System

Abstract

A system is provided.SOLUTION: A system comprising: means for obtaining forecasted weather data based on an event date and location; means for suggesting indoor or outdoor activities suitable for the event based on the weather data; and means for displaying the suggested activities to a 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] Traditionally, weather changes on the day of an event have a significant impact on the success of the event, necessitating appropriate changes to plans. However, the process of manually analyzing weather forecast data and determining appropriate activities is time-consuming and labor-intensive. Therefore, there is a need for a system that automatically analyzes weather forecasts based on the date and location of the event and suggests appropriate activities. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including means for acquiring predicted weather data based on the date and location of an event, means for suggesting indoor or outdoor activities suitable for the event based on the weather data, and means for displaying the suggested activities to a user. In particular, the present invention provides a system that automatically and efficiently suggests activities according to the weather by acquiring the weather data from an external weather forecast API and determining the date and location of the event based on input from a user.

[0006] "Event" means a gathering or occasion planned for a specific purpose at a specific date and place.

[0007] "Event Date" means the date on which the Event actually takes place.

[0008] "Location" refers to the geographic location where the Event actually takes place.

[0009] "Weather Data" refers to information including weather conditions (e.g., temperature, precipitation, wind speed, etc.) at a particular location and time.

[0010] "Indoor activities" refers to activities or events that are intended to be done indoors (e.g., going to the movies, bowling, visiting a museum, etc.).

[0011] "Outdoor activities" refers to activities and events that are intended to be carried out outdoors (e.g., picnics, cycling, walking, etc.).

[0012] A "suggestion" is a recommended option or action based on specific conditions or circumstances.

[0013] "User" refers to an individual or organization that uses the system. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

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

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

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

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0029] 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.

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

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] The present invention relates to a system that obtains predicted weather data based on the date and location of an event, suggests appropriate indoor or outdoor activities, and displays them to users, with the aim of improving user convenience and increasing the success rate of the event.

[0036] Overall system flow

[0037] 1. User enters event information

[0038] The user enters the date and location of the event on the terminal, for example, "2023-10-20" and "Tokyo."

[0039] 2. The device sends a request to the server

[0040] Based on the input event information, the device sends a request to a server dedicated to weather forecast APIs, which then calls the weather forecast API and retrieves weather data for the specified date and location.

[0041] 3. The server analyzes the weather data

[0042] The server analyzes the weather data and determines the weather on the day of the event. For example, it may obtain data indicating "sunny" from a weather forecast API.

[0043] 4. The server suggests activities

[0044] The server then selects the appropriate activity (indoor or outdoor) based on the analyzed weather data. For example, if it's sunny, it will suggest outdoor activities such as "picnic," "cycling," and "walking."

[0045] 5. The server sends the proposal back to the device

[0046] Data containing a list of suggested activities is sent back to the device in JSON format.

[0047] 6. The device displays suggestions to the user

[0048] The device then analyzes the returned suggestions and displays them to the user in an easy-to-understand format, such as "It's sunny, so we suggest the following outdoor activities: picnic, cycling, walking."

[0049] Specific examples

[0050] For example, suppose a user is planning an event in "Tokyo" on "2023-10-20." In this case, when the user enters this information into the device, the device sends a request to the weather forecast API server. The server retrieves weather data for "Tokyo" from the weather forecast API and analyzes the results to determine that it will be "sunny." Based on the analysis results, the server suggests outdoor activities such as "picnic," "cycling," and "walking," and sends this information back to the device. Finally, the device displays the suggested activities to the user.

[0051] This system allows users to efficiently plan events by automatically suggesting activities suitable for the event date and location, and by selecting activities appropriate for the weather, it can increase participant satisfaction.

[0052] The processing flow will be explained below.

[0053] Step 1:

[0054] The user enters the date and location of the event. For example, the user enters "2023-10-20" and "Tokyo" into the terminal. The terminal stores this information and proceeds to the next processing step.

[0055] Step 2:

[0056] The device sends a request to the server based on the input information. Specifically, it generates a request to use the weather forecast API and sends it to the server. This request includes information about the date and location of the event.

[0057] Step 3:

[0058] The server sends a request to the weather forecast API to get weather data for a specified date and location. Here, the server accesses an external weather forecast API endpoint and receives weather data in JSON format.

[0059] Step 4:

[0060] The weather data acquired by the server is analyzed. Specifically, the JSON data is analyzed and daytime weather information for the event is extracted. For example, it identifies whether the weather is "sunny," "cloudy," or "rainy."

[0061] Step 5:

[0062] The server suggests activities based on the analyzed weather data. If the weather is "sunny" or "cloudy," the server selects outdoor activities such as "picnic," "cycling," or "walking." If the weather is "rainy," the server selects indoor activities such as "watching a movie," "bowling," or "visiting a museum."

[0063] Step 6:

[0064] The server returns a list of suggested activities in JSON format to the device, along with the selected activity, along with the event date and location information.

[0065] Step 7:

[0066] The device parses the activity suggestions received from the server. The device parses the received JSON data and extracts the suggested activities.

[0067] Step 8:

[0068] The device displays suggested activities to the user. The device clearly displays the analysis results and displays a message such as, "It's sunny today, so we suggest the following outdoor activities: picnic, cycling, walking."

[0069] This allows users to easily find the best activities for their event date and location.

[0070] Example 1

[0071] 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."

[0072] In conventional event planning, it is difficult to select appropriate activities based on the weather, and there is a high risk that outdoor events will be canceled due to bad weather, especially. Furthermore, users have to check the weather forecast and select activities based on it, which reduces the chances of the event being successful. There is a need to solve these problems and improve user convenience.

[0073] 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.

[0074] In this invention, the server includes a means for the user to input event information, a means for the terminal to transmit the event information to the server, and a means for the server to analyze weather data and select appropriate activities. This allows the user to receive suggestions for optimal activities based on the weather simply by inputting the event information, increasing the success rate of the event and significantly reducing the user's effort.

[0075] "Event information" is information about the date and location of an event designated by the user.

[0076] "Weather data" is meteorological information for a specified date and location, including temperature, probability of precipitation, weather conditions, and the like.

[0077] "Indoor activities" are activities or events that take place inside a building and are less susceptible to weather.

[0078] "Outdoor activities" are activities or events that take place outdoors and are subject to weather.

[0079] A "user" is a person or organization that uses this system to input event information and receive activity suggestions.

[0080] A "terminal" is a device used by a user to input event information and display activity suggestions.

[0081] The "server" is the central computing system responsible for acquiring, analyzing, and suggesting activities on the weather data.

[0082] A "weather forecast API" is an external service that provides weather information over the Internet and is used by servers to obtain weather data.

[0083] "Activity suggestions" refers to providing the user with suitable indoor or outdoor activities based on the acquired weather data.

[0084] The "JSON format" is a type of data exchange format that is lightweight, easy to read, and suitable for data communication between programs.

[0085] An "HTTP request" is a communication protocol that allows a client to request data from a server, and is primarily used when using web services.

[0086] MODE FOR CARRYING OUT THE INVENTION

[0087] The present invention is a system that obtains predicted weather data based on the date and location of an event, and then suggests and displays suitable indoor or outdoor activities to the user based on the results. The main purpose of this system is to improve user convenience and increase the success rate of the event. A detailed implementation method of this system is described below.

[0088] 1. Enter your event information

[0089] The user uses the device to input the date and location of the event. Specifically, they enter information such as "2023-10-20" and "Tokyo" through an input form. This input can be done via a web browser or a dedicated application.

[0090] 2. Sending event information

[0091] The device sends the event information obtained from the user to the server. Specifically, it generates an HTTP request and sends it to a server dedicated to weather forecast APIs. The server uses an HTTP GET request to obtain weather data for the specified date and location from an external API (e.g., OpenWeatherMap or WeatherAPI).

[0092] 3. Weather data acquisition and analysis

[0093] The server analyzes weather data obtained from an external weather forecast API. The obtained data is in JSON format, and the server parses it to extract the necessary weather information. For example, the server identifies the information "sunny" from the analyzed weather data.

[0094] 4. Activity Selection

[0095] The server then selects appropriate activities based on the analysis results. These activities are chosen from a predefined list, and the selection criteria vary depending on the weather conditions. For example, if it's sunny, outdoor activities such as "picnic," "cycling," and "walking" will be suggested.

[0096] 5. Sending data from the server to the device

[0097] The selected activity list is sent back to the device from the server in JSON format, including the name and brief description of the suggested activity.

[0098] 6. Display of Suggestions

[0099] The device parses the received JSON data and displays the analysis results in a user-friendly format. For example, it may display text such as "It's sunny, so the following outdoor activities are suggested: picnic, cycling, walking." This allows the user to easily select the most suitable activity.

[0100] As a concrete example, if a user is planning an event in "Tokyo" on "2023-10-20," the user enters this information into the device, and the device sends a request to the server. The server retrieves weather data for "Tokyo" from the weather forecast API and analyzes the results to determine that it is "sunny." Based on the analysis results, the server suggests outdoor activities such as "picnic," "cycling," and "walking," and sends this information back to the device. Finally, the device displays the suggested activities to the user.

[0101] As an example of a prompt sentence, the following prompt sentence can be input to the generative AI model:

[0102] "I'm planning to hold an event in Tokyo on 2023-10-20. Please analyze the weather forecast data for this date and suggest appropriate activities."

[0103] This system allows users to receive appropriate activity suggestions based on the weather, enabling efficient event planning and is expected to increase participant satisfaction.

[0104] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0105] Step 1:

[0106] The user enters the event information.

[0107] The user enters the date and location of the event on the device. This information is received through a form, and the user presses the "Submit" button to move to the next step. The specific information entered is, for example, "2023-10-20" and "Tokyo."

[0108] input:

[0109] Date of event (e.g. 2023-10-20)

[0110] Venue (e.g. Tokyo)

[0111] output:

[0112] Request to send event information (e.g. HTTP request)

[0113] Step 2:

[0114] The device sends a request to the server.

[0115] Based on the event information entered by the user, the device generates request data and sends it to the server as an HTTP GET request. At this time, the device accesses a specific API endpoint and requests the acquisition of weather data.

[0116] input:

[0117] Event information (date, location)

[0118] output:

[0119] HTTP request to the server

[0120] Step 3:

[0121] The server retrieves the weather data.

[0122] The server accesses an external weather forecast API based on the received request to retrieve weather data for the specified date and location. This process uses an HTTP GET request to retrieve the weather forecast, adding the API key and parameters.

[0123] input:

[0124] HTTP request to the server

[0125] output:

[0126] Weather data from an external API (JSON format)

[0127] Step 4:

[0128] The server analyzes the weather data.

[0129] The server analyzes the acquired weather data and identifies the weather on the day of the event. It parses the JSON format data and extracts weather conditions such as "sunny" or "rainy" from the "weather" key. The analysis results are processed by flagging any that match a specific weather condition.

[0130] input:

[0131] Weather data obtained from an external API (JSON format)

[0132] output:

[0133] Weather data analysis results (e.g. "Sunny")

[0134] Step 5:

[0135] The server suggests activities.

[0136] The server then selects appropriate activities from a predefined list based on the analyzed weather data. For example, if the weather is sunny, outdoor activities such as "picnic," "cycling," and "walking" are suggested.

[0137] input:

[0138] Weather data analysis results (e.g. "Sunny")

[0139] output:

[0140] List of suggested activities (e.g., "picnic," "cycling," "walking")

[0141] Step 6:

[0142] The server sends the proposal back to the device.

[0143] The selected activity list is sent back to the device from the server in JSON format, including the name and brief description of the suggested activity.

[0144] input:

[0145] List of suggested activities (e.g., "picnic," "cycling," "walking")

[0146] output:

[0147] Response data to the terminal (JSON format)

[0148] Step 7:

[0149] The terminal displays the suggestions to the user.

[0150] The device parses the received JSON data and displays the analysis results in a user-friendly format, such as "It's sunny, so the following outdoor activities are suggested: picnic, cycling, walking."

[0151] input:

[0152] Response data from the server (JSON format)

[0153] output:

[0154] What to show the user (e.g., "It's a sunny day, so we suggest the following outdoor activities: picnic, cycling, walking")

[0155] (Application example 1)

[0156] 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."

[0157] The challenge is to increase the success rate of events planned by users by quickly and efficiently suggesting appropriate activities according to the weather on the day of the event. In particular, there is a need to provide an environment in virtual stores where users can receive appropriate activity suggestions in real time when planning an event at a desired date, time, and location.

[0158] 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.

[0159] In this invention, the server includes means for acquiring predicted weather data based on the date and location of an event, means for proposing indoor or outdoor activities suitable for the event based on the weather data, means for displaying the proposed activities to a user, means for proposing the activities in a virtual store, and means for a user to input event information in the virtual store application. This allows a user to receive appropriate activity suggestions based on the date and location of the event in real time, enabling efficient event planning.

[0160] "Event information" is data about a specific date and geographic location that a user plans.

[0161] "Weather Data" means data regarding predicted weather conditions for a specified date and location.

[0162] A "weather forecast API" is an application programming interface for externally obtaining weather data for a specified date and location.

[0163] "User" refers to a person who plans an event and uses the system to receive suggestions for suitable activities.

[0164] "Indoor activities" refer to activities that can be carried out inside a building.

[0165] "Outdoor activities" refers to activities that can be carried out outdoors.

[0166] A "virtual store" is a virtual retail space operated on the Internet that can be accessed and used by users.

[0167] A "virtual store application" is software that allows users to input event information within a virtual store and receive suggestions for appropriate activities.

[0168] The present invention relates to an event planning assistant system for a virtual store, which allows a user to receive appropriate activity suggestions based on real-time weather information when planning an event at any date, time, and location.

[0169] System configuration

[0170] The system includes the following components:

[0171] 1. User terminal: A device that provides an interface for users to input event information (date, time, location). Examples include smartphones and smart glasses.

[0172] 2. Server: A program runs that uses the weather forecast API to obtain weather data for the specified date, time, and location, and then suggests appropriate activities based on that data.

[0173] 3. Weather API: Refers to an external weather forecast service from which weather data is obtained (e.g., Weather API).

[0174] 4. Virtual store application: Software that is installed on the user's device and allows the user to input event information, connect to the server to obtain weather data, and receive suggestions.

[0175] Data processing and calculation

[0176] Operation of the user terminal: The user inputs the date and location of the event. This input data is sent to the server.

[0177] Server Action:

[0178] Obtaining weather data: The server uses the weather forecast API to obtain weather information for the specified date, time, and location.

[0179] Data analysis: Analyze the acquired weather data and identify weather conditions such as "sunny" or "rainy."

[0180] Activity Suggestion: Based on the analyzed weather data, it suggests suitable activities (indoor or outdoor). For example, if it's sunny, it suggests outdoor activities (picnic, cycling, walking), and if it's raining, it suggests indoor activities (watching movies, shopping, cafes).

[0181] Data return: A list of suggested activities is returned to the user terminal.

[0182] Display on user terminal: The user terminal analyzes the returned proposal content and displays it in a format that is easy for the user to understand.

[0183] Specific examples

[0184] For example, suppose a user is planning an event in "Osaka" on "2023-12-25." In this case, when the user enters the date and location, the application sends a request to the weather forecast API server. The server retrieves weather data for "Osaka" from the weather forecast API, and the result may be "Snow." Based on the analysis results, the server suggests indoor activities such as "Movies," "Shopping," or "Cafe." This information is sent back to the user's device, and the user can check the suggested activities on their smartphone or smart glasses.

[0185] Example prompts to input to the generative AI model

[0186] Write an application program that suggests appropriate activities based on the weather information for that day and location when a user plans an event for a specific date, time, and location. Specifically, the program will ask the user to enter the date, time, and location of the event, query the weather forecast API, and suggest indoor or outdoor activities based on the weather data obtained. It will also have a function to display the suggested activities to the user.

[0187] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0188] Step 1:

[0189] User enters event information

[0190] The user uses the terminal to input the date and location of the event.

[0191] Input: Date (e.g., 2023-12-25), Venue (e.g., Osaka)

[0192] Output: Request data from the terminal to the server (event date, venue)

[0193] Step 2:

[0194] The device sends a request to the server

[0195] Based on the event information entered on the device, the device sends a request to the weather forecast API server.

[0196] Input: Event information entered by the user (date, location)

[0197] Output: Request data to the weather forecast API server

[0198] Step 3:

[0199] The server retrieves weather data

[0200] The server calls the weather forecast API to retrieve weather data for the specified date and location.

[0201] Input: Request data to the weather forecast API (event date, venue)

[0202] Output: Weather data from the weather forecast API (e.g., snow)

[0203] Step 4:

[0204] The server analyzes the weather data

[0205] The server analyzes the weather data it has acquired and identifies the weather conditions on the day the event is held.

[0206] Input: Weather data

[0207] Output: Analyzed weather conditions (e.g. snow)

[0208] Step 5:

[0209] Server suggests activities

[0210] The server selects the appropriate activity (indoor or outdoor) based on the analyzed weather data.

[0211] Input: Analyzed weather conditions

[0212] Output: A list of suggested activities (e.g., watching movies, shopping, going to a cafe)

[0213] Step 6:

[0214] The server sends the proposal back to the device

[0215] Data containing a list of suggested activities is sent back to the device in JSON format.

[0216] Input: List of suggested activities

[0217] Output: Data returned to the device (activity list in JSON format)

[0218] Step 7:

[0219] The device displays suggestions to the user

[0220] The device analyzes the returned suggestions and displays them to the user in an easy-to-understand format.

[0221] Input: Data to be returned to the device (activity list in JSON format)

[0222] Output: Activity suggestions displayed to the user (e.g., watching a movie, shopping, going to a cafe)

[0223] 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.

[0224] The present invention combines a system that acquires predicted weather data based on the date and location of an event, suggests appropriate indoor or outdoor activities, and displays them to the user, with an emotion engine. This system allows for more appropriate activity suggestions based on the user's emotional state.

[0225] Overall system flow

[0226] 1. User enters event information

[0227] The user enters the date and location of the event into the terminal, for example, "2023-10-20" and "Tokyo."

[0228] 2. The device sends a request to the server

[0229] The device sends a request to a weather forecast server based on the event information entered, including the date and location of the event.

[0230] 3. The server retrieves the weather data

[0231] The server sends a request to the weather forecast API to retrieve weather data for the specified date and location. As an example, consider retrieving the data "sunny" from the weather forecast API.

[0232] 4. The server analyzes the weather data

[0233] The server analyzes the acquired weather data and determines the weather information for the day of the event, such as whether the weather is "sunny," "cloudy," or "rainy."

[0234] 5. The server uses the emotion engine to analyze the user's emotions.

[0235] The server uses an emotion engine to analyze the user's current emotion data, which is collected based on the user's biometric signals and past behavioral history.

[0236] 6. The server suggests activities

[0237] The server then suggests the most suitable activity based on weather data and emotion data obtained from the emotion engine. For example, if it is sunny and the user feels like relaxing, it will suggest "picnic" or "walking."

[0238] 7. The server sends the proposal back to the device

[0239] A list of suggested activities is returned to the device in JSON format, and the server returns the selected activities along with the event date and location information.

[0240] 8. The device displays suggestions to the user

[0241] The device analyzes the returned suggestions and displays them to the user in an easy-to-understand format, such as "Since it's sunny, we suggest the following relaxing outdoor activities: picnic, walking."

[0242] Specific examples

[0243] For example, suppose a user is planning an event in "Tokyo" on "2023-10-20." When the user enters this information into the device, the device sends a request to the weather forecast server. The server retrieves weather data for "Tokyo" from the weather forecast API and obtains the analysis result "sunny." Next, the emotion engine analyzes the user's current psychological state and determines that the user wants to relax. Based on this, the server suggests relaxing outdoor activities such as "picnic" or "walking" and sends the information back to the device. Finally, the device displays the suggested activities to the user.

[0244] In this way, the system has the ability to suggest optimal activities based on the user's emotions and weather conditions, thereby increasing user satisfaction.

[0245] The processing flow will be explained below.

[0246] Step 1:

[0247] The user enters the date and location of the event. For example, "2023-10-20" and "Tokyo" into the device. The device stores this information and proceeds to the next step.

[0248] Step 2:

[0249] The device sends a request to the server based on the input information. The device generates a request including information about the event date and location, and sends it to the server that uses the weather forecast API.

[0250] Step 3:

[0251] The server sends a request to the weather forecast API to retrieve weather data for the specified date and location. The server then accesses an external weather forecast API endpoint to retrieve weather data in JSON format.

[0252] Step 4:

[0253] The server analyzes the weather data it has acquired. The server analyzes the JSON data and identifies the weather information for the event date and location. For example, it extracts weather information such as "sunny," "cloudy," and "rainy."

[0254] Step 5:

[0255] The server uses an emotion engine to analyze the user's emotions. The server inputs the bio-signals and past behavioral history collected from the user into the emotion engine to determine the user's current emotional state. For example, it determines whether the user feels like relaxing.

[0256] Step 6:

[0257] The server suggests activities based on weather data and emotion data. For example, if the weather is "sunny" and the user feels like relaxing, the server will select relaxing outdoor activities such as "picnic" or "walking."

[0258] Step 7:

[0259] The server returns a list of suggested activities in JSON format to the device, and the server returns the selected activities along with the event date and location information to the device.

[0260] Step 8:

[0261] The device parses the activity suggestions received from the server. The device parses the received JSON data and extracts the suggested activities.

[0262] Step 9:

[0263] The device displays suggested activities to the user, such as a message like "It's a sunny day, so we suggest the following relaxing outdoor activities: picnic, walking."

[0264] This concludes the specific processing flow of the activity suggestion system that takes user emotions into account. This system automatically suggests optimal activities based on the user's emotional state and weather conditions.

[0265] Example 2

[0266] 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."

[0267] Conventional event suggestion systems suggest activities based on weather data predicted based on the date and location of the event, but do not consider the user's emotional state when suggesting activities. This can lead to suggested activities that do not match the user's psychological state, resulting in a decrease in user satisfaction.

[0268] 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.

[0269] In this invention, the server includes means for acquiring predicted weather data based on the date and location of the event, means for suggesting indoor or outdoor activities suitable for the event based on the weather data, means for analyzing the user's emotional state, means for selecting an optimal activity based on the weather data and the user's emotional state, and means for displaying the selected activity to the user. This makes it possible to suggest activities that take the user's emotional state into consideration, thereby increasing user satisfaction.

[0270] The "event date" is the specific date on which the event planned by the user will take place.

[0271] A "location" is a geographical location, including the physical location where an event takes place, such as a city or a particular facility.

[0272] "Weather Data" refers to weather information for a particular date and location, including various factors such as temperature, chance of precipitation, wind speed, etc.

[0273] The "user's emotional state" refers to the user's current psychological condition, and includes various emotions such as relaxation, stress, and excitement.

[0274] "Activity" refers to the actions or activities that a user actually performs during an event, and includes specific actions such as a picnic or walking.

[0275] "Means for suggesting" refers to a method or process for selecting the most suitable activity based on the acquired weather data and emotional state and notifying the user of it.

[0276] "Display means" refers to a method or device, such as a smartphone or computer screen, for visually presenting the suggested activity to the user.

[0277] "Emotion engine" refers to a system that includes software or hardware for analyzing a user's emotional state.

[0278] A "weather forecast API" is an application programming interface for obtaining external weather forecast data.

[0279] The "JSON format" is a standardized data exchange format for representing data in a lightweight, easy-to-read text format.

[0280] The present invention is a system that obtains predicted weather data based on the date and location of an event, suggests appropriate indoor or outdoor activities, and displays them to the user. This system also incorporates an emotion engine, which can suggest optimal activities according to the user's emotional state.

[0281] Hardware and software used

[0282] The system uses the following major hardware and software:

[0283] 1. User Device:

[0284] The event will be hosted on devices such as smartphones, computers, and tablets, which can connect to the internet and provide an interface for users to enter event information.

[0285] 2. Server:

[0286] High performance computer systems are used, including systems with web server functionality to process requests, parse data, call external APIs, and run the emotion engine.

[0287] 3. Weather Forecast API:

[0288] An application programming interface is used to provide external weather information, for example, a "weather API" to retrieve weather data for a specific date and location.

[0289] 4. Emotion Engine:

[0290] Software or services are used to analyze the user's emotional state, for example, by using the "Emotion API" to analyze the user's emotional data.

[0291] System Operation Overview

[0292] 1. User enters event information:

[0293] The user uses the device to specify the date and location of the event. For example, they enter "2023-10-20" and "Tokyo." The device has a dedicated input form that allows the user to easily enter information.

[0294] 2. The device sends a request to the server:

[0295] The device sends the event information entered by the user to the server as JSON format data.

[0296] 3. The server retrieves the weather data:

[0297] The server sends a request to the weather API to retrieve weather data for the specified date and location, including information such as temperature, chance of precipitation, and wind speed.

[0298] 4. The server analyzes the weather data:

[0299] The server analyzes the weather data and determines the weather conditions on the day of the event, for example, whether the weather will be "sunny," "cloudy," "rainy," etc.

[0300] 5. The server uses the emotion engine to analyze the user's emotions:

[0301] The server uses an emotion engine to analyze the user's current emotional state, which utilizes bio-signal data and past behavioral history to identify the user's emotional state.

[0302] 6. Server suggests activity:

[0303] The server then suggests the best activity based on the analyzed weather and emotion data. For example, if it's sunny and the user is in the mood to relax, it will suggest a picnic or a walk.

[0304] 7. The server sends the proposal back to the device:

[0305] A list of suggested activities is returned to the device in JSON format.

[0306] 8. The device displays suggestions to the user:

[0307] The device analyzes the data received from the server and displays it in a user-friendly format, for example, "Since it's sunny, we suggest the following relaxing outdoor activities: picnic, walking."

[0308] Specific examples

[0309] For example, suppose a user is planning an event in "Tokyo" on "2023-10-20." When the user enters this information into the device, the device sends a request to the weather forecast server. The server retrieves weather data for Tokyo from the weather forecast API and obtains the analysis result "sunny." Next, the emotion engine analyzes the user's current psychological state and determines that the user wants to relax. Based on this, the server suggests relaxing outdoor activities such as "picnic" or "walking" and sends the information back to the device. Finally, the device displays the suggested activities to the user.

[0310] Prompt Sentence Examples

[0311] Here are some example prompts to input to a generative AI model:

[0312] A user is planning an event in Tokyo on 2023-10-20. The user's current psychological state is that they want to relax. Considering this situation, retrieve weather data from a weather forecast API and suggest appropriate activities.

[0313] In this way, the system has the ability to suggest optimal activities based on the user's emotions and weather conditions, thereby increasing user satisfaction.

[0314] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0315] Step 1:

[0316] The user enters the event information.

[0317] Specific behavior:

[0318] Users access the system using a device such as a smartphone or computer and enter the event date and location. For example, they enter "Date: 2023-10-20" and "Location: Tokyo."

[0319] Input: Event date and location

[0320] Output: Entered event information (date and location)

[0321] Step 2:

[0322] The device sends a request to the server.

[0323] Specific behavior:

[0324] The device converts the event information entered by the user into JSON format and sends an HTTP request to the server.

[0325] Input: Entered event information (date and location)

[0326] Data processing: Convert event information into JSON format

[0327] Output: Event information in JSON format

[0328] Step 3:

[0329] The server retrieves the weather data.

[0330] Specific behavior:

[0331] The server sends a request to the weather forecast API to retrieve weather data for a specific date and location. For example, retrieve weather data for the date "2023-10-20" and location "Tokyo." This data includes temperature, probability of precipitation, wind speed, etc.

[0332] Input: Event information in JSON format

[0333] Data calculation: Send a request to the weather forecast API to obtain weather data

[0334] Output: Weather data (e.g. sunny)

[0335] Step 4:

[0336] The server analyzes the weather data.

[0337] Specific behavior:

[0338] The server analyzes the weather data it has acquired and determines the weather conditions during the day of the event, such as whether it will be sunny, cloudy, or rainy.

[0339] Input: Obtained weather data

[0340] Data Calculation: Weather Data Analysis

[0341] Output: Analysis results (weather conditions: sunny)

[0342] Step 5:

[0343] The server uses an emotion engine to analyze the user's emotions.

[0344] Specific behavior:

[0345] The server sends a request to the emotion engine based on the user's biosignal data and past behavioral history to analyze the user's current emotional state. For example, it identifies the emotion "I want to relax."

[0346] Input: User's biosignal data, past behavior history

[0347] Data Computation: Emotion Analysis with Emotion Engine

[0348] Output: Analysis results (emotional state: Relaxed)

[0349] Step 6:

[0350] The server suggests activities.

[0351] Specific behavior:

[0352] The server selects the most suitable activity based on weather and emotional data. For example, if the weather is sunny and you feel like relaxing, it creates an activity list. Suggestions like "picnic" and "walking" are given.

[0353] Input: Parsed weather data, user emotional state

[0354] Data processing: Selecting the best activity

[0355] Output: Activity list (e.g. picnic, walking)

[0356] Step 7:

[0357] The server sends the proposal back to the device.

[0358] Specific behavior:

[0359] The server generates an activity list and sends it back to the device in JSON format, which includes the dates and locations of the suggested activities and events.

[0360] Input: Activity list, event information

[0361] Data processing: Convert the activity list to JSON format

[0362] Output: Proposal in JSON format

[0363] Step 8:

[0364] The terminal displays the suggestions to the user.

[0365] Specific behavior:

[0366] The device analyzes the data received from the server and displays it in a user-friendly format. For example, it displays "The weather in Tokyo on 2023-10-20 is sunny. Recommended activities are: picnic, walking."

[0367] Input: Proposal content in JSON format

[0368] Data processing: Analyze the proposal content and convert it into a display format

[0369] Output: The suggestions that are displayed to the user

[0370] (Application example 2)

[0371] 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."

[0372] Conventional activity suggestion systems based on weather forecast data make uniform suggestions without considering the user's emotional state. This can result in suggested activities that do not match the user's current mood, which can lead to lower user satisfaction. Furthermore, they are unable to appropriately recommend products and services that the user desires, resulting in ineffective sales promotion, especially in the area of ​​shopping. Therefore, there is a need for a system that can suggest more personalized activities and products based on the user's emotions, thereby improving user satisfaction and experience.

[0373] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring predicted weather data based on the date and location of an event, means for suggesting indoor or outdoor activities suitable for the event based on the weather data, means for displaying the suggested activities to the user, means for analyzing the user's emotion data, means for suggesting specific products based on the weather data and emotion data, and means for displaying the identified products to the user. This makes it possible to suggest more appropriate activities and products according to the user's emotional state, thereby improving user satisfaction.

[0374] "Event" means a particular activity or occurrence taking place on a particular date and at a particular location.

[0375] "Weather Data" means meteorological information relating to a particular date, time and location, generally including factors such as temperature, precipitation, and wind speed.

[0376] "Indoor activities" refers to activities and entertainment that take place inside a building.

[0377] "Outdoor activities" refers to activities and recreation that take place outside of buildings.

[0378] "User" refers to the entity that uses this system, an individual or organization that receives weather forecast data and activity suggestions.

[0379] "Emotion data" is information that reflects the user's psychological state and is obtained through biometric signals, text analysis, and the like.

[0380] "Product Suggestion" refers to a product or service recommended to a user based on certain criteria.

[0381] "Activity suggestions" refers to recommended activities and pastimes based on a particular date and weather conditions, as well as the user's emotional state.

[0382] The present invention relates to a system that obtains predicted weather data based on the date and location of an event, and combines it with a user's emotional data to suggest specific products or activities. This system can increase user satisfaction by making suggestions based on the user's individual emotional state.

[0383] Overall system structure

[0384] The system includes the following main components:

[0385] 1. Weather data acquisition part:

[0386] The server retrieves weather data for the specified date and location from an external weather API (e.g., OpenWeatherMap API).

[0387] 2. Emotion data analysis unit:

[0388] The server uses an emotion analysis engine (e.g., IBM Watson® Emotion Analysis API) to analyze the user's emotion data, which is obtained from text entered directly by the user into the device or from biometric devices such as a smartwatch.

[0389] 3. Activities and Product Proposal Department:

[0390] The server identifies activities and products suitable for the user based on the acquired weather data and the analyzed emotion data.

[0391] 4. Proposal content display area:

[0392] The terminal displays the suggestions returned from the server to the user.

[0393] Hardware and software examples

[0394] Hardware:

[0395] Mobile devices such as smartphones and tablets

[0396] Biosignal acquisition devices such as smartwatches and fitness bands (optional)

[0397] software:

[0398] Weather forecast API (e.g. OpenWeatherMap API)

[0399] Emotion analysis API (e.g. IBM Watson Emotion Analysis API)

[0400] Programming language (e.g. Python)

[0401] Operation flow

[0402] An example of a specific operation of the system is shown below.

[0403] 1. User enters event information:

[0404] The user enters the shopping date and location into the terminal. For example, "2023-10-20" and "Tokyo."

[0405] 2. Get weather data:

[0406] The server retrieves weather data for the specified date and location through the weather forecast API. For example, the weather data for "sunny" is retrieved.

[0407] 3. Emotional Data Analysis:

[0408] The server uses an emotion analysis engine to analyze the user's current emotional state, for example, determining that the user feels "relaxed."

[0409] 4. Activity and Product Suggestions:

[0410] The server uses weather and emotion data to suggest activities and products suitable for the user, such as "picnic equipment," "outdoor reading chair," and "walking shoes."

[0411] 5. View Proposals:

[0412] The terminal displays the proposal content received from the server to the user.

[0413] Specific examples

[0414] For example, suppose a user plans to go shopping in "Tokyo" on "2023-10-20." When the user enters this information into the device, the device retrieves weather data via a weather forecast API, which parses it as "sunny." Next, the sentiment analysis engine analyzes the user's emotional data and determines that the user wants to relax. Based on this, the server suggests relaxing outdoor activity products such as "picnic equipment," "outdoor reading chair," and "walking shoes." Finally, the device displays the suggested products to the user.

[0415] Prompt Sentence Examples

[0416] Here are some example input and output prompts:

[0417] Example of input prompt sentence:

[0418] A user is planning to go shopping in "Tokyo" on "2023-10-20." They also state that their current mood is "I want to relax." The weather forecast data from the weather forecast API is "Sunny." Based on these conditions, what products should you suggest?

[0419] Example of output prompt statement:

[0420] For a shopping plan in Tokyo on "2023-10-20," the following products are suggested based on the sunny weather forecast and the user's desire to "relax":

[0421] 1. Picnic equipment

[0422] 2. Outdoor reading chair

[0423] 3. Walking shoes

[0424] In this way, the system can suggest optimal products and activities according to the user's emotional state, thereby increasing user satisfaction.

[0425] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0426] Step 1:

[0427] The user enters event information into the terminal. Specifically, the shopping date and location. The entered event information is "2023-10-20" and "Tokyo." Once this data is entered, the terminal sends it to the server. The input is passed to the server as initial data.

[0428] Step 2:

[0429] The server obtains weather forecast data. The server sends a request to a weather forecast API (e.g., OpenWeatherMap API) based on the received event information ("2023-10-20" and "Tokyo"). The API responds with weather data (e.g., "sunny"). The server analyzes this weather data and determines the weather conditions for the specified date.

[0430] Step 3:

[0431] The server analyzes the emotional data. The server uses an emotion analysis engine (e.g., IBM Watson Emotion Analysis API) to analyze the user's emotional state. This information is collected based on text entered by the user (e.g., "I want to relax") and data from biometric devices such as smartwatches. By analyzing the input data, the user's emotional state (e.g., "Relaxed") is identified.

[0432] Step 4:

[0433] The server suggests activities and products. The server selects appropriate activities and products based on weather data ("sunny") and emotion data ("relaxed"). For example, for a user who wants to relax on a sunny day, "picnic equipment," "outdoor reading chair," and "walking shoes" are suggested. This selected information is formed as suggestion data.

[0434] Step 5:

[0435] The server sends the recommendations back to the device. The server sends a list of selected activities and products in JSON format to the device, including the date and location of the event. The JSON data is passed to the device.

[0436] Step 6:

[0437] The device displays the suggestions to the user. The device analyzes the suggestion data received from the server and displays it in a format that is easy for the user to understand. For example, it might say, "For your shopping plans in Tokyo on 2023-10-20, we suggest the following relaxing products for a sunny day: picnic equipment, outdoor reading chair, and walking shoes." The suggested information is presented to the user visually.

[0438] 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.

[0439] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0440] 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.

[0441] [Second embodiment]

[0442] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0443] 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.

[0444] 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).

[0445] 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.

[0446] 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.

[0447] 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).

[0448] 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.

[0449] 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.

[0450] 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.

[0451] 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.

[0452] 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.

[0453] 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."

[0454] The present invention relates to a system that obtains predicted weather data based on the date and location of an event, suggests appropriate indoor or outdoor activities, and displays them to users, with the aim of improving user convenience and increasing the success rate of the event.

[0455] Overall system flow

[0456] 1. User enters event information

[0457] The user enters the date and location of the event on the terminal, for example, "2023-10-20" and "Tokyo."

[0458] 2. The device sends a request to the server

[0459] Based on the input event information, the device sends a request to a server dedicated to weather forecast APIs, which then calls the weather forecast API and retrieves weather data for the specified date and location.

[0460] 3. The server analyzes the weather data

[0461] The server analyzes the weather data and determines the weather on the day of the event. For example, it may obtain data indicating "sunny" from a weather forecast API.

[0462] 4. The server suggests activities

[0463] The server then selects the appropriate activity (indoor or outdoor) based on the analyzed weather data. For example, if it's sunny, it will suggest outdoor activities such as "picnic," "cycling," and "walking."

[0464] 5. The server sends the proposal back to the device

[0465] Data containing a list of suggested activities is sent back to the device in JSON format.

[0466] 6. The device displays suggestions to the user

[0467] The device then analyzes the returned suggestions and displays them to the user in an easy-to-understand format, such as "It's sunny, so we suggest the following outdoor activities: picnic, cycling, walking."

[0468] Specific examples

[0469] For example, suppose a user is planning an event in "Tokyo" on "2023-10-20." In this case, when the user enters this information into the device, the device sends a request to the weather forecast API server. The server retrieves weather data for "Tokyo" from the weather forecast API and analyzes the results to determine that it will be "sunny." Based on the analysis results, the server suggests outdoor activities such as "picnic," "cycling," and "walking," and sends this information back to the device. Finally, the device displays the suggested activities to the user.

[0470] This system allows users to efficiently plan events by automatically suggesting activities suitable for the event date and location, and by selecting activities appropriate for the weather, it can increase participant satisfaction.

[0471] The processing flow will be explained below.

[0472] Step 1:

[0473] The user enters the date and location of the event. For example, the user enters "2023-10-20" and "Tokyo" into the terminal. The terminal stores this information and proceeds to the next processing step.

[0474] Step 2:

[0475] The device sends a request to the server based on the input information. Specifically, it generates a request to use the weather forecast API and sends it to the server. This request includes information about the date and location of the event.

[0476] Step 3:

[0477] The server sends a request to the weather forecast API to get weather data for a specified date and location. Here, the server accesses an external weather forecast API endpoint and receives weather data in JSON format.

[0478] Step 4:

[0479] The weather data acquired by the server is analyzed. Specifically, the JSON data is analyzed and daytime weather information for the event is extracted. For example, it identifies whether the weather is "sunny," "cloudy," or "rainy."

[0480] Step 5:

[0481] The server suggests activities based on the analyzed weather data. If the weather is "sunny" or "cloudy," the server selects outdoor activities such as "picnic," "cycling," or "walking." If the weather is "rainy," the server selects indoor activities such as "watching a movie," "bowling," or "visiting a museum."

[0482] Step 6:

[0483] The server returns a list of suggested activities in JSON format to the device, along with the selected activity, along with the event date and location information.

[0484] Step 7:

[0485] The device parses the activity suggestions received from the server. The device parses the received JSON data and extracts the suggested activities.

[0486] Step 8:

[0487] The device displays suggested activities to the user. The device clearly displays the analysis results and displays a message such as, "It's sunny today, so we suggest the following outdoor activities: picnic, cycling, walking."

[0488] This allows users to easily find the best activities for their event date and location.

[0489] Example 1

[0490] 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."

[0491] In conventional event planning, it is difficult to select appropriate activities based on the weather, and there is a high risk that outdoor events will be canceled due to bad weather, especially. Furthermore, users have to check the weather forecast and select activities based on it, which reduces the chances of the event being successful. There is a need to solve these problems and improve user convenience.

[0492] 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.

[0493] In this invention, the server includes a means for the user to input event information, a means for the terminal to transmit the event information to the server, and a means for the server to analyze weather data and select appropriate activities. This allows the user to receive suggestions for optimal activities based on the weather simply by inputting the event information, increasing the success rate of the event and significantly reducing the user's effort.

[0494] "Event information" is information about the date and location of an event designated by the user.

[0495] "Weather data" is meteorological information for a specified date and location, including temperature, probability of precipitation, weather conditions, and the like.

[0496] "Indoor activities" are activities or events that take place inside a building and are less susceptible to weather.

[0497] "Outdoor activities" are activities or events that take place outdoors and are subject to weather.

[0498] A "user" is a person or organization that uses this system to input event information and receive activity suggestions.

[0499] A "terminal" is a device used by a user to input event information and display activity suggestions.

[0500] The "server" is the central computing system responsible for acquiring, analyzing, and suggesting activities on the weather data.

[0501] A "weather forecast API" is an external service that provides weather information over the Internet and is used by servers to obtain weather data.

[0502] "Activity suggestions" refers to providing the user with suitable indoor or outdoor activities based on the acquired weather data.

[0503] The "JSON format" is a type of data exchange format that is lightweight, easy to read, and suitable for data communication between programs.

[0504] An "HTTP request" is a communication protocol that allows a client to request data from a server, and is primarily used when using web services.

[0505] MODE FOR CARRYING OUT THE INVENTION

[0506] The present invention is a system that obtains predicted weather data based on the date and location of an event, and then suggests and displays suitable indoor or outdoor activities to the user based on the results. The main purpose of this system is to improve user convenience and increase the success rate of the event. A detailed implementation method of this system is described below.

[0507] 1. Enter your event information

[0508] The user uses the device to input the date and location of the event. Specifically, they enter information such as "2023-10-20" and "Tokyo" through an input form. This input can be done via a web browser or a dedicated application.

[0509] 2. Sending event information

[0510] The device sends the event information obtained from the user to the server. Specifically, it generates an HTTP request and sends it to a server dedicated to weather forecast APIs. The server uses an HTTP GET request to obtain weather data for the specified date and location from an external API (e.g., OpenWeatherMap or WeatherAPI).

[0511] 3. Weather data acquisition and analysis

[0512] The server analyzes weather data obtained from an external weather forecast API. The obtained data is in JSON format, and the server parses it to extract the necessary weather information. For example, the server identifies the information "sunny" from the analyzed weather data.

[0513] 4. Activity Selection

[0514] The server then selects appropriate activities based on the analysis results. These activities are chosen from a predefined list, and the selection criteria vary depending on the weather conditions. For example, if it's sunny, outdoor activities such as "picnic," "cycling," and "walking" will be suggested.

[0515] 5. Sending data from the server to the device

[0516] The selected activity list is sent back to the device from the server in JSON format, including the name and brief description of the suggested activity.

[0517] 6. Display of Suggestions

[0518] The device parses the received JSON data and displays the analysis results in a user-friendly format. For example, it may display text such as "It's sunny, so the following outdoor activities are suggested: picnic, cycling, walking." This allows the user to easily select the most suitable activity.

[0519] As a concrete example, if a user is planning an event in "Tokyo" on "2023-10-20," the user enters this information into the device, and the device sends a request to the server. The server retrieves weather data for "Tokyo" from the weather forecast API and analyzes the results to determine that it is "sunny." Based on the analysis results, the server suggests outdoor activities such as "picnic," "cycling," and "walking," and sends this information back to the device. Finally, the device displays the suggested activities to the user.

[0520] As an example of a prompt sentence, the following prompt sentence can be input to the generative AI model:

[0521] "I'm planning to hold an event in Tokyo on 2023-10-20. Please analyze the weather forecast data for this date and suggest appropriate activities."

[0522] This system allows users to receive appropriate activity suggestions based on the weather, enabling efficient event planning and is expected to increase participant satisfaction.

[0523] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0524] Step 1:

[0525] The user enters the event information.

[0526] The user enters the date and location of the event on the device. This information is received through a form, and the user presses the "Submit" button to move to the next step. The specific information entered is, for example, "2023-10-20" and "Tokyo."

[0527] input:

[0528] Date of event (e.g. 2023-10-20)

[0529] Venue (e.g. Tokyo)

[0530] output:

[0531] Request to send event information (e.g. HTTP request)

[0532] Step 2:

[0533] The device sends a request to the server.

[0534] Based on the event information entered by the user, the device generates request data and sends it to the server as an HTTP GET request. At this time, the device accesses a specific API endpoint and requests the acquisition of weather data.

[0535] input:

[0536] Event information (date, location)

[0537] output:

[0538] HTTP request to the server

[0539] Step 3:

[0540] The server retrieves the weather data.

[0541] The server accesses an external weather forecast API based on the received request to retrieve weather data for the specified date and location. This process uses an HTTP GET request to retrieve the weather forecast, adding the API key and parameters.

[0542] input:

[0543] HTTP request to the server

[0544] output:

[0545] Weather data from an external API (JSON format)

[0546] Step 4:

[0547] The server analyzes the weather data.

[0548] The server analyzes the acquired weather data and identifies the weather on the day of the event. It parses the JSON format data and extracts weather conditions such as "sunny" or "rainy" from the "weather" key. The analysis results are processed by flagging any that match a specific weather condition.

[0549] input:

[0550] Weather data obtained from an external API (JSON format)

[0551] output:

[0552] Weather data analysis results (e.g. "Sunny")

[0553] Step 5:

[0554] The server suggests activities.

[0555] The server then selects appropriate activities from a predefined list based on the analyzed weather data. For example, if the weather is sunny, outdoor activities such as "picnic," "cycling," and "walking" are suggested.

[0556] input:

[0557] Weather data analysis results (e.g. "Sunny")

[0558] output:

[0559] List of suggested activities (e.g., "picnic," "cycling," "walking")

[0560] Step 6:

[0561] The server sends the proposal back to the device.

[0562] The selected activity list is sent back to the device from the server in JSON format, including the name and brief description of the suggested activity.

[0563] input:

[0564] List of suggested activities (e.g., "picnic," "cycling," "walking")

[0565] output:

[0566] Response data to the terminal (JSON format)

[0567] Step 7:

[0568] The terminal displays the suggestions to the user.

[0569] The device parses the received JSON data and displays the analysis results in a user-friendly format, such as "It's sunny, so the following outdoor activities are suggested: picnic, cycling, walking."

[0570] input:

[0571] Response data from the server (JSON format)

[0572] output:

[0573] What to show the user (e.g., "It's a sunny day, so we suggest the following outdoor activities: picnic, cycling, walking")

[0574] (Application example 1)

[0575] 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."

[0576] The challenge is to increase the success rate of events planned by users by quickly and efficiently suggesting appropriate activities according to the weather on the day of the event. In particular, there is a need to provide an environment in virtual stores where users can receive appropriate activity suggestions in real time when planning an event at a desired date, time, and location.

[0577] 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.

[0578] In this invention, the server includes means for acquiring predicted weather data based on the date and location of an event, means for proposing indoor or outdoor activities suitable for the event based on the weather data, means for displaying the proposed activities to a user, means for proposing the activities in a virtual store, and means for a user to input event information in the virtual store application. This allows a user to receive appropriate activity suggestions based on the date and location of the event in real time, enabling efficient event planning.

[0579] "Event information" is data about a specific date and geographic location that a user plans.

[0580] "Weather Data" means data regarding predicted weather conditions for a specified date and location.

[0581] A "weather forecast API" is an application programming interface for externally obtaining weather data for a specified date and location.

[0582] "User" refers to a person who plans an event and uses the system to receive suggestions for suitable activities.

[0583] "Indoor activities" refer to activities that can be carried out inside a building.

[0584] "Outdoor activities" refers to activities that can be carried out outdoors.

[0585] A "virtual store" is a virtual retail space operated on the Internet that can be accessed and used by users.

[0586] A "virtual store application" is software that allows users to input event information within a virtual store and receive suggestions for appropriate activities.

[0587] The present invention relates to an event planning assistant system for a virtual store, which allows a user to receive appropriate activity suggestions based on real-time weather information when planning an event at any date, time, and location.

[0588] System configuration

[0589] The system includes the following components:

[0590] 1. User terminal: A device that provides an interface for users to input event information (date, time, location). Examples include smartphones and smart glasses.

[0591] 2. Server: A program runs that uses the weather forecast API to obtain weather data for the specified date, time, and location, and then suggests appropriate activities based on that data.

[0592] 3. Weather API: Refers to an external weather forecast service from which weather data is obtained (e.g., Weather API).

[0593] 4. Virtual store application: Software that is installed on the user's device and allows the user to input event information, connect to the server to obtain weather data, and receive suggestions.

[0594] Data processing and calculation

[0595] Operation of the user terminal: The user inputs the date and location of the event. This input data is sent to the server.

[0596] Server Action:

[0597] Obtaining weather data: The server uses the weather forecast API to obtain weather information for the specified date, time, and location.

[0598] Data analysis: Analyze the acquired weather data and identify weather conditions such as "sunny" or "rainy."

[0599] Activity Suggestion: Based on the analyzed weather data, it suggests suitable activities (indoor or outdoor). For example, if it's sunny, it suggests outdoor activities (picnic, cycling, walking), and if it's raining, it suggests indoor activities (watching movies, shopping, cafes).

[0600] Data return: A list of suggested activities is returned to the user terminal.

[0601] Display on user terminal: The user terminal analyzes the returned proposal content and displays it in a format that is easy for the user to understand.

[0602] Specific examples

[0603] For example, suppose a user is planning an event in "Osaka" on "2023-12-25." In this case, when the user enters the date and location, the application sends a request to the weather forecast API server. The server retrieves weather data for "Osaka" from the weather forecast API, and the result may be "Snow." Based on the analysis results, the server suggests indoor activities such as "Movies," "Shopping," or "Cafe." This information is sent back to the user's device, and the user can check the suggested activities on their smartphone or smart glasses.

[0604] Example prompts to input to the generative AI model

[0605] Write an application program that suggests appropriate activities based on the weather information for that day and location when a user plans an event for a specific date, time, and location. Specifically, the program will ask the user to enter the date, time, and location of the event, query the weather forecast API, and suggest indoor or outdoor activities based on the weather data obtained. It will also have a function to display the suggested activities to the user.

[0606] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0607] Step 1:

[0608] User enters event information

[0609] The user uses the terminal to input the date and location of the event.

[0610] Input: Date (e.g., 2023-12-25), Venue (e.g., Osaka)

[0611] Output: Request data from the terminal to the server (event date, venue)

[0612] Step 2:

[0613] The device sends a request to the server

[0614] Based on the event information entered on the device, the device sends a request to the weather forecast API server.

[0615] Input: Event information entered by the user (date, location)

[0616] Output: Request data to the weather forecast API server

[0617] Step 3:

[0618] The server retrieves weather data

[0619] The server calls the weather forecast API to retrieve weather data for the specified date and location.

[0620] Input: Request data to the weather forecast API (event date, venue)

[0621] Output: Weather data from the weather forecast API (e.g., snow)

[0622] Step 4:

[0623] The server analyzes the weather data

[0624] The server analyzes the weather data it has acquired and identifies the weather conditions on the day the event is held.

[0625] Input: Weather data

[0626] Output: Analyzed weather conditions (e.g. snow)

[0627] Step 5:

[0628] Server suggests activities

[0629] The server selects the appropriate activity (indoor or outdoor) based on the analyzed weather data.

[0630] Input: Analyzed weather conditions

[0631] Output: A list of suggested activities (e.g., watching movies, shopping, going to a cafe)

[0632] Step 6:

[0633] The server sends the proposal back to the device

[0634] Data containing a list of suggested activities is sent back to the device in JSON format.

[0635] Input: List of suggested activities

[0636] Output: Data returned to the device (activity list in JSON format)

[0637] Step 7:

[0638] The device displays suggestions to the user

[0639] The device analyzes the returned suggestions and displays them to the user in an easy-to-understand format.

[0640] Input: Data to be returned to the device (activity list in JSON format)

[0641] Output: Activity suggestions displayed to the user (e.g., watching a movie, shopping, going to a cafe)

[0642] 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.

[0643] The present invention combines a system that acquires predicted weather data based on the date and location of an event, suggests appropriate indoor or outdoor activities, and displays them to the user, with an emotion engine. This system allows for more appropriate activity suggestions based on the user's emotional state.

[0644] Overall system flow

[0645] 1. User enters event information

[0646] The user enters the date and location of the event into the terminal, for example, "2023-10-20" and "Tokyo."

[0647] 2. The device sends a request to the server

[0648] The device sends a request to a weather forecast server based on the event information entered, including the date and location of the event.

[0649] 3. The server retrieves the weather data

[0650] The server sends a request to the weather forecast API to retrieve weather data for the specified date and location. As an example, consider retrieving the data "sunny" from the weather forecast API.

[0651] 4. The server analyzes the weather data

[0652] The server analyzes the acquired weather data and determines the weather information for the day of the event, such as whether the weather is "sunny," "cloudy," or "rainy."

[0653] 5. The server uses the emotion engine to analyze the user's emotions.

[0654] The server uses an emotion engine to analyze the user's current emotion data, which is collected based on the user's biometric signals and past behavioral history.

[0655] 6. The server suggests activities

[0656] The server then suggests the most suitable activity based on weather data and emotion data obtained from the emotion engine. For example, if it is sunny and the user feels like relaxing, it will suggest "picnic" or "walking."

[0657] 7. The server sends the proposal back to the device

[0658] A list of suggested activities is returned to the device in JSON format, and the server returns the selected activities along with the event date and location information.

[0659] 8. The device displays suggestions to the user

[0660] The device analyzes the returned suggestions and displays them to the user in an easy-to-understand format, such as "Since it's sunny, we suggest the following relaxing outdoor activities: picnic, walking."

[0661] Specific examples

[0662] For example, suppose a user is planning an event in "Tokyo" on "2023-10-20." When the user enters this information into the device, the device sends a request to the weather forecast server. The server retrieves weather data for "Tokyo" from the weather forecast API and obtains the analysis result "sunny." Next, the emotion engine analyzes the user's current psychological state and determines that the user wants to relax. Based on this, the server suggests relaxing outdoor activities such as "picnic" or "walking" and sends the information back to the device. Finally, the device displays the suggested activities to the user.

[0663] In this way, the system has the ability to suggest optimal activities based on the user's emotions and weather conditions, thereby increasing user satisfaction.

[0664] The processing flow will be explained below.

[0665] Step 1:

[0666] The user enters the date and location of the event. For example, "2023-10-20" and "Tokyo" into the device. The device stores this information and proceeds to the next step.

[0667] Step 2:

[0668] The device sends a request to the server based on the input information. The device generates a request including information about the event date and location, and sends it to the server that uses the weather forecast API.

[0669] Step 3:

[0670] The server sends a request to the weather forecast API to retrieve weather data for the specified date and location. The server then accesses an external weather forecast API endpoint to retrieve weather data in JSON format.

[0671] Step 4:

[0672] The server analyzes the weather data it has acquired. The server analyzes the JSON data and identifies the weather information for the event date and location. For example, it extracts weather information such as "sunny," "cloudy," and "rainy."

[0673] Step 5:

[0674] The server uses an emotion engine to analyze the user's emotions. The server inputs the bio-signals and past behavioral history collected from the user into the emotion engine to determine the user's current emotional state. For example, it determines whether the user feels like relaxing.

[0675] Step 6:

[0676] The server suggests activities based on weather data and emotion data. For example, if the weather is "sunny" and the user feels like relaxing, the server will select relaxing outdoor activities such as "picnic" or "walking."

[0677] Step 7:

[0678] The server returns a list of suggested activities in JSON format to the device, and the server returns the selected activities along with the event date and location information to the device.

[0679] Step 8:

[0680] The device parses the activity suggestions received from the server. The device parses the received JSON data and extracts the suggested activities.

[0681] Step 9:

[0682] The device displays suggested activities to the user, such as a message like "It's a sunny day, so we suggest the following relaxing outdoor activities: picnic, walking."

[0683] This concludes the specific processing flow of the activity suggestion system that takes user emotions into account. This system automatically suggests optimal activities based on the user's emotional state and weather conditions.

[0684] Example 2

[0685] 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."

[0686] Conventional event suggestion systems suggest activities based on weather data predicted based on the date and location of the event, but do not consider the user's emotional state when suggesting activities. This can lead to suggested activities that do not match the user's psychological state, resulting in a decrease in user satisfaction.

[0687] 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.

[0688] In this invention, the server includes means for acquiring predicted weather data based on the date and location of the event, means for suggesting indoor or outdoor activities suitable for the event based on the weather data, means for analyzing the user's emotional state, means for selecting an optimal activity based on the weather data and the user's emotional state, and means for displaying the selected activity to the user. This makes it possible to suggest activities that take the user's emotional state into consideration, thereby increasing user satisfaction.

[0689] The "event date" is the specific date on which the event planned by the user will take place.

[0690] A "location" is a geographical location, including the physical location where an event takes place, such as a city or a particular facility.

[0691] "Weather Data" refers to weather information for a particular date and location, including various factors such as temperature, chance of precipitation, wind speed, etc.

[0692] The "user's emotional state" refers to the user's current psychological condition, and includes various emotions such as relaxation, stress, and excitement.

[0693] "Activity" refers to the actions or activities that a user actually performs during an event, and includes specific actions such as a picnic or walking.

[0694] "Means for suggesting" refers to a method or process for selecting the most suitable activity based on the acquired weather data and emotional state and notifying the user of it.

[0695] "Display means" refers to a method or device, such as a smartphone or computer screen, for visually presenting the suggested activity to the user.

[0696] "Emotion engine" refers to a system that includes software or hardware for analyzing a user's emotional state.

[0697] A "weather forecast API" is an application programming interface for obtaining external weather forecast data.

[0698] The "JSON format" is a standardized data exchange format for representing data in a lightweight, easy-to-read text format.

[0699] The present invention is a system that obtains predicted weather data based on the date and location of an event, suggests appropriate indoor or outdoor activities, and displays them to the user. This system also incorporates an emotion engine, which can suggest optimal activities according to the user's emotional state.

[0700] Hardware and software used

[0701] The system uses the following major hardware and software:

[0702] 1. User Device:

[0703] The event will be hosted on devices such as smartphones, computers, and tablets, which can connect to the internet and provide an interface for users to enter event information.

[0704] 2. Server:

[0705] High performance computer systems are used, including systems with web server functionality to process requests, parse data, call external APIs, and run the emotion engine.

[0706] 3. Weather Forecast API:

[0707] An application programming interface is used to provide external weather information, for example, a "weather API" to retrieve weather data for a specific date and location.

[0708] 4. Emotion Engine:

[0709] Software or services are used to analyze the user's emotional state, for example, by using the "Emotion API" to analyze the user's emotional data.

[0710] System Operation Overview

[0711] 1. User enters event information:

[0712] The user uses the device to specify the date and location of the event. For example, they enter "2023-10-20" and "Tokyo." The device has a dedicated input form that allows the user to easily enter information.

[0713] 2. The device sends a request to the server:

[0714] The device sends the event information entered by the user to the server as JSON format data.

[0715] 3. The server retrieves the weather data:

[0716] The server sends a request to the weather API to retrieve weather data for the specified date and location, including information such as temperature, chance of precipitation, and wind speed.

[0717] 4. The server analyzes the weather data:

[0718] The server analyzes the weather data and determines the weather conditions on the day of the event, for example, whether the weather will be "sunny," "cloudy," "rainy," etc.

[0719] 5. The server uses the emotion engine to analyze the user's emotions:

[0720] The server uses an emotion engine to analyze the user's current emotional state, which utilizes bio-signal data and past behavioral history to identify the user's emotional state.

[0721] 6. Server suggests activity:

[0722] The server then suggests the best activity based on the analyzed weather and emotion data. For example, if it's sunny and the user is in the mood to relax, it will suggest a picnic or a walk.

[0723] 7. The server sends the proposal back to the device:

[0724] A list of suggested activities is returned to the device in JSON format.

[0725] 8. The device displays suggestions to the user:

[0726] The device analyzes the data received from the server and displays it in a user-friendly format, for example, "Since it's sunny, we suggest the following relaxing outdoor activities: picnic, walking."

[0727] Specific examples

[0728] For example, suppose a user is planning an event in "Tokyo" on "2023-10-20." When the user enters this information into the device, the device sends a request to the weather forecast server. The server retrieves weather data for Tokyo from the weather forecast API and obtains the analysis result "sunny." Next, the emotion engine analyzes the user's current psychological state and determines that the user wants to relax. Based on this, the server suggests relaxing outdoor activities such as "picnic" or "walking" and sends the information back to the device. Finally, the device displays the suggested activities to the user.

[0729] Prompt Sentence Examples

[0730] Here are some example prompts to input to a generative AI model:

[0731] A user is planning an event in Tokyo on 2023-10-20. The user's current psychological state is that they want to relax. Considering this situation, retrieve weather data from a weather forecast API and suggest appropriate activities.

[0732] In this way, the system has the ability to suggest optimal activities based on the user's emotions and weather conditions, thereby increasing user satisfaction.

[0733] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0734] Step 1:

[0735] The user enters the event information.

[0736] Specific behavior:

[0737] Users access the system using a device such as a smartphone or computer and enter the event date and location. For example, they enter "Date: 2023-10-20" and "Location: Tokyo."

[0738] Input: Event date and location

[0739] Output: Entered event information (date and location)

[0740] Step 2:

[0741] The device sends a request to the server.

[0742] Specific behavior:

[0743] The device converts the event information entered by the user into JSON format and sends an HTTP request to the server.

[0744] Input: Entered event information (date and location)

[0745] Data processing: Convert event information into JSON format

[0746] Output: Event information in JSON format

[0747] Step 3:

[0748] The server retrieves the weather data.

[0749] Specific behavior:

[0750] The server sends a request to the weather forecast API to retrieve weather data for a specific date and location. For example, retrieve weather data for the date "2023-10-20" and location "Tokyo." This data includes temperature, probability of precipitation, wind speed, etc.

[0751] Input: Event information in JSON format

[0752] Data calculation: Send a request to the weather forecast API to obtain weather data

[0753] Output: Weather data (e.g. sunny)

[0754] Step 4:

[0755] The server analyzes the weather data.

[0756] Specific behavior:

[0757] The server analyzes the weather data it has acquired and determines the weather conditions during the day of the event, such as whether it will be sunny, cloudy, or rainy.

[0758] Input: Obtained weather data

[0759] Data Calculation: Weather Data Analysis

[0760] Output: Analysis results (weather conditions: sunny)

[0761] Step 5:

[0762] The server uses an emotion engine to analyze the user's emotions.

[0763] Specific behavior:

[0764] The server sends a request to the emotion engine based on the user's biosignal data and past behavioral history to analyze the user's current emotional state. For example, it identifies the emotion "I want to relax."

[0765] Input: User's biosignal data, past behavior history

[0766] Data Computation: Emotion Analysis with Emotion Engine

[0767] Output: Analysis results (emotional state: Relaxed)

[0768] Step 6:

[0769] The server suggests activities.

[0770] Specific behavior:

[0771] The server selects the most suitable activity based on weather and emotional data. For example, if the weather is sunny and you feel like relaxing, it creates an activity list. Suggestions like "picnic" and "walking" are given.

[0772] Input: Parsed weather data, user emotional state

[0773] Data processing: Selecting the best activity

[0774] Output: Activity list (e.g. picnic, walking)

[0775] Step 7:

[0776] The server sends the proposal back to the device.

[0777] Specific behavior:

[0778] The server generates an activity list and sends it back to the device in JSON format, which includes the dates and locations of the suggested activities and events.

[0779] Input: Activity list, event information

[0780] Data processing: Convert the activity list to JSON format

[0781] Output: Proposal in JSON format

[0782] Step 8:

[0783] The terminal displays the suggestions to the user.

[0784] Specific behavior:

[0785] The device analyzes the data received from the server and displays it in a user-friendly format. For example, it displays "The weather in Tokyo on 2023-10-20 is sunny. Recommended activities are: picnic, walking."

[0786] Input: Proposal content in JSON format

[0787] Data processing: Analyze the proposal content and convert it into a display format

[0788] Output: The suggestions that are displayed to the user

[0789] (Application example 2)

[0790] 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."

[0791] Conventional activity suggestion systems based on weather forecast data make uniform suggestions without considering the user's emotional state. This can result in suggested activities that do not match the user's current mood, which can lead to lower user satisfaction. Furthermore, they are unable to appropriately recommend products and services that the user desires, resulting in ineffective sales promotion, especially in the area of ​​shopping. Therefore, there is a need for a system that can suggest more personalized activities and products based on the user's emotions, thereby improving user satisfaction and experience.

[0792] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring predicted weather data based on the date and location of an event, means for suggesting indoor or outdoor activities suitable for the event based on the weather data, means for displaying the suggested activities to the user, means for analyzing the user's emotion data, means for suggesting specific products based on the weather data and emotion data, and means for displaying the identified products to the user. This makes it possible to suggest more appropriate activities and products according to the user's emotional state, thereby improving user satisfaction.

[0793] "Event" means a particular activity or occurrence taking place on a particular date and at a particular location.

[0794] "Weather Data" means meteorological information relating to a particular date, time and location, generally including factors such as temperature, precipitation, and wind speed.

[0795] "Indoor activities" refers to activities and entertainment that take place inside a building.

[0796] "Outdoor activities" refers to activities and recreation that take place outside of buildings.

[0797] "User" refers to the entity that uses this system, an individual or organization that receives weather forecast data and activity suggestions.

[0798] "Emotion data" is information that reflects the user's psychological state and is obtained through biometric signals, text analysis, and the like.

[0799] "Product Suggestion" refers to a product or service recommended to a user based on certain criteria.

[0800] "Activity suggestions" refers to recommended activities and pastimes based on a particular date and weather conditions, as well as the user's emotional state.

[0801] The present invention relates to a system that obtains predicted weather data based on the date and location of an event, and combines it with a user's emotional data to suggest specific products or activities. This system can increase user satisfaction by making suggestions based on the user's individual emotional state.

[0802] Overall system structure

[0803] The system includes the following main components:

[0804] 1. Weather data acquisition part:

[0805] The server retrieves weather data for the specified date and location from an external weather API (e.g., OpenWeatherMap API).

[0806] 2. Emotion data analysis unit:

[0807] The server uses an emotion analysis engine (e.g., IBM Watson Emotion Analysis API) to analyze the user's emotion data, which is obtained from text entered directly by the user into the device or from biometric devices such as a smartwatch.

[0808] 3. Activities and Product Proposal Department:

[0809] The server identifies activities and products suitable for the user based on the acquired weather data and the analyzed emotion data.

[0810] 4. Proposal content display area:

[0811] The terminal displays the suggestions returned from the server to the user.

[0812] Hardware and software examples

[0813] Hardware:

[0814] Mobile devices such as smartphones and tablets

[0815] Biosignal acquisition devices such as smartwatches and fitness bands (optional)

[0816] software:

[0817] Weather forecast API (e.g. OpenWeatherMap API)

[0818] Emotion analysis API (e.g. IBM Watson Emotion Analysis API)

[0819] Programming language (e.g. Python)

[0820] Operation flow

[0821] An example of a specific operation of the system is shown below.

[0822] 1. User enters event information:

[0823] The user enters the shopping date and location into the terminal. For example, "2023-10-20" and "Tokyo."

[0824] 2. Get weather data:

[0825] The server retrieves weather data for the specified date and location through the weather forecast API. For example, the weather data for "sunny" is retrieved.

[0826] 3. Emotional Data Analysis:

[0827] The server uses an emotion analysis engine to analyze the user's current emotional state, for example, determining that the user feels "relaxed."

[0828] 4. Activity and Product Suggestions:

[0829] The server uses weather and emotion data to suggest activities and products suitable for the user, such as "picnic equipment," "outdoor reading chair," and "walking shoes."

[0830] 5. View Proposals:

[0831] The terminal displays the proposal content received from the server to the user.

[0832] Specific examples

[0833] For example, suppose a user plans to go shopping in "Tokyo" on "2023-10-20." When the user enters this information into the device, the device retrieves weather data via a weather forecast API, which parses it as "sunny." Next, the sentiment analysis engine analyzes the user's emotional data and determines that the user wants to relax. Based on this, the server suggests relaxing outdoor activity products such as "picnic equipment," "outdoor reading chair," and "walking shoes." Finally, the device displays the suggested products to the user.

[0834] Prompt Sentence Examples

[0835] Here are some example input and output prompts:

[0836] Example of input prompt sentence:

[0837] A user is planning to go shopping in "Tokyo" on "2023-10-20." They also state that their current mood is "I want to relax." The weather forecast data from the weather forecast API is "Sunny." Based on these conditions, what products should you suggest?

[0838] Example of output prompt statement:

[0839] For a shopping plan in Tokyo on "2023-10-20," the following products are suggested based on the sunny weather forecast and the user's desire to "relax":

[0840] 1. Picnic equipment

[0841] 2. Outdoor reading chair

[0842] 3. Walking shoes

[0843] In this way, the system can suggest optimal products and activities according to the user's emotional state, thereby increasing user satisfaction.

[0844] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0845] Step 1:

[0846] The user enters event information into the terminal. Specifically, the shopping date and location. The entered event information is "2023-10-20" and "Tokyo." Once this data is entered, the terminal sends it to the server. The input is passed to the server as initial data.

[0847] Step 2:

[0848] The server obtains weather forecast data. The server sends a request to a weather forecast API (e.g., OpenWeatherMap API) based on the received event information ("2023-10-20" and "Tokyo"). The API responds with weather data (e.g., "sunny"). The server analyzes this weather data and determines the weather conditions for the specified date.

[0849] Step 3:

[0850] The server analyzes the emotional data. The server uses an emotion analysis engine (e.g., IBM Watson Emotion Analysis API) to analyze the user's emotional state. This information is collected based on text entered by the user (e.g., "I want to relax") and data from biometric devices such as smartwatches. By analyzing the input data, the user's emotional state (e.g., "Relaxed") is identified.

[0851] Step 4:

[0852] The server suggests activities and products. The server selects appropriate activities and products based on weather data ("sunny") and emotion data ("relaxed"). For example, for a user who wants to relax on a sunny day, "picnic equipment," "outdoor reading chair," and "walking shoes" are suggested. This selected information is formed as suggestion data.

[0853] Step 5:

[0854] The server sends the recommendations back to the device. The server sends a list of selected activities and products in JSON format to the device, including the date and location of the event. The JSON data is passed to the device.

[0855] Step 6:

[0856] The device displays the suggestions to the user. The device analyzes the suggestion data received from the server and displays it in a format that is easy for the user to understand. For example, it might say, "For your shopping plans in Tokyo on 2023-10-20, we suggest the following relaxing products for a sunny day: picnic equipment, outdoor reading chair, and walking shoes." The suggested information is presented to the user visually.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] [Third embodiment]

[0861] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0862] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0863] 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).

[0864] 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.

[0865] 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.

[0866] 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).

[0867] 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.

[0868] 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.

[0869] 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.

[0870] 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.

[0871] 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.

[0872] 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."

[0873] The present invention relates to a system that obtains predicted weather data based on the date and location of an event, suggests appropriate indoor or outdoor activities, and displays them to users, with the aim of improving user convenience and increasing the success rate of the event.

[0874] Overall system flow

[0875] 1. User enters event information

[0876] The user enters the date and location of the event on the terminal, for example, "2023-10-20" and "Tokyo."

[0877] 2. The device sends a request to the server

[0878] Based on the input event information, the device sends a request to a server dedicated to weather forecast APIs, which then calls the weather forecast API and retrieves weather data for the specified date and location.

[0879] 3. The server analyzes the weather data

[0880] The server analyzes the weather data and determines the weather on the day of the event. For example, it may obtain data indicating "sunny" from a weather forecast API.

[0881] 4. The server suggests activities

[0882] The server then selects the appropriate activity (indoor or outdoor) based on the analyzed weather data. For example, if it's sunny, it will suggest outdoor activities such as "picnic," "cycling," and "walking."

[0883] 5. The server sends the proposal back to the device

[0884] Data containing a list of suggested activities is sent back to the device in JSON format.

[0885] 6. The device displays suggestions to the user

[0886] The device then analyzes the returned suggestions and displays them to the user in an easy-to-understand format, such as "It's sunny, so we suggest the following outdoor activities: picnic, cycling, walking."

[0887] Specific examples

[0888] For example, suppose a user is planning an event in "Tokyo" on "2023-10-20." In this case, when the user enters this information into the device, the device sends a request to the weather forecast API server. The server retrieves weather data for "Tokyo" from the weather forecast API and analyzes the results to determine that it will be "sunny." Based on the analysis results, the server suggests outdoor activities such as "picnic," "cycling," and "walking," and sends this information back to the device. Finally, the device displays the suggested activities to the user.

[0889] This system allows users to efficiently plan events by automatically suggesting activities suitable for the event date and location, and by selecting activities appropriate for the weather, it can increase participant satisfaction.

[0890] The processing flow will be explained below.

[0891] Step 1:

[0892] The user enters the date and location of the event. For example, the user enters "2023-10-20" and "Tokyo" into the terminal. The terminal stores this information and proceeds to the next processing step.

[0893] Step 2:

[0894] The device sends a request to the server based on the input information. Specifically, it generates a request to use the weather forecast API and sends it to the server. This request includes information about the date and location of the event.

[0895] Step 3:

[0896] The server sends a request to the weather forecast API to get weather data for a specified date and location. Here, the server accesses an external weather forecast API endpoint and receives weather data in JSON format.

[0897] Step 4:

[0898] The weather data acquired by the server is analyzed. Specifically, the JSON data is analyzed and daytime weather information for the event is extracted. For example, it identifies whether the weather is "sunny," "cloudy," or "rainy."

[0899] Step 5:

[0900] The server suggests activities based on the analyzed weather data. If the weather is "sunny" or "cloudy," the server selects outdoor activities such as "picnic," "cycling," or "walking." If the weather is "rainy," the server selects indoor activities such as "watching a movie," "bowling," or "visiting a museum."

[0901] Step 6:

[0902] The server returns a list of suggested activities in JSON format to the device, along with the selected activity, along with the event date and location information.

[0903] Step 7:

[0904] The device parses the activity suggestions received from the server. The device parses the received JSON data and extracts the suggested activities.

[0905] Step 8:

[0906] The device displays suggested activities to the user. The device clearly displays the analysis results and displays a message such as, "It's sunny today, so we suggest the following outdoor activities: picnic, cycling, walking."

[0907] This allows users to easily find the best activities for their event date and location.

[0908] Example 1

[0909] 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."

[0910] In conventional event planning, it is difficult to select appropriate activities based on the weather, and there is a high risk that outdoor events will be canceled due to bad weather, especially. Furthermore, users have to check the weather forecast and select activities based on it, which reduces the chances of the event being successful. There is a need to solve these problems and improve user convenience.

[0911] 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.

[0912] In this invention, the server includes a means for the user to input event information, a means for the terminal to transmit the event information to the server, and a means for the server to analyze weather data and select appropriate activities. This allows the user to receive suggestions for optimal activities based on the weather simply by inputting the event information, increasing the success rate of the event and significantly reducing the user's effort.

[0913] "Event information" is information about the date and location of an event designated by the user.

[0914] "Weather data" is meteorological information for a specified date and location, including temperature, probability of precipitation, weather conditions, and the like.

[0915] "Indoor activities" are activities or events that take place inside a building and are less susceptible to weather.

[0916] "Outdoor activities" are activities or events that take place outdoors and are subject to weather.

[0917] A "user" is a person or organization that uses this system to input event information and receive activity suggestions.

[0918] A "terminal" is a device used by a user to input event information and display activity suggestions.

[0919] The "server" is the central computing system responsible for acquiring, analyzing, and suggesting activities on the weather data.

[0920] A "weather forecast API" is an external service that provides weather information over the Internet and is used by servers to obtain weather data.

[0921] "Activity suggestions" refers to providing the user with suitable indoor or outdoor activities based on the acquired weather data.

[0922] The "JSON format" is a type of data exchange format that is lightweight, easy to read, and suitable for data communication between programs.

[0923] An "HTTP request" is a communication protocol that allows a client to request data from a server, and is primarily used when using web services.

[0924] MODE FOR CARRYING OUT THE INVENTION

[0925] The present invention is a system that obtains predicted weather data based on the date and location of an event, and then suggests and displays suitable indoor or outdoor activities to the user based on the results. The main purpose of this system is to improve user convenience and increase the success rate of the event. A detailed implementation method of this system is described below.

[0926] 1. Enter your event information

[0927] The user uses the device to input the date and location of the event. Specifically, they enter information such as "2023-10-20" and "Tokyo" through an input form. This input can be done via a web browser or a dedicated application.

[0928] 2. Sending event information

[0929] The device sends the event information obtained from the user to the server. Specifically, it generates an HTTP request and sends it to a server dedicated to weather forecast APIs. The server uses an HTTP GET request to obtain weather data for the specified date and location from an external API (e.g., OpenWeatherMap or WeatherAPI).

[0930] 3. Weather data acquisition and analysis

[0931] The server analyzes weather data obtained from an external weather forecast API. The obtained data is in JSON format, and the server parses it to extract the necessary weather information. For example, the server identifies the information "sunny" from the analyzed weather data.

[0932] 4. Activity Selection

[0933] The server then selects appropriate activities based on the analysis results. These activities are chosen from a predefined list, and the selection criteria vary depending on the weather conditions. For example, if it's sunny, outdoor activities such as "picnic," "cycling," and "walking" will be suggested.

[0934] 5. Sending data from the server to the device

[0935] The selected activity list is sent back to the device from the server in JSON format, including the name and brief description of the suggested activity.

[0936] 6. Display of Suggestions

[0937] The device parses the received JSON data and displays the analysis results in a user-friendly format. For example, it may display text such as "It's sunny, so the following outdoor activities are suggested: picnic, cycling, walking." This allows the user to easily select the most suitable activity.

[0938] As a concrete example, if a user is planning an event in "Tokyo" on "2023-10-20," the user enters this information into the device, and the device sends a request to the server. The server retrieves weather data for "Tokyo" from the weather forecast API and analyzes the results to determine that it is "sunny." Based on the analysis results, the server suggests outdoor activities such as "picnic," "cycling," and "walking," and sends this information back to the device. Finally, the device displays the suggested activities to the user.

[0939] As an example of a prompt sentence, the following prompt sentence can be input to the generative AI model:

[0940] "I'm planning to hold an event in Tokyo on 2023-10-20. Please analyze the weather forecast data for this date and suggest appropriate activities."

[0941] This system allows users to receive appropriate activity suggestions based on the weather, enabling efficient event planning and is expected to increase participant satisfaction.

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

[0943] Step 1:

[0944] The user enters the event information.

[0945] The user enters the date and location of the event on the device. This information is received through a form, and the user presses the "Submit" button to move to the next step. The specific information entered is, for example, "2023-10-20" and "Tokyo."

[0946] input:

[0947] Date of event (e.g. 2023-10-20)

[0948] Venue (e.g. Tokyo)

[0949] output:

[0950] Request to send event information (e.g. HTTP request)

[0951] Step 2:

[0952] The device sends a request to the server.

[0953] Based on the event information entered by the user, the device generates request data and sends it to the server as an HTTP GET request. At this time, the device accesses a specific API endpoint and requests the acquisition of weather data.

[0954] input:

[0955] Event information (date, location)

[0956] output:

[0957] HTTP request to the server

[0958] Step 3:

[0959] The server retrieves the weather data.

[0960] The server accesses an external weather forecast API based on the received request to retrieve weather data for the specified date and location. This process uses an HTTP GET request to retrieve the weather forecast, adding the API key and parameters.

[0961] input:

[0962] HTTP request to the server

[0963] output:

[0964] Weather data from an external API (JSON format)

[0965] Step 4:

[0966] The server analyzes the weather data.

[0967] The server analyzes the acquired weather data and identifies the weather on the day of the event. It parses the JSON format data and extracts weather conditions such as "sunny" or "rainy" from the "weather" key. The analysis results are processed by flagging any that match a specific weather condition.

[0968] input:

[0969] Weather data obtained from an external API (JSON format)

[0970] output:

[0971] Weather data analysis results (e.g. "Sunny")

[0972] Step 5:

[0973] The server suggests activities.

[0974] The server then selects appropriate activities from a predefined list based on the analyzed weather data. For example, if the weather is sunny, outdoor activities such as "picnic," "cycling," and "walking" are suggested.

[0975] input:

[0976] Weather data analysis results (e.g. "Sunny")

[0977] output:

[0978] List of suggested activities (e.g., "picnic," "cycling," "walking")

[0979] Step 6:

[0980] The server sends the proposal back to the device.

[0981] The selected activity list is sent back to the device from the server in JSON format, including the name and brief description of the suggested activity.

[0982] input:

[0983] List of suggested activities (e.g., "picnic," "cycling," "walking")

[0984] output:

[0985] Response data to the terminal (JSON format)

[0986] Step 7:

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

[0988] The device parses the received JSON data and displays the analysis results in a user-friendly format, such as "It's sunny, so the following outdoor activities are suggested: picnic, cycling, walking."

[0989] input:

[0990] Response data from the server (JSON format)

[0991] output:

[0992] What to show the user (e.g., "It's a sunny day, so we suggest the following outdoor activities: picnic, cycling, walking")

[0993] (Application example 1)

[0994] 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."

[0995] The challenge is to increase the success rate of events planned by users by quickly and efficiently suggesting appropriate activities according to the weather on the day of the event. In particular, there is a need to provide an environment in virtual stores where users can receive appropriate activity suggestions in real time when planning an event at a desired date, time, and location.

[0996] 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.

[0997] In this invention, the server includes means for acquiring predicted weather data based on the date and location of an event, means for proposing indoor or outdoor activities suitable for the event based on the weather data, means for displaying the proposed activities to a user, means for proposing the activities in a virtual store, and means for a user to input event information in the virtual store application. This allows a user to receive appropriate activity suggestions based on the date and location of the event in real time, enabling efficient event planning.

[0998] "Event information" is data about a specific date and geographic location that a user plans.

[0999] "Weather Data" means data regarding predicted weather conditions for a specified date and location.

[1000] A "weather forecast API" is an application programming interface for externally obtaining weather data for a specified date and location.

[1001] "User" refers to a person who plans an event and uses the system to receive suggestions for suitable activities.

[1002] "Indoor activities" refer to activities that can be carried out inside a building.

[1003] "Outdoor activities" refers to activities that can be carried out outdoors.

[1004] A "virtual store" is a virtual retail space operated on the Internet that can be accessed and used by users.

[1005] A "virtual store application" is software that allows users to input event information within a virtual store and receive suggestions for appropriate activities.

[1006] The present invention relates to an event planning assistant system for a virtual store, which allows a user to receive appropriate activity suggestions based on real-time weather information when planning an event at any date, time, and location.

[1007] System configuration

[1008] The system includes the following components:

[1009] 1. User terminal: A device that provides an interface for users to input event information (date, time, location). Examples include smartphones and smart glasses.

[1010] 2. Server: A program runs that uses the weather forecast API to obtain weather data for the specified date, time, and location, and then suggests appropriate activities based on that data.

[1011] 3. Weather API: Refers to an external weather forecast service from which weather data is obtained (e.g., Weather API).

[1012] 4. Virtual store application: Software that is installed on the user's device and allows the user to input event information, connect to the server to obtain weather data, and receive suggestions.

[1013] Data processing and calculation

[1014] Operation of the user terminal: The user inputs the date and location of the event. This input data is sent to the server.

[1015] Server Action:

[1016] Obtaining weather data: The server uses the weather forecast API to obtain weather information for the specified date, time, and location.

[1017] Data analysis: Analyze the acquired weather data and identify weather conditions such as "sunny" or "rainy."

[1018] Activity Suggestion: Based on the analyzed weather data, it suggests suitable activities (indoor or outdoor). For example, if it's sunny, it suggests outdoor activities (picnic, cycling, walking), and if it's raining, it suggests indoor activities (watching movies, shopping, cafes).

[1019] Data return: A list of suggested activities is returned to the user terminal.

[1020] Display on user terminal: The user terminal analyzes the returned proposal content and displays it in a format that is easy for the user to understand.

[1021] Specific examples

[1022] For example, suppose a user is planning an event in "Osaka" on "2023-12-25." In this case, when the user enters the date and location, the application sends a request to the weather forecast API server. The server retrieves weather data for "Osaka" from the weather forecast API, and the result may be "Snow." Based on the analysis results, the server suggests indoor activities such as "Movies," "Shopping," or "Cafe." This information is sent back to the user's device, and the user can check the suggested activities on their smartphone or smart glasses.

[1023] Example prompts to input to the generative AI model

[1024] Write an application program that suggests appropriate activities based on the weather information for that day and location when a user plans an event for a specific date, time, and location. Specifically, the program will ask the user to enter the date, time, and location of the event, query the weather forecast API, and suggest indoor or outdoor activities based on the weather data obtained. It will also have a function to display the suggested activities to the user.

[1025] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1026] Step 1:

[1027] User enters event information

[1028] The user uses the terminal to input the date and location of the event.

[1029] Input: Date (e.g., 2023-12-25), Venue (e.g., Osaka)

[1030] Output: Request data from the terminal to the server (event date, venue)

[1031] Step 2:

[1032] The device sends a request to the server

[1033] Based on the event information entered on the device, the device sends a request to the weather forecast API server.

[1034] Input: Event information entered by the user (date, location)

[1035] Output: Request data to the weather forecast API server

[1036] Step 3:

[1037] The server retrieves weather data

[1038] The server calls the weather forecast API to retrieve weather data for the specified date and location.

[1039] Input: Request data to the weather forecast API (event date, venue)

[1040] Output: Weather data from the weather forecast API (e.g., snow)

[1041] Step 4:

[1042] The server analyzes the weather data

[1043] The server analyzes the weather data it has acquired and identifies the weather conditions on the day the event is held.

[1044] Input: Weather data

[1045] Output: Analyzed weather conditions (e.g. snow)

[1046] Step 5:

[1047] Server suggests activities

[1048] The server selects the appropriate activity (indoor or outdoor) based on the analyzed weather data.

[1049] Input: Analyzed weather conditions

[1050] Output: A list of suggested activities (e.g., watching movies, shopping, going to a cafe)

[1051] Step 6:

[1052] The server sends the proposal back to the device

[1053] Data containing a list of suggested activities is sent back to the device in JSON format.

[1054] Input: List of suggested activities

[1055] Output: Data returned to the device (activity list in JSON format)

[1056] Step 7:

[1057] The device displays suggestions to the user

[1058] The device analyzes the returned suggestions and displays them to the user in an easy-to-understand format.

[1059] Input: Data to be returned to the device (activity list in JSON format)

[1060] Output: Activity suggestions displayed to the user (e.g., watching a movie, shopping, going to a cafe)

[1061] 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.

[1062] The present invention combines a system that acquires predicted weather data based on the date and location of an event, suggests appropriate indoor or outdoor activities, and displays them to the user, with an emotion engine. This system allows for more appropriate activity suggestions based on the user's emotional state.

[1063] Overall system flow

[1064] 1. User enters event information

[1065] The user enters the date and location of the event into the terminal, for example, "2023-10-20" and "Tokyo."

[1066] 2. The device sends a request to the server

[1067] The device sends a request to a weather forecast server based on the event information entered, including the date and location of the event.

[1068] 3. The server retrieves the weather data

[1069] The server sends a request to the weather forecast API to retrieve weather data for the specified date and location. As an example, consider retrieving the data "sunny" from the weather forecast API.

[1070] 4. The server analyzes the weather data

[1071] The server analyzes the acquired weather data and determines the weather information for the day of the event, such as whether the weather is "sunny," "cloudy," or "rainy."

[1072] 5. The server uses the emotion engine to analyze the user's emotions.

[1073] The server uses an emotion engine to analyze the user's current emotion data, which is collected based on the user's biometric signals and past behavioral history.

[1074] 6. The server suggests activities

[1075] The server then suggests the most suitable activity based on weather data and emotion data obtained from the emotion engine. For example, if it is sunny and the user feels like relaxing, it will suggest "picnic" or "walking."

[1076] 7. The server sends the proposal back to the device

[1077] A list of suggested activities is returned to the device in JSON format, and the server returns the selected activities along with the event date and location information.

[1078] 8. The device displays suggestions to the user

[1079] The device analyzes the returned suggestions and displays them to the user in an easy-to-understand format, such as "Since it's sunny, we suggest the following relaxing outdoor activities: picnic, walking."

[1080] Specific examples

[1081] For example, suppose a user is planning an event in "Tokyo" on "2023-10-20." When the user enters this information into the device, the device sends a request to the weather forecast server. The server retrieves weather data for "Tokyo" from the weather forecast API and obtains the analysis result "sunny." Next, the emotion engine analyzes the user's current psychological state and determines that the user wants to relax. Based on this, the server suggests relaxing outdoor activities such as "picnic" or "walking" and sends the information back to the device. Finally, the device displays the suggested activities to the user.

[1082] In this way, the system has the ability to suggest optimal activities based on the user's emotions and weather conditions, thereby increasing user satisfaction.

[1083] The processing flow will be explained below.

[1084] Step 1:

[1085] The user enters the date and location of the event. For example, "2023-10-20" and "Tokyo" into the device. The device stores this information and proceeds to the next step.

[1086] Step 2:

[1087] The device sends a request to the server based on the input information. The device generates a request including information about the event date and location, and sends it to the server that uses the weather forecast API.

[1088] Step 3:

[1089] The server sends a request to the weather forecast API to retrieve weather data for the specified date and location. The server then accesses an external weather forecast API endpoint to retrieve weather data in JSON format.

[1090] Step 4:

[1091] The server analyzes the weather data it has acquired. The server analyzes the JSON data and identifies the weather information for the event date and location. For example, it extracts weather information such as "sunny," "cloudy," and "rainy."

[1092] Step 5:

[1093] The server uses an emotion engine to analyze the user's emotions. The server inputs the bio-signals and past behavioral history collected from the user into the emotion engine to determine the user's current emotional state. For example, it determines whether the user feels like relaxing.

[1094] Step 6:

[1095] The server suggests activities based on weather data and emotion data. For example, if the weather is "sunny" and the user feels like relaxing, the server will select relaxing outdoor activities such as "picnic" or "walking."

[1096] Step 7:

[1097] The server returns a list of suggested activities in JSON format to the device, and the server returns the selected activities along with the event date and location information to the device.

[1098] Step 8:

[1099] The device parses the activity suggestions received from the server. The device parses the received JSON data and extracts the suggested activities.

[1100] Step 9:

[1101] The device displays suggested activities to the user, such as a message like "It's a sunny day, so we suggest the following relaxing outdoor activities: picnic, walking."

[1102] This concludes the specific processing flow of the activity suggestion system that takes user emotions into account. This system automatically suggests optimal activities based on the user's emotional state and weather conditions.

[1103] Example 2

[1104] 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."

[1105] Conventional event suggestion systems suggest activities based on weather data predicted based on the date and location of the event, but do not consider the user's emotional state when suggesting activities. This can lead to suggested activities that do not match the user's psychological state, resulting in a decrease in user satisfaction.

[1106] 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.

[1107] In this invention, the server includes means for acquiring predicted weather data based on the date and location of the event, means for suggesting indoor or outdoor activities suitable for the event based on the weather data, means for analyzing the user's emotional state, means for selecting an optimal activity based on the weather data and the user's emotional state, and means for displaying the selected activity to the user. This makes it possible to suggest activities that take the user's emotional state into consideration, thereby increasing user satisfaction.

[1108] The "event date" is the specific date on which the event planned by the user will take place.

[1109] A "location" is a geographical location, including the physical location where an event takes place, such as a city or a particular facility.

[1110] "Weather Data" refers to weather information for a particular date and location, including various factors such as temperature, chance of precipitation, wind speed, etc.

[1111] The "user's emotional state" refers to the user's current psychological condition, and includes various emotions such as relaxation, stress, and excitement.

[1112] "Activity" refers to the actions or activities that a user actually performs during an event, and includes specific actions such as a picnic or walking.

[1113] "Means for suggesting" refers to a method or process for selecting the most suitable activity based on the acquired weather data and emotional state and notifying the user of it.

[1114] "Display means" refers to a method or device, such as a smartphone or computer screen, for visually presenting the suggested activity to the user.

[1115] "Emotion engine" refers to a system that includes software or hardware for analyzing a user's emotional state.

[1116] A "weather forecast API" is an application programming interface for obtaining external weather forecast data.

[1117] The "JSON format" is a standardized data exchange format for representing data in a lightweight, easy-to-read text format.

[1118] The present invention is a system that obtains predicted weather data based on the date and location of an event, suggests appropriate indoor or outdoor activities, and displays them to the user. This system also incorporates an emotion engine, which can suggest optimal activities according to the user's emotional state.

[1119] Hardware and software used

[1120] The system uses the following major hardware and software:

[1121] 1. User Device:

[1122] The event will be hosted on devices such as smartphones, computers, and tablets, which can connect to the internet and provide an interface for users to enter event information.

[1123] 2. Server:

[1124] High performance computer systems are used, including systems with web server functionality to process requests, parse data, call external APIs, and run the emotion engine.

[1125] 3. Weather Forecast API:

[1126] An application programming interface is used to provide external weather information, for example, a "weather API" to retrieve weather data for a specific date and location.

[1127] 4. Emotion Engine:

[1128] Software or services are used to analyze the user's emotional state, for example, by using the "Emotion API" to analyze the user's emotional data.

[1129] System Operation Overview

[1130] 1. User enters event information:

[1131] The user uses the device to specify the date and location of the event. For example, they enter "2023-10-20" and "Tokyo." The device has a dedicated input form that allows the user to easily enter information.

[1132] 2. The device sends a request to the server:

[1133] The device sends the event information entered by the user to the server as JSON format data.

[1134] 3. The server retrieves the weather data:

[1135] The server sends a request to the weather API to retrieve weather data for the specified date and location, including information such as temperature, chance of precipitation, and wind speed.

[1136] 4. The server analyzes the weather data:

[1137] The server analyzes the weather data and determines the weather conditions on the day of the event, for example, whether the weather will be "sunny," "cloudy," "rainy," etc.

[1138] 5. The server uses the emotion engine to analyze the user's emotions:

[1139] The server uses an emotion engine to analyze the user's current emotional state, which utilizes bio-signal data and past behavioral history to identify the user's emotional state.

[1140] 6. Server suggests activity:

[1141] The server then suggests the best activity based on the analyzed weather and emotion data. For example, if it's sunny and the user is in the mood to relax, it will suggest a picnic or a walk.

[1142] 7. The server sends the proposal back to the device:

[1143] A list of suggested activities is returned to the device in JSON format.

[1144] 8. The device displays suggestions to the user:

[1145] The device analyzes the data received from the server and displays it in a user-friendly format, for example, "Since it's sunny, we suggest the following relaxing outdoor activities: picnic, walking."

[1146] Specific examples

[1147] For example, suppose a user is planning an event in "Tokyo" on "2023-10-20." When the user enters this information into the device, the device sends a request to the weather forecast server. The server retrieves weather data for Tokyo from the weather forecast API and obtains the analysis result "sunny." Next, the emotion engine analyzes the user's current psychological state and determines that the user wants to relax. Based on this, the server suggests relaxing outdoor activities such as "picnic" or "walking" and sends the information back to the device. Finally, the device displays the suggested activities to the user.

[1148] Prompt Sentence Examples

[1149] Here are some example prompts to input to a generative AI model:

[1150] A user is planning an event in Tokyo on 2023-10-20. The user's current psychological state is that they want to relax. Considering this situation, retrieve weather data from a weather forecast API and suggest appropriate activities.

[1151] In this way, the system has the ability to suggest optimal activities based on the user's emotions and weather conditions, thereby increasing user satisfaction.

[1152] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1153] Step 1:

[1154] The user enters the event information.

[1155] Specific behavior:

[1156] Users access the system using a device such as a smartphone or computer and enter the event date and location. For example, they enter "Date: 2023-10-20" and "Location: Tokyo."

[1157] Input: Event date and location

[1158] Output: Entered event information (date and location)

[1159] Step 2:

[1160] The device sends a request to the server.

[1161] Specific behavior:

[1162] The device converts the event information entered by the user into JSON format and sends an HTTP request to the server.

[1163] Input: Entered event information (date and location)

[1164] Data processing: Convert event information into JSON format

[1165] Output: Event information in JSON format

[1166] Step 3:

[1167] The server retrieves the weather data.

[1168] Specific behavior:

[1169] The server sends a request to the weather forecast API to retrieve weather data for a specific date and location. For example, retrieve weather data for the date "2023-10-20" and location "Tokyo." This data includes temperature, probability of precipitation, wind speed, etc.

[1170] Input: Event information in JSON format

[1171] Data calculation: Send a request to the weather forecast API to obtain weather data

[1172] Output: Weather data (e.g. sunny)

[1173] Step 4:

[1174] The server analyzes the weather data.

[1175] Specific behavior:

[1176] The server analyzes the weather data it has acquired and determines the weather conditions during the day of the event, such as whether it will be sunny, cloudy, or rainy.

[1177] Input: Obtained weather data

[1178] Data Calculation: Weather Data Analysis

[1179] Output: Analysis results (weather conditions: sunny)

[1180] Step 5:

[1181] The server uses an emotion engine to analyze the user's emotions.

[1182] Specific behavior:

[1183] The server sends a request to the emotion engine based on the user's biosignal data and past behavioral history to analyze the user's current emotional state. For example, it identifies the emotion "I want to relax."

[1184] Input: User's biosignal data, past behavior history

[1185] Data Computation: Emotion Analysis with Emotion Engine

[1186] Output: Analysis results (emotional state: Relaxed)

[1187] Step 6:

[1188] The server suggests activities.

[1189] Specific behavior:

[1190] The server selects the most suitable activity based on weather and emotional data. For example, if the weather is sunny and you feel like relaxing, it creates an activity list. Suggestions like "picnic" and "walking" are given.

[1191] Input: Parsed weather data, user emotional state

[1192] Data processing: Selecting the best activity

[1193] Output: Activity list (e.g. picnic, walking)

[1194] Step 7:

[1195] The server sends the proposal back to the device.

[1196] Specific behavior:

[1197] The server generates an activity list and sends it back to the device in JSON format, which includes the dates and locations of the suggested activities and events.

[1198] Input: Activity list, event information

[1199] Data processing: Convert the activity list to JSON format

[1200] Output: Proposal in JSON format

[1201] Step 8:

[1202] The terminal displays the suggestions to the user.

[1203] Specific behavior:

[1204] The device analyzes the data received from the server and displays it in a user-friendly format. For example, it displays "The weather in Tokyo on 2023-10-20 is sunny. Recommended activities are: picnic, walking."

[1205] Input: Proposal content in JSON format

[1206] Data processing: Analyze the proposal content and convert it into a display format

[1207] Output: The suggestions that are displayed to the user

[1208] (Application example 2)

[1209] 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."

[1210] Conventional activity suggestion systems based on weather forecast data make uniform suggestions without considering the user's emotional state. This can result in suggested activities that do not match the user's current mood, which can lead to lower user satisfaction. Furthermore, they are unable to appropriately recommend products and services that the user desires, resulting in ineffective sales promotion, especially in the area of ​​shopping. Therefore, there is a need for a system that can suggest more personalized activities and products based on the user's emotions, thereby improving user satisfaction and experience.

[1211] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring predicted weather data based on the date and location of an event, means for suggesting indoor or outdoor activities suitable for the event based on the weather data, means for displaying the suggested activities to the user, means for analyzing the user's emotion data, means for suggesting specific products based on the weather data and emotion data, and means for displaying the identified products to the user. This makes it possible to suggest more appropriate activities and products according to the user's emotional state, thereby improving user satisfaction.

[1212] "Event" means a particular activity or occurrence taking place on a particular date and at a particular location.

[1213] "Weather Data" means meteorological information relating to a particular date, time and location, generally including factors such as temperature, precipitation, and wind speed.

[1214] "Indoor activities" refers to activities and entertainment that take place inside a building.

[1215] "Outdoor activities" refers to activities and recreation that take place outside of buildings.

[1216] "User" refers to the entity that uses this system, an individual or organization that receives weather forecast data and activity suggestions.

[1217] "Emotion data" is information that reflects the user's psychological state and is obtained through biometric signals, text analysis, and the like.

[1218] "Product Suggestion" refers to a product or service recommended to a user based on certain criteria.

[1219] "Activity suggestions" refers to recommended activities and pastimes based on a particular date and weather conditions, as well as the user's emotional state.

[1220] The present invention relates to a system that obtains predicted weather data based on the date and location of an event, and combines it with a user's emotional data to suggest specific products or activities. This system can increase user satisfaction by making suggestions based on the user's individual emotional state.

[1221] Overall system structure

[1222] The system includes the following main components:

[1223] 1. Weather data acquisition part:

[1224] The server retrieves weather data for the specified date and location from an external weather API (e.g., OpenWeatherMap API).

[1225] 2. Emotion data analysis unit:

[1226] The server uses an emotion analysis engine (e.g., IBM Watson Emotion Analysis API) to analyze the user's emotion data, which is obtained from text entered directly by the user into the device or from biometric devices such as a smartwatch.

[1227] 3. Activities and Product Proposal Department:

[1228] The server identifies activities and products suitable for the user based on the acquired weather data and the analyzed emotion data.

[1229] 4. Proposal content display area:

[1230] The terminal displays the suggestions returned from the server to the user.

[1231] Hardware and software examples

[1232] Hardware:

[1233] Mobile devices such as smartphones and tablets

[1234] Biosignal acquisition devices such as smartwatches and fitness bands (optional)

[1235] software:

[1236] Weather forecast API (e.g. OpenWeatherMap API)

[1237] Emotion analysis API (e.g. IBM Watson Emotion Analysis API)

[1238] Programming language (e.g. Python)

[1239] Operation flow

[1240] An example of a specific operation of the system is shown below.

[1241] 1. User enters event information:

[1242] The user enters the shopping date and location into the terminal. For example, "2023-10-20" and "Tokyo."

[1243] 2. Get weather data:

[1244] The server retrieves weather data for the specified date and location through the weather forecast API. For example, the weather data for "sunny" is retrieved.

[1245] 3. Emotional Data Analysis:

[1246] The server uses an emotion analysis engine to analyze the user's current emotional state, for example, determining that the user feels "relaxed."

[1247] 4. Activity and Product Suggestions:

[1248] The server uses weather and emotion data to suggest activities and products suitable for the user, such as "picnic equipment," "outdoor reading chair," and "walking shoes."

[1249] 5. View Proposals:

[1250] The terminal displays the proposal content received from the server to the user.

[1251] Specific examples

[1252] For example, suppose a user plans to go shopping in "Tokyo" on "2023-10-20." When the user enters this information into the device, the device retrieves weather data via a weather forecast API, which parses it as "sunny." Next, the sentiment analysis engine analyzes the user's emotional data and determines that the user wants to relax. Based on this, the server suggests relaxing outdoor activity products such as "picnic equipment," "outdoor reading chair," and "walking shoes." Finally, the device displays the suggested products to the user.

[1253] Prompt Sentence Examples

[1254] Here are some example input and output prompts:

[1255] Example of input prompt sentence:

[1256] A user is planning to go shopping in "Tokyo" on "2023-10-20." They also state that their current mood is "I want to relax." The weather forecast data from the weather forecast API is "Sunny." Based on these conditions, what products should you suggest?

[1257] Example of output prompt statement:

[1258] For a shopping plan in Tokyo on "2023-10-20," the following products are suggested based on the sunny weather forecast and the user's desire to "relax":

[1259] 1. Picnic equipment

[1260] 2. Outdoor reading chair

[1261] 3. Walking shoes

[1262] In this way, the system can suggest optimal products and activities according to the user's emotional state, thereby increasing user satisfaction.

[1263] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1264] Step 1:

[1265] The user enters event information into the terminal. Specifically, the shopping date and location. The entered event information is "2023-10-20" and "Tokyo." Once this data is entered, the terminal sends it to the server. The input is passed to the server as initial data.

[1266] Step 2:

[1267] The server obtains weather forecast data. The server sends a request to a weather forecast API (e.g., OpenWeatherMap API) based on the received event information ("2023-10-20" and "Tokyo"). The API responds with weather data (e.g., "sunny"). The server analyzes this weather data and determines the weather conditions for the specified date.

[1268] Step 3:

[1269] The server analyzes the emotional data. The server uses an emotion analysis engine (e.g., IBM Watson Emotion Analysis API) to analyze the user's emotional state. This information is collected based on text entered by the user (e.g., "I want to relax") and data from biometric devices such as smartwatches. By analyzing the input data, the user's emotional state (e.g., "Relaxed") is identified.

[1270] Step 4:

[1271] The server suggests activities and products. The server selects appropriate activities and products based on weather data ("sunny") and emotion data ("relaxed"). For example, for a user who wants to relax on a sunny day, "picnic equipment," "outdoor reading chair," and "walking shoes" are suggested. This selected information is formed as suggestion data.

[1272] Step 5:

[1273] The server sends the recommendations back to the device. The server sends a list of selected activities and products in JSON format to the device, including the date and location of the event. The JSON data is passed to the device.

[1274] Step 6:

[1275] The device displays the suggestions to the user. The device analyzes the suggestion data received from the server and displays it in a format that is easy for the user to understand. For example, it might say, "For your shopping plans in Tokyo on 2023-10-20, we suggest the following relaxing products for a sunny day: picnic equipment, outdoor reading chair, and walking shoes." The suggested information is presented to the user visually.

[1276] 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.

[1277] 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.

[1278] 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.

[1279] [Fourth embodiment]

[1280] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1281] 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.

[1282] 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).

[1283] 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.

[1284] 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.

[1285] 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).

[1286] 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.

[1287] 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.

[1288] 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.

[1289] 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.

[1290] 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.

[1291] 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.

[1292] 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."

[1293] The present invention relates to a system that obtains predicted weather data based on the date and location of an event, suggests appropriate indoor or outdoor activities, and displays them to users, with the aim of improving user convenience and increasing the success rate of the event.

[1294] Overall system flow

[1295] 1. User enters event information

[1296] The user enters the date and location of the event on the terminal, for example, "2023-10-20" and "Tokyo."

[1297] 2. The device sends a request to the server

[1298] Based on the input event information, the device sends a request to a server dedicated to weather forecast APIs, which then calls the weather forecast API and retrieves weather data for the specified date and location.

[1299] 3. The server analyzes the weather data

[1300] The server analyzes the weather data and determines the weather on the day of the event. For example, it may obtain data indicating "sunny" from a weather forecast API.

[1301] 4. The server suggests activities

[1302] The server then selects the appropriate activity (indoor or outdoor) based on the analyzed weather data. For example, if it's sunny, it will suggest outdoor activities such as "picnic," "cycling," and "walking."

[1303] 5. The server sends the proposal back to the device

[1304] Data containing a list of suggested activities is sent back to the device in JSON format.

[1305] 6. The device displays suggestions to the user

[1306] The device then analyzes the returned suggestions and displays them to the user in an easy-to-understand format, such as "It's sunny, so we suggest the following outdoor activities: picnic, cycling, walking."

[1307] Specific examples

[1308] For example, suppose a user is planning an event in "Tokyo" on "2023-10-20." In this case, when the user enters this information into the device, the device sends a request to the weather forecast API server. The server retrieves weather data for "Tokyo" from the weather forecast API and analyzes the results to determine that it will be "sunny." Based on the analysis results, the server suggests outdoor activities such as "picnic," "cycling," and "walking," and sends this information back to the device. Finally, the device displays the suggested activities to the user.

[1309] This system allows users to efficiently plan events by automatically suggesting activities suitable for the event date and location, and by selecting activities appropriate for the weather, it can increase participant satisfaction.

[1310] The processing flow will be explained below.

[1311] Step 1:

[1312] The user enters the date and location of the event. For example, the user enters "2023-10-20" and "Tokyo" into the terminal. The terminal stores this information and proceeds to the next processing step.

[1313] Step 2:

[1314] The device sends a request to the server based on the input information. Specifically, it generates a request to use the weather forecast API and sends it to the server. This request includes information about the date and location of the event.

[1315] Step 3:

[1316] The server sends a request to the weather forecast API to get weather data for a specified date and location. Here, the server accesses an external weather forecast API endpoint and receives weather data in JSON format.

[1317] Step 4:

[1318] The weather data acquired by the server is analyzed. Specifically, the JSON data is analyzed and daytime weather information for the event is extracted. For example, it identifies whether the weather is "sunny," "cloudy," or "rainy."

[1319] Step 5:

[1320] The server suggests activities based on the analyzed weather data. If the weather is "sunny" or "cloudy," the server selects outdoor activities such as "picnic," "cycling," or "walking." If the weather is "rainy," the server selects indoor activities such as "watching a movie," "bowling," or "visiting a museum."

[1321] Step 6:

[1322] The server returns a list of suggested activities in JSON format to the device, along with the selected activity, along with the event date and location information.

[1323] Step 7:

[1324] The device parses the activity suggestions received from the server. The device parses the received JSON data and extracts the suggested activities.

[1325] Step 8:

[1326] The device displays suggested activities to the user. The device clearly displays the analysis results and displays a message such as, "It's sunny today, so we suggest the following outdoor activities: picnic, cycling, walking."

[1327] This allows users to easily find the best activities for their event date and location.

[1328] Example 1

[1329] 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."

[1330] In conventional event planning, it is difficult to select appropriate activities based on the weather, and there is a high risk that outdoor events will be canceled due to bad weather, especially. Furthermore, users have to check the weather forecast and select activities based on it, which reduces the chances of the event being successful. There is a need to solve these problems and improve user convenience.

[1331] 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.

[1332] In this invention, the server includes a means for the user to input event information, a means for the terminal to transmit the event information to the server, and a means for the server to analyze weather data and select appropriate activities. This allows the user to receive suggestions for optimal activities based on the weather simply by inputting the event information, increasing the success rate of the event and significantly reducing the user's effort.

[1333] "Event information" is information about the date and location of an event designated by the user.

[1334] "Weather data" is meteorological information for a specified date and location, including temperature, probability of precipitation, weather conditions, and the like.

[1335] "Indoor activities" are activities or events that take place inside a building and are less susceptible to weather.

[1336] "Outdoor activities" are activities or events that take place outdoors and are subject to weather.

[1337] A "user" is a person or organization that uses this system to input event information and receive activity suggestions.

[1338] A "terminal" is a device used by a user to input event information and display activity suggestions.

[1339] The "server" is the central computing system responsible for acquiring, analyzing, and suggesting activities on the weather data.

[1340] A "weather forecast API" is an external service that provides weather information over the Internet and is used by servers to obtain weather data.

[1341] "Activity suggestions" refers to providing the user with suitable indoor or outdoor activities based on the acquired weather data.

[1342] The "JSON format" is a type of data exchange format that is lightweight, easy to read, and suitable for data communication between programs.

[1343] An "HTTP request" is a communication protocol that allows a client to request data from a server, and is primarily used when using web services.

[1344] MODE FOR CARRYING OUT THE INVENTION

[1345] The present invention is a system that obtains predicted weather data based on the date and location of an event, and then suggests and displays suitable indoor or outdoor activities to the user based on the results. The main purpose of this system is to improve user convenience and increase the success rate of the event. A detailed implementation method of this system is described below.

[1346] 1. Enter your event information

[1347] The user uses the device to input the date and location of the event. Specifically, they enter information such as "2023-10-20" and "Tokyo" through an input form. This input can be done via a web browser or a dedicated application.

[1348] 2. Sending event information

[1349] The device sends the event information obtained from the user to the server. Specifically, it generates an HTTP request and sends it to a server dedicated to weather forecast APIs. The server uses an HTTP GET request to obtain weather data for the specified date and location from an external API (e.g., OpenWeatherMap or WeatherAPI).

[1350] 3. Weather data acquisition and analysis

[1351] The server analyzes weather data obtained from an external weather forecast API. The obtained data is in JSON format, and the server parses it to extract the necessary weather information. For example, the server identifies the information "sunny" from the analyzed weather data.

[1352] 4. Activity Selection

[1353] The server then selects appropriate activities based on the analysis results. These activities are chosen from a predefined list, and the selection criteria vary depending on the weather conditions. For example, if it's sunny, outdoor activities such as "picnic," "cycling," and "walking" will be suggested.

[1354] 5. Sending data from the server to the device

[1355] The selected activity list is sent back to the device from the server in JSON format, including the name and brief description of the suggested activity.

[1356] 6. Display of Suggestions

[1357] The device parses the received JSON data and displays the analysis results in a user-friendly format. For example, it may display text such as "It's sunny, so the following outdoor activities are suggested: picnic, cycling, walking." This allows the user to easily select the most suitable activity.

[1358] As a concrete example, if a user is planning an event in "Tokyo" on "2023-10-20," the user enters this information into the device, and the device sends a request to the server. The server retrieves weather data for "Tokyo" from the weather forecast API and analyzes the results to determine that it is "sunny." Based on the analysis results, the server suggests outdoor activities such as "picnic," "cycling," and "walking," and sends this information back to the device. Finally, the device displays the suggested activities to the user.

[1359] As an example of a prompt sentence, the following prompt sentence can be input to the generative AI model:

[1360] "I'm planning to hold an event in Tokyo on 2023-10-20. Please analyze the weather forecast data for this date and suggest appropriate activities."

[1361] This system allows users to receive appropriate activity suggestions based on the weather, enabling efficient event planning and is expected to increase participant satisfaction.

[1362] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1363] Step 1:

[1364] The user enters the event information.

[1365] The user enters the date and location of the event on the device. This information is received through a form, and the user presses the "Submit" button to move to the next step. The specific information entered is, for example, "2023-10-20" and "Tokyo."

[1366] input:

[1367] Date of event (e.g. 2023-10-20)

[1368] Venue (e.g. Tokyo)

[1369] output:

[1370] Request to send event information (e.g. HTTP request)

[1371] Step 2:

[1372] The device sends a request to the server.

[1373] Based on the event information entered by the user, the device generates request data and sends it to the server as an HTTP GET request. At this time, the device accesses a specific API endpoint and requests the acquisition of weather data.

[1374] input:

[1375] Event information (date, location)

[1376] output:

[1377] HTTP request to the server

[1378] Step 3:

[1379] The server retrieves the weather data.

[1380] The server accesses an external weather forecast API based on the received request to retrieve weather data for the specified date and location. This process uses an HTTP GET request to retrieve the weather forecast, adding the API key and parameters.

[1381] input:

[1382] HTTP request to the server

[1383] output:

[1384] Weather data from an external API (JSON format)

[1385] Step 4:

[1386] The server analyzes the weather data.

[1387] The server analyzes the acquired weather data and identifies the weather on the day of the event. It parses the JSON format data and extracts weather conditions such as "sunny" or "rainy" from the "weather" key. The analysis results are processed by flagging any that match a specific weather condition.

[1388] input:

[1389] Weather data obtained from an external API (JSON format)

[1390] output:

[1391] Weather data analysis results (e.g. "Sunny")

[1392] Step 5:

[1393] The server suggests activities.

[1394] The server then selects appropriate activities from a predefined list based on the analyzed weather data. For example, if the weather is sunny, outdoor activities such as "picnic," "cycling," and "walking" are suggested.

[1395] input:

[1396] Weather data analysis results (e.g. "Sunny")

[1397] output:

[1398] List of suggested activities (e.g., "picnic," "cycling," "walking")

[1399] Step 6:

[1400] The server sends the proposal back to the device.

[1401] The selected activity list is sent back to the device from the server in JSON format, including the name and brief description of the suggested activity.

[1402] input:

[1403] List of suggested activities (e.g., "picnic," "cycling," "walking")

[1404] output:

[1405] Response data to the terminal (JSON format)

[1406] Step 7:

[1407] The terminal displays the suggestions to the user.

[1408] The device parses the received JSON data and displays the analysis results in a user-friendly format, such as "It's sunny, so the following outdoor activities are suggested: picnic, cycling, walking."

[1409] input:

[1410] Response data from the server (JSON format)

[1411] output:

[1412] What to show the user (e.g., "It's a sunny day, so we suggest the following outdoor activities: picnic, cycling, walking")

[1413] (Application example 1)

[1414] 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."

[1415] The challenge is to increase the success rate of events planned by users by quickly and efficiently suggesting appropriate activities according to the weather on the day of the event. In particular, there is a need to provide an environment in virtual stores where users can receive appropriate activity suggestions in real time when planning an event at a desired date, time, and location.

[1416] 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.

[1417] In this invention, the server includes means for acquiring predicted weather data based on the date and location of an event, means for proposing indoor or outdoor activities suitable for the event based on the weather data, means for displaying the proposed activities to a user, means for proposing the activities in a virtual store, and means for a user to input event information in the virtual store application. This allows a user to receive appropriate activity suggestions based on the date and location of the event in real time, enabling efficient event planning.

[1418] "Event information" is data about a specific date and geographic location that a user plans.

[1419] "Weather Data" means data regarding predicted weather conditions for a specified date and location.

[1420] A "weather forecast API" is an application programming interface for externally obtaining weather data for a specified date and location.

[1421] "User" refers to a person who plans an event and uses the system to receive suggestions for suitable activities.

[1422] "Indoor activities" refer to activities that can be carried out inside a building.

[1423] "Outdoor activities" refers to activities that can be carried out outdoors.

[1424] A "virtual store" is a virtual retail space operated on the Internet that can be accessed and used by users.

[1425] A "virtual store application" is software that allows users to input event information within a virtual store and receive suggestions for appropriate activities.

[1426] The present invention relates to an event planning assistant system for a virtual store, which allows a user to receive appropriate activity suggestions based on real-time weather information when planning an event at any date, time, and location.

[1427] System configuration

[1428] The system includes the following components:

[1429] 1. User terminal: A device that provides an interface for users to input event information (date, time, location). Examples include smartphones and smart glasses.

[1430] 2. Server: A program runs that uses the weather forecast API to obtain weather data for the specified date, time, and location, and then suggests appropriate activities based on that data.

[1431] 3. Weather API: Refers to an external weather forecast service from which weather data is obtained (e.g., Weather API).

[1432] 4. Virtual store application: Software that is installed on the user's device and allows the user to input event information, connect to the server to obtain weather data, and receive suggestions.

[1433] Data processing and calculation

[1434] Operation of the user terminal: The user inputs the date and location of the event. This input data is sent to the server.

[1435] Server Action:

[1436] Obtaining weather data: The server uses the weather forecast API to obtain weather information for the specified date, time, and location.

[1437] Data analysis: Analyze the acquired weather data and identify weather conditions such as "sunny" or "rainy."

[1438] Activity Suggestion: Based on the analyzed weather data, it suggests suitable activities (indoor or outdoor). For example, if it's sunny, it suggests outdoor activities (picnic, cycling, walking), and if it's raining, it suggests indoor activities (watching movies, shopping, cafes).

[1439] Data return: A list of suggested activities is returned to the user terminal.

[1440] Display on user terminal: The user terminal analyzes the returned proposal content and displays it in a format that is easy for the user to understand.

[1441] Specific examples

[1442] For example, suppose a user is planning an event in "Osaka" on "2023-12-25." In this case, when the user enters the date and location, the application sends a request to the weather forecast API server. The server retrieves weather data for "Osaka" from the weather forecast API, and the result may be "Snow." Based on the analysis results, the server suggests indoor activities such as "Movies," "Shopping," or "Cafe." This information is sent back to the user's device, and the user can check the suggested activities on their smartphone or smart glasses.

[1443] Example prompts to input to the generative AI model

[1444] Write an application program that suggests appropriate activities based on the weather information for that day and location when a user plans an event for a specific date, time, and location. Specifically, the program will ask the user to enter the date, time, and location of the event, query the weather forecast API, and suggest indoor or outdoor activities based on the weather data obtained. It will also have a function to display the suggested activities to the user.

[1445] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1446] Step 1:

[1447] User enters event information

[1448] The user uses the terminal to input the date and location of the event.

[1449] Input: Date (e.g., 2023-12-25), Venue (e.g., Osaka)

[1450] Output: Request data from the terminal to the server (event date, venue)

[1451] Step 2:

[1452] The device sends a request to the server

[1453] Based on the event information entered on the device, the device sends a request to the weather forecast API server.

[1454] Input: Event information entered by the user (date, location)

[1455] Output: Request data to the weather forecast API server

[1456] Step 3:

[1457] The server retrieves weather data

[1458] The server calls the weather forecast API to retrieve weather data for the specified date and location.

[1459] Input: Request data to the weather forecast API (event date, venue)

[1460] Output: Weather data from the weather forecast API (e.g., snow)

[1461] Step 4:

[1462] The server analyzes the weather data

[1463] The server analyzes the weather data it has acquired and identifies the weather conditions on the day the event is held.

[1464] Input: Weather data

[1465] Output: Analyzed weather conditions (e.g. snow)

[1466] Step 5:

[1467] Server suggests activities

[1468] The server selects the appropriate activity (indoor or outdoor) based on the analyzed weather data.

[1469] Input: Analyzed weather conditions

[1470] Output: A list of suggested activities (e.g., watching movies, shopping, going to a cafe)

[1471] Step 6:

[1472] The server sends the proposal back to the device

[1473] Data containing a list of suggested activities is sent back to the device in JSON format.

[1474] Input: List of suggested activities

[1475] Output: Data returned to the device (activity list in JSON format)

[1476] Step 7:

[1477] The device displays suggestions to the user

[1478] The device analyzes the returned suggestions and displays them to the user in an easy-to-understand format.

[1479] Input: Data to be returned to the device (activity list in JSON format)

[1480] Output: Activity suggestions displayed to the user (e.g., watching a movie, shopping, going to a cafe)

[1481] 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.

[1482] The present invention combines a system that acquires predicted weather data based on the date and location of an event, suggests appropriate indoor or outdoor activities, and displays them to the user, with an emotion engine. This system allows for more appropriate activity suggestions based on the user's emotional state.

[1483] Overall system flow

[1484] 1. User enters event information

[1485] The user enters the date and location of the event into the terminal, for example, "2023-10-20" and "Tokyo."

[1486] 2. The device sends a request to the server

[1487] The device sends a request to a weather forecast server based on the event information entered, including the date and location of the event.

[1488] 3. The server retrieves the weather data

[1489] The server sends a request to the weather forecast API to retrieve weather data for the specified date and location. As an example, consider retrieving the data "sunny" from the weather forecast API.

[1490] 4. The server analyzes the weather data

[1491] The server analyzes the acquired weather data and determines the weather information for the day of the event, such as whether the weather is "sunny," "cloudy," or "rainy."

[1492] 5. The server uses the emotion engine to analyze the user's emotions.

[1493] The server uses an emotion engine to analyze the user's current emotion data, which is collected based on the user's biometric signals and past behavioral history.

[1494] 6. The server suggests activities

[1495] The server then suggests the most suitable activity based on weather data and emotion data obtained from the emotion engine. For example, if it is sunny and the user feels like relaxing, it will suggest "picnic" or "walking."

[1496] 7. The server sends the proposal back to the device

[1497] A list of suggested activities is returned to the device in JSON format, and the server returns the selected activities along with the event date and location information.

[1498] 8. The device displays suggestions to the user

[1499] The device analyzes the returned suggestions and displays them to the user in an easy-to-understand format, such as "Since it's sunny, we suggest the following relaxing outdoor activities: picnic, walking."

[1500] Specific examples

[1501] For example, suppose a user is planning an event in "Tokyo" on "2023-10-20." When the user enters this information into the device, the device sends a request to the weather forecast server. The server retrieves weather data for "Tokyo" from the weather forecast API and obtains the analysis result "sunny." Next, the emotion engine analyzes the user's current psychological state and determines that the user wants to relax. Based on this, the server suggests relaxing outdoor activities such as "picnic" or "walking" and sends the information back to the device. Finally, the device displays the suggested activities to the user.

[1502] In this way, the system has the ability to suggest optimal activities based on the user's emotions and weather conditions, thereby increasing user satisfaction.

[1503] The processing flow will be explained below.

[1504] Step 1:

[1505] The user enters the date and location of the event. For example, "2023-10-20" and "Tokyo" into the device. The device stores this information and proceeds to the next step.

[1506] Step 2:

[1507] The device sends a request to the server based on the input information. The device generates a request including information about the event date and location, and sends it to the server that uses the weather forecast API.

[1508] Step 3:

[1509] The server sends a request to the weather forecast API to retrieve weather data for the specified date and location. The server then accesses an external weather forecast API endpoint to retrieve weather data in JSON format.

[1510] Step 4:

[1511] The server analyzes the weather data it has acquired. The server analyzes the JSON data and identifies the weather information for the event date and location. For example, it extracts weather information such as "sunny," "cloudy," and "rainy."

[1512] Step 5:

[1513] The server uses an emotion engine to analyze the user's emotions. The server inputs the bio-signals and past behavioral history collected from the user into the emotion engine to determine the user's current emotional state. For example, it determines whether the user feels like relaxing.

[1514] Step 6:

[1515] The server suggests activities based on weather data and emotion data. For example, if the weather is "sunny" and the user feels like relaxing, the server will select relaxing outdoor activities such as "picnic" or "walking."

[1516] Step 7:

[1517] The server returns a list of suggested activities in JSON format to the device, and the server returns the selected activities along with the event date and location information to the device.

[1518] Step 8:

[1519] The device parses the activity suggestions received from the server. The device parses the received JSON data and extracts the suggested activities.

[1520] Step 9:

[1521] The device displays suggested activities to the user, such as a message like "It's a sunny day, so we suggest the following relaxing outdoor activities: picnic, walking."

[1522] This concludes the specific processing flow of the activity suggestion system that takes user emotions into account. This system automatically suggests optimal activities based on the user's emotional state and weather conditions.

[1523] Example 2

[1524] 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."

[1525] Conventional event suggestion systems suggest activities based on weather data predicted based on the date and location of the event, but do not consider the user's emotional state when suggesting activities. This can lead to suggested activities that do not match the user's psychological state, resulting in a decrease in user satisfaction.

[1526] 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.

[1527] In this invention, the server includes means for acquiring predicted weather data based on the date and location of the event, means for suggesting indoor or outdoor activities suitable for the event based on the weather data, means for analyzing the user's emotional state, means for selecting an optimal activity based on the weather data and the user's emotional state, and means for displaying the selected activity to the user. This makes it possible to suggest activities that take the user's emotional state into consideration, thereby increasing user satisfaction.

[1528] The "event date" is the specific date on which the event planned by the user will take place.

[1529] A "location" is a geographical location, including the physical location where an event takes place, such as a city or a particular facility.

[1530] "Weather Data" refers to weather information for a particular date and location, including various factors such as temperature, chance of precipitation, wind speed, etc.

[1531] The "user's emotional state" refers to the user's current psychological condition, and includes various emotions such as relaxation, stress, and excitement.

[1532] "Activity" refers to the actions or activities that a user actually performs during an event, and includes specific actions such as a picnic or walking.

[1533] "Means for suggesting" refers to a method or process for selecting the most suitable activity based on the acquired weather data and emotional state and notifying the user of it.

[1534] "Display means" refers to a method or device, such as a smartphone or computer screen, for visually presenting the suggested activity to the user.

[1535] "Emotion engine" refers to a system that includes software or hardware for analyzing a user's emotional state.

[1536] A "weather forecast API" is an application programming interface for obtaining external weather forecast data.

[1537] The "JSON format" is a standardized data exchange format for representing data in a lightweight, easy-to-read text format.

[1538] The present invention is a system that obtains predicted weather data based on the date and location of an event, suggests appropriate indoor or outdoor activities, and displays them to the user. This system also incorporates an emotion engine, which can suggest optimal activities according to the user's emotional state.

[1539] Hardware and software used

[1540] The system uses the following major hardware and software:

[1541] 1. User Device:

[1542] The event will be hosted on devices such as smartphones, computers, and tablets, which can connect to the internet and provide an interface for users to enter event information.

[1543] 2. Server:

[1544] High performance computer systems are used, including systems with web server functionality to process requests, parse data, call external APIs, and run the emotion engine.

[1545] 3. Weather Forecast API:

[1546] An application programming interface is used to provide external weather information, for example, a "weather API" to retrieve weather data for a specific date and location.

[1547] 4. Emotion Engine:

[1548] Software or services are used to analyze the user's emotional state, for example, by using the "Emotion API" to analyze the user's emotional data.

[1549] System Operation Overview

[1550] 1. User enters event information:

[1551] The user uses the device to specify the date and location of the event. For example, they enter "2023-10-20" and "Tokyo." The device has a dedicated input form that allows the user to easily enter information.

[1552] 2. The device sends a request to the server:

[1553] The device sends the event information entered by the user to the server as JSON format data.

[1554] 3. The server retrieves the weather data:

[1555] The server sends a request to the weather API to retrieve weather data for the specified date and location, including information such as temperature, chance of precipitation, and wind speed.

[1556] 4. The server analyzes the weather data:

[1557] The server analyzes the weather data and determines the weather conditions on the day of the event, for example, whether the weather will be "sunny," "cloudy," "rainy," etc.

[1558] 5. The server uses the emotion engine to analyze the user's emotions:

[1559] The server uses an emotion engine to analyze the user's current emotional state, which utilizes bio-signal data and past behavioral history to identify the user's emotional state.

[1560] 6. Server suggests activity:

[1561] The server then suggests the best activity based on the analyzed weather and emotion data. For example, if it's sunny and the user is in the mood to relax, it will suggest a picnic or a walk.

[1562] 7. The server sends the proposal back to the device:

[1563] A list of suggested activities is returned to the device in JSON format.

[1564] 8. The device displays suggestions to the user:

[1565] The device analyzes the data received from the server and displays it in a user-friendly format, for example, "Since it's sunny, we suggest the following relaxing outdoor activities: picnic, walking."

[1566] Specific examples

[1567] For example, suppose a user is planning an event in "Tokyo" on "2023-10-20." When the user enters this information into the device, the device sends a request to the weather forecast server. The server retrieves weather data for Tokyo from the weather forecast API and obtains the analysis result "sunny." Next, the emotion engine analyzes the user's current psychological state and determines that the user wants to relax. Based on this, the server suggests relaxing outdoor activities such as "picnic" or "walking" and sends the information back to the device. Finally, the device displays the suggested activities to the user.

[1568] Prompt Sentence Examples

[1569] Here are some example prompts to input to a generative AI model:

[1570] A user is planning an event in Tokyo on 2023-10-20. The user's current psychological state is that they want to relax. Considering this situation, retrieve weather data from a weather forecast API and suggest appropriate activities.

[1571] In this way, the system has the ability to suggest optimal activities based on the user's emotions and weather conditions, thereby increasing user satisfaction.

[1572] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1573] Step 1:

[1574] The user enters the event information.

[1575] Specific behavior:

[1576] Users access the system using a device such as a smartphone or computer and enter the event date and location. For example, they enter "Date: 2023-10-20" and "Location: Tokyo."

[1577] Input: Event date and location

[1578] Output: Entered event information (date and location)

[1579] Step 2:

[1580] The device sends a request to the server.

[1581] Specific behavior:

[1582] The device converts the event information entered by the user into JSON format and sends an HTTP request to the server.

[1583] Input: Entered event information (date and location)

[1584] Data processing: Convert event information into JSON format

[1585] Output: Event information in JSON format

[1586] Step 3:

[1587] The server retrieves the weather data.

[1588] Specific behavior:

[1589] The server sends a request to the weather forecast API to retrieve weather data for a specific date and location. For example, retrieve weather data for the date "2023-10-20" and location "Tokyo." This data includes temperature, probability of precipitation, wind speed, etc.

[1590] Input: Event information in JSON format

[1591] Data calculation: Send a request to the weather forecast API to obtain weather data

[1592] Output: Weather data (e.g. sunny)

[1593] Step 4:

[1594] The server analyzes the weather data.

[1595] Specific behavior:

[1596] The server analyzes the weather data it has acquired and determines the weather conditions during the day of the event, such as whether it will be sunny, cloudy, or rainy.

[1597] Input: Obtained weather data

[1598] Data Calculation: Weather Data Analysis

[1599] Output: Analysis results (weather conditions: sunny)

[1600] Step 5:

[1601] The server uses an emotion engine to analyze the user's emotions.

[1602] Specific behavior:

[1603] The server sends a request to the emotion engine based on the user's biosignal data and past behavioral history to analyze the user's current emotional state. For example, it identifies the emotion "I want to relax."

[1604] Input: User's biosignal data, past behavior history

[1605] Data Computation: Emotion Analysis with Emotion Engine

[1606] Output: Analysis results (emotional state: Relaxed)

[1607] Step 6:

[1608] The server suggests activities.

[1609] Specific behavior:

[1610] The server selects the most suitable activity based on weather and emotional data. For example, if the weather is sunny and you feel like relaxing, it creates an activity list. Suggestions like "picnic" and "walking" are given.

[1611] Input: Parsed weather data, user emotional state

[1612] Data processing: Selecting the best activity

[1613] Output: Activity list (e.g. picnic, walking)

[1614] Step 7:

[1615] The server sends the proposal back to the device.

[1616] Specific behavior:

[1617] The server generates an activity list and sends it back to the device in JSON format, which includes the dates and locations of the suggested activities and events.

[1618] Input: Activity list, event information

[1619] Data processing: Convert the activity list to JSON format

[1620] Output: Proposal in JSON format

[1621] Step 8:

[1622] The terminal displays the suggestions to the user.

[1623] Specific behavior:

[1624] The device analyzes the data received from the server and displays it in a user-friendly format. For example, it displays "The weather in Tokyo on 2023-10-20 is sunny. Recommended activities are: picnic, walking."

[1625] Input: Proposal content in JSON format

[1626] Data processing: Analyze the proposal content and convert it into a display format

[1627] Output: The suggestions that are displayed to the user

[1628] (Application example 2)

[1629] 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."

[1630] Conventional activity suggestion systems based on weather forecast data make uniform suggestions without considering the user's emotional state. This can result in suggested activities that do not match the user's current mood, which can lead to lower user satisfaction. Furthermore, they are unable to appropriately recommend products and services that the user desires, resulting in ineffective sales promotion, especially in the area of ​​shopping. Therefore, there is a need for a system that can suggest more personalized activities and products based on the user's emotions, thereby improving user satisfaction and experience.

[1631] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring predicted weather data based on the date and location of an event, means for suggesting indoor or outdoor activities suitable for the event based on the weather data, means for displaying the suggested activities to the user, means for analyzing the user's emotion data, means for suggesting specific products based on the weather data and emotion data, and means for displaying the identified products to the user. This makes it possible to suggest more appropriate activities and products according to the user's emotional state, thereby improving user satisfaction.

[1632] "Event" means a particular activity or occurrence taking place on a particular date and at a particular location.

[1633] "Weather Data" means meteorological information relating to a particular date, time and location, generally including factors such as temperature, precipitation, and wind speed.

[1634] "Indoor activities" refers to activities and entertainment that take place inside a building.

[1635] "Outdoor activities" refers to activities and recreation that take place outside of buildings.

[1636] "User" refers to the entity that uses this system, an individual or organization that receives weather forecast data and activity suggestions.

[1637] "Emotion data" is information that reflects the user's psychological state and is obtained through biometric signals, text analysis, and the like.

[1638] "Product Suggestion" refers to a product or service recommended to a user based on certain criteria.

[1639] "Activity suggestions" refers to recommended activities and pastimes based on a particular date and weather conditions, as well as the user's emotional state.

[1640] The present invention relates to a system that obtains predicted weather data based on the date and location of an event, and combines it with a user's emotional data to suggest specific products or activities. This system can increase user satisfaction by making suggestions based on the user's individual emotional state.

[1641] Overall system structure

[1642] The system includes the following main components:

[1643] 1. Weather data acquisition part:

[1644] The server retrieves weather data for the specified date and location from an external weather API (e.g., OpenWeatherMap API).

[1645] 2. Emotion data analysis unit:

[1646] The server uses an emotion analysis engine (e.g., IBM Watson Emotion Analysis API) to analyze the user's emotion data, which is obtained from text entered directly by the user into the device or from biometric devices such as a smartwatch.

[1647] 3. Activities and Product Proposal Department:

[1648] The server identifies activities and products suitable for the user based on the acquired weather data and the analyzed emotion data.

[1649] 4. Proposal content display area:

[1650] The terminal displays the suggestions returned from the server to the user.

[1651] Hardware and software examples

[1652] Hardware:

[1653] Mobile devices such as smartphones and tablets

[1654] Biosignal acquisition devices such as smartwatches and fitness bands (optional)

[1655] software:

[1656] Weather forecast API (e.g. OpenWeatherMap API)

[1657] Emotion analysis API (e.g. IBM Watson Emotion Analysis API)

[1658] Programming language (e.g. Python)

[1659] Operation flow

[1660] An example of a specific operation of the system is shown below.

[1661] 1. User enters event information:

[1662] The user enters the shopping date and location into the terminal. For example, "2023-10-20" and "Tokyo."

[1663] 2. Get weather data:

[1664] The server retrieves weather data for the specified date and location through the weather forecast API. For example, the weather data for "sunny" is retrieved.

[1665] 3. Emotional Data Analysis:

[1666] The server uses an emotion analysis engine to analyze the user's current emotional state, for example, determining that the user feels "relaxed."

[1667] 4. Activity and Product Suggestions:

[1668] The server uses weather and emotion data to suggest activities and products suitable for the user, such as "picnic equipment," "outdoor reading chair," and "walking shoes."

[1669] 5. View Proposals:

[1670] The terminal displays the proposal content received from the server to the user.

[1671] Specific examples

[1672] For example, suppose a user plans to go shopping in "Tokyo" on "2023-10-20." When the user enters this information into the device, the device retrieves weather data via a weather forecast API, which parses it as "sunny." Next, the sentiment analysis engine analyzes the user's emotional data and determines that the user wants to relax. Based on this, the server suggests relaxing outdoor activity products such as "picnic equipment," "outdoor reading chair," and "walking shoes." Finally, the device displays the suggested products to the user.

[1673] Prompt Sentence Examples

[1674] Here are some example input and output prompts:

[1675] Example of input prompt sentence:

[1676] A user is planning to go shopping in "Tokyo" on "2023-10-20." They also state that their current mood is "I want to relax." The weather forecast data from the weather forecast API is "Sunny." Based on these conditions, what products should you suggest?

[1677] Example of output prompt statement:

[1678] For a shopping plan in Tokyo on "2023-10-20," the following products are suggested based on the sunny weather forecast and the user's desire to "relax":

[1679] 1. Picnic equipment

[1680] 2. Outdoor reading chair

[1681] 3. Walking shoes

[1682] In this way, the system can suggest optimal products and activities according to the user's emotional state, thereby increasing user satisfaction.

[1683] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1684] Step 1:

[1685] The user enters event information into the terminal. Specifically, the shopping date and location. The entered event information is "2023-10-20" and "Tokyo." Once this data is entered, the terminal sends it to the server. The input is passed to the server as initial data.

[1686] Step 2:

[1687] The server obtains weather forecast data. The server sends a request to a weather forecast API (e.g., OpenWeatherMap API) based on the received event information ("2023-10-20" and "Tokyo"). The API responds with weather data (e.g., "sunny"). The server analyzes this weather data and determines the weather conditions for the specified date.

[1688] Step 3:

[1689] The server analyzes the emotional data. The server uses an emotion analysis engine (e.g., IBM Watson Emotion Analysis API) to analyze the user's emotional state. This information is collected based on text entered by the user (e.g., "I want to relax") and data from biometric devices such as smartwatches. By analyzing the input data, the user's emotional state (e.g., "Relaxed") is identified.

[1690] Step 4:

[1691] The server suggests activities and products. The server selects appropriate activities and products based on weather data ("sunny") and emotion data ("relaxed"). For example, for a user who wants to relax on a sunny day, "picnic equipment," "outdoor reading chair," and "walking shoes" are suggested. This selected information is formed as suggestion data.

[1692] Step 5:

[1693] The server sends the recommendations back to the device. The server sends a list of selected activities and products in JSON format to the device, including the date and location of the event. The JSON data is passed to the device.

[1694] Step 6:

[1695] The device displays the suggestions to the user. The device analyzes the suggestion data received from the server and displays it in a format that is easy for the user to understand. For example, it might say, "For your shopping plans in Tokyo on 2023-10-20, we suggest the following relaxing products for a sunny day: picnic equipment, outdoor reading chair, and walking shoes." The suggested information is presented to the user visually.

[1696] 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.

[1697] 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.

[1698] 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.

[1699] 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.

[1700] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1701] 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.

[1702] 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).

[1703] 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.

[1704] 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."

[1705] 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.

[1706] 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).

[1707] 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.

[1708] 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.

[1709] 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.

[1710] 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.

[1711] 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.

[1712] 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.

[1713] 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.

[1714] 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.

[1715] 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.

[1716] 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.

[1717] The following is further disclosed regarding the above embodiment.

[1718] (Claim 1)

[1719] means for obtaining predicted weather data based on the date and location of the event;

[1720] means for suggesting indoor or outdoor activities suitable for the event based on the weather data;

[1721] means for displaying the suggested activities to a user;

[1722] A system including:

[1723] (Claim 2)

[1724] 10. The system of claim 1, wherein the weather data is obtained from an external weather forecast API.

[1725] (Claim 3)

[1726] 10. The system of claim 1, wherein the date and location of the event are determined based on input from a user.

[1727] "Example 1"

[1728] (Claim 1)

[1729] means for obtaining predicted weather data based on the date and location of the event;

[1730] means for suggesting indoor or outdoor activities suitable for the event based on the weather data;

[1731] means for displaying the suggested activities to a user;

[1732] a means for a user to input event information;

[1733] A means for the terminal to transmit event information to a server;

[1734] A means by which the server analyzes the weather data and selects appropriate activities;

[1735] A system including:

[1736] (Claim 2)

[1737] 10. The system of claim 1, wherein the weather data is obtained from an external weather forecast API.

[1738] (Claim 3)

[1739] 10. The system of claim 1, wherein the date and location of the event are determined based on input from a user.

[1740] "Application Example 1"

[1741] (Claim 1)

[1742] means for obtaining predicted weather data based on the date and location of the event;

[1743] means for suggesting indoor or outdoor activities suitable for the event based on the weather data;

[1744] means for displaying the suggested activities to a user;

[1745] means for suggesting said activities in a virtual store;

[1746] a means for a user to input event information in the virtual store application;

[1747] A system including:

[1748] (Claim 2)

[1749] 10. The system of claim 1, wherein the weather data is obtained from an external weather forecast API.

[1750] (Claim 3)

[1751] 10. The system of claim 1, wherein the date and location of the event are determined based on input from a user.

[1752] "Example 2: Combining Emotion Engines"

[1753] (Claim 1)

[1754] means for obtaining predicted weather data based on the date and location of the event;

[1755] means for suggesting indoor or outdoor activities suitable for the event based on the weather data;

[1756] means for analyzing the emotional state of a user;

[1757] means for selecting an optimal activity based on the weather data and the user's emotional state;

[1758] means for displaying the selected activity to a user;

[1759] A system including:

[1760] (Claim 2)

[1761] 10. The system of claim 1, wherein the weather data is obtained from an external weather forecast API.

[1762] (Claim 3)

[1763] 10. The system of claim 1, wherein the date and location of the event are determined based on input from a user.

[1764] "Application example 2 when combining emotion engines"

[1765] (Claim 1)

[1766] means for obtaining predicted weather data based on the date and location of the event;

[1767] means for suggesting indoor or outdoor activities suitable for the event based on the weather data;

[1768] means for displaying the suggested activities to a user;

[1769] means for analyzing user emotion data;

[1770] means for suggesting specific products based on the weather data and emotion data;

[1771] means for displaying the identified product to a user;

[1772] A system including:

[1773] (Claim 2)

[1774] 10. The system of claim 1, wherein the weather data is obtained from an external weather forecast API.

[1775] (Claim 3)

[1776] 10. The system of claim 1, wherein the date and location of the event are determined based on input from a user. [Explanation of symbols]

[1777] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for obtaining predicted weather data based on the date and location of the event; means for suggesting indoor or outdoor activities suitable for the event based on the weather data; means for displaying the suggested activities to a user; A system including:

2. The system of claim 1 , wherein the weather data is obtained from an external weather forecast API.

3. The system of claim 1 , wherein the date and location of the event are determined based on input from a user.

Images