System

Abstract

A system is provided.SOLUTION: A system comprising: an input means for inputting information about what a user wants to do; a transmitting means for transmitting the information to a server; a collecting means for collecting the latest relevant information based on the information; a generating means for generating an optimal vacation plan based on the collected information and the user's condition; a transmitting means for transmitting the generated plan to the user; and a displaying means for displaying the plan to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] There is a problem in that it takes a lot of time for users to find the best plan to spend their free time meaningfully when a sudden change in weather or schedule occurs. With conventional tools, users have to individually check the latest information and the congestion status of facilities, making it difficult to make quick and appropriate decisions. [Means for solving the problem]

[0005] This invention provides a system with the function of receiving information about what users want to do and automatically collecting the latest related information based on that information. Specifically, the system includes an input means for inputting information about what users want to do, a transmission means for transmitting the information to a server, a collection means for collecting the latest related information based on the information, a generation means for generating an optimal plan based on the collected information and the user's conditions, a transmission means for transmitting the generated plan to the user, and a display means for displaying the plan to the user. This system allows users to quickly and easily obtain the optimal time-killing plan.

[0006] "Input means" refers to a device or software function that allows a user to input information about what they want to do.

[0007] The "transmission means" is a device or software function for transmitting input information to a server via a network.

[0008] "Collector" refers to a device or software function that allows the server to automatically obtain the latest relevant information from multiple sources on the Internet based on the user's requirements.

[0009] The "generation means" is a device or software function for matching the collected information with the user's conditions and generating an optimal time-killing plan.

[0010] "Display means" refers to a device or software function for visually displaying the generated plan to a user.

[0011] "User" refers to a person who uses the system to input information about what they want to do and utilizes the proposed plan.

[0012] "The latest relevant information" refers to the latest information such as the current weather, facility operating status, and congestion status, obtained from news sites, social networking services, etc.

[0013] The "optimal plan" is a suggestion for killing time generated by an AI algorithm based on the criteria entered by the user and taking into account the latest relevant information collected. [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 is a system that, when a user inputs information about what they want to do, proposes an optimal time-killing plan based on that information. Specific embodiments of the system will be described in detail below.

[0036] The user enters information

[0037] The user uses a device (e.g., a smartphone or PC) to input information about what they want to do. This information includes location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., two people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor activities (e.g., indoors).

[0038] The device sends the information to the server

[0039] The terminal sends the information entered by the user to the server. This information consists of multiple fields and is sent in a generic data format such as JSON.

[0040] The server collects the latest information from social media and news sites.

[0041] The server collects the latest relevant information from the Internet based on the user's input. Specifically, it uses the APIs of social networking services and news sites to obtain the latest news, current weather, crowding status, event information, and other information for the relevant location.

[0042] The server collects the latest data from the facility.

[0043] The server also collects data provided by the facility operator, including facility availability, special service offers, price ranges, etc.

[0044] The server generates the optimal plan using an AI algorithm

[0045] The server uses an AI algorithm to generate the optimal time-killing plan based on the latest relevant information collected and the user's input criteria. The AI ​​selects the plan that best suits the user's preferences, taking into account factors such as traffic congestion, budget, and current weather.

[0046] The server sends the generated plan to the device.

[0047] The server sends the generated plan to the device in JSON format, etc. The plan includes detailed information such as specific locations, time frames, estimated costs within the budget, reference reviews and ratings, and congestion status.

[0048] The device displays the plan to the user.

[0049] The terminal will display the plan in a user-friendly format, for example:

[0050] Recommended Plan:

[0051] Location: Cafe A, Shibuya, Tokyo

[0052] Time: 15:00 - 16:00

[0053] Budget: Under 2000 yen

[0054] Customer Review: ★★★★☆

[0055] Availability: Currently empty

[0056] This allows users to easily find the best time-killing plan in real time.

[0057] Specific examples

[0058] If a user inputs "I want to find a cafe for two in Tokyo starting at 3 PM, my budget is 2000 yen, and I prefer indoor dining," the server will generate a plan based on the latest information it has collected: "Cafe A in Shibuya, Tokyo is the best choice at 3 PM, and the price is within my budget," and send it to the device. The device will then display this plan in detail to the user.

[0059] In this way, this system allows users to efficiently choose ways to kill time even when they suddenly have free time, and spend it meaningfully.

[0060] The processing flow will be explained below.

[0061] Program processing steps

[0062] Step 1:

[0063] The user enters information about what they want to do on the device. They enter a specific location, time, number of people, genre, budget, and preference for indoor / outdoor use into input fields.

[0064] Step 2:

[0065] The terminal converts the input information into a data format such as JSON and sends it to the server as an HTTP POST request.

[0066] Step 3:

[0067] The server parses the received request data and extracts the information entered by the user, including location, time, number of people, genre, budget, and preference for indoor / outdoor.

[0068] Step 4:

[0069] The server uses the APIs of social media and news sites to collect the latest information about the location specified by the user. Specifically, it calls the news API to retrieve the latest articles and news about the location. It also uses the social media API to retrieve recent posts and trending information about the location.

[0070] Step 5:

[0071] The server accesses databases and APIs provided by facility operators to collect information such as availability and congestion status of facilities that meet the user's criteria, as well as information on special services offered.

[0072] Step 6:

[0073] The server combines the latest information collected with the facility's own data and prepares it for passing to the AI ​​algorithm. This combined data includes news, social media trends, facility availability, congestion status, price range, and more.

[0074] Step 7:

[0075] The server runs an AI algorithm, comparing the integrated data with the user's requirements to generate the optimal time-killing plan. The AI ​​analyzes the collected information and selects the plan that best suits the user's needs, taking into account factors such as weather, congestion, and budget.

[0076] Step 8:

[0077] The server converts the generated plan back into a data format such as JSON and sends it to the terminal as an HTTP response.

[0078] Step 9:

[0079] The device analyzes the plan data received from the server and displays it in a format that is easy for the user to view, including the location of the best facility, the time frame, cost estimates within the budget, reviews and ratings, and congestion status.

[0080] These detailed processing steps allow the user to easily input information about what they want to do and quickly obtain the best time-killing plan based on that information.

[0081] Example 1

[0082] 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."

[0083] Conventional systems have had the problem of making it difficult for users to find the best time-killing plan when they suddenly have some free time. In particular, they lacked the means to collect the latest information and, based on that information, propose a plan that met the user's conditions and preferences. Furthermore, since they were unable to plan based on the facility's congestion status or real-time information, it was difficult for users to spend their time efficiently.

[0084] 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.

[0085] In this invention, the server includes input means for inputting information about what the user wants to do, transmission means for transmitting the information to the server, collection means for collecting the latest related information from social networking services and news sites based on the information, collection means for collecting data provided by facilities, generation means for generating an optimal time-killing plan using an AI algorithm based on the collected information and the user's conditions, transmission means for transmitting the generated plan to the user, and display means for displaying the plan to the user. This allows the user to obtain an optimal time-killing plan based on the latest information in real time, allowing them to spend their time efficiently even when they have sudden free time.

[0086] A "user" is an individual or group who uses the system to input information about what they want to do and receives suggestions for ways to kill time.

[0087] "Server" refers to a computer system that receives information sent by users, collects and processes various data, and sends the generated plan to terminals.

[0088] "Input means" refers to a software or hardware mechanism for inputting information about what a user wants to do via a terminal.

[0089] The "transmission means" is a communication function for transmitting information input by the user to the server.

[0090] "Collection means" is a function that allows the server to obtain the latest relevant information from various information sources on the Internet.

[0091] The "generation means" is a function that uses an AI algorithm to generate the optimal time-killing plan based on the collected information and the user's conditions.

[0092] The "display means" is a software or hardware mechanism for displaying the generated plan on a terminal in a format that is easy for the user to understand.

[0093] "Social networking services" refers to online platforms such as Twitter and Facebook, which allow users to post and share information.

[0094] "News site" refers to a website that contains current news articles and information.

[0095] "Facility-provided data" refers to information such as availability, special services, and price ranges that facility operators make public via APIs, etc.

[0096] An "AI algorithm" is a machine learning technology or data processing method that analyzes multiple collected data and generates an optimal plan based on user input conditions.

[0097] A "time-killing plan" is a specific activity suggestion provided to help users spend their free time effectively.

[0098] The present invention is a system that, when a user inputs information about what they want to do, proposes an optimal time-killing plan based on that information. Specific embodiments of the system will be described in detail below.

[0099] The user enters information

[0100] Users use devices such as smartphones or computers to enter information about what they want to do into a dedicated input form. Information to be entered includes location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., 2 people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor or outdoor activities (e.g., indoors). Specifically, users enter information into the fields on the screen and click the "Submit" button.

[0101] The device sends the information to the server

[0102] The device sends the data entered by the user to the server in a data format such as JSON. An HTTP POST request is used for sending the data. For example, the data may contain information such as "{ "Location": "Tokyo", "Time": "15:00", "Number of people": 2, "Genre": "Cafe", "Budget": 2000, "Indoor / Outdoor": "Indoor"}".

[0103] The server collects information from social media and news sites.

[0104] The server uses the received data to collect the latest information from social media and news sites. Specifically, it uses the APIs of social media sites such as Twitter and Facebook to obtain the latest information on the relevant area. It also uses RSS feeds and APIs from news sites to collect data such as current weather, event information, and crowding levels.

[0105] The server collects facility-provided data

[0106] The server uses the facility's API to obtain information about the facility's availability, special services, price range, etc. This allows the server to take into account the facility's status, which is updated in real time.

[0107] The server generates the optimal plan using an AI algorithm

[0108] The server provides the latest collected data and user input information to an AI algorithm, which then comprehensively evaluates the user's desired conditions (e.g., congestion, budget, weather) and generates the optimal time-killing plan. Using a machine learning model, the algorithm recommends a plan that takes congestion and weather into account.

[0109] The server sends the generated plan to the device.

[0110] The server then sends the generated plan to the device in JSON format. The plan includes details such as the specific location, time frame, estimated costs within the budget, reviews and ratings for reference, and congestion status. The plan is typically sent as an HTTP response.

[0111] The device displays the plan to the user.

[0112] The device will then display the received plan in a user-friendly format, for example:

[0113] Location: Cafe A, Shibuya, Tokyo

[0114] Time: 15:00 - 16:00

[0115] Budget: Under 2000 yen

[0116] Customer Review: ★★★★☆

[0117] Availability: Currently empty

[0118] This allows the user to obtain the best time-killing plan in real time.

[0119] Specific examples

[0120] For example, if a user inputs "I want to find a cafe for two in Tokyo starting at 3 PM, my budget is 2,000 yen, and I prefer it to be indoors," the device will send that information in JSON format to the server. The server will then generate the optimal plan based on data from social media, news sites, and facilities. The server will generate a plan such as "Cafe A in Shibuya, Tokyo is the best place for 3 PM, and the price is within my budget," and send it to the device. The device will then display this information in detail to the user, allowing them to find the optimal plan for killing time.

[0121] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0122] Step 1: User Enters Information

[0123] The user uses a device (smartphone or PC) to input information about what they want to do. The input items are location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., 2 people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor use (e.g., indoors). Once the input is complete, the user clicks the "Submit" button.

[0124] Input: User's desired conditions (location, time, number of people, genre, budget, indoor / outdoor)

[0125] Output: The input information is saved in a data field in the terminal.

[0126] Step 2: The device sends the information to the server

[0127] The device encodes the information entered by the user into JSON format and sends it to the server using an HTTP POST request. At this time, the information field contains data such as "{ "Location": "Tokyo", "Time": "15:00", "Number of people": 2, "Genre": "Cafe", "Budget": 2000, "Indoor / Outdoor": "Indoor"}".

[0128] Input: Information entered by the user

[0129] Output: JSON format data sent to the server

[0130] Step 3: The server collects information from social media and news sites.

[0131] The server uses the APIs of social media and news sites to collect relevant information based on the received user information. Based on the specified location and time, the server retrieves the latest local news, event information, and weather information from the APIs of Twitter and Facebook.

[0132] Input: User information in JSON format

[0133] Output: Latest information collected from social media and news sites (e.g., latest local news, weather, event information)

[0134] Step 4: Server collects facility-provided data

[0135] The server uses the API provided by the facility operator to collect information such as facility availability, special services, price range, etc. This allows the server to obtain real-time data about a specific facility.

[0136] Input: Facility-related request parameters (e.g., location, genre, budget)

[0137] Output: Collected facility-provided data (availability, special services, price range)

[0138] Step 5: The server analyzes the data using AI algorithms and generates an optimal plan

[0139] The server then supplies the collected data from social media, news sites, and facilities to an AI algorithm for analysis. This AI algorithm then comprehensively evaluates the user's desired conditions and generates the optimal time-killing plan. For example, it may recommend the best facility within a user's budget, taking into account crowding and weather conditions.

[0140] Input: User information, SNS information, news site information, facility data

[0141] Output: The best time-killing plan

[0142] Step 6: The server sends the generated plan to the device

[0143] The server then encodes the generated itinerary into JSON format and sends it to the device using an HTTP response, which includes data such as location, time frame, estimated cost within budget, user ratings, and occupancy status.

[0144] Input: The best time-killing plan

[0145] Output: Plan data in JSON format sent to the device

[0146] Step 7: The device displays the plan to the user

[0147] The device displays the received plan in an easy-to-read format for the user. For example, details such as "Cafe A in Shibuya, Tokyo, from 3:00 PM to 4:00 PM, budget within 2,000 yen, customer rating ★★★★☆, currently available" are displayed.

[0148] Input: Plan data sent from the server

[0149] Output: A specific time-killing plan displayed to the user

[0150] (Application example 1)

[0151] 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."

[0152] In modern society, there is a demand for systems that allow users to make effective use of their limited free time. However, existing systems have limited functionality in providing optimal time-killing plans based on a user's specific conditions or current location. In particular, when it comes to food delivery, there has been a lack of systems that can instantly respond to changing conditions such as a user's location, budget, and waiting time. This has made it difficult for users to find the optimal delivery plan.

[0153] 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.

[0154] In this invention, the server includes input means for inputting information about what the user wants to do, transmission means for transmitting the information to the server, collection means for collecting the latest related information based on the information, generation means for generating an optimal plan based on the collected information and the user's conditions, transmission means for transmitting the generated plan to the user, display means for displaying the plan to the user, and means for inputting the user's location information, food genre, budget, and waiting time and proposing an optimal delivery plan, thereby enabling the user to quickly find the optimal food delivery plan that meets their conditions.

[0155] "User information" refers to information about what the user wants to do, including location information, cuisine genre, budget, waiting time, etc.

[0156] "Input means" refers to a means for inputting information about what the user wants to do into the terminal.

[0157] The "transmission means" is a means for transmitting information input by the user to the server.

[0158] The "collection means" is a means for collecting the latest related information based on the information entered by the user.

[0159] The "generation means" is a means for generating an optimal plan based on the collected information and the user's conditions.

[0160] The "display means" is a means for displaying the generated plan to the user.

[0161] The "Food Delivery Plan" is a plan that suggests the most suitable restaurant and menu based on the user's location, cuisine type, budget, waiting time, and other conditions.

[0162] A "delivery service" is a service that delivers food to a location specified by the user.

[0163] "Related information" refers to the latest information obtained from social networking services, news sites, review platforms, etc.

[0164] "Crowding status" is information that indicates how crowded a particular facility or service is currently.

[0165] This invention is a system that allows users to effectively utilize their limited free time, and proposes plans that are particularly specialized for food delivery. A specific embodiment of this system will be described in detail below.

[0166] System Overview

[0167] Using a device such as a smartphone, a user inputs information about what they want to do, such as their current location, desired cuisine genre, budget, maximum waiting time, etc. This information is sent from the device to the server.

[0168] Hardware and software used

[0169] Hardware: Smartphone (iOS / Android)

[0170] Software: Python 3.8+, requests library, generative AI model (e.g., profile-based recommendation engine)

[0171] Data processing and calculation flow

[0172] 1. Data Entry

[0173] The user uses the terminal to input necessary information (for example, current location, cuisine genre, budget, waiting time, etc.).

[0174] These data are transmitted from the terminal to the server.

[0175] 2. Data Collection

[0176] The server collects relevant information from multiple data sources, including social networking services (SNS), news sites, and review platforms.

[0177] The collected data is structured in a general-purpose data format such as JSON.

[0178] 3. Generated by AI algorithms

[0179] The server generates an optimal food delivery plan based on the collected data and the user's requirements using a generative AI model, such as one that uses deep learning or machine learning techniques.

[0180] This process takes into account the user's location, cuisine, budget, wait time limit, and review ratings.

[0181] 4. Submitting and Viewing Plans

[0182] The server sends the generated optimal plan to the device in JSON format.

[0183] The device then displays the received plan to the user, showing the best restaurant, estimated time, menu items within the budget, and ratings of recommended menu items.

[0184] Specific examples

[0185] For example, if the user enters the following criteria:

[0186] Current location: Tokyo

[0187] Cuisines: Pizza

[0188] Budget: 1,500 yen

[0189] Maximum waiting time: 30 minutes

[0190] Based on this, the server gathers relevant information and generates a plan like this:

[0191] Restaurant: "Pizza House Tokyo"

[0192] Menu: Margherita pizza

[0193] Price: 1,400 yen

[0194] Estimated wait time: 25 minutes

[0195] Review rating: ★★★★☆

[0196] Prompt Sentence Examples

[0197] "Generate the best food delivery plan that matches the user's criteria. The criteria are as follows:

[0198] Current location: Tokyo

[0199] Cuisines: Pizza

[0200] Budget: 1,500 yen

[0201] Maximum waiting time: 30 minutes

[0202] The AI ​​model takes into account the latest restaurant information and reviews to provide the best plan.”

[0203] In this way, the system allows users to quickly and easily find the best food delivery plan that meets their requirements.

[0204] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0205] Step 1:

[0206] The user uses a device such as a smartphone to input information such as their current location, desired cuisine type, budget, and maximum waiting time. At this stage, the user inputs the conditions related to what they want into the device, and these conditions are saved in a general-purpose format such as JSON.

[0207] input:

[0208] current location

[0209] Desired cuisine genre

[0210] budget

[0211] Waiting time limit

[0212] output:

[0213] Input data in JSON format

[0214] Specific behavior:

[0215] The user enters the required information into the input form and presses the submit button.

[0216] Step 2:

[0217] The device sends the information entered by the user to the server. At this stage, the device sends the JSON formatted input data that it saved earlier to the server using an HTTP request.

[0218] input:

[0219] User-supplied data in JSON format

[0220] output:

[0221] HTTP request to the server

[0222] Specific behavior:

[0223] Use a library to generate and send HTTP requests (e.g. requests).

[0224] Step 3:

[0225] The server collects relevant information based on the conditions entered by the user from multiple data sources, such as social media, news sites, and review platforms. The collected data is saved in a unified format (e.g., JSON format).

[0226] input:

[0227] Filtering information based on user conditions

[0228] output:

[0229] Data collected from social networking services, news sites, and review platforms

[0230] Specific behavior:

[0231] Collect information by calling multiple APIs (e.g., social media API, review API).

[0232] Step 4:

[0233] The server generates the optimal food delivery plan based on the collected information and the user's requirements using a generative AI model. The generative AI model implements a recommendation algorithm using deep learning and machine learning techniques to calculate the plan that best matches the user's requirements.

[0234] input:

[0235] Data collected

[0236] User Conditions

[0237] output:

[0238] Data on the best food delivery plans

[0239] Specific behavior:

[0240] Input data into an AI model (e.g., a recommendation engine) to generate a plan.

[0241] Step 5:

[0242] The server sends the generated optimal food delivery plan to the device. The plan is sent in a general format such as JSON.

[0243] input:

[0244] Data on the best food delivery plans

[0245] output:

[0246] HTTP response to the device

[0247] Specific behavior:

[0248] Use a library (e.g. a web framework such as Flask) to generate and send HTTP responses.

[0249] Step 6:

[0250] The device then displays the received food delivery plan to the user, showing the best restaurant, estimated time, menu items within the budget, and ratings of recommended menu items.

[0251] input:

[0252] Food delivery plan sent from the server

[0253] output:

[0254] Display data for users

[0255] Specific behavior:

[0256] Visually display data using presentational UI components (e.g. HTML, CSS, JavaScript).

[0257] This allows users to quickly and easily find the best food delivery plan that meets their requirements.

[0258] 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.

[0259] This system allows users to input information about what they want to do and proposes optimal time-killing plans based on that information. Furthermore, by combining it with an emotion engine, it can analyze the user's emotional state and provide optimal plans based on that state.

[0260] The user enters information

[0261] The user uses a device (e.g., a smartphone or PC) to input information about what they want to do. This information includes location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., two people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor activities (e.g., indoors).

[0262] Emotion engine recognizes user emotions

[0263] The device activates an emotion engine that recognizes the user's emotions based on the user's input information and interface operation history. The emotion engine uses natural language processing and machine learning techniques to analyze the user's psychological state. The results of this analysis are expressed as the user's condition (for example, stressed, relaxed, excited, etc.).

[0264] The device sends the information to the server

[0265] The device sends the information entered by the user and the emotional state recognized by the emotion engine to the server in a general-purpose data format such as JSON.

[0266] The server collects the latest information from social media and news sites.

[0267] The server uses the APIs of social media and news sites to collect the latest relevant information based on the user's input information and emotional state. Specifically, it calls the news API to retrieve the latest articles and news about the location. It also uses the social media API to retrieve recent posts and trending information about the location.

[0268] The server collects the latest data from the facility.

[0269] The server accesses databases and APIs provided by facility operators to collect information such as availability and congestion status of facilities that meet the user's criteria, as well as information on special services offered.

[0270] The server generates the optimal plan using an AI algorithm

[0271] The server combines the latest collected information with the facility's data and uses an AI algorithm to generate the optimal time-killing plan. The server also takes into account the user's emotional state and selects the plan that will most satisfy the user. For example, if the server detects that the user is under stress, it will select a plan that provides a relaxing environment.

[0272] The server sends the generated plan to the device.

[0273] The server converts the generated plan back into a data format such as JSON format and sends it to the terminal as an HTTP response.

[0274] The device displays the plan to the user.

[0275] The device analyzes the plan data received from the server and displays it in a user-friendly format, including the location of the best facility, the time frame, estimated costs within the budget, reviews and ratings, the occupancy status, and the reasons for the recommendation based on the emotion engine.

[0276] Specific examples

[0277] If a user inputs "I'd like to find a cafe for two in Tokyo starting at 3 PM, my budget is 2,000 yen, and I'd prefer it to be indoors," and the emotion engine recognizes the user's stress level, the server will generate a plan based on the latest information it has collected: "A 'Relaxation Cafe' in Shibuya, Tokyo is ideal for 3 PM, and the price is within my budget," and send it to the device. The device will then display this plan in detail to the user, adding, "Based on your current emotional state, we've recommended a relaxing cafe."

[0278] In this way, the system not only allows users to kill time, but also allows them to quickly and easily obtain a plan that best suits their emotional state.

[0279] The processing flow will be explained below.

[0280] Program processing steps

[0281] Step 1:

[0282] The user enters information about what they want to do on the device. They enter a specific location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., 2 people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor use (e.g., indoors) into input fields.

[0283] Step 2:

[0284] The device collects the input information and activates the emotion engine. The emotion engine analyzes the user's emotions based on the information the user inputs and the operation history of the interface. For example, if the user inputs a lot of characters in a short period of time, it will recognize that the user is under stress.

[0285] Step 3:

[0286] The emotion engine generates the results of its analysis as user condition data, which includes the user's psychological state, such as stress, relaxation, or excitement.

[0287] Step 4:

[0288] The device converts the user's input information and the condition data generated by the emotion engine into a data format such as JSON and sends it to the server.

[0289] Step 5:

[0290] The server parses (analyzes) the request data it receives and extracts the conditions entered by the user and the condition data based on the emotion engine.

[0291] Step 6:

[0292] The server uses the APIs of social media and news sites to collect the latest information about the location specified by the user. Specifically, it calls the news API to obtain the latest articles and news about the location, and uses the social media API to obtain recent posts and trending information related to the location.

[0293] Step 7:

[0294] The server accesses databases and APIs provided by facility operators to collect information such as availability, congestion, and special service availability at facilities that meet the user's criteria.

[0295] Step 8:

[0296] The server combines the latest information collected by the server with data from the facility and uses an AI algorithm to generate an optimal time-killing plan. This plan also takes into account the user's emotional state. For example, if the system detects that the user is under stress, it will select a plan that provides a relaxing environment.

[0297] Step 9:

[0298] The server converts the generated plan data into a data format such as JSON and sends it to the terminal as an HTTP response.

[0299] Step 10:

[0300] The device analyzes the plan data received from the server and displays it in a user-friendly format, including the location of the best facility, the time frame, the estimated cost within the budget, reviews and ratings, the occupancy status, and the reason for the recommendation based on the emotion engine.

[0301] Specific examples

[0302] Example input:

[0303] The user inputs, "I want to find a cafe for two in Tokyo from 3pm. My budget is 2000 yen, preferably indoors." The emotion engine also recognizes the user's stress level.

[0304] Example output:

[0305] Based on the latest information and facility data collected by the server, the AI ​​generates a plan suggesting that a "Relax Cafe" in Shibuya, Tokyo, is optimal for 3 PM and within budget, and sends it to the device. The device displays this plan in detail to the user, adding, "Based on your current emotional state, we have recommended a relaxing cafe."

[0306] Recommended Plan:

[0307] Location: Relax Cafe in Shibuya, Tokyo

[0308] Time: 15:00 - 16:00

[0309] Budget: Under 2000 yen

[0310] Customer Review: ★★★★☆

[0311] Availability: Currently empty

[0312] Reason for recommendation: Based on your current emotional state, we recommended a relaxing cafe.

[0313] In this way, the system not only allows users to kill time, but also allows them to easily obtain a plan that is optimal for their emotional state.

[0314] Example 2

[0315] 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."

[0316] Existing systems simply provide time-killing plans based on location, time, budget, and other criteria, without considering the user's current emotional state. This makes it difficult for users to quickly find an appropriate plan that truly relaxes them and reduces stress. Furthermore, these systems do not integrate the latest information from social media and news sites or the congestion status of facilities. This creates a need for systems that provide optimal time-killing plans tailored to the user's needs.

[0317] 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.

[0318] In this invention, the server includes input means for inputting information about things the user wants to do, emotion recognition means for recognizing the information and the user's emotional state, transmission means for transmitting the information and the emotional state to the server, collection means for acquiring the latest information from social networking services and news sites based on the information and the emotional state, generation means for generating an optimal time-killing plan based on the information, the emotional state, and the collected information, transmission means for transmitting the generated plan to the user, and display means for displaying the plan to the user. This makes it possible to quickly and easily provide an optimal time-killing plan based on the latest related information while taking into account the user's current emotional state.

[0319] "Input means" refers to an interface for inputting information about what the user wants to do into the terminal.

[0320] "Emotion recognition means" refers to a function for analyzing and recognizing a user's emotional state based on the user's input information and operation history using natural language processing and machine learning technology.

[0321] The "transmission means" refers to a function for transmitting the information input by the user and the emotional state recognized by the emotion recognition means to the server in data format.

[0322] "Collection means" refers to the function that allows the server to use the APIs of social networking services and news sites to collect the latest information based on the user's input information and emotional state.

[0323] The "generation means" refers to a function that integrates the latest information and facility data collected by the collection means, and generates an optimal time-killing plan using an AI algorithm, taking into consideration the user's emotional state.

[0324] "Display means" refers to a function for analyzing the optimal time-killing plan sent from the server, formatting it in a format that is easy for the user to view, and displaying it on the terminal.

[0325] The term "server" refers to a central processing unit that receives information and emotional states sent by users, collects related information, generates plans, and transmits the generated plans to terminals.

[0326] "Terminal" refers to a device through which a user inputs information, communicates with the server, and receives the generated plan. Specifically, this includes smartphones, PCs, etc.

[0327] This system allows users to input information about what they want to do and proposes optimal time-killing plans based on that information. Furthermore, by combining it with an emotion engine, it can analyze the user's emotional state and provide optimal plans based on that state.

[0328] The user enters information

[0329] Users use devices such as smartphones or computers to input information about what they want to do, including location, time, number of people, genre, budget, and preference for indoor or outdoor activities.

[0330] Emotion engine recognizes user emotions

[0331] The device activates an emotion engine based on the user's input information and the application's operation history. The emotion engine uses natural language processing and machine learning technologies (such as Python's NLP library or TensorFlow) to analyze the user's psychological state. The analysis results are expressed as a condition, such as "stressed," "relaxed," or "excited."

[0332] The device sends the information to the server

[0333] The device sends the information entered by the user and the emotional state recognized by the emotion engine to the server. The data is sent in a general data format such as JSON (e.g., “{"Location": "Tokyo", "Time": "15:00", "Number of people": "2", "Genre": "Cafe", "Budget": "2000 yen", "Indoor": "Preferred", "Emotional state": "Stressed"}”).

[0334] The server collects the latest information from social media and news sites.

[0335] Based on the user's input information and emotional state, the server collects the latest related information using APIs of social media and news sites (e.g., Twitter API, News API, etc.), thereby obtaining recent posts, trending information, the latest articles, and news related to the location.

[0336] The server collects the latest data from the facility.

[0337] The server accesses databases and APIs provided by facility operators to collect information on facility availability and special service availability that matches the user's criteria. For example, this includes information on facility seat availability and whether or not special services are available.

[0338] The server generates the optimal plan using an AI algorithm

[0339] The server combines the collected latest information with the facility's data and uses a generative AI model (e.g., trend prediction model or recommendation model) to generate an optimal time-killing plan. The server also takes into account the user's emotional state and selects a plan that will most satisfy the user. For example, if the server detects that the user is under stress, it selects a plan that provides a relaxing environment.

[0340] The server sends the generated plan to the device.

[0341] The server converts the generated plan back into a data format such as JSON format and sends it to the terminal as an HTTP response.

[0342] The device displays the plan to the user.

[0343] The device analyzes the plan data received from the server and displays it in a user-friendly format, including the location of the best facility, the time frame, estimated costs within the budget, reviews and ratings, the occupancy status, and the reasons for the recommendation based on an emotion engine.

[0344] Specific examples

[0345] For example, if a user inputs "I'd like to find a cafe for two in Tokyo starting at 3 PM, with a budget of 2,000 yen and preferably indoors," and the emotion engine recognizes the user's stress level, the server will generate a plan based on the latest information it has collected: "A 'Relaxation Cafe' in Shibuya, Tokyo is ideal for 3 PM, and the price is within budget," and send it to the device. The device will then display this plan in detail to the user, adding a note that "Based on your current emotional state, we have recommended a relaxing cafe."

[0346] In this way, the system not only allows users to kill time, but also allows them to quickly and easily obtain a plan that best suits their emotional state.

[0347] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0348] Step 1:

[0349] Users input information about what they want to do into the device. Specifically, they input the location, time, number of people, genre, budget, and preference for indoor or outdoor activities on the screen of their smartphone or computer, and then press the send button.

[0350] Input: User's own input: "Location: Tokyo", "Time: 15:00", "Number of people: 2", "Genre: Cafe", "Budget: 2000 yen", "Indoor: Preferred"

[0351] Output: The input information is passed to the next emotion recognition means.

[0352] Step 2:

[0353] The emotion engine recognizes the user's emotions. The device activates the emotion engine based on the information just entered and the app's operation history. The emotion engine uses natural language processing and machine learning technologies to analyze the user's psychological state.

[0354] Input: User input information and operation history

[0355] Data processing method: Analyze the input data using a natural language processing library (e.g., spaCy or NLTK) and apply a sentiment classification algorithm (e.g., SVM, Random Forest).

[0356] Output: The recognition result is "Emotional state: Stressed".

[0357] Step 3:

[0358] The device sends the input information and the perceived emotional state to the server, where the data is packaged in JSON format and sent as an HTTP POST request.

[0359] Input: Input information and emotional state

[0360] Data Calculation: Converting data to JSON format and creating HTTP requests

[0361] Output: An HTTP POST request is made to the server, sending the entire data.

[0362] Step 4:

[0363] The server collects the latest information from social media and news sites. Based on the information received, the server calls social media APIs (e.g., Twitter API) and news APIs (e.g., NewsAPI) to retrieve the latest related articles and trending information.

[0364] Input: User input and emotional state

[0365] Data calculation: Sending a query to the API (e.g. "Tokyo Cafe Latest News") and analyzing the received response

[0366] Output: A dataset of the latest articles and social media posts.

[0367] Step 5:

[0368] The server collects the latest data from the facility, accesses the facility operator's database and API, and obtains information about availability and special services that match the user's criteria.

[0369] Input: User's condition and emotional state

[0370] Data Calculation: Sending API queries and parsing response data

[0371] Output: A dataset of facility availability and special offers.

[0372] Step 6:

[0373] The server generates the optimal plan using an AI algorithm, integrating the collected data sets and using a generative AI model to create the optimal plan.

[0374] Input: Latest articles, social media posting data, facility availability information, special service information

[0375] Data Computing: Data integration and application of AI algorithms (e.g., multi-label classifiers and recommendation systems)

[0376] Output: The optimal time-killing plan to be provided to the user is generated.

[0377] Step 7:

[0378] The server sends the generated plan to the terminal. The generated plan is converted to JSON format and sent to the terminal as an HTTP response.

[0379] Input: Generated optimal time-killing plan

[0380] Data operations: converting to JSON format and creating an HTTP response

[0381] Output: An HTTP response is generated and sent to the device.

[0382] Step 8:

[0383] The terminal displays the plan to the user. It analyzes the plan data received from the server, formats it in a format that is easy for the user to view, and displays it.

[0384] Input: Plan data in JSON format

[0385] Data computation: Data analysis and visualization (e.g., display using front-end libraries)

[0386] Output: The user is shown "Relax Cafe" with a message saying "Based on your current emotional state, we have recommended a cafe where you can relax."

[0387] (Application example 2)

[0388] 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."

[0389] While conventional systems have the ability to provide optimal plans based on the user's preferences and desired conditions, they lack the ability to take into account the user's emotional state. This poses a challenge: they are unable to quickly provide plans that meet the user's psychological needs, especially when they are stressed or want to relax. Furthermore, there are limitations to the suggestions they can make for specific genres of activities or services (e.g., food delivery), making it difficult to fully satisfy the diverse needs of users.

[0390] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0391] In this invention, the server includes input means for inputting information about what the user wants to do, transmission means for transmitting the information and the user's emotional state to the server, collection means for collecting related information based on the information and the emotional state, generation means for generating an optimal delivery plan based on the collected information and the user's state, transmission means for transmitting the generated plan to the user, and display means for displaying the plan to the user. This makes it possible to propose an optimal delivery plan that takes the user's psychological state into consideration.

[0392] "Input means" refers to a device or interface for inputting information about what the user wants to do.

[0393] "Transmitting means" refers to the devices and protocols used to transmit input information and the user's emotional state to the server.

[0394] The "collection means" refers to devices or software that allow the server to collect relevant information based on input information and emotional state.

[0395] The "generation means" refers to a device or algorithm that generates an optimal delivery plan based on the collected information and the user's status.

[0396] The "display means" is a device or interface for presenting the generated plan to the user.

[0397] A "social networking service" is a service or platform that allows users to interact with each other over the Internet.

[0398] "News delivery methods" are systems and services that provide the latest news and information.

[0399] A "food delivery service" is a service that allows you to order food and drinks and have them delivered to a specified location.

[0400] "Mental state" refers to the user's subjective feelings and mental condition.

[0401] The present invention relates to a system for proposing an optimal delivery plan in consideration of the emotional state of a user. A detailed embodiment for realizing this system will be described below.

[0402] Main components and technologies used

[0403] 1. Input Method

[0404] It is a device or interface for users to input information about what they want to do. For example, a smartphone app falls into this category, and is implemented as a cross-platform application using React Native.

[0405] 2. Transmission Method

[0406] It is a device and protocol for transmitting input information and the user's emotional state to a server. It mainly uses the HTTP protocol, and data is transmitted in JSON format.

[0407] 3. Collection Method

[0408] This is a device or software that allows the server to collect relevant information based on input information and emotional state. The Axios library is used to collect data, and the latest information is obtained from social networking service (SNS) APIs and news sources.

[0409] 4. Generation means

[0410] These are devices and algorithms that generate optimal delivery plans based on collected information and the user's status. A generative AI model using TensorFlow is used as a powerful tool.

[0411] 5. Display means

[0412] This is the device or interface for presenting the generated plan to the user. React Native UI components are used to display it within the application.

[0413] System Operation Overview

[0414] The server generates an optimal delivery plan through the following steps and provides it to the user.

[0415] 1. Enter your user information

[0416] Users input desired meal information (e.g., type of food, budget, number of people, time) through a smartphone app. The emotion engine also analyzes the user's psychological state, for example, if the user is under stress.

[0417] 2. Data transmission

[0418] The entered information and the user's emotional state are formatted and sent to the server in JSON format.

[0419] 3. Data Collection

[0420] The server collects the latest relevant information using the APIs of related food delivery services (e.g., UberEats API and DoorDash API) and social media APIs (e.g., Twitter API).

[0421] 4. Generating the optimal plan

[0422] The AI ​​algorithm uses the collected data to generate an optimal meal plan that takes into account the user's emotional state and preferences, using a deep learning model powered by TensorFlow.

[0423] 5. Submitting and Viewing Plans

[0424] The generated plan is converted back to JSON format and sent to the smartphone app, which displays the plan in an easy-to-understand format to the user, along with the reasons for the proposal.

[0425] Specific examples

[0426] For example, if a user enters "Chinese food," "under 2,000 yen," "for two people," "7 p.m." and "looking to relieve stress" into a smartphone app, the emotion engine will check the user's stress level from their operation history. The app will collect the latest related information and suggest "We recommend the Chinese restaurant 'Relax Garden.'" Furthermore, the app will display relaxing music and menu recommendations.

[0427] Prompt Sentence Examples

[0428] "Enter the user's emotional state and preferences, and generate a meal plan based on the latest food delivery information. The plan should also emphasize relaxation."

[0429] This system makes it possible to propose delivery plans that optimally take into account the user's psychological state.

[0430] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0431] Step 1:

[0432] Users use a smartphone app to input information about the meal they want (e.g., type of meal, budget, number of people, time) and their current emotional state (e.g., desire to relieve stress).

[0433] Input: genre, budget, number of people, time, emotional state

[0434] Output: User information (JSON format)

[0435] Specific behavior: The user enters information in an interface developed using React Native and presses the "Submit" button.

[0436] Step 2:

[0437] The device formats the input user information and emotional state into JSON format and sends it to the server using the HTTP protocol.

[0438] Input: User information (JSON format)

[0439] Output: HTTP request sent to the server

[0440] Specific operation: In the React Native application, an HTTP POST request is created using the Axios library and sent to the server.

[0441] Step 3:

[0442] The server analyzes the received user information and emotional state and collects related information. Here, it calls the API of social media sites and food delivery services to obtain related data.

[0443] Input: User information (JSON format), emotional state

[0444] Output: Relevant information collected

[0445] Specific operation: A server implemented using Node.js and Express.js calls the Twitter API and Uber Eats API using the Axios library to collect data.

[0446] Step 4:

[0447] The server generates an optimal delivery plan based on the collected information and the user's emotional state using a generative AI model powered by TensorFlow.

[0448] Input: Collected relevant information, emotional state

[0449] Output: Optimal delivery plan

[0450] Specific operation: The collected data is input into a TensorFlow deep learning model to generate an optimal plan.

[0451] Step 5:

[0452] The server formats the generated delivery plan again into JSON format and sends it to the terminal as an HTTP response.

[0453] Input: Optimal delivery plan (JSON format)

[0454] Output: Plan sent as HTTP response

[0455] Specific operation: The generated plan is converted to JSON and sent as an HTTP response using Express.js in Node.js.

[0456] Step 6:

[0457] The device analyzes the received delivery plan and displays it in a format that is easy for the user to view. The app also displays the reason for the proposal and additional information that may have a relaxing effect (e.g., relaxing music).

[0458] Input: Optimal delivery plan (JSON format)

[0459] Output: The delivery plan displayed to the user

[0460] What it does: Uses React Native to display the best delivery plan on the screen, along with additional information.

[0461] This processing step allows for the proposal of an optimal delivery plan that takes into account the user's psychological state.

[0462] 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.

[0463] 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.

[0464] 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.

[0465] [Second embodiment]

[0466] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0467] 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.

[0468] 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).

[0469] 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.

[0470] 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.

[0471] 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).

[0472] 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.

[0473] 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.

[0474] 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.

[0475] 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.

[0476] 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.

[0477] 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."

[0478] The present invention is a system that, when a user inputs information about what they want to do, proposes an optimal time-killing plan based on that information. Specific embodiments of the system will be described in detail below.

[0479] The user enters information

[0480] The user uses a device (e.g., a smartphone or PC) to input information about what they want to do. This information includes location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., two people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor activities (e.g., indoors).

[0481] The device sends the information to the server

[0482] The terminal sends the information entered by the user to the server. This information consists of multiple fields and is sent in a generic data format such as JSON.

[0483] The server collects the latest information from social media and news sites.

[0484] The server collects the latest relevant information from the Internet based on the user's input. Specifically, it uses the APIs of social networking services and news sites to obtain the latest news, current weather, crowding status, event information, and other information for the relevant location.

[0485] The server collects the latest data from the facility.

[0486] The server also collects data provided by the facility operator, including facility availability, special service offers, price ranges, etc.

[0487] The server generates the optimal plan using an AI algorithm

[0488] The server uses an AI algorithm to generate the optimal time-killing plan based on the latest relevant information collected and the user's input criteria. The AI ​​selects the plan that best suits the user's preferences, taking into account factors such as traffic congestion, budget, and current weather.

[0489] The server sends the generated plan to the device.

[0490] The server sends the generated plan to the device in JSON format, etc. The plan includes detailed information such as specific locations, time frames, estimated costs within the budget, reference reviews and ratings, and congestion status.

[0491] The device displays the plan to the user.

[0492] The terminal will display the plan in a user-friendly format, for example:

[0493] Recommended Plan:

[0494] Location: Cafe A, Shibuya, Tokyo

[0495] Time: 15:00 - 16:00

[0496] Budget: Under 2000 yen

[0497] Customer Review: ★★★★☆

[0498] Availability: Currently empty

[0499] This allows users to easily find the best time-killing plan in real time.

[0500] Specific examples

[0501] If a user inputs "I want to find a cafe for two in Tokyo starting at 3 PM, my budget is 2000 yen, and I prefer indoor dining," the server will generate a plan based on the latest information it has collected: "Cafe A in Shibuya, Tokyo is the best choice at 3 PM, and the price is within my budget," and send it to the device. The device will then display this plan in detail to the user.

[0502] In this way, this system allows users to efficiently choose ways to kill time even when they suddenly have free time, and spend it meaningfully.

[0503] The processing flow will be explained below.

[0504] Program processing steps

[0505] Step 1:

[0506] The user enters information about what they want to do on the device. They enter a specific location, time, number of people, genre, budget, and preference for indoor / outdoor use into input fields.

[0507] Step 2:

[0508] The terminal converts the input information into a data format such as JSON and sends it to the server as an HTTP POST request.

[0509] Step 3:

[0510] The server parses the received request data and extracts the information entered by the user, including location, time, number of people, genre, budget, and preference for indoor / outdoor.

[0511] Step 4:

[0512] The server uses the APIs of social media and news sites to collect the latest information about the location specified by the user. Specifically, it calls the news API to retrieve the latest articles and news about the location. It also uses the social media API to retrieve recent posts and trending information about the location.

[0513] Step 5:

[0514] The server accesses databases and APIs provided by facility operators to collect information such as availability and congestion status of facilities that meet the user's criteria, as well as information on special services offered.

[0515] Step 6:

[0516] The server combines the latest information collected with the facility's own data and prepares it for passing to the AI ​​algorithm. This combined data includes news, social media trends, facility availability, congestion status, price range, and more.

[0517] Step 7:

[0518] The server runs an AI algorithm, comparing the integrated data with the user's requirements to generate the optimal time-killing plan. The AI ​​analyzes the collected information and selects the plan that best suits the user's needs, taking into account factors such as weather, congestion, and budget.

[0519] Step 8:

[0520] The server converts the generated plan back into a data format such as JSON and sends it to the terminal as an HTTP response.

[0521] Step 9:

[0522] The device analyzes the plan data received from the server and displays it in a format that is easy for the user to view, including the location of the best facility, the time frame, cost estimates within the budget, reviews and ratings, and congestion status.

[0523] These detailed processing steps allow the user to easily input information about what they want to do and quickly obtain the best time-killing plan based on that information.

[0524] Example 1

[0525] 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."

[0526] Conventional systems have had the problem of making it difficult for users to find the best time-killing plan when they suddenly have some free time. In particular, they lacked the means to collect the latest information and, based on that information, propose a plan that met the user's conditions and preferences. Furthermore, since they were unable to plan based on the facility's congestion status or real-time information, it was difficult for users to spend their time efficiently.

[0527] 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.

[0528] In this invention, the server includes input means for inputting information about what the user wants to do, transmission means for transmitting the information to the server, collection means for collecting the latest related information from social networking services and news sites based on the information, collection means for collecting data provided by facilities, generation means for generating an optimal time-killing plan using an AI algorithm based on the collected information and the user's conditions, transmission means for transmitting the generated plan to the user, and display means for displaying the plan to the user. This allows the user to obtain an optimal time-killing plan based on the latest information in real time, allowing them to spend their time efficiently even when they have sudden free time.

[0529] A "user" is an individual or group who uses the system to input information about what they want to do and receives suggestions for ways to kill time.

[0530] "Server" refers to a computer system that receives information sent by users, collects and processes various data, and sends the generated plan to terminals.

[0531] "Input means" refers to a software or hardware mechanism for inputting information about what a user wants to do via a terminal.

[0532] The "transmission means" is a communication function for transmitting information input by the user to the server.

[0533] "Collection means" is a function that allows the server to obtain the latest relevant information from various information sources on the Internet.

[0534] The "generation means" is a function that uses an AI algorithm to generate the optimal time-killing plan based on the collected information and the user's conditions.

[0535] The "display means" is a software or hardware mechanism for displaying the generated plan on a terminal in a format that is easy for the user to understand.

[0536] "Social networking services" refers to online platforms such as Twitter and Facebook, which allow users to post and share information.

[0537] "News site" refers to a website that contains current news articles and information.

[0538] "Facility-provided data" refers to information such as availability, special services, and price ranges that facility operators make public via APIs, etc.

[0539] An "AI algorithm" is a machine learning technology or data processing method that analyzes multiple collected data and generates an optimal plan based on user input conditions.

[0540] A "time-killing plan" is a specific activity suggestion provided to help users spend their free time effectively.

[0541] The present invention is a system that, when a user inputs information about what they want to do, proposes an optimal time-killing plan based on that information. Specific embodiments of the system will be described in detail below.

[0542] The user enters information

[0543] Users use devices such as smartphones or computers to enter information about what they want to do into a dedicated input form. Information to be entered includes location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., 2 people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor or outdoor activities (e.g., indoors). Specifically, users enter information into the fields on the screen and click the "Submit" button.

[0544] The device sends the information to the server

[0545] The device sends the data entered by the user to the server in a data format such as JSON. An HTTP POST request is used for sending the data. For example, the data may contain information such as "{ "Location": "Tokyo", "Time": "15:00", "Number of people": 2, "Genre": "Cafe", "Budget": 2000, "Indoor / Outdoor": "Indoor"}".

[0546] The server collects information from social media and news sites.

[0547] The server uses the received data to collect the latest information from social media and news sites. Specifically, it uses the APIs of social media sites such as Twitter and Facebook to obtain the latest information on the relevant area. It also uses RSS feeds and APIs from news sites to collect data such as current weather, event information, and crowding levels.

[0548] The server collects facility-provided data

[0549] The server uses the facility's API to obtain information about the facility's availability, special services, price range, etc. This allows the server to take into account the facility's status, which is updated in real time.

[0550] The server generates the optimal plan using an AI algorithm

[0551] The server provides the latest collected data and user input information to an AI algorithm, which then comprehensively evaluates the user's desired conditions (e.g., congestion, budget, weather) and generates the optimal time-killing plan. Using a machine learning model, the algorithm recommends a plan that takes congestion and weather into account.

[0552] The server sends the generated plan to the device.

[0553] The server then sends the generated plan to the device in JSON format. The plan includes details such as the specific location, time frame, estimated costs within the budget, reviews and ratings for reference, and congestion status. The plan is typically sent as an HTTP response.

[0554] The device displays the plan to the user.

[0555] The device will then display the received plan in a user-friendly format, for example:

[0556] Location: Cafe A, Shibuya, Tokyo

[0557] Time: 15:00 - 16:00

[0558] Budget: Under 2000 yen

[0559] Customer Review: ★★★★☆

[0560] Availability: Currently empty

[0561] This allows the user to obtain the best time-killing plan in real time.

[0562] Specific examples

[0563] For example, if a user inputs "I want to find a cafe for two in Tokyo starting at 3 PM, my budget is 2,000 yen, and I prefer it to be indoors," the device will send that information in JSON format to the server. The server will then generate the optimal plan based on data from social media, news sites, and facilities. The server will generate a plan such as "Cafe A in Shibuya, Tokyo is the best place for 3 PM, and the price is within my budget," and send it to the device. The device will then display this information in detail to the user, allowing them to find the optimal plan for killing time.

[0564] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0565] Step 1: User Enters Information

[0566] The user uses a device (smartphone or PC) to input information about what they want to do. The input items are location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., 2 people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor use (e.g., indoors). Once the input is complete, the user clicks the "Submit" button.

[0567] Input: User's desired conditions (location, time, number of people, genre, budget, indoor / outdoor)

[0568] Output: The input information is saved in a data field in the terminal.

[0569] Step 2: The device sends the information to the server

[0570] The device encodes the information entered by the user into JSON format and sends it to the server using an HTTP POST request. At this time, the information field contains data such as "{ "Location": "Tokyo", "Time": "15:00", "Number of people": 2, "Genre": "Cafe", "Budget": 2000, "Indoor / Outdoor": "Indoor"}".

[0571] Input: Information entered by the user

[0572] Output: JSON format data sent to the server

[0573] Step 3: The server collects information from social media and news sites.

[0574] The server uses the APIs of social media and news sites to collect relevant information based on the received user information. Based on the specified location and time, the server retrieves the latest local news, event information, and weather information from the APIs of Twitter and Facebook.

[0575] Input: User information in JSON format

[0576] Output: Latest information collected from social media and news sites (e.g., latest local news, weather, event information)

[0577] Step 4: Server collects facility-provided data

[0578] The server uses the API provided by the facility operator to collect information such as facility availability, special services, price range, etc. This allows the server to obtain real-time data about a specific facility.

[0579] Input: Facility-related request parameters (e.g., location, genre, budget)

[0580] Output: Collected facility-provided data (availability, special services, price range)

[0581] Step 5: The server analyzes the data using AI algorithms and generates an optimal plan

[0582] The server then supplies the collected data from social media, news sites, and facilities to an AI algorithm for analysis. This AI algorithm then comprehensively evaluates the user's desired conditions and generates the optimal time-killing plan. For example, it may recommend the best facility within a user's budget, taking into account crowding and weather conditions.

[0583] Input: User information, SNS information, news site information, facility data

[0584] Output: The best time-killing plan

[0585] Step 6: The server sends the generated plan to the device

[0586] The server then encodes the generated itinerary into JSON format and sends it to the device using an HTTP response, which includes data such as location, time frame, estimated cost within budget, user ratings, and occupancy status.

[0587] Input: The best time-killing plan

[0588] Output: Plan data in JSON format sent to the device

[0589] Step 7: The device displays the plan to the user

[0590] The device displays the received plan in an easy-to-read format for the user. For example, details such as "Cafe A in Shibuya, Tokyo, from 3:00 PM to 4:00 PM, budget within 2,000 yen, customer rating ★★★★☆, currently available" are displayed.

[0591] Input: Plan data sent from the server

[0592] Output: A specific time-killing plan displayed to the user

[0593] (Application example 1)

[0594] 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."

[0595] In modern society, there is a demand for systems that allow users to make effective use of their limited free time. However, existing systems have limited functionality in providing optimal time-killing plans based on a user's specific conditions or current location. In particular, when it comes to food delivery, there has been a lack of systems that can instantly respond to changing conditions such as a user's location, budget, and waiting time. This has made it difficult for users to find the optimal delivery plan.

[0596] 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.

[0597] In this invention, the server includes input means for inputting information about what the user wants to do, transmission means for transmitting the information to the server, collection means for collecting the latest related information based on the information, generation means for generating an optimal plan based on the collected information and the user's conditions, transmission means for transmitting the generated plan to the user, display means for displaying the plan to the user, and means for inputting the user's location information, food genre, budget, and waiting time and proposing an optimal delivery plan, thereby enabling the user to quickly find the optimal food delivery plan that meets their conditions.

[0598] "User information" refers to information about what the user wants to do, including location information, cuisine genre, budget, waiting time, etc.

[0599] "Input means" refers to a means for inputting information about what the user wants to do into the terminal.

[0600] The "transmission means" is a means for transmitting information input by the user to the server.

[0601] The "collection means" is a means for collecting the latest related information based on the information entered by the user.

[0602] The "generation means" is a means for generating an optimal plan based on the collected information and the user's conditions.

[0603] The "display means" is a means for displaying the generated plan to the user.

[0604] The "Food Delivery Plan" is a plan that suggests the most suitable restaurant and menu based on the user's location, cuisine type, budget, waiting time, and other conditions.

[0605] A "delivery service" is a service that delivers food to a location specified by the user.

[0606] "Related information" refers to the latest information obtained from social networking services, news sites, review platforms, etc.

[0607] "Crowding status" is information that indicates how crowded a particular facility or service is currently.

[0608] This invention is a system that allows users to effectively utilize their limited free time, and proposes plans that are particularly specialized for food delivery. A specific embodiment of this system will be described in detail below.

[0609] System Overview

[0610] Using a device such as a smartphone, a user inputs information about what they want to do, such as their current location, desired cuisine genre, budget, maximum waiting time, etc. This information is sent from the device to the server.

[0611] Hardware and software used

[0612] Hardware: Smartphone (iOS / Android)

[0613] Software: Python 3.8+, requests library, generative AI model (e.g., profile-based recommendation engine)

[0614] Data processing and calculation flow

[0615] 1. Data Entry

[0616] The user uses the terminal to input necessary information (for example, current location, cuisine genre, budget, waiting time, etc.).

[0617] These data are transmitted from the terminal to the server.

[0618] 2. Data Collection

[0619] The server collects relevant information from multiple data sources, including social networking services (SNS), news sites, and review platforms.

[0620] The collected data is structured in a general-purpose data format such as JSON.

[0621] 3. Generated by AI algorithms

[0622] The server generates an optimal food delivery plan based on the collected data and the user's requirements using a generative AI model, such as one that uses deep learning or machine learning techniques.

[0623] This process takes into account the user's location, cuisine, budget, wait time limit, and review ratings.

[0624] 4. Submitting and Viewing Plans

[0625] The server sends the generated optimal plan to the device in JSON format.

[0626] The device then displays the received plan to the user, showing the best restaurant, estimated time, menu items within the budget, and ratings of recommended menu items.

[0627] Specific examples

[0628] For example, if the user enters the following criteria:

[0629] Current location: Tokyo

[0630] Cuisines: Pizza

[0631] Budget: 1,500 yen

[0632] Maximum waiting time: 30 minutes

[0633] Based on this, the server gathers relevant information and generates a plan like this:

[0634] Restaurant: "Pizza House Tokyo"

[0635] Menu: Margherita pizza

[0636] Price: 1,400 yen

[0637] Estimated wait time: 25 minutes

[0638] Review rating: ★★★★☆

[0639] Prompt Sentence Examples

[0640] "Generate the best food delivery plan that matches the user's criteria. The criteria are as follows:

[0641] Current location: Tokyo

[0642] Cuisines: Pizza

[0643] Budget: 1,500 yen

[0644] Maximum waiting time: 30 minutes

[0645] The AI ​​model takes into account the latest restaurant information and reviews to provide the best plan.”

[0646] In this way, the system allows users to quickly and easily find the best food delivery plan that meets their requirements.

[0647] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0648] Step 1:

[0649] The user uses a device such as a smartphone to input information such as their current location, desired cuisine type, budget, and maximum waiting time. At this stage, the user inputs the conditions related to what they want into the device, and these conditions are saved in a general-purpose format such as JSON.

[0650] input:

[0651] current location

[0652] Desired cuisine genre

[0653] budget

[0654] Waiting time limit

[0655] output:

[0656] Input data in JSON format

[0657] Specific behavior:

[0658] The user enters the required information into the input form and presses the submit button.

[0659] Step 2:

[0660] The device sends the information entered by the user to the server. At this stage, the device sends the JSON formatted input data that it saved earlier to the server using an HTTP request.

[0661] input:

[0662] User-supplied data in JSON format

[0663] output:

[0664] HTTP request to the server

[0665] Specific behavior:

[0666] Use a library to generate and send HTTP requests (e.g. requests).

[0667] Step 3:

[0668] The server collects relevant information based on the conditions entered by the user from multiple data sources, such as social media, news sites, and review platforms. The collected data is saved in a unified format (e.g., JSON format).

[0669] input:

[0670] Filtering information based on user conditions

[0671] output:

[0672] Data collected from social networking services, news sites, and review platforms

[0673] Specific behavior:

[0674] Collect information by calling multiple APIs (e.g., social media API, review API).

[0675] Step 4:

[0676] The server generates the optimal food delivery plan based on the collected information and the user's requirements using a generative AI model. The generative AI model implements a recommendation algorithm using deep learning and machine learning techniques to calculate the plan that best matches the user's requirements.

[0677] input:

[0678] Data collected

[0679] User Conditions

[0680] output:

[0681] Data on the best food delivery plans

[0682] Specific behavior:

[0683] Input data into an AI model (e.g., a recommendation engine) to generate a plan.

[0684] Step 5:

[0685] The server sends the generated optimal food delivery plan to the device. The plan is sent in a general format such as JSON.

[0686] input:

[0687] Data on the best food delivery plans

[0688] output:

[0689] HTTP response to the device

[0690] Specific behavior:

[0691] Use a library (e.g. a web framework such as Flask) to generate and send HTTP responses.

[0692] Step 6:

[0693] The device then displays the received food delivery plan to the user, showing the best restaurant, estimated time, menu items within the budget, and ratings of recommended menu items.

[0694] input:

[0695] Food delivery plan sent from the server

[0696] output:

[0697] Display data for users

[0698] Specific behavior:

[0699] Visually display data using presentational UI components (e.g. HTML, CSS, JavaScript).

[0700] This allows users to quickly and easily find the best food delivery plan that meets their requirements.

[0701] 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.

[0702] This system allows users to input information about what they want to do and proposes optimal time-killing plans based on that information. Furthermore, by combining it with an emotion engine, it can analyze the user's emotional state and provide optimal plans based on that state.

[0703] The user enters information

[0704] The user uses a device (e.g., a smartphone or PC) to input information about what they want to do. This information includes location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., two people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor activities (e.g., indoors).

[0705] Emotion engine recognizes user emotions

[0706] The device activates an emotion engine that recognizes the user's emotions based on the user's input information and interface operation history. The emotion engine uses natural language processing and machine learning techniques to analyze the user's psychological state. The results of this analysis are expressed as the user's condition (for example, stressed, relaxed, excited, etc.).

[0707] The device sends the information to the server

[0708] The device sends the information entered by the user and the emotional state recognized by the emotion engine to the server in a general-purpose data format such as JSON.

[0709] The server collects the latest information from social media and news sites.

[0710] The server uses the APIs of social media and news sites to collect the latest relevant information based on the user's input information and emotional state. Specifically, it calls the news API to retrieve the latest articles and news about the location. It also uses the social media API to retrieve recent posts and trending information about the location.

[0711] The server collects the latest data from the facility.

[0712] The server accesses databases and APIs provided by facility operators to collect information such as availability and congestion status of facilities that meet the user's criteria, as well as information on special services offered.

[0713] The server generates the optimal plan using an AI algorithm

[0714] The server combines the latest collected information with the facility's data and uses an AI algorithm to generate the optimal time-killing plan. The server also takes into account the user's emotional state and selects the plan that will most satisfy the user. For example, if the server detects that the user is under stress, it will select a plan that provides a relaxing environment.

[0715] The server sends the generated plan to the device.

[0716] The server converts the generated plan back into a data format such as JSON format and sends it to the terminal as an HTTP response.

[0717] The device displays the plan to the user.

[0718] The device analyzes the plan data received from the server and displays it in a user-friendly format, including the location of the best facility, the time frame, estimated costs within the budget, reviews and ratings, the occupancy status, and the reasons for the recommendation based on the emotion engine.

[0719] Specific examples

[0720] If a user inputs "I'd like to find a cafe for two in Tokyo starting at 3 PM, my budget is 2,000 yen, and I'd prefer it to be indoors," and the emotion engine recognizes the user's stress level, the server will generate a plan based on the latest information it has collected: "A 'Relaxation Cafe' in Shibuya, Tokyo is ideal for 3 PM, and the price is within my budget," and send it to the device. The device will then display this plan in detail to the user, adding, "Based on your current emotional state, we've recommended a relaxing cafe."

[0721] In this way, the system not only allows users to kill time, but also allows them to quickly and easily obtain a plan that best suits their emotional state.

[0722] The processing flow will be explained below.

[0723] Program processing steps

[0724] Step 1:

[0725] The user enters information about what they want to do on the device. They enter a specific location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., 2 people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor use (e.g., indoors) into input fields.

[0726] Step 2:

[0727] The device collects the input information and activates the emotion engine. The emotion engine analyzes the user's emotions based on the information the user inputs and the operation history of the interface. For example, if the user inputs a lot of characters in a short period of time, it will recognize that the user is under stress.

[0728] Step 3:

[0729] The emotion engine generates the results of its analysis as user condition data, which includes the user's psychological state, such as stress, relaxation, or excitement.

[0730] Step 4:

[0731] The device converts the user's input information and the condition data generated by the emotion engine into a data format such as JSON and sends it to the server.

[0732] Step 5:

[0733] The server parses (analyzes) the request data it receives and extracts the conditions entered by the user and the condition data based on the emotion engine.

[0734] Step 6:

[0735] The server uses the APIs of social media and news sites to collect the latest information about the location specified by the user. Specifically, it calls the news API to obtain the latest articles and news about the location, and uses the social media API to obtain recent posts and trending information related to the location.

[0736] Step 7:

[0737] The server accesses databases and APIs provided by facility operators to collect information such as availability, congestion, and special service availability at facilities that meet the user's criteria.

[0738] Step 8:

[0739] The server combines the latest information collected by the server with data from the facility and uses an AI algorithm to generate an optimal time-killing plan. This plan also takes into account the user's emotional state. For example, if the system detects that the user is under stress, it will select a plan that provides a relaxing environment.

[0740] Step 9:

[0741] The server converts the generated plan data into a data format such as JSON and sends it to the terminal as an HTTP response.

[0742] Step 10:

[0743] The device analyzes the plan data received from the server and displays it in a user-friendly format, including the location of the best facility, the time frame, the estimated cost within the budget, reviews and ratings, the occupancy status, and the reason for the recommendation based on the emotion engine.

[0744] Specific examples

[0745] Example input:

[0746] The user inputs, "I want to find a cafe for two in Tokyo from 3pm. My budget is 2000 yen, preferably indoors." The emotion engine also recognizes the user's stress level.

[0747] Example output:

[0748] Based on the latest information and facility data collected by the server, the AI ​​generates a plan suggesting that a "Relax Cafe" in Shibuya, Tokyo, is optimal for 3 PM and within budget, and sends it to the device. The device displays this plan in detail to the user, adding, "Based on your current emotional state, we have recommended a relaxing cafe."

[0749] Recommended Plan:

[0750] Location: Relax Cafe in Shibuya, Tokyo

[0751] Time: 15:00 - 16:00

[0752] Budget: Under 2000 yen

[0753] Customer Review: ★★★★☆

[0754] Availability: Currently empty

[0755] Reason for recommendation: Based on your current emotional state, we recommended a relaxing cafe.

[0756] In this way, the system not only allows users to kill time, but also allows them to easily obtain a plan that is optimal for their emotional state.

[0757] Example 2

[0758] 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."

[0759] Existing systems simply provide time-killing plans based on location, time, budget, and other criteria, without considering the user's current emotional state. This makes it difficult for users to quickly find an appropriate plan that truly relaxes them and reduces stress. Furthermore, these systems do not integrate the latest information from social media and news sites or the congestion status of facilities. This creates a need for systems that provide optimal time-killing plans tailored to the user's needs.

[0760] 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.

[0761] In this invention, the server includes input means for inputting information about things the user wants to do, emotion recognition means for recognizing the information and the user's emotional state, transmission means for transmitting the information and the emotional state to the server, collection means for acquiring the latest information from social networking services and news sites based on the information and the emotional state, generation means for generating an optimal time-killing plan based on the information, the emotional state, and the collected information, transmission means for transmitting the generated plan to the user, and display means for displaying the plan to the user. This makes it possible to quickly and easily provide an optimal time-killing plan based on the latest related information while taking into account the user's current emotional state.

[0762] "Input means" refers to an interface for inputting information about what the user wants to do into the terminal.

[0763] "Emotion recognition means" refers to a function for analyzing and recognizing a user's emotional state based on the user's input information and operation history using natural language processing and machine learning technology.

[0764] The "transmission means" refers to a function for transmitting the information input by the user and the emotional state recognized by the emotion recognition means to the server in data format.

[0765] "Collection means" refers to the function that allows the server to use the APIs of social networking services and news sites to collect the latest information based on the user's input information and emotional state.

[0766] The "generation means" refers to a function that integrates the latest information and facility data collected by the collection means, and generates an optimal time-killing plan using an AI algorithm, taking into consideration the user's emotional state.

[0767] "Display means" refers to a function for analyzing the optimal time-killing plan sent from the server, formatting it in a format that is easy for the user to view, and displaying it on the terminal.

[0768] The term "server" refers to a central processing unit that receives information and emotional states sent by users, collects related information, generates plans, and transmits the generated plans to terminals.

[0769] "Terminal" refers to a device through which a user inputs information, communicates with the server, and receives the generated plan. Specifically, this includes smartphones, PCs, etc.

[0770] This system allows users to input information about what they want to do and proposes optimal time-killing plans based on that information. Furthermore, by combining it with an emotion engine, it can analyze the user's emotional state and provide optimal plans based on that state.

[0771] The user enters information

[0772] Users use devices such as smartphones or computers to input information about what they want to do, including location, time, number of people, genre, budget, and preference for indoor or outdoor activities.

[0773] Emotion engine recognizes user emotions

[0774] The device activates an emotion engine based on the user's input information and the application's operation history. The emotion engine uses natural language processing and machine learning technologies (such as Python's NLP library or TensorFlow) to analyze the user's psychological state. The analysis results are expressed as a condition, such as "stressed," "relaxed," or "excited."

[0775] The device sends the information to the server

[0776] The device sends the information entered by the user and the emotional state recognized by the emotion engine to the server. The data is sent in a general data format such as JSON (e.g., "{"Location": "Tokyo", "Time": "15:00", "Number of people": "2", "Genre": "Cafe", "Budget": "2000 yen", "Indoor": "Preferred", "Emotional state": "Stressed"}").

[0777] The server collects the latest information from social media and news sites.

[0778] Based on the user's input information and emotional state, the server collects the latest related information using APIs of social media and news sites (e.g., Twitter API, News API, etc.), thereby obtaining recent posts, trending information, the latest articles, and news related to the location.

[0779] The server collects the latest data from the facility.

[0780] The server accesses databases and APIs provided by facility operators to collect information on facility availability and special service availability that matches the user's criteria. For example, this includes information on facility seat availability and whether or not special services are available.

[0781] The server generates the optimal plan using an AI algorithm

[0782] The server combines the collected latest information with the facility's data and uses a generative AI model (e.g., trend prediction model or recommendation model) to generate an optimal time-killing plan. The server also takes into account the user's emotional state and selects a plan that will most satisfy the user. For example, if the server detects that the user is under stress, it selects a plan that provides a relaxing environment.

[0783] The server sends the generated plan to the device.

[0784] The server converts the generated plan back into a data format such as JSON format and sends it to the terminal as an HTTP response.

[0785] The device displays the plan to the user.

[0786] The device analyzes the plan data received from the server and displays it in a user-friendly format, including the location of the best facility, the time frame, estimated costs within the budget, reviews and ratings, the occupancy status, and the reasons for the recommendation based on an emotion engine.

[0787] Specific examples

[0788] For example, if a user inputs "I'd like to find a cafe for two in Tokyo starting at 3 PM, with a budget of 2,000 yen and preferably indoors," and the emotion engine recognizes the user's stress level, the server will generate a plan based on the latest information it has collected: "A 'Relaxation Cafe' in Shibuya, Tokyo is ideal for 3 PM, and the price is within budget," and send it to the device. The device will then display this plan in detail to the user, adding a note that "Based on your current emotional state, we have recommended a relaxing cafe."

[0789] In this way, the system not only allows users to kill time, but also allows them to quickly and easily obtain a plan that best suits their emotional state.

[0790] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0791] Step 1:

[0792] Users input information about what they want to do into the device. Specifically, they input the location, time, number of people, genre, budget, and preference for indoor or outdoor activities on the screen of their smartphone or computer, and then press the send button.

[0793] Input: User's own input: "Location: Tokyo", "Time: 15:00", "Number of people: 2", "Genre: Cafe", "Budget: 2000 yen", "Indoor: Preferred"

[0794] Output: The input information is passed to the next emotion recognition means.

[0795] Step 2:

[0796] The emotion engine recognizes the user's emotions. The device activates the emotion engine based on the information just entered and the app's operation history. The emotion engine uses natural language processing and machine learning technologies to analyze the user's psychological state.

[0797] Input: User input information and operation history

[0798] Data processing method: Analyze the input data using a natural language processing library (e.g., spaCy or NLTK) and apply a sentiment classification algorithm (e.g., SVM, Random Forest).

[0799] Output: The recognition result is "Emotional state: Stressed".

[0800] Step 3:

[0801] The device sends the input information and the perceived emotional state to the server, where the data is packaged in JSON format and sent as an HTTP POST request.

[0802] Input: Input information and emotional state

[0803] Data Calculation: Converting data to JSON format and creating HTTP requests

[0804] Output: An HTTP POST request is made to the server, sending the entire data.

[0805] Step 4:

[0806] The server collects the latest information from social media and news sites. Based on the information received, the server calls social media APIs (e.g., Twitter API) and news APIs (e.g., NewsAPI) to retrieve the latest related articles and trending information.

[0807] Input: User input and emotional state

[0808] Data calculation: Sending a query to the API (e.g. "Tokyo Cafe Latest News") and analyzing the received response

[0809] Output: A dataset of the latest articles and social media posts.

[0810] Step 5:

[0811] The server collects the latest data from the facility, accesses the facility operator's database and API, and obtains information about availability and special services that match the user's criteria.

[0812] Input: User's condition and emotional state

[0813] Data Calculation: Sending API queries and parsing response data

[0814] Output: A dataset of facility availability and special offers.

[0815] Step 6:

[0816] The server generates the optimal plan using an AI algorithm, integrating the collected data sets and using a generative AI model to create the optimal plan.

[0817] Input: Latest articles, social media posting data, facility availability information, special service information

[0818] Data Computing: Data integration and application of AI algorithms (e.g., multi-label classifiers and recommendation systems)

[0819] Output: The optimal time-killing plan to be provided to the user is generated.

[0820] Step 7:

[0821] The server sends the generated plan to the terminal. The generated plan is converted to JSON format and sent to the terminal as an HTTP response.

[0822] Input: Generated optimal time-killing plan

[0823] Data operations: converting to JSON format and creating an HTTP response

[0824] Output: An HTTP response is generated and sent to the device.

[0825] Step 8:

[0826] The terminal displays the plan to the user. It analyzes the plan data received from the server, formats it in a format that is easy for the user to view, and displays it.

[0827] Input: Plan data in JSON format

[0828] Data computation: Data analysis and visualization (e.g., display using front-end libraries)

[0829] Output: The user is shown "Relax Cafe" with a message saying "Based on your current emotional state, we have recommended a cafe where you can relax."

[0830] (Application example 2)

[0831] 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."

[0832] While conventional systems have the ability to provide optimal plans based on the user's preferences and desired conditions, they lack the ability to take into account the user's emotional state. This poses a challenge: they are unable to quickly provide plans that meet the user's psychological needs, especially when they are stressed or want to relax. Furthermore, there are limitations to the suggestions they can make for specific genres of activities or services (e.g., food delivery), making it difficult to fully satisfy the diverse needs of users.

[0833] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0834] In this invention, the server includes input means for inputting information about what the user wants to do, transmission means for transmitting the information and the user's emotional state to the server, collection means for collecting related information based on the information and the emotional state, generation means for generating an optimal delivery plan based on the collected information and the user's state, transmission means for transmitting the generated plan to the user, and display means for displaying the plan to the user. This makes it possible to propose an optimal delivery plan that takes the user's psychological state into consideration.

[0835] "Input means" refers to a device or interface for inputting information about what the user wants to do.

[0836] "Transmitting means" refers to the devices and protocols used to transmit input information and the user's emotional state to the server.

[0837] The "collection means" refers to devices or software that allow the server to collect relevant information based on input information and emotional state.

[0838] The "generation means" refers to a device or algorithm that generates an optimal delivery plan based on the collected information and the user's status.

[0839] The "display means" is a device or interface for presenting the generated plan to the user.

[0840] A "social networking service" is a service or platform that allows users to interact with each other over the Internet.

[0841] "News delivery methods" are systems and services that provide the latest news and information.

[0842] A "food delivery service" is a service that allows you to order food and drinks and have them delivered to a specified location.

[0843] "Mental state" refers to the user's subjective feelings and mental condition.

[0844] The present invention relates to a system for proposing an optimal delivery plan in consideration of the emotional state of a user. A detailed embodiment for realizing this system will be described below.

[0845] Main components and technologies used

[0846] 1. Input Method

[0847] It is a device or interface for users to input information about what they want to do. For example, a smartphone app falls into this category, and is implemented as a cross-platform application using React Native.

[0848] 2. Transmission Method

[0849] It is a device and protocol for transmitting input information and the user's emotional state to a server. It mainly uses the HTTP protocol, and data is transmitted in JSON format.

[0850] 3. Collection Method

[0851] This is a device or software that allows the server to collect relevant information based on input information and emotional state. The Axios library is used to collect data, and the latest information is obtained from social networking service (SNS) APIs and news sources.

[0852] 4. Generation means

[0853] These are devices and algorithms that generate optimal delivery plans based on collected information and the user's status. A generative AI model using TensorFlow is used as a powerful tool.

[0854] 5. Display means

[0855] This is the device or interface for presenting the generated plan to the user. React Native UI components are used to display it within the application.

[0856] System Operation Overview

[0857] The server generates an optimal delivery plan through the following steps and provides it to the user.

[0858] 1. Enter your user information

[0859] Users input desired meal information (e.g., type of food, budget, number of people, time) through a smartphone app. The emotion engine also analyzes the user's psychological state, for example, if the user is under stress.

[0860] 2. Data transmission

[0861] The entered information and the user's emotional state are formatted and sent to the server in JSON format.

[0862] 3. Data Collection

[0863] The server collects the latest relevant information using the APIs of related food delivery services (e.g., UberEats API and DoorDash API) and social media APIs (e.g., Twitter API).

[0864] 4. Generating the optimal plan

[0865] The AI ​​algorithm uses the collected data to generate an optimal meal plan that takes into account the user's emotional state and preferences, using a deep learning model powered by TensorFlow.

[0866] 5. Submitting and Viewing Plans

[0867] The generated plan is converted back to JSON format and sent to the smartphone app, which displays the plan in an easy-to-understand format to the user, along with the reasons for the proposal.

[0868] Specific examples

[0869] For example, if a user enters "Chinese food," "under 2,000 yen," "for two people," "7 p.m." and "looking to relieve stress" into a smartphone app, the emotion engine will check the user's stress level from their operation history. The app will collect the latest related information and suggest "We recommend the Chinese restaurant 'Relax Garden.'" Furthermore, the app will display relaxing music and menu recommendations.

[0870] Prompt Sentence Examples

[0871] "Enter the user's emotional state and preferences, and generate a meal plan based on the latest food delivery information. The plan should also emphasize relaxation."

[0872] This system makes it possible to propose delivery plans that optimally take into account the user's psychological state.

[0873] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0874] Step 1:

[0875] Users use a smartphone app to input information about the meal they want (e.g., type of meal, budget, number of people, time) and their current emotional state (e.g., desire to relieve stress).

[0876] Input: genre, budget, number of people, time, emotional state

[0877] Output: User information (JSON format)

[0878] Specific behavior: The user enters information in an interface developed using React Native and presses the "Submit" button.

[0879] Step 2:

[0880] The device formats the input user information and emotional state into JSON format and sends it to the server using the HTTP protocol.

[0881] Input: User information (JSON format)

[0882] Output: HTTP request sent to the server

[0883] Specific operation: In the React Native application, an HTTP POST request is created using the Axios library and sent to the server.

[0884] Step 3:

[0885] The server analyzes the received user information and emotional state and collects related information. Here, it calls the API of social media sites and food delivery services to obtain related data.

[0886] Input: User information (JSON format), emotional state

[0887] Output: Relevant information collected

[0888] Specific operation: A server implemented using Node.js and Express.js calls the Twitter API and Uber Eats API using the Axios library to collect data.

[0889] Step 4:

[0890] The server generates an optimal delivery plan based on the collected information and the user's emotional state using a generative AI model powered by TensorFlow.

[0891] Input: Collected relevant information, emotional state

[0892] Output: Optimal delivery plan

[0893] Specific operation: The collected data is input into a TensorFlow deep learning model to generate an optimal plan.

[0894] Step 5:

[0895] The server formats the generated delivery plan again into JSON format and sends it to the terminal as an HTTP response.

[0896] Input: Optimal delivery plan (JSON format)

[0897] Output: Plan sent as HTTP response

[0898] Specific operation: The generated plan is converted to JSON and sent as an HTTP response using Express.js in Node.js.

[0899] Step 6:

[0900] The device analyzes the received delivery plan and displays it in a format that is easy for the user to view. The app also displays the reason for the proposal and additional information that may have a relaxing effect (e.g., relaxing music).

[0901] Input: Optimal delivery plan (JSON format)

[0902] Output: The delivery plan displayed to the user

[0903] What it does: Uses React Native to display the best delivery plan on the screen, along with additional information.

[0904] This processing step allows for the proposal of an optimal delivery plan that takes into account the user's psychological state.

[0905] 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.

[0906] 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.

[0907] 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.

[0908] [Third embodiment]

[0909] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0910] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0911] 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).

[0912] 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.

[0913] 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.

[0914] 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).

[0915] 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.

[0916] 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.

[0917] 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.

[0918] 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.

[0919] 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.

[0920] 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."

[0921] The present invention is a system that, when a user inputs information about what they want to do, proposes an optimal time-killing plan based on that information. Specific embodiments of the system will be described in detail below.

[0922] The user enters information

[0923] The user uses a device (e.g., a smartphone or PC) to input information about what they want to do. This information includes location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., two people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor activities (e.g., indoors).

[0924] The device sends the information to the server

[0925] The terminal sends the information entered by the user to the server. This information consists of multiple fields and is sent in a generic data format such as JSON.

[0926] The server collects the latest information from social media and news sites.

[0927] The server collects the latest relevant information from the Internet based on the user's input. Specifically, it uses the APIs of social networking services and news sites to obtain the latest news, current weather, crowding status, event information, and other information for the relevant location.

[0928] The server collects the latest data from the facility.

[0929] The server also collects data provided by the facility operator, including facility availability, special service offers, price ranges, etc.

[0930] The server generates the optimal plan using an AI algorithm

[0931] The server uses an AI algorithm to generate the optimal time-killing plan based on the latest relevant information collected and the user's input criteria. The AI ​​selects the plan that best suits the user's preferences, taking into account factors such as traffic congestion, budget, and current weather.

[0932] The server sends the generated plan to the device.

[0933] The server sends the generated plan to the device in JSON format, etc. The plan includes detailed information such as specific locations, time frames, estimated costs within the budget, reference reviews and ratings, and congestion status.

[0934] The device displays the plan to the user.

[0935] The terminal will display the plan in a user-friendly format, for example:

[0936] Recommended Plan:

[0937] Location: Cafe A, Shibuya, Tokyo

[0938] Time: 15:00 - 16:00

[0939] Budget: Under 2000 yen

[0940] Customer Review: ★★★★☆

[0941] Availability: Currently empty

[0942] This allows users to easily find the best time-killing plan in real time.

[0943] Specific examples

[0944] If a user inputs "I want to find a cafe for two in Tokyo starting at 3 PM, my budget is 2000 yen, and I prefer indoor dining," the server will generate a plan based on the latest information it has collected: "Cafe A in Shibuya, Tokyo is the best choice at 3 PM, and the price is within my budget," and send it to the device. The device will then display this plan in detail to the user.

[0945] In this way, this system allows users to efficiently choose ways to kill time even when they suddenly have free time, and spend it meaningfully.

[0946] The processing flow will be explained below.

[0947] Program processing steps

[0948] Step 1:

[0949] The user enters information about what they want to do on the device. They enter a specific location, time, number of people, genre, budget, and preference for indoor / outdoor use into input fields.

[0950] Step 2:

[0951] The terminal converts the input information into a data format such as JSON and sends it to the server as an HTTP POST request.

[0952] Step 3:

[0953] The server parses the received request data and extracts the information entered by the user, including location, time, number of people, genre, budget, and preference for indoor / outdoor.

[0954] Step 4:

[0955] The server uses the APIs of social media and news sites to collect the latest information about the location specified by the user. Specifically, it calls the news API to retrieve the latest articles and news about the location. It also uses the social media API to retrieve recent posts and trending information about the location.

[0956] Step 5:

[0957] The server accesses databases and APIs provided by facility operators to collect information such as availability and congestion status of facilities that meet the user's criteria, as well as information on special services offered.

[0958] Step 6:

[0959] The server combines the latest information collected with the facility's own data and prepares it for passing to the AI ​​algorithm. This combined data includes news, social media trends, facility availability, congestion status, price range, and more.

[0960] Step 7:

[0961] The server runs an AI algorithm, comparing the integrated data with the user's requirements to generate the optimal time-killing plan. The AI ​​analyzes the collected information and selects the plan that best suits the user's needs, taking into account factors such as weather, congestion, and budget.

[0962] Step 8:

[0963] The server converts the generated plan back into a data format such as JSON and sends it to the terminal as an HTTP response.

[0964] Step 9:

[0965] The device analyzes the plan data received from the server and displays it in a format that is easy for the user to view, including the location of the best facility, the time frame, cost estimates within the budget, reviews and ratings, and congestion status.

[0966] These detailed processing steps allow the user to easily input information about what they want to do and quickly obtain the best time-killing plan based on that information.

[0967] Example 1

[0968] 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."

[0969] Conventional systems have had the problem of making it difficult for users to find the best time-killing plan when they suddenly have some free time. In particular, they lacked the means to collect the latest information and, based on that information, propose a plan that met the user's conditions and preferences. Furthermore, since they were unable to plan based on the facility's congestion status or real-time information, it was difficult for users to spend their time efficiently.

[0970] 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.

[0971] In this invention, the server includes input means for inputting information about what the user wants to do, transmission means for transmitting the information to the server, collection means for collecting the latest related information from social networking services and news sites based on the information, collection means for collecting data provided by facilities, generation means for generating an optimal time-killing plan using an AI algorithm based on the collected information and the user's conditions, transmission means for transmitting the generated plan to the user, and display means for displaying the plan to the user. This allows the user to obtain an optimal time-killing plan based on the latest information in real time, allowing them to spend their time efficiently even when they have sudden free time.

[0972] A "user" is an individual or group who uses the system to input information about what they want to do and receives suggestions for ways to kill time.

[0973] "Server" refers to a computer system that receives information sent by users, collects and processes various data, and sends the generated plan to terminals.

[0974] "Input means" refers to a software or hardware mechanism for inputting information about what a user wants to do via a terminal.

[0975] The "transmission means" is a communication function for transmitting information input by the user to the server.

[0976] "Collection means" is a function that allows the server to obtain the latest relevant information from various information sources on the Internet.

[0977] The "generation means" is a function that uses an AI algorithm to generate the optimal time-killing plan based on the collected information and the user's conditions.

[0978] The "display means" is a software or hardware mechanism for displaying the generated plan on a terminal in a format that is easy for the user to understand.

[0979] "Social networking services" refers to online platforms such as Twitter and Facebook, which allow users to post and share information.

[0980] "News site" refers to a website that contains current news articles and information.

[0981] "Facility-provided data" refers to information such as availability, special services, and price ranges that facility operators make public via APIs, etc.

[0982] An "AI algorithm" is a machine learning technology or data processing method that analyzes multiple collected data and generates an optimal plan based on user input conditions.

[0983] A "time-killing plan" is a specific activity suggestion provided to help users spend their free time effectively.

[0984] The present invention is a system that, when a user inputs information about what they want to do, proposes an optimal time-killing plan based on that information. Specific embodiments of the system will be described in detail below.

[0985] The user enters information

[0986] Users use devices such as smartphones or computers to enter information about what they want to do into a dedicated input form. Information to be entered includes location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., 2 people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor or outdoor activities (e.g., indoors). Specifically, users enter information into the fields on the screen and click the "Submit" button.

[0987] The device sends the information to the server

[0988] The device sends the data entered by the user to the server in a data format such as JSON. An HTTP POST request is used for sending the data. For example, the data may contain information such as "{ "Location": "Tokyo", "Time": "15:00", "Number of people": 2, "Genre": "Cafe", "Budget": 2000, "Indoor / Outdoor": "Indoor"}".

[0989] The server collects information from social media and news sites.

[0990] The server uses the received data to collect the latest information from social media and news sites. Specifically, it uses the APIs of social media sites such as Twitter and Facebook to obtain the latest information on the relevant area. It also uses RSS feeds and APIs from news sites to collect data such as current weather, event information, and crowding levels.

[0991] The server collects facility-provided data

[0992] The server uses the facility's API to obtain information about the facility's availability, special services, price range, etc. This allows the server to take into account the facility's status, which is updated in real time.

[0993] The server generates the optimal plan using an AI algorithm

[0994] The server provides the latest collected data and user input information to an AI algorithm, which then comprehensively evaluates the user's desired conditions (e.g., congestion, budget, weather) and generates the optimal time-killing plan. Using a machine learning model, the algorithm recommends a plan that takes congestion and weather into account.

[0995] The server sends the generated plan to the device.

[0996] The server then sends the generated plan to the device in JSON format. The plan includes details such as the specific location, time frame, estimated costs within the budget, reviews and ratings for reference, and congestion status. The plan is typically sent as an HTTP response.

[0997] The device displays the plan to the user.

[0998] The device will then display the received plan in a user-friendly format, for example:

[0999] Location: Cafe A, Shibuya, Tokyo

[1000] Time: 15:00 - 16:00

[1001] Budget: Under 2000 yen

[1002] Customer Review: ★★★★☆

[1003] Availability: Currently empty

[1004] This allows the user to obtain the best time-killing plan in real time.

[1005] Specific examples

[1006] For example, if a user inputs "I want to find a cafe for two in Tokyo starting at 3 PM, my budget is 2,000 yen, and I prefer it to be indoors," the device will send that information in JSON format to the server. The server will then generate the optimal plan based on data from social media, news sites, and facilities. The server will generate a plan such as "Cafe A in Shibuya, Tokyo is the best place for 3 PM, and the price is within my budget," and send it to the device. The device will then display this information in detail to the user, allowing them to find the optimal plan for killing time.

[1007] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1008] Step 1: User Enters Information

[1009] The user uses a device (smartphone or PC) to input information about what they want to do. The input items are location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., 2 people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor use (e.g., indoors). Once the input is complete, the user clicks the "Submit" button.

[1010] Input: User's desired conditions (location, time, number of people, genre, budget, indoor / outdoor)

[1011] Output: The input information is saved in a data field in the terminal.

[1012] Step 2: The device sends the information to the server

[1013] The device encodes the information entered by the user into JSON format and sends it to the server using an HTTP POST request. At this time, the information field contains data such as "{ "Location": "Tokyo", "Time": "15:00", "Number of people": 2, "Genre": "Cafe", "Budget": 2000, "Indoor / Outdoor": "Indoor"}".

[1014] Input: Information entered by the user

[1015] Output: JSON format data sent to the server

[1016] Step 3: The server collects information from social media and news sites.

[1017] The server uses the APIs of social media and news sites to collect relevant information based on the received user information. Based on the specified location and time, the server retrieves the latest local news, event information, and weather information from the APIs of Twitter and Facebook.

[1018] Input: User information in JSON format

[1019] Output: Latest information collected from social media and news sites (e.g., latest local news, weather, event information)

[1020] Step 4: Server collects facility-provided data

[1021] The server uses the API provided by the facility operator to collect information such as facility availability, special services, price range, etc. This allows the server to obtain real-time data about a specific facility.

[1022] Input: Facility-related request parameters (e.g., location, genre, budget)

[1023] Output: Collected facility-provided data (availability, special services, price range)

[1024] Step 5: The server analyzes the data using AI algorithms and generates an optimal plan

[1025] The server then supplies the collected data from social media, news sites, and facilities to an AI algorithm for analysis. This AI algorithm then comprehensively evaluates the user's desired conditions and generates the optimal time-killing plan. For example, it may recommend the best facility within a user's budget, taking into account crowding and weather conditions.

[1026] Input: User information, SNS information, news site information, facility data

[1027] Output: The best time-killing plan

[1028] Step 6: The server sends the generated plan to the device

[1029] The server then encodes the generated itinerary into JSON format and sends it to the device using an HTTP response, which includes data such as location, time frame, estimated cost within budget, user ratings, and occupancy status.

[1030] Input: The best time-killing plan

[1031] Output: Plan data in JSON format sent to the device

[1032] Step 7: The device displays the plan to the user

[1033] The device displays the received plan in an easy-to-read format for the user. For example, details such as "Cafe A in Shibuya, Tokyo, from 3:00 PM to 4:00 PM, budget within 2,000 yen, customer rating ★★★★☆, currently available" are displayed.

[1034] Input: Plan data sent from the server

[1035] Output: A specific time-killing plan displayed to the user

[1036] (Application example 1)

[1037] 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."

[1038] In modern society, there is a demand for systems that allow users to make effective use of their limited free time. However, existing systems have limited functionality in providing optimal time-killing plans based on a user's specific conditions or current location. In particular, when it comes to food delivery, there has been a lack of systems that can instantly respond to changing conditions such as a user's location, budget, and waiting time. This has made it difficult for users to find the optimal delivery plan.

[1039] 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.

[1040] In this invention, the server includes input means for inputting information about what the user wants to do, transmission means for transmitting the information to the server, collection means for collecting the latest related information based on the information, generation means for generating an optimal plan based on the collected information and the user's conditions, transmission means for transmitting the generated plan to the user, display means for displaying the plan to the user, and means for inputting the user's location information, food genre, budget, and waiting time and proposing an optimal delivery plan, thereby enabling the user to quickly find the optimal food delivery plan that meets their conditions.

[1041] "User information" refers to information about what the user wants to do, including location information, cuisine genre, budget, waiting time, etc.

[1042] "Input means" refers to a means for inputting information about what the user wants to do into the terminal.

[1043] The "transmission means" is a means for transmitting information input by the user to the server.

[1044] The "collection means" is a means for collecting the latest related information based on the information entered by the user.

[1045] The "generation means" is a means for generating an optimal plan based on the collected information and the user's conditions.

[1046] The "display means" is a means for displaying the generated plan to the user.

[1047] The "Food Delivery Plan" is a plan that suggests the most suitable restaurant and menu based on the user's location, cuisine type, budget, waiting time, and other conditions.

[1048] A "delivery service" is a service that delivers food to a location specified by the user.

[1049] "Related information" refers to the latest information obtained from social networking services, news sites, review platforms, etc.

[1050] "Crowding status" is information that indicates how crowded a particular facility or service is currently.

[1051] This invention is a system that allows users to effectively utilize their limited free time, and proposes plans that are particularly specialized for food delivery. A specific embodiment of this system will be described in detail below.

[1052] System Overview

[1053] Using a device such as a smartphone, a user inputs information about what they want to do, such as their current location, desired cuisine genre, budget, maximum waiting time, etc. This information is sent from the device to the server.

[1054] Hardware and software used

[1055] Hardware: Smartphone (iOS / Android)

[1056] Software: Python 3.8+, requests library, generative AI model (e.g., profile-based recommendation engine)

[1057] Data processing and calculation flow

[1058] 1. Data Entry

[1059] The user uses the terminal to input necessary information (for example, current location, cuisine genre, budget, waiting time, etc.).

[1060] These data are transmitted from the terminal to the server.

[1061] 2. Data Collection

[1062] The server collects relevant information from multiple data sources, including social networking services (SNS), news sites, and review platforms.

[1063] The collected data is structured in a general-purpose data format such as JSON.

[1064] 3. Generated by AI algorithms

[1065] The server generates an optimal food delivery plan based on the collected data and the user's requirements using a generative AI model, such as one that uses deep learning or machine learning techniques.

[1066] This process takes into account the user's location, cuisine, budget, wait time limit, and review ratings.

[1067] 4. Submitting and Viewing Plans

[1068] The server sends the generated optimal plan to the device in JSON format.

[1069] The device then displays the received plan to the user, showing the best restaurant, estimated time, menu items within the budget, and ratings of recommended menu items.

[1070] Specific examples

[1071] For example, if the user enters the following criteria:

[1072] Current location: Tokyo

[1073] Cuisines: Pizza

[1074] Budget: 1,500 yen

[1075] Maximum waiting time: 30 minutes

[1076] Based on this, the server gathers relevant information and generates a plan like this:

[1077] Restaurant: "Pizza House Tokyo"

[1078] Menu: Margherita pizza

[1079] Price: 1,400 yen

[1080] Estimated wait time: 25 minutes

[1081] Review rating: ★★★★☆

[1082] Prompt Sentence Examples

[1083] "Generate the best food delivery plan that matches the user's criteria. The criteria are as follows:

[1084] Current location: Tokyo

[1085] Cuisines: Pizza

[1086] Budget: 1,500 yen

[1087] Maximum waiting time: 30 minutes

[1088] The AI ​​model takes into account the latest restaurant information and reviews to provide the best plan.”

[1089] In this way, the system allows users to quickly and easily find the best food delivery plan that meets their requirements.

[1090] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1091] Step 1:

[1092] The user uses a device such as a smartphone to input information such as their current location, desired cuisine type, budget, and maximum waiting time. At this stage, the user inputs the conditions related to what they want into the device, and these conditions are saved in a general-purpose format such as JSON.

[1093] input:

[1094] current location

[1095] Desired cuisine genre

[1096] budget

[1097] Waiting time limit

[1098] output:

[1099] Input data in JSON format

[1100] Specific behavior:

[1101] The user enters the required information into the input form and presses the submit button.

[1102] Step 2:

[1103] The device sends the information entered by the user to the server. At this stage, the device sends the JSON formatted input data that it saved earlier to the server using an HTTP request.

[1104] input:

[1105] User-supplied data in JSON format

[1106] output:

[1107] HTTP request to the server

[1108] Specific behavior:

[1109] Use a library to generate and send HTTP requests (e.g. requests).

[1110] Step 3:

[1111] The server collects relevant information based on the conditions entered by the user from multiple data sources, such as social media, news sites, and review platforms. The collected data is saved in a unified format (e.g., JSON format).

[1112] input:

[1113] Filtering information based on user conditions

[1114] output:

[1115] Data collected from social networking services, news sites, and review platforms

[1116] Specific behavior:

[1117] Collect information by calling multiple APIs (e.g., social media API, review API).

[1118] Step 4:

[1119] The server generates the optimal food delivery plan based on the collected information and the user's requirements using a generative AI model. The generative AI model implements a recommendation algorithm using deep learning and machine learning techniques to calculate the plan that best matches the user's requirements.

[1120] input:

[1121] Data collected

[1122] User Conditions

[1123] output:

[1124] Data on the best food delivery plans

[1125] Specific behavior:

[1126] Input data into an AI model (e.g., a recommendation engine) to generate a plan.

[1127] Step 5:

[1128] The server sends the generated optimal food delivery plan to the device. The plan is sent in a general format such as JSON.

[1129] input:

[1130] Data on the best food delivery plans

[1131] output:

[1132] HTTP response to the device

[1133] Specific behavior:

[1134] Use a library (e.g. a web framework such as Flask) to generate and send HTTP responses.

[1135] Step 6:

[1136] The device then displays the received food delivery plan to the user, showing the best restaurant, estimated time, menu items within the budget, and ratings of recommended menu items.

[1137] input:

[1138] Food delivery plan sent from the server

[1139] output:

[1140] Display data for users

[1141] Specific behavior:

[1142] Visually display data using presentational UI components (e.g. HTML, CSS, JavaScript).

[1143] This allows users to quickly and easily find the best food delivery plan that meets their requirements.

[1144] 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.

[1145] This system allows users to input information about what they want to do and proposes optimal time-killing plans based on that information. Furthermore, by combining it with an emotion engine, it can analyze the user's emotional state and provide optimal plans based on that state.

[1146] The user enters information

[1147] The user uses a device (e.g., a smartphone or PC) to input information about what they want to do. This information includes location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., two people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor activities (e.g., indoors).

[1148] Emotion engine recognizes user emotions

[1149] The device activates an emotion engine that recognizes the user's emotions based on the user's input information and interface operation history. The emotion engine uses natural language processing and machine learning techniques to analyze the user's psychological state. The results of this analysis are expressed as the user's condition (for example, stressed, relaxed, excited, etc.).

[1150] The device sends the information to the server

[1151] The device sends the information entered by the user and the emotional state recognized by the emotion engine to the server in a general-purpose data format such as JSON.

[1152] The server collects the latest information from social media and news sites.

[1153] The server uses the APIs of social media and news sites to collect the latest relevant information based on the user's input information and emotional state. Specifically, it calls the news API to retrieve the latest articles and news about the location. It also uses the social media API to retrieve recent posts and trending information about the location.

[1154] The server collects the latest data from the facility.

[1155] The server accesses databases and APIs provided by facility operators to collect information such as availability and congestion status of facilities that meet the user's criteria, as well as information on special services offered.

[1156] The server generates the optimal plan using an AI algorithm

[1157] The server combines the latest collected information with the facility's data and uses an AI algorithm to generate the optimal time-killing plan. The server also takes into account the user's emotional state and selects the plan that will most satisfy the user. For example, if the server detects that the user is under stress, it will select a plan that provides a relaxing environment.

[1158] The server sends the generated plan to the device.

[1159] The server converts the generated plan back into a data format such as JSON format and sends it to the terminal as an HTTP response.

[1160] The device displays the plan to the user.

[1161] The device analyzes the plan data received from the server and displays it in a user-friendly format, including the location of the best facility, the time frame, estimated costs within the budget, reviews and ratings, the occupancy status, and the reasons for the recommendation based on the emotion engine.

[1162] Specific examples

[1163] If a user inputs "I'd like to find a cafe for two in Tokyo starting at 3 PM, my budget is 2,000 yen, and I'd prefer it to be indoors," and the emotion engine recognizes the user's stress level, the server will generate a plan based on the latest information it has collected: "A 'Relaxation Cafe' in Shibuya, Tokyo is ideal for 3 PM, and the price is within my budget," and send it to the device. The device will then display this plan in detail to the user, adding, "Based on your current emotional state, we've recommended a relaxing cafe."

[1164] In this way, the system not only allows users to kill time, but also allows them to quickly and easily obtain a plan that best suits their emotional state.

[1165] The processing flow will be explained below.

[1166] Program processing steps

[1167] Step 1:

[1168] The user enters information about what they want to do on the device. They enter a specific location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., 2 people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor use (e.g., indoors) into input fields.

[1169] Step 2:

[1170] The device collects the input information and activates the emotion engine. The emotion engine analyzes the user's emotions based on the information the user inputs and the operation history of the interface. For example, if the user inputs a lot of characters in a short period of time, it will recognize that the user is under stress.

[1171] Step 3:

[1172] The emotion engine generates the results of its analysis as user condition data, which includes the user's psychological state, such as stress, relaxation, or excitement.

[1173] Step 4:

[1174] The device converts the user's input information and the condition data generated by the emotion engine into a data format such as JSON and sends it to the server.

[1175] Step 5:

[1176] The server parses (analyzes) the request data it receives and extracts the conditions entered by the user and the condition data based on the emotion engine.

[1177] Step 6:

[1178] The server uses the APIs of social media and news sites to collect the latest information about the location specified by the user. Specifically, it calls the news API to obtain the latest articles and news about the location, and uses the social media API to obtain recent posts and trending information related to the location.

[1179] Step 7:

[1180] The server accesses databases and APIs provided by facility operators to collect information such as availability, congestion, and special service availability at facilities that meet the user's criteria.

[1181] Step 8:

[1182] The server combines the latest information collected by the server with data from the facility and uses an AI algorithm to generate an optimal time-killing plan. This plan also takes into account the user's emotional state. For example, if the system detects that the user is under stress, it will select a plan that provides a relaxing environment.

[1183] Step 9:

[1184] The server converts the generated plan data into a data format such as JSON and sends it to the terminal as an HTTP response.

[1185] Step 10:

[1186] The device analyzes the plan data received from the server and displays it in a user-friendly format, including the location of the best facility, the time frame, the estimated cost within the budget, reviews and ratings, the occupancy status, and the reason for the recommendation based on the emotion engine.

[1187] Specific examples

[1188] Example input:

[1189] The user inputs, "I want to find a cafe for two in Tokyo from 3pm. My budget is 2000 yen, preferably indoors." The emotion engine also recognizes the user's stress level.

[1190] Example output:

[1191] Based on the latest information and facility data collected by the server, the AI ​​generates a plan suggesting that a "Relax Cafe" in Shibuya, Tokyo, is optimal for 3 PM and within budget, and sends it to the device. The device displays this plan in detail to the user, adding, "Based on your current emotional state, we have recommended a relaxing cafe."

[1192] Recommended Plan:

[1193] Location: Relax Cafe in Shibuya, Tokyo

[1194] Time: 15:00 - 16:00

[1195] Budget: Under 2000 yen

[1196] Customer Review: ★★★★☆

[1197] Availability: Currently empty

[1198] Reason for recommendation: Based on your current emotional state, we recommended a relaxing cafe.

[1199] In this way, the system not only allows users to kill time, but also allows them to easily obtain a plan that is optimal for their emotional state.

[1200] Example 2

[1201] 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."

[1202] Existing systems simply provide time-killing plans based on location, time, budget, and other criteria, without considering the user's current emotional state. This makes it difficult for users to quickly find an appropriate plan that truly relaxes them and reduces stress. Furthermore, these systems do not integrate the latest information from social media and news sites or the congestion status of facilities. This creates a need for systems that provide optimal time-killing plans tailored to the user's needs.

[1203] 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.

[1204] In this invention, the server includes input means for inputting information about things the user wants to do, emotion recognition means for recognizing the information and the user's emotional state, transmission means for transmitting the information and the emotional state to the server, collection means for acquiring the latest information from social networking services and news sites based on the information and the emotional state, generation means for generating an optimal time-killing plan based on the information, the emotional state, and the collected information, transmission means for transmitting the generated plan to the user, and display means for displaying the plan to the user. This makes it possible to quickly and easily provide an optimal time-killing plan based on the latest related information while taking into account the user's current emotional state.

[1205] "Input means" refers to an interface for inputting information about what the user wants to do into the terminal.

[1206] "Emotion recognition means" refers to a function for analyzing and recognizing a user's emotional state based on the user's input information and operation history using natural language processing and machine learning technology.

[1207] The "transmission means" refers to a function for transmitting the information input by the user and the emotional state recognized by the emotion recognition means to the server in data format.

[1208] "Collection means" refers to the function that allows the server to use the APIs of social networking services and news sites to collect the latest information based on the user's input information and emotional state.

[1209] The "generation means" refers to a function that integrates the latest information and facility data collected by the collection means, and generates an optimal time-killing plan using an AI algorithm, taking into consideration the user's emotional state.

[1210] "Display means" refers to a function for analyzing the optimal time-killing plan sent from the server, formatting it in a format that is easy for the user to view, and displaying it on the terminal.

[1211] The term "server" refers to a central processing unit that receives information and emotional states sent by users, collects related information, generates plans, and transmits the generated plans to terminals.

[1212] "Terminal" refers to a device through which a user inputs information, communicates with the server, and receives the generated plan. Specifically, this includes smartphones, PCs, etc.

[1213] This system allows users to input information about what they want to do and proposes optimal time-killing plans based on that information. Furthermore, by combining it with an emotion engine, it can analyze the user's emotional state and provide optimal plans based on that state.

[1214] The user enters information

[1215] Users use devices such as smartphones or computers to input information about what they want to do, including location, time, number of people, genre, budget, and preference for indoor or outdoor activities.

[1216] Emotion engine recognizes user emotions

[1217] The device activates an emotion engine based on the user's input information and the application's operation history. The emotion engine uses natural language processing and machine learning technologies (such as Python's NLP library or TensorFlow) to analyze the user's psychological state. The analysis results are expressed as a condition, such as "stressed," "relaxed," or "excited."

[1218] The device sends the information to the server

[1219] The device sends the information entered by the user and the emotional state recognized by the emotion engine to the server. The data is sent in a general data format such as JSON (e.g., "{"Location": "Tokyo", "Time": "15:00", "Number of people": "2", "Genre": "Cafe", "Budget": "2000 yen", "Indoor": "Preferred", "Emotional state": "Stressed"}").

[1220] The server collects the latest information from social media and news sites.

[1221] Based on the user's input information and emotional state, the server collects the latest related information using APIs of social media and news sites (e.g., Twitter API, News API, etc.), thereby obtaining recent posts, trending information, the latest articles, and news related to the location.

[1222] The server collects the latest data from the facility.

[1223] The server accesses databases and APIs provided by facility operators to collect information on facility availability and special service availability that matches the user's criteria. For example, this includes information on facility seat availability and whether or not special services are available.

[1224] The server generates the optimal plan using an AI algorithm

[1225] The server combines the collected latest information with the facility's data and uses a generative AI model (e.g., trend prediction model or recommendation model) to generate an optimal time-killing plan. The server also takes into account the user's emotional state and selects a plan that will most satisfy the user. For example, if the server detects that the user is under stress, it selects a plan that provides a relaxing environment.

[1226] The server sends the generated plan to the device.

[1227] The server converts the generated plan back into a data format such as JSON format and sends it to the terminal as an HTTP response.

[1228] The device displays the plan to the user.

[1229] The device analyzes the plan data received from the server and displays it in a user-friendly format, including the location of the best facility, the time frame, estimated costs within the budget, reviews and ratings, the occupancy status, and the reasons for the recommendation based on an emotion engine.

[1230] Specific examples

[1231] For example, if a user inputs "I'd like to find a cafe for two in Tokyo starting at 3 PM, with a budget of 2,000 yen and preferably indoors," and the emotion engine recognizes the user's stress level, the server will generate a plan based on the latest information it has collected: "A 'Relaxation Cafe' in Shibuya, Tokyo is ideal for 3 PM, and the price is within budget," and send it to the device. The device will then display this plan in detail to the user, adding a note that "Based on your current emotional state, we have recommended a relaxing cafe."

[1232] In this way, the system not only allows users to kill time, but also allows them to quickly and easily obtain a plan that best suits their emotional state.

[1233] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1234] Step 1:

[1235] Users input information about what they want to do into the device. Specifically, they input the location, time, number of people, genre, budget, and preference for indoor or outdoor activities on the screen of their smartphone or computer, and then press the send button.

[1236] Input: User's own input: "Location: Tokyo", "Time: 15:00", "Number of people: 2", "Genre: Cafe", "Budget: 2000 yen", "Indoor: Preferred"

[1237] Output: The input information is passed to the next emotion recognition means.

[1238] Step 2:

[1239] The emotion engine recognizes the user's emotions. The device activates the emotion engine based on the information just entered and the app's operation history. The emotion engine uses natural language processing and machine learning technologies to analyze the user's psychological state.

[1240] Input: User input information and operation history

[1241] Data processing method: Analyze the input data using a natural language processing library (e.g., spaCy or NLTK) and apply a sentiment classification algorithm (e.g., SVM, Random Forest).

[1242] Output: The recognition result is "Emotional state: Stressed".

[1243] Step 3:

[1244] The device sends the input information and the perceived emotional state to the server, where the data is packaged in JSON format and sent as an HTTP POST request.

[1245] Input: Input information and emotional state

[1246] Data Calculation: Converting data to JSON format and creating HTTP requests

[1247] Output: An HTTP POST request is made to the server, sending the entire data.

[1248] Step 4:

[1249] The server collects the latest information from social media and news sites. Based on the information received, the server calls social media APIs (e.g., Twitter API) and news APIs (e.g., NewsAPI) to retrieve the latest related articles and trending information.

[1250] Input: User input and emotional state

[1251] Data calculation: Sending a query to the API (e.g. "Tokyo Cafe Latest News") and analyzing the received response

[1252] Output: A dataset of the latest articles and social media posts.

[1253] Step 5:

[1254] The server collects the latest data from the facility, accesses the facility operator's database and API, and obtains information about availability and special services that match the user's criteria.

[1255] Input: User's condition and emotional state

[1256] Data Calculation: Sending API queries and parsing response data

[1257] Output: A dataset of facility availability and special offers.

[1258] Step 6:

[1259] The server generates the optimal plan using an AI algorithm, integrating the collected data sets and using a generative AI model to create the optimal plan.

[1260] Input: Latest articles, social media posting data, facility availability information, special service information

[1261] Data Computing: Data integration and application of AI algorithms (e.g., multi-label classifiers and recommendation systems)

[1262] Output: The optimal time-killing plan to be provided to the user is generated.

[1263] Step 7:

[1264] The server sends the generated plan to the terminal. The generated plan is converted to JSON format and sent to the terminal as an HTTP response.

[1265] Input: Generated optimal time-killing plan

[1266] Data operations: converting to JSON format and creating an HTTP response

[1267] Output: An HTTP response is generated and sent to the device.

[1268] Step 8:

[1269] The terminal displays the plan to the user. It analyzes the plan data received from the server, formats it in a format that is easy for the user to view, and displays it.

[1270] Input: Plan data in JSON format

[1271] Data computation: Data analysis and visualization (e.g., display using front-end libraries)

[1272] Output: The user is shown "Relax Cafe" with a message saying "Based on your current emotional state, we have recommended a cafe where you can relax."

[1273] (Application example 2)

[1274] 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."

[1275] While conventional systems have the ability to provide optimal plans based on the user's preferences and desired conditions, they lack the ability to take into account the user's emotional state. This poses a challenge: they are unable to quickly provide plans that meet the user's psychological needs, especially when they are stressed or want to relax. Furthermore, there are limitations to the suggestions they can make for specific genres of activities or services (e.g., food delivery), making it difficult to fully satisfy the diverse needs of users.

[1276] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1277] In this invention, the server includes input means for inputting information about what the user wants to do, transmission means for transmitting the information and the user's emotional state to the server, collection means for collecting related information based on the information and the emotional state, generation means for generating an optimal delivery plan based on the collected information and the user's state, transmission means for transmitting the generated plan to the user, and display means for displaying the plan to the user. This makes it possible to propose an optimal delivery plan that takes the user's psychological state into consideration.

[1278] "Input means" refers to a device or interface for inputting information about what the user wants to do.

[1279] "Transmitting means" refers to the devices and protocols used to transmit input information and the user's emotional state to the server.

[1280] The "collection means" refers to devices or software that allow the server to collect relevant information based on input information and emotional state.

[1281] The "generation means" refers to a device or algorithm that generates an optimal delivery plan based on the collected information and the user's status.

[1282] The "display means" is a device or interface for presenting the generated plan to the user.

[1283] A "social networking service" is a service or platform that allows users to interact with each other over the Internet.

[1284] "News delivery methods" are systems and services that provide the latest news and information.

[1285] A "food delivery service" is a service that allows you to order food and drinks and have them delivered to a specified location.

[1286] "Mental state" refers to the user's subjective feelings and mental condition.

[1287] The present invention relates to a system for proposing an optimal delivery plan in consideration of the emotional state of a user. A detailed embodiment for realizing this system will be described below.

[1288] Main components and technologies used

[1289] 1. Input Method

[1290] It is a device or interface for users to input information about what they want to do. For example, a smartphone app falls into this category, and is implemented as a cross-platform application using React Native.

[1291] 2. Transmission Method

[1292] It is a device and protocol for transmitting input information and the user's emotional state to a server. It mainly uses the HTTP protocol, and data is transmitted in JSON format.

[1293] 3. Collection Method

[1294] This is a device or software that allows the server to collect relevant information based on input information and emotional state. The Axios library is used to collect data, and the latest information is obtained from social networking service (SNS) APIs and news sources.

[1295] 4. Generation means

[1296] These are devices and algorithms that generate optimal delivery plans based on collected information and the user's status. A generative AI model using TensorFlow is used as a powerful tool.

[1297] 5. Display means

[1298] This is the device or interface for presenting the generated plan to the user. React Native UI components are used to display it within the application.

[1299] System Operation Overview

[1300] The server generates an optimal delivery plan through the following steps and provides it to the user.

[1301] 1. Enter your user information

[1302] Users input desired meal information (e.g., type of food, budget, number of people, time) through a smartphone app. The emotion engine also analyzes the user's psychological state, for example, if the user is under stress.

[1303] 2. Data transmission

[1304] The entered information and the user's emotional state are formatted and sent to the server in JSON format.

[1305] 3. Data Collection

[1306] The server collects the latest relevant information using the APIs of related food delivery services (e.g., UberEats API and DoorDash API) and social media APIs (e.g., Twitter API).

[1307] 4. Generating the optimal plan

[1308] The AI ​​algorithm uses the collected data to generate an optimal meal plan that takes into account the user's emotional state and preferences, using a deep learning model powered by TensorFlow.

[1309] 5. Submitting and Viewing Plans

[1310] The generated plan is converted back to JSON format and sent to the smartphone app, which displays the plan in an easy-to-understand format to the user, along with the reasons for the proposal.

[1311] Specific examples

[1312] For example, if a user enters "Chinese food," "under 2,000 yen," "for two people," "7 p.m." and "looking to relieve stress" into a smartphone app, the emotion engine will check the user's stress level from their operation history. The app will collect the latest related information and suggest "We recommend the Chinese restaurant 'Relax Garden.'" Furthermore, the app will display relaxing music and menu recommendations.

[1313] Prompt Sentence Examples

[1314] "Enter the user's emotional state and preferences, and generate a meal plan based on the latest food delivery information. The plan should also emphasize relaxation."

[1315] This system makes it possible to propose delivery plans that optimally take into account the user's psychological state.

[1316] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1317] Step 1:

[1318] Users use a smartphone app to input information about the meal they want (e.g., type of meal, budget, number of people, time) and their current emotional state (e.g., desire to relieve stress).

[1319] Input: genre, budget, number of people, time, emotional state

[1320] Output: User information (JSON format)

[1321] Specific behavior: The user enters information in an interface developed using React Native and presses the "Submit" button.

[1322] Step 2:

[1323] The device formats the input user information and emotional state into JSON format and sends it to the server using the HTTP protocol.

[1324] Input: User information (JSON format)

[1325] Output: HTTP request sent to the server

[1326] Specific operation: In the React Native application, an HTTP POST request is created using the Axios library and sent to the server.

[1327] Step 3:

[1328] The server analyzes the received user information and emotional state and collects related information. Here, it calls the API of social media sites and food delivery services to obtain related data.

[1329] Input: User information (JSON format), emotional state

[1330] Output: Relevant information collected

[1331] Specific operation: A server implemented using Node.js and Express.js calls the Twitter API and Uber Eats API using the Axios library to collect data.

[1332] Step 4:

[1333] The server generates an optimal delivery plan based on the collected information and the user's emotional state using a generative AI model powered by TensorFlow.

[1334] Input: Collected relevant information, emotional state

[1335] Output: Optimal delivery plan

[1336] Specific operation: The collected data is input into a TensorFlow deep learning model to generate an optimal plan.

[1337] Step 5:

[1338] The server formats the generated delivery plan again into JSON format and sends it to the terminal as an HTTP response.

[1339] Input: Optimal delivery plan (JSON format)

[1340] Output: Plan sent as HTTP response

[1341] Specific operation: The generated plan is converted to JSON and sent as an HTTP response using Express.js in Node.js.

[1342] Step 6:

[1343] The device analyzes the received delivery plan and displays it in a format that is easy for the user to view. The app also displays the reason for the proposal and additional information that may have a relaxing effect (e.g., relaxing music).

[1344] Input: Optimal delivery plan (JSON format)

[1345] Output: The delivery plan displayed to the user

[1346] What it does: Uses React Native to display the best delivery plan on the screen, along with additional information.

[1347] This processing step allows for the proposal of an optimal delivery plan that takes into account the user's psychological state.

[1348] 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.

[1349] 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.

[1350] 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.

[1351] [Fourth embodiment]

[1352] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1353] 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.

[1354] 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).

[1355] 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.

[1356] 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.

[1357] 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).

[1358] 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.

[1359] 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.

[1360] 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.

[1361] 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.

[1362] 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.

[1363] 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.

[1364] 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."

[1365] The present invention is a system that, when a user inputs information about what they want to do, proposes an optimal time-killing plan based on that information. Specific embodiments of the system will be described in detail below.

[1366] The user enters information

[1367] The user uses a device (e.g., a smartphone or PC) to input information about what they want to do. This information includes location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., two people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor activities (e.g., indoors).

[1368] The device sends the information to the server

[1369] The terminal sends the information entered by the user to the server. This information consists of multiple fields and is sent in a generic data format such as JSON.

[1370] The server collects the latest information from social media and news sites.

[1371] The server collects the latest relevant information from the Internet based on the user's input. Specifically, it uses the APIs of social networking services and news sites to obtain the latest news, current weather, crowding status, event information, and other information for the relevant location.

[1372] The server collects the latest data from the facility.

[1373] The server also collects data provided by the facility operator, including facility availability, special service offers, price ranges, etc.

[1374] The server generates the optimal plan using an AI algorithm

[1375] The server uses an AI algorithm to generate the optimal time-killing plan based on the latest relevant information collected and the user's input criteria. The AI ​​selects the plan that best suits the user's preferences, taking into account factors such as traffic congestion, budget, and current weather.

[1376] The server sends the generated plan to the device.

[1377] The server sends the generated plan to the device in JSON format, etc. The plan includes detailed information such as specific locations, time frames, estimated costs within the budget, reference reviews and ratings, and congestion status.

[1378] The device displays the plan to the user.

[1379] The terminal will display the plan in a user-friendly format, for example:

[1380] Recommended Plan:

[1381] Location: Cafe A, Shibuya, Tokyo

[1382] Time: 15:00 - 16:00

[1383] Budget: Under 2000 yen

[1384] Customer Review: ★★★★☆

[1385] Availability: Currently empty

[1386] This allows users to easily find the best time-killing plan in real time.

[1387] Specific examples

[1388] If a user inputs "I want to find a cafe for two in Tokyo starting at 3 PM, my budget is 2000 yen, and I prefer indoor dining," the server will generate a plan based on the latest information it has collected: "Cafe A in Shibuya, Tokyo is the best choice at 3 PM, and the price is within my budget," and send it to the device. The device will then display this plan in detail to the user.

[1389] In this way, this system allows users to efficiently choose ways to kill time even when they suddenly have free time, and spend it meaningfully.

[1390] The processing flow will be explained below.

[1391] Program processing steps

[1392] Step 1:

[1393] The user enters information about what they want to do on the device. They enter a specific location, time, number of people, genre, budget, and preference for indoor / outdoor use into input fields.

[1394] Step 2:

[1395] The terminal converts the input information into a data format such as JSON and sends it to the server as an HTTP POST request.

[1396] Step 3:

[1397] The server parses the received request data and extracts the information entered by the user, including location, time, number of people, genre, budget, and preference for indoor / outdoor.

[1398] Step 4:

[1399] The server uses the APIs of social media and news sites to collect the latest information about the location specified by the user. Specifically, it calls the news API to retrieve the latest articles and news about the location. It also uses the social media API to retrieve recent posts and trending information about the location.

[1400] Step 5:

[1401] The server accesses databases and APIs provided by facility operators to collect information such as availability and congestion status of facilities that meet the user's criteria, as well as information on special services offered.

[1402] Step 6:

[1403] The server combines the latest information collected with the facility's own data and prepares it for passing to the AI ​​algorithm. This combined data includes news, social media trends, facility availability, congestion status, price range, and more.

[1404] Step 7:

[1405] The server runs an AI algorithm, comparing the integrated data with the user's requirements to generate the optimal time-killing plan. The AI ​​analyzes the collected information and selects the plan that best suits the user's needs, taking into account factors such as weather, congestion, and budget.

[1406] Step 8:

[1407] The server converts the generated plan back into a data format such as JSON and sends it to the terminal as an HTTP response.

[1408] Step 9:

[1409] The device analyzes the plan data received from the server and displays it in a format that is easy for the user to view, including the location of the best facility, the time frame, cost estimates within the budget, reviews and ratings, and congestion status.

[1410] These detailed processing steps allow the user to easily input information about what they want to do and quickly obtain the best time-killing plan based on that information.

[1411] Example 1

[1412] 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."

[1413] Conventional systems have had the problem of making it difficult for users to find the best time-killing plan when they suddenly have some free time. In particular, they lacked the means to collect the latest information and, based on that information, propose a plan that met the user's conditions and preferences. Furthermore, since they were unable to plan based on the facility's congestion status or real-time information, it was difficult for users to spend their time efficiently.

[1414] 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.

[1415] In this invention, the server includes input means for inputting information about what the user wants to do, transmission means for transmitting the information to the server, collection means for collecting the latest related information from social networking services and news sites based on the information, collection means for collecting data provided by facilities, generation means for generating an optimal time-killing plan using an AI algorithm based on the collected information and the user's conditions, transmission means for transmitting the generated plan to the user, and display means for displaying the plan to the user. This allows the user to obtain an optimal time-killing plan based on the latest information in real time, allowing them to spend their time efficiently even when they have sudden free time.

[1416] A "user" is an individual or group who uses the system to input information about what they want to do and receives suggestions for ways to kill time.

[1417] "Server" refers to a computer system that receives information sent by users, collects and processes various data, and sends the generated plan to terminals.

[1418] "Input means" refers to a software or hardware mechanism for inputting information about what a user wants to do via a terminal.

[1419] The "transmission means" is a communication function for transmitting information input by the user to the server.

[1420] "Collection means" is a function that allows the server to obtain the latest relevant information from various information sources on the Internet.

[1421] The "generation means" is a function that uses an AI algorithm to generate the optimal time-killing plan based on the collected information and the user's conditions.

[1422] The "display means" is a software or hardware mechanism for displaying the generated plan on a terminal in a format that is easy for the user to understand.

[1423] "Social networking services" refers to online platforms such as Twitter and Facebook, which allow users to post and share information.

[1424] "News site" refers to a website that contains current news articles and information.

[1425] "Facility-provided data" refers to information such as availability, special services, and price ranges that facility operators make public via APIs, etc.

[1426] An "AI algorithm" is a machine learning technology or data processing method that analyzes multiple collected data and generates an optimal plan based on user input conditions.

[1427] A "time-killing plan" is a specific activity suggestion provided to help users spend their free time effectively.

[1428] The present invention is a system that, when a user inputs information about what they want to do, proposes an optimal time-killing plan based on that information. Specific embodiments of the system will be described in detail below.

[1429] The user enters information

[1430] Users use devices such as smartphones or computers to enter information about what they want to do into a dedicated input form. Information to be entered includes location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., 2 people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor or outdoor activities (e.g., indoors). Specifically, users enter information into the fields on the screen and click the "Submit" button.

[1431] The device sends the information to the server

[1432] The device sends the data entered by the user to the server in a data format such as JSON. An HTTP POST request is used for sending the data. For example, the data may contain information such as "{ "Location": "Tokyo", "Time": "15:00", "Number of people": 2, "Genre": "Cafe", "Budget": 2000, "Indoor / Outdoor": "Indoor"}".

[1433] The server collects information from social media and news sites.

[1434] The server uses the received data to collect the latest information from social media and news sites. Specifically, it uses the APIs of social media sites such as Twitter and Facebook to obtain the latest information on the relevant area. It also uses RSS feeds and APIs from news sites to collect data such as current weather, event information, and crowding levels.

[1435] The server collects facility-provided data

[1436] The server uses the facility's API to obtain information about the facility's availability, special services, price range, etc. This allows the server to take into account the facility's status, which is updated in real time.

[1437] The server generates the optimal plan using an AI algorithm

[1438] The server provides the latest collected data and user input information to an AI algorithm, which then comprehensively evaluates the user's desired conditions (e.g., congestion, budget, weather) and generates the optimal time-killing plan. Using a machine learning model, the algorithm recommends a plan that takes congestion and weather into account.

[1439] The server sends the generated plan to the device.

[1440] The server then sends the generated plan to the device in JSON format. The plan includes details such as the specific location, time frame, estimated costs within the budget, reviews and ratings for reference, and congestion status. The plan is typically sent as an HTTP response.

[1441] The device displays the plan to the user.

[1442] The device will then display the received plan in a user-friendly format, for example:

[1443] Location: Cafe A, Shibuya, Tokyo

[1444] Time: 15:00 - 16:00

[1445] Budget: Under 2000 yen

[1446] Customer Review: ★★★★☆

[1447] Availability: Currently empty

[1448] This allows the user to obtain the best time-killing plan in real time.

[1449] Specific examples

[1450] For example, if a user inputs "I want to find a cafe for two in Tokyo starting at 3 PM, my budget is 2,000 yen, and I prefer it to be indoors," the device will send that information in JSON format to the server. The server will then generate the optimal plan based on data from social media, news sites, and facilities. The server will generate a plan such as "Cafe A in Shibuya, Tokyo is the best place for 3 PM, and the price is within my budget," and send it to the device. The device will then display this information in detail to the user, allowing them to find the optimal plan for killing time.

[1451] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1452] Step 1: User Enters Information

[1453] The user uses a device (smartphone or PC) to input information about what they want to do. The input items are location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., 2 people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor use (e.g., indoors). Once the input is complete, the user clicks the "Submit" button.

[1454] Input: User's desired conditions (location, time, number of people, genre, budget, indoor / outdoor)

[1455] Output: The input information is saved in a data field in the terminal.

[1456] Step 2: The device sends the information to the server

[1457] The device encodes the information entered by the user into JSON format and sends it to the server using an HTTP POST request. At this time, the information field contains data such as "{ "Location": "Tokyo", "Time": "15:00", "Number of people": 2, "Genre": "Cafe", "Budget": 2000, "Indoor / Outdoor": "Indoor"}".

[1458] Input: Information entered by the user

[1459] Output: JSON format data sent to the server

[1460] Step 3: The server collects information from social media and news sites.

[1461] The server uses the APIs of social media and news sites to collect relevant information based on the received user information. Based on the specified location and time, the server retrieves the latest local news, event information, and weather information from the APIs of Twitter and Facebook.

[1462] Input: User information in JSON format

[1463] Output: Latest information collected from social media and news sites (e.g., latest local news, weather, event information)

[1464] Step 4: Server collects facility-provided data

[1465] The server uses the API provided by the facility operator to collect information such as facility availability, special services, price range, etc. This allows the server to obtain real-time data about a specific facility.

[1466] Input: Facility-related request parameters (e.g., location, genre, budget)

[1467] Output: Collected facility-provided data (availability, special services, price range)

[1468] Step 5: The server analyzes the data using AI algorithms and generates an optimal plan

[1469] The server then supplies the collected data from social media, news sites, and facilities to an AI algorithm for analysis. This AI algorithm then comprehensively evaluates the user's desired conditions and generates the optimal time-killing plan. For example, it may recommend the best facility within a user's budget, taking into account crowding and weather conditions.

[1470] Input: User information, SNS information, news site information, facility data

[1471] Output: The best time-killing plan

[1472] Step 6: The server sends the generated plan to the device

[1473] The server then encodes the generated itinerary into JSON format and sends it to the device using an HTTP response, which includes data such as location, time frame, estimated cost within budget, user ratings, and occupancy status.

[1474] Input: The best time-killing plan

[1475] Output: Plan data in JSON format sent to the device

[1476] Step 7: The device displays the plan to the user

[1477] The device displays the received plan in an easy-to-read format for the user. For example, details such as "Cafe A in Shibuya, Tokyo, from 3:00 PM to 4:00 PM, budget within 2,000 yen, customer rating ★★★★☆, currently available" are displayed.

[1478] Input: Plan data sent from the server

[1479] Output: A specific time-killing plan displayed to the user

[1480] (Application example 1)

[1481] 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."

[1482] In modern society, there is a demand for systems that allow users to make effective use of their limited free time. However, existing systems have limited functionality in providing optimal time-killing plans based on a user's specific conditions or current location. In particular, when it comes to food delivery, there has been a lack of systems that can instantly respond to changing conditions such as a user's location, budget, and waiting time. This has made it difficult for users to find the optimal delivery plan.

[1483] 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.

[1484] In this invention, the server includes input means for inputting information about what the user wants to do, transmission means for transmitting the information to the server, collection means for collecting the latest related information based on the information, generation means for generating an optimal plan based on the collected information and the user's conditions, transmission means for transmitting the generated plan to the user, display means for displaying the plan to the user, and means for inputting the user's location information, food genre, budget, and waiting time and proposing an optimal delivery plan, thereby enabling the user to quickly find the optimal food delivery plan that meets their conditions.

[1485] "User information" refers to information about what the user wants to do, including location information, cuisine genre, budget, waiting time, etc.

[1486] "Input means" refers to a means for inputting information about what the user wants to do into the terminal.

[1487] The "transmission means" is a means for transmitting information input by the user to the server.

[1488] The "collection means" is a means for collecting the latest related information based on the information entered by the user.

[1489] The "generation means" is a means for generating an optimal plan based on the collected information and the user's conditions.

[1490] The "display means" is a means for displaying the generated plan to the user.

[1491] The "Food Delivery Plan" is a plan that suggests the most suitable restaurant and menu based on the user's location, cuisine type, budget, waiting time, and other conditions.

[1492] A "delivery service" is a service that delivers food to a location specified by the user.

[1493] "Related information" refers to the latest information obtained from social networking services, news sites, review platforms, etc.

[1494] "Crowding status" is information that indicates how crowded a particular facility or service is currently.

[1495] This invention is a system that allows users to effectively utilize their limited free time, and proposes plans that are particularly specialized for food delivery. A specific embodiment of this system will be described in detail below.

[1496] System Overview

[1497] Using a device such as a smartphone, a user inputs information about what they want to do, such as their current location, desired cuisine genre, budget, maximum waiting time, etc. This information is sent from the device to the server.

[1498] Hardware and software used

[1499] Hardware: Smartphone (iOS / Android)

[1500] Software: Python 3.8+, requests library, generative AI model (e.g., profile-based recommendation engine)

[1501] Data processing and calculation flow

[1502] 1. Data Entry

[1503] The user uses the terminal to input necessary information (for example, current location, cuisine genre, budget, waiting time, etc.).

[1504] These data are transmitted from the terminal to the server.

[1505] 2. Data Collection

[1506] The server collects relevant information from multiple data sources, including social networking services (SNS), news sites, and review platforms.

[1507] The collected data is structured in a general-purpose data format such as JSON.

[1508] 3. Generated by AI algorithms

[1509] The server generates an optimal food delivery plan based on the collected data and the user's requirements using a generative AI model, such as one that uses deep learning or machine learning techniques.

[1510] This process takes into account the user's location, cuisine, budget, wait time limit, and review ratings.

[1511] 4. Submitting and Viewing Plans

[1512] The server sends the generated optimal plan to the device in JSON format.

[1513] The device then displays the received plan to the user, showing the best restaurant, estimated time, menu items within the budget, and ratings of recommended menu items.

[1514] Specific examples

[1515] For example, if the user enters the following criteria:

[1516] Current location: Tokyo

[1517] Cuisines: Pizza

[1518] Budget: 1,500 yen

[1519] Maximum waiting time: 30 minutes

[1520] Based on this, the server gathers relevant information and generates a plan like this:

[1521] Restaurant: "Pizza House Tokyo"

[1522] Menu: Margherita pizza

[1523] Price: 1,400 yen

[1524] Estimated wait time: 25 minutes

[1525] Review rating: ★★★★☆

[1526] Prompt Sentence Examples

[1527] "Generate the best food delivery plan that matches the user's criteria. The criteria are as follows:

[1528] Current location: Tokyo

[1529] Cuisines: Pizza

[1530] Budget: 1,500 yen

[1531] Maximum waiting time: 30 minutes

[1532] The AI ​​model takes into account the latest restaurant information and reviews to provide the best plan.”

[1533] In this way, the system allows users to quickly and easily find the best food delivery plan that meets their requirements.

[1534] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1535] Step 1:

[1536] The user uses a device such as a smartphone to input information such as their current location, desired cuisine type, budget, and maximum waiting time. At this stage, the user inputs the conditions related to what they want into the device, and these conditions are saved in a general-purpose format such as JSON.

[1537] input:

[1538] current location

[1539] Desired cuisine genre

[1540] budget

[1541] Waiting time limit

[1542] output:

[1543] Input data in JSON format

[1544] Specific behavior:

[1545] The user enters the required information into the input form and presses the submit button.

[1546] Step 2:

[1547] The device sends the information entered by the user to the server. At this stage, the device sends the JSON formatted input data that it saved earlier to the server using an HTTP request.

[1548] input:

[1549] User-supplied data in JSON format

[1550] output:

[1551] HTTP request to the server

[1552] Specific behavior:

[1553] Use a library to generate and send HTTP requests (e.g. requests).

[1554] Step 3:

[1555] The server collects relevant information based on the conditions entered by the user from multiple data sources, such as social media, news sites, and review platforms. The collected data is saved in a unified format (e.g., JSON format).

[1556] input:

[1557] Filtering information based on user conditions

[1558] output:

[1559] Data collected from social networking services, news sites, and review platforms

[1560] Specific behavior:

[1561] Collect information by calling multiple APIs (e.g., social media API, review API).

[1562] Step 4:

[1563] The server generates the optimal food delivery plan based on the collected information and the user's requirements using a generative AI model. The generative AI model implements a recommendation algorithm using deep learning and machine learning techniques to calculate the plan that best matches the user's requirements.

[1564] input:

[1565] Data collected

[1566] User Conditions

[1567] output:

[1568] Data on the best food delivery plans

[1569] Specific behavior:

[1570] Input data into an AI model (e.g., a recommendation engine) to generate a plan.

[1571] Step 5:

[1572] The server sends the generated optimal food delivery plan to the device. The plan is sent in a general format such as JSON.

[1573] input:

[1574] Data on the best food delivery plans

[1575] output:

[1576] HTTP response to the device

[1577] Specific behavior:

[1578] Use a library (e.g. a web framework such as Flask) to generate and send HTTP responses.

[1579] Step 6:

[1580] The device then displays the received food delivery plan to the user, showing the best restaurant, estimated time, menu items within the budget, and ratings of recommended menu items.

[1581] input:

[1582] Food delivery plan sent from the server

[1583] output:

[1584] Display data for users

[1585] Specific behavior:

[1586] Visually display data using presentational UI components (e.g. HTML, CSS, JavaScript).

[1587] This allows users to quickly and easily find the best food delivery plan that meets their requirements.

[1588] 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.

[1589] This system allows users to input information about what they want to do and proposes optimal time-killing plans based on that information. Furthermore, by combining it with an emotion engine, it can analyze the user's emotional state and provide optimal plans based on that state.

[1590] The user enters information

[1591] The user uses a device (e.g., a smartphone or PC) to input information about what they want to do. This information includes location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., two people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor activities (e.g., indoors).

[1592] Emotion engine recognizes user emotions

[1593] The device activates an emotion engine that recognizes the user's emotions based on the user's input information and interface operation history. The emotion engine uses natural language processing and machine learning techniques to analyze the user's psychological state. The results of this analysis are expressed as the user's condition (for example, stressed, relaxed, excited, etc.).

[1594] The device sends the information to the server

[1595] The device sends the information entered by the user and the emotional state recognized by the emotion engine to the server in a general-purpose data format such as JSON.

[1596] The server collects the latest information from social media and news sites.

[1597] The server uses the APIs of social media and news sites to collect the latest relevant information based on the user's input information and emotional state. Specifically, it calls the news API to retrieve the latest articles and news about the location. It also uses the social media API to retrieve recent posts and trending information about the location.

[1598] The server collects the latest data from the facility.

[1599] The server accesses databases and APIs provided by facility operators to collect information such as availability and congestion status of facilities that meet the user's criteria, as well as information on special services offered.

[1600] The server generates the optimal plan using an AI algorithm

[1601] The server combines the latest collected information with the facility's data and uses an AI algorithm to generate the optimal time-killing plan. The server also takes into account the user's emotional state and selects the plan that will most satisfy the user. For example, if the server detects that the user is under stress, it will select a plan that provides a relaxing environment.

[1602] The server sends the generated plan to the device.

[1603] The server converts the generated plan back into a data format such as JSON format and sends it to the terminal as an HTTP response.

[1604] The device displays the plan to the user.

[1605] The device analyzes the plan data received from the server and displays it in a user-friendly format, including the location of the best facility, the time frame, estimated costs within the budget, reviews and ratings, the occupancy status, and the reasons for the recommendation based on the emotion engine.

[1606] Specific examples

[1607] If a user inputs "I'd like to find a cafe for two in Tokyo starting at 3 PM, my budget is 2,000 yen, and I'd prefer it to be indoors," and the emotion engine recognizes the user's stress level, the server will generate a plan based on the latest information it has collected: "A 'Relaxation Cafe' in Shibuya, Tokyo is ideal for 3 PM, and the price is within my budget," and send it to the device. The device will then display this plan in detail to the user, adding, "Based on your current emotional state, we've recommended a relaxing cafe."

[1608] In this way, the system not only allows users to kill time, but also allows them to quickly and easily obtain a plan that best suits their emotional state.

[1609] The processing flow will be explained below.

[1610] Program processing steps

[1611] Step 1:

[1612] The user enters information about what they want to do on the device. They enter a specific location (e.g., Tokyo), time (e.g., 3:00 PM), number of people (e.g., 2 people), genre (e.g., cafe), budget (e.g., 2,000 yen), and preference for indoor / outdoor use (e.g., indoors) into input fields.

[1613] Step 2:

[1614] The device collects the input information and activates the emotion engine. The emotion engine analyzes the user's emotions based on the information the user inputs and the operation history of the interface. For example, if the user inputs a lot of characters in a short period of time, it will recognize that the user is under stress.

[1615] Step 3:

[1616] The emotion engine generates the results of its analysis as user condition data, which includes the user's psychological state, such as stress, relaxation, or excitement.

[1617] Step 4:

[1618] The device converts the user's input information and the condition data generated by the emotion engine into a data format such as JSON and sends it to the server.

[1619] Step 5:

[1620] The server parses (analyzes) the request data it receives and extracts the conditions entered by the user and the condition data based on the emotion engine.

[1621] Step 6:

[1622] The server uses the APIs of social media and news sites to collect the latest information about the location specified by the user. Specifically, it calls the news API to obtain the latest articles and news about the location, and uses the social media API to obtain recent posts and trending information related to the location.

[1623] Step 7:

[1624] The server accesses databases and APIs provided by facility operators to collect information such as availability, congestion, and special service availability at facilities that meet the user's criteria.

[1625] Step 8:

[1626] The server combines the latest information collected by the server with data from the facility and uses an AI algorithm to generate an optimal time-killing plan. This plan also takes into account the user's emotional state. For example, if the system detects that the user is under stress, it will select a plan that provides a relaxing environment.

[1627] Step 9:

[1628] The server converts the generated plan data into a data format such as JSON and sends it to the terminal as an HTTP response.

[1629] Step 10:

[1630] The device analyzes the plan data received from the server and displays it in a user-friendly format, including the location of the best facility, the time frame, the estimated cost within the budget, reviews and ratings, the occupancy status, and the reason for the recommendation based on the emotion engine.

[1631] Specific examples

[1632] Example input:

[1633] The user inputs, "I want to find a cafe for two in Tokyo from 3pm. My budget is 2000 yen, preferably indoors." The emotion engine also recognizes the user's stress level.

[1634] Example output:

[1635] Based on the latest information and facility data collected by the server, the AI ​​generates a plan suggesting that a "Relax Cafe" in Shibuya, Tokyo, is optimal for 3 PM and within budget, and sends it to the device. The device displays this plan in detail to the user, adding, "Based on your current emotional state, we have recommended a relaxing cafe."

[1636] Recommended Plan:

[1637] Location: Relax Cafe in Shibuya, Tokyo

[1638] Time: 15:00 - 16:00

[1639] Budget: Under 2000 yen

[1640] Customer Review: ★★★★☆

[1641] Availability: Currently empty

[1642] Reason for recommendation: Based on your current emotional state, we recommended a relaxing cafe.

[1643] In this way, the system not only allows users to kill time, but also allows them to easily obtain a plan that is optimal for their emotional state.

[1644] Example 2

[1645] 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."

[1646] Existing systems simply provide time-killing plans based on location, time, budget, and other criteria, without considering the user's current emotional state. This makes it difficult for users to quickly find an appropriate plan that truly relaxes them and reduces stress. Furthermore, these systems do not integrate the latest information from social media and news sites or the congestion status of facilities. This creates a need for systems that provide optimal time-killing plans tailored to the user's needs.

[1647] 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.

[1648] In this invention, the server includes input means for inputting information about things the user wants to do, emotion recognition means for recognizing the information and the user's emotional state, transmission means for transmitting the information and the emotional state to the server, collection means for acquiring the latest information from social networking services and news sites based on the information and the emotional state, generation means for generating an optimal time-killing plan based on the information, the emotional state, and the collected information, transmission means for transmitting the generated plan to the user, and display means for displaying the plan to the user. This makes it possible to quickly and easily provide an optimal time-killing plan based on the latest related information while taking into account the user's current emotional state.

[1649] "Input means" refers to an interface for inputting information about what the user wants to do into the terminal.

[1650] "Emotion recognition means" refers to a function for analyzing and recognizing a user's emotional state based on the user's input information and operation history using natural language processing and machine learning technology.

[1651] The "transmission means" refers to a function for transmitting the information input by the user and the emotional state recognized by the emotion recognition means to the server in data format.

[1652] "Collection means" refers to the function that allows the server to use the APIs of social networking services and news sites to collect the latest information based on the user's input information and emotional state.

[1653] The "generation means" refers to a function that integrates the latest information and facility data collected by the collection means, and generates an optimal time-killing plan using an AI algorithm, taking into consideration the user's emotional state.

[1654] "Display means" refers to a function for analyzing the optimal time-killing plan sent from the server, formatting it in a format that is easy for the user to view, and displaying it on the terminal.

[1655] The term "server" refers to a central processing unit that receives information and emotional states sent by users, collects related information, generates plans, and transmits the generated plans to terminals.

[1656] "Terminal" refers to a device through which a user inputs information, communicates with the server, and receives the generated plan. Specifically, this includes smartphones, PCs, etc.

[1657] This system allows users to input information about what they want to do and proposes optimal time-killing plans based on that information. Furthermore, by combining it with an emotion engine, it can analyze the user's emotional state and provide optimal plans based on that state.

[1658] The user enters information

[1659] Users use devices such as smartphones or computers to input information about what they want to do, including location, time, number of people, genre, budget, and preference for indoor or outdoor activities.

[1660] Emotion engine recognizes user emotions

[1661] The device activates an emotion engine based on the user's input information and the application's operation history. The emotion engine uses natural language processing and machine learning technologies (such as Python's NLP library or TensorFlow) to analyze the user's psychological state. The analysis results are expressed as a condition, such as "stressed," "relaxed," or "excited."

[1662] The device sends the information to the server

[1663] The device sends the information entered by the user and the emotional state recognized by the emotion engine to the server. The data is sent in a general data format such as JSON (e.g., "{"Location": "Tokyo", "Time": "15:00", "Number of people": "2", "Genre": "Cafe", "Budget": "2000 yen", "Indoor": "Preferred", "Emotional state": "Stressed"}").

[1664] The server collects the latest information from social media and news sites.

[1665] Based on the user's input information and emotional state, the server collects the latest related information using APIs of social media and news sites (e.g., Twitter API, News API, etc.), thereby obtaining recent posts, trending information, the latest articles, and news related to the location.

[1666] The server collects the latest data from the facility.

[1667] The server accesses databases and APIs provided by facility operators to collect information on facility availability and special service availability that matches the user's criteria. For example, this includes information on facility seat availability and whether or not special services are available.

[1668] The server generates the optimal plan using an AI algorithm

[1669] The server combines the collected latest information with the facility's data and uses a generative AI model (e.g., trend prediction model or recommendation model) to generate an optimal time-killing plan. The server also takes into account the user's emotional state and selects a plan that will most satisfy the user. For example, if the server detects that the user is under stress, it selects a plan that provides a relaxing environment.

[1670] The server sends the generated plan to the device.

[1671] The server converts the generated plan back into a data format such as JSON format and sends it to the terminal as an HTTP response.

[1672] The device displays the plan to the user.

[1673] The device analyzes the plan data received from the server and displays it in a user-friendly format, including the location of the best facility, the time frame, estimated costs within the budget, reviews and ratings, the occupancy status, and the reasons for the recommendation based on an emotion engine.

[1674] Specific examples

[1675] For example, if a user inputs "I'd like to find a cafe for two in Tokyo starting at 3 PM, with a budget of 2,000 yen and preferably indoors," and the emotion engine recognizes the user's stress level, the server will generate a plan based on the latest information it has collected: "A 'Relaxation Cafe' in Shibuya, Tokyo is ideal for 3 PM, and the price is within budget," and send it to the device. The device will then display this plan in detail to the user, adding a note that "Based on your current emotional state, we have recommended a relaxing cafe."

[1676] In this way, the system not only allows users to kill time, but also allows them to quickly and easily obtain a plan that best suits their emotional state.

[1677] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1678] Step 1:

[1679] Users input information about what they want to do into the device. Specifically, they input the location, time, number of people, genre, budget, and preference for indoor or outdoor activities on the screen of their smartphone or computer, and then press the send button.

[1680] Input: User's own input: "Location: Tokyo", "Time: 15:00", "Number of people: 2", "Genre: Cafe", "Budget: 2000 yen", "Indoor: Preferred"

[1681] Output: The input information is passed to the next emotion recognition means.

[1682] Step 2:

[1683] The emotion engine recognizes the user's emotions. The device activates the emotion engine based on the information just entered and the app's operation history. The emotion engine uses natural language processing and machine learning technologies to analyze the user's psychological state.

[1684] Input: User input information and operation history

[1685] Data processing method: Analyze the input data using a natural language processing library (e.g., spaCy or NLTK) and apply a sentiment classification algorithm (e.g., SVM, Random Forest).

[1686] Output: The recognition result is "Emotional state: Stressed".

[1687] Step 3:

[1688] The device sends the input information and the perceived emotional state to the server, where the data is packaged in JSON format and sent as an HTTP POST request.

[1689] Input: Input information and emotional state

[1690] Data Calculation: Converting data to JSON format and creating HTTP requests

[1691] Output: An HTTP POST request is made to the server, sending the entire data.

[1692] Step 4:

[1693] The server collects the latest information from social media and news sites. Based on the information received, the server calls social media APIs (e.g., Twitter API) and news APIs (e.g., NewsAPI) to retrieve the latest related articles and trending information.

[1694] Input: User input and emotional state

[1695] Data calculation: Sending a query to the API (e.g. "Tokyo Cafe Latest News") and analyzing the received response

[1696] Output: A dataset of the latest articles and social media posts.

[1697] Step 5:

[1698] The server collects the latest data from the facility, accesses the facility operator's database and API, and obtains information about availability and special services that match the user's criteria.

[1699] Input: User's condition and emotional state

[1700] Data Calculation: Sending API queries and parsing response data

[1701] Output: A dataset of facility availability and special offers.

[1702] Step 6:

[1703] The server generates the optimal plan using an AI algorithm, integrating the collected data sets and using a generative AI model to create the optimal plan.

[1704] Input: Latest articles, social media posting data, facility availability information, special service information

[1705] Data Computing: Data integration and application of AI algorithms (e.g., multi-label classifiers and recommendation systems)

[1706] Output: The optimal time-killing plan to be provided to the user is generated.

[1707] Step 7:

[1708] The server sends the generated plan to the terminal. The generated plan is converted to JSON format and sent to the terminal as an HTTP response.

[1709] Input: Generated optimal time-killing plan

[1710] Data operations: converting to JSON format and creating an HTTP response

[1711] Output: An HTTP response is generated and sent to the device.

[1712] Step 8:

[1713] The terminal displays the plan to the user. It analyzes the plan data received from the server, formats it in a format that is easy for the user to view, and displays it.

[1714] Input: Plan data in JSON format

[1715] Data computation: Data analysis and visualization (e.g., display using front-end libraries)

[1716] Output: The user is shown "Relax Cafe" with a message saying "Based on your current emotional state, we have recommended a cafe where you can relax."

[1717] (Application example 2)

[1718] 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."

[1719] While conventional systems have the ability to provide optimal plans based on the user's preferences and desired conditions, they lack the ability to take into account the user's emotional state. This poses a challenge: they are unable to quickly provide plans that meet the user's psychological needs, especially when they are stressed or want to relax. Furthermore, there are limitations to the suggestions they can make for specific genres of activities or services (e.g., food delivery), making it difficult to fully satisfy the diverse needs of users.

[1720] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1721] In this invention, the server includes input means for inputting information about what the user wants to do, transmission means for transmitting the information and the user's emotional state to the server, collection means for collecting related information based on the information and the emotional state, generation means for generating an optimal delivery plan based on the collected information and the user's state, transmission means for transmitting the generated plan to the user, and display means for displaying the plan to the user. This makes it possible to propose an optimal delivery plan that takes the user's psychological state into consideration.

[1722] "Input means" refers to a device or interface for inputting information about what the user wants to do.

[1723] "Transmitting means" refers to the devices and protocols used to transmit input information and the user's emotional state to the server.

[1724] The "collection means" refers to devices or software that allow the server to collect relevant information based on input information and emotional state.

[1725] The "generation means" refers to a device or algorithm that generates an optimal delivery plan based on the collected information and the user's status.

[1726] The "display means" is a device or interface for presenting the generated plan to the user.

[1727] A "social networking service" is a service or platform that allows users to interact with each other over the Internet.

[1728] "News delivery methods" are systems and services that provide the latest news and information.

[1729] A "food delivery service" is a service that allows you to order food and drinks and have them delivered to a specified location.

[1730] "Mental state" refers to the user's subjective feelings and mental condition.

[1731] The present invention relates to a system for proposing an optimal delivery plan in consideration of the emotional state of a user. A detailed embodiment for realizing this system will be described below.

[1732] Main components and technologies used

[1733] 1. Input Method

[1734] It is a device or interface for users to input information about what they want to do. For example, a smartphone app falls into this category, and is implemented as a cross-platform application using React Native.

[1735] 2. Transmission Method

[1736] It is a device and protocol for transmitting input information and the user's emotional state to a server. It mainly uses the HTTP protocol, and data is transmitted in JSON format.

[1737] 3. Collection Method

[1738] This is a device or software that allows the server to collect relevant information based on input information and emotional state. The Axios library is used to collect data, and the latest information is obtained from social networking service (SNS) APIs and news sources.

[1739] 4. Generation means

[1740] These are devices and algorithms that generate optimal delivery plans based on collected information and the user's status. A generative AI model using TensorFlow is used as a powerful tool.

[1741] 5. Display means

[1742] This is the device or interface for presenting the generated plan to the user. React Native UI components are used to display it within the application.

[1743] System Operation Overview

[1744] The server generates an optimal delivery plan through the following steps and provides it to the user.

[1745] 1. Enter your user information

[1746] Users input desired meal information (e.g., type of food, budget, number of people, time) through a smartphone app. The emotion engine also analyzes the user's psychological state, for example, if the user is under stress.

[1747] 2. Data transmission

[1748] The entered information and the user's emotional state are formatted and sent to the server in JSON format.

[1749] 3. Data Collection

[1750] The server collects the latest relevant information using the APIs of related food delivery services (e.g., UberEats API and DoorDash API) and social media APIs (e.g., Twitter API).

[1751] 4. Generating the optimal plan

[1752] The AI ​​algorithm uses the collected data to generate an optimal meal plan that takes into account the user's emotional state and preferences, using a deep learning model powered by TensorFlow.

[1753] 5. Submitting and Viewing Plans

[1754] The generated plan is converted back to JSON format and sent to the smartphone app, which displays the plan in an easy-to-understand format to the user, along with the reasons for the proposal.

[1755] Specific examples

[1756] For example, if a user enters "Chinese food," "under 2,000 yen," "for two people," "7 p.m." and "looking to relieve stress" into a smartphone app, the emotion engine will check the user's stress level from their operation history. The app will collect the latest related information and suggest "We recommend the Chinese restaurant 'Relax Garden.'" Furthermore, the app will display relaxing music and menu recommendations.

[1757] Prompt Sentence Examples

[1758] "Enter the user's emotional state and preferences, and generate a meal plan based on the latest food delivery information. The plan should also emphasize relaxation."

[1759] This system makes it possible to propose delivery plans that optimally take into account the user's psychological state.

[1760] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1761] Step 1:

[1762] Users use a smartphone app to input information about the meal they want (e.g., type of meal, budget, number of people, time) and their current emotional state (e.g., desire to relieve stress).

[1763] Input: genre, budget, number of people, time, emotional state

[1764] Output: User information (JSON format)

[1765] Specific behavior: The user enters information in an interface developed using React Native and presses the "Submit" button.

[1766] Step 2:

[1767] The device formats the input user information and emotional state into JSON format and sends it to the server using the HTTP protocol.

[1768] Input: User information (JSON format)

[1769] Output: HTTP request sent to the server

[1770] Specific operation: In the React Native application, an HTTP POST request is created using the Axios library and sent to the server.

[1771] Step 3:

[1772] The server analyzes the received user information and emotional state and collects related information. Here, it calls the API of social media sites and food delivery services to obtain related data.

[1773] Input: User information (JSON format), emotional state

[1774] Output: Relevant information collected

[1775] Specific operation: A server implemented using Node.js and Express.js calls the Twitter API and Uber Eats API using the Axios library to collect data.

[1776] Step 4:

[1777] The server generates an optimal delivery plan based on the collected information and the user's emotional state using a generative AI model powered by TensorFlow.

[1778] Input: Collected relevant information, emotional state

[1779] Output: Optimal delivery plan

[1780] Specific operation: The collected data is input into a TensorFlow deep learning model to generate an optimal plan.

[1781] Step 5:

[1782] The server formats the generated delivery plan again into JSON format and sends it to the terminal as an HTTP response.

[1783] Input: Optimal delivery plan (JSON format)

[1784] Output: Plan sent as HTTP response

[1785] Specific operation: The generated plan is converted to JSON and sent as an HTTP response using Express.js in Node.js.

[1786] Step 6:

[1787] The device analyzes the received delivery plan and displays it in a format that is easy for the user to view. The app also displays the reason for the proposal and additional information that may have a relaxing effect (e.g., relaxing music).

[1788] Input: Optimal delivery plan (JSON format)

[1789] Output: The delivery plan displayed to the user

[1790] What it does: Uses React Native to display the best delivery plan on the screen, along with additional information.

[1791] This processing step allows for the proposal of an optimal delivery plan that takes into account the user's psychological state.

[1792] 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.

[1793] 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.

[1794] 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.

[1795] 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.

[1796] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1797] 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.

[1798] 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).

[1799] 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.

[1800] 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."

[1801] 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.

[1802] 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).

[1803] 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.

[1804] 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.

[1805] 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.

[1806] 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.

[1807] 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.

[1808] 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.

[1809] 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.

[1810] 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.

[1811] 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.

[1812] 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.

[1813] The following is further disclosed regarding the above embodiment.

[1814] (Claim 1)

[1815] an input means for inputting information about what the user wants to do;

[1816] a transmitting means for transmitting the information to a server;

[1817] a collection means for collecting the latest related information based on the information;

[1818] A generating means for generating an optimal time-killing plan based on the collected information and the user's conditions;

[1819] a transmitting means for transmitting the generated plan to a user;

[1820] The system includes a display means for displaying the plan to a user.

[1821] (Claim 2)

[1822] 2. The system according to claim 1, wherein the collection means acquires the latest information from social networking services and news sites.

[1823] (Claim 3)

[1824] 2. The system according to claim 1, wherein the generating means generates an optimal plan based on information regarding the congestion status and business status of the facility.

[1825] "Example 1"

[1826] (Claim 1)

[1827] an input means for inputting information about what the user wants to do;

[1828] a transmitting means for transmitting the information to a server;

[1829] a collection means for collecting the latest related information from social networking services and news sites based on the information;

[1830] a collection means for collecting facility-provided data;

[1831] A generation means for generating an optimal time-killing plan using an AI algorithm based on the collected information and the user's conditions;

[1832] a transmitting means for transmitting the generated plan to a user;

[1833] The system includes a display means for displaying the plan to a user.

[1834] (Claim 2)

[1835] 2. The system according to claim 1, wherein the collection means acquires the latest information from social networking services and news sites.

[1836] (Claim 3)

[1837] 2. The system according to claim 1, wherein the generating means generates an optimal plan based on information regarding the congestion status and business status of the facility.

[1838] "Application Example 1"

[1839] (Claim 1)

[1840] an input means for inputting information about what the user wants to do;

[1841] a transmitting means for transmitting the information to a server;

[1842] a collection means for collecting the latest related information based on the information;

[1843] A generating means for generating an optimal plan based on the collected information and the user's conditions;

[1844] a transmitting means for transmitting the generated plan to a user;

[1845] a display means for displaying the plan to a user;

[1846] It is a way to suggest the best delivery plan by inputting the user's location information, food genre, budget, and waiting time.

[1847] A system including:

[1848] (Claim 2)

[1849] 2. The system according to claim 1, wherein the collection means acquires the latest information from social networking services, news sites, and review platforms.

[1850] (Claim 3)

[1851] 2. The system according to claim 1, wherein the generating means generates an optimal plan based on information regarding the congestion and business status of the delivery service.

[1852] "Example 2: Combining Emotion Engines"

[1853] (Claim 1)

[1854] an input means for inputting information about what the user wants to do;

[1855] emotion recognition means for recognizing the information and the user's emotional state;

[1856] transmitting means for transmitting the information and emotional state to a server;

[1857] A collection means for acquiring the latest information from social networking services and news sites based on the information and emotional state;

[1858] a generating means for generating an optimal time-killing plan based on the information, the emotional state, and the collected information;

[1859] a transmitting means for transmitting the generated plan to a user;

[1860] The system includes a display means for displaying the plan to a user.

[1861] (Claim 2)

[1862] 2. The system according to claim 1, wherein the collection means acquires the latest information using an API of a social networking service or a news site.

[1863] (Claim 3)

[1864] 2. The system according to claim 1, wherein the generating means generates an optimal plan based on information regarding the congestion status and business status of the facility.

[1865] "Application example 2 when combining emotion engines"

[1866] (Claim 1)

[1867] an input means for inputting information about what the user wants to do;

[1868] transmitting means for transmitting the information and the user's emotional state to a server;

[1869] a collection means for collecting relevant information based on the information and the emotional state;

[1870] A generating means for generating an optimal delivery plan based on the collected information and the user's status;

[1871] a transmitting means for transmitting the generated plan to a user;

[1872] The system includes a display means for displaying the plan to a user.

[1873] (Claim 2)

[1874] 2. The system according to claim 1, wherein the collection means acquires the latest information from a social networking service or a news source.

[1875] (Claim 3)

[1876] 2. The system according to claim 1, wherein the generating means generates an optimal delivery plan based on information regarding the food delivery service provision method and the user's psychological state. [Explanation of symbols]

[1877] 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. an input means for inputting information about what the user wants to do; a transmitting means for transmitting the information to a server; a collection means for collecting the latest related information based on the information; A generating means for generating an optimal time-killing plan based on the collected information and the user's conditions; a transmitting means for transmitting the generated plan to a user; The system includes a display means for displaying the plan to a user.

2. 2. The system according to claim 1, wherein the collection means acquires the latest information from social networking services and news sites.

3. 2. The system according to claim 1, wherein the generating means generates an optimal plan based on information relating to the congestion status and business status of the facility.

Images