System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving user input information and generating a trip plan based on the input information; means for collecting weather information, seasonal information, local event information, crowdedness information, and user review information; means for generating a plurality of candidate plans based on the collected information and evaluating the candidate plans to select an optimal plan; and means for presenting the optimal plan to the user.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] Many people struggle with how to make the most of unexpected free time, such as waiting to meet up with a friend or having no plans for a holiday. Conventional outing planning tools require users to manually collect, compare, and combine a large amount of information, which is time-consuming and labor-intensive. Furthermore, there are no tools available that automatically generate plans that take into account real-time weather information, seasonal event information, crowd levels, and user reviews. Given this background, there is a need for a system that provides optimal outing plans based on users' preferences, budget, and available time. [Means for solving the problem]

[0005] The present invention provides a system including: means for receiving user input information and generating an outing plan based on the input information; means for collecting weather information, seasonal information, local event information, congestion information, and user review information; means for generating multiple candidate plans based on the collected information and evaluating the candidate plans to select an optimal plan; and means for presenting the optimal plan to the user. This allows users to centrally manage scattered information and spend their free time in an efficient and enjoyable manner. The system also includes means for analyzing the user's input information and identifying preferred activities, available time, and budget; and means for comprehensively considering weather information, seasonal information, local event information, congestion information, and user review information when evaluating multiple candidate plans. This makes it possible to provide a plan that best suits the user's needs.

[0006] A "User" is an individual who enters information into the system through the user interface and receives a generated plan from the system.

[0007] "Input Information" is data such as preferences, budget, and available time that a user provides to the system.

[0008] An "outing plan" is a suggestion of activities and places to visit for a specific time period, generated by the system based on user input.

[0009] "Climate information" is data about weather conditions on a particular day or period.

[0010] "Seasonal information" is data about features and events associated with the seasons or specific times of the year.

[0011] "Local event information" is data about public events such as festivals, exhibitions, and concerts held in a specific local area.

[0012] "Crowding information" is data that indicates the degree of crowding in a particular place or time period.

[0013] "User review information" is data in which past users have left ratings and comments about specific places or activities.

[0014] "Collection means" refers to a series of processes and systems for obtaining weather information, seasonal information, local event information, congestion information, and user review information.

[0015] "Means for generating multiple candidate plans" refers to a process and system that uses collected information to create multiple outing plans that match the user's input information.

[0016] "Evaluation means" refers to the process and system for evaluating multiple candidate plans and identifying the optimal plan.

[0017] "Presentation method" refers to the process and system that displays the optimal plan to the user.

[0018] "Analysis Tools" refers to the processes and systems that perform detailed analysis of the input information provided by the User to identify the User's preferred activities, available time, and budget. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6]FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] The present invention is a system that proposes optimal outing plans based on a user's input of their preferences, budget, and available time. Hereinafter, an embodiment of the present invention will be described in detail.

[0041] System configuration

[0042] The system mainly consists of the following components:

[0043] 1. User device: The device (smartphone, tablet, PC, etc.) through which the user enters information and receives the plan.

[0044] 2. Server: The main processing unit that analyzes the input information from the user and generates and evaluates the trip plan.

[0045] 3. Database: Stores weather information, seasonal information, local event information, congestion information, and user review information and makes it accessible from the server.

[0046] Program processing

[0047] 1. Receiving user input

[0048] User

[0049] The user accesses a dedicated app or web platform and enters information such as preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), etc. This information is sent to the server by the device.

[0050] 2. Analysis of input information

[0051] server

[0052] The server analyzes the input information received from the user, which determines the user's preferences, available time, and budget.

[0053] 3. Data collection

[0054] server

[0055] The server collects the following information from the database:

[0056] Weather information: Weather on the specified date.

[0057] Seasonal information: Characteristic events at specific times.

[0058] Local Event Information: Public events in designated areas.

[0059] Congestion information: Congestion levels in various locations.

[0060] User review information: Past user reviews.

[0061] 4. Generating multiple candidate plans

[0062] server

[0063] The server generates multiple itineraries based on the collected information, matching the user's input information. For example, the following itineraries may be generated:

[0064] Option 1: Relax for an hour at a cafe in front of the station, then spend two hours visiting a special exhibition at the art museum.

[0065] Option 2: Spend 1.5 hours at a cafe downtown, then spend 1.5 hours touring the art museum.

[0066] 5. Plan Evaluation and Selection

[0067] server

[0068] The generated candidate plans are evaluated. The evaluation includes comprehensive information on weather, season, local events, congestion, and user reviews. The most suitable plan is selected from the evaluation results.

[0069] 6. Presenting the plan

[0070] server

[0071] The best plan is then formatted and sent to the user, including a specific schedule and details of the destinations (names, addresses, reviews, and estimated wait times).

[0072] Terminal

[0073] The user's terminal displays the plan details received from the server, and the user can plan their outing according to this plan.

[0074] Specific examples

[0075] Consider the following real-world scenario:

[0076] example

[0077] On a Saturday afternoon, a user opens the app and enters the following information:

[0078] Likes: Cafes, art museums

[0079] Budget: 5,000 yen

[0080] Available time: 3 hours

[0081] Receiving user input

[0082] The user enters the above information and presses the send button. The device sends the information to the server.

[0083] Analysis of input information

[0084] The server analyzes your preferences, availability, and budget and begins to collect data based on this information.

[0085] Data collection

[0086] The server gathers from a database information about Saturday's weather (clear), the museum's fall special exhibitions, the area's crowd level (relatively low), and relevant user reviews.

[0087] Generate multiple candidate plans

[0088] Based on the data collected, the server generates a plan like this:

[0089] Option 1: Relax for an hour at Cafe A in front of the station, then spend two hours visiting a special exhibition at Museum B.

[0090] Option 2: Spend 1.5 hours at Cafe C in the downtown area, then visit Museum D for 1.5 hours.

[0091] Plan evaluation and selection

[0092] The server evaluates the candidate plans and selects the best one. For example, candidate 1 is determined to be the best.

[0093] Presenting the plan

[0094] The server sends details of the optimal plan to the user's device, which displays it.

[0095] In this way, users can plan their outings efficiently and enjoyably. The system automatically provides the best plan, taking into account weather, season, events, crowd levels, and reviews.

[0096] The processing flow will be explained below.

[0097] Step 1:

[0098] Terminal

[0099] The user accesses a dedicated app or web platform and enters information such as preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), etc. Once the information is complete, the user presses the submit button.

[0100] Step 2:

[0101] Terminal

[0102] The information entered by the user is sent to the server, including preferred activities, available time, and budget.

[0103] Step 3:

[0104] server

[0105] The server analyzes the input information received from the user to determine the user's preferences, available time, and budget.

[0106] Step 4:

[0107] server

[0108] The server collects weather information, seasonal information, local event information, crowding information, and user reviews from a database.

[0109] Step 5:

[0110] Obtaining weather information: The server collects weather information for the specified date.

[0111] Acquisition of seasonal information: The server collects events at specific times and characteristics specific to the season.

[0112] Acquisition of local event information: The server collects information about events held in a specified area.

[0113] Obtaining congestion information: The server collects congestion information for each location.

[0114] Obtaining user review information: The server collects relevant past user reviews.

[0115] Step 6:

[0116] server

[0117] Based on the collected information, the server generates multiple candidate plans that match the user's input information. The generated plans reflect the user's preferred activities and time allocation within the user's budget.

[0118] Step 7:

[0119] server

[0120] Each candidate plan will be evaluated, taking into consideration the following factors:

[0121] Local Weather

[0122] Seasonal Events

[0123] Local Events

[0124] Congestion level

[0125] User reviews

[0126] Step 8:

[0127] server

[0128] Based on the evaluation results, the most appropriate plan is selected. For example, the following plan may be determined to be optimal:

[0129] Relax for an hour at a cafe in front of the station, then spend two hours visiting the museum's special exhibition.

[0130] Step 9:

[0131] server

[0132] Format details of the selected best plan, including the name of the destination, its location, reviews, and estimated wait time.

[0133] Step 10:

[0134] server

[0135] The server sends details of the best plan to the user's device.

[0136] Step 11:

[0137] Terminal

[0138] The user device receives the plan details sent from the server and displays them in a user-friendly format.

[0139] Step 12:

[0140] User

[0141] The user reviews the proposed plan, and if they are satisfied with it, they accept it and register it as a schedule. If they are not satisfied, they press the regenerate button to request a new plan.

[0142] Step 13:

[0143] server

[0144] If regeneration is requested, the same process is performed again to generate and provide a new plan.

[0145] Example 1

[0146] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0147] Conventional outing planning systems have difficulty providing optimal plans that fully consider individual requirements such as user preferences, budget, and available time. Furthermore, they are unable to generate outing plans by comprehensively evaluating environmental information such as weather and event crowding, which prevents them from increasing user satisfaction. To solve these problems, a system capable of more advanced information analysis and appropriate plan generation is needed.

[0148] 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.

[0149] In this invention, the server includes means for receiving user input information and generating an outing plan based on the input information, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, means for generating multiple candidate plans based on the collected information and evaluating the candidate plans to select an optimal plan, means for presenting the optimal plan to the user, means for analyzing the user input information and identifying preferences, budget, and available time, means for collecting related information from a database based on the identified information, means for evaluating the multiple generated candidate plans and selecting an optimal plan based on an overall evaluation score, means for sending details of the selected plan to the user terminal and displaying the details to the user, means for evaluating and optimizing the outing plan using a generative AI model, and means for inputting prompt sentences into the generative AI model to generate an outing plan. This makes it possible to provide an optimal outing plan by comprehensively evaluating individual requirements based on the user input information and environmental information.

[0150] "User-entered information" is data such as preferences, budget, and available time that a user inputs into the system.

[0151] An "outing plan" is a proposal that includes the user's outing schedule and details of places to visit, generated based on the user's input information and collected environmental information.

[0152] "Weather information" is weather forecast data for a specified date.

[0153] "Seasonal information" is information about events and unique activities related to a particular time of year.

[0154] "Local event information" is information about public events held in a specific local area.

[0155] "Crowding level information" is information about the congestion status of a specific area or facility.

[0156] "User review information" refers to reviews and ratings provided by other users in the past.

[0157] The "multiple candidate plans" are multiple outing suggestions generated based on the user's input information and the collected environmental information.

[0158] The "optimal plan" is the most suitable outing plan selected from multiple candidate plans by comprehensively evaluating the user's requirements and environmental information.

[0159] A "generative AI model" is an artificial intelligence model that generates and optimizes outing plans based on user input information and collected environmental information.

[0160] A "prompt sentence" is an instruction sentence that is input to the generative AI model to generate an outing plan.

[0161] MODE FOR CARRYING OUT THE INVENTION

[0162] The present invention relates to a system that proposes optimal outing plans by allowing a user to input their preferences, budget, and available time. Hereinafter, an embodiment of the present invention will be described in detail.

[0163] System configuration

[0164] The system mainly consists of the following components:

[0165] 1. User device: The device (smartphone, tablet, PC, etc.) through which the user enters information and receives travel plans.

[0166] 2. Server: The main processing unit that analyzes input information from users and generates and evaluates outing plans.

[0167] 3. Database: Stores weather information, seasonal information, local event information, congestion information, and user review information and makes it accessible from the server.

[0168] Program processing

[0169] 1. Receiving user input

[0170] A user accesses a dedicated app or web platform and enters information such as their preferences (e.g., cafes, museums), budget (e.g., 5,000 yen), available time (e.g., 3 hours), etc. This information is sent to the server using a reactive form or HTTP request.

[0171] 2. Analysis of input information

[0172] The server parses the input information it receives using a script written in Python or JavaScript that parses the JSON data to identify the user's preferences, budget, and available time.

[0173] 3. Data collection

[0174] The server connects to a database or external API to gather the necessary information, for example using SQL queries to get the following information:

[0175] Climate information: Weather forecast for a specific date

[0176] Seasonal information: Events related to the current season

[0177] Local Event Information: Public events in designated areas

[0178] Congestion information: Congestion status of designated areas

[0179] User review information: reviews and ratings from other users

[0180] 4. Generating candidate plans

[0181] The server generates multiple itineraries based on the collected information, using an algorithm to generate the following itineraries:

[0182] Option 1: Relax for an hour at Cafe A in front of the station, then spend two hours visiting a special exhibition at Museum B.

[0183] Option 2: Spend 1.5 hours at Cafe C in the downtown area and then visit Museum D for 1.5 hours.

[0184] 5. Evaluation and selection of plans

[0185] The server evaluates the generated candidate plans, using a comprehensive set of information including weather, season, local events, congestion, and user reviews.

[0186] The server selects the optimal plan based on the overall evaluation points.

[0187] 6. Presenting the plan

[0188] The server sends the details of the optimal plan to the user's device, which then displays the information, allowing the user to plan their outing according to the plan provided.

[0189] Specific examples

[0190] For example, on a Saturday afternoon, a user opens the app and enters the following information:

[0191] Likes: Cafes, art museums

[0192] Budget: 5,000 yen

[0193] Available time: 3 hours

[0194] Once the user submits their input, the device sends the information to a server, which analyzes the user's preferences, budget, and available time, and then gathers relevant data from a database or external API, such as sunny weather information, special museum exhibitions, local congestion levels, and past user reviews.

[0195] The server then generates multiple candidate plans based on this data, evaluates the plans, selects the plan with the highest evaluation points, formats the specific schedule and details of the places to visit, and sends it to the user's device.

[0196] Prompt Sentence Examples

[0197] Examples of prompts for generative AI models include:

[0198] "The user is looking for a 3-hour outing plan with a budget of 5000 yen, where the user prefers cafes and museums on a Saturday afternoon. Generate multiple possible outing plans, and then rate and present the best plan. Information to consider includes weather forecasts, seasonal events, local public events, crowd data, and user reviews."

[0199] This makes it possible to provide users with optimal outing plans.

[0200] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0201] Step 1:

[0202] Receiving user input

[0203] Users access a dedicated app or web platform and enter their preferences, budget, and available time.

[0204] Specific operation: The user enters their preferences (e.g., "cafe, museum"), their budget (5,000 yen), and the duration (3 hours) into the form, then presses the submit button.

[0205] The terminal receives this input information and sends it to the server.

[0206] Specific operation: Sends input data to the server as an HTTP POST request.

[0207] Input (device): User preferences, budget, and available time.

[0208] Output (Terminal → Server): HTTP request containing input information.

[0209] Step 2:

[0210] Analysis of input information

[0211] The server analyzes the received input information.

[0212] What it does: The server runs a parsing script written in Python or JavaScript that parses the JSON data and stores preferences, budget, and available time in separate variables.

[0213] Input (server): JSON data containing user input information.

[0214] Output (server): Parsed individual variables (preferences, budget, available time).

[0215] Step 3:

[0216] Data collection

[0217] The server connects to a database or external API to collect the necessary information.

[0218] What it does: It uses SQL queries and API requests to retrieve the following information:

[0219] Weather information: Get the weather forecast for the specified date from the API.

[0220] Seasonal information: Retrieves events related to the current season from the database.

[0221] Local Event Information: Retrieve public events in a specified area from a database or API.

[0222] Congestion information: Obtain the congestion status of the specified area from the API.

[0223] User review information: Retrieve other users' reviews and ratings from our database.

[0224] Input (server): Parsed user input information.

[0225] Output (server): Collected data (weather information, seasonal information, local event information, congestion information, user review information).

[0226] Step 4:

[0227] Generate candidate plans

[0228] The server generates multiple outing plans based on the collected information.

[0229] What it does: It uses an algorithm to generate a list of plans based on your preferences, budget, and availability. For example, it might generate plans like this:

[0230] Option 1: Relax for an hour at a cafe in front of the station, then spend two hours visiting a special exhibition at the museum.

[0231] Option 2: Spend 1.5 hours at a cafe downtown and 1.5 hours visiting the art museum.

[0232] Input (Server): Collected data and analyzed user input information.

[0233] Output (server): Multiple candidate plans generated.

[0234] Step 5:

[0235] Plan evaluation and selection

[0236] The server evaluates the generated candidate plans.

[0237] Specific operation: Calculates rating points for each plan. These rating points are calculated taking into account weather information, seasonal information, local event information, crowding information, and user reviews. For example, visiting an art museum on a sunny day will earn you a high rating point.

[0238] The server selects the optimal plan from the evaluation results.

[0239] Specific operation: Select the plan with the highest overall evaluation points.

[0240] Input (server): Multiple generated candidate plans.

[0241] Output (server): Optimal plan.

[0242] Step 6:

[0243] Presenting the plan

[0244] The server sends the details of the selected optimal plan to the user terminal,

[0245] Specific operation: The details of the selected plan (schedule, details of destinations) are formatted in HTML or JSON format and sent as an HTTP response.

[0246] The terminal displays the plan details received from the server.

[0247] Specific behavior: Provides the user with visual details of the plan according to a display format.

[0248] Input (server → terminal): Details of the optimal plan.

[0249] Output (terminal): Displayed outing plan.

[0250] By following these steps, users can plan their outings efficiently and enjoyably.

[0251] (Application example 1)

[0252] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0253] In today's world, users often find it difficult to efficiently find personalized content that meets their preferences. Furthermore, there are no systems that suggest optimal content based on available viewing time or device type, so users must search for the appropriate content themselves, which is time-consuming. To solve this problem, a system is needed that can automatically generate and suggest personalized content plans based on user input.

[0254] 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.

[0255] In this invention, the server includes means for receiving user input information and generating a personalized content plan based on the input information, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, and means for generating multiple candidate plans based on the collected information and evaluating these candidate plans to select an optimal content plan. This makes it possible to efficiently propose an optimal content plan based on the user's preferences, available viewing time, and device used.

[0256] "User input information" refers to information entered by the user, such as preferences, available viewing times, and device type.

[0257] A "personalized content plan" is a customized recommendation of content such as movies, music, articles, etc. based on user input information.

[0258] "Climate information" is data about weather collected from outside.

[0259] "Seasonal information" is information about events and general activities associated with a particular time of year.

[0260] "Local event information" is information about events and occasions held in a specific local area.

[0261] "Crowding level information" is information about the congestion level of a specific location or event.

[0262] "User review information" refers to ratings and opinions from other users regarding services and content provided in the past.

[0263] "Server" is the primary processing unit that analyzes user input, generates personalized content plans, and collects and evaluates information.

[0264] "Device" refers to the terminal used by the user, such as a smartphone, smart glasses, or head-mounted display.

[0265] "Analysis" means deciphering the information entered by the user and performing appropriate processing based on that content.

[0266] The "optimal plan" is the plan that best meets the user's requirements from among multiple candidate plans.

[0267] "Evaluation" is the process of comparing the generated candidate plans and selecting the plan that best suits the user's requirements.

[0268] This invention is a system that proposes personalized content plans based on user preferences, available viewing times, and devices. This system is composed of a user terminal, a server, and a database.

[0269] System configuration

[0270] 1. User Device:

[0271] To input information, users use devices such as smartphones, smart glasses, and head-mounted displays, which then send the input information, such as user preferences, available viewing time, and the type of device used, to a server.

[0272] 2. Server:

[0273] The server receives user input information, analyzes it, and generates the optimal content plan. It uses a Python server program, an SQL database, and the Flask framework that provides a REST API. The server performs the following processes:

[0274] Analyzes user input to determine preferred content, viewing times, and devices.

[0275] Relevant information (weather information, seasonal information, local event information, congestion information, user review information) is collected from the database.

[0276] Based on the collected information, multiple candidate plans are generated and the optimal plan is selected after evaluation.

[0277] The selected optimal content plan is sent to the user's device.

[0278] 3. Database:

[0279] The database stores weather information, seasonal information, local event information, congestion information, and user review information and makes them accessible from the server.

[0280] Program processing explanation

[0281] Hardware and Software Used

[0282] Hardware: Smartphones, smart glasses, head-mounted displays

[0283] Software: Python, SQL database, Flask framework

[0284] Data processing and calculation

[0285] 1. Analysis of input information:

[0286] The server analyzes data entered by the user, such as preferred content, available viewing time, and device type, thereby identifying the user's preferences, available viewing time, and device type.

[0287] 2. Data Collection:

[0288] The server collects information from the database about the weather, seasons, local events, crowding levels, and user reviews, providing users with the latest information that meets their requirements in real time.

[0289] 3. Generate and evaluate candidate plans:

[0290] The server generates multiple candidate content plans based on the collected information, evaluates each plan to best match the user's preferences, available viewing time, and other conditions, and selects the optimal plan.

[0291] 4. Present the plan:

[0292] The server sends the details of the selected optimal plan (e.g., movie title, album name, viewing time, rating, etc.) to the user's device, which displays it on the screen and allows the user to watch the suggested content.

[0293] Specific examples

[0294] As an example, consider the following scenario:

[0295] User Input:

[0296] Favorites: Action movies, rock music

[0297] Viewing time: 2 hours

[0298] Device: Smartphone

[0299] The user opens the app and enters the above information. The device sends the information to the server, which then uses it to gather relevant data from its database. The server then generates a content plan that looks like this:

[0300] Option 1: Watch a 1.5 hour action movie, a 30 minute rock album

[0301] Nominations: 2.50 minute action short films, 1.5 hour documentaries

[0302] The server evaluates these candidate plans and selects the best plan (e.g., candidate 1 is determined to be the best), then sends details of the best plan to the user's device, which displays it.

[0303] Examples of prompts for generative AI models

[0304] "Generate the optimal content plan based on the user's preferences, available viewing time, and device they are using. The user's preferences are 'action movies' and 'rock music'. The available viewing time is 2 hours. The device is a smartphone."

[0305] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0306] Step 1:

[0307] The device accepts user input of preferences, available viewing time, and device type. The device receives the user input and sends it to the server. The input includes preferences (e.g., action movies, rock music), available viewing time (e.g., 2 hours), and device (e.g., smartphone). The output is the user input sent to the server.

[0308] Step 2:

[0309] The server receives user input information sent from the device. The received data includes user preferences, available viewing time, and device type. This data is analyzed to identify user preferences and conditions. The input is the user input information, and the output is the analyzed user preferences, available viewing time, and device type.

[0310] Step 3:

[0311] The server collects relevant information (weather information, seasonal information, local event information, congestion information, and user review information) from the database. The input is the analyzed user conditions, and an SQL query is executed to retrieve the required data based on those conditions. The output is the collected weather information, seasonal information, local event information, congestion information, and user review information.

[0312] Step 4:

[0313] The server generates multiple candidate content plans based on the collected information. Specifically, it creates plans by combining appropriate movies, music, articles, etc. based on the user's preferences and available viewing time. The input includes the collected information and the user's conditions, and the output is the generated multiple candidate plans.

[0314] Step 5:

[0315] The server evaluates the generated multiple candidate plans and selects the optimal content plan. The evaluation takes into consideration a comprehensive range of factors, including user preferences, available viewing times, weather information, seasonal information, local event information, congestion information, and user reviews. The input is multiple candidate plans, and the output is the evaluated optimal content plan.

[0316] Step 6:

[0317] The server formats and sends details of the optimal content plan to the user's device, including the content title, viewing time, rating, etc. The input is the optimal plan that has been evaluated, and the output is the detailed information of the plan to be sent.

[0318] Step 7:

[0319] The terminal displays the details of the optimal content plan received from the server to the user. The user can watch movies, music, articles, etc. according to the proposed content plan. The input is the detailed plan information sent from the server, and the output is the detailed content plan displayed to the user.

[0320] In this way, the system can provide the user with the most suitable content plan.

[0321] 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.

[0322] The present invention is a system that recognizes the user's current emotional state by utilizing an emotion engine in addition to information input by the user, and proposes an optimal outing plan. Hereinafter, an embodiment of the present invention will be described in detail.

[0323] System configuration

[0324] The system mainly consists of the following components:

[0325] 1. User device: A device (smartphone, tablet, PC, etc.) through which the user inputs information, receives plans, and provides feedback on their emotional state.

[0326] 2. Server: The main processing unit that analyzes input information and emotional information from users and generates and evaluates outing plans.

[0327] 3. Database: Stores weather information, seasonal information, local event information, crowding information, user review information, and sentiment data and makes them accessible from the server.

[0328] 4. Emotion Engine: An engine that recognizes the user's emotional state and uses that information to help generate and evaluate plans.

[0329] Program processing

[0330] 1. Receiving user input

[0331] User

[0332] The user accesses a dedicated app or web platform and inputs their preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), and their current emotional state. The emotional state can be input using text, multiple-choice format, or voice recognition. This information is sent to the server by the device.

[0333] 2. Analysis of input information

[0334] server

[0335] The server analyzes the input and emotional information received from the user to determine the user's preferences, available time, budget, and current emotional state.

[0336] 3. Data collection

[0337] server

[0338] The server collects the following information from the database:

[0339] Weather information: Weather on the specified date.

[0340] Seasonal information: Events that occur at specific times or features specific to the season.

[0341] Local event information: Information about events taking place in a specified area.

[0342] Congestion information: Congestion levels in various locations.

[0343] User review information: Reviews from past users.

[0344] Emotional data: Past user emotional information and associated plan evaluations.

[0345] 4. Generating multiple candidate plans

[0346] server

[0347] Based on the collected information, the server generates multiple candidate plans that match the user's input and emotional information. For example, the following plans are generated:

[0348] Option 1: Relax for an hour at a cafe in front of the station, then spend two hours visiting a special exhibition at the museum.

[0349] Option 2: Spend 1.5 hours at a cafe in the downtown area, then spend 1.5 hours touring the art museum.

[0350] 5. Plan Evaluation and Selection

[0351] Emotion Engine

[0352] The emotion engine evaluates multiple candidate plans based on the user's current emotional state. Emotional information is taken into account as an important factor in the evaluation. Plans that induce positive emotions are given a higher rating.

[0353] server

[0354] The most suitable plan is selected based on the evaluation results of the emotion engine. For example, if the user is looking to relax, a plan that includes spending time in a quiet cafe may be selected.

[0355] 6. Presenting the plan

[0356] server

[0357] The details of the selected best plan are formatted and sent to the user, including a specific schedule and details of the destinations (names, addresses, reviews, estimated wait times).

[0358] Terminal

[0359] The user device receives the plan details sent from the server and displays them in a user-friendly format.

[0360] Specific examples

[0361] Consider the following real-world scenario:

[0362] example

[0363] On a Saturday afternoon, a user opens the app and enters the following information:

[0364] Likes: Cafes, art museums

[0365] Budget: 5,000 yen

[0366] Available time: 3 hours

[0367] Emotional state: Feeling stressed

[0368] Receiving User Input

[0369] The user enters the above information and presses the send button. The device sends the information to the server.

[0370] Analysis of input information

[0371] The server analyzes your preferences, available time, budget, and emotional state, and begins to collect data based on this information.

[0372] Data collection

[0373] The server collects information from a database about Saturday's weather (sunny), the museum's fall special exhibition, the area's crowd level (relatively low), relevant user reviews, and sentiment data.

[0374] Generate multiple candidate plans

[0375] The server generates a plan based on the collected data and emotional information, such as:

[0376] Option 1: Relax for an hour at a quiet cafe A in front of the station, then spend two hours visiting a special exhibition at museum B.

[0377] Option 2: Spend 1.5 hours at the highly satisfying Cafe C in the downtown area, then spend 1.5 hours touring Museum D.

[0378] Plan evaluation and selection

[0379] The emotion engine evaluates the candidate plans and determines that candidate 1 is the best, as it provides a quiet environment that helps reduce stress.

[0380] Presenting the plan

[0381] The server sends details of the best plan to the user's device, which displays it.

[0382] In this way, users can plan trips that are both efficient and emotionally satisfying. The system automatically provides the optimal plan by taking into account weather, season, events, crowding, reviews, and user emotional information.

[0383] The processing flow will be explained below.

[0384] Step 1:

[0385] User

[0386] Users access a dedicated app or web platform and enter their preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), and current emotional state (e.g., feeling stressed). After entering this information, they press the send button.

[0387] Step 2:

[0388] Terminal

[0389] The information entered by the user is sent to a server, including preferred activities, available time, budget, and emotional state.

[0390] Step 3:

[0391] server

[0392] The server analyzes the input and emotional information received from the user to determine the user's preferences, available time, budget, and emotional state.

[0393] Step 4:

[0394] server

[0395] The server collects weather information, seasonal information, local event information, congestion information, and user review information from a database.

[0396] Step 5:

[0397] Obtaining weather information: The server collects weather information for the specified date.

[0398] Acquisition of seasonal information: The server collects events at specific times and characteristics specific to the season.

[0399] Acquisition of local event information: The server collects information about events held in a specified area.

[0400] Obtaining congestion information: The server collects congestion information for each location.

[0401] Obtaining user review information: The server collects relevant past user reviews.

[0402] Acquiring emotional data: The server collects past user emotional information and associated plan evaluation data.

[0403] Step 6:

[0404] server

[0405] Based on the collected information, the server generates multiple candidate plans that match the user's input and emotional information. The generated plans reflect the user's preferred activities and time allocation within a budget.

[0406] Step 7:

[0407] server

[0408] Each candidate plan will be evaluated, taking into consideration the following factors:

[0409] Local Weather

[0410] Seasonal Events

[0411] Local Events

[0412] Congestion level

[0413] User reviews

[0414] emotional information

[0415] Step 8:

[0416] Emotion Engine

[0417] The emotion engine prioritizes multiple generated candidate plans based on the user's current emotional state, with plans that induce positive emotions being given a higher rating.

[0418] Step 9:

[0419] server

[0420] The emotion engine evaluates the plan to find the most suitable one. For example, if the user is feeling stressed, a plan that offers a quiet and relaxing environment may be selected.

[0421] Step 10:

[0422] server

[0423] The details of the selected best plan are formatted and sent to the user, including the name of the destination, its location, reviews, and estimated wait time.

[0424] Step 11:

[0425] Terminal

[0426] The user device receives the plan details sent from the server and displays them in a user-friendly format.

[0427] Step 12:

[0428] User

[0429] The user reviews the proposed plan, and if they are satisfied with it, they accept it and register it as a schedule. If they are not satisfied, they press the regenerate button to request a new plan.

[0430] Step 13:

[0431] server

[0432] If regeneration is requested, the same process is performed again to generate and provide a new plan.

[0433] Example 2

[0434] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0435] Conventional outing plan generation systems provide outing plans based on user input information, but they have the problem of not being able to provide plans that take into account the user's current emotional state. This can result in outing plans that do not match the user's emotional state, which can reduce satisfaction. Another issue is that the information collected is limited, making it difficult to gather enough data to provide a more comprehensive plan.

[0436] 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.

[0437] In this invention, the server includes means for receiving information input by the user and generating an outing plan, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, means for recognizing the emotional state and evaluating the outing plan based on the recognized emotional information, means for generating a plurality of candidate plans based on the collected information and emotional information, evaluating these candidate plans, and selecting an optimal plan, and means for presenting the optimal plan to the user. This makes it possible to provide an outing plan that suits the user's emotional state, thereby increasing user satisfaction.

[0438] "User-entered information" refers to data such as preferences, budget, available time, and current emotional state that a user enters through a dedicated application or web platform.

[0439] An "outing itinerary" is a series of suggested activities and places to visit that are generated based on user input and collected data.

[0440] "Emotional information" is data based on information that recognizes the user's current emotional state.

[0441] "Weather information" is data about the weather on a specified date, and is obtained from a weather forecast service or the like.

[0442] "Seasonal information" is data relating to events associated with specific times and characteristics specific to the season.

[0443] "Local event information" is data related to events held within a specified area.

[0444] "Crowding information" is data on the congestion situation in each area.

[0445] "User review information" is data about past users' ratings and impressions of facilities and events.

[0446] An "emotion engine" is a processing device or software that recognizes the user's emotional state and evaluates outing plans based on that information.

[0447] "Candidate plans" are multiple outing plans that are generated based on the user's input information and collected data.

[0448] The present invention is a system that recognizes the user's current emotional state and proposes an optimal outing plan by utilizing an emotion engine in addition to information input by the user. Hereinafter, an embodiment of the present invention will be described in detail.

[0449] System configuration

[0450] The system mainly consists of the following components:

[0451] 1. User device: A device (smartphone, tablet, PC, etc.) through which the user inputs information, receives plans, and provides feedback on their emotional state.

[0452] 2. Server: The main processing unit that analyzes input information and emotional information from users and generates and evaluates outing plans.

[0453] 3. Database: Stores weather information, seasonal information, local event information, congestion information, user review information, and emotion data and makes them accessible from the server.

[0454] 4. Emotion Engine: An engine that recognizes the user's emotional state and uses that information to help generate and evaluate plans.

[0455] Program processing

[0456] 1. Receiving user input

[0457] User

[0458] The user accesses a dedicated app or web platform and inputs their preferences, budget, available time, and current emotional state, which can be input via text, multiple choice, or voice recognition. This information is then sent by the device to the server.

[0459] 2. Analysis of input information

[0460] server

[0461] The server analyzes the input received from the user to determine the user's preferences, budget, available time, and current emotional state.

[0462] 3. Data collection

[0463] server

[0464] The server collects the following information from the database:

[0465] Weather information: Weather on a specified date

[0466] Seasonal information: Events and seasonal features

[0467] Local event information: Information on events held in designated areas

[0468] Congestion information: Congestion levels in various areas

[0469] User review information: Reviews from past users

[0470] Emotional data: Evaluating past user emotional information and related plans

[0471] 4. Generating Multiple Candidate Plans

[0472] server

[0473] Based on the collected information, the server generates multiple candidate plans that match the user's input information and emotional information.

[0474] 5. Evaluation and selection of plans

[0475] Emotion Engine

[0476] The emotion engine evaluates multiple candidate plans based on the user's current emotional state. Emotional information is taken into account as an important factor in the evaluation. Plans that induce positive emotions are given a higher rating.

[0477] server

[0478] The most suitable plan is selected based on the evaluation results of the emotion engine.

[0479] 6. Presenting the plan

[0480] server

[0481] The details of the selected best plan are formatted and sent to the user, including a specific schedule and details of the destinations (names, addresses, reviews, estimated wait times).

[0482] Terminal

[0483] The user terminal receives the plan details sent from the server and displays them in a user-friendly format.

[0484] Specific examples

[0485] Consider the following real-world scenario:

[0486] example

[0487] On a Saturday afternoon, a user opens the app and enters the following information:

[0488] Likes: Cafes, art museums

[0489] Budget: 5,000 yen

[0490] Available time: 3 hours

[0491] Emotional state: Feeling stressed

[0492] Prompt Sentence Examples

[0493] "When the user inputs their emotional state, the server generates the optimal outing plan based on that information."

[0494] "Use the emotion engine to evaluate and select plans that elicit positive emotions from users."

[0495] "Create an outing plan based on the specified criteria and send it to the user."

[0496] In this way, users can plan trips that are both efficient and emotionally satisfying. The system automatically provides optimal trip plans by taking into account weather, seasons, events, crowding levels, reviews, and users' emotional information.

[0497] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0498] System program processing flow

[0499] Step 1:

[0500] Receiving user input

[0501] Subject: User

[0502] The user accesses a dedicated app or web platform and enters their preferences, budget, available time, and current emotional state. The entered information is sent from the device to the server by pressing the send button. Specifically, the user opens the smartphone app, enters information into the displayed form, and clicks the send button. At this time, when the input is submitted, the device sends the data to the server.

[0503] Inputs: User preferences, budget, available time, emotional state

[0504] Output: User input information is sent to the server

[0505] Step 2:

[0506] Analysis of input information

[0507] Subject: Server

[0508] The server analyzes the received user input information. Specifically, it extracts information and categorizes it into categories such as preferences, budget, available time, and emotional state. This information is temporarily stored for use in the next processing step. The server then performs the appropriate data conversion and database storage for analysis.

[0509] Input: User-entered information

[0510] Output: Preferences, budget, available time, and emotional state are identified and stored in a temporary database

[0511] Step 3:

[0512] Data collection

[0513] Subject: Server

[0514] The server accesses the database and collects the following information:

[0515] Weather information: Data from the weather API

[0516] Seasonal information: Data about events occurring at specific times

[0517] Local event information: Information on events held in designated areas

[0518] Congestion information: Real-time congestion status

[0519] User review information: Past user reviews

[0520] Emotion data: Past emotional information and related evaluation information of plans

[0521] The server collects this information by running SQL queries against a database and stores it in temporary data storage.

[0522] Input: User-entered information stored in a temporary database

[0523] Output: Collected weather information, seasonal information, local event information, congestion information, user review information, emotion data

[0524] Step 4:

[0525] Generate multiple candidate plans

[0526] Subject: Server

[0527] The server generates multiple candidate plans based on the collected data and user input, including the names, addresses, travel time, budget, etc. The server uses an appropriate algorithm to evaluate the relevance of the data and generate multiple candidate plans.

[0528] Input: Parsed user input information, collected data

[0529] Output: Multiple candidate plans (destination names, addresses, travel time, budget, etc.)

[0530] Step 5:

[0531] Plan evaluation and selection

[0532] Subject: Emotion Engine and Server

[0533] The emotion engine evaluates the generated candidate plans based on the user's current emotional state. This evaluation emphasizes factors that elicit positive emotions from the user. The server selects the optimal plan based on the emotion engine's evaluation results.

[0534] Input: Multiple candidate plans, emotion information

[0535] Output: Evaluated candidate plans and selection of the best plan

[0536] Step 6:

[0537] Presenting the plan

[0538] Subject: Server and Terminal

[0539] The server formats the details of the selected optimal plan and sends it to the user. The plan includes a specific schedule and details of the destinations (names, addresses, reviews, expected waiting times). The user's device then receives the plan details sent from the server and displays them in a user-friendly format.

[0540] Input: Optimal plan

[0541] Output: Plan details displayed on the user's terminal

[0542] In this way, users can plan trips that are both efficient and emotionally satisfying. The system automatically provides optimal trip plans by taking into account weather, seasons, events, crowding levels, reviews, and users' emotional information.

[0543] (Application example 2)

[0544] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0545] Conventional outing plan generation systems generate plans based on basic user information, but do not take the user's emotional state into consideration, making it difficult to provide a truly satisfying plan for the user. Furthermore, they do not suggest specific products or services, making it difficult to provide a shopping experience that is optimal for the user's current emotional state.

[0546] 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.

[0547] In this invention, the server includes means for receiving input information from a user and generating an outing plan based on the input information, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, means for generating a plurality of candidate plans based on the collected information and evaluating these candidate plans to select an optimal plan, means for analyzing the user's emotional state and suggesting products and services optimal for that emotional state, and means for presenting the optimal plan and the suggested products and services to the user, thereby enabling optimal outing plans and shopping suggestions tailored to the user's emotional state.

[0548] "User Input" means information that a User provides through an application or web platform, such as personal preferences, available time, budget, or emotional state.

[0549] An "outing plan" is an action plan that suggests places to visit and a schedule based on conditions specified by the user.

[0550] "Climate information" refers to meteorological data such as weather, temperature, and precipitation at a specific date, time, and location.

[0551] "Seasonal information" is data about events and activities related to a particular season and the characteristics specific to that season.

[0552] "Regional event information" is information about various events held in a specified region.

[0553] "Crowding level information" is data that indicates the congestion level of a specific location or event.

[0554] "User review information" refers to data regarding the ratings and opinions of past users on services and products provided.

[0555] "Emotional state" refers to the user's current mental and psychological state (e.g., stress, happiness, fatigue).

[0556] An "emotion engine" is a system that analyzes the user's input information and behavioral data to recognize their current emotional state and make suggestions and evaluations based on that.

[0557] "Goods and Services" refers to the tangible goods and activities and services available to you.

[0558] A "shopping platform" is a platform for purchasing and proposing products and services online.

[0559] This invention is a system that utilizes an emotion engine to recognize the user's current emotional state in addition to input information from the user, and then suggests outing plans, products, and services. This system is composed of the following elements:

[0560] System configuration

[0561] 1. User Device

[0562] A device where a user enters information and receives proposed plans and products. Examples include smartphones, tablets, and PCs.

[0563] 2. Server

[0564] It is the main processing device that analyzes input information and emotional information from users and generates outing plans, products and services.

[0565] 3. Database

[0566] Weather information, seasonal information, local event information, congestion information, user review information, and emotion data are stored and made accessible from a server.

[0567] 4. Emotion Engine

[0568] It is an engine that recognizes the user's emotional state and uses that information to generate and evaluate plans and suggest products and services. Specific examples include Azure Cognitive Services and IBM Watson.

[0569] Program processing

[0570] Receiving user input

[0571] Users access a dedicated app or web platform and enter their preferences, budget, available time, and their current emotional state, which can be entered via text, multiple choice, or voice recognition. This information is then sent to the server by the device.

[0572] Analysis of input information

[0573] The server analyzes the input and emotional information received from the user to determine the user's preferences, available time, budget, and current emotional state.

[0574] Data collection

[0575] The server collects the following information from the database:

[0576] Weather information: Weather on the specified date.

[0577] Seasonal information: Events that occur at specific times or features specific to the season.

[0578] Local event information: Information about events taking place in a specified area.

[0579] Congestion information: Congestion levels in various locations.

[0580] User review information: Reviews from past users.

[0581] Emotional data: Past user emotional information and associated plan evaluations.

[0582] Proposing multiple candidate plans and products / services

[0583] Based on the collected information, the server generates multiple candidate plans and products / services that match the user's input information and emotional information, while simultaneously proposing optimal products and services according to the user's emotional state.

[0584] Evaluating and selecting plans, products and services

[0585] The emotion engine evaluates multiple candidate plans and products / services based on the user's current emotional state. Emotional information is taken into account as an important factor in the evaluation. Plans and product proposals that induce positive emotions are given higher ratings.

[0586] Offering plans, products and services

[0587] The server formats the most suitable plan and product / service details and sends them to the user. The plan includes a specific schedule and details of the destinations (name, address, reviews, expected waiting time). The user's device receives the plan and product / service details sent from the server and displays them in a user-friendly format.

[0588] Specific examples

[0589] On a Saturday afternoon, a user opens the app and enters the following information:

[0590] Likes: Cafes, art museums

[0591] Budget: 5,000 yen

[0592] Available time: 3 hours

[0593] Emotional state: Feeling stressed

[0594] The server analyzes this information and collects related data from the database.The server then uses an emotion engine to suggest plans and products that will help reduce stress (for example, relaxation goods or aroma candles).Examples of plans, products, and services that are best suited to the user include the following:

[0595] The plan: Relax for an hour at a quiet cafe in front of the station, then spend two hours visiting a special exhibition at the museum.

[0596] Products: Relaxation items, aroma candles, herbal tea.

[0597] Example prompts for generative AI models

[0598] "My emotional state is 'stressed'. Please suggest products that would be best suited to this state."

[0599] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0600] Step 1:

[0601] Receiving user input

[0602] The user opens the application or web platform and enters information such as their preferences for cafes, museums, etc., their budget (e.g., 5,000 yen), the amount of time available (e.g., 3 hours), and their current emotional state (e.g., feeling stressed). This information is then sent by the device to the server.

[0603] Inputs: User preferences, budget, available time, emotional state

[0604] Output: User input sent to the server

[0605] Step 2:

[0606] Analysis of input information

[0607] The server analyzes the received user input to determine the user's preferences, budget, available time, and emotional state, taking into account past user behavior and emotional data from a database.

[0608] Input: User-entered information

[0609] Output: Analyzed user preferences, budget, available time, emotional state

[0610] Step 3:

[0611] Data collection

[0612] Based on the analyzed user information, the server collects weather information, seasonal information, local event information, congestion information, user review information, and emotion data from the database, which will later serve as the basis for plans and products.

[0613] Input: Analyzed user preferences, budget, available time, emotional state

[0614] Output: Collected weather information, seasonal information, local event information, crowding information, user review information, and sentiment data

[0615] Step 4:

[0616] Generate multiple candidate plans and products / services

[0617] The server generates multiple candidate plans and products / services based on the collected data and matched to the user's input and emotional information. For example, if the user is feeling stressed, the plan may include a quiet cafe where they can relax or recommended relaxation products.

[0618] Input: Collected information and the user's emotional state

[0619] Output: Multiple candidate plans and products / services

[0620] Step 5:

[0621] Evaluating and selecting plans, products and services

[0622] The emotion engine evaluates the generated multiple candidate plans and products / services based on the user's emotional state. Plans and product proposals that induce positive emotions are given higher ratings. The server selects the most suitable plan, product, or service based on the evaluation results.

[0623] Input: Multiple candidate plans and products / services

[0624] Output: Optimal plans and products / services based on emotional state

[0625] Step 6:

[0626] Offering plans, products and services

[0627] The server formats the details of the selected optimal plan and products / services and sends them to the user's device. The device receives this and displays it in a format that is easy for the user to understand. For example, the plan schedule and recommended products are displayed on the smartphone screen.

[0628] Input: Best plan and product / service

[0629] Output: Plan and product / service details displayed on the user's device

[0630] 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.

[0631] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0632] 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.

[0633] [Second embodiment]

[0634] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0635] 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.

[0636] 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).

[0637] 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.

[0638] 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.

[0639] 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).

[0640] 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.

[0641] 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.

[0642] 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.

[0643] 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.

[0644] 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.

[0645] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0646] The present invention is a system that proposes optimal outing plans based on a user's input of their preferences, budget, and available time. Hereinafter, an embodiment of the present invention will be described in detail.

[0647] System configuration

[0648] The system mainly consists of the following components:

[0649] 1. User device: The device (smartphone, tablet, PC, etc.) through which the user enters information and receives the plan.

[0650] 2. Server: The main processing unit that analyzes the input information from the user and generates and evaluates the trip plan.

[0651] 3. Database: Stores weather information, seasonal information, local event information, congestion information, and user review information and makes it accessible from the server.

[0652] Program processing

[0653] 1. Receiving user input

[0654] User

[0655] The user accesses a dedicated app or web platform and enters information such as preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), etc. This information is sent to the server by the device.

[0656] 2. Analysis of input information

[0657] server

[0658] The server analyzes the input information received from the user, which determines the user's preferences, available time, and budget.

[0659] 3. Data collection

[0660] server

[0661] The server collects the following information from the database:

[0662] Weather information: Weather on the specified date.

[0663] Seasonal information: Characteristic events at specific times.

[0664] Local Event Information: Public events in designated areas.

[0665] Congestion information: Congestion levels in various locations.

[0666] User review information: Past user reviews.

[0667] 4. Generating multiple candidate plans

[0668] server

[0669] The server generates multiple itineraries based on the collected information, matching the user's input information. For example, the following itineraries may be generated:

[0670] Option 1: Relax for an hour at a cafe in front of the station, then spend two hours visiting a special exhibition at the art museum.

[0671] Option 2: Spend 1.5 hours at a cafe downtown, then spend 1.5 hours touring the art museum.

[0672] 5. Plan Evaluation and Selection

[0673] server

[0674] The generated candidate plans are evaluated. The evaluation includes comprehensive information on weather, season, local events, congestion, and user reviews. The most suitable plan is selected from the evaluation results.

[0675] 6. Presenting the plan

[0676] server

[0677] The best plan is then formatted and sent to the user, including a specific schedule and details of the destinations (names, addresses, reviews, and estimated wait times).

[0678] Terminal

[0679] The user's terminal displays the plan details received from the server, and the user can plan their outing according to this plan.

[0680] Specific examples

[0681] Consider the following real-world scenario:

[0682] example

[0683] On a Saturday afternoon, a user opens the app and enters the following information:

[0684] Likes: Cafes, art museums

[0685] Budget: 5,000 yen

[0686] Available time: 3 hours

[0687] Receiving user input

[0688] The user enters the above information and presses the send button. The device sends the information to the server.

[0689] Analysis of input information

[0690] The server analyzes your preferences, availability, and budget and begins to collect data based on this information.

[0691] Data collection

[0692] The server gathers from a database information about Saturday's weather (clear), the museum's fall special exhibitions, the area's crowd level (relatively low), and relevant user reviews.

[0693] Generate multiple candidate plans

[0694] Based on the data collected, the server generates a plan like this:

[0695] Option 1: Relax for an hour at Cafe A in front of the station, then spend two hours visiting a special exhibition at Museum B.

[0696] Option 2: Spend 1.5 hours at Cafe C in the downtown area, then visit Museum D for 1.5 hours.

[0697] Plan evaluation and selection

[0698] The server evaluates the candidate plans and selects the best one. For example, candidate 1 is determined to be the best.

[0699] Presenting the plan

[0700] The server sends details of the optimal plan to the user's device, which displays it.

[0701] In this way, users can plan their outings efficiently and enjoyably. The system automatically provides the best plan, taking into account weather, season, events, crowd levels, and reviews.

[0702] The processing flow will be explained below.

[0703] Step 1:

[0704] Terminal

[0705] The user accesses a dedicated app or web platform and enters information such as preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), etc. Once the information is complete, the user presses the submit button.

[0706] Step 2:

[0707] Terminal

[0708] The information entered by the user is sent to the server, including preferred activities, available time, and budget.

[0709] Step 3:

[0710] server

[0711] The server analyzes the input information received from the user to determine the user's preferences, available time, and budget.

[0712] Step 4:

[0713] server

[0714] The server collects weather information, seasonal information, local event information, crowding information, and user reviews from a database.

[0715] Step 5:

[0716] Obtaining weather information: The server collects weather information for the specified date.

[0717] Acquisition of seasonal information: The server collects events at specific times and characteristics specific to the season.

[0718] Acquisition of local event information: The server collects information about events held in a specified area.

[0719] Obtaining congestion information: The server collects congestion information for each location.

[0720] Obtaining user review information: The server collects relevant past user reviews.

[0721] Step 6:

[0722] server

[0723] Based on the collected information, the server generates multiple candidate plans that match the user's input information. The generated plans reflect the user's preferred activities and time allocation within the user's budget.

[0724] Step 7:

[0725] server

[0726] Each candidate plan will be evaluated, taking into consideration the following factors:

[0727] Local Weather

[0728] Seasonal Events

[0729] Local Events

[0730] Congestion level

[0731] User reviews

[0732] Step 8:

[0733] server

[0734] Based on the evaluation results, the most appropriate plan is selected. For example, the following plan may be determined to be optimal:

[0735] Relax for an hour at a cafe in front of the station, then spend two hours visiting the museum's special exhibition.

[0736] Step 9:

[0737] server

[0738] Format details of the selected best plan, including the name of the destination, its location, reviews, and estimated wait time.

[0739] Step 10:

[0740] server

[0741] The server sends details of the best plan to the user's device.

[0742] Step 11:

[0743] Terminal

[0744] The user device receives the plan details sent from the server and displays them in a user-friendly format.

[0745] Step 12:

[0746] User

[0747] The user reviews the proposed plan, and if they are satisfied with it, they accept it and register it as a schedule. If they are not satisfied, they press the regenerate button to request a new plan.

[0748] Step 13:

[0749] server

[0750] If regeneration is requested, the same process is performed again to generate and provide a new plan.

[0751] Example 1

[0752] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0753] Conventional outing planning systems have difficulty providing optimal plans that fully consider individual requirements such as user preferences, budget, and available time. Furthermore, they are unable to generate outing plans by comprehensively evaluating environmental information such as weather and event crowding, which prevents them from increasing user satisfaction. To solve these problems, a system capable of more advanced information analysis and appropriate plan generation is needed.

[0754] 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.

[0755] In this invention, the server includes means for receiving user input information and generating an outing plan based on the input information, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, means for generating multiple candidate plans based on the collected information and evaluating the candidate plans to select an optimal plan, means for presenting the optimal plan to the user, means for analyzing the user input information and identifying preferences, budget, and available time, means for collecting related information from a database based on the identified information, means for evaluating the multiple generated candidate plans and selecting an optimal plan based on an overall evaluation score, means for sending details of the selected plan to the user terminal and displaying the details to the user, means for evaluating and optimizing the outing plan using a generative AI model, and means for inputting prompt sentences into the generative AI model to generate an outing plan. This makes it possible to provide an optimal outing plan by comprehensively evaluating individual requirements based on the user input information and environmental information.

[0756] "User-entered information" is data such as preferences, budget, and available time that a user inputs into the system.

[0757] An "outing plan" is a proposal that includes the user's outing schedule and details of places to visit, generated based on the user's input information and collected environmental information.

[0758] "Weather information" is weather forecast data for a specified date.

[0759] "Seasonal information" is information about events and unique activities related to a particular time of year.

[0760] "Local event information" is information about public events held in a specific local area.

[0761] "Crowding level information" is information about the congestion status of a specific area or facility.

[0762] "User review information" refers to reviews and ratings provided by other users in the past.

[0763] The "multiple candidate plans" are multiple outing suggestions generated based on the user's input information and the collected environmental information.

[0764] The "optimal plan" is the most suitable outing plan selected from multiple candidate plans by comprehensively evaluating the user's requirements and environmental information.

[0765] A "generative AI model" is an artificial intelligence model that generates and optimizes outing plans based on user input information and collected environmental information.

[0766] A "prompt sentence" is an instruction sentence that is input to the generative AI model to generate an outing plan.

[0767] MODE FOR CARRYING OUT THE INVENTION

[0768] The present invention relates to a system that proposes optimal outing plans by allowing a user to input their preferences, budget, and available time. Hereinafter, an embodiment of the present invention will be described in detail.

[0769] System configuration

[0770] The system mainly consists of the following components:

[0771] 1. User device: The device (smartphone, tablet, PC, etc.) through which the user enters information and receives travel plans.

[0772] 2. Server: The main processing unit that analyzes input information from users and generates and evaluates outing plans.

[0773] 3. Database: Stores weather information, seasonal information, local event information, congestion information, and user review information and makes it accessible from the server.

[0774] Program processing

[0775] 1. Receiving user input

[0776] A user accesses a dedicated app or web platform and enters information such as preferences (e.g., cafes, museums), budget (e.g., 5,000 yen), available time (e.g., 3 hours), etc. This information is sent to the server using a reactive form or HTTP request.

[0777] 2. Analysis of input information

[0778] The server parses the input information it receives using a script written in Python or JavaScript that parses the JSON data to identify the user's preferences, budget, and available time.

[0779] 3. Data collection

[0780] The server connects to a database or external API to gather the necessary information, for example using SQL queries to get the following information:

[0781] Climate information: Weather forecast for a specific date

[0782] Seasonal information: Events related to the current season

[0783] Local Event Information: Public events in designated areas

[0784] Congestion information: Congestion status of designated areas

[0785] User review information: reviews and ratings from other users

[0786] 4. Generating candidate plans

[0787] The server generates multiple itineraries based on the collected information, using an algorithm to generate the following itineraries:

[0788] Option 1: Relax for an hour at Cafe A in front of the station, then spend two hours visiting a special exhibition at Museum B.

[0789] Option 2: Spend 1.5 hours at Cafe C in the downtown area and then visit Museum D for 1.5 hours.

[0790] 5. Evaluation and selection of plans

[0791] The server evaluates the generated candidate plans, using a comprehensive set of information including weather, season, local events, congestion, and user reviews.

[0792] The server selects the optimal plan based on the overall evaluation points.

[0793] 6. Presenting the plan

[0794] The server sends the details of the optimal plan to the user's device, which then displays the information, allowing the user to plan their outing according to the plan provided.

[0795] Specific examples

[0796] For example, on a Saturday afternoon, a user opens the app and enters the following information:

[0797] Likes: Cafes, art museums

[0798] Budget: 5,000 yen

[0799] Available time: 3 hours

[0800] Once the user submits their input, the device sends the information to a server, which analyzes the user's preferences, budget, and available time, and then gathers relevant data from a database or external API, such as sunny weather information, special museum exhibitions, local congestion levels, and past user reviews.

[0801] The server then generates multiple candidate plans based on this data, evaluates the plans, selects the plan with the highest evaluation points, formats the specific schedule and details of the places to visit, and sends it to the user's device.

[0802] Prompt Sentence Examples

[0803] Examples of prompts for generative AI models include:

[0804] "The user is looking for a 3-hour outing plan with a budget of 5000 yen, where the user prefers cafes and museums on a Saturday afternoon. Generate multiple possible outing plans, and then rate and present the best plan. Information to consider includes weather forecasts, seasonal events, local public events, crowd data, and user reviews."

[0805] This makes it possible to provide users with optimal outing plans.

[0806] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0807] Step 1:

[0808] Receiving user input

[0809] Users access a dedicated app or web platform and enter their preferences, budget, and available time.

[0810] Specific operation: The user enters their preferences (e.g., "cafe, museum"), their budget (5,000 yen), and the duration (3 hours) into the form, then presses the submit button.

[0811] The terminal receives this input information and sends it to the server.

[0812] Specific operation: Sends input data to the server as an HTTP POST request.

[0813] Input (device): User preferences, budget, and available time.

[0814] Output (Terminal → Server): HTTP request containing input information.

[0815] Step 2:

[0816] Analysis of input information

[0817] The server analyzes the received input information.

[0818] What it does: The server runs a parsing script written in Python or JavaScript that parses the JSON data and stores preferences, budget, and available time in separate variables.

[0819] Input (server): JSON data containing user input information.

[0820] Output (server): Parsed individual variables (preferences, budget, available time).

[0821] Step 3:

[0822] Data collection

[0823] The server connects to a database or external API to collect the necessary information.

[0824] What it does: It uses SQL queries and API requests to retrieve the following information:

[0825] Weather information: Get the weather forecast for the specified date from the API.

[0826] Seasonal information: Retrieves events related to the current season from the database.

[0827] Local Event Information: Retrieve public events in a specified area from a database or API.

[0828] Congestion information: Obtain the congestion status of the specified area from the API.

[0829] User review information: Retrieve other users' reviews and ratings from our database.

[0830] Input (server): Parsed user input information.

[0831] Output (server): Collected data (weather information, seasonal information, local event information, congestion information, user review information).

[0832] Step 4:

[0833] Generate candidate plans

[0834] The server generates multiple outing plans based on the collected information.

[0835] What it does: It uses an algorithm to generate a list of plans based on your preferences, budget, and availability. For example, it might generate plans like this:

[0836] Option 1: Relax for an hour at a cafe in front of the station, then spend two hours visiting a special exhibition at the museum.

[0837] Option 2: Spend 1.5 hours at a cafe downtown and 1.5 hours visiting the art museum.

[0838] Input (Server): Collected data and analyzed user input information.

[0839] Output (server): Multiple candidate plans generated.

[0840] Step 5:

[0841] Plan evaluation and selection

[0842] The server evaluates the generated candidate plans.

[0843] Specific operation: Calculates rating points for each plan. These rating points are calculated taking into account weather information, seasonal information, local event information, crowding information, and user reviews. For example, visiting an art museum on a sunny day will earn you a high rating point.

[0844] The server selects the optimal plan from the evaluation results.

[0845] Specific operation: Select the plan with the highest overall evaluation points.

[0846] Input (server): Multiple generated candidate plans.

[0847] Output (server): Optimal plan.

[0848] Step 6:

[0849] Presenting the plan

[0850] The server sends the details of the selected optimal plan to the user terminal,

[0851] Specific operation: The details of the selected plan (schedule, details of destinations) are formatted in HTML or JSON format and sent as an HTTP response.

[0852] The terminal displays the plan details received from the server.

[0853] Specific behavior: Provides the user with visual details of the plan according to a display format.

[0854] Input (server → terminal): Details of the optimal plan.

[0855] Output (terminal): Displayed outing plan.

[0856] By following these steps, users can plan their outings efficiently and enjoyably.

[0857] (Application example 1)

[0858] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0859] In today's world, users often find it difficult to efficiently find personalized content that meets their preferences. Furthermore, there are no systems that suggest optimal content based on available viewing time or device type, so users must search for the appropriate content themselves, which is time-consuming. To solve this problem, a system is needed that can automatically generate and suggest personalized content plans based on user input.

[0860] 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.

[0861] In this invention, the server includes means for receiving user input information and generating a personalized content plan based on the input information, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, and means for generating multiple candidate plans based on the collected information and evaluating these candidate plans to select an optimal content plan. This makes it possible to efficiently propose an optimal content plan based on the user's preferences, available viewing time, and device used.

[0862] "User input information" refers to information entered by the user, such as preferences, available viewing times, and device type.

[0863] A "personalized content plan" is a customized recommendation of content such as movies, music, articles, etc. based on user input information.

[0864] "Climate information" is data about weather collected from outside.

[0865] "Seasonal information" is information about events and general activities associated with a particular time of year.

[0866] "Local event information" is information about events and occasions held in a specific local area.

[0867] "Crowding level information" is information about the congestion level of a specific location or event.

[0868] "User review information" refers to ratings and opinions from other users regarding services and content provided in the past.

[0869] "Server" is the primary processing unit that analyzes user input, generates personalized content plans, and collects and evaluates information.

[0870] "Device" refers to the terminal used by the user, such as a smartphone, smart glasses, or head-mounted display.

[0871] "Analysis" means deciphering the information entered by the user and performing appropriate processing based on that content.

[0872] The "optimal plan" is the plan that best meets the user's requirements from among multiple candidate plans.

[0873] "Evaluation" is the process of comparing the generated candidate plans and selecting the plan that best suits the user's requirements.

[0874] This invention is a system that proposes personalized content plans based on user preferences, available viewing times, and devices. This system is composed of a user terminal, a server, and a database.

[0875] System configuration

[0876] 1. User Device:

[0877] To input information, users use devices such as smartphones, smart glasses, and head-mounted displays, which then send the input information, such as user preferences, available viewing time, and the type of device used, to a server.

[0878] 2. Server:

[0879] The server receives user input information, analyzes it, and generates the optimal content plan. It uses a Python server program, an SQL database, and the Flask framework that provides a REST API. The server performs the following processes:

[0880] Analyzes user input to determine preferred content, viewing times, and devices.

[0881] Relevant information (weather information, seasonal information, local event information, congestion information, user review information) is collected from the database.

[0882] Based on the collected information, multiple candidate plans are generated and the optimal plan is selected after evaluation.

[0883] The selected optimal content plan is sent to the user's device.

[0884] 3. Database:

[0885] The database stores weather information, seasonal information, local event information, congestion information, and user review information and makes them accessible from the server.

[0886] Program processing explanation

[0887] Hardware and Software Used

[0888] Hardware: Smartphones, smart glasses, head-mounted displays

[0889] Software: Python, SQL database, Flask framework

[0890] Data processing and calculation

[0891] 1. Analysis of input information:

[0892] The server analyzes data entered by the user, such as preferred content, available viewing time, and device type, thereby identifying the user's preferences, available viewing time, and device type.

[0893] 2. Data Collection:

[0894] The server collects information from the database about the weather, seasons, local events, crowding levels, and user reviews, providing users with the latest information that meets their requirements in real time.

[0895] 3. Generate and evaluate candidate plans:

[0896] The server generates multiple candidate content plans based on the collected information, evaluates each plan to best match the user's preferences, available viewing time, and other conditions, and selects the optimal plan.

[0897] 4. Present the plan:

[0898] The server sends the details of the selected optimal plan (e.g., movie title, album name, viewing time, rating, etc.) to the user's device, which displays it on the screen and allows the user to watch the suggested content.

[0899] Specific examples

[0900] As an example, consider the following scenario:

[0901] User Input:

[0902] Favorites: Action movies, rock music

[0903] Viewing time: 2 hours

[0904] Device: Smartphone

[0905] The user opens the app and enters the above information. The device sends the information to the server, which then uses it to gather relevant data from its database. The server then generates a content plan that looks like this:

[0906] Option 1: Watch a 1.5 hour action movie, a 30 minute rock album

[0907] Nominations: 2.50 minute action short films, 1.5 hour documentaries

[0908] The server evaluates these candidate plans and selects the best plan (e.g., candidate 1 is determined to be the best), then sends details of the best plan to the user's device, which displays it.

[0909] Examples of prompts for generative AI models

[0910] "Generate the optimal content plan based on the user's preferences, available viewing time, and device they are using. The user's preferences are 'action movies' and 'rock music'. The available viewing time is 2 hours. The device is a smartphone."

[0911] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0912] Step 1:

[0913] The device accepts user input of preferences, available viewing time, and device type. The device receives the user input and sends it to the server. The input includes preferences (e.g., action movies, rock music), available viewing time (e.g., 2 hours), and device (e.g., smartphone). The output is the user input sent to the server.

[0914] Step 2:

[0915] The server receives user input information sent from the device. The received data includes user preferences, available viewing time, and device type. This data is analyzed to identify user preferences and conditions. The input is the user input information, and the output is the analyzed user preferences, available viewing time, and device type.

[0916] Step 3:

[0917] The server collects relevant information (weather information, seasonal information, local event information, congestion information, and user review information) from the database. The input is the analyzed user conditions, and an SQL query is executed to retrieve the required data based on those conditions. The output is the collected weather information, seasonal information, local event information, congestion information, and user review information.

[0918] Step 4:

[0919] The server generates multiple candidate content plans based on the collected information. Specifically, it creates plans by combining appropriate movies, music, articles, etc. based on the user's preferences and available viewing time. The input includes the collected information and the user's conditions, and the output is the generated multiple candidate plans.

[0920] Step 5:

[0921] The server evaluates the generated multiple candidate plans and selects the optimal content plan. The evaluation takes into consideration a comprehensive range of factors, including user preferences, available viewing times, weather information, seasonal information, local event information, congestion information, and user reviews. The input is multiple candidate plans, and the output is the evaluated optimal content plan.

[0922] Step 6:

[0923] The server formats and sends details of the optimal content plan to the user's device, including the content title, viewing time, rating, etc. The input is the optimal plan that has been evaluated, and the output is the detailed information of the plan to be sent.

[0924] Step 7:

[0925] The terminal displays the details of the optimal content plan received from the server to the user. The user can watch movies, music, articles, etc. according to the proposed content plan. The input is the detailed plan information sent from the server, and the output is the detailed content plan displayed to the user.

[0926] In this way, the system can provide the user with the most suitable content plan.

[0927] 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.

[0928] The present invention is a system that recognizes the user's current emotional state by utilizing an emotion engine in addition to information input by the user, and proposes an optimal outing plan. Hereinafter, an embodiment of the present invention will be described in detail.

[0929] System configuration

[0930] The system mainly consists of the following components:

[0931] 1. User device: A device (smartphone, tablet, PC, etc.) through which the user inputs information, receives plans, and provides feedback on their emotional state.

[0932] 2. Server: The main processing unit that analyzes input information and emotional information from users and generates and evaluates outing plans.

[0933] 3. Database: Stores weather information, seasonal information, local event information, crowding information, user review information, and sentiment data and makes them accessible from the server.

[0934] 4. Emotion Engine: An engine that recognizes the user's emotional state and uses that information to help generate and evaluate plans.

[0935] Program processing

[0936] 1. Receiving user input

[0937] User

[0938] The user accesses a dedicated app or web platform and inputs their preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), and their current emotional state. The emotional state can be input using text, multiple-choice format, or voice recognition. This information is sent to the server by the device.

[0939] 2. Analysis of input information

[0940] server

[0941] The server analyzes the input and emotional information received from the user to determine the user's preferences, available time, budget, and current emotional state.

[0942] 3. Data collection

[0943] server

[0944] The server collects the following information from the database:

[0945] Weather information: Weather on the specified date.

[0946] Seasonal information: Events that occur at specific times or features specific to the season.

[0947] Local event information: Information about events taking place in a specified area.

[0948] Congestion information: Congestion levels in various locations.

[0949] User review information: Reviews from past users.

[0950] Emotional data: Past user emotional information and associated plan evaluations.

[0951] 4. Generating multiple candidate plans

[0952] server

[0953] Based on the collected information, the server generates multiple candidate plans that match the user's input and emotional information. For example, the following plans are generated:

[0954] Option 1: Relax for an hour at a cafe in front of the station, then spend two hours visiting a special exhibition at the museum.

[0955] Option 2: Spend 1.5 hours at a cafe in the downtown area, then spend 1.5 hours touring the art museum.

[0956] 5. Plan Evaluation and Selection

[0957] Emotion Engine

[0958] The emotion engine evaluates multiple candidate plans based on the user's current emotional state. Emotional information is taken into account as an important factor in the evaluation. Plans that induce positive emotions are given a higher rating.

[0959] server

[0960] The most suitable plan is selected based on the evaluation results of the emotion engine. For example, if the user is looking to relax, a plan that includes spending time in a quiet cafe may be selected.

[0961] 6. Presenting the plan

[0962] server

[0963] The details of the selected best plan are formatted and sent to the user, including a specific schedule and details of the destinations (names, addresses, reviews, estimated wait times).

[0964] Terminal

[0965] The user device receives the plan details sent from the server and displays them in a user-friendly format.

[0966] Specific examples

[0967] Consider the following real-world scenario:

[0968] example

[0969] On a Saturday afternoon, a user opens the app and enters the following information:

[0970] Likes: Cafes, art museums

[0971] Budget: 5,000 yen

[0972] Available time: 3 hours

[0973] Emotional state: Feeling stressed

[0974] Receiving User Input

[0975] The user enters the above information and presses the send button. The device sends the information to the server.

[0976] Analysis of input information

[0977] The server analyzes your preferences, available time, budget, and emotional state, and begins to collect data based on this information.

[0978] Data collection

[0979] The server collects information from a database about Saturday's weather (sunny), the museum's fall special exhibition, the area's crowd level (relatively low), relevant user reviews, and sentiment data.

[0980] Generate multiple candidate plans

[0981] The server generates a plan based on the collected data and emotional information, such as:

[0982] Option 1: Relax for an hour at a quiet cafe A in front of the station, then spend two hours visiting a special exhibition at museum B.

[0983] Option 2: Spend 1.5 hours at the highly satisfying Cafe C in the downtown area, then spend 1.5 hours touring Museum D.

[0984] Plan evaluation and selection

[0985] The emotion engine evaluates the candidate plans and determines that candidate 1 is the best, as it provides a quiet environment that helps reduce stress.

[0986] Presenting the plan

[0987] The server sends details of the best plan to the user's device, which displays it.

[0988] In this way, users can plan trips that are both efficient and emotionally satisfying. The system automatically provides the optimal plan by taking into account weather, season, events, crowding, reviews, and user emotional information.

[0989] The processing flow will be explained below.

[0990] Step 1:

[0991] User

[0992] Users access a dedicated app or web platform and enter their preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), and current emotional state (e.g., feeling stressed). After entering this information, they press the send button.

[0993] Step 2:

[0994] Terminal

[0995] The information entered by the user is sent to a server, including preferred activities, available time, budget, and emotional state.

[0996] Step 3:

[0997] server

[0998] The server analyzes the input and emotional information received from the user to determine the user's preferences, available time, budget, and emotional state.

[0999] Step 4:

[1000] server

[1001] The server collects weather information, seasonal information, local event information, congestion information, and user review information from a database.

[1002] Step 5:

[1003] Obtaining weather information: The server collects weather information for the specified date.

[1004] Acquisition of seasonal information: The server collects events at specific times and characteristics specific to the season.

[1005] Acquisition of local event information: The server collects information about events held in a specified area.

[1006] Obtaining congestion information: The server collects congestion information for each location.

[1007] Obtaining user review information: The server collects relevant past user reviews.

[1008] Acquiring emotional data: The server collects past user emotional information and associated plan evaluation data.

[1009] Step 6:

[1010] server

[1011] Based on the collected information, the server generates multiple candidate plans that match the user's input and emotional information. The generated plans reflect the user's preferred activities and time allocation within a budget.

[1012] Step 7:

[1013] server

[1014] Each candidate plan will be evaluated, taking into consideration the following factors:

[1015] Local Weather

[1016] Seasonal Events

[1017] Local Events

[1018] Congestion level

[1019] User reviews

[1020] emotional information

[1021] Step 8:

[1022] Emotion Engine

[1023] The emotion engine prioritizes multiple generated candidate plans based on the user's current emotional state, with plans that induce positive emotions being given a higher rating.

[1024] Step 9:

[1025] server

[1026] The emotion engine evaluates the plan to find the most suitable one. For example, if the user is feeling stressed, a plan that offers a quiet and relaxing environment may be selected.

[1027] Step 10:

[1028] server

[1029] The details of the selected best plan are formatted and sent to the user, including the name of the destination, its location, reviews, and estimated wait time.

[1030] Step 11:

[1031] Terminal

[1032] The user device receives the plan details sent from the server and displays them in a user-friendly format.

[1033] Step 12:

[1034] User

[1035] The user reviews the proposed plan, and if they are satisfied with it, they accept it and register it as a schedule. If they are not satisfied, they press the regenerate button to request a new plan.

[1036] Step 13:

[1037] server

[1038] If regeneration is requested, the same process is performed again to generate and provide a new plan.

[1039] Example 2

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

[1041] Conventional outing plan generation systems provide outing plans based on user input information, but they have the problem of not being able to provide plans that take into account the user's current emotional state. This can result in outing plans that do not match the user's emotional state, which can reduce satisfaction. Another issue is that the information collected is limited, making it difficult to gather enough data to provide a more comprehensive plan.

[1042] 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.

[1043] In this invention, the server includes means for receiving information input by the user and generating an outing plan, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, means for recognizing the emotional state and evaluating the outing plan based on the recognized emotional information, means for generating a plurality of candidate plans based on the collected information and emotional information, evaluating these candidate plans, and selecting an optimal plan, and means for presenting the optimal plan to the user. This makes it possible to provide an outing plan that suits the user's emotional state, thereby increasing user satisfaction.

[1044] "User-entered information" refers to data such as preferences, budget, available time, and current emotional state that a user enters through a dedicated application or web platform.

[1045] An "outing itinerary" is a series of suggested activities and places to visit that are generated based on user input and collected data.

[1046] "Emotional information" is data based on information that recognizes the user's current emotional state.

[1047] "Weather information" is data about the weather on a specified date, and is obtained from a weather forecast service or the like.

[1048] "Seasonal information" is data relating to events associated with specific times and characteristics specific to the season.

[1049] "Local event information" is data related to events held within a specified area.

[1050] "Crowding information" is data on the congestion situation in each area.

[1051] "User review information" is data about past users' ratings and impressions of facilities and events.

[1052] An "emotion engine" is a processing device or software that recognizes the user's emotional state and evaluates outing plans based on that information.

[1053] "Candidate plans" are multiple outing plans that are generated based on the user's input information and collected data.

[1054] The present invention is a system that recognizes the user's current emotional state and proposes an optimal outing plan by utilizing an emotion engine in addition to information input by the user. Hereinafter, an embodiment of the present invention will be described in detail.

[1055] System configuration

[1056] The system mainly consists of the following components:

[1057] 1. User device: A device (smartphone, tablet, PC, etc.) through which the user inputs information, receives plans, and provides feedback on their emotional state.

[1058] 2. Server: The main processing unit that analyzes input information and emotional information from users and generates and evaluates outing plans.

[1059] 3. Database: Stores weather information, seasonal information, local event information, congestion information, user review information, and emotion data and makes them accessible from the server.

[1060] 4. Emotion Engine: An engine that recognizes the user's emotional state and uses that information to help generate and evaluate plans.

[1061] Program processing

[1062] 1. Receiving user input

[1063] User

[1064] The user accesses a dedicated app or web platform and inputs their preferences, budget, available time, and current emotional state, which can be input via text, multiple choice, or voice recognition. This information is then sent by the device to the server.

[1065] 2. Analysis of input information

[1066] server

[1067] The server analyzes the input received from the user to determine the user's preferences, budget, available time, and current emotional state.

[1068] 3. Data collection

[1069] server

[1070] The server collects the following information from the database:

[1071] Weather information: Weather on a specified date

[1072] Seasonal information: Events and seasonal features

[1073] Local event information: Information on events held in designated areas

[1074] Congestion information: Congestion levels in various areas

[1075] User review information: Reviews from past users

[1076] Emotional data: Evaluating past user emotional information and related plans

[1077] 4. Generating Multiple Candidate Plans

[1078] server

[1079] Based on the collected information, the server generates multiple candidate plans that match the user's input information and emotional information.

[1080] 5. Evaluation and selection of plans

[1081] Emotion Engine

[1082] The emotion engine evaluates multiple candidate plans based on the user's current emotional state. Emotional information is taken into account as an important factor in the evaluation. Plans that induce positive emotions are given a higher rating.

[1083] server

[1084] The most suitable plan is selected based on the evaluation results of the emotion engine.

[1085] 6. Presenting the plan

[1086] server

[1087] The details of the selected best plan are formatted and sent to the user, including a specific schedule and details of the destinations (names, addresses, reviews, estimated wait times).

[1088] Terminal

[1089] The user terminal receives the plan details sent from the server and displays them in a user-friendly format.

[1090] Specific examples

[1091] Consider the following real-world scenario:

[1092] example

[1093] On a Saturday afternoon, a user opens the app and enters the following information:

[1094] Likes: Cafes, art museums

[1095] Budget: 5,000 yen

[1096] Available time: 3 hours

[1097] Emotional state: Feeling stressed

[1098] Prompt Sentence Examples

[1099] "When the user inputs their emotional state, the server generates the optimal outing plan based on that information."

[1100] "Use the emotion engine to evaluate and select plans that elicit positive emotions from users."

[1101] "Create an outing plan based on the specified criteria and send it to the user."

[1102] In this way, users can plan trips that are both efficient and emotionally satisfying. The system automatically provides optimal trip plans by taking into account weather, seasons, events, crowding levels, reviews, and users' emotional information.

[1103] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1104] System program processing flow

[1105] Step 1:

[1106] Receiving user input

[1107] Subject: User

[1108] The user accesses a dedicated app or web platform and enters their preferences, budget, available time, and current emotional state. The entered information is sent from the device to the server by pressing the send button. Specifically, the user opens the smartphone app, enters information into the displayed form, and clicks the send button. At this time, when the input is submitted, the device sends the data to the server.

[1109] Inputs: User preferences, budget, available time, emotional state

[1110] Output: User input information is sent to the server

[1111] Step 2:

[1112] Analysis of input information

[1113] Subject: Server

[1114] The server analyzes the received user input information. Specifically, it extracts information and categorizes it into categories such as preferences, budget, available time, and emotional state. This information is temporarily stored for use in the next processing step. The server then performs the appropriate data conversion and database storage for analysis.

[1115] Input: User-entered information

[1116] Output: Preferences, budget, available time, and emotional state are identified and stored in a temporary database

[1117] Step 3:

[1118] Data collection

[1119] Subject: Server

[1120] The server accesses the database and collects the following information:

[1121] Weather information: Data from the weather API

[1122] Seasonal information: Data about events occurring at specific times

[1123] Local event information: Information on events held in designated areas

[1124] Congestion information: Real-time congestion status

[1125] User review information: Past user reviews

[1126] Emotion data: Past emotional information and related evaluation information of plans

[1127] The server collects this information by running SQL queries against a database and stores it in temporary data storage.

[1128] Input: User-entered information stored in a temporary database

[1129] Output: Collected weather information, seasonal information, local event information, congestion information, user review information, emotion data

[1130] Step 4:

[1131] Generate multiple candidate plans

[1132] Subject: Server

[1133] The server generates multiple candidate plans based on the collected data and user input, including the names, addresses, travel time, budget, etc. The server uses an appropriate algorithm to evaluate the relevance of the data and generate multiple candidate plans.

[1134] Input: Parsed user input information, collected data

[1135] Output: Multiple candidate plans (destination names, addresses, travel time, budget, etc.)

[1136] Step 5:

[1137] Plan evaluation and selection

[1138] Subject: Emotion Engine and Server

[1139] The emotion engine evaluates the generated candidate plans based on the user's current emotional state. This evaluation emphasizes factors that elicit positive emotions from the user. The server selects the optimal plan based on the emotion engine's evaluation results.

[1140] Input: Multiple candidate plans, emotion information

[1141] Output: Evaluated candidate plans and selection of the best plan

[1142] Step 6:

[1143] Presenting the plan

[1144] Subject: Server and Terminal

[1145] The server formats the details of the selected optimal plan and sends it to the user. The plan includes a specific schedule and details of the destinations (names, addresses, reviews, expected waiting times). The user's device then receives the plan details sent from the server and displays them in a user-friendly format.

[1146] Input: Optimal plan

[1147] Output: Plan details displayed on the user's terminal

[1148] In this way, users can plan trips that are both efficient and emotionally satisfying. The system automatically provides optimal trip plans by taking into account weather, seasons, events, crowding levels, reviews, and users' emotional information.

[1149] (Application example 2)

[1150] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1151] Conventional outing plan generation systems generate plans based on basic user information, but do not take the user's emotional state into consideration, making it difficult to provide a truly satisfying plan for the user. Furthermore, they do not suggest specific products or services, making it difficult to provide a shopping experience that is optimal for the user's current emotional state.

[1152] 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.

[1153] In this invention, the server includes means for receiving input information from a user and generating an outing plan based on the input information, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, means for generating a plurality of candidate plans based on the collected information and evaluating these candidate plans to select an optimal plan, means for analyzing the user's emotional state and suggesting products and services optimal for that emotional state, and means for presenting the optimal plan and the suggested products and services to the user, thereby enabling optimal outing plans and shopping suggestions tailored to the user's emotional state.

[1154] "User Input" means information that a User provides through an application or web platform, such as personal preferences, available time, budget, or emotional state.

[1155] An "outing plan" is an action plan that suggests places to visit and a schedule based on conditions specified by the user.

[1156] "Climate information" refers to meteorological data such as weather, temperature, and precipitation at a specific date, time, and location.

[1157] "Seasonal information" is data about events and activities related to a particular season and the characteristics specific to that season.

[1158] "Regional event information" is information about various events held in a specified region.

[1159] "Crowding level information" is data that indicates the congestion level of a specific location or event.

[1160] "User review information" refers to data regarding the ratings and opinions of past users on services and products provided.

[1161] "Emotional state" refers to the user's current mental and psychological state (e.g., stress, happiness, fatigue).

[1162] An "emotion engine" is a system that analyzes the user's input information and behavioral data to recognize their current emotional state and make suggestions and evaluations based on that.

[1163] "Goods and Services" refers to the tangible goods and activities and services available to you.

[1164] A "shopping platform" is a platform for purchasing and proposing products and services online.

[1165] This invention is a system that utilizes an emotion engine to recognize the user's current emotional state in addition to input information from the user, and then suggests outing plans, products, and services. This system is composed of the following elements:

[1166] System configuration

[1167] 1. User Device

[1168] A device where a user enters information and receives proposed plans and products. Examples include smartphones, tablets, and PCs.

[1169] 2. Server

[1170] It is the main processing device that analyzes input information and emotional information from users and generates outing plans, products and services.

[1171] 3. Database

[1172] Weather information, seasonal information, local event information, congestion information, user review information, and emotion data are stored and made accessible from a server.

[1173] 4. Emotion Engine

[1174] It is an engine that recognizes the user's emotional state and uses that information to generate and evaluate plans and suggest products and services. Specific examples include Azure Cognitive Services and IBM Watson.

[1175] Program processing

[1176] Receiving user input

[1177] Users access a dedicated app or web platform and enter their preferences, budget, available time, and their current emotional state, which can be entered via text, multiple choice, or voice recognition. This information is then sent to the server by the device.

[1178] Analysis of input information

[1179] The server analyzes the input and emotional information received from the user to determine the user's preferences, available time, budget, and current emotional state.

[1180] Data collection

[1181] The server collects the following information from the database:

[1182] Weather information: Weather on the specified date.

[1183] Seasonal information: Events that occur at specific times or features specific to the season.

[1184] Local event information: Information about events taking place in a specified area.

[1185] Congestion information: Congestion levels in various locations.

[1186] User review information: Reviews from past users.

[1187] Emotional data: Past user emotional information and associated plan evaluations.

[1188] Proposing multiple candidate plans and products / services

[1189] Based on the collected information, the server generates multiple candidate plans and products / services that match the user's input information and emotional information, while simultaneously proposing optimal products and services according to the user's emotional state.

[1190] Evaluating and selecting plans, products and services

[1191] The emotion engine evaluates multiple candidate plans and products / services based on the user's current emotional state. Emotional information is taken into account as an important factor in the evaluation. Plans and product proposals that induce positive emotions are given higher ratings.

[1192] Offering plans, products and services

[1193] The server formats the most suitable plan and product / service details and sends them to the user. The plan includes a specific schedule and details of the destinations (name, address, reviews, expected waiting time). The user's device receives the plan and product / service details sent from the server and displays them in a user-friendly format.

[1194] Specific examples

[1195] On a Saturday afternoon, a user opens the app and enters the following information:

[1196] Likes: Cafes, art museums

[1197] Budget: 5,000 yen

[1198] Available time: 3 hours

[1199] Emotional state: Feeling stressed

[1200] The server analyzes this information and collects related data from the database.The server then uses an emotion engine to suggest plans and products that will help reduce stress (for example, relaxation goods or aroma candles).Examples of plans, products, and services that are best suited to the user include the following:

[1201] The plan: Relax for an hour at a quiet cafe in front of the station, then spend two hours visiting a special exhibition at the museum.

[1202] Products: Relaxation items, aroma candles, herbal tea.

[1203] Example prompts for generative AI models

[1204] "My emotional state is 'stressed'. Please suggest products that would be best suited to this state."

[1205] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1206] Step 1:

[1207] Receiving user input

[1208] The user opens the application or web platform and enters information such as their preferences for cafes, museums, etc., their budget (e.g., 5,000 yen), the amount of time available (e.g., 3 hours), and their current emotional state (e.g., feeling stressed). This information is then sent by the device to the server.

[1209] Inputs: User preferences, budget, available time, emotional state

[1210] Output: User input sent to the server

[1211] Step 2:

[1212] Analysis of input information

[1213] The server analyzes the received user input to determine the user's preferences, budget, available time, and emotional state, taking into account past user behavior and emotional data from a database.

[1214] Input: User-entered information

[1215] Output: Analyzed user preferences, budget, available time, emotional state

[1216] Step 3:

[1217] Data collection

[1218] Based on the analyzed user information, the server collects weather information, seasonal information, local event information, congestion information, user review information, and emotion data from the database, which will later serve as the basis for plans and products.

[1219] Input: Analyzed user preferences, budget, available time, emotional state

[1220] Output: Collected weather information, seasonal information, local event information, crowding information, user review information, and sentiment data

[1221] Step 4:

[1222] Generate multiple candidate plans and products / services

[1223] The server generates multiple candidate plans and products / services based on the collected data and matched to the user's input and emotional information. For example, if the user is feeling stressed, the plan may include a quiet cafe where they can relax or recommended relaxation products.

[1224] Input: Collected information and the user's emotional state

[1225] Output: Multiple candidate plans and products / services

[1226] Step 5:

[1227] Evaluating and selecting plans, products and services

[1228] The emotion engine evaluates the generated multiple candidate plans and products / services based on the user's emotional state. Plans and product proposals that induce positive emotions are given higher ratings. The server selects the most suitable plan, product, or service based on the evaluation results.

[1229] Input: Multiple candidate plans and products / services

[1230] Output: Optimal plans and products / services based on emotional state

[1231] Step 6:

[1232] Offering plans, products and services

[1233] The server formats the details of the selected optimal plan and products / services and sends them to the user's device. The device receives this and displays it in a format that is easy for the user to understand. For example, the plan schedule and recommended products are displayed on the smartphone screen.

[1234] Input: Best plan and product / service

[1235] Output: Plan and product / service details displayed on the user's device

[1236] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1237] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1238] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1239] [Third embodiment]

[1240] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1241] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1242] 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).

[1243] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1244] 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.

[1245] 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).

[1246] 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.

[1247] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1248] 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.

[1249] 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.

[1250] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1251] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1252] The present invention is a system that proposes optimal outing plans based on a user's input of their preferences, budget, and available time. Hereinafter, an embodiment of the present invention will be described in detail.

[1253] System configuration

[1254] The system mainly consists of the following components:

[1255] 1. User device: The device (smartphone, tablet, PC, etc.) through which the user enters information and receives the plan.

[1256] 2. Server: The main processing unit that analyzes the input information from the user and generates and evaluates the trip plan.

[1257] 3. Database: Stores weather information, seasonal information, local event information, congestion information, and user review information and makes it accessible from the server.

[1258] Program processing

[1259] 1. Receiving user input

[1260] User

[1261] The user accesses a dedicated app or web platform and enters information such as preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), etc. This information is sent to the server by the device.

[1262] 2. Analysis of input information

[1263] server

[1264] The server analyzes the input information received from the user, which determines the user's preferences, available time, and budget.

[1265] 3. Data collection

[1266] server

[1267] The server collects the following information from the database:

[1268] Weather information: Weather on the specified date.

[1269] Seasonal information: Characteristic events at specific times.

[1270] Local Event Information: Public events in designated areas.

[1271] Congestion information: Congestion levels in various locations.

[1272] User review information: Past user reviews.

[1273] 4. Generating multiple candidate plans

[1274] server

[1275] The server generates multiple itineraries based on the collected information, matching the user's input information. For example, the following itineraries may be generated:

[1276] Option 1: Relax for an hour at a cafe in front of the station, then spend two hours visiting a special exhibition at the art museum.

[1277] Option 2: Spend 1.5 hours at a cafe downtown, then spend 1.5 hours touring the art museum.

[1278] 5. Plan Evaluation and Selection

[1279] server

[1280] The generated candidate plans are evaluated. The evaluation includes comprehensive information on weather, season, local events, congestion, and user reviews. The most suitable plan is selected from the evaluation results.

[1281] 6. Presenting the plan

[1282] server

[1283] The best plan is then formatted and sent to the user, including a specific schedule and details of the destinations (names, addresses, reviews, and estimated wait times).

[1284] Terminal

[1285] The user's terminal displays the plan details received from the server, and the user can plan their outing according to this plan.

[1286] Specific examples

[1287] Consider the following real-world scenario:

[1288] example

[1289] On a Saturday afternoon, a user opens the app and enters the following information:

[1290] Likes: Cafes, art museums

[1291] Budget: 5,000 yen

[1292] Available time: 3 hours

[1293] Receiving user input

[1294] The user enters the above information and presses the send button. The device sends the information to the server.

[1295] Analysis of input information

[1296] The server analyzes your preferences, availability, and budget and begins to collect data based on this information.

[1297] Data collection

[1298] The server gathers from a database information about Saturday's weather (clear), the museum's fall special exhibitions, the area's crowd level (relatively low), and relevant user reviews.

[1299] Generate multiple candidate plans

[1300] Based on the data collected, the server generates a plan like this:

[1301] Option 1: Relax for an hour at Cafe A in front of the station, then spend two hours visiting a special exhibition at Museum B.

[1302] Option 2: Spend 1.5 hours at Cafe C in the downtown area, then visit Museum D for 1.5 hours.

[1303] Plan evaluation and selection

[1304] The server evaluates the candidate plans and selects the best one. For example, candidate 1 is determined to be the best.

[1305] Presenting the plan

[1306] The server sends details of the optimal plan to the user's device, which displays it.

[1307] In this way, users can plan their outings efficiently and enjoyably. The system automatically provides the best plan, taking into account weather, season, events, crowd levels, and reviews.

[1308] The processing flow will be explained below.

[1309] Step 1:

[1310] Terminal

[1311] The user accesses a dedicated app or web platform and enters information such as preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), etc. Once the information is complete, the user presses the submit button.

[1312] Step 2:

[1313] Terminal

[1314] The information entered by the user is sent to the server, including preferred activities, available time, and budget.

[1315] Step 3:

[1316] server

[1317] The server analyzes the input information received from the user to determine the user's preferences, available time, and budget.

[1318] Step 4:

[1319] server

[1320] The server collects weather information, seasonal information, local event information, crowding information, and user reviews from a database.

[1321] Step 5:

[1322] Obtaining weather information: The server collects weather information for the specified date.

[1323] Acquisition of seasonal information: The server collects events at specific times and characteristics specific to the season.

[1324] Acquisition of local event information: The server collects information about events held in a specified area.

[1325] Obtaining congestion information: The server collects congestion information for each location.

[1326] Obtaining user review information: The server collects relevant past user reviews.

[1327] Step 6:

[1328] server

[1329] Based on the collected information, the server generates multiple candidate plans that match the user's input information. The generated plans reflect the user's preferred activities and time allocation within the user's budget.

[1330] Step 7:

[1331] server

[1332] Each candidate plan will be evaluated, taking into consideration the following factors:

[1333] Local Weather

[1334] Seasonal Events

[1335] Local Events

[1336] Congestion level

[1337] User reviews

[1338] Step 8:

[1339] server

[1340] Based on the evaluation results, the most appropriate plan is selected. For example, the following plan may be determined to be optimal:

[1341] Relax for an hour at a cafe in front of the station, then spend two hours visiting the museum's special exhibition.

[1342] Step 9:

[1343] server

[1344] Format details of the selected best plan, including the name of the destination, its location, reviews, and estimated wait time.

[1345] Step 10:

[1346] server

[1347] The server sends details of the best plan to the user's device.

[1348] Step 11:

[1349] Terminal

[1350] The user device receives the plan details sent from the server and displays them in a user-friendly format.

[1351] Step 12:

[1352] User

[1353] The user reviews the proposed plan, and if they are satisfied with it, they accept it and register it as a schedule. If they are not satisfied, they press the regenerate button to request a new plan.

[1354] Step 13:

[1355] server

[1356] If regeneration is requested, the same process is performed again to generate and provide a new plan.

[1357] Example 1

[1358] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1359] Conventional outing planning systems have difficulty providing optimal plans that fully consider individual requirements such as user preferences, budget, and available time. Furthermore, they are unable to generate outing plans by comprehensively evaluating environmental information such as weather and event crowding, which prevents them from increasing user satisfaction. To solve these problems, a system capable of more advanced information analysis and appropriate plan generation is needed.

[1360] 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.

[1361] In this invention, the server includes means for receiving user input information and generating an outing plan based on the input information, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, means for generating multiple candidate plans based on the collected information and evaluating the candidate plans to select an optimal plan, means for presenting the optimal plan to the user, means for analyzing the user input information and identifying preferences, budget, and available time, means for collecting related information from a database based on the identified information, means for evaluating the multiple generated candidate plans and selecting an optimal plan based on an overall evaluation score, means for sending details of the selected plan to the user terminal and displaying the details to the user, means for evaluating and optimizing the outing plan using a generative AI model, and means for inputting prompt sentences into the generative AI model to generate an outing plan. This makes it possible to provide an optimal outing plan by comprehensively evaluating individual requirements based on the user input information and environmental information.

[1362] "User-entered information" is data such as preferences, budget, and available time that a user inputs into the system.

[1363] An "outing plan" is a proposal that includes the user's outing schedule and details of places to visit, generated based on the user's input information and collected environmental information.

[1364] "Weather information" is weather forecast data for a specified date.

[1365] "Seasonal information" is information about events and unique activities related to a particular time of year.

[1366] "Local event information" is information about public events held in a specific local area.

[1367] "Crowding level information" is information about the congestion status of a specific area or facility.

[1368] "User review information" refers to reviews and ratings provided by other users in the past.

[1369] The "multiple candidate plans" are multiple outing suggestions generated based on the user's input information and the collected environmental information.

[1370] The "optimal plan" is the most suitable outing plan selected from multiple candidate plans by comprehensively evaluating the user's requirements and environmental information.

[1371] A "generative AI model" is an artificial intelligence model that generates and optimizes outing plans based on user input information and collected environmental information.

[1372] A "prompt sentence" is an instruction sentence that is input to the generative AI model to generate an outing plan.

[1373] MODE FOR CARRYING OUT THE INVENTION

[1374] The present invention relates to a system that proposes optimal outing plans by allowing a user to input their preferences, budget, and available time. Hereinafter, an embodiment of the present invention will be described in detail.

[1375] System configuration

[1376] The system mainly consists of the following components:

[1377] 1. User device: The device (smartphone, tablet, PC, etc.) through which the user enters information and receives travel plans.

[1378] 2. Server: The main processing unit that analyzes input information from users and generates and evaluates outing plans.

[1379] 3. Database: Stores weather information, seasonal information, local event information, congestion information, and user review information and makes it accessible from the server.

[1380] Program processing

[1381] 1. Receiving user input

[1382] A user accesses a dedicated app or web platform and enters information such as preferences (e.g., cafes, museums), budget (e.g., 5,000 yen), available time (e.g., 3 hours), etc. This information is sent to the server using a reactive form or HTTP request.

[1383] 2. Analysis of input information

[1384] The server parses the input information it receives using a script written in Python or JavaScript that parses the JSON data to identify the user's preferences, budget, and available time.

[1385] 3. Data collection

[1386] The server connects to a database or external API to gather the necessary information, for example using SQL queries to get the following information:

[1387] Climate information: Weather forecast for a specific date

[1388] Seasonal information: Events related to the current season

[1389] Local Event Information: Public events in designated areas

[1390] Congestion information: Congestion status of designated areas

[1391] User review information: reviews and ratings from other users

[1392] 4. Generating candidate plans

[1393] The server generates multiple itineraries based on the collected information, using an algorithm to generate the following itineraries:

[1394] Option 1: Relax for an hour at Cafe A in front of the station, then spend two hours visiting a special exhibition at Museum B.

[1395] Option 2: Spend 1.5 hours at Cafe C in the downtown area and then visit Museum D for 1.5 hours.

[1396] 5. Evaluation and selection of plans

[1397] The server evaluates the generated candidate plans, using a comprehensive set of information including weather, season, local events, congestion, and user reviews.

[1398] The server selects the optimal plan based on the overall evaluation points.

[1399] 6. Presenting the plan

[1400] The server sends the details of the optimal plan to the user's device, which then displays the information, allowing the user to plan their outing according to the plan provided.

[1401] Specific examples

[1402] For example, on a Saturday afternoon, a user opens the app and enters the following information:

[1403] Likes: Cafes, art museums

[1404] Budget: 5,000 yen

[1405] Available time: 3 hours

[1406] Once the user submits their input, the device sends the information to a server, which analyzes the user's preferences, budget, and available time, and then gathers relevant data from a database or external API, such as sunny weather information, special museum exhibitions, local congestion levels, and past user reviews.

[1407] The server then generates multiple candidate plans based on this data, evaluates the plans, selects the plan with the highest evaluation points, formats the specific schedule and details of the places to visit, and sends it to the user's device.

[1408] Prompt Sentence Examples

[1409] Examples of prompts for generative AI models include:

[1410] "The user is looking for a 3-hour outing plan with a budget of 5000 yen, where the user prefers cafes and museums on a Saturday afternoon. Generate multiple possible outing plans, and then rate and present the best plan. Information to consider includes weather forecasts, seasonal events, local public events, crowd data, and user reviews."

[1411] This makes it possible to provide users with optimal outing plans.

[1412] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1413] Step 1:

[1414] Receiving user input

[1415] Users access a dedicated app or web platform and enter their preferences, budget, and available time.

[1416] Specific operation: The user enters their preferences (e.g., "cafe, museum"), their budget (5,000 yen), and the duration (3 hours) into the form, then presses the submit button.

[1417] The terminal receives this input information and sends it to the server.

[1418] Specific operation: Sends input data to the server as an HTTP POST request.

[1419] Input (device): User preferences, budget, and available time.

[1420] Output (Terminal → Server): HTTP request containing input information.

[1421] Step 2:

[1422] Analysis of input information

[1423] The server analyzes the received input information.

[1424] What it does: The server runs a parsing script written in Python or JavaScript that parses the JSON data and stores preferences, budget, and available time in separate variables.

[1425] Input (server): JSON data containing user input information.

[1426] Output (server): Parsed individual variables (preferences, budget, available time).

[1427] Step 3:

[1428] Data collection

[1429] The server connects to a database or external API to collect the necessary information.

[1430] What it does: It uses SQL queries and API requests to retrieve the following information:

[1431] Weather information: Get the weather forecast for the specified date from the API.

[1432] Seasonal information: Retrieves events related to the current season from the database.

[1433] Local Event Information: Retrieve public events in a specified area from a database or API.

[1434] Congestion information: Obtain the congestion status of the specified area from the API.

[1435] User review information: Retrieve other users' reviews and ratings from our database.

[1436] Input (server): Parsed user input information.

[1437] Output (server): Collected data (weather information, seasonal information, local event information, congestion information, user review information).

[1438] Step 4:

[1439] Generate candidate plans

[1440] The server generates multiple outing plans based on the collected information.

[1441] What it does: It uses an algorithm to generate a list of plans based on your preferences, budget, and availability. For example, it might generate plans like this:

[1442] Option 1: Relax for an hour at a cafe in front of the station, then spend two hours visiting a special exhibition at the museum.

[1443] Option 2: Spend 1.5 hours at a cafe downtown and 1.5 hours visiting the art museum.

[1444] Input (Server): Collected data and analyzed user input information.

[1445] Output (server): Multiple candidate plans generated.

[1446] Step 5:

[1447] Plan evaluation and selection

[1448] The server evaluates the generated candidate plans.

[1449] Specific operation: Calculates rating points for each plan. These rating points are calculated taking into account weather information, seasonal information, local event information, crowding information, and user reviews. For example, visiting an art museum on a sunny day will earn you a high rating point.

[1450] The server selects the optimal plan from the evaluation results.

[1451] Specific operation: Select the plan with the highest overall evaluation points.

[1452] Input (server): Multiple generated candidate plans.

[1453] Output (server): Optimal plan.

[1454] Step 6:

[1455] Presenting the plan

[1456] The server sends the details of the selected optimal plan to the user terminal,

[1457] Specific operation: The details of the selected plan (schedule, details of destinations) are formatted in HTML or JSON format and sent as an HTTP response.

[1458] The terminal displays the plan details received from the server.

[1459] Specific behavior: Provides the user with visual details of the plan according to a display format.

[1460] Input (server → terminal): Details of the optimal plan.

[1461] Output (terminal): Displayed outing plan.

[1462] By following these steps, users can plan their outings efficiently and enjoyably.

[1463] (Application example 1)

[1464] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1465] In today's world, users often find it difficult to efficiently find personalized content that meets their preferences. Furthermore, there are no systems that suggest optimal content based on available viewing time or device type, so users must search for the appropriate content themselves, which is time-consuming. To solve this problem, a system is needed that can automatically generate and suggest personalized content plans based on user input.

[1466] 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.

[1467] In this invention, the server includes means for receiving user input information and generating a personalized content plan based on the input information, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, and means for generating multiple candidate plans based on the collected information and evaluating these candidate plans to select an optimal content plan. This makes it possible to efficiently propose an optimal content plan based on the user's preferences, available viewing time, and device used.

[1468] "User input information" refers to information entered by the user, such as preferences, available viewing times, and device type.

[1469] A "personalized content plan" is a customized recommendation of content such as movies, music, articles, etc. based on user input information.

[1470] "Climate information" is data about weather collected from outside.

[1471] "Seasonal information" is information about events and general activities associated with a particular time of year.

[1472] "Local event information" is information about events and occasions held in a specific local area.

[1473] "Crowding level information" is information about the congestion level of a specific location or event.

[1474] "User review information" refers to ratings and opinions from other users regarding services and content provided in the past.

[1475] "Server" is the primary processing unit that analyzes user input, generates personalized content plans, and collects and evaluates information.

[1476] "Device" refers to the terminal used by the user, such as a smartphone, smart glasses, or head-mounted display.

[1477] "Analysis" means deciphering the information entered by the user and performing appropriate processing based on that content.

[1478] The "optimal plan" is the plan that best meets the user's requirements from among multiple candidate plans.

[1479] "Evaluation" is the process of comparing the generated candidate plans and selecting the plan that best suits the user's requirements.

[1480] This invention is a system that proposes personalized content plans based on user preferences, available viewing times, and devices. This system is composed of a user terminal, a server, and a database.

[1481] System configuration

[1482] 1. User Device:

[1483] To input information, users use devices such as smartphones, smart glasses, and head-mounted displays, which then send the input information, such as user preferences, available viewing time, and the type of device used, to a server.

[1484] 2. Server:

[1485] The server receives user input information, analyzes it, and generates the optimal content plan. It uses a Python server program, an SQL database, and the Flask framework that provides a REST API. The server performs the following processes:

[1486] Analyzes user input to determine preferred content, viewing times, and devices.

[1487] Relevant information (weather information, seasonal information, local event information, congestion information, user review information) is collected from the database.

[1488] Based on the collected information, multiple candidate plans are generated and the optimal plan is selected after evaluation.

[1489] The selected optimal content plan is sent to the user's device.

[1490] 3. Database:

[1491] The database stores weather information, seasonal information, local event information, congestion information, and user review information and makes them accessible from the server.

[1492] Program processing explanation

[1493] Hardware and Software Used

[1494] Hardware: Smartphones, smart glasses, head-mounted displays

[1495] Software: Python, SQL database, Flask framework

[1496] Data processing and calculation

[1497] 1. Analysis of input information:

[1498] The server analyzes data entered by the user, such as preferred content, available viewing time, and device type, thereby identifying the user's preferences, available viewing time, and device type.

[1499] 2. Data Collection:

[1500] The server collects information from the database about the weather, seasons, local events, crowding levels, and user reviews, providing users with the latest information that meets their requirements in real time.

[1501] 3. Generate and evaluate candidate plans:

[1502] The server generates multiple candidate content plans based on the collected information, evaluates each plan to best match the user's preferences, available viewing time, and other conditions, and selects the optimal plan.

[1503] 4. Present the plan:

[1504] The server sends the details of the selected optimal plan (e.g., movie title, album name, viewing time, rating, etc.) to the user's device, which displays it on the screen and allows the user to watch the suggested content.

[1505] Specific examples

[1506] As an example, consider the following scenario:

[1507] User Input:

[1508] Favorites: Action movies, rock music

[1509] Viewing time: 2 hours

[1510] Device: Smartphone

[1511] The user opens the app and enters the above information. The device sends the information to the server, which then uses it to gather relevant data from its database. The server then generates a content plan that looks like this:

[1512] Option 1: Watch a 1.5 hour action movie, a 30 minute rock album

[1513] Nominations: 2.50 minute action short films, 1.5 hour documentaries

[1514] The server evaluates these candidate plans and selects the best plan (e.g., candidate 1 is determined to be the best), then sends details of the best plan to the user's device, which displays it.

[1515] Examples of prompts for generative AI models

[1516] "Generate the optimal content plan based on the user's preferences, available viewing time, and device they are using. The user's preferences are 'action movies' and 'rock music'. The available viewing time is 2 hours. The device is a smartphone."

[1517] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1518] Step 1:

[1519] The device accepts user input of preferences, available viewing time, and device type. The device receives the user input and sends it to the server. The input includes preferences (e.g., action movies, rock music), available viewing time (e.g., 2 hours), and device (e.g., smartphone). The output is the user input sent to the server.

[1520] Step 2:

[1521] The server receives user input information sent from the device. The received data includes user preferences, available viewing time, and device type. This data is analyzed to identify user preferences and conditions. The input is the user input information, and the output is the analyzed user preferences, available viewing time, and device type.

[1522] Step 3:

[1523] The server collects relevant information (weather information, seasonal information, local event information, congestion information, and user review information) from the database. The input is the analyzed user conditions, and an SQL query is executed to retrieve the required data based on those conditions. The output is the collected weather information, seasonal information, local event information, congestion information, and user review information.

[1524] Step 4:

[1525] The server generates multiple candidate content plans based on the collected information. Specifically, it creates plans by combining appropriate movies, music, articles, etc. based on the user's preferences and available viewing time. The input includes the collected information and the user's conditions, and the output is the generated multiple candidate plans.

[1526] Step 5:

[1527] The server evaluates the generated multiple candidate plans and selects the optimal content plan. The evaluation takes into consideration a comprehensive range of factors, including user preferences, available viewing times, weather information, seasonal information, local event information, congestion information, and user reviews. The input is multiple candidate plans, and the output is the evaluated optimal content plan.

[1528] Step 6:

[1529] The server formats and sends details of the optimal content plan to the user's device, including the content title, viewing time, rating, etc. The input is the optimal plan that has been evaluated, and the output is the detailed information of the plan to be sent.

[1530] Step 7:

[1531] The terminal displays the details of the optimal content plan received from the server to the user. The user can watch movies, music, articles, etc. according to the proposed content plan. The input is the detailed plan information sent from the server, and the output is the detailed content plan displayed to the user.

[1532] In this way, the system can provide the user with the most suitable content plan.

[1533] 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.

[1534] The present invention is a system that recognizes the user's current emotional state by utilizing an emotion engine in addition to information input by the user, and proposes an optimal outing plan. Hereinafter, an embodiment of the present invention will be described in detail.

[1535] System configuration

[1536] The system mainly consists of the following components:

[1537] 1. User device: A device (smartphone, tablet, PC, etc.) through which the user inputs information, receives plans, and provides feedback on their emotional state.

[1538] 2. Server: The main processing unit that analyzes input information and emotional information from users and generates and evaluates outing plans.

[1539] 3. Database: Stores weather information, seasonal information, local event information, crowding information, user review information, and sentiment data and makes them accessible from the server.

[1540] 4. Emotion Engine: An engine that recognizes the user's emotional state and uses that information to help generate and evaluate plans.

[1541] Program processing

[1542] 1. Receiving user input

[1543] User

[1544] The user accesses a dedicated app or web platform and inputs their preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), and their current emotional state. The emotional state can be input using text, multiple-choice format, or voice recognition. This information is sent to the server by the device.

[1545] 2. Analysis of input information

[1546] server

[1547] The server analyzes the input and emotional information received from the user to determine the user's preferences, available time, budget, and current emotional state.

[1548] 3. Data collection

[1549] server

[1550] The server collects the following information from the database:

[1551] Weather information: Weather on the specified date.

[1552] Seasonal information: Events that occur at specific times or features specific to the season.

[1553] Local event information: Information about events taking place in a specified area.

[1554] Congestion information: Congestion levels in various locations.

[1555] User review information: Reviews from past users.

[1556] Emotional data: Past user emotional information and associated plan evaluations.

[1557] 4. Generating multiple candidate plans

[1558] server

[1559] Based on the collected information, the server generates multiple candidate plans that match the user's input and emotional information. For example, the following plans are generated:

[1560] Option 1: Relax for an hour at a cafe in front of the station, then spend two hours visiting a special exhibition at the museum.

[1561] Option 2: Spend 1.5 hours at a cafe in the downtown area, then spend 1.5 hours touring the art museum.

[1562] 5. Plan Evaluation and Selection

[1563] Emotion Engine

[1564] The emotion engine evaluates multiple candidate plans based on the user's current emotional state. Emotional information is taken into account as an important factor in the evaluation. Plans that induce positive emotions are given a higher rating.

[1565] server

[1566] The most suitable plan is selected based on the evaluation results of the emotion engine. For example, if the user is looking to relax, a plan that includes spending time in a quiet cafe may be selected.

[1567] 6. Presenting the plan

[1568] server

[1569] The details of the selected best plan are formatted and sent to the user, including a specific schedule and details of the destinations (names, addresses, reviews, estimated wait times).

[1570] Terminal

[1571] The user device receives the plan details sent from the server and displays them in a user-friendly format.

[1572] Specific examples

[1573] Consider the following real-world scenario:

[1574] example

[1575] On a Saturday afternoon, a user opens the app and enters the following information:

[1576] Likes: Cafes, art museums

[1577] Budget: 5,000 yen

[1578] Available time: 3 hours

[1579] Emotional state: Feeling stressed

[1580] Receiving User Input

[1581] The user enters the above information and presses the send button. The device sends the information to the server.

[1582] Analysis of input information

[1583] The server analyzes your preferences, available time, budget, and emotional state, and begins to collect data based on this information.

[1584] Data collection

[1585] The server collects information from a database about Saturday's weather (sunny), the museum's fall special exhibition, the area's crowd level (relatively low), relevant user reviews, and sentiment data.

[1586] Generate multiple candidate plans

[1587] The server generates a plan based on the collected data and emotional information, such as:

[1588] Option 1: Relax for an hour at a quiet cafe A in front of the station, then spend two hours visiting a special exhibition at museum B.

[1589] Option 2: Spend 1.5 hours at the highly satisfying Cafe C in the downtown area, then spend 1.5 hours touring Museum D.

[1590] Plan evaluation and selection

[1591] The emotion engine evaluates the candidate plans and determines that candidate 1 is the best, as it provides a quiet environment that helps reduce stress.

[1592] Presenting the plan

[1593] The server sends details of the best plan to the user's device, which displays it.

[1594] In this way, users can plan trips that are both efficient and emotionally satisfying. The system automatically provides the optimal plan by taking into account weather, season, events, crowding, reviews, and user emotional information.

[1595] The processing flow will be explained below.

[1596] Step 1:

[1597] User

[1598] Users access a dedicated app or web platform and enter their preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), and current emotional state (e.g., feeling stressed). After entering this information, they press the send button.

[1599] Step 2:

[1600] Terminal

[1601] The information entered by the user is sent to a server, including preferred activities, available time, budget, and emotional state.

[1602] Step 3:

[1603] server

[1604] The server analyzes the input and emotional information received from the user to determine the user's preferences, available time, budget, and emotional state.

[1605] Step 4:

[1606] server

[1607] The server collects weather information, seasonal information, local event information, congestion information, and user review information from a database.

[1608] Step 5:

[1609] Obtaining weather information: The server collects weather information for the specified date.

[1610] Acquisition of seasonal information: The server collects events at specific times and characteristics specific to the season.

[1611] Acquisition of local event information: The server collects information about events held in a specified area.

[1612] Obtaining congestion information: The server collects congestion information for each location.

[1613] Obtaining user review information: The server collects relevant past user reviews.

[1614] Acquiring emotional data: The server collects past user emotional information and associated plan evaluation data.

[1615] Step 6:

[1616] server

[1617] Based on the collected information, the server generates multiple candidate plans that match the user's input and emotional information. The generated plans reflect the user's preferred activities and time allocation within a budget.

[1618] Step 7:

[1619] server

[1620] Each candidate plan will be evaluated, taking into consideration the following factors:

[1621] Local Weather

[1622] Seasonal Events

[1623] Local Events

[1624] Congestion level

[1625] User reviews

[1626] emotional information

[1627] Step 8:

[1628] Emotion Engine

[1629] The emotion engine prioritizes multiple generated candidate plans based on the user's current emotional state, with plans that induce positive emotions being given a higher rating.

[1630] Step 9:

[1631] server

[1632] The emotion engine evaluates the plan to find the most suitable one. For example, if the user is feeling stressed, a plan that offers a quiet and relaxing environment may be selected.

[1633] Step 10:

[1634] server

[1635] The details of the selected best plan are formatted and sent to the user, including the name of the destination, its location, reviews, and estimated wait time.

[1636] Step 11:

[1637] Terminal

[1638] The user device receives the plan details sent from the server and displays them in a user-friendly format.

[1639] Step 12:

[1640] User

[1641] The user reviews the proposed plan, and if they are satisfied with it, they accept it and register it as a schedule. If they are not satisfied, they press the regenerate button to request a new plan.

[1642] Step 13:

[1643] server

[1644] If regeneration is requested, the same process is performed again to generate and provide a new plan.

[1645] Example 2

[1646] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1647] Conventional outing plan generation systems provide outing plans based on user input information, but they have the problem of not being able to provide plans that take into account the user's current emotional state. This can result in outing plans that do not match the user's emotional state, which can reduce satisfaction. Another issue is that the information collected is limited, making it difficult to gather enough data to provide a more comprehensive plan.

[1648] 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.

[1649] In this invention, the server includes means for receiving information input by the user and generating an outing plan, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, means for recognizing the emotional state and evaluating the outing plan based on the recognized emotional information, means for generating a plurality of candidate plans based on the collected information and emotional information, evaluating these candidate plans, and selecting an optimal plan, and means for presenting the optimal plan to the user. This makes it possible to provide an outing plan that suits the user's emotional state, thereby increasing user satisfaction.

[1650] "User-entered information" refers to data such as preferences, budget, available time, and current emotional state that a user enters through a dedicated application or web platform.

[1651] An "outing itinerary" is a series of suggested activities and places to visit that are generated based on user input and collected data.

[1652] "Emotional information" is data based on information that recognizes the user's current emotional state.

[1653] "Weather information" is data about the weather on a specified date, and is obtained from a weather forecast service or the like.

[1654] "Seasonal information" is data relating to events associated with specific times and characteristics specific to the season.

[1655] "Local event information" is data related to events held within a specified area.

[1656] "Crowding information" is data on the congestion situation in each area.

[1657] "User review information" is data about past users' ratings and impressions of facilities and events.

[1658] An "emotion engine" is a processing device or software that recognizes the user's emotional state and evaluates outing plans based on that information.

[1659] "Candidate plans" are multiple outing plans that are generated based on the user's input information and collected data.

[1660] The present invention is a system that recognizes the user's current emotional state and proposes an optimal outing plan by utilizing an emotion engine in addition to information input by the user. Hereinafter, an embodiment of the present invention will be described in detail.

[1661] System configuration

[1662] The system mainly consists of the following components:

[1663] 1. User device: A device (smartphone, tablet, PC, etc.) through which the user inputs information, receives plans, and provides feedback on their emotional state.

[1664] 2. Server: The main processing unit that analyzes input information and emotional information from users and generates and evaluates outing plans.

[1665] 3. Database: Stores weather information, seasonal information, local event information, congestion information, user review information, and emotion data and makes them accessible from the server.

[1666] 4. Emotion Engine: An engine that recognizes the user's emotional state and uses that information to help generate and evaluate plans.

[1667] Program processing

[1668] 1. Receiving user input

[1669] User

[1670] The user accesses a dedicated app or web platform and inputs their preferences, budget, available time, and current emotional state, which can be input via text, multiple choice, or voice recognition. This information is then sent by the device to the server.

[1671] 2. Analysis of input information

[1672] server

[1673] The server analyzes the input received from the user to determine the user's preferences, budget, available time, and current emotional state.

[1674] 3. Data collection

[1675] server

[1676] The server collects the following information from the database:

[1677] Weather information: Weather on a specified date

[1678] Seasonal information: Events and seasonal features

[1679] Local event information: Information on events held in designated areas

[1680] Congestion information: Congestion levels in various areas

[1681] User review information: Reviews from past users

[1682] Emotional data: Evaluating past user emotional information and related plans

[1683] 4. Generating Multiple Candidate Plans

[1684] server

[1685] Based on the collected information, the server generates multiple candidate plans that match the user's input information and emotional information.

[1686] 5. Evaluation and selection of plans

[1687] Emotion Engine

[1688] The emotion engine evaluates multiple candidate plans based on the user's current emotional state. Emotional information is taken into account as an important factor in the evaluation. Plans that induce positive emotions are given a higher rating.

[1689] server

[1690] The most suitable plan is selected based on the evaluation results of the emotion engine.

[1691] 6. Presenting the plan

[1692] server

[1693] The details of the selected best plan are formatted and sent to the user, including a specific schedule and details of the destinations (names, addresses, reviews, estimated wait times).

[1694] Terminal

[1695] The user terminal receives the plan details sent from the server and displays them in a user-friendly format.

[1696] Specific examples

[1697] Consider the following real-world scenario:

[1698] example

[1699] On a Saturday afternoon, a user opens the app and enters the following information:

[1700] Likes: Cafes, art museums

[1701] Budget: 5,000 yen

[1702] Available time: 3 hours

[1703] Emotional state: Feeling stressed

[1704] Prompt Sentence Examples

[1705] "When the user inputs their emotional state, the server generates the optimal outing plan based on that information."

[1706] "Use the emotion engine to evaluate and select plans that elicit positive emotions from users."

[1707] "Create an outing plan based on the specified criteria and send it to the user."

[1708] In this way, users can plan trips that are both efficient and emotionally satisfying. The system automatically provides optimal trip plans by taking into account weather, seasons, events, crowding levels, reviews, and users' emotional information.

[1709] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1710] System program processing flow

[1711] Step 1:

[1712] Receiving user input

[1713] Subject: User

[1714] The user accesses a dedicated app or web platform and enters their preferences, budget, available time, and current emotional state. The entered information is sent from the device to the server by pressing the send button. Specifically, the user opens the smartphone app, enters information into the displayed form, and clicks the send button. At this time, when the input is submitted, the device sends the data to the server.

[1715] Inputs: User preferences, budget, available time, emotional state

[1716] Output: User input information is sent to the server

[1717] Step 2:

[1718] Analysis of input information

[1719] Subject: Server

[1720] The server analyzes the received user input information. Specifically, it extracts information and categorizes it into categories such as preferences, budget, available time, and emotional state. This information is temporarily stored for use in the next processing step. The server then performs the appropriate data conversion and database storage for analysis.

[1721] Input: User-entered information

[1722] Output: Preferences, budget, available time, and emotional state are identified and stored in a temporary database

[1723] Step 3:

[1724] Data collection

[1725] Subject: Server

[1726] The server accesses the database and collects the following information:

[1727] Weather information: Data from the weather API

[1728] Seasonal information: Data about events occurring at specific times

[1729] Local event information: Information on events held in designated areas

[1730] Congestion information: Real-time congestion status

[1731] User review information: Past user reviews

[1732] Emotion data: Past emotional information and related evaluation information of plans

[1733] The server collects this information by running SQL queries against a database and stores it in temporary data storage.

[1734] Input: User-entered information stored in a temporary database

[1735] Output: Collected weather information, seasonal information, local event information, congestion information, user review information, emotion data

[1736] Step 4:

[1737] Generate multiple candidate plans

[1738] Subject: Server

[1739] The server generates multiple candidate plans based on the collected data and user input, including the names, addresses, travel time, budget, etc. The server uses an appropriate algorithm to evaluate the relevance of the data and generate multiple candidate plans.

[1740] Input: Parsed user input information, collected data

[1741] Output: Multiple candidate plans (destination names, addresses, travel time, budget, etc.)

[1742] Step 5:

[1743] Plan evaluation and selection

[1744] Subject: Emotion Engine and Server

[1745] The emotion engine evaluates the generated candidate plans based on the user's current emotional state. This evaluation emphasizes factors that elicit positive emotions from the user. The server selects the optimal plan based on the emotion engine's evaluation results.

[1746] Input: Multiple candidate plans, emotion information

[1747] Output: Evaluated candidate plans and selection of the best plan

[1748] Step 6:

[1749] Presenting the plan

[1750] Subject: Server and Terminal

[1751] The server formats the details of the selected optimal plan and sends it to the user. The plan includes a specific schedule and details of the destinations (names, addresses, reviews, expected waiting times). The user's device then receives the plan details sent from the server and displays them in a user-friendly format.

[1752] Input: Optimal plan

[1753] Output: Plan details displayed on the user's terminal

[1754] In this way, users can plan trips that are both efficient and emotionally satisfying. The system automatically provides optimal trip plans by taking into account weather, seasons, events, crowding levels, reviews, and users' emotional information.

[1755] (Application example 2)

[1756] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1757] Conventional outing plan generation systems generate plans based on basic user information, but do not take the user's emotional state into consideration, making it difficult to provide a truly satisfying plan for the user. Furthermore, they do not suggest specific products or services, making it difficult to provide a shopping experience that is optimal for the user's current emotional state.

[1758] 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.

[1759] In this invention, the server includes means for receiving input information from a user and generating an outing plan based on the input information, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, means for generating a plurality of candidate plans based on the collected information and evaluating these candidate plans to select an optimal plan, means for analyzing the user's emotional state and suggesting products and services optimal for that emotional state, and means for presenting the optimal plan and the suggested products and services to the user, thereby enabling optimal outing plans and shopping suggestions tailored to the user's emotional state.

[1760] "User Input" means information that a User provides through an application or web platform, such as personal preferences, available time, budget, or emotional state.

[1761] An "outing plan" is an action plan that suggests places to visit and a schedule based on conditions specified by the user.

[1762] "Climate information" refers to meteorological data such as weather, temperature, and precipitation at a specific date, time, and location.

[1763] "Seasonal information" is data about events and activities related to a particular season and the characteristics specific to that season.

[1764] "Regional event information" is information about various events held in a specified region.

[1765] "Crowding level information" is data that indicates the congestion level of a specific location or event.

[1766] "User review information" refers to data regarding the ratings and opinions of past users on services and products provided.

[1767] "Emotional state" refers to the user's current mental and psychological state (e.g., stress, happiness, fatigue).

[1768] An "emotion engine" is a system that analyzes the user's input information and behavioral data to recognize their current emotional state and make suggestions and evaluations based on that.

[1769] "Goods and Services" refers to the tangible goods and activities and services available to you.

[1770] A "shopping platform" is a platform for purchasing and proposing products and services online.

[1771] This invention is a system that utilizes an emotion engine to recognize the user's current emotional state in addition to input information from the user, and then suggests outing plans, products, and services. This system is composed of the following elements:

[1772] System configuration

[1773] 1. User Device

[1774] A device where a user enters information and receives proposed plans and products. Examples include smartphones, tablets, and PCs.

[1775] 2. Server

[1776] It is the main processing device that analyzes input information and emotional information from users and generates outing plans, products and services.

[1777] 3. Database

[1778] Weather information, seasonal information, local event information, congestion information, user review information, and emotion data are stored and made accessible from a server.

[1779] 4. Emotion Engine

[1780] It is an engine that recognizes the user's emotional state and uses that information to generate and evaluate plans and suggest products and services. Specific examples include Azure Cognitive Services and IBM Watson.

[1781] Program processing

[1782] Receiving user input

[1783] Users access a dedicated app or web platform and enter their preferences, budget, available time, and their current emotional state, which can be entered via text, multiple choice, or voice recognition. This information is then sent to the server by the device.

[1784] Analysis of input information

[1785] The server analyzes the input and emotional information received from the user to determine the user's preferences, available time, budget, and current emotional state.

[1786] Data collection

[1787] The server collects the following information from the database:

[1788] Weather information: Weather on the specified date.

[1789] Seasonal information: Events that occur at specific times or features specific to the season.

[1790] Local event information: Information about events taking place in a specified area.

[1791] Congestion information: Congestion levels in various locations.

[1792] User review information: Reviews from past users.

[1793] Emotional data: Past user emotional information and associated plan evaluations.

[1794] Proposing multiple candidate plans and products / services

[1795] Based on the collected information, the server generates multiple candidate plans and products / services that match the user's input information and emotional information, while simultaneously proposing optimal products and services according to the user's emotional state.

[1796] Evaluating and selecting plans, products and services

[1797] The emotion engine evaluates multiple candidate plans and products / services based on the user's current emotional state. Emotional information is taken into account as an important factor in the evaluation. Plans and product proposals that induce positive emotions are given higher ratings.

[1798] Offering plans, products and services

[1799] The server formats the most suitable plan and product / service details and sends them to the user. The plan includes a specific schedule and details of the destinations (name, address, reviews, expected waiting time). The user's device receives the plan and product / service details sent from the server and displays them in a user-friendly format.

[1800] Specific examples

[1801] On a Saturday afternoon, a user opens the app and enters the following information:

[1802] Likes: Cafes, art museums

[1803] Budget: 5,000 yen

[1804] Available time: 3 hours

[1805] Emotional state: Feeling stressed

[1806] The server analyzes this information and collects related data from the database.The server then uses an emotion engine to suggest plans and products that will help reduce stress (for example, relaxation goods or aroma candles).Examples of plans, products, and services that are best suited to the user include the following:

[1807] The plan: Relax for an hour at a quiet cafe in front of the station, then spend two hours visiting a special exhibition at the museum.

[1808] Products: Relaxation items, aroma candles, herbal tea.

[1809] Example prompts for generative AI models

[1810] "My emotional state is 'stressed'. Please suggest products that would be best suited to this state."

[1811] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1812] Step 1:

[1813] Receiving user input

[1814] The user opens the application or web platform and enters information such as their preferences for cafes, museums, etc., their budget (e.g., 5,000 yen), the amount of time available (e.g., 3 hours), and their current emotional state (e.g., feeling stressed). This information is then sent by the device to the server.

[1815] Inputs: User preferences, budget, available time, emotional state

[1816] Output: User input sent to the server

[1817] Step 2:

[1818] Analysis of input information

[1819] The server analyzes the received user input to determine the user's preferences, budget, available time, and emotional state, taking into account past user behavior and emotional data from a database.

[1820] Input: User-entered information

[1821] Output: Analyzed user preferences, budget, available time, emotional state

[1822] Step 3:

[1823] Data collection

[1824] Based on the analyzed user information, the server collects weather information, seasonal information, local event information, congestion information, user review information, and emotion data from the database, which will later serve as the basis for plans and products.

[1825] Input: Analyzed user preferences, budget, available time, emotional state

[1826] Output: Collected weather information, seasonal information, local event information, crowding information, user review information, and sentiment data

[1827] Step 4:

[1828] Generate multiple candidate plans and products / services

[1829] The server generates multiple candidate plans and products / services based on the collected data and matched to the user's input and emotional information. For example, if the user is feeling stressed, the plan may include a quiet cafe where they can relax or recommended relaxation products.

[1830] Input: Collected information and the user's emotional state

[1831] Output: Multiple candidate plans and products / services

[1832] Step 5:

[1833] Evaluating and selecting plans, products and services

[1834] The emotion engine evaluates the generated multiple candidate plans and products / services based on the user's emotional state. Plans and product proposals that induce positive emotions are given higher ratings. The server selects the most suitable plan, product, or service based on the evaluation results.

[1835] Input: Multiple candidate plans and products / services

[1836] Output: Optimal plans and products / services based on emotional state

[1837] Step 6:

[1838] Offering plans, products and services

[1839] The server formats the details of the selected optimal plan and products / services and sends them to the user's device. The device receives this and displays it in a format that is easy for the user to understand. For example, the plan schedule and recommended products are displayed on the smartphone screen.

[1840] Input: Best plan and product / service

[1841] Output: Plan and product / service details displayed on the user's device

[1842] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1843] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1844] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1845] [Fourth embodiment]

[1846] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1847] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1848] 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).

[1849] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1850] 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.

[1851] 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).

[1852] 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.

[1853] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1854] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1855] 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.

[1856] 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.

[1857] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1858] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1859] The present invention is a system that proposes optimal outing plans based on a user's input of their preferences, budget, and available time. Hereinafter, an embodiment of the present invention will be described in detail.

[1860] System configuration

[1861] The system mainly consists of the following components:

[1862] 1. User device: The device (smartphone, tablet, PC, etc.) through which the user enters information and receives the plan.

[1863] 2. Server: The main processing unit that analyzes the input information from the user and generates and evaluates the trip plan.

[1864] 3. Database: Stores weather information, seasonal information, local event information, congestion information, and user review information and makes it accessible from the server.

[1865] Program processing

[1866] 1. Receiving user input

[1867] User

[1868] The user accesses a dedicated app or web platform and enters information such as preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), etc. This information is sent to the server by the device.

[1869] 2. Analysis of input information

[1870] server

[1871] The server analyzes the input information received from the user, which determines the user's preferences, available time, and budget.

[1872] 3. Data collection

[1873] server

[1874] The server collects the following information from the database:

[1875] Weather information: Weather on the specified date.

[1876] Seasonal information: Characteristic events at specific times.

[1877] Local Event Information: Public events in designated areas.

[1878] Congestion information: Congestion levels in various locations.

[1879] User review information: Past user reviews.

[1880] 4. Generating multiple candidate plans

[1881] server

[1882] The server generates multiple itineraries based on the collected information, matching the user's input information. For example, the following itineraries may be generated:

[1883] Option 1: Relax for an hour at a cafe in front of the station, then spend two hours visiting a special exhibition at the art museum.

[1884] Option 2: Spend 1.5 hours at a cafe downtown, then spend 1.5 hours touring the art museum.

[1885] 5. Plan Evaluation and Selection

[1886] server

[1887] The generated candidate plans are evaluated. The evaluation includes comprehensive information on weather, season, local events, congestion, and user reviews. The most suitable plan is selected from the evaluation results.

[1888] 6. Presenting the plan

[1889] server

[1890] The best plan is then formatted and sent to the user, including a specific schedule and details of the destinations (names, addresses, reviews, and estimated wait times).

[1891] Terminal

[1892] The user's terminal displays the plan details received from the server, and the user can plan their outing according to this plan.

[1893] Specific examples

[1894] Consider the following real-world scenario:

[1895] example

[1896] On a Saturday afternoon, a user opens the app and enters the following information:

[1897] Likes: Cafes, art museums

[1898] Budget: 5,000 yen

[1899] Available time: 3 hours

[1900] Receiving user input

[1901] The user enters the above information and presses the send button. The device sends the information to the server.

[1902] Analysis of input information

[1903] The server analyzes your preferences, availability, and budget and begins to collect data based on this information.

[1904] Data collection

[1905] The server gathers from a database information about Saturday's weather (clear), the museum's fall special exhibitions, the area's crowd level (relatively low), and relevant user reviews.

[1906] Generate multiple candidate plans

[1907] Based on the data collected, the server generates a plan like this:

[1908] Option 1: Relax for an hour at Cafe A in front of the station, then spend two hours visiting a special exhibition at Museum B.

[1909] Option 2: Spend 1.5 hours at Cafe C in the downtown area, then visit Museum D for 1.5 hours.

[1910] Plan evaluation and selection

[1911] The server evaluates the candidate plans and selects the best one. For example, candidate 1 is determined to be the best.

[1912] Presenting the plan

[1913] The server sends details of the optimal plan to the user's device, which displays it.

[1914] In this way, users can plan their outings efficiently and enjoyably. The system automatically provides the best plan, taking into account weather, season, events, crowd levels, and reviews.

[1915] The processing flow will be explained below.

[1916] Step 1:

[1917] Terminal

[1918] The user accesses a dedicated app or web platform and enters information such as preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), etc. Once the information is complete, the user presses the submit button.

[1919] Step 2:

[1920] Terminal

[1921] The information entered by the user is sent to the server, including preferred activities, available time, and budget.

[1922] Step 3:

[1923] server

[1924] The server analyzes the input information received from the user to determine the user's preferences, available time, and budget.

[1925] Step 4:

[1926] server

[1927] The server collects weather information, seasonal information, local event information, crowding information, and user reviews from a database.

[1928] Step 5:

[1929] Obtaining weather information: The server collects weather information for the specified date.

[1930] Acquisition of seasonal information: The server collects events at specific times and characteristics specific to the season.

[1931] Acquisition of local event information: The server collects information about events held in a specified area.

[1932] Obtaining congestion information: The server collects congestion information for each location.

[1933] Obtaining user review information: The server collects relevant past user reviews.

[1934] Step 6:

[1935] server

[1936] Based on the collected information, the server generates multiple candidate plans that match the user's input information. The generated plans reflect the user's preferred activities and time allocation within the user's budget.

[1937] Step 7:

[1938] server

[1939] Each candidate plan will be evaluated, taking into consideration the following factors:

[1940] Local Weather

[1941] Seasonal Events

[1942] Local Events

[1943] Congestion level

[1944] User reviews

[1945] Step 8:

[1946] server

[1947] Based on the evaluation results, the most appropriate plan is selected. For example, the following plan may be determined to be optimal:

[1948] Relax for an hour at a cafe in front of the station, then spend two hours visiting the museum's special exhibition.

[1949] Step 9:

[1950] server

[1951] Format details of the selected best plan, including the name of the destination, its location, reviews, and estimated wait time.

[1952] Step 10:

[1953] server

[1954] The server sends details of the best plan to the user's device.

[1955] Step 11:

[1956] Terminal

[1957] The user device receives the plan details sent from the server and displays them in a user-friendly format.

[1958] Step 12:

[1959] User

[1960] The user reviews the proposed plan, and if they are satisfied with it, they accept it and register it as a schedule. If they are not satisfied, they press the regenerate button to request a new plan.

[1961] Step 13:

[1962] server

[1963] If regeneration is requested, the same process is performed again to generate and provide a new plan.

[1964] Example 1

[1965] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1966] Conventional outing planning systems have difficulty providing optimal plans that fully consider individual requirements such as user preferences, budget, and available time. Furthermore, they are unable to generate outing plans by comprehensively evaluating environmental information such as weather and event crowding, which prevents them from increasing user satisfaction. To solve these problems, a system capable of more advanced information analysis and appropriate plan generation is needed.

[1967] 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.

[1968] In this invention, the server includes means for receiving user input information and generating an outing plan based on the input information, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, means for generating multiple candidate plans based on the collected information and evaluating the candidate plans to select an optimal plan, means for presenting the optimal plan to the user, means for analyzing the user input information and identifying preferences, budget, and available time, means for collecting related information from a database based on the identified information, means for evaluating the multiple generated candidate plans and selecting an optimal plan based on an overall evaluation score, means for sending details of the selected plan to the user terminal and displaying the details to the user, means for evaluating and optimizing the outing plan using a generative AI model, and means for inputting prompt sentences into the generative AI model to generate an outing plan. This makes it possible to provide an optimal outing plan by comprehensively evaluating individual requirements based on the user input information and environmental information.

[1969] "User-entered information" is data such as preferences, budget, and available time that a user inputs into the system.

[1970] An "outing plan" is a proposal that includes the user's outing schedule and details of places to visit, generated based on the user's input information and collected environmental information.

[1971] "Weather information" is weather forecast data for a specified date.

[1972] "Seasonal information" is information about events and unique activities related to a particular time of year.

[1973] "Local event information" is information about public events held in a specific local area.

[1974] "Crowding level information" is information about the congestion status of a specific area or facility.

[1975] "User review information" refers to reviews and ratings provided by other users in the past.

[1976] The "multiple candidate plans" are multiple outing suggestions generated based on the user's input information and the collected environmental information.

[1977] The "optimal plan" is the most suitable outing plan selected from multiple candidate plans by comprehensively evaluating the user's requirements and environmental information.

[1978] A "generative AI model" is an artificial intelligence model that generates and optimizes outing plans based on user input information and collected environmental information.

[1979] A "prompt sentence" is an instruction sentence that is input to the generative AI model to generate an outing plan.

[1980] MODE FOR CARRYING OUT THE INVENTION

[1981] The present invention relates to a system that proposes optimal outing plans by allowing a user to input their preferences, budget, and available time. Hereinafter, an embodiment of the present invention will be described in detail.

[1982] System configuration

[1983] The system mainly consists of the following components:

[1984] 1. User device: The device (smartphone, tablet, PC, etc.) through which the user enters information and receives travel plans.

[1985] 2. Server: The main processing unit that analyzes input information from users and generates and evaluates outing plans.

[1986] 3. Database: Stores weather information, seasonal information, local event information, congestion information, and user review information and makes it accessible from the server.

[1987] Program processing

[1988] 1. Receiving user input

[1989] A user accesses a dedicated app or web platform and enters information such as preferences (e.g., cafes, museums), budget (e.g., 5,000 yen), available time (e.g., 3 hours), etc. This information is sent to the server using a reactive form or HTTP request.

[1990] 2. Analysis of input information

[1991] The server parses the input information it receives using a script written in Python or JavaScript that parses the JSON data to identify the user's preferences, budget, and available time.

[1992] 3. Data collection

[1993] The server connects to a database or external API to gather the necessary information, for example using SQL queries to get the following information:

[1994] Climate information: Weather forecast for a specific date

[1995] Seasonal information: Events related to the current season

[1996] Local Event Information: Public events in designated areas

[1997] Congestion information: Congestion status of designated areas

[1998] User review information: reviews and ratings from other users

[1999] 4. Generating candidate plans

[2000] The server generates multiple itineraries based on the collected information, using an algorithm to generate the following itineraries:

[2001] Option 1: Relax for an hour at Cafe A in front of the station, then spend two hours visiting a special exhibition at Museum B.

[2002] Option 2: Spend 1.5 hours at Cafe C in the downtown area and then visit Museum D for 1.5 hours.

[2003] 5. Evaluation and selection of plans

[2004] The server evaluates the generated candidate plans, using a comprehensive set of information including weather, season, local events, congestion, and user reviews.

[2005] The server selects the optimal plan based on the overall evaluation points.

[2006] 6. Presenting the plan

[2007] The server sends the details of the optimal plan to the user's device, which then displays the information, allowing the user to plan their outing according to the plan provided.

[2008] Specific examples

[2009] For example, on a Saturday afternoon, a user opens the app and enters the following information:

[2010] Likes: Cafes, art museums

[2011] Budget: 5,000 yen

[2012] Available time: 3 hours

[2013] Once the user submits their input, the device sends the information to a server, which analyzes the user's preferences, budget, and available time, and then gathers relevant data from a database or external API, such as sunny weather information, special museum exhibitions, local congestion levels, and past user reviews.

[2014] The server then generates multiple candidate plans based on this data, evaluates the plans, selects the plan with the highest evaluation points, formats the specific schedule and details of the places to visit, and sends it to the user's device.

[2015] Prompt Sentence Examples

[2016] Examples of prompts for generative AI models include:

[2017] "The user is looking for a 3-hour outing plan with a budget of 5000 yen, where the user prefers cafes and museums on a Saturday afternoon. Generate multiple possible outing plans, and then rate and present the best plan. Information to consider includes weather forecasts, seasonal events, local public events, crowd data, and user reviews."

[2018] This makes it possible to provide users with optimal outing plans.

[2019] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2020] Step 1:

[2021] Receiving user input

[2022] Users access a dedicated app or web platform and enter their preferences, budget, and available time.

[2023] Specific operation: The user enters their preferences (e.g., "cafe, museum"), their budget (5,000 yen), and the duration (3 hours) into the form, then presses the submit button.

[2024] The terminal receives this input information and sends it to the server.

[2025] Specific operation: Sends input data to the server as an HTTP POST request.

[2026] Input (device): User preferences, budget, and available time.

[2027] Output (Terminal → Server): HTTP request containing input information.

[2028] Step 2:

[2029] Analysis of input information

[2030] The server analyzes the received input information.

[2031] What it does: The server runs a parsing script written in Python or JavaScript that parses the JSON data and stores preferences, budget, and available time in separate variables.

[2032] Input (server): JSON data containing user input information.

[2033] Output (server): Parsed individual variables (preferences, budget, available time).

[2034] Step 3:

[2035] Data collection

[2036] The server connects to a database or external API to collect the necessary information.

[2037] What it does: It uses SQL queries and API requests to retrieve the following information:

[2038] Weather information: Get the weather forecast for the specified date from the API.

[2039] Seasonal information: Retrieves events related to the current season from the database.

[2040] Local Event Information: Retrieve public events in a specified area from a database or API.

[2041] Congestion information: Obtain the congestion status of the specified area from the API.

[2042] User review information: Retrieve other users' reviews and ratings from our database.

[2043] Input (server): Parsed user input information.

[2044] Output (server): Collected data (weather information, seasonal information, local event information, congestion information, user review information).

[2045] Step 4:

[2046] Generate candidate plans

[2047] The server generates multiple outing plans based on the collected information.

[2048] What it does: It uses an algorithm to generate a list of plans based on your preferences, budget, and availability. For example, it might generate plans like this:

[2049] Option 1: Relax for an hour at a cafe in front of the station, then spend two hours visiting a special exhibition at the museum.

[2050] Option 2: Spend 1.5 hours at a cafe downtown and 1.5 hours visiting the art museum.

[2051] Input (Server): Collected data and analyzed user input information.

[2052] Output (server): Multiple candidate plans generated.

[2053] Step 5:

[2054] Plan evaluation and selection

[2055] The server evaluates the generated candidate plans.

[2056] Specific operation: Calculates rating points for each plan. These rating points are calculated taking into account weather information, seasonal information, local event information, crowding information, and user reviews. For example, visiting an art museum on a sunny day will earn you a high rating point.

[2057] The server selects the optimal plan from the evaluation results.

[2058] Specific operation: Select the plan with the highest overall evaluation points.

[2059] Input (server): Multiple generated candidate plans.

[2060] Output (server): Optimal plan.

[2061] Step 6:

[2062] Presenting the plan

[2063] The server sends the details of the selected optimal plan to the user terminal,

[2064] Specific operation: The details of the selected plan (schedule, details of destinations) are formatted in HTML or JSON format and sent as an HTTP response.

[2065] The terminal displays the plan details received from the server.

[2066] Specific behavior: Provides the user with visual details of the plan according to a display format.

[2067] Input (server → terminal): Details of the optimal plan.

[2068] Output (terminal): Displayed outing plan.

[2069] By following these steps, users can plan their outings efficiently and enjoyably.

[2070] (Application example 1)

[2071] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2072] In today's world, users often find it difficult to efficiently find personalized content that meets their preferences. Furthermore, there are no systems that suggest optimal content based on available viewing time or device type, so users must search for the appropriate content themselves, which is time-consuming. To solve this problem, a system is needed that can automatically generate and suggest personalized content plans based on user input.

[2073] 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.

[2074] In this invention, the server includes means for receiving user input information and generating a personalized content plan based on the input information, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, and means for generating multiple candidate plans based on the collected information and evaluating these candidate plans to select an optimal content plan. This makes it possible to efficiently propose an optimal content plan based on the user's preferences, available viewing time, and device used.

[2075] "User input information" refers to information entered by the user, such as preferences, available viewing times, and device type.

[2076] A "personalized content plan" is a customized recommendation of content such as movies, music, articles, etc. based on user input information.

[2077] "Climate information" is data about weather collected from outside.

[2078] "Seasonal information" is information about events and general activities associated with a particular time of year.

[2079] "Local event information" is information about events and occasions held in a specific local area.

[2080] "Crowding level information" is information about the congestion level of a specific location or event.

[2081] "User review information" refers to ratings and opinions from other users regarding services and content provided in the past.

[2082] "Server" is the primary processing unit that analyzes user input, generates personalized content plans, and collects and evaluates information.

[2083] "Device" refers to the terminal used by the user, such as a smartphone, smart glasses, or head-mounted display.

[2084] "Analysis" means deciphering the information entered by the user and performing appropriate processing based on that content.

[2085] The "optimal plan" is the plan that best meets the user's requirements from among multiple candidate plans.

[2086] "Evaluation" is the process of comparing the generated candidate plans and selecting the plan that best suits the user's requirements.

[2087] This invention is a system that proposes personalized content plans based on user preferences, available viewing times, and devices. This system is composed of a user terminal, a server, and a database.

[2088] System configuration

[2089] 1. User Device:

[2090] To input information, users use devices such as smartphones, smart glasses, and head-mounted displays, which then send the input information, such as user preferences, available viewing time, and the type of device used, to a server.

[2091] 2. Server:

[2092] The server receives user input information, analyzes it, and generates the optimal content plan. It uses a Python server program, an SQL database, and the Flask framework that provides a REST API. The server performs the following processes:

[2093] Analyzes user input to determine preferred content, viewing times, and devices.

[2094] Relevant information (weather information, seasonal information, local event information, congestion information, user review information) is collected from the database.

[2095] Based on the collected information, multiple candidate plans are generated and the optimal plan is selected after evaluation.

[2096] The selected optimal content plan is sent to the user's device.

[2097] 3. Database:

[2098] The database stores weather information, seasonal information, local event information, congestion information, and user review information and makes them accessible from the server.

[2099] Program processing explanation

[2100] Hardware and Software Used

[2101] Hardware: Smartphones, smart glasses, head-mounted displays

[2102] Software: Python, SQL database, Flask framework

[2103] Data processing and calculation

[2104] 1. Analysis of input information:

[2105] The server analyzes data entered by the user, such as preferred content, available viewing time, and device type, thereby identifying the user's preferences, available viewing time, and device type.

[2106] 2. Data Collection:

[2107] The server collects information from the database about the weather, seasons, local events, crowding levels, and user reviews, providing users with the latest information that meets their requirements in real time.

[2108] 3. Generate and evaluate candidate plans:

[2109] The server generates multiple candidate content plans based on the collected information, evaluates each plan to best match the user's preferences, available viewing time, and other conditions, and selects the optimal plan.

[2110] 4. Present the plan:

[2111] The server sends the details of the selected optimal plan (e.g., movie title, album name, viewing time, rating, etc.) to the user's device, which displays it on the screen and allows the user to watch the suggested content.

[2112] Specific examples

[2113] As an example, consider the following scenario:

[2114] User Input:

[2115] Favorites: Action movies, rock music

[2116] Viewing time: 2 hours

[2117] Device: Smartphone

[2118] The user opens the app and enters the above information. The device sends the information to the server, which then uses it to gather relevant data from its database. The server then generates a content plan that looks like this:

[2119] Option 1: Watch a 1.5 hour action movie, a 30 minute rock album

[2120] Nominations: 2.50 minute action short films, 1.5 hour documentaries

[2121] The server evaluates these candidate plans and selects the best plan (e.g., candidate 1 is determined to be the best), then sends details of the best plan to the user's device, which displays it.

[2122] Examples of prompts for generative AI models

[2123] "Generate the optimal content plan based on the user's preferences, available viewing time, and device they are using. The user's preferences are 'action movies' and 'rock music'. The available viewing time is 2 hours. The device is a smartphone."

[2124] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2125] Step 1:

[2126] The device accepts user input of preferences, available viewing time, and device type. The device receives the user input and sends it to the server. The input includes preferences (e.g., action movies, rock music), available viewing time (e.g., 2 hours), and device (e.g., smartphone). The output is the user input sent to the server.

[2127] Step 2:

[2128] The server receives user input information sent from the device. The received data includes user preferences, available viewing time, and device type. This data is analyzed to identify user preferences and conditions. The input is the user input information, and the output is the analyzed user preferences, available viewing time, and device type.

[2129] Step 3:

[2130] The server collects relevant information (weather information, seasonal information, local event information, congestion information, and user review information) from the database. The input is the analyzed user conditions, and an SQL query is executed to retrieve the required data based on those conditions. The output is the collected weather information, seasonal information, local event information, congestion information, and user review information.

[2131] Step 4:

[2132] The server generates multiple candidate content plans based on the collected information. Specifically, it creates plans by combining appropriate movies, music, articles, etc. based on the user's preferences and available viewing time. The input includes the collected information and the user's conditions, and the output is the generated multiple candidate plans.

[2133] Step 5:

[2134] The server evaluates the generated multiple candidate plans and selects the optimal content plan. The evaluation takes into consideration a comprehensive range of factors, including user preferences, available viewing times, weather information, seasonal information, local event information, congestion information, and user reviews. The input is multiple candidate plans, and the output is the evaluated optimal content plan.

[2135] Step 6:

[2136] The server formats and sends details of the optimal content plan to the user's device, including the content title, viewing time, rating, etc. The input is the optimal plan that has been evaluated, and the output is the detailed information of the plan to be sent.

[2137] Step 7:

[2138] The terminal displays the details of the optimal content plan received from the server to the user. The user can watch movies, music, articles, etc. according to the proposed content plan. The input is the detailed plan information sent from the server, and the output is the detailed content plan displayed to the user.

[2139] In this way, the system can provide the user with the most suitable content plan.

[2140] 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.

[2141] The present invention is a system that recognizes the user's current emotional state by utilizing an emotion engine in addition to information input by the user, and proposes an optimal outing plan. Hereinafter, an embodiment of the present invention will be described in detail.

[2142] System configuration

[2143] The system mainly consists of the following components:

[2144] 1. User device: A device (smartphone, tablet, PC, etc.) through which the user inputs information, receives plans, and provides feedback on their emotional state.

[2145] 2. Server: The main processing unit that analyzes input information and emotional information from users and generates and evaluates outing plans.

[2146] 3. Database: Stores weather information, seasonal information, local event information, crowding information, user review information, and sentiment data and makes them accessible from the server.

[2147] 4. Emotion Engine: An engine that recognizes the user's emotional state and uses that information to help generate and evaluate plans.

[2148] Program processing

[2149] 1. Receiving user input

[2150] User

[2151] The user accesses a dedicated app or web platform and inputs their preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), and their current emotional state. The emotional state can be input using text, multiple-choice format, or voice recognition. This information is sent to the server by the device.

[2152] 2. Analysis of input information

[2153] server

[2154] The server analyzes the input and emotional information received from the user to determine the user's preferences, available time, budget, and current emotional state.

[2155] 3. Data collection

[2156] server

[2157] The server collects the following information from the database:

[2158] Weather information: Weather on the specified date.

[2159] Seasonal information: Events that occur at specific times or features specific to the season.

[2160] Local event information: Information about events taking place in a specified area.

[2161] Congestion information: Congestion levels in various locations.

[2162] User review information: Reviews from past users.

[2163] Emotional data: Past user emotional information and associated plan evaluations.

[2164] 4. Generating multiple candidate plans

[2165] server

[2166] Based on the collected information, the server generates multiple candidate plans that match the user's input and emotional information. For example, the following plans are generated:

[2167] Option 1: Relax for an hour at a cafe in front of the station, then spend two hours visiting a special exhibition at the museum.

[2168] Option 2: Spend 1.5 hours at a cafe in the downtown area, then spend 1.5 hours touring the art museum.

[2169] 5. Plan Evaluation and Selection

[2170] Emotion Engine

[2171] The emotion engine evaluates multiple candidate plans based on the user's current emotional state. Emotional information is taken into account as an important factor in the evaluation. Plans that induce positive emotions are given a higher rating.

[2172] server

[2173] The most suitable plan is selected based on the evaluation results of the emotion engine. For example, if the user is looking to relax, a plan that includes spending time in a quiet cafe may be selected.

[2174] 6. Presenting the plan

[2175] server

[2176] The details of the selected best plan are formatted and sent to the user, including a specific schedule and details of the destinations (names, addresses, reviews, estimated wait times).

[2177] Terminal

[2178] The user device receives the plan details sent from the server and displays them in a user-friendly format.

[2179] Specific examples

[2180] Consider the following real-world scenario:

[2181] example

[2182] On a Saturday afternoon, a user opens the app and enters the following information:

[2183] Likes: Cafes, art museums

[2184] Budget: 5,000 yen

[2185] Available time: 3 hours

[2186] Emotional state: Feeling stressed

[2187] Receiving User Input

[2188] The user enters the above information and presses the send button. The device sends the information to the server.

[2189] Analysis of input information

[2190] The server analyzes your preferences, available time, budget, and emotional state, and begins to collect data based on this information.

[2191] Data collection

[2192] The server collects information from a database about Saturday's weather (sunny), the museum's fall special exhibition, the area's crowd level (relatively low), relevant user reviews, and sentiment data.

[2193] Generate multiple candidate plans

[2194] The server generates a plan based on the collected data and emotional information, such as:

[2195] Option 1: Relax for an hour at a quiet cafe A in front of the station, then spend two hours visiting a special exhibition at museum B.

[2196] Option 2: Spend 1.5 hours at the highly satisfying Cafe C in the downtown area, then spend 1.5 hours touring Museum D.

[2197] Plan evaluation and selection

[2198] The emotion engine evaluates the candidate plans and determines that candidate 1 is the best, as it provides a quiet environment that helps reduce stress.

[2199] Presenting the plan

[2200] The server sends details of the best plan to the user's device, which displays it.

[2201] In this way, users can plan trips that are both efficient and emotionally satisfying. The system automatically provides the optimal plan by taking into account weather, season, events, crowding, reviews, and user emotional information.

[2202] The processing flow will be explained below.

[2203] Step 1:

[2204] User

[2205] Users access a dedicated app or web platform and enter their preferences (e.g., cafe, museum), budget (e.g., 5,000 yen), available time (e.g., 3 hours), and current emotional state (e.g., feeling stressed). After entering this information, they press the send button.

[2206] Step 2:

[2207] Terminal

[2208] The information entered by the user is sent to a server, including preferred activities, available time, budget, and emotional state.

[2209] Step 3:

[2210] server

[2211] The server analyzes the input and emotional information received from the user to determine the user's preferences, available time, budget, and emotional state.

[2212] Step 4:

[2213] server

[2214] The server collects weather information, seasonal information, local event information, congestion information, and user review information from a database.

[2215] Step 5:

[2216] Obtaining weather information: The server collects weather information for the specified date.

[2217] Acquisition of seasonal information: The server collects events at specific times and characteristics specific to the season.

[2218] Acquisition of local event information: The server collects information about events held in a specified area.

[2219] Obtaining congestion information: The server collects congestion information for each location.

[2220] Obtaining user review information: The server collects relevant past user reviews.

[2221] Acquiring emotional data: The server collects past user emotional information and associated plan evaluation data.

[2222] Step 6:

[2223] server

[2224] Based on the collected information, the server generates multiple candidate plans that match the user's input and emotional information. The generated plans reflect the user's preferred activities and time allocation within a budget.

[2225] Step 7:

[2226] server

[2227] Each candidate plan will be evaluated, taking into consideration the following factors:

[2228] Local Weather

[2229] Seasonal Events

[2230] Local Events

[2231] Congestion level

[2232] User reviews

[2233] emotional information

[2234] Step 8:

[2235] Emotion Engine

[2236] The emotion engine prioritizes multiple generated candidate plans based on the user's current emotional state, with plans that induce positive emotions being given a higher rating.

[2237] Step 9:

[2238] server

[2239] The emotion engine evaluates the plan to find the most suitable one. For example, if the user is feeling stressed, a plan that offers a quiet and relaxing environment may be selected.

[2240] Step 10:

[2241] server

[2242] The details of the selected best plan are formatted and sent to the user, including the name of the destination, its location, reviews, and estimated wait time.

[2243] Step 11:

[2244] Terminal

[2245] The user device receives the plan details sent from the server and displays them in a user-friendly format.

[2246] Step 12:

[2247] User

[2248] The user reviews the proposed plan, and if they are satisfied with it, they accept it and register it as a schedule. If they are not satisfied, they press the regenerate button to request a new plan.

[2249] Step 13:

[2250] server

[2251] If regeneration is requested, the same process is performed again to generate and provide a new plan.

[2252] Example 2

[2253] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2254] Conventional outing plan generation systems provide outing plans based on user input information, but they have the problem of not being able to provide plans that take into account the user's current emotional state. This can result in outing plans that do not match the user's emotional state, which can reduce satisfaction. Another issue is that the information collected is limited, making it difficult to gather enough data to provide a more comprehensive plan.

[2255] 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.

[2256] In this invention, the server includes means for receiving information input by the user and generating an outing plan, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, means for recognizing the emotional state and evaluating the outing plan based on the recognized emotional information, means for generating a plurality of candidate plans based on the collected information and emotional information, evaluating these candidate plans, and selecting an optimal plan, and means for presenting the optimal plan to the user. This makes it possible to provide an outing plan that suits the user's emotional state, thereby increasing user satisfaction.

[2257] "User-entered information" refers to data such as preferences, budget, available time, and current emotional state that a user enters through a dedicated application or web platform.

[2258] An "outing itinerary" is a series of suggested activities and places to visit that are generated based on user input and collected data.

[2259] "Emotional information" is data based on information that recognizes the user's current emotional state.

[2260] "Weather information" is data about the weather on a specified date, and is obtained from a weather forecast service or the like.

[2261] "Seasonal information" is data relating to events associated with specific times and characteristics specific to the season.

[2262] "Local event information" is data related to events held within a specified area.

[2263] "Crowding information" is data on the congestion situation in each area.

[2264] "User review information" is data about past users' ratings and impressions of facilities and events.

[2265] An "emotion engine" is a processing device or software that recognizes the user's emotional state and evaluates outing plans based on that information.

[2266] "Candidate plans" are multiple outing plans that are generated based on the user's input information and collected data.

[2267] The present invention is a system that recognizes the user's current emotional state and proposes an optimal outing plan by utilizing an emotion engine in addition to information input by the user. Hereinafter, an embodiment of the present invention will be described in detail.

[2268] System configuration

[2269] The system mainly consists of the following components:

[2270] 1. User device: A device (smartphone, tablet, PC, etc.) through which the user inputs information, receives plans, and provides feedback on their emotional state.

[2271] 2. Server: The main processing unit that analyzes input information and emotional information from users and generates and evaluates outing plans.

[2272] 3. Database: Stores weather information, seasonal information, local event information, congestion information, user review information, and emotion data and makes them accessible from the server.

[2273] 4. Emotion Engine: An engine that recognizes the user's emotional state and uses that information to help generate and evaluate plans.

[2274] Program processing

[2275] 1. Receiving user input

[2276] User

[2277] The user accesses a dedicated app or web platform and inputs their preferences, budget, available time, and current emotional state, which can be input via text, multiple choice, or voice recognition. This information is then sent by the device to the server.

[2278] 2. Analysis of input information

[2279] server

[2280] The server analyzes the input received from the user to determine the user's preferences, budget, available time, and current emotional state.

[2281] 3. Data collection

[2282] server

[2283] The server collects the following information from the database:

[2284] Weather information: Weather on a specified date

[2285] Seasonal information: Events and seasonal features

[2286] Local event information: Information on events held in designated areas

[2287] Congestion information: Congestion levels in various areas

[2288] User review information: Reviews from past users

[2289] Emotional data: Evaluating past user emotional information and related plans

[2290] 4. Generating Multiple Candidate Plans

[2291] server

[2292] Based on the collected information, the server generates multiple candidate plans that match the user's input information and emotional information.

[2293] 5. Evaluation and selection of plans

[2294] Emotion Engine

[2295] The emotion engine evaluates multiple candidate plans based on the user's current emotional state. Emotional information is taken into account as an important factor in the evaluation. Plans that induce positive emotions are given a higher rating.

[2296] server

[2297] The most suitable plan is selected based on the evaluation results of the emotion engine.

[2298] 6. Presenting the plan

[2299] server

[2300] The details of the selected best plan are formatted and sent to the user, including a specific schedule and details of the destinations (names, addresses, reviews, estimated wait times).

[2301] Terminal

[2302] The user terminal receives the plan details sent from the server and displays them in a user-friendly format.

[2303] Specific examples

[2304] Consider the following real-world scenario:

[2305] example

[2306] On a Saturday afternoon, a user opens the app and enters the following information:

[2307] Likes: Cafes, art museums

[2308] Budget: 5,000 yen

[2309] Available time: 3 hours

[2310] Emotional state: Feeling stressed

[2311] Prompt Sentence Examples

[2312] "When the user inputs their emotional state, the server generates the optimal outing plan based on that information."

[2313] "Use the emotion engine to evaluate and select plans that elicit positive emotions from users."

[2314] "Create an outing plan based on the specified criteria and send it to the user."

[2315] In this way, users can plan trips that are both efficient and emotionally satisfying. The system automatically provides optimal trip plans by taking into account weather, seasons, events, crowding levels, reviews, and users' emotional information.

[2316] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2317] System program processing flow

[2318] Step 1:

[2319] Receiving user input

[2320] Subject: User

[2321] The user accesses a dedicated app or web platform and enters their preferences, budget, available time, and current emotional state. The entered information is sent from the device to the server by pressing the send button. Specifically, the user opens the smartphone app, enters information into the displayed form, and clicks the send button. At this time, when the input is submitted, the device sends the data to the server.

[2322] Inputs: User preferences, budget, available time, emotional state

[2323] Output: User input information is sent to the server

[2324] Step 2:

[2325] Analysis of input information

[2326] Subject: Server

[2327] The server analyzes the received user input information. Specifically, it extracts information and categorizes it into categories such as preferences, budget, available time, and emotional state. This information is temporarily stored for use in the next processing step. The server then performs the appropriate data conversion and database storage for analysis.

[2328] Input: User-entered information

[2329] Output: Preferences, budget, available time, and emotional state are identified and stored in a temporary database

[2330] Step 3:

[2331] Data collection

[2332] Subject: Server

[2333] The server accesses the database and collects the following information:

[2334] Weather information: Data from the weather API

[2335] Seasonal information: Data about events occurring at specific times

[2336] Local event information: Information on events held in designated areas

[2337] Congestion information: Real-time congestion status

[2338] User review information: Past user reviews

[2339] Emotion data: Past emotional information and related evaluation information of plans

[2340] The server collects this information by running SQL queries against a database and stores it in temporary data storage.

[2341] Input: User-entered information stored in a temporary database

[2342] Output: Collected weather information, seasonal information, local event information, congestion information, user review information, emotion data

[2343] Step 4:

[2344] Generate multiple candidate plans

[2345] Subject: Server

[2346] The server generates multiple candidate plans based on the collected data and user input, including the names, addresses, travel time, budget, etc. The server uses an appropriate algorithm to evaluate the relevance of the data and generate multiple candidate plans.

[2347] Input: Parsed user input information, collected data

[2348] Output: Multiple candidate plans (destination names, addresses, travel time, budget, etc.)

[2349] Step 5:

[2350] Plan evaluation and selection

[2351] Subject: Emotion Engine and Server

[2352] The emotion engine evaluates the generated candidate plans based on the user's current emotional state. This evaluation emphasizes factors that elicit positive emotions from the user. The server selects the optimal plan based on the emotion engine's evaluation results.

[2353] Input: Multiple candidate plans, emotion information

[2354] Output: Evaluated candidate plans and selection of the best plan

[2355] Step 6:

[2356] Presenting the plan

[2357] Subject: Server and Terminal

[2358] The server formats the details of the selected optimal plan and sends it to the user. The plan includes a specific schedule and details of the destinations (names, addresses, reviews, expected waiting times). The user's device then receives the plan details sent from the server and displays them in a user-friendly format.

[2359] Input: Optimal plan

[2360] Output: Plan details displayed on the user's terminal

[2361] In this way, users can plan trips that are both efficient and emotionally satisfying. The system automatically provides optimal trip plans by taking into account weather, seasons, events, crowding levels, reviews, and users' emotional information.

[2362] (Application example 2)

[2363] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2364] Conventional outing plan generation systems generate plans based on basic user information, but do not take the user's emotional state into consideration, making it difficult to provide a truly satisfying plan for the user. Furthermore, they do not suggest specific products or services, making it difficult to provide a shopping experience that is optimal for the user's current emotional state.

[2365] 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.

[2366] In this invention, the server includes means for receiving input information from a user and generating an outing plan based on the input information, means for collecting weather information, seasonal information, local event information, congestion information, and user review information, means for generating a plurality of candidate plans based on the collected information and evaluating these candidate plans to select an optimal plan, means for analyzing the user's emotional state and suggesting products and services optimal for that emotional state, and means for presenting the optimal plan and the suggested products and services to the user, thereby enabling optimal outing plans and shopping suggestions tailored to the user's emotional state.

[2367] "User Input" means information that a User provides through an application or web platform, such as personal preferences, available time, budget, or emotional state.

[2368] An "outing plan" is an action plan that suggests places to visit and a schedule based on conditions specified by the user.

[2369] "Climate information" refers to meteorological data such as weather, temperature, and precipitation at a specific date, time, and location.

[2370] "Seasonal information" is data about events and activities related to a particular season and the characteristics specific to that season.

[2371] "Regional event information" is information about various events held in a specified region.

[2372] "Crowding level information" is data that indicates the congestion level of a specific location or event.

[2373] "User review information" refers to data regarding the ratings and opinions of past users on services and products provided.

[2374] "Emotional state" refers to the user's current mental and psychological state (e.g., stress, happiness, fatigue).

[2375] An "emotion engine" is a system that analyzes the user's input information and behavioral data to recognize their current emotional state and make suggestions and evaluations based on that.

[2376] "Goods and Services" refers to the tangible goods and activities and services available to you.

[2377] A "shopping platform" is a platform for purchasing and proposing products and services online.

[2378] This invention is a system that utilizes an emotion engine to recognize the user's current emotional state in addition to input information from the user, and then suggests outing plans, products, and services. This system is composed of the following elements:

[2379] System configuration

[2380] 1. User Device

[2381] A device where a user enters information and receives proposed plans and products. Examples include smartphones, tablets, and PCs.

[2382] 2. Server

[2383] It is the main processing device that analyzes input information and emotional information from users and generates outing plans, products and services.

[2384] 3. Database

[2385] Weather information, seasonal information, local event information, congestion information, user review information, and emotion data are stored and made accessible from a server.

[2386] 4. Emotion Engine

[2387] It is an engine that recognizes the user's emotional state and uses that information to generate and evaluate plans and suggest products and services. Specific examples include Azure Cognitive Services and IBM Watson.

[2388] Program processing

[2389] Receiving user input

[2390] Users access a dedicated app or web platform and enter their preferences, budget, available time, and their current emotional state, which can be entered via text, multiple choice, or voice recognition. This information is then sent to the server by the device.

[2391] Analysis of input information

[2392] The server analyzes the input and emotional information received from the user to determine the user's preferences, available time, budget, and current emotional state.

[2393] Data collection

[2394] The server collects the following information from the database:

[2395] Weather information: Weather on the specified date.

[2396] Seasonal information: Events that occur at specific times or features specific to the season.

[2397] Local event information: Information about events taking place in a specified area.

[2398] Congestion information: Congestion levels in various locations.

[2399] User review information: Reviews from past users.

[2400] Emotional data: Past user emotional information and associated plan evaluations.

[2401] Proposing multiple candidate plans and products / services

[2402] Based on the collected information, the server generates multiple candidate plans and products / services that match the user's input information and emotional information, while simultaneously proposing optimal products and services according to the user's emotional state.

[2403] Evaluating and selecting plans, products and services

[2404] The emotion engine evaluates multiple candidate plans and products / services based on the user's current emotional state. Emotional information is taken into account as an important factor in the evaluation. Plans and product proposals that induce positive emotions are given higher ratings.

[2405] Offering plans, products and services

[2406] The server formats the most suitable plan and product / service details and sends them to the user. The plan includes a specific schedule and details of the destinations (name, address, reviews, expected waiting time). The user's device receives the plan and product / service details sent from the server and displays them in a user-friendly format.

[2407] Specific examples

[2408] On a Saturday afternoon, a user opens the app and enters the following information:

[2409] Likes: Cafes, art museums

[2410] Budget: 5,000 yen

[2411] Available time: 3 hours

[2412] Emotional state: Feeling stressed

[2413] The server analyzes this information and collects related data from the database.The server then uses an emotion engine to suggest plans and products that will help reduce stress (for example, relaxation goods or aroma candles).Examples of plans, products, and services that are best suited to the user include the following:

[2414] The plan: Relax for an hour at a quiet cafe in front of the station, then spend two hours visiting a special exhibition at the museum.

[2415] Products: Relaxation items, aroma candles, herbal tea.

[2416] Example prompts for generative AI models

[2417] "My emotional state is 'stressed'. Please suggest products that would be best suited to this state."

[2418] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2419] Step 1:

[2420] Receiving user input

[2421] The user opens the application or web platform and enters information such as their preferences for cafes, museums, etc., their budget (e.g., 5,000 yen), the amount of time available (e.g., 3 hours), and their current emotional state (e.g., feeling stressed). This information is then sent by the device to the server.

[2422] Inputs: User preferences, budget, available time, emotional state

[2423] Output: User input sent to the server

[2424] Step 2:

[2425] Analysis of input information

[2426] The server analyzes the received user input to determine the user's preferences, budget, available time, and emotional state, taking into account past user behavior and emotional data from a database.

[2427] Input: User-entered information

[2428] Output: Analyzed user preferences, budget, available time, emotional state

[2429] Step 3:

[2430] Data collection

[2431] Based on the analyzed user information, the server collects weather information, seasonal information, local event information, congestion information, user review information, and emotion data from the database, which will later serve as the basis for plans and products.

[2432] Input: Analyzed user preferences, budget, available time, emotional state

[2433] Output: Collected weather information, seasonal information, local event information, crowding information, user review information, and sentiment data

[2434] Step 4:

[2435] Generate multiple candidate plans and products / services

[2436] The server generates multiple candidate plans and products / services based on the collected data and matched to the user's input and emotional information. For example, if the user is feeling stressed, the plan may include a quiet cafe where they can relax or recommended relaxation products.

[2437] Input: Collected information and the user's emotional state

[2438] Output: Multiple candidate plans and products / services

[2439] Step 5:

[2440] Evaluating and selecting plans, products and services

[2441] The emotion engine evaluates the generated multiple candidate plans and products / services based on the user's emotional state. Plans and product proposals that induce positive emotions are given higher ratings. The server selects the most suitable plan, product, or service based on the evaluation results.

[2442] Input: Multiple candidate plans and products / services

[2443] Output: Optimal plans and products / services based on emotional state

[2444] Step 6:

[2445] Offering plans, products and services

[2446] The server formats the details of the selected optimal plan and products / services and sends them to the user's device. The device receives this and displays it in a format that is easy for the user to understand. For example, the plan schedule and recommended products are displayed on the smartphone screen.

[2447] Input: Best plan and product / service

[2448] Output: Plan and product / service details displayed on the user's device

[2449] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2450] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2451] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2452] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2453] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2454] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2455] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2456] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2457] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2458] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2459] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2460] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2461] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2462] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2463] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2464] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2465] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2466] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2467] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2468] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2469] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2470] The following is further disclosed regarding the above embodiment.

[2471] (Claim 1)

[2472] means for receiving input information from a user and generating an outing plan based on the input information;

[2473] A means for collecting weather information, seasonal information, local event information, congestion information, and user review information;

[2474] means for generating a plurality of candidate plans based on the collected information, and evaluating the candidate plans to select an optimal plan;

[2475] The system includes a means for presenting the optimal plan to a user.

[2476] (Claim 2)

[2477] 10. The system of claim 1, further comprising means for analyzing the user's input information to identify preferred activities, available time, and budget.

[2478] (Claim 3) 【...

Claims

1. means for receiving input information from a user and generating an outing plan based on the input information; A means for collecting weather information, seasonal information, local event information, congestion information, and user review information; means for generating a plurality of candidate plans based on the collected information, and evaluating the candidate plans to select an optimal plan; The system includes a means for presenting the optimal plan to a user.

2. 10. The system of claim 1, further comprising means for analyzing the user's input information to identify preferred activities, available time, and budget.

3. The system according to claim 1 , further comprising means for comprehensively considering weather information, seasonal information, local event information, congestion information, and user review information in evaluating the plurality of candidate plans.

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