it validates the data to ensure that it is in the correct format. For example, it checks whether all required fields have been entered and whether the numeric range is correct.

[2067] Input: Data submitted by the user

[2068] Data processing: format check, required field input check, numerical range check

[2069] Output: Validated data

[2070] If the validation is successful, the terminal transmits the data to the server.

[2071] Step 3:

[2072] The server receives the data sent from the device and stores it in a database.

[2073] Input: Validated data sent from the terminal

[2074] Data processing: Saving to database

[2075] Output: Saved data

[2076] Step 4:

[2077] The server uses generative AI to obtain nutritional information for each ingredient from a food ingredient database, such as the calories in pasta or the vitamin C content of tomatoes, and then calculates the total calories, allergy information, and religious compatibility information.

[2078] Input: Saved data

[2079] Data processing: Obtaining nutritional information from the food ingredient database, calculating total calories, and calculating allergy and religious information.

[2080] Output: Analysis results

[2081] Step 5:

[2082] The server uses VR and 3D modeling technology to generate a virtual presentation of the new menu items, which are then presented as 3D models that can be viewed from all angles.

[2083] Input: Analysis results

[2084] Data processing: Creating virtual presentation images using VR and 3D modeling technology

[2085] Output: Virtual presentation image

[2086] Step 6:

[2087] The server sends the analysis results and the generated virtual presentation image to the terminal.

[2088] Input: Analysis results, virtual presentation image

[2089] Data processing: Data integration

[2090] Output: Analysis results and virtual presentation images sent to the device

[2091] Step 7:

[2092] The terminal displays the information received from the server to the user, who can check the finished image of the new menu, as well as information on ingredients and allergies.

[2093] Input: Analysis results and virtual presentation images sent from the server

[2094] Data processing: Conversion to display format

[2095] Output: Displayed information

[2096] Step 8:

[2097] The user inputs feedback based on the analysis results. For example, they can enter comments such as "I'd like to reduce the amount of tomatoes" or "I'd like to change the cooking method." The feedback is sent to the server via the device.

[2098] Input: Analysis results and feedback opinions

[2099] Data processing: Adding feedback

[2100] Output: Feedback sent to the server

[2101] Step 9:

[2102] The server receives feedback from the user. At the same time, it uses an emotion engine to analyze the user's emotions based on their feedback, facial expressions, tone of voice, etc. It determines whether the user is expressing positive or negative emotions.

[2103] Input: Feedback and user emotional data (facial expressions, tone of voice, etc.)

[2104] Data processing: Sentiment analysis

[2105] Output: Emotion analysis results

[2106] Step 10:

[2107] The server reanalyzes the emotion data obtained from the emotion engine, and if the user gives negative feedback, it suggests alternative ingredients and cooking methods.

[2108] Input: Sentiment analysis results and feedback content

[2109] Data processing: reanalysis, generation of proposals

[2110] Output: Reanalysis results and recommendations

[2111] Step 11:

[2112] The server sends the reanalyzed data and the new virtual presentation image to the terminal, which provides new analysis results.

[2113] Input: Reanalysis results and new proposals

[2114] Data processing: Data integration

[2115] Output: Reanalysis results and virtual presentation image sent to the device

[2116] Step 12:

[2117] The device displays the reanalysis results to the user, who then provides feedback based on the new information. This process is repeated until the user is satisfied.

[2118] Input: Reanalysis results and virtual serving image sent from the server

[2119] Data processing: Conversion to display format

[2120] Output: Displayed reanalysis results and virtual presentation image

[2121] This series of processing steps allows users to efficiently develop and evaluate new menus, and feedback that takes user emotions into consideration makes it possible to develop menus that will provide high levels of satisfaction.

[2122] (Application example 2)

[2123] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2124] The traditional new menu development process was cost-inefficient, resulting in a lot of wasted ingredients and time, and requiring multiple prototypes. Furthermore, there was no way to provide feedback or suggestions that directly reflected user sentiment, resulting in low satisfaction with the final menu. To solve these problems, a system is needed that can efficiently and quickly develop new menus and make accurate suggestions based on user sentiment.

[2125] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2126] In this invention, the server includes means for receiving ingredient information, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related companies, means for verifying that the format of the entered information is correct, means for analyzing the received information using a generation AI and virtually providing ingredient data, calorie calculations, halal compliance information, and allergy information, means for generating virtual presentation images using virtual reality and 3D modeling technology, means for transmitting the analysis results and the virtual presentation images to a terminal for displaying them, means for providing an emotion engine for recognizing and analyzing user emotions, and means for providing feedback and suggestions based on the user emotions. This enables more efficient new menu development and more accurate suggestions based on user emotions.

[2127] "Restaurants or food-related companies" refers to businesses that develop and offer new menu items.

[2128] A "new menu" is a new dish or food that has never been offered before.

[2129] "Ingredient information" refers to detailed information about the types, quantities, origins, etc. of the various ingredients used in the new menu.

[2130] "Cooking method" refers to the specific cooking steps and methods used with ingredients.

[2131] "Calorie restriction" refers to a standard or requirement for keeping the total calories per meal within a specific range.

[2132] "Allergy information" refers to information about the possibility of an allergic reaction to a particular food ingredient.

[2133] "Means for receiving" refers to the method or technology for receiving information from a user.

[2134] "Verification means" refers to methods or techniques used to verify that received information conforms to its format and content.

[2135] "Generative AI" refers to artificial intelligence techniques used to analyze input data and generate the necessary information.

[2136] "Food ingredient data" refers to data on the nutrients and characteristics contained in each food ingredient.

[2137] "Calculating calories" refers to the process of calculating total calories based on ingredient information.

[2138] "Halal compatibility information" refers to information that indicates whether or not a food is suitable for consumption by Muslims.

[2139] "Virtual provision means" refers to methods and technologies for providing information or images that do not physically exist in a virtual space.

[2140] "Virtual reality" is a technology that provides a realistic experience within a computer-generated virtual environment.

[2141] "3D modeling technology" refers to the techniques and tools used to construct 3D virtual objects.

[2142] "Generative means" refers to methods and techniques for producing new information and images.

[2143] A "display terminal" is a device that allows a user to visually confirm information or images.

[2144] An "emotion engine" is a technology that recognizes and analyzes emotions from a user's facial expressions, tone of voice, etc.

[2145] "Means of providing" refers to methods or means for incorporating specific functions or technologies into a system.

[2146] "Feedback and suggestion means" refers to methods and technologies for providing advice and new suggestions based on analysis results and user sentiment.

[2147] "Means for reanalysis" refers to methods and techniques for re-analyzing data based on feedback or new data.

[2148] This invention is a system that supports the rapid and efficient development of new menus by linking user terminals, servers, generation AI, and emotion engines. This system collects input data, validates and analyzes data, generates virtual images, analyzes emotions, and receives and reanalyzes feedback. Specific implementation methods for the system are described below.

[2149] Hardware and software used

[2150] 1. User device: Uses input devices such as computers and tablets.

[2151] 2. Server: Serves as the central computer that performs analytical processing. Specific software uses generative AI technology.

[2152] 3. Generative AI: Artificial intelligence techniques used for data analysis and virtual presentation image generation.

[2153] 4. Emotion Engine: Technology that analyzes the user's facial expressions and tone of voice to recognize emotions. Uses "some_emotion_recognition_library" as the specific library.

[2154] 5. VR and 3D modeling technology: Technology used to generate virtual presentation images. For specific software, use "some_vr_library".

[2155] Data processing and calculation

[2156] The user terminal collects data such as ingredients, cooking methods, calorie restrictions, and allergy information for new menu items, and verifies that the entered information is in the correct format.

[2157] For example: "Ingredients: pasta, tomato, olive oil, basil", "Cooking method: boiling, frying", "Calorie limit: 500 kcal or less", "Allergy information: gluten-free"

[2158] The server receives data sent from the device and uses AI to analyze ingredient data, calorie calculations, halal compliance information, and allergy information, while also using VR and 3D modeling technology to generate virtual presentation images.

[2159] Example: "The generated virtual presentation image is provided in a format that can be viewed from all directions."

[2160] The emotion engine analyzes feedback from the user, facial expressions during operation, tone of voice, and other factors to recognize the user's emotions.

[2161] For example: "If the user expresses positive emotions, it will be considered positive and other cooking suggestions will be made."

[2162] Specific examples

[2163] For example, if a chef wants to develop a new "low-calorie pasta menu," he or she can use the system as follows:

[2164] 1. Enter ingredient information, cooking method, calorie restrictions, and allergy information into the user terminal.

[2165] 2. The server analyzes the data and generates a virtual presentation image.

[2166] 3. The user checks the analysis results and the virtual presentation image and provides feedback.

[2167] 4. The emotion engine analyzes the feedback and re-suggests the menu if necessary.

[2168] Prompt Sentence Examples

[2169] "This pasta dish uses five ingredients and aims to be under 500 kcal. Basil and tomato are the main ingredients. It is cooked both boiled and sautéed. It is gluten-free. Please generate detailed ingredient information and a virtual serving image for this dish."

[2170] As described above, using this system will make the new menu development process more efficient and enable proposals that will provide high levels of satisfaction based on user emotions.

[2171] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2172] Step 1:

[2173] The user inputs information about ingredients, cooking methods, calorie restrictions, and allergy information for a new menu item into the user terminal. Examples of input data include "Ingredients: pasta, tomato, olive oil, basil," "Cooking method: boiling, stir-frying," "Calorie restrictions: under 500 kcal," and "Allergy information: gluten-free." After input, the user terminal temporarily stores this information.

[2174] Step 2:

[2175] The terminal verifies that the format of the temporarily saved data is correct. For example, it checks whether all required fields have been entered and whether the numeric range is appropriate. If the format is correct, the terminal sends the data to the server. The input here is the menu information entered by the user, and the output is the verified data.

[2176] Step 3:

[2177] The server receives the data sent from the device and stores it. Next, it uses generative AI to obtain nutritional information for each ingredient from the ingredient database and calculates total calories, allergy information, and halal compliance information. For example, it obtains the calorie and nutritional information for "pasta" based on the received ingredient information. The input is verified menu information, and the output is the analysis results.

[2178] Step 4:

[2179] The server uses VR and 3D modeling technology to generate a virtual presentation image based on the analysis results. For example, it generates a 3D model of the appearance of low-calorie pasta. This allows users to check the appearance of the menu from all angles. The input is the analysis results, and the output is a 3D model of the presentation image.

[2180] Step 5:

[2181] The server sends the analysis results and a virtual presentation image to the terminal. The user terminal receives this and displays it to the user. For example, the analysis results may be displayed as "Calories: 480 kcal" or "Nutritional information: High in vitamin C, rich in iron." The input is the analysis results and a 3D image, and the output is visualized data that the user can view.

[2182] Step 6:

[2183] The user checks the displayed analysis results and the virtual presentation image and inputs feedback. The user's device sends this feedback to the server. For example, the user sends a specific request such as "I'd like more tomatoes." The input is the user's feedback, and the output is the feedback data.

[2184] Step 7:

[2185] The server receives the feedback and analyzes the user's emotions using an emotion engine. For example, the analysis result may be, "There are many positive opinions, but they would like to increase the amount of tomatoes." The input is the user's feedback, and the output is the emotion analysis result.

[2186] Step 8:

[2187] The server then uses the generative AI again to perform a new analysis based on the results of the emotion analysis. For example, it recalculates the nutritional content and calories if the amount of tomato is increased, and generates a new virtual presentation image. The input is the emotion analysis result and the reconfigured menu information, and the output is the reanalysis result and the new virtual presentation image.

[2188] Step 9:

[2189] The server sends the reanalysis results and a new virtual presentation image to the terminal and displays them to the user. The user then provides feedback and makes further adjustments as necessary. Ultimately, a new menu that satisfies the user is finalized. The input is the reanalysis results and a new 3D image, and the output is final confirmation data and the completion of the continuous feedback cycle.

[2190] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2191] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2192] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2193] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2194] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2195] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2196] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2197] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2198] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The oth...

Claims

1. A means for receiving information on ingredients, cooking methods, calorie restrictions, and allergy information for new menu items entered by restaurants or food-related businesses; a means for verifying that the information entered is in the correct format; A means for analyzing the received information using a generating AI and virtually providing food ingredient data, calorie calculations, halal compliance information, and allergy information; A means for generating a virtual presentation image using VR and modeling technology; means for transmitting the analysis results and the virtual presentation image to a terminal for displaying the analysis results and the virtual presentation image; A system including:

2. means for receiving feedback from a user based on the analysis results; a means for reanalyzing based on the feedback received; The system of claim 1 further comprising:

3. A means for generating a report for evaluating new menu items; A means to provide virtual presentation images from all angles using 3D modeling technology, The system of claim 1 further comprising:

Images