System

Abstract

A system is provided.SOLUTION: The system includes a means for inputting parameters such as a starting point, a moving means, a departure time, a budget, a required time, the number of going-out persons, calorie consumption, and the desired number of steps from a user, a means for receiving and analyzing the inputted parameters, a means for generating a plan considering health consciousness by using a generation AI based on the analyzed parameters, a means for transmitting the generated plan, and a means for allowing the user to select and confirm the generated plan.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Traditionally, planning a holiday outing often required a lot of time and effort, and it was difficult to find innovative ideas. Furthermore, creating a plan that reflected modern health trends was even more difficult. To solve this problem, a system that provides efficient and health-conscious outing plans is needed. [Means for solving the problem]

[0005] This invention provides a means for the user to input parameters such as the departure point, mode of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc., and includes a means for receiving and analyzing the input data. It also includes a means for generating an outing plan that takes health-consciousness into consideration using a generation AI based on the analyzed data, and a means for sending the generated outing plan to the user's terminal. Furthermore, by providing a means for the user to select and confirm the generated outing plan, a system is realized that allows users to easily create efficient and health-conscious outing plans.

[0006] A "user" refers to a person who uses the system to create an outing plan.

[0007] The "starting point" refers to a point designated by the user as the starting point of the outing plan.

[0008] "Transportation" refers to the means of transportation or travel method used by the user while carrying out the outing plan.

[0009] "Departure time" refers to the time when the user plans to start going out.

[0010] The "budget" refers to the upper limit of expenses that the user plans to spend on the outing plan.

[0011] "Duration" refers to the total time the user plans to spend out.

[0012] "Number of people going out" refers to the number of people accompanying you on an outing.

[0013] "Calories burned" refers to the target amount of calories that the user will burn during the outing plan.

[0014] The "desired number of steps" refers to the target number of steps that the user plans to walk during the outing plan.

[0015] "Input means" refers to the interface or method by which a user inputs parameters into the system.

[0016] "Means for receiving" refers to a mechanism or method by which the server receives user input data sent from the terminal.

[0017] "Means for analysis" refers to the algorithms and functions for analyzing the received data and extracting the information necessary to generate an appropriate outing plan.

[0018] "Generative AI" refers to artificial intelligence technology that automatically generates outing plans based on received and analyzed data.

[0019] "Means of generation" refers to the process or method of using generation AI to create an outing plan that meets the user's requests.

[0020] "Terminal" refers to a device (e.g., smartphone, PC) through which a user accesses the system and enters and confirms plans.

[0021] "Transmission means" refers to a communication method or protocol for transmitting the generated outing plan from the server to the user's terminal.

[0022] "Means for selection" refers to the interface or method by which a user selects one of the plans presented.

[0023] The "means for determining" refers to the process or method by which the user's selected plan is finally determined and recorded by the server. [Brief explanation of the drawings]

[0024] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0025] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0026] First, the terms used in the following description will be explained.

[0027] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0028] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0029] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0030] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0031] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0032] [First embodiment]

[0033] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0034] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0035] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0036] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0037] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0038] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0039] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0040] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0041] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0042] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0043] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0044] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0045] The present invention provides a system for enabling people to enjoy going out on holidays efficiently and in a health-conscious manner. Specific embodiments of this system will be described below.

[0046] Overall system configuration

[0047] The system mainly consists of the following components:

[0048] 1. User's device (e.g. smartphone or PC)

[0049] 2. Server

[0050] 3. Generation AI

[0051] 4. Database

[0052] User operations

[0053] A user first accesses the system using a dedicated application or website and logs in.

[0054] The user inputs parameters related to the outing plan (starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.).

[0055] Sending and Receiving Data

[0056] The terminal converts all parameters entered by the user into JSON format and sends them to the server using the stable and secure HTTPS protocol.

[0057] The server receives this data and prepares it for analysis.

[0058] Data analysis and generation using AI

[0059] The server temporarily stores the received data and analyzes each parameter using an analysis algorithm.

[0060] The analyzed data is passed to the generation AI, which then generates an outing plan that best suits the user's needs.

[0061] The AI ​​takes into account the user's specified calorie consumption and desired number of steps, and compares it with past data when generating a health-oriented plan to provide a highly accurate plan.

[0062] Generate and send trip plans

[0063] The AI ​​generates multiple outing plans, each of which includes destinations, activities, how to use public transportation, estimated calories burned, estimated number of steps, etc.

[0064] The server sends the generated plans to the user's device in JSON format.

[0065] User plan selection and confirmation

[0066] The user checks the multiple plans presented on the terminal and selects the most suitable one from among them.

[0067] Once the selection is confirmed, the server stores the user's selection in a database and sends a confirmation to the user's device.

[0068] Specific examples

[0069] For example:

[0070] User A plans to go out on a holiday and logs in to the dedicated app. Next, he enters the following parameters:

[0071] Starting point: Tokyo Station

[0072] Transportation: Train and walking

[0073] Departure time: 10:00 AM

[0074] Budget: 5,000 yen

[0075] Duration: 5 hours

[0076] Number of people going out: 2

[0077] Calories burned: 300 calories

[0078] Desired number of steps: 8,000 steps

[0079] The device sends this information to the server, which receives it and analyzes it. The analysis results are passed to the generation AI, which then generates a plan like this:

[0080] Plan A: Visit to Ueno Zoo + Shopping in Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps)

[0081] Plan B: Visit Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps)

[0082] These plans are sent to the user's terminal, and User A selects and confirms Plan A. The server stores this selection information in the database and sends a confirmation notice to User A.

[0083] In this way, the user can easily obtain an outing plan that incorporates health-conscious ideas.

[0084] The processing flow will be explained below.

[0085] Step 1:

[0086] The user accesses a dedicated application or website and logs in. The user inputs parameters such as the departure point, transportation method, departure time, budget, required time, number of people going out, calories burned, and desired number of steps.

[0087] Step 2:

[0088] The terminal converts the data entered by the user into JSON format, which contains all the user's parameters.

[0089] Step 3:

[0090] The terminal sends the converted data to the server using the HTTPS protocol, which ensures secure transmission of the data.

[0091] Step 4:

[0092] The server receives the data received from the device and prepares it for analysis, converting it into an appropriate format and passing it to the analysis algorithm.

[0093] Step 5:

[0094] The server analyzes the received data using an analysis algorithm and prepares to pass the analysis results to the generation AI.

[0095] Step 6:

[0096] The AI ​​then generates an optimal outing plan based on the analyzed data, taking into account the user's desired calorie consumption and number of steps.

[0097] Step 7:

[0098] The AI ​​generates multiple different outing plans, each of which includes details such as destinations, activities, how to use public transport, estimated calories burned, and estimated number of steps.

[0099] Step 8:

[0100] The server sends multiple candidates for the generated outing plan to the user's device in JSON format.

[0101] Step 9:

[0102] The terminal displays the received outing plans on the user interface, and the user can check the plans and select the one they want.

[0103] Step 10:

[0104] The plan selected by the user is sent from the device to the server, and the selection is confirmed.

[0105] Step 11:

[0106] The server saves the user's selection in a database, confirming that the selection has been finalized.

[0107] Step 12:

[0108] The server sends a confirmation of the selection to the user's device, and the process is completed when the user receives and confirms the notification.

[0109] Example 1

[0110] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0111] Nowadays, many people are looking for ways to efficiently enjoy their holidays while maintaining their health. However, there is a lack of specific systems and methods to meet this demand. In addition, when users create their own outing plans that take health-consciousness into consideration, it takes a lot of time and effort. As a result, many people are unable to create appropriate outing plans, making it difficult to spend their holidays in a healthy manner.

[0112] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0113] In this invention, the server includes means for inputting parameters such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc. from the user, means for converting the input data into JSON format and sending it to the server using the HTTPS protocol, means for saving the received JSON format data and analyzing it using an analysis algorithm, means for sending the analysis results to the generation AI as prompt text, which generates multiple outing plans based on the user's requirements, means for sending the generated outing plans to the user's terminal in JSON format, and means for the user to select a presented plan and store the selected information in a database. This allows the user to easily obtain outing plans that incorporate health-conscious ideas.

[0114] "User" refers to an individual or organization who uses the system and creates outing plans through this system.

[0115] A "terminal" is a device used by a user to access the system, including a smartphone, PC, tablet, etc.

[0116] The "server" is a central computer that manages and controls the entire system, and is responsible for receiving and analyzing data sent by users and coordinating with the generating AI.

[0117] "Generative AI" is a type of artificial intelligence that refers to algorithms or models that generate optimal outing plans based on input data.

[0118] "Database" refers to an information storage device for efficiently storing and managing user input information, generated outing plans, selection information, etc.

[0119] "Parameters" are items of information that a user inputs into the system, such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.

[0120] The "HTTPS protocol" is a network communication protocol used when a user sends data from a device to a server, and is responsible for ensuring the secure transmission and reception of data.

[0121] The "JSON format" is a standard format for describing data in text format, and is used to efficiently send user input information to a server.

[0122] "Analysis algorithm" refers to a program with calculation procedures for analyzing data received by the server, and performs initial data processing to meet user requirements.

[0123] A "prompt sentence" is a command sentence used to send a specific generation request to the generation AI, and includes instructions that reflect the user's requirements.

[0124] An "outing plan" is an outing plan proposed by the generation AI based on the user's requirements, and includes details such as destinations, activities, how to use public transportation, planned calories burned, and planned number of steps.

[0125] "Data archiving" refers to the process by which the server temporarily or permanently stores the data it receives on a storage device.

[0126] "Data transmission" refers to the process of transferring data from a user's terminal to a server or from a server to a user's terminal.

[0127] "Calories burned" refers to the amount of energy consumed by the user while executing the going out plan.

[0128] The "desired number of steps" refers to the number of steps that the user wishes to walk while executing the outing plan.

[0129] The present invention provides a system that allows users to enjoy their holidays efficiently and with a focus on health. This system utilizes generation AI based on user input to generate optimal outing plans. Specific embodiments of this system are described below.

[0130] Overall system configuration

[0131] The system mainly consists of the following components:

[0132] 1. User's device (e.g., smartphone or personal computer)

[0133] 2. Server

[0134] 3. Generation AI

[0135] 4. Database

[0136] User operations

[0137] Users access a dedicated application or website, log in with their authentication information, and then enter parameters such as starting point, mode of transportation, departure time, budget, travel time, number of people going out, calories burned, and desired number of steps.

[0138] After the user enters various parameters, the information is converted into JSON format by the terminal and sent to the server using the HTTPS protocol. It is worth noting that this system uses secure data encryption, which is an important specification for protecting user privacy.

[0139] Server Processing

[0140] The server receives the JSON-formatted data sent from the device and temporarily stores it. Next, it analyzes each parameter using an analysis algorithm. This analysis is generally performed using Python libraries such as Pandas and NumPy.

[0141] The analysis results are sent to the generation AI as a prompt. For example, we generate a prompt that instructs the AI ​​to generate a plan departing from Tokyo Station, with a budget of 5,000 yen, consuming 300 calories, and requiring no more than 8,000 steps. This prompt looks like this:

[0142] Users are asked to create a plan to travel from Tokyo Station by train and on foot, with a budget of 5,000 yen, 300 calories burned, and a desired number of steps of 8,000 or less.

[0143] Processing of generated AI

[0144] The generation AI generates multiple outing plans based on the given prompt. The generation AI takes into account past data and the user's history to generate the optimal plan for the user. As a concrete example, the following plans are generated:

[0145] Plan A: Visit to Ueno Zoo + Shopping in Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps)

[0146] Plan B: Visit Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps)

[0147] These generated plans are converted back to JSON format and sent to the server, which then sends the generated plans to the user's device.

[0148] User plan selection

[0149] The user checks the multiple plans presented on the terminal and selects the most suitable one. Once the selection is confirmed, the server saves the selection information in a database and sends a confirmation notice to the user's terminal. When the user receives this confirmation notice, they know that the plan has been confirmed.

[0150] In this way, users can easily obtain outing plans that incorporate health-conscious ideas. This system enables users to enjoy their holidays efficiently and healthily.

[0151] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0152] Step 1: User parameter input

[0153] The user accesses a dedicated application or website and inputs parameters such as the starting point, mode of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc. The input parameters are sent to the terminal. Specifically, the user enters the required information into the form and presses the "Submit" button.

[0154] Input: Departure point, transportation method, departure time, budget, required time, number of people going out, calories burned, desired number of steps

[0155] Output: Parameter data in JSON format

[0156] Step 2: Sending data

[0157] The terminal converts the input parameters into JSON format and sends them to the server using the HTTPS protocol. Specifically, the terminal sends a POST request to the endpoint, and the data is encrypted and sent.

[0158] Input: Parameter data in JSON format

[0159] Output: Data sent to the server

[0160] Step 3: Receiving and storing data

[0161] The server receives the JSON format data sent from the device and temporarily stores it in a database. The received data is stored as is, but is prepared for later analysis.

[0162] Input: Parameter data sent in JSON format

[0163] Output: Parameter data stored in the database

[0164] Step 4: Analyze the data

[0165] The server analyzes the stored data using Python libraries such as Pandas and NumPy, converting each parameter into an appropriate format. Specific operations include reading the data, extracting necessary fields, and cleaning the data.

[0166] Input: Parameter data stored in the database

[0167] Output: Parsed parameter data

[0168] Step 5: Sending prompts to the generation AI

[0169] The server generates a prompt based on the analyzed data and sends it to the generation AI. Prompt generation involves converting the user's input data into an appropriate context. For example, a prompt might be created such as, "The user should create a plan departing from Tokyo Station, with a budget of 5,000 yen, consuming 300 calories, and requiring no more than 8,000 steps."

[0170] Input: Parsed parameter data

[0171] Output: The prompt sent to the generation AI

[0172] Step 6: Generate your trip plan

[0173] The generation AI generates an outing plan based on the prompt text. The generation AI references past data and user history to generate multiple plans. The generated plan includes specific destinations and activities, how to use public transportation, estimated calories burned, and estimated number of steps. Specifically, the generation AI model makes optimal suggestions based on the input prompt.

[0174] Input: Prompt sent to the generation AI

[0175] Output: Generated itinerary

[0176] Step 7: Submit your trip plan

[0177] The server converts the outing plan received from the generation AI into JSON format and sends it to the user's device. Specifically, the server receives the output of the generation AI and sends the data to the user's device through an endpoint.

[0178] Input: Generated trip plan

[0179] Output: Trip plan sent to the user's device in JSON format

[0180] Step 8: User Plan Selection

[0181] The user checks the multiple outing plans presented on the device and selects the most suitable one. Specifically, the user checks the details of each plan and clicks the "Select" button.

[0182] Input: Trip plan sent in JSON format

[0183] Output: Selected outing plan

[0184] Step 9: Save your selections and receive confirmation

[0185] The server stores the information of the outing plan selected by the user in a database and sends a confirmation notice to the user's terminal, specifically, by recording the selection information in the database and generating a confirmation message to send to the user's terminal.

[0186] Input: Selected outing plan

[0187] Output: Selection information stored in the database, confirmation sent to the user's device

[0188] (Application example 1)

[0189] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0190] Conventional outing plan generation systems provide outing plans that take health into consideration, but do not suggest meal plans for users. A plan that supports health-conscious outings, including the contents of meals eaten while out, is needed. Furthermore, to achieve comprehensive health management, there is a need for meal plans that are linked to outing plans.

[0191] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0192] In this invention, the server includes means for inputting parameters such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, type of meal, budget, calories per meal, etc. from the user, means for receiving and analyzing the input data, and means for generating an outing plan and meal plan that takes health into consideration using a generation AI based on the analyzed data. This allows the user to ensure consistency in not only the activities they do while out, but also their meal plan, taking health into consideration.

[0193] The "starting point" refers to the point where the user starts going out.

[0194] "Transportation" refers to the means of transportation used to travel from a departure point to a destination.

[0195] "Departure time" refers to the specific time when the user starts going out.

[0196] "Budget" refers to the amount of money planned to be spent on outings and related activities.

[0197] "Time required" refers to the length of time required for the entire outdoor activity.

[0198] "Number of people going out" refers to the number of people who participate in outdoor activities.

[0199] "Calories burned" refers to the amount of energy consumed during outdoor activities.

[0200] The "desired number of steps" refers to the number of steps that are expected to be taken during outdoor activities.

[0201] "Meal type" refers to the type of meal the user desires (e.g., breakfast, lunch, dinner, etc.).

[0202] "Generative AI" refers to artificial intelligence that automatically generates appropriate outing and meal plans based on user input data.

[0203] "Determining a plan" refers to the act of the user selecting the most suitable plan from the proposed plans and making a final decision.

[0204] A specific system and method for implementing the present invention will now be described.

[0205] System Configuration

[0206] The system consists of the following components:

[0207] 1. User's device (smartphone, PC)

[0208] 2. Server

[0209] 3. Generative AI Models

[0210] 4. Database

[0211] User operations

[0212] The user first logs in to a dedicated application or website, then enters the following parameters:

[0213] Departure Point

[0214] Transportation

[0215] Departure time

[0216] budget

[0217] Travel time

[0218] Number of people going out

[0219] Calories burned

[0220] Desired number of steps

[0221] Type of meal (e.g. breakfast, lunch, dinner)

[0222] Budget per meal

[0223] Calories per serving

[0224] Sending and Receiving Data

[0225] The user's device converts the input data into JSON format and sends it to the server using the HTTPS protocol. The server then analyzes the received data and prepares it for passing to the generative AI model.

[0226] Analyzing data and using generative AI models

[0227] The server runs the received data through an analysis algorithm and prepares the data to be passed to the generative AI model, which then generates optimal outing and meal plans based on the user's requests.The generative AI model also references past data to improve accuracy.

[0228] Generate and submit a plan

[0229] The generative AI model generates an outing plan and a meal plan, each containing the following information:

[0230] Destinations

[0231] activity

[0232] means of transportation

[0233] Estimated calorie consumption

[0234] Planned steps

[0235] Meal contents

[0236] Dining

[0237] Calorie and food budget

[0238] The server sends the generated plan in JSON format to the user's device.

[0239] User plan selection and confirmation

[0240] The user checks the displayed plans and selects the most suitable one. After selection, the server saves the selection information in the database and sends a confirmation notice to the user's device.

[0241] Specific examples

[0242] User A plans to go out and have lunch on a day off and enters the following parameters:

[0243] Starting point: Shibuya Ward

[0244] Transportation: Train and walking

[0245] Departure time: 10:00 AM

[0246] Budget: 8,000 yen

[0247] Duration: 6 hours

[0248] Number of people going out: 2

[0249] Calories burned: 500 calories

[0250] Desired number of steps: 10,000 steps

[0251] Meal type: Lunch

[0252] Budget per meal: 1,500 yen

[0253] Calories per serving: 600 calories

[0254] Based on the information sent to the server, the generative AI model analyzes and provides the following plan:

[0255] Plan A: Walk + Museum Visit + Healthy Lunch (Estimated calories burned: 520 calories, Estimated steps: 9,500 steps, Estimated calories for lunch: 580 calories)

[0256] Plan B: Walk in the park + Shopping + Low-calorie restaurant lunch (Estimated calories burned: 480 calories, Estimated steps: 10,500 steps, Estimated calories for lunch: 590 calories)

[0257] User A selects Plan A, and the server saves the selection in the database and sends a confirmation.

[0258] Main hardware and software used

[0259] Hardware: Web server (e.g. AWS EC2)

[0260] Software: Flask (Python library), HTTP protocol, generative AI (via API)

[0261] Prompt Sentence Examples

[0262] "Please suggest a healthy meal plan for location: Shibuya Ward, type: lunch, budget: 1500 yen, calories: 600 kcal."

[0263] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0264] Step 1:

[0265] The user logs in to a dedicated application or website and enters the following parameters: starting point, transportation method, departure time, budget, required time, number of people going out, calories burned, desired number of steps, type of meal, budget per meal, and calories per meal. This data is entered into the user's device and converted into JSON format.

[0266] Step 2:

[0267] The user's device sends the data converted into JSON format to the server using the HTTPS protocol, where it is encrypted to ensure security.

[0268] Step 3:

[0269] The server receives the data sent from the user's device, analyzes it using an analysis algorithm, and prepares it for passing to the generative AI model. Specifically, it checks the data for consistency and whether there is any missing information or data in the wrong format.

[0270] Step 4:

[0271] The server inputs the analyzed data into a generative AI model, which generates prompts and then generates health-conscious outing and meal plans based on the prompts.

[0272] Example: "Please suggest a healthy meal plan for location: Shibuya Ward, type: lunch, budget: 1500 yen, calories: 600 kcal."

[0273] Step 5:

[0274] The generative AI model generates multiple plans based on the input prompts. The generated outing and meal plans include destinations, activities, transportation, estimated calories burned, estimated steps, meal contents, meal locations, estimated calories for each meal, and budget.

[0275] Step 6:

[0276] The server sends multiple plans generated by the generative AI model to the user's device, where the plans are sent in JSON format and displayed on the user's device.

[0277] Step 7:

[0278] The user checks the multiple plans presented on the terminal and selects the most suitable one. Once the selection is confirmed, the information is sent from the user's terminal to the server.

[0279] Step 8:

[0280] The server stores the user's selected plan in a database and sends a confirmation notice to the user's terminal, so that the user can go out and eat according to the plan.

[0281] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0282] The present invention provides a system for planning a holiday outing that takes into account the user's emotions and allows the user to enjoy an efficient and health-conscious lifestyle. Specific embodiments of this system will be described below.

[0283] Overall system configuration

[0284] The system mainly consists of the following components:

[0285] 1. User's device (e.g. smartphone or PC)

[0286] 2. Server

[0287] 3. Generation AI

[0288] 4. Emotion Engine

[0289] 5. Database

[0290] User operations

[0291] A user first accesses the system using a dedicated application or website and logs in.

[0292] The user inputs parameters related to the outing plan (starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.).

[0293] Using the Emotion Engine

[0294] The emotion engine uses a camera and microphone to analyze facial expressions and voice while the user is typing, recognizing the user's emotional state.

[0295] Emotion data is captured in real time to assist the user in the input process.

[0296] Sending and Receiving Data

[0297] The terminal converts the data and emotion data entered by the user into JSON format and sends it to the server using the HTTPS protocol.

[0298] The server receives this data and prepares it for analysis.

[0299] Data analysis and generation using AI

[0300] The server temporarily stores the received data and analyzes each parameter and emotion data using an analysis algorithm.

[0301] The analyzed data is passed to the generation AI, which then generates an outing plan that best suits the user's needs and emotional state.

[0302] The AI ​​takes into account the user's specified calorie consumption, desired number of steps, and emotional state, and compares it with past data to generate a health-oriented plan, providing a highly accurate plan.

[0303] Generate and send trip plans

[0304] The AI ​​generates multiple outing plans, each of which includes destinations, activities, how to use public transportation, estimated calories burned, estimated number of steps, and content appropriate to the user's emotional state.

[0305] The server sends the generated plans to the user's device in JSON format.

[0306] User plan selection and confirmation

[0307] The user checks the multiple plans presented on the terminal and selects the most suitable one from among them.

[0308] Once the selection is confirmed, the server stores the user's selection in a database and sends a confirmation to the user's device.

[0309] Specific examples

[0310] For example:

[0311] User A plans to go out on a holiday and logs in to the dedicated app. Next, he enters the following parameters:

[0312] Starting point: Tokyo Station

[0313] Transportation: Train and walking

[0314] Departure time: 10:00 AM

[0315] Budget: 5,000 yen

[0316] Duration: 5 hours

[0317] Number of people going out: 2

[0318] Calories burned: 300 calories

[0319] Desired number of steps: 8,000 steps

[0320] While inputting, the emotion engine analyzes User A's facial expressions and voice and recognizes their current emotional state as "enjoyment." The device sends this information to the server, which receives the information and analyzes it. The analysis results and emotion data are passed to the generation AI, which generates the following plan:

[0321] Plan A: Visit to Ueno Zoo + Shopping at Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps, Reason for suggestion: Matches the emotion of enjoyment)

[0322] Plan B: Visit to Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps, Reason for suggestion: Matches the emotion of enjoyment)

[0323] These plans are sent to the user's terminal, and User A selects and confirms Plan A. The server stores this selection information in the database and sends a confirmation notice to User A.

[0324] In this way, the user can easily obtain an outing plan that incorporates health consciousness and emotional state.

[0325] The processing flow will be explained below.

[0326] Step 1:

[0327] The user accesses a dedicated application or website and logs in. The user inputs parameters such as the departure point, transportation method, departure time, budget, required time, number of people going out, calories burned, and desired number of steps.

[0328] Step 2:

[0329] The emotion engine uses the user's camera and microphone to analyze facial expressions and voice to recognize the user's emotional state in real time, detecting emotions such as joy, sadness, and fun.

[0330] Step 3:

[0331] The device converts all data and emotion data entered by the user into JSON format, which includes all the user's parameters.

[0332] Step 4:

[0333] The terminal sends the converted data to the server using the HTTPS protocol, which ensures secure transmission of the data.

[0334] Step 5:

[0335] The server receives the data received from the device and prepares it for analysis, converting it into an appropriate format and passing it to the analysis algorithm.

[0336] Step 6:

[0337] The server uses an analysis algorithm to analyze the received data and emotional data, for example, matching the user's input parameters with their emotional state.

[0338] Step 7:

[0339] The server passes the analysis results to the generation AI, which prepares to generate the optimal outing plan based on the user's requests and emotional state.

[0340] Step 8:

[0341] The AI ​​generates multiple outing plans based on the user's calorie consumption, desired number of steps, and emotional state. Each plan includes destinations, activities, how to use public transportation, planned calorie consumption, planned number of steps, and content appropriate for the user's emotional state.

[0342] Step 9:

[0343] The server sends multiple candidates for the generated outing plan to the user's device in JSON format.

[0344] Step 10:

[0345] The terminal displays the received outing plans on the user interface, and the user can check the plans and select the one they want.

[0346] Step 11:

[0347] The plan selected by the user is sent from the device to the server, and the selection is confirmed.

[0348] Step 12:

[0349] The server saves the user's selection in a database, confirming that the selection has been finalized.

[0350] Step 13:

[0351] The server sends a confirmation of the selection to the user's device, and the process is completed when the user receives and confirms the notification.

[0352] Example 2

[0353] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0354] Conventional outing plan creation systems have difficulty providing plans that fully consider the user's emotional state and health preferences. Furthermore, they have been unable to meet modern user needs, such as secure transmission of user input data and evaluation of exercise volume. As a result, they often provide plans that are unsatisfactory for users.

[0355] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting parameters such as a starting point, a means of transportation, a departure time, a budget, a required time, the number of accompanying persons, calories burned, and a desired number of steps from a user; means for analyzing the user's facial expressions and voice using a camera and a microphone to collect emotional data; means for receiving the input data and emotional data, converting it into JSON format, and transmitting it to the server; means for storing the received data in the server and analyzing it using an analytical algorithm; means for using a generation AI based on the analyzed data to generate a health-oriented outing plan that is optimal for the user's requests and emotional state; means for transmitting the generated outing plan to the user's terminal; and means for the user to select the generated outing plan and store the selected information in a database. This makes it possible to provide an outing plan that takes into account the user's emotional state and health-orientedness.

[0356] "User" refers to an individual who uses the system to create an outing plan.

[0357] A "terminal" refers to an electronic device used by a user to manipulate input data, such as a smartphone or a personal computer.

[0358] "Server" refers to the computer system that receives and stores data sent by users, analyzes it, and generates plans.

[0359] "Database" refers to a system for storing user inputs and selections.

[0360] "Generative AI" refers to artificial intelligence that generates optimal outing plans based on the user's requests and emotional state.

[0361] An "emotion engine" refers to software that analyzes a user's facial expressions and voice to collect emotional data.

[0362] The "starting point" refers to the starting point of the user's outing plan.

[0363] "Transportation" refers to the means of transportation used by the user when going out.

[0364] "Departure time" refers to the time when the user starts going out.

[0365] The "budget" refers to the amount of money that a user can spend when going out.

[0366] "Time required" refers to the time the user plans to spend going out.

[0367] "Number of people accompanying" refers to the number of other people who go out with the user.

[0368] "Calories burned" refers to the amount of calories the user plans to burn while out.

[0369] The "desired number of steps" refers to the number of steps that the user wishes to achieve while out and about.

[0370] "Emotion data" refers to data that indicates the user's emotional state, obtained as a result of the emotion engine's analysis of the user's facial expressions and voice.

[0371] "JSON format" refers to a lightweight data interchange format that is widely used to send and receive data.

[0372] "Analysis Algorithm" refers to the computational method used by the Server to analyze Data.

[0373] A "health-oriented outing plan" refers to an outing plan that takes into consideration the user's health, and includes a plan that takes into consideration the amount of exercise, such as calories burned and number of steps.

[0374] The present invention provides a system that provides an outing plan that takes into account the user's emotional state and health preferences. The system is composed of the following elements:

[0375] 1. User's device (e.g. smartphone or PC)

[0376] 2. Server

[0377] 3. Generative AI (e.g. OpenAI GPT-3)

[0378] 4. Emotion engine (e.g. Affectiva SDK)

[0379] 5. Database (e.g. MySQL)

[0380] User operations

[0381] A user accesses a dedicated application or website and logs in by entering their username and password. This action causes the device to send the user's authentication information to the server, which then checks the database to authenticate the user. If authentication is successful, the server generates a session token and sends it back to the device.

[0382] Enter your outing plan

[0383] After a successful login, the user enters the following parameters regarding their travel plans:

[0384] Departure Point

[0385] Transportation

[0386] Departure time

[0387] budget

[0388] Travel time

[0389] Number of people accompanying

[0390] Calories burned

[0391] Desired number of steps

[0392] The device collects this data in real time.

[0393] Using the Emotion Engine

[0394] The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice and collect their current emotional state in real time. For example, the emotion engine (Affectiva SDK) identifies the user's emotional state from their facial expressions and voice and generates emotion data such as "enjoyment" or "relaxation." This emotion data is stored on the device.

[0395] Sending and Receiving Data

[0396] The device converts the parameters and emotion data entered by the user into JSON format and sends it to the server using the HTTPS protocol. The server receives this data and stores it in a database.

[0397] Analyze data and generate plans

[0398] The server analyzes the stored data based on an analysis algorithm, evaluating each parameter and emotional data. The analysis results are then passed to the generation AI (OpenAI GPT-3), which generates an outing plan that best suits the user's needs and emotional state. For example, the following prompt sentence is input to the generation AI:

[0399] "Generate an outing plan for the user. User input parameters are as follows:

[0400] Starting point: Tokyo Station

[0401] Transportation: Train and walking

[0402] Departure time: 10:00 AM

[0403] Budget: 5,000 yen

[0404] Duration: 5 hours

[0405] Number of people accompanying: 2 people

[0406] Calories burned: 300 calories

[0407] Desired number of steps: 8000 steps

[0408] Current emotional state: Enjoyment

[0409] Based on these, please suggest two outing plans that suit the user's health preferences and emotional state.

[0410] The AI ​​generates multiple outing plans based on the user's needs and emotional state. Each plan includes destinations, activities, transportation, estimated calories burned, estimated number of steps, and a reason for suggesting the plan based on the user's emotional state.

[0411] Sending and selecting outing plans

[0412] The server converts the generated outing plan into JSON format and sends it to the user's device. The user reviews the multiple plans provided and selects the most suitable one. Once the selection is confirmed, the device notifies the server of the selected plan, and the server stores this information in a database. The server also sends a selection confirmation to the user.

[0413] Specific examples

[0414] For example, if User A is planning to go out on a holiday, he / she will follow the steps below:

[0415] User A logs in to the dedicated app and enters the following parameters:

[0416] Starting point: Tokyo Station

[0417] Transportation: Train and walking

[0418] Departure time: 10:00 AM

[0419] Budget: 5,000 yen

[0420] Duration: 5 hours

[0421] Number of people accompanying: 2 people

[0422] Calories burned: 300 calories

[0423] Desired number of steps: 8,000 steps

[0424] While inputting, the emotion engine analyzes User A's facial expressions and voice and recognizes their current emotional state as "fun." The device sends this information to the server, which receives and analyzes the information. The analysis results and emotion data are then passed to the generation AI, which generates the following outing plan:

[0425] Plan A: Visit to Ueno Zoo + Shopping at Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps, Reason for suggestion: Matches the emotion of enjoyment)

[0426] Plan B: Visit to Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps, Reason for suggestion: Matches the emotion of enjoyment)

[0427] These plans are sent to the user's device, and User A selects and confirms Plan A. The server stores this selection information in a database and sends a confirmation notice to User A. In this way, users can easily obtain outing plans that incorporate their emotional state and health preferences.

[0428] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0429] Step 1: User Login

[0430] A user accesses a dedicated application or website and logs in by entering their username and password. The device receives these authentication information as input and sends it to the server via the HTTPS protocol. The server checks it against a database and authenticates the user. If authentication is successful, the server generates a session token and sends it back to the device as output.

[0431] Specific behavior:

[0432] The user launches the app and enters their username and password on the login screen.

[0433] The terminal sends the input data to the server.

[0434] The server checks the credentials in the database.

[0435] If authentication is successful, the server generates a session token and returns it to the terminal.

[0436] Step 2: Enter the user's travel plans

[0437] The user inputs parameters related to their trip plan through the application interface, including the starting point, mode of transportation, departure time, budget, travel time, number of people accompanying them, calories burned, and desired number of steps. The device receives this data as input and collects it in real time.

[0438] Specific behavior:

[0439] The user enters the parameters of the trip plan into a form in the application.

[0440] The terminal stores these data in variables and prepares to send them to the server in the next step.

[0441] Step 3: Collecting emotion data with the emotion engine

[0442] The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice to collect emotion data. Emotion data includes emotions such as "enjoyment" and "relaxation." The emotion engine receives this data as input and generates emotion data as output.

[0443] Specific behavior:

[0444] The emotion engine analyzes camera footage and audio data as input.

[0445] The emotional state of the user is identified from facial expressions and voice, and emotional data is generated.

[0446] The generated emotion data is stored in the terminal.

[0447] Step 4: Sending data

[0448] The device converts the parameters of the outing plan and emotion data entered by the user into JSON format, and sends the converted JSON data as input to the server using the HTTPS protocol.

[0449] Specific behavior:

[0450] The device converts the outing plan parameters and emotion data into JSON format.

[0451] The converted JSON data is sent to the server via HTTPS protocol.

[0452] Step 5: Receiving and storing data

[0453] The server receives JSON data sent from the terminal and takes it in as input. It saves the received data in the database and generates a save completion status as output.

[0454] Specific behavior:

[0455] The server receives the HTTPS request and parses the JSON data.

[0456] The parsed data is stored in a database.

[0457] Generates a save completion status.

[0458] Step 6: Analyze the data

[0459] The server retrieves data stored in the database and analyzes the input data using an analysis algorithm. The analysis results are output as prompts to be passed to the generation AI.

[0460] Specific behavior:

[0461] The server retrieves the stored data from the database.

[0462] Data analysis algorithms evaluate each parameter and emotion data.

[0463] Generate prompts for generative AI models.

[0464] Step 7: Generate a plan using generative AI

[0465] The generative AI (e.g., OpenAI GPT-3) receives prompts sent from the server as input and generates the optimal outing plan. The generated plan is output to the server as multiple options.

[0466] Specific behavior:

[0467] The generative AI model receives the prompt sentence as input.

[0468] To generate multiple outing plans based on a user's emotional state and health preferences.

[0469] The generated plan is sent back to the server.

[0470] Step 8: Submit your plan

[0471] The server converts the generated outing plan into JSON format and sends it to the device, which then analyzes the received data and displays it to the user.

[0472] Specific behavior:

[0473] The server formats the generated plan into JSON.

[0474] Sends JSON data to the terminal via HTTPS protocol.

[0475] The terminal analyzes the received data and displays it to the user.

[0476] Step 9: User plan selection and confirmation

[0477] The user reviews multiple outing plans displayed on the device and selects the most suitable one. The device receives the selected plan information as input and sends it to the server. The server stores this information in a database and returns a selection confirmation to the device.

[0478] Specific behavior:

[0479] The user checks the outing plan on the terminal and clicks the selection button.

[0480] The terminal transmits information about the selected plan to the server.

[0481] The server stores the selection information in a database.

[0482] The server sends a confirmation of the selection back to the terminal.

[0483] (Application example 2)

[0484] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0485] Conventional outing plan generation systems do not consider the user's emotional state when proposing plans, which can result in low user satisfaction. Furthermore, if outing plans could be proposed that reflect the user's intuitive emotional state, rather than just taking health-consciousness into account, a more fulfilling experience could be provided. The present invention aims to provide a system that generates outing plans that also consider the user's emotional state, thereby increasing user satisfaction.

[0486] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0487] In this invention, the server includes means for inputting parameters such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc. from the user, means for receiving and analyzing the input data and emotional state data, and means for generating an outing plan that takes into account health orientation and emotional state using a generation AI based on the analyzed data, thereby making it possible to provide an outing plan optimized for the user's emotional state.

[0488] The "starting point" refers to the location where the user starts going out.

[0489] "Transportation" refers to the means of transportation used by the user when out and about.

[0490] "Departure time" refers to the time when the user starts going out.

[0491] The "budget" refers to the upper limit of the amount of money that the user can spend on this outing.

[0492] The "required time" refers to the total time the user plans to spend out.

[0493] The "number of people going out" refers to the number of people accompanying the user on an outing.

[0494] "Calories burned" refers to the amount of calories the user plans to burn while out.

[0495] The "desired number of steps" refers to the number of steps the user wishes to walk while out.

[0496] "Emotional state" refers to the user's current emotional or psychological state.

[0497] "Input means" refers to a device or method by which a user inputs parameters into the system.

[0498] "Means for receiving and analyzing" refers to a device or method for receiving parameters and emotion data input by a user and analyzing them.

[0499] "Means for generating" refers to a device or method for generating an outing plan based on input data using a generating AI.

[0500] The "transmitting means" refers to a device or method for transmitting the generated outing plan to the user's terminal.

[0501] The "means for selecting and confirming" refers to a device or method that allows a user to select from among the proposed outing plans and confirm the plan.

[0502] This system optimizes the shopping experience in brick-and-mortar stores by generating health-conscious outing plans that take into account the user's emotions. This system mainly consists of a user's device, a server, a generative AI model, an emotion engine, and a database.

[0503] First, users access the system using a dedicated smartphone application and log in. Next, they input parameters such as the starting point, mode of transportation, departure time, budget, travel time, number of people going out, calories burned, desired number of steps, etc. While the user is entering information, the emotion engine uses the camera and microphone to analyze facial expressions and voice to recognize the user's emotional state.

[0504] The device converts this input data and emotional data into JSON format and sends it to the server using the HTTPS protocol. The server receives this data and temporarily stores it. An analysis algorithm analyzes each parameter and emotional data. The analyzed data is passed to the generation AI, which generates an outing plan that is optimal for the user's needs and emotional state. The generation AI generates a health-oriented plan taking into account the user's specified calories burned, desired number of steps, and emotional state.

[0505] The generated plans are sent from the server to the user's device as multiple candidates. The user reviews the plans and selects the most suitable one. Once the selection is confirmed, the server saves the selection information in a database and sends a confirmation notice to the user.

[0506] This system uses a virtual library called "EmotionAnalyzer" for analyzing user emotions and "RecommendationEngine" for generating AI, which makes it possible to suggest products and stores according to the user's emotional state.

[0507] Specific examples

[0508] Consider a case where a user is shopping at a brick-and-mortar store (e.g., a shopping mall). The user logs in to the app and enters the following parameters:

[0509] Starting point: Shinjuku

[0510] Transportation: Walking

[0511] Departure time: 3:00 PM

[0512] Budget: 10,000 yen

[0513] Duration: 3 hours

[0514] Number of people going out: 1 person

[0515] Calories burned: 200 calories

[0516] Desired number of steps: 5,000 steps

[0517] The emotion engine analyzes the user's facial expressions and voice and recognizes their current emotional state as "fun." The server receives this information and uses the generative AI to generate the following plan:

[0518] Plan A: Shopping at Clothing Store A + Relax at the Book Cafe

[0519] Plan B: Shopping at Accessory Store B + Walking in the Park

[0520] These plans are sent to the user's terminal, and the user can select the most suitable plan, thus providing a pleasant shopping experience that matches his or her emotional state.

[0521] Prompt Sentence Examples

[0522] It's 3 PM and the user wants to enjoy shopping in Shinjuku within a budget of 10,000 yen. Sentiment analysis indicates the user is in the "Enjoy" state. What products and stores would you recommend?

[0523] This system allows users to plan their outings more effectively based on their emotional state.

[0524] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0525] Step 1:

[0526] Users log in to the application using their smartphone and enter parameters such as the starting point, mode of transportation, departure time, budget, travel time, number of people going out, calories burned, desired number of steps, etc. The entered information is temporarily saved by the application. Examples of input data include the starting point "Shinjuku," mode of transportation "walking," and budget "10,000 yen."

[0527] Step 2:

[0528] The emotion engine uses the camera and microphone to analyze the user's facial expressions and voice to recognize their current emotional state. For example, it can identify that the user is in an "enjoyment" emotional state based on their facial expressions and voice. The acquired emotional data is temporarily saved along with the input parameters.

[0529] Step 3:

[0530] The device converts the input parameters and emotion data into JSON format and sends it to the server using the HTTPS protocol. The data sent includes the starting point (Shinjuku), the budget (10,000 yen), and the emotional state (fun).

[0531] Step 4:

[0532] The server temporarily stores the received data before applying the analysis algorithm, which categorizes the data into parameters and emotional data.

[0533] Step 5:

[0534] The server runs an analysis algorithm to analyze the received parameters and emotional data. This analysis identifies the elements necessary to create an outing plan based on the user's starting point, budget, emotional state, etc. The server then selects an appropriate activity based on the input data "fun."

[0535] Step 6:

[0536] The analyzed data is passed to a generation AI, which generates an outing plan that best suits the user's needs and emotional state. The generation AI outputs multiple plans using, for example, a "Recommendation Engine." Specifically, it generates plans such as "Plan A: Shopping at a clothing store + Relax at a cafe" and "Plan B: Shopping at an accessory store + Walking in the park."

[0537] Step 7:

[0538] The server then converts the generated outing plan back into JSON format and sends it to the user's device. The data sent includes multiple outing plans, each with detailed activity and reason descriptions.

[0539] Step 8:

[0540] The user checks the multiple plans presented on the terminal and selects the most suitable one. The plan selected by the user is sent to the server by the application, and the selection information is saved in the database.

[0541] Step 9:

[0542] The server sends a confirmation notification of the selected plan to the user's terminal, allowing the user to confirm that the selected plan has been confirmed.

[0543] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0544] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0545] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0546] [Second embodiment]

[0547] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0548] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0549] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0550] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0551] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0552] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0553] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0554] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0555] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0556] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0557] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0558] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0559] The present invention provides a system for enabling people to enjoy going out on holidays efficiently and in a health-conscious manner. Specific embodiments of this system will be described below.

[0560] Overall system configuration

[0561] The system mainly consists of the following components:

[0562] 1. User's device (e.g. smartphone or PC)

[0563] 2. Server

[0564] 3. Generation AI

[0565] 4. Database

[0566] User operations

[0567] A user first accesses the system using a dedicated application or website and logs in.

[0568] The user inputs parameters related to the outing plan (starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.).

[0569] Sending and Receiving Data

[0570] The terminal converts all parameters entered by the user into JSON format and sends them to the server using the stable and secure HTTPS protocol.

[0571] The server receives this data and prepares it for analysis.

[0572] Data analysis and generation using AI

[0573] The server temporarily stores the received data and analyzes each parameter using an analysis algorithm.

[0574] The analyzed data is passed to the generation AI, which then generates an outing plan that best suits the user's needs.

[0575] The AI ​​takes into account the user's specified calorie consumption and desired number of steps, and compares it with past data when generating a health-oriented plan to provide a highly accurate plan.

[0576] Generate and send trip plans

[0577] The AI ​​generates multiple outing plans, each of which includes destinations, activities, how to use public transportation, estimated calories burned, estimated number of steps, etc.

[0578] The server sends the generated plans to the user's device in JSON format.

[0579] User plan selection and confirmation

[0580] The user checks the multiple plans presented on the terminal and selects the most suitable one from among them.

[0581] Once the selection is confirmed, the server stores the user's selection in a database and sends a confirmation to the user's device.

[0582] Specific examples

[0583] For example:

[0584] User A plans to go out on a holiday and logs in to the dedicated app. Next, he enters the following parameters:

[0585] Starting point: Tokyo Station

[0586] Transportation: Train and walking

[0587] Departure time: 10:00 AM

[0588] Budget: 5,000 yen

[0589] Duration: 5 hours

[0590] Number of people going out: 2

[0591] Calories burned: 300 calories

[0592] Desired number of steps: 8,000 steps

[0593] The device sends this information to the server, which receives it and analyzes it. The analysis results are passed to the generation AI, which then generates a plan like this:

[0594] Plan A: Visit to Ueno Zoo + Shopping in Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps)

[0595] Plan B: Visit Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps)

[0596] These plans are sent to the user's terminal, and User A selects and confirms Plan A. The server stores this selection information in the database and sends a confirmation notice to User A.

[0597] In this way, the user can easily obtain an outing plan that incorporates health-conscious ideas.

[0598] The processing flow will be explained below.

[0599] Step 1:

[0600] The user accesses a dedicated application or website and logs in. The user inputs parameters such as the departure point, transportation method, departure time, budget, required time, number of people going out, calories burned, and desired number of steps.

[0601] Step 2:

[0602] The terminal converts the data entered by the user into JSON format, which contains all the user's parameters.

[0603] Step 3:

[0604] The terminal sends the converted data to the server using the HTTPS protocol, which ensures secure transmission of the data.

[0605] Step 4:

[0606] The server receives the data received from the device and prepares it for analysis, converting it into an appropriate format and passing it to the analysis algorithm.

[0607] Step 5:

[0608] The server analyzes the received data using an analysis algorithm and prepares to pass the analysis results to the generation AI.

[0609] Step 6:

[0610] The AI ​​then generates an optimal outing plan based on the analyzed data, taking into account the user's desired calorie consumption and number of steps.

[0611] Step 7:

[0612] The AI ​​generates multiple different outing plans, each of which includes details such as destinations, activities, how to use public transport, estimated calories burned, and estimated number of steps.

[0613] Step 8:

[0614] The server sends multiple candidates for the generated outing plan to the user's device in JSON format.

[0615] Step 9:

[0616] The terminal displays the received outing plans on the user interface, and the user can check the plans and select the one they want.

[0617] Step 10:

[0618] The plan selected by the user is sent from the device to the server, and the selection is confirmed.

[0619] Step 11:

[0620] The server saves the user's selection in a database, confirming that the selection has been finalized.

[0621] Step 12:

[0622] The server sends a confirmation of the selection to the user's device, and the process is completed when the user receives and confirms the notification.

[0623] Example 1

[0624] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0625] Nowadays, many people are looking for ways to efficiently enjoy their holidays while maintaining their health. However, there is a lack of specific systems and methods to meet this demand. In addition, when users create their own outing plans that take health-consciousness into consideration, it takes a lot of time and effort. As a result, many people are unable to create appropriate outing plans, making it difficult to spend their holidays in a healthy manner.

[0626] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0627] In this invention, the server includes means for inputting parameters such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc. from the user, means for converting the input data into JSON format and sending it to the server using the HTTPS protocol, means for saving the received JSON format data and analyzing it using an analysis algorithm, means for sending the analysis results to the generation AI as prompt text, which generates multiple outing plans based on the user's requirements, means for sending the generated outing plans to the user's terminal in JSON format, and means for the user to select a presented plan and store the selected information in a database. This allows the user to easily obtain outing plans that incorporate health-conscious ideas.

[0628] "User" refers to an individual or organization who uses the system and creates outing plans through this system.

[0629] A "terminal" is a device used by a user to access the system, including a smartphone, PC, tablet, etc.

[0630] The "server" is a central computer that manages and controls the entire system, and is responsible for receiving and analyzing data sent by users and coordinating with the generating AI.

[0631] "Generative AI" is a type of artificial intelligence that refers to algorithms or models that generate optimal outing plans based on input data.

[0632] "Database" refers to an information storage device for efficiently storing and managing user input information, generated outing plans, selection information, etc.

[0633] "Parameters" are items of information that a user inputs into the system, such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.

[0634] The "HTTPS protocol" is a network communication protocol used when a user sends data from a device to a server, and is responsible for ensuring the secure transmission and reception of data.

[0635] The "JSON format" is a standard format for describing data in text format, and is used to efficiently send user input information to a server.

[0636] "Analysis algorithm" refers to a program with calculation procedures for analyzing data received by the server, and performs initial data processing to meet user requirements.

[0637] A "prompt sentence" is a command sentence used to send a specific generation request to the generation AI, and includes instructions that reflect the user's requirements.

[0638] An "outing plan" is an outing plan proposed by the generation AI based on the user's requirements, and includes details such as destinations, activities, how to use public transportation, planned calories burned, and planned number of steps.

[0639] "Data archiving" refers to the process by which the server temporarily or permanently stores the data it receives on a storage device.

[0640] "Data transmission" refers to the process of transferring data from a user's terminal to a server or from a server to a user's terminal.

[0641] "Calories burned" refers to the amount of energy consumed by the user while executing the going out plan.

[0642] The "desired number of steps" refers to the number of steps that the user wishes to walk while executing the outing plan.

[0643] The present invention provides a system that allows users to enjoy their holidays efficiently and with a focus on health. This system utilizes generation AI based on user input to generate optimal outing plans. Specific embodiments of this system are described below.

[0644] Overall system configuration

[0645] The system mainly consists of the following components:

[0646] 1. User's device (e.g., smartphone or personal computer)

[0647] 2. Server

[0648] 3. Generation AI

[0649] 4. Database

[0650] User operations

[0651] Users access a dedicated application or website, log in with their authentication information, and then enter parameters such as starting point, mode of transportation, departure time, budget, travel time, number of people going out, calories burned, and desired number of steps.

[0652] After the user enters various parameters, the information is converted into JSON format by the terminal and sent to the server using the HTTPS protocol. It is worth noting that this system uses secure data encryption, which is an important specification for protecting user privacy.

[0653] Server Processing

[0654] The server receives the JSON-formatted data sent from the device and temporarily stores it. Next, it analyzes each parameter using an analysis algorithm. This analysis is generally performed using Python libraries such as Pandas and NumPy.

[0655] The analysis results are sent to the generation AI as a prompt. For example, we generate a prompt that instructs the AI ​​to generate a plan departing from Tokyo Station, with a budget of 5,000 yen, consuming 300 calories, and requiring no more than 8,000 steps. This prompt looks like this:

[0656] Users are asked to create a plan to travel from Tokyo Station by train and on foot, with a budget of 5,000 yen, 300 calories burned, and a desired number of steps of 8,000 or less.

[0657] Processing of generated AI

[0658] The generation AI generates multiple outing plans based on the given prompt. The generation AI takes into account past data and the user's history to generate the optimal plan for the user. As a concrete example, the following plans are generated:

[0659] Plan A: Visit to Ueno Zoo + Shopping in Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps)

[0660] Plan B: Visit Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps)

[0661] These generated plans are converted back to JSON format and sent to the server, which then sends the generated plans to the user's device.

[0662] User plan selection

[0663] The user checks the multiple plans presented on the terminal and selects the most suitable one. Once the selection is confirmed, the server saves the selection information in a database and sends a confirmation notice to the user's terminal. When the user receives this confirmation notice, they know that the plan has been confirmed.

[0664] In this way, users can easily obtain outing plans that incorporate health-conscious ideas. This system enables users to enjoy their holidays efficiently and healthily.

[0665] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0666] Step 1: User parameter input

[0667] The user accesses a dedicated application or website and inputs parameters such as the starting point, mode of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc. The input parameters are sent to the terminal. Specifically, the user enters the required information into the form and presses the "Submit" button.

[0668] Input: Departure point, transportation method, departure time, budget, required time, number of people going out, calories burned, desired number of steps

[0669] Output: Parameter data in JSON format

[0670] Step 2: Sending data

[0671] The terminal converts the input parameters into JSON format and sends them to the server using the HTTPS protocol. Specifically, the terminal sends a POST request to the endpoint, and the data is encrypted and sent.

[0672] Input: Parameter data in JSON format

[0673] Output: Data sent to the server

[0674] Step 3: Receiving and storing data

[0675] The server receives the JSON format data sent from the device and temporarily stores it in a database. The received data is stored as is, but is prepared for later analysis.

[0676] Input: Parameter data sent in JSON format

[0677] Output: Parameter data stored in the database

[0678] Step 4: Analyze the data

[0679] The server analyzes the stored data using Python libraries such as Pandas and NumPy, converting each parameter into an appropriate format. Specific operations include reading the data, extracting necessary fields, and cleaning the data.

[0680] Input: Parameter data stored in the database

[0681] Output: Parsed parameter data

[0682] Step 5: Sending prompts to the generation AI

[0683] The server generates a prompt based on the analyzed data and sends it to the generation AI. Prompt generation involves converting the user's input data into an appropriate context. For example, a prompt might be created such as, "The user should create a plan departing from Tokyo Station, with a budget of 5,000 yen, consuming 300 calories, and requiring no more than 8,000 steps."

[0684] Input: Parsed parameter data

[0685] Output: The prompt sent to the generation AI

[0686] Step 6: Generate your trip plan

[0687] The generation AI generates an outing plan based on the prompt text. The generation AI references past data and user history to generate multiple plans. The generated plan includes specific destinations and activities, how to use public transportation, estimated calories burned, and estimated number of steps. Specifically, the generation AI model makes optimal suggestions based on the input prompt.

[0688] Input: Prompt sent to the generation AI

[0689] Output: Generated itinerary

[0690] Step 7: Submit your trip plan

[0691] The server converts the outing plan received from the generation AI into JSON format and sends it to the user's device. Specifically, the server receives the output of the generation AI and sends the data to the user's device through an endpoint.

[0692] Input: Generated trip plan

[0693] Output: Trip plan sent to the user's device in JSON format

[0694] Step 8: User Plan Selection

[0695] The user checks the multiple outing plans presented on the device and selects the most suitable one. Specifically, the user checks the details of each plan and clicks the "Select" button.

[0696] Input: Trip plan sent in JSON format

[0697] Output: Selected outing plan

[0698] Step 9: Save your selections and receive confirmation

[0699] The server stores the information of the outing plan selected by the user in a database and sends a confirmation notice to the user's terminal, specifically, by recording the selection information in the database and generating a confirmation message to send to the user's terminal.

[0700] Input: Selected outing plan

[0701] Output: Selection information stored in the database, confirmation sent to the user's device

[0702] (Application example 1)

[0703] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0704] Conventional outing plan generation systems provide outing plans that take health into consideration, but do not suggest meal plans for users. A plan that supports health-conscious outings, including the contents of meals eaten while out, is needed. Furthermore, to achieve comprehensive health management, there is a need for meal plans that are linked to outing plans.

[0705] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0706] In this invention, the server includes means for inputting parameters such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, type of meal, budget, calories per meal, etc. from the user, means for receiving and analyzing the input data, and means for generating an outing plan and meal plan that takes health into consideration using a generation AI based on the analyzed data. This allows the user to ensure consistency in not only the activities they do while out, but also their meal plan, taking health into consideration.

[0707] The "starting point" refers to the point where the user starts going out.

[0708] "Transportation" refers to the means of transportation used to travel from a departure point to a destination.

[0709] "Departure time" refers to the specific time when the user starts going out.

[0710] "Budget" refers to the amount of money planned to be spent on outings and related activities.

[0711] "Time required" refers to the length of time required for the entire outdoor activity.

[0712] "Number of people going out" refers to the number of people who participate in outdoor activities.

[0713] "Calories burned" refers to the amount of energy consumed during outdoor activities.

[0714] The "desired number of steps" refers to the number of steps that are expected to be taken during outdoor activities.

[0715] "Meal type" refers to the type of meal the user desires (e.g., breakfast, lunch, dinner, etc.).

[0716] "Generative AI" refers to artificial intelligence that automatically generates appropriate outing and meal plans based on user input data.

[0717] "Determining a plan" refers to the act of the user selecting the most suitable plan from the proposed plans and making a final decision.

[0718] A specific system and method for implementing the present invention will now be described.

[0719] System Configuration

[0720] The system consists of the following components:

[0721] 1. User's device (smartphone, PC)

[0722] 2. Server

[0723] 3. Generative AI Models

[0724] 4. Database

[0725] User operations

[0726] The user first logs in to a dedicated application or website, then enters the following parameters:

[0727] Departure Point

[0728] Transportation

[0729] Departure time

[0730] budget

[0731] Travel time

[0732] Number of people going out

[0733] Calories burned

[0734] Desired number of steps

[0735] Type of meal (e.g. breakfast, lunch, dinner)

[0736] Budget per meal

[0737] Calories per serving

[0738] Sending and Receiving Data

[0739] The user's device converts the input data into JSON format and sends it to the server using the HTTPS protocol. The server then analyzes the received data and prepares it for passing to the generative AI model.

[0740] Analyzing data and using generative AI models

[0741] The server runs the received data through an analysis algorithm and prepares the data to be passed to the generative AI model, which then generates optimal outing and meal plans based on the user's requests.The generative AI model also references past data to improve accuracy.

[0742] Generate and submit a plan

[0743] The generative AI model generates an outing plan and a meal plan, each containing the following information:

[0744] Destinations

[0745] activity

[0746] means of transportation

[0747] Estimated calorie consumption

[0748] Planned steps

[0749] Meal contents

[0750] Dining

[0751] Calorie and food budget

[0752] The server sends the generated plan in JSON format to the user's device.

[0753] User plan selection and confirmation

[0754] The user checks the displayed plans and selects the most suitable one. After selection, the server saves the selection information in the database and sends a confirmation notice to the user's device.

[0755] Specific examples

[0756] User A plans to go out and have lunch on a day off and enters the following parameters:

[0757] Starting point: Shibuya Ward

[0758] Transportation: Train and walking

[0759] Departure time: 10:00 AM

[0760] Budget: 8,000 yen

[0761] Duration: 6 hours

[0762] Number of people going out: 2

[0763] Calories burned: 500 calories

[0764] Desired number of steps: 10,000 steps

[0765] Meal type: Lunch

[0766] Budget per meal: 1,500 yen

[0767] Calories per serving: 600 calories

[0768] Based on the information sent to the server, the generative AI model analyzes and provides the following plan:

[0769] Plan A: Walk + Museum Visit + Healthy Lunch (Estimated calories burned: 520 calories, Estimated steps: 9,500 steps, Estimated calories for lunch: 580 calories)

[0770] Plan B: Walk in the park + Shopping + Low-calorie restaurant lunch (Estimated calories burned: 480 calories, Estimated steps: 10,500 steps, Estimated calories for lunch: 590 calories)

[0771] User A selects Plan A, and the server saves the selection in the database and sends a confirmation.

[0772] Main hardware and software used

[0773] Hardware: Web server (e.g. AWS EC2)

[0774] Software: Flask (Python library), HTTP protocol, generative AI (via API)

[0775] Prompt Sentence Examples

[0776] "Please suggest a healthy meal plan for location: Shibuya Ward, type: lunch, budget: 1500 yen, calories: 600 kcal."

[0777] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0778] Step 1:

[0779] The user logs in to a dedicated application or website and enters the following parameters: starting point, transportation method, departure time, budget, required time, number of people going out, calories burned, desired number of steps, type of meal, budget per meal, and calories per meal. This data is entered into the user's device and converted into JSON format.

[0780] Step 2:

[0781] The user's device sends the data converted into JSON format to the server using the HTTPS protocol, where it is encrypted to ensure security.

[0782] Step 3:

[0783] The server receives the data sent from the user's device, analyzes it using an analysis algorithm, and prepares it for passing to the generative AI model. Specifically, it checks the data for consistency and whether there is any missing information or data in the wrong format.

[0784] Step 4:

[0785] The server inputs the analyzed data into a generative AI model, which generates prompts and then generates health-conscious outing and meal plans based on the prompts.

[0786] Example: "Please suggest a healthy meal plan for location: Shibuya Ward, type: lunch, budget: 1500 yen, calories: 600 kcal."

[0787] Step 5:

[0788] The generative AI model generates multiple plans based on the input prompts. The generated outing and meal plans include destinations, activities, transportation, estimated calories burned, estimated steps, meal contents, meal locations, estimated calories for each meal, and budget.

[0789] Step 6:

[0790] The server sends multiple plans generated by the generative AI model to the user's device, where the plans are sent in JSON format and displayed on the user's device.

[0791] Step 7:

[0792] The user checks the multiple plans presented on the terminal and selects the most suitable one. Once the selection is confirmed, the information is sent from the user's terminal to the server.

[0793] Step 8:

[0794] The server stores the user's selected plan in a database and sends a confirmation notice to the user's terminal, so that the user can go out and eat according to the plan.

[0795] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0796] The present invention provides a system for planning a holiday outing that takes into account the user's emotions and allows the user to enjoy an efficient and health-conscious lifestyle. Specific embodiments of this system will be described below.

[0797] Overall system configuration

[0798] The system mainly consists of the following components:

[0799] 1. User's device (e.g. smartphone or PC)

[0800] 2. Server

[0801] 3. Generation AI

[0802] 4. Emotion Engine

[0803] 5. Database

[0804] User operations

[0805] A user first accesses the system using a dedicated application or website and logs in.

[0806] The user inputs parameters related to the outing plan (starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.).

[0807] Using the Emotion Engine

[0808] The emotion engine uses a camera and microphone to analyze facial expressions and voice while the user is typing, recognizing the user's emotional state.

[0809] Emotion data is captured in real time to assist the user in the input process.

[0810] Sending and Receiving Data

[0811] The terminal converts the data and emotion data entered by the user into JSON format and sends it to the server using the HTTPS protocol.

[0812] The server receives this data and prepares it for analysis.

[0813] Data analysis and generation using AI

[0814] The server temporarily stores the received data and analyzes each parameter and emotion data using an analysis algorithm.

[0815] The analyzed data is passed to the generation AI, which then generates an outing plan that best suits the user's needs and emotional state.

[0816] The AI ​​takes into account the user's specified calorie consumption, desired number of steps, and emotional state, and compares it with past data to generate a health-oriented plan, providing a highly accurate plan.

[0817] Generate and send trip plans

[0818] The AI ​​generates multiple outing plans, each of which includes destinations, activities, how to use public transportation, estimated calories burned, estimated number of steps, and content appropriate to the user's emotional state.

[0819] The server sends the generated plans to the user's device in JSON format.

[0820] User plan selection and confirmation

[0821] The user checks the multiple plans presented on the terminal and selects the most suitable one from among them.

[0822] Once the selection is confirmed, the server stores the user's selection in a database and sends a confirmation to the user's device.

[0823] Specific examples

[0824] For example:

[0825] User A plans to go out on a holiday and logs in to the dedicated app. Next, he enters the following parameters:

[0826] Starting point: Tokyo Station

[0827] Transportation: Train and walking

[0828] Departure time: 10:00 AM

[0829] Budget: 5,000 yen

[0830] Duration: 5 hours

[0831] Number of people going out: 2

[0832] Calories burned: 300 calories

[0833] Desired number of steps: 8,000 steps

[0834] While inputting, the emotion engine analyzes User A's facial expressions and voice and recognizes their current emotional state as "enjoyment." The device sends this information to the server, which receives the information and analyzes it. The analysis results and emotion data are passed to the generation AI, which generates the following plan:

[0835] Plan A: Visit to Ueno Zoo + Shopping at Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps, Reason for suggestion: Matches the emotion of enjoyment)

[0836] Plan B: Visit to Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps, Reason for suggestion: Matches the emotion of enjoyment)

[0837] These plans are sent to the user's terminal, and User A selects and confirms Plan A. The server stores this selection information in the database and sends a confirmation notice to User A.

[0838] In this way, the user can easily obtain an outing plan that incorporates health consciousness and emotional state.

[0839] The processing flow will be explained below.

[0840] Step 1:

[0841] The user accesses a dedicated application or website and logs in. The user inputs parameters such as the departure point, transportation method, departure time, budget, required time, number of people going out, calories burned, and desired number of steps.

[0842] Step 2:

[0843] The emotion engine uses the user's camera and microphone to analyze facial expressions and voice to recognize the user's emotional state in real time, detecting emotions such as joy, sadness, and fun.

[0844] Step 3:

[0845] The device converts all data and emotion data entered by the user into JSON format, which includes all the user's parameters.

[0846] Step 4:

[0847] The terminal sends the converted data to the server using the HTTPS protocol, which ensures secure transmission of the data.

[0848] Step 5:

[0849] The server receives the data received from the device and prepares it for analysis, converting it into an appropriate format and passing it to the analysis algorithm.

[0850] Step 6:

[0851] The server uses an analysis algorithm to analyze the received data and emotional data, for example, matching the user's input parameters with their emotional state.

[0852] Step 7:

[0853] The server passes the analysis results to the generation AI, which prepares to generate the optimal outing plan based on the user's requests and emotional state.

[0854] Step 8:

[0855] The AI ​​generates multiple outing plans based on the user's calorie consumption, desired number of steps, and emotional state. Each plan includes destinations, activities, how to use public transportation, planned calorie consumption, planned number of steps, and content appropriate for the user's emotional state.

[0856] Step 9:

[0857] The server sends multiple candidates for the generated outing plan to the user's device in JSON format.

[0858] Step 10:

[0859] The terminal displays the received outing plans on the user interface, and the user can check the plans and select the one they want.

[0860] Step 11:

[0861] The plan selected by the user is sent from the device to the server, and the selection is confirmed.

[0862] Step 12:

[0863] The server saves the user's selection in a database, confirming that the selection has been finalized.

[0864] Step 13:

[0865] The server sends a confirmation of the selection to the user's device, and the process is completed when the user receives and confirms the notification.

[0866] Example 2

[0867] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0868] Conventional outing plan creation systems have difficulty providing plans that fully consider the user's emotional state and health preferences. Furthermore, they have been unable to meet modern user needs, such as secure transmission of user input data and evaluation of exercise volume. As a result, they often provide plans that are unsatisfactory for users.

[0869] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting parameters such as a starting point, a means of transportation, a departure time, a budget, a required time, the number of accompanying persons, calories burned, and a desired number of steps from a user; means for analyzing the user's facial expressions and voice using a camera and a microphone to collect emotional data; means for receiving the input data and emotional data, converting it into JSON format, and transmitting it to the server; means for storing the received data in the server and analyzing it using an analytical algorithm; means for using a generation AI based on the analyzed data to generate a health-oriented outing plan that is optimal for the user's requests and emotional state; means for transmitting the generated outing plan to the user's terminal; and means for the user to select the generated outing plan and store the selected information in a database. This makes it possible to provide an outing plan that takes into account the user's emotional state and health-orientedness.

[0870] "User" refers to an individual who uses the system to create an outing plan.

[0871] A "terminal" refers to an electronic device used by a user to manipulate input data, such as a smartphone or a personal computer.

[0872] "Server" refers to the computer system that receives and stores data sent by users, analyzes it, and generates plans.

[0873] "Database" refers to a system for storing user inputs and selections.

[0874] "Generative AI" refers to artificial intelligence that generates optimal outing plans based on the user's requests and emotional state.

[0875] An "emotion engine" refers to software that analyzes a user's facial expressions and voice to collect emotional data.

[0876] The "starting point" refers to the starting point of the user's outing plan.

[0877] "Transportation" refers to the means of transportation used by the user when going out.

[0878] "Departure time" refers to the time when the user starts going out.

[0879] The "budget" refers to the amount of money that a user can spend when going out.

[0880] "Time required" refers to the time the user plans to spend going out.

[0881] "Number of people accompanying" refers to the number of other people who go out with the user.

[0882] "Calories burned" refers to the amount of calories the user plans to burn while out.

[0883] The "desired number of steps" refers to the number of steps that the user wishes to achieve while out and about.

[0884] "Emotion data" refers to data that indicates the user's emotional state, obtained as a result of the emotion engine's analysis of the user's facial expressions and voice.

[0885] "JSON format" refers to a lightweight data interchange format that is widely used to send and receive data.

[0886] "Analysis Algorithm" refers to the computational method used by the Server to analyze Data.

[0887] A "health-oriented outing plan" refers to an outing plan that takes into consideration the user's health, and includes a plan that takes into consideration the amount of exercise, such as calories burned and number of steps.

[0888] The present invention provides a system that provides an outing plan that takes into account the user's emotional state and health preferences. The system is composed of the following elements:

[0889] 1. User's device (e.g. smartphone or PC)

[0890] 2. Server

[0891] 3. Generative AI (e.g. OpenAI GPT-3)

[0892] 4. Emotion engine (e.g. Affectiva SDK)

[0893] 5. Database (e.g. MySQL)

[0894] User operations

[0895] A user accesses a dedicated application or website and logs in by entering their username and password. This action causes the device to send the user's authentication information to the server, which then checks the database to authenticate the user. If authentication is successful, the server generates a session token and sends it back to the device.

[0896] Enter your outing plan

[0897] After a successful login, the user enters the following parameters regarding their travel plans:

[0898] Departure Point

[0899] Transportation

[0900] Departure time

[0901] budget

[0902] Travel time

[0903] Number of people accompanying

[0904] Calories burned

[0905] Desired number of steps

[0906] The device collects this data in real time.

[0907] Using the Emotion Engine

[0908] The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice and collect their current emotional state in real time. For example, the emotion engine (Affectiva SDK) identifies the user's emotional state from their facial expressions and voice and generates emotion data such as "enjoyment" or "relaxation." This emotion data is stored on the device.

[0909] Sending and Receiving Data

[0910] The device converts the parameters and emotion data entered by the user into JSON format and sends it to the server using the HTTPS protocol. The server receives this data and stores it in a database.

[0911] Analyze data and generate plans

[0912] The server analyzes the stored data based on an analysis algorithm, evaluating each parameter and emotional data. The analysis results are then passed to the generation AI (OpenAI GPT-3), which generates an outing plan that best suits the user's needs and emotional state. For example, the following prompt sentence is input to the generation AI:

[0913] "Generate an outing plan for the user. User input parameters are as follows:

[0914] Starting point: Tokyo Station

[0915] Transportation: Train and walking

[0916] Departure time: 10:00 AM

[0917] Budget: 5,000 yen

[0918] Duration: 5 hours

[0919] Number of people accompanying: 2 people

[0920] Calories burned: 300 calories

[0921] Desired number of steps: 8000 steps

[0922] Current emotional state: Enjoyment

[0923] Based on these, please suggest two outing plans that suit the user's health preferences and emotional state.

[0924] The AI ​​generates multiple outing plans based on the user's needs and emotional state. Each plan includes destinations, activities, transportation, estimated calories burned, estimated number of steps, and a reason for suggesting the plan based on the user's emotional state.

[0925] Sending and selecting outing plans

[0926] The server converts the generated outing plan into JSON format and sends it to the user's device. The user reviews the multiple plans provided and selects the most suitable one. Once the selection is confirmed, the device notifies the server of the selected plan, and the server stores this information in a database. The server also sends a selection confirmation to the user.

[0927] Specific examples

[0928] For example, if User A is planning to go out on a holiday, he / she will follow the steps below:

[0929] User A logs in to the dedicated app and enters the following parameters:

[0930] Starting point: Tokyo Station

[0931] Transportation: Train and walking

[0932] Departure time: 10:00 AM

[0933] Budget: 5,000 yen

[0934] Duration: 5 hours

[0935] Number of people accompanying: 2 people

[0936] Calories burned: 300 calories

[0937] Desired number of steps: 8,000 steps

[0938] While inputting, the emotion engine analyzes User A's facial expressions and voice and recognizes their current emotional state as "fun." The device sends this information to the server, which receives and analyzes the information. The analysis results and emotion data are then passed to the generation AI, which generates the following outing plan:

[0939] Plan A: Visit to Ueno Zoo + Shopping at Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps, Reason for suggestion: Matches the emotion of enjoyment)

[0940] Plan B: Visit to Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps, Reason for suggestion: Matches the emotion of enjoyment)

[0941] These plans are sent to the user's device, and User A selects and confirms Plan A. The server stores this selection information in a database and sends a confirmation notice to User A. In this way, users can easily obtain outing plans that incorporate their emotional state and health preferences.

[0942] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0943] Step 1: User Login

[0944] A user accesses a dedicated application or website and logs in by entering their username and password. The device receives these authentication information as input and sends it to the server via the HTTPS protocol. The server checks it against a database and authenticates the user. If authentication is successful, the server generates a session token and sends it back to the device as output.

[0945] Specific behavior:

[0946] The user launches the app and enters their username and password on the login screen.

[0947] The terminal sends the input data to the server.

[0948] The server checks the credentials in the database.

[0949] If authentication is successful, the server generates a session token and returns it to the terminal.

[0950] Step 2: Enter the user's travel plans

[0951] The user inputs parameters related to their trip plan through the application interface, including the starting point, mode of transportation, departure time, budget, travel time, number of people accompanying them, calories burned, and desired number of steps. The device receives this data as input and collects it in real time.

[0952] Specific behavior:

[0953] The user enters the parameters of the trip plan into a form in the application.

[0954] The terminal stores these data in variables and prepares to send them to the server in the next step.

[0955] Step 3: Collecting emotion data with the emotion engine

[0956] The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice to collect emotion data. Emotion data includes emotions such as "enjoyment" and "relaxation." The emotion engine receives this data as input and generates emotion data as output.

[0957] Specific behavior:

[0958] The emotion engine analyzes camera footage and audio data as input.

[0959] The emotional state of the user is identified from facial expressions and voice, and emotional data is generated.

[0960] The generated emotion data is stored in the terminal.

[0961] Step 4: Sending data

[0962] The device converts the parameters of the outing plan and emotion data entered by the user into JSON format, and sends the converted JSON data as input to the server using the HTTPS protocol.

[0963] Specific behavior:

[0964] The device converts the outing plan parameters and emotion data into JSON format.

[0965] The converted JSON data is sent to the server via HTTPS protocol.

[0966] Step 5: Receiving and storing data

[0967] The server receives JSON data sent from the terminal and takes it in as input. It saves the received data in the database and generates a save completion status as output.

[0968] Specific behavior:

[0969] The server receives the HTTPS request and parses the JSON data.

[0970] The parsed data is stored in a database.

[0971] Generates a save completion status.

[0972] Step 6: Analyze the data

[0973] The server retrieves data stored in the database and analyzes the input data using an analysis algorithm. The analysis results are output as prompts to be passed to the generation AI.

[0974] Specific behavior:

[0975] The server retrieves the stored data from the database.

[0976] Data analysis algorithms evaluate each parameter and emotion data.

[0977] Generate prompts for generative AI models.

[0978] Step 7: Generate a plan using generative AI

[0979] The generative AI (e.g., OpenAI GPT-3) receives prompts sent from the server as input and generates the optimal outing plan. The generated plan is output to the server as multiple options.

[0980] Specific behavior:

[0981] The generative AI model receives the prompt sentence as input.

[0982] To generate multiple outing plans based on a user's emotional state and health preferences.

[0983] The generated plan is sent back to the server.

[0984] Step 8: Submit your plan

[0985] The server converts the generated outing plan into JSON format and sends it to the device, which then analyzes the received data and displays it to the user.

[0986] Specific behavior:

[0987] The server formats the generated plan into JSON.

[0988] Sends JSON data to the terminal via HTTPS protocol.

[0989] The terminal analyzes the received data and displays it to the user.

[0990] Step 9: User plan selection and confirmation

[0991] The user reviews multiple outing plans displayed on the device and selects the most suitable one. The device receives the selected plan information as input and sends it to the server. The server stores this information in a database and returns a selection confirmation to the device.

[0992] Specific behavior:

[0993] The user checks the outing plan on the terminal and clicks the selection button.

[0994] The terminal transmits information about the selected plan to the server.

[0995] The server stores the selection information in a database.

[0996] The server sends a confirmation of the selection back to the terminal.

[0997] (Application example 2)

[0998] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0999] Conventional outing plan generation systems do not consider the user's emotional state when proposing plans, which can result in low user satisfaction. Furthermore, if outing plans could be proposed that reflect the user's intuitive emotional state, rather than just taking health-consciousness into account, a more fulfilling experience could be provided. The present invention aims to provide a system that generates outing plans that also consider the user's emotional state, thereby increasing user satisfaction.

[1000] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1001] In this invention, the server includes means for inputting parameters such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc. from the user, means for receiving and analyzing the input data and emotional state data, and means for generating an outing plan that takes into account health orientation and emotional state using a generation AI based on the analyzed data, thereby making it possible to provide an outing plan optimized for the user's emotional state.

[1002] The "starting point" refers to the location where the user starts going out.

[1003] "Transportation" refers to the means of transportation used by the user when out and about.

[1004] "Departure time" refers to the time when the user starts going out.

[1005] The "budget" refers to the upper limit of the amount of money that the user can spend on this outing.

[1006] The "required time" refers to the total time the user plans to spend out.

[1007] The "number of people going out" refers to the number of people accompanying the user on an outing.

[1008] "Calories burned" refers to the amount of calories the user plans to burn while out.

[1009] The "desired number of steps" refers to the number of steps the user wishes to walk while out.

[1010] "Emotional state" refers to the user's current emotional or psychological state.

[1011] "Input means" refers to a device or method by which a user inputs parameters into the system.

[1012] "Means for receiving and analyzing" refers to a device or method for receiving parameters and emotion data input by a user and analyzing them.

[1013] "Means for generating" refers to a device or method for generating an outing plan based on input data using a generating AI.

[1014] The "transmitting means" refers to a device or method for transmitting the generated outing plan to the user's terminal.

[1015] The "means for selecting and confirming" refers to a device or method that allows a user to select from among the proposed outing plans and confirm the plan.

[1016] This system optimizes the shopping experience in brick-and-mortar stores by generating health-conscious outing plans that take into account the user's emotions. This system mainly consists of a user's device, a server, a generative AI model, an emotion engine, and a database.

[1017] First, users access the system using a dedicated smartphone application and log in. Next, they input parameters such as the starting point, mode of transportation, departure time, budget, travel time, number of people going out, calories burned, desired number of steps, etc. While the user is entering information, the emotion engine uses the camera and microphone to analyze facial expressions and voice to recognize the user's emotional state.

[1018] The device converts this input data and emotional data into JSON format and sends it to the server using the HTTPS protocol. The server receives this data and temporarily stores it. An analysis algorithm analyzes each parameter and emotional data. The analyzed data is passed to the generation AI, which generates an outing plan that is optimal for the user's needs and emotional state. The generation AI generates a health-oriented plan taking into account the user's specified calories burned, desired number of steps, and emotional state.

[1019] The generated plans are sent from the server to the user's device as multiple candidates. The user reviews the plans and selects the most suitable one. Once the selection is confirmed, the server saves the selection information in a database and sends a confirmation notice to the user.

[1020] This system uses a virtual library called "EmotionAnalyzer" for analyzing user emotions and "RecommendationEngine" for generating AI, which makes it possible to suggest products and stores according to the user's emotional state.

[1021] Specific examples

[1022] Consider a case where a user is shopping at a brick-and-mortar store (e.g., a shopping mall). The user logs in to the app and enters the following parameters:

[1023] Starting point: Shinjuku

[1024] Transportation: Walking

[1025] Departure time: 3:00 PM

[1026] Budget: 10,000 yen

[1027] Duration: 3 hours

[1028] Number of people going out: 1 person

[1029] Calories burned: 200 calories

[1030] Desired number of steps: 5,000 steps

[1031] The emotion engine analyzes the user's facial expressions and voice and recognizes their current emotional state as "fun." The server receives this information and uses the generative AI to generate the following plan:

[1032] Plan A: Shopping at Clothing Store A + Relax at the Book Cafe

[1033] Plan B: Shopping at Accessory Store B + Walking in the Park

[1034] These plans are sent to the user's terminal, and the user can select the most suitable plan, thus providing a pleasant shopping experience that matches his or her emotional state.

[1035] Prompt Sentence Examples

[1036] It's 3 PM and the user wants to enjoy shopping in Shinjuku within a budget of 10,000 yen. Sentiment analysis indicates the user is in the "Enjoy" state. What products and stores would you recommend?

[1037] This system allows users to plan their outings more effectively based on their emotional state.

[1038] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1039] Step 1:

[1040] Users log in to the application using their smartphone and enter parameters such as the starting point, mode of transportation, departure time, budget, travel time, number of people going out, calories burned, desired number of steps, etc. The entered information is temporarily saved by the application. Examples of input data include the starting point "Shinjuku," mode of transportation "walking," and budget "10,000 yen."

[1041] Step 2:

[1042] The emotion engine uses the camera and microphone to analyze the user's facial expressions and voice to recognize their current emotional state. For example, it can identify that the user is in an "enjoyment" emotional state based on their facial expressions and voice. The acquired emotional data is temporarily saved along with the input parameters.

[1043] Step 3:

[1044] The device converts the input parameters and emotion data into JSON format and sends it to the server using the HTTPS protocol. The data sent includes the starting point (Shinjuku), the budget (10,000 yen), and the emotional state (fun).

[1045] Step 4:

[1046] The server temporarily stores the received data before applying the analysis algorithm, which categorizes the data into parameters and emotional data.

[1047] Step 5:

[1048] The server runs an analysis algorithm to analyze the received parameters and emotional data. This analysis identifies the elements necessary to create an outing plan based on the user's starting point, budget, emotional state, etc. The server then selects an appropriate activity based on the input data "fun."

[1049] Step 6:

[1050] The analyzed data is passed to a generation AI, which generates an outing plan that best suits the user's needs and emotional state. The generation AI outputs multiple plans using, for example, a "Recommendation Engine." Specifically, it generates plans such as "Plan A: Shopping at a clothing store + Relax at a cafe" and "Plan B: Shopping at an accessory store + Walking in the park."

[1051] Step 7:

[1052] The server then converts the generated outing plan back into JSON format and sends it to the user's device. The data sent includes multiple outing plans, each with detailed activity and reason descriptions.

[1053] Step 8:

[1054] The user checks the multiple plans presented on the terminal and selects the most suitable one. The plan selected by the user is sent to the server by the application, and the selection information is saved in the database.

[1055] Step 9:

[1056] The server sends a confirmation notification of the selected plan to the user's terminal, allowing the user to confirm that the selected plan has been confirmed.

[1057] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1058] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1059] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1060] [Third embodiment]

[1061] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1062] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1063] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1064] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1065] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1066] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1067] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1068] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1069] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1070] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1071] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1072] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1073] The present invention provides a system for enabling people to enjoy going out on holidays efficiently and in a health-conscious manner. Specific embodiments of this system will be described below.

[1074] Overall system configuration

[1075] The system mainly consists of the following components:

[1076] 1. User's device (e.g. smartphone or PC)

[1077] 2. Server

[1078] 3. Generation AI

[1079] 4. Database

[1080] User operations

[1081] A user first accesses the system using a dedicated application or website and logs in.

[1082] The user inputs parameters related to the outing plan (starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.).

[1083] Sending and Receiving Data

[1084] The terminal converts all parameters entered by the user into JSON format and sends them to the server using the stable and secure HTTPS protocol.

[1085] The server receives this data and prepares it for analysis.

[1086] Data analysis and generation using AI

[1087] The server temporarily stores the received data and analyzes each parameter using an analysis algorithm.

[1088] The analyzed data is passed to the generation AI, which then generates an outing plan that best suits the user's needs.

[1089] The AI ​​takes into account the user's specified calorie consumption and desired number of steps, and compares it with past data when generating a health-oriented plan to provide a highly accurate plan.

[1090] Generate and send trip plans

[1091] The AI ​​generates multiple outing plans, each of which includes destinations, activities, how to use public transportation, estimated calories burned, estimated number of steps, etc.

[1092] The server sends the generated plans to the user's device in JSON format.

[1093] User plan selection and confirmation

[1094] The user checks the multiple plans presented on the terminal and selects the most suitable one from among them.

[1095] Once the selection is confirmed, the server stores the user's selection in a database and sends a confirmation to the user's device.

[1096] Specific examples

[1097] For example:

[1098] User A plans to go out on a holiday and logs in to the dedicated app. Next, he enters the following parameters:

[1099] Starting point: Tokyo Station

[1100] Transportation: Train and walking

[1101] Departure time: 10:00 AM

[1102] Budget: 5,000 yen

[1103] Duration: 5 hours

[1104] Number of people going out: 2

[1105] Calories burned: 300 calories

[1106] Desired number of steps: 8,000 steps

[1107] The device sends this information to the server, which receives it and analyzes it. The analysis results are passed to the generation AI, which then generates a plan like this:

[1108] Plan A: Visit to Ueno Zoo + Shopping in Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps)

[1109] Plan B: Visit Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps)

[1110] These plans are sent to the user's terminal, and User A selects and confirms Plan A. The server stores this selection information in the database and sends a confirmation notice to User A.

[1111] In this way, the user can easily obtain an outing plan that incorporates health-conscious ideas.

[1112] The processing flow will be explained below.

[1113] Step 1:

[1114] The user accesses a dedicated application or website and logs in. The user inputs parameters such as the departure point, transportation method, departure time, budget, required time, number of people going out, calories burned, and desired number of steps.

[1115] Step 2:

[1116] The terminal converts the data entered by the user into JSON format, which contains all the user's parameters.

[1117] Step 3:

[1118] The terminal sends the converted data to the server using the HTTPS protocol, which ensures secure transmission of the data.

[1119] Step 4:

[1120] The server receives the data received from the device and prepares it for analysis, converting it into an appropriate format and passing it to the analysis algorithm.

[1121] Step 5:

[1122] The server analyzes the received data using an analysis algorithm and prepares to pass the analysis results to the generation AI.

[1123] Step 6:

[1124] The AI ​​then generates an optimal outing plan based on the analyzed data, taking into account the user's desired calorie consumption and number of steps.

[1125] Step 7:

[1126] The AI ​​generates multiple different outing plans, each of which includes details such as destinations, activities, how to use public transport, estimated calories burned, and estimated number of steps.

[1127] Step 8:

[1128] The server sends multiple candidates for the generated outing plan to the user's device in JSON format.

[1129] Step 9:

[1130] The terminal displays the received outing plans on the user interface, and the user can check the plans and select the one they want.

[1131] Step 10:

[1132] The plan selected by the user is sent from the device to the server, and the selection is confirmed.

[1133] Step 11:

[1134] The server saves the user's selection in a database, confirming that the selection has been finalized.

[1135] Step 12:

[1136] The server sends a confirmation of the selection to the user's device, and the process is completed when the user receives and confirms the notification.

[1137] Example 1

[1138] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1139] Nowadays, many people are looking for ways to efficiently enjoy their holidays while maintaining their health. However, there is a lack of specific systems and methods to meet this demand. In addition, when users create their own outing plans that take health-consciousness into consideration, it takes a lot of time and effort. As a result, many people are unable to create appropriate outing plans, making it difficult to spend their holidays in a healthy manner.

[1140] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1141] In this invention, the server includes means for inputting parameters such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc. from the user, means for converting the input data into JSON format and sending it to the server using the HTTPS protocol, means for saving the received JSON format data and analyzing it using an analysis algorithm, means for sending the analysis results to the generation AI as prompt text, which generates multiple outing plans based on the user's requirements, means for sending the generated outing plans to the user's terminal in JSON format, and means for the user to select a presented plan and store the selected information in a database. This allows the user to easily obtain outing plans that incorporate health-conscious ideas.

[1142] "User" refers to an individual or organization who uses the system and creates outing plans through this system.

[1143] A "terminal" is a device used by a user to access the system, including a smartphone, PC, tablet, etc.

[1144] The "server" is a central computer that manages and controls the entire system, and is responsible for receiving and analyzing data sent by users and coordinating with the generating AI.

[1145] "Generative AI" is a type of artificial intelligence that refers to algorithms or models that generate optimal outing plans based on input data.

[1146] "Database" refers to an information storage device for efficiently storing and managing user input information, generated outing plans, selection information, etc.

[1147] "Parameters" are items of information that a user inputs into the system, such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.

[1148] The "HTTPS protocol" is a network communication protocol used when a user sends data from a device to a server, and is responsible for ensuring the secure transmission and reception of data.

[1149] The "JSON format" is a standard format for describing data in text format, and is used to efficiently send user input information to a server.

[1150] "Analysis algorithm" refers to a program with calculation procedures for analyzing data received by the server, and performs initial data processing to meet user requirements.

[1151] A "prompt sentence" is a command sentence used to send a specific generation request to the generation AI, and includes instructions that reflect the user's requirements.

[1152] An "outing plan" is an outing plan proposed by the generation AI based on the user's requirements, and includes details such as destinations, activities, how to use public transportation, planned calories burned, and planned number of steps.

[1153] "Data archiving" refers to the process by which the server temporarily or permanently stores the data it receives on a storage device.

[1154] "Data transmission" refers to the process of transferring data from a user's terminal to a server or from a server to a user's terminal.

[1155] "Calories burned" refers to the amount of energy consumed by the user while executing the going out plan.

[1156] The "desired number of steps" refers to the number of steps that the user wishes to walk while executing the outing plan.

[1157] The present invention provides a system that allows users to enjoy their holidays efficiently and with a focus on health. This system utilizes generation AI based on user input to generate optimal outing plans. Specific embodiments of this system are described below.

[1158] Overall system configuration

[1159] The system mainly consists of the following components:

[1160] 1. User's device (e.g., smartphone or personal computer)

[1161] 2. Server

[1162] 3. Generation AI

[1163] 4. Database

[1164] User operations

[1165] Users access a dedicated application or website, log in with their authentication information, and then enter parameters such as starting point, mode of transportation, departure time, budget, travel time, number of people going out, calories burned, and desired number of steps.

[1166] After the user enters various parameters, the information is converted into JSON format by the terminal and sent to the server using the HTTPS protocol. It is worth noting that this system uses secure data encryption, which is an important specification for protecting user privacy.

[1167] Server Processing

[1168] The server receives the JSON-formatted data sent from the device and temporarily stores it. Next, it analyzes each parameter using an analysis algorithm. This analysis is generally performed using Python libraries such as Pandas and NumPy.

[1169] The analysis results are sent to the generation AI as a prompt. For example, we generate a prompt that instructs the AI ​​to generate a plan departing from Tokyo Station, with a budget of 5,000 yen, consuming 300 calories, and requiring no more than 8,000 steps. This prompt looks like this:

[1170] Users are asked to create a plan to travel from Tokyo Station by train and on foot, with a budget of 5,000 yen, 300 calories burned, and a desired number of steps of 8,000 or less.

[1171] Processing of generated AI

[1172] The generation AI generates multiple outing plans based on the given prompt. The generation AI takes into account past data and the user's history to generate the optimal plan for the user. As a concrete example, the following plans are generated:

[1173] Plan A: Visit to Ueno Zoo + Shopping in Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps)

[1174] Plan B: Visit Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps)

[1175] These generated plans are converted back to JSON format and sent to the server, which then sends the generated plans to the user's device.

[1176] User plan selection

[1177] The user checks the multiple plans presented on the terminal and selects the most suitable one. Once the selection is confirmed, the server saves the selection information in a database and sends a confirmation notice to the user's terminal. When the user receives this confirmation notice, they know that the plan has been confirmed.

[1178] In this way, users can easily obtain outing plans that incorporate health-conscious ideas. This system enables users to enjoy their holidays efficiently and healthily.

[1179] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1180] Step 1: User parameter input

[1181] The user accesses a dedicated application or website and inputs parameters such as the starting point, mode of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc. The input parameters are sent to the terminal. Specifically, the user enters the required information into the form and presses the "Submit" button.

[1182] Input: Departure point, transportation method, departure time, budget, required time, number of people going out, calories burned, desired number of steps

[1183] Output: Parameter data in JSON format

[1184] Step 2: Sending data

[1185] The terminal converts the input parameters into JSON format and sends them to the server using the HTTPS protocol. Specifically, the terminal sends a POST request to the endpoint, and the data is encrypted and sent.

[1186] Input: Parameter data in JSON format

[1187] Output: Data sent to the server

[1188] Step 3: Receiving and storing data

[1189] The server receives the JSON format data sent from the device and temporarily stores it in a database. The received data is stored as is, but is prepared for later analysis.

[1190] Input: Parameter data sent in JSON format

[1191] Output: Parameter data stored in the database

[1192] Step 4: Analyze the data

[1193] The server analyzes the stored data using Python libraries such as Pandas and NumPy, converting each parameter into an appropriate format. Specific operations include reading the data, extracting necessary fields, and cleaning the data.

[1194] Input: Parameter data stored in the database

[1195] Output: Parsed parameter data

[1196] Step 5: Sending prompts to the generation AI

[1197] The server generates a prompt based on the analyzed data and sends it to the generation AI. Prompt generation involves converting the user's input data into an appropriate context. For example, a prompt might be created such as, "The user should create a plan departing from Tokyo Station, with a budget of 5,000 yen, consuming 300 calories, and requiring no more than 8,000 steps."

[1198] Input: Parsed parameter data

[1199] Output: The prompt sent to the generation AI

[1200] Step 6: Generate your trip plan

[1201] The generation AI generates an outing plan based on the prompt text. The generation AI references past data and user history to generate multiple plans. The generated plan includes specific destinations and activities, how to use public transportation, estimated calories burned, and estimated number of steps. Specifically, the generation AI model makes optimal suggestions based on the input prompt.

[1202] Input: Prompt sent to the generation AI

[1203] Output: Generated itinerary

[1204] Step 7: Submit your trip plan

[1205] The server converts the outing plan received from the generation AI into JSON format and sends it to the user's device. Specifically, the server receives the output of the generation AI and sends the data to the user's device through an endpoint.

[1206] Input: Generated trip plan

[1207] Output: Trip plan sent to the user's device in JSON format

[1208] Step 8: User Plan Selection

[1209] The user checks the multiple outing plans presented on the device and selects the most suitable one. Specifically, the user checks the details of each plan and clicks the "Select" button.

[1210] Input: Trip plan sent in JSON format

[1211] Output: Selected outing plan

[1212] Step 9: Save your selections and receive confirmation

[1213] The server stores the information of the outing plan selected by the user in a database and sends a confirmation notice to the user's terminal, specifically, by recording the selection information in the database and generating a confirmation message to send to the user's terminal.

[1214] Input: Selected outing plan

[1215] Output: Selection information stored in the database, confirmation sent to the user's device

[1216] (Application example 1)

[1217] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1218] Conventional outing plan generation systems provide outing plans that take health into consideration, but do not suggest meal plans for users. A plan that supports health-conscious outings, including the contents of meals eaten while out, is needed. Furthermore, to achieve comprehensive health management, there is a need for meal plans that are linked to outing plans.

[1219] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1220] In this invention, the server includes means for inputting parameters such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, type of meal, budget, calories per meal, etc. from the user, means for receiving and analyzing the input data, and means for generating an outing plan and meal plan that takes health into consideration using a generation AI based on the analyzed data. This allows the user to ensure consistency in not only the activities they do while out, but also their meal plan, taking health into consideration.

[1221] The "starting point" refers to the point where the user starts going out.

[1222] "Transportation" refers to the means of transportation used to travel from a departure point to a destination.

[1223] "Departure time" refers to the specific time when the user starts going out.

[1224] "Budget" refers to the amount of money planned to be spent on outings and related activities.

[1225] "Time required" refers to the length of time required for the entire outdoor activity.

[1226] "Number of people going out" refers to the number of people who participate in outdoor activities.

[1227] "Calories burned" refers to the amount of energy consumed during outdoor activities.

[1228] The "desired number of steps" refers to the number of steps that are expected to be taken during outdoor activities.

[1229] "Meal type" refers to the type of meal the user desires (e.g., breakfast, lunch, dinner, etc.).

[1230] "Generative AI" refers to artificial intelligence that automatically generates appropriate outing and meal plans based on user input data.

[1231] "Determining a plan" refers to the act of the user selecting the most suitable plan from the proposed plans and making a final decision.

[1232] A specific system and method for implementing the present invention will now be described.

[1233] System Configuration

[1234] The system consists of the following components:

[1235] 1. User's device (smartphone, PC)

[1236] 2. Server

[1237] 3. Generative AI Models

[1238] 4. Database

[1239] User operations

[1240] The user first logs in to a dedicated application or website, then enters the following parameters:

[1241] Departure Point

[1242] Transportation

[1243] Departure time

[1244] budget

[1245] Travel time

[1246] Number of people going out

[1247] Calories burned

[1248] Desired number of steps

[1249] Type of meal (e.g. breakfast, lunch, dinner)

[1250] Budget per meal

[1251] Calories per serving

[1252] Sending and Receiving Data

[1253] The user's device converts the input data into JSON format and sends it to the server using the HTTPS protocol. The server then analyzes the received data and prepares it for passing to the generative AI model.

[1254] Analyzing data and using generative AI models

[1255] The server runs the received data through an analysis algorithm and prepares the data to be passed to the generative AI model, which then generates optimal outing and meal plans based on the user's requests.The generative AI model also references past data to improve accuracy.

[1256] Generate and submit a plan

[1257] The generative AI model generates an outing plan and a meal plan, each containing the following information:

[1258] Destinations

[1259] activity

[1260] means of transportation

[1261] Estimated calorie consumption

[1262] Planned steps

[1263] Meal contents

[1264] Dining

[1265] Calorie and food budget

[1266] The server sends the generated plan in JSON format to the user's device.

[1267] User plan selection and confirmation

[1268] The user checks the displayed plans and selects the most suitable one. After selection, the server saves the selection information in the database and sends a confirmation notice to the user's device.

[1269] Specific examples

[1270] User A plans to go out and have lunch on a day off and enters the following parameters:

[1271] Starting point: Shibuya Ward

[1272] Transportation: Train and walking

[1273] Departure time: 10:00 AM

[1274] Budget: 8,000 yen

[1275] Duration: 6 hours

[1276] Number of people going out: 2

[1277] Calories burned: 500 calories

[1278] Desired number of steps: 10,000 steps

[1279] Meal type: Lunch

[1280] Budget per meal: 1,500 yen

[1281] Calories per serving: 600 calories

[1282] Based on the information sent to the server, the generative AI model analyzes and provides the following plan:

[1283] Plan A: Walk + Museum Visit + Healthy Lunch (Estimated calories burned: 520 calories, Estimated steps: 9,500 steps, Estimated calories for lunch: 580 calories)

[1284] Plan B: Walk in the park + Shopping + Low-calorie restaurant lunch (Estimated calories burned: 480 calories, Estimated steps: 10,500 steps, Estimated calories for lunch: 590 calories)

[1285] User A selects Plan A, and the server saves the selection in the database and sends a confirmation.

[1286] Main hardware and software used

[1287] Hardware: Web server (e.g. AWS EC2)

[1288] Software: Flask (Python library), HTTP protocol, generative AI (via API)

[1289] Prompt Sentence Examples

[1290] "Please suggest a healthy meal plan for location: Shibuya Ward, type: lunch, budget: 1500 yen, calories: 600 kcal."

[1291] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1292] Step 1:

[1293] The user logs in to a dedicated application or website and enters the following parameters: starting point, transportation method, departure time, budget, required time, number of people going out, calories burned, desired number of steps, type of meal, budget per meal, and calories per meal. This data is entered into the user's device and converted into JSON format.

[1294] Step 2:

[1295] The user's device sends the data converted into JSON format to the server using the HTTPS protocol, where it is encrypted to ensure security.

[1296] Step 3:

[1297] The server receives the data sent from the user's device, analyzes it using an analysis algorithm, and prepares it for passing to the generative AI model. Specifically, it checks the data for consistency and whether there is any missing information or data in the wrong format.

[1298] Step 4:

[1299] The server inputs the analyzed data into a generative AI model, which generates prompts and then generates health-conscious outing and meal plans based on the prompts.

[1300] Example: "Please suggest a healthy meal plan for location: Shibuya Ward, type: lunch, budget: 1500 yen, calories: 600 kcal."

[1301] Step 5:

[1302] The generative AI model generates multiple plans based on the input prompts. The generated outing and meal plans include destinations, activities, transportation, estimated calories burned, estimated steps, meal contents, meal locations, estimated calories for each meal, and budget.

[1303] Step 6:

[1304] The server sends multiple plans generated by the generative AI model to the user's device, where the plans are sent in JSON format and displayed on the user's device.

[1305] Step 7:

[1306] The user checks the multiple plans presented on the terminal and selects the most suitable one. Once the selection is confirmed, the information is sent from the user's terminal to the server.

[1307] Step 8:

[1308] The server stores the user's selected plan in a database and sends a confirmation notice to the user's terminal, so that the user can go out and eat according to the plan.

[1309] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1310] The present invention provides a system for planning a holiday outing that takes into account the user's emotions and allows the user to enjoy an efficient and health-conscious lifestyle. Specific embodiments of this system will be described below.

[1311] Overall system configuration

[1312] The system mainly consists of the following components:

[1313] 1. User's device (e.g. smartphone or PC)

[1314] 2. Server

[1315] 3. Generation AI

[1316] 4. Emotion Engine

[1317] 5. Database

[1318] User operations

[1319] A user first accesses the system using a dedicated application or website and logs in.

[1320] The user inputs parameters related to the outing plan (starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.).

[1321] Using the Emotion Engine

[1322] The emotion engine uses a camera and microphone to analyze facial expressions and voice while the user is typing, recognizing the user's emotional state.

[1323] Emotion data is captured in real time to assist the user in the input process.

[1324] Sending and Receiving Data

[1325] The terminal converts the data and emotion data entered by the user into JSON format and sends it to the server using the HTTPS protocol.

[1326] The server receives this data and prepares it for analysis.

[1327] Data analysis and generation using AI

[1328] The server temporarily stores the received data and analyzes each parameter and emotion data using an analysis algorithm.

[1329] The analyzed data is passed to the generation AI, which then generates an outing plan that best suits the user's needs and emotional state.

[1330] The AI ​​takes into account the user's specified calorie consumption, desired number of steps, and emotional state, and compares it with past data to generate a health-oriented plan, providing a highly accurate plan.

[1331] Generate and send trip plans

[1332] The AI ​​generates multiple outing plans, each of which includes destinations, activities, how to use public transportation, estimated calories burned, estimated number of steps, and content appropriate to the user's emotional state.

[1333] The server sends the generated plans to the user's device in JSON format.

[1334] User plan selection and confirmation

[1335] The user checks the multiple plans presented on the terminal and selects the most suitable one from among them.

[1336] Once the selection is confirmed, the server stores the user's selection in a database and sends a confirmation to the user's device.

[1337] Specific examples

[1338] For example:

[1339] User A plans to go out on a holiday and logs in to the dedicated app. Next, he enters the following parameters:

[1340] Starting point: Tokyo Station

[1341] Transportation: Train and walking

[1342] Departure time: 10:00 AM

[1343] Budget: 5,000 yen

[1344] Duration: 5 hours

[1345] Number of people going out: 2

[1346] Calories burned: 300 calories

[1347] Desired number of steps: 8,000 steps

[1348] While inputting, the emotion engine analyzes User A's facial expressions and voice and recognizes their current emotional state as "enjoyment." The device sends this information to the server, which receives the information and analyzes it. The analysis results and emotion data are passed to the generation AI, which generates the following plan:

[1349] Plan A: Visit to Ueno Zoo + Shopping at Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps, Reason for suggestion: Matches the emotion of enjoyment)

[1350] Plan B: Visit to Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps, Reason for suggestion: Matches the emotion of enjoyment)

[1351] These plans are sent to the user's terminal, and User A selects and confirms Plan A. The server stores this selection information in the database and sends a confirmation notice to User A.

[1352] In this way, the user can easily obtain an outing plan that incorporates health consciousness and emotional state.

[1353] The processing flow will be explained below.

[1354] Step 1:

[1355] The user accesses a dedicated application or website and logs in. The user inputs parameters such as the departure point, transportation method, departure time, budget, required time, number of people going out, calories burned, and desired number of steps.

[1356] Step 2:

[1357] The emotion engine uses the user's camera and microphone to analyze facial expressions and voice to recognize the user's emotional state in real time, detecting emotions such as joy, sadness, and fun.

[1358] Step 3:

[1359] The device converts all data and emotion data entered by the user into JSON format, which includes all the user's parameters.

[1360] Step 4:

[1361] The terminal sends the converted data to the server using the HTTPS protocol, which ensures secure transmission of the data.

[1362] Step 5:

[1363] The server receives the data received from the device and prepares it for analysis, converting it into an appropriate format and passing it to the analysis algorithm.

[1364] Step 6:

[1365] The server uses an analysis algorithm to analyze the received data and emotional data, for example, matching the user's input parameters with their emotional state.

[1366] Step 7:

[1367] The server passes the analysis results to the generation AI, which prepares to generate the optimal outing plan based on the user's requests and emotional state.

[1368] Step 8:

[1369] The AI ​​generates multiple outing plans based on the user's calorie consumption, desired number of steps, and emotional state. Each plan includes destinations, activities, how to use public transportation, planned calorie consumption, planned number of steps, and content appropriate for the user's emotional state.

[1370] Step 9:

[1371] The server sends multiple candidates for the generated outing plan to the user's device in JSON format.

[1372] Step 10:

[1373] The terminal displays the received outing plans on the user interface, and the user can check the plans and select the one they want.

[1374] Step 11:

[1375] The plan selected by the user is sent from the device to the server, and the selection is confirmed.

[1376] Step 12:

[1377] The server saves the user's selection in a database, confirming that the selection has been finalized.

[1378] Step 13:

[1379] The server sends a confirmation of the selection to the user's device, and the process is completed when the user receives and confirms the notification.

[1380] Example 2

[1381] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1382] Conventional outing plan creation systems have difficulty providing plans that fully consider the user's emotional state and health preferences. Furthermore, they have been unable to meet modern user needs, such as secure transmission of user input data and evaluation of exercise volume. As a result, they often provide plans that are unsatisfactory for users.

[1383] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting parameters such as a starting point, a means of transportation, a departure time, a budget, a required time, the number of accompanying persons, calories burned, and a desired number of steps from a user; means for analyzing the user's facial expressions and voice using a camera and a microphone to collect emotional data; means for receiving the input data and emotional data, converting it into JSON format, and transmitting it to the server; means for storing the received data in the server and analyzing it using an analytical algorithm; means for using a generation AI based on the analyzed data to generate a health-oriented outing plan that is optimal for the user's requests and emotional state; means for transmitting the generated outing plan to the user's terminal; and means for the user to select the generated outing plan and store the selected information in a database. This makes it possible to provide an outing plan that takes into account the user's emotional state and health-orientedness.

[1384] "User" refers to an individual who uses the system to create an outing plan.

[1385] A "terminal" refers to an electronic device used by a user to manipulate input data, such as a smartphone or a personal computer.

[1386] "Server" refers to the computer system that receives and stores data sent by users, analyzes it, and generates plans.

[1387] "Database" refers to a system for storing user inputs and selections.

[1388] "Generative AI" refers to artificial intelligence that generates optimal outing plans based on the user's requests and emotional state.

[1389] An "emotion engine" refers to software that analyzes a user's facial expressions and voice to collect emotional data.

[1390] The "starting point" refers to the starting point of the user's outing plan.

[1391] "Transportation" refers to the means of transportation used by the user when going out.

[1392] "Departure time" refers to the time when the user starts going out.

[1393] The "budget" refers to the amount of money that a user can spend when going out.

[1394] "Time required" refers to the time the user plans to spend going out.

[1395] "Number of people accompanying" refers to the number of other people who go out with the user.

[1396] "Calories burned" refers to the amount of calories the user plans to burn while out.

[1397] The "desired number of steps" refers to the number of steps that the user wishes to achieve while out and about.

[1398] "Emotion data" refers to data that indicates the user's emotional state, obtained as a result of the emotion engine's analysis of the user's facial expressions and voice.

[1399] "JSON format" refers to a lightweight data interchange format that is widely used to send and receive data.

[1400] "Analysis Algorithm" refers to the computational method used by the Server to analyze Data.

[1401] A "health-oriented outing plan" refers to an outing plan that takes into consideration the user's health, and includes a plan that takes into consideration the amount of exercise, such as calories burned and number of steps.

[1402] The present invention provides a system that provides an outing plan that takes into account the user's emotional state and health preferences. The system is composed of the following elements:

[1403] 1. User's device (e.g. smartphone or PC)

[1404] 2. Server

[1405] 3. Generative AI (e.g. OpenAI GPT-3)

[1406] 4. Emotion engine (e.g. Affectiva SDK)

[1407] 5. Database (e.g. MySQL)

[1408] User operations

[1409] A user accesses a dedicated application or website and logs in by entering their username and password. This action causes the device to send the user's authentication information to the server, which then checks the database to authenticate the user. If authentication is successful, the server generates a session token and sends it back to the device.

[1410] Enter your outing plan

[1411] After a successful login, the user enters the following parameters regarding their travel plans:

[1412] Departure Point

[1413] Transportation

[1414] Departure time

[1415] budget

[1416] Travel time

[1417] Number of people accompanying

[1418] Calories burned

[1419] Desired number of steps

[1420] The device collects this data in real time.

[1421] Using the Emotion Engine

[1422] The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice and collect their current emotional state in real time. For example, the emotion engine (Affectiva SDK) identifies the user's emotional state from their facial expressions and voice and generates emotion data such as "enjoyment" or "relaxation." This emotion data is stored on the device.

[1423] Sending and Receiving Data

[1424] The device converts the parameters and emotion data entered by the user into JSON format and sends it to the server using the HTTPS protocol. The server receives this data and stores it in a database.

[1425] Analyze data and generate plans

[1426] The server analyzes the stored data based on an analysis algorithm, evaluating each parameter and emotional data. The analysis results are then passed to the generation AI (OpenAI GPT-3), which generates an outing plan that best suits the user's needs and emotional state. For example, the following prompt sentence is input to the generation AI:

[1427] "Generate an outing plan for the user. User input parameters are as follows:

[1428] Starting point: Tokyo Station

[1429] Transportation: Train and walking

[1430] Departure time: 10:00 AM

[1431] Budget: 5,000 yen

[1432] Duration: 5 hours

[1433] Number of people accompanying: 2 people

[1434] Calories burned: 300 calories

[1435] Desired number of steps: 8000 steps

[1436] Current emotional state: Enjoyment

[1437] Based on these, please suggest two outing plans that suit the user's health preferences and emotional state.

[1438] The AI ​​generates multiple outing plans based on the user's needs and emotional state. Each plan includes destinations, activities, transportation, estimated calories burned, estimated number of steps, and a reason for suggesting the plan based on the user's emotional state.

[1439] Sending and selecting outing plans

[1440] The server converts the generated outing plan into JSON format and sends it to the user's device. The user reviews the multiple plans provided and selects the most suitable one. Once the selection is confirmed, the device notifies the server of the selected plan, and the server stores this information in a database. The server also sends a selection confirmation to the user.

[1441] Specific examples

[1442] For example, if User A is planning to go out on a holiday, he / she will follow the steps below:

[1443] User A logs in to the dedicated app and enters the following parameters:

[1444] Starting point: Tokyo Station

[1445] Transportation: Train and walking

[1446] Departure time: 10:00 AM

[1447] Budget: 5,000 yen

[1448] Duration: 5 hours

[1449] Number of people accompanying: 2 people

[1450] Calories burned: 300 calories

[1451] Desired number of steps: 8,000 steps

[1452] While inputting, the emotion engine analyzes User A's facial expressions and voice and recognizes their current emotional state as "fun." The device sends this information to the server, which receives and analyzes the information. The analysis results and emotion data are then passed to the generation AI, which generates the following outing plan:

[1453] Plan A: Visit to Ueno Zoo + Shopping at Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps, Reason for suggestion: Matches the emotion of enjoyment)

[1454] Plan B: Visit to Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps, Reason for suggestion: Matches the emotion of enjoyment)

[1455] These plans are sent to the user's device, and User A selects and confirms Plan A. The server stores this selection information in a database and sends a confirmation notice to User A. In this way, users can easily obtain outing plans that incorporate their emotional state and health preferences.

[1456] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1457] Step 1: User Login

[1458] A user accesses a dedicated application or website and logs in by entering their username and password. The device receives these authentication information as input and sends it to the server via the HTTPS protocol. The server checks it against a database and authenticates the user. If authentication is successful, the server generates a session token and sends it back to the device as output.

[1459] Specific behavior:

[1460] The user launches the app and enters their username and password on the login screen.

[1461] The terminal sends the input data to the server.

[1462] The server checks the credentials in the database.

[1463] If authentication is successful, the server generates a session token and returns it to the terminal.

[1464] Step 2: Enter the user's travel plans

[1465] The user inputs parameters related to their trip plan through the application interface, including the starting point, mode of transportation, departure time, budget, travel time, number of people accompanying them, calories burned, and desired number of steps. The device receives this data as input and collects it in real time.

[1466] Specific behavior:

[1467] The user enters the parameters of the trip plan into a form in the application.

[1468] The terminal stores these data in variables and prepares to send them to the server in the next step.

[1469] Step 3: Collecting emotion data with the emotion engine

[1470] The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice to collect emotion data. Emotion data includes emotions such as "enjoyment" and "relaxation." The emotion engine receives this data as input and generates emotion data as output.

[1471] Specific behavior:

[1472] The emotion engine analyzes camera footage and audio data as input.

[1473] The emotional state of the user is identified from facial expressions and voice, and emotional data is generated.

[1474] The generated emotion data is stored in the terminal.

[1475] Step 4: Sending data

[1476] The device converts the parameters of the outing plan and emotion data entered by the user into JSON format, and sends the converted JSON data as input to the server using the HTTPS protocol.

[1477] Specific behavior:

[1478] The device converts the outing plan parameters and emotion data into JSON format.

[1479] The converted JSON data is sent to the server via HTTPS protocol.

[1480] Step 5: Receiving and storing data

[1481] The server receives JSON data sent from the terminal and takes it in as input. It saves the received data in the database and generates a save completion status as output.

[1482] Specific behavior:

[1483] The server receives the HTTPS request and parses the JSON data.

[1484] The parsed data is stored in a database.

[1485] Generates a save completion status.

[1486] Step 6: Analyze the data

[1487] The server retrieves data stored in the database and analyzes the input data using an analysis algorithm. The analysis results are output as prompts to be passed to the generation AI.

[1488] Specific behavior:

[1489] The server retrieves the stored data from the database.

[1490] Data analysis algorithms evaluate each parameter and emotion data.

[1491] Generate prompts for generative AI models.

[1492] Step 7: Generate a plan using generative AI

[1493] The generative AI (e.g., OpenAI GPT-3) receives prompts sent from the server as input and generates the optimal outing plan. The generated plan is output to the server as multiple options.

[1494] Specific behavior:

[1495] The generative AI model receives the prompt sentence as input.

[1496] To generate multiple outing plans based on a user's emotional state and health preferences.

[1497] The generated plan is sent back to the server.

[1498] Step 8: Submit your plan

[1499] The server converts the generated outing plan into JSON format and sends it to the device, which then analyzes the received data and displays it to the user.

[1500] Specific behavior:

[1501] The server formats the generated plan into JSON.

[1502] Sends JSON data to the terminal via HTTPS protocol.

[1503] The terminal analyzes the received data and displays it to the user.

[1504] Step 9: User plan selection and confirmation

[1505] The user reviews multiple outing plans displayed on the device and selects the most suitable one. The device receives the selected plan information as input and sends it to the server. The server stores this information in a database and returns a selection confirmation to the device.

[1506] Specific behavior:

[1507] The user checks the outing plan on the terminal and clicks the selection button.

[1508] The terminal transmits information about the selected plan to the server.

[1509] The server stores the selection information in a database.

[1510] The server sends a confirmation of the selection back to the terminal.

[1511] (Application example 2)

[1512] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1513] Conventional outing plan generation systems do not consider the user's emotional state when proposing plans, which can result in low user satisfaction. Furthermore, if outing plans could be proposed that reflect the user's intuitive emotional state, rather than just taking health-consciousness into account, a more fulfilling experience could be provided. The present invention aims to provide a system that generates outing plans that also consider the user's emotional state, thereby increasing user satisfaction.

[1514] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1515] In this invention, the server includes means for inputting parameters such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc. from the user, means for receiving and analyzing the input data and emotional state data, and means for generating an outing plan that takes into account health orientation and emotional state using a generation AI based on the analyzed data, thereby making it possible to provide an outing plan optimized for the user's emotional state.

[1516] The "starting point" refers to the location where the user starts going out.

[1517] "Transportation" refers to the means of transportation used by the user when out and about.

[1518] "Departure time" refers to the time when the user starts going out.

[1519] The "budget" refers to the upper limit of the amount of money that the user can spend on this outing.

[1520] The "required time" refers to the total time the user plans to spend out.

[1521] The "number of people going out" refers to the number of people accompanying the user on an outing.

[1522] "Calories burned" refers to the amount of calories the user plans to burn while out.

[1523] The "desired number of steps" refers to the number of steps the user wishes to walk while out.

[1524] "Emotional state" refers to the user's current emotional or psychological state.

[1525] "Input means" refers to a device or method by which a user inputs parameters into the system.

[1526] "Means for receiving and analyzing" refers to a device or method for receiving parameters and emotion data input by a user and analyzing them.

[1527] "Means for generating" refers to a device or method for generating an outing plan based on input data using a generating AI.

[1528] The "transmitting means" refers to a device or method for transmitting the generated outing plan to the user's terminal.

[1529] The "means for selecting and confirming" refers to a device or method that allows a user to select from among the proposed outing plans and confirm the plan.

[1530] This system optimizes the shopping experience in brick-and-mortar stores by generating health-conscious outing plans that take into account the user's emotions. This system mainly consists of a user's device, a server, a generative AI model, an emotion engine, and a database.

[1531] First, users access the system using a dedicated smartphone application and log in. Next, they input parameters such as the starting point, mode of transportation, departure time, budget, travel time, number of people going out, calories burned, desired number of steps, etc. While the user is entering information, the emotion engine uses the camera and microphone to analyze facial expressions and voice to recognize the user's emotional state.

[1532] The device converts this input data and emotional data into JSON format and sends it to the server using the HTTPS protocol. The server receives this data and temporarily stores it. An analysis algorithm analyzes each parameter and emotional data. The analyzed data is passed to the generation AI, which generates an outing plan that is optimal for the user's needs and emotional state. The generation AI generates a health-oriented plan taking into account the user's specified calories burned, desired number of steps, and emotional state.

[1533] The generated plans are sent from the server to the user's device as multiple candidates. The user reviews the plans and selects the most suitable one. Once the selection is confirmed, the server saves the selection information in a database and sends a confirmation notice to the user.

[1534] This system uses a virtual library called "EmotionAnalyzer" for analyzing user emotions and "RecommendationEngine" for generating AI, which makes it possible to suggest products and stores according to the user's emotional state.

[1535] Specific examples

[1536] Consider a case where a user is shopping at a brick-and-mortar store (e.g., a shopping mall). The user logs in to the app and enters the following parameters:

[1537] Starting point: Shinjuku

[1538] Transportation: Walking

[1539] Departure time: 3:00 PM

[1540] Budget: 10,000 yen

[1541] Duration: 3 hours

[1542] Number of people going out: 1 person

[1543] Calories burned: 200 calories

[1544] Desired number of steps: 5,000 steps

[1545] The emotion engine analyzes the user's facial expressions and voice and recognizes their current emotional state as "fun." The server receives this information and uses the generative AI to generate the following plan:

[1546] Plan A: Shopping at Clothing Store A + Relax at the Book Cafe

[1547] Plan B: Shopping at Accessory Store B + Walking in the Park

[1548] These plans are sent to the user's terminal, and the user can select the most suitable plan, thus providing a pleasant shopping experience that matches his or her emotional state.

[1549] Prompt Sentence Examples

[1550] It's 3 PM and the user wants to enjoy shopping in Shinjuku within a budget of 10,000 yen. Sentiment analysis indicates the user is in the "Enjoy" state. What products and stores would you recommend?

[1551] This system allows users to plan their outings more effectively based on their emotional state.

[1552] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1553] Step 1:

[1554] Users log in to the application using their smartphone and enter parameters such as the starting point, mode of transportation, departure time, budget, travel time, number of people going out, calories burned, desired number of steps, etc. The entered information is temporarily saved by the application. Examples of input data include the starting point "Shinjuku," mode of transportation "walking," and budget "10,000 yen."

[1555] Step 2:

[1556] The emotion engine uses the camera and microphone to analyze the user's facial expressions and voice to recognize their current emotional state. For example, it can identify that the user is in an "enjoyment" emotional state based on their facial expressions and voice. The acquired emotional data is temporarily saved along with the input parameters.

[1557] Step 3:

[1558] The device converts the input parameters and emotion data into JSON format and sends it to the server using the HTTPS protocol. The data sent includes the starting point (Shinjuku), the budget (10,000 yen), and the emotional state (fun).

[1559] Step 4:

[1560] The server temporarily stores the received data before applying the analysis algorithm, which categorizes the data into parameters and emotional data.

[1561] Step 5:

[1562] The server runs an analysis algorithm to analyze the received parameters and emotional data. This analysis identifies the elements necessary to create an outing plan based on the user's starting point, budget, emotional state, etc. The server then selects an appropriate activity based on the input data "fun."

[1563] Step 6:

[1564] The analyzed data is passed to a generation AI, which generates an outing plan that best suits the user's needs and emotional state. The generation AI outputs multiple plans using, for example, a "Recommendation Engine." Specifically, it generates plans such as "Plan A: Shopping at a clothing store + Relax at a cafe" and "Plan B: Shopping at an accessory store + Walking in the park."

[1565] Step 7:

[1566] The server then converts the generated outing plan back into JSON format and sends it to the user's device. The data sent includes multiple outing plans, each with detailed activity and reason descriptions.

[1567] Step 8:

[1568] The user checks the multiple plans presented on the terminal and selects the most suitable one. The plan selected by the user is sent to the server by the application, and the selection information is saved in the database.

[1569] Step 9:

[1570] The server sends a confirmation notification of the selected plan to the user's terminal, allowing the user to confirm that the selected plan has been confirmed.

[1571] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1572] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1573] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1574] [Fourth embodiment]

[1575] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1576] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1577] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1578] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1579] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1580] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1581] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1582] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1583] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1584] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1585] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1586] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1587] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1588] The present invention provides a system for enabling people to enjoy going out on holidays efficiently and in a health-conscious manner. Specific embodiments of this system will be described below.

[1589] Overall system configuration

[1590] The system mainly consists of the following components:

[1591] 1. User's device (e.g. smartphone or PC)

[1592] 2. Server

[1593] 3. Generation AI

[1594] 4. Database

[1595] User operations

[1596] A user first accesses the system using a dedicated application or website and logs in.

[1597] The user inputs parameters related to the outing plan (starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.).

[1598] Sending and Receiving Data

[1599] The terminal converts all parameters entered by the user into JSON format and sends them to the server using the stable and secure HTTPS protocol.

[1600] The server receives this data and prepares it for analysis.

[1601] Data analysis and generation using AI

[1602] The server temporarily stores the received data and analyzes each parameter using an analysis algorithm.

[1603] The analyzed data is passed to the generation AI, which then generates an outing plan that best suits the user's needs.

[1604] The AI ​​takes into account the user's specified calorie consumption and desired number of steps, and compares it with past data when generating a health-oriented plan to provide a highly accurate plan.

[1605] Generate and send trip plans

[1606] The AI ​​generates multiple outing plans, each of which includes destinations, activities, how to use public transportation, estimated calories burned, estimated number of steps, etc.

[1607] The server sends the generated plans to the user's device in JSON format.

[1608] User plan selection and confirmation

[1609] The user checks the multiple plans presented on the terminal and selects the most suitable one from among them.

[1610] Once the selection is confirmed, the server stores the user's selection in a database and sends a confirmation to the user's device.

[1611] Specific examples

[1612] For example:

[1613] User A plans to go out on a holiday and logs in to the dedicated app. Next, he enters the following parameters:

[1614] Starting point: Tokyo Station

[1615] Transportation: Train and walking

[1616] Departure time: 10:00 AM

[1617] Budget: 5,000 yen

[1618] Duration: 5 hours

[1619] Number of people going out: 2

[1620] Calories burned: 300 calories

[1621] Desired number of steps: 8,000 steps

[1622] The device sends this information to the server, which receives it and analyzes it. The analysis results are passed to the generation AI, which then generates a plan like this:

[1623] Plan A: Visit to Ueno Zoo + Shopping in Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps)

[1624] Plan B: Visit Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps)

[1625] These plans are sent to the user's terminal, and User A selects and confirms Plan A. The server stores this selection information in the database and sends a confirmation notice to User A.

[1626] In this way, the user can easily obtain an outing plan that incorporates health-conscious ideas.

[1627] The processing flow will be explained below.

[1628] Step 1:

[1629] The user accesses a dedicated application or website and logs in. The user inputs parameters such as the departure point, transportation method, departure time, budget, required time, number of people going out, calories burned, and desired number of steps.

[1630] Step 2:

[1631] The terminal converts the data entered by the user into JSON format, which contains all the user's parameters.

[1632] Step 3:

[1633] The terminal sends the converted data to the server using the HTTPS protocol, which ensures secure transmission of the data.

[1634] Step 4:

[1635] The server receives the data received from the device and prepares it for analysis, converting it into an appropriate format and passing it to the analysis algorithm.

[1636] Step 5:

[1637] The server analyzes the received data using an analysis algorithm and prepares to pass the analysis results to the generation AI.

[1638] Step 6:

[1639] The AI ​​then generates an optimal outing plan based on the analyzed data, taking into account the user's desired calorie consumption and number of steps.

[1640] Step 7:

[1641] The AI ​​generates multiple different outing plans, each of which includes details such as destinations, activities, how to use public transport, estimated calories burned, and estimated number of steps.

[1642] Step 8:

[1643] The server sends multiple candidates for the generated outing plan to the user's device in JSON format.

[1644] Step 9:

[1645] The terminal displays the received outing plans on the user interface, and the user can check the plans and select the one they want.

[1646] Step 10:

[1647] The plan selected by the user is sent from the device to the server, and the selection is confirmed.

[1648] Step 11:

[1649] The server saves the user's selection in a database, confirming that the selection has been finalized.

[1650] Step 12:

[1651] The server sends a confirmation of the selection to the user's device, and the process is completed when the user receives and confirms the notification.

[1652] Example 1

[1653] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1654] Nowadays, many people are looking for ways to efficiently enjoy their holidays while maintaining their health. However, there is a lack of specific systems and methods to meet this demand. In addition, when users create their own outing plans that take health-consciousness into consideration, it takes a lot of time and effort. As a result, many people are unable to create appropriate outing plans, making it difficult to spend their holidays in a healthy manner.

[1655] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1656] In this invention, the server includes means for inputting parameters such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc. from the user, means for converting the input data into JSON format and sending it to the server using the HTTPS protocol, means for saving the received JSON format data and analyzing it using an analysis algorithm, means for sending the analysis results to the generation AI as prompt text, which generates multiple outing plans based on the user's requirements, means for sending the generated outing plans to the user's terminal in JSON format, and means for the user to select a presented plan and store the selected information in a database. This allows the user to easily obtain outing plans that incorporate health-conscious ideas.

[1657] "User" refers to an individual or organization who uses the system and creates outing plans through this system.

[1658] A "terminal" is a device used by a user to access the system, including a smartphone, PC, tablet, etc.

[1659] The "server" is a central computer that manages and controls the entire system, and is responsible for receiving and analyzing data sent by users and coordinating with the generating AI.

[1660] "Generative AI" is a type of artificial intelligence that refers to algorithms or models that generate optimal outing plans based on input data.

[1661] "Database" refers to an information storage device for efficiently storing and managing user input information, generated outing plans, selection information, etc.

[1662] "Parameters" are items of information that a user inputs into the system, such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.

[1663] The "HTTPS protocol" is a network communication protocol used when a user sends data from a device to a server, and is responsible for ensuring the secure transmission and reception of data.

[1664] The "JSON format" is a standard format for describing data in text format, and is used to efficiently send user input information to a server.

[1665] "Analysis algorithm" refers to a program with calculation procedures for analyzing data received by the server, and performs initial data processing to meet user requirements.

[1666] A "prompt sentence" is a command sentence used to send a specific generation request to the generation AI, and includes instructions that reflect the user's requirements.

[1667] An "outing plan" is an outing plan proposed by the generation AI based on the user's requirements, and includes details such as destinations, activities, how to use public transportation, planned calories burned, and planned number of steps.

[1668] "Data archiving" refers to the process by which the server temporarily or permanently stores the data it receives on a storage device.

[1669] "Data transmission" refers to the process of transferring data from a user's terminal to a server or from a server to a user's terminal.

[1670] "Calories burned" refers to the amount of energy consumed by the user while executing the going out plan.

[1671] The "desired number of steps" refers to the number of steps that the user wishes to walk while executing the outing plan.

[1672] The present invention provides a system that allows users to enjoy their holidays efficiently and with a focus on health. This system utilizes generation AI based on user input to generate optimal outing plans. Specific embodiments of this system are described below.

[1673] Overall system configuration

[1674] The system mainly consists of the following components:

[1675] 1. User's device (e.g., smartphone or personal computer)

[1676] 2. Server

[1677] 3. Generation AI

[1678] 4. Database

[1679] User operations

[1680] Users access a dedicated application or website, log in with their authentication information, and then enter parameters such as starting point, mode of transportation, departure time, budget, travel time, number of people going out, calories burned, and desired number of steps.

[1681] After the user enters various parameters, the information is converted into JSON format by the terminal and sent to the server using the HTTPS protocol. It is worth noting that this system uses secure data encryption, which is an important specification for protecting user privacy.

[1682] Server Processing

[1683] The server receives the JSON-formatted data sent from the device and temporarily stores it. Next, it analyzes each parameter using an analysis algorithm. This analysis is generally performed using Python libraries such as Pandas and NumPy.

[1684] The analysis results are sent to the generation AI as a prompt. For example, we generate a prompt that instructs the AI ​​to generate a plan departing from Tokyo Station, with a budget of 5,000 yen, consuming 300 calories, and requiring no more than 8,000 steps. This prompt looks like this:

[1685] Users are asked to create a plan to travel from Tokyo Station by train and on foot, with a budget of 5,000 yen, 300 calories burned, and a desired number of steps of 8,000 or less.

[1686] Processing of generated AI

[1687] The generation AI generates multiple outing plans based on the given prompt. The generation AI takes into account past data and the user's history to generate the optimal plan for the user. As a concrete example, the following plans are generated:

[1688] Plan A: Visit to Ueno Zoo + Shopping in Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps)

[1689] Plan B: Visit Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps)

[1690] These generated plans are converted back to JSON format and sent to the server, which then sends the generated plans to the user's device.

[1691] User plan selection

[1692] The user checks the multiple plans presented on the terminal and selects the most suitable one. Once the selection is confirmed, the server saves the selection information in a database and sends a confirmation notice to the user's terminal. When the user receives this confirmation notice, they know that the plan has been confirmed.

[1693] In this way, users can easily obtain outing plans that incorporate health-conscious ideas. This system enables users to enjoy their holidays efficiently and healthily.

[1694] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1695] Step 1: User parameter input

[1696] The user accesses a dedicated application or website and inputs parameters such as the starting point, mode of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc. The input parameters are sent to the terminal. Specifically, the user enters the required information into the form and presses the "Submit" button.

[1697] Input: Departure point, transportation method, departure time, budget, required time, number of people going out, calories burned, desired number of steps

[1698] Output: Parameter data in JSON format

[1699] Step 2: Sending data

[1700] The terminal converts the input parameters into JSON format and sends them to the server using the HTTPS protocol. Specifically, the terminal sends a POST request to the endpoint, and the data is encrypted and sent.

[1701] Input: Parameter data in JSON format

[1702] Output: Data sent to the server

[1703] Step 3: Receiving and storing data

[1704] The server receives the JSON format data sent from the device and temporarily stores it in a database. The received data is stored as is, but is prepared for later analysis.

[1705] Input: Parameter data sent in JSON format

[1706] Output: Parameter data stored in the database

[1707] Step 4: Analyze the data

[1708] The server analyzes the stored data using Python libraries such as Pandas and NumPy, converting each parameter into an appropriate format. Specific operations include reading the data, extracting necessary fields, and cleaning the data.

[1709] Input: Parameter data stored in the database

[1710] Output: Parsed parameter data

[1711] Step 5: Sending prompts to the generation AI

[1712] The server generates a prompt based on the analyzed data and sends it to the generation AI. Prompt generation involves converting the user's input data into an appropriate context. For example, a prompt might be created such as, "The user should create a plan departing from Tokyo Station, with a budget of 5,000 yen, consuming 300 calories, and requiring no more than 8,000 steps."

[1713] Input: Parsed parameter data

[1714] Output: The prompt sent to the generation AI

[1715] Step 6: Generate your trip plan

[1716] The generation AI generates an outing plan based on the prompt text. The generation AI references past data and user history to generate multiple plans. The generated plan includes specific destinations and activities, how to use public transportation, estimated calories burned, and estimated number of steps. Specifically, the generation AI model makes optimal suggestions based on the input prompt.

[1717] Input: Prompt sent to the generation AI

[1718] Output: Generated itinerary

[1719] Step 7: Submit your trip plan

[1720] The server converts the outing plan received from the generation AI into JSON format and sends it to the user's device. Specifically, the server receives the output of the generation AI and sends the data to the user's device through an endpoint.

[1721] Input: Generated trip plan

[1722] Output: Trip plan sent to the user's device in JSON format

[1723] Step 8: User Plan Selection

[1724] The user checks the multiple outing plans presented on the device and selects the most suitable one. Specifically, the user checks the details of each plan and clicks the "Select" button.

[1725] Input: Trip plan sent in JSON format

[1726] Output: Selected outing plan

[1727] Step 9: Save your selections and receive confirmation

[1728] The server stores the information of the outing plan selected by the user in a database and sends a confirmation notice to the user's terminal, specifically, by recording the selection information in the database and generating a confirmation message to send to the user's terminal.

[1729] Input: Selected outing plan

[1730] Output: Selection information stored in the database, confirmation sent to the user's device

[1731] (Application example 1)

[1732] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1733] Conventional outing plan generation systems provide outing plans that take health into consideration, but do not suggest meal plans for users. A plan that supports health-conscious outings, including the contents of meals eaten while out, is needed. Furthermore, to achieve comprehensive health management, there is a need for meal plans that are linked to outing plans.

[1734] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1735] In this invention, the server includes means for inputting parameters such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, type of meal, budget, calories per meal, etc. from the user, means for receiving and analyzing the input data, and means for generating an outing plan and meal plan that takes health into consideration using a generation AI based on the analyzed data. This allows the user to ensure consistency in not only the activities they do while out, but also their meal plan, taking health into consideration.

[1736] The "starting point" refers to the point where the user starts going out.

[1737] "Transportation" refers to the means of transportation used to travel from a departure point to a destination.

[1738] "Departure time" refers to the specific time when the user starts going out.

[1739] "Budget" refers to the amount of money planned to be spent on outings and related activities.

[1740] "Time required" refers to the length of time required for the entire outdoor activity.

[1741] "Number of people going out" refers to the number of people who participate in outdoor activities.

[1742] "Calories burned" refers to the amount of energy consumed during outdoor activities.

[1743] The "desired number of steps" refers to the number of steps that are expected to be taken during outdoor activities.

[1744] "Meal type" refers to the type of meal the user desires (e.g., breakfast, lunch, dinner, etc.).

[1745] "Generative AI" refers to artificial intelligence that automatically generates appropriate outing and meal plans based on user input data.

[1746] "Determining a plan" refers to the act of the user selecting the most suitable plan from the proposed plans and making a final decision.

[1747] A specific system and method for implementing the present invention will now be described.

[1748] System Configuration

[1749] The system consists of the following components:

[1750] 1. User's device (smartphone, PC)

[1751] 2. Server

[1752] 3. Generative AI Models

[1753] 4. Database

[1754] User operations

[1755] The user first logs in to a dedicated application or website, then enters the following parameters:

[1756] Departure Point

[1757] Transportation

[1758] Departure time

[1759] budget

[1760] Travel time

[1761] Number of people going out

[1762] Calories burned

[1763] Desired number of steps

[1764] Type of meal (e.g. breakfast, lunch, dinner)

[1765] Budget per meal

[1766] Calories per serving

[1767] Sending and Receiving Data

[1768] The user's device converts the input data into JSON format and sends it to the server using the HTTPS protocol. The server then analyzes the received data and prepares it for passing to the generative AI model.

[1769] Analyzing data and using generative AI models

[1770] The server runs the received data through an analysis algorithm and prepares the data to be passed to the generative AI model, which then generates optimal outing and meal plans based on the user's requests.The generative AI model also references past data to improve accuracy.

[1771] Generate and submit a plan

[1772] The generative AI model generates an outing plan and a meal plan, each containing the following information:

[1773] Destinations

[1774] activity

[1775] means of transportation

[1776] Estimated calorie consumption

[1777] Planned steps

[1778] Meal contents

[1779] Dining

[1780] Calorie and food budget

[1781] The server sends the generated plan in JSON format to the user's device.

[1782] User plan selection and confirmation

[1783] The user checks the displayed plans and selects the most suitable one. After selection, the server saves the selection information in the database and sends a confirmation notice to the user's device.

[1784] Specific examples

[1785] User A plans to go out and have lunch on a day off and enters the following parameters:

[1786] Starting point: Shibuya Ward

[1787] Transportation: Train and walking

[1788] Departure time: 10:00 AM

[1789] Budget: 8,000 yen

[1790] Duration: 6 hours

[1791] Number of people going out: 2

[1792] Calories burned: 500 calories

[1793] Desired number of steps: 10,000 steps

[1794] Meal type: Lunch

[1795] Budget per meal: 1,500 yen

[1796] Calories per serving: 600 calories

[1797] Based on the information sent to the server, the generative AI model analyzes and provides the following plan:

[1798] Plan A: Walk + Museum Visit + Healthy Lunch (Estimated calories burned: 520 calories, Estimated steps: 9,500 steps, Estimated calories for lunch: 580 calories)

[1799] Plan B: Walk in the park + Shopping + Low-calorie restaurant lunch (Estimated calories burned: 480 calories, Estimated steps: 10,500 steps, Estimated calories for lunch: 590 calories)

[1800] User A selects Plan A, and the server saves the selection in the database and sends a confirmation.

[1801] Main hardware and software used

[1802] Hardware: Web server (e.g. AWS EC2)

[1803] Software: Flask (Python library), HTTP protocol, generative AI (via API)

[1804] Prompt Sentence Examples

[1805] "Please suggest a healthy meal plan for location: Shibuya Ward, type: lunch, budget: 1500 yen, calories: 600 kcal."

[1806] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1807] Step 1:

[1808] The user logs in to a dedicated application or website and enters the following parameters: starting point, transportation method, departure time, budget, required time, number of people going out, calories burned, desired number of steps, type of meal, budget per meal, and calories per meal. This data is entered into the user's device and converted into JSON format.

[1809] Step 2:

[1810] The user's device sends the data converted into JSON format to the server using the HTTPS protocol, where it is encrypted to ensure security.

[1811] Step 3:

[1812] The server receives the data sent from the user's device, analyzes it using an analysis algorithm, and prepares it for passing to the generative AI model. Specifically, it checks the data for consistency and whether there is any missing information or data in the wrong format.

[1813] Step 4:

[1814] The server inputs the analyzed data into a generative AI model, which generates prompts and then generates health-conscious outing and meal plans based on the prompts.

[1815] Example: "Please suggest a healthy meal plan for location: Shibuya Ward, type: lunch, budget: 1500 yen, calories: 600 kcal."

[1816] Step 5:

[1817] The generative AI model generates multiple plans based on the input prompts. The generated outing and meal plans include destinations, activities, transportation, estimated calories burned, estimated steps, meal contents, meal locations, estimated calories for each meal, and budget.

[1818] Step 6:

[1819] The server sends multiple plans generated by the generative AI model to the user's device, where the plans are sent in JSON format and displayed on the user's device.

[1820] Step 7:

[1821] The user checks the multiple plans presented on the terminal and selects the most suitable one. Once the selection is confirmed, the information is sent from the user's terminal to the server.

[1822] Step 8:

[1823] The server stores the user's selected plan in a database and sends a confirmation notice to the user's terminal, so that the user can go out and eat according to the plan.

[1824] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1825] The present invention provides a system for planning a holiday outing that takes into account the user's emotions and allows the user to enjoy an efficient and health-conscious lifestyle. Specific embodiments of this system will be described below.

[1826] Overall system configuration

[1827] The system mainly consists of the following components:

[1828] 1. User's device (e.g. smartphone or PC)

[1829] 2. Server

[1830] 3. Generation AI

[1831] 4. Emotion Engine

[1832] 5. Database

[1833] User operations

[1834] A user first accesses the system using a dedicated application or website and logs in.

[1835] The user inputs parameters related to the outing plan (starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.).

[1836] Using the Emotion Engine

[1837] The emotion engine uses a camera and microphone to analyze facial expressions and voice while the user is typing, recognizing the user's emotional state.

[1838] Emotion data is captured in real time to assist the user in the input process.

[1839] Sending and Receiving Data

[1840] The terminal converts the data and emotion data entered by the user into JSON format and sends it to the server using the HTTPS protocol.

[1841] The server receives this data and prepares it for analysis.

[1842] Data analysis and generation using AI

[1843] The server temporarily stores the received data and analyzes each parameter and emotion data using an analysis algorithm.

[1844] The analyzed data is passed to the generation AI, which then generates an outing plan that best suits the user's needs and emotional state.

[1845] The AI ​​takes into account the user's specified calorie consumption, desired number of steps, and emotional state, and compares it with past data to generate a health-oriented plan, providing a highly accurate plan.

[1846] Generate and send trip plans

[1847] The AI ​​generates multiple outing plans, each of which includes destinations, activities, how to use public transportation, estimated calories burned, estimated number of steps, and content appropriate to the user's emotional state.

[1848] The server sends the generated plans to the user's device in JSON format.

[1849] User plan selection and confirmation

[1850] The user checks the multiple plans presented on the terminal and selects the most suitable one from among them.

[1851] Once the selection is confirmed, the server stores the user's selection in a database and sends a confirmation to the user's device.

[1852] Specific examples

[1853] For example:

[1854] User A plans to go out on a holiday and logs in to the dedicated app. Next, he enters the following parameters:

[1855] Starting point: Tokyo Station

[1856] Transportation: Train and walking

[1857] Departure time: 10:00 AM

[1858] Budget: 5,000 yen

[1859] Duration: 5 hours

[1860] Number of people going out: 2

[1861] Calories burned: 300 calories

[1862] Desired number of steps: 8,000 steps

[1863] While inputting, the emotion engine analyzes User A's facial expressions and voice and recognizes their current emotional state as "enjoyment." The device sends this information to the server, which receives the information and analyzes it. The analysis results and emotion data are passed to the generation AI, which generates the following plan:

[1864] Plan A: Visit to Ueno Zoo + Shopping at Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps, Reason for suggestion: Matches the emotion of enjoyment)

[1865] Plan B: Visit to Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps, Reason for suggestion: Matches the emotion of enjoyment)

[1866] These plans are sent to the user's terminal, and User A selects and confirms Plan A. The server stores this selection information in the database and sends a confirmation notice to User A.

[1867] In this way, the user can easily obtain an outing plan that incorporates health consciousness and emotional state.

[1868] The processing flow will be explained below.

[1869] Step 1:

[1870] The user accesses a dedicated application or website and logs in. The user inputs parameters such as the departure point, transportation method, departure time, budget, required time, number of people going out, calories burned, and desired number of steps.

[1871] Step 2:

[1872] The emotion engine uses the user's camera and microphone to analyze facial expressions and voice to recognize the user's emotional state in real time, detecting emotions such as joy, sadness, and fun.

[1873] Step 3:

[1874] The device converts all data and emotion data entered by the user into JSON format, which includes all the user's parameters.

[1875] Step 4:

[1876] The terminal sends the converted data to the server using the HTTPS protocol, which ensures secure transmission of the data.

[1877] Step 5:

[1878] The server receives the data received from the device and prepares it for analysis, converting it into an appropriate format and passing it to the analysis algorithm.

[1879] Step 6:

[1880] The server uses an analysis algorithm to analyze the received data and emotional data, for example, matching the user's input parameters with their emotional state.

[1881] Step 7:

[1882] The server passes the analysis results to the generation AI, which prepares to generate the optimal outing plan based on the user's requests and emotional state.

[1883] Step 8:

[1884] The AI ​​generates multiple outing plans based on the user's calorie consumption, desired number of steps, and emotional state. Each plan includes destinations, activities, how to use public transportation, planned calorie consumption, planned number of steps, and content appropriate for the user's emotional state.

[1885] Step 9:

[1886] The server sends multiple candidates for the generated outing plan to the user's device in JSON format.

[1887] Step 10:

[1888] The terminal displays the received outing plans on the user interface, and the user can check the plans and select the one they want.

[1889] Step 11:

[1890] The plan selected by the user is sent from the device to the server, and the selection is confirmed.

[1891] Step 12:

[1892] The server saves the user's selection in a database, confirming that the selection has been finalized.

[1893] Step 13:

[1894] The server sends a confirmation of the selection to the user's device, and the process is completed when the user receives and confirms the notification.

[1895] Example 2

[1896] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1897] Conventional outing plan creation systems have difficulty providing plans that fully consider the user's emotional state and health preferences. Furthermore, they have been unable to meet modern user needs, such as secure transmission of user input data and evaluation of exercise volume. As a result, they often provide plans that are unsatisfactory for users.

[1898] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: means for inputting parameters such as a starting point, a means of transportation, a departure time, a budget, a required time, the number of accompanying persons, calories burned, and a desired number of steps from a user; means for analyzing the user's facial expressions and voice using a camera and a microphone to collect emotional data; means for receiving the input data and emotional data, converting it into JSON format, and transmitting it to the server; means for storing the received data in the server and analyzing it using an analytical algorithm; means for using a generation AI based on the analyzed data to generate a health-oriented outing plan that is optimal for the user's requests and emotional state; means for transmitting the generated outing plan to the user's terminal; and means for the user to select the generated outing plan and store the selected information in a database. This makes it possible to provide an outing plan that takes into account the user's emotional state and health-orientedness.

[1899] "User" refers to an individual who uses the system to create an outing plan.

[1900] A "terminal" refers to an electronic device used by a user to manipulate input data, such as a smartphone or a personal computer.

[1901] "Server" refers to the computer system that receives and stores data sent by users, analyzes it, and generates plans.

[1902] "Database" refers to a system for storing user inputs and selections.

[1903] "Generative AI" refers to artificial intelligence that generates optimal outing plans based on the user's requests and emotional state.

[1904] An "emotion engine" refers to software that analyzes a user's facial expressions and voice to collect emotional data.

[1905] The "starting point" refers to the starting point of the user's outing plan.

[1906] "Transportation" refers to the means of transportation used by the user when going out.

[1907] "Departure time" refers to the time when the user starts going out.

[1908] The "budget" refers to the amount of money that a user can spend when going out.

[1909] "Time required" refers to the time the user plans to spend going out.

[1910] "Number of people accompanying" refers to the number of other people who go out with the user.

[1911] "Calories burned" refers to the amount of calories the user plans to burn while out.

[1912] The "desired number of steps" refers to the number of steps that the user wishes to achieve while out and about.

[1913] "Emotion data" refers to data that indicates the user's emotional state, obtained as a result of the emotion engine's analysis of the user's facial expressions and voice.

[1914] "JSON format" refers to a lightweight data interchange format that is widely used to send and receive data.

[1915] "Analysis Algorithm" refers to the computational method used by the Server to analyze Data.

[1916] A "health-oriented outing plan" refers to an outing plan that takes into consideration the user's health, and includes a plan that takes into consideration the amount of exercise, such as calories burned and number of steps.

[1917] The present invention provides a system that provides an outing plan that takes into account the user's emotional state and health preferences. The system is composed of the following elements:

[1918] 1. User's device (e.g. smartphone or PC)

[1919] 2. Server

[1920] 3. Generative AI (e.g. OpenAI GPT-3)

[1921] 4. Emotion engine (e.g. Affectiva SDK)

[1922] 5. Database (e.g. MySQL)

[1923] User operations

[1924] A user accesses a dedicated application or website and logs in by entering their username and password. This action causes the device to send the user's authentication information to the server, which then checks the database to authenticate the user. If authentication is successful, the server generates a session token and sends it back to the device.

[1925] Enter your outing plan

[1926] After a successful login, the user enters the following parameters regarding their travel plans:

[1927] Departure Point

[1928] Transportation

[1929] Departure time

[1930] budget

[1931] Travel time

[1932] Number of people accompanying

[1933] Calories burned

[1934] Desired number of steps

[1935] The device collects this data in real time.

[1936] Using the Emotion Engine

[1937] The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice and collect their current emotional state in real time. For example, the emotion engine (Affectiva SDK) identifies the user's emotional state from their facial expressions and voice and generates emotion data such as "enjoyment" or "relaxation." This emotion data is stored on the device.

[1938] Sending and Receiving Data

[1939] The device converts the parameters and emotion data entered by the user into JSON format and sends it to the server using the HTTPS protocol. The server receives this data and stores it in a database.

[1940] Analyze data and generate plans

[1941] The server analyzes the stored data based on an analysis algorithm, evaluating each parameter and emotional data. The analysis results are then passed to the generation AI (OpenAI GPT-3), which generates an outing plan that best suits the user's needs and emotional state. For example, the following prompt sentence is input to the generation AI:

[1942] "Generate an outing plan for the user. User input parameters are as follows:

[1943] Starting point: Tokyo Station

[1944] Transportation: Train and walking

[1945] Departure time: 10:00 AM

[1946] Budget: 5,000 yen

[1947] Duration: 5 hours

[1948] Number of people accompanying: 2 people

[1949] Calories burned: 300 calories

[1950] Desired number of steps: 8000 steps

[1951] Current emotional state: Enjoyment

[1952] Based on these, please suggest two outing plans that suit the user's health preferences and emotional state.

[1953] The AI ​​generates multiple outing plans based on the user's needs and emotional state. Each plan includes destinations, activities, transportation, estimated calories burned, estimated number of steps, and a reason for suggesting the plan based on the user's emotional state.

[1954] Sending and selecting outing plans

[1955] The server converts the generated outing plan into JSON format and sends it to the user's device. The user reviews the multiple plans provided and selects the most suitable one. Once the selection is confirmed, the device notifies the server of the selected plan, and the server stores this information in a database. The server also sends a selection confirmation to the user.

[1956] Specific examples

[1957] For example, if User A is planning to go out on a holiday, he / she will follow the steps below:

[1958] User A logs in to the dedicated app and enters the following parameters:

[1959] Starting point: Tokyo Station

[1960] Transportation: Train and walking

[1961] Departure time: 10:00 AM

[1962] Budget: 5,000 yen

[1963] Duration: 5 hours

[1964] Number of people accompanying: 2 people

[1965] Calories burned: 300 calories

[1966] Desired number of steps: 8,000 steps

[1967] While inputting, the emotion engine analyzes User A's facial expressions and voice and recognizes their current emotional state as "fun." The device sends this information to the server, which receives and analyzes the information. The analysis results and emotion data are then passed to the generation AI, which generates the following outing plan:

[1968] Plan A: Visit to Ueno Zoo + Shopping at Ameyoko (Estimated calories burned: 320 calories, Estimated steps: 8,500 steps, Reason for suggestion: Matches the emotion of enjoyment)

[1969] Plan B: Visit to Sensoji Temple + Stroll along Nakamise Shopping Street (Estimated calories burned: 290 calories, Estimated steps: 7,800 steps, Reason for suggestion: Matches the emotion of enjoyment)

[1970] These plans are sent to the user's device, and User A selects and confirms Plan A. The server stores this selection information in a database and sends a confirmation notice to User A. In this way, users can easily obtain outing plans that incorporate their emotional state and health preferences.

[1971] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1972] Step 1: User Login

[1973] A user accesses a dedicated application or website and logs in by entering their username and password. The device receives these authentication information as input and sends it to the server via the HTTPS protocol. The server checks it against a database and authenticates the user. If authentication is successful, the server generates a session token and sends it back to the device as output.

[1974] Specific behavior:

[1975] The user launches the app and enters their username and password on the login screen.

[1976] The terminal sends the input data to the server.

[1977] The server checks the credentials in the database.

[1978] If authentication is successful, the server generates a session token and returns it to the terminal.

[1979] Step 2: Enter the user's travel plans

[1980] The user inputs parameters related to their trip plan through the application interface, including the starting point, mode of transportation, departure time, budget, travel time, number of people accompanying them, calories burned, and desired number of steps. The device receives this data as input and collects it in real time.

[1981] Specific behavior:

[1982] The user enters the parameters of the trip plan into a form in the application.

[1983] The terminal stores these data in variables and prepares to send them to the server in the next step.

[1984] Step 3: Collecting emotion data with the emotion engine

[1985] The emotion engine uses the device's built-in camera and microphone to analyze the user's facial expressions and voice to collect emotion data. Emotion data includes emotions such as "enjoyment" and "relaxation." The emotion engine receives this data as input and generates emotion data as output.

[1986] Specific behavior:

[1987] The emotion engine analyzes camera footage and audio data as input.

[1988] The emotional state of the user is identified from facial expressions and voice, and emotional data is generated.

[1989] The generated emotion data is stored in the terminal.

[1990] Step 4: Sending data

[1991] The device converts the parameters of the outing plan and emotion data entered by the user into JSON format, and sends the converted JSON data as input to the server using the HTTPS protocol.

[1992] Specific behavior:

[1993] The device converts the outing plan parameters and emotion data into JSON format.

[1994] The converted JSON data is sent to the server via HTTPS protocol.

[1995] Step 5: Receiving and storing data

[1996] The server receives JSON data sent from the terminal and takes it in as input. It saves the received data in the database and generates a save completion status as output.

[1997] Specific behavior:

[1998] The server receives the HTTPS request and parses the JSON data.

[1999] The parsed data is stored in a database.

[2000] Generates a save completion status.

[2001] Step 6: Analyze the data

[2002] The server retrieves data stored in the database and analyzes the input data using an analysis algorithm. The analysis results are output as prompts to be passed to the generation AI.

[2003] Specific behavior:

[2004] The server retrieves the stored data from the database.

[2005] Data analysis algorithms evaluate each parameter and emotion data.

[2006] Generate prompts for generative AI models.

[2007] Step 7: Generate a plan using generative AI

[2008] The generative AI (e.g., OpenAI GPT-3) receives prompts sent from the server as input and generates the optimal outing plan. The generated plan is output to the server as multiple options.

[2009] Specific behavior:

[2010] The generative AI model receives the prompt sentence as input.

[2011] To generate multiple outing plans based on a user's emotional state and health preferences.

[2012] The generated plan is sent back to the server.

[2013] Step 8: Submit your plan

[2014] The server converts the generated outing plan into JSON format and sends it to the device, which then analyzes the received data and displays it to the user.

[2015] Specific behavior:

[2016] The server formats the generated plan into JSON.

[2017] Sends JSON data to the terminal via HTTPS protocol.

[2018] The terminal analyzes the received data and displays it to the user.

[2019] Step 9: User plan selection and confirmation

[2020] The user reviews multiple outing plans displayed on the device and selects the most suitable one. The device receives the selected plan information as input and sends it to the server. The server stores this information in a database and returns a selection confirmation to the device.

[2021] Specific behavior:

[2022] The user checks the outing plan on the terminal and clicks the selection button.

[2023] The terminal transmits information about the selected plan to the server.

[2024] The server stores the selection information in a database.

[2025] The server sends a confirmation of the selection back to the terminal.

[2026] (Application example 2)

[2027] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2028] Conventional outing plan generation systems do not consider the user's emotional state when proposing plans, which can result in low user satisfaction. Furthermore, if outing plans could be proposed that reflect the user's intuitive emotional state, rather than just taking health-consciousness into account, a more fulfilling experience could be provided. The present invention aims to provide a system that generates outing plans that also consider the user's emotional state, thereby increasing user satisfaction.

[2029] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2030] In this invention, the server includes means for inputting parameters such as the starting point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc. from the user, means for receiving and analyzing the input data and emotional state data, and means for generating an outing plan that takes into account health orientation and emotional state using a generation AI based on the analyzed data, thereby making it possible to provide an outing plan optimized for the user's emotional state.

[2031] The "starting point" refers to the location where the user starts going out.

[2032] "Transportation" refers to the means of transportation used by the user when out and about.

[2033] "Departure time" refers to the time when the user starts going out.

[2034] The "budget" refers to the upper limit of the amount of money that the user can spend on this outing.

[2035] The "required time" refers to the total time the user plans to spend out.

[2036] The "number of people going out" refers to the number of people accompanying the user on an outing.

[2037] "Calories burned" refers to the amount of calories the user plans to burn while out.

[2038] The "desired number of steps" refers to the number of steps the user wishes to walk while out.

[2039] "Emotional state" refers to the user's current emotional or psychological state.

[2040] "Input means" refers to a device or method by which a user inputs parameters into the system.

[2041] "Means for receiving and analyzing" refers to a device or method for receiving parameters and emotion data input by a user and analyzing them.

[2042] "Means for generating" refers to a device or method for generating an outing plan based on input data using a generating AI.

[2043] The "transmitting means" refers to a device or method for transmitting the generated outing plan to the user's terminal.

[2044] The "means for selecting and confirming" refers to a device or method that allows a user to select from among the proposed outing plans and confirm the plan.

[2045] This system optimizes the shopping experience in brick-and-mortar stores by generating health-conscious outing plans that take into account the user's emotions. This system mainly consists of a user's device, a server, a generative AI model, an emotion engine, and a database.

[2046] First, users access the system using a dedicated smartphone application and log in. Next, they input parameters such as the starting point, mode of transportation, departure time, budget, travel time, number of people going out, calories burned, desired number of steps, etc. While the user is entering information, the emotion engine uses the camera and microphone to analyze facial expressions and voice to recognize the user's emotional state.

[2047] The device converts this input data and emotional data into JSON format and sends it to the server using the HTTPS protocol. The server receives this data and temporarily stores it. An analysis algorithm analyzes each parameter and emotional data. The analyzed data is passed to the generation AI, which generates an outing plan that is optimal for the user's needs and emotional state. The generation AI generates a health-oriented plan taking into account the user's specified calories burned, desired number of steps, and emotional state.

[2048] The generated plans are sent from the server to the user's device as multiple candidates. The user reviews the plans and selects the most suitable one. Once the selection is confirmed, the server saves the selection information in a database and sends a confirmation notice to the user.

[2049] This system uses a virtual library called "EmotionAnalyzer" for analyzing user emotions and "RecommendationEngine" for generating AI, which makes it possible to suggest products and stores according to the user's emotional state.

[2050] Specific examples

[2051] Consider a case where a user is shopping at a brick-and-mortar store (e.g., a shopping mall). The user logs in to the app and enters the following parameters:

[2052] Starting point: Shinjuku

[2053] Transportation: Walking

[2054] Departure time: 3:00 PM

[2055] Budget: 10,000 yen

[2056] Duration: 3 hours

[2057] Number of people going out: 1 person

[2058] Calories burned: 200 calories

[2059] Desired number of steps: 5,000 steps

[2060] The emotion engine analyzes the user's facial expressions and voice and recognizes their current emotional state as "fun." The server receives this information and uses the generative AI to generate the following plan:

[2061] Plan A: Shopping at Clothing Store A + Relax at the Book Cafe

[2062] Plan B: Shopping at Accessory Store B + Walking in the Park

[2063] These plans are sent to the user's terminal, and the user can select the most suitable plan, thus providing a pleasant shopping experience that matches his or her emotional state.

[2064] Prompt Sentence Examples

[2065] It's 3 PM and the user wants to enjoy shopping in Shinjuku within a budget of 10,000 yen. Sentiment analysis indicates the user is in the "Enjoy" state. What products and stores would you recommend?

[2066] This system allows users to plan their outings more effectively based on their emotional state.

[2067] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2068] Step 1:

[2069] Users log in to the application using their smartphone and enter parameters such as the starting point, mode of transportation, departure time, budget, travel time, number of people going out, calories burned, desired number of steps, etc. The entered information is temporarily saved by the application. Examples of input data include the starting point "Shinjuku," mode of transportation "walking," and budget "10,000 yen."

[2070] Step 2:

[2071] The emotion engine uses the camera and microphone to analyze the user's facial expressions and voice to recognize their current emotional state. For example, it can identify that the user is in an "enjoyment" emotional state based on their facial expressions and voice. The acquired emotional data is temporarily saved along with the input parameters.

[2072] Step 3:

[2073] The device converts the input parameters and emotion data into JSON format and sends it to the server using the HTTPS protocol. The data sent includes the starting point (Shinjuku), the budget (10,000 yen), and the emotional state (fun).

[2074] Step 4:

[2075] The server temporarily stores the received data before applying the analysis algorithm, which categorizes the data into parameters and emotional data.

[2076] Step 5:

[2077] The server runs an analysis algorithm to analyze the received parameters and emotional data. This analysis identifies the elements necessary to create an outing plan based on the user's starting point, budget, emotional state, etc. The server then selects an appropriate activity based on the input data "fun."

[2078] Step 6:

[2079] The analyzed data is passed to a generation AI, which generates an outing plan that best suits the user's needs and emotional state. The generation AI outputs multiple plans using, for example, a "Recommendation Engine." Specifically, it generates plans such as "Plan A: Shopping at a clothing store + Relax at a cafe" and "Plan B: Shopping at an accessory store + Walking in the park."

[2080] Step 7:

[2081] The server then converts the generated outing plan back into JSON format and sends it to the user's device. The data sent includes multiple outing plans, each with detailed activity and reason descriptions.

[2082] Step 8:

[2083] The user checks the multiple plans presented on the terminal and selects the most suitable one. The plan selected by the user is sent to the server by the application, and the selection information is saved in the database.

[2084] Step 9:

[2085] The server sends a confirmation notification of the selected plan to the user's terminal, allowing the user to confirm that the selected plan has been confirmed.

[2086] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2087] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2088] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2089] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2090] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2091] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2092] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2093] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2094] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2095] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2096] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2097] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2098] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2099] 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.

[2100] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2101] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2102] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[2103] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2104] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2105] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2106] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2107] The following is further disclosed regarding the above embodiment.

[2108] (Claim 1)

[2109] A means for the user to input parameters such as the departure point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.;

[2110] means for receiving and analyzing input data;

[2111] A means for generating outing plans that take into account health-consciousness using AI based on the analyzed data;

[2112] means for transmitting the generated outing plan to a user's terminal;

[2113] A means for a user to select and confirm the generated outing plan;

[2114] A system including:

[2115] (Claim 2)

[2116] 10. The system of claim 1, further comprising means for encrypting the input data before transmitting it.

[2117] (Claim 3)

[2118] 2. The system according to claim 1, further comprising means for evaluating the amount of exercise in the outing plan based on the calories to be consumed and the desired number of steps input by the user.

[2119] "Example 1"

[2120] (Claim 1)

[2121] A means for the user to input parameters such as the departure point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.;

[2122] A means for converting input data into JSON format and sending it to a server using the HTTPS protocol;

[2123] A means for storing the received JSON format data and analyzing it using an analysis algorithm;

[2124] A means for transmitting the analysis results to the generation AI as prompt sentences, and for the generation AI to generate multiple outing plans based on the user's requirements;

[2125] A means for sending the generated outing plan to the user's device in JSON format;

[2126] A means for allowing a user to select a plan from the presented options and store the selection in a database;

[2127] A system including:

[2128] (Claim 2)

[2129] 10. The system of claim 1, further comprising means for encrypting input data before transmitting it.

[2130] (Claim 3)

[2131] 2. The system according to claim 1, further comprising means for evaluating the amount of exercise in the outing plan based on the calories burned and the desired number of steps input by the user, and providing a highly accurate plan by referring to past data.

[2132] "Application Example 1"

[2133] (Claim 1)

[2134] A means for the user to input parameters such as the departure point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, type of meal, budget, calories per meal, etc.

[2135] means for receiving and analyzing input data;

[2136] A means for generating outing plans and meal plans that take into account health-consciousness using AI based on the analyzed data;

[2137] means for transmitting the generated outing plan and meal plan to a user's terminal;

[2138] A means for the user to select and confirm the generated outing and meal plans;

[2139] A system including:

[2140] (Claim 2)

[2141] 10. The system of claim 1, further comprising means for encrypting the input data before transmitting it.

[2142] (Claim 3)

[2143] 2. The system of claim 1, further comprising means for evaluating the amount of exercise in the outing plan and the calories in the meal plan based on the calories to be consumed and the desired number of steps input by the user.

[2144] "Example 2: Combining Emotion Engines"

[2145] (Claim 1)

[2146] A means for the user to input parameters such as the starting point, means of transportation, departure time, budget, required time, number of accompanying persons, calories burned, desired number of steps, etc.;

[2147] A means of collecting emotional data by analyzing the user's facial expressions and voice using a camera and microphone;

[2148] A means for receiving input data and emotion data, converting them into JSON format, and transmitting them to a server;

[2149] A means for storing the received data on a server and analyzing it using an analysis algorithm;

[2150] A means for generating a health-oriented outing plan that is optimal for the user's needs and emotional state using a generation AI based on the analyzed data;

[2151] means for transmitting the generated outing plan to a user's terminal;

[2152] A means for a user to select the generated outing plan and store the selection information in a database;

[2153] A system including:

[2154] (Claim 2)

[2155] 10. The system of claim 1, further comprising means for encrypting and transmitting the input data and emotion data.

[2156] (Claim 3)

[2157] 2. The system according to claim 1, further comprising means for evaluating the amount of exercise in the outing plan based on the calories to be consumed and the desired number of steps input by the user.

[2158] "Application example 2 when combining emotion engines"

[2159] (Claim 1)

[2160] A means for the user to input parameters such as the departure point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.;

[2161] means for receiving and analyzing input data and emotional state data;

[2162] A means for generating an outing plan that takes into account health-consciousness and emotional state using AI based on the analyzed data;

[2163] means for transmitting the generated outing plan to a user's terminal;

[2164] A means for a user to select and confirm the generated outing plan;

[2165] A system including:

[2166] (Claim 2)

[2167] 10. The system of claim 1, further comprising means for encrypting the input data before transmitting it.

[2168] (Claim 3)

[2169] 2. The system according to claim 1, further comprising means for evaluating the amount of exercise in the outing plan based on the calories to be consumed and the desired number of steps input by the user. [Explanation of symbols]

[2170] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for the user to input parameters such as the departure point, means of transportation, departure time, budget, required time, number of people going out, calories burned, desired number of steps, etc.; means for receiving and analyzing input data; A means for generating outing plans that take into account health-consciousness using AI based on the analyzed data; means for transmitting the generated outing plan to a user's terminal; A means for a user to select and confirm the generated outing plan; A system including:

2. 2. The system according to claim 1, further comprising means for encrypting said input data before transmitting it.

3. The system according to claim 1 , further comprising means for evaluating the amount of exercise in the outing plan based on the calories to be consumed and the desired number of steps input by the user.

Images