System

Abstract

To provide a system.SOLUTION: The system includes: means of receiving an input of destination or target exercise intensity from a user; means of acquiring positional information of the user; means of proposing the destination in a form of dialogue using a generative AI based on the input information and the positional information of the user; means of recognizing user emotion by using an emotion engine; and means of optimizing the destination based on the recognized emotional information of 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 a description and related instruction sentence regarding 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] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] In recent years, the market for health-conscious fitness and people flow businesses has been expanding, but it is difficult for users to receive appropriate suggestions based on their destination and exercise intensity. In addition, there is a demand for a method to effectively utilize users' location information and sell it to companies. [Means for solving the problem]

[0005] The present invention provides a system including a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, and a means for acquiring the user's location information.Furthermore, the present invention provides a means for selling the user's location information to companies as people flow data, thereby solving these problems. [Brief description of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 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. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 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. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a process flow of the data processing system in the first embodiment of the first form example. [Figure 12] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the application example 1 of the first embodiment. [Figure 13] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the second embodiment of the second embodiment. [Figure 14] FIG. 13 is a sequence diagram showing a process flow of the data processing system in application example 2 of embodiment 2. [Figure 15] FIG. 13 is a sequence diagram showing a process flow of a data processing system in a third embodiment of the present invention. [Figure 16] FIG. 13 is a sequence diagram showing a process flow of the data processing system in the third application example of the third embodiment. [Figure 17] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when combined with an emotion engine. [Figure 19] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system according to the embodiment 2 of the second embodiment in the case where an emotion engine is combined. [Figure 20] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when combined with an emotion engine. [Figure 21] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the embodiment 3 of the form example 3 in the case where an emotion engine is combined. [Figure 22] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when combined with an emotion engine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0009] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by the processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0014] [First embodiment]

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

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (e.g., voice and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

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

[0023] As shown in Fig. 2, 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. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process 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 process program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads out the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0027] "Example 1"

[0028] The present invention is realized as a smartphone application. The user inputs a destination or a target exercise intensity through the application. The input information is sent to a generative AI, which automatically suggests destinations in an interactive format. The suggestions are optimized based on the user's input information, providing results tailored to the user's needs.

[0029] "Example 2"

[0030] Furthermore, in this embodiment of the present invention, the location information of the user is acquired and sold to companies as people flow data. The location information is acquired using the GPS function of the user's smartphone. The acquired location information is processed as people flow data and provided to companies. This allows companies to use it for market research, formulating advertising strategies, and so on.

[0031] "Example 3"

[0032] As a specific example, if a user inputs a goal of "running 5km," the AI ​​will suggest the optimal route to run 5km from the user's current location. The user's movement information will also be provided to companies as people flow data, and for example, sporting goods stores can use the information to target advertisements.

[0033] The process flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: The user opens the smartphone application and enters the destination or target exercise intensity.

[0036] Step 2: The input information is sent to the generative AI.

[0037] Step 3: The AI ​​automatically suggests destinations in a conversational format, and the suggestions are optimized based on the user's input to provide results tailored to the user's needs.

[0038] "Example 2"

[0039] Step 1: Obtain the user's location using the smartphone's GPS function.

[0040] Step 2: The acquired location information is processed as people flow data.

[0041] Step 3: The processed people flow data is provided to companies, who can then use it for market research, advertising strategy development, and more.

[0042] "Example 3"

[0043] Step 1: User enters goal "run 5km".

[0044] Step 2: The AI ​​will suggest the best route for driving within a distance of 5km from the user's current location.

[0045] Step 3: The user's movement information is provided to companies as people flow data. For example, sporting goods stores can use the information to target advertisements.

[0046] Example 1

[0047] Next, a description will be given of Example 1 of the embodiment 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".

[0048] In conventional exercise planning support systems, users had to decide their own destination and exercise intensity, making it difficult to find the optimal exercise plan. In addition, there was a lack of means to effectively utilize the user's location information, making it difficult to make suggestions that met the user's needs.

[0049] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for transmitting the input information to the generative AI model, a means for analyzing the input information using the generative AI model and generating an optimal proposal, a means for displaying the generated proposal to the user, and a means for acquiring the user's location information. This allows the user to easily find an optimal exercise plan, and makes it possible to realize a proposal that utilizes the user's location information.

[0050] "User" refers to any individual or entity that uses the System.

[0051] "Destination" refers to the place the user wants to reach.

[0052] "Exercise intensity" refers to the strength or amount of exercise that a user aims for.

[0053] "Means of input" refers to the interface that allows users to communicate their destination and exercise intensity to the system.

[0054] A "generative AI model" refers to an artificial intelligence model that analyzes user input information and generates optimal suggestions.

[0055] "Means of transmitting" refers to the communications means for sending user input information to the generative AI model.

[0056] "Means of analysis" refers to the process by which the generative AI model analyzes the user's input information and generates optimal suggestions.

[0057] "Means for generating suggestions" refers to the process by which a generative AI model creates suggestions for a user based on the results of the analysis.

[0058] "Means for displaying" refers to an interface for visually showing the generated suggestions to a user.

[0059] "Location Information" means data that indicates a User's current geographic location.

[0060] "Means of collection" refers to the technologies and devices used to collect user location information.

[0061] "People flow data" refers to data that aggregates the location information of multiple users and shows their movement patterns and behavioral tendencies.

[0062] "Means of selling to businesses" refers to the process by which collected human flow data is provided to businesses for commercial purposes.

[0063] A "subscription format" refers to a business model in which a service can be used on an ongoing basis by paying a periodic fee.

[0064] "Mobile information terminal application" refers to software that runs on mobile information terminals such as smartphones and tablets.

[0065] This invention is a system that uses a generative AI model to suggest an optimal exercise plan when a user inputs a destination or a target exercise intensity. The system is realized as a smartphone application.

[0066] The user starts the application and inputs the destination or the target exercise intensity. For example, the user inputs "I want to walk for 30 minutes." This input information is acquired by the terminal and transmitted to the server via the Internet.

[0067] The server passes the received input information to a generative AI model (e.g., GPT-4 (registered trademark) by OpenAI (registered trademark). The generative AI model analyzes the user's input information and generates optimal suggestions. For example, it generates a suggestion such as, "How about walking along the path along the nearby river?"

[0068] The generated suggestions are sent from the server to the terminal, and the terminal displays the suggestions to the user, who can review the suggestions and select or modify them as necessary.

[0069] As a concrete example, consider a case where a user inputs, "I want to go for a 30-minute walk." When this information is sent to the generative AI model, the AI ​​might suggest, "How about walking along the path next to a nearby river?"

[0070] Here is an example of a prompt to be input to the generative AI model:

[0071] User input: I want to go for a 30 minute walk

[0072] AI Response: How about walking along a nearby river path?

[0073] The system also includes a means to obtain the user's location information and optimizes suggestions by taking into account data such as the user's current location and past exercise history, allowing users to easily find the optimal exercise plan.

[0074] It also includes a way for companies to sell users' location information to them as people flow data, which the companies can use for marketing purposes and to improve their services.

[0075] The system is provided as a subscription-based mobile information terminal application, allowing users to use the service continuously by paying a periodic fee.

[0076] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0077] Step 1:

[0078] A user launches an application. A user launches an application by tapping the application icon on the home screen of their smartphone. When the application launches, the main screen is displayed. The input is the user's operation, and the output is the application's main screen.

[0079] Step 2:

[0080] A user inputs a destination or a target exercise intensity. A user inputs "I want to go to a nearby park" or "I want to take a 30-minute walk" into an application's input field. The input is the user's text input, and the output is the retrieval of the input information.

[0081] Step 3:

[0082] The terminal sends input information to the generative AI model. The terminal receives the user's input information and sends it to the server via the Internet. At this time, the input information is properly formatted and converted into a form that the generative AI model can understand. The input is the user's input information, and the output is the data sent to the server.

[0083] Step 4:

[0084] The server analyzes the input information using a generative AI model and generates optimal suggestions. The server passes the input information it receives to a generative AI model (e.g., OpenAI's GPT-4). The generative AI model analyzes the input information and generates optimal suggestions based on the user's needs. For example, it generates a suggestion such as, "How about walking along the path along the nearby river?" The input is the user's input information, and the output is the generated suggestion.

[0085] Step 5:

[0086] The server sends the generated proposal to the terminal. The server sends the proposal obtained from the generative AI model to the terminal. At this time, the proposal is formatted in a format that is easy for the user to understand. The input is the generated proposal, and the output is the data to be sent to the terminal.

[0087] Step 6:

[0088] The terminal displays the proposal to the user. The terminal displays the proposal received from the server to the user. The user can check the proposal on the application screen. The input is the proposal data from the server, and the output is the display to the user.

[0089] Step 7:

[0090] The user reviews the suggestions and selects or modifies them if necessary. The user reviews the suggestions and selects the suggestion if satisfied. If necessary, they can also modify the suggestion. For example, if they don't like the suggested location, they can request an alternative location. The input is the suggestion data from the server and the output is the user's selection or modification.

[0091] (Application example 1)

[0092] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0093] Conventional food delivery services have the problem that users have to search for restaurants and place orders themselves, which is time-consuming. In addition, there was no system that suggested the best restaurant based on the user's location information or exercise intensity, so it could not fully meet the needs of users.

[0094] 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.

[0095] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for displaying the location information of the proposed destination on a map, and a means for checking whether the proposed destination is compatible with the service and, if so, providing an ordering link. This allows the user to easily find the best restaurant based on the location information and exercise intensity without having to search for it themselves.

[0096] "User" refers to an individual who uses the system to input their destination and exercise intensity and receive suggestions.

[0097] "Destination" refers to the place the user wants to reach.

[0098] "Exercise intensity" refers to the level and type of exercise a user aims to achieve.

[0099] "Generative AI" refers to artificial intelligence that generates optimal suggestions in an interactive format based on input information.

[0100] "Interactive" refers to a format in which the user and system exchange information through questions and answers.

[0101] "Location Information" refers to geographic information about a User's current location or a specific place.

[0102] "Means for displaying on a map" means a method for visually illustrating the location of a proposed destination using a mapping application or mapping service.

[0103] "Service verification means" refers to a method to verify whether a proposed destination supports a particular service (e.g. food delivery).

[0104] "Means for providing an order link" refers to a method for providing a link or button that enables a User to place an order at a suggested destination.

[0105] A system for implementing this invention includes means for a user to input a destination or a target exercise intensity, means for automatically suggesting destinations in an interactive format using generative AI based on the input information, means for acquiring user location information, means for displaying the location information of the suggested destination on a map, and means for checking whether the proposed destination is compatible with the service and, if so, providing an order link.

[0106] Hardware and Software Used

[0107] Hardware: Smartphone

[0108] software:

[0109] Mobile application development frameworks (e.g. React Native)

[0110] Generative AI models (e.g. OpenAI GPT-4)

[0111] Map API (e.g. Google Maps API)

[0112] Food delivery API (e.g. Uber Eats API)

[0113] Data processing and calculation

[0114] Getting User Input

[0115] Users open the smartphone application and input their destination or target exercise intensity, for example, "a restaurant within a 10-minute walk from home."

[0116] Sending prompts to generative AI

[0117] A prompt is sent to the generative AI based on the input information. An example of a prompt sentence is, "The user is looking for a restaurant within a 10-minute walk from his / her home. Please suggest some recommended restaurants."

[0118] AI-driven proposal generation

[0119] Generative AI will suggest the best restaurant based on prompts, for example, "There are three nearby restaurants: Restaurant A, Cafe B, and Diner C."

[0120] Integration with Map API

[0121] Get the location of the suggested restaurants using Map API and display it to the user. Mark the location of the suggested restaurants on the map using Google Maps API.

[0122] Integration with food delivery API

[0123] Check if the suggested restaurants offer food delivery services and provide an order link if so. Use the Uber Eats API to display the menu and order link for the suggested restaurants.

[0124] Examples

[0125] A user opens the application and inputs "restaurants within a 10-minute walk from home." The generative AI then suggests "Restaurant A, Cafe B, and Diner C," and displays them on a map using the Google Maps API. It also uses the Uber Eats API to provide menus and ordering links for each restaurant.

[0126] Examples of prompt statements

[0127] A user is looking for a restaurant within a 10-minute walk from their home. Please suggest a restaurant.

[0128] In this way, users can easily find the best restaurants based on their location and activity level, without having to search for them themselves.

[0129] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0130] Step 1:

[0131] The user opens the smartphone application and inputs the destination or the target exercise intensity. The input information is temporarily saved in the application. For example, the user inputs "restaurants within a 10-minute walk from home."

[0132] Step 2:

[0133] The device sends the input information to the generative AI as a prompt. An example of a prompt is, "The user is looking for a restaurant within a 10-minute walk from his / her home. Please recommend some restaurants." The input data is sent in text format.

[0134] Step 3:

[0135] The server uses generative AI to suggest the best restaurant based on the prompts. The generative AI analyzes the input information and lists restaurants that fit the user's needs. For example, "Restaurant A, Cafe B, Diner C" is suggested.

[0136] Step 4:

[0137] The server retrieves the location of the suggested restaurants using a map API (e.g., Google Maps API). The location information is retrieved in the form of latitude and longitude, and is stored as data to be visually displayed to the user.

[0138] Step 5:

[0139] The device displays the location of the suggested restaurant on a map based on the location information obtained from the map API. The user can check the location of the suggested restaurant on the screen of their smartphone.

[0140] Step 6:

[0141] The server uses a food delivery API (e.g. Uber Eats API) to check if the suggested restaurants offer food delivery services, and if so, retrieves the menu and ordering links for each restaurant.

[0142] Step 7:

[0143] The terminal displays the menu and order link retrieved from the food delivery API to the user. The user can check the suggested restaurant menu on the smartphone screen and place the order by clicking the order link.

[0144] In this way, users can easily find the best restaurant based on their location and exercise intensity without having to search for it themselves.

[0145] Example 2

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

[0147] Conventional location information acquisition systems only acquired the user's location information, but the means to effectively utilize that information were limited. There was also a lack of systems that provided detailed people flow data that companies could use for market research and the formulation of advertising strategies. Furthermore, there was no system that made appropriate suggestions based on the user's destination or exercise intensity.

[0148] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring user location information, a means for storing the acquired location information in a database, a means for generating people flow data based on the stored location information, and a means for providing the generated people flow data to companies. This makes it possible to effectively utilize the user's location information and provide detailed people flow data that companies can use for market research and the formulation of advertising strategies. In addition, appropriate suggestions can be made based on the user's destination and exercise intensity.

[0149] "Destination" refers to the place the user wants to reach.

[0150] "Exercise intensity" refers to the level of exercise strength or load that a user aims for.

[0151] "Generative AI" refers to artificial intelligence that automatically makes suggestions in an interactive format based on information entered by the user.

[0152] "Location Information" means geographic data that may include a User's current latitude and longitude.

[0153] "Database" refers to an information management system for storing acquired location information.

[0154] "People flow data" refers to data on the flow of people obtained by aggregating and analyzing the location information of multiple users.

[0155] "Providing to businesses" refers to providing the generated people flow data in a form that can be used by businesses.

[0156] "Subscription format" refers to a format in which a service can be used on an ongoing basis by paying a periodic fee.

[0157] "Smartphone application" refers to a software program that runs on a smartphone.

[0158] "Data analysis tool" refers to software for analyzing stored location information to generate people flow data.

[0159] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0160] The present invention is a system that acquires user location information, generates people flow data based on the information, and provides the data to businesses. A specific embodiment of the system will be described below.

[0161] server

[0162] The server receives location information from the user's smartphone. Specifically, the server receives an HTTP POST request and analyzes the location data included in the request body. The hardware used is the server, and the software used is an HTTP server (e.g., Apache (registered trademark), Nginx).

[0163] The received location information is stored in a database. The server stores the location information in the database using an INSERT query. For example, the server executes the following query in a MySQL (registered trademark) database: "INSERT INTO location_data (user_id, latitude, longitude, timestamp) VALUES (...)".

[0164] The stored location information is analyzed using Python's Pandas library to generate people flow data. The server responds to data requests from companies through an API server using Flask, and returns people flow data in JSON format.

[0165] Terminal

[0166] The device obtains the user's location information using the GPS function. Specifically, the device periodically activates the GPS sensor and obtains the current latitude and longitude. The hardware used is a smartphone, and the software used is the GPS function (e.g., ANDROID (registered trademark)'s LocationManager).

[0167] The obtained location information is sent to the server by creating an HTTP POST request and including the location information data in the request body. For example, the Retrofit library is used to send the data to the server.

[0168] User

[0169] The user enables the GPS function of the smartphone. Specifically, the user opens the settings app of the smartphone and turns on the "Location Information" setting.

[0170] The user also agrees to the provision of location information. Specifically, the user taps the "Agree" button in response to the message "Do you agree to provide location information?" on the application's consent screen.

[0171] Examples

[0172] Example 1: Acquiring and sending location information

[0173] When a user is in a shopping mall, he / she activates the GPS function of his / her smartphone. The device acquires the user's current location and transmits the location information to a server. The server stores the received location information in a database and later processes it as people flow data.

[0174] Example 2: Providing people flow data for companies

[0175] The server analyzes the foot traffic data for a particular area and provides it to businesses, who may use it to decide where to open new stores, for example.

[0176] Example prompts for generative AI models

[0177] "Please explain the process of the system that obtains user location information and provides it to companies as people flow data. Please also specify the names of any specific hardware or software."

[0178] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0179] Program processing flow

[0180] Step 1: Get the user's location

[0181] Subject: Terminal

[0182] The device obtains the user's location information using the GPS function. Specifically, the device periodically activates the GPS sensor and obtains the current latitude and longitude. The hardware used is a smartphone, and the software used is the GPS function (e.g. Android's LocationManager).

[0183] Input: Location request from the GPS sensor

[0184] Output: The user's current latitude and longitude.

[0185] Step 2: Send location information

[0186] Subject: Terminal

[0187] The device sends the acquired location information to the server. Specifically, the device creates an HTTP POST request, includes the location data in the request body, and sends it to the server. The software used is an HTTP client library (e.g., Retrofit).

[0188] Input: User's current latitude and longitude

[0189] Output: HTTP POST request to the server

[0190] Step 3: Receiving location information

[0191] Subject: Server

[0192] The server receives location information from the user's smartphone. Specifically, the server receives an HTTP POST request and analyzes the location data included in the request body. The hardware used is the server, and the software used is an HTTP server (e.g., Apache, Nginx).

[0193] Input: HTTP POST request

[0194] Output: Geolocation data

[0195] Step 4: Save location

[0196] Subject: Server

[0197] The server stores the received location information in a database. Specifically, the server stores the location information in the database using an INSERT query. The hardware used is a server, and the software used is a database management system (e.g., MySQL).

[0198] Input: Geolocation data

[0199] Output: Save results to database

[0200] Step 5: Generate people flow data

[0201] Subject: Server

[0202] The server generates people flow data based on the stored location information. Specifically, the server uses Python's Pandas library to aggregate the location information data and analyze people flow patterns for specific areas and time periods.

[0203] Input: Location information stored in the database

[0204] Output: People flow data

[0205] Step 6: Providing data to businesses

[0206] Subject: Server

[0207] The server provides the generated people flow data to companies. Specifically, the server responds to data requests from companies through an API server using Flask, and returns people flow data in JSON format.

[0208] Input: People flow data

[0209] Output: JSON formatted data response to the company.

[0210] (Application example 2)

[0211] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0212] Conventional ad delivery systems have had difficulty effectively utilizing users' location information to deliver ads. In addition, there were limited means for companies to obtain real-time human flow data necessary for market research and formulating advertising strategies. This made it difficult to maximize the effectiveness of advertising, and companies were looking for more efficient data utilization in their marketing activities.

[0213] 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. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring user location information, a means for analyzing the acquired location information and processing it as people flow data, and a means for delivering advertisements based on the analysis results. This makes it possible to acquire user location information in real time and deliver optimal advertisements based on the analysis results. In addition, companies can use this people flow data to efficiently conduct market research and formulate advertising strategies.

[0214] "Destination" refers to the specific location to which a User wishes to travel.

[0215] "Exercise intensity" is an indicator of the level of energy expenditure or physical activity that a user wants to achieve during exercise.

[0216] "Generative AI" refers to artificial intelligence technology that automatically generates appropriate suggestions in an interactive format based on input information.

[0217] "Interactive style" refers to a form of communication in which a user and a system exchange information with each other.

[0218] "Location Information" is data that indicates a user's current geographic location.

[0219] "Analysis" refers to the process of processing acquired data and converting it into meaningful information.

[0220] "People flow data" is data that shows the movement patterns of people in specific areas and at specific times.

[0221] "Advertising" refers to information promoting a particular product or service.

[0222] "Delivery" refers to the act of delivering specific information to users.

[0223] A "subscription format" refers to a business model in which a service can be used on an ongoing basis by paying a regular fee.

[0224] "Smartphone application" refers to a software program that runs on a smartphone.

[0225] The following system configuration and processing procedure will be described as an embodiment of the present invention.

[0226] System Configuration

[0227] The system consists of the user's smartphone, a server, and an ad delivery server. The smartphone is equipped with a GPS function and is used to obtain the user's location information. The server uses a generative AI model to interactively suggest destinations based on the user's input information, and analyzes the obtained location information to generate people flow data. The ad delivery server delivers the most suitable advertisements to the user based on the analysis results.

[0228] Hardware and Software Used

[0229] Smartphone: Any device with GPS functionality

[0230] Server: A computer for running data analysis and generative AI models

[0231] Advertisement delivery server: External server for delivering advertisements

[0232] Software: Python, requests library, geopy library

[0233] Data processing and calculation

[0234] 1. Obtaining location information: Obtaining the user's location information in real time using the smartphone's GPS function.

[0235] 2. Data analysis: The server analyzes the acquired location information and processes it as people flow data. This analysis involves estimating the density of people flow by combining the location information and the current time.

[0236] 3. Advertisement delivery: Based on the analysis results, the server generates advertisements that meet specific conditions (e.g., high pedestrian density) and delivers them to users via the ad delivery server.

[0237] Examples

[0238] For example, if a user is near Tokyo Station, the GPS function of the smartphone is used to obtain location information. The server analyzes this location information and determines that the density of people flowing around Tokyo Station is high. Based on the analysis results, an advertisement such as "Special sale! Check it out now!" is generated and delivered to the user via the advertisement delivery server.

[0239] Examples of prompt statements

[0240] An example of a prompt for a generative AI model is as follows:

[0241] Please develop an application that acquires user location information, analyzes the data, and provides it to companies as people flow data. Specifically, this application will acquire location information using the GPS function of smartphones and deliver advertisements based on the analysis results. Ad delivery will be done using an external ad server API.

[0242] The above is an embodiment of the present invention.

[0243] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0244] Step 1:

[0245] The user inputs the destination or the target exercise intensity using a smartphone. The input information is sent to the server by the smartphone application. The input data includes the geographic information of the destination and the numerical value of the exercise intensity.

[0246] Step 2:

[0247] The server uses a generative AI model to automatically suggest destinations interactively based on the received input data. The generative AI model analyzes the user's input information and generates optimal destinations. This process also takes into account the user's past travel history and current location information. The generated destination information is sent to the user's smartphone.

[0248] Step 3:

[0249] The user's smartphone acquires location information in real time using the GPS function. The acquired location information is periodically sent to a server. The location information data includes latitude, longitude, and timestamp.

[0250] Step 4:

[0251] The server analyzes the received location information and processes it as people flow data. The analysis includes clustering the location information and calculating the people flow density by time period. As a result of the analysis, people flow data is generated. This data shows the movement patterns of people in a specific area and time period.

[0252] Step 5:

[0253] The server generates advertisements based on the analysis results. In the advertisement generation process, the advertisement content is selected according to specific conditions (e.g., when the pedestrian flow density is high) taking into account the pedestrian flow data. The generated advertisement content is sent to the advertisement distribution server.

[0254] Step 6:

[0255] The ad delivery server delivers the received ad content to the user's smartphone. The ad is displayed at the optimal time based on the user's current location information and people flow data. The user can check the ad on their smartphone.

[0256] The above are the specific processing steps of this system.

[0257] Example 3

[0258] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0259] Conventional exercise support systems lack the functionality to suggest optimal routes based on the user's target exercise distance and exercise intensity. In addition, there are limited means to effectively utilize user movement information, making it difficult to provide useful data to companies.

[0260] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for calculating an optimal route based on the acquired location information, a means for providing the user with the calculation results, and a means for saving the user's movement information in a database. This allows the user to exercise efficiently, and companies to obtain valuable data for target advertising.

[0261] "User" refers to an individual who uses the system to set exercise goals and exercise based on those goals.

[0262] A "destination" refers to a specific location or distance that a user sets as their exercise goal.

[0263] "Exercise intensity" refers to the strain or difficulty a user wants to achieve while exercising.

[0264] "Generative AI" refers to artificial intelligence that automatically suggests destinations and exercise routes in an interactive format based on information entered by the user.

[0265] "Location information" refers to data that indicates a user's current location and travel route.

[0266] "Optimal route" refers to an efficient and safe exercise path calculated based on the user's exercise goals.

[0267] "Database" refers to an information system for storing and managing User movement information and other related data.

[0268] "People flow data" refers to data that is compiled and analyzed from user movement information, and can be used by companies for marketing and advertising purposes.

[0269] "Mobile information terminal application" refers to software that runs on mobile information terminals such as smartphones and tablets.

[0270] The present invention is a system for allowing a user to set an exercise goal and for proposing an optimal exercise route based on the goal. A specific embodiment of this system will be described below.

[0271] First, the user inputs his / her exercise goal using a mobile information terminal application. For example, he / she inputs a goal such as "running 5km." This input data is sent from the terminal to the server. The server receives the data using an HTTP request.

[0272] The server uses generative AI to calculate the optimal exercise route based on the received data. For this calculation, it uses map services such as Google Maps API and OpenStreetMap API. Specifically, it obtains the user's current location and calculates the optimal route for driving a distance of 5km from there. The calculation result is returned to the terminal in JSON format.

[0273] The device displays the received route information to the user. Specifically, the device displays a map on the app screen and draws the optimal route on the map. The user then starts running according to this route.

[0274] When a user starts running, the device sends the user's movement information to the server in real time. Specifically, GPS data is sent to the server periodically. The server stores the received movement information in a database. The database can be a SQL database or a NoSQL database.

[0275] The stored movement information is provided to companies as people flow data. Companies can use this data to target advertisements. For example, a sporting goods store can deliver advertisements to users who go running in a specific area.

[0276] As a concrete example, consider the case where a user inputs a goal of "running 5km". The user opens a smartphone app and inputs "running 5km". The app sends the information to a server, which uses the Google Maps API to calculate the optimal route. The calculation result is sent back to the app, and the user starts running according to the route.

[0277] Example prompt:

[0278] If a user enters a goal of "running 5km", the server will use the Google Maps API to calculate the optimal route and provide the result to the user. The user's movement information will also be stored in a database and provided to the company.

[0279] This system allows users to exercise efficiently and companies to obtain valuable data for targeted advertising. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0280] Step 1:

[0281] The user inputs a goal. The user opens a mobile information terminal application and inputs a goal such as "run 5km." The input data includes information such as the target distance and exercise intensity. The input data is sent from the terminal to the server.

[0282] Step 2:

[0283] The terminal sends the input data to the server. The terminal sends the goal data entered by the user to the server using an HTTP POST request. The input data also includes the user's current location information. The server analyzes the received data and proceeds to the next process.

[0284] Step 3:

[0285] The server calculates the optimal route. Based on the received destination data and current location information, the server uses the Google Maps API or OpenStreetMap API to calculate the optimal route. Specifically, it sends an API request, analyzes the returned data, and generates the optimal route. The calculation result is returned to the terminal in JSON format.

[0286] Step 4:

[0287] The server returns the calculation results to the device. The server returns the calculated route information to the device using an HTTP response. The output data includes detailed route information, distance, estimated time, etc. The device analyzes the received data and prepares it for display to the user.

[0288] Step 5:

[0289] The device displays the route to the user. The device then displays the received route information on the app screen. Specifically, the device displays a map and draws the optimal route on the map. The user then starts running according to this route.

[0290] Step 6:

[0291] The user starts running according to the route. The user starts running according to the route displayed on the device. Specifically, the user runs while following the audio and visual guides of the app.

[0292] Step 7:

[0293] The device transmits the user's movement information to the server. The device periodically transmits the user's GPS data to the server. Specifically, it transmits the current location information to the server every minute. The input data includes the user's current location and movement route.

[0294] Step 8:

[0295] The server stores the movement information in a database. The server stores the received GPS data in a SQL or NoSQL database. Specifically, it stores the data using an INSERT statement. The stored data is later used for analysis and provision to companies.

[0296] Step 9:

[0297] The server provides companies with people flow data. The server analyzes the stored movement information and provides it to companies. Specifically, the server exports the data in CSV format and sends it to companies. Companies can use this data to target advertisements.

[0298] (Application example 3)

[0299] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0300] Conventional running applications lack the functionality to suggest optimal routes based on the target distance set by the user. In addition, there is no mechanism to effectively utilize the user's exercise data and generate data for companies to deliver targeted advertisements. This leads to issues such as the inability to fully utilize the convenience for users and the marketing effectiveness of companies.

[0301] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0302] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for collecting the user's exercise data, anonymizing it and providing it to a company, and a means for generating data for a company to deliver targeted advertisements. This not only allows the user to receive suggestions for the optimal running route, but also enables a company to deliver effective targeted advertisements based on the collected data.

[0303] A "destination" refers to a specific location a user wants to reach.

[0304] "Target exercise intensity" refers to the exercise intensity or load that the user wants to achieve.

[0305] "Generative AI" refers to artificial intelligence technology that generates optimal suggestions based on user input information.

[0306] "Interaction style" refers to the way in which a user and a system exchange information with each other.

[0307] "Location information" refers to data that indicates a user's current location.

[0308] "Exercise Data" refers to information relating to a User's exercise (distance, time, route, etc.).

[0309] "Anonymization" refers to processing data so that individuals cannot be identified.

[0310] "Enterprise" refers to a legal entity or organization that provides goods or services.

[0311] "Targeted advertising" refers to advertising that is delivered to a specific demographic.

[0312] "Means of generating data" refers to the methods and techniques that create the data needed for a specific purpose.

[0313] "Subscription format" refers to a format in which a service can be used by paying a periodic fee.

[0314] "Smartphone application" refers to a software program that runs on a smartphone.

[0315] A system for implementing this invention includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for collecting the user's exercise data, anonymizing it and providing it to companies, and a means for generating data for companies to deliver targeted advertisements.

[0316] Hardware and Software Configuration

[0317] Hardware: Smartphone (iOS or Android)

[0318] Software: Python, Requests library, JSON library

[0319] Data processing and calculation

[0320] 1. User input: The user uses the smartphone application to input a destination or target exercise intensity.

[0321] 2. Use of generative AI: The server uses generative AI based on the user's input information to interactively suggest the optimal running route.

[0322] 3. Obtaining location information: The user's current location is obtained using the smartphone's GPS function.

[0323] 4. Collection of athletic data: User running data (distance, time, route, etc.) is collected and anonymized.

[0324] 5. Data provision: The collected exercise data is provided to companies, which then use this data to deliver targeted advertisements.

[0325] Examples

[0326] A user opens the smartphone app and enters their goal of "running 5km." The app then suggests the best route based on the user's current location. After the run, the app collects the user's running data, anonymizes it, and provides it to companies. Sporting goods stores use this data to deliver advertisements for running shoes to the user.

[0327] Examples of prompt statements

[0328] If a user inputs a goal of "running 5km", the AI ​​should suggest the best route to run 5km from the user's current location. Also, implement a function to collect the user's movement information as people flow data and provide it to companies.

[0329] In this way, not only can users receive recommendations for optimal running routes, but companies can also use the collected data to deliver targeted advertising.

[0330] The flow of the specific process in the application example 3 will be described with reference to FIG.

[0331] Step 1:

[0332] The user opens the smartphone application and inputs a destination or a target exercise intensity.

[0333] Input: Destination or target exercise intensity

[0334] Output: User input information

[0335] Specific actions: The user enters the destination or target exercise intensity into the app's input form and presses the submit button.

[0336] Step 2:

[0337] The server receives the user's input information and uses generative AI to interactively suggest the optimal running route.

[0338] Input: User input information

[0339] Output: Optimal running route

[0340] Specific operation: The server inputs the user's input information as prompts into the generative AI model and generates the optimal running route.

[0341] Step 3:

[0342] The device obtains the user's current location using the smartphone's GPS function.

[0343] Input: None (GPS function activation)

[0344] Output: User's current location

[0345] Specific operations: The device activates the GPS function, obtains the user's current location, and sends it to the server.

[0346] Step 4:

[0347] The server combines the user's current location information with the optimal running route and presents the route to the user.

[0348] Input: User's current location, optimal running route

[0349] Output: The running route presented to the user.

[0350] Specific operation: The server combines the current location information with the generated route and sends the route information to the user's smartphone.

[0351] Step 5:

[0352] The user starts running, and the device collects running data (distance, time, route) in real time.

[0353] Input: User's running data

[0354] Output: Collected running data

[0355] Specific operation: The device uses GPS and timer functions to record the user's running data in real time.

[0356] Step 6:

[0357] The server receives the collected running data, anonymizes it, and provides it to the company.

[0358] Input: Collected running data

[0359] Output: Anonymized running data

[0360] What it does: The server anonymizes the running data and sends it to the company's database.

[0361] Step 7:

[0362] Companies will generate targeted advertisements based on anonymized running data and deliver them to users.

[0363] Input: Anonymized running data

[0364] Output: Targeted ads

[0365] How it works: The company analyzes the data it receives, generates advertisements based on the user's interests and behavior, and delivers them to the user's smartphone.

[0366] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0367] "Example 1"

[0368] As one embodiment of the present invention, there is a system that combines an emotion engine that recognizes the user's emotions. In this system, when the user inputs a destination or a target exercise intensity, the generative AI automatically suggests a destination in a dialogue format based on the input information. Furthermore, the system acquires the user's location information and sells the information to companies as people flow data. An emotion engine that recognizes the user's emotions is also built in. This emotion engine recognizes emotions from the user's voice, facial expression, text input, etc., and the generative AI suggests a destination based on the emotion. Specifically, if the user inputs "running 5km" as a goal and the emotion of joy is recognized at that time, the AI ​​will take that emotion into consideration and suggest a running course around a beautiful park, for example.

[0369] "Example 2"

[0370] In another embodiment of the present invention, an emotion engine recognizes the user's emotion, and a generative AI suggests exercise intensity based on the emotion. Specifically, if the user expresses an emotion such as "I want to relieve stress," the AI ​​takes the emotion into account and suggests high-intensity exercise, for example.

[0371] "Example 3"

[0372] Furthermore, as another embodiment of the present invention, there is a system in which an emotion engine recognizes the emotion of a user, a generative AI suggests a destination based on that emotion, and based on that suggestion, the user's movement information is provided to a company as people flow data. Specifically, if a user expresses an emotion of "wanting to relax," the AI ​​takes that emotion into consideration and suggests, for example, a quiet cafe, and provides the user's movement information to the owner of the cafe or restaurant.

[0373] The process flow of each embodiment will be described below.

[0374] "Example 1"

[0375] Step 1: The user enters their destination or target exercise intensity into the app.

[0376] Step 2: Based on the input information, the generative AI automatically suggests destinations in an interactive format.

[0377] Step 3: Obtain user location information and sell that information to companies as people flow data.

[0378] Step 4: The emotion engine recognizes emotions from the user's voice, facial expressions, text input, etc.

[0379] Step 5: Generative AI suggests destinations based on the recognized emotions.

[0380] "Example 2"

[0381] Step 1: The emotion engine recognizes the user's emotion.

[0382] Step 2: Based on the recognized emotions, the generative AI suggests exercise intensity.

[0383] "Example 3"

[0384] Step 1: The emotion engine recognizes the user's emotion.

[0385] Step 2: Generative AI suggests destinations based on the recognized emotions.

[0386] Step 3: The user navigates based on the suggestion.

[0387] Step 4: User movement information is provided to companies as people flow data.

[0388] Example 1

[0389] Next, a description will be given of Example 1 of the embodiment 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".

[0390] In conventional systems, when users input their destination and exercise intensity, it was difficult to provide optimal suggestions that took into account their emotions and location information at the time. In addition, there were limited ways to effectively utilize users' location information, so it could not be used effectively when providing data to companies. This meant that improvements to the user experience and effective use of data were not fully achieved.

[0391] 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.

[0392] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for recognizing the user's emotion, and a means for optimizing the destination based on the recognized emotion information. This makes it possible to suggest an optimal destination taking into account the user's emotion and location information, improving the user experience and enabling effective use of data provided to companies.

[0393] "User" refers to an individual who uses the system to input their destination and exercise intensity and receive suggestions.

[0394] "Destination" refers to the place or location the user wants to reach.

[0395] "Exercise intensity" refers to the strength or amount of exercise that a user aims for.

[0396] "Generative AI" refers to artificial intelligence that automatically suggests destinations in an interactive format based on information entered by the user.

[0397] "Interaction style" refers to the way in which a user and a system exchange information with each other.

[0398] "Location Information" means data that indicates a User's current geographic location.

[0399] "Emotion" refers to the psychological state recognized from the user's voice, facial expressions, text input, etc.

[0400] "Emotion engine" refers to software or hardware for recognizing a user's emotions.

[0401] "Optimization" refers to the process of selecting the most suitable destination based on user input and sentiment information.

[0402] "People flow data" refers to data that aggregates user location information, anonymizes it, and provides it to companies.

[0403] "Subscription format" refers to a format in which a service can be used by paying a periodic fee.

[0404] "Smartphone application" refers to software that runs on a smartphone.

[0405] This invention is a system realized as a smartphone application. The user inputs the destination or the target exercise intensity through the application. The input information is sent to a generative AI, which automatically suggests destinations in an interactive format. The suggestions are optimized based on the user's input information, providing results tailored to the user's needs.

[0406] The system uses the following major hardware and software:

[0407] 1. Smartphone: A device on which a user runs applications.

[0408] 2. Generative AI: Artificial intelligence that suggests optimal destinations based on user input. Specifically, we use OpenAI's GPT-4.

[0409] 3. Emotion engine: Software that recognizes emotions from the user's voice, facial expressions, and text input. Specifically, it uses Microsoft's Azure Cognitive Services.

[0410] The user launches the application and inputs the destination or the target exercise intensity. For example, the user inputs a goal of "running 5km." This input information is sent to the generative AI within the application. The generative AI suggests the optimal destination based on the information input by the user. At this time, the user's location information is also obtained, and this information is sold to companies as people flow data.

[0411] In addition, the emotion engine recognizes emotions from the user's voice, facial expressions, text input, etc. For example, if a user inputs "5km run" and the emotion of joy is recognized, the generative AI will take that emotion into account and suggest a running course around a beautiful park.

[0412] For example, a user launches the application and inputs a goal of "running 5km." If the user inputs this with a smile, the emotion engine recognizes the emotion of joy. Based on this information, the generative AI suggests a running course around a beautiful park.

[0413] Example prompt:

[0414] If a user inputs a goal of "running 5km" and recognizes the emotion of joy, suggest the best running course.

[0415] In this way, a system is created in which generative AI suggests optimal destinations based on the user's input information and emotions.

[0416] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0417] Step 1:

[0418] The user launches an application.

[0419] Specifically, a user taps an application icon on their smartphone to launch the application, and an input screen is displayed.

[0420] Input: None

[0421] Output: Application home screen

[0422] Step 2:

[0423] The user inputs a destination or target exercise intensity.

[0424] As a specific action, the user inputs a destination or exercise intensity, such as "5km run," into an input field.

[0425] Input: User input information (e.g. "5km run")

[0426] Output: Input information is saved within the application

[0427] Step 3:

[0428] The terminal sends the input information to the generative AI.

[0429] Specifically, the device sends the user's input information to the server, which then passes it on to the generative AI.

[0430] Input: User input information

[0431] Output: Input information passed to the generative AI

[0432] Step 4:

[0433] The server uses generative AI to suggest the optimal destination.

[0434] Specifically, the server uses generative AI (e.g. GPT-4) to generate the best destination based on the user's input. For example, for a "5km run," it will suggest a running course around a beautiful park.

[0435] Input: Input information passed to the generative AI

[0436] Output: Optimal destination suggestions

[0437] Step 5:

[0438] The device obtains the user's location information.

[0439] Specifically, the terminal uses its GPS function to obtain the user's current location and transmits that information to the server.

[0440] Input: None

[0441] Output: User's location

[0442] Step 6:

[0443] The server sells the location information to companies as people flow data.

[0444] Specifically, the location information acquired by the server is processed as people flow data, anonymized, and sold to companies.

[0445] Input: User's location

[0446] Output: People flow data sold to businesses

[0447] Step 7:

[0448] The terminal recognizes the user's emotions.

[0449] Specifically, the device uses an emotion engine (e.g., Azure Cognitive Services) to recognize emotions from the user's voice, facial expressions, and text input. For example, if a user types "5km run" with a smile, the emotion of joy is recognized.

[0450] Input: User voice, facial expressions, and text input

[0451] Output: Recognized emotion information

[0452] Step 8:

[0453] The server optimizes the destination based on emotion information.

[0454] Specifically, the server optimizes the destinations proposed by the generative AI based on the emotion information sent from the emotion engine. For example, if the emotion of joy is recognized, it will suggest a running course with a beautiful view.

[0455] Input: Recognized emotion information, generative AI suggestions

[0456] Output: Optimized destination suggestions

[0457] Step 9:

[0458] The terminal presents the optimized destination to the user.

[0459] In particular, the terminal displays the optimized destinations to the user, and the user can review and select the suggested destinations.

[0460] Input: Optimized destination suggestions

[0461] Output: The optimized destination presented to the user.

[0462] (Application example 1)

[0463] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0464] Conventional food delivery systems have difficulty in suggesting optimal restaurants and menus based on the user's food type and calorie goal. In addition, suggestions do not take into account the user's emotions, which may result in lower user satisfaction. Furthermore, there is a lack of effective ways to utilize the user's location information, making it difficult to provide people flow data for businesses.

[0465] The identification process by the identification processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for recognizing the user's emotions, and a means for adjusting the content of the proposal based on the recognized emotions. This makes it possible to suggest optimal restaurants and menus based on the user's type of food and calorie goals, and further, by making suggestions that take the user's emotions into consideration, user satisfaction is improved. In addition, by effectively utilizing the user's location information, it becomes possible to provide people flow data for companies.

[0466] "User" means an individual or organization that uses the System.

[0467] "Destination" refers to the place the user wants to reach.

[0468] "Exercise intensity" refers to the strength or amount of exercise that the user aims for.

[0469] "Generative AI" is an artificial intelligence system that generates suggestions in an interactive format based on input information.

[0470] An "interactive" style is one in which the user and the system exchange information with each other.

[0471] "Location Information" is data that indicates a user's current geographic location.

[0472] "Means of recognizing emotions" refers to technology that identifies emotions from a user's voice, facial expressions, text input, etc.

[0473] "Means for adjusting the content of suggestions" refers to the function by which the generative AI optimizes the content of suggestions based on recognized emotions.

[0474] "People flow data" is data that is compiled and analyzed from users' location information.

[0475] "Means for selling to businesses" refers to methods and systems for providing collected people flow data to businesses.

[0476] A "subscription format" is a format in which a service can be used by paying a periodic fee.

[0477] A "smartphone application" is a software program that runs on a smartphone.

[0478] As an embodiment of the present invention, a food delivery system using a smartphone application will be described as an example.

[0479] System Configuration

[0480] The system consists of the following main components:

[0481] 1. User device: A smartphone with the smartphone application installed.

[0482] 2. Server: A server equipped with a generative AI and emotion recognition engine.

[0483] 3. Database: A database that stores restaurant information, menu information, and user information.

[0484] Program Processing

[0485] User Device

[0486] The user terminal provides an interface for users to input their food type and calorie goal. Once the user completes the input, the information is sent to the server. Data is also collected to recognize emotions through the user's voice, facial expressions, and text input.

[0487] server

[0488] The server does the following:

[0489] 1. Generative AI: Receives user input information (type of food, calorie goal) and suggests optimal restaurants and menus in an interactive format. Generative AI such as OpenAI's "GPT-3 (registered trademark)" is used.

[0490] 2. Emotion recognition engine: Recognizes emotions from the user's voice, facial expressions, and text input. Google Cloud's "Cloud Speech-to-Text" and "Cloud Vision API" are used as emotion recognition engines.

[0491] 3. Tailored suggestions: Based on the recognized emotion, generative AI will optimize the suggestions. For example, if the user expresses the emotion of “happiness,” it will provide more positive suggestions.

[0492] Database

[0493] The database stores restaurant information, menu information, and user information, allowing the server to quickly retrieve required information.

[0494] Examples

[0495] If a user opens a smartphone application, enters "Japanese food" and "500 kcal," and the emotion recognition engine recognizes "joy," the generative AI will generate a prompt like this:

[0496] A user wants Japanese food and has a calorie goal of 500kcal. The emotion is joy. Suggest the best restaurant and menu.

[0497] Based on this prompt, the generative AI will suggest healthy menu items under 500 kcal at a nearby delicious Japanese restaurant.

[0498] Hardware and Software

[0499] User device: Smartphone (iOS or Android)

[0500] Server: High-performance cloud server (e.g. Amazon Web Services, Google Cloud Platform)

[0501] Generative AI: OpenAI's "GPT-3"

[0502] Emotion recognition engine: Google Cloud's "Cloud Speech-to-Text" and "Cloud Vision API"

[0503] Database: Relational database (e.g. MySQL, PostgreSQL)

[0504] In this way, a system can be created that provides an optimal food delivery experience based on the user's needs and emotions.

[0505] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0506] Step 1:

[0507] A user opens a smartphone application and inputs the type of meal (e.g., Japanese, Western, Chinese) and the calorie goal. The input information is sent from the user's terminal to the server. The input data is the type of meal and the calorie goal.

[0508] Step 2:

[0509] The user terminal collects emotion data through the user's voice, facial expression, and text input. The collected emotion data is sent from the user terminal to the server. The input data is voice, facial expression, and text input.

[0510] Step 3:

[0511] The server uses an emotion recognition engine to recognize the user's emotions from the received voice, facial expressions, and text input. Google Cloud's "Cloud Speech-to-Text" and "Cloud Vision API" are used as emotion recognition engines. The input data are voice, facial expressions, and text input, and the output data is the recognized emotion.

[0512] Step 4:

[0513] The server generates a prompt sentence for the generative AI based on the user's input information (type of meal, calorie goal) and the recognized emotion. OpenAI's "GPT-3" is used as the generative AI. The input data is the type of meal, calorie goal, and recognized emotion, and the output data is the prompt sentence.

[0514] Step 5:

[0515] The server sends the prompt to the generative AI, which generates optimal restaurant and menu suggestions. The generative AI generates suggestions based on the prompt. The input data is the prompt, and the output data is the suggested restaurants and menus.

[0516] Step 6:

[0517] The server sends the suggested restaurants and menus to the user terminal. The user terminal displays the suggestions to the user. The input data are the suggested restaurants and menus, and the output data are the suggestions displayed to the user.

[0518] Step 7:

[0519] The user selects a suggested restaurant and menu and confirms the order. The user terminal sends the order information to the server. The input data is the user's selection and the order information.

[0520] Step 8:

[0521] The server obtains the user's location information and optimizes the delivery options. The location information is obtained from the user's terminal. The input data is the user's location information, and the output data is the optimized delivery options.

[0522] Step 9:

[0523] The server sells the user's location information to companies as people flow data. The input data is the user's location information, and the output data is the people flow data provided to companies.

[0524] In this way, a system can be created that provides an optimal food delivery experience based on the user's needs and emotions.

[0525] Example 2

[0526] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0527] Conventional systems not only collected users' location information, but also had limited means of effectively utilizing that information. In addition, there were no systems that suggested appropriate exercise intensity based on the user's emotions. This made it difficult to provide personalized services that met the needs of users. Furthermore, there were issues with data processing and provision methods when selling the acquired location information to companies.

[0528] 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.

[0529] In this invention, the server includes a means for acquiring user location information, a means for transmitting the acquired location information to the server through a data collection application, a means for the server to collect the location information received and process it as people flow data, a means for an emotion recognition engine to recognize the user's emotion, a means for transmitting the recognized emotion data to a generative AI, a means for the generative AI to suggest an exercise intensity based on the emotion data, and a means for notifying the user of the suggested exercise intensity. This makes it possible to effectively utilize the user's location information and sell it to companies, as well as to make personalized exercise suggestions based on the user's emotion.

[0530] "User location information" means the latitude and longitude data of the user's current location.

[0531] A "data collection application" is software that obtains a user's location information and transmits it to a server.

[0532] A "server" is a computer system for receiving, processing and storing data.

[0533] "People flow data" is data that compiles the number and trends of users in a specific location at a specific time.

[0534] An "emotion recognition engine" is software that analyzes a user's facial expressions and tone of voice to recognize emotions.

[0535] "Generative AI" is artificial intelligence that makes appropriate suggestions or generates results based on input data.

[0536] "Exercise intensity" is an indicator of the strength or load of exercise.

[0537] A "notification means" is a method or device for conveying information to a user.

[0538] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0539] This invention includes a system that acquires users' location information and sells it to companies as people flow data, and a system in which an emotion engine recognizes the user's emotions and a generative AI suggests exercise intensity.

[0540] Hardware and Software Used

[0541] Hardware:

[0542] User's smartphone

[0543] Wearable devices (e.g. smart watches)

[0544] software:

[0545] Smartphone GPS function

[0546] Data Collection Applications

[0547] Data Processing Server

[0548] Emotion Recognition Engine

[0549] Generative AI

[0550] Exercise suggestion application

[0551] Data processing and calculation

[0552] Get the user's location:

[0553] The user's smartphone uses the GPS function to obtain current location information. Specifically, the smartphone's GPS sensor receives signals from satellites and calculates latitude and longitude. For example, if a user is in a shopping mall, the smartphone's GPS identifies the location and obtains latitude 35.6895 and longitude 139.6917 (for Tokyo).

[0554] Location transmission:

[0555] The data collection application sends the acquired location information to a server. Specifically, the smartphone sends the location information to the server via an Internet connection. For example, the smartphone sends location information (latitude 35.6895, longitude 139.6917) to the server in real time.

[0556] Generating people flow data:

[0557] The server collects the location information it receives and processes it as people flow data. Specifically, the server collects the number of users at a specific location during a specific time period and generates statistical data. For example, the server collects the number of users at a shopping mall every hour and generates data such as "1,000 people visited between 12:00 and 13:00."

[0558] Enterprise data provider:

[0559] The processed foot traffic data is provided to companies. Specifically, the server displays the statistical data generated by the server on the company's dashboard or provides it through an API. For example, the server displays "shopping mall foot traffic data" on an advertising agency's dashboard so that the company can view it.

[0560] User emotion recognition:

[0561] The emotion recognition engine recognizes the user's emotions. Specifically, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice. For example, when a user speaks into the smartphone's camera, the emotion recognition engine determines that the user is "stressed."

[0562] Sending emotion data:

[0563] The recognized emotion data is sent to the generative AI. Specifically, the smartphone sends the emotion data to the generative AI server via the internet. For example, the smartphone sends emotion data such as "I feel stressed" to the server.

[0564] Exercise intensity suggestions:

[0565] The generative AI suggests exercise intensity based on emotion data. Specifically, the generative AI analyzes emotion data and calculates appropriate exercise intensity. For example, the generative AI suggests high-intensity exercise (e.g. 30 minutes of jogging) in response to the emotion "I want to relieve stress."

[0566] Proposal Notification:

[0567] Notify the user of the suggested exercise intensity. Specifically, the smartphone notification function is used to display the exercise suggestion to the user. For example, the smartphone displays a notification to the user saying, "We recommend that you jog for 30 minutes."

[0568] Examples

[0569] Example prompt:

[0570] "Get user location information and generate shopping mall traffic data."

[0571] "Suggest an appropriate exercise intensity for users when they are feeling stressed."

[0572] The above is an embodiment of the present invention.

[0573] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0574] Step 1:

[0575] Getting the user's location

[0576] Input: The user's smartphone uses the GPS to obtain their current location.

[0577] Data processing and calculation: The smartphone's GPS sensor receives signals from satellites and calculates latitude and longitude.

[0578] Output: Latitude and longitude data (e.g. 35.6895 latitude, 139.6917 longitude).

[0579] What happens: If a user is in a shopping mall, the smartphone's GPS will determine its location and obtain latitude 35.6895 and longitude 139.6917 (for Tokyo, for example).

[0580] Step 2:

[0581] Sending location information

[0582] Input: The acquired location information (latitude and longitude data).

[0583] Data processing and calculation: The data collection application sends the location information to a server via an Internet connection.

[0584] Output: The location sent to the server.

[0585] Specific operation: The smartphone sends location information (latitude 35.6895, longitude 139.6917) to the server in real time.

[0586] Step 3:

[0587] Generating people flow data

[0588] Input: The location information received by the server.

[0589] Data processing and calculation: The server compiles the number of users in a specific location at a specific time and generates statistical data.

[0590] Output: People flow data (e.g. "1000 people visited between 12:00-13:00").

[0591] Specific operation: The server counts the number of users in the shopping mall every hour and generates data such as "1,000 people visited between 12:00 and 13:00."

[0592] Step 4:

[0593] Providing data for businesses

[0594] Input: Processed people flow data.

[0595] Data processing and calculation: The statistical data generated by the server is displayed on the company's dashboard or provided via API.

[0596] Output: People flow data available to businesses.

[0597] What it does: The server displays "shopping mall foot traffic data" on the ad agency's dashboard, making it available for companies to view.

[0598] Step 5:

[0599] User emotion recognition

[0600] Input: The user's facial expressions and tone of voice.

[0601] Data processing and calculation: The emotion recognition engine analyzes the user's facial expressions and tone of voice to recognize emotions.

[0602] Output: Recognized emotion data (e.g. "I feel stressed").

[0603] How it works: When a user speaks into their smartphone's camera, the emotion recognition engine determines that they are "stressed."

[0604] Step 6:

[0605] Sending emotion data

[0606] Input: Recognized emotion data.

[0607] Data processing and calculation: The smartphone sends emotion data via the internet to the generative AI server.

[0608] Output: The emotion data sent to the server.

[0609] Specific operation: The smartphone sends emotional data indicating "feeling stressed" to the server.

[0610] Step 7:

[0611] Exercise intensity suggestions

[0612] Input: emotion data.

[0613] Data processing and calculation: Generative AI analyzes emotion data and calculates appropriate exercise intensity.

[0614] Output: Suggested exercise intensity (e.g. "30 minutes of jogging").

[0615] Specific behavior: In response to the emotion of "wanting to relieve stress," the generative AI suggests high-intensity exercise (e.g. 30 minutes of jogging).

[0616] Step 8:

[0617] Proposal Notification

[0618] Input: Suggested exercise intensity.

[0619] Data processing and calculation: Use the smartphone's notification function to display exercise suggestions to the user.

[0620] Output: Exercise suggestions notified to the user.

[0621] What happens: The phone displays a notification to the user saying, "We recommend you go for a 30 minute jog."

[0622] (Application example 2)

[0623] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0624] Conventional advertising systems display uniform advertisements without considering the user's location information or emotions, which results in many advertisements that do not match the user's interests. In addition, because advertisements are not optimized based on the user's emotions, there is also the issue of reduced advertising effectiveness.

[0625] 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.

[0626] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using a generative AI based on the input information, a means for acquiring the user's location information, a means for recognizing the user's emotions, a means for the generative AI to optimize advertisements based on the recognized emotions, and a means for displaying the optimized advertisements to the user. This makes it possible to display optimal advertisements in real time based on the user's location information and emotions.

[0627] "Destination" refers to the specific location to which a User wishes to travel.

[0628] "Exercise intensity" refers to the level of strength or load of the exercise performed by a user.

[0629] "Generative AI" refers to artificial intelligence that makes suggestions or generates ideas in an interactive format based on input information.

[0630] "Interaction style" refers to the way in which a user and a system exchange information with each other.

[0631] "Location Information" refers to geographic data that indicates a User's current location.

[0632] "Means of recognizing emotions" refers to technology that detects emotions from the user's facial expressions, voice, etc.

[0633] "Means of optimizing advertising" refers to technology that selects the most appropriate advertisement based on the user's location information and emotions.

[0634] An "optimized ad" is an ad that best suits the user's current situation and emotions.

[0635] "Subscription format" refers to a format in which a service can be used by paying a periodic fee.

[0636] "Smartphone application" refers to software that runs on a smartphone.

[0637] The system for implementing this invention utilizes the user's smartphone as the main hardware. The system includes the following main components:

[0638] 1. A means for the user to input a destination or target exercise intensity:

[0639] Users input their destination and exercise intensity through a smartphone application, which then transmits the user's desired destination and exercise intensity to the system.

[0640] 2. A means to automatically suggest destinations in a dialogue format using generative AI:

[0641] Based on the input information, generative AI (e.g. OpenAI GPT-4) will interactively suggest the best destination for the user, allowing the user to select a destination that best suits their needs.

[0642] 3. How to obtain user location information:

[0643] Use the smartphone's GPS function to obtain the user's current location. Use a location information acquisition library such as Google Maps API.

[0644] 4. How to recognize user emotions:

[0645] Using the smartphone camera and microphone, it recognizes emotions from the user's facial expressions and voice, using emotion recognition libraries such as Microsoft Azure Face API and Google Cloud Speech-to-Text.

[0646] 5. How generative AI can optimize ads based on perceived emotions:

[0647] Based on the acquired location information and emotion data, generative AI selects the optimal ad, which is best suited to the user's current situation and emotions.

[0648] 6. How to display optimized ads to users:

[0649] The optimized ads are then displayed to users through smartphone applications, allowing users to see ads that are tailored to their interests.

[0650] Hardware and Software Used

[0651] Hardware: Smartphone (GPS function, camera, microphone)

[0652] software:

[0653] GPS data acquisition library (e.g. Google Maps API)

[0654] Emotion recognition libraries (e.g. Microsoft Azure Face API, Google Cloud Speech-to-Text)

[0655] Generative AI models (e.g. OpenAI GPT-4)

[0656] Examples

[0657] Let's say a user is in a shopping mall. The smartphone's GPS function acquires location information, and the emotion recognition system detects that the user is "having fun." Based on this information, the generative AI proposes "advertisements for new fashion items" and displays them on the user's smartphone.

[0658] Examples of prompt statements

[0659] User location: Shopping mall

[0660] User sentiment: Enjoying it

[0661] Suggested Ad: New Fashion Items

[0662] In this way, ads can be served in real time that best suit the user's current situation and emotions.

[0663] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0664] Step 1:

[0665] The user starts the smartphone application and inputs the destination or the target exercise intensity. The input information is sent to the server. The input data includes the name of the destination and the level of exercise intensity.

[0666] Step 2:

[0667] The server uses a generative AI based on the input information to interactively suggest the best destination to the user. The generative AI analyzes the user's input data and generates appropriate destinations. The generated destination candidates are sent to the user's smartphone.

[0668] Step 3:

[0669] The user's smartphone acquires the current location using the GPS function. The acquired location information is sent to the server. The location information includes latitude and longitude data.

[0670] Step 4:

[0671] The server uses the smartphone's camera and microphone to recognize the user's emotions. It analyzes facial expression data captured by the camera and voice data recorded by the microphone using an emotion recognition library (e.g. Microsoft Azure Face API, Google Cloud Speech-to-Text) to identify the user's emotions. The recognized emotion data is stored on the server.

[0672] Step 5:

[0673] The server uses a generative AI to select the optimal advertisement based on the acquired location information and emotion data. The generative AI analyzes the location information and emotion data to generate an advertisement that is most suitable for the user's current situation and emotion. The generated advertisement data is sent to the user's smartphone.

[0674] Step 6:

[0675] The user's smartphone displays optimized advertisements that match the user's interests and concerns, enhancing the user's experience.

[0676] In this way, optimal ads can be served in real time based on the user's location and emotions.

[0677] Example 3

[0678] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0679] Conventional systems lack the functionality to suggest optimal routes and destinations based on the goals and emotions set by the user. In addition, the means to effectively collect user movement information and provide it to companies are limited. This makes it difficult to make personalized suggestions according to user needs, and companies are also unable to carry out effective marketing such as targeted advertising.

[0680] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0681] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using a generative AI based on the input information, a means for acquiring the user's location information, a means for recognizing the user's emotions, a means for the generative AI to suggest a destination based on the recognized emotions, a means for collecting the user's movement information, and a means for providing the collected movement information to a company. This enables personalized suggestions based on the user's goals and emotions, and allows companies to carry out effective marketing such as targeted advertising.

[0682] "User" refers to an individual who uses the system to input their destination and exercise intensity and receive suggestions.

[0683] A "destination" refers to the place or location a user wants to reach.

[0684] "Exercise intensity" refers to the level of difficulty or load of the exercise set by the user.

[0685] "Generative AI" refers to artificial intelligence that automatically generates and suggests destinations and routes in an interactive format based on input information.

[0686] "Location information" refers to latitude and longitude data that indicates a user's current location.

[0687] "Emotion" refers to the psychological state or mood exhibited by a user.

[0688] "Means of recognizing emotions" refers to technology that analyzes and recognizes emotions from user input and actions.

[0689] "Movement information" refers to data that indicates changes in a user's route or location when they move.

[0690] "Company" refers to a legal entity that uses user movement information for marketing and targeted advertising.

[0691] A "subscription format" refers to a business model in which a service can be used on an ongoing basis by paying a periodic fee.

[0692] A "mobile information terminal application" refers to software that runs on a mobile information terminal such as a smartphone or tablet.

[0693] This invention is a system that proposes optimal routes and destinations based on the goals and emotions set by a user, and provides the travel information to companies. A specific embodiment of this system will be described below.

[0694] System Configuration

[0695] This system consists of terminals used by users, servers that process data, and external companies. The terminals are mobile information terminals such as smartphones and tablets, and the servers are located on the cloud. The system has the following main functions:

[0696] 1. A means for the user to input a destination or target exercise intensity

[0697] Through a smartphone application, users input their destination and exercise intensity, for example, a goal such as "I want to run 5km" or "I want to relax."

[0698] 2. A means to automatically suggest destinations in a dialogue format using generative AI based on input information

[0699] The server receives the input information and uses a generative AI model to generate optimal destinations and routes. The generative AI model generates prompts based on the user's input and makes suggestions in a dialogue format.

[0700] 3. How to obtain user location information

[0701] The device uses the GPS sensor to obtain the user's current location, which is then sent to the server.

[0702] 4. How to Recognize User Emotions

[0703] The server uses an emotion engine to recognize emotions from the user's input and actions. For example, it analyzes the user's emotion from the input "I want to relax."

[0704] 5. How generative AI can suggest destinations based on perceived emotions

[0705] Based on the recognized emotions, the server uses a generative AI model to suggest appropriate destinations, for example a quiet cafe for a user who wants to relax.

[0706] 6. Means of collecting user movement information

[0707] The device collects user movement information using a GPS sensor, and the collected movement information is sent to a server.

[0708] 7. Means of providing collected mobility information to companies

[0709] The server stores the collected movement information in a database and provides it to companies, who use the data for targeted advertising and marketing.

[0710] Examples

[0711] Example of a goal-based route suggestion

[0712] A user enters a goal of "run 5km."

[0713] The server uses the Google Maps API to calculate the optimal route and send it back to the device.

[0714] The device will show the user a 5km route from home via the park and back.

[0715] Examples of emotion-based destination suggestions

[0716] The user types "I want to relax" into the device.

[0717] The server recognizes this emotion using an emotion engine and suggests destinations using generative AI.

[0718] The device will show the user "quiet cafes nearby."

[0719] Examples of prompt statements

[0720] "I want to do a 5km run. What is the best route?"

[0721] "I want to relax. Can you recommend some places?"

[0722] This system proposes optimal routes and destinations based on the user's goals and emotions, and provides the travel information to companies, enabling use in targeted advertising, etc. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0723] Step 1:

[0724] The user enters a goal.

[0725] Input: The user inputs a goal, such as "run 5km" or "I want to relax," through a smartphone application.

[0726] Specific behavior: A user opens the app, enters a goal in the text box, and presses the submit button.

[0727] Output: The entered target data is saved to the terminal.

[0728] Step 2:

[0729] The device transmits the goal to the server.

[0730] Input: The target data entered in step 1.

[0731] Specific operations: The terminal generates an HTTP request and sends the target data to the server.

[0732] Output: The server receives the target data.

[0733] Step 3:

[0734] The server calculates the optimal route.

[0735] Input: The target data received by the server.

[0736] Specific operation: The server sends a request to the Google Maps API to calculate the optimal route for driving within a distance of 5km from the user's current location.

[0737] Output: The calculated route data is saved on the server.

[0738] Step 4:

[0739] The server sends the calculation results back to the terminal.

[0740] Input: The route data calculated in step 3.

[0741] Specific operation: The server generates an HTTP response and sends route data to the terminal.

[0742] Output: The device receives the route data.

[0743] Step 5:

[0744] The device displays the route to the user.

[0745] Input: The route data received in step 4.

[0746] Specific operation: The device analyzes the route data and uses a map application to show the user a "5km route from home via the park and back."

[0747] Output: The user can visually see the optimal route.

[0748] Step 6:

[0749] The terminal collects movement information.

[0750] Input: The user's location.

[0751] Specific operation: The device records latitude and longitude information at regular intervals using the GPS sensor.

[0752] Output: The collected movement information is stored on the device.

[0753] Step 7:

[0754] The terminal transmits movement information to the server.

[0755] Input: Movement information collected in step 6.

[0756] Specific operation: The terminal generates an HTTP POST request and sends the movement information to the server.

[0757] Output: The server receives the movement information.

[0758] Step 8:

[0759] The server provides the travel information to the enterprise.

[0760] Input: The movement information received in step 7.

[0761] How it works: The server stores movement information in a database and provides the data through an API that companies can access.

[0762] Output: Businesses can obtain movement information and use it for targeted advertising and marketing.

[0763] Step 9:

[0764] The user inputs the emotion.

[0765] Input: The user inputs emotions such as "I want to relax" through a smartphone application.

[0766] Specific behavior: A user opens the app, enters their emotion in the text box, and presses the send button.

[0767] Output: The input emotion data is saved on the device.

[0768] Step 10:

[0769] The device transmits the emotion to the server.

[0770] Input: Emotion data entered in step 9.

[0771] Specific operation: The device generates an HTTP request and sends emotion data to the server.

[0772] Output: The server receives the emotion data.

[0773] Step 11:

[0774] The server recognizes the emotion.

[0775] Input: Emotion data received in step 10.

[0776] Specific operation: The server uses an emotion analysis algorithm to analyze the input data and recognize the user's emotion.

[0777] Output: The recognized emotion data is stored on the server.

[0778] Step 12:

[0779] The server suggests destinations.

[0780] Input: Emotion data recognized in step 11.

[0781] How it works: The server uses a generative AI model to suggest destinations (such as a quiet cafe) based on the user's emotions.

[0782] Output: The proposed destination data is stored on the server.

[0783] Step 13:

[0784] The server sends the proposal results back to the terminal.

[0785] Input: The destination data proposed in step 12.

[0786] Specific operation: The server generates an HTTP response and sends destination data to the terminal.

[0787] Output: The terminal receives the destination data.

[0788] Step 14:

[0789] The device displays the destination to the user.

[0790] Input: The destination data received in step 13.

[0791] How it works: The device analyzes the destination data and uses the map application to show the user "quiet cafes nearby."

[0792] Output: The user can visually confirm the suggested destinations.

[0793] Step 15:

[0794] The terminal collects movement information.

[0795] Input: The user's location.

[0796] Specific operation: The device records latitude and longitude information at regular intervals using the GPS sensor.

[0797] Output: The collected movement information is stored on the device.

[0798] Step 16:

[0799] The terminal transmits movement information to the server.

[0800] Input: Movement information collected in step 15.

[0801] Specific operation: The terminal generates an HTTP POST request and sends the movement information to the server.

[0802] Output: The server receives the movement information.

[0803] Step 17:

[0804] The server provides the travel information to the enterprise.

[0805] Input: The movement information received in step 16.

[0806] How it works: The server stores movement information in a database and provides the data through an API that companies can access.

[0807] Output: Businesses can obtain movement information and use it for targeted advertising and marketing.

[0808] (Application example 3)

[0809] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0810] Conventional systems were unable to suggest optimal routes and destinations based on users' goals and emotions, and lacked the means to effectively provide travel information to advertisers, which meant that users could not make personalized suggestions based on their needs, and advertisers could not effectively target their ads.

[0811] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0812] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using a generative AI based on the input information, a means for acquiring the user's location information, an emotion engine for recognizing the user's emotions, a means for the generative AI to suggest a destination based on the emotion, and a means for providing information on the proposed route and destination to an advertiser. This makes it possible to suggest optimal routes and destinations according to the user's goals and emotions, and to effectively provide the travel information to an advertiser.

[0813] "Destination" refers to the place or location the user wants to reach.

[0814] "Exercise intensity" refers to the level of strength or load of the exercise performed by a user.

[0815] "Generative AI" refers to artificial intelligence that generates optimal suggestions in an interactive format based on user input.

[0816] "Location Information" means data that indicates a User's current geographic location.

[0817] An "emotion engine" refers to a system that recognizes a user's emotions and makes appropriate suggestions based on those emotions.

[0818] "Advertiser" refers to a company or organization that uses user movement information to deliver targeted advertising.

[0819] "People flow data" refers to data compiled and analyzed from user movement information.

[0820] "Subscription format" refers to a format in which a service can be used by paying a periodic fee.

[0821] "Smartphone application" refers to a software program that runs on a smartphone.

[0822] A system for implementing this invention includes means for a user to input a destination or a target exercise intensity, means for automatically suggesting destinations in an interactive format using generative AI based on the input information, means for acquiring user location information, an emotion engine that recognizes the user's emotions, means for the generative AI to suggest destinations based on the emotions, and means for providing advertisers with information on the suggested route and destinations.

[0823] Program processing explanation

[0824] The server receives information about the destination and exercise intensity input by the user through a smartphone application. It then uses generative AI to interactively suggest optimal routes and destinations based on the input information. At this time, it obtains the user's location information and calculates the optimal route in real time.

[0825] In addition, the emotion engine recognizes the user's emotions, and the generative AI suggests appropriate destinations based on those emotions. For example, if the user expresses the emotion "I want to relax," it will suggest a quiet cafe or other relaxing place.

[0826] Suggested routes and destinations are provided to advertisers, who can use the information to target ads to users -- for example, if a user is out running, they could show ads for sporting goods stores along the user's route.

[0827] Hardware and Software Used

[0828] Hardware: Smartphone

[0829] Software: Python, generative AI model, emotion engine, API using HTTP requests

[0830] Examples

[0831] If a user sets a goal of "running 5km," the following prompt sentence can be input into the generative AI model:

[0832] Example prompt:

[0833] The user's goal is to "run 5km". The current location is Tokyo (latitude: 35.6895, longitude: 139.6917). Please suggest the best running route.

[0834] By inputting this prompt into a generative AI model, the optimal running route can be suggested. Also, if the user inputs the emotion "I want to relax," a quiet cafe can be suggested and an advertisement for that cafe can be displayed.

[0835] The flow of the specific process in the application example 3 will be described with reference to FIG.

[0836] Step 1:

[0837] The user starts the smartphone application and inputs a destination or a target exercise intensity.

[0838] Input: Destination or exercise intensity information

[0839] Output: The entered information is sent to the server.

[0840] Step 2:

[0841] The server receives information on the destination or exercise intensity sent from the user.

[0842] Input: User-entered destination or exercise intensity information

[0843] Output: Generate a prompt for the generative AI model based on the received information.

[0844] Step 3:

[0845] The server uses a generative AI model to interactively suggest optimal routes and destinations based on the input information.

[0846] Input: Generated prompt text

[0847] Output: Optimal route and destination suggestions

[0848] Step 4:

[0849] The server obtains the user's location information.

[0850] Input: User's current location

[0851] Output: Calculate the best route in real time based on the obtained location information

[0852] Step 5:

[0853] The server uses an emotion engine to recognize the user's emotions.

[0854] Input: User emotion data

[0855] Output: Recognized emotion information

[0856] Step 6:

[0857] The server generates an AI model based on emotions and suggests appropriate destinations.

[0858] Input: Recognized emotion information

[0859] Output: Sentiment-based destination suggestions

[0860] Step 7:

[0861] The server provides suggested route and destination information to advertisers.

[0862] Input: Proposed route and destination information

[0863] Output: Data provided to advertisers

[0864] Step 8:

[0865] Advertisers use the data provided to target advertisements.

[0866] Input: Provided user movement information

[0867] Output: Displaying targeted ads

[0868] In this way, at each step, data processing and calculations are performed based on the information input by the user, optimal routes and destinations are suggested, and this information is provided to advertisers, thereby realizing targeted advertising.

[0869] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice 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 voice data.

[0870] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[0871] Another example of generative AI is Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0872] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0873] [Second embodiment]

[0874] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0875] 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.

[0876] 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 wide area network (WAN) and / or a local area network (LAN).

[0877] 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.

[0878] 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 the voice according to instructions from the processor 46.

[0879] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0880] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0881] Fig. 4 shows an example of 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.

[0882] 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.

[0883] 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.

[0884] 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.

[0885] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0886] "Example 1"

[0887] The present invention is realized as a smartphone application. The user inputs a destination or a target exercise intensity through the application. The input information is sent to a generative AI, which automatically suggests destinations in an interactive format. The suggestions are optimized based on the user's input information, providing results tailored to the user's needs.

[0888] "Example 2"

[0889] Furthermore, in this embodiment of the present invention, the location information of the user is acquired and sold to companies as people flow data. The location information is acquired using the GPS function of the user's smartphone. The acquired location information is processed as people flow data and provided to companies. This allows companies to use it for market research, formulating advertising strategies, and so on.

[0890] "Example 3"

[0891] As a specific example, if a user inputs a goal of "running 5km," the AI ​​will suggest the optimal route to run 5km from the user's current location. The user's movement information will also be provided to companies as people flow data, and for example, sporting goods stores can use the information to target advertisements.

[0892] The process flow of each embodiment will be described below.

[0893] "Example 1"

[0894] Step 1: The user opens the smartphone application and enters the destination or target exercise intensity.

[0895] Step 2: The input information is sent to the generative AI.

[0896] Step 3: The AI ​​automatically suggests destinations in a conversational format, and the suggestions are optimized based on the user's input to provide results tailored to the user's needs.

[0897] "Example 2"

[0898] Step 1: Obtain the user's location using the smartphone's GPS function.

[0899] Step 2: The acquired location information is processed as people flow data.

[0900] Step 3: The processed people flow data is provided to companies, who can then use it for market research, advertising strategy development, and more.

[0901] "Example 3"

[0902] Step 1: User enters goal "run 5km".

[0903] Step 2: The AI ​​will suggest the best route for driving within a distance of 5km from the user's current location.

[0904] Step 3: The user's movement information is provided to companies as people flow data. For example, sporting goods stores can use the information to target advertisements.

[0905] Example 1

[0906] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0907] In conventional exercise planning support systems, users had to decide their own destination and exercise intensity, making it difficult to find the optimal exercise plan. In addition, there was a lack of means to effectively utilize the user's location information, making it difficult to make suggestions that met the user's needs.

[0908] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for transmitting the input information to the generative AI model, a means for analyzing the input information using the generative AI model and generating an optimal proposal, a means for displaying the generated proposal to the user, and a means for acquiring the user's location information. This allows the user to easily find an optimal exercise plan, and makes it possible to realize a proposal that utilizes the user's location information.

[0909] "User" refers to any individual or entity that uses the System.

[0910] "Destination" refers to the place the user wants to reach.

[0911] "Exercise intensity" refers to the strength or amount of exercise that a user aims for.

[0912] "Means of input" refers to the interface that allows users to communicate their destination and exercise intensity to the system.

[0913] A "generative AI model" refers to an artificial intelligence model that analyzes user input information and generates optimal suggestions.

[0914] "Means of transmitting" refers to the communications means for sending user input information to the generative AI model.

[0915] "Means of analysis" refers to the process by which the generative AI model analyzes the user's input information and generates optimal suggestions.

[0916] "Means for generating suggestions" refers to the process by which a generative AI model creates suggestions for a user based on the results of the analysis.

[0917] "Means for displaying" refers to an interface for visually showing the generated suggestions to a user.

[0918] "Location Information" means data that indicates a User's current geographic location.

[0919] "Means of collection" refers to the technologies and devices used to collect user location information.

[0920] "People flow data" refers to data that aggregates the location information of multiple users and shows their movement patterns and behavioral tendencies.

[0921] "Means of selling to businesses" refers to the process by which collected human flow data is provided to businesses for commercial purposes.

[0922] A "subscription format" refers to a business model in which a service can be used on an ongoing basis by paying a periodic fee.

[0923] "Mobile information terminal application" refers to software that runs on mobile information terminals such as smartphones and tablets.

[0924] This invention is a system that uses a generative AI model to suggest an optimal exercise plan when a user inputs a destination or a target exercise intensity. The system is realized as a smartphone application.

[0925] The user starts the application and inputs the destination or the target exercise intensity. For example, the user inputs "I want to walk for 30 minutes." This input information is acquired by the terminal and transmitted to the server via the Internet.

[0926] The server passes the received input information to a generative AI model (for example, OpenAI's GPT-4). The generative AI model analyzes the user's input information and generates optimal suggestions. For example, it generates a suggestion such as, "How about walking along the path along the nearby river?"

[0927] The generated suggestions are sent from the server to the terminal, and the terminal displays the suggestions to the user, who can review the suggestions and select or modify them as necessary.

[0928] As a concrete example, consider a case where a user inputs, "I want to go for a 30-minute walk." When this information is sent to the generative AI model, the AI ​​might suggest, "How about walking along the path next to a nearby river?"

[0929] Here is an example of a prompt to be input to the generative AI model:

[0930] User input: I want to go for a 30 minute walk

[0931] AI Response: How about walking along a nearby river path?

[0932] The system also includes a means to obtain the user's location information and optimizes suggestions by taking into account data such as the user's current location and past exercise history, allowing users to easily find the optimal exercise plan.

[0933] It also includes a way for companies to sell users' location information to them as people flow data, which the companies can use for marketing purposes and to improve their services.

[0934] The system is provided as a subscription-based mobile information terminal application, allowing users to use the service continuously by paying a periodic fee.

[0935] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0936] Step 1:

[0937] A user launches an application. A user launches an application by tapping the application icon on the home screen of their smartphone. When the application launches, the main screen is displayed. The input is the user's operation, and the output is the application's main screen.

[0938] Step 2:

[0939] A user inputs a destination or a target exercise intensity. A user inputs "I want to go to a nearby park" or "I want to take a 30-minute walk" into an application's input field. The input is the user's text input, and the output is the retrieval of the input information.

[0940] Step 3:

[0941] The terminal sends input information to the generative AI model. The terminal receives the user's input information and sends it to the server via the Internet. At this time, the input information is properly formatted and converted into a form that the generative AI model can understand. The input is the user's input information, and the output is the data sent to the server.

[0942] Step 4:

[0943] The server analyzes the input information using a generative AI model and generates optimal suggestions. The server passes the input information it receives to a generative AI model (e.g., OpenAI's GPT-4). The generative AI model analyzes the input information and generates optimal suggestions based on the user's needs. For example, it generates a suggestion such as, "How about walking along the path along the nearby river?" The input is the user's input information, and the output is the generated suggestion.

[0944] Step 5:

[0945] The server sends the generated proposal to the terminal. The server sends the proposal obtained from the generative AI model to the terminal. At this time, the proposal is formatted in a format that is easy for the user to understand. The input is the generated proposal, and the output is the data to be sent to the terminal.

[0946] Step 6:

[0947] The terminal displays the proposal to the user. The terminal displays the proposal received from the server to the user. The user can check the proposal on the application screen. The input is the proposal data from the server, and the output is the display to the user.

[0948] Step 7:

[0949] The user reviews the suggestions and selects or modifies them if necessary. The user reviews the suggestions and selects the suggestion if satisfied. If necessary, they can also modify the suggestion. For example, if they don't like the suggested location, they can request an alternative location. The input is the suggestion data from the server and the output is the user's selection or modification.

[0950] (Application example 1)

[0951] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0952] Conventional food delivery services have the problem that users have to search for restaurants and place orders themselves, which is time-consuming. In addition, there was no system that suggested the best restaurant based on the user's location information or exercise intensity, so it could not fully meet the needs of users.

[0953] 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.

[0954] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for displaying the location information of the proposed destination on a map, and a means for checking whether the proposed destination is compatible with the service and, if so, providing an ordering link. This allows the user to easily find the best restaurant based on the location information and exercise intensity without having to search for it themselves.

[0955] "User" refers to an individual who uses the system to input their destination and exercise intensity and receive suggestions.

[0956] "Destination" refers to the place the user wants to reach.

[0957] "Exercise intensity" refers to the level and type of exercise a user aims to achieve.

[0958] "Generative AI" refers to artificial intelligence that generates optimal suggestions in an interactive format based on input information.

[0959] "Interactive" refers to a format in which the user and system exchange information through questions and answers.

[0960] "Location Information" refers to geographic information about a User's current location or a specific place.

[0961] "Means for displaying on a map" means a method for visually illustrating the location of a proposed destination using a mapping application or mapping service.

[0962] "Service verification means" refers to a method to verify whether a proposed destination supports a particular service (e.g. food delivery).

[0963] "Means for providing an order link" refers to a method for providing a link or button that enables a User to place an order at a suggested destination.

[0964] A system for implementing this invention includes means for a user to input a destination or a target exercise intensity, means for automatically suggesting destinations in an interactive format using generative AI based on the input information, means for acquiring user location information, means for displaying the location information of the suggested destination on a map, and means for checking whether the proposed destination is compatible with the service and, if so, providing an order link.

[0965] Hardware and Software Used

[0966] Hardware: Smartphone

[0967] software:

[0968] Mobile application development frameworks (e.g. React Native)

[0969] Generative AI models (e.g. OpenAI GPT-4)

[0970] Map API (e.g. Google Maps API)

[0971] Food delivery API (e.g. Uber Eats API)

[0972] Data processing and calculation

[0973] Getting User Input

[0974] Users open the smartphone application and input their destination or target exercise intensity, for example, "a restaurant within a 10-minute walk from home."

[0975] Sending prompts to generative AI

[0976] A prompt is sent to the generative AI based on the input information. An example of a prompt sentence is, "The user is looking for a restaurant within a 10-minute walk from his / her home. Please suggest some recommended restaurants."

[0977] AI-driven proposal generation

[0978] Generative AI will suggest the best restaurant based on prompts, for example, "There are three nearby restaurants: Restaurant A, Cafe B, and Diner C."

[0979] Integration with Map API

[0980] Get the location of the suggested restaurants using Map API and display it to the user. Mark the location of the suggested restaurants on the map using Google Maps API.

[0981] Integration with food delivery API

[0982] Check if the suggested restaurants offer food delivery services and provide an order link if so. Use the Uber Eats API to display the menu and order link for the suggested restaurants.

[0983] Examples

[0984] A user opens the application and inputs "restaurants within a 10-minute walk from home." The generative AI then suggests "Restaurant A, Cafe B, and Diner C," and displays them on a map using the Google Maps API. It also uses the Uber Eats API to provide menus and ordering links for each restaurant.

[0985] Examples of prompt statements

[0986] A user is looking for a restaurant within a 10-minute walk from their home. Please suggest a restaurant.

[0987] In this way, users can easily find the best restaurants based on their location and activity level, without having to search for them themselves.

[0988] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0989] Step 1:

[0990] The user opens the smartphone application and inputs the destination or the target exercise intensity. The input information is temporarily saved in the application. For example, the user inputs "restaurants within a 10-minute walk from home."

[0991] Step 2:

[0992] The device sends the input information to the generative AI as a prompt. An example of a prompt is, "The user is looking for a restaurant within a 10-minute walk from his / her home. Please recommend some restaurants." The input data is sent in text format.

[0993] Step 3:

[0994] The server uses generative AI to suggest the best restaurant based on the prompts. The generative AI analyzes the input information and lists restaurants that fit the user's needs. For example, "Restaurant A, Cafe B, Diner C" is suggested.

[0995] Step 4:

[0996] The server retrieves the location of the suggested restaurants using a map API (e.g., Google Maps API). The location information is retrieved in the form of latitude and longitude, and is stored as data to be visually displayed to the user.

[0997] Step 5:

[0998] The device displays the location of the suggested restaurant on a map based on the location information obtained from the map API. The user can check the location of the suggested restaurant on the screen of their smartphone.

[0999] Step 6:

[1000] The server uses a food delivery API (e.g. Uber Eats API) to check if the suggested restaurants offer food delivery services, and if so, retrieves the menu and ordering links for each restaurant.

[1001] Step 7:

[1002] The terminal displays the menu and order link retrieved from the food delivery API to the user. The user can check the suggested restaurant menu on the smartphone screen and place the order by clicking the order link.

[1003] In this way, users can easily find the best restaurant based on their location and exercise intensity without having to search for it themselves.

[1004] Example 2

[1005] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[1006] Conventional location information acquisition systems only acquired the user's location information, but the means to effectively utilize that information were limited. There was also a lack of systems that provided detailed people flow data that companies could use for market research and the formulation of advertising strategies. Furthermore, there was no system that made appropriate suggestions based on the user's destination or exercise intensity.

[1007] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring user location information, a means for storing the acquired location information in a database, a means for generating people flow data based on the stored location information, and a means for providing the generated people flow data to companies. This makes it possible to effectively utilize the user's location information and provide detailed people flow data that companies can use for market research and the formulation of advertising strategies. In addition, appropriate suggestions can be made based on the user's destination and exercise intensity.

[1008] "Destination" refers to the place the user wants to reach.

[1009] "Exercise intensity" refers to the level of exercise strength or load that a user aims for.

[1010] "Generative AI" refers to artificial intelligence that automatically makes suggestions in an interactive format based on information entered by the user.

[1011] "Location Information" means geographic data that may include a User's current latitude and longitude.

[1012] "Database" refers to an information management system for storing acquired location information.

[1013] "People flow data" refers to data on the flow of people obtained by aggregating and analyzing the location information of multiple users.

[1014] "Providing to businesses" refers to providing the generated people flow data in a form that can be used by businesses.

[1015] "Subscription format" refers to a format in which a service can be used on an ongoing basis by paying a periodic fee.

[1016] "Smartphone application" refers to a software program that runs on a smartphone.

[1017] "Data analysis tool" refers to software for analyzing stored location information to generate people flow data.

[1018] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1019] The present invention is a system that acquires user location information, generates people flow data based on the information, and provides the data to businesses. A specific embodiment of the system will be described below.

[1020] server

[1021] The server receives location information from the user's smartphone. Specifically, the server receives an HTTP POST request and analyzes the location data included in the request body. The hardware used is the server, and the software used is an HTTP server (e.g., Apache, Nginx).

[1022] The received location information is stored in a database. The server stores the location information in the database using an INSERT query. For example, execute the following query in a MySQL database: INSERT INTO location_data (user_id, latitude, longitude, timestamp) VALUES (...).

[1023] The stored location information is analyzed using Python's Pandas library to generate people flow data. The server responds to data requests from companies through an API server using Flask, and returns people flow data in JSON format.

[1024] Terminal

[1025] The device obtains the user's location information using the GPS function. Specifically, the device periodically activates the GPS sensor and obtains the current latitude and longitude. The hardware used is a smartphone, and the software used is the GPS function (e.g. Android's LocationManager).

[1026] The obtained location information is sent to the server by creating an HTTP POST request and including the location information data in the request body. For example, the Retrofit library is used to send the data to the server.

[1027] User

[1028] The user enables the GPS function of the smartphone. Specifically, the user opens the settings app of the smartphone and turns on the "Location Information" setting.

[1029] The user also agrees to the provision of location information. Specifically, the user taps the "Agree" button in response to the message "Do you agree to provide location information?" on the application's consent screen.

[1030] Examples

[1031] Example 1: Acquiring and sending location information

[1032] When a user is in a shopping mall, he / she activates the GPS function of his / her smartphone. The device acquires the user's current location and transmits the location information to a server. The server stores the received location information in a database and later processes it as people flow data.

[1033] Example 2: Providing people flow data for companies

[1034] The server analyzes the foot traffic data for a particular area and provides it to businesses, who may use it to decide where to open new stores, for example.

[1035] Example prompts for generative AI models

[1036] "Please explain the process of the system that obtains user location information and provides it to companies as people flow data. Please also specify the names of any specific hardware or software."

[1037] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1038] Program processing flow

[1039] Step 1: Get the user's location

[1040] Subject: Terminal

[1041] The device obtains the user's location information using the GPS function. Specifically, the device periodically activates the GPS sensor and obtains the current latitude and longitude. The hardware used is a smartphone, and the software used is the GPS function (e.g. Android's LocationManager).

[1042] Input: Location request from the GPS sensor

[1043] Output: The user's current latitude and longitude.

[1044] Step 2: Send location information

[1045] Subject: Terminal

[1046] The device sends the acquired location information to the server. Specifically, the device creates an HTTP POST request, includes the location data in the request body, and sends it to the server. The software used is an HTTP client library (e.g., Retrofit).

[1047] Input: User's current latitude and longitude

[1048] Output: HTTP POST request to the server

[1049] Step 3: Receiving location information

[1050] Subject: Server

[1051] The server receives location information from the user's smartphone. Specifically, the server receives an HTTP POST request and analyzes the location data included in the request body. The hardware used is the server, and the software used is an HTTP server (e.g., Apache, Nginx).

[1052] Input: HTTP POST request

[1053] Output: Geolocation data

[1054] Step 4: Save location

[1055] Subject: Server

[1056] The server stores the received location information in a database. Specifically, the server stores the location information in the database using an INSERT query. The hardware used is a server, and the software used is a database management system (e.g., MySQL).

[1057] Input: Geolocation data

[1058] Output: Save results to database

[1059] Step 5: Generate people flow data

[1060] Subject: Server

[1061] The server generates people flow data based on the stored location information. Specifically, the server uses Python's Pandas library to aggregate the location information data and analyze people flow patterns for specific areas and time periods.

[1062] Input: Location information stored in the database

[1063] Output: People flow data

[1064] Step 6: Providing data to businesses

[1065] Subject: Server

[1066] The server provides the generated people flow data to companies. Specifically, the server responds to data requests from companies through an API server using Flask, and returns people flow data in JSON format.

[1067] Input: People flow data

[1068] Output: JSON formatted data response to the company.

[1069] (Application example 2)

[1070] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1071] Conventional ad delivery systems have had difficulty effectively utilizing users' location information to deliver ads. In addition, there were limited means for companies to obtain real-time human flow data necessary for market research and formulating advertising strategies. This made it difficult to maximize the effectiveness of advertising, and companies were looking for more efficient data utilization in their marketing activities.

[1072] 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. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring user location information, a means for analyzing the acquired location information and processing it as people flow data, and a means for delivering advertisements based on the analysis results. This makes it possible to acquire user location information in real time and deliver optimal advertisements based on the analysis results. In addition, companies can use this people flow data to efficiently conduct market research and formulate advertising strategies.

[1073] "Destination" refers to the specific location to which a User wishes to travel.

[1074] "Exercise intensity" is an indicator of the level of energy expenditure or physical activity that a user wants to achieve during exercise.

[1075] "Generative AI" refers to artificial intelligence technology that automatically generates appropriate suggestions in an interactive format based on input information.

[1076] "Interactive style" refers to a form of communication in which a user and a system exchange information with each other.

[1077] "Location Information" is data that indicates a user's current geographic location.

[1078] "Analysis" refers to the process of processing acquired data and converting it into meaningful information.

[1079] "People flow data" is data that shows the movement patterns of people in specific areas and at specific times.

[1080] "Advertising" refers to information promoting a particular product or service.

[1081] "Delivery" refers to the act of delivering specific information to users.

[1082] A "subscription format" refers to a business model in which a service can be used on an ongoing basis by paying a regular fee.

[1083] "Smartphone application" refers to a software program that runs on a smartphone.

[1084] The following system configuration and processing procedure will be described as an embodiment of the present invention.

[1085] System Configuration

[1086] The system consists of the user's smartphone, a server, and an ad delivery server. The smartphone is equipped with a GPS function and is used to obtain the user's location information. The server uses a generative AI model to interactively suggest destinations based on the user's input information, and analyzes the obtained location information to generate people flow data. The ad delivery server delivers the most suitable advertisements to the user based on the analysis results.

[1087] Hardware and Software Used

[1088] Smartphone: Any device with GPS functionality

[1089] Server: A computer for running data analysis and generative AI models

[1090] Advertisement delivery server: External server for delivering advertisements

[1091] Software: Python, requests library, geopy library

[1092] Data processing and calculation

[1093] 1. Obtaining location information: Obtaining the user's location information in real time using the smartphone's GPS function.

[1094] 2. Data analysis: The server analyzes the acquired location information and processes it as people flow data. This analysis involves estimating the density of people flow by combining the location information and the current time.

[1095] 3. Advertisement delivery: Based on the analysis results, the server generates advertisements that meet specific conditions (e.g., high pedestrian density) and delivers them to users via the ad delivery server.

[1096] Examples

[1097] For example, if a user is near Tokyo Station, the GPS function of the smartphone is used to obtain location information. The server analyzes this location information and determines that the density of people flowing around Tokyo Station is high. Based on the analysis results, an advertisement such as "Special sale! Check it out now!" is generated and delivered to the user via the advertisement delivery server.

[1098] Examples of prompt statements

[1099] An example of a prompt for a generative AI model is as follows:

[1100] Please develop an application that acquires user location information, analyzes the data, and provides it to companies as people flow data. Specifically, this application will acquire location information using the GPS function of smartphones and deliver advertisements based on the analysis results. Ad delivery will be done using an external ad server API.

[1101] The above is an embodiment of the present invention.

[1102] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1103] Step 1:

[1104] The user inputs the destination or the target exercise intensity using a smartphone. The input information is sent to the server by the smartphone application. The input data includes the geographic information of the destination and the numerical value of the exercise intensity.

[1105] Step 2:

[1106] The server uses a generative AI model to automatically suggest destinations interactively based on the received input data. The generative AI model analyzes the user's input information and generates optimal destinations. This process also takes into account the user's past travel history and current location information. The generated destination information is sent to the user's smartphone.

[1107] Step 3:

[1108] The user's smartphone acquires location information in real time using the GPS function. The acquired location information is periodically sent to a server. The location information data includes latitude, longitude, and timestamp.

[1109] Step 4:

[1110] The server analyzes the received location information and processes it as people flow data. The analysis includes clustering the location information and calculating the people flow density by time period. As a result of the analysis, people flow data is generated. This data shows the movement patterns of people in a specific area and time period.

[1111] Step 5:

[1112] The server generates advertisements based on the analysis results. In the advertisement generation process, the advertisement content is selected according to specific conditions (e.g., when the pedestrian flow density is high) taking into account the pedestrian flow data. The generated advertisement content is sent to the advertisement distribution server.

[1113] Step 6:

[1114] The ad delivery server delivers the received ad content to the user's smartphone. The ad is displayed at the optimal time based on the user's current location information and people flow data. The user can check the ad on their smartphone.

[1115] The above are the specific processing steps of this system.

[1116] Example 3

[1117] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1118] Conventional exercise support systems lack the functionality to suggest optimal routes based on the user's target exercise distance and exercise intensity. In addition, there are limited means to effectively utilize user movement information, making it difficult to provide useful data to companies.

[1119] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for calculating an optimal route based on the acquired location information, a means for providing the user with the calculation results, and a means for saving the user's movement information in a database. This allows the user to exercise efficiently, and companies to obtain valuable data for target advertising.

[1120] "User" refers to an individual who uses the system to set exercise goals and exercise based on those goals.

[1121] A "destination" refers to a specific location or distance that a user sets as their exercise goal.

[1122] "Exercise intensity" refers to the strain or difficulty a user wants to achieve while exercising.

[1123] "Generative AI" refers to artificial intelligence that automatically suggests destinations and exercise routes in an interactive format based on information entered by the user.

[1124] "Location information" refers to data that indicates a user's current location and travel route.

[1125] "Optimal route" refers to an efficient and safe exercise path calculated based on the user's exercise goals.

[1126] "Database" refers to an information system for storing and managing User movement information and other related data.

[1127] "People flow data" refers to data that is compiled and analyzed from user movement information, and can be used by companies for marketing and advertising purposes.

[1128] "Mobile information terminal application" refers to software that runs on mobile information terminals such as smartphones and tablets.

[1129] The present invention is a system for allowing a user to set an exercise goal and for proposing an optimal exercise route based on the goal. A specific embodiment of this system will be described below.

[1130] First, the user inputs his / her exercise goal using a mobile information terminal application. For example, he / she inputs a goal such as "running 5km." This input data is sent from the terminal to the server. The server receives the data using an HTTP request.

[1131] The server uses generative AI to calculate the optimal exercise route based on the received data. For this calculation, it uses map services such as Google Maps API and OpenStreetMap API. Specifically, it obtains the user's current location and calculates the optimal route for driving a distance of 5km from there. The calculation result is returned to the terminal in JSON format.

[1132] The device displays the received route information to the user. Specifically, the device displays a map on the app screen and draws the optimal route on the map. The user then starts running according to this route.

[1133] When a user starts running, the device sends the user's movement information to the server in real time. Specifically, GPS data is sent to the server periodically. The server stores the received movement information in a database. The database can be a SQL database or a NoSQL database.

[1134] The stored movement information is provided to companies as people flow data. Companies can use this data to target advertisements. For example, a sporting goods store can deliver advertisements to users who go running in a specific area.

[1135] As a concrete example, consider the case where a user inputs a goal of "running 5km". The user opens a smartphone app and inputs "running 5km". The app sends the information to a server, which uses the Google Maps API to calculate the optimal route. The calculation result is sent back to the app, and the user starts running according to the route.

[1136] Example prompt:

[1137] If a user enters a goal of "running 5km", the server will use the Google Maps API to calculate the optimal route and provide the result to the user. The user's movement information will also be stored in a database and provided to the company.

[1138] This system allows users to exercise efficiently and companies to obtain valuable data for targeted advertising. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1139] Step 1:

[1140] The user inputs a goal. The user opens a mobile information terminal application and inputs a goal such as "run 5km." The input data includes information such as the target distance and exercise intensity. The input data is sent from the terminal to the server.

[1141] Step 2:

[1142] The terminal sends the input data to the server. The terminal sends the goal data entered by the user to the server using an HTTP POST request. The input data also includes the user's current location information. The server analyzes the received data and proceeds to the next process.

[1143] Step 3:

[1144] The server calculates the optimal route. Based on the received destination data and current location information, the server uses the Google Maps API or OpenStreetMap API to calculate the optimal route. Specifically, it sends an API request, analyzes the returned data, and generates the optimal route. The calculation result is returned to the terminal in JSON format.

[1145] Step 4:

[1146] The server returns the calculation results to the device. The server returns the calculated route information to the device using an HTTP response. The output data includes detailed route information, distance, estimated time, etc. The device analyzes the received data and prepares it for display to the user.

[1147] Step 5:

[1148] The device displays the route to the user. The device then displays the received route information on the app screen. Specifically, the device displays a map and draws the optimal route on the map. The user then starts running according to this route.

[1149] Step 6:

[1150] The user starts running according to the route. The user starts running according to the route displayed on the device. Specifically, the user runs while following the audio and visual guides of the app.

[1151] Step 7:

[1152] The device transmits the user's movement information to the server. The device periodically transmits the user's GPS data to the server. Specifically, it transmits the current location information to the server every minute. The input data includes the user's current location and movement route.

[1153] Step 8:

[1154] The server stores the movement information in a database. The server stores the received GPS data in a SQL or NoSQL database. Specifically, it stores the data using an INSERT statement. The stored data is later used for analysis and provision to companies.

[1155] Step 9:

[1156] The server provides companies with people flow data. The server analyzes the stored movement information and provides it to companies. Specifically, the server exports the data in CSV format and sends it to companies. Companies can use this data to target advertisements.

[1157] (Application example 3)

[1158] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1159] Conventional running applications lack the functionality to suggest optimal routes based on the target distance set by the user. In addition, there is no mechanism to effectively utilize the user's exercise data and generate data for companies to deliver targeted advertisements. This leads to issues such as the inability to fully utilize the convenience for users and the marketing effectiveness of companies.

[1160] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1161] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for collecting the user's exercise data, anonymizing it and providing it to a company, and a means for generating data for a company to deliver targeted advertisements. This not only allows the user to receive suggestions for the optimal running route, but also enables a company to deliver effective targeted advertisements based on the collected data.

[1162] A "destination" refers to a specific location a user wants to reach.

[1163] "Target exercise intensity" refers to the exercise intensity or load that the user wants to achieve.

[1164] "Generative AI" refers to artificial intelligence technology that generates optimal suggestions based on user input information.

[1165] "Interaction style" refers to the way in which a user and a system exchange information with each other.

[1166] "Location information" refers to data that indicates a user's current location.

[1167] "Exercise Data" refers to information relating to a User's exercise (distance, time, route, etc.).

[1168] "Anonymization" refers to processing data so that individuals cannot be identified.

[1169] "Enterprise" refers to a legal entity or organization that provides goods or services.

[1170] "Targeted advertising" refers to advertising that is delivered to a specific demographic.

[1171] "Means of generating data" refers to the methods and techniques that create the data needed for a specific purpose.

[1172] "Subscription format" refers to a format in which a service can be used by paying a periodic fee.

[1173] "Smartphone application" refers to a software program that runs on a smartphone.

[1174] A system for implementing this invention includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for collecting the user's exercise data, anonymizing it and providing it to companies, and a means for generating data for companies to deliver targeted advertisements.

[1175] Hardware and Software Configuration

[1176] Hardware: Smartphone (iOS or Android)

[1177] Software: Python, Requests library, JSON library

[1178] Data processing and calculation

[1179] 1. User input: The user uses the smartphone application to input a destination or target exercise intensity.

[1180] 2. Use of generative AI: The server uses generative AI based on the user's input information to interactively suggest the optimal running route.

[1181] 3. Obtaining location information: The user's current location is obtained using the smartphone's GPS function.

[1182] 4. Collection of athletic data: User running data (distance, time, route, etc.) is collected and anonymized.

[1183] 5. Data provision: The collected exercise data is provided to companies, which then use this data to deliver targeted advertisements.

[1184] Examples

[1185] A user opens the smartphone app and enters their goal of "running 5km." The app then suggests the best route based on the user's current location. After the run, the app collects the user's running data, anonymizes it, and provides it to companies. Sporting goods stores use this data to deliver advertisements for running shoes to the user.

[1186] Examples of prompt statements

[1187] If a user inputs a goal of "running 5km", the AI ​​should suggest the best route to run 5km from the user's current location. Also, implement a function to collect the user's movement information as people flow data and provide it to companies.

[1188] In this way, not only can users receive recommendations for optimal running routes, but companies can also use the collected data to deliver targeted advertising.

[1189] The flow of the specific process in the application example 3 will be described with reference to FIG.

[1190] Step 1:

[1191] The user opens the smartphone application and inputs a destination or a target exercise intensity.

[1192] Input: Destination or target exercise intensity

[1193] Output: User input information

[1194] Specific actions: The user enters the destination or target exercise intensity into the app's input form and presses the submit button.

[1195] Step 2:

[1196] The server receives the user's input information and uses generative AI to interactively suggest the optimal running route.

[1197] Input: User input information

[1198] Output: Optimal running route

[1199] Specific operation: The server inputs the user's input information as prompts into the generative AI model and generates the optimal running route.

[1200] Step 3:

[1201] The device obtains the user's current location using the smartphone's GPS function.

[1202] Input: None (GPS function activation)

[1203] Output: User's current location

[1204] Specific operations: The device activates the GPS function, obtains the user's current location, and sends it to the server.

[1205] Step 4:

[1206] The server combines the user's current location information with the optimal running route and presents the route to the user.

[1207] Input: User's current location, optimal running route

[1208] Output: The running route presented to the user.

[1209] Specific operation: The server combines the current location information with the generated route and sends the route information to the user's smartphone.

[1210] Step 5:

[1211] The user starts running, and the device collects running data (distance, time, route) in real time.

[1212] Input: User's running data

[1213] Output: Collected running data

[1214] Specific operation: The device uses GPS and timer functions to record the user's running data in real time.

[1215] Step 6:

[1216] The server receives the collected running data, anonymizes it, and provides it to the company.

[1217] Input: Collected running data

[1218] Output: Anonymized running data

[1219] What it does: The server anonymizes the running data and sends it to the company's database.

[1220] Step 7:

[1221] Companies will generate targeted advertisements based on anonymized running data and deliver them to users.

[1222] Input: Anonymized running data

[1223] Output: Targeted ads

[1224] How it works: The company analyzes the data it receives, generates advertisements based on the user's interests and behavior, and delivers them to the user's smartphone.

[1225] In addition, 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.

[1226] "Example 1"

[1227] As one embodiment of the present invention, there is a system that combines an emotion engine that recognizes the user's emotions. In this system, when the user inputs a destination or a target exercise intensity, the generative AI automatically suggests a destination in a dialogue format based on the input information. Furthermore, the system acquires the user's location information and sells the information to companies as people flow data. An emotion engine that recognizes the user's emotions is also built in. This emotion engine recognizes emotions from the user's voice, facial expression, text input, etc., and the generative AI suggests a destination based on the emotion. Specifically, if the user inputs "running 5km" as a goal and the emotion of joy is recognized at that time, the AI ​​will take that emotion into consideration and suggest a running course around a beautiful park, for example.

[1228] "Example 2"

[1229] In another embodiment of the present invention, an emotion engine recognizes the user's emotion, and a generative AI suggests exercise intensity based on the emotion. Specifically, if the user expresses an emotion such as "I want to relieve stress," the AI ​​takes the emotion into account and suggests high-intensity exercise, for example.

[1230] "Example 3"

[1231] Furthermore, as another embodiment of the present invention, there is a system in which an emotion engine recognizes the emotion of a user, a generative AI suggests a destination based on that emotion, and based on that suggestion, the user's movement information is provided to a company as people flow data. Specifically, if a user expresses an emotion of "wanting to relax," the AI ​​takes that emotion into consideration and suggests, for example, a quiet cafe, and provides the user's movement information to the owner of the cafe or restaurant.

[1232] The process flow of each embodiment will be described below.

[1233] "Example 1"

[1234] Step 1: The user enters their destination or target exercise intensity into the app.

[1235] Step 2: Based on the input information, the generative AI automatically suggests destinations in an interactive format.

[1236] Step 3: Obtain user location information and sell that information to companies as people flow data.

[1237] Step 4: The emotion engine recognizes emotions from the user's voice, facial expressions, text input, etc.

[1238] Step 5: Generative AI suggests destinations based on the recognized emotions.

[1239] "Example 2"

[1240] Step 1: The emotion engine recognizes the user's emotion.

[1241] Step 2: Based on the recognized emotions, the generative AI suggests exercise intensity.

[1242] "Example 3"

[1243] Step 1: The emotion engine recognizes the user's emotion.

[1244] Step 2: Generative AI suggests destinations based on the recognized emotions.

[1245] Step 3: The user navigates based on the suggestion.

[1246] Step 4: User movement information is provided to companies as people flow data.

[1247] Example 1

[1248] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1249] In conventional systems, when users input their destination and exercise intensity, it was difficult to provide optimal suggestions that took into account their emotions and location information at the time. In addition, there were limited ways to effectively utilize users' location information, so it could not be used effectively when providing data to companies. This meant that improvements to the user experience and effective use of data were not fully achieved.

[1250] 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.

[1251] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for recognizing the user's emotion, and a means for optimizing the destination based on the recognized emotion information. This makes it possible to suggest an optimal destination taking into account the user's emotion and location information, improving the user experience and enabling effective use of data provided to companies.

[1252] "User" refers to an individual who uses the system to input their destination and exercise intensity and receive suggestions.

[1253] "Destination" refers to the place or location the user wants to reach.

[1254] "Exercise intensity" refers to the strength or amount of exercise that a user aims for.

[1255] "Generative AI" refers to artificial intelligence that automatically suggests destinations in an interactive format based on information entered by the user.

[1256] "Interaction style" refers to the way in which a user and a system exchange information with each other.

[1257] "Location Information" means data that indicates a User's current geographic location.

[1258] "Emotion" refers to the psychological state recognized from the user's voice, facial expressions, text input, etc.

[1259] "Emotion engine" refers to software or hardware for recognizing a user's emotions.

[1260] "Optimization" refers to the process of selecting the most suitable destination based on user input and sentiment information.

[1261] "People flow data" refers to data that aggregates user location information, anonymizes it, and provides it to companies.

[1262] "Subscription format" refers to a format in which a service can be used by paying a periodic fee.

[1263] "Smartphone application" refers to software that runs on a smartphone.

[1264] This invention is a system realized as a smartphone application. The user inputs the destination or the target exercise intensity through the application. The input information is sent to a generative AI, which automatically suggests destinations in an interactive format. The suggestions are optimized based on the user's input information, providing results tailored to the user's needs.

[1265] The system uses the following major hardware and software:

[1266] 1. Smartphone: A device on which a user runs applications.

[1267] 2. Generative AI: Artificial intelligence that suggests optimal destinations based on user input. Specifically, we use OpenAI's GPT-4.

[1268] 3. Emotion engine: Software that recognizes emotions from the user's voice, facial expressions, and text input. Specifically, it uses Microsoft's Azure Cognitive Services.

[1269] The user launches the application and inputs the destination or the target exercise intensity. For example, the user inputs a goal of "running 5km." This input information is sent to the generative AI within the application. The generative AI suggests the optimal destination based on the information input by the user. At this time, the user's location information is also obtained, and this information is sold to companies as people flow data.

[1270] In addition, the emotion engine recognizes emotions from the user's voice, facial expressions, text input, etc. For example, if a user inputs "5km run" and the emotion of joy is recognized, the generative AI will take that emotion into account and suggest a running course around a beautiful park.

[1271] For example, a user launches the application and inputs a goal of "running 5km." If the user inputs this with a smile, the emotion engine recognizes the emotion of joy. Based on this information, the generative AI suggests a running course around a beautiful park.

[1272] Example prompt:

[1273] If a user inputs a goal of "running 5km" and recognizes the emotion of joy, suggest the best running course.

[1274] In this way, a system is created in which generative AI suggests optimal destinations based on the user's input information and emotions.

[1275] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1276] Step 1:

[1277] The user launches an application.

[1278] Specifically, a user taps an application icon on their smartphone to launch the application, and an input screen is displayed.

[1279] Input: None

[1280] Output: Application home screen

[1281] Step 2:

[1282] The user inputs a destination or target exercise intensity.

[1283] As a specific action, the user inputs a destination or exercise intensity, such as "5km run," into an input field.

[1284] Input: User input information (e.g. "5km run")

[1285] Output: Input information is saved within the application

[1286] Step 3:

[1287] The terminal sends the input information to the generative AI.

[1288] Specifically, the device sends the user's input information to the server, which then passes it on to the generative AI.

[1289] Input: User input information

[1290] Output: Input information passed to the generative AI

[1291] Step 4:

[1292] The server uses generative AI to suggest the optimal destination.

[1293] Specifically, the server uses generative AI (e.g. GPT-4) to generate the best destination based on the user's input. For example, for a "5km run," it will suggest a running course around a beautiful park.

[1294] Input: Input information passed to the generative AI

[1295] Output: Optimal destination suggestions

[1296] Step 5:

[1297] The device obtains the user's location information.

[1298] Specifically, the terminal uses its GPS function to obtain the user's current location and transmits that information to the server.

[1299] Input: None

[1300] Output: User's location

[1301] Step 6:

[1302] The server sells the location information to companies as people flow data.

[1303] Specifically, the location information acquired by the server is processed as people flow data, anonymized, and sold to companies.

[1304] Input: User's location

[1305] Output: People flow data sold to businesses

[1306] Step 7:

[1307] The terminal recognizes the user's emotions.

[1308] Specifically, the device uses an emotion engine (e.g., Azure Cognitive Services) to recognize emotions from the user's voice, facial expressions, and text input. For example, if a user types "5km run" with a smile, the emotion of joy is recognized.

[1309] Input: User voice, facial expressions, and text input

[1310] Output: Recognized emotion information

[1311] Step 8:

[1312] The server optimizes the destination based on emotion information.

[1313] Specifically, the server optimizes the destinations proposed by the generative AI based on the emotion information sent from the emotion engine. For example, if the emotion of joy is recognized, it will suggest a running course with a beautiful view.

[1314] Input: Recognized emotion information, generative AI suggestions

[1315] Output: Optimized destination suggestions

[1316] Step 9:

[1317] The terminal presents the optimized destination to the user.

[1318] In particular, the terminal displays the optimized destinations to the user, and the user can review and select the suggested destinations.

[1319] Input: Optimized destination suggestions

[1320] Output: The optimized destination presented to the user.

[1321] (Application example 1)

[1322] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1323] Conventional food delivery systems have difficulty in suggesting optimal restaurants and menus based on the user's food type and calorie goal. In addition, suggestions do not take into account the user's emotions, which may result in lower user satisfaction. Furthermore, there is a lack of effective ways to utilize the user's location information, making it difficult to provide people flow data for businesses.

[1324] The identification process by the identification processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for recognizing the user's emotions, and a means for adjusting the content of the proposal based on the recognized emotions. This makes it possible to suggest optimal restaurants and menus based on the user's type of food and calorie goals, and further, by making suggestions that take the user's emotions into consideration, user satisfaction is improved. In addition, by effectively utilizing the user's location information, it becomes possible to provide people flow data for companies.

[1325] "User" means an individual or organization that uses the System.

[1326] "Destination" refers to the place the user wants to reach.

[1327] "Exercise intensity" refers to the strength or amount of exercise that the user aims for.

[1328] "Generative AI" is an artificial intelligence system that generates suggestions in an interactive format based on input information.

[1329] An "interactive" style is one in which the user and the system exchange information with each other.

[1330] "Location Information" is data that indicates a user's current geographic location.

[1331] "Means of recognizing emotions" refers to technology that identifies emotions from a user's voice, facial expressions, text input, etc.

[1332] "Means for adjusting the content of suggestions" refers to the function by which the generative AI optimizes the content of suggestions based on recognized emotions.

[1333] "People flow data" is data that is compiled and analyzed from users' location information.

[1334] "Means for selling to businesses" refers to methods and systems for providing collected people flow data to businesses.

[1335] A "subscription format" is a format in which a service can be used by paying a periodic fee.

[1336] A "smartphone application" is a software program that runs on a smartphone.

[1337] As an embodiment of the present invention, a food delivery system using a smartphone application will be described as an example.

[1338] System Configuration

[1339] The system consists of the following main components:

[1340] 1. User device: A smartphone with the smartphone application installed.

[1341] 2. Server: A server equipped with a generative AI and emotion recognition engine.

[1342] 3. Database: A database that stores restaurant information, menu information, and user information.

[1343] Program Processing

[1344] User Device

[1345] The user terminal provides an interface for users to input their food type and calorie goal. Once the user completes the input, the information is sent to the server. Data is also collected to recognize emotions through the user's voice, facial expressions, and text input.

[1346] server

[1347] The server does the following:

[1348] 1. Generative AI: Receives user input (type of food, calorie goal) and suggests optimal restaurants and menus in an interactive format. OpenAI's "GPT-3" and other generative AI are used.

[1349] 2. Emotion recognition engine: Recognizes emotions from the user's voice, facial expressions, and text input. Google Cloud's "Cloud Speech-to-Text" and "Cloud Vision API" are used as emotion recognition engines.

[1350] 3. Tailored suggestions: Based on the recognized emotion, generative AI will optimize the suggestions. For example, if the user expresses the emotion of “happiness,” it will provide more positive suggestions.

[1351] Database

[1352] The database stores restaurant information, menu information, and user information, allowing the server to quickly retrieve required information.

[1353] Examples

[1354] If a user opens a smartphone application, enters "Japanese food" and "500 kcal," and the emotion recognition engine recognizes "joy," the generative AI will generate a prompt like this:

[1355] A user wants Japanese food and has a calorie goal of 500kcal. The emotion is joy. Suggest the best restaurant and menu.

[1356] Based on this prompt, the generative AI will suggest healthy menu items under 500 kcal at a nearby delicious Japanese restaurant.

[1357] Hardware and Software

[1358] User device: Smartphone (iOS or Android)

[1359] Server: High-performance cloud server (e.g. Amazon Web Services, Google Cloud Platform)

[1360] Generative AI: OpenAI's "GPT-3"

[1361] Emotion recognition engine: Google Cloud's "Cloud Speech-to-Text" and "Cloud Vision API"

[1362] Database: Relational database (e.g. MySQL, PostgreSQL)

[1363] In this way, a system can be created that provides an optimal food delivery experience based on the user's needs and emotions.

[1364] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1365] Step 1:

[1366] A user opens a smartphone application and inputs the type of meal (e.g., Japanese, Western, Chinese) and the calorie goal. The input information is sent from the user's terminal to the server. The input data is the type of meal and the calorie goal.

[1367] Step 2:

[1368] The user terminal collects emotion data through the user's voice, facial expression, and text input. The collected emotion data is sent from the user terminal to the server. The input data is voice, facial expression, and text input.

[1369] Step 3:

[1370] The server uses an emotion recognition engine to recognize the user's emotions from the received voice, facial expressions, and text input. Google Cloud's "Cloud Speech-to-Text" and "Cloud Vision API" are used as emotion recognition engines. The input data are voice, facial expressions, and text input, and the output data is the recognized emotion.

[1371] Step 4:

[1372] The server generates a prompt sentence for the generative AI based on the user's input information (type of meal, calorie goal) and the recognized emotion. OpenAI's "GPT-3" is used as the generative AI. The input data is the type of meal, calorie goal, and recognized emotion, and the output data is the prompt sentence.

[1373] Step 5:

[1374] The server sends the prompt to the generative AI, which generates optimal restaurant and menu suggestions. The generative AI generates suggestions based on the prompt. The input data is the prompt, and the output data is the suggested restaurants and menus.

[1375] Step 6:

[1376] The server sends the suggested restaurants and menus to the user terminal. The user terminal displays the suggestions to the user. The input data are the suggested restaurants and menus, and the output data are the suggestions displayed to the user.

[1377] Step 7:

[1378] The user selects a suggested restaurant and menu and confirms the order. The user terminal sends the order information to the server. The input data is the user's selection and the order information.

[1379] Step 8:

[1380] The server obtains the user's location information and optimizes the delivery options. The location information is obtained from the user's terminal. The input data is the user's location information, and the output data is the optimized delivery options.

[1381] Step 9:

[1382] The server sells the user's location information to companies as people flow data. The input data is the user's location information, and the output data is the people flow data provided to companies.

[1383] In this way, a system can be created that provides an optimal food delivery experience based on the user's needs and emotions.

[1384] Example 2

[1385] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[1386] Conventional systems not only collected users' location information, but also had limited means of effectively utilizing that information. In addition, there were no systems that suggested appropriate exercise intensity based on the user's emotions. This made it difficult to provide personalized services that met the needs of users. Furthermore, there were issues with data processing and provision methods when selling the acquired location information to companies.

[1387] 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.

[1388] In this invention, the server includes a means for acquiring user location information, a means for transmitting the acquired location information to the server through a data collection application, a means for the server to collect the location information received and process it as people flow data, a means for an emotion recognition engine to recognize the user's emotion, a means for transmitting the recognized emotion data to a generative AI, a means for the generative AI to suggest an exercise intensity based on the emotion data, and a means for notifying the user of the suggested exercise intensity. This makes it possible to effectively utilize the user's location information and sell it to companies, as well as to make personalized exercise suggestions based on the user's emotion.

[1389] "User location information" means the latitude and longitude data of the user's current location.

[1390] A "data collection application" is software that obtains a user's location information and transmits it to a server.

[1391] A "server" is a computer system for receiving, processing and storing data.

[1392] "People flow data" is data that compiles the number and trends of users in a specific location at a specific time.

[1393] An "emotion recognition engine" is software that analyzes a user's facial expressions and tone of voice to recognize emotions.

[1394] "Generative AI" is artificial intelligence that makes appropriate suggestions or generates results based on input data.

[1395] "Exercise intensity" is an indicator of the strength or load of exercise.

[1396] A "notification means" is a method or device for conveying information to a user.

[1397] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1398] This invention includes a system that acquires users' location information and sells it to companies as people flow data, and a system in which an emotion engine recognizes the user's emotions and a generative AI suggests exercise intensity.

[1399] Hardware and Software Used

[1400] Hardware:

[1401] User's smartphone

[1402] Wearable devices (e.g. smart watches)

[1403] software:

[1404] Smartphone GPS function

[1405] Data Collection Applications

[1406] Data Processing Server

[1407] Emotion Recognition Engine

[1408] Generative AI

[1409] Exercise suggestion application

[1410] Data processing and calculation

[1411] Get the user's location:

[1412] The user's smartphone uses the GPS function to obtain current location information. Specifically, the smartphone's GPS sensor receives signals from satellites and calculates latitude and longitude. For example, if a user is in a shopping mall, the smartphone's GPS identifies the location and obtains latitude 35.6895 and longitude 139.6917 (for Tokyo).

[1413] Location transmission:

[1414] The data collection application sends the acquired location information to a server. Specifically, the smartphone sends the location information to the server via an Internet connection. For example, the smartphone sends location information (latitude 35.6895, longitude 139.6917) to the server in real time.

[1415] Generating people flow data:

[1416] The server collects the location information it receives and processes it as people flow data. Specifically, the server collects the number of users at a specific location during a specific time period and generates statistical data. For example, the server collects the number of users at a shopping mall every hour and generates data such as "1,000 people visited between 12:00 and 13:00."

[1417] Enterprise data provider:

[1418] The processed foot traffic data is provided to companies. Specifically, the server displays the statistical data generated by the server on the company's dashboard or provides it through an API. For example, the server displays "shopping mall foot traffic data" on an advertising agency's dashboard so that the company can view it.

[1419] User emotion recognition:

[1420] The emotion recognition engine recognizes the user's emotions. Specifically, it uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice. For example, when a user speaks into the smartphone's camera, the emotion recognition engine determines that the user is "stressed."

[1421] Sending emotion data:

[1422] The recognized emotion data is sent to the generative AI. Specifically, the smartphone sends the emotion data to the generative AI server via the internet. For example, the smartphone sends emotion data such as "I feel stressed" to the server.

[1423] Exercise intensity suggestions:

[1424] The generative AI suggests exercise intensity based on emotion data. Specifically, the generative AI analyzes emotion data and calculates appropriate exercise intensity. For example, the generative AI suggests high-intensity exercise (e.g. 30 minutes of jogging) in response to the emotion "I want to relieve stress."

[1425] Proposal Notification:

[1426] Notify the user of the suggested exercise intensity. Specifically, the smartphone notification function is used to display the exercise suggestion to the user. For example, the smartphone displays a notification to the user saying, "We recommend that you jog for 30 minutes."

[1427] Examples

[1428] Example prompt:

[1429] "Get user location information and generate shopping mall traffic data."

[1430] "Suggest an appropriate exercise intensity for users when they are feeling stressed."

[1431] The above is an embodiment of the present invention.

[1432] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1433] Step 1:

[1434] Getting the user's location

[1435] Input: The user's smartphone uses the GPS to obtain their current location.

[1436] Data processing and calculation: The smartphone's GPS sensor receives signals from satellites and calculates latitude and longitude.

[1437] Output: Latitude and longitude data (e.g. 35.6895 latitude, 139.6917 longitude).

[1438] What happens: If a user is in a shopping mall, the smartphone's GPS will determine its location and obtain latitude 35.6895 and longitude 139.6917 (for Tokyo, for example).

[1439] Step 2:

[1440] Sending location information

[1441] Input: The acquired location information (latitude and longitude data).

[1442] Data processing and calculation: The data collection application sends the location information to a server via an Internet connection.

[1443] Output: The location sent to the server.

[1444] Specific operation: The smartphone sends location information (latitude 35.6895, longitude 139.6917) to the server in real time.

[1445] Step 3:

[1446] Generating people flow data

[1447] Input: The location information received by the server.

[1448] Data processing and calculation: The server compiles the number of users in a specific location at a specific time and generates statistical data.

[1449] Output: People flow data (e.g. "1000 people visited between 12:00-13:00").

[1450] Specific operation: The server counts the number of users in the shopping mall every hour and generates data such as "1,000 people visited between 12:00 and 13:00."

[1451] Step 4:

[1452] Providing data for businesses

[1453] Input: Processed people flow data.

[1454] Data processing and calculation: The statistical data generated by the server is displayed on the company's dashboard or provided via API.

[1455] Output: People flow data available to businesses.

[1456] What it does: The server displays "shopping mall foot traffic data" on the ad agency's dashboard, making it available for companies to view.

[1457] Step 5:

[1458] User emotion recognition

[1459] Input: The user's facial expressions and tone of voice.

[1460] Data processing and calculation: The emotion recognition engine analyzes the user's facial expressions and tone of voice to recognize emotions.

[1461] Output: Recognized emotion data (e.g. "I feel stressed").

[1462] How it works: When a user speaks into their smartphone's camera, the emotion recognition engine determines that they are "stressed."

[1463] Step 6:

[1464] Sending emotion data

[1465] Input: Recognized emotion data.

[1466] Data processing and calculation: The smartphone sends emotion data via the internet to the generative AI server.

[1467] Output: The emotion data sent to the server.

[1468] Specific operation: The smartphone sends emotional data indicating "feeling stressed" to the server.

[1469] Step 7:

[1470] Exercise intensity suggestions

[1471] Input: emotion data.

[1472] Data processing and calculation: Generative AI analyzes emotion data and calculates appropriate exercise intensity.

[1473] Output: Suggested exercise intensity (e.g. "30 minutes of jogging").

[1474] Specific behavior: In response to the emotion of "wanting to relieve stress," the generative AI suggests high-intensity exercise (e.g. 30 minutes of jogging).

[1475] Step 8:

[1476] Proposal Notification

[1477] Input: Suggested exercise intensity.

[1478] Data processing and calculation: Use the smartphone's notification function to display exercise suggestions to the user.

[1479] Output: Exercise suggestions notified to the user.

[1480] What happens: The phone displays a notification to the user saying, "We recommend you go for a 30 minute jog."

[1481] (Application example 2)

[1482] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1483] Conventional advertising systems display uniform advertisements without considering the user's location information or emotions, which results in many advertisements that do not match the user's interests. In addition, because advertisements are not optimized based on the user's emotions, there is also the issue of reduced advertising effectiveness.

[1484] 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.

[1485] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using a generative AI based on the input information, a means for acquiring the user's location information, a means for recognizing the user's emotions, a means for the generative AI to optimize advertisements based on the recognized emotions, and a means for displaying the optimized advertisements to the user. This makes it possible to display optimal advertisements in real time based on the user's location information and emotions.

[1486] "Destination" refers to the specific location to which a User wishes to travel.

[1487] "Exercise intensity" refers to the level of strength or load of the exercise performed by a user.

[1488] "Generative AI" refers to artificial intelligence that makes suggestions or generates ideas in an interactive format based on input information.

[1489] "Interaction style" refers to the way in which a user and a system exchange information with each other.

[1490] "Location Information" refers to geographic data that indicates a User's current location.

[1491] "Means of recognizing emotions" refers to technology that detects emotions from the user's facial expressions, voice, etc.

[1492] "Means of optimizing advertising" refers to technology that selects the most appropriate advertisement based on the user's location information and emotions.

[1493] An "optimized ad" is an ad that best suits the user's current situation and emotions.

[1494] "Subscription format" refers to a format in which a service can be used by paying a periodic fee.

[1495] "Smartphone application" refers to software that runs on a smartphone.

[1496] The system for implementing this invention utilizes the user's smartphone as the main hardware. The system includes the following main components:

[1497] 1. A means for the user to input a destination or target exercise intensity:

[1498] Users input their destination and exercise intensity through a smartphone application, which then transmits the user's desired destination and exercise intensity to the system.

[1499] 2. A means to automatically suggest destinations in a dialogue format using generative AI:

[1500] Based on the input information, generative AI (e.g. OpenAI GPT-4) will interactively suggest the best destination for the user, allowing the user to select a destination that best suits their needs.

[1501] 3. How to obtain user location information:

[1502] Use the smartphone's GPS function to obtain the user's current location. Use a location information acquisition library such as Google Maps API.

[1503] 4. How to recognize user emotions:

[1504] Using the smartphone camera and microphone, it recognizes emotions from the user's facial expressions and voice, using emotion recognition libraries such as Microsoft Azure Face API and Google Cloud Speech-to-Text.

[1505] 5. How generative AI can optimize ads based on perceived emotions:

[1506] Based on the acquired location information and emotion data, generative AI selects the optimal ad, which is best suited to the user's current situation and emotions.

[1507] 6. How to display optimized ads to users:

[1508] The optimized ads are then displayed to users through smartphone applications, allowing users to see ads that are tailored to their interests.

[1509] Hardware and Software Used

[1510] Hardware: Smartphone (GPS function, camera, microphone)

[1511] software:

[1512] GPS data acquisition library (e.g. Google Maps API)

[1513] Emotion recognition libraries (e.g. Microsoft Azure Face API, Google Cloud Speech-to-Text)

[1514] Generative AI models (e.g. OpenAI GPT-4)

[1515] Examples

[1516] Let's say a user is in a shopping mall. The smartphone's GPS function acquires location information, and the emotion recognition system detects that the user is "having fun." Based on this information, the generative AI proposes "advertisements for new fashion items" and displays them on the user's smartphone.

[1517] Examples of prompt statements

[1518] User location: Shopping mall

[1519] User sentiment: Enjoying it

[1520] Suggested Ad: New Fashion Items

[1521] In this way, ads can be served in real time that best suit the user's current situation and emotions.

[1522] The flow of the identification process in the application example 2 will be described with reference to FIG.

[1523] Step 1:

[1524] The user starts the smartphone application and inputs the destination or the target exercise intensity. The input information is sent to the server. The input data includes the name of the destination and the level of exercise intensity.

[1525] Step 2:

[1526] The server uses a generative AI based on the input information to interactively suggest the best destination to the user. The generative AI analyzes the user's input data and generates appropriate destinations. The generated destination candidates are sent to the user's smartphone.

[1527] Step 3:

[1528] The user's smartphone acquires the current location using the GPS function. The acquired location information is sent to the server. The location information includes latitude and longitude data.

[1529] Step 4:

[1530] The server uses the smartphone's camera and microphone to recognize the user's emotions. It analyzes facial expression data captured by the camera and voice data recorded by the microphone using an emotion recognition library (e.g. Microsoft Azure Face API, Google Cloud Speech-to-Text) to identify the user's emotions. The recognized emotion data is stored on the server.

[1531] Step 5:

[1532] The server uses a generative AI to select the optimal advertisement based on the acquired location information and emotion data. The generative AI analyzes the location information and emotion data to generate an advertisement that is most suitable for the user's current situation and emotion. The generated advertisement data is sent to the user's smartphone.

[1533] Step 6:

[1534] The user's smartphone displays optimized advertisements that match the user's interests and concerns, enhancing the user's experience.

[1535] In this way, optimal ads can be served in real time based on the user's location and emotions.

[1536] Example 3

[1537] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1538] Conventional systems lack the functionality to suggest optimal routes and destinations based on the goals and emotions set by the user. In addition, the means to effectively collect user movement information and provide it to companies are limited. This makes it difficult to make personalized suggestions according to user needs, and companies are also unable to carry out effective marketing such as targeted advertising.

[1539] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1540] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using a generative AI based on the input information, a means for acquiring the user's location information, a means for recognizing the user's emotions, a means for the generative AI to suggest a destination based on the recognized emotions, a means for collecting the user's movement information, and a means for providing the collected movement information to a company. This enables personalized suggestions based on the user's goals and emotions, and allows companies to carry out effective marketing such as targeted advertising.

[1541] "User" refers to an individual who uses the system to input their destination and exercise intensity and receive suggestions.

[1542] A "destination" refers to the place or location a user wants to reach.

[1543] "Exercise intensity" refers to the level of difficulty or load of the exercise set by the user.

[1544] "Generative AI" refers to artificial intelligence that automatically generates and suggests destinations and routes in an interactive format based on input information.

[1545] "Location information" refers to latitude and longitude data that indicates a user's current location.

[1546] "Emotion" refers to the psychological state or mood exhibited by a user.

[1547] "Means of recognizing emotions" refers to technology that analyzes and recognizes emotions from user input and actions.

[1548] "Movement information" refers to data that indicates changes in a user's route or location when they move.

[1549] "Company" refers to a legal entity that uses user movement information for marketing and targeted advertising.

[1550] A "subscription format" refers to a business model in which a service can be used on an ongoing basis by paying a periodic fee.

[1551] A "mobile information terminal application" refers to software that runs on a mobile information terminal such as a smartphone or tablet.

[1552] This invention is a system that proposes optimal routes and destinations based on the goals and emotions set by a user, and provides the travel information to companies. A specific embodiment of this system will be described below.

[1553] System Configuration

[1554] This system consists of terminals used by users, servers that process data, and external companies. The terminals are mobile information terminals such as smartphones and tablets, and the servers are located on the cloud. The system has the following main functions:

[1555] 1. A means for the user to input a destination or target exercise intensity

[1556] Through a smartphone application, users input their destination and exercise intensity, for example, a goal such as "I want to run 5km" or "I want to relax."

[1557] 2. A means to automatically suggest destinations in a dialogue format using generative AI based on input information

[1558] The server receives the input information and uses a generative AI model to generate optimal destinations and routes. The generative AI model generates prompts based on the user's input and makes suggestions in a dialogue format.

[1559] 3. How to obtain user location information

[1560] The device uses the GPS sensor to obtain the user's current location, which is then sent to the server.

[1561] 4. How to Recognize User Emotions

[1562] The server uses an emotion engine to recognize emotions from the user's input and actions. For example, it analyzes the user's emotion from the input "I want to relax."

[1563] 5. How generative AI can suggest destinations based on perceived emotions

[1564] Based on the recognized emotions, the server uses a generative AI model to suggest appropriate destinations, for example a quiet cafe for a user who wants to relax.

[1565] 6. Means of collecting user movement information

[1566] The device collects user movement information using a GPS sensor, and the collected movement information is sent to a server.

[1567] 7. Means of providing collected mobility information to companies

[1568] The server stores the collected movement information in a database and provides it to companies, who use the data for targeted advertising and marketing.

[1569] Examples

[1570] Example of a goal-based route suggestion

[1571] A user enters a goal of "run 5km."

[1572] The server uses the Google Maps API to calculate the optimal route and send it back to the device.

[1573] The device will show the user a 5km route from home via the park and back.

[1574] Examples of emotion-based destination suggestions

[1575] The user types "I want to relax" into the device.

[1576] The server recognizes this emotion using an emotion engine and suggests destinations using generative AI.

[1577] The device will show the user "quiet cafes nearby."

[1578] Examples of prompt statements

[1579] "I want to do a 5km run. What is the best route?"

[1580] "I want to relax. Can you recommend some places?"

[1581] This system proposes optimal routes and destinations based on the user's goals and emotions, and provides the travel information to companies, enabling use in targeted advertising, etc. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1582] Step 1:

[1583] The user enters a goal.

[1584] Input: The user inputs a goal, such as "run 5km" or "I want to relax," through a smartphone application.

[1585] Specific behavior: A user opens the app, enters a goal in the text box, and presses the submit button.

[1586] Output: The entered target data is saved to the terminal.

[1587] Step 2:

[1588] The device transmits the goal to the server.

[1589] Input: The target data entered in step 1.

[1590] Specific operations: The terminal generates an HTTP request and sends the target data to the server.

[1591] Output: The server receives the target data.

[1592] Step 3:

[1593] The server calculates the optimal route.

[1594] Input: The target data received by the server.

[1595] Specific operation: The server sends a request to the Google Maps API to calculate the optimal route for driving within a distance of 5km from the user's current location.

[1596] Output: The calculated route data is saved on the server.

[1597] Step 4:

[1598] The server sends the calculation results back to the terminal.

[1599] Input: The route data calculated in step 3.

[1600] Specific operation: The server generates an HTTP response and sends route data to the terminal.

[1601] Output: The device receives the route data.

[1602] Step 5:

[1603] The device displays the route to the user.

[1604] Input: The route data received in step 4.

[1605] Specific operation: The device analyzes the route data and uses a map application to show the user a "5km route from home via the park and back."

[1606] Output: The user can visually see the optimal route.

[1607] Step 6:

[1608] The terminal collects movement information.

[1609] Input: The user's location.

[1610] Specific operation: The device records latitude and longitude information at regular intervals using the GPS sensor.

[1611] Output: The collected movement information is stored on the device.

[1612] Step 7:

[1613] The terminal transmits movement information to the server.

[1614] Input: Movement information collected in step 6.

[1615] Specific operation: The terminal generates an HTTP POST request and sends the movement information to the server.

[1616] Output: The server receives the movement information.

[1617] Step 8:

[1618] The server provides the travel information to the enterprise.

[1619] Input: The movement information received in step 7.

[1620] How it works: The server stores movement information in a database and provides the data through an API that companies can access.

[1621] Output: Businesses can obtain movement information and use it for targeted advertising and marketing.

[1622] Step 9:

[1623] The user inputs the emotion.

[1624] Input: The user inputs emotions such as "I want to relax" through a smartphone application.

[1625] Specific behavior: A user opens the app, enters their emotion in the text box, and presses the send button.

[1626] Output: The input emotion data is saved on the device.

[1627] Step 10:

[1628] The device transmits the emotion to the server.

[1629] Input: Emotion data entered in step 9.

[1630] Specific operation: The device generates an HTTP request and sends emotion data to the server.

[1631] Output: The server receives the emotion data.

[1632] Step 11:

[1633] The server recognizes the emotion.

[1634] Input: Emotion data received in step 10.

[1635] Specific operation: The server uses an emotion analysis algorithm to analyze the input data and recognize the user's emotion.

[1636] Output: The recognized emotion data is stored on the server.

[1637] Step 12:

[1638] The server suggests destinations.

[1639] Input: Emotion data recognized in step 11.

[1640] How it works: The server uses a generative AI model to suggest destinations (such as a quiet cafe) based on the user's emotions.

[1641] Output: The proposed destination data is stored on the server.

[1642] Step 13:

[1643] The server sends the proposal results back to the terminal.

[1644] Input: The destination data proposed in step 12.

[1645] Specific operation: The server generates an HTTP response and sends destination data to the terminal.

[1646] Output: The terminal receives the destination data.

[1647] Step 14:

[1648] The device displays the destination to the user.

[1649] Input: The destination data received in step 13.

[1650] How it works: The device analyzes the destination data and uses the map application to show the user "quiet cafes nearby."

[1651] Output: The user can visually confirm the suggested destinations.

[1652] Step 15:

[1653] The terminal collects movement information.

[1654] Input: The user's location.

[1655] Specific operation: The device records latitude and longitude information at regular intervals using the GPS sensor.

[1656] Output: The collected movement information is stored on the device.

[1657] Step 16:

[1658] The terminal transmits movement information to the server.

[1659] Input: Movement information collected in step 15.

[1660] Specific operation: The terminal generates an HTTP POST request and sends the movement information to the server.

[1661] Output: The server receives the movement information.

[1662] Step 17:

[1663] The server provides the travel information to the enterprise.

[1664] Input: The movement information received in step 16.

[1665] How it works: The server stores movement information in a database and provides the data through an API that companies can access.

[1666] Output: Businesses can obtain movement information and use it for targeted advertising and marketing.

[1667] (Application example 3)

[1668] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1669] Conventional systems were unable to suggest optimal routes and destinations based on users' goals and emotions, and lacked the means to effectively provide travel information to advertisers, which meant that users could not make personalized suggestions based on their needs, and advertisers could not effectively target their ads.

[1670] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1671] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using a generative AI based on the input information, a means for acquiring the user's location information, an emotion engine for recognizing the user's emotions, a means for the generative AI to suggest a destination based on the emotion, and a means for providing information on the proposed route and destination to an advertiser. This makes it possible to suggest optimal routes and destinations according to the user's goals and emotions, and to effectively provide the travel information to an advertiser.

[1672] "Destination" refers to the place or location the user wants to reach.

[1673] "Exercise intensity" refers to the level of strength or load of the exercise performed by a user.

[1674] "Generative AI" refers to artificial intelligence that generates optimal suggestions in an interactive format based on user input.

[1675] "Location Information" means data that indicates a User's current geographic location.

[1676] An "emotion engine" refers to a system that recognizes a user's emotions and makes appropriate suggestions based on those emotions.

[1677] "Advertiser" refers to a company or organization that uses user movement information to deliver targeted advertising.

[1678] "People flow data" refers to data compiled and analyzed from user movement information.

[1679] "Subscription format" refers to a format in which a service can be used by paying a periodic fee.

[1680] "Smartphone application" refers to a software program that runs on a smartphone.

[1681] A system for implementing this invention includes means for a user to input a destination or a target exercise intensity, means for automatically suggesting destinations in an interactive format using generative AI based on the input information, means for acquiring user location information, an emotion engine that recognizes the user's emotions, means for the generative AI to suggest destinations based on the emotions, and means for providing advertisers with information on the suggested route and destinations.

[1682] Program processing explanation

[1683] The server receives information about the destination and exercise intensity input by the user through a smartphone application. It then uses generative AI to interactively suggest optimal routes and destinations based on the input information. At this time, it obtains the user's location information and calculates the optimal route in real time.

[1684] In addition, the emotion engine recognizes the user's emotions, and the generative AI suggests appropriate destinations based on those emotions. For example, if the user expresses the emotion "I want to relax," it will suggest a quiet cafe or other relaxing place.

[1685] Suggested routes and destinations are provided to advertisers, who can use the information to target ads to users -- for example, if a user is out running, they could show ads for sporting goods stores along the user's route.

[1686] Hardware and Software Used

[1687] Hardware: Smartphone

[1688] Software: Python, generative AI model, emotion engine, API using HTTP requests

[1689] Examples

[1690] If a user sets a goal of "running 5km," the following prompt sentence can be input into the generative AI model:

[1691] Example prompt:

[1692] The user's goal is to "run 5km". The current location is Tokyo (latitude: 35.6895, longitude: 139.6917). Please suggest the best running route.

[1693] By inputting this prompt into a generative AI model, the optimal running route can be suggested. Also, if the user inputs the emotion "I want to relax," a quiet cafe can be suggested and an advertisement for that cafe can be displayed.

[1694] The flow of the specific process in the application example 3 will be described with reference to FIG.

[1695] Step 1:

[1696] The user starts the smartphone application and inputs a destination or a target exercise intensity.

[1697] Input: Destination or exercise intensity information

[1698] Output: The entered information is sent to the server.

[1699] Step 2:

[1700] The server receives information on the destination or exercise intensity sent from the user.

[1701] Input: User-entered destination or exercise intensity information

[1702] Output: Generate a prompt for the generative AI model based on the received information.

[1703] Step 3:

[1704] The server uses a generative AI model to interactively suggest optimal routes and destinations based on the input information.

[1705] Input: Generated prompt text

[1706] Output: Optimal route and destination suggestions

[1707] Step 4:

[1708] The server obtains the user's location information.

[1709] Input: User's current location

[1710] Output: Calculate the best route in real time based on the obtained location information

[1711] Step 5:

[1712] The server uses an emotion engine to recognize the user's emotions.

[1713] Input: User emotion data

[1714] Output: Recognized emotion information

[1715] Step 6:

[1716] The server generates an AI model based on emotions and suggests appropriate destinations.

[1717] Input: Recognized emotion information

[1718] Output: Sentiment-based destination suggestions

[1719] Step 7:

[1720] The server provides suggested route and destination information to advertisers.

[1721] Input: Proposed route and destination information

[1722] Output: Data provided to advertisers

[1723] Step 8:

[1724] Advertisers use the data provided to target advertisements.

[1725] Input: Provided user movement information

[1726] Output: Displaying targeted ads

[1727] In this way, at each step, data processing and calculations are performed based on the information input by the user, optimal routes and destinations are suggested, and this information is provided to advertisers, thereby realizing targeted advertising.

[1728] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the 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.

[1729] 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> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[1730] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1731] 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 smart glasses 214.

[1732] [Third embodiment]

[1733] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1734] 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.

[1735] 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 wide area network (WAN) and / or a local area network (LAN).

[1736] 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.

[1737] 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 the voice according to instructions from the processor 46.

[1738] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1739] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1740] Fig. 6 shows an example of 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.

[1741] 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.

[1742] 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.

[1743] In the headset type terminal 314, 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.

[1744] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1745] "Example 1"

[1746] The present invention is realized as a smartphone application. The user inputs a destination or a target exercise intensity through the application. The input information is sent to a generative AI, which automatically suggests destinations in an interactive format. The suggestions are optimized based on the user's input information, providing results tailored to the user's needs.

[1747] "Example 2"

[1748] Furthermore, in this embodiment of the present invention, the location information of the user is acquired and sold to companies as people flow data. The location information is acquired using the GPS function of the user's smartphone. The acquired location information is processed as people flow data and provided to companies. This allows companies to use it for market research, formulating advertising strategies, and so on.

[1749] "Example 3"

[1750] As a specific example, if a user inputs a goal of "running 5km," the AI ​​will suggest the optimal route to run 5km from the user's current location. The user's movement information will also be provided to companies as people flow data, and for example, sporting goods stores can use the information to target advertisements.

[1751] The process flow of each embodiment will be described below.

[1752] "Example 1"

[1753] Step 1: The user opens the smartphone application and enters the destination or target exercise intensity.

[1754] Step 2: The input information is sent to the generative AI.

[1755] Step 3: The AI ​​automatically suggests destinations in a conversational format, and the suggestions are optimized based on the user's input to provide results tailored to the user's needs.

[1756] "Example 2"

[1757] Step 1: Obtain the user's location using the smartphone's GPS function.

[1758] Step 2: The acquired location information is processed as people flow data.

[1759] Step 3: The processed people flow data is provided to companies, who can then use it for market research, advertising strategy development, and more.

[1760] "Example 3"

[1761] Step 1: User enters goal "run 5km".

[1762] Step 2: The AI ​​will suggest the best route for driving within a distance of 5km from the user's current location.

[1763] Step 3: The user's movement information is provided to companies as people flow data. For example, sporting goods stores can use the information to target advertisements.

[1764] Example 1

[1765] Next, a description will be given of Example 1 of the embodiment 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".

[1766] In conventional exercise planning support systems, users had to decide their own destination and exercise intensity, making it difficult to find the optimal exercise plan. In addition, there was a lack of means to effectively utilize the user's location information, making it difficult to make suggestions that met the user's needs.

[1767] The identification process by the identification processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for transmitting the input information to the generative AI model, a means for analyzing the input information using the generative AI model and generating an optimal proposal, a means for displaying the generated proposal to the user, and a means for acquiring the user's location information. This allows the user to easily find an optimal exercise plan, and makes it possible to realize a proposal that utilizes the user's location information.

[1768] "User" refers to any individual or entity that uses the System.

[1769] "Destination" refers to the place the user wants to reach.

[1770] "Exercise intensity" refers to the strength or amount of exercise that a user aims for.

[1771] "Means of input" refers to the interface that allows users to communicate their destination and exercise intensity to the system.

[1772] A "generative AI model" refers to an artificial intelligence model that analyzes user input information and generates optimal suggestions.

[1773] "Means of transmitting" refers to the communications means for sending user input information to the generative AI model.

[1774] "Means of analysis" refers to the process by which the generative AI model analyzes the user's input information and generates optimal suggestions.

[1775] "Means for generating suggestions" refers to the process by which a generative AI model creates suggestions for a user based on the results of the analysis.

[1776] "Means for displaying" refers to an interface for visually showing the generated suggestions to a user.

[1777] "Location Information" means data that indicates a User's current geographic location.

[1778] "Means of collection" refers to the technologies and devices used to collect user location information.

[1779] "People flow data" refers to data that aggregates the location information of multiple users and shows their movement patterns and behavioral tendencies.

[1780] "Means of selling to businesses" refers to the process by which collected human flow data is provided to businesses for commercial purposes.

[1781] A "subscription format" refers to a business model in which a service can be used on an ongoing basis by paying a periodic fee.

[1782] "Mobile information terminal application" refers to software that runs on mobile information terminals such as smartphones and tablets.

[1783] This invention is a system that uses a generative AI model to suggest an optimal exercise plan when a user inputs a destination or a target exercise intensity. The system is realized as a smartphone application.

[1784] The user starts the application and inputs the destination or the target exercise intensity. For example, the user inputs "I want to walk for 30 minutes." This input information is acquired by the terminal and transmitted to the server via the Internet.

[1785] The server passes the received input information to a generative AI model (for example, OpenAI's GPT-4). The generative AI model analyzes the user's input information and generates optimal suggestions. For example, it generates a suggestion such as, "How about walking along the path along the nearby river?"

[1786] The generated suggestions are sent from the server to the terminal, and the terminal displays the suggestions to the user, who can review the suggestions and select or modify them as necessary.

[1787] As a concrete example, consider a case where a user inputs, "I want to go for a 30-minute walk." When this information is sent to the generative AI model, the AI ​​might suggest, "How about walking along the path next to a nearby river?"

[1788] Here is an example of a prompt to be input to the generative AI model:

[1789] User input: I want to go for a 30 minute walk

[1790] AI Response: How about walking along a nearby river path?

[1791] The system also includes a means to obtain the user's location information and optimizes suggestions by taking into account data such as the user's current location and past exercise history, allowing users to easily find the optimal exercise plan.

[1792] It also includes a way for companies to sell users' location information to them as people flow data, which the companies can use for marketing purposes and to improve their services.

[1793] The system is provided as a subscription-based mobile information terminal application, allowing users to use the service continuously by paying a periodic fee.

[1794] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1795] Step 1:

[1796] A user launches an application. A user launches an application by tapping the application icon on the home screen of their smartphone. When the application launches, the main screen is displayed. The input is the user's operation, and the output is the application's main screen.

[1797] Step 2:

[1798] A user inputs a destination or a target exercise intensity. A user inputs "I want to go to a nearby park" or "I want to take a 30-minute walk" into an application's input field. The input is the user's text input, and the output is the retrieval of the input information.

[1799] Step 3:

[1800] The terminal sends input information to the generative AI model. The terminal receives the user's input information and sends it to the server via the Internet. At this time, the input information is properly formatted and converted into a form that the generative AI model can understand. The input is the user's input information, and the output is the data sent to the server.

[1801] Step 4:

[1802] The server analyzes the input information using a generative AI model and generates optimal suggestions. The server passes the input information it receives to a generative AI model (e.g., OpenAI's GPT-4). The generative AI model analyzes the input information and generates optimal suggestions based on the user's needs. For example, it generates a suggestion such as, "How about walking along the path along the nearby river?" The input is the user's input information, and the output is the generated suggestion.

[1803] Step 5:

[1804] The server sends the generated proposal to the terminal. The server sends the proposal obtained from the generative AI model to the terminal. At this time, the proposal is formatted in a format that is easy for the user to understand. The input is the generated proposal, and the output is the data to be sent to the terminal.

[1805] Step 6:

[1806] The terminal displays the proposal to the user. The terminal displays the proposal received from the server to the user. The user can check the proposal on the application screen. The input is the proposal data from the server, and the output is the display to the user.

[1807] Step 7:

[1808] The user reviews the suggestions and selects or modifies them if necessary. The user reviews the suggestions and selects the suggestion if satisfied. If necessary, they can also modify the suggestion. For example, if they don't like the suggested location, they can request an alternative location. The input is the suggestion data from the server and the output is the user's selection or modification.

[1809] (Application example 1)

[1810] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1811] Conventional food delivery services have the problem that users have to search for restaurants and place orders themselves, which is time-consuming. In addition, there was no system that suggested the best restaurant based on the user's location information or exercise intensity, so it could not fully meet the needs of users.

[1812] 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.

[1813] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for displaying the location information of the proposed destination on a map, and a means for checking whether the proposed destination is compatible with the service and, if so, providing an ordering link. This allows the user to easily find the best restaurant based on the location information and exercise intensity without having to search for it themselves.

[1814] "User" refers to an individual who uses the system to input their destination and exercise intensity and receive suggestions.

[1815] "Destination" refers to the place the user wants to reach.

[1816] "Exercise intensity" refers to the level and type of exercise a user aims to achieve.

[1817] "Generative AI" refers to artificial intelligence that generates optimal suggestions in an interactive format based on input information.

[1818] "Interactive" refers to a format in which the user and system exchange information through questions and answers.

[1819] "Location Information" refers to geographic information about a User's current location or a specific place.

[1820] "Means for displaying on a map" means a method for visually illustrating the location of a proposed destination using a mapping application or mapping service.

[1821] "Service verification means" refers to a method to verify whether a proposed destination supports a particular service (e.g. food delivery).

[1822] "Means for providing an order link" refers to a method for providing a link or button that enables a User to place an order at a suggested destination.

[1823] A system for implementing this invention includes means for a user to input a destination or a target exercise intensity, means for automatically suggesting destinations in an interactive format using generative AI based on the input information, means for acquiring user location information, means for displaying the location information of the suggested destination on a map, and means for checking whether the proposed destination is compatible with the service and, if so, providing an order link.

[1824] Hardware and Software Used

[1825] Hardware: Smartphone

[1826] software:

[1827] Mobile application development frameworks (e.g. React Native)

[1828] Generative AI models (e.g. OpenAI GPT-4)

[1829] Map API (e.g. Google Maps API)

[1830] Food delivery API (e.g. Uber Eats API)

[1831] Data processing and calculation

[1832] Getting User Input

[1833] Users open the smartphone application and input their destination or target exercise intensity, for example, "a restaurant within a 10-minute walk from home."

[1834] Sending prompts to generative AI

[1835] A prompt is sent to the generative AI based on the input information. An example of a prompt sentence is, "The user is looking for a restaurant within a 10-minute walk from his / her home. Please suggest some recommended restaurants."

[1836] AI-driven proposal generation

[1837] Generative AI will suggest the best restaurant based on prompts, for example, "There are three nearby restaurants: Restaurant A, Cafe B, and Diner C."

[1838] Integration with Map API

[1839] Get the location of the suggested restaurants using Map API and display it to the user. Mark the location of the suggested restaurants on the map using Google Maps API.

[1840] Integration with food delivery API

[1841] Check if the suggested restaurants offer food delivery services and provide an order link if so. Use the Uber Eats API to display the menu and order link for the suggested restaurants.

[1842] Examples

[1843] A user opens the application and inputs "restaurants within a 10-minute walk from home." The generative AI then suggests "Restaurant A, Cafe B, and Diner C," and displays them on a map using the Google Maps API. It also uses the Uber Eats API to provide menus and ordering links for each restaurant.

[1844] Examples of prompt statements

[1845] A user is looking for a restaurant within a 10-minute walk from their home. Please suggest a restaurant.

[1846] In this way, users can easily find the best restaurants based on their location and activity level, without having to search for them themselves.

[1847] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1848] Step 1:

[1849] The user opens the smartphone application and inputs the destination or the target exercise intensity. The input information is temporarily saved in the application. For example, the user inputs "restaurants within a 10-minute walk from home."

[1850] Step 2:

[1851] The device sends the input information to the generative AI as a prompt. An example of a prompt is, "The user is looking for a restaurant within a 10-minute walk from his / her home. Please recommend some restaurants." The input data is sent in text format.

[1852] Step 3:

[1853] The server uses generative AI to suggest the best restaurant based on the prompts. The generative AI analyzes the input information and lists restaurants that fit the user's needs. For example, "Restaurant A, Cafe B, Diner C" is suggested.

[1854] Step 4:

[1855] The server retrieves the location of the suggested restaurants using a map API (e.g., Google Maps API). The location information is retrieved in the form of latitude and longitude, and is stored as data to be visually displayed to the user.

[1856] Step 5:

[1857] The device displays the location of the suggested restaurant on a map based on the location information obtained from the map API. The user can check the location of the suggested restaurant on the screen of their smartphone.

[1858] Step 6:

[1859] The server uses a food delivery API (e.g. Uber Eats API) to check if the suggested restaurants offer food delivery services, and if so, retrieves the menu and ordering links for each restaurant.

[1860] Step 7:

[1861] The terminal displays the menu and order link retrieved from the food delivery API to the user. The user can check the suggested restaurant menu on the smartphone screen and place the order by clicking the order link.

[1862] In this way, users can easily find the best restaurant based on their location and exercise intensity without having to search for it themselves.

[1863] Example 2

[1864] Next, a second embodiment of the second form will be described. 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".

[1865] Conventional location information acquisition systems only acquired the user's location information, but the means to effectively utilize that information were limited. There was also a lack of systems that provided detailed people flow data that companies could use for market research and the formulation of advertising strategies. Furthermore, there was no system that made appropriate suggestions based on the user's destination or exercise intensity.

[1866] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring user location information, a means for storing the acquired location information in a database, a means for generating people flow data based on the stored location information, and a means for providing the generated people flow data to companies. This makes it possible to effectively utilize the user's location information and provide detailed people flow data that companies can use for market research and the formulation of advertising strategies. In addition, appropriate suggestions can be made based on the user's destination and exercise intensity.

[1867] "Destination" refers to the place the user wants to reach.

[1868] "Exercise intensity" refers to the level of exercise strength or load that a user aims for.

[1869] "Generative AI" refers to artificial intelligence that automatically makes suggestions in an interactive format based on information entered by the user.

[1870] "Location Information" means geographic data that may include a User's current latitude and longitude.

[1871] "Database" refers to an information management system for storing acquired location information.

[1872] "People flow data" refers to data on the flow of people obtained by aggregating and analyzing the location information of multiple users.

[1873] "Providing to businesses" refers to providing the generated people flow data in a form that can be used by businesses.

[1874] "Subscription format" refers to a format in which a service can be used on an ongoing basis by paying a periodic fee.

[1875] "Smartphone application" refers to a software program that runs on a smartphone.

[1876] "Data analysis tool" refers to software for analyzing stored location information to generate people flow data.

[1877] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1878] The present invention is a system that acquires user location information, generates people flow data based on the information, and provides the data to businesses. A specific embodiment of the system will be described below.

[1879] server

[1880] The server receives location information from the user's smartphone. Specifically, the server receives an HTTP POST request and analyzes the location data included in the request body. The hardware used is the server, and the software used is an HTTP server (e.g., Apache, Nginx).

[1881] The received location information is stored in a database. The server stores the location information in the database using an INSERT query. For example, execute the following query in a MySQL database: INSERT INTO location_data (user_id, latitude, longitude, timestamp) VALUES (...).

[1882] The stored location information is analyzed using Python's Pandas library to generate people flow data. The server responds to data requests from companies through an API server using Flask, and returns people flow data in JSON format.

[1883] Terminal

[1884] The device obtains the user's location information using the GPS function. Specifically, the device periodically activates the GPS sensor and obtains the current latitude and longitude. The hardware used is a smartphone, and the software used is the GPS function (e.g. Android's LocationManager).

[1885] The obtained location information is sent to the server by creating an HTTP POST request and including the location information data in the request body. For example, the Retrofit library is used to send the data to the server.

[1886] User

[1887] The user enables the GPS function of the smartphone. Specifically, the user opens the settings app of the smartphone and turns on the "Location Information" setting.

[1888] The user also agrees to the provision of location information. Specifically, the user taps the "Agree" button in response to the message "Do you agree to provide location information?" on the application's consent screen.

[1889] Examples

[1890] Example 1: Acquiring and sending location information

[1891] When a user is in a shopping mall, he / she activates the GPS function of his / her smartphone. The device acquires the user's current location and transmits the location information to a server. The server stores the received location information in a database and later processes it as people flow data.

[1892] Example 2: Providing people flow data for companies

[1893] The server analyzes the foot traffic data for a particular area and provides it to businesses, who may use it to decide where to open new stores, for example.

[1894] Example prompts for generative AI models

[1895] "Please explain the process of the system that obtains user location information and provides it to companies as people flow data. Please also specify the names of any specific hardware or software."

[1896] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1897] Program processing flow

[1898] Step 1: Get the user's location

[1899] Subject: Terminal

[1900] The device obtains the user's location information using the GPS function. Specifically, the device periodically activates the GPS sensor and obtains the current latitude and longitude. The hardware used is a smartphone, and the software used is the GPS function (e.g. Android's LocationManager).

[1901] Input: Location request from the GPS sensor

[1902] Output: The user's current latitude and longitude.

[1903] Step 2: Send location information

[1904] Subject: Terminal

[1905] The device sends the acquired location information to the server. Specifically, the device creates an HTTP POST request, includes the location data in the request body, and sends it to the server. The software used is an HTTP client library (e.g., Retrofit).

[1906] Input: User's current latitude and longitude

[1907] Output: HTTP POST request to the server

[1908] Step 3: Receiving location information

[1909] Subject: Server

[1910] The server receives location information from the user's smartphone. Specifically, the server receives an HTTP POST request and analyzes the location data included in the request body. The hardware used is the server, and the software used is an HTTP server (e.g., Apache, Nginx).

[1911] Input: HTTP POST request

[1912] Output: Geolocation data

[1913] Step 4: Save location

[1914] Subject: Server

[1915] The server stores the received location information in a database. Specifically, the server stores the location information in the database using an INSERT query. The hardware used is a server, and the software used is a database management system (e.g., MySQL).

[1916] Input: Geolocation data

[1917] Output: Save results to database

[1918] Step 5: Generate people flow data

[1919] Subject: Server

[1920] The server generates people flow data based on the stored location information. Specifically, the server uses Python's Pandas library to aggregate the location information data and analyze people flow patterns for specific areas and time periods.

[1921] Input: Location information stored in the database

[1922] Output: People flow data

[1923] Step 6: Providing data to businesses

[1924] Subject: Server

[1925] The server provides the generated people flow data to companies. Specifically, the server responds to data requests from companies through an API server using Flask, and returns people flow data in JSON format.

[1926] Input: People flow data

[1927] Output: JSON formatted data response to the company.

[1928] (Application example 2)

[1929] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1930] Conventional ad delivery systems have had difficulty effectively utilizing users' location information to deliver ads. In addition, there were limited means for companies to obtain real-time human flow data necessary for market research and formulating advertising strategies. This made it difficult to maximize the effectiveness of advertising, and companies were looking for more efficient data utilization in their marketing activities.

[1931] 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. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring user location information, a means for analyzing the acquired location information and processing it as people flow data, and a means for delivering advertisements based on the analysis results. This makes it possible to acquire user location information in real time and deliver optimal advertisements based on the analysis results. In addition, companies can use this people flow data to efficiently conduct market research and formulate advertising strategies.

[1932] "Destination" refers to the specific location to which a User wishes to travel.

[1933] "Exercise intensity" is an indicator of the level of energy expenditure or physical activity that a user wants to achieve during exercise.

[1934] "Generative AI" refers to artificial intelligence technology that automatically generates appropriate suggestions in an interactive format based on input information.

[1935] "Interactive style" refers to a form of communication in which a user and a system exchange information with each other.

[1936] "Location Information" is data that indicates a user's current geographic location.

[1937] "Analysis" refers to the process of processing acquired data and converting it into meaningful information.

[1938] "People flow data" is data that shows the movement patterns of people in specific areas and at specific times.

[1939] "Advertising" refers to information promoting a particular product or service.

[1940] "Delivery" refers to the act of delivering specific information to users.

[1941] A "subscription format" refers to a business model in which a service can be used on an ongoing basis by paying a regular fee.

[1942] "Smartphone application" refers to a software program that runs on a smartphone.

[1943] The following system configuration and processing procedure will be described as an embodiment of the present invention.

[1944] System Configuration

[1945] The system consists of the user's smartphone, a server, and an ad delivery server. The smartphone is equipped with a GPS function and is used to obtain the user's location information. The server uses a generative AI model to interactively suggest destinations based on the user's input information, and analyzes the obtained location information to generate people flow data. The ad delivery server delivers the most suitable advertisements to the user based on the analysis results.

[1946] Hardware and Software Used

[1947] Smartphone: Any device with GPS functionality

[1948] Server: A computer for running data analysis and generative AI models

[1949] Advertisement delivery server: External server for delivering advertisements

[1950] Software: Python, requests library, geopy library

[1951] Data processing and calculation

[1952] 1. Obtaining location information: Obtaining the user's location information in real time using the smartphone's GPS function.

[1953] 2. Data analysis: The server analyzes the acquired location information and processes it as people flow data. This analysis involves estimating the density of people flow by combining the location information and the current time.

[1954] 3. Advertisement delivery: Based on the analysis results, the server generates advertisements that meet specific conditions (e.g., high pedestrian density) and delivers them to users via the ad delivery server.

[1955] Examples

[1956] For example, if a user is near Tokyo Station, the GPS function of the smartphone is used to obtain location information. The server analyzes this location information and determines that the density of people flowing around Tokyo Station is high. Based on the analysis results, an advertisement such as "Special sale! Check it out now!" is generated and delivered to the user via the advertisement delivery server.

[1957] Examples of prompt statements

[1958] An example of a prompt for a generative AI model is as follows:

[1959] Please develop an application that acquires user location information, analyzes the data, and provides it to companies as people flow data. Specifically, this application will acquire location information using the GPS function of smartphones and deliver advertisements based on the analysis results. Ad delivery will be done using an external ad server API.

[1960] The above is an embodiment of the present invention.

[1961] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1962] Step 1:

[1963] The user inputs the destination or the target exercise intensity using a smartphone. The input information is sent to the server by the smartphone application. The input data includes the geographic information of the destination and the numerical value of the exercise intensity.

[1964] Step 2:

[1965] The server uses a generative AI model to automatically suggest destinations interactively based on the received input data. The generative AI model analyzes the user's input information and generates optimal destinations. This process also takes into account the user's past travel history and current location information. The generated destination information is sent to the user's smartphone.

[1966] Step 3:

[1967] The user's smartphone acquires location information in real time using the GPS function. The acquired location information is periodically sent to a server. The location information data includes latitude, longitude, and timestamp.

[1968] Step 4:

[1969] The server analyzes the received location information and processes it as people flow data. The analysis includes clustering the location information and calculating the people flow density by time period. As a result of the analysis, people flow data is generated. This data shows the movement patterns of people in a specific area and time period.

[1970] Step 5:

[1971] The server generates advertisements based on the analysis results. In the advertisement generation process, the advertisement content is selected according to specific conditions (e.g., when the pedestrian flow density is high) taking into account the pedestrian flow data. The generated advertisement content is sent to the advertisement distribution server.

[1972] Step 6:

[1973] The ad delivery server delivers the received ad content to the user's smartphone. The ad is displayed at the optimal time based on the user's current location information and people flow data. The user can check the ad on their smartphone.

[1974] The above are the specific processing steps of this system.

[1975] Example 3

[1976] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1977] Conventional exercise support systems lack the functionality to suggest optimal routes based on the user's target exercise distance and exercise intensity. In addition, there are limited means to effectively utilize user movement information, making it difficult to provide useful data to companies.

[1978] The identification process by the identification processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for the user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for calculating an optimal route based on the acquired location information, a means for providing the user with the calculation results, and a means for saving the user's movement information in a database. This allows the user to exercise efficiently, and companies to obtain valuable data for target advertising.

[1979] "User" refers to an individual who uses the system to set exercise goals and exercise based on those goals.

[1980] A "destination" refers to a specific location or distance that a user sets as their exercise goal.

[1981] "Exercise intensity" refers to the strain or difficulty a user wants to achieve while exercising.

[1982] "Generative AI" refers to artificial intelligence that automatically suggests destinations and exercise routes in an interactive format based on information entered by the user.

[1983] "Location information" refers to data that indicates a user's current location and travel route.

[1984] "Optimal route" refers to an efficient and safe exercise path calculated based on the user's exercise goals.

[1985] "Database" refers to an information system for storing and managing User movement information and other related data.

[1986] "People flow data" refers to data that is compiled and analyzed from user movement information, and can be used by companies for marketing and advertising purposes.

[1987] "Mobile information terminal application" refers to software that runs on mobile information terminals such as smartphones and tablets.

[1988] The present invention is a system for allowing a user to set an exercise goal and for proposing an optimal exercise route based on the goal. A specific embodiment of this system will be described below.

[1989] First, the user inputs his / her exercise goal using a mobile information terminal application. For example, he / she inputs a goal such as "running 5km." This input data is sent from the terminal to the server. The server receives the data using an HTTP request.

[1990] The server uses generative AI to calculate the optimal exercise route based on the received data. For this calculation, it uses map services such as Google Maps API and OpenStreetMap API. Specifically, it obtains the user's current location and calculates the optimal route for driving a distance of 5km from there. The calculation result is returned to the terminal in JSON format.

[1991] The device displays the received route information to the user. Specifically, the device displays a map on the app screen and draws the optimal route on the map. The user then starts running according to this route.

[1992] When a user starts running, the device sends the user's movement information to the server in real time. Specifically, GPS data is sent to the server periodically. The server stores the received movement information in a database. The database can be a SQL database or a NoSQL database.

[1993] The stored movement information is provided to companies as people flow data. Companies can use this data to target advertisements. For example, a sporting goods store can deliver advertisements to users who go running in a specific area.

[1994] As a concrete example, consider the case where a user inputs a goal of "running 5km". The user opens a smartphone app and inputs "running 5km". The app sends the information to a server, which uses the Google Maps API to calculate the optimal route. The calculation result is sent back to the app, and the user starts running according to the route.

[1995] Example prompt:

[1996] If a user enters a goal of "running 5km", the server will use the Google Maps API to calculate the optimal route and provide the result to the user. The user's movement information will also be stored in a database and provided to the company.

[1997] This system allows users to exercise efficiently and companies to obtain valuable data for targeted advertising. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1998] Step 1:

[1999] The user inputs a goal. The user opens a mobile information terminal application and inputs a goal such as "run 5km." The input data includes information such as the target distance and exercise intensity. The input data is sent from the terminal to the server.

[2000] Step 2:

[2001] The terminal sends the input data to the server. The terminal sends the goal data entered by the user to the server using an HTTP POST request. The input data also includes the user's current location information. The server analyzes the received data and proceeds to the next process.

[2002] Step 3:

[2003] The server calculates the optimal route. Based on the received destination data and current location information, the server uses the Google Maps API or OpenStreetMap API to calculate the optimal route. Specifically, it sends an API request, analyzes the returned data, and generates the optimal route. The calculation result is returned to the terminal in JSON format.

[2004] Step 4:

[2005] The server returns the calculation results to the device. The server returns the calculated route information to the device using an HTTP response. The output data includes detailed route information, distance, estimated time, etc. The device analyzes the received data and prepares it for display to the user.

[2006] Step 5:

[2007] The device displays the route to the user. The device then displays the received route information on the app screen. Specifically, the device displays a map and draws the optimal route on the map. The user then starts running according to this route.

[2008] Step 6:

[2009] The user starts running according to the route. The user starts running according to the route displayed on the device. Specifically, the user runs while following the audio and visual guides of the app.

[2010] Step 7:

[2011] The device transmits the user's movement information to the server. The device periodically transmits the user's GPS data to the server. Specifically, it transmits the current location information to the server every minute. The input data includes the user's current location and movement route.

[2012] Step 8:

[2013] The server stores the movement information in a database. The server stores the received GPS data in a SQL or NoSQL database. Specifically, it stores the data using an INSERT statement. The stored data is later used for analysis and provision to companies.

[2014] Step 9:

[2015] The server provides companies with people flow data. The server analyzes the stored movement information and provides it to companies. Specifically, the server exports the data in CSV format and sends it to companies. Companies can use this data to target advertisements.

[2016] (Application example 3)

[2017] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[2018] Conventional running applications lack the functionality to suggest optimal routes based on the target distance set by the user. In addition, there is no mechanism to effectively utilize the user's exercise data and generate data for companies to deliver targeted advertisements. This leads to issues such as the inability to fully utilize the convenience for users and the marketing effectiveness of companies.

[2019] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[2020] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for collecting the user's exercise data, anonymizing it and providing it to a company, and a means for generating data for a company to deliver targeted advertisements. This not only allows the user to receive suggestions for the optimal running route, but also enables a company to deliver effective targeted advertisements based on the collected data.

[2021] A "destination" refers to a specific location a user wants to reach.

[2022] "Target exercise intensity" refers to the exercise intensity or load that the user wants to achieve.

[2023] "Generative AI" refers to artificial intelligence technology that generates optimal suggestions based on user input information.

[2024] "Interaction style" refers to the way in which a user and a system exchange information with each other.

[2025] "Location information" refers to data that indicates a user's current location.

[2026] "Exercise Data" refers to information relating to a User's exercise (distance, time, route, etc.).

[2027] "Anonymization" refers to processing data so that individuals cannot be identified.

[2028] "Enterprise" refers to a legal entity or organization that provides goods or services.

[2029] "Targeted advertising" refers to advertising that is delivered to a specific demographic.

[2030] "Means of generating data" refers to the methods and techniques that create the data needed for a specific purpose.

[2031] "Subscription format" refers to a format in which a service can be used by paying a periodic fee.

[2032] "Smartphone application" refers to a software program that runs on a smartphone.

[2033] A system for implementing this invention includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for collecting the user's exercise data, anonymizing it and providing it to companies, and a means for generating data for companies to deliver targeted advertisements.

[2034] Hardware and Software Configuration

[2035] Hardware: Smartphone (iOS or Android)

[2036] Software: Python, Requests library, JSON library

[2037] Data processing and calculation

[2038] 1. User input: The user uses the smartphone application to input a destination or target exercise intensity.

[2039] 2. Use of generative AI: The server uses generative AI based on the user's input information to interactively suggest the optimal running route.

[2040] 3. Obtaining location information: The user's current location is obtained using the smartphone's GPS function.

[2041] 4. Collection of athletic data: User running data (distance, time, route, etc.) is collected and anonymized.

[2042] 5. Data provision: The collected exercise data is provided to companies, which then use this data to deliver targeted advertisements.

[2043] Examples

[2044] A user opens the smartphone app and enters their goal of "running 5km." The app then suggests the best route based on the user's current location. After the run, the app collects the user's running data, anonymizes it, and provides it to companies. Sporting goods stores use this data to deliver advertisements for running shoes to the user.

[2045] Examples of prompt statements

[2046] If a user inputs a goal of "running 5km", the AI ​​should suggest the best route to run 5km from the user's current location. Also, implement a function to collect the user's movement information as people flow data and provide it to companies.

[2047] In this way, not only can users receive recommendations for optimal running routes, but companies can also use the collected data to deliver targeted advertising.

[2048] The flow of the specific process in the application example 3 will be described with reference to FIG.

[2049] Step 1:

[2050] The user opens the smartphone application and inputs a destination or a target exercise intensity.

[2051] Input: Destination or target exercise intensity

[2052] Output: User input information

[2053] Specific actions: The user enters the destination or target exercise intensity into the app's input form and presses the submit button.

[2054] Step 2:

[2055] The server receives the user's input information and uses generative AI to interactively suggest the optimal running route.

[2056] Input: User input information

[2057] Output: Optimal running route

[2058] Specific operation: The server inputs the user's input information as prompts into the generative AI model and generates the optimal running route.

[2059] Step 3:

[2060] The device obtains the user's current location using the smartphone's GPS function.

[2061] Input: None (GPS function activation)

[2062] Output: User's current location

[2063] Specific operations: The device activates the GPS function, obtains the user's current location, and sends it to the server.

[2064] Step 4:

[2065] The server combines the user's current location information with the optimal running route and presents the route to the user.

[2066] Input: User's current location, optimal running route

[2067] Output: The running route presented to the user.

[2068] Specific operation: The server combines the current location information with the generated route and sends the route information to the user's smartphone.

[2069] Step 5:

[2070] The user starts running, and the device collects running data (distance, time, route) in real time.

[2071] Input: User's running data

[2072] Output: Collected running data

[2073] Specific operation: The device uses GPS and timer functions to record the user's running data in real time.

[2074] Step 6:

[2075] The server receives the collected running data, anonymizes it, and provides it to the company.

[2076] Input: Collected running data

[2077] Output: Anonymized running data

[2078] What it does: The server anonymizes the running data and sends it to the company's database.

[2079] Step 7:

[2080] Companies will generate targeted advertisements based on anonymized running data and deliver them to users.

[2081] Input: Anonymized running data

[2082] Output: Targeted ads

[2083] How it works: The company analyzes the data it receives, generates advertisements based on the user's interests and behavior, and delivers them to the user's smartphone.

[2084] In addition, 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.

[2085] "Example 1"

[2086] As one embodiment of the present invention, there is a system that combines an emotion engine that recognizes the user's emotions. In this system, when the user inputs a destination or a target exercise intensity, the generative AI automatically suggests a destination in a dialogue format based on the input information. Furthermore, the system acquires the user's location information and sells the information to companies as people flow data. An emotion engine that recognizes the user's emotions is also built in. This emotion engine recognizes emotions from the user's voice, facial expression, text input, etc., and the generative AI suggests a destination based on the emotion. Specifically, if the user inputs "running 5km" as a goal and the emotion of joy is recognized at that time, the AI ​​will take that emotion into consideration and suggest a running course around a beautiful park, for example.

[2087] "Example 2"

[2088] In another embodiment of the present invention, an emotion engine recognizes the user's emotion, and a generative AI suggests exercise intensity based on the emotion. Specifically, if the user expresses an emotion such as "I want to relieve stress," the AI ​​takes the emotion into account and suggests high-intensity exercise, for example.

[2089] "Example 3"

[2090] Furthermore, as another embodiment of the present invention, there is a system in which an emotion engine recognizes the emotion of a user, a generative AI suggests a destination based on that emotion, and based on that suggestion, the user's movement information is provided to a company as people flow data. Specifically, if a user expresses an emotion of "wanting to relax," the AI ​​takes that emotion into consideration and suggests, for example, a quiet cafe, and provides the user's movement information to the owner of the cafe or restaurant.

[2091] The process flow of each embodiment will be described below.

[2092] "Example 1"

[2093] Step 1: The user enters their destination or target exercise intensity into the app.

[2094] Step 2: Based on the input information, the generative AI automatically suggests destinations in an interactive format.

[2095] Step 3: Obtain user location information and sell that information to companies as people flow data.

[2096] Step 4: The emotion engine recognizes emotions from the user's voice, facial expressions, text input, etc.

[2097] Step 5: Generative AI suggests destinations based on the recognized emotions.

[2098] "Example 2"

[2099] Step 1: The emotion engine recognizes the user's emotion.

[2100] Step 2: Based on the recognized emotions, the generative AI suggests exercise intensity.

[2101] "Example 3"

[2102] Step 1: The emotion engine recognizes the user's emotion.

[2103] Step 2: Generative AI suggests destinations based on the recognized emotions.

[2104] Step 3: The user navigates based on the suggestion.

[2105] Step 4: User movement information is provided to companies as people flow data.

[2106] Example 1

[2107] Next, a description will be given of Example 1 of the embodiment 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".

[2108] In conventional systems, when users input their destination and exercise intensity, it was difficult to provide optimal suggestions that took into account their emotions and location information at the time. In addition, there were limited ways to effectively utilize users' location information, so it could not be used effectively when providing data to companies. This meant that improvements to the user experience and effective use of data were not fully achieved.

[2109] 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.

[2110] In this invention, the server includes a means for a user to input a destination or a target exercise intensity, a means for automatically suggesting a destination in an interactive format using generative AI based on the input information, a means for acquiring the user's location information, a means for recognizing the user's emotion, and a means for optimizing the destination based on the recognized emotion information. This makes it possible to suggest an optimal destination taking into account the user's emotion and location information, improving the user experience and enabling effective use of data provided to companies.

[2111] "User" refers to an individual who uses the system to input their destination and exercise intensity and receive suggestions.

[2112] "Destination" refers to the place or location the user wants to reach.

[2113] "Exercise intensity" refers to the strength or amount of exercise that a user aims for.

[2114] "Generative AI" refers to artificial intelligence that automatically suggests destinations in an interactive format based on information entered by the user.

[2115] "Interaction style" refers to the way in which a user and a system exchange information with each other.

[2116] "Location Information" means data that indicates a User's current geographic locatio...

Claims

1. A means for receiving an input of a destination or a target exercise intensity from a user; means for acquiring location information of the user; A means for suggesting a destination in an interactive format using generative AI based on the input information and the user's location information; means for recognizing an emotion of the user using an emotion engine; A means for optimizing a destination based on the recognized user emotion information; A system including:

2. The system of claim 1 , further comprising means for selling the user's location information as people flow data.

3. 3. The system according to claim 1 or 2, provided as a subscription-based smartphone application.

Images