system

Abstract

We provide the system. [Solution] A means of inputting the user's location information, Methods that use artificial intelligence to collect information from the internet, A means for analyzing the collected information to generate cost-effective meal plans, A means for displaying the generated meal plan to the user, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Due to rising prices and stagnant wages, saving has become essential in households. However, in order to effectively reduce food expenses, a lot of information collection and appropriate judgment are required. However, it is not easy for users to select the most optimal meal plan within limited time, which has become a cause of increasing household burden.

Means for Solving the Problems

[0005] The present invention provides a system that collects information on the Internet based on the location information of a user using artificial intelligence and analyzes the obtained information to propose the most cost-effective meal plan. This system comprehensively collects and analyzes price information of food sales locations and campaign information of food and beverage establishments, and presents an optimal choice for the user, thereby realizing a means for saving household expenses.

[0006] "User location information" refers to geographical data of the user's current location or a specified address, and is used to provide location-based information.

[0007] "Information on the Internet" refers to publicly available information accessible from various websites and databases online, and specifically includes information such as pricing and promotional offers.

[0008] "Artificial intelligence" refers to technology that enables computers to analyze and make decisions based on data, and to mimic human intellectual activity.

[0009] A "meal plan" refers to a specific meal plan or selection of options proposed to optimize food expenses, based on collected and analyzed information.

[0010] "Places where groceries are sold" refers to physical stores where food can be purchased, such as supermarkets and grocery stores, as well as online platforms.

[0011] "Pricing information" refers to information about the price of goods or services, and is used for comparison and optimization.

[0012] "Food and beverage establishments" refer to places of business such as restaurants and cafes that serve meals, and are places that provide consumers with a dining experience.

[0013] "Campaign information" refers to information about discounts and benefits offered during a specific period, and describes the content of sales promotion activities directed at consumers. [Brief explanation of the drawing]

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

Embodiments for Carrying Out the Invention

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

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

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

[0018] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

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

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

[0022] [First Embodiment]

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

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

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

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

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

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

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

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

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

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

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

[0035] The system of this invention starts operating when a user enters their home or current address information via a terminal. Based on the entered information, the server collects price and promotional information about supermarkets and restaurants in the surrounding area from public and commercial databases on the internet. Artificial intelligence on the server analyzes the collected data and generates the most economical meal plan for the user.

[0036] The analysis results received by the terminal from the server include a list of ingredients the user can purchase, recipes using those ingredients, and details of campaigns at nearby restaurants. By viewing this information through the terminal's interface, users can select the optimal meal plan.

[0037] For example, if a user enters the address "Shinjuku Ward," the server retrieves data on all valid grocery stores within the specified area. For instance, it might find information indicating that curry ingredients can be purchased for a total of 400 yen at Supermarket A, and that a limited-time omelet rice dish is available for 600 yen at Restaurant B. The server analyzes these options and presents them to the user through the application screen. The user can then decide which plan to implement based on their budget and preferences. This allows the user to manage their food expenses most effectively within a limited budget.

[0038] This system combines efficient data analysis with an intuitive user interface to help users solve the important problem of saving on food expenses.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The user enters their home or current address on the device. The device receives this information, formats the data, and prepares to send it to the server.

[0042] Step 2:

[0043] The device sends address data to the server. The server receives this information and uses it to identify the relevant area.

[0044] Step 3:

[0045] The server accesses an internet database to collect price and promotional information for nearby grocery stores and restaurants based on the address.

[0046] Step 4:

[0047] The server uses artificial intelligence to analyze the collected data. A wide range of factors, including price, distance, and campaign duration, are considered to generate the optimal meal plan.

[0048] Step 5:

[0049] The server sends the analyzed results to the terminal. This includes a specific list of ingredients, recipe suggestions, and information on recommended stores.

[0050] Step 6:

[0051] The device visually displays the results on the user interface. The information is presented in an easy-to-understand format to facilitate comparison and consideration by the user.

[0052] Step 7:

[0053] The system selects the optimal meal plan based on the information provided to the user. It then determines the next steps necessary to execute the selected plan, such as purchasing ingredients or visiting a restaurant.

[0054] Step 8:

[0055] Users can act based on their decisions and reduce their food expenses in ways suggested by the system.

[0056] (Example 1)

[0057] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0058] The amount of information needed to select an efficient and economical meal plan is vast, and collecting and analyzing it independently is a time-consuming and laborious task for individuals. Furthermore, keeping track of fluctuating prices and campaign information in real time and proposing optimized meal plans has been difficult with traditional methods. Therefore, there was a need for a system that could quickly generate cost-effective consumption plans based on the latest price data and campaign information for specific regions, and that users could easily utilize.

[0059] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0060] In this invention, the server includes means for inputting location information based on the user's place of residence or current location, means for using an information processing device that aggregates public and commercial data on the internet, means for analyzing the collected data and generating cost-effective consumption plans using a generation AI model, and means for displaying the generated consumption plans on the terminal screen. This makes it possible for users to easily select the optimal meal plan based on the latest price information available in real time without having to collect information individually.

[0061] "Location information based on the user's place of residence or current location" refers to information that indicates where the user is currently staying or living, and is data used to identify the user's geographical location.

[0062] An "information processing device for aggregating public and commercial data on the internet" is a computer system that can quickly and efficiently collect and aggregate necessary information from public and commercial databases that are publicly available on the internet.

[0063] A "generative AI model" is a collection of artificial intelligence algorithms or programs used to generate optimal consumption suggestions for users, and has the function of making new suggestions based on past data and existing information.

[0064] A "cost-effective consumption plan" refers to a proposal or plan that minimizes the costs incurred by the user while enabling them to engage in consumption activities in the most efficient and effective way.

[0065] "Means for presenting the generated consumption plan on the terminal screen" refers to technologies and methods for visually displaying the consumption plan generated by the server to the user via the terminal's display.

[0066] "Price data for grocery sales locations" refers to information about the prices of groceries in specific regions or stores, and is data necessary for users to consider when making a purchase.

[0067] "Promotional campaign data for dining establishments" refers to information about special discounts and offers provided by restaurants and eateries, and is used to broaden users' choices when dining out.

[0068] This system begins with the user entering their home or current address information using a terminal. The terminal has an interface for sending location information to a server, which initiates the system's operation. The server uses a sophisticated information processing device to collect price and promotional information for supermarkets and restaurants from public and commercial databases on the internet.

[0069] The data analysis on the server focuses on generating the most economical spending plan for the user based on the collected information, utilizing a generative AI model. This AI model has the ability to compare price data and promotional information in detail and optimize the plan according to the user's past choices and preferences.

[0070] As a concrete example, consider a case where a user enters the address "Shinjuku Ward." The server retrieves data from valid grocery stores and restaurants within the specified area, gathering information such as whether curry ingredients are available for 400 yen at supermarket A and whether a limited-time menu is being offered at restaurant B. This allows the user to easily choose to buy curry ingredients for 400 yen and enjoy a specific menu item for 600 yen.

[0071] The generated meal plans are visually displayed on the device screen and presented in a way that is easy for the user to understand. An example of a prompt message is, "Please suggest a cost-effective meal plan using ingredients that can be purchased at nearby supermarkets for a user living in Shinjuku Ward."

[0072] This system allows users to efficiently and effectively manage their food expenses based on the latest price information collected in real time, eliminating the need to collect information independently. Thus, the combination of efficient data analysis and an intuitive user interface meets the user's need to save on food costs.

[0073] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0074] Step 1:

[0075] The user enters their home or current address information through the terminal. The entered address information triggers the system to start, and this information is sent to the server via the terminal. Input: Address information such as "Shinjuku Ward". Output: Location information data sent to the server.

[0076] Step 2:

[0077] The server accesses public and commercial databases on the internet based on received location information and uses a collection module to gather price and promotional information for supermarkets and restaurants in a specified area. Input: Location data. Output: Dataset of collected price and promotional information.

[0078] Step 3:

[0079] The server's AI model analyzes the collected dataset. This analysis process considers price comparison algorithms and the user's past choices to generate cost-effective meal suggestions. Input: Dataset of collected price and campaign information. Output: Optimized meal suggestions.

[0080] Step 4:

[0081] The server sends the generated meal plan to the terminal. The transmitted information includes a list of available ingredients, their locations, and menu suggestions for restaurants. Input: Optimized meal plan. Output: Meal plan information sent to the terminal.

[0082] Step 5:

[0083] The terminal displays received meal plan information on its screen, and the user selects the optimal plan based on cost-effectiveness and personal preferences through the interface. Input: Received meal plan information. Output: User's plan selection result.

[0084] Step 6:

[0085] The user takes actual purchasing and dining actions based on their selected plan. The user provides feedback to the system, which is used to improve future suggestions. Input: User's selection results. Output: Feedback on executed purchasing and dining actions.

[0086] (Application Example 1)

[0087] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0088] To provide efficient and economical dining plans, there is a need to support food expense management by collecting real-time information on nearby grocery stores and restaurants based on the user's location, and instantly generating and presenting the optimal plan. However, there is a lack of a method to comprehensively achieve this.

[0089] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0090] In this invention, the server includes means for inputting the user's location information, means for using intelligent processing to collect data from the Internet, and means for analyzing the collected data to generate an economically efficient dining plan. This allows the user to receive, select, and order the optimal dining plan based on their location.

[0091] "User location information" refers to geographical information about the user's current location, and is data that serves as a basis for the system to provide appropriate dining plans.

[0092] "Intelligent processing" refers to the process of collecting useful data from the internet using artificial intelligence and machine learning technologies, and performing appropriate information analysis.

[0093] An "economical dining plan" is a proposal designed to provide users with the necessary ingredients and meals at a cost-effective and affordable price.

[0094] A "food sales outlet" refers to a facility that sells food products to general consumers, such as a supermarket or grocery store.

[0095] A "food and beverage establishment" refers to a commercial facility that provides food and beverages, such as a restaurant or cafe.

[0096] "Discount information" refers to information about price reductions and promotions offered by restaurants and grocery stores to customers, enabling them to make economical choices.

[0097] "Real-time data collection" refers to the process of continuously updating information on the internet and obtaining the latest information on the spot.

[0098] The system that realizes this invention mainly consists of a server and a user terminal. The server, connected to the internet, utilizes intelligent processing to acquire data from nearby grocery stores and restaurants based on location information entered by the user. The specific software used for this includes Firebase for database management and the Google® Maps API for acquiring location information. The collected data is analyzed by an artificial intelligence algorithm using TENSORFLOW® to generate a cost-effective dining plan for the user.

[0099] The user's device displays this dining plan and provides an interface for the user to select and order. This interface is developed using React Native and is designed to run efficiently on smartphones.

[0100] For example, if a user is in Shinjuku Ward, the server uses this location information to collect data on nearby supermarkets and restaurants and provides the most affordable grocery and meal options. For instance, if the user inputs "I want to order a good value curry set," the generative AI model will present the cheapest and most economical option in that area.

[0101] An example of a prompt message would be, "Please recommend some food delivery options in Shinjuku Ward. I'd like to know the cheapest curry in this area."

[0102] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0103] Step 1:

[0104] The user enters their location information on the terminal. The input data is acquired by the terminal and sent directly to the server. The server then receives the user's location information as the starting point for data processing.

[0105] Step 2:

[0106] The server uses the Google Maps API to obtain accurate geographic location data from the user's entered location information. This API call takes location information as input and outputs geographic coordinates (latitude and longitude). The obtained geographic location plays a crucial role in subsequent data collection.

[0107] Step 3:

[0108] The server accesses the Firebase database to collect data on nearby grocery stores and restaurants based on location information. Here, geographic coordinates are input, and price and promotional information for grocery stores and restaurants is output. This involves using database queries to extract relevant store information.

[0109] Step 4:

[0110] The server uses TensorFlow to analyze collected data and generate economically efficient dining plans. The input is acquired price and promotional information, and the output is the optimal dining plan to present to the user. The generative AI model identifies the most cost-effective option. This analysis step includes data filtering and statistical calculations.

[0111] Step 5:

[0112] The generated dining plan is sent to the device, where it is displayed to the user. The device is designed to allow users to easily browse and select through an interface developed with React Native. The output optimal plan is displayed in an interactive GUI, prompting the user to make a selection.

[0113] Step 6:

[0114] The user selects a dining plan displayed on the terminal and places an order. The terminal then sends the selected order information back to the server. Finally, the server processes the order data and transmits the order to the selected location. This ensures the order is processed correctly and the user's request is fulfilled. This step involves the transmission and confirmation of the selected data.

[0115] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0116] This invention combines an emotion engine with a system for optimizing a user's food expenses to propose meal suggestions that take the user's emotional state into account. The system configuration is as follows:

[0117] This system begins with the user entering their location information via a terminal. The location information entered by the user is then transmitted to a server by the terminal. Based on this information, the server collects data on grocery stores and restaurants in the surrounding area from the internet.

[0118] At this point, the server uses artificial intelligence to analyze the collected data and generate cost-effective meal suggestions. An emotion engine then joins the process, acquiring the user's emotions from the device's interface. The emotion engine analyzes the user's input, actions, and, in some cases, voice and facial expressions, and sends the results back to the server.

[0119] The server leverages the user's emotional information to personalize the generated meal suggestions. For example, if a user is feeling stressed, it can suggest easy-to-prepare dishes or foods with relaxing properties. Conversely, if a user is in a mood to try something new, it can recommend recipes using ingredients different from what they usually use.

[0120] The generated meal suggestions are customized to reflect the user's emotional state and are displayed on the device. The device presents these suggested meal options to the user in a visually easy-to-understand format.

[0121] For example, suppose a user enters an address in "Minato Ward," and the system retrieves information that the ingredients for pasta at Supermarket D cost 400 yen and pizza at Restaurant E costs 600 yen. Furthermore, if the system determines that the user needs to relax, it can suggest a simple pasta recipe or pizza from Restaurant E served with tea. In this way, the present invention not only pursues cost efficiency but also provides meal options that are sensitive to the user's emotions.

[0122] The following describes the processing flow.

[0123] Step 1:

[0124] The user enters their location information on the device. The device prepares to receive this information and organizes the address data entered by the user.

[0125] Step 2:

[0126] The terminal sends address data to the server. The server receives this information and prepares to begin analysis.

[0127] Step 3:

[0128] The server collects price and promotional information for nearby grocery stores and restaurants from the internet. The server accesses a database to enable this.

[0129] Step 4:

[0130] The server uses artificial intelligence to analyze collected data and generate cost-effective meal plans. The server selects the optimal plan considering factors such as price, distance, and restaurant ratings.

[0131] Step 5:

[0132] Users input their current emotional state using an emotional interface via their device. Emotional input can be selected from options or automatically detected.

[0133] Step 6:

[0134] The device sends user emotion information to the server. The server receives this data and uses it to customize meal suggestions.

[0135] Step 7:

[0136] The server adjusts meal suggestions based on the user's emotional data. For example, if the server detects a desire to relax, it will recommend a plan that includes easy-to-prepare meals and foods with calming effects.

[0137] Step 8:

[0138] The server sends a customized meal plan to the device. The device receives this information and displays it in a visually easy-to-understand format on the user interface.

[0139] Step 9:

[0140] The system selects the optimal meal plan based on the information provided to the user. Users can consider suggestions tailored to their emotional state and decide on a plan based on their personal preferences and needs.

[0141] Step 10:

[0142] The system acts according to the plan selected by the user. For example, it can efficiently manage food expenses by going to the supermarket to purchase selected ingredients or visiting restaurants.

[0143] (Example 2)

[0144] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0145] Modern consumers seek optimal meal choices tailored to their individual economic circumstances and emotional states, while utilizing a wide range of options. However, current systems are limited to selections based on location and simple price information, making it difficult to provide personalized meal suggestions that incorporate emotional states. Against this backdrop, the challenge lies in providing meal suggestions that consider not only the user's economic efficiency but also their emotional satisfaction.

[0146] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0147] In this invention, the server includes means for inputting information related to the user's location, means for using an intelligent analysis device that collects information from a global information network, and means for analyzing the user's emotional state and personalizing meal suggestions generated based on that state. This enables the user to make meal choices that are both economically efficient and emotionally satisfying.

[0148] "Information related to the user's location" refers to data that indicates the user's current location or a specific region, obtained through location-based services, etc.

[0149] A "global information network" refers to a large-scale data source, including the internet, from which diverse information can be collected.

[0150] An "intelligent analysis device" is a system that uses artificial intelligence and machine learning algorithms to process data and obtain analysis results.

[0151] An "economically effective meal plan" is a meal proposal designed to maximize cost-effectiveness, offering a choice that balances the user's budget with quality.

[0152] "User emotional state" refers to data that indicates the psychological and emotional state a user is experiencing, and is analyzed from voice and facial expressions.

[0153] A "personalized meal plan" is a meal suggestion customized to individual needs and preferences, based on collected data and the user's emotional state.

[0154] "Methods using intelligent analytical devices" refer to the process of analyzing data and extracting useful information using artificial intelligence technology.

[0155] The system of this invention begins with the user inputting information related to their location. The user uses a terminal to input their address and GPS information and transmits this information to a server. Based on this, the server collects data on nearby grocery stores and restaurants using a global information network, such as various database services. In this process, it is possible to use the Google Maps API or other geographic information services.

[0156] The server analyzes the collected information using intelligent analysis equipment. Specifically, it uses a generative AI model (for example, GPT-3® or a similar model) to generate cost-effective meal plans. During this process, the AI ​​is given instructions such as "Please list cost-effective ingredients from region X" as a prompt.

[0157] On the other hand, the device is equipped with means to analyze the user's emotional state. Users can either directly input their emotions or have their emotional state analyzed through a voice interface or camera. This operation utilizes emotion recognition libraries, such as Google Cloud's Vision API. The analyzed emotional information is sent to a server.

[0158] The server uses this emotional information to personalize pre-generated meal suggestions. Specifically, if a user is feeling stressed, it can suggest simple, relaxing meals.

[0159] Ultimately, the device visually presents these personalized meal suggestions to the user. The device's interface is designed using React Native and other popular development frameworks.

[0160] As a concrete example, a user enters the address of a specific city, and the server analyzes data on the location and price to suggest the most suitable meal. If the emotion engine determines that the user is seeking relaxation, it can suggest a meal paired with herbal tea. In this way, the system enables meal selection that takes both economic and emotional factors into consideration.

[0161] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0162] Step 1:

[0163] The user enters their current location information through the device's interface. This includes manual entry of an address or automatic acquisition using GPS functionality. The entered location information is sent from the device to the server. This information forms the basis for collecting the geographic data required in the next step.

[0164] Step 2:

[0165] The server collects data from the information network based on location information received from the user. Specifically, it uses geographic information services such as the Google Maps API to obtain information about food supply locations and restaurants. Based on this input information, it forms relevant datasets within the target area.

[0166] Step 3:

[0167] The server processes the collected data using an intelligent analysis device to generate cost-effective meal plans. This process utilizes a generative AI model, analyzing the user's location information and prompt statement, "List cost-effective ingredients in area X." As a result, meal plans that minimize costs while ensuring high satisfaction are generated.

[0168] Step 4:

[0169] The user inputs their emotional state into the device, or uses a voice interface or camera to analyze their emotions. The device then collects emotional data using an emotion recognition library. The collected emotional information is sent to a server.

[0170] Step 5:

[0171] The server uses the received emotional information to personalize meal suggestions. In this process, it analyzes emotional data and combines ingredients and menu items that are appropriate for the user's emotional state. For example, it suggests foods with relaxing effects to a user seeking relaxation.

[0172] Step 6:

[0173] The terminal visually presents personalized meal suggestions received from the server to the user. The displayed interface is designed with frameworks such as React Native, presenting information in a way that is easy for the user to understand. This allows the user to make meal choices that are both economically and emotionally satisfying.

[0174] (Application Example 2)

[0175] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0176] In daily life, users sometimes find it difficult to choose meals that are appropriate for their emotional state and location. Finding a suitable meal quickly is particularly challenging when stressed or in need of relaxation. Therefore, there is a need for a system that automatically receives and allows users to select the optimal meal based on their emotional state.

[0177] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0178] In this invention, the server includes means for inputting the user's location information, means for using artificial intelligence to collect information from the internet, and means for recognizing and acquiring the user's emotional state. This makes it possible to provide a cost-effective meal plan that is personalized according to the user's current emotional state.

[0179] "Means for inputting user location information" refers to a device or software that acquires data to determine the user's current location.

[0180] "Methods using artificial intelligence to collect information from the internet" refers to processes that utilize artificial intelligence technology to collect and analyze data on food products and dining facilities via the internet.

[0181] "A method for generating cost-effective meal plans" refers to an algorithm that, based on collected data, considers cost and convenience to propose the optimal meal plan to the user.

[0182] "Means for recognizing and acquiring a user's emotional state" refers to technology that analyzes the user's facial expressions, voice, and operation data, and estimates and digitizes their emotions.

[0183] "Means of displaying or presenting personalized meal suggestions visually or audibly" refers to a system that visually displays customized meal suggestions on a screen, tailored to the user's emotional state, or provides audible guidance through an audio output device.

[0184] The system that realizes this invention utilizes a user terminal, a server, and artificial intelligence technology. First, the user inputs location information via the terminal. This information is acquired using a GPS module and transmitted from the terminal to the server. Based on the acquired location information, the server collects information on grocery stores and restaurants on the internet. Web scraping technology and artificial intelligence are used to access the database for this collection.

[0185] Next, the server analyzes the collected information using the AI ​​model "PyTorch" to generate cost-effective meal suggestions. Furthermore, the user's emotional state is analyzed by emotion recognition software "Emotion AI" via the terminal's camera and microphone, and this information is sent to the server. Based on this emotional information, the meal suggestions are personalized. The personalized meal suggestions are displayed visually or audibly on the user's interface. GUI software is used for visual display, and a speech synthesis library is used for audio output.

[0186] For example, if a user is relaxing at home and wants meal suggestions, the device sends a prompt saying, "I want a relaxing meal." The server analyzes the location to find the nearest restaurants, generates suggestions such as dishes containing healing herbs, and sends the results back to the device.

[0187] Example of a prompt:

[0188] "Please suggest some relaxing dining options in Minato Ward. Our users are experiencing some stress."

[0189] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0190] Step 1:

[0191] The user inputs location information via their device. This input consists of data from a GPS module indicating the user's current location. The device then transmits this location information to the server.

[0192] Step 2:

[0193] The server collects data on grocery store locations and restaurants from the internet based on the received location information. This data collection uses web scraping techniques to extract necessary information from databases containing food prices and menu information. The output is detailed regional data.

[0194] Step 3:

[0195] The server analyzes the collected data using the AI ​​model "PyTorch" to generate cost-effective meal plans. Here, location data collected as input is used to process the data and select the optimal ingredient purchase options and dining menus. The output is the generated meal plan.

[0196] Step 4:

[0197] The user activates the emotion recognition function on their device. This function uses "Emotion AI" to analyze data collected through the camera and microphone to identify the user's emotional state. The input consists of facial expressions and voice data, and the output is the user's emotional state.

[0198] Step 5:

[0199] The server collects the user's emotional information and personalizes the previously generated meal plan according to that emotion. Using the emotional data, it customizes the meal plan by incorporating ingredients and cooking methods that promote relaxation. The output is the personalized meal plan.

[0200] Step 6:

[0201] The terminal presents personalized meal suggestions to the user visually or audibly. GUI software is used to provide visual explanations on the display, and a text-to-speech library reads the instructions aloud. The user then uses this information to make the optimal meal choice.

[0202] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0203] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0204] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0205] [Second Embodiment]

[0206] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0207] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0208] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0209] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0210] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0211] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0212] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0213] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0214] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0215] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0216] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0217] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0218] The system of this invention starts operating when a user enters their home or current address information via a terminal. Based on the entered information, the server collects price and promotional information about supermarkets and restaurants in the surrounding area from public and commercial databases on the internet. Artificial intelligence on the server analyzes the collected data and generates the most economical meal plan for the user.

[0219] The analysis results received by the terminal from the server include a list of ingredients the user can purchase, recipes using those ingredients, and details of campaigns at nearby restaurants. By viewing this information through the terminal's interface, users can select the optimal meal plan.

[0220] For example, if a user enters the address "Shinjuku Ward," the server retrieves data on all valid grocery stores within the specified area. For instance, it might find information indicating that curry ingredients can be purchased for a total of 400 yen at Supermarket A, and that a limited-time omelet rice dish is available for 600 yen at Restaurant B. The server analyzes these options and presents them to the user through the application screen. The user can then decide which plan to implement based on their budget and preferences. This allows the user to manage their food expenses most effectively within a limited budget.

[0221] This system combines efficient data analysis with an intuitive user interface to help users solve the important problem of saving on food expenses.

[0222] The following describes the processing flow.

[0223] Step 1:

[0224] The user enters their home or current address on the device. The device receives this information, formats the data, and prepares to send it to the server.

[0225] Step 2:

[0226] The device sends address data to the server. The server receives this information and uses it to identify the relevant area.

[0227] Step 3:

[0228] The server accesses an internet database to collect price and promotional information for nearby grocery stores and restaurants based on the address.

[0229] Step 4:

[0230] The server uses artificial intelligence to analyze the collected data. A wide range of factors, including price, distance, and campaign duration, are considered to generate the optimal meal plan.

[0231] Step 5:

[0232] The server sends the analyzed results to the terminal. This includes a specific list of ingredients, recipe suggestions, and information on recommended stores.

[0233] Step 6:

[0234] The device visually displays the results on the user interface. The information is presented in an easy-to-understand format to facilitate comparison and consideration by the user.

[0235] Step 7:

[0236] The system selects the optimal meal plan based on the information provided to the user. It then determines the next steps necessary to execute the selected plan, such as purchasing ingredients or visiting a restaurant.

[0237] Step 8:

[0238] Users can act based on their decisions and reduce their food expenses in ways suggested by the system.

[0239] (Example 1)

[0240] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0241] The amount of information needed to select an efficient and economical meal plan is vast, and collecting and analyzing it independently is a time-consuming and laborious task for individuals. Furthermore, keeping track of fluctuating prices and campaign information in real time and proposing optimized meal plans has been difficult with traditional methods. Therefore, there was a need for a system that could quickly generate cost-effective consumption plans based on the latest price data and campaign information for specific regions, and that users could easily utilize.

[0242] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0243] In this invention, the server includes means for inputting location information based on the user's place of residence or current location, means for using an information processing device that aggregates public and commercial data on the internet, means for analyzing the collected data and generating cost-effective consumption plans using a generation AI model, and means for displaying the generated consumption plans on the terminal screen. This makes it possible for users to easily select the optimal meal plan based on the latest price information available in real time without having to collect information individually.

[0244] "Location information based on the user's place of residence or current location" refers to information that indicates where the user is currently staying or living, and is data used to identify the user's geographical location.

[0245] An "information processing device for aggregating public and commercial data on the internet" is a computer system that can quickly and efficiently collect and aggregate necessary information from public and commercial databases that are publicly available on the internet.

[0246] A "generative AI model" is a collection of artificial intelligence algorithms or programs used to generate optimal consumption suggestions for users, and has the function of making new suggestions based on past data and existing information.

[0247] A "cost-effective consumption plan" refers to a proposal or plan that minimizes the costs incurred by the user while enabling them to engage in consumption activities in the most efficient and effective way.

[0248] "Means for presenting the generated consumption plan on the terminal screen" refers to technologies and methods for visually displaying the consumption plan generated by the server to the user via the terminal's display.

[0249] "Price data for grocery sales locations" refers to information about the prices of groceries in specific regions or stores, and is data necessary for users to consider when making a purchase.

[0250] "Promotional campaign data for dining establishments" refers to information about special discounts and offers provided by restaurants and eateries, and is used to broaden users' choices when dining out.

[0251] This system begins with the user entering their home or current address information using a terminal. The terminal has an interface for sending location information to a server, which initiates the system's operation. The server uses a sophisticated information processing device to collect price and promotional information for supermarkets and restaurants from public and commercial databases on the internet.

[0252] The data analysis on the server focuses on generating the most economical spending plan for the user based on the collected information, utilizing a generative AI model. This AI model has the ability to compare price data and promotional information in detail and optimize the plan according to the user's past choices and preferences.

[0253] As a concrete example, consider a case where a user enters the address "Shinjuku Ward." The server retrieves data from valid grocery stores and restaurants within the specified area, gathering information such as whether curry ingredients are available for 400 yen at supermarket A and whether a limited-time menu is being offered at restaurant B. This allows the user to easily choose to buy curry ingredients for 400 yen and enjoy a specific menu item for 600 yen.

[0254] The generated meal plans are visually displayed on the device screen and presented in a way that is easy for the user to understand. An example of a prompt message is, "Please suggest a cost-effective meal plan using ingredients that can be purchased at nearby supermarkets for a user living in Shinjuku Ward."

[0255] This system allows users to efficiently and effectively manage their food expenses based on the latest price information collected in real time, eliminating the need to collect information independently. Thus, the combination of efficient data analysis and an intuitive user interface meets the user's need to save on food costs.

[0256] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0257] Step 1:

[0258] The user enters their home or current address information through the terminal. The entered address information triggers the system to start, and this information is sent to the server via the terminal. Input: Address information such as "Shinjuku Ward". Output: Location information data sent to the server.

[0259] Step 2:

[0260] The server accesses public and commercial databases on the internet based on received location information and uses a collection module to gather price and promotional information for supermarkets and restaurants in a specified area. Input: Location data. Output: Dataset of collected price and promotional information.

[0261] Step 3:

[0262] The server's AI model analyzes the collected dataset. This analysis process considers price comparison algorithms and the user's past choices to generate cost-effective meal suggestions. Input: Dataset of collected price and campaign information. Output: Optimized meal suggestions.

[0263] Step 4:

[0264] The server sends the generated meal plan to the terminal. The transmitted information includes a list of available ingredients, their locations, and menu suggestions for restaurants. Input: Optimized meal plan. Output: Meal plan information sent to the terminal.

[0265] Step 5:

[0266] The terminal displays received meal plan information on its screen, and the user selects the optimal plan based on cost-effectiveness and personal preferences through the interface. Input: Received meal plan information. Output: User's plan selection result.

[0267] Step 6:

[0268] The user takes actual purchasing and dining actions based on their selected plan. The user provides feedback to the system, which is used to improve future suggestions. Input: User's selection results. Output: Feedback on executed purchasing and dining actions.

[0269] (Application Example 1)

[0270] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0271] To provide efficient and economical dining plans, there is a need to support food expense management by collecting real-time information on nearby grocery stores and restaurants based on the user's location, and instantly generating and presenting the optimal plan. However, there is a lack of a method to comprehensively achieve this.

[0272] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0273] In this invention, the server includes means for inputting the user's location information, means for using intelligent processing to collect data from the Internet, and means for analyzing the collected data to generate an economically efficient dining plan. This allows the user to receive, select, and order the optimal dining plan based on their location.

[0274] "User location information" refers to geographical information about the user's current location, and is data that serves as a basis for the system to provide appropriate dining plans.

[0275] "Intelligent processing" refers to the process of collecting useful data from the internet using artificial intelligence and machine learning technologies, and performing appropriate information analysis.

[0276] An "economical dining plan" is a proposal designed to provide users with the necessary ingredients and meals at a cost-effective and affordable price.

[0277] A "food sales outlet" refers to a facility that sells food products to general consumers, such as a supermarket or grocery store.

[0278] A "food and beverage establishment" refers to a commercial facility that provides food and beverages, such as a restaurant or cafe.

[0279] "Discount information" refers to information on price cuts and campaigns provided by food and beverage outlets and food product sales outlets to customers, enabling economic choices.

[0280] "Collect in real time" refers to the process of continuously updating information on the Internet and obtaining the latest status on-site.

[0281] The system for realizing this invention mainly consists of a server and a user's terminal. The server utilizes intelligent processing while connected to the Internet and acquires data from surrounding food product sales outlets and food and beverage outlets based on the location information input by the user. For the specific software used in this, Firebase is applied to database management, and the Google Maps API is utilized for obtaining location information. The collected data is analyzed by an artificial intelligence algorithm using TensorFlow to generate a diet plan that is excellent in economy for the user.

[0282] The user's terminal displays this diet plan and provides an interface for the user to make selections and place orders. This interface is developed using React Native and is designed to operate efficiently on smartphones.

[0283] As a specific example, when the user is in Shinjuku Ward, the server collects data on surrounding supermarkets and restaurants based on this location information and provides the most affordable food ingredients and meal options. For example, when the user inputs "want to order an affordable curry set", the generated AI model presents the most inexpensive and economical options within that area.

[0284] Examples of prompt sentences are like "Tell me the recommended food delivery options in Shinjuku Ward. I want to know the cheapest curry in this area."

[0285] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0286] Step 1:

[0287] The user inputs their location information on the terminal. The input data is acquired by the terminal and directly sent to the server. As a result, the server receives the user's location information as the basis for data processing.

[0288] Step 2:

[0289] The server uses the Google Maps API to obtain accurate geographical location data from the location information input by the user. In this API call, the location information is used as the input, and geographical coordinates (latitude and longitude) are output. The obtained geographical location plays an important role in the next data collection.

[0290] Step 3:

[0291] The server accesses the Firebase database and collects data on surrounding food sales points and dining establishments based on the location information. Here, the geographical coordinates are used as the input, and price information and campaign information related to food and dining facilities are obtained as the output. This includes the process of extracting relevant store information by utilizing database queries.

[0292] Step 4:

[0293] The server uses TensorFlow to analyze the collected data and generate an economically excellent dining plan. The input here is the obtained price information and campaign information, and the output is the optimal dining plan for presenting to the user. The generated AI model identifies the plan with the best cost performance. This analysis step includes data filtering and statistical calculation processing.

[0294] Step 5:

[0295] The generated dining plan is sent to the device, where it is displayed to the user. The device is designed to allow users to easily browse and select through an interface developed with React Native. The output optimal plan is displayed in an interactive GUI, prompting the user to make a selection.

[0296] Step 6:

[0297] The user selects a dining plan displayed on the terminal and places an order. The terminal then sends the selected order information back to the server. Finally, the server processes the order data and transmits the order to the selected location. This ensures the order is processed correctly and the user's request is fulfilled. This step involves the transmission and confirmation of the selected data.

[0298] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0299] This invention combines an emotion engine with a system for optimizing a user's food expenses to propose meal suggestions that take the user's emotional state into account. The system configuration is as follows:

[0300] This system begins with the user entering their location information via a terminal. The location information entered by the user is then transmitted to a server by the terminal. Based on this information, the server collects data on grocery stores and restaurants in the surrounding area from the internet.

[0301] At this point, the server uses artificial intelligence to analyze the collected data and generate cost-effective meal suggestions. An emotion engine then joins the process, acquiring the user's emotions from the device's interface. The emotion engine analyzes the user's input, actions, and, in some cases, voice and facial expressions, and sends the results back to the server.

[0302] The server utilizes the user's emotional information to personalize the generated meal plans. For example, when the user is feeling stressed, it is possible to propose dishes that can be easily cooked or foods with a relaxing effect. Conversely, if the user is in an emotional state where they want to challenge something new, recipes using ingredients different from usual can be recommended.

[0303] The generated meal plans are customized to reflect the user's emotional state and are displayed on the terminal. The terminal presents these proposed meal plans to the user in a visually easy-to-see form.

[0304] To give a specific example, assume that the user enters an address in "Minato Ward" and the system obtains information that the ingredients for pasta at D Supermarket selected by the system cost 400 yen and the pizza at E Restaurant costs 600 yen. Further, if the system determines that the user needs relaxation, it can propose a simple pasta recipe or the pizza at E Restaurant provided in combination with tea. Thus, the present invention not only pursues cost efficiency but also provides meal options in a way that takes into account the user's emotions.

[0305] The following describes the processing flow.

[0306] Step 1:

[0307] The user inputs their location information on the terminal. The terminal prepares to receive this information and arranges the address data input by the user.

[0308] Step 2:

[0309] The terminal transmits the address data to the server. The server receives this information and prepares to start analysis.

[0310] Step 3:

[0311] The server collects price and promotional information for nearby grocery stores and restaurants from the internet. The server accesses a database to enable this.

[0312] Step 4:

[0313] The server uses artificial intelligence to analyze collected data and generate cost-effective meal plans. The server selects the optimal plan considering factors such as price, distance, and restaurant ratings.

[0314] Step 5:

[0315] Users input their current emotional state using an emotional interface via their device. Emotional input can be selected from options or automatically detected.

[0316] Step 6:

[0317] The device sends user emotion information to the server. The server receives this data and uses it to customize meal suggestions.

[0318] Step 7:

[0319] The server adjusts meal suggestions based on the user's emotional data. For example, if the server detects a desire to relax, it will recommend a plan that includes easy-to-prepare meals and foods with calming effects.

[0320] Step 8:

[0321] The server sends a customized meal plan to the device. The device receives this information and displays it in a visually easy-to-understand format on the user interface.

[0322] Step 9:

[0323] The system selects the optimal meal plan based on the information provided to the user. Users can consider suggestions tailored to their emotional state and decide on a plan based on their personal preferences and needs.

[0324] Step 10:

[0325] The system acts according to the plan selected by the user. For example, it can efficiently manage food expenses by going to the supermarket to purchase selected ingredients or visiting restaurants.

[0326] (Example 2)

[0327] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0328] Modern consumers seek optimal meal choices tailored to their individual economic circumstances and emotional states, while utilizing a wide range of options. However, current systems are limited to selections based on location and simple price information, making it difficult to provide personalized meal suggestions that incorporate emotional states. Against this backdrop, the challenge lies in providing meal suggestions that consider not only the user's economic efficiency but also their emotional satisfaction.

[0329] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0330] In this invention, the server includes means for inputting information related to the user's location, means for using an intelligent analysis device that collects information from a global information network, and means for analyzing the user's emotional state and personalizing meal suggestions generated based on that state. This enables the user to make meal choices that are both economically efficient and emotionally satisfying.

[0331] "Information related to the user's location" refers to data that indicates the user's current location or a specific region, obtained through location-based services, etc.

[0332] A "global information network" refers to a large-scale data source, including the internet, from which diverse information can be collected.

[0333] An "intelligent analysis device" is a system that uses artificial intelligence and machine learning algorithms to process data and obtain analysis results.

[0334] An "economically effective meal plan" is a meal proposal designed to maximize cost-effectiveness, offering a choice that balances the user's budget with quality.

[0335] "User emotional state" refers to data that indicates the psychological and emotional state a user is experiencing, and is analyzed from voice and facial expressions.

[0336] A "personalized meal plan" is a meal suggestion customized to individual needs and preferences, based on collected data and the user's emotional state.

[0337] "Methods using intelligent analytical devices" refer to the process of analyzing data and extracting useful information using artificial intelligence technology.

[0338] The system of this invention begins with the user inputting information related to their location. The user uses a terminal to input their address and GPS information and transmits this information to a server. Based on this, the server collects data on nearby grocery stores and restaurants using a global information network, such as various database services. In this process, it is possible to use the Google Maps API or other geographic information services.

[0339] The server analyzes the collected information using intelligent analysis equipment. Specifically, it uses a generative AI model (such as GPT-3 or a similar model) to generate cost-effective meal plans. During this process, the AI ​​is given instructions such as "Please list cost-effective ingredients from region X" as a prompt.

[0340] On the other hand, the device is equipped with means to analyze the user's emotional state. Users can either directly input their emotions or have their emotional state analyzed through a voice interface or camera. This operation utilizes emotion recognition libraries, such as Google Cloud's Vision API. The analyzed emotional information is sent to a server.

[0341] The server uses this emotional information to personalize pre-generated meal suggestions. Specifically, if a user is feeling stressed, it can suggest simple, relaxing meals.

[0342] Ultimately, the device visually presents these personalized meal suggestions to the user. The device's interface is designed using React Native and other popular development frameworks.

[0343] As a concrete example, a user enters the address of a specific city, and the server analyzes data on the location and price to suggest the most suitable meal. If the emotion engine determines that the user is seeking relaxation, it can suggest a meal paired with herbal tea. In this way, the system enables meal selection that takes both economic and emotional factors into consideration.

[0344] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0345] Step 1:

[0346] The user enters their current location information through the device's interface. This includes manual entry of an address or automatic acquisition using GPS functionality. The entered location information is sent from the device to the server. This information forms the basis for collecting the geographic data required in the next step.

[0347] Step 2:

[0348] The server collects data from the information network based on location information received from the user. Specifically, it uses geographic information services such as the Google Maps API to obtain information about food supply locations and restaurants. Based on this input information, it forms relevant datasets within the target area.

[0349] Step 3:

[0350] The server processes the collected data using an intelligent analysis device to generate cost-effective meal plans. This process utilizes a generative AI model, analyzing the user's location information and prompt statement, "List cost-effective ingredients in area X." As a result, meal plans that minimize costs while ensuring high satisfaction are generated.

[0351] Step 4:

[0352] The user inputs their emotional state into the device, or uses a voice interface or camera to analyze their emotions. The device then collects emotional data using an emotion recognition library. The collected emotional information is sent to a server.

[0353] Step 5:

[0354] The server uses the received emotional information to personalize meal suggestions. In this process, it analyzes emotional data and combines ingredients and menu items that are appropriate for the user's emotional state. For example, it suggests foods with relaxing effects to a user seeking relaxation.

[0355] Step 6:

[0356] The terminal visually presents personalized meal suggestions received from the server to the user. The displayed interface is designed with frameworks such as React Native, presenting information in a way that is easy for the user to understand. This allows the user to make meal choices that are both economically and emotionally satisfying.

[0357] (Application Example 2)

[0358] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0359] In daily life, users sometimes find it difficult to choose meals that are appropriate for their emotional state and location. Finding a suitable meal quickly is particularly challenging when stressed or in need of relaxation. Therefore, there is a need for a system that automatically receives and allows users to select the optimal meal based on their emotional state.

[0360] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0361] In this invention, the server includes means for inputting the user's location information, means for using artificial intelligence to collect information from the internet, and means for recognizing and acquiring the user's emotional state. This makes it possible to provide a cost-effective meal plan that is personalized according to the user's current emotional state.

[0362] "Means for inputting user location information" refers to a device or software that acquires data to determine the user's current location.

[0363] "Methods using artificial intelligence to collect information from the internet" refers to processes that utilize artificial intelligence technology to collect and analyze data on food products and dining facilities via the internet.

[0364] "A method for generating cost-effective meal plans" refers to an algorithm that, based on collected data, considers cost and convenience to propose the optimal meal plan to the user.

[0365] "Means for recognizing and acquiring a user's emotional state" refers to technology that analyzes the user's facial expressions, voice, and operation data, and estimates and digitizes their emotions.

[0366] "Means of displaying or presenting personalized meal suggestions visually or audibly" refers to a system that visually displays customized meal suggestions on a screen, tailored to the user's emotional state, or provides audible guidance through an audio output device.

[0367] The system that realizes this invention utilizes a user terminal, a server, and artificial intelligence technology. First, the user inputs location information via the terminal. This information is acquired using a GPS module and transmitted from the terminal to the server. Based on the acquired location information, the server collects information on grocery stores and restaurants on the internet. Web scraping technology and artificial intelligence are used to access the database for this collection.

[0368] Next, the server analyzes the collected information using the AI ​​model "PyTorch" to generate cost-effective meal suggestions. Furthermore, the user's emotional state is analyzed by emotion recognition software "Emotion AI" via the terminal's camera and microphone, and this information is sent to the server. Based on this emotional information, the meal suggestions are personalized. The personalized meal suggestions are displayed visually or audibly on the user's interface. GUI software is used for visual display, and a speech synthesis library is used for audio output.

[0369] For example, if a user is relaxing at home and wants meal suggestions, the device sends a prompt saying, "I want a relaxing meal." The server analyzes the location to find the nearest restaurants, generates suggestions such as dishes containing healing herbs, and sends the results back to the device.

[0370] Example of a prompt:

[0371] "Please suggest some relaxing dining options in Minato Ward. Our users are experiencing some stress."

[0372] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0373] Step 1:

[0374] The user inputs location information via their device. This input consists of data from a GPS module indicating the user's current location. The device then transmits this location information to the server.

[0375] Step 2:

[0376] The server collects data on grocery store locations and restaurants from the internet based on the received location information. This data collection uses web scraping techniques to extract necessary information from databases containing food prices and menu information. The output is detailed regional data.

[0377] Step 3:

[0378] The server analyzes the collected data using the AI ​​model "PyTorch" to generate cost-effective meal plans. Here, location data collected as input is used to process the data and select the optimal ingredient purchase options and dining menus. The output is the generated meal plan.

[0379] Step 4:

[0380] The user activates the emotion recognition function on their device. This function uses "Emotion AI" to analyze data collected through the camera and microphone to identify the user's emotional state. The input consists of facial expressions and voice data, and the output is the user's emotional state.

[0381] Step 5:

[0382] The server collects the user's emotional information and personalizes the previously generated meal plan according to that emotion. Using the emotional data, it customizes the meal plan by incorporating ingredients and cooking methods that promote relaxation. The output is the personalized meal plan.

[0383] Step 6:

[0384] The terminal presents personalized meal suggestions to the user visually or audibly. GUI software is used to provide visual explanations on the display, and a text-to-speech library reads the instructions aloud. The user then uses this information to make the optimal meal choice.

[0385] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0386] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0387] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0388] [Third Embodiment]

[0389] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0390] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0391] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0392] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0393] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0394] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0395] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0396] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0397] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0398] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0399] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0400] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0401] The system of this invention starts operating when a user enters their home or current address information via a terminal. Based on the entered information, the server collects price and promotional information about supermarkets and restaurants in the surrounding area from public and commercial databases on the internet. Artificial intelligence on the server analyzes the collected data and generates the most economical meal plan for the user.

[0402] The analysis results received by the terminal from the server include a list of ingredients the user can purchase, recipes using those ingredients, and details of campaigns at nearby restaurants. By viewing this information through the terminal's interface, users can select the optimal meal plan.

[0403] For example, if a user enters the address "Shinjuku Ward," the server retrieves data on all valid grocery stores within the specified area. For instance, it might find information indicating that curry ingredients can be purchased for a total of 400 yen at Supermarket A, and that a limited-time omelet rice dish is available for 600 yen at Restaurant B. The server analyzes these options and presents them to the user through the application screen. The user can then decide which plan to implement based on their budget and preferences. This allows the user to manage their food expenses most effectively within a limited budget.

[0404] This system combines efficient data analysis with an intuitive user interface to help users solve the important problem of saving on food expenses.

[0405] The following describes the processing flow.

[0406] Step 1:

[0407] The user enters their home or current address on the device. The device receives this information, formats the data, and prepares to send it to the server.

[0408] Step 2:

[0409] The device sends address data to the server. The server receives this information and uses it to identify the relevant area.

[0410] Step 3:

[0411] The server accesses an internet database to collect price and promotional information for nearby grocery stores and restaurants based on the address.

[0412] Step 4:

[0413] The server uses artificial intelligence to analyze the collected data. A wide range of factors, including price, distance, and campaign duration, are considered to generate the optimal meal plan.

[0414] Step 5:

[0415] The server sends the analyzed results to the terminal. This includes a specific list of ingredients, recipe suggestions, and information on recommended stores.

[0416] Step 6:

[0417] The device visually displays the results on the user interface. The information is presented in an easy-to-understand format to facilitate comparison and consideration by the user.

[0418] Step 7:

[0419] The system selects the optimal meal plan based on the information provided to the user. It then determines the next steps necessary to execute the selected plan, such as purchasing ingredients or visiting a restaurant.

[0420] Step 8:

[0421] Users can act based on their decisions and reduce their food expenses in ways suggested by the system.

[0422] (Example 1)

[0423] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0424] The amount of information needed to select an efficient and economical meal plan is vast, and collecting and analyzing it independently is a time-consuming and laborious task for individuals. Furthermore, keeping track of fluctuating prices and campaign information in real time and proposing optimized meal plans has been difficult with traditional methods. Therefore, there was a need for a system that could quickly generate cost-effective consumption plans based on the latest price data and campaign information for specific regions, and that users could easily utilize.

[0425] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0426] In this invention, the server includes means for inputting location information based on the user's place of residence or current location, means for using an information processing device that aggregates public and commercial data on the internet, means for analyzing the collected data and generating cost-effective consumption plans using a generation AI model, and means for displaying the generated consumption plans on the terminal screen. This makes it possible for users to easily select the optimal meal plan based on the latest price information available in real time without having to collect information individually.

[0427] "Location information based on the user's place of residence or current location" refers to information that indicates where the user is currently staying or living, and is data used to identify the user's geographical location.

[0428] An "information processing device for aggregating public and commercial data on the internet" is a computer system that can quickly and efficiently collect and aggregate necessary information from public and commercial databases that are publicly available on the internet.

[0429] A "generative AI model" is a collection of artificial intelligence algorithms or programs used to generate optimal consumption suggestions for users, and has the function of making new suggestions based on past data and existing information.

[0430] A "cost-effective consumption plan" refers to a proposal or plan that minimizes the costs incurred by the user while enabling them to engage in consumption activities in the most efficient and effective way.

[0431] "Means for presenting the generated consumption plan on the terminal screen" refers to technologies and methods for visually displaying the consumption plan generated by the server to the user via the terminal's display.

[0432] "Price data for grocery sales locations" refers to information about the prices of groceries in specific regions or stores, and is data necessary for users to consider when making a purchase.

[0433] "Promotional campaign data for dining establishments" refers to information about special discounts and offers provided by restaurants and eateries, and is used to broaden users' choices when dining out.

[0434] This system begins with the user entering their home or current address information using a terminal. The terminal has an interface for sending location information to a server, which initiates the system's operation. The server uses a sophisticated information processing device to collect price and promotional information for supermarkets and restaurants from public and commercial databases on the internet.

[0435] The data analysis on the server focuses on generating the most economical spending plan for the user based on the collected information, utilizing a generative AI model. This AI model has the ability to compare price data and promotional information in detail and optimize the plan according to the user's past choices and preferences.

[0436] As a concrete example, consider a case where a user enters the address "Shinjuku Ward." The server retrieves data from valid grocery stores and restaurants within the specified area, gathering information such as whether curry ingredients are available for 400 yen at supermarket A and whether a limited-time menu is being offered at restaurant B. This allows the user to easily choose to buy curry ingredients for 400 yen and enjoy a specific menu item for 600 yen.

[0437] The generated meal plans are visually displayed on the device screen and presented in a way that is easy for the user to understand. An example of a prompt message is, "Please suggest a cost-effective meal plan using ingredients that can be purchased at nearby supermarkets for a user living in Shinjuku Ward."

[0438] This system allows users to efficiently and effectively manage their food expenses based on the latest price information collected in real time, eliminating the need to collect information independently. Thus, the combination of efficient data analysis and an intuitive user interface meets the user's need to save on food costs.

[0439] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0440] Step 1:

[0441] The user enters their home or current address information through the terminal. The entered address information triggers the system to start, and this information is sent to the server via the terminal. Input: Address information such as "Shinjuku Ward". Output: Location information data sent to the server.

[0442] Step 2:

[0443] The server accesses public and commercial databases on the internet based on received location information and uses a collection module to gather price and promotional information for supermarkets and restaurants in a specified area. Input: Location data. Output: Dataset of collected price and promotional information.

[0444] Step 3:

[0445] The server's AI model analyzes the collected dataset. This analysis process considers price comparison algorithms and the user's past choices to generate cost-effective meal suggestions. Input: Dataset of collected price and campaign information. Output: Optimized meal suggestions.

[0446] Step 4:

[0447] The server sends the generated meal plan to the terminal. The transmitted information includes a list of available ingredients, their locations, and menu suggestions for restaurants. Input: Optimized meal plan. Output: Meal plan information sent to the terminal.

[0448] Step 5:

[0449] The terminal displays received meal plan information on its screen, and the user selects the optimal plan based on cost-effectiveness and personal preferences through the interface. Input: Received meal plan information. Output: User's plan selection result.

[0450] Step 6:

[0451] The user takes actual purchasing and dining actions based on their selected plan. The user provides feedback to the system, which is used to improve future suggestions. Input: User's selection results. Output: Feedback on executed purchasing and dining actions.

[0452] (Application Example 1)

[0453] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0454] To provide efficient and economical dining plans, there is a need to support food expense management by collecting real-time information on nearby grocery stores and restaurants based on the user's location, and instantly generating and presenting the optimal plan. However, there is a lack of a method to comprehensively achieve this.

[0455] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0456] In this invention, the server includes means for inputting the user's location information, means for using intelligent processing to collect data from the Internet, and means for analyzing the collected data to generate an economically efficient dining plan. This allows the user to receive, select, and order the optimal dining plan based on their location.

[0457] "User location information" refers to geographical information about the user's current location, and is data that serves as a basis for the system to provide appropriate dining plans.

[0458] "Intelligent processing" refers to the process of collecting useful data from the internet using artificial intelligence and machine learning technologies, and performing appropriate information analysis.

[0459] An "economical dining plan" is a proposal designed to provide users with the necessary ingredients and meals at a cost-effective and affordable price.

[0460] A "food sales outlet" refers to a facility that sells food products to general consumers, such as a supermarket or grocery store.

[0461] A "food and beverage establishment" refers to a commercial facility that provides food and beverages, such as a restaurant or cafe.

[0462] "Discount information" refers to information about price reductions and promotions offered by restaurants and grocery stores to customers, enabling them to make economical choices.

[0463] "Real-time data collection" refers to the process of continuously updating information on the internet and obtaining the latest information on the spot.

[0464] The system that realizes this invention mainly consists of a server and a user terminal. The server, connected to the internet, utilizes intelligent processing to acquire data from nearby grocery stores and restaurants based on location information entered by the user. The specific software used for this includes Firebase for database management and the Google Maps API for acquiring location information. The collected data is analyzed by an artificial intelligence algorithm using TensorFlow to generate a cost-effective dining plan for the user.

[0465] The user's device displays this dining plan and provides an interface for the user to select and order. This interface is developed using React Native and is designed to run efficiently on smartphones.

[0466] For example, if a user is in Shinjuku Ward, the server uses this location information to collect data on nearby supermarkets and restaurants and provides the most affordable grocery and meal options. For instance, if the user inputs "I want to order a good value curry set," the generative AI model will present the cheapest and most economical option in that area.

[0467] An example of a prompt message would be, "Please recommend some food delivery options in Shinjuku Ward. I'd like to know the cheapest curry in this area."

[0468] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0469] Step 1:

[0470] The user enters their location information on the terminal. The input data is acquired by the terminal and sent directly to the server. The server then receives the user's location information as the starting point for data processing.

[0471] Step 2:

[0472] The server uses the Google Maps API to obtain accurate geographic location data from the user's entered location information. This API call takes location information as input and outputs geographic coordinates (latitude and longitude). The obtained geographic location plays a crucial role in subsequent data collection.

[0473] Step 3:

[0474] The server accesses the Firebase database to collect data on nearby grocery stores and restaurants based on location information. Here, geographic coordinates are input, and price and promotional information for grocery stores and restaurants is output. This involves using database queries to extract relevant store information.

[0475] Step 4:

[0476] The server uses TensorFlow to analyze collected data and generate economically efficient dining plans. The input is acquired price and promotional information, and the output is the optimal dining plan to present to the user. The generative AI model identifies the most cost-effective option. This analysis step includes data filtering and statistical calculations.

[0477] Step 5:

[0478] The generated dining plan is sent to the device, where it is displayed to the user. The device is designed to allow users to easily browse and select through an interface developed with React Native. The output optimal plan is displayed in an interactive GUI, prompting the user to make a selection.

[0479] Step 6:

[0480] The user selects a dining plan displayed on the terminal and places an order. The terminal then sends the selected order information back to the server. Finally, the server processes the order data and transmits the order to the selected location. This ensures the order is processed correctly and the user's request is fulfilled. This step involves the transmission and confirmation of the selected data.

[0481] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0482] This invention combines an emotion engine with a system for optimizing a user's food expenses to propose meal suggestions that take the user's emotional state into account. The system configuration is as follows:

[0483] This system begins with the user entering their location information via a terminal. The location information entered by the user is then transmitted to a server by the terminal. Based on this information, the server collects data on grocery stores and restaurants in the surrounding area from the internet.

[0484] At this point, the server uses artificial intelligence to analyze the collected data and generate cost-effective meal suggestions. An emotion engine then joins the process, acquiring the user's emotions from the device's interface. The emotion engine analyzes the user's input, actions, and, in some cases, voice and facial expressions, and sends the results back to the server.

[0485] The server leverages the user's emotional information to personalize the generated meal suggestions. For example, if a user is feeling stressed, it can suggest easy-to-prepare dishes or foods with relaxing properties. Conversely, if a user is in a mood to try something new, it can recommend recipes using ingredients different from what they usually use.

[0486] The generated meal suggestions are customized to reflect the user's emotional state and are displayed on the device. The device presents these suggested meal options to the user in a visually easy-to-understand format.

[0487] For example, suppose a user enters an address in "Minato Ward," and the system retrieves information that the ingredients for pasta at Supermarket D cost 400 yen and pizza at Restaurant E costs 600 yen. Furthermore, if the system determines that the user needs to relax, it can suggest a simple pasta recipe or pizza from Restaurant E served with tea. In this way, the present invention not only pursues cost efficiency but also provides meal options that are sensitive to the user's emotions.

[0488] The following describes the processing flow.

[0489] Step 1:

[0490] The user enters their location information on the device. The device prepares to receive this information and organizes the address data entered by the user.

[0491] Step 2:

[0492] The terminal sends address data to the server. The server receives this information and prepares to begin analysis.

[0493] Step 3:

[0494] The server collects price and promotional information for nearby grocery stores and restaurants from the internet. The server accesses a database to enable this.

[0495] Step 4:

[0496] The server uses artificial intelligence to analyze collected data and generate cost-effective meal plans. The server selects the optimal plan considering factors such as price, distance, and restaurant ratings.

[0497] Step 5:

[0498] Users input their current emotional state using an emotional interface via their device. Emotional input can be selected from options or automatically detected.

[0499] Step 6:

[0500] The device sends user emotion information to the server. The server receives this data and uses it to customize meal suggestions.

[0501] Step 7:

[0502] The server adjusts meal suggestions based on the user's emotional data. For example, if the server detects a desire to relax, it will recommend a plan that includes easy-to-prepare meals and foods with calming effects.

[0503] Step 8:

[0504] The server sends a customized meal plan to the device. The device receives this information and displays it in a visually easy-to-understand format on the user interface.

[0505] Step 9:

[0506] The system selects the optimal meal plan based on the information provided to the user. Users can consider suggestions tailored to their emotional state and decide on a plan based on their personal preferences and needs.

[0507] Step 10:

[0508] The system acts according to the plan selected by the user. For example, it can efficiently manage food expenses by going to the supermarket to purchase selected ingredients or visiting restaurants.

[0509] (Example 2)

[0510] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0511] Modern consumers seek optimal meal choices tailored to their individual economic circumstances and emotional states, while utilizing a wide range of options. However, current systems are limited to selections based on location and simple price information, making it difficult to provide personalized meal suggestions that incorporate emotional states. Against this backdrop, the challenge lies in providing meal suggestions that consider not only the user's economic efficiency but also their emotional satisfaction.

[0512] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0513] In this invention, the server includes means for inputting information related to the user's location, means for using an intelligent analysis device that collects information from a global information network, and means for analyzing the user's emotional state and personalizing meal suggestions generated based on that state. This enables the user to make meal choices that are both economically efficient and emotionally satisfying.

[0514] "Information related to the user's location" refers to data that indicates the user's current location or a specific region, obtained through location-based services, etc.

[0515] A "global information network" refers to a large-scale data source, including the internet, from which diverse information can be collected.

[0516] An "intelligent analysis device" is a system that uses artificial intelligence and machine learning algorithms to process data and obtain analysis results.

[0517] An "economically effective meal plan" is a meal proposal designed to maximize cost-effectiveness, offering a choice that balances the user's budget with quality.

[0518] "User emotional state" refers to data that indicates the psychological and emotional state a user is experiencing, and is analyzed from voice and facial expressions.

[0519] A "personalized meal plan" is a meal suggestion customized to individual needs and preferences, based on collected data and the user's emotional state.

[0520] "Methods using intelligent analytical devices" refer to the process of analyzing data and extracting useful information using artificial intelligence technology.

[0521] The system of this invention begins with the user inputting information related to their location. The user uses a terminal to input their address and GPS information and transmits this information to a server. Based on this, the server collects data on nearby grocery stores and restaurants using a global information network, such as various database services. In this process, it is possible to use the Google Maps API or other geographic information services.

[0522] The server analyzes the collected information using intelligent analysis equipment. Specifically, it uses a generative AI model (such as GPT-3 or a similar model) to generate cost-effective meal plans. During this process, the AI ​​is given instructions such as "Please list cost-effective ingredients from region X" as a prompt.

[0523] On the other hand, the device is equipped with means to analyze the user's emotional state. Users can either directly input their emotions or have their emotional state analyzed through a voice interface or camera. This operation utilizes emotion recognition libraries, such as Google Cloud's Vision API. The analyzed emotional information is sent to a server.

[0524] The server uses this emotional information to personalize pre-generated meal suggestions. Specifically, if a user is feeling stressed, it can suggest simple, relaxing meals.

[0525] Ultimately, the device visually presents these personalized meal suggestions to the user. The device's interface is designed using React Native and other popular development frameworks.

[0526] As a concrete example, a user enters the address of a specific city, and the server analyzes data on the location and price to suggest the most suitable meal. If the emotion engine determines that the user is seeking relaxation, it can suggest a meal paired with herbal tea. In this way, the system enables meal selection that takes both economic and emotional factors into consideration.

[0527] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0528] Step 1:

[0529] The user enters their current location information through the device's interface. This includes manual entry of an address or automatic acquisition using GPS functionality. The entered location information is sent from the device to the server. This information forms the basis for collecting the geographic data required in the next step.

[0530] Step 2:

[0531] The server collects data from the information network based on location information received from the user. Specifically, it uses geographic information services such as the Google Maps API to obtain information about food supply locations and restaurants. Based on this input information, it forms relevant datasets within the target area.

[0532] Step 3:

[0533] The server processes the collected data using an intelligent analysis device to generate cost-effective meal plans. This process utilizes a generative AI model, analyzing the user's location information and prompt statement, "List cost-effective ingredients in area X." As a result, meal plans that minimize costs while ensuring high satisfaction are generated.

[0534] Step 4:

[0535] The user inputs their emotional state into the device, or uses a voice interface or camera to analyze their emotions. The device then collects emotional data using an emotion recognition library. The collected emotional information is sent to a server.

[0536] Step 5:

[0537] The server uses the received emotional information to personalize meal suggestions. In this process, it analyzes emotional data and combines ingredients and menu items that are appropriate for the user's emotional state. For example, it suggests foods with relaxing effects to a user seeking relaxation.

[0538] Step 6:

[0539] The terminal visually presents personalized meal suggestions received from the server to the user. The displayed interface is designed with frameworks such as React Native, presenting information in a way that is easy for the user to understand. This allows the user to make meal choices that are both economically and emotionally satisfying.

[0540] (Application Example 2)

[0541] Next, we will explain Application Example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0542] In daily life, users sometimes find it difficult to choose meals that are appropriate for their emotional state and location. Finding a suitable meal quickly is particularly challenging when stressed or in need of relaxation. Therefore, there is a need for a system that automatically receives and allows users to select the optimal meal based on their emotional state.

[0543] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0544] In this invention, the server includes means for inputting the user's location information, means for using artificial intelligence to collect information from the internet, and means for recognizing and acquiring the user's emotional state. This makes it possible to provide a cost-effective meal plan that is personalized according to the user's current emotional state.

[0545] "Means for inputting user location information" refers to a device or software that acquires data to determine the user's current location.

[0546] "Methods using artificial intelligence to collect information from the internet" refers to processes that utilize artificial intelligence technology to collect and analyze data on food products and dining facilities via the internet.

[0547] "A method for generating cost-effective meal plans" refers to an algorithm that, based on collected data, considers cost and convenience to propose the optimal meal plan to the user.

[0548] "Means for recognizing and acquiring a user's emotional state" refers to technology that analyzes the user's facial expressions, voice, and operation data, and estimates and digitizes their emotions.

[0549] "Means of displaying or presenting personalized meal suggestions visually or audibly" refers to a system that visually displays customized meal suggestions on a screen, tailored to the user's emotional state, or provides audible guidance through an audio output device.

[0550] The system that realizes this invention utilizes a user terminal, a server, and artificial intelligence technology. First, the user inputs location information via the terminal. This information is acquired using a GPS module and transmitted from the terminal to the server. Based on the acquired location information, the server collects information on grocery stores and restaurants on the internet. Web scraping technology and artificial intelligence are used to access the database for this collection.

[0551] Next, the server analyzes the collected information using the AI ​​model "PyTorch" to generate cost-effective meal suggestions. Furthermore, the user's emotional state is analyzed by emotion recognition software "Emotion AI" via the terminal's camera and microphone, and this information is sent to the server. Based on this emotional information, the meal suggestions are personalized. The personalized meal suggestions are displayed visually or audibly on the user's interface. GUI software is used for visual display, and a speech synthesis library is used for audio output.

[0552] For example, if a user is relaxing at home and wants meal suggestions, the device sends a prompt saying, "I want a relaxing meal." The server analyzes the location to find the nearest restaurants, generates suggestions such as dishes containing healing herbs, and sends the results back to the device.

[0553] Example of a prompt:

[0554] "Please suggest some relaxing dining options in Minato Ward. Our users are experiencing some stress."

[0555] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0556] Step 1:

[0557] The user inputs location information via their device. This input consists of data from a GPS module indicating the user's current location. The device then transmits this location information to the server.

[0558] Step 2:

[0559] The server collects data on grocery store locations and restaurants from the internet based on the received location information. This data collection uses web scraping techniques to extract necessary information from databases containing food prices and menu information. The output is detailed regional data.

[0560] Step 3:

[0561] The server analyzes the collected data using the AI ​​model "PyTorch" to generate cost-effective meal plans. Here, location data collected as input is used to process the data and select the optimal ingredient purchase options and dining menus. The output is the generated meal plan.

[0562] Step 4:

[0563] The user activates the emotion recognition function on their device. This function uses "Emotion AI" to analyze data collected through the camera and microphone to identify the user's emotional state. The input consists of facial expressions and voice data, and the output is the user's emotional state.

[0564] Step 5:

[0565] The server collects the user's emotional information and personalizes the previously generated meal plan according to that emotion. Using the emotional data, it customizes the meal plan by incorporating ingredients and cooking methods that promote relaxation. The output is the personalized meal plan.

[0566] Step 6:

[0567] The terminal presents personalized meal suggestions to the user visually or audibly. GUI software is used to provide visual explanations on the display, and a text-to-speech library reads the instructions aloud. The user then uses this information to make the optimal meal choice.

[0568] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0569] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0570] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0571] [Fourth Embodiment]

[0572] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0573] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0574] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0575] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0576] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0577] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0578] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0579] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0580] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0581] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0582] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0583] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0584] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0585] The system of this invention starts operating when a user enters their home or current address information via a terminal. Based on the entered information, the server collects price and promotional information about supermarkets and restaurants in the surrounding area from public and commercial databases on the internet. Artificial intelligence on the server analyzes the collected data and generates the most economical meal plan for the user.

[0586] The analysis results received by the terminal from the server include a list of ingredients the user can purchase, recipes using those ingredients, and details of campaigns at nearby restaurants. By viewing this information through the terminal's interface, users can select the optimal meal plan.

[0587] For example, if a user enters the address "Shinjuku Ward," the server retrieves data on all valid grocery stores within the specified area. For instance, it might find information indicating that curry ingredients can be purchased for a total of 400 yen at Supermarket A, and that a limited-time omelet rice dish is available for 600 yen at Restaurant B. The server analyzes these options and presents them to the user through the application screen. The user can then decide which plan to implement based on their budget and preferences. This allows the user to manage their food expenses most effectively within a limited budget.

[0588] This system combines efficient data analysis with an intuitive user interface to help users solve the important problem of saving on food expenses.

[0589] The following describes the processing flow.

[0590] Step 1:

[0591] The user enters their home or current address on the device. The device receives this information, formats the data, and prepares to send it to the server.

[0592] Step 2:

[0593] The device sends address data to the server. The server receives this information and uses it to identify the relevant area.

[0594] Step 3:

[0595] The server accesses an internet database to collect price and promotional information for nearby grocery stores and restaurants based on the address.

[0596] Step 4:

[0597] The server uses artificial intelligence to analyze the collected data. A wide range of factors, including price, distance, and campaign duration, are considered to generate the optimal meal plan.

[0598] Step 5:

[0599] The server sends the analyzed results to the terminal. This includes a specific list of ingredients, recipe suggestions, and information on recommended stores.

[0600] Step 6:

[0601] The device visually displays the results on the user interface. The information is presented in an easy-to-understand format to facilitate comparison and consideration by the user.

[0602] Step 7:

[0603] The system selects the optimal meal plan based on the information provided to the user. It then determines the next steps necessary to execute the selected plan, such as purchasing ingredients or visiting a restaurant.

[0604] Step 8:

[0605] Users can act based on their decisions and reduce their food expenses in ways suggested by the system.

[0606] (Example 1)

[0607] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0608] The amount of information needed to select an efficient and economical meal plan is vast, and collecting and analyzing it independently is a time-consuming and laborious task for individuals. Furthermore, keeping track of fluctuating prices and campaign information in real time and proposing optimized meal plans has been difficult with traditional methods. Therefore, there was a need for a system that could quickly generate cost-effective consumption plans based on the latest price data and campaign information for specific regions, and that users could easily utilize.

[0609] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0610] In this invention, the server includes means for inputting location information based on the user's place of residence or current location, means for using an information processing device that aggregates public and commercial data on the internet, means for analyzing the collected data and generating cost-effective consumption plans using a generation AI model, and means for displaying the generated consumption plans on the terminal screen. This makes it possible for users to easily select the optimal meal plan based on the latest price information available in real time without having to collect information individually.

[0611] "Location information based on the user's place of residence or current location" refers to information that indicates where the user is currently staying or living, and is data used to identify the user's geographical location.

[0612] An "information processing device for aggregating public and commercial data on the internet" is a computer system that can quickly and efficiently collect and aggregate necessary information from public and commercial databases that are publicly available on the internet.

[0613] A "generative AI model" is a collection of artificial intelligence algorithms or programs used to generate optimal consumption suggestions for users, and has the function of making new suggestions based on past data and existing information.

[0614] A "cost-effective consumption plan" refers to a proposal or plan that minimizes the costs incurred by the user while enabling them to engage in consumption activities in the most efficient and effective way.

[0615] "Means for presenting the generated consumption plan on the terminal screen" refers to technologies and methods for visually displaying the consumption plan generated by the server to the user via the terminal's display.

[0616] "Price data for grocery sales locations" refers to information about the prices of groceries in specific regions or stores, and is data necessary for users to consider when making a purchase.

[0617] "Promotional campaign data for dining establishments" refers to information about special discounts and offers provided by restaurants and eateries, and is used to broaden users' choices when dining out.

[0618] This system begins with the user entering their home or current address information using a terminal. The terminal has an interface for sending location information to a server, which initiates the system's operation. The server uses a sophisticated information processing device to collect price and promotional information for supermarkets and restaurants from public and commercial databases on the internet.

[0619] The data analysis on the server focuses on generating the most economical spending plan for the user based on the collected information, utilizing a generative AI model. This AI model has the ability to compare price data and promotional information in detail and optimize the plan according to the user's past choices and preferences.

[0620] As a concrete example, consider a case where a user enters the address "Shinjuku Ward." The server retrieves data from valid grocery stores and restaurants within the specified area, gathering information such as whether curry ingredients are available for 400 yen at supermarket A and whether a limited-time menu is being offered at restaurant B. This allows the user to easily choose to buy curry ingredients for 400 yen and enjoy a specific menu item for 600 yen.

[0621] The generated meal plans are visually displayed on the device screen and presented in a way that is easy for the user to understand. An example of a prompt message is, "Please suggest a cost-effective meal plan using ingredients that can be purchased at nearby supermarkets for a user living in Shinjuku Ward."

[0622] This system allows users to efficiently and effectively manage their food expenses based on the latest price information collected in real time, eliminating the need to collect information independently. Thus, the combination of efficient data analysis and an intuitive user interface meets the user's need to save on food costs.

[0623] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0624] Step 1:

[0625] The user enters their home or current address information through the terminal. The entered address information triggers the system to start, and this information is sent to the server via the terminal. Input: Address information such as "Shinjuku Ward". Output: Location information data sent to the server.

[0626] Step 2:

[0627] The server accesses public and commercial databases on the internet based on received location information and uses a collection module to gather price and promotional information for supermarkets and restaurants in a specified area. Input: Location data. Output: Dataset of collected price and promotional information.

[0628] Step 3:

[0629] The server's AI model analyzes the collected dataset. This analysis process considers price comparison algorithms and the user's past choices to generate cost-effective meal suggestions. Input: Dataset of collected price and campaign information. Output: Optimized meal suggestions.

[0630] Step 4:

[0631] The server sends the generated meal plan to the terminal. The transmitted information includes a list of available ingredients, their locations, and menu suggestions for restaurants. Input: Optimized meal plan. Output: Meal plan information sent to the terminal.

[0632] Step 5:

[0633] The terminal displays received meal plan information on its screen, and the user selects the optimal plan based on cost-effectiveness and personal preferences through the interface. Input: Received meal plan information. Output: User's plan selection result.

[0634] Step 6:

[0635] The user takes actual purchasing and dining actions based on their selected plan. The user provides feedback to the system, which is used to improve future suggestions. Input: User's selection results. Output: Feedback on executed purchasing and dining actions.

[0636] (Application Example 1)

[0637] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0638] To provide efficient and economical dining plans, there is a need to support food expense management by collecting real-time information on nearby grocery stores and restaurants based on the user's location, and instantly generating and presenting the optimal plan. However, there is a lack of a method to comprehensively achieve this.

[0639] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0640] In this invention, the server includes means for inputting the user's location information, means for using intelligent processing to collect data from the Internet, and means for analyzing the collected data to generate an economically efficient dining plan. This allows the user to receive, select, and order the optimal dining plan based on their location.

[0641] "User location information" refers to geographical information about the user's current location, and is data that serves as a basis for the system to provide appropriate dining plans.

[0642] "Intelligent processing" refers to the process of collecting useful data from the internet using artificial intelligence and machine learning technologies, and performing appropriate information analysis.

[0643] An "economical dining plan" is a proposal designed to provide users with the necessary ingredients and meals at a cost-effective and affordable price.

[0644] A "food sales outlet" refers to a facility that sells food products to general consumers, such as a supermarket or grocery store.

[0645] A "food and beverage establishment" refers to a commercial facility that provides food and beverages, such as a restaurant or cafe.

[0646] "Discount information" refers to information about price reductions and promotions offered by restaurants and grocery stores to customers, enabling them to make economical choices.

[0647] "Real-time data collection" refers to the process of continuously updating information on the internet and obtaining the latest information on the spot.

[0648] The system that realizes this invention mainly consists of a server and a user terminal. The server, connected to the internet, utilizes intelligent processing to acquire data from nearby grocery stores and restaurants based on location information entered by the user. The specific software used for this includes Firebase for database management and the Google Maps API for acquiring location information. The collected data is analyzed by an artificial intelligence algorithm using TensorFlow to generate a cost-effective dining plan for the user.

[0649] The user's device displays this dining plan and provides an interface for the user to select and order. This interface is developed using React Native and is designed to run efficiently on smartphones.

[0650] For example, if a user is in Shinjuku Ward, the server uses this location information to collect data on nearby supermarkets and restaurants and provides the most affordable grocery and meal options. For instance, if the user inputs "I want to order a good value curry set," the generative AI model will present the cheapest and most economical option in that area.

[0651] An example of a prompt message would be, "Please recommend some food delivery options in Shinjuku Ward. I'd like to know the cheapest curry in this area."

[0652] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0653] Step 1:

[0654] The user enters their location information on the terminal. The input data is acquired by the terminal and sent directly to the server. The server then receives the user's location information as the starting point for data processing.

[0655] Step 2:

[0656] The server uses the Google Maps API to obtain accurate geographic location data from the user's entered location information. This API call takes location information as input and outputs geographic coordinates (latitude and longitude). The obtained geographic location plays a crucial role in subsequent data collection.

[0657] Step 3:

[0658] The server accesses the Firebase database to collect data on nearby grocery stores and restaurants based on location information. Here, geographic coordinates are input, and price and promotional information for grocery stores and restaurants is output. This involves using database queries to extract relevant store information.

[0659] Step 4:

[0660] The server uses TensorFlow to analyze collected data and generate economically efficient dining plans. The input is acquired price and promotional information, and the output is the optimal dining plan to present to the user. The generative AI model identifies the most cost-effective option. This analysis step includes data filtering and statistical calculations.

[0661] Step 5:

[0662] The generated dining plan is sent to the device, where it is displayed to the user. The device is designed to allow users to easily browse and select through an interface developed with React Native. The output optimal plan is displayed in an interactive GUI, prompting the user to make a selection.

[0663] Step 6:

[0664] The user selects a dining plan displayed on the terminal and places an order. The terminal then sends the selected order information back to the server. Finally, the server processes the order data and transmits the order to the selected location. This ensures the order is processed correctly and the user's request is fulfilled. This step involves the transmission and confirmation of the selected data.

[0665] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0666] This invention combines an emotion engine with a system for optimizing a user's food expenses to propose meal suggestions that take the user's emotional state into account. The system configuration is as follows:

[0667] This system begins with the user entering their location information via a terminal. The location information entered by the user is then transmitted to a server by the terminal. Based on this information, the server collects data on grocery stores and restaurants in the surrounding area from the internet.

[0668] At this point, the server uses artificial intelligence to analyze the collected data and generate cost-effective meal suggestions. An emotion engine then joins the process, acquiring the user's emotions from the device's interface. The emotion engine analyzes the user's input, actions, and, in some cases, voice and facial expressions, and sends the results back to the server.

[0669] The server leverages the user's emotional information to personalize the generated meal suggestions. For example, if a user is feeling stressed, it can suggest easy-to-prepare dishes or foods with relaxing properties. Conversely, if a user is in a mood to try something new, it can recommend recipes using ingredients different from what they usually use.

[0670] The generated meal suggestions are customized to reflect the user's emotional state and are displayed on the device. The device presents these suggested meal options to the user in a visually easy-to-understand format.

[0671] For example, suppose a user enters an address in "Minato Ward," and the system retrieves information that the ingredients for pasta at Supermarket D cost 400 yen and pizza at Restaurant E costs 600 yen. Furthermore, if the system determines that the user needs to relax, it can suggest a simple pasta recipe or pizza from Restaurant E served with tea. In this way, the present invention not only pursues cost efficiency but also provides meal options that are sensitive to the user's emotions.

[0672] The following describes the processing flow.

[0673] Step 1:

[0674] The user enters their location information on the device. The device prepares to receive this information and organizes the address data entered by the user.

[0675] Step 2:

[0676] The terminal sends address data to the server. The server receives this information and prepares to begin analysis.

[0677] Step 3:

[0678] The server collects price and promotional information for nearby grocery stores and restaurants from the internet. The server accesses a database to enable this.

[0679] Step 4:

[0680] The server uses artificial intelligence to analyze collected data and generate cost-effective meal plans. The server selects the optimal plan considering factors such as price, distance, and restaurant ratings.

[0681] Step 5:

[0682] Users input their current emotional state using an emotional interface via their device. Emotional input can be selected from options or automatically detected.

[0683] Step 6:

[0684] The device sends user emotion information to the server. The server receives this data and uses it to customize meal suggestions.

[0685] Step 7:

[0686] The server adjusts meal suggestions based on the user's emotional data. For example, if the server detects a desire to relax, it will recommend a plan that includes easy-to-prepare meals and foods with calming effects.

[0687] Step 8:

[0688] The server sends a customized meal plan to the device. The device receives this information and displays it in a visually easy-to-understand format on the user interface.

[0689] Step 9:

[0690] The system selects the optimal meal plan based on the information provided to the user. Users can consider suggestions tailored to their emotional state and decide on a plan based on their personal preferences and needs.

[0691] Step 10:

[0692] The system acts according to the plan selected by the user. For example, it can efficiently manage food expenses by going to the supermarket to purchase selected ingredients or visiting restaurants.

[0693] (Example 2)

[0694] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0695] Modern consumers seek optimal meal choices tailored to their individual economic circumstances and emotional states, while utilizing a wide range of options. However, current systems are limited to selections based on location and simple price information, making it difficult to provide personalized meal suggestions that incorporate emotional states. Against this backdrop, the challenge lies in providing meal suggestions that consider not only the user's economic efficiency but also their emotional satisfaction.

[0696] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0697] In this invention, the server includes means for inputting information related to the user's location, means for using an intelligent analysis device that collects information from a global information network, and means for analyzing the user's emotional state and personalizing meal suggestions generated based on that state. This enables the user to make meal choices that are both economically efficient and emotionally satisfying.

[0698] "Information related to the user's location" refers to data that indicates the user's current location or a specific region, obtained through location-based services, etc.

[0699] A "global information network" refers to a large-scale data source, including the internet, from which diverse information can be collected.

[0700] An "intelligent analysis device" is a system that uses artificial intelligence and machine learning algorithms to process data and obtain analysis results.

[0701] An "economically effective meal plan" is a meal proposal designed to maximize cost-effectiveness, offering a choice that balances the user's budget with quality.

[0702] "User emotional state" refers to data that indicates the psychological and emotional state a user is experiencing, and is analyzed from voice and facial expressions.

[0703] A "personalized meal plan" is a meal suggestion customized to individual needs and preferences, based on collected data and the user's emotional state.

[0704] "Methods using intelligent analytical devices" refer to the process of analyzing data and extracting useful information using artificial intelligence technology.

[0705] The system of this invention begins with the user inputting information related to their location. The user uses a terminal to input their address and GPS information and transmits this information to a server. Based on this, the server collects data on nearby grocery stores and restaurants using a global information network, such as various database services. In this process, it is possible to use the Google Maps API or other geographic information services.

[0706] The server analyzes the collected information using intelligent analysis equipment. Specifically, it uses a generative AI model (such as GPT-3 or a similar model) to generate cost-effective meal plans. During this process, the AI ​​is given instructions such as "Please list cost-effective ingredients from region X" as a prompt.

[0707] On the other hand, the device is equipped with means to analyze the user's emotional state. Users can either directly input their emotions or have their emotional state analyzed through a voice interface or camera. This operation utilizes emotion recognition libraries, such as Google Cloud's Vision API. The analyzed emotional information is sent to a server.

[0708] The server uses this emotional information to personalize pre-generated meal suggestions. Specifically, if a user is feeling stressed, it can suggest simple, relaxing meals.

[0709] Ultimately, the device visually presents these personalized meal suggestions to the user. The device's interface is designed using React Native and other popular development frameworks.

[0710] As a concrete example, a user enters the address of a specific city, and the server analyzes data on the location and price to suggest the most suitable meal. If the emotion engine determines that the user is seeking relaxation, it can suggest a meal paired with herbal tea. In this way, the system enables meal selection that takes both economic and emotional factors into consideration.

[0711] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0712] Step 1:

[0713] The user enters their current location information through the device's interface. This includes manual entry of an address or automatic acquisition using GPS functionality. The entered location information is sent from the device to the server. This information forms the basis for collecting the geographic data required in the next step.

[0714] Step 2:

[0715] The server collects data from the information network based on location information received from the user. Specifically, it uses geographic information services such as the Google Maps API to obtain information about food supply locations and restaurants. Based on this input information, it forms relevant datasets within the target area.

[0716] Step 3:

[0717] The server processes the collected data using an intelligent analysis device to generate cost-effective meal plans. This process utilizes a generative AI model, analyzing the user's location information and prompt statement, "List cost-effective ingredients in area X." As a result, meal plans that minimize costs while ensuring high satisfaction are generated.

[0718] Step 4:

[0719] The user inputs their emotional state into the device, or uses a voice interface or camera to analyze their emotions. The device then collects emotional data using an emotion recognition library. The collected emotional information is sent to a server.

[0720] Step 5:

[0721] The server uses the received emotional information to personalize meal suggestions. In this process, it analyzes emotional data and combines ingredients and menu items that are appropriate for the user's emotional state. For example, it suggests foods with relaxing effects to a user seeking relaxation.

[0722] Step 6:

[0723] The terminal visually presents personalized meal suggestions received from the server to the user. The displayed interface is designed with frameworks such as React Native, presenting information in a way that is easy for the user to understand. This allows the user to make meal choices that are both economically and emotionally satisfying.

[0724] (Application Example 2)

[0725] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0726] In daily life, users sometimes find it difficult to choose meals that are appropriate for their emotional state and location. Finding a suitable meal quickly is particularly challenging when stressed or in need of relaxation. Therefore, there is a need for a system that automatically receives and allows users to select the optimal meal based on their emotional state.

[0727] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0728] In this invention, the server includes means for inputting the user's location information, means for using artificial intelligence to collect information from the internet, and means for recognizing and acquiring the user's emotional state. This makes it possible to provide a cost-effective meal plan that is personalized according to the user's current emotional state.

[0729] "Means for inputting user location information" refers to a device or software that acquires data to determine the user's current location.

[0730] "Methods using artificial intelligence to collect information from the internet" refers to processes that utilize artificial intelligence technology to collect and analyze data on food products and dining facilities via the internet.

[0731] "A method for generating cost-effective meal plans" refers to an algorithm that, based on collected data, considers cost and convenience to propose the optimal meal plan to the user.

[0732] "Means for recognizing and acquiring a user's emotional state" refers to technology that analyzes the user's facial expressions, voice, and operation data, and estimates and digitizes their emotions.

[0733] "Means of displaying or presenting personalized meal suggestions visually or audibly" refers to a system that visually displays customized meal suggestions on a screen, tailored to the user's emotional state, or provides audible guidance through an audio output device.

[0734] The system that realizes this invention utilizes a user terminal, a server, and artificial intelligence technology. First, the user inputs location information via the terminal. This information is acquired using a GPS module and transmitted from the terminal to the server. Based on the acquired location information, the server collects information on grocery stores and restaurants on the internet. Web scraping technology and artificial intelligence are used to access the database for this collection.

[0735] Next, the server analyzes the collected information using the AI ​​model "PyTorch" to generate cost-effective meal suggestions. Furthermore, the user's emotional state is analyzed by emotion recognition software "Emotion AI" via the terminal's camera and microphone, and this information is sent to the server. Based on this emotional information, the meal suggestions are personalized. The personalized meal suggestions are displayed visually or audibly on the user's interface. GUI software is used for visual display, and a speech synthesis library is used for audio output.

[0736] For example, if a user is relaxing at home and wants meal suggestions, the device sends a prompt saying, "I want a relaxing meal." The server analyzes the location to find the nearest restaurants, generates suggestions such as dishes containing healing herbs, and sends the results back to the device.

[0737] Example of a prompt:

[0738] "Please suggest some relaxing dining options in Minato Ward. Our users are experiencing some stress."

[0739] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0740] Step 1:

[0741] The user inputs location information via their device. This input consists of data from a GPS module indicating the user's current location. The device then transmits this location information to the server.

[0742] Step 2:

[0743] The server collects data on grocery store locations and restaurants from the internet based on the received location information. This data collection uses web scraping techniques to extract necessary information from databases containing food prices and menu information. The output is detailed regional data.

[0744] Step 3:

[0745] The server analyzes the collected data using the AI ​​model "PyTorch" to generate cost-effective meal plans. Here, location data collected as input is used to process the data and select the optimal ingredient purchase options and dining menus. The output is the generated meal plan.

[0746] Step 4:

[0747] The user activates the emotion recognition function on their device. This function uses "Emotion AI" to analyze data collected through the camera and microphone to identify the user's emotional state. The input consists of facial expressions and voice data, and the output is the user's emotional state.

[0748] Step 5:

[0749] The server collects the user's emotional information and personalizes the previously generated meal plan according to that emotion. Using the emotional data, it customizes the meal plan by incorporating ingredients and cooking methods that promote relaxation. The output is the personalized meal plan.

[0750] Step 6:

[0751] The terminal presents personalized meal suggestions to the user visually or audibly. GUI software is used to provide visual explanations on the display, and a text-to-speech library reads the instructions aloud. The user then uses this information to make the optimal meal choice.

[0752] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0753] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0754] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0755] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0756] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0757] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0758] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0759] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0760] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0761] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0762] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0763] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0764] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0765] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0766] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0767] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0768] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0769] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0770] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0771] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0772] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0773] The following is further disclosed regarding the embodiments described above.

[0774] (Claim 1)

[0775] A means of inputting the user's location information,

[0776] Methods that use artificial intelligence to collect information from the internet,

[0777] A means for analyzing the collected information to generate cost-effective meal plans,

[0778] A means for displaying the generated meal plan to the user,

[0779] A system that includes this.

[0780] (Claim 2)

[0781] The system according to claim 1, further comprising means for collecting the aforementioned information from the Internet from a database including price information of food sales locations and campaign information of food and beverage establishments.

[0782] (Claim 3)

[0783] The system according to claim 1, wherein the generated meal plan includes a list of ingredients for the dish, their purchase locations, and menu information for a dining establishment.

[0784] "Example 1"

[0785] (Claim 1)

[0786] A means for inputting location information based on the user's place of residence or current location,

[0787] A means of using an information processing device that collects public and commercial data on the internet,

[0788] A means for analyzing the collected data and generating cost-effective consumption plans using a generation AI model,

[0789] A means for displaying the generated consumption plan on the terminal screen,

[0790] A system that includes this.

[0791] (Claim 2)

[0792] The system according to claim 1, wherein the information processing device includes means for collecting information from a set of information including price data of food sales locations on the internet and promotional campaign data of food service locations.

[0793] (Claim 3)

[0794] The system according to claim 1, wherein the generated consumption plan includes a list of production materials and information on where they can be obtained, as well as menu suggestions for a meal service location.

[0795] "Application Example 1"

[0796] (Claim 1)

[0797] A means of entering the user's location information,

[0798] A means of using intelligent processing to collect data from the internet,

[0799] A means for analyzing the collected data and generating a cost-effective dining plan,

[0800] A means for presenting the generated dining plan to the user,

[0801] Based on the analyzed information, a means for completing the order,

[0802] A system that includes this.

[0803] (Claim 2)

[0804] The system according to claim 1, further comprising means for collecting the aforementioned data from the Internet from a dataset including price data of food sales locations and discount information of restaurants.

[0805] (Claim 3)

[0806] The system according to claim 1, wherein the generated dining plan includes a list of ingredients, their acquisition locations, and food information at the dining establishment.

[0807] "Example 2 of combining an emotion engine"

[0808] (Claim 1)

[0809] A means of inputting information related to the user's location,

[0810] A means of using an intelligent analytical device that collects information from a global information network,

[0811] A means for analyzing the collected information to generate a meal plan with high economic effectiveness,

[0812] A means of analyzing the user's emotional state,

[0813] A means for individualizing the meal plan generated based on the aforementioned emotional state,

[0814] Means for displaying the personalized meal plan to the user,

[0815] A system that includes this.

[0816] (Claim 2)

[0817] The system according to claim 1, comprising means for collecting information on the global information network from a medium including price information of food supply locations and special information of food and beverage establishments.

[0818] (Claim 3)

[0819] The system according to claim 1, wherein the personalized meal plan includes a catalog of cooking ingredients and their source, and information on their provision at a dining facility.

[0820] "Application example 2 of combining emotional engines"

[0821] (Claim 1)

[0822] A means of inputting the user's location information,

[0823] Methods that use artificial intelligence to collect information from the internet,

[0824] A means for analyzing the collected information to generate cost-effective meal plans,

[0825] Means for recognizing and acquiring the user's emotional state,

[0826] A means for personalizing meal suggestions based on the user's emotional information,

[0827] Means for displaying or presenting the personalized meal plan to the user visually or audibly,

[0828] A system that includes this.

[0829] (Claim 2)

[0830] The system according to claim 1, further comprising means for collecting the aforementioned information from the Internet from a database including price information of food sales locations and campaign information of food and beverage establishments, and for using emotion analysis software to analyze the emotions of the user.

[0831] (Claim 3)

[0832] The system according to claim 1, wherein the personalized meal plan includes a list of ingredients for the dish, their purchase locations, and menu information for dining establishments, and further provides recommendation information tailored to the user's emotional state. [Explanation of Symbols]

[0833] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of inputting the user's location information, Methods that use artificial intelligence to collect information from the internet, A means for analyzing the collected information to generate cost-effective meal plans, A means for displaying the generated meal plan to the user, A system that includes this.

2. The system according to claim 1, further comprising means for collecting the aforementioned information from the Internet from a database including price information of food sales locations and campaign information of food and beverage establishments.

3. The system according to claim 1, wherein the generated meal plan includes a list of ingredients for the dish, their purchase locations, and menu information for a dining establishment.

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