System

Abstract

To provide a system configured to allow a user to efficiently make a plan for the weekend and manage preparations in a unified manner.SOLUTION: A system includes: means for acquiring information on hobbies or weekend plan of a user; means for generating a prompt text to generate contents of activities to be proposed to the user, on the basis of the acquired hobbies or weekend plan of the user; means for generating the contents of activities to be proposed to the user, using the generated prompt text and a generative AI model; proposal means for proposing the generated contents of activities to the user; reservation means for making a reservation related to the proposed contents of activities; means for providing weather information related to the proposed contents of activities; and means for providing menu information related to the proposed contents of activities.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] People are so busy with work and housework during the weekdays that they don't have time to make plans for the weekend, which means they can't fully enjoy their precious weekends.In addition, there is the issue of how difficult it is to centrally manage and efficiently manage the many preparations required for weekend activities, such as booking and arranging activities, checking the weather forecast, and planning menus. [Means for solving the problem]

[0005] The system provides a means to suggest weekend activities that take into account the user's hobbies and schedules. It also provides a means to make reservations and arrangements related to the suggested activities, a means to provide weather forecasts related to the activities, a means to consider menus related to the activities, and a means to suggest new connections through social media posts. This allows users to efficiently plan their weekend schedules and manage preparations in a centralized manner. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] The system of the present invention has a means for suggesting weekend activities taking into account the user's hobbies and schedule. Specifically, the system stores the user's registered hobbies and schedule in a database and suggests weekend activities based on them. For example, if the user has registered that camping is a hobby, the system suggests weekend camping.

[0029] "Example 2"

[0030] The system of the present invention also has a means for making reservations and arrangements related to the proposed activity. Specifically, the system automatically makes the reservations and arrangements necessary for the proposed activity. For example, if camping is proposed, the system searches for available campsites and makes reservations after obtaining the user's approval.

[0031] "Example 3"

[0032] The system of the present invention further includes a means for providing a weather forecast related to the activity. Specifically, the system obtains a weather forecast based on the date, time, and location of the proposed activity and provides it to the user. For example, if a user plans to go camping, the system provides a weather forecast for that day, particularly detailed wind information.

[0033] "Example 4"

[0034] The system of the present invention also includes a means for considering menus related to the activity. Specifically, the system proposes menus suitable for the proposed activity. For example, in the case of camping, the system proposes menus for camping meals that are easy to prepare.

[0035] "Example 5"

[0036] Furthermore, the system of the present invention has a means for suggesting new connections through social media posts. Specifically, the system analyzes social media posts related to the proposed activity and recommends other users who share the same hobby. For example, the system may recommend other users who post camping photos and suggest new connections.

[0037] The processing flow of each embodiment will be described below.

[0038] "Example 1"

[0039] Step 1: The user registers their hobbies and plans in the system.

[0040] Step 2: The system stores the registered information in a database.

[0041] Step 3: The system will suggest weekend activities based on the stored information. For example, if the user has registered that camping is a hobby, it will suggest weekend camping.

[0042] "Example 2"

[0043] Step 1: The system automatically schedules and schedules the proposed activity.

[0044] Step 2: For example, if you suggest camping, the system will search for available campsites.

[0045] Step 3: The system asks the user if they want to approve the campsite reservation, and if approved, makes the reservation.

[0046] "Example 3"

[0047] Step 1: The system retrieves weather forecasts based on the date, time, and location of the proposed activity.

[0048] Step 2: The system will provide the retrieved weather forecast to the user. For example, if you are planning to go camping, the system will provide the weather forecast for that day, especially detailed wind information.

[0049] "Example 4"

[0050] Step 1: The system suggests a menu appropriate for the proposed activity.

[0051] Step 2: For example, if you're camping, the system will suggest easy-to-prepare camping meals.

[0052] "Example 5"

[0053] Step 1: The system analyzes social media posts related to the proposed activity.

[0054] Step 2: Based on the analysis results, the system recommends other users with similar interests.

[0055] Step 3: For example, recommend other users who post camping photos and suggest new connections.

[0056] Example 1

[0057] Next, a description will be given of Example 1 of Form 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."

[0058] Conventional weekend activity suggestion systems are required to comprehensively provide a wide range of functions, including not only taking into account the user's hobbies and schedules, but also related reservations and scheduling, weather forecasts, menu planning, and new connection suggestions. However, there was no system that provided all of these functions in a unified manner, forcing users to use multiple applications and services. Furthermore, advanced suggestion functions utilizing generative AI models were lacking. This resulted in reduced user convenience and the inability to obtain optimal weekend activity suggestions.

[0059] 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.

[0060] In this invention, the server includes a means for storing the user's hobbies and schedule in a database, a means for generating weekend activity suggestions using a generative AI model, and a means for notifying the user of the generated suggestions, thereby enabling optimal weekend activity suggestions based on the user's hobbies and schedule.

[0061] "A means of suggesting weekend activities taking into consideration the user's hobbies and schedule" is a function that suggests optimal weekend activities based on the hobbies and schedule information registered by the user.

[0062] The "means for making reservations and arrangements related to the proposed activity" is a function for automatically making reservations and preparations necessary for the proposed activity.

[0063] "Means for providing weather forecasts relevant to an activity" is a function for providing weather information that will affect the proposed activity.

[0064] The "means for considering menus related to activities" is a function for considering meal menus suitable for the proposed activity.

[0065] "A means to suggest new connections through social media posts" is a function that allows users to suggest connecting with new people through social media.

[0066] "Means for saving user's hobbies and schedules in a database" is a function for storing information about hobbies and schedules entered by the user in a database.

[0067] The "means for generating weekend activity suggestions using a generative AI model" is a function for utilizing a generative AI model to suggest optimal weekend activities to a user.

[0068] "Means for notifying the user of generated suggestions" is a function for informing the user of activity suggestions generated by the generative AI model.

[0069] This invention is a system that suggests weekend activities based on a user's hobbies and schedule. The system stores the user's registered hobbies and schedule in a database and suggests weekend activities based on that information. Specifically, the system works in cooperation with the server, terminal, and user elements.

[0070] Hardware and software used

[0071] server

[0072] The server receives the data sent by the user and stores it in a database. The server manages the data using a relational database such as MySQL (registered trademark) or PostgreSQL. It also uses a generative AI model (e.g., OpenAI (registered trademark)'s GPT-3 (registered trademark)) to generate weekend activity suggestions for the user.

[0073] Terminal

[0074] The device provides an interface for users to input their hobbies and schedules. This can be a smartphone app or a web application. The device has a communication function to send the data entered by the user to a server.

[0075] User

[0076] The user inputs his / her hobbies and plans using the terminal. For example, the user inputs "I like camping and I'm free next weekend." This information is sent to the server via the terminal.

[0077] Data processing and calculation

[0078] Data storage

[0079] The server receives the data sent from the device, analyzes it, and saves it in a database. For example, it stores information such as the user ID, hobbies, and schedule in the corresponding columns.

[0080] Weekend Activity Suggestions

[0081] As the weekend approaches, the server runs a periodic job (for example, a Cron job) to retrieve the user's hobbies and schedule from the database. Based on the retrieved data, it generates a prompt to send to the generative AI model. For example, it generates a prompt such as, "The user's hobby is camping, and they are free next weekend. Please suggest some recommended activities." This prompt is sent to the generative AI model, which then generates suggested weekend activities.

[0082] Proposal Notification

[0083] The generated suggestions are sent from the server to the device. The device then notifies the user of the received suggestions. For example, the smartphone app's notification function could be used to display a suggestion such as, "The weather is nice next weekend, so why not enjoy camping at a nearby campground?"

[0084] Specific examples

[0085] For example, a user uses a smartphone app to input "Camping is my hobby and I'm free next weekend." The device sends this information to the server, which stores it in a database. As the weekend approaches, the server sends a prompt to the generative AI model: "My hobby is camping and I'm free next weekend. Please suggest some recommended activities." The generative AI model generates a suggestion: "The weather is nice next weekend, so how about enjoying camping at a nearby campground?" The server then sends this to the device. The device then notifies the user of this suggestion.

[0086] In this way, the system can provide optimal weekend activity suggestions based on the user's hobbies and schedule.

[0087] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0088] Step 1:

[0089] A user inputs their hobbies and plans using a terminal. For example, a user inputs "I like camping and I'm free next weekend." This input data is converted to JSON format on the terminal and sent to the server using an HTTP POST request. The input is information about the user's hobbies and plans, and the output is data sent to the server.

[0090] Step 2:

[0091] The server receives the HTTP POST request sent from the device. It analyzes the received data and extracts the user's hobbies and schedule. The server uses a MySQL database to store the extracted data in the appropriate table. For example, information such as user ID, hobbies, and schedule is stored in the corresponding columns. The input is data from the device, and the output is saved in the database.

[0092] Step 3:

[0093] As the weekend approaches, the server runs a periodic job (for example, a Cron job) to retrieve the user's hobbies and schedule from the database. Based on the retrieved data, it generates a prompt to send to the generative AI model. For example, it generates a prompt such as, "The user's hobby is camping, and they are free next weekend. Please suggest some recommended activities." The input is the user's hobbies and schedule information retrieved from the database, and the output is the generated prompt.

[0094] Step 4:

[0095] The server sends the generated prompt to a generative AI model, which then generates weekend activity suggestions based on the prompt. The generated suggestions are returned to the server. The input is the generated prompt, and the output is the suggestions from the generative AI model.

[0096] Step 5:

[0097] The server sends the proposal received from the generative AI model to the device. The device notifies the user of the received proposal. For example, a smartphone app's notification function can be used to display a proposal such as, "The weather is nice next weekend, why not enjoy camping at a nearby campground?" The input is the proposal from the generative AI model, and the output is a notification to the user.

[0098] (Application example 1)

[0099] Next, a description will be given of Application Example 1 of Embodiment 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."

[0100] Conventional weekend activity suggestion systems not only consider users' hobbies and schedules, but also provide a wide range of functions, such as reservations and scheduling related to the suggested activities, weather forecasts, menu planning, and suggesting new connections through social media posts. However, few systems offer these functions in an integrated manner, and they do not fully satisfy user convenience. Furthermore, they lack the ability to collect feedback to improve the accuracy of suggestions, or advanced suggestion functions using generative AI models. This poses a challenge in suggesting weekend activities that satisfy users.

[0101] 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.

[0102] In this invention, the server includes means for suggesting weekend activities taking into consideration the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for suggesting activities based on the user's hobbies and schedule using a generative AI model, means for delivering content related to the suggested activities, and means for collecting user feedback to improve the accuracy of the suggestions. This makes it possible to suggest weekend activities that meet the diverse needs of users, thereby increasing user satisfaction.

[0103] "User" means any individual or entity that uses the System.

[0104] "Hobbies" are activities or interests that a user engages in for fun and enjoyment.

[0105] A "to-do" is an activity or event that a user plans to take place at a specific time in the future.

[0106] "Weekend activities" are leisure and hobby activities that a user plans to do over the weekend.

[0107] "Suggestions" are recommendations for weekend activities made by the system to the user.

[0108] "Reservation" means the process of reserving in advance a location or service related to a proposed activity.

[0109] "Set-up" refers to the specific plans and preparations for carrying out the proposed activity.

[0110] "Weather forecast" means local weather information relevant to the proposed activity.

[0111] A "menu" is a meal plan related to a proposed activity.

[0112] "SNS posting" refers to the act of a user sharing information on a social networking service.

[0113] "New connections" are the new relationships and communities that users build through social media posts.

[0114] A "generative AI model" is an algorithm that uses artificial intelligence to suggest activities based on a user's hobbies and schedule.

[0115] "Content" is information or media (videos, articles, event information, etc.) related to the proposed activity.

[0116] "Feedback" refers to the evaluations and opinions that users give to suggestions.

[0117] "Accuracy" is the degree to which the suggestions match the user's expectations and needs.

[0118] A system for carrying out this invention includes a plurality of means for suggesting weekend activities taking into consideration a user's hobbies and schedule, specifically means for storing the user's hobbies and schedule in a database and using a generative AI model to suggest weekend activities based on the hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing a weather forecast related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for delivering content related to the suggested activities, and means for collecting user feedback to improve the accuracy of the suggestions.

[0119] Hardware and software used

[0120] Hardware: Smartphones, servers

[0121] Software: Python, SQLite (database management), OpenAI API (generative AI model)

[0122] Data processing and calculation

[0123] 1. Database management: The server uses SQLite to store users' hobbies and schedules. When users enter their hobbies and schedules via their smartphones, the information is sent to the server and stored in the database.

[0124] 2. Generative AI model: The server uses the OpenAI API to suggest weekend activities based on the user's hobbies and schedule. It generates prompts based on user information retrieved from the database and inputs them into the generative AI model.

[0125] 3. Suggestion Generation: Retrieve suggestions from the generative AI model and display them to the user, along with related bookings, scheduling, weather forecasts, menu planning, and social media post suggestions.

[0126] 4. Content Delivery: Deliver content to users, such as videos, articles, and event information related to the proposed activity.

[0127] 5. Feedback collection: User ratings and opinions on suggestions are collected and stored in a database, which helps improve the accuracy of the generative AI model's suggestions.

[0128] Specific examples

[0129] For example, if a user lists their hobbies as "camping" and "hiking" and has Saturdays free, the server will generate the following prompt:

[0130] The user's hobbies are camping and hiking, and they are free on Saturdays. Please suggest some recommended activities for the weekend.

[0131] This prompt is input into a generative AI model, which then generates suggestions such as, "How about enjoying a hike in the nearby mountains on Saturday, followed by a night at a campsite?" Based on this suggestion, the server makes reservations for available campsites, schedules the trip, provides weather forecasts, suggests related menus, and suggests social media posts.

[0132] In this way, weekend activities can be proposed that meet the diverse needs of users, thereby improving user satisfaction.

[0133] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0134] Step 1:

[0135] A user uses a smartphone to input their hobbies and schedule. The input hobbies and schedule are sent from the smartphone to a server. The server receives this information and stores it in an SQLite database. The input data is hobbies (e.g., camping, hiking) and schedule (e.g., free on Saturdays). The user's hobbies and schedule are then saved in the database.

[0136] Step 2:

[0137] The server retrieves the user's hobbies and schedule from the database. Based on the retrieved data, it generates a prompt sentence to input into the generative AI model. Specifically, it creates a sentence that combines hobbies and schedule. For example, it generates a prompt sentence such as, "The user's hobbies are camping and hiking, and they are free on Saturdays. Please suggest some recommended activities for the weekend."

[0138] Step 3:

[0139] The server sends the generated prompt to the OpenAI API. The OpenAI API uses a generative AI model based on the prompt to suggest suitable weekend activities for the user. The generative AI model analyzes the input prompt and generates appropriate activity suggestions. For example, it generates a suggestion such as, "How about enjoying a hike in the nearby mountains on Saturday, followed by a night at a campsite?"

[0140] Step 4:

[0141] The server receives suggestions from the generative AI model and displays them to the user. It also provides information for making reservations and planning related to the suggested activities. For example, it displays search results and reservation links for available campsites. It also provides weather forecasts and menu suggestions related to the suggested activities.

[0142] Step 5:

[0143] The user inputs feedback on the proposed activity. The feedback is sent from the smartphone to the server. The server receives this feedback and stores it in a database. The feedback data includes evaluations and opinions of the proposal.

[0144] Step 6:

[0145] The server uses the collected feedback to improve the accuracy of the generative AI model's proposals. Specifically, it analyzes the feedback data and uses it as training data for the generative AI model. This improves the accuracy of future proposals.

[0146] Step 7:

[0147] The server delivers content related to the proposed activity (such as videos, articles, and event information) to the user. The content provides information related to the proposed activity and is of interest to the user. For example, content such as how to prepare for camping or hiking trails may be delivered.

[0148] In this way, weekend activities are suggested based on the user's hobbies and schedule, improving the user's satisfaction.

[0149] Example 2

[0150] Next, a description will be given of Example 2 of Form 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."

[0151] With conventional systems, when planning weekend activities, users had to use multiple websites and applications to gather information and make reservations and arrangements. This required a lot of time and effort, and often made planning complicated. Furthermore, there was no system that centrally provided activity-related information, such as weather forecasts, related menu suggestions, and suggestions for new connections. This made it difficult for users to maintain consistency in their plans and select the most appropriate activities.

[0152] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for suggesting weekend activities taking into account the user's hobbies and schedule, a means for making reservations and arrangements related to the proposed activities, a means for analyzing the proposed activities using a generative AI model, a means for collecting information necessary for the proposed activities, a means for presenting suggestions to the user and obtaining approval, a means for providing a weather forecast related to the activities, a means for considering menus related to the activities, and a means for suggesting new connections through social media posts. This allows users to plan weekend activities within a single system, obtain necessary information in a unified manner, and efficiently make reservations and arrangements.

[0153] A "User" is an individual who utilizes the System to plan weekend activities and make reservations and arrangements related to the proposed activities.

[0154] "Hobbies" are activities or interests that a user engages in for personal enjoyment.

[0155] A "to-do" is an activity or event that a user plans to take place at a specific time in the future.

[0156] "Weekend activities" are leisure and hobby activities that a user plans to do over the weekend.

[0157] "Suggestion method" is a function in which the system automatically suggests weekend activities taking into account the user's hobbies and schedule.

[0158] "Means for making reservations and arrangements" refers to the system's ability to automatically make reservations and arrangements related to the proposed activity.

[0159] A "generative AI model" is an artificial intelligence model used to analyze user input and generate appropriate suggestions or information.

[0160] The "means of analysis" is a function that uses a generative AI model to analyze user input and identify necessary information and reservations.

[0161] "Means for collecting information" refers to the ability to collect information required for the proposed activity from the internet and other data sources.

[0162] "Means for presenting proposals and obtaining approval" is a function for presenting proposals to users based on collected information and obtaining approval from the users.

[0163] A "means for providing weather forecasts" is a function that provides a user with weather forecasts relevant to a proposed activity.

[0164] The "means for considering menus" is a function that considers meal menus related to the proposed activity and suggests them to the user.

[0165] "A means of suggesting new connections through social media posts" is a function that allows users to suggest connections with new people by posting on social media.

[0166] The present invention is a system that allows a user to plan weekend activities and automatically makes reservations and arrangements related to the proposed activities. A specific embodiment of this system will be described below.

[0167] System Overview

[0168] The system takes into account the user's hobbies and schedule to suggest weekend activities, and then makes related reservations and arrangements. It also uses a generative AI model to analyze the suggested activities, gather necessary information, and present it to the user. It also includes features related to the activities, such as weather forecasts, meal suggestions, and new connections.

[0169] Hardware and software used

[0170] User device: smartphone, PC, etc.

[0171] Server: Cloud server, database server

[0172] Generative AI models: Natural language processing models such as GPT-4®

[0173] Web browser: GOOGLE CHROME (registered trademark), Mozilla Firefox, etc.

[0174] Dedicated application: A mobile application dedicated to the system

[0175] Web scraping tools: Beautiful Soup, Selenium, etc.

[0176] API: Campsite reservation system API, weather forecast API

[0177] Program processing

[0178] 1. Accepting user input

[0179] The user uses the device to input the activity they want to do. For example, the user opens a dedicated application on their smartphone and inputs, "I want to go camping this weekend."

[0180] 2. Analyze the proposed actions using a generative AI model

[0181] The server receives the user's input and analyzes it using a generative AI model (e.g., GPT-4). Specifically, the user's input is sent to the generative AI model as a prompt, which identifies the necessary reservations and arrangements.

[0182] Example prompt: "User says they want to go camping this weekend. Find available campsites and gather information to make a reservation."

[0183] 3. Gather the necessary information

[0184] The server collects information needed for the proposed activity via the Internet. For example, it accesses a campsite reservation site and searches for available campsites. It then uses a web scraping tool or API to obtain information about available campsites.

[0185] 4. Present suggestions to users

[0186] Based on the information collected by the server, the server presents suggestions to the user. For example, it might display a message on the user's device saying, "The following campsites are available. Would you like to make a reservation?" Specifically, it sends a message to the user via a dedicated application or web browser.

[0187] 5. Get User Approval

[0188] The user uses the device to check and approve the proposal from the server. For example, the user enters "Yes, please make a reservation." The user's input is sent to the server via a dedicated application or web browser.

[0189] 6. Make a reservation

[0190] The server receives the user's approval and makes the necessary reservations for the proposed activity. For example, it uses the API of a campground reservation system to confirm the campground reservation. Once the reservation is complete, the server sends a notification to the user that the reservation is complete.

[0191] Specific examples

[0192] If a user inputs "I want to go camping this weekend," the server analyzes it using a generative AI model and determines that a campsite reservation is required. Next, the server searches for available campsites via the Internet and presents suggestions to the user, saying, "The following campsites are available. Would you like to make a reservation?" If the user confirms, "Yes, please make a reservation," the server makes the reservation using the API of the campsite reservation system and sends the user a notification that the reservation is complete.

[0193] In this way, the system automatically makes reservations and arrangements related to activities proposed by the user.

[0194] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0195] Step 1:

[0196] The user proposes an activity. The user uses the device to input the activity they want to do. For example, the user opens a dedicated application on their smartphone and inputs by voice, "I want to go camping this weekend." This input is sent to the server.

[0197] Step 2:

[0198] The server analyzes the proposed activities using a generative AI model. The server receives the user's input and analyzes it using a generative AI model (e.g., GPT-4). Specifically, the server sends the user's input as a prompt to the generative AI model, which identifies the necessary reservations and arrangements. The input is the user's proposal, and the output is the analysis result, which is information on the necessary reservations and arrangements.

[0199] Step 3:

[0200] The server collects the necessary information. The server collects the information required for the proposed activity via the Internet. For example, access a campsite reservation site and search for available campsites. Use a web scraping tool or API to obtain campsite availability. The input is instructions for collecting information based on the analysis results, and the output is the collected information on campsite availability.

[0201] Step 4:

[0202] The server presents suggestions to the user. The server presents suggestions to the user based on the collected information. For example, it displays a message on the user's device saying, "The following campsites are available. Would you like to make a reservation?" Specifically, it sends a message to the user through a dedicated application or web browser. The input is the collected information, and the output is a suggested message to the user.

[0203] Step 5:

[0204] The user approves the proposal. The user uses the terminal to check and approve the proposal from the server. For example, the user enters the text "Yes, please make a reservation." The user's input is sent to the server via a dedicated application or web browser. The input is the user's approval message, and the output is approval information sent to the server.

[0205] Step 6:

[0206] The server makes the reservation. With the user's approval, the server makes the reservation required for the proposed activity. For example, the server uses the API of a campsite reservation system to confirm the campsite reservation. Once the reservation is complete, the server sends a notification to the user that the reservation is complete. The input is the user's approval information, and the output is a notification that the reservation is complete.

[0207] (Application example 2)

[0208] Next, a description will be given of Application Example 2 of Form 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."

[0209] In today's busy lifestyles, it takes time and effort for users to plan weekend activities and make related reservations and arrangements. It is also time-consuming to search for and reserve restaurants and delivery services related to the suggested meals. Furthermore, it is difficult to centrally manage weather forecasts and suggestions for new connections using social media. A system that can solve these issues is needed.

[0210] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for suggesting weekend activities taking into account the user's hobbies and schedule, means for making reservations and arrangements related to the proposed activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, and means for searching for available dining facilities and delivery services related to the proposed meals and making reservations and orders after obtaining the user's approval. This allows the user to centrally plan weekend activities and efficiently make related reservations and arrangements.

[0211] "A means of suggesting weekend activities taking into consideration the user's hobbies and schedule" is a function that automatically suggests optimal weekend activities based on the user's past behavioral history, preferences, and schedule information.

[0212] The "means for making reservations and arrangements related to the proposed activity" is a function for automatically making reservations for facilities and services required for the proposed activity and making the necessary preparations.

[0213] "Means for providing weather forecasts relevant to activities" refers to a function that provides weather information that may affect the proposed activity and gives appropriate advice to the user.

[0214] The "means for considering menus related to activities" is a function that suggests meal menus that match the proposed activity and provides the necessary ingredients and recipes.

[0215] "A means of suggesting new connections through social media posts" is a function that suggests new connections with other users who share common hobbies and interests based on the content that users post on social media.

[0216] "Means of searching for available dining establishments and delivery services related to the proposed meal and making reservations or orders after obtaining user approval" refers to a function that searches for available dining establishments and delivery services based on the meal proposed to the user and automatically makes reservations or orders after obtaining user confirmation.

[0217] A system for implementing this invention has functions that take into account a user's hobbies and schedules, suggest weekend activities, and make reservations and arrangements related to the suggested activities. It also has functions to provide weather forecasts related to the activities, consider menus related to the activities, and suggest new connections through social media posts. It also has functions to search for available restaurants and delivery services related to the suggested meals, and make reservations or orders after obtaining the user's approval.

[0218] System configuration

[0219] The system consists of the following major components:

[0220] 1. User terminal: A device such as a smartphone or tablet that provides the interface for users to interact with the system.

[0221] 2. Server: This is the central component that processes user data and performs functions such as providing suggestions, bookings, and weather forecasts.

[0222] 3. Database: Stores user hobbies, schedules, past activity history, weather information, information on restaurants, etc.

[0223] Program processing

[0224] The server performs the following process.

[0225] 1. Obtaining the user's hobbies and schedule: Obtaining the user's hobbies and schedule based on data sent from the user's device.

[0226] 2. Weekend activity suggestions: Based on the collected data, a generative AI model is used to suggest the best weekend activities for the user.

[0227] 3. Reservation and scheduling: Automatically book facilities and services related to the proposed activity.

[0228] 4. Providing weather forecasts: Providing weather information that may affect the proposed activity.

[0229] 5. Menu planning: Suggest a meal menu to match the proposed activities and provide the necessary ingredients and recipes.

[0230] 6. Suggesting new connections through social media posts: Analyzes users' social media posts and suggests new connections with other users who share common hobbies and interests.

[0231] 7. Search and book restaurants and delivery services: Based on the suggested meal, search for available restaurants and delivery services and automatically make reservations or orders after user confirmation.

[0232] Hardware and software used

[0233] Hardware: smartphones, tablets, servers

[0234] Software: Generative AI model, database management system, weather forecast API, social media analysis tool

[0235] Specific examples

[0236] For example, if a user says, "I want to eat sushi in Tokyo," the system operates as follows:

[0237] 1. The user device sends information to the server saying, "I want to eat sushi in Tokyo."

[0238] 2. The server uses the generative AI model to search for available sushi restaurants in Tokyo.

[0239] 3. Suggest search results to the user and obtain their approval.

[0240] 4. After approval, the server will automatically make a reservation at the sushi restaurant.

[0241] 5. Send a reservation completion notification to the user's device.

[0242] Example prompt sentence:

[0243] User location: Tokyo

[0244] Favorite food: Sushi

[0245] In this way, users can plan their weekend activities in one place and efficiently make related reservations and arrangements.

[0246] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0247] Step 1:

[0248] The user's device receives the user's location information and favorite food as input. For example, the user may enter information such as "I want to eat sushi in Tokyo." The device then sends this information to the server.

[0249] Step 2:

[0250] The server uses a generative AI model to search for appropriate restaurants based on the user's location information and preferred dishes. Specifically, it inputs the location information and type of food and retrieves a list of relevant restaurants from a database. The output is a list of relevant restaurants.

[0251] Step 3:

[0252] The server sends the list of restaurants to the user's terminal, which displays the list to the user and asks for their approval. The user then selects the restaurant they want from the list.

[0253] Step 4:

[0254] The user device sends the user's selection to the server. The server receives the information for making a reservation at the selected restaurant as input and executes the reservation by calling the reservation API. The output is a confirmation of the reservation.

[0255] Step 5:

[0256] The server sends reservation confirmation information to the user terminal. The user terminal displays this confirmation information to the user. The user confirms that the reservation is complete.

[0257] Step 6:

[0258] The server calls a weather API to provide weather forecasts relevant to the proposed activity. The input is the user's location and the date and time of the activity, and the output is the corresponding weather forecast information.

[0259] Step 7:

[0260] The server transmits the acquired weather forecast information to the user's device, which displays this information to the user to help them plan their activities.

[0261] Step 8:

[0262] The server uses a generative AI model to consider menu items related to the proposed activity and proposes appropriate menus. The input is the type of activity and the user's preferences, and the output is a list of suggested menus.

[0263] Step 9:

[0264] The server sends a list of suggested menus to the user terminal, which displays the list to the user and asks for their approval, and the user selects the desired menu from the list.

[0265] Step 10:

[0266] The server analyzes the user's social media posts using a social media analysis tool to suggest new connections through social media posts. The input is the user's social media posts, and the output is a list of other users who share common hobbies and interests.

[0267] Step 11:

[0268] The server sends the list of other users to the user's device. The user's device displays this list to the user and suggests new connections. The user selects a new connection from the list.

[0269] Example 3

[0270] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0271] Previous systems proposed activities based on users' hobbies and schedules, and related weather forecasts, meal suggestions, and new connection suggestions were provided separately, without being integrated. Furthermore, there was a lack of weather forecasts that took wind information into account, and suggestions for new connections through social media posts. This meant that users had to spend a lot of time and effort planning and preparing for activities.

[0272] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0273] In this invention, the server includes means for suggesting weekend activities taking into consideration the user's hobbies and schedule, means for making reservations and arrangements related to the proposed activities, means for obtaining a weather forecast based on the date, time, and location of the proposed activities and providing detailed information, particularly on wind conditions, means for suggesting a menu suitable for the proposed activities, and means for analyzing SNS posts related to the proposed activities and recommending other users with the same hobbies. This allows users to plan and prepare for activities in an integrated manner using a single system, significantly reducing the effort and time required.

[0274] "User" refers to an individual or organization that uses the system to receive activity suggestions and information.

[0275] "Hobbies" refers to activities or areas of interest that a user engages in for personal enjoyment.

[0276] "To Do" refers to activities or events that a user plans to do in the future.

[0277] "Weekend Activities" refers to the leisure and hobby activities that a user plans to undertake over the weekend.

[0278] "Suggestion means" refers to methods and technologies for selecting and presenting appropriate activities to users based on their hobbies and schedules.

[0279] "Reservation and scheduling means" means the methods and techniques for making reservations and arrangements for facilities and services related to the proposed activity.

[0280] "Means for obtaining weather forecasts" refers to methods and technologies for obtaining weather information for a specific date, time, and location from an external weather information service.

[0281] "Wind information" refers to meteorological data such as wind speed and direction at a specific date, time and location.

[0282] "Method of suggesting meals" refers to a method or technology for selecting and presenting to the user a meal menu appropriate for the proposed activity.

[0283] "Means for analyzing SNS posts" refers to methods and technologies for analyzing the content of posts on social networking services and extracting information related to users' interests and concerns.

[0284] "Means for recommending other users with the same hobbies" refers to methods and technologies for identifying and introducing other users who share the same hobbies or interests as the user based on the analysis of SNS posts.

[0285] The present invention is a system that suggests weekend activities based on a user's hobbies and schedule, and provides related weather forecasts, menus, and new connections. Specific embodiments of this system are described below.

[0286] System configuration

[0287] This system is mainly composed of three elements: a server, a terminal, and a user. The server receives input from users, processes various data, and generates results. The terminal is a device through which users enter input and display results from the server. A user is an individual or organization that uses the system to receive activity suggestions and information.

[0288] Hardware and software used

[0289] Server: Use a server machine equipped with a high-performance processor and a large amount of memory. Specifically, you can use a cloud service (for example, Amazon Web Services or Google (registered trademark) Cloud Platform).

[0290] Device: Using a device that can be controlled by the user, such as a smartphone, tablet, or computer.

[0291] Weather Forecast API: Use external weather information providers such as the OpenWeatherMap API.

[0292] SNS API: Use APIs of social networking services such as Instagram API.

[0293] Database: Use a database system (e.g., MySQL or PostgreSQL) to manage the menu database and user information database.

[0294] Program processing

[0295] Providing weather forecasts

[0296] 1. The user enters the date, time, and location of the activity into the device.

[0297] 2. The terminal sends the entered information to the server.

[0298] 3. The server creates and sends a request to the weather forecast API based on the received date, time, and location information.

[0299] 4. The weather API returns weather forecast data for the specified date, time, and location.

[0300] 5. The server parses the returned weather forecast data, extracting, among other things, wind information.

[0301] 6. The server formats the analysis results and generates data to provide to the user.

[0302] 7. The server sends the generated data to the terminal.

[0303] 8. The device displays the received data to the user.

[0304] Examples:

[0305] A user types in "Camping in Tokyo on October 15, 2023."

[0306] The server sends a request to the OpenWeatherMap API to get the weather forecast for Tokyo on October 15, 2023.

[0307] The server extracts information, particularly wind speed and direction, and notifies the user, "It will be windy that day, so be careful."

[0308] Example prompt sentence:

[0309] "We are planning to go camping in Tokyo on October 15, 2023. What is the weather forecast?"

[0310] Menu suggestions

[0311] 1. The user inputs a proposed activity (e.g., camping) into the terminal.

[0312] 2. The terminal sends the entered information to the server.

[0313] 3. The server searches the menu database for suitable menus for the proposed activity.

[0314] 4. The server selects appropriate menus from the search results and suggests them to the user.

[0315] 5. The server sends the selected menu to the terminal.

[0316] 6. The device displays the received menu to the user.

[0317] Examples:

[0318] User types "camping."

[0319] The server searches a database of camping food recipes and suggests "easy-to-cook barbecue sets" and "foil-baked recipes."

[0320] Example prompt sentence:

[0321] "Please tell me some easy meals suitable for camping."

[0322] Proposing new connections through social media posts

[0323] 1. The user inputs a proposed activity (e.g., camping) into the terminal.

[0324] 2. The terminal sends the entered information to the server.

[0325] 3. The server collects social media posts related to the proposed activity.

[0326] 4. The server analyzes the collected social media posts and identifies other users with the same interests.

[0327] 5. The server recommends the identified users and suggests new connections.

[0328] 6. The server sends the recommended user list to the terminal.

[0329] 7. The terminal displays the received list to the user.

[0330] Examples:

[0331] User types "camping."

[0332] The server uses the Instagram API to collect posts with the hashtag "camping."

[0333] The server identifies other users who have posted camping photos and suggests to the user, "Would you like to connect with this user?"

[0334] Example prompt sentence:

[0335] "Please analyze SNS posts related to camping and recommend users who have the same hobby." The flow of the identification process in the third embodiment will be described with reference to FIG.

[0336] Providing weather forecasts

[0337] Step 1: Receive user input.

[0338] The user enters the date, time and location of the activity into the terminal.

[0339] Input: Date and time of the activity (e.g. October 15, 2023) and location (e.g. Tokyo).

[0340] Output: The date, time, and location information entered.

[0341] Step 2: Send the input information to the server.

[0342] The terminal transmits the input information to the server.

[0343] Input: Date, time, and location information entered by the user.

[0344] Output: Date, time and location information sent to the server.

[0345] Step 3: Send a request to the weather API.

[0346] The server creates and sends a request to the weather forecast API based on the received date, time, and location information.

[0347] Input: Date, time and location information sent to the server.

[0348] Data processing: Generate requests for the weather forecast API.

[0349] Output: The request sent to the weather API.

[0350] Step 4: Receive weather forecast data.

[0351] The Weather API returns weather forecast data for a specified date, time, and location.

[0352] Input: The request sent to the weather API.

[0353] Output: Weather forecast data (e.g. temperature, probability of precipitation, wind speed, wind direction).

[0354] Step 5: Analyze the weather forecast data.

[0355] The server analyzes the received weather forecast data and extracts, among other things, wind information.

[0356] Input: Weather forecast data.

[0357] Data processing: Extract wind speed and direction information.

[0358] Output: Analysis results (especially wind information).

[0359] Step 6: Generate the data to provide to the user.

[0360] The server formats the analysis results and generates data to provide to the user.

[0361] Input: Analysis results.

[0362] Data processing: Generate notification messages for users.

[0363] Output: Data provided to the user (e.g., "It's windy that day, so be careful").

[0364] Step 7: Send the generated data to the terminal

[0365] The server transmits the generated data to the terminal.

[0366] Input: The data you provide to the user.

[0367] Output: Data sent to the terminal.

[0368] Step 8: Display the data to the user.

[0369] The terminal displays the received data to the user.

[0370] Input: The data sent by the server.

[0371] Output: The notification message displayed to the user.

[0372] Menu suggestions

[0373] Step 1: Receive user input.

[0374] The user inputs a proposed activity (eg, camping) into the terminal.

[0375] Input: Proposed activity (e.g. camping).

[0376] Output: The activity information entered.

[0377] Step 2: Send the input information to the server.

[0378] The terminal transmits the input information to the server.

[0379] Input: Activity information entered by the user.

[0380] Output: Activity information sent to the server.

[0381] Step 3: Search the menu database.

[0382] The server searches a menu database that matches the proposed activity.

[0383] Input: Activity information sent to the server.

[0384] Data processing: Generate search queries for the menu database.

[0385] Output: Search results (suitable meals).

[0386] Step 4: Choose a suitable menu.

[0387] The server selects appropriate menus from the search results and suggests them to the user.

[0388] Input: Search results.

[0389] Data processing: Select an appropriate menu.

[0390] Output: Selected menu.

[0391] Step 5: Send the selected menu to your device.

[0392] The server transmits the selected menu to the terminal.

[0393] Input: Selected menu.

[0394] Output: Menu information sent to the device.

[0395] Step 6: Display the menu to the user.

[0396] The device displays the received menu to the user.

[0397] Input: Menu information sent from the server.

[0398] Output: The menu displayed to the user.

[0399] Proposing new connections through social media posts

[0400] Step 1: Receive user input.

[0401] The user inputs a proposed activity (eg, camping) into the terminal.

[0402] Input: Proposed activity (e.g. camping).

[0403] Output: The activity information entered.

[0404] Step 2: Send the input information to the server.

[0405] The terminal transmits the input information to the server.

[0406] Input: Activity information entered by the user.

[0407] Output: Activity information sent to the server.

[0408] Step 3: Collect social media posts.

[0409] The server collects social media posts related to the proposed activity.

[0410] Input: Activity information sent to the server.

[0411] Data processing: Collect related posts using SNS API.

[0412] Output: Collected social media posts.

[0413] Step 4: Analyze your social media posts.

[0414] The server analyzes the collected social media posts and identifies other users with the same interests.

[0415] Input: Collected social media posts.

[0416] Data processing: Analysis of posted content.

[0417] Output: A list of users with the same interests.

[0418] Step 5: Propose a new connection.

[0419] The server recommends identified users and suggests new connections.

[0420] Input: A list of users with similar interests.

[0421] Data processing: Generate recommendation messages.

[0422] Output: A list of recommended users.

[0423] Step 6: Send the recommended user list to the device.

[0424] The server transmits a list of recommended users to the terminal.

[0425] Input: A list of users to recommend.

[0426] Output: The user list sent to the device.

[0427] Step 7: Display the list to the user.

[0428] The terminal displays the received list to the user.

[0429] Input: The user list sent by the server.

[0430] Output: The recommendation list displayed to the user.

[0431] (Application example 3)

[0432] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0433] Conventional activity suggestion systems suggest activities based on the user's hobbies and schedules, as well as weather forecasts, menu suggestions, and suggestions for new connections through social media. However, these functions are often provided separately, resulting in a lack of an integrated system. Furthermore, they do not order ingredients related to the suggested activities or generate menus using generative AI models, which does not sufficiently improve user convenience. Furthermore, for certain activities, such as camping, there is a need for searching and booking available campsites and providing weather forecasts that take wind information into account. An integrated system is needed to solve these issues.

[0434] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0435] In this invention, the server includes means for suggesting weekend activities taking into consideration the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for ordering ingredients related to the suggested activities, and means for generating menus suitable for the activities using a generative AI model. This allows the user to consistently perform activities from suggesting to preparing and carrying out activities, and forming new connections, all in one system.

[0436] "A means for suggesting weekend activities taking into consideration the user's hobbies and schedule" is a function that automatically suggests optimal weekend activities based on the hobbies and schedule entered by the user.

[0437] The "means for making reservations and arrangements related to the proposed activity" is a function for automatically making reservations and preparations necessary for the proposed activity.

[0438] A "means for providing weather forecasts relevant to an activity" is a function that provides detailed weather forecasts based on the date, time, and location of a proposed activity.

[0439] The "means for considering menus related to activities" is a function that automatically suggests menus suitable for the proposed activity.

[0440] "A means of suggesting new connections through social media posts" is a function that analyzes a user's social media posts and recommends other users who share the same hobbies.

[0441] "Means for ordering ingredients related to the proposed activity" means functionality that allows for online ordering of ingredients needed for the proposed activity.

[0442] "Means for generating a menu appropriate for an activity using a generative AI model" is a function that uses a generative AI model to automatically generate a menu that is optimal for a proposed activity.

[0443] "Means for searching for and reserving available campsites" is a function for searching for available campsites and making reservations.

[0444] The "means for assessing the impact of wind on an activity" is a function for assessing the impact of wind on a proposed activity based on wind information in a weather forecast.

[0445] A system for implementing this invention includes means for suggesting weekend activities taking into account a user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for ordering ingredients related to the suggested activities, and means for generating menus suitable for the activities using a generative AI model.

[0446] Hardware and software used

[0447] Hardware: Smartphone

[0448] Software: Weather forecast APIs (e.g., OpenWeatherMap), food delivery APIs (e.g., Uber Eats API), social media APIs (e.g., Instagram API), generative AI models (e.g., GPT-4)

[0449] Data processing and calculation

[0450] 1. A way to suggest weekend activities based on the user's hobbies and schedule:

[0451] Users enter their hobbies and plans into a smartphone app.

[0452] The server analyzes the entered data and suggests optimal weekend activities.

[0453] 2. How to make reservations or arrangements related to the proposed activity:

[0454] Automatically schedule and schedule the necessary appointments based on suggested activities.

[0455] For example, booking a campsite or arranging transportation.

[0456] 3. Means of providing weather forecasts relevant to the activity:

[0457] The server uses a weather API to retrieve the weather forecast based on the date, time, and location of the proposed activity.

[0458] In particular, it provides detailed wind information and displays it to the user.

[0459] 4. Ways to consider menus related to activities:

[0460] The server uses a generative AI model to generate a menu appropriate for the proposed activities.

[0461] For example, when camping, we suggest easy-to-cook camping meal menus.

[0462] 5. Ways to suggest new connections through social media posts:

[0463] The user links their social media account.

[0464] The server uses a social networking API to retrieve camping-related posts from users and recommend other users with the same hobbies.

[0465] 6. Means of ordering ingredients related to the proposed activity:

[0466] The server uses a food delivery API to allow ordering of ingredients needed for the proposed meal.

[0467] Specific examples

[0468] A user enters "Planning to camp at Mt. Fuji on October 15, 2023." The server displays "The weather forecast for Mt. Fuji on October 15 is sunny, with a wind speed of 5 m / s." The server then "suggests a barbecue set and hot sandwiches as suitable menu items for camping," and allows the user to "order ingredients for the barbecue set and hot sandwiches through a food delivery service." The server also "recommends other users who post camping photos on social media."

[0469] Prompt Sentence Examples

[0470] A user is planning a camping trip to Mount Fuji on October 15, 2023. Please suggest suitable weather forecasts and camping meals for this date. Also, please recommend other users who have posted camping photos on social media.

[0471] The above is an embodiment of the present invention.

[0472] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0473] Step 1:

[0474] A user enters information about their hobbies and plans into a smartphone app.

[0475] Input: Information about the user's hobbies and plans (e.g., camping, October 15, 2023, Mt. Fuji)

[0476] Data processing: The server analyzes the entered data and identifies the user's hobbies and schedule.

[0477] Output: Analyzed hobby and schedule data

[0478] Step 2:

[0479] The server then suggests optimal weekend activities based on the analyzed data.

[0480] Input: Analyzed hobby and schedule data

[0481] Data calculation: The server refers to the database and searches for activities that match the user's hobbies and schedule.

[0482] Output: Suggested activities (e.g. camping)

[0483] Step 3:

[0484] The server makes the reservations and arrangements associated with the proposed activity.

[0485] Input: Proposed activity (e.g. camping)

[0486] Data processing: The server searches for available campsites and makes reservations.

[0487] Output: Reservation confirmation information

[0488] Step 4:

[0489] The server provides a weather forecast based on the date, time and location of the proposed activity.

[0490] Input: Date, time and location of proposed activity (e.g. October 15, 2023, Mt. Fuji)

[0491] Data calculation: The server uses the weather forecast API to obtain the weather forecast for the specified date, time and location.

[0492] Output: Weather forecast information (e.g. sunny, wind speed 5m / s)

[0493] Step 5:

[0494] The server uses a generative AI model to generate a menu appropriate for the proposed activities.

[0495] Input: Proposed activity (e.g. camping)

[0496] Data calculation: The server uses a generative AI model to generate a menu suitable for camping.

[0497] Output: Suggested menu items (e.g., BBQ set, hot sandwich)

[0498] Step 6:

[0499] The server allows you to order the ingredients needed for the proposed menu.

[0500] Input: Suggested menu (e.g., BBQ set, hot sandwich)

[0501] Data processing: The server uses the food delivery API to order the necessary ingredients.

[0502] Output: Order confirmation information

[0503] Step 7:

[0504] The user links their social media account.

[0505] Input: User's SNS account information

[0506] Data processing: The server uses the SNS API to retrieve users' camping-related posts.

[0507] Output: Retrieved SNS post data

[0508] Step 8:

[0509] The server analyzes the SNS posts and recommends other users with the same hobbies.

[0510] Input: Retrieved SNS post data

[0511] Data computation: The server uses the generative AI model to identify other users with similar interests.

[0512] Output: Recommended user information

[0513] The above are the specific processing steps of the system for implementing the present invention.

[0514] 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.

[0515] "Example 1"

[0516] In one embodiment of the present invention, the emotion engine recognizes a user's emotions and tailors suggested activities based on the user's emotions. For example, if the emotion engine recognizes that the user is feeling stressed, it may suggest relaxation activities, such as a spa or massage. Alternatively, if the emotion engine recognizes that the user is feeling joyful, it may suggest activities that allow the user to share that joy, such as a party with friends.

[0517] "Example 2"

[0518] The emotion engine also adjusts new connection suggestions based on the user's emotions. For example, if it detects that the user is feeling lonely, it will recommend other users with similar interests and suggest new connections. If it detects that the user is feeling excited, it will recommend other users attending events that share that excitement.

[0519] "Example 3"

[0520] Additionally, the emotion engine considers activity-related menus based on the user's emotions: if it detects that the user is feeling down, it will suggest comfort foods, and if it detects that the user is feeling joy, it will suggest special meals to celebrate that joy.

[0521] "Example 4"

[0522] The emotion engine also schedules and makes reservations for activities based on the user's emotions. For example, if it recognizes that the user is feeling tense, it will automatically schedule activities aimed at relaxation. If it recognizes that the user is feeling relaxed, it will automatically schedule activities to maintain that sense of relaxation.

[0523] "Example 5"

[0524] Furthermore, the emotion engine provides weather forecasts relevant to activities based on the user's emotions. Specifically, if it recognizes that the user is feeling anxious, it will provide a detailed weather forecast to reduce that anxiety. If it recognizes that the user is feeling excited, it will provide a good weather forecast to maintain that excitement.

[0525] The processing flow of each embodiment will be described below.

[0526] "Example 1"

[0527] Step 1: The emotion engine recognizes the user's emotion.

[0528] Step 2: The emotion engine adjusts the activity suggestions based on the emotion.

[0529] Step 3: For example, if the user recognizes that they are feeling stressed, suggest a relaxation activity, such as a spa or massage.

[0530] Step 4: If the app recognizes that the user is experiencing joy, it will suggest activities that allow them to share that joy, such as partying with friends.

[0531] "Example 2"

[0532] Step 1: The emotion engine recognizes the user's emotion.

[0533] Step 2: The emotion engine tailors new connection suggestions based on that emotion.

[0534] Step 3: For example, if the app recognizes that a user is feeling lonely, it will recommend other users with similar interests and suggest new connections.

[0535] Step 4: If we recognize that a user is feeling excited, we will recommend other users who are attending the event who share that excitement.

[0536] "Example 3"

[0537] Step 1: The emotion engine recognizes the user's emotion.

[0538] Step 2: The emotion engine considers menu items related to the activity based on the emotion.

[0539] Step 3: For example, if the user recognizes they are feeling depressed, suggest comfort foods.

[0540] Step 4: If the app detects that the user is experiencing joy, it will suggest a special meal to celebrate that joy.

[0541] "Example 4"

[0542] Step 1: The emotion engine recognizes the user's emotion.

[0543] Step 2: The emotion engine makes bookings and arrangements related to the activity based on the emotion.

[0544] Step 3: For example, if the system recognizes that the user is feeling tense, it will automatically schedule a relaxation activity.

[0545] Step 4: If the system recognizes that the user feels safe, it will automatically schedule activities to maintain that feeling of safety.

[0546] "Example 5"

[0547] Step 1: The emotion engine recognizes the user's emotion.

[0548] Step 2: The emotion engine provides a weather forecast relevant to the activity based on the emotion.

[0549] Step 3: For example, if it recognizes that the user is feeling anxious, it provides a detailed weather forecast to alleviate that anxiety.

[0550] Step 4: If the app detects that the user is feeling excited, it will provide a good weather forecast to maintain that excitement.

[0551] Example 1

[0552] Next, a description will be given of Example 1 of Form 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."

[0553] Previous weekend activity suggestion systems were unable to consider the user's emotional state, let alone their hobbies and schedules. This made it difficult to suggest optimal activities when the user was feeling stressed or happy. Furthermore, they lacked comprehensive support for suggested activities, such as bookings, scheduling, weather forecasts, menu planning, and new connection suggestions.

[0554] 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.

[0555] In this invention, the server includes means for suggesting weekend activities taking into account the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, and means for recognizing the user's emotions and adjusting the suggested activities based on the emotions, thereby enabling optimal weekend activity suggestions taking into account the user's hobbies and emotional state.

[0556] "User" refers to any individual or entity that uses the System.

[0557] "Hobbies" refer to activities or interests that a user engages in for fun and enjoyment.

[0558] "To Do" refers to activities or events that a user plans to do in the future.

[0559] "Weekend Activities" refers to activities or events that users are suggested to do over the weekend.

[0560] "Method of suggestion" refers to the method of selecting the best weekend activities based on the user's hobbies and schedule and presenting them to the user.

[0561] "Booking and Arrangement Means" means a method for making reservations or arrangements related to a proposed activity.

[0562] "Means for providing weather forecasts" refers to a method for providing a user with weather information relevant to a proposed activity.

[0563] "Method for considering menu" refers to a method for considering and proposing meal menus related to the proposed activity.

[0564] "Methods of suggesting new connections through social media posts" refers to methods by which users suggest connecting with new people through social media.

[0565] "Means for recognizing emotions" refers to methods for analyzing user input data and behavioral data to determine the user's emotional state.

[0566] "Means for tailoring activity suggestions based on emotions" refers to a method for optimizing suggested activities based on a recognized emotional state of a user.

[0567] MODE FOR CARRYING OUT THE INVENTION

[0568] The present invention is a system that suggests weekend activities based on a user's hobbies and schedule. This system also considers the user's emotional state and can suggest optimal activities. Specific embodiments of this system are described below.

[0569] Hardware and software used

[0570] This system uses the following hardware and software:

[0571] Server: Database Management System (DBMS), emotion engine, generative AI model

[0572] Devices: smartphones, computers, tablets

[0573] Software: Dedicated application, web browser

[0574] Data storage and processing

[0575] Users use a device to enter their hobbies and plans through a dedicated application or web browser. For example, if a user wants to register "camping" or "hiking" as a hobby, they enter that information into the input form on the device and click the submit button.

[0576] The server receives the data sent by the device. The server analyzes the received data and saves information such as "camping" and "hiking" to the "hobbies" table in the database. Once saving is complete, the server returns a message to the device indicating that saving is complete.

[0577] Emotion recognition and activity suggestion

[0578] The server starts the emotion engine and analyzes the user's input data and behavioral data. For example, if the user inputs "I'm tired," the emotion engine analyzes the data and determines that the user is feeling stressed. The emotion engine returns the result to the server.

[0579] The server retrieves the user's hobby data from the database and selects the optimal weekend activity based on the results of the emotion engine. For example, if a user registers "camping" as a hobby and the emotion engine recognizes that the user is feeling stressed, the server generates data to suggest "spa" or "massage."

[0580] Proposal Notification

[0581] The server sends the generated proposal data to the device. The device then notifies the user of the received proposal data. For example, the device screen will display "Go to the spa this weekend to relax." The user can review the proposal and make reservations or plans as needed.

[0582] Examples and prompts

[0583] As a concrete example, consider the case where User A has registered "camping" and "hiking" as his or her hobbies and is currently feeling stressed. In this case, the server retrieves User A's hobbies from the database and recognizes that User A is feeling stressed using the emotion engine. As a result, the server suggests activities aimed at relaxation, such as "spa" or "massage."

[0584] Example prompt sentence:

[0585] "If User A has registered camping and hiking as a hobby and is currently feeling stressed, what weekend activities would you suggest?"

[0586] The system aims to improve users' quality of life by suggesting optimal weekend activities that take into account their hobbies and emotions.

[0587] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0588] Step 1:

[0589] Users register their hobbies and schedules

[0590] The user uses the device to access a dedicated application or web browser and enter their hobbies and plans. For example, if the user wants to register "camping" or "hiking" as a hobby, they enter that information into the input form on the device and click the submit button. The input data is sent from the device to the server.

[0591] Step 2:

[0592] The server saves the registered data in a database.

[0593] The server analyzes the data received from the device and saves it in the "Hobbies" table of the database. For example, if a user registers "camping" as a hobby, that information is saved in the database. When saving is complete, the server returns a message to the device indicating that saving is complete. The input is the user's hobby and schedule data, and the output is the information saved in the database.

[0594] Step 3:

[0595] The server uses an emotion engine to recognize the user's emotion.

[0596] The server launches the emotion engine and analyzes the user's input data and behavioral data. For example, if the user inputs "tired," the emotion engine analyzes the data and determines that the user is feeling stressed. The emotion engine returns the results to the server. The input is data related to the user's emotions, and the output is the result of emotion recognition by the emotion engine.

[0597] Step 4:

[0598] The server suggests weekend activities based on the user's hobbies and emotions.

[0599] The server retrieves the user's hobby data from the database and selects the optimal weekend activity based on the results of the emotion engine. For example, if a user registers "camping" as a hobby and the emotion engine recognizes that the user is feeling stressed, the server generates data to suggest "spa" or "massage." The input is the user's hobby data and the result of emotion recognition, and the output is data on the suggested activities.

[0600] Step 5:

[0601] The terminal notifies the user of the proposed activity.

[0602] The server sends the generated suggestion data to the device. The device then notifies the user of the received suggestion data. For example, the device screen displays "Go to the spa this weekend to relax." The user can review the suggestion and make reservations or plans as needed. The input is the data of the suggested activity, and the output is a notification to the user.

[0603] (Application example 1)

[0604] Next, a description will be given of Application Example 1 of Embodiment 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."

[0605] Conventional weekend activity suggestion systems are required to suggest activities that take into account not only the user's hobbies and schedule, but also the user's emotional state. Furthermore, there is a lack of systems that can provide information on physical store activities and events related to the suggested activities. Furthermore, a method for properly notifying the user of suggested activities is also needed.

[0606] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for suggesting weekend activities taking into account the user's hobbies and schedule, means for making reservations and arrangements related to the proposed activities, means for providing a weather forecast related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for recognizing the user's emotions and adjusting the suggested activities based on the emotions, means for suggesting activities and events at brick-and-mortar stores related to the proposed activities, and means for notifying the user of the suggested activities. This makes it possible to suggest optimal weekend activities taking into account the user's emotional state, and to provide information on activities and events at brick-and-mortar stores and notify the user of the suggested activities.

[0607] "A means of suggesting weekend activities taking into consideration the user's hobbies and schedule" is a function that suggests activities suitable for the weekend based on the hobbies and schedule information registered by the user.

[0608] The "means for making reservations and arrangements related to the proposed activity" is a function for automatically making reservations and preparations necessary for the proposed activity.

[0609] "Means for providing weather forecasts relevant to an activity" is a function for providing weather information that will affect the proposed activity.

[0610] The "means for considering menus related to activities" is a function for considering meal menus suitable for the proposed activity.

[0611] "Means of proposing new connections through social media posts" is a function that allows users to post information related to the proposed activity on social media and build new relationships.

[0612] The "means for recognizing a user's emotion and adjusting suggested activities based on the emotion" is a function for recognizing a user's emotional state and adjusting suggested activities in accordance with the emotion.

[0613] The "means for suggesting in-store activities and events related to the proposed activity" is a function for providing information about in-store activities and events related to the proposed activity.

[0614] The "means for notifying the user of a proposed activity" is a function for notifying the user of a proposed activity.

[0615] The system for implementing the present invention includes a number of means for suggesting weekend activities taking into account the user's hobbies, schedule, and emotional state. Specific embodiments of this system are described below.

[0616] Hardware and software used

[0617] Hardware: Smartphone (camera, microphone)

[0618] Software: Python, TENSORFLOW (registered trademark) (emotion recognition model), SQLite (database), Flask (backend), React Native (frontend)

[0619] Data processing and calculation

[0620] 1. Database setup: The server uses SQLite to set up a database to store users' hobbies and schedules. Users use their smartphones to register their hobbies and schedules in the application.

[0621] 2. Building an emotion recognition model: The server uses TensorFlow to build a model that recognizes user emotions based on data acquired from the smartphone's camera and microphone. When a user uses the application, emotions are recognized in real time through the camera and microphone.

[0622] 3. Activity suggestion algorithm: The server implements an algorithm that suggests activities suitable for the weekend based on the user's hobbies, schedule, and emotional state. The suggested activities include information on activities and events at physical stores.

[0623] 4. Notification function: The server implements a function to notify users of suggested activities. Users can receive the suggested activities via their smartphones.

[0624] Specific examples

[0625] 1. Hobby / Schedule Registration: A user registers "camping" and "watching movies" as hobbies.

[0626] 2. Emotion recognition: The system recognizes when the user is stressed.

[0627] 3. Activity Suggestion: The server will suggest nearby spas and massage parlors as relaxation activities.

[0628] 4. Notification: The user will be notified of the proposed activity on their smartphone.

[0629] Prompt Sentence Examples

[0630] Develop an application that suggests weekend activities based on the user's hobbies, schedule, and emotional state. If a user lists "camping" and "watching movies" as hobbies and is feeling stressed, include a feature that suggests activities aimed at relaxation.

[0631] In this way, it is possible to suggest optimal weekend activities that take into account the user's hobbies and emotional state, and to provide information on activities and events in physical stores and provide appropriate notifications.

[0632] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0633] Step 1:

[0634] A user uses a smartphone to register their hobbies and plans. They enter their hobbies and plans into the application's input form and press the send button. The entered data is sent from the device to the server. The server stores the received data in an SQLite database. The input is the user's hobbies and plans information, and the output is the information stored in the database.

[0635] Step 2:

[0636] The user launches the application and performs emotion recognition via the camera or microphone. The device acquires data from the camera or microphone in real time and inputs it into a TensorFlow model. The model recognizes the user's emotion and sends the results to a server. The input is data acquired from the camera or microphone, and the output is information about the recognized emotion.

[0637] Step 3:

[0638] The server suggests activities based on the user's hobbies, schedule, and emotional state. The server retrieves the user's hobbies and schedule information from the database, combines it with the emotion recognition results, and runs the activity suggestion algorithm. The algorithm selects weekend activities suitable for the user and generates information about them. The input is the user's hobbies, schedule, and emotional state information, and the output is information about suggested activities.

[0639] Step 4:

[0640] The server searches for activity and event information at physical stores related to the proposed activity. Based on the proposed activity, the server searches a database of relevant physical stores to obtain appropriate activity and event information. The input is the proposed activity information, and the output is the activity and event information at the relevant physical stores.

[0641] Step 5:

[0642] The server notifies the user of the proposed activity. The server aggregates the proposed activity and related physical store information and generates a notification message. The generated notification message is sent to the terminal and displayed to the user. The input is the proposed activity and physical store information, and the output is the notification message sent to the user.

[0643] Step 6:

[0644] The user receives a notification and confirms the proposed activity. The user taps the notification on their smartphone and opens the application to confirm the details of the proposed activity. The input is the notification message, and the output is the details of the activity confirmed by the user.

[0645] In this way, it becomes possible to suggest optimal weekend activities that take into account the user's hobbies and emotional state, and to provide information on activities and events in physical stores and provide appropriate notifications.

[0646] Example 2

[0647] Next, a description will be given of Example 2 of Form 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."

[0648] While previous systems could suggest weekend activities based on users' hobbies and schedules, they lacked the ability to automatically book and schedule related activities. They also lacked the ability to suggest new connections based on users' emotions. This can lead to users feeling lonely or missing opportunities to participate in events that share their excitement.

[0649] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0650] In this invention, the server includes means for suggesting weekend activities taking into consideration the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for analyzing the user's emotions and suggesting new connections, and means for suggesting new connections through social media posts. This allows the user to automatically make reservations and arrangements related to the suggested activities, and by being suggested new connections based on emotions, it becomes possible to reduce feelings of loneliness and participate in events where they can share excitement.

[0651] "User" refers to any individual or entity that uses the System.

[0652] "Hobbies" refer to activities or interests that a user engages in for personal enjoyment.

[0653] "To Do" refers to activities or events that a user plans to do in the future.

[0654] "Weekend Activities" refers to the activities and events that a user plans to do over the weekend.

[0655] "Means of suggestion" refers to the system's ability to suggest appropriate activities based on the user's hobbies and schedule.

[0656] "Means for making reservations and scheduling" refers to functionality for automatically making reservations for locations or services related to a proposed activity.

[0657] "Means for providing weather forecasts" refers to functionality for providing local weather information relevant to the proposed activity.

[0658] "Method for planning meals" refers to a function for planning meal menus related to a proposed activity.

[0659] "Means for analyzing emotions" refers to a function that analyzes the user's emotions and makes appropriate suggestions based on the results.

[0660] "Means to suggest new connections" refers to a function that suggests new relationships and events based on the user's emotions and hobbies.

[0661] "A means of suggesting new connections through social media posts" refers to a function that suggests new relationships and events based on the content that users post on social media.

[0662] MODE FOR CARRYING OUT THE INVENTION

[0663] The present invention is a system that takes into account the user's hobbies and schedules, suggests weekend activities, and automatically makes reservations and arrangements related to the suggested activities. It also has the function of analyzing the user's emotions and suggesting new connections.

[0664] Hardware and software used

[0665] This system uses the following hardware and software:

[0666] Server: A server for data processing and communication with external APIs.

[0667] Device: A device such as a smartphone or computer operated by a user.

[0668] External APIs: External services such as Google Maps API, Booking.com API, etc.

[0669] Generative AI models: Sentiment analysis engines such as OpenAI's GPT-4.

[0670] Specific operation of the system

[0671] 1. The user proposes an activity (e.g., camping) through the device interface.

[0672] 2. The device sends the user's suggestions to the server.

[0673] 3. The server analyzes the activity suggestions received from the user and uses the Google Maps API or Booking.com API to search for available locations (e.g., campgrounds) related to the suggested activity.

[0674] 4. The server presents the search results to the user and asks for approval.

[0675] 5. If the user approves, the server will automatically make the reservation.

[0676] 6. The device collects the user's emotional data and sends it to the server.

[0677] 7. The server analyzes the user's emotions using the emotion engine.

[0678] 8. Based on the analysis results of the emotion engine, the server recommends other users with the same hobbies if the user feels lonely.

[0679] 9. If a user is feeling excited, the server will recommend other users who are participating in the event who share that excitement.

[0680] 10. The server presents the recommendation results to the user and suggests new connections if the user shows interest.

[0681] Specific examples

[0682] Camping reservation: When a user is offered camping, the server uses Google Maps API to search for available campsites and makes the reservation after getting the user's approval.

[0683] Using the emotion engine: If the emotion engine analyzes that the user is feeling lonely, the server will recommend other users who share the same interests.

[0684] Prompt Sentence Examples

[0685] Camping reservation prompt: "When a user is offered a camping spot, explain how to search for available campsites and make a reservation after the user's approval."

[0686] Emotion Engine Prompt: "If the emotion engine determines that a user feels lonely, explain how it can recommend other users who share the same interests."

[0687] The above is an embodiment of the present invention.

[0688] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0689] Step 1:

[0690] The user suggests an activity (e.g., camping) through the device interface.

[0691] Input: Activity suggestions that users type into their device (e.g., "camping").

[0692] Output: Data on the proposed activity is sent from the device to the server.

[0693] Specific actions: The user opens the app on their smartphone, selects "camping," and presses the suggestion button.

[0694] Step 2:

[0695] The terminal transmits the user's suggestions to the server.

[0696] Input: Data of the activity suggested by the user.

[0697] Output: The proposed activity data is sent to the server.

[0698] Specific operation: The device receives user input and sends the data to a server over the Internet.

[0699] Step 3:

[0700] The server analyzes the activity suggestions received from the user.

[0701] Input: Data for the proposed activity.

[0702] Output: The search query related to the activity.

[0703] Specific behavior: The server analyzes the received data and generates the query "Search for campsites."

[0704] Step 4:

[0705] The server uses the Google Maps API or Booking.com API to search for available locations (e.g., campgrounds) related to the proposed activity.

[0706] Input: A search query related to the activity.

[0707] Output: A list of available campsites.

[0708] What happens: The server calls the Google Maps API to search for available campsites in the specified area.

[0709] Step 5:

[0710] The server presents the search results to the user and asks for approval.

[0711] Input: A list of available campsites.

[0712] Output: Campsite options presented to the user.

[0713] Specific operation: The server presents the search results "Campsite A," "Campsite B," and "Campsite C" to the user.

[0714] Step 6:

[0715] If the user approves, the server will automatically make the reservation.

[0716] Input: Campsite data selected by the user.

[0717] Output: Confirmation of successful booking.

[0718] Specific behavior: When the user selects and approves "Campsite B," the server completes the reservation for "Campsite B" using the Booking.com API.

[0719] Step 7:

[0720] The device collects the user's emotional data and sends it to the server.

[0721] Input: User sentiment data (e.g. chat history, activity logs).

[0722] Output: Emotion data is sent to the server.

[0723] What it does: The device collects the user's recent chat history and activity log and sends them to the server.

[0724] Step 8:

[0725] The server uses an emotion engine to analyze the user's emotions.

[0726] Input: User emotion data.

[0727] Output: Emotion analysis results.

[0728] Specific operation: The server uses an emotion engine (e.g., OpenAI's GPT-4) to analyze that "the user feels lonely."

[0729] Step 9:

[0730] Based on the analysis results of the emotion engine, the server recommends other users with the same hobbies if the user feels lonely.

[0731] Input: Sentiment analysis results.

[0732] Output: A list of recommended users.

[0733] Specific operation: The server searches the database for other users who have the same hobby (e.g., camping) and generates a recommendation list of "User X," "User Y," and "User Z."

[0734] Step 10:

[0735] If a user is feeling excited, the server will recommend other users attending the event who share that excitement.

[0736] Input: Sentiment analysis results.

[0737] Output: A list of recommended events.

[0738] Specific operation: The server searches the database for other users who are participating in events that share their excitement, and generates a recommendation list of "Event A," "Event B," and "Event C."

[0739] Step 11:

[0740] The server presents the recommendation results to the user and suggests new connections if the user shows interest.

[0741] Input: A list of recommended users or events.

[0742] Output: New connection suggestions.

[0743] Specific operation: The server presents a recommendation list to the user, and if the user shows interest in "User X," it creates a chat room with "User X" and proposes a new connection.

[0744] (Application example 2)

[0745] Next, a description will be given of Application Example 2 of Form 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."

[0746] Previous systems did not suggest activities or meals based on the user's emotions, making it difficult to increase the user's psychological satisfaction. Furthermore, they lacked the functionality to automatically make reservations and arrangements related to the suggested activities and meals, which increased the user's workload. Furthermore, they lacked the functionality to suggest new connections with other users who share the same hobbies and interests.

[0747] 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.

[0748] In this invention, the server includes means for suggesting weekend activities based on the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for recognizing the user's emotions and suggesting meals based on those emotions, means for making reservations and arranging delivery at restaurants related to the suggested meals, and means for suggesting connections with other users who share the same food preferences. This allows for suggestions of activities and meals based on the user's emotions, thereby increasing the user's psychological satisfaction. Furthermore, by automatically making reservations and arrangements related to the suggested activities and meals, the user's effort can be reduced. Furthermore, by suggesting new connections with other users who share the same hobbies and interests, the user's social connections can be strengthened.

[0749] "A means of suggesting weekend activities taking into consideration the user's hobbies and schedule" is a function that automatically suggests appropriate weekend activities based on the user's past activity history and calendar information.

[0750] The "means for making reservations and arrangements related to the proposed activity" is a function for automatically making reservations and preparations necessary for the proposed activity.

[0751] A "means for providing weather forecasts relevant to an activity" is a function that provides weather information that affects the proposed activity.

[0752] The "means for considering menus related to activities" is a function that suggests meal menus suitable for the proposed activity.

[0753] "A means of suggesting new connections through social media posts" is a function that analyzes a user's social media posts and suggests new connections with other users who share the same hobbies and interests.

[0754] "Means for recognizing the user's emotions and suggesting meals based on those emotions" refers to a function that detects the user's emotions using an emotion recognition engine and suggests meals based on those emotions.

[0755] "Means for making reservations at restaurants related to the proposed meals and arranging delivery" refers to a function that automatically makes reservations at restaurants that provide the proposed meals and arranges delivery.

[0756] "Means to suggest connections with other users who share the same food preferences" is a function that suggests new connections with other users who share the same preferences based on the user's food preferences.

[0757] A system for implementing this invention suggests activities and meals based on a user's emotions and automatically makes reservations and arrangements related to the suggestions. The system includes means for suggesting weekend activities taking into account the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for recognizing the user's emotions and suggesting meals based on the emotions, means for making reservations and arranging delivery at restaurants related to the suggested meals, and means for suggesting connections with other users who share the same food preferences.

[0758] 1. System Program

[0759] The system operates using the following hardware and software:

[0760] Hardware: Smartphone

[0761] Software: EmotionEngine (emotion recognition engine), RestaurantAPI (restaurant information API), UserProfile (user profile management)

[0762] 2. Program Processing

[0763] The server uses the Emotion Engine to detect the user's emotions. Then, based on the detected emotions, it uses the Restaurant API to suggest appropriate meals. Reservations and delivery arrangements for restaurants related to the suggested meals are automatically made through the Restaurant API. It also uses the User Profile to search for other users with the same food preferences and suggests new connections.

[0764] The specific processing flow is as follows:

[0765] 1. Emotion Recognition: The server uses the EmotionEngine to detect the user's emotions.

[0766] 2. Meal Suggestion: Based on the detected emotions, the server uses RestaurantAPI to suggest suitable meals.

[0767] 3. Reservations and scheduling: The server automatically makes restaurant reservations and arranges delivery for the suggested meals.

[0768] 4. Proposing new connections: The server uses the UserProfile to search for other users who share the same food preferences and propose new connections.

[0769] 3. Specific Examples

[0770] As a concrete example, the prompt sentence for when the user feels "lonely" is as follows:

[0771] user_id = '12345'

[0772] app.suggest_food(user_id)

[0773] When this prompt statement is executed, the server performs the following steps:

[0774] 1. EmotionEngine recognizes the user's emotion as "loneliness."

[0775] 2. UserProfile searches for other users with the same food preferences and suggests connections.

[0776] 3. If no suitable users are found, use RestaurantAPI to suggest meals based on "neutral" sentiment.

[0777] In this way, it is possible to suggest activities and meals based on the user's emotions, thereby increasing the user's psychological satisfaction. It also reduces the user's effort by automatically making reservations and arrangements related to the suggested activities and meals. Furthermore, it strengthens the user's social connections by suggesting new connections with other users who share the same hobbies and interests.

[0778] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0779] Step 1:

[0780] The server uses the EmotionEngine to recognize the user's emotions. The user provides voice, text, or image data as input. The EmotionEngine analyzes this data and classifies the user's emotions into categories such as "lonely," "excited," or "neutral." The output is the recognized emotion.

[0781] Step 2:

[0782] The server calls RestaurantAPI to suggest appropriate meals based on the recognized emotions. As input, the user's emotion data and the user's food preferences and allergy information are provided. Based on this data, RestaurantAPI generates a list of meals that are optimal for the user. As output, the list of suggested meals is obtained.

[0783] Step 3:

[0784] The server then makes restaurant reservations and arranges delivery for the suggested meals. The input is a list of suggested meals and the user's location. The server uses this data to find the best restaurant and arranges the reservation and delivery. The output is a reservation confirmation and delivery details.

[0785] Step 4:

[0786] The server uses UserProfile to suggest connections with other users who share the same food preferences if the user feels lonely. As input, the user's food preferences and past behavior history are provided. Based on this data, UserProfile searches for other users who share the same preferences and suggests connections. As output, a list of suggested users is obtained.

[0787] Step 5:

[0788] The server proposes new connections through social media posts to promote connections with the suggested users. As input, a list of suggested users and the user's social media account information are provided. Based on this data, the server proposes connections on social media and sends messages or requests to follow. As output, confirmation of the new connections on social media is obtained.

[0789] Example 3

[0790] Next, a third embodiment of the third embodiment will be described. 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."

[0791] In conventional systems, activity suggestions based on the user's hobbies and schedule, as well as related reservations, weather forecasts, and menu suggestions, were made individually, making it difficult for users to obtain consistent information. In addition, suggestions did not take the user's emotions into consideration, making it impossible to make optimal suggestions based on the user's psychological state. This led to a problem of reduced user satisfaction.

[0792] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0793] In this invention, the server includes means for suggesting weekend activities taking into consideration the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing a weather forecast related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for analyzing the user's emotions and making suggestions related to activities based thereon, means for providing a detailed weather forecast based on the user's emotions, means for booking activities for the purpose of relaxation based on the user's emotions, and means for suggesting comfort food based on the user's emotions. This allows the user to obtain consistent information and further allows the user to receive optimal suggestions according to their emotions.

[0794] "User" refers to any individual or entity that uses the System.

[0795] "Hobbies" refers to activities or areas of interest that a user engages in for personal enjoyment.

[0796] "To Do" refers to activities or events that a user plans to do in the future.

[0797] "Activity" refers to a specific action or event that a user takes.

[0798] "Suggestion" refers to recommendations or advice the system gives to the user.

[0799] "Reservation" refers to the process by which a User reserves in advance the use of a particular service or facility.

[0800] "Dandori" refers to the planning and preparations required to smoothly carry out an activity.

[0801] "Weather forecast" refers to information predicting weather conditions for a particular date, time and location.

[0802] A "menu" refers to a combination of dishes or meals suitable for a particular activity.

[0803] "SNS posting" refers to the transmission of information by users on social networking services.

[0804] "New connections" refers to relationships with other users that a user meets through the system.

[0805] "Emotion" refers to the user's psychological state or mood.

[0806] "Emotion engine" refers to the functionality within the system that analyzes user emotions and makes suggestions based on them.

[0807] "Comfort food" refers to food that is meant to comfort the user.

[0808] "Relaxation" refers to activities and methods that allow users to relax.

[0809] MODE FOR CARRYING OUT THE INVENTION

[0810] This invention is a system that suggests weekend activities based on the user's hobbies and schedule. Based on the user's input information, this system makes suggestions for activities, reservations, weather forecasts, meal suggestions, suggestions for new connections through social media posts, and suggestions based on the user's emotions.

[0811] Hardware and software used

[0812] This system operates among three parties: a server, a terminal, and a user. The server plays a central role in data processing and analysis, while the terminal receives input from the user and communicates with the server. The user accesses the system through the terminal and inputs the necessary information.

[0813] The specific software used is as follows:

[0814] OpenWeatherMap API: An API for getting weather forecasts.

[0815] Recipe database: A database for suggesting menus suitable for activities.

[0816] SNS API: An API for analyzing social media posts and suggesting new connections.

[0817] Sentiment engine: An engine for analyzing user emotions and making suggestions based on them.

[0818] Specific operation of the system

[0819] 1. Providing weather forecasts:

[0820] The user enters the date, time and location of the activity.

[0821] The terminal transmits the input information to the server.

[0822] The server retrieves the weather forecast using the OpenWeatherMap API.

[0823] The weather forecast obtained by the server is analyzed, and detailed information, particularly on wind, is extracted.

[0824] The server sends the analysis results to the device.

[0825] The device displays the weather forecast to the user.

[0826] Example: A user inputs "I'm planning to go camping next Saturday." The device sends this information to a server, which then makes a request to the OpenWeatherMap API to retrieve weather information for the specified date, time, and location. The server extracts detailed information such as wind speed and direction from the retrieved weather information, and the device displays to the user, "Next Saturday's weather will be sunny, with a wind speed of 10 km / h."

[0827] Example prompt: "We're planning a camping trip next Saturday. What's the weather forecast for that day?"

[0828] 2. Menu suggestions:

[0829] The user enters the type of activity.

[0830] The terminal transmits the input information to the server.

[0831] The server searches a recipe database and retrieves a menu suitable for the activity.

[0832] The server sends the acquired menu to the terminal.

[0833] The device displays the menu to the user.

[0834] Example: A user types, "Tell me some easy camping recipes." The device sends this information to a server, which searches a recipe database and retrieves recipes such as "Hamburg steak in foil" and "S'mores over a campfire." The server sends the retrieved recipes to the device, which then displays to the user, "Here's the recipe for Hamburg steak in foil."

[0835] Example prompt: "Can you give me some easy camping recipes?"

[0836] 3. Proposing new connections through social media posts:

[0837] Users post on social media related to the activity.

[0838] The device sends the post content to the server.

[0839] The server analyzes the relevant posts using the SNS API.

[0840] The server finds other users with similar interests.

[0841] The server sends recommended user information to the terminal.

[0842] The device will display recommended users to the user.

[0843] Example: A user types, "I posted a photo of camping." The device sends this information to a server, which uses a social media API to analyze posts with hashtags like "camping" or "outdoors." The server finds other users with the same hobby and sends that information to the device. The device then displays to the user, "Here are other users with the same hobby."

[0844] Example prompt: "I posted a photo of me camping. Can you tell me who shares the same hobby?"

[0845] 4. Menu suggestions using an emotional engine:

[0846] The user inputs their current emotion.

[0847] The terminal transmits the input information to the server.

[0848] The server uses an emotion engine to analyze the user's emotions.

[0849] The server will suggest a suitable menu based on your emotions.

[0850] The server sends the suggested menu to the terminal.

[0851] The device displays the menu to the user.

[0852] Example: A user types, "I'm feeling depressed today." The device sends this information to a server, which uses an emotion engine to analyze it as "depressed." The server then suggests comfort foods such as "chocolate cake" or "cream stew." The server then sends the suggested menu to the device, which then displays to the user, "Here's the chocolate cake recipe."

[0853] Example prompt: "I'm feeling down today. Can you recommend a comforting meal?"

[0854] 5. Booking and scheduling with emotion engine:

[0855] The user inputs their current emotion.

[0856] The terminal transmits the input information to the server.

[0857] The server uses an emotion engine to analyze the user's emotions.

[0858] The server schedules suitable activities based on the emotion.

[0859] The server transmits the reservation information to the terminal.

[0860] The terminal displays the reservation information to the user.

[0861] Example: A user types "I feel nervous." The device sends this information to a server, which uses an emotion engine to analyze it as "I feel nervous." The server then suggests booking a "massage" or "yoga class." The server then sends the booking information to the device, which then displays a message to the user saying "Your massage has been booked."

[0862] Example prompt: "I'm feeling nervous. Please schedule an activity that will help me relax."

[0863] 6. Emotion engine provides weather forecasts:

[0864] The user inputs their current emotion.

[0865] The terminal transmits the input information to the server.

[0866] The server uses an emotion engine to analyze the user's emotions.

[0867] The server retrieves detailed weather forecasts based on emotions.

[0868] The weather forecast obtained by the server is sent to the terminal.

[0869] The device displays the weather forecast to the user.

[0870] Example: A user inputs "I feel anxious." The device sends this information to a server, which uses its emotion engine to analyze it as "I feel anxious." The server retrieves a detailed weather forecast using the OpenWeatherMap API. The server sends the retrieved weather forecast to the device, which then displays to the user, "Tomorrow's weather will be sunny with a wind speed of 5 km / h."

[0871] An example of a prompt sentence is: "I'm feeling anxious. Please tell me in detail about the weather tomorrow." The flow of the specific processing in the third embodiment will be described with reference to FIG.

[0872] Providing weather forecasts

[0873] Step 1:

[0874] The user enters the date, time and location of the activity.

[0875] Input: Date, time and location of the activity

[0876] Output: Date, time and location information entered

[0877] What happens: A user types into their device, "I'm planning a camping trip next Saturday."

[0878] Step 2:

[0879] The terminal transmits the input information to the server.

[0880] Input: Date, time, and location information entered by the user

[0881] Output: Date, time and location information sent to the server

[0882] Specific operation: The device sends the user's input information to the server.

[0883] Step 3:

[0884] The server retrieves the weather forecast using the OpenWeatherMap API.

[0885] Input: Date, time and location information sent to the server

[0886] Output: Weather forecast data obtained from the OpenWeatherMap API

[0887] What happens: The server sends a request to the OpenWeatherMap API to retrieve weather information for the specified date, time, and location.

[0888] Step 4:

[0889] The weather forecast obtained by the server is analyzed, and detailed information, particularly on wind, is extracted.

[0890] Input: Weather forecast data obtained from the OpenWeatherMap API

[0891] Output: Analyzed weather forecast data (especially wind information)

[0892] Specific operation: Extract detailed information such as wind speed and direction from the weather information obtained by the server.

[0893] Step 5:

[0894] The server sends the analysis results to the device.

[0895] Input: Parsed weather forecast data

[0896] Output: Analysis results sent to the device

[0897] Specific operation: The server sends the analysis results to the device.

[0898] Step 6:

[0899] The device displays the weather forecast to the user.

[0900] Input: Analysis results sent to the device

[0901] Output: The weather forecast displayed to the user

[0902] Specific behavior: The device displays to the user, "Next Saturday's weather will be sunny with a wind speed of 10 km / h."

[0903] Menu suggestions

[0904] Step 1:

[0905] The user inputs the type of activity.

[0906] Input: Activity Type

[0907] Output: Information about the type of activity entered

[0908] What happens: A user types into their device, "What are some easy camping recipes?"

[0909] Step 2:

[0910] The terminal transmits the input information to the server.

[0911] Input: Activity type information entered by the user

[0912] Output: Information about the type of activity sent to the server

[0913] Specific operation: The device sends the user's input information to the server.

[0914] Step 3:

[0915] The server searches a recipe database and retrieves a menu suitable for the activity.

[0916] Input: Information about the type of activity sent to the server

[0917] Output: Menu information retrieved from the recipe database

[0918] What happens: The server searches a recipe database and retrieves recipes such as "Hamburg steaks in foil" and "S'mores over a campfire."

[0919] Step 4:

[0920] The server sends the acquired menu to the terminal.

[0921] Input: Menu information retrieved from the recipe database

[0922] Output: Menu information sent to the device

[0923] Specific operation: The server sends the obtained recipe to the device.

[0924] Step 5:

[0925] The terminal displays the menu to the user.

[0926] Input: Menu information sent to the device

[0927] Output: Menu information displayed to the user

[0928] What happens: The device displays to the user, "Here's the recipe for foil-baked hamburger steak."

[0929] Proposing new connections through social media posts

[0930] Step 1:

[0931] A user posts an activity on social media.

[0932] Input: Social media posts related to the activity

[0933] Output: Input social media post content

[0934] What happens: A user types "I posted a camping photo" into their device.

[0935] Step 2:

[0936] The device sends the post content to the server.

[0937] Input: Social media post content entered by the user

[0938] Output: Social media post content sent to the server

[0939] Specific operation: The device sends the user's input information to the server.

[0940] Step 3:

[0941] The server analyzes the relevant posts using the SNS API.

[0942] Input: Social media post content sent to the server

[0943] Output: Analysis of related posts obtained from the SNS API

[0944] What it does: The server uses social media APIs to analyze posts with hashtags such as "camping" and "outdoors."

[0945] Step 4:

[0946] The server finds other users with the same interests.

[0947] Input: Analysis results of related posts obtained from the SNS API

[0948] Output: Information about other users with the same interests

[0949] Specific behavior: The server finds other users with the same interests and retrieves their information.

[0950] Step 5:

[0951] The server transmits recommended user information to the terminal.

[0952] Input: Information about other users with the same interests

[0953] Output: Recommended user information sent to the device

[0954] Specific operation: The server sends recommended user information to the terminal.

[0955] Step 6:

[0956] The terminal displays recommended users to the user.

[0957] Input: Recommended user information sent to the device

[0958] Output: Recommendation information displayed to the user

[0959] Specific behavior: The device displays to the user, "Here are users with the same interests."

[0960] Menu suggestions using an emotion engine

[0961] Step 1:

[0962] The user inputs their current emotion.

[0963] Input: Current Emotion

[0964] Output: Input emotion information

[0965] What happens: A user types "I'm feeling down today" into their device.

[0966] Step 2:

[0967] The terminal transmits the input information to the server.

[0968] Input: Emotion information entered by the user

[0969] Output: Emotion information sent to the server

[0970] Specific operation: The device sends the user's input information to the server.

[0971] Step 3:

[0972] The server uses an emotion engine to analyze the user's emotions.

[0973] Input: Emotion information sent to the server

[0974] Output: Sentiment analysis results by the emotion engine

[0975] Specific behavior: The server uses the emotion engine to analyze that the person is "depressed."

[0976] Step 4:

[0977] The server will suggest a suitable menu based on your emotions.

[0978] Input: Sentiment analysis results from the emotion engine

[0979] Output: Suggested menu information

[0980] What it does: The server suggests comfort foods like "chocolate cake" or "cream stew."

[0981] Step 5:

[0982] The server sends the suggested menu to the terminal.

[0983] Input: Suggested menu information

[0984] Output: Menu information sent to the device

[0985] Specific operation: The server sends the suggested menu to the device.

[0986] Step 6:

[0987] The terminal displays the menu to the user.

[0988] Input: Menu information sent to the device

[0989] Output: Menu information displayed to the user

[0990] What happens: The device displays to the user, "Here's the chocolate cake recipe."

[0991] Emotional engine for booking and scheduling

[0992] Step 1:

[0993] The user inputs their current emotion.

[0994] Input: Current Emotion

[0995] Output: Input emotion information

[0996] Specific action: The user types "I'm nervous" into the terminal.

[0997] Step 2:

[0998] The terminal transmits the input information to the server.

[0999] Input: Emotion information entered by the user

[1000] Output: Emotion information sent to the server

[1001] Specific operation: The device sends the user's input information to the server.

[1002] Step 3:

[1003] The server uses an emotion engine to analyze the user's emotions.

[1004] Input: Emotion information sent to the server

[1005] Output: Sentiment analysis results by the emotion engine

[1006] Specific behavior: The server uses the emotion engine to analyze that the person is "nervous."

[1007] Step 4:

[1008] The server schedules suitable activities based on the emotion.

[1009] Input: Sentiment analysis results from the emotion engine

[1010] Output: Booked activity information

[1011] What happens: The server suggests booking a "massage" or "yoga class."

[1012] Step 5:

[1013] The server transmits the reservation information to the terminal.

[1014] Input: Scheduled activity information

[1015] Output: Reservation information sent to the terminal

[1016] Specific operation: The server sends reservation information to the terminal.

[1017] Step 6:

[1018] The terminal displays the reservation information to the user.

[1019] Input: Reservation information sent to the terminal

[1020] Output: Reservation information displayed to the user

[1021] What happens: The device displays to the user, "Your massage reservation has been completed."

[1022] Providing weather forecasts with an emotion engine

[1023] Step 1:

[1024] The user inputs their current emotion.

[1025] Input: Current Emotion

[1026] Output: Input emotion information

[1027] Specific action: The user types "I feel anxious" into the device.

[1028] Step 2:

[1029] The terminal transmits the input information to the server.

[1030] Input: Emotion information entered by the user

[1031] Output: Emotion information sent to the server

[1032] Specific operation: The device sends the user's input information to the server.

[1033] Step 3:

[1034] The server uses an emotion engine to analyze the user's emotions.

[1035] Input: Emotion information sent to the server

[1036] Output: Sentiment analysis results by the emotion engine

[1037] Specific behavior: The server uses the emotion engine to analyze that the person is "feeling anxious."

[1038] Step 4:

[1039] The server retrieves detailed weather forecasts based on emotions.

[1040] Input: Sentiment analysis results from the emotion engine

[1041] Output: Detailed weather forecast data

[1042] What happens: The server uses the OpenWeatherMap API to get a detailed weather forecast.

[1043] Step 5:

[1044] The weather forecast obtained by the server is sent to the terminal.

[1045] Input: Detailed weather forecast data

[1046] Output: Weather forecast data sent to the device

[1047] Specific operation: The weather forecast obtained by the server is sent to the device.

[1048] Step 6:

[1049] The device displays the weather forecast to the user.

[1050] Input: Weather forecast data sent to the device

[1051] Output: The weather forecast displayed to the user

[1052] Specific behavior: The device displays to the user, "Tomorrow's weather will be sunny with a wind speed of 5 km / h."

[1053] (Application example 3)

[1054] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1055] While conventional activity suggestion systems make suggestions based on a user's hobbies and schedules, they lack comprehensive suggestions that take into account the user's emotions, weather forecasts, and social media integration. Furthermore, because menu and reservation suggestions are not based on the user's emotions, the user experience is not fully improved. Furthermore, the quality of suggestions is limited because they do not use generative AI models to suggest menus or prompts. To solve these issues, comprehensive suggestions that take into account the user's emotions, weather forecasts, and social media integration are needed.

[1056] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1057] In this invention, the server includes: means for suggesting weekend activities taking into account the user's hobbies and schedules; means for making reservations and arrangements related to the suggested activities; means for providing a weather forecast related to the activities; means for considering menus related to the activities; means for suggesting new connections through social media posts; means for suggesting menus based on the user's emotions; means for making reservations and arrangements based on the user's emotions; means for providing a weather forecast based on the user's emotions; means for suggesting optimal meals based on the user's activities and emotions; means for improving the user experience by utilizing the weather forecast and social media; means for generating menus using a generative AI model; and means for inputting prompt sentences into the generative AI model. This enables comprehensive suggestions that take into account the user's emotions, weather forecast, and social media integration, thereby improving the user experience.

[1058] "User's hobbies and plans" refers to activities that the user is interested in, as well as events and schedules that the user has planned in advance.

[1059] "Weekend activities" refers to leisure activities, events, hobbies, etc. that a user plans to do over the weekend.

[1060] "Booking and Arranging" means reserving locations and services, and making any necessary preparations or arrangements related to the proposed activity.

[1061] "Weather forecast" refers to information predicting weather conditions for a particular date, time and location.

[1062] A "menu" refers to a menu or recipe of a meal appropriate for a particular activity or situation.

[1063] "SNS posts" refer to content such as text, images, and videos that users share on social networking services.

[1064] "New connections" refers to new interactions and relationships with other users who share the same hobbies and interests.

[1065] "Means for suggesting menus based on emotions" refers to a method of analyzing the user's emotional state and suggesting meal menus accordingly.

[1066] "Emotion-based booking and scheduling" refers to a method that analyzes a user's emotional state and automatically books or prepares activities accordingly.

[1067] "Means for providing weather forecasts based on emotions" refers to a method for analyzing a user's emotional state and providing a detailed weather forecast accordingly.

[1068] "Method for suggesting optimal meals" refers to a method for suggesting the most suitable meal menu based on the user's activities and emotions.

[1069] "Methods of utilizing weather forecasts and social media to improve user experience" refers to methods of utilizing weather forecast information and social media data to improve the user experience.

[1070] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to generate new information or suggestions from data.

[1071] A "prompt" refers to an instruction or question input to a generative AI model.

[1072] A system for implementing this invention includes means for suggesting weekend activities taking into consideration a user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing a weather forecast related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for suggesting menus based on a user's emotions, means for making reservations and arrangements based on a user's emotions, means for providing a weather forecast based on a user's emotions, means for suggesting optimal meals based on a user's activities and emotions, means for improving user experience by utilizing weather forecasts and social media, means for generating menus using a generative AI model, and means for inputting prompt sentences into the generative AI model.

[1073] Hardware and software used

[1074] Hardware: Smartphones, smart glasses, head-mounted displays

[1075] Software: Weather forecast APIs (e.g., OpenWeatherMap), social media APIs (e.g., Twitter API), sentiment analysis APIs (e.g., IBM Watson®), food delivery APIs (e.g., Uber Eats API)

[1076] Data processing and calculation

[1077] The server receives the user's hobbies and schedule as input and suggests weekend activities. It coordinates with the reservation system to make the necessary arrangements to make reservations and schedules related to the suggested activities. It uses a weather forecast API to retrieve and analyze weather information for the specified date, time, and location to provide a weather forecast related to the activities. It takes wind information into particular consideration and provides it to the user.

[1078] To suggest a menu based on the user's emotions, a sentiment analysis API is used to analyze the user's emotional state, and the corresponding meal menu is input as a prompt to the generative AI model. The generated menu is then provided to the user. For example, a prompt such as "Please tell me some easy recipes for camping" is input to the generative AI model, and the generated recipe is provided.

[1079] To suggest new connections through social media posts, we use social media APIs to retrieve users' posts and recommend other users with the same hobbies. For example, we can recommend other users who post camping photos and suggest new connections.

[1080] To make reservations and arrangements based on user emotions, the app uses a sentiment analysis API to analyze the user's emotional state and automatically book and prepare activities accordingly. For example, if the user is nervous, it will automatically book activities aimed at relaxation.

[1081] To provide weather forecasts based on user emotions, we use sentiment analysis APIs to analyze the user's emotional state and provide detailed weather forecasts accordingly. For example, if the user is feeling anxious, we provide detailed weather forecasts to alleviate that anxiety.

[1082] Examples of concrete examples and prompts

[1083] Specific examples

[1084] Weather forecast linkage function:

[1085] If a user asks, "What's the weather like for camping tomorrow?", the system retrieves data from the weather forecast API and answers, "It will be sunny tomorrow with a wind speed of 5 m / s."

[1086] Menu suggestion feature:

[1087] If a user asks, "Please tell me some easy meals to make while camping," the generative AI model will input the prompt, "Please tell me some easy meals to make while camping," and provide the generated recipe.

[1088] Prompt Sentence Examples

[1089] "Get the weather forecast for a specified date, time and location, detailing wind speed and chance of precipitation."

[1090] Please tell me some easy camping recipes.

[1091] This will enable comprehensive suggestions that take into account user emotions, weather forecasts, and social media integration, improving the user experience.

[1092] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1093] Step 1:

[1094] The user uses the terminal to input his / her hobbies and plans.

[1095] Input: User's hobbies and schedule

[1096] Output: Entered hobby and schedule data

[1097] Specific operation: A user uses a smartphone or smart glasses to input hobbies or plans. For example, they input "I plan to go camping this weekend."

[1098] Step 2:

[1099] The server suggests weekend activities based on the entered hobbies and schedule.

[1100] Input: Hobbies and schedule data

[1101] Output: Proposed activities

[1102] Specific operation: The server refers to the database and suggests suitable activities based on the entered hobbies and schedule. For example, it suggests "barbecue at a campsite."

[1103] Step 3:

[1104] The server makes the bookings and arrangements associated with the proposed activity.

[1105] Input: Proposed activity

[1106] Output: Reservation confirmation information

[1107] Specific operation: The server connects to the reservation system and makes the necessary reservations and arrangements for the proposed activity, for example, notifying the user that "campsite reservations have been completed."

[1108] Step 4:

[1109] A server provides weather forecasts relevant to the activity.

[1110] Input: Date, time and location of proposed activity

[1111] Output:Weather forecast information

[1112] Specific operation: The server uses the weather forecast API to obtain and analyze weather information for the specified date, time, and location. For example, it displays "Tomorrow will be sunny, with a wind speed of 5 m / s."

[1113] Step 5:

[1114] The server considers menus related to the activity.

[1115] Input: Proposed activity

[1116] Output: Suggested menu

[1117] Specific operation: The server inputs a prompt to the generated AI model, such as "Please tell me some recipes for easy meals to make at camp," and provides the generated recipes to the user.

[1118] Step 6:

[1119] The server suggests new connections through social media posts.

[1120] Input: User's social media posts

[1121] Output: Recommended users

[1122] Specific operation: The server uses the SNS API to retrieve the user's posts and recommend other users with the same hobbies. For example, it may notify the user by saying, "Recommend other users who post camping photos."

[1123] Step 7:

[1124] The server suggests menus based on the user's emotions.

[1125] Input: User's emotional state

[1126] Output: Suggested menu

[1127] Specific operation: The server uses an emotion analysis API to analyze the user's emotional state, inputs the corresponding meal menu into the generation AI model as a prompt sentence, and provides the generated menu to the user.

[1128] Step 8:

[1129] The server makes reservations and arrangements based on the user's emotions.

[1130] Input: User's emotional state

[1131] Output: Reservation confirmation information

[1132] Specific operation: The server uses the sentiment analysis API to analyze the user's emotional state and automatically reserves and prepares activities accordingly, for example, notifying the user that "reservation of a relaxation activity has been completed."

[1133] Step 9:

[1134] The server provides a weather forecast based on the user's emotions.

[1135] Input: User's emotional state

[1136] Output: Detailed weather forecast information

[1137] Specific operation: The server uses the sentiment analysis API to analyze the user's emotional state and provide a detailed weather forecast accordingly. For example, it displays "We provide a detailed weather forecast to reduce anxiety."

[1138] Step 10:

[1139] The server suggests the best meal based on the user's activities and emotions.

[1140] Input: User activity and emotional state

[1141] Output: Suggested meals

[1142] Specific operation: The server inputs a prompt to the generative AI model, such as "Please suggest the best meal based on the user's activities and emotions," and provides the generated meal to the user.

[1143] Step 11:

[1144] The server utilizes weather forecasts and social media to improve the user experience.

[1145] Input: Weather forecast information, SNS data

[1146] Output: Improved user experience

[1147] Specific operation: The server analyzes data obtained using weather forecast APIs and SNS APIs and provides information to improve the user experience, such as a notification that "We will suggest suitable activities based on the weather forecast."

[1148] 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.

[1149] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) 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.

[1150] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1151] 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.

[1152] [Second embodiment]

[1153] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[1154] 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.

[1155] 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.

[1156] The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and 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).

[1157] 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.

[1158] 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.

[1159] 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).

[1160] 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.

[1161] 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.

[1162] 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.

[1163] 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.

[1164] 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.

[1165] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1166] "Example 1"

[1167] The system of the present invention has a means for suggesting weekend activities taking into account the user's hobbies and schedule. Specifically, the system stores the user's registered hobbies and schedule in a database and suggests weekend activities based on them. For example, if the user has registered that camping is a hobby, the system suggests weekend camping.

[1168] "Example 2"

[1169] The system of the present invention also has a means for making reservations and arrangements related to the proposed activity. Specifically, the system automatically makes the reservations and arrangements necessary for the proposed activity. For example, if camping is proposed, the system searches for available campsites and makes reservations after obtaining the user's approval.

[1170] "Example 3"

[1171] The system of the present invention further includes a means for providing a weather forecast related to the activity. Specifically, the system obtains a weather forecast based on the date, time, and location of the proposed activity and provides it to the user. For example, if a user plans to go camping, the system provides a weather forecast for that day, particularly detailed wind information.

[1172] "Example 4"

[1173] The system of the present invention also has a means for considering menus related to the activity. Specifically, it proposes menus suitable for the proposed activity. For example, in the case of camping, it proposes menus for camping meals that are easy to prepare.

[1174] "Example 5"

[1175] Furthermore, the system of the present invention has a means for suggesting new connections through social media posts. Specifically, the system analyzes social media posts related to the proposed activity and recommends other users who share the same hobby. For example, the system may recommend other users who post camping photos and suggest new connections.

[1176] The processing flow of each embodiment will be described below.

[1177] "Example 1"

[1178] Step 1: The user registers their hobbies and schedule in the system.

[1179] Step 2: The system stores the registered information in a database.

[1180] Step 3: The system will suggest weekend activities based on the stored information. For example, if the user has registered that camping is a hobby, the system will suggest weekend camping.

[1181] "Example 2"

[1182] Step 1: The system automatically schedules and schedules the proposed activity.

[1183] Step 2: For example, if you suggest camping, the system will search for available campsites.

[1184] Step 3: The system asks the user if they want to approve the campsite reservation, and if approved, makes the reservation.

[1185] "Example 3"

[1186] Step 1: The system retrieves weather forecasts based on the date, time, and location of the proposed activity.

[1187] Step 2: The system will provide the retrieved weather forecast to the user. For example, if you are planning to go camping, the system will provide the weather forecast for that day, especially detailed wind information.

[1188] "Example 4"

[1189] Step 1: The system suggests a menu appropriate for the proposed activity.

[1190] Step 2: For example, if you're camping, the system will suggest easy-to-prepare camping meals.

[1191] "Example 5"

[1192] Step 1: The system analyzes social media posts related to the proposed activity.

[1193] Step 2: Based on the analysis results, the system recommends other users with similar interests.

[1194] Step 3: For example, recommend other users who post camping photos and suggest new connections.

[1195] Example 1

[1196] Next, a description will be given of Example 1 of Form 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."

[1197] Conventional weekend activity suggestion systems are required to comprehensively provide a wide range of functions, including not only taking into account the user's hobbies and schedules, but also related reservations and planning, weather forecasts, menu planning, and new connection suggestions. However, there was no system that provided all of these functions in a unified manner, forcing users to use multiple applications and services. Furthermore, advanced suggestion functions utilizing generative AI models were lacking. This resulted in reduced user convenience and the inability to obtain optimal weekend activity suggestions.

[1198] 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.

[1199] In this invention, the server includes a means for storing the user's hobbies and schedule in a database, a means for generating weekend activity suggestions using a generative AI model, and a means for notifying the user of the generated suggestions, thereby enabling optimal weekend activity suggestions based on the user's hobbies and schedule.

[1200] "A means of suggesting weekend activities taking into consideration the user's hobbies and schedule" is a function that suggests optimal weekend activities based on the hobbies and schedule information registered by the user.

[1201] The "means for making reservations and arrangements related to the proposed activity" is a function for automatically making reservations and preparations necessary for the proposed activity.

[1202] "Means for providing weather forecasts relevant to an activity" is a function for providing weather information that will affect the proposed activity.

[1203] The "means for considering menus related to activities" is a function for considering meal menus suitable for the proposed activity.

[1204] "A means to suggest new connections through social media posts" is a function that allows users to suggest connecting with new people through social media.

[1205] "Means for saving user's hobbies and schedules in a database" is a function for storing information about hobbies and schedules entered by the user in a database.

[1206] The "means for generating weekend activity suggestions using a generative AI model" is a function for utilizing a generative AI model to suggest optimal weekend activities to a user.

[1207] "Means for notifying the user of generated suggestions" is a function for informing the user of activity suggestions generated by the generative AI model.

[1208] This invention is a system that suggests weekend activities based on a user's hobbies and schedule. The system stores the user's registered hobbies and schedule in a database and suggests weekend activities based on that information. Specifically, the system works in cooperation with the server, terminal, and user elements.

[1209] Hardware and software used

[1210] server

[1211] The server receives the data sent by the user and stores it in a database. The server manages the data using a relational database such as MySQL or PostgreSQL. It also uses a generative AI model (e.g., OpenAI's GPT-3) to generate weekend activity suggestions for the user.

[1212] Terminal

[1213] The device provides an interface for users to input their hobbies and schedules. This can be a smartphone app or a web application. The device has a communication function to send the data entered by the user to a server.

[1214] User

[1215] The user inputs his / her hobbies and plans using the terminal. For example, the user inputs "I like camping and I'm free next weekend." This information is sent to the server via the terminal.

[1216] Data processing and calculation

[1217] Data storage

[1218] The server receives the data sent from the device, analyzes it, and saves it in a database. For example, it stores information such as the user ID, hobbies, and schedule in the corresponding columns.

[1219] Weekend Activity Suggestions

[1220] As the weekend approaches, the server runs a periodic job (for example, a Cron job) to retrieve the user's hobbies and schedule from the database. Based on the retrieved data, it generates a prompt to send to the generative AI model. For example, it generates a prompt such as, "The user's hobby is camping, and they are free next weekend. Please suggest some recommended activities." This prompt is sent to the generative AI model, which then generates suggested weekend activities.

[1221] Proposal Notification

[1222] The generated suggestions are sent from the server to the device. The device then notifies the user of the received suggestions. For example, the smartphone app's notification function could be used to display a suggestion such as, "The weather is nice next weekend, so why not enjoy camping at a nearby campground?"

[1223] Specific examples

[1224] For example, a user uses a smartphone app to input "Camping is my hobby and I'm free next weekend." The device sends this information to the server, which stores it in a database. As the weekend approaches, the server sends a prompt to the generative AI model: "My hobby is camping and I'm free next weekend. Please suggest some recommended activities." The generative AI model generates a suggestion: "The weather is nice next weekend, so how about enjoying camping at a nearby campground?" The server then sends this to the device. The device then notifies the user of this suggestion.

[1225] In this way, the system can provide optimal weekend activity suggestions based on the user's hobbies and schedule.

[1226] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1227] Step 1:

[1228] A user inputs their hobbies and plans using a terminal. For example, a user inputs "I like camping and I'm free next weekend." This input data is converted to JSON format on the terminal and sent to the server using an HTTP POST request. The input is information about the user's hobbies and plans, and the output is data sent to the server.

[1229] Step 2:

[1230] The server receives the HTTP POST request sent from the device. It analyzes the received data and extracts the user's hobbies and schedule. The server uses a MySQL database to store the extracted data in the appropriate table. For example, information such as user ID, hobbies, and schedule is stored in the corresponding columns. The input is data from the device, and the output is saved in the database.

[1231] Step 3:

[1232] As the weekend approaches, the server runs a periodic job (for example, a Cron job) to retrieve the user's hobbies and schedule from the database. Based on the retrieved data, it generates a prompt to send to the generative AI model. For example, it generates a prompt such as, "The user's hobby is camping, and they are free next weekend. Please suggest some recommended activities." The input is the user's hobbies and schedule information retrieved from the database, and the output is the generated prompt.

[1233] Step 4:

[1234] The server sends the generated prompt to a generative AI model, which then generates weekend activity suggestions based on the prompt. The generated suggestions are returned to the server. The input is the generated prompt, and the output is the suggestions from the generative AI model.

[1235] Step 5:

[1236] The server sends the proposal received from the generative AI model to the device. The device notifies the user of the received proposal. For example, a smartphone app's notification function can be used to display a proposal such as, "The weather is nice next weekend, why not enjoy camping at a nearby campground?" The input is the proposal from the generative AI model, and the output is a notification to the user.

[1237] (Application example 1)

[1238] Next, a description will be given of Application Example 1 of Form 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."

[1239] Conventional weekend activity suggestion systems not only consider users' hobbies and schedules, but also provide a wide range of functions, such as reservations and scheduling related to the suggested activities, weather forecasts, menu planning, and suggesting new connections through social media posts. However, few systems offer these functions in an integrated manner, and they do not fully satisfy user convenience. Furthermore, they lack the ability to collect feedback to improve the accuracy of suggestions, or advanced suggestion functions using generative AI models. This poses a challenge in suggesting weekend activities that satisfy users.

[1240] 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.

[1241] In this invention, the server includes means for suggesting weekend activities taking into consideration the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for suggesting activities based on the user's hobbies and schedule using a generative AI model, means for delivering content related to the suggested activities, and means for collecting user feedback to improve the accuracy of the suggestions. This makes it possible to suggest weekend activities that meet the diverse needs of users, thereby increasing user satisfaction.

[1242] "User" means any individual or entity that uses the System.

[1243] "Hobbies" are activities or interests that a user engages in for fun and enjoyment.

[1244] A "to-do" is an activity or event that a user plans to take place at a specific time in the future.

[1245] "Weekend activities" are leisure and hobby activities that a user plans to do over the weekend.

[1246] "Suggestions" are recommendations for weekend activities made by the system to the user.

[1247] "Reservation" means the process of reserving in advance a location or service related to a proposed activity.

[1248] "Set-up" refers to the specific plans and preparations for carrying out the proposed activity.

[1249] "Weather forecast" means local weather information relevant to the proposed activity.

[1250] A "menu" is a meal plan related to a proposed activity.

[1251] "SNS posting" refers to the act of a user sharing information on a social networking service.

[1252] "New connections" are the new relationships and communities that users build through social media posts.

[1253] A "generative AI model" is an algorithm that uses artificial intelligence to suggest activities based on a user's hobbies and schedule.

[1254] "Content" is information or media (videos, articles, event information, etc.) related to the proposed activity.

[1255] "Feedback" refers to the evaluations and opinions that users give to suggestions.

[1256] "Accuracy" is the degree to which the suggestions match the user's expectations and needs.

[1257] A system for carrying out this invention includes a plurality of means for suggesting weekend activities taking into consideration a user's hobbies and schedule, specifically means for storing the user's hobbies and schedule in a database and using a generative AI model to suggest weekend activities based on the hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing a weather forecast related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for delivering content related to the suggested activities, and means for collecting user feedback to improve the accuracy of the suggestions.

[1258] Hardware and software used

[1259] Hardware: Smartphones, servers

[1260] Software: Python, SQLite (database management), OpenAI API (generative AI model)

[1261] Data processing and calculation

[1262] 1. Database management: The server uses SQLite to store users' hobbies and schedules. When users enter their hobbies and schedules via their smartphones, the information is sent to the server and stored in the database.

[1263] 2. Generative AI model: The server uses the OpenAI API to suggest weekend activities based on the user's hobbies and schedule. It generates prompts based on user information retrieved from the database and inputs them into the generative AI model.

[1264] 3. Suggestion Generation: Retrieve suggestions from the generative AI model and display them to the user, along with related bookings, scheduling, weather forecasts, menu planning, and social media post suggestions.

[1265] 4. Content Delivery: Deliver content to users, such as videos, articles, and event information related to the proposed activity.

[1266] 5. Feedback collection: User ratings and opinions on suggestions are collected and stored in a database, which helps improve the accuracy of the generative AI model's suggestions.

[1267] Specific examples

[1268] For example, if a user lists their hobbies as "camping" and "hiking" and has Saturdays free, the server will generate the following prompt:

[1269] The user's hobbies are camping and hiking, and they are free on Saturdays. Please suggest some recommended activities for the weekend.

[1270] This prompt is input into a generative AI model, which then generates suggestions such as, "How about enjoying a hike in the nearby mountains on Saturday, followed by a night at a campsite?" Based on this suggestion, the server makes reservations for available campsites, schedules the trip, provides weather forecasts, suggests related menus, and suggests social media posts.

[1271] In this way, weekend activities can be proposed that meet the diverse needs of users, thereby improving user satisfaction.

[1272] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1273] Step 1:

[1274] A user uses a smartphone to input their hobbies and schedule. The input hobbies and schedule are sent from the smartphone to a server. The server receives this information and stores it in an SQLite database. The input data is hobbies (e.g., camping, hiking) and schedule (e.g., free on Saturdays). The user's hobbies and schedule are then saved in the database.

[1275] Step 2:

[1276] The server retrieves the user's hobbies and schedule from the database. Based on the retrieved data, it generates a prompt sentence to input into the generative AI model. Specifically, it creates a sentence that combines hobbies and schedule. For example, it generates a prompt sentence such as, "The user's hobbies are camping and hiking, and they are free on Saturdays. Please suggest some recommended activities for the weekend."

[1277] Step 3:

[1278] The server sends the generated prompt to the OpenAI API. The OpenAI API uses a generative AI model based on the prompt to suggest suitable weekend activities for the user. The generative AI model analyzes the input prompt and generates appropriate activity suggestions. For example, it generates a suggestion such as, "How about enjoying a hike in the nearby mountains on Saturday, followed by a night at a campsite?"

[1279] Step 4:

[1280] The server receives suggestions from the generative AI model and displays them to the user. It also provides information for making reservations and planning related to the suggested activities. For example, it displays search results and reservation links for available campsites. It also provides weather forecasts and menu suggestions related to the suggested activities.

[1281] Step 5:

[1282] The user inputs feedback on the proposed activity. The feedback is sent from the smartphone to the server. The server receives this feedback and stores it in a database. The feedback data includes evaluations and opinions of the proposal.

[1283] Step 6:

[1284] The server uses the collected feedback to improve the accuracy of the generative AI model's proposals. Specifically, it analyzes the feedback data and uses it as training data for the generative AI model. This improves the accuracy of future proposals.

[1285] Step 7:

[1286] The server delivers content related to the proposed activity (such as videos, articles, and event information) to the user. The content provides information related to the proposed activity and is of interest to the user. For example, content such as how to prepare for camping or hiking trails may be delivered.

[1287] In this way, weekend activities are suggested based on the user's hobbies and schedule, improving the user's satisfaction.

[1288] Example 2

[1289] Next, a description will be given of Example 2 of Form 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."

[1290] In conventional systems, when planning weekend activities, users had to use multiple websites and applications to gather information and make reservations and arrangements. This required a lot of time and effort, and often made planning complicated. In addition, there was no system that provided all the information related to activities, such as weather forecasts, related menu suggestions, and suggestions for new connections, all in one place. This made it difficult for users to maintain consistency in their plans and select the most suitable activities.

[1291] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for suggesting weekend activities taking into account the user's hobbies and schedule, a means for making reservations and arrangements related to the proposed activities, a means for analyzing the proposed activities using a generative AI model, a means for collecting information necessary for the proposed activities, a means for presenting suggestions to the user and obtaining approval, a means for providing a weather forecast related to the activities, a means for considering menus related to the activities, and a means for suggesting new connections through social media posts. This allows users to plan weekend activities within a single system, obtain necessary information in a unified manner, and efficiently make reservations and arrangements.

[1292] A "User" is an individual who utilizes the System to plan weekend activities and make reservations and arrangements related to the proposed activities.

[1293] "Hobbies" are activities or interests that a user engages in for personal enjoyment.

[1294] A "to-do" is an activity or event that a user plans to take place at a specific time in the future.

[1295] "Weekend activities" are leisure and hobby activities that a user plans to do over the weekend.

[1296] "Suggestion method" is a function in which the system automatically suggests weekend activities taking into account the user's hobbies and schedule.

[1297] "Means for making reservations and arrangements" refers to the system's ability to automatically make reservations and arrangements related to the proposed activity.

[1298] A "generative AI model" is an artificial intelligence model used to analyze user input and generate appropriate suggestions or information.

[1299] The "means of analysis" is a function that uses a generative AI model to analyze user input and identify necessary information and reservations.

[1300] "Means for collecting information" refers to the ability to collect information required for the proposed activity from the internet and other data sources.

[1301] "Means for presenting proposals and obtaining approval" is a function for presenting proposals to users based on collected information and obtaining approval from the users.

[1302] A "means for providing weather forecasts" is a function that provides a user with weather forecasts relevant to a proposed activity.

[1303] The "means for considering menus" is a function that considers meal menus related to the proposed activity and suggests them to the user.

[1304] "A means of suggesting new connections through social media posts" is a function that allows users to suggest connections with new people by posting on social media.

[1305] The present invention is a system that allows a user to plan weekend activities and automatically makes reservations and arrangements related to the proposed activities. A specific embodiment of this system will be described below.

[1306] System Overview

[1307] The system takes into account the user's hobbies and schedule to suggest weekend activities, and then makes related reservations and arrangements. It also uses a generative AI model to analyze the suggested activities, gather necessary information, and present it to the user. It also includes features related to the activities, such as weather forecasts, meal suggestions, and new connections.

[1308] Hardware and software used

[1309] User device: smartphone, PC, etc.

[1310] Server: Cloud server, database server

[1311] Generative AI models: Natural language processing models such as GPT-4

[1312] Web browser: Google Chrome, Mozilla Firefox, etc.

[1313] Dedicated application: A mobile application dedicated to the system

[1314] Web scraping tools: Beautiful Soup, Selenium, etc.

[1315] API: Campsite reservation system API, weather forecast API

[1316] Program processing

[1317] 1. Accepting user input

[1318] The user uses the device to input the activity they want to do. For example, the user opens a dedicated application on their smartphone and inputs, "I want to go camping this weekend."

[1319] 2. Analyze the proposed actions using a generative AI model.

[1320] The server receives the user's input and analyzes it using a generative AI model (e.g., GPT-4). Specifically, the user's input is sent to the generative AI model as a prompt, which identifies the necessary reservations and arrangements.

[1321] Example prompt: "User says they want to go camping this weekend. Find available campsites and gather information to make a reservation."

[1322] 3. Gather the necessary information.

[1323] The server collects information needed for the proposed activity via the Internet. For example, it accesses a campsite reservation site and searches for available campsites. It then uses a web scraping tool or API to obtain information about available campsites.

[1324] 4. Present the suggestion to the user.

[1325] Based on the information collected by the server, the server presents suggestions to the user. For example, it might display a message on the user's device saying, "The following campsites are available. Would you like to make a reservation?" Specifically, it sends a message to the user via a dedicated application or web browser.

[1326] 5. Obtain user approval.

[1327] The user uses the device to check and approve the proposal from the server. For example, the user enters "Yes, please make a reservation." The user's input is sent to the server via a dedicated application or web browser.

[1328] 6. Make a reservation.

[1329] The server receives the user's approval and makes the necessary reservations for the proposed activity. For example, it uses the API of a campground reservation system to confirm the campground reservation. Once the reservation is complete, the server sends a notification to the user that the reservation is complete.

[1330] Specific examples

[1331] If a user inputs "I want to go camping this weekend," the server analyzes it using a generative AI model and determines that a campsite reservation is required. Next, the server searches for available campsites via the Internet and presents suggestions to the user, saying, "The following campsites are available. Would you like to make a reservation?" If the user confirms, "Yes, please make a reservation," the server makes the reservation using the API of the campsite reservation system and sends the user a notification that the reservation is complete.

[1332] In this way, the system automatically makes reservations and arrangements related to activities proposed by the user.

[1333] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1334] Step 1:

[1335] The user proposes an activity. The user uses the device to input the activity they want to do. For example, the user opens a dedicated application on their smartphone and inputs by voice, "I want to go camping this weekend." This input is sent to the server.

[1336] Step 2:

[1337] The server analyzes the proposed activities using a generative AI model. The server receives the user's input and analyzes it using a generative AI model (e.g., GPT-4). Specifically, the server sends the user's input as a prompt to the generative AI model, which identifies the necessary reservations and arrangements. The input is the user's proposal, and the output is the analysis result, which is information on the necessary reservations and arrangements.

[1338] Step 3:

[1339] The server collects the necessary information. The server collects the information required for the proposed activity via the Internet. For example, access a campsite reservation site and search for available campsites. Use a web scraping tool or API to obtain campsite availability. The input is instructions for collecting information based on the analysis results, and the output is the collected information on campsite availability.

[1340] Step 4:

[1341] The server presents suggestions to the user. The server presents suggestions to the user based on the collected information. For example, it displays a message on the user's device saying, "The following campsites are available. Would you like to make a reservation?" Specifically, it sends a message to the user through a dedicated application or web browser. The input is the collected information, and the output is a suggested message to the user.

[1342] Step 5:

[1343] The user approves the proposal. The user uses the terminal to check and approve the proposal from the server. For example, the user enters the text "Yes, please make a reservation." The user's input is sent to the server via a dedicated application or web browser. The input is the user's approval message, and the output is approval information sent to the server.

[1344] Step 6:

[1345] The server makes the reservation. With the user's approval, the server makes the reservation required for the proposed activity. For example, the server uses the API of a campsite reservation system to confirm the campsite reservation. Once the reservation is complete, the server sends a notification to the user that the reservation is complete. The input is the user's approval information, and the output is a notification that the reservation is complete.

[1346] (Application example 2)

[1347] Next, a description will be given of Application Example 2 of Form 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."

[1348] In today's busy lifestyles, it takes time and effort for users to plan weekend activities and make related reservations and arrangements. It is also time-consuming to search for and reserve restaurants and delivery services related to the suggested meals. Furthermore, it is difficult to centrally manage weather forecasts and suggestions for new connections using social media. A system that can solve these issues is needed.

[1349] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for suggesting weekend activities taking into account the user's hobbies and schedule, means for making reservations and arrangements related to the proposed activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, and means for searching for available dining facilities and delivery services related to the proposed meals and making reservations and orders after obtaining the user's approval. This allows the user to centrally plan weekend activities and efficiently make related reservations and arrangements.

[1350] "A means of suggesting weekend activities taking into consideration the user's hobbies and schedule" is a function that automatically suggests optimal weekend activities based on the user's past behavioral history, preferences, and schedule information.

[1351] The "means for making reservations and arrangements related to the proposed activity" is a function for automatically making reservations for facilities and services required for the proposed activity and making the necessary preparations.

[1352] "Means for providing weather forecasts relevant to activities" refers to a function that provides weather information that may affect the proposed activity and gives appropriate advice to the user.

[1353] The "means for considering menus related to activities" is a function that suggests meal menus that match the proposed activity and provides the necessary ingredients and recipes.

[1354] "A means of suggesting new connections through social media posts" is a function that suggests new connections with other users who share common hobbies and interests based on the content that users post on social media.

[1355] "Means of searching for available dining establishments and delivery services related to the proposed meal and making reservations or orders after obtaining user approval" refers to a function that searches for available dining establishments and delivery services based on the meal proposed to the user and automatically makes reservations or orders after obtaining user confirmation.

[1356] A system for implementing this invention has functions that take into account a user's hobbies and schedules, suggest weekend activities, and make reservations and arrangements related to the suggested activities. It also has functions to provide weather forecasts related to the activities, consider menus related to the activities, and suggest new connections through social media posts. It also has functions to search for available restaurants and delivery services related to the suggested meals, and make reservations or orders after obtaining the user's approval.

[1357] System configuration

[1358] The system consists of the following major components:

[1359] 1. User terminal: A device such as a smartphone or tablet that provides the interface for users to interact with the system.

[1360] 2. Server: This is the central component that processes user data and performs functions such as providing suggestions, bookings, and weather forecasts.

[1361] 3. Database: Stores user hobbies, schedules, past activity history, weather information, information on restaurants, etc.

[1362] Program processing

[1363] The server performs the following process.

[1364] 1. Obtaining the user's hobbies and schedule: Obtaining the user's hobbies and schedule based on data sent from the user's device.

[1365] 2. Weekend activity suggestions: Based on the collected data, a generative AI model is used to suggest the best weekend activities for the user.

[1366] 3. Reservation and scheduling: Automatically book facilities and services related to the proposed activity.

[1367] 4. Providing weather forecasts: Providing weather information that may affect the proposed activity.

[1368] 5. Menu planning: Suggest a meal menu to match the proposed activities and provide the necessary ingredients and recipes.

[1369] 6. Suggesting new connections through social media posts: Analyzes users' social media posts and suggests new connections with other users who share common hobbies and interests.

[1370] 7. Search and book restaurants and delivery services: Based on the suggested meal, search for available restaurants and delivery services and automatically make reservations or orders after receiving user confirmation.

[1371] Hardware and software used

[1372] Hardware: smartphones, tablets, servers

[1373] Software: Generative AI model, database management system, weather forecast API, social media analysis tool

[1374] Specific examples

[1375] For example, if a user says, "I want to eat sushi in Tokyo," the system operates as follows:

[1376] 1. The user device sends information to the server saying, "I want to eat sushi in Tokyo."

[1377] 2. The server uses the generative AI model to search for available sushi restaurants in Tokyo.

[1378] 3. Suggest search results to the user and obtain their approval.

[1379] 4. After approval, the server will automatically make a reservation at the sushi restaurant.

[1380] 5. Send a reservation completion notification to the user's device.

[1381] Example prompt sentence:

[1382] User location: Tokyo

[1383] Favorite food: Sushi

[1384] In this way, users can plan their weekend activities in one place and efficiently make related reservations and arrangements.

[1385] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1386] Step 1:

[1387] The user's device receives the user's location information and favorite food as input. For example, the user may enter information such as "I want to eat sushi in Tokyo." The device then sends this information to the server.

[1388] Step 2:

[1389] The server uses a generative AI model to search for appropriate restaurants based on the user's location information and preferred dishes. Specifically, it inputs the location information and type of food and retrieves a list of relevant restaurants from a database. The output is a list of relevant restaurants.

[1390] Step 3:

[1391] The server sends the list of restaurants to the user's terminal, which displays the list to the user and asks for their approval. The user then selects the restaurant they want from the list.

[1392] Step 4:

[1393] The user device sends the user's selection to the server. The server receives the information for making a reservation at the selected restaurant as input and executes the reservation by calling the reservation API. The output is a confirmation of the reservation.

[1394] Step 5:

[1395] The server sends reservation confirmation information to the user terminal. The user terminal displays this confirmation information to the user. The user confirms that the reservation is complete.

[1396] Step 6:

[1397] The server calls a weather API to provide weather forecasts relevant to the proposed activity. The input is the user's location and the date and time of the activity, and the output is the corresponding weather forecast information.

[1398] Step 7:

[1399] The server transmits the acquired weather forecast information to the user's device, which displays this information to the user to help them plan their activities.

[1400] Step 8:

[1401] The server uses a generative AI model to consider menu items related to the proposed activity and proposes appropriate menus. The input is the type of activity and the user's preferences, and the output is a list of suggested menus.

[1402] Step 9:

[1403] The server sends a list of suggested menus to the user terminal, which displays the list to the user and asks for their approval, and the user selects the desired menu from the list.

[1404] Step 10:

[1405] The server analyzes the user's social media posts using a social media analysis tool to suggest new connections through social media posts. The input is the user's social media posts, and the output is a list of other users who share common hobbies and interests.

[1406] Step 11:

[1407] The server sends the list of other users to the user's device. The user's device displays this list to the user and suggests new connections. The user selects a new connection from the list.

[1408] Example 3

[1409] Next, a description will be given of Example 3 of Form Example 3. 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."

[1410] Previous systems proposed activities based on users' hobbies and schedules, and related weather forecasts, meal suggestions, and new connection suggestions were provided separately, without being integrated. Furthermore, there was a lack of weather forecasts that took wind information into account, and suggestions for new connections through social media posts. This meant that users had to spend a lot of time and effort planning and preparing for activities.

[1411] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1412] In this invention, the server includes means for suggesting weekend activities taking into consideration the user's hobbies and schedule, means for making reservations and arrangements related to the proposed activities, means for obtaining a weather forecast based on the date, time, and location of the proposed activities and providing detailed information, particularly on wind conditions, means for suggesting a menu suitable for the proposed activities, and means for analyzing SNS posts related to the proposed activities and recommending other users with the same hobbies. This allows users to plan and prepare for activities in an integrated manner using a single system, significantly reducing the effort and time required.

[1413] "User" refers to an individual or organization that uses the system to receive activity suggestions and information.

[1414] "Hobbies" refers to activities or areas of interest that a user engages in for personal enjoyment.

[1415] "To Do" refers to activities or events that a user plans to do in the future.

[1416] "Weekend Activities" refers to the leisure and hobby activities that a user plans to undertake over the weekend.

[1417] "Suggestion means" refers to methods and technologies for selecting and presenting appropriate activities to users based on their hobbies and schedules.

[1418] "Reservation and scheduling means" means the methods and techniques for making reservations and arrangements for facilities and services related to the proposed activity.

[1419] "Means for obtaining weather forecasts" refers to methods and technologies for obtaining weather information for a specific date, time, and location from an external weather information service.

[1420] "Wind information" refers to meteorological data such as wind speed and direction at a specific date, time and location.

[1421] "Method of suggesting meals" refers to a method or technology for selecting and presenting to the user a meal menu appropriate for the proposed activity.

[1422] "Means for analyzing SNS posts" refers to methods and technologies for analyzing the content of posts on social networking services and extracting information related to users' interests and concerns.

[1423] "Means for recommending other users with the same hobbies" refers to methods and technologies for identifying and introducing other users who share the same hobbies or interests as the user based on the analysis of SNS posts.

[1424] The present invention is a system that suggests weekend activities based on a user's hobbies and schedule, and provides related weather forecasts, menus, and new connections. Specific embodiments of this system are described below.

[1425] System configuration

[1426] This system is mainly composed of three elements: a server, a terminal, and a user. The server receives input from users, processes various data, and generates results. The terminal is a device through which users enter input and display results from the server. A user is an individual or organization that uses the system to receive activity suggestions and information.

[1427] Hardware and software used

[1428] Server: Use a server machine equipped with a high-performance processor and a large amount of memory. Specifically, you can use cloud services (for example, Amazon Web Services or Google Cloud Platform).

[1429] Device: Using a device that can be controlled by the user, such as a smartphone, tablet, or computer.

[1430] Weather Forecast API: Use external weather information providers such as the OpenWeatherMap API.

[1431] SNS API: Use APIs of social networking services such as Instagram API.

[1432] Database: Use a database system (e.g., MySQL or PostgreSQL) to manage the menu database and user information database.

[1433] Program processing

[1434] Providing weather forecasts

[1435] 1. The user enters the date, time, and location of the activity into the device.

[1436] 2. The terminal sends the entered information to the server.

[1437] 3. The server creates and sends a request to the weather forecast API based on the received date, time, and location information.

[1438] 4. The weather API returns weather forecast data for the specified date, time, and location.

[1439] 5. The server parses the returned weather forecast data, extracting, among other things, wind information.

[1440] 6. The server formats the analysis results and generates data to provide to the user.

[1441] 7. The server sends the generated data to the terminal.

[1442] 8. The device displays the received data to the user.

[1443] Examples:

[1444] A user types in "Camping in Tokyo on October 15, 2023."

[1445] The server sends a request to the OpenWeatherMap API to get the weather forecast for Tokyo on October 15, 2023.

[1446] The server extracts information, particularly wind speed and direction, and notifies the user, "It will be windy that day, so be careful."

[1447] Example prompt sentence:

[1448] "We are planning to go camping in Tokyo on October 15, 2023. What is the weather forecast?"

[1449] Menu suggestions

[1450] 1. The user inputs a proposed activity (e.g., camping) into the terminal.

[1451] 2. The terminal sends the entered information to the server.

[1452] 3. The server searches the menu database for suitable menus for the proposed activity.

[1453] 4. The server selects appropriate menus from the search results and suggests them to the user.

[1454] 5. The server sends the selected menu to the terminal.

[1455] 6. The device displays the received menu to the user.

[1456] Examples:

[1457] User types "camping."

[1458] The server searches a database of camping food recipes and suggests "easy-to-cook barbecue sets" and "foil-baked recipes."

[1459] Example prompt sentence:

[1460] "Please tell me some easy meals suitable for camping."

[1461] Proposing new connections through social media posts

[1462] 1. The user inputs a proposed activity (e.g., camping) into the terminal.

[1463] 2. The terminal sends the entered information to the server.

[1464] 3. The server collects social media posts related to the proposed activity.

[1465] 4. The server analyzes the collected social media posts and identifies other users with the same interests.

[1466] 5. The server recommends the identified users and suggests new connections.

[1467] 6. The server sends the recommended user list to the terminal.

[1468] 7. The terminal displays the received list to the user.

[1469] Examples:

[1470] User types "camping."

[1471] The server uses the Instagram API to collect posts with the hashtag "camping."

[1472] The server identifies other users who have posted camping photos and suggests to the user, "Would you like to connect with this user?"

[1473] Example prompt sentence:

[1474] "Please analyze SNS posts related to camping and recommend users who have the same hobby." The flow of the identification process in the third embodiment will be described with reference to FIG.

[1475] Providing weather forecasts

[1476] Step 1: Receive user input.

[1477] The user enters the date, time and location of the activity into the terminal.

[1478] Input: Date and time of the activity (e.g. October 15, 2023) and location (e.g. Tokyo).

[1479] Output: The date, time, and location information entered.

[1480] Step 2: Send the input information to the server.

[1481] The terminal transmits the input information to the server.

[1482] Input: Date, time, and location information entered by the user.

[1483] Output: Date, time and location information sent to the server.

[1484] Step 3: Send a request to the weather API.

[1485] The server creates and sends a request to the weather forecast API based on the received date, time, and location information.

[1486] Input: Date, time and location information sent to the server.

[1487] Data processing: Generate requests for the weather forecast API.

[1488] Output: The request sent to the weather API.

[1489] Step 4: Receive weather forecast data.

[1490] The Weather API returns weather forecast data for a specified date, time, and location.

[1491] Input: The request sent to the weather API.

[1492] Output: Weather forecast data (e.g. temperature, probability of precipitation, wind speed, wind direction).

[1493] Step 5: Analyze the weather forecast data.

[1494] The server analyzes the received weather forecast data and extracts, among other things, wind information.

[1495] Input: Weather forecast data.

[1496] Data processing: Extract wind speed and direction information.

[1497] Output: Analysis results (especially wind information).

[1498] Step 6: Generate the data to provide to the user.

[1499] The server formats the analysis results and generates data to provide to the user.

[1500] Input: Analysis results.

[1501] Data processing: Generate notification messages for users.

[1502] Output: Data provided to the user (e.g., "It's windy that day, so be careful").

[1503] Step 7: Send the generated data to the terminal.

[1504] The server transmits the generated data to the terminal.

[1505] Input: The data you provide to the user.

[1506] Output: Data sent to the terminal.

[1507] Step 8: Display the data to the user.

[1508] The terminal displays the received data to the user.

[1509] Input: The data sent by the server.

[1510] Output: The notification message displayed to the user.

[1511] Menu suggestions

[1512] Step 1: Receive user input.

[1513] The user inputs a proposed activity (eg, camping) into the terminal.

[1514] Input: Proposed activity (e.g. camping).

[1515] Output: The activity information entered.

[1516] Step 2: Send the input information to the server

[1517] The terminal transmits the input information to the server.

[1518] Input: Activity information entered by the user.

[1519] Output: Activity information sent to the server.

[1520] Step 3: Search the menu database.

[1521] The server searches a menu database that matches the proposed activity.

[1522] Input: Activity information sent to the server.

[1523] Data processing: Generate search queries for the menu database.

[1524] Output: Search results (suitable meals).

[1525] Step 4: Choose a suitable menu.

[1526] The server selects appropriate menus from the search results and suggests them to the user.

[1527] Input: Search results.

[1528] Data processing: Select an appropriate menu.

[1529] Output: Selected menu.

[1530] Step 5: Send the selected menu to your device.

[1531] The server transmits the selected menu to the terminal.

[1532] Input: Selected menu.

[1533] Output: Menu information sent to the device.

[1534] Step 6: Display the menu to the user.

[1535] The device displays the received menu to the user.

[1536] Input: Menu information sent from the server.

[1537] Output: The menu displayed to the user.

[1538] Proposing new connections through social media posts

[1539] Step 1: Receive user input.

[1540] The user inputs a proposed activity (eg, camping) into the terminal.

[1541] Input: Proposed activity (e.g. camping).

[1542] Output: The activity information entered.

[1543] Step 2: Send the input information to the server.

[1544] The terminal transmits the input information to the server.

[1545] Input: Activity information entered by the user.

[1546] Output: Activity information sent to the server.

[1547] Step 3: Collect social media posts.

[1548] The server collects social media posts related to the proposed activity.

[1549] Input: Activity information sent to the server.

[1550] Data processing: Collect related posts using SNS API.

[1551] Output: Collected social media posts.

[1552] Step 4: Analyze your social media posts.

[1553] The server analyzes the collected social media posts and identifies other users with the same interests.

[1554] Input: Collected social media posts.

[1555] Data processing: Analysis of posted content.

[1556] Output: A list of users with the same interests.

[1557] Step 5: Propose a new connection.

[1558] The server recommends identified users and suggests new connections.

[1559] Input: A list of users with similar interests.

[1560] Data processing: Generate recommendation messages.

[1561] Output: A list of recommended users.

[1562] Step 6: Send the recommended user list to the device.

[1563] The server transmits a list of recommended users to the terminal.

[1564] Input: A list of users to recommend.

[1565] Output: The user list sent to the device.

[1566] Step 7: Display the list to the user.

[1567] The terminal displays the received list to the user.

[1568] Input: The user list sent by the server.

[1569] Output: The recommendation list displayed to the user.

[1570] (Application example 3)

[1571] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1572] Conventional activity suggestion systems suggest activities based on the user's hobbies and schedules, as well as weather forecasts, menu suggestions, and suggestions for new connections through social media. However, these functions are often provided separately, resulting in a lack of an integrated system. Furthermore, they do not order ingredients related to the suggested activities or generate menus using generative AI models, which does not sufficiently improve user convenience. Furthermore, for certain activities, such as camping, there is a need for searching and booking available campsites and providing weather forecasts that take wind information into account. An integrated system is needed to solve these issues.

[1573] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1574] In this invention, the server includes means for suggesting weekend activities taking into consideration the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for ordering ingredients related to the suggested activities, and means for generating menus suitable for the activities using a generative AI model. This allows the user to consistently perform activities from suggesting to preparing and carrying out activities, and forming new connections, all in one system.

[1575] "A means for suggesting weekend activities taking into consideration the user's hobbies and schedule" is a function that automatically suggests optimal weekend activities based on the hobbies and schedule entered by the user.

[1576] The "means for making reservations and arrangements related to the proposed activity" is a function for automatically making reservations and preparations necessary for the proposed activity.

[1577] A "means for providing weather forecasts relevant to an activity" is a function that provides detailed weather forecasts based on the date, time, and location of a proposed activity.

[1578] The "means for considering menus related to activities" is a function that automatically suggests menus suitable for the proposed activity.

[1579] "A means of suggesting new connections through social media posts" is a function that analyzes a user's social media posts and recommends other users who share the same hobbies.

[1580] "Means for ordering ingredients related to the proposed activity" means functionality that allows for online ordering of ingredients needed for the proposed activity.

[1581] "Means for generating a menu appropriate for an activity using a generative AI model" is a function that uses a generative AI model to automatically generate a menu that is optimal for a proposed activity.

[1582] "Means for searching for and reserving available campsites" is a function for searching for available campsites and making reservations.

[1583] The "means for assessing the impact of wind on an activity" is a function for assessing the impact of wind on a proposed activity based on wind information in a weather forecast.

[1584] A system for implementing this invention includes means for suggesting weekend activities taking into account a user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for ordering ingredients related to the suggested activities, and means for generating menus suitable for the activities using a generative AI model.

[1585] Hardware and software used

[1586] Hardware: Smartphone

[1587] Software: Weather forecast APIs (e.g., OpenWeatherMap), food delivery APIs (e.g., Uber Eats API), social media APIs (e.g., Instagram API), generative AI models (e.g., GPT-4)

[1588] Data processing and calculation

[1589] 1. A way to suggest weekend activities based on the user's hobbies and schedule:

[1590] Users enter their hobbies and plans into a smartphone app.

[1591] The server analyzes the entered data and suggests optimal weekend activities.

[1592] 2. How to make reservations or arrangements related to the proposed activity:

[1593] Automatically schedule and schedule the necessary appointments based on suggested activities.

[1594] For example, booking a campsite or arranging transportation.

[1595] 3. Means of providing weather forecasts relevant to the activity:

[1596] The server uses a weather API to retrieve the weather forecast based on the date, time, and location of the proposed activity.

[1597] In particular, it provides detailed wind information and displays it to the user.

[1598] 4. Ways to consider menus related to activities:

[1599] The server uses a generative AI model to generate a menu appropriate for the proposed activities.

[1600] For example, when camping, we suggest easy-to-cook camping meal menus.

[1601] 5. Ways to suggest new connections through social media posts:

[1602] The user links their social media account.

[1603] The server uses a social networking API to retrieve camping-related posts from users and recommend other users with the same hobbies.

[1604] 6. Means of ordering ingredients related to the proposed activity:

[1605] The server uses a food delivery API to allow ordering of ingredients needed for the proposed meal.

[1606] Specific examples

[1607] A user enters "Planning to camp at Mt. Fuji on October 15, 2023." The server displays "The weather forecast for Mt. Fuji on October 15 is sunny, with a wind speed of 5 m / s." The server then "suggests a barbecue set and hot sandwiches as suitable menu items for camping," and allows the user to "order ingredients for the barbecue set and hot sandwiches through a food delivery service." The server also "recommends other users who post camping photos on social media."

[1608] Prompt Sentence Examples

[1609] A user is planning a camping trip to Mount Fuji on October 15, 2023. Please suggest suitable weather forecasts and camping meals for this date. Also, please recommend other users who have posted camping photos on social media.

[1610] The above is an embodiment of the present invention.

[1611] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1612] Step 1:

[1613] A user enters information about their hobbies and plans into a smartphone app.

[1614] Input: Information about the user's hobbies and plans (e.g., camping, October 15, 2023, Mt. Fuji)

[1615] Data processing: The server analyzes the entered data and identifies the user's hobbies and schedule.

[1616] Output: Analyzed hobby and schedule data

[1617] Step 2:

[1618] The server then suggests optimal weekend activities based on the analyzed data.

[1619] Input: Analyzed hobby and schedule data

[1620] Data calculation: The server refers to the database and searches for activities that match the user's hobbies and schedule.

[1621] Output: Suggested activities (e.g. camping)

[1622] Step 3:

[1623] The server makes the reservations and arrangements associated with the proposed activity.

[1624] Input: Proposed activity (e.g. camping)

[1625] Data processing: The server searches for available campsites and makes reservations.

[1626] Output: Reservation confirmation information

[1627] Step 4:

[1628] The server provides a weather forecast based on the date, time and location of the proposed activity.

[1629] Input: Date, time and location of proposed activity (e.g. October 15, 2023, Mt. Fuji)

[1630] Data calculation: The server uses the weather forecast API to obtain the weather forecast for the specified date, time and location.

[1631] Output: Weather forecast information (e.g. sunny, wind speed 5m / s)

[1632] Step 5:

[1633] The server uses a generative AI model to generate a menu appropriate for the proposed activities.

[1634] Input: Proposed activity (e.g. camping)

[1635] Data calculation: The server uses a generative AI model to generate a menu suitable for camping.

[1636] Output: Suggested menu items (e.g., BBQ set, hot sandwich)

[1637] Step 6:

[1638] The server allows you to order the ingredients needed for the proposed menu.

[1639] Input: Suggested menu (e.g., BBQ set, hot sandwich)

[1640] Data processing: The server uses the food delivery API to order the necessary ingredients.

[1641] Output: Order confirmation information

[1642] Step 7:

[1643] The user links their social media account.

[1644] Input: User's SNS account information

[1645] Data processing: The server uses the SNS API to retrieve users' camping-related posts.

[1646] Output: Retrieved SNS post data

[1647] Step 8:

[1648] The server analyzes the SNS posts and recommends other users with the same hobbies.

[1649] Input: Retrieved SNS post data

[1650] Data computation: The server uses the generative AI model to identify other users with similar interests.

[1651] Output: Recommended user information

[1652] The above are the specific processing steps of the system for implementing the present invention.

[1653] 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.

[1654] "Example 1"

[1655] In one embodiment of the present invention, the emotion engine recognizes a user's emotions and tailors suggested activities based on the user's emotions. For example, if the emotion engine recognizes that the user is feeling stressed, it may suggest relaxation activities, such as a spa or massage. Alternatively, if the emotion engine recognizes that the user is feeling joyful, it may suggest activities that allow the user to share that joy, such as a party with friends.

[1656] "Example 2"

[1657] The emotion engine also adjusts new connection suggestions based on the user's emotions. For example, if it detects that the user is feeling lonely, it will recommend other users with similar interests and suggest new connections. If it detects that the user is feeling excited, it will recommend other users attending events that share that excitement.

[1658] "Example 3"

[1659] Additionally, the emotion engine considers activity-related menus based on the user's emotions: if it detects that the user is feeling down, it will suggest comfort foods, and if it detects that the user is feeling joy, it will suggest special meals to celebrate that joy.

[1660] "Example 4"

[1661] The emotion engine also schedules and reserves activities based on the user's emotions. For example, if it recognizes that the user is feeling tense, it will automatically reserve activities aimed at relaxation. If it recognizes that the user is feeling relaxed, it will automatically reserve activities to maintain that sense of relaxation.

[1662] "Example 5"

[1663] Furthermore, the emotion engine provides weather forecasts relevant to activities based on the user's emotions. Specifically, if it recognizes that the user is feeling anxious, it will provide a detailed weather forecast to reduce that anxiety. If it recognizes that the user is feeling excited, it will provide a good weather forecast to maintain that excitement.

[1664] The processing flow of each embodiment will be described below.

[1665] "Example 1"

[1666] Step 1: The emotion engine recognizes the user's emotion.

[1667] Step 2: The emotion engine adjusts the activity suggestions based on the emotion.

[1668] Step 3: For example, if the user recognizes that they are feeling stressed, suggest a relaxation activity, such as a spa or massage.

[1669] Step 4: If the app recognizes that the user is experiencing joy, it will suggest activities that allow them to share that joy, such as partying with friends.

[1670] "Example 2"

[1671] Step 1: The emotion engine recognizes the user's emotion.

[1672] Step 2: The emotion engine tailors new connection suggestions based on that emotion.

[1673] Step 3: For example, if the app recognizes that a user is feeling lonely, it will recommend other users with similar interests and suggest new connections.

[1674] Step 4: If we recognize that a user is feeling excited, we will recommend other users who are attending the event who share that excitement.

[1675] "Example 3"

[1676] Step 1: The emotion engine recognizes the user's emotion.

[1677] Step 2: The emotion engine considers menu items related to the activity based on the emotion.

[1678] Step 3: For example, if the user recognizes they are feeling depressed, suggest comfort foods.

[1679] Step 4: If the app detects that the user is experiencing joy, it will suggest a special meal to celebrate that joy.

[1680] "Example 4"

[1681] Step 1: The emotion engine recognizes the user's emotion.

[1682] Step 2: The emotion engine makes bookings and arrangements related to the activity based on the emotion.

[1683] Step 3: For example, if the system recognizes that the user is feeling tense, it will automatically schedule a relaxation activity.

[1684] Step 4: If the system recognizes that the user feels safe, it will automatically schedule activities to maintain that feeling of safety.

[1685] "Example 5"

[1686] Step 1: The emotion engine recognizes the user's emotion.

[1687] Step 2: The emotion engine provides a weather forecast relevant to the activity based on the emotion.

[1688] Step 3: For example, if it recognizes that the user is feeling anxious, it provides a detailed weather forecast to alleviate that anxiety.

[1689] Step 4: If the app detects that the user is feeling excited, it will provide a good weather forecast to maintain that excitement.

[1690] Example 1

[1691] Next, a description will be given of Example 1 of Form 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."

[1692] Previous weekend activity suggestion systems were unable to consider the user's emotional state, let alone their hobbies and schedules. This made it difficult to suggest optimal activities when the user was feeling stressed or happy. Furthermore, they lacked comprehensive support for suggested activities, such as bookings, scheduling, weather forecasts, menu planning, and new connection suggestions.

[1693] 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.

[1694] In this invention, the server includes means for suggesting weekend activities taking into account the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, and means for recognizing the user's emotions and adjusting the suggested activities based on the emotions, thereby enabling optimal weekend activity suggestions taking into account the user's hobbies and emotional state.

[1695] "User" refers to any individual or entity that uses the System.

[1696] "Hobbies" refer to activities or interests that a user engages in for fun and enjoyment.

[1697] "To Do" refers to activities or events that a user plans to do in the future.

[1698] "Weekend Activities" refers to activities or events that users are suggested to do over the weekend.

[1699] "Method of suggestion" refers to the method of selecting the best weekend activities based on the user's hobbies and schedule and presenting them to the user.

[1700] "Booking and Arrangement Means" means a method for making reservations or arrangements related to a proposed activity.

[1701] "Means for providing weather forecasts" refers to a method for providing a user with weather information relevant to a proposed activity.

[1702] "Method for considering menu" refers to a method for considering and proposing meal menus related to the proposed activity.

[1703] "Methods of suggesting new connections through social media posts" refers to methods by which users suggest connecting with new people through social media.

[1704] "Means for recognizing emotions" refers to methods for analyzing user input data and behavioral data to determine the user's emotional state.

[1705] "Means for tailoring activity suggestions based on emotions" refers to a method for optimizing suggested activities based on a recognized emotional state of a user.

[1706] MODE FOR CARRYING OUT THE INVENTION

[1707] The present invention is a system that suggests weekend activities based on a user's hobbies and schedule. This system also considers the user's emotional state and can suggest optimal activities. Specific embodiments of this system are described below.

[1708] Hardware and software used

[1709] This system uses the following hardware and software:

[1710] Server: Database Management System (DBMS), emotion engine, generative AI model

[1711] Devices: smartphones, computers, tablets

[1712] Software: Dedicated application, web browser

[1713] Data storage and processing

[1714] Users use a device to enter their hobbies and plans through a dedicated application or web browser. For example, if a user wants to register "camping" or "hiking" as a hobby, they enter that information into the input form on the device and click the submit button.

[1715] The server receives the data sent by the device. The server analyzes the received data and saves information such as "camping" and "hiking" to the "hobbies" table in the database. Once saving is complete, the server returns a message to the device indicating that saving is complete.

[1716] Emotion recognition and activity suggestion

[1717] The server starts the emotion engine and analyzes the user's input data and behavioral data. For example, if the user inputs "I'm tired," the emotion engine analyzes the data and determines that the user is feeling stressed. The emotion engine returns the result to the server.

[1718] The server retrieves the user's hobby data from the database and selects the optimal weekend activity based on the results of the emotion engine. For example, if a user registers "camping" as a hobby and the emotion engine recognizes that the user is feeling stressed, the server generates data to suggest "spa" or "massage."

[1719] Proposal Notification

[1720] The server sends the generated proposal data to the device. The device then notifies the user of the received proposal data. For example, the device screen will display "Go to the spa this weekend to relax." The user can review the proposal and make reservations or plans as needed.

[1721] Examples and prompts

[1722] As a concrete example, consider the case where User A has registered "camping" and "hiking" as his or her hobbies and is currently feeling stressed. In this case, the server retrieves User A's hobbies from the database and recognizes that User A is feeling stressed using the emotion engine. As a result, the server suggests activities aimed at relaxation, such as "spa" or "massage."

[1723] Example prompt sentence:

[1724] "If User A has registered camping and hiking as a hobby and is currently feeling stressed, what weekend activities would you suggest?"

[1725] The system aims to improve users' quality of life by suggesting optimal weekend activities that take into account their hobbies and emotions.

[1726] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1727] Step 1:

[1728] Users register their hobbies and schedules

[1729] The user uses the device to access a dedicated application or web browser and enter their hobbies and plans. For example, if the user wants to register "camping" or "hiking" as a hobby, they enter that information into the input form on the device and click the submit button. The input data is sent from the device to the server.

[1730] Step 2:

[1731] The server saves the registered data in a database.

[1732] The server analyzes the data received from the device and saves it in the "Hobbies" table of the database. For example, if a user registers "camping" as a hobby, that information is saved in the database. When saving is complete, the server returns a message to the device indicating that saving is complete. The input is the user's hobby and schedule data, and the output is the information saved in the database.

[1733] Step 3:

[1734] The server uses an emotion engine to recognize the user's emotion.

[1735] The server launches the emotion engine and analyzes the user's input data and behavioral data. For example, if the user inputs "tired," the emotion engine analyzes the data and determines that the user is feeling stressed. The emotion engine returns the results to the server. The input is data related to the user's emotions, and the output is the result of emotion recognition by the emotion engine.

[1736] Step 4:

[1737] The server suggests weekend activities based on the user's hobbies and emotions.

[1738] The server retrieves the user's hobby data from the database and selects the optimal weekend activity based on the results of the emotion engine. For example, if a user registers "camping" as a hobby and the emotion engine recognizes that the user is feeling stressed, the server generates data to suggest "spa" or "massage." The input is the user's hobby data and the result of emotion recognition, and the output is data on the suggested activities.

[1739] Step 5:

[1740] The terminal notifies the user of the proposed activity.

[1741] The server sends the generated suggestion data to the device. The device then notifies the user of the received suggestion data. For example, the device screen displays "Go to the spa this weekend to relax." The user can review the suggestion and make reservations or plans as needed. The input is the data of the suggested activity, and the output is a notification to the user.

[1742] (Application example 1)

[1743] Next, a description will be given of Application Example 1 of Form 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."

[1744] Conventional weekend activity suggestion systems are required to suggest activities that take into account not only the user's hobbies and schedule, but also the user's emotional state. Furthermore, there is a lack of systems that can provide information on physical store activities and events related to the suggested activities. Furthermore, a method for properly notifying the user of suggested activities is also needed.

[1745] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for suggesting weekend activities taking into account the user's hobbies and schedule, means for making reservations and arrangements related to the proposed activities, means for providing a weather forecast related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for recognizing the user's emotions and adjusting the suggested activities based on the emotions, means for suggesting activities and events at brick-and-mortar stores related to the proposed activities, and means for notifying the user of the suggested activities. This makes it possible to suggest optimal weekend activities taking into account the user's emotional state, and to provide information on activities and events at brick-and-mortar stores and notify the user of the suggested activities.

[1746] "A means of suggesting weekend activities taking into consideration the user's hobbies and schedule" is a function that suggests activities suitable for the weekend based on the hobbies and schedule information registered by the user.

[1747] The "means for making reservations and arrangements related to the proposed activity" is a function for automatically making reservations and preparations necessary for the proposed activity.

[1748] "Means for providing weather forecasts relevant to an activity" is a function for providing weather information that will affect the proposed activity.

[1749] The "means for considering menus related to activities" is a function for considering meal menus suitable for the proposed activity.

[1750] "Means of proposing new connections through social media posts" is a function that allows users to post information related to the proposed activity on social media and build new relationships.

[1751] The "means for recognizing a user's emotion and adjusting suggested activities based on the emotion" is a function for recognizing a user's emotional state and adjusting suggested activities in accordance with the emotion.

[1752] The "means for suggesting in-store activities and events related to the proposed activity" is a function for providing information about in-store activities and events related to the proposed activity.

[1753] The "means for notifying the user of a proposed activity" is a function for notifying the user of a proposed activity.

[1754] The system for implementing the present invention includes a number of means for suggesting weekend activities taking into account the user's hobbies, schedule, and emotional state. Specific embodiments of this system are described below.

[1755] Hardware and software used

[1756] Hardware: Smartphone (camera, microphone)

[1757] Software: Python, TensorFlow (emotion recognition model), SQLite (database), Flask (backend), React Native (frontend)

[1758] Data processing and calculation

[1759] 1. Database setup: The server uses SQLite to set up a database to store users' hobbies and schedules. Users use their smartphones to register their hobbies and schedules in the application.

[1760] 2. Building an emotion recognition model: The server uses TensorFlow to build a model that recognizes user emotions based on data acquired from the smartphone's camera and microphone. When a user uses the application, emotions are recognized in real time through the camera and microphone.

[1761] 3. Activity suggestion algorithm: The server implements an algorithm that suggests activities suitable for the weekend based on the user's hobbies, schedule, and emotional state. The suggested activities include information on activities and events at physical stores.

[1762] 4. Notification function: The server implements a function to notify users of suggested activities. Users can receive the suggested activities via their smartphones.

[1763] Specific examples

[1764] 1. Hobby / Schedule Registration: A user registers "camping" and "watching movies" as hobbies.

[1765] 2. Emotion recognition: The system recognizes when the user is stressed.

[1766] 3. Activity Suggestion: The server will suggest nearby spas and massage parlors as relaxation activities.

[1767] 4. Notification: The user will be notified of the proposed activity on their smartphone.

[1768] Prompt Sentence Examples

[1769] Develop an application that suggests weekend activities based on the user's hobbies, schedule, and emotional state. If a user lists "camping" and "watching movies" as hobbies and is feeling stressed, include a feature that suggests activities aimed at relaxation.

[1770] In this way, it is possible to suggest optimal weekend activities that take into account the user's hobbies and emotional state, and to provide information on activities and events in physical stores and provide appropriate notifications.

[1771] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1772] Step 1:

[1773] A user uses a smartphone to register their hobbies and plans. They enter their hobbies and plans into the application's input form and press the send button. The entered data is sent from the device to the server. The server stores the received data in an SQLite database. The input is the user's hobbies and plans information, and the output is the information stored in the database.

[1774] Step 2:

[1775] The user launches the application and performs emotion recognition via the camera or microphone. The device acquires data from the camera or microphone in real time and inputs it into a TensorFlow model. The model recognizes the user's emotion and sends the results to a server. The input is data acquired from the camera or microphone, and the output is information about the recognized emotion.

[1776] Step 3:

[1777] The server suggests activities based on the user's hobbies, schedule, and emotional state. The server retrieves the user's hobbies and schedule information from the database, combines it with the emotion recognition results, and runs the activity suggestion algorithm. The algorithm selects weekend activities suitable for the user and generates information about them. The input is the user's hobbies, schedule, and emotional state information, and the output is information about suggested activities.

[1778] Step 4:

[1779] The server searches for activity and event information at physical stores related to the proposed activity. Based on the proposed activity, the server searches a database of relevant physical stores to obtain appropriate activity and event information. The input is the proposed activity information, and the output is the activity and event information at the relevant physical stores.

[1780] Step 5:

[1781] The server notifies the user of the proposed activity. The server aggregates the proposed activity and related physical store information and generates a notification message. The generated notification message is sent to the terminal and displayed to the user. The input is the proposed activity and physical store information, and the output is the notification message sent to the user.

[1782] Step 6:

[1783] The user receives a notification and confirms the proposed activity. The user taps the notification on their smartphone and opens the application to confirm the details of the proposed activity. The input is the notification message, and the output is the details of the activity confirmed by the user.

[1784] In this way, it becomes possible to suggest optimal weekend activities that take into account the user's hobbies and emotional state, and to provide information on activities and events in physical stores and provide appropriate notifications.

[1785] Example 2

[1786] Next, a description will be given of Example 2 of Form 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."

[1787] While previous systems could suggest weekend activities based on users' hobbies and schedules, they lacked the ability to automatically book and schedule related activities. They also lacked the ability to suggest new connections based on users' emotions. This can lead to users feeling lonely or missing opportunities to participate in events that share their excitement.

[1788] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1789] In this invention, the server includes means for suggesting weekend activities taking into consideration the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for analyzing the user's emotions and suggesting new connections, and means for suggesting new connections through social media posts. This allows the user to automatically make reservations and arrangements related to the suggested activities, and by being suggested new connections based on emotions, it becomes possible to reduce feelings of loneliness and participate in events where they can share excitement.

[1790] "User" refers to any individual or entity that uses the System.

[1791] "Hobbies" refer to activities or interests that a user engages in for personal enjoyment.

[1792] "To Do" refers to activities or events that a user plans to do in the future.

[1793] "Weekend Activities" refers to the activities and events that a user plans to do over the weekend.

[1794] "Means of suggestion" refers to the system's ability to suggest appropriate activities based on the user's hobbies and schedule.

[1795] "Means for making reservations and scheduling" refers to functionality for automatically making reservations for locations or services related to a proposed activity.

[1796] "Means for providing weather forecasts" refers to functionality for providing local weather information relevant to the proposed activity.

[1797] "Method for planning meals" refers to a function for planning meal menus related to a proposed activity.

[1798] "Means for analyzing emotions" refers to a function that analyzes the user's emotions and makes appropriate suggestions based on the results.

[1799] "Means to suggest new connections" refers to a function that suggests new relationships and events based on the user's emotions and hobbies.

[1800] "A means of suggesting new connections through social media posts" refers to a function that suggests new relationships and events based on the content that users post on social media.

[1801] MODE FOR CARRYING OUT THE INVENTION

[1802] The present invention is a system that takes into account the user's hobbies and schedules, suggests weekend activities, and automatically makes reservations and arrangements related to the suggested activities. It also has the function of analyzing the user's emotions and suggesting new connections.

[1803] Hardware and software used

[1804] This system uses the following hardware and software:

[1805] Server: A server for data processing and communication with external APIs.

[1806] Device: A device such as a smartphone or computer operated by a user.

[1807] External APIs: External services such as Google Maps API, Booking.com API, etc.

[1808] Generative AI models: Sentiment analysis engines such as OpenAI's GPT-4.

[1809] Specific operation of the system

[1810] 1. The user proposes an activity (e.g., camping) through the device interface.

[1811] 2. The device sends the user's suggestions to the server.

[1812] 3. The server analyzes the activity suggestions received from the user and uses the Google Maps API or Booking.com API to search for available locations (e.g., campgrounds) related to the suggested activity.

[1813] 4. The server presents the search results to the user and asks for approval.

[1814] 5. If the user approves, the server will automatically make the reservation.

[1815] 6. The device collects the user's emotional data and sends it to the server.

[1816] 7. The server analyzes the user's emotions using the emotion engine.

[1817] 8. Based on the analysis results of the emotion engine, the server recommends other users with the same hobbies if the user feels lonely.

[1818] 9. If a user is feeling excited, the server will recommend other users who are participating in the event who share that excitement.

[1819] 10. The server presents the recommendation results to the user and suggests new connections if the user shows interest.

[1820] Specific examples

[1821] Camping reservation: When a user is offered camping, the server uses Google Maps API to search for available campsites and makes the reservation after getting the user's approval.

[1822] Using the emotion engine: If the emotion engine analyzes that the user is feeling lonely, the server will recommend other users who share the same interests.

[1823] Prompt Sentence Examples

[1824] Camping reservation prompt: "When a user is offered a camping spot, explain how to search for available campsites and make a reservation after the user's approval."

[1825] Emotion Engine Prompt: "If the emotion engine determines that a user feels lonely, explain how it can recommend other users who share the same interests."

[1826] The above is an embodiment of the present invention.

[1827] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1828] Step 1:

[1829] The user suggests an activity (e.g., camping) through the device interface.

[1830] Input: Activity suggestions that users type into their device (e.g., "camping").

[1831] Output: Data on the proposed activity is sent from the device to the server.

[1832] Specific actions: The user opens the app on their smartphone, selects "camping," and presses the suggestion button.

[1833] Step 2:

[1834] The terminal transmits the user's suggestions to the server.

[1835] Input: Data of the activity suggested by the user.

[1836] Output: The proposed activity data is sent to the server.

[1837] Specific operation: The device receives user input and sends the data to a server over the Internet.

[1838] Step 3:

[1839] The server analyzes the activity suggestions received from the user.

[1840] Input: Data for the proposed activity.

[1841] Output: The search query related to the activity.

[1842] Specific behavior: The server analyzes the received data and generates the query "Search for campsites."

[1843] Step 4:

[1844] The server uses the Google Maps API or Booking.com API to search for available locations (e.g., campgrounds) related to the proposed activity.

[1845] Input: A search query related to the activity.

[1846] Output: A list of available campsites.

[1847] What happens: The server calls the Google Maps API to search for available campsites in the specified area.

[1848] Step 5:

[1849] The server presents the search results to the user and asks for approval.

[1850] Input: A list of available campsites.

[1851] Output: Campsite options presented to the user.

[1852] Specific operation: The server presents the search results "Campsite A," "Campsite B," and "Campsite C" to the user.

[1853] Step 6:

[1854] If the user approves, the server will automatically make the reservation.

[1855] Input: Campsite data selected by the user.

[1856] Output: Confirmation of successful booking.

[1857] Specific behavior: When the user selects and approves "Campsite B," the server completes the reservation for "Campsite B" using the Booking.com API.

[1858] Step 7:

[1859] The device collects the user's emotional data and sends it to the server.

[1860] Input: User sentiment data (e.g. chat history, activity logs).

[1861] Output: Emotion data is sent to the server.

[1862] What it does: The device collects the user's recent chat history and activity log and sends them to the server.

[1863] Step 8:

[1864] The server uses an emotion engine to analyze the user's emotions.

[1865] Input: User emotion data.

[1866] Output: Emotion analysis results.

[1867] Specific operation: The server uses an emotion engine (e.g., OpenAI's GPT-4) to analyze that "the user feels lonely."

[1868] Step 9:

[1869] Based on the analysis results of the emotion engine, the server recommends other users with the same hobbies if the user feels lonely.

[1870] Input: Sentiment analysis results.

[1871] Output: A list of recommended users.

[1872] Specific operation: The server searches the database for other users who have the same hobby (e.g., camping) and generates a recommendation list of "User X," "User Y," and "User Z."

[1873] Step 10:

[1874] If a user is feeling excited, the server will recommend other users attending the event who share that excitement.

[1875] Input: Sentiment analysis results.

[1876] Output: A list of recommended events.

[1877] Specific operation: The server searches the database for other users who are participating in events that share their excitement, and generates a recommendation list of "Event A," "Event B," and "Event C."

[1878] Step 11:

[1879] The server presents the recommendation results to the user and suggests new connections if the user shows interest.

[1880] Input: A list of recommended users or events.

[1881] Output: New connection suggestions.

[1882] Specific operation: The server presents a recommendation list to the user, and if the user shows interest in "User X," it creates a chat room with "User X" and proposes a new connection.

[1883] (Application example 2)

[1884] Next, a description will be given of Application Example 2 of Form 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."

[1885] Previous systems did not suggest activities or meals based on the user's emotions, making it difficult to increase the user's psychological satisfaction. Furthermore, they lacked the functionality to automatically make reservations and arrangements related to the suggested activities and meals, which increased the user's workload. Furthermore, they lacked the functionality to suggest new connections with other users who share the same hobbies and interests.

[1886] 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.

[1887] In this invention, the server includes means for suggesting weekend activities based on the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for recognizing the user's emotions and suggesting meals based on those emotions, means for making reservations and arranging delivery at restaurants related to the suggested meals, and means for suggesting connections with other users who share the same food preferences. This allows for suggestions of activities and meals based on the user's emotions, thereby increasing the user's psychological satisfaction. Furthermore, by automatically making reservations and arrangements related to the suggested activities and meals, the user's effort can be reduced. Furthermore, by suggesting new connections with other users who share the same hobbies and interests, the user's social connections can be strengthened.

[1888] "A means of suggesting weekend activities taking into consideration the user's hobbies and schedule" is a function that automatically suggests appropriate weekend activities based on the user's past activity history and calendar information.

[1889] The "means for making reservations and arrangements related to the proposed activity" is a function for automatically making reservations and preparations necessary for the proposed activity.

[1890] A "means for providing weather forecasts relevant to an activity" is a function that provides weather information that affects the proposed activity.

[1891] The "means for considering menus related to activities" is a function that suggests meal menus suitable for the proposed activity.

[1892] "A means of suggesting new connections through social media posts" is a function that analyzes a user's social media posts and suggests new connections with other users who share the same hobbies and interests.

[1893] "Means for recognizing the user's emotions and suggesting meals based on those emotions" refers to a function that detects the user's emotions using an emotion recognition engine and suggests meals based on those emotions.

[1894] "Means for making reservations at restaurants related to the proposed meals and arranging delivery" refers to a function that automatically makes reservations at restaurants that provide the proposed meals and arranges delivery.

[1895] "Means to suggest connections with other users who share the same food preferences" is a function that suggests new connections with other users who share the same preferences based on the user's food preferences.

[1896] A system for implementing this invention suggests activities and meals based on a user's emotions and automatically makes reservations and arrangements related to the suggestions. The system includes means for suggesting weekend activities taking into account the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing weather forecasts related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for recognizing the user's emotions and suggesting meals based on the emotions, means for making reservations and arranging delivery at restaurants related to the suggested meals, and means for suggesting connections with other users who share the same food preferences.

[1897] 1. System Program

[1898] The system operates using the following hardware and software:

[1899] Hardware: Smartphone

[1900] Software: EmotionEngine (emotion recognition engine), RestaurantAPI (restaurant information API), UserProfile (user profile management)

[1901] 2. Program Processing

[1902] The server uses the Emotion Engine to detect the user's emotions. Then, based on the detected emotions, it uses the Restaurant API to suggest appropriate meals. Reservations and delivery arrangements for restaurants related to the suggested meals are automatically made through the Restaurant API. It also uses the User Profile to search for other users with the same food preferences and suggests new connections.

[1903] The specific processing flow is as follows:

[1904] 1. Emotion Recognition: The server uses the EmotionEngine to detect the user's emotions.

[1905] 2. Meal Suggestion: Based on the detected emotions, the server uses RestaurantAPI to suggest suitable meals.

[1906] 3. Reservations and scheduling: The server automatically makes restaurant reservations and arranges delivery for the suggested meals.

[1907] 4. Proposing new connections: The server uses the UserProfile to search for other users who share the same food preferences and propose new connections.

[1908] 3. Specific Examples

[1909] As a concrete example, the prompt sentence for when the user feels "lonely" is as follows:

[1910] user_id = '12345'

[1911] app.suggest_food(user_id)

[1912] When this prompt statement is executed, the server performs the following steps:

[1913] 1. EmotionEngine recognizes the user's emotion as "loneliness."

[1914] 2. UserProfile searches for other users with the same food preferences and suggests connections.

[1915] 3. If no suitable users are found, use RestaurantAPI to suggest meals based on "neutral" sentiment.

[1916] In this way, it is possible to suggest activities and meals based on the user's emotions, thereby increasing the user's psychological satisfaction. It also reduces the user's effort by automatically making reservations and arrangements related to the suggested activities and meals. Furthermore, it strengthens the user's social connections by suggesting new connections with other users who share the same hobbies and interests.

[1917] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1918] Step 1:

[1919] The server uses the EmotionEngine to recognize the user's emotions. The user provides voice, text, or image data as input. The EmotionEngine analyzes this data and classifies the user's emotions into categories such as "lonely," "excited," or "neutral." The output is the recognized emotion.

[1920] Step 2:

[1921] The server calls RestaurantAPI to suggest appropriate meals based on the recognized emotions. As input, the user's emotion data and the user's food preferences and allergy information are provided. Based on this data, RestaurantAPI generates a list of meals that are optimal for the user. As output, the list of suggested meals is obtained.

[1922] Step 3:

[1923] The server then makes restaurant reservations and arranges delivery for the suggested meals. The input is a list of suggested meals and the user's location. The server uses this data to find the best restaurant and arranges the reservation and delivery. The output is a reservation confirmation and delivery details.

[1924] Step 4:

[1925] The server uses UserProfile to suggest connections with other users who share the same food preferences if the user feels lonely. As input, the user's food preferences and past behavior history are provided. Based on this data, UserProfile searches for other users who share the same preferences and suggests connections. As output, a list of suggested users is obtained.

[1926] Step 5:

[1927] The server proposes new connections through social media posts to promote connections with the suggested users. As input, a list of suggested users and the user's social media account information are provided. Based on this data, the server proposes connections on social media and sends messages or requests to follow. As output, confirmation of the new connections on social media is obtained.

[1928] Example 3

[1929] Next, a description will be given of Example 3 of Form Example 3. 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."

[1930] In conventional systems, activity suggestions based on the user's hobbies and schedule, as well as related reservations, weather forecasts, and menu suggestions, were made individually, making it difficult for users to obtain consistent information. In addition, suggestions did not take the user's emotions into consideration, making it impossible to make optimal suggestions based on the user's psychological state. This led to a problem of reduced user satisfaction.

[1931] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1932] In this invention, the server includes means for suggesting weekend activities taking into consideration the user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing a weather forecast related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for analyzing the user's emotions and making suggestions related to activities based thereon, means for providing a detailed weather forecast based on the user's emotions, means for booking activities for the purpose of relaxation based on the user's emotions, and means for suggesting comfort food based on the user's emotions. This allows the user to obtain consistent information and further allows the user to receive optimal suggestions according to their emotions.

[1933] "User" refers to any individual or entity that uses the System.

[1934] "Hobbies" refers to activities or areas of interest that a user engages in for personal enjoyment.

[1935] "To Do" refers to activities or events that a user plans to do in the future.

[1936] "Activity" refers to a specific action or event that a user takes.

[1937] "Suggestion" refers to recommendations or advice the system gives to the user.

[1938] "Reservation" refers to the process by which a User reserves in advance the use of a particular service or facility.

[1939] "Dandori" refers to the planning and preparations required to smoothly carry out an activity.

[1940] "Weather forecast" refers to information predicting weather conditions for a particular date, time and location.

[1941] A "menu" refers to a combination of dishes or meals suitable for a particular activity.

[1942] "SNS posting" refers to the transmission of information by users on social networking services.

[1943] "New connections" refers to relationships with other users that a user meets through the system.

[1944] "Emotion" refers to the user's psychological state or mood.

[1945] "Emotion engine" refers to the functionality within the system that analyzes user emotions and makes suggestions based on them.

[1946] "Comfort food" refers to food that is meant to comfort the user.

[1947] "Relaxation" refers to activities and methods that allow users to relax.

[1948] MODE FOR CARRYING OUT THE INVENTION

[1949] This invention is a system that suggests weekend activities based on the user's hobbies and schedule. Based on the user's input information, this system makes suggestions for activities, reservations, weather forecasts, meal suggestions, suggestions for new connections through social media posts, and suggestions based on the user's emotions.

[1950] Hardware and software used

[1951] This system operates among three parties: a server, a terminal, and a user. The server plays a central role in data processing and analysis, while the terminal receives input from the user and communicates with the server. The user accesses the system through the terminal and inputs the necessary information.

[1952] The specific software used is as follows:

[1953] OpenWeatherMap API: An API for getting weather forecasts.

[1954] Recipe database: A database for suggesting menus suitable for activities.

[1955] SNS API: An API for analyzing social media posts and suggesting new connections.

[1956] Sentiment engine: An engine for analyzing user emotions and making suggestions based on them.

[1957] Specific operation of the system

[1958] 1. Providing weather forecasts:

[1959] The user enters the date, time and location of the activity.

[1960] The terminal transmits the input information to the server.

[1961] The server retrieves the weather forecast using the OpenWeatherMap API.

[1962] The weather forecast obtained by the server is analyzed, and detailed information, particularly on wind, is extracted.

[1963] The server sends the analysis results to the device.

[1964] The device displays the weather forecast to the user.

[1965] Example: A user inputs "I'm planning to go camping next Saturday." The device sends this information to a server, which then makes a request to the OpenWeatherMap API to retrieve weather information for the specified date, time, and location. The server extracts detailed information such as wind speed and direction from the retrieved weather information, and the device displays to the user, "Next Saturday's weather will be sunny, with a wind speed of 10 km / h."

[1966] Example prompt: "We're planning a camping trip next Saturday. What's the weather forecast for that day?"

[1967] 2. Menu suggestions:

[1968] The user enters the type of activity.

[1969] The terminal transmits the input information to the server.

[1970] The server searches a recipe database and retrieves a menu suitable for the activity.

[1971] The server sends the acquired menu to the terminal.

[1972] The device displays the menu to the user.

[1973] Example: A user types, "Tell me some easy camping recipes." The device sends this information to a server, which searches a recipe database and retrieves recipes such as "Hamburg steak in foil" and "S'mores over a campfire." The server sends the retrieved recipes to the device, which then displays to the user, "Here's the recipe for Hamburg steak in foil."

[1974] Example prompt: "Can you give me some easy camping recipes?"

[1975] 3. Proposing new connections through social media posts:

[1976] Users post on social media related to the activity.

[1977] The device sends the post content to the server.

[1978] The server analyzes the relevant posts using the SNS API.

[1979] The server finds other users with similar interests.

[1980] The server sends recommended user information to the terminal.

[1981] The device will display recommended users to the user.

[1982] Example: A user types, "I posted a photo of camping." The device sends this information to a server, which uses a social media API to analyze posts with hashtags like "camping" or "outdoors." The server finds other users with the same hobby and sends that information to the device. The device then displays to the user, "Here are other users with the same hobby."

[1983] Example prompt: "I posted a photo of me camping. Can you tell me who shares the same hobby?"

[1984] 4. Menu suggestions using an emotional engine:

[1985] The user inputs their current emotion.

[1986] The terminal transmits the input information to the server.

[1987] The server uses an emotion engine to analyze the user's emotions.

[1988] The server will suggest a suitable menu based on your emotions.

[1989] The server sends the suggested menu to the terminal.

[1990] The device displays the menu to the user.

[1991] Example: A user types, "I'm feeling depressed today." The device sends this information to a server, which uses an emotion engine to analyze it as "depressed." The server then suggests comfort foods such as "chocolate cake" or "cream stew." The server then sends the suggested menu to the device, which then displays to the user, "Here's the chocolate cake recipe."

[1992] Example prompt: "I'm feeling down today. Can you recommend a comforting meal?"

[1993] 5. Booking and scheduling with emotion engine:

[1994] The user inputs their current emotion.

[1995] The terminal transmits the input information to the server.

[1996] The server uses an emotion engine to analyze the user's emotions.

[1997] The server schedules suitable activities based on the emotion.

[1998] The server transmits the reservation information to the terminal.

[1999] The terminal displays the reservation information to the user.

[2000] Example: A user types "I feel nervous." The device sends this information to a server, which uses an emotion engine to analyze it as "I feel nervous." The server then suggests booking a "massage" or "yoga class." The server then sends the booking information to the device, which then displays a message to the user saying "Your massage has been booked."

[2001] Example prompt: "I'm feeling nervous. Please schedule an activity that will help me relax."

[2002] 6. Emotion engine provides weather forecasts:

[2003] The user inputs their current emotion.

[2004] The terminal transmits the input information to the server.

[2005] The server uses an emotion engine to analyze the user's emotions.

[2006] The server retrieves detailed weather forecasts based on emotions.

[2007] The weather forecast obtained by the server is sent to the terminal.

[2008] The device displays the weather forecast to the user.

[2009] Example: A user inputs "I feel anxious." The device sends this information to a server, which uses its emotion engine to analyze it as "I feel anxious." The server retrieves a detailed weather forecast using the OpenWeatherMap API. The server sends the retrieved weather forecast to the device, which then displays to the user, "Tomorrow's weather will be sunny with a wind speed of 5 km / h."

[2010] An example of a prompt sentence is: "I'm feeling anxious. Please tell me in detail about the weather tomorrow." The flow of the specific processing in the third embodiment will be described with reference to FIG.

[2011] Providing weather forecasts

[2012] Step 1:

[2013] The user enters the date, time and location of the activity.

[2014] Input: Date, time and location of the activity

[2015] Output: Date, time and location information entered

[2016] What happens: A user types into their device, "I'm planning a camping trip next Saturday."

[2017] Step 2:

[2018] The terminal transmits the input information to the server.

[2019] Input: Date, time, and location information entered by the user

[2020] Output: Date, time and location information sent to the server

[2021] Specific operation: The device sends the user's input information to the server.

[2022] Step 3:

[2023] The server retrieves the weather forecast using the OpenWeatherMap API.

[2024] Input: Date, time and location information sent to the server

[2025] Output: Weather forecast data obtained from the OpenWeatherMap API

[2026] What happens: The server sends a request to the OpenWeatherMap API to retrieve weather information for the specified date, time, and location.

[2027] Step 4:

[2028] The weather forecast obtained by the server is analyzed, and detailed information, particularly on wind, is extracted.

[2029] Input: Weather forecast data obtained from the OpenWeatherMap API

[2030] Output: Analyzed weather forecast data (especially wind information)

[2031] Specific operation: Extract detailed information such as wind speed and direction from the weather information obtained by the server.

[2032] Step 5:

[2033] The server sends the analysis results to the device.

[2034] Input: Parsed weather forecast data

[2035] Output: Analysis results sent to the device

[2036] Specific operation: The server sends the analysis results to the device.

[2037] Step 6:

[2038] The device displays the weather forecast to the user.

[2039] Input: Analysis results sent to the device

[2040] Output: The weather forecast displayed to the user

[2041] Specific behavior: The device displays to the user, "Next Saturday's weather will be sunny with a wind speed of 10 km / h."

[2042] Menu suggestions

[2043] Step 1:

[2044] The user inputs the type of activity.

[2045] Input: Activity Type

[2046] Output: Information about the type of activity entered

[2047] What happens: A user types into their device, "What are some easy camping recipes?"

[2048] Step 2:

[2049] The terminal transmits the input information to the server.

[2050] Input: Activity type information entered by the user

[2051] Output: Information about the type of activity sent to the server

[2052] Specific operation: The device sends the user's input information to the server.

[2053] Step 3:

[2054] The server searches a recipe database and retrieves a menu suitable for the activity.

[2055] Input: Information about the type of activity sent to the server

[2056] Output: Menu information retrieved from the recipe database

[2057] What happens: The server searches a recipe database and retrieves recipes such as "Hamburg steaks in foil" and "S'mores over a campfire."

[2058] Step 4:

[2059] The server sends the acquired menu to the terminal.

[2060] Input: Menu information retrieved from the recipe database

[2061] Output: Menu information sent to the device

[2062] Specific operation: The server sends the obtained recipe to the device.

[2063] Step 5:

[2064] The terminal displays the menu to the user.

[2065] Input: Menu information sent to the device

[2066] Output: Menu information displayed to the user

[2067] What happens: The device displays to the user, "Here's the recipe for foil-baked hamburger steak."

[2068] Proposing new connections through social media posts

[2069] Step 1:

[2070] A user posts an activity on social media.

[2071] Input: Social media posts related to the activity

[2072] Output: Input social media post content

[2073] What happens: A user types "I posted a camping photo" into their device.

[2074] Step 2:

[2075] The device sends the post content to the server.

[2076] Input: Social media post content entered by the user

[2077] Output: Social media post content sent to the server

[2078] Specific operation: The device sends the user's input information to the server.

[2079] Step 3:

[2080] The server analyzes the relevant posts using the SNS API.

[2081] Input: Social media post content sent to the server

[2082] Output: Analysis of related posts obtained from the SNS API

[2083] What it does: The server uses social media APIs to analyze posts with hashtags such as "camping" and "outdoors."

[2084] Step 4:

[2085] The server finds other users with the same interests.

[2086] Input: Analysis results of related posts obtained from the SNS API

[2087] Output: Information about other users with the same interests

[2088] Specific behavior: The server finds other users with the same interests and retrieves their information.

[2089] Step 5:

[2090] The server transmits recommended user information to the terminal.

[2091] Input: Information about other users with the same interests

[2092] Output: Recommended user information sent to the device

[2093] Specific operation: The server sends recommended user information to the terminal.

[2094] Step 6:

[2095] The terminal displays recommended users to the user.

[2096] Input: Recommended user information sent to the device

[2097] Output: Recommendation information displayed to the user

[2098] Specific behavior: The device displays to the user, "Here are users with the same interests."

[2099] Menu suggestions using an emotion engine

[2100] Step 1:

[2101] The user inputs their current emotion.

[2102] Input: Current Emotion

[2103] Output: Input emotion information

[2104] What happens: A user types "I'm feeling down today" into their device.

[2105] Step 2:

[2106] The terminal transmits the input information to the server.

[2107] Input: Emotion information entered by the user

[2108] Output: Emotion information sent to the server

[2109] Specific operation: The device sends the user's input information to the server.

[2110] Step 3:

[2111] The server uses an emotion engine to analyze the user's emotions.

[2112] Input: Emotion information sent to the server

[2113] Output: Sentiment analysis results by the emotion engine

[2114] Specific behavior: The server uses the emotion engine to analyze that the person is "depressed."

[2115] Step 4:

[2116] The server will suggest a suitable menu based on your emotions.

[2117] Input: Sentiment analysis results from the emotion engine

[2118] Output: Suggested menu information

[2119] What it does: The server suggests comfort foods like "chocolate cake" or "cream stew."

[2120] Step 5:

[2121] The server sends the suggested menu to the terminal.

[2122] Input: Suggested menu information

[2123] Output: Menu information sent to the device

[2124] Specific operation: The server sends the suggested menu to the device.

[2125] Step 6:

[2126] The terminal displays the menu to the user.

[2127] Input: Menu information sent to the device

[2128] Output: Menu information displayed to the user

[2129] What happens: The device displays to the user, "Here's the chocolate cake recipe."

[2130] Emotional engine for booking and scheduling

[2131] Step 1:

[2132] The user inputs their current emotion.

[2133] Input: Current Emotion

[2134] Output: Input emotion information

[2135] Specific action: The user types "I'm nervous" into the terminal.

[2136] Step 2:

[2137] The terminal transmits the input information to the server.

[2138] Input: Emotion information entered by the user

[2139] Output: Emotion information sent to the server

[2140] Specific operation: The device sends the user's input information to the server.

[2141] Step 3:

[2142] The server uses an emotion engine to analyze the user's emotions.

[2143] Input: Emotion information sent to the server

[2144] Output: Sentiment analysis results by the emotion engine

[2145] Specific behavior: The server uses the emotion engine to analyze that the person is "nervous."

[2146] Step 4:

[2147] The server schedules suitable activities based on the emotion.

[2148] Input: Sentiment analysis results from the emotion engine

[2149] Output: Booked activity information

[2150] What happens: The server suggests booking a "massage" or "yoga class."

[2151] Step 5:

[2152] The server transmits the reservation information to the terminal.

[2153] Input: Scheduled activity information

[2154] Output: Reservation information sent to the terminal

[2155] Specific operation: The server sends reservation information to the terminal.

[2156] Step 6:

[2157] The terminal displays the reservation information to the user.

[2158] Input: Reservation information sent to the terminal

[2159] Output: Reservation information displayed to the user

[2160] What happens: The device displays to the user, "Your massage reservation has been completed."

[2161] Providing weather forecasts with an emotion engine

[2162] Step 1:

[2163] The user inputs their current emotion.

[2164] Input: Current Emotion

[2165] Output: Input emotion information

[2166] Specific action: The user types "I feel anxious" into the device.

[2167] Step 2:

[2168] The terminal transmits the input information to the server.

[2169] Input: Emotion information entered by the user

[2170] Output: Emotion information sent to the server

[2171] Specific operation: The device sends the user's input information to the server.

[2172] Step 3:

[2173] The server uses an emotion engine to analyze the user's emotions.

[2174] Input: Emotion information sent to the server

[2175] Output: Sentiment analysis results by the emotion engine

[2176] Specific behavior: The server uses the emotion engine to analyze that the person is "feeling anxious."

[2177] Step 4:

[2178] The server retrieves detailed weather forecasts based on emotions.

[2179] Input: Sentiment analysis results from the emotion engine

[2180] Output: Detailed weather forecast data

[2181] What happens: The server uses the OpenWeatherMap API to get a detailed weather forecast.

[2182] Step 5:

[2183] The weather forecast obtained by the server is sent to the terminal.

[2184] Input: Detailed weather forecast data

[2185] Output: Weather forecast data sent to the device

[2186] Specific operation: The weather forecast obtained by the server is sent to the device.

[2187] Step 6:

[2188] The device displays the weather forecast to the user.

[2189] Input: Weather forecast data sent to the device

[2190] Output: The weather forecast displayed to the user

[2191] Specific behavior: The device displays to the user, "Tomorrow's weather will be sunny with a wind speed of 5 km / h."

[2192] (Application example 3)

[2193] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[2194] While conventional activity suggestion systems make suggestions based on a user's hobbies and schedules, they lack comprehensive suggestions that take into account the user's emotions, weather forecasts, and social media integration. Furthermore, because menu and reservation suggestions are not based on the user's emotions, the user experience is not fully improved. Furthermore, the quality of suggestions is limited because they do not use generative AI models to suggest menus or prompts. To solve these issues, comprehensive suggestions that take into account the user's emotions, weather forecasts, and social media integration are needed.

[2195] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[2196] In this invention, the server includes: means for suggesting weekend activities taking into account the user's hobbies and schedules; means for making reservations and arrangements related to the suggested activities; means for providing a weather forecast related to the activities; means for considering menus related to the activities; means for suggesting new connections through social media posts; means for suggesting menus based on the user's emotions; means for making reservations and arrangements based on the user's emotions; means for providing a weather forecast based on the user's emotions; means for suggesting optimal meals based on the user's activities and emotions; means for improving the user experience by utilizing the weather forecast and social media; means for generating menus using a generative AI model; and means for inputting prompt sentences into the generative AI model. This enables comprehensive suggestions that take into account the user's emotions, weather forecast, and social media integration, thereby improving the user experience.

[2197] "User's hobbies and plans" refers to activities that the user is interested in, as well as events and schedules that the user has planned in advance.

[2198] "Weekend activities" refers to leisure activities, events, hobbies, etc. that a user plans to do over the weekend.

[2199] "Booking and Arranging" means reserving locations and services, and making any necessary preparations or arrangements related to the proposed activity.

[2200] "Weather forecast" refers to information predicting weather conditions for a particular date, time and location.

[2201] A "menu" refers to a menu or recipe of a meal appropriate for a particular activity or situation.

[2202] "SNS posts" refer to content such as text, images, and videos that users share on social networking services.

[2203] "New connections" refers to new interactions and relationships with other users who share the same hobbies and interests.

[2204] "Means for suggesting menus based on emotions" refers to a method of analyzing the user's emotional state and suggesting meal menus accordingly.

[2205] "Emotion-based booking and scheduling" refers to a method that analyzes a user's emotional state and automatically books or prepares activities accordingly.

[2206] "Means for providing weather forecasts based on emotions" refers to a method for analyzing a user's emotional state and providing a detailed weather forecast accordingly.

[2207] "Method for suggesting optimal meals" refers to a method for suggesting the most suitable meal menu based on the user's activities and emotions.

[2208] "Methods of utilizing weather forecasts and social media to improve user experience" refers to methods of utilizing weather forecast information and social media data to improve the user experience.

[2209] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to generate new information or suggestions from data.

[2210] A "prompt" refers to an instruction or question input to a generative AI model.

[2211] A system for implementing this invention includes means for suggesting weekend activities taking into consideration a user's hobbies and schedule, means for making reservations and arrangements related to the suggested activities, means for providing a weather forecast related to the activities, means for considering menus related to the activities, means for suggesting new connections through social media posts, means for suggesting menus based on a user's emotions, means for making reservations and arrangements based on a user's emotions, means for providing a weather forecast based on a user's emotions, means for suggesting optimal meals based on a user's activities and emotions, means for improving user experience by utilizing weather forecasts and social media, means for generating menus using a generative AI model, and means for inputting prompt sentences into the generative AI model.

[2212] Hardware and software used

[2213] Hardware: Smartphones, smart glasses, head-mounted displays

[2214] Software: Weather forecast APIs (e.g., OpenWeatherMap), social media APIs (e.g., Twitter API), sentiment analysis APIs (e.g., IBM Watson), food delivery APIs (e.g., Uber Eats API)

[2215] Data processing and calculation

[2216] The server receives the user's hobbies and schedule as input and suggests weekend activities. It coordinates with the reservation system to make the necessary arrangements to make reservations and schedules related to the suggested activities. It uses a weather forecast API to retrieve and analyze weather information for the specified date, time, and location to provide a weather forecast related to the activities. It takes wind information into particular consideration and provides it to the user.

[2217] To suggest a menu based on the user's emotions, a sentiment analysis API is used to analyze the user's emotional state, and the corresponding meal menu is input as a prompt to the generative AI model. The generated menu is then provided to the user. For example, a prompt such as "Please tell me some easy recipes for camping" is input to the generative AI model, and the generated recipe is provided.

[2218] To suggest new connections through social media posts, we use social media APIs to retrieve users' posts and recommend other users with the same hobbies. For example, we can recommend other users who post camping photos and suggest new connections.

[2219] To make reservations and arrangements based on user emotions, the app uses a sentiment analysis API to analyze the user's emotional state and automatically book and prepare activities accordingly. For example, if the user is nervous, it will automatically book activities aimed at relaxation.

[2220] To provide weather forecasts based on user emotions, we use sentiment analysis APIs to analyze the user's emotional state and provide detailed weather forecasts accordingly. For example, if the user is feeling anxious, we provide detailed weather forecasts to alleviate that anxiety.

[2221] Examples of concrete examples and prompts

[2222] Specific examples

[2223] Weather forecast linkage function:

[2224] If a user asks, "What's the weather like for camping tomorrow?", the system retrieves data from the weather forecast API and answers, "It will be sunny tomorrow with a wind speed of 5 m / s."

[2225] Menu suggestion feature:

[2226] If a user asks, "Please tell me some easy meals to make while camping," the generative AI model will input the prompt, "Please tell me some easy meals to make while camping," and provide the generated recipe.

[2227] Prompt Sentence Examples

[2228] "Get the weather forecast for a specified date, time and location, detailing wind speed and chance of precipitation."

[2229] Please tell me some easy camping recipes.

[2230] This will enable comprehensive suggestions that take into account user emotions, weather forecasts, and social media integration, improving the user experience.

[2231] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[2232] Step 1:

[2233] The user uses the terminal to input his / her hobbies and plans.

[2234] Input: User's hobbies and schedule

[2235] Output: Entered hobby and schedule data

[2236] Specific operation: A user uses a smartphone or smart glasses to input hobbies or plans. For example, they input "I plan to go camping this weekend."

[2237] Step 2:

[2238] The server suggests weekend activities based on the entered hobbies and schedule.

[2239] Input: Hobbies and schedule data

[2240] Output: Proposed activities

[2241] Specific operation: The server refers to the database and suggests suitable activities based on the enter...

Claims

1. A means of obtaining information about the user's hobbies and weekend plans; A means for generating a prompt sentence for instructing the user to generate activities to be suggested to the user based on the acquired hobbies and weekend plans of the user; A means for generating an activity content to be suggested to a user using the generated prompt sentence and the generation AI model; A suggestion means for suggesting the generated activity content to a user; a reservation means for making reservations related to the proposed activities; a means for providing a weather forecast relevant to the proposed activity; A means for providing menu information related to the proposed activity; A system including:

2. the reservation means searches for and reserves an available campsite when the proposed activity is camping; The system of claim 1 .

3. means for recognizing an emotional state of the user using an emotion engine; The suggestion means adjusts the activity content suggested to the user based on the recognized emotional state of the user. The system of claim 1 .

Images