system

Abstract

Provide a system. [Solution] means for receiving user input information; a means for obtaining real-time weather information; A means of understanding the congestion situation in the area, means for calculating an optimal walking route based on the user's input information, weather information, and congestion status; means for displaying the calculated walking route and points of interest to the user; A system including:

Description

[Technical Field]

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

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

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

[0004] Conventional walking route suggestion systems have difficulty providing optimal routes that meet the specific needs and objectives of users. Furthermore, they cannot calculate routes that take into account real-time information such as weather and congestion, which can make them inconvenient for users. Furthermore, they have issues with contributing to local revitalization, as users have fewer opportunities to explore new stores or unusual routes. [Means for solving the problem]

[0005] The present invention provides a system that provides optimal walking routes tailored to a user's specific needs based on user input information, real-time weather information, and local congestion. Specifically, the system includes a means for receiving user input information, a means for acquiring real-time weather information, a means for grasping local congestion, a means for calculating the optimal walking route based on this information, and a means for displaying the calculated walking route and points of interest to the user. This system allows users to explore routes they don't usually take and new stores, contributing to the revitalization of the local area.

[0006] "User input information" is information including the purpose of the walk, the desired duration, the current location, and so on.

[0007] "Weather information" is information about current and forecast weather conditions.

[0008] "Congestion status" refers to information about the density and flow of people and traffic in a particular area.

[0009] A "walking route" is a route that includes a route from a user's starting point to a destination and points of interest along the way.

[0010] "Points of interest" are interesting places such as new stores or landmarks located along the walking route.

[0011] The "means for calculating the optimal walking route" is a function that determines a walking route using an algorithm based on user input information, weather information, and congestion status.

[0012] "Means of display" refers to the function of visually providing information to the user using the device's display or AR technology. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0014] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0017] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0018] 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.

[0019] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] 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.

[0026] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0031] 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.

[0032] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0033] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0034] Overall system overview

[0035] This invention is a system that provides optimal walking routes based on information entered by the user, real-time weather information, and congestion status. This system provides users with opportunities to explore routes they don't usually take and new stores, contributing to the revitalization of local areas.

[0036] System Components

[0037] 1. User device (smartphone or AR device): Provides an interface where users can input the purpose of their walk, the required time, and their current location obtained via GPS. It also displays the calculated walking route and points of interest.

[0038] 2. Server: Receives requests from users and obtains information such as weather and congestion status using external APIs. Based on this information, it calculates the optimal walking route and sends it to the user's device.

[0039] 3. External API: An API that provides weather information and an API that provides congestion status.

[0040] Program processing overview

[0041] Enter and submit user information

[0042] 1. User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[0043] 2. User: Enter the desired duration (e.g. 1 hour).

[0044] 3. Device: Obtain current location using GPS function.

[0045] 4. Terminal: The user's input information and current location are compiled in JSON format and sent to the server.

[0046] Obtaining weather and congestion information

[0047] 1. Server: Receives requests from users.

[0048] Example: Relaxation purpose, required time 1 hour, current location Shinjuku Station.

[0049] 2. Server: Sends a request to the weather API to get the current weather information (e.g. sunny).

[0050] 3. Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[0051] Route calculation

[0052] 1. Server: Calculates the optimal walking route based on the user's input information, weather information, and congestion status obtained so far.

[0053] Example: Select a route that passes through Shinjuku Gyoen and leads to a new cafe.

[0054] 2. Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[0055] 3. Server: The optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the device.

[0056] Route presentation and AR information display

[0057] 1. Terminal: Interprets the route information received from the server and displays the route on a map.

[0058] 2. Device: Use the AR function to display markers or pop-ups at points of interest (e.g., new cafes or landmarks).

[0059] 3. User: Check the route through the app and start your walk.

[0060] Advertisement display

[0061] 1. Device: Prepares to display AR ads when approaching a specific point on the route.

[0062] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[0063] 2. User: Check the ads while walking and respond to the ads that interest them.

[0064] 3. Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[0065] In this way, this system not only provides users with the best walking route, but also contributes to revitalizing local commercial activity. By taking into account weather and congestion, it provides users with a comfortable walking experience and can also generate revenue from advertisers.

[0066] The processing flow will be explained below.

[0067] Step 1:

[0068] User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[0069] Step 2:

[0070] User: Enter the desired duration (e.g., 1 hour).

[0071] Step 3:

[0072] Device: Obtain current location using GPS function.

[0073] Step 4:

[0074] Terminal: The user's input information and current location are compiled in JSON format and sent to the server.

[0075] Step 5:

[0076] Server: Receives requests from users.

[0077] Example: Relaxation purpose, required time 1 hour, current location Shinjuku Station.

[0078] Step 6:

[0079] Server: Sends a request to the weather API to get current weather information (e.g. sunny).

[0080] Step 7:

[0081] Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[0082] Step 8:

[0083] Server: Calculates the optimal walking route based on the user's input information, weather information, and congestion status acquired so far.

[0084] Example: Select a route that passes through Shinjuku Gyoen and leads to a new cafe.

[0085] Step 9:

[0086] Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[0087] Step 10:

[0088] Server: Optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the terminal.

[0089] Step 11:

[0090] Terminal: Interprets the route information received from the server and displays the route on a map.

[0091] Step 12:

[0092] Device: Use the AR function to display markers and pop-ups at points of interest (e.g., new cafes or landmarks).

[0093] Step 13:

[0094] User: Check the route through the app and start the walk.

[0095] Step 14:

[0096] Device: Prepares to display AR ads as it approaches a specific point on its route.

[0097] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[0098] Step 15:

[0099] Users: Check out ads while walking and respond to ads that interest them.

[0100] Step 16:

[0101] Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[0102] Example 1

[0103] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0104] Conventional walking route provision systems have difficulty taking into account individual user objectives and real-time environmental factors (weather, congestion, etc.). Furthermore, they lack the functionality to stimulate local commercial activity through advertising. As a result, there is a need for systems that not only increase user satisfaction but also help explore new stores in the area and stimulate commercial activity.

[0105] 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.

[0106] In this invention, the server includes means for receiving user input information, means for acquiring real-time weather information, means for grasping the local congestion status, means for calculating an optimal walking route based on the user input information, the weather information, and the congestion status, means for displaying the calculated walking route and points of interest to the user, means for displaying advertisements when the user approaches points of interest, and means for collecting and accumulating the user's responses to the advertisements as statistical data. This makes it possible to provide an optimal walking route that takes into account the user's individual goals and real-time environmental factors. It can also realize support for local revitalization and commercial activities.

[0107] "User input information" refers to data provided by the user to the system, specifically the purpose of the walk (e.g., relaxation, exercise), the required time, current location, etc.

[0108] "Real-time weather information" refers to data indicating current weather conditions, obtained from an external weather API.

[0109] "Regional congestion status" is data indicating the current level of congestion in a specific area, and is obtained from an external congestion API.

[0110] "Calculating the optimal walking route" refers to the process of using an algorithm to calculate the optimal walking route for the user based on information input by the user, weather information, and congestion status.

[0111] "Calculated walking route" refers to route information derived by calculating the optimal walking route.

[0112] "Points of interest" refer to noteworthy places and stores along the walking route, and are intended to attract the user's interest.

[0113] "Augmented reality display means" refers to a function that uses AR (augmented reality) technology to display virtual information superimposed on real scenery.

[0114] The "means for displaying advertisements" refers to a function for displaying advertisement information when the user approaches a point of interest.

[0115] "Means for collecting users' responses to advertisements and accumulating them as statistical data" refers to the function of collecting data on the actions users take in response to displayed advertisements and saving this data as statistical information.

[0116] This invention is a system that provides optimal walking routes based on information entered by the user, real-time weather information, and congestion status. This system provides users with opportunities to explore routes they don't usually take and new stores, contributing to the revitalization of local areas.

[0117] System Components

[0118] 1. User device (smartphone or augmented reality device)

[0119] It provides an interface for users to input the purpose of their walk, the estimated time, and their current location obtained via GPS.

[0120] View calculated walking routes and points of interest.

[0121] 2. Server

[0122] Receives requests from users and obtains information using external APIs such as weather and congestion status.

[0123] Based on this information, the optimal walking route is calculated and sent to the user's terminal.

[0124] 3. External API

[0125] An API that provides weather information and an API that provides congestion status.

[0126] Program processing overview (example)

[0127] 1. Enter and submit user information

[0128] The user starts the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, or discovering new shops). For example, the user taps "Relax" on the app's menu screen.

[0129] The user inputs the desired time required (e.g., 1 hour). Specifically, the user inputs "1 hour" in the time input field and presses the submit button.

[0130] The device uses the GPS function to obtain the current location. The app calls the GPS module in the background to obtain the current latitude and longitude.

[0131] The user's input information and current location are compiled in JSON format and sent to the server.

[0132] 2. Obtaining weather and congestion information

[0133] The server receives a request from the user. Specifically, the server analyzes the HTTP request and obtains the user's purpose, required time, and current latitude and longitude.

[0134] The server sends a request to the weather API to obtain current weather information. The server sends the latitude and longitude of "Shinjuku Station" to the weather API and obtains the weather information "Sunny" in return.

[0135] The server sends a request to the congestion API to obtain the local congestion status. The server sends information about the area around "Shinjuku Station" to the congestion API, and receives the congestion status "slightly crowded" in return.

[0136] 3. Route calculation

[0137] The server calculates the optimal walking route based on user input, weather information, and traffic congestion. Specifically, the server applies an algorithm to generate a route that goes "via Shinjuku Gyoen → new cafe → return to Shinjuku Station."

[0138] The server applies an algorithm that prioritizes unusual routes and new stores, and adds points. For example, the algorithm adds "newly opened cafes" and "places where special events are held" to the route.

[0139] The server compiles optimal route information and points of interest in JSON format and sends it to the terminal.

[0140] 4. Route presentation and AR information display

[0141] The device interprets the route information received from the server and displays the route on a map. The app calls the map module and displays the route "Shinjuku Station → Shinjuku Gyoen → New Cafe."

[0142] The device uses augmented reality to display markers and pop-ups at points of interest. For example, the AR module displays a marker at the location of a "new cafe" and a pop-up with a "discount coupon."

[0143] The user checks the route through the app and starts the walk. The user checks the displayed route and actually starts the walk.

[0144] 5. Advertising

[0145] When the device approaches a specific point on the route, it prepares to display an advertisement. When the user approaches a cafe, the device calls the AR module and prepares a "special discount coupon."

[0146] Users can view ads while walking and interact with content they are interested in. For example, they can tap on a coupon displayed in an AR pop-up to view more information.

[0147] When a user takes an action on an advertisement, the terminal sends the information to the server and stores it as statistical data. When a user acquires a coupon, the information is sent to the server and recorded in the database.

[0148] Examples of prompt statements

[0149] When inputting a prompt to a generative AI model to suggest a route, use the following prompt:

[0150] "The current weather is sunny, the estimated travel time is one hour, and I'm at Shinjuku Station. Please suggest a recommended walking route for relaxation."

[0151] "It's cloudy, and I'd like to take a 30-minute walking route starting from Shinjuku Station for exercise. Please suggest a route that passes through new stores."

[0152] The system's main functions are to provide a comfortable walking experience by taking into account the user's individual needs and real-time environmental factors, and to support local commercial activities. Users can easily check their walking routes through the app and enjoy the fun of exploring new places. In addition, advertisements and collected statistical data are used by local businesses, contributing to the revitalization of commercial activities.

[0153] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0154] Step 1:

[0155] User: Launches the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[0156] Specific action: The user taps "Relax" on the app's menu screen.

[0157] Input: User intent

[0158] Output: Objective is selected

[0159] Step 2:

[0160] User: Enter the desired duration (e.g., 1 hour).

[0161] Specific behavior: The user enters "1 hour" in the time input field and presses the submit button.

[0162] Input: Time required

[0163] Output: Time is input

[0164] Step 3:

[0165] Device: Obtain current location using GPS function.

[0166] Specific behavior: The app calls the GPS module in the background to get the current latitude and longitude.

[0167] Input: GPS function

[0168] Output: Current location (latitude, longitude)

[0169] Step 4:

[0170] Terminal: The user's input information and current location are compiled in JSON format and sent to the server.

[0171] Specific operation: Generates JSON data and sends it to the server via an HTTP request.

[0172] Input: User's purpose, time required, current location

[0173] Output: Request sent to server

[0174] Step 5:

[0175] Server: Receives requests from users.

[0176] What it does: The server analyzes the HTTP request and obtains data about the user's purpose, time required, and current location.

[0177] Input: HTTP request

[0178] Output: User's purpose, time required, and current location

[0179] Step 6:

[0180] Server: Sends a request to the weather API to get current weather information.

[0181] Specific operation: Sends an HTTP request to the weather API and receives weather information.

[0182] Input: Current location (latitude, longitude)

[0183] Output: Weather information (e.g. sunny)

[0184] Step 7:

[0185] Server: Sends a request to the congestion API to obtain the local congestion status.

[0186] Specific operation: Send an HTTP request to the congestion API and receive congestion information.

[0187] Input: Current location (latitude, longitude)

[0188] Output: Congestion information (e.g., slightly crowded)

[0189] Step 8:

[0190] Server: Calculates the optimal walking route based on user input, weather information, and congestion status.

[0191] What it does: Apply algorithms to calculate optimal routes and points of interest.

[0192] Input: User's purpose, travel time, current location, weather information, congestion information

[0193] Output: Optimal walking route (e.g. Shinjuku Gyoen → New cafe)

[0194] Step 9:

[0195] Server: Optimal route information and points of interest are compiled in JSON format and sent to the terminal.

[0196] Specific operation: Generates JSON data and sends it to the terminal as an HTTP response.

[0197] Input: Best walking route, points of interest

[0198] Output: Sending a response to the device

[0199] Step 10:

[0200] Terminal: Interprets the route information received from the server and displays the route on a map.

[0201] Specific operation: Calls the map module and displays the route on the map.

[0202] Input: Route information, points of interest

[0203] Output: Route display on map

[0204] Step 11:

[0205] Device: Use the AR function to display markers and pop-ups at points of interest.

[0206] Specific operation: The AR module displays markers and popups at points of interest.

[0207] Input: Points of Interest

[0208] Output: AR display

[0209] Step 12:

[0210] User: Check the route through the app and start the walk.

[0211] Specific behavior: The user checks the displayed route and starts walking.

[0212] Input: Route display (map, AR)

[0213] Output: Start of walk

[0214] Step 13:

[0215] Terminal: Prepares to display advertisements as you approach certain points along your route.

[0216] Specific operation: The AR module detects when the user approaches a specific point and prepares an advertisement.

[0217] Input: GPS data, specific points

[0218] Output: Ad Ready

[0219] Step 14:

[0220] Users: Check out ads while walking and respond to ads that interest them.

[0221] Specific behavior: The user taps on the coupon displayed in the AR popup to view more information.

[0222] Input: AR ad

[0223] Output: User response

[0224] Step 15:

[0225] Terminal: When a user takes action on an advertisement, the information is sent to the server and stored as statistical data.

[0226] Specific behavior: Records user actions and sends them to the server.

[0227] Input: User action data

[0228] Output: Sending data to the server, accumulating statistical data

[0229] (Application example 1)

[0230] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0231] In today's world, it is difficult for users to enjoy a pleasant walk and discover new local commercial facilities at the same time. This becomes even more difficult when external factors such as weather and congestion affect the activities. Therefore, there is a need for a system that takes weather and congestion into account and provides optimal routes that allow users to comfortably discover new stores and commercial facilities. Furthermore, utilizing such a system to revitalize local commercial activities is also an important issue.

[0232] 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.

[0233] In this invention, the server includes a means for receiving user input information, a means for acquiring real-time weather information, and a means for grasping the local congestion status, thereby making it possible to calculate optimal walking routes and shopping routes based on the user input information, weather information, and congestion status, and display them to the user.

[0234] "User input information" refers to information such as purpose, required time, and current location that the user provides to the system.

[0235] "Real-time weather information" refers to current weather and forecast information based on that weather, and is data obtained from an external API.

[0236] "Regional congestion status" is information indicating the degree of congestion of people and vehicles in a specified area, and is also data obtained from an external API.

[0237] The "optimal walking route" is the most suitable walking route for the user, calculated based on the user's input information, real-time weather information, and local congestion status.

[0238] "Points of interest" are spots such as new stores and landmarks that the user may be interested in along the optimal walking route.

[0239] A "purchase path" is the optimal route for a user to reach a particular physical store, and may include a walking route.

[0240] "Recommended stores" are commercial facilities and stores that the system recommends to users based on its own algorithms and data.

[0241] "Augmented reality display means" refers to a means for displaying points of interest and recommended stores using augmented reality technology, and utilizes devices such as smart glasses and head-mounted displays.

[0242] Overall system overview

[0243] This invention is a system that provides optimal walking and shopping routes based on information entered by users, real-time weather information, and congestion status. This system uses devices such as smartphones, smart glasses, and head-mounted displays to provide users with opportunities to explore routes they don't usually take and new stores, thereby revitalizing local commercial activity.

[0244] Program processing overview

[0245] Enter and submit user information

[0246] The server receives the user's purpose information, required time, and current location obtained by GPS input using a smartphone or AR device. The user inputs the purpose of the walk (e.g., relaxation, exercise, discovering new shops) and the desired duration (e.g., 1 hour), and the device obtains the user's current location using its GPS function. The user's input information and current location are compiled in JSON format and sent to the server.

[0247] Obtaining weather and congestion information

[0248] The server receives a request from a user and obtains weather information and congestion information from the weather API and congestion API, respectively. For example, the server sends a request to the weather API to obtain current weather information (e.g., sunny), and then sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[0249] Route calculation

[0250] The server calculates optimal walking and shopping routes based on the user's input information, weather information, and congestion status. For example, it selects a route that passes through Shinjuku Gyoen National Garden and finds new cafes, and applies an algorithm that prioritizes exploring routes that are not usually taken and new commercial facilities. The calculation results, including optimal route information and points of interest, are sent to the device in JSON format.

[0251] Route presentation and AR information display

[0252] The device interprets the route information received from the server and displays the route on a map. It also uses AR functionality to display markers and pop-ups at points of interest and recommended stores. The user can check the suggested optimal route through the app and begin their walk or shopping.

[0253] The hardware used includes smartphones, smart glasses (e.g., Google® Glass®, HoloLens®), and head-mounted displays (e.g., Oculus Rift, HTC Vive).The software used includes Python, the Requests module (API requests), Geopy (GPS information acquisition), OpenWeatherMap API (weather information acquisition), and Crowd API (crowding status acquisition).

[0254] Prompts and Sentence Examples

[0255] "Create a program that suggests the best walking route based on user input and current location, taking into account weather and traffic conditions. The program's functionality would include:

[0256] 1. Obtain the user's purpose, required time, and current location.

[0257] 2. Collect weather and crowd data using weather and crowd APIs.

[0258] 3. Calculate routes based on weather, congestion, and user preferences.

[0259] 4. The calculation results are provided to the user and displayed on a smartphone or AR device.

[0260] Example of the results:

[0261] Shinjuku Station: Starting point

[0262] Shinjuku Gyoen: A place to relax

[0263] New Cafe: What to Look For

[0264] Please create your code based on this."

[0265] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0266] Step 1:

[0267] The user launches a smartphone app or AR device and inputs the purpose of their walk (e.g., relaxation, exercise, or discovering new shops) and the desired duration (e.g., 1 hour). The device also uses its GPS function to obtain the user's current location. This information is then compiled as user input.

[0268] Input: Destination, travel time, current location

[0269] Output: User input information (purpose, time required, current location in JSON format)

[0270] Step 2:

[0271] The terminal compiles the acquired user input information into JSON format and sends it to the server.

[0272] Input: User input information (purpose, time required, current location in JSON format)

[0273] Output: User input sent to the server

[0274] Step 3:

[0275] The server receives the user's input information, sends a request to the weather API to obtain current weather information, and sends a request to the congestion API to obtain local congestion information.

[0276] Input: User input information (purpose, time required, current location in JSON format)

[0277] Data processing: Weather API request, Congestion API request

[0278] Output: Weather information, congestion information (JSON format)

[0279] Step 4:

[0280] The server calculates optimal walking and shopping routes based on weather information, congestion information, and user input, using an algorithm that prioritizes less commonly used routes and new commercial facilities.

[0281] Input: User input information, weather information, and congestion information (all in JSON format)

[0282] Data calculation: Calculation of optimal routes and purchase paths (using algorithms)

[0283] Output: Optimal walking and shopping routes, points of interest (JSON format)

[0284] Step 5:

[0285] The server compiles the calculated optimal walking route, shopping route, and points of interest in JSON format and sends it to the device.

[0286] Input: Optimal walking route, shopping route, points of interest (JSON format)

[0287] Output: Route information and points of interest sent to the device

[0288] Step 6:

[0289] The terminal interprets the route information and points of interest received from the server and displays the route on a map. It also uses an augmented reality display means to display markers and pop-ups at points of interest and recommended stores.

[0290] Input: Route information and points of interest sent to the device (JSON format)

[0291] Output: The route, points of interest, markers and popups displayed to the user

[0292] Step 7:

[0293] Users can view suggested routes and begin their walk or purchase through the app. As users approach specific points of interest, the device displays additional information and advertisements.

[0294] Input: Route information and points of interest confirmed by the user

[0295] Output: Additional information or advertisements based on user behavior

[0296] These processing steps allow users to have a comfortable and efficient walking and shopping experience, and also contribute to the discovery of new commercial facilities and the revitalization of local areas.

[0297] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0298] Overall system overview

[0299] This system provides optimal walking routes based on real-time weather and congestion information, along with information entered by the user. By combining this with an emotion engine that recognizes the user's emotions, the system selects routes and suggests points of interest that match the user's psychological state.

[0300] System Components

[0301] 1. User device (smartphone or AR device): Provides an interface where users can input the purpose of their walk, the required time, and their current location obtained via GPS. It also uses an emotion engine to recognize the user's emotions and displays the calculated walking route and points of interest.

[0302] 2. Server: Receives requests from users and obtains information such as weather and congestion status using external APIs. Furthermore, it calculates the optimal walking route based on this information and the user's emotional information, and sends it to the user's device.

[0303] 3. External API: An API that provides weather information and an API that provides congestion status.

[0304] 4. Emotion engine: Uses the user's camera or other sensors to recognize emotions from the user's facial expressions and voice.

[0305] Program processing overview

[0306] Enter and submit user information

[0307] 1. User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[0308] 2. User: Enter the desired duration (e.g. 1 hour).

[0309] 3. Device: Obtain current location using GPS function.

[0310] 4. Terminal: Activate the emotion engine and recognize the user's emotions.

[0311] 5. Terminal: User input information, current location, and emotion information are compiled in JSON format and sent to the server.

[0312] Obtaining weather and congestion information

[0313] 1. Server: Receives requests from users.

[0314] Example: Purpose: Relaxation, Time required: 1 hour, Current location: Shinjuku Station, Emotion: "Slightly stressed."

[0315] 2. Server: Sends a request to the weather API to get the current weather information (e.g. sunny).

[0316] 3. Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[0317] Route calculation

[0318] 1. Server: Calculates the optimal walking route based on the user's input information, weather information, congestion status, and emotional information acquired so far.

[0319] Example: Select a route that passes through Shinjuku Gyoen National Garden and leads to a new cafe. Prioritize quiet areas to reduce user stress.

[0320] 2. Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[0321] 3. Server: The optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the device.

[0322] Route presentation and AR information display

[0323] 1. Terminal: Interprets the route information received from the server and displays the route on a map.

[0324] 2. Device: Use the AR function to display markers or pop-ups at points of interest (e.g., new cafes or landmarks).

[0325] 3. User: Check the route through the app and start your walk.

[0326] Example: Take a route that passes through Shinjuku Gyoen National Garden and arrive at a new cafe.

[0327] Advertisement display

[0328] 1. Device: Prepares to display AR ads when approaching a specific point on the route.

[0329] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[0330] 2. User: Check the ads while walking and respond to the ads that interest them.

[0331] 3. Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[0332] In this way, the system provides an optimal walking route based on the user's emotional state, providing a more personalized experience for the user. By comprehensively taking into account weather, congestion, and emotional information, the system can provide a comfortable walking experience for the user and contribute to revitalizing local commercial activity.

[0333] The processing flow will be explained below.

[0334] Step 1:

[0335] User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[0336] Step 2:

[0337] User: Enter the desired duration (e.g., 1 hour).

[0338] Step 3:

[0339] Device: Obtain current location using GPS function.

[0340] Step 4:

[0341] Device: Uses a camera or microphone to provide the user's face and voice to the emotion engine.

[0342] Step 5:

[0343] On the device: The emotion engine analyzes the user's emotions and identifies their current emotional state (e.g., stress, anxiety, joy).

[0344] Step 6:

[0345] Terminal: User input information, current location, and emotion information are compiled in JSON format and sent to the server.

[0346] Step 7:

[0347] Server: Receives requests from users.

[0348] Example: Purpose: Relaxation, Time required: 1 hour, Current location: Shinjuku Station, Emotion: "Slightly stressed."

[0349] Step 8:

[0350] Server: Sends a request to the weather API to get current weather information (e.g. sunny).

[0351] Step 9:

[0352] Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[0353] Step 10:

[0354] Server: Calculates the optimal walking route based on user input, weather information, congestion status, and emotional information.

[0355] If the emotion is "stress," prioritize quieter routes and relaxing spots.

[0356] Step 11:

[0357] Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[0358] Step 12:

[0359] Server: Optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the terminal.

[0360] Step 13:

[0361] Terminal: Interprets the route information received from the server and displays the route on a map.

[0362] Step 14:

[0363] Device: Use the AR function to display markers and pop-ups at points of interest (e.g., new cafes or landmarks).

[0364] Step 15:

[0365] User: Check the route through the app and start the walk.

[0366] Step 16:

[0367] Device: Prepares to display AR ads when approaching a specific point on the route.

[0368] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[0369] Step 17:

[0370] Users: Check out ads while walking and respond to ads that interest them.

[0371] Step 18:

[0372] Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[0373] Example 2

[0374] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0375] Conventional walking route provision systems calculate routes by taking into account only weather information and congestion status, and therefore are unable to provide optimal routes that reflect the user's psychological state. Furthermore, there is a lack of means to provide a personalized experience that takes into account the user's emotions. This makes it difficult to provide walking routes that satisfy users, and there are also issues with limited contribution to local commercial activity.

[0376] 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 receiving user input information, a means for acquiring real-time weather information, a means for grasping the local congestion state, a means for recognizing the user's emotions, a means for calculating an optimal walking route based on the user's input information, weather information, congestion state, and emotion information, and a means for displaying the calculated walking route and points of interest to the user. This makes it possible to provide a personalized optimal walking route that takes into account the user's psychological state, real-time weather, and congestion state.

[0377] "User input information" refers to information such as the purpose of the walk and the required time provided by the user to the system.

[0378] "Real-time weather information" means data about current weather conditions in a specified area.

[0379] "Local congestion status" is information about the current level of congestion of people and vehicles at a specific location or route.

[0380] "Means for recognizing the user's emotions" refers to technology that analyzes the user's facial expressions and voice to determine their psychological state and emotions.

[0381] The "means for calculating the optimal walking route" is an algorithm or program for calculating the most suitable walking route for the user based on the user's input information and real-time weather information, congestion status, and emotional information.

[0382] The "calculated walking route" is a walking route derived by the means for calculating the optimal walking route described above.

[0383] "Points of interest" are places that are considered worth visiting by the user during a walk, such as new stores or landmarks.

[0384] "Augmented reality display means" is a technology that displays digital information overlaid on real-world scenery, and is a means of visually providing information such as points of interest on the user's device.

[0385] Overall system overview

[0386] This system provides optimal walking routes based on user input, real-time weather information, and local congestion status. The system also features an emotion engine that recognizes the user's emotions, and selects routes and suggests points of interest that match the user's psychological state.

[0387] System Components

[0388] 1. User device (smartphone or augmented reality device): The user inputs the purpose and duration of the walk, obtains the current location using GPS, and uses an emotion engine to recognize the user's emotions and displays the calculated walking route and points of interest.

[0389] 2. Server: Receives requests from users and obtains information such as weather and congestion status using external APIs. Based on this information and the user's emotional state, the server calculates the optimal walking route and sends it to the user's device.

[0390] 3. External API: An API that provides weather information and an API that provides congestion information.

[0391] 4. Emotion engine: Uses the user's camera or other sensors to recognize emotions from the user's facial expressions and voice.

[0392] Program processing overview

[0393] Enter and submit user information

[0394] The user opens the smartphone app and selects the purpose of their walk (e.g., relaxation, exercise, or discovering new stores). Next, they enter the desired duration (e.g., 1 hour), and the device uses its GPS function to obtain their current location. The device then activates an emotion engine that analyzes the user's facial expressions and voice to recognize their emotions. This information is then compiled in JSON format and sent to the server.

[0395] Obtaining weather and congestion information

[0396] The server receives a request from the user, sends a request to the weather API to get current weather information, and sends a request to the congestion API to get the local congestion status.

[0397] Walking route calculation

[0398] The server calculates the optimal walking route based on the user's input information, weather information, congestion status, and emotional information it has acquired so far. To reduce user stress, it prioritizes quiet areas and selects routes that include new shops and points of interest. This information is compiled in JSON format and sent to the user's device.

[0399] Route presentation and AR information display

[0400] The user's device interprets the route information received from the server and displays the route on a map. It also uses AR functionality to display markers and pop-ups at points of interest (new cafes and landmarks). The user checks the route through the app and begins their walk.

[0401] Specific actions

[0402] A user wants to take a relaxing walk, inputs the required time of one hour and their current location as Shinjuku Station, and the emotion engine recognizes the user as slightly stressed. The server retrieves "sunny" from the weather API and "somewhat crowded around Shinjuku Station" from the congestion API. The server then calculates a route to the cafe via Shinjuku Gyoen and sends it to the user.

[0403] Prompt Sentence Examples

[0404] "If the user selects "relaxation" as the purpose of the walk, the duration is one hour, the current location is Shinjuku Station, and the emotion is "slightly stressed," the system should calculate the optimal walking route via Shinjuku Gyoen."

[0405] "Recognize the user's emotional state and suggest optimal walking routes and points of interest based on that."

[0406] In this way, the system comprehensively considers the user's psychological state, real-time weather, and congestion, and provides the user with an optimal personalized walking route, which can also contribute to revitalizing local commercial activity.

[0407] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0408] Step 1:

[0409] User: Opens the smartphone app and selects the purpose of the walk. For example, the user selects "relaxation." This is the input information.

[0410] Step 2:

[0411] User: Enter the desired duration. For example, specify "1 hour." This input information will also be used in subsequent processing.

[0412] Step 3:

[0413] Device: Uses GPS to obtain current location. For example, obtain "Shinjuku Station." This is added to the input information.

[0414] Step 4:

[0415] Device: The emotion engine is activated and the smartphone's camera and microphone are used to recognize the user's emotions. As a result of emotion analysis, information such as "slightly stressed" is obtained. This emotional information also becomes part of the input data.

[0416] Step 5:

[0417] Device: The user's input information, current location, and emotion information are compiled into JSON format and sent to the server as an HTTP POST request. Specifically, the JSON structure shown below is generated.

[0418] json

[0419] {

[0420] "Purpose": "Relax",

[0421] "Duration": "1 hour",

[0422] "Current Location": "Shinjuku Station",

[0423] "Emotion": "Slightly stressed"

[0424] }

[0425] Step 6:

[0426] Server: Analyzes the request received from the user and sends a request to the weather API to obtain current weather information. For example, the information obtained is "sunny." This becomes the newly added input information.

[0427] Step 7:

[0428] Server: Next, a request is sent to the congestion API to obtain the local congestion status. For example, information such as "The area around Shinjuku Station is somewhat crowded" is obtained. This congestion information also becomes part of the input data.

[0429] Step 8:

[0430] Server: Calculates the optimal walking route based on the user's input information, weather information, congestion status, and emotional information acquired so far. For example, it calculates a route to reach a cafe via Shinjuku Gyoen. The calculated route information and points of interest are generated as output.

[0431] Step 9:

[0432] Server: The output walking route information and points of interest are compiled into JSON format and sent to the device. Specifically, the JSON structure shown below is generated.

[0433] json

[0434] {

[0435] "Route": "Route via Shinjuku Gyoen",

[0436] "Featured": "New Cafe"

[0437] }

[0438] Step 10:

[0439] Terminal: Analyzes the JSON data received from the server and displays the route in a map application. For example, it draws a "route to reach the cafe via Shinjuku Gyoen" on the map.

[0440] Step 11:

[0441] Device: Activate the AR function to display markers and pop-ups at points of interest along the route. For example, place AR markers at "new cafes" or "landmarks."

[0442] Step 12:

[0443] User: Check the route and points of interest on the app screen and start a walk. For example, execute "Go through Shinjuku Gyoen" and "Reach the cafe."

[0444] Step 13:

[0445] Device: Prepares to display AR advertisements when the user approaches a specific point on the route. For example, "approaching a cafe" and "displaying an AR advertisement with a special discount coupon."

[0446] Step 14:

[0447] User: Check out advertisements (e.g., special discount coupons) while walking and respond to advertisements that interest them.

[0448] Step 15:

[0449] Terminal: When a user takes an action on an advertisement (for example, obtains a coupon), the information is sent to the server in JSON format and stored in a database as statistical data.

[0450] (Application example 2)

[0451] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0452] Conventional walking route suggestion systems have limited means of taking into account weather information and local congestion, making it difficult to select an optimal route that reflects the user's psychological state. Furthermore, for certain tasks, such as delivery, it has not been possible to provide an optimal route that takes into account the psychological state of the delivery staff. This has resulted in a lack of routes that are comfortable and efficient for both users and delivery staff.

[0453] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user input information, means for acquiring real-time weather information, means for understanding the local congestion situation, means for recognizing the user's emotions, means for selecting a route and suggesting points of interest based on the user's psychological state, means for displaying the calculated walking route and points of interest to the user, means for providing the optimal delivery route taking into account the psychological state of the delivery staff, and means for displaying information and advertisements when approaching specific points. This makes it possible to provide the user and delivery staff with optimal routes and information that comprehensively take into account their psychological state and the external environment.

[0454] "User input information" refers to information sent by the user via the terminal, including the user's current location, destination, required travel time, and other requirements.

[0455] "Real-time weather information" refers to the latest weather data obtained from external APIs, etc., and includes current weather and forecast information.

[0456] "Regional congestion status" is information indicating the degree of concentration of people and vehicles in a specific area, and is obtained from external APIs, etc.

[0457] "User emotions" refers to analyzing the user's psychological state and mood using cameras, audio sensors, etc.

[0458] "Route selection based on psychological state" refers to the process of selecting the most suitable route for a user based on the user's emotional information.

[0459] "Points of interest" refer to places, stores, etc. that may catch the user's interest while walking or during delivery.

[0460] "The psychological state of delivery staff" refers to the mental state and stress level of the staff performing delivery work.

[0461] The "optimal delivery route" refers to the most efficient and comfortable route calculated by comprehensively taking into consideration the mental state of the delivery staff, weather information, and congestion conditions.

[0462] "Means for displaying information or advertisements" refers to a method for visually displaying information or advertisements related to a location to a user when the user approaches a specific point.

[0463] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to specific embodiments.

[0464] Overall system configuration

[0465] The system collects and analyzes user input, real-time weather information, local congestion status, and user sentiment information to provide the optimal walking or delivery route. The system includes the following main components:

[0466] 1. User device (smartphone or AR device)

[0467] It provides an interface for collecting and sending user input information, current location, and emotion information to the server.

[0468] It displays the optimal route and points of interest, and displays information and advertisements when you approach certain points.

[0469] 2. Server

[0470] Receive requests from users and obtain weather information and congestion status.

[0471] The optimal route is calculated based on the user's input information, weather information, congestion status, and emotional information, and transmitted to the user.

[0472] 3. External API

[0473] API for obtaining weather information (e.g. OpenWeatherMap API)

[0474] API to obtain congestion status (e.g., Google Maps Traffic API)

[0475] 4. Emotion Engine

[0476] APIs that utilize camera and audio sensors to recognize user emotions (e.g., Microsoft® Azure® Face API)

[0477] Program processing

[0478] The program in this system works as follows:

[0479] 1. Enter and submit user information

[0480] The user uses the user terminal to input the destination of the walk or delivery, the required time, the current location, etc.

[0481] The emotion engine is activated and recognizes emotions from the user's facial expressions and voice.

[0482] This information is compiled in JSON format and sent to the server.

[0483] 2. Obtaining weather information and congestion status

[0484] The server uses an external API to obtain current weather information and local congestion status.

[0485] 3. Route calculation

[0486] The server calculates the optimal walking or delivery route based on the user's input information, weather information, congestion status, and emotional information.

[0487] For delivery staff, the system takes into account their psychological state and provides routes that minimize stress, including points of interest that match the user's specified objectives.

[0488] 4. Route presentation and information display

[0489] The calculated route information and points of interest are transmitted to the user terminal.

[0490] The user terminal displays route information on a map, and also displays information and advertisements when the user approaches a specific point.

[0491] Specific examples

[0492] For example, if a delivery staff member inputs "Shinjuku Station" as their current location and their emotional information is recognized as "slightly stressed," the server will calculate the optimal route to the delivery destination, taking into account the current weather information (e.g., sunny) and congestion status (e.g., slightly crowded), prioritizing quieter routes. Additionally, when the delivery staff member approaches the delivery destination, specific information and advertisements will be displayed in AR.

[0493] The system can use a generative AI model with prompts like this:

[0494] "If the user is stressed, if the weather is bad, calculate the optimal delivery route with a focus on safety."

[0495] "If a user wants to discover new stores, calculate a walking route that reflects that desire."

[0496] In this way, the embodiments of the invention provide specific means for providing an optimal experience by comprehensively considering the psychology and environmental information of the user and delivery staff.

[0497] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0498] Step 1:

[0499] The user uses the device to input their current location, destination, purpose of walk or delivery, and required time. This information is formatted in JSON format. The device also uses the camera and microphone to collect the user's emotional data, which is analyzed by the emotion engine. The results of this analysis are also added to the JSON format. Input data: current location, destination, purpose of walk or delivery, required time, emotional data. Output data: input information and emotional data in JSON format.

[0500] Step 2:

[0501] The device sends formatted JSON formatted data to the server. The server receives this data and begins parsing it. Input data: Input information and emotion data in JSON format. Output data: None.

[0502] Step 3:

[0503] The server uses an external API to get real-time weather information based on the user's current location. It sends a request to the weather API (e.g., OpenWeatherMap API) and receives weather information as a response. Input data: current location. Output data: weather information.

[0504] Step 4:

[0505] The server also uses an external API to obtain the local congestion status based on the user's current location. It sends a request to the congestion status API (e.g., Google Maps Traffic API) and receives congestion status data as a response. Input data: current location. Output data: congestion status data.

[0506] Step 5:

[0507] The server integrates the received user input information, emotion data, weather information, and congestion status to calculate the optimal walking or delivery route. A route calculation algorithm is used to select a route that takes into account the user's psychological state and congestion status. Input data: User input information, emotion data, weather information, congestion status data. Output data: Optimal route information.

[0508] Step 6:

[0509] The server formats the calculated optimal route information and points of interest in JSON format and sends it to the terminal. Input data: optimal route information, points of interest information. Output data: route information and points of interest in JSON format.

[0510] Step 7:

[0511] The device analyzes the route information and points of interest in JSON format received from the server and displays them to the user through a map app or AR display. When the user approaches a specific point, related information or advertisements are displayed. Input data: Route information and points of interest in JSON format. Output data: Visual display to the user.

[0512] Step 8:

[0513] The user begins traveling along the route and reaches a specific point of interest or delivery destination. The user's behavior data and collected ad response data are then sent to the server and used for statistical analysis. Input data: user behavior data, ad response data. Output data: statistical data.

[0514] Through the above steps, a system is realized that provides optimal routes and information that comprehensively consider the user's emotional state and external environmental information.

[0515] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0516] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0517] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0518] [Second embodiment]

[0519] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0520] 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.

[0521] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0522] 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.

[0523] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0524] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0525] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0526] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0527] 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.

[0528] 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.

[0529] 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.

[0530] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0531] Overall system overview

[0532] This invention is a system that provides optimal walking routes based on information entered by the user, real-time weather information, and congestion status. This system provides users with opportunities to explore routes they don't usually take and new stores, contributing to the revitalization of local areas.

[0533] System Components

[0534] 1. User device (smartphone or AR device): Provides an interface where users can input the purpose of their walk, the required time, and their current location obtained via GPS. It also displays the calculated walking route and points of interest.

[0535] 2. Server: Receives requests from users and obtains information such as weather and congestion status using external APIs. Based on this information, it calculates the optimal walking route and sends it to the user's device.

[0536] 3. External API: An API that provides weather information and an API that provides congestion status.

[0537] Program processing overview

[0538] Enter and submit user information

[0539] 1. User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[0540] 2. User: Enter the desired duration (e.g. 1 hour).

[0541] 3. Device: Obtain current location using GPS function.

[0542] 4. Terminal: The user's input information and current location are compiled in JSON format and sent to the server.

[0543] Obtaining weather and congestion information

[0544] 1. Server: Receives requests from users.

[0545] Example: Relaxation purpose, required time 1 hour, current location Shinjuku Station.

[0546] 2. Server: Sends a request to the weather API to get the current weather information (e.g. sunny).

[0547] 3. Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[0548] Route calculation

[0549] 1. Server: Calculates the optimal walking route based on the user's input information, weather information, and congestion status obtained so far.

[0550] Example: Select a route that passes through Shinjuku Gyoen and leads to a new cafe.

[0551] 2. Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[0552] 3. Server: The optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the device.

[0553] Route presentation and AR information display

[0554] 1. Terminal: Interprets the route information received from the server and displays the route on a map.

[0555] 2. Device: Use the AR function to display markers or pop-ups at points of interest (e.g., new cafes or landmarks).

[0556] 3. User: Check the route through the app and start your walk.

[0557] Advertisement display

[0558] 1. Device: Prepares to display AR ads when approaching a specific point on the route.

[0559] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[0560] 2. User: Check the ads while walking and respond to the ads that interest them.

[0561] 3. Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[0562] In this way, this system not only provides users with the best walking route, but also contributes to revitalizing local commercial activity. By taking into account weather and congestion, it provides users with a comfortable walking experience and can also generate revenue from advertisers.

[0563] The processing flow will be explained below.

[0564] Step 1:

[0565] User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[0566] Step 2:

[0567] User: Enter the desired duration (e.g., 1 hour).

[0568] Step 3:

[0569] Device: Obtain current location using GPS function.

[0570] Step 4:

[0571] Terminal: The user's input information and current location are compiled in JSON format and sent to the server.

[0572] Step 5:

[0573] Server: Receives requests from users.

[0574] Example: Relaxation purpose, required time 1 hour, current location Shinjuku Station.

[0575] Step 6:

[0576] Server: Sends a request to the weather API to get current weather information (e.g. sunny).

[0577] Step 7:

[0578] Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[0579] Step 8:

[0580] Server: Calculates the optimal walking route based on the user's input information, weather information, and congestion status acquired so far.

[0581] Example: Select a route that passes through Shinjuku Gyoen and leads to a new cafe.

[0582] Step 9:

[0583] Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[0584] Step 10:

[0585] Server: Optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the terminal.

[0586] Step 11:

[0587] Terminal: Interprets the route information received from the server and displays the route on a map.

[0588] Step 12:

[0589] Device: Use the AR function to display markers and pop-ups at points of interest (e.g., new cafes or landmarks).

[0590] Step 13:

[0591] User: Check the route through the app and start the walk.

[0592] Step 14:

[0593] Device: Prepares to display AR ads as it approaches a specific point on its route.

[0594] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[0595] Step 15:

[0596] Users: Check out ads while walking and respond to ads that interest them.

[0597] Step 16:

[0598] Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[0599] Example 1

[0600] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0601] Conventional walking route provision systems have difficulty taking into account individual user objectives and real-time environmental factors (weather, congestion, etc.). Furthermore, they lack the functionality to stimulate local commercial activity through advertising. As a result, there is a need for systems that not only increase user satisfaction but also help explore new stores in the area and stimulate commercial activity.

[0602] 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.

[0603] In this invention, the server includes means for receiving user input information, means for acquiring real-time weather information, means for grasping the local congestion status, means for calculating an optimal walking route based on the user input information, the weather information, and the congestion status, means for displaying the calculated walking route and points of interest to the user, means for displaying advertisements when the user approaches points of interest, and means for collecting and accumulating the user's responses to the advertisements as statistical data. This makes it possible to provide an optimal walking route that takes into account the user's individual goals and real-time environmental factors. It can also realize support for local revitalization and commercial activities.

[0604] "User input information" refers to data provided by the user to the system, specifically the purpose of the walk (e.g., relaxation, exercise), the required time, current location, etc.

[0605] "Real-time weather information" refers to data indicating current weather conditions, obtained from an external weather API.

[0606] "Regional congestion status" is data indicating the current level of congestion in a specific area, and is obtained from an external congestion API.

[0607] "Calculating the optimal walking route" refers to the process of using an algorithm to calculate the optimal walking route for the user based on information input by the user, weather information, and congestion status.

[0608] "Calculated walking route" refers to route information derived by calculating the optimal walking route.

[0609] "Points of interest" refer to noteworthy places and stores along the walking route, and are intended to attract the user's interest.

[0610] "Augmented reality display means" refers to a function that uses AR (augmented reality) technology to display virtual information superimposed on real scenery.

[0611] The "means for displaying advertisements" refers to a function for displaying advertisement information when the user approaches a point of interest.

[0612] "Means for collecting users' responses to advertisements and accumulating them as statistical data" refers to the function of collecting data on the actions users take in response to displayed advertisements and saving this data as statistical information.

[0613] This invention is a system that provides optimal walking routes based on information entered by the user, real-time weather information, and congestion status. This system provides users with opportunities to explore routes they don't usually take and new stores, contributing to the revitalization of local areas.

[0614] System Components

[0615] 1. User device (smartphone or augmented reality device)

[0616] It provides an interface for users to input the purpose of their walk, the estimated time, and their current location obtained via GPS.

[0617] View calculated walking routes and points of interest.

[0618] 2. Server

[0619] Receives requests from users and obtains information using external APIs such as weather and congestion status.

[0620] Based on this information, the optimal walking route is calculated and sent to the user's terminal.

[0621] 3. External API

[0622] An API that provides weather information and an API that provides congestion status.

[0623] Program processing overview (example)

[0624] 1. Enter and submit user information

[0625] The user starts the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, or discovering new shops). For example, the user taps "Relax" on the app's menu screen.

[0626] The user inputs the desired time required (e.g., 1 hour). Specifically, the user inputs "1 hour" in the time input field and presses the submit button.

[0627] The device uses the GPS function to obtain the current location. The app calls the GPS module in the background to obtain the current latitude and longitude.

[0628] The user's input information and current location are compiled in JSON format and sent to the server.

[0629] 2. Obtaining weather and congestion information

[0630] The server receives a request from the user. Specifically, the server analyzes the HTTP request and obtains the user's purpose, required time, and current latitude and longitude.

[0631] The server sends a request to the weather API to obtain current weather information. The server sends the latitude and longitude of "Shinjuku Station" to the weather API and obtains the weather information "Sunny" in return.

[0632] The server sends a request to the congestion API to obtain the local congestion status. The server sends information about the area around "Shinjuku Station" to the congestion API, and receives the congestion status "slightly crowded" in return.

[0633] 3. Route calculation

[0634] The server calculates the optimal walking route based on user input, weather information, and traffic congestion. Specifically, the server applies an algorithm to generate a route that goes "via Shinjuku Gyoen → new cafe → return to Shinjuku Station."

[0635] The server applies an algorithm that prioritizes unusual routes and new stores, and adds points. For example, the algorithm adds "newly opened cafes" and "places where special events are held" to the route.

[0636] The server compiles optimal route information and points of interest in JSON format and sends it to the terminal.

[0637] 4. Route presentation and AR information display

[0638] The device interprets the route information received from the server and displays the route on a map. The app calls the map module and displays the route "Shinjuku Station → Shinjuku Gyoen → New Cafe."

[0639] The device uses augmented reality to display markers and pop-ups at points of interest. For example, the AR module displays a marker at the location of a "new cafe" and a pop-up with a "discount coupon."

[0640] The user checks the route through the app and starts the walk. The user checks the displayed route and actually starts the walk.

[0641] 5. Advertising

[0642] When the device approaches a specific point on the route, it prepares to display an advertisement. When the user approaches a cafe, the device calls the AR module and prepares a "special discount coupon."

[0643] Users can view ads while walking and interact with content they are interested in. For example, they can tap on a coupon displayed in an AR pop-up to view more information.

[0644] When a user takes an action on an advertisement, the terminal sends the information to the server and stores it as statistical data. When a user acquires a coupon, the information is sent to the server and recorded in the database.

[0645] Examples of prompt statements

[0646] When inputting a prompt to a generative AI model to suggest a route, use the following prompt:

[0647] "The current weather is sunny, the estimated travel time is one hour, and I'm at Shinjuku Station. Please suggest a recommended walking route for relaxation."

[0648] "It's cloudy, and I'd like to take a 30-minute walking route starting from Shinjuku Station for exercise. Please suggest a route that passes through new stores."

[0649] The system's main functions are to provide a comfortable walking experience by taking into account the user's individual needs and real-time environmental factors, and to support local commercial activities. Users can easily check their walking routes through the app and enjoy the fun of exploring new places. In addition, advertisements and collected statistical data are used by local businesses, contributing to the revitalization of commercial activities.

[0650] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0651] Step 1:

[0652] User: Launches the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[0653] Specific action: The user taps "Relax" on the app's menu screen.

[0654] Input: User intent

[0655] Output: Objective is selected

[0656] Step 2:

[0657] User: Enter the desired duration (e.g., 1 hour).

[0658] Specific behavior: The user enters "1 hour" in the time input field and presses the submit button.

[0659] Input: Time required

[0660] Output: Time is input

[0661] Step 3:

[0662] Device: Obtain current location using GPS function.

[0663] Specific behavior: The app calls the GPS module in the background to get the current latitude and longitude.

[0664] Input: GPS function

[0665] Output: Current location (latitude, longitude)

[0666] Step 4:

[0667] Terminal: The user's input information and current location are compiled in JSON format and sent to the server.

[0668] Specific operation: Generates JSON data and sends it to the server via an HTTP request.

[0669] Input: User's purpose, time required, current location

[0670] Output: Request sent to server

[0671] Step 5:

[0672] Server: Receives requests from users.

[0673] What it does: The server analyzes the HTTP request and obtains data about the user's purpose, time required, and current location.

[0674] Input: HTTP request

[0675] Output: User's purpose, time required, and current location

[0676] Step 6:

[0677] Server: Sends a request to the weather API to get current weather information.

[0678] Specific operation: Sends an HTTP request to the weather API and receives weather information.

[0679] Input: Current location (latitude, longitude)

[0680] Output: Weather information (e.g. sunny)

[0681] Step 7:

[0682] Server: Sends a request to the congestion API to obtain the local congestion status.

[0683] Specific operation: Send an HTTP request to the congestion API and receive congestion information.

[0684] Input: Current location (latitude, longitude)

[0685] Output: Congestion information (e.g., slightly crowded)

[0686] Step 8:

[0687] Server: Calculates the optimal walking route based on user input, weather information, and congestion status.

[0688] What it does: Apply algorithms to calculate optimal routes and points of interest.

[0689] Input: User's purpose, travel time, current location, weather information, congestion information

[0690] Output: Optimal walking route (e.g. Shinjuku Gyoen → New cafe)

[0691] Step 9:

[0692] Server: Optimal route information and points of interest are compiled in JSON format and sent to the terminal.

[0693] Specific operation: Generates JSON data and sends it to the terminal as an HTTP response.

[0694] Input: Best walking route, points of interest

[0695] Output: Sending a response to the device

[0696] Step 10:

[0697] Terminal: Interprets the route information received from the server and displays the route on a map.

[0698] Specific operation: Calls the map module and displays the route on the map.

[0699] Input: Route information, points of interest

[0700] Output: Route display on map

[0701] Step 11:

[0702] Device: Use the AR function to display markers and pop-ups at points of interest.

[0703] Specific operation: The AR module displays markers and popups at points of interest.

[0704] Input: Points of Interest

[0705] Output: AR display

[0706] Step 12:

[0707] User: Check the route through the app and start the walk.

[0708] Specific behavior: The user checks the displayed route and starts walking.

[0709] Input: Route display (map, AR)

[0710] Output: Start of walk

[0711] Step 13:

[0712] Terminal: Prepares to display advertisements as you approach certain points along your route.

[0713] Specific operation: The AR module detects when the user approaches a specific point and prepares an advertisement.

[0714] Input: GPS data, specific points

[0715] Output: Ad Ready

[0716] Step 14:

[0717] Users: Check out ads while walking and respond to ads that interest them.

[0718] Specific behavior: The user taps on the coupon displayed in the AR popup to view more information.

[0719] Input: AR ad

[0720] Output: User response

[0721] Step 15:

[0722] Terminal: When a user takes action on an advertisement, the information is sent to the server and stored as statistical data.

[0723] Specific behavior: Records user actions and sends them to the server.

[0724] Input: User action data

[0725] Output: Sending data to the server, accumulating statistical data

[0726] (Application example 1)

[0727] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0728] In today's world, it is difficult for users to enjoy a pleasant walk and discover new local commercial facilities at the same time. This becomes even more difficult when external factors such as weather and congestion affect the activities. Therefore, there is a need for a system that takes weather and congestion into account and provides optimal routes that allow users to comfortably discover new stores and commercial facilities. Furthermore, utilizing such a system to revitalize local commercial activities is also an important issue.

[0729] 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.

[0730] In this invention, the server includes a means for receiving user input information, a means for acquiring real-time weather information, and a means for grasping the local congestion status, thereby making it possible to calculate optimal walking routes and shopping routes based on the user input information, weather information, and congestion status, and display them to the user.

[0731] "User input information" refers to information such as purpose, required time, and current location that the user provides to the system.

[0732] "Real-time weather information" refers to current weather and forecast information based on that weather, and is data obtained from an external API.

[0733] "Regional congestion status" is information indicating the degree of congestion of people and vehicles in a specified area, and is also data obtained from an external API.

[0734] The "optimal walking route" is the most suitable walking route for the user, calculated based on the user's input information, real-time weather information, and local congestion status.

[0735] "Points of interest" are spots such as new stores and landmarks that the user may be interested in along the optimal walking route.

[0736] A "purchase path" is the optimal route for a user to reach a particular physical store, and may include a walking route.

[0737] "Recommended stores" are commercial facilities and stores that the system recommends to users based on its own algorithms and data.

[0738] "Augmented reality display means" refers to a means for displaying points of interest and recommended stores using augmented reality technology, and utilizes devices such as smart glasses and head-mounted displays.

[0739] Overall system overview

[0740] This invention is a system that provides optimal walking and shopping routes based on information entered by users, real-time weather information, and congestion status. This system uses devices such as smartphones, smart glasses, and head-mounted displays to provide users with opportunities to explore routes they don't usually take and new stores, thereby revitalizing local commercial activity.

[0741] Program processing overview

[0742] Enter and submit user information

[0743] The server receives the user's purpose information, required time, and current location obtained by GPS input using a smartphone or AR device. The user inputs the purpose of the walk (e.g., relaxation, exercise, discovering new shops) and the desired duration (e.g., 1 hour), and the device obtains the user's current location using its GPS function. The user's input information and current location are compiled in JSON format and sent to the server.

[0744] Obtaining weather and congestion information

[0745] The server receives a request from a user and obtains weather information and congestion information from the weather API and congestion API, respectively. For example, the server sends a request to the weather API to obtain current weather information (e.g., sunny), and then sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[0746] Route calculation

[0747] The server calculates optimal walking and shopping routes based on the user's input information, weather information, and congestion status. For example, it selects a route that passes through Shinjuku Gyoen National Garden and finds new cafes, and applies an algorithm that prioritizes exploring routes that are not usually taken and new commercial facilities. The calculation results, including optimal route information and points of interest, are sent to the device in JSON format.

[0748] Route presentation and AR information display

[0749] The device interprets the route information received from the server and displays the route on a map. It also uses AR functionality to display markers and pop-ups at points of interest and recommended stores. The user can check the suggested optimal route through the app and begin their walk or shopping.

[0750] The hardware used includes smartphones, smart glasses (e.g., Google Glass, HoloLens), and head-mounted displays (e.g., Oculus Rift, HTC Vive).The software used includes Python, the Requests module (API requests), Geopy (GPS information acquisition), OpenWeatherMap API (weather information acquisition), and Crowd API (crowding status acquisition).

[0751] Prompts and Sentence Examples

[0752] "Create a program that suggests the best walking route based on user input and current location, taking into account weather and traffic conditions. The program's functionality would include:

[0753] 1. Obtain the user's purpose, required time, and current location.

[0754] 2. Collect weather and crowd data using weather and crowd APIs.

[0755] 3. Calculate routes based on weather, congestion, and user preferences.

[0756] 4. The calculation results are provided to the user and displayed on a smartphone or AR device.

[0757] Example of the results:

[0758] Shinjuku Station: Starting point

[0759] Shinjuku Gyoen: A place to relax

[0760] New Cafe: What to Look For

[0761] Please create your code based on this."

[0762] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0763] Step 1:

[0764] The user launches a smartphone app or AR device and inputs the purpose of their walk (e.g., relaxation, exercise, or discovering new shops) and the desired duration (e.g., 1 hour). The device also uses its GPS function to obtain the user's current location. This information is then compiled as user input.

[0765] Input: Destination, travel time, current location

[0766] Output: User input information (purpose, time required, current location in JSON format)

[0767] Step 2:

[0768] The terminal compiles the acquired user input information into JSON format and sends it to the server.

[0769] Input: User input information (purpose, time required, current location in JSON format)

[0770] Output: User input sent to the server

[0771] Step 3:

[0772] The server receives the user's input information, sends a request to the weather API to obtain current weather information, and sends a request to the congestion API to obtain local congestion information.

[0773] Input: User input information (purpose, time required, current location in JSON format)

[0774] Data processing: Weather API request, Congestion API request

[0775] Output: Weather information, congestion information (JSON format)

[0776] Step 4:

[0777] The server calculates optimal walking and shopping routes based on weather information, congestion information, and user input, using an algorithm that prioritizes less commonly used routes and new commercial facilities.

[0778] Input: User input information, weather information, and congestion information (all in JSON format)

[0779] Data calculation: Calculation of optimal routes and purchase paths (using algorithms)

[0780] Output: Optimal walking and shopping routes, points of interest (JSON format)

[0781] Step 5:

[0782] The server compiles the calculated optimal walking route, shopping route, and points of interest in JSON format and sends it to the device.

[0783] Input: Optimal walking route, shopping route, points of interest (JSON format)

[0784] Output: Route information and points of interest sent to the device

[0785] Step 6:

[0786] The terminal interprets the route information and points of interest received from the server and displays the route on a map. It also uses an augmented reality display means to display markers and pop-ups at points of interest and recommended stores.

[0787] Input: Route information and points of interest sent to the device (JSON format)

[0788] Output: The route, points of interest, markers and popups displayed to the user

[0789] Step 7:

[0790] Users can view suggested routes and begin their walk or purchase through the app. As users approach specific points of interest, the device displays additional information and advertisements.

[0791] Input: Route information and points of interest confirmed by the user

[0792] Output: Additional information or advertisements based on user behavior

[0793] These processing steps allow users to have a comfortable and efficient walking and shopping experience, and also contribute to the discovery of new commercial facilities and the revitalization of local areas.

[0794] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0795] Overall system overview

[0796] This system provides optimal walking routes based on real-time weather and congestion information, along with information entered by the user. By combining this with an emotion engine that recognizes the user's emotions, the system selects routes and suggests points of interest that match the user's psychological state.

[0797] System Components

[0798] 1. User device (smartphone or AR device): Provides an interface where users can input the purpose of their walk, the required time, and their current location obtained via GPS. It also uses an emotion engine to recognize the user's emotions and displays the calculated walking route and points of interest.

[0799] 2. Server: Receives requests from users and obtains information such as weather and congestion status using external APIs. Furthermore, it calculates the optimal walking route based on this information and the user's emotional information, and sends it to the user's device.

[0800] 3. External API: An API that provides weather information and an API that provides congestion status.

[0801] 4. Emotion engine: Uses the user's camera or other sensors to recognize emotions from the user's facial expressions and voice.

[0802] Program processing overview

[0803] Enter and submit user information

[0804] 1. User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[0805] 2. User: Enter the desired duration (e.g. 1 hour).

[0806] 3. Device: Obtain current location using GPS function.

[0807] 4. Terminal: Activate the emotion engine and recognize the user's emotions.

[0808] 5. Terminal: User input information, current location, and emotion information are compiled in JSON format and sent to the server.

[0809] Obtaining weather and congestion information

[0810] 1. Server: Receives requests from users.

[0811] Example: Purpose: Relaxation, Time required: 1 hour, Current location: Shinjuku Station, Emotion: "Slightly stressed."

[0812] 2. Server: Sends a request to the weather API to get the current weather information (e.g. sunny).

[0813] 3. Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[0814] Route calculation

[0815] 1. Server: Calculates the optimal walking route based on the user's input information, weather information, congestion status, and emotional information acquired so far.

[0816] Example: Select a route that passes through Shinjuku Gyoen National Garden and leads to a new cafe. Prioritize quiet areas to reduce user stress.

[0817] 2. Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[0818] 3. Server: The optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the device.

[0819] Route presentation and AR information display

[0820] 1. Terminal: Interprets the route information received from the server and displays the route on a map.

[0821] 2. Device: Use the AR function to display markers or pop-ups at points of interest (e.g., new cafes or landmarks).

[0822] 3. User: Check the route through the app and start your walk.

[0823] Example: Take a route that passes through Shinjuku Gyoen National Garden and arrive at a new cafe.

[0824] Advertisement display

[0825] 1. Device: Prepares to display AR ads when approaching a specific point on the route.

[0826] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[0827] 2. User: Check the ads while walking and respond to the ads that interest them.

[0828] 3. Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[0829] In this way, the system provides an optimal walking route based on the user's emotional state, providing a more personalized experience for the user. By comprehensively taking into account weather, congestion, and emotional information, the system can provide a comfortable walking experience for the user and contribute to revitalizing local commercial activity.

[0830] The processing flow will be explained below.

[0831] Step 1:

[0832] User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[0833] Step 2:

[0834] User: Enter the desired duration (e.g., 1 hour).

[0835] Step 3:

[0836] Device: Obtain current location using GPS function.

[0837] Step 4:

[0838] Device: Uses a camera or microphone to provide the user's face and voice to the emotion engine.

[0839] Step 5:

[0840] On the device: The emotion engine analyzes the user's emotions and identifies their current emotional state (e.g., stress, anxiety, joy).

[0841] Step 6:

[0842] Terminal: User input information, current location, and emotion information are compiled in JSON format and sent to the server.

[0843] Step 7:

[0844] Server: Receives requests from users.

[0845] Example: Purpose: Relaxation, Time required: 1 hour, Current location: Shinjuku Station, Emotion: "Slightly stressed."

[0846] Step 8:

[0847] Server: Sends a request to the weather API to get current weather information (e.g. sunny).

[0848] Step 9:

[0849] Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[0850] Step 10:

[0851] Server: Calculates the optimal walking route based on user input, weather information, congestion status, and emotional information.

[0852] If the emotion is "stress," prioritize quieter routes and relaxing spots.

[0853] Step 11:

[0854] Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[0855] Step 12:

[0856] Server: Optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the terminal.

[0857] Step 13:

[0858] Terminal: Interprets the route information received from the server and displays the route on a map.

[0859] Step 14:

[0860] Device: Use the AR function to display markers and pop-ups at points of interest (e.g., new cafes or landmarks).

[0861] Step 15:

[0862] User: Check the route through the app and start the walk.

[0863] Step 16:

[0864] Device: Prepares to display AR ads when approaching a specific point on the route.

[0865] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[0866] Step 17:

[0867] Users: Check out ads while walking and respond to ads that interest them.

[0868] Step 18:

[0869] Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[0870] Example 2

[0871] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0872] Conventional walking route provision systems calculate routes by taking into account only weather information and congestion status, and therefore are unable to provide optimal routes that reflect the user's psychological state. Furthermore, there is a lack of means to provide a personalized experience that takes into account the user's emotions. This makes it difficult to provide walking routes that satisfy users, and there are also issues with limited contribution to local commercial activity.

[0873] 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 receiving user input information, a means for acquiring real-time weather information, a means for grasping the local congestion state, a means for recognizing the user's emotions, a means for calculating an optimal walking route based on the user's input information, weather information, congestion state, and emotion information, and a means for displaying the calculated walking route and points of interest to the user. This makes it possible to provide a personalized optimal walking route that takes into account the user's psychological state, real-time weather, and congestion state.

[0874] "User input information" refers to information such as the purpose of the walk and the required time provided by the user to the system.

[0875] "Real-time weather information" means data about current weather conditions in a specified area.

[0876] "Local congestion status" is information about the current level of congestion of people and vehicles at a specific location or route.

[0877] "Means for recognizing the user's emotions" refers to technology that analyzes the user's facial expressions and voice to determine their psychological state and emotions.

[0878] The "means for calculating the optimal walking route" is an algorithm or program for calculating the most suitable walking route for the user based on the user's input information and real-time weather information, congestion status, and emotional information.

[0879] The "calculated walking route" is a walking route derived by the means for calculating the optimal walking route described above.

[0880] "Points of interest" are places that are considered worth visiting by the user during a walk, such as new stores or landmarks.

[0881] "Augmented reality display means" is a technology that displays digital information overlaid on real-world scenery, and is a means of visually providing information such as points of interest on the user's device.

[0882] Overall system overview

[0883] This system provides optimal walking routes based on user input, real-time weather information, and local congestion status. The system also features an emotion engine that recognizes the user's emotions, and selects routes and suggests points of interest that match the user's psychological state.

[0884] System Components

[0885] 1. User device (smartphone or augmented reality device): The user inputs the purpose and duration of the walk, obtains the current location using GPS, and uses an emotion engine to recognize the user's emotions and displays the calculated walking route and points of interest.

[0886] 2. Server: Receives requests from users and obtains information such as weather and congestion status using external APIs. Based on this information and the user's emotional state, the server calculates the optimal walking route and sends it to the user's device.

[0887] 3. External API: An API that provides weather information and an API that provides congestion information.

[0888] 4. Emotion engine: Uses the user's camera or other sensors to recognize emotions from the user's facial expressions and voice.

[0889] Program processing overview

[0890] Enter and submit user information

[0891] The user opens the smartphone app and selects the purpose of their walk (e.g., relaxation, exercise, or discovering new stores). Next, they enter the desired duration (e.g., 1 hour), and the device uses its GPS function to obtain their current location. The device then activates an emotion engine that analyzes the user's facial expressions and voice to recognize their emotions. This information is then compiled in JSON format and sent to the server.

[0892] Obtaining weather and congestion information

[0893] The server receives a request from the user, sends a request to the weather API to get current weather information, and sends a request to the congestion API to get the local congestion status.

[0894] Walking route calculation

[0895] The server calculates the optimal walking route based on the user's input information, weather information, congestion status, and emotional information it has acquired so far. To reduce user stress, it prioritizes quiet areas and selects routes that include new shops and points of interest. This information is compiled in JSON format and sent to the user's device.

[0896] Route presentation and AR information display

[0897] The user's device interprets the route information received from the server and displays the route on a map. It also uses AR functionality to display markers and pop-ups at points of interest (new cafes and landmarks). The user checks the route through the app and begins their walk.

[0898] Specific actions

[0899] A user wants to take a relaxing walk, inputs the required time of one hour and their current location as Shinjuku Station, and the emotion engine recognizes the user as slightly stressed. The server retrieves "sunny" from the weather API and "somewhat crowded around Shinjuku Station" from the congestion API. The server then calculates a route to the cafe via Shinjuku Gyoen and sends it to the user.

[0900] Prompt Sentence Examples

[0901] "If the user selects "relaxation" as the purpose of the walk, the duration is one hour, the current location is Shinjuku Station, and the emotion is "slightly stressed," the system should calculate the optimal walking route via Shinjuku Gyoen."

[0902] "Recognize the user's emotional state and suggest optimal walking routes and points of interest based on that."

[0903] In this way, the system comprehensively considers the user's psychological state, real-time weather, and congestion, and provides the user with an optimal personalized walking route, which can also contribute to revitalizing local commercial activity.

[0904] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0905] Step 1:

[0906] User: Opens the smartphone app and selects the purpose of the walk. For example, the user selects "relaxation." This is the input information.

[0907] Step 2:

[0908] User: Enter the desired duration. For example, specify "1 hour." This input information will also be used in subsequent processing.

[0909] Step 3:

[0910] Device: Uses GPS to obtain current location. For example, obtain "Shinjuku Station." This is added to the input information.

[0911] Step 4:

[0912] Device: The emotion engine is activated and the smartphone's camera and microphone are used to recognize the user's emotions. As a result of emotion analysis, information such as "slightly stressed" is obtained. This emotional information also becomes part of the input data.

[0913] Step 5:

[0914] Device: The user's input information, current location, and emotion information are compiled into JSON format and sent to the server as an HTTP POST request. Specifically, the JSON structure shown below is generated.

[0915] json

[0916] {

[0917] "Purpose": "Relax",

[0918] "Duration": "1 hour",

[0919] "Current Location": "Shinjuku Station",

[0920] "Emotion": "Slightly stressed"

[0921] }

[0922] Step 6:

[0923] Server: Analyzes the request received from the user and sends a request to the weather API to obtain current weather information. For example, the information obtained is "sunny." This becomes the newly added input information.

[0924] Step 7:

[0925] Server: Next, a request is sent to the congestion API to obtain the local congestion status. For example, information such as "The area around Shinjuku Station is somewhat crowded" is obtained. This congestion information also becomes part of the input data.

[0926] Step 8:

[0927] Server: Calculates the optimal walking route based on the user's input information, weather information, congestion status, and emotional information acquired so far. For example, it calculates a route to reach a cafe via Shinjuku Gyoen. The calculated route information and points of interest are generated as output.

[0928] Step 9:

[0929] Server: The output walking route information and points of interest are compiled into JSON format and sent to the device. Specifically, the JSON structure shown below is generated.

[0930] json

[0931] {

[0932] "Route": "Route via Shinjuku Gyoen",

[0933] "Featured": "New Cafe"

[0934] }

[0935] Step 10:

[0936] Terminal: Analyzes the JSON data received from the server and displays the route in a map application. For example, it draws a "route to reach the cafe via Shinjuku Gyoen" on the map.

[0937] Step 11:

[0938] Device: Activate the AR function to display markers and pop-ups at points of interest along the route. For example, place AR markers at "new cafes" or "landmarks."

[0939] Step 12:

[0940] User: Check the route and points of interest on the app screen and start a walk. For example, execute "Go through Shinjuku Gyoen" and "Reach the cafe."

[0941] Step 13:

[0942] Device: Prepares to display AR advertisements when the user approaches a specific point on the route. For example, "approaching a cafe" and "displaying an AR advertisement with a special discount coupon."

[0943] Step 14:

[0944] User: Check out advertisements (e.g., special discount coupons) while walking and respond to advertisements that interest them.

[0945] Step 15:

[0946] Terminal: When a user takes an action on an advertisement (for example, obtains a coupon), the information is sent to the server in JSON format and stored in a database as statistical data.

[0947] (Application example 2)

[0948] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0949] Conventional walking route suggestion systems have limited means of taking into account weather information and local congestion, making it difficult to select an optimal route that reflects the user's psychological state. Furthermore, for certain tasks, such as delivery, it has not been possible to provide an optimal route that takes into account the psychological state of the delivery staff. This has resulted in a lack of routes that are comfortable and efficient for both users and delivery staff.

[0950] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user input information, means for acquiring real-time weather information, means for understanding the local congestion situation, means for recognizing the user's emotions, means for selecting a route and suggesting points of interest based on the user's psychological state, means for displaying the calculated walking route and points of interest to the user, means for providing the optimal delivery route taking into account the psychological state of the delivery staff, and means for displaying information and advertisements when approaching specific points. This makes it possible to provide the user and delivery staff with optimal routes and information that comprehensively take into account their psychological state and the external environment.

[0951] "User input information" refers to information sent by the user via the terminal, including the user's current location, destination, required travel time, and other requirements.

[0952] "Real-time weather information" refers to the latest weather data obtained from external APIs, etc., and includes current weather and forecast information.

[0953] "Regional congestion status" is information indicating the degree of concentration of people and vehicles in a specific area, and is obtained from external APIs, etc.

[0954] "User emotions" refers to analyzing the user's psychological state and mood using cameras, audio sensors, etc.

[0955] "Route selection based on psychological state" refers to the process of selecting the most suitable route for a user based on the user's emotional information.

[0956] "Points of interest" refer to places, stores, etc. that may catch the user's interest while walking or during delivery.

[0957] "The psychological state of delivery staff" refers to the mental state and stress level of the staff performing delivery work.

[0958] The "optimal delivery route" refers to the most efficient and comfortable route calculated by comprehensively taking into consideration the mental state of the delivery staff, weather information, and congestion conditions.

[0959] "Means for displaying information or advertisements" refers to a method for visually displaying information or advertisements related to a location to a user when the user approaches a specific point.

[0960] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to specific embodiments.

[0961] Overall system configuration

[0962] The system collects and analyzes user input, real-time weather information, local congestion status, and user sentiment information to provide the optimal walking or delivery route. The system includes the following main components:

[0963] 1. User device (smartphone or AR device)

[0964] It provides an interface for collecting and sending user input information, current location, and emotion information to the server.

[0965] It displays the optimal route and points of interest, and displays information and advertisements when you approach certain points.

[0966] 2. Server

[0967] Receive requests from users and obtain weather information and congestion status.

[0968] The optimal route is calculated based on the user's input information, weather information, congestion status, and emotional information, and transmitted to the user.

[0969] 3. External API

[0970] API for obtaining weather information (e.g. OpenWeatherMap API)

[0971] API to obtain congestion status (e.g., Google Maps Traffic API)

[0972] 4. Emotion Engine

[0973] APIs that utilize camera and audio sensors to recognize user emotions (e.g., Microsoft Azure Face API)

[0974] Program processing

[0975] The program in this system works as follows:

[0976] 1. Enter and submit user information

[0977] The user uses the user terminal to input the destination of the walk or delivery, the required time, the current location, etc.

[0978] The emotion engine is activated and recognizes emotions from the user's facial expressions and voice.

[0979] This information is compiled in JSON format and sent to the server.

[0980] 2. Obtaining weather information and congestion status

[0981] The server uses an external API to obtain current weather information and local congestion status.

[0982] 3. Route calculation

[0983] The server calculates the optimal walking or delivery route based on the user's input information, weather information, congestion status, and emotional information.

[0984] For delivery staff, the system takes into account their psychological state and provides routes that minimize stress, including points of interest that match the user's specified objectives.

[0985] 4. Route presentation and information display

[0986] The calculated route information and points of interest are transmitted to the user terminal.

[0987] The user terminal displays route information on a map, and also displays information and advertisements when the user approaches a specific point.

[0988] Specific examples

[0989] For example, if a delivery staff member inputs "Shinjuku Station" as their current location and their emotional information is recognized as "slightly stressed," the server will calculate the optimal route to the delivery destination, taking into account the current weather information (e.g., sunny) and congestion status (e.g., slightly crowded), prioritizing quieter routes. Additionally, when the delivery staff member approaches the delivery destination, specific information and advertisements will be displayed in AR.

[0990] The system can use a generative AI model with prompts like this:

[0991] "If the user is stressed, if the weather is bad, calculate the optimal delivery route with a focus on safety."

[0992] "If a user wants to discover new stores, calculate a walking route that reflects that desire."

[0993] In this way, the embodiments of the invention provide specific means for providing an optimal experience by comprehensively considering the psychology and environmental information of the user and delivery staff.

[0994] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0995] Step 1:

[0996] The user uses the device to input their current location, destination, purpose of walk or delivery, and required time. This information is formatted in JSON format. The device also uses the camera and microphone to collect the user's emotional data, which is analyzed by the emotion engine. The results of this analysis are also added to the JSON format. Input data: current location, destination, purpose of walk or delivery, required time, emotional data. Output data: input information and emotional data in JSON format.

[0997] Step 2:

[0998] The device sends formatted JSON formatted data to the server. The server receives this data and begins parsing it. Input data: Input information and emotion data in JSON format. Output data: None.

[0999] Step 3:

[1000] The server uses an external API to get real-time weather information based on the user's current location. It sends a request to the weather API (e.g., OpenWeatherMap API) and receives weather information as a response. Input data: current location. Output data: weather information.

[1001] Step 4:

[1002] The server also uses an external API to obtain the local congestion status based on the user's current location. It sends a request to the congestion status API (e.g., Google Maps Traffic API) and receives congestion status data as a response. Input data: current location. Output data: congestion status data.

[1003] Step 5:

[1004] The server integrates the received user input information, emotion data, weather information, and congestion status to calculate the optimal walking or delivery route. A route calculation algorithm is used to select a route that takes into account the user's psychological state and congestion status. Input data: User input information, emotion data, weather information, congestion status data. Output data: Optimal route information.

[1005] Step 6:

[1006] The server formats the calculated optimal route information and points of interest in JSON format and sends it to the terminal. Input data: optimal route information, points of interest information. Output data: route information and points of interest in JSON format.

[1007] Step 7:

[1008] The device analyzes the route information and points of interest in JSON format received from the server and displays them to the user through a map app or AR display. When the user approaches a specific point, related information or advertisements are displayed. Input data: Route information and points of interest in JSON format. Output data: Visual display to the user.

[1009] Step 8:

[1010] The user begins traveling along the route and reaches a specific point of interest or delivery destination. The user's behavior data and collected ad response data are then sent to the server and used for statistical analysis. Input data: user behavior data, ad response data. Output data: statistical data.

[1011] Through the above steps, a system is realized that provides optimal routes and information that comprehensively consider the user's emotional state and external environmental information.

[1012] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1013] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1014] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1015] [Third embodiment]

[1016] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1017] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1019] 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.

[1020] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1021] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1023] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1024] 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.

[1025] 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.

[1026] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1027] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1028] Overall system overview

[1029] This invention is a system that provides optimal walking routes based on information entered by the user, real-time weather information, and congestion status. This system provides users with opportunities to explore routes they don't usually take and new stores, contributing to the revitalization of local areas.

[1030] System Components

[1031] 1. User device (smartphone or AR device): Provides an interface where users can input the purpose of their walk, the required time, and their current location obtained via GPS. It also displays the calculated walking route and points of interest.

[1032] 2. Server: Receives requests from users and obtains information such as weather and congestion status using external APIs. Based on this information, it calculates the optimal walking route and sends it to the user's device.

[1033] 3. External API: An API that provides weather information and an API that provides congestion status.

[1034] Program processing overview

[1035] Enter and submit user information

[1036] 1. User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[1037] 2. User: Enter the desired duration (e.g. 1 hour).

[1038] 3. Device: Obtain current location using GPS function.

[1039] 4. Terminal: The user's input information and current location are compiled in JSON format and sent to the server.

[1040] Obtaining weather and congestion information

[1041] 1. Server: Receives requests from users.

[1042] Example: Relaxation purpose, required time 1 hour, current location Shinjuku Station.

[1043] 2. Server: Sends a request to the weather API to get the current weather information (e.g. sunny).

[1044] 3. Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[1045] Route calculation

[1046] 1. Server: Calculates the optimal walking route based on the user's input information, weather information, and congestion status obtained so far.

[1047] Example: Select a route that passes through Shinjuku Gyoen and leads to a new cafe.

[1048] 2. Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[1049] 3. Server: The optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the device.

[1050] Route presentation and AR information display

[1051] 1. Terminal: Interprets the route information received from the server and displays the route on a map.

[1052] 2. Device: Use the AR function to display markers or pop-ups at points of interest (e.g., new cafes or landmarks).

[1053] 3. User: Check the route through the app and start your walk.

[1054] Advertisement display

[1055] 1. Device: Prepares to display AR ads when approaching a specific point on the route.

[1056] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[1057] 2. User: Check the ads while walking and respond to the ads that interest them.

[1058] 3. Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[1059] In this way, this system not only provides users with the best walking route, but also contributes to revitalizing local commercial activity. By taking into account weather and congestion, it provides users with a comfortable walking experience and can also generate revenue from advertisers.

[1060] The processing flow will be explained below.

[1061] Step 1:

[1062] User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[1063] Step 2:

[1064] User: Enter the desired duration (e.g., 1 hour).

[1065] Step 3:

[1066] Device: Obtain current location using GPS function.

[1067] Step 4:

[1068] Terminal: The user's input information and current location are compiled in JSON format and sent to the server.

[1069] Step 5:

[1070] Server: Receives requests from users.

[1071] Example: Relaxation purpose, required time 1 hour, current location Shinjuku Station.

[1072] Step 6:

[1073] Server: Sends a request to the weather API to get current weather information (e.g. sunny).

[1074] Step 7:

[1075] Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[1076] Step 8:

[1077] Server: Calculates the optimal walking route based on the user's input information, weather information, and congestion status acquired so far.

[1078] Example: Select a route that passes through Shinjuku Gyoen and leads to a new cafe.

[1079] Step 9:

[1080] Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[1081] Step 10:

[1082] Server: Optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the terminal.

[1083] Step 11:

[1084] Terminal: Interprets the route information received from the server and displays the route on a map.

[1085] Step 12:

[1086] Device: Use the AR function to display markers and pop-ups at points of interest (e.g., new cafes or landmarks).

[1087] Step 13:

[1088] User: Check the route through the app and start the walk.

[1089] Step 14:

[1090] Device: Prepares to display AR ads as it approaches a specific point on its route.

[1091] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[1092] Step 15:

[1093] Users: Check out ads while walking and respond to ads that interest them.

[1094] Step 16:

[1095] Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[1096] Example 1

[1097] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1098] Conventional walking route provision systems have difficulty taking into account individual user objectives and real-time environmental factors (weather, congestion, etc.). Furthermore, they lack the functionality to stimulate local commercial activity through advertising. As a result, there is a need for systems that not only increase user satisfaction but also help explore new stores in the area and stimulate commercial activity.

[1099] 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.

[1100] In this invention, the server includes means for receiving user input information, means for acquiring real-time weather information, means for grasping the local congestion status, means for calculating an optimal walking route based on the user input information, the weather information, and the congestion status, means for displaying the calculated walking route and points of interest to the user, means for displaying advertisements when the user approaches points of interest, and means for collecting and accumulating the user's responses to the advertisements as statistical data. This makes it possible to provide an optimal walking route that takes into account the user's individual goals and real-time environmental factors. It can also realize support for local revitalization and commercial activities.

[1101] "User input information" refers to data provided by the user to the system, specifically the purpose of the walk (e.g., relaxation, exercise), the required time, current location, etc.

[1102] "Real-time weather information" refers to data indicating current weather conditions, obtained from an external weather API.

[1103] "Regional congestion status" is data indicating the current level of congestion in a specific area, and is obtained from an external congestion API.

[1104] "Calculating the optimal walking route" refers to the process of using an algorithm to calculate the optimal walking route for the user based on information input by the user, weather information, and congestion status.

[1105] "Calculated walking route" refers to route information derived by calculating the optimal walking route.

[1106] "Points of interest" refer to noteworthy places and stores along the walking route, and are intended to attract the user's interest.

[1107] "Augmented reality display means" refers to a function that uses AR (augmented reality) technology to display virtual information superimposed on real scenery.

[1108] The "means for displaying advertisements" refers to a function for displaying advertisement information when the user approaches a point of interest.

[1109] "Means for collecting users' responses to advertisements and accumulating them as statistical data" refers to the function of collecting data on the actions users take in response to displayed advertisements and saving this data as statistical information.

[1110] This invention is a system that provides optimal walking routes based on information entered by the user, real-time weather information, and congestion status. This system provides users with opportunities to explore routes they don't usually take and new stores, contributing to the revitalization of local areas.

[1111] System Components

[1112] 1. User device (smartphone or augmented reality device)

[1113] It provides an interface for users to input the purpose of their walk, the estimated time, and their current location obtained via GPS.

[1114] View calculated walking routes and points of interest.

[1115] 2. Server

[1116] Receives requests from users and obtains information using external APIs such as weather and congestion status.

[1117] Based on this information, the optimal walking route is calculated and sent to the user's terminal.

[1118] 3. External API

[1119] An API that provides weather information and an API that provides congestion status.

[1120] Program processing overview (example)

[1121] 1. Enter and submit user information

[1122] The user starts the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, or discovering new shops). For example, the user taps "Relax" on the app's menu screen.

[1123] The user inputs the desired time required (e.g., 1 hour). Specifically, the user inputs "1 hour" in the time input field and presses the submit button.

[1124] The device uses the GPS function to obtain the current location. The app calls the GPS module in the background to obtain the current latitude and longitude.

[1125] The user's input information and current location are compiled in JSON format and sent to the server.

[1126] 2. Obtaining weather and congestion information

[1127] The server receives a request from the user. Specifically, the server analyzes the HTTP request and obtains the user's purpose, required time, and current latitude and longitude.

[1128] The server sends a request to the weather API to obtain current weather information. The server sends the latitude and longitude of "Shinjuku Station" to the weather API and obtains the weather information "Sunny" in return.

[1129] The server sends a request to the congestion API to obtain the local congestion status. The server sends information about the area around "Shinjuku Station" to the congestion API, and receives the congestion status "slightly crowded" in return.

[1130] 3. Route calculation

[1131] The server calculates the optimal walking route based on user input, weather information, and traffic congestion. Specifically, the server applies an algorithm to generate a route that goes "via Shinjuku Gyoen → new cafe → return to Shinjuku Station."

[1132] The server applies an algorithm that prioritizes unusual routes and new stores, and adds points. For example, the algorithm adds "newly opened cafes" and "places where special events are held" to the route.

[1133] The server compiles optimal route information and points of interest in JSON format and sends it to the terminal.

[1134] 4. Route presentation and AR information display

[1135] The device interprets the route information received from the server and displays the route on a map. The app calls the map module and displays the route "Shinjuku Station → Shinjuku Gyoen → New Cafe."

[1136] The device uses augmented reality to display markers and pop-ups at points of interest. For example, the AR module displays a marker at the location of a "new cafe" and a pop-up with a "discount coupon."

[1137] The user checks the route through the app and starts the walk. The user checks the displayed route and actually starts the walk.

[1138] 5. Advertising

[1139] When the device approaches a specific point on the route, it prepares to display an advertisement. When the user approaches a cafe, the device calls the AR module and prepares a "special discount coupon."

[1140] Users can view ads while walking and interact with content they are interested in. For example, they can tap on a coupon displayed in an AR pop-up to view more information.

[1141] When a user takes an action on an advertisement, the terminal sends the information to the server and stores it as statistical data. When a user acquires a coupon, the information is sent to the server and recorded in the database.

[1142] Examples of prompt statements

[1143] When inputting a prompt to a generative AI model to suggest a route, use the following prompt:

[1144] "The current weather is sunny, the estimated travel time is one hour, and I'm at Shinjuku Station. Please suggest a recommended walking route for relaxation."

[1145] "It's cloudy, and I'd like to take a 30-minute walking route starting from Shinjuku Station for exercise. Please suggest a route that passes through new stores."

[1146] The system's main functions are to provide a comfortable walking experience by taking into account the user's individual needs and real-time environmental factors, and to support local commercial activities. Users can easily check their walking routes through the app and enjoy the fun of exploring new places. In addition, advertisements and collected statistical data are used by local businesses, contributing to the revitalization of commercial activities.

[1147] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1148] Step 1:

[1149] User: Launches the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[1150] Specific action: The user taps "Relax" on the app's menu screen.

[1151] Input: User intent

[1152] Output: Objective is selected

[1153] Step 2:

[1154] User: Enter the desired duration (e.g., 1 hour).

[1155] Specific behavior: The user enters "1 hour" in the time input field and presses the submit button.

[1156] Input: Time required

[1157] Output: Time is input

[1158] Step 3:

[1159] Device: Obtain current location using GPS function.

[1160] Specific behavior: The app calls the GPS module in the background to get the current latitude and longitude.

[1161] Input: GPS function

[1162] Output: Current location (latitude, longitude)

[1163] Step 4:

[1164] Terminal: The user's input information and current location are compiled in JSON format and sent to the server.

[1165] Specific operation: Generates JSON data and sends it to the server via an HTTP request.

[1166] Input: User's purpose, time required, current location

[1167] Output: Request sent to server

[1168] Step 5:

[1169] Server: Receives requests from users.

[1170] What it does: The server analyzes the HTTP request and obtains data about the user's purpose, time required, and current location.

[1171] Input: HTTP request

[1172] Output: User's purpose, time required, and current location

[1173] Step 6:

[1174] Server: Sends a request to the weather API to get current weather information.

[1175] Specific operation: Sends an HTTP request to the weather API and receives weather information.

[1176] Input: Current location (latitude, longitude)

[1177] Output: Weather information (e.g. sunny)

[1178] Step 7:

[1179] Server: Sends a request to the congestion API to obtain the local congestion status.

[1180] Specific operation: Send an HTTP request to the congestion API and receive congestion information.

[1181] Input: Current location (latitude, longitude)

[1182] Output: Congestion information (e.g., slightly crowded)

[1183] Step 8:

[1184] Server: Calculates the optimal walking route based on user input, weather information, and congestion status.

[1185] What it does: Apply algorithms to calculate optimal routes and points of interest.

[1186] Input: User's purpose, travel time, current location, weather information, congestion information

[1187] Output: Optimal walking route (e.g. Shinjuku Gyoen → New cafe)

[1188] Step 9:

[1189] Server: Optimal route information and points of interest are compiled in JSON format and sent to the terminal.

[1190] Specific operation: Generates JSON data and sends it to the terminal as an HTTP response.

[1191] Input: Best walking route, points of interest

[1192] Output: Sending a response to the device

[1193] Step 10:

[1194] Terminal: Interprets the route information received from the server and displays the route on a map.

[1195] Specific operation: Calls the map module and displays the route on the map.

[1196] Input: Route information, points of interest

[1197] Output: Route display on map

[1198] Step 11:

[1199] Device: Use the AR function to display markers and pop-ups at points of interest.

[1200] Specific operation: The AR module displays markers and popups at points of interest.

[1201] Input: Points of Interest

[1202] Output: AR display

[1203] Step 12:

[1204] User: Check the route through the app and start the walk.

[1205] Specific behavior: The user checks the displayed route and starts walking.

[1206] Input: Route display (map, AR)

[1207] Output: Start of walk

[1208] Step 13:

[1209] Terminal: Prepares to display advertisements as you approach certain points along your route.

[1210] Specific operation: The AR module detects when the user approaches a specific point and prepares an advertisement.

[1211] Input: GPS data, specific points

[1212] Output: Ad Ready

[1213] Step 14:

[1214] Users: Check out ads while walking and respond to ads that interest them.

[1215] Specific behavior: The user taps on the coupon displayed in the AR popup to view more information.

[1216] Input: AR ad

[1217] Output: User response

[1218] Step 15:

[1219] Terminal: When a user takes action on an advertisement, the information is sent to the server and stored as statistical data.

[1220] Specific behavior: Records user actions and sends them to the server.

[1221] Input: User action data

[1222] Output: Sending data to the server, accumulating statistical data

[1223] (Application example 1)

[1224] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1225] In today's world, it is difficult for users to enjoy a pleasant walk and discover new local commercial facilities at the same time. This becomes even more difficult when external factors such as weather and congestion affect the activities. Therefore, there is a need for a system that takes weather and congestion into account and provides optimal routes that allow users to comfortably discover new stores and commercial facilities. Furthermore, utilizing such a system to revitalize local commercial activities is also an important issue.

[1226] 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.

[1227] In this invention, the server includes a means for receiving user input information, a means for acquiring real-time weather information, and a means for grasping the local congestion status, thereby making it possible to calculate optimal walking routes and shopping routes based on the user input information, weather information, and congestion status, and display them to the user.

[1228] "User input information" refers to information such as purpose, required time, and current location that the user provides to the system.

[1229] "Real-time weather information" refers to current weather and forecast information based on that weather, and is data obtained from an external API.

[1230] "Regional congestion status" is information indicating the degree of congestion of people and vehicles in a specified area, and is also data obtained from an external API.

[1231] The "optimal walking route" is the most suitable walking route for the user, calculated based on the user's input information, real-time weather information, and local congestion status.

[1232] "Points of interest" are spots such as new stores and landmarks that the user may be interested in along the optimal walking route.

[1233] A "purchase path" is the optimal route for a user to reach a particular physical store, and may include a walking route.

[1234] "Recommended stores" are commercial facilities and stores that the system recommends to users based on its own algorithms and data.

[1235] "Augmented reality display means" refers to a means for displaying points of interest and recommended stores using augmented reality technology, and utilizes devices such as smart glasses and head-mounted displays.

[1236] Overall system overview

[1237] This invention is a system that provides optimal walking and shopping routes based on information entered by users, real-time weather information, and congestion status. This system uses devices such as smartphones, smart glasses, and head-mounted displays to provide users with opportunities to explore routes they don't usually take and new stores, thereby revitalizing local commercial activity.

[1238] Program processing overview

[1239] Enter and submit user information

[1240] The server receives the user's purpose information, required time, and current location obtained by GPS input using a smartphone or AR device. The user inputs the purpose of the walk (e.g., relaxation, exercise, discovering new shops) and the desired duration (e.g., 1 hour), and the device obtains the user's current location using its GPS function. The user's input information and current location are compiled in JSON format and sent to the server.

[1241] Obtaining weather and congestion information

[1242] The server receives a request from a user and obtains weather information and congestion information from the weather API and congestion API, respectively. For example, the server sends a request to the weather API to obtain current weather information (e.g., sunny), and then sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[1243] Route calculation

[1244] The server calculates optimal walking and shopping routes based on the user's input information, weather information, and congestion status. For example, it selects a route that passes through Shinjuku Gyoen National Garden and finds new cafes, and applies an algorithm that prioritizes exploring routes that are not usually taken and new commercial facilities. The calculation results, including optimal route information and points of interest, are sent to the device in JSON format.

[1245] Route presentation and AR information display

[1246] The device interprets the route information received from the server and displays the route on a map. It also uses AR functionality to display markers and pop-ups at points of interest and recommended stores. The user can check the suggested optimal route through the app and begin their walk or shopping.

[1247] The hardware used includes smartphones, smart glasses (e.g., Google Glass, HoloLens), and head-mounted displays (e.g., Oculus Rift, HTC Vive).The software used includes Python, the Requests module (API requests), Geopy (GPS information acquisition), OpenWeatherMap API (weather information acquisition), and Crowd API (crowding status acquisition).

[1248] Prompts and Sentence Examples

[1249] "Create a program that suggests the best walking route based on user input and current location, taking into account weather and traffic conditions. The program's functionality would include:

[1250] 1. Obtain the user's purpose, required time, and current location.

[1251] 2. Collect weather and crowd data using weather and crowd APIs.

[1252] 3. Calculate routes based on weather, congestion, and user preferences.

[1253] 4. The calculation results are provided to the user and displayed on a smartphone or AR device.

[1254] Example of the results:

[1255] Shinjuku Station: Starting point

[1256] Shinjuku Gyoen: A place to relax

[1257] New Cafe: What to Look For

[1258] Please create your code based on this."

[1259] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1260] Step 1:

[1261] The user launches a smartphone app or AR device and inputs the purpose of their walk (e.g., relaxation, exercise, or discovering new shops) and the desired duration (e.g., 1 hour). The device also uses its GPS function to obtain the user's current location. This information is then compiled as user input.

[1262] Input: Destination, travel time, current location

[1263] Output: User input information (purpose, time required, current location in JSON format)

[1264] Step 2:

[1265] The terminal compiles the acquired user input information into JSON format and sends it to the server.

[1266] Input: User input information (purpose, time required, current location in JSON format)

[1267] Output: User input sent to the server

[1268] Step 3:

[1269] The server receives the user's input information, sends a request to the weather API to obtain current weather information, and sends a request to the congestion API to obtain local congestion information.

[1270] Input: User input information (purpose, time required, current location in JSON format)

[1271] Data processing: Weather API request, Congestion API request

[1272] Output: Weather information, congestion information (JSON format)

[1273] Step 4:

[1274] The server calculates optimal walking and shopping routes based on weather information, congestion information, and user input, using an algorithm that prioritizes less commonly used routes and new commercial facilities.

[1275] Input: User input information, weather information, and congestion information (all in JSON format)

[1276] Data calculation: Calculation of optimal routes and purchase paths (using algorithms)

[1277] Output: Optimal walking and shopping routes, points of interest (JSON format)

[1278] Step 5:

[1279] The server compiles the calculated optimal walking route, shopping route, and points of interest in JSON format and sends it to the device.

[1280] Input: Optimal walking route, shopping route, points of interest (JSON format)

[1281] Output: Route information and points of interest sent to the device

[1282] Step 6:

[1283] The terminal interprets the route information and points of interest received from the server and displays the route on a map. It also uses an augmented reality display means to display markers and pop-ups at points of interest and recommended stores.

[1284] Input: Route information and points of interest sent to the device (JSON format)

[1285] Output: The route, points of interest, markers and popups displayed to the user

[1286] Step 7:

[1287] Users can view suggested routes and begin their walk or purchase through the app. As users approach specific points of interest, the device displays additional information and advertisements.

[1288] Input: Route information and points of interest confirmed by the user

[1289] Output: Additional information or advertisements based on user behavior

[1290] These processing steps allow users to have a comfortable and efficient walking and shopping experience, and also contribute to the discovery of new commercial facilities and the revitalization of local areas.

[1291] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1292] Overall system overview

[1293] This system provides optimal walking routes based on real-time weather and congestion information, along with information entered by the user. By combining this with an emotion engine that recognizes the user's emotions, the system selects routes and suggests points of interest that match the user's psychological state.

[1294] System Components

[1295] 1. User device (smartphone or AR device): Provides an interface where users can input the purpose of their walk, the required time, and their current location obtained via GPS. It also uses an emotion engine to recognize the user's emotions and displays the calculated walking route and points of interest.

[1296] 2. Server: Receives requests from users and obtains information such as weather and congestion status using external APIs. Furthermore, it calculates the optimal walking route based on this information and the user's emotional information, and sends it to the user's device.

[1297] 3. External API: An API that provides weather information and an API that provides congestion status.

[1298] 4. Emotion engine: Uses the user's camera or other sensors to recognize emotions from the user's facial expressions and voice.

[1299] Program processing overview

[1300] Enter and submit user information

[1301] 1. User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[1302] 2. User: Enter the desired duration (e.g. 1 hour).

[1303] 3. Device: Obtain current location using GPS function.

[1304] 4. Terminal: Activate the emotion engine and recognize the user's emotions.

[1305] 5. Terminal: User input information, current location, and emotion information are compiled in JSON format and sent to the server.

[1306] Obtaining weather and congestion information

[1307] 1. Server: Receives requests from users.

[1308] Example: Purpose: Relaxation, Time required: 1 hour, Current location: Shinjuku Station, Emotion: "Slightly stressed."

[1309] 2. Server: Sends a request to the weather API to get the current weather information (e.g. sunny).

[1310] 3. Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[1311] Route calculation

[1312] 1. Server: Calculates the optimal walking route based on the user's input information, weather information, congestion status, and emotional information acquired so far.

[1313] Example: Select a route that passes through Shinjuku Gyoen National Garden and leads to a new cafe. Prioritize quiet areas to reduce user stress.

[1314] 2. Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[1315] 3. Server: The optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the device.

[1316] Route presentation and AR information display

[1317] 1. Terminal: Interprets the route information received from the server and displays the route on a map.

[1318] 2. Device: Use the AR function to display markers or pop-ups at points of interest (e.g., new cafes or landmarks).

[1319] 3. User: Check the route through the app and start your walk.

[1320] Example: Take a route that passes through Shinjuku Gyoen National Garden and arrive at a new cafe.

[1321] Advertisement display

[1322] 1. Device: Prepares to display AR ads when approaching a specific point on the route.

[1323] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[1324] 2. User: Check the ads while walking and respond to the ads that interest them.

[1325] 3. Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[1326] In this way, the system provides an optimal walking route based on the user's emotional state, providing a more personalized experience for the user. By comprehensively taking into account weather, congestion, and emotional information, the system can provide a comfortable walking experience for the user and contribute to revitalizing local commercial activity.

[1327] The processing flow will be explained below.

[1328] Step 1:

[1329] User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[1330] Step 2:

[1331] User: Enter the desired duration (e.g., 1 hour).

[1332] Step 3:

[1333] Device: Obtain current location using GPS function.

[1334] Step 4:

[1335] Device: Uses a camera or microphone to provide the user's face and voice to the emotion engine.

[1336] Step 5:

[1337] On the device: The emotion engine analyzes the user's emotions and identifies their current emotional state (e.g., stress, anxiety, joy).

[1338] Step 6:

[1339] Terminal: User input information, current location, and emotion information are compiled in JSON format and sent to the server.

[1340] Step 7:

[1341] Server: Receives requests from users.

[1342] Example: Purpose: Relaxation, Time required: 1 hour, Current location: Shinjuku Station, Emotion: "Slightly stressed."

[1343] Step 8:

[1344] Server: Sends a request to the weather API to get current weather information (e.g. sunny).

[1345] Step 9:

[1346] Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[1347] Step 10:

[1348] Server: Calculates the optimal walking route based on user input, weather information, congestion status, and emotional information.

[1349] If the emotion is "stress," prioritize quieter routes and relaxing spots.

[1350] Step 11:

[1351] Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[1352] Step 12:

[1353] Server: Optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the terminal.

[1354] Step 13:

[1355] Terminal: Interprets the route information received from the server and displays the route on a map.

[1356] Step 14:

[1357] Device: Use the AR function to display markers and pop-ups at points of interest (e.g., new cafes or landmarks).

[1358] Step 15:

[1359] User: Check the route through the app and start the walk.

[1360] Step 16:

[1361] Device: Prepares to display AR ads when approaching a specific point on the route.

[1362] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[1363] Step 17:

[1364] Users: Check out ads while walking and respond to ads that interest them.

[1365] Step 18:

[1366] Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[1367] Example 2

[1368] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1369] Conventional walking route provision systems calculate routes by taking into account only weather information and congestion status, and therefore are unable to provide optimal routes that reflect the user's psychological state. Furthermore, there is a lack of means to provide a personalized experience that takes into account the user's emotions. This makes it difficult to provide walking routes that satisfy users, and there are also issues with limited contribution to local commercial activity.

[1370] 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 receiving user input information, a means for acquiring real-time weather information, a means for grasping the local congestion state, a means for recognizing the user's emotions, a means for calculating an optimal walking route based on the user's input information, weather information, congestion state, and emotion information, and a means for displaying the calculated walking route and points of interest to the user. This makes it possible to provide a personalized optimal walking route that takes into account the user's psychological state, real-time weather, and congestion state.

[1371] "User input information" refers to information such as the purpose of the walk and the required time provided by the user to the system.

[1372] "Real-time weather information" means data about current weather conditions in a specified area.

[1373] "Local congestion status" is information about the current level of congestion of people and vehicles at a specific location or route.

[1374] "Means for recognizing the user's emotions" refers to technology that analyzes the user's facial expressions and voice to determine their psychological state and emotions.

[1375] The "means for calculating the optimal walking route" is an algorithm or program for calculating the most suitable walking route for the user based on the user's input information and real-time weather information, congestion status, and emotional information.

[1376] The "calculated walking route" is a walking route derived by the means for calculating the optimal walking route described above.

[1377] "Points of interest" are places that are considered worth visiting by the user during a walk, such as new stores or landmarks.

[1378] "Augmented reality display means" is a technology that displays digital information overlaid on real-world scenery, and is a means of visually providing information such as points of interest on the user's device.

[1379] Overall system overview

[1380] This system provides optimal walking routes based on user input, real-time weather information, and local congestion status. The system also features an emotion engine that recognizes the user's emotions, and selects routes and suggests points of interest that match the user's psychological state.

[1381] System Components

[1382] 1. User device (smartphone or augmented reality device): The user inputs the purpose and duration of the walk, obtains the current location using GPS, and uses an emotion engine to recognize the user's emotions and displays the calculated walking route and points of interest.

[1383] 2. Server: Receives requests from users and obtains information such as weather and congestion status using external APIs. Based on this information and the user's emotional state, the server calculates the optimal walking route and sends it to the user's device.

[1384] 3. External API: An API that provides weather information and an API that provides congestion information.

[1385] 4. Emotion engine: Uses the user's camera or other sensors to recognize emotions from the user's facial expressions and voice.

[1386] Program processing overview

[1387] Enter and submit user information

[1388] The user opens the smartphone app and selects the purpose of their walk (e.g., relaxation, exercise, or discovering new stores). Next, they enter the desired duration (e.g., 1 hour), and the device uses its GPS function to obtain their current location. The device then activates an emotion engine that analyzes the user's facial expressions and voice to recognize their emotions. This information is then compiled in JSON format and sent to the server.

[1389] Obtaining weather and congestion information

[1390] The server receives a request from the user, sends a request to the weather API to get current weather information, and sends a request to the congestion API to get the local congestion status.

[1391] Walking route calculation

[1392] The server calculates the optimal walking route based on the user's input information, weather information, congestion status, and emotional information it has acquired so far. To reduce user stress, it prioritizes quiet areas and selects routes that include new shops and points of interest. This information is compiled in JSON format and sent to the user's device.

[1393] Route presentation and AR information display

[1394] The user's device interprets the route information received from the server and displays the route on a map. It also uses AR functionality to display markers and pop-ups at points of interest (new cafes and landmarks). The user checks the route through the app and begins their walk.

[1395] Specific actions

[1396] A user wants to take a relaxing walk, inputs the required time of one hour and their current location as Shinjuku Station, and the emotion engine recognizes the user as slightly stressed. The server retrieves "sunny" from the weather API and "somewhat crowded around Shinjuku Station" from the congestion API. The server then calculates a route to the cafe via Shinjuku Gyoen and sends it to the user.

[1397] Prompt Sentence Examples

[1398] "If the user selects "relaxation" as the purpose of the walk, the duration is one hour, the current location is Shinjuku Station, and the emotion is "slightly stressed," the system should calculate the optimal walking route via Shinjuku Gyoen."

[1399] "Recognize the user's emotional state and suggest optimal walking routes and points of interest based on that."

[1400] In this way, the system comprehensively considers the user's psychological state, real-time weather, and congestion, and provides the user with an optimal personalized walking route, which can also contribute to revitalizing local commercial activity.

[1401] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1402] Step 1:

[1403] User: Opens the smartphone app and selects the purpose of the walk. For example, the user selects "relaxation." This is the input information.

[1404] Step 2:

[1405] User: Enter the desired duration. For example, specify "1 hour." This input information will also be used in subsequent processing.

[1406] Step 3:

[1407] Device: Uses GPS to obtain current location. For example, obtain "Shinjuku Station." This is added to the input information.

[1408] Step 4:

[1409] Device: The emotion engine is activated and the smartphone's camera and microphone are used to recognize the user's emotions. As a result of emotion analysis, information such as "slightly stressed" is obtained. This emotional information also becomes part of the input data.

[1410] Step 5:

[1411] Device: The user's input information, current location, and emotion information are compiled into JSON format and sent to the server as an HTTP POST request. Specifically, the JSON structure shown below is generated.

[1412] json

[1413] {

[1414] "Purpose": "Relax",

[1415] "Duration": "1 hour",

[1416] "Current Location": "Shinjuku Station",

[1417] "Emotion": "Slightly stressed"

[1418] }

[1419] Step 6:

[1420] Server: Analyzes the request received from the user and sends a request to the weather API to obtain current weather information. For example, the information obtained is "sunny." This becomes the newly added input information.

[1421] Step 7:

[1422] Server: Next, a request is sent to the congestion API to obtain the local congestion status. For example, information such as "The area around Shinjuku Station is somewhat crowded" is obtained. This congestion information also becomes part of the input data.

[1423] Step 8:

[1424] Server: Calculates the optimal walking route based on the user's input information, weather information, congestion status, and emotional information acquired so far. For example, it calculates a route to reach a cafe via Shinjuku Gyoen. The calculated route information and points of interest are generated as output.

[1425] Step 9:

[1426] Server: The output walking route information and points of interest are compiled into JSON format and sent to the device. Specifically, the JSON structure shown below is generated.

[1427] json

[1428] {

[1429] "Route": "Route via Shinjuku Gyoen",

[1430] "Featured": "New Cafe"

[1431] }

[1432] Step 10:

[1433] Terminal: Analyzes the JSON data received from the server and displays the route in a map application. For example, it draws a "route to reach the cafe via Shinjuku Gyoen" on the map.

[1434] Step 11:

[1435] Device: Activate the AR function to display markers and pop-ups at points of interest along the route. For example, place AR markers at "new cafes" or "landmarks."

[1436] Step 12:

[1437] User: Check the route and points of interest on the app screen and start a walk. For example, execute "Go through Shinjuku Gyoen" and "Reach the cafe."

[1438] Step 13:

[1439] Device: Prepares to display AR advertisements when the user approaches a specific point on the route. For example, "approaching a cafe" and "displaying an AR advertisement with a special discount coupon."

[1440] Step 14:

[1441] User: Check out advertisements (e.g., special discount coupons) while walking and respond to advertisements that interest them.

[1442] Step 15:

[1443] Terminal: When a user takes an action on an advertisement (for example, obtains a coupon), the information is sent to the server in JSON format and stored in a database as statistical data.

[1444] (Application example 2)

[1445] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1446] Conventional walking route suggestion systems have limited means of taking into account weather information and local congestion, making it difficult to select an optimal route that reflects the user's psychological state. Furthermore, for certain tasks, such as delivery, it has not been possible to provide an optimal route that takes into account the psychological state of the delivery staff. This has resulted in a lack of routes that are comfortable and efficient for both users and delivery staff.

[1447] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user input information, means for acquiring real-time weather information, means for understanding the local congestion situation, means for recognizing the user's emotions, means for selecting a route and suggesting points of interest based on the user's psychological state, means for displaying the calculated walking route and points of interest to the user, means for providing the optimal delivery route taking into account the psychological state of the delivery staff, and means for displaying information and advertisements when approaching specific points. This makes it possible to provide the user and delivery staff with optimal routes and information that comprehensively take into account their psychological state and the external environment.

[1448] "User input information" refers to information sent by the user via the terminal, including the user's current location, destination, required travel time, and other requirements.

[1449] "Real-time weather information" refers to the latest weather data obtained from external APIs, etc., and includes current weather and forecast information.

[1450] "Regional congestion status" is information indicating the degree of concentration of people and vehicles in a specific area, and is obtained from external APIs, etc.

[1451] "User emotions" refers to analyzing the user's psychological state and mood using cameras, audio sensors, etc.

[1452] "Route selection based on psychological state" refers to the process of selecting the most suitable route for a user based on the user's emotional information.

[1453] "Points of interest" refer to places, stores, etc. that may catch the user's interest while walking or during delivery.

[1454] "The psychological state of delivery staff" refers to the mental state and stress level of the staff performing delivery work.

[1455] The "optimal delivery route" refers to the most efficient and comfortable route calculated by comprehensively taking into consideration the mental state of the delivery staff, weather information, and congestion conditions.

[1456] "Means for displaying information or advertisements" refers to a method for visually displaying information or advertisements related to a location to a user when the user approaches a specific point.

[1457] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to specific embodiments.

[1458] Overall system configuration

[1459] The system collects and analyzes user input, real-time weather information, local congestion status, and user sentiment information to provide the optimal walking or delivery route. The system includes the following main components:

[1460] 1. User device (smartphone or AR device)

[1461] It provides an interface for collecting and sending user input information, current location, and emotion information to the server.

[1462] It displays the optimal route and points of interest, and displays information and advertisements when you approach certain points.

[1463] 2. Server

[1464] Receive requests from users and obtain weather information and congestion status.

[1465] The optimal route is calculated based on the user's input information, weather information, congestion status, and emotional information, and transmitted to the user.

[1466] 3. External API

[1467] API for obtaining weather information (e.g. OpenWeatherMap API)

[1468] API to obtain congestion status (e.g., Google Maps Traffic API)

[1469] 4. Emotion Engine

[1470] APIs that utilize camera and audio sensors to recognize user emotions (e.g., Microsoft Azure Face API)

[1471] Program processing

[1472] The program in this system works as follows:

[1473] 1. Enter and submit user information

[1474] The user uses the user terminal to input the destination of the walk or delivery, the required time, the current location, etc.

[1475] The emotion engine is activated and recognizes emotions from the user's facial expressions and voice.

[1476] This information is compiled in JSON format and sent to the server.

[1477] 2. Obtaining weather information and congestion status

[1478] The server uses an external API to obtain current weather information and local congestion status.

[1479] 3. Route calculation

[1480] The server calculates the optimal walking or delivery route based on the user's input information, weather information, congestion status, and emotional information.

[1481] For delivery staff, the system takes into account their psychological state and provides routes that minimize stress, including points of interest that match the user's specified objectives.

[1482] 4. Route presentation and information display

[1483] The calculated route information and points of interest are transmitted to the user terminal.

[1484] The user terminal displays route information on a map, and also displays information and advertisements when the user approaches a specific point.

[1485] Specific examples

[1486] For example, if a delivery staff member inputs "Shinjuku Station" as their current location and their emotional information is recognized as "slightly stressed," the server will calculate the optimal route to the delivery destination, taking into account the current weather information (e.g., sunny) and congestion status (e.g., slightly crowded), prioritizing quieter routes. Additionally, when the delivery staff member approaches the delivery destination, specific information and advertisements will be displayed in AR.

[1487] The system can use a generative AI model with prompts like this:

[1488] "If the user is stressed, if the weather is bad, calculate the optimal delivery route with a focus on safety."

[1489] "If a user wants to discover new stores, calculate a walking route that reflects that desire."

[1490] In this way, the embodiments of the invention provide specific means for providing an optimal experience by comprehensively considering the psychology and environmental information of the user and delivery staff.

[1491] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1492] Step 1:

[1493] The user uses the device to input their current location, destination, purpose of walk or delivery, and required time. This information is formatted in JSON format. The device also uses the camera and microphone to collect the user's emotional data, which is analyzed by the emotion engine. The results of this analysis are also added to the JSON format. Input data: current location, destination, purpose of walk or delivery, required time, emotional data. Output data: input information and emotional data in JSON format.

[1494] Step 2:

[1495] The device sends formatted JSON formatted data to the server. The server receives this data and begins parsing it. Input data: Input information and emotion data in JSON format. Output data: None.

[1496] Step 3:

[1497] The server uses an external API to get real-time weather information based on the user's current location. It sends a request to the weather API (e.g., OpenWeatherMap API) and receives weather information as a response. Input data: current location. Output data: weather information.

[1498] Step 4:

[1499] The server also uses an external API to obtain the local congestion status based on the user's current location. It sends a request to the congestion status API (e.g., Google Maps Traffic API) and receives congestion status data as a response. Input data: current location. Output data: congestion status data.

[1500] Step 5:

[1501] The server integrates the received user input information, emotion data, weather information, and congestion status to calculate the optimal walking or delivery route. A route calculation algorithm is used to select a route that takes into account the user's psychological state and congestion status. Input data: User input information, emotion data, weather information, congestion status data. Output data: Optimal route information.

[1502] Step 6:

[1503] The server formats the calculated optimal route information and points of interest in JSON format and sends it to the terminal. Input data: optimal route information, points of interest information. Output data: route information and points of interest in JSON format.

[1504] Step 7:

[1505] The device analyzes the route information and points of interest in JSON format received from the server and displays them to the user through a map app or AR display. When the user approaches a specific point, related information or advertisements are displayed. Input data: Route information and points of interest in JSON format. Output data: Visual display to the user.

[1506] Step 8:

[1507] The user begins traveling along the route and reaches a specific point of interest or delivery destination. The user's behavior data and collected ad response data are then sent to the server and used for statistical analysis. Input data: user behavior data, ad response data. Output data: statistical data.

[1508] Through the above steps, a system is realized that provides optimal routes and information that comprehensively consider the user's emotional state and external environmental information.

[1509] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1510] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1511] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1512] [Fourth embodiment]

[1513] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1514] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1515] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1516] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1517] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1518] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1519] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1520] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1521] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1522] 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.

[1523] 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.

[1524] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1525] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1526] Overall system overview

[1527] This invention is a system that provides optimal walking routes based on information entered by the user, real-time weather information, and congestion status. This system provides users with opportunities to explore routes they don't usually take and new stores, contributing to the revitalization of local areas.

[1528] System Components

[1529] 1. User device (smartphone or AR device): Provides an interface where users can input the purpose of their walk, the required time, and their current location obtained via GPS. It also displays the calculated walking route and points of interest.

[1530] 2. Server: Receives requests from users and obtains information such as weather and congestion status using external APIs. Based on this information, it calculates the optimal walking route and sends it to the user's device.

[1531] 3. External API: An API that provides weather information and an API that provides congestion status.

[1532] Program processing overview

[1533] Enter and submit user information

[1534] 1. User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[1535] 2. User: Enter the desired duration (e.g. 1 hour).

[1536] 3. Device: Obtain current location using GPS function.

[1537] 4. Terminal: The user's input information and current location are compiled in JSON format and sent to the server.

[1538] Obtaining weather and congestion information

[1539] 1. Server: Receives requests from users.

[1540] Example: Relaxation purpose, required time 1 hour, current location Shinjuku Station.

[1541] 2. Server: Sends a request to the weather API to get the current weather information (e.g. sunny).

[1542] 3. Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[1543] Route calculation

[1544] 1. Server: Calculates the optimal walking route based on the user's input information, weather information, and congestion status obtained so far.

[1545] Example: Select a route that passes through Shinjuku Gyoen and leads to a new cafe.

[1546] 2. Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[1547] 3. Server: The optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the device.

[1548] Route presentation and AR information display

[1549] 1. Terminal: Interprets the route information received from the server and displays the route on a map.

[1550] 2. Device: Use the AR function to display markers or pop-ups at points of interest (e.g., new cafes or landmarks).

[1551] 3. User: Check the route through the app and start your walk.

[1552] Advertisement display

[1553] 1. Device: Prepares to display AR ads when approaching a specific point on the route.

[1554] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[1555] 2. User: Check the ads while walking and respond to the ads that interest them.

[1556] 3. Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[1557] In this way, this system not only provides users with the best walking route, but also contributes to revitalizing local commercial activity. By taking into account weather and congestion, it provides users with a comfortable walking experience and can also generate revenue from advertisers.

[1558] The processing flow will be explained below.

[1559] Step 1:

[1560] User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[1561] Step 2:

[1562] User: Enter the desired duration (e.g., 1 hour).

[1563] Step 3:

[1564] Device: Obtain current location using GPS function.

[1565] Step 4:

[1566] Terminal: The user's input information and current location are compiled in JSON format and sent to the server.

[1567] Step 5:

[1568] Server: Receives requests from users.

[1569] Example: Relaxation purpose, required time 1 hour, current location Shinjuku Station.

[1570] Step 6:

[1571] Server: Sends a request to the weather API to get current weather information (e.g. sunny).

[1572] Step 7:

[1573] Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[1574] Step 8:

[1575] Server: Calculates the optimal walking route based on the user's input information, weather information, and congestion status acquired so far.

[1576] Example: Select a route that passes through Shinjuku Gyoen and leads to a new cafe.

[1577] Step 9:

[1578] Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[1579] Step 10:

[1580] Server: Optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the terminal.

[1581] Step 11:

[1582] Terminal: Interprets the route information received from the server and displays the route on a map.

[1583] Step 12:

[1584] Device: Use the AR function to display markers and pop-ups at points of interest (e.g., new cafes or landmarks).

[1585] Step 13:

[1586] User: Check the route through the app and start the walk.

[1587] Step 14:

[1588] Device: Prepares to display AR ads as it approaches a specific point on its route.

[1589] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[1590] Step 15:

[1591] Users: Check out ads while walking and respond to ads that interest them.

[1592] Step 16:

[1593] Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[1594] Example 1

[1595] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1596] Conventional walking route provision systems have difficulty taking into account individual user objectives and real-time environmental factors (weather, congestion, etc.). Furthermore, they lack the functionality to stimulate local commercial activity through advertising. As a result, there is a need for systems that not only increase user satisfaction but also help explore new stores in the area and stimulate commercial activity.

[1597] 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.

[1598] In this invention, the server includes means for receiving user input information, means for acquiring real-time weather information, means for grasping the local congestion status, means for calculating an optimal walking route based on the user input information, the weather information, and the congestion status, means for displaying the calculated walking route and points of interest to the user, means for displaying advertisements when the user approaches points of interest, and means for collecting and accumulating the user's responses to the advertisements as statistical data. This makes it possible to provide an optimal walking route that takes into account the user's individual goals and real-time environmental factors. It can also realize support for local revitalization and commercial activities.

[1599] "User input information" refers to data provided by the user to the system, specifically the purpose of the walk (e.g., relaxation, exercise), the required time, current location, etc.

[1600] "Real-time weather information" refers to data indicating current weather conditions, obtained from an external weather API.

[1601] "Regional congestion status" is data indicating the current level of congestion in a specific area, and is obtained from an external congestion API.

[1602] "Calculating the optimal walking route" refers to the process of using an algorithm to calculate the optimal walking route for the user based on information input by the user, weather information, and congestion status.

[1603] "Calculated walking route" refers to route information derived by calculating the optimal walking route.

[1604] "Points of interest" refer to noteworthy places and stores along the walking route, and are intended to attract the user's interest.

[1605] "Augmented reality display means" refers to a function that uses AR (augmented reality) technology to display virtual information superimposed on real scenery.

[1606] The "means for displaying advertisements" refers to a function for displaying advertisement information when the user approaches a point of interest.

[1607] "Means for collecting users' responses to advertisements and accumulating them as statistical data" refers to the function of collecting data on the actions users take in response to displayed advertisements and saving this data as statistical information.

[1608] This invention is a system that provides optimal walking routes based on information entered by the user, real-time weather information, and congestion status. This system provides users with opportunities to explore routes they don't usually take and new stores, contributing to the revitalization of local areas.

[1609] System Components

[1610] 1. User device (smartphone or augmented reality device)

[1611] It provides an interface for users to input the purpose of their walk, the estimated time, and their current location obtained via GPS.

[1612] View calculated walking routes and points of interest.

[1613] 2. Server

[1614] Receives requests from users and obtains information using external APIs such as weather and congestion status.

[1615] Based on this information, the optimal walking route is calculated and sent to the user's terminal.

[1616] 3. External API

[1617] An API that provides weather information and an API that provides congestion status.

[1618] Program processing overview (example)

[1619] 1. Enter and submit user information

[1620] The user starts the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, or discovering new shops). For example, the user taps "Relax" on the app's menu screen.

[1621] The user inputs the desired time required (e.g., 1 hour). Specifically, the user inputs "1 hour" in the time input field and presses the submit button.

[1622] The device uses the GPS function to obtain the current location. The app calls the GPS module in the background to obtain the current latitude and longitude.

[1623] The user's input information and current location are compiled in JSON format and sent to the server.

[1624] 2. Obtaining weather and congestion information

[1625] The server receives a request from the user. Specifically, the server analyzes the HTTP request and obtains the user's purpose, required time, and current latitude and longitude.

[1626] The server sends a request to the weather API to obtain current weather information. The server sends the latitude and longitude of "Shinjuku Station" to the weather API and obtains the weather information "Sunny" in return.

[1627] The server sends a request to the congestion API to obtain the local congestion status. The server sends information about the area around "Shinjuku Station" to the congestion API, and receives the congestion status "slightly crowded" in return.

[1628] 3. Route calculation

[1629] The server calculates the optimal walking route based on user input, weather information, and traffic congestion. Specifically, the server applies an algorithm to generate a route that goes "via Shinjuku Gyoen → new cafe → return to Shinjuku Station."

[1630] The server applies an algorithm that prioritizes unusual routes and new stores, and adds points. For example, the algorithm adds "newly opened cafes" and "places where special events are held" to the route.

[1631] The server compiles optimal route information and points of interest in JSON format and sends it to the terminal.

[1632] 4. Route presentation and AR information display

[1633] The device interprets the route information received from the server and displays the route on a map. The app calls the map module and displays the route "Shinjuku Station → Shinjuku Gyoen → New Cafe."

[1634] The device uses augmented reality to display markers and pop-ups at points of interest. For example, the AR module displays a marker at the location of a "new cafe" and a pop-up with a "discount coupon."

[1635] The user checks the route through the app and starts the walk. The user checks the displayed route and actually starts the walk.

[1636] 5. Advertising

[1637] When the device approaches a specific point on the route, it prepares to display an advertisement. When the user approaches a cafe, the device calls the AR module and prepares a "special discount coupon."

[1638] Users can view ads while walking and interact with content they are interested in. For example, they can tap on a coupon displayed in an AR pop-up to view more information.

[1639] When a user takes an action on an advertisement, the terminal sends the information to the server and stores it as statistical data. When a user acquires a coupon, the information is sent to the server and recorded in the database.

[1640] Examples of prompt statements

[1641] When inputting a prompt to a generative AI model to suggest a route, use the following prompt:

[1642] "The current weather is sunny, the estimated travel time is one hour, and I'm at Shinjuku Station. Please suggest a recommended walking route for relaxation."

[1643] "It's cloudy, and I'd like to take a 30-minute walking route starting from Shinjuku Station for exercise. Please suggest a route that passes through new stores."

[1644] The system's main functions are to provide a comfortable walking experience by taking into account the user's individual needs and real-time environmental factors, and to support local commercial activities. Users can easily check their walking routes through the app and enjoy the fun of exploring new places. In addition, advertisements and collected statistical data are used by local businesses, contributing to the revitalization of commercial activities.

[1645] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1646] Step 1:

[1647] User: Launches the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[1648] Specific action: The user taps "Relax" on the app's menu screen.

[1649] Input: User intent

[1650] Output: Objective is selected

[1651] Step 2:

[1652] User: Enter the desired duration (e.g., 1 hour).

[1653] Specific behavior: The user enters "1 hour" in the time input field and presses the submit button.

[1654] Input: Time required

[1655] Output: Time is input

[1656] Step 3:

[1657] Device: Obtain current location using GPS function.

[1658] Specific behavior: The app calls the GPS module in the background to get the current latitude and longitude.

[1659] Input: GPS function

[1660] Output: Current location (latitude, longitude)

[1661] Step 4:

[1662] Terminal: The user's input information and current location are compiled in JSON format and sent to the server.

[1663] Specific operation: Generates JSON data and sends it to the server via an HTTP request.

[1664] Input: User's purpose, time required, current location

[1665] Output: Request sent to server

[1666] Step 5:

[1667] Server: Receives requests from users.

[1668] What it does: The server analyzes the HTTP request and obtains data about the user's purpose, time required, and current location.

[1669] Input: HTTP request

[1670] Output: User's purpose, time required, and current location

[1671] Step 6:

[1672] Server: Sends a request to the weather API to get current weather information.

[1673] Specific operation: Sends an HTTP request to the weather API and receives weather information.

[1674] Input: Current location (latitude, longitude)

[1675] Output: Weather information (e.g. sunny)

[1676] Step 7:

[1677] Server: Sends a request to the congestion API to obtain the local congestion status.

[1678] Specific operation: Send an HTTP request to the congestion API and receive congestion information.

[1679] Input: Current location (latitude, longitude)

[1680] Output: Congestion information (e.g., slightly crowded)

[1681] Step 8:

[1682] Server: Calculates the optimal walking route based on user input, weather information, and congestion status.

[1683] What it does: Apply algorithms to calculate optimal routes and points of interest.

[1684] Input: User's purpose, travel time, current location, weather information, congestion information

[1685] Output: Optimal walking route (e.g. Shinjuku Gyoen → New cafe)

[1686] Step 9:

[1687] Server: Optimal route information and points of interest are compiled in JSON format and sent to the terminal.

[1688] Specific operation: Generates JSON data and sends it to the terminal as an HTTP response.

[1689] Input: Best walking route, points of interest

[1690] Output: Sending a response to the device

[1691] Step 10:

[1692] Terminal: Interprets the route information received from the server and displays the route on a map.

[1693] Specific operation: Calls the map module and displays the route on the map.

[1694] Input: Route information, points of interest

[1695] Output: Route display on map

[1696] Step 11:

[1697] Device: Use the AR function to display markers and pop-ups at points of interest.

[1698] Specific operation: The AR module displays markers and popups at points of interest.

[1699] Input: Points of Interest

[1700] Output: AR display

[1701] Step 12:

[1702] User: Check the route through the app and start the walk.

[1703] Specific behavior: The user checks the displayed route and starts walking.

[1704] Input: Route display (map, AR)

[1705] Output: Start of walk

[1706] Step 13:

[1707] Terminal: Prepares to display advertisements as you approach certain points along your route.

[1708] Specific operation: The AR module detects when the user approaches a specific point and prepares an advertisement.

[1709] Input: GPS data, specific points

[1710] Output: Ad Ready

[1711] Step 14:

[1712] Users: Check out ads while walking and respond to ads that interest them.

[1713] Specific behavior: The user taps on the coupon displayed in the AR popup to view more information.

[1714] Input: AR ad

[1715] Output: User response

[1716] Step 15:

[1717] Terminal: When a user takes action on an advertisement, the information is sent to the server and stored as statistical data.

[1718] Specific behavior: Records user actions and sends them to the server.

[1719] Input: User action data

[1720] Output: Sending data to the server, accumulating statistical data

[1721] (Application example 1)

[1722] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1723] In today's world, it is difficult for users to enjoy a pleasant walk and discover new local commercial facilities at the same time. This becomes even more difficult when external factors such as weather and congestion affect the activities. Therefore, there is a need for a system that takes weather and congestion into account and provides optimal routes that allow users to comfortably discover new stores and commercial facilities. Furthermore, utilizing such a system to revitalize local commercial activities is also an important issue.

[1724] 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.

[1725] In this invention, the server includes a means for receiving user input information, a means for acquiring real-time weather information, and a means for grasping the local congestion status, thereby making it possible to calculate optimal walking routes and shopping routes based on the user input information, weather information, and congestion status, and display them to the user.

[1726] "User input information" refers to information such as purpose, required time, and current location that the user provides to the system.

[1727] "Real-time weather information" refers to current weather and forecast information based on that weather, and is data obtained from an external API.

[1728] "Regional congestion status" is information indicating the degree of congestion of people and vehicles in a specified area, and is also data obtained from an external API.

[1729] The "optimal walking route" is the most suitable walking route for the user, calculated based on the user's input information, real-time weather information, and local congestion status.

[1730] "Points of interest" are spots such as new stores and landmarks that the user may be interested in along the optimal walking route.

[1731] A "purchase path" is the optimal route for a user to reach a particular physical store, and may include a walking route.

[1732] "Recommended stores" are commercial facilities and stores that the system recommends to users based on its own algorithms and data.

[1733] "Augmented reality display means" refers to a means for displaying points of interest and recommended stores using augmented reality technology, and utilizes devices such as smart glasses and head-mounted displays.

[1734] Overall system overview

[1735] This invention is a system that provides optimal walking and shopping routes based on information entered by users, real-time weather information, and congestion status. This system uses devices such as smartphones, smart glasses, and head-mounted displays to provide users with opportunities to explore routes they don't usually take and new stores, thereby revitalizing local commercial activity.

[1736] Program processing overview

[1737] Enter and submit user information

[1738] The server receives the user's purpose information, required time, and current location obtained by GPS input using a smartphone or AR device. The user inputs the purpose of the walk (e.g., relaxation, exercise, discovering new shops) and the desired duration (e.g., 1 hour), and the device obtains the user's current location using its GPS function. The user's input information and current location are compiled in JSON format and sent to the server.

[1739] Obtaining weather and congestion information

[1740] The server receives a request from a user and obtains weather information and congestion information from the weather API and congestion API, respectively. For example, the server sends a request to the weather API to obtain current weather information (e.g., sunny), and then sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[1741] Route calculation

[1742] The server calculates optimal walking and shopping routes based on the user's input information, weather information, and congestion status. For example, it selects a route that passes through Shinjuku Gyoen National Garden and finds new cafes, and applies an algorithm that prioritizes exploring routes that are not usually taken and new commercial facilities. The calculation results, including optimal route information and points of interest, are sent to the device in JSON format.

[1743] Route presentation and AR information display

[1744] The device interprets the route information received from the server and displays the route on a map. It also uses AR functionality to display markers and pop-ups at points of interest and recommended stores. The user can check the suggested optimal route through the app and begin their walk or shopping.

[1745] The hardware used includes smartphones, smart glasses (e.g., Google Glass, HoloLens), and head-mounted displays (e.g., Oculus Rift, HTC Vive).The software used includes Python, the Requests module (API requests), Geopy (GPS information acquisition), OpenWeatherMap API (weather information acquisition), and Crowd API (crowding status acquisition).

[1746] Prompts and Sentence Examples

[1747] "Create a program that suggests the best walking route based on user input and current location, taking into account weather and traffic conditions. The program's functionality would include:

[1748] 1. Obtain the user's purpose, required time, and current location.

[1749] 2. Collect weather and crowd data using weather and crowd APIs.

[1750] 3. Calculate routes based on weather, congestion, and user preferences.

[1751] 4. The calculation results are provided to the user and displayed on a smartphone or AR device.

[1752] Example of the results:

[1753] Shinjuku Station: Starting point

[1754] Shinjuku Gyoen: A place to relax

[1755] New Cafe: What to Look For

[1756] Please create your code based on this."

[1757] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1758] Step 1:

[1759] The user launches a smartphone app or AR device and inputs the purpose of their walk (e.g., relaxation, exercise, or discovering new shops) and the desired duration (e.g., 1 hour). The device also uses its GPS function to obtain the user's current location. This information is then compiled as user input.

[1760] Input: Destination, travel time, current location

[1761] Output: User input information (purpose, time required, current location in JSON format)

[1762] Step 2:

[1763] The terminal compiles the acquired user input information into JSON format and sends it to the server.

[1764] Input: User input information (purpose, time required, current location in JSON format)

[1765] Output: User input sent to the server

[1766] Step 3:

[1767] The server receives the user's input information, sends a request to the weather API to obtain current weather information, and sends a request to the congestion API to obtain local congestion information.

[1768] Input: User input information (purpose, time required, current location in JSON format)

[1769] Data processing: Weather API request, Congestion API request

[1770] Output: Weather information, congestion information (JSON format)

[1771] Step 4:

[1772] The server calculates optimal walking and shopping routes based on weather information, congestion information, and user input, using an algorithm that prioritizes less commonly used routes and new commercial facilities.

[1773] Input: User input information, weather information, and congestion information (all in JSON format)

[1774] Data calculation: Calculation of optimal routes and purchase paths (using algorithms)

[1775] Output: Optimal walking and shopping routes, points of interest (JSON format)

[1776] Step 5:

[1777] The server compiles the calculated optimal walking route, shopping route, and points of interest in JSON format and sends it to the device.

[1778] Input: Optimal walking route, shopping route, points of interest (JSON format)

[1779] Output: Route information and points of interest sent to the device

[1780] Step 6:

[1781] The terminal interprets the route information and points of interest received from the server and displays the route on a map. It also uses an augmented reality display means to display markers and pop-ups at points of interest and recommended stores.

[1782] Input: Route information and points of interest sent to the device (JSON format)

[1783] Output: The route, points of interest, markers and popups displayed to the user

[1784] Step 7:

[1785] Users can view suggested routes and begin their walk or purchase through the app. As users approach specific points of interest, the device displays additional information and advertisements.

[1786] Input: Route information and points of interest confirmed by the user

[1787] Output: Additional information or advertisements based on user behavior

[1788] These processing steps allow users to have a comfortable and efficient walking and shopping experience, and also contribute to the discovery of new commercial facilities and the revitalization of local areas.

[1789] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1790] Overall system overview

[1791] This system provides optimal walking routes based on real-time weather and congestion information, along with information entered by the user. By combining this with an emotion engine that recognizes the user's emotions, the system selects routes and suggests points of interest that match the user's psychological state.

[1792] System Components

[1793] 1. User device (smartphone or AR device): Provides an interface where users can input the purpose of their walk, the required time, and their current location obtained via GPS. It also uses an emotion engine to recognize the user's emotions and displays the calculated walking route and points of interest.

[1794] 2. Server: Receives requests from users and obtains information such as weather and congestion status using external APIs. Furthermore, it calculates the optimal walking route based on this information and the user's emotional information, and sends it to the user's device.

[1795] 3. External API: An API that provides weather information and an API that provides congestion status.

[1796] 4. Emotion engine: Uses the user's camera or other sensors to recognize emotions from the user's facial expressions and voice.

[1797] Program processing overview

[1798] Enter and submit user information

[1799] 1. User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[1800] 2. User: Enter the desired duration (e.g. 1 hour).

[1801] 3. Device: Obtain current location using GPS function.

[1802] 4. Terminal: Activate the emotion engine and recognize the user's emotions.

[1803] 5. Terminal: User input information, current location, and emotion information are compiled in JSON format and sent to the server.

[1804] Obtaining weather and congestion information

[1805] 1. Server: Receives requests from users.

[1806] Example: Purpose: Relaxation, Time required: 1 hour, Current location: Shinjuku Station, Emotion: "Slightly stressed."

[1807] 2. Server: Sends a request to the weather API to get the current weather information (e.g. sunny).

[1808] 3. Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[1809] Route calculation

[1810] 1. Server: Calculates the optimal walking route based on the user's input information, weather information, congestion status, and emotional information acquired so far.

[1811] Example: Select a route that passes through Shinjuku Gyoen National Garden and leads to a new cafe. Prioritize quiet areas to reduce user stress.

[1812] 2. Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[1813] 3. Server: The optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the device.

[1814] Route presentation and AR information display

[1815] 1. Terminal: Interprets the route information received from the server and displays the route on a map.

[1816] 2. Device: Use the AR function to display markers or pop-ups at points of interest (e.g., new cafes or landmarks).

[1817] 3. User: Check the route through the app and start your walk.

[1818] Example: Take a route that passes through Shinjuku Gyoen National Garden and arrive at a new cafe.

[1819] Advertisement display

[1820] 1. Device: Prepares to display AR ads when approaching a specific point on the route.

[1821] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[1822] 2. User: Check the ads while walking and respond to the ads that interest them.

[1823] 3. Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[1824] In this way, the system provides an optimal walking route based on the user's emotional state, providing a more personalized experience for the user. By comprehensively taking into account weather, congestion, and emotional information, the system can provide a comfortable walking experience for the user and contribute to revitalizing local commercial activity.

[1825] The processing flow will be explained below.

[1826] Step 1:

[1827] User: Opens the smartphone app and selects the purpose of the walk (e.g., relaxation, exercise, discovering new shops).

[1828] Step 2:

[1829] User: Enter the desired duration (e.g., 1 hour).

[1830] Step 3:

[1831] Device: Obtain current location using GPS function.

[1832] Step 4:

[1833] Device: Uses a camera or microphone to provide the user's face and voice to the emotion engine.

[1834] Step 5:

[1835] On the device: The emotion engine analyzes the user's emotions and identifies their current emotional state (e.g., stress, anxiety, joy).

[1836] Step 6:

[1837] Terminal: User input information, current location, and emotion information are compiled in JSON format and sent to the server.

[1838] Step 7:

[1839] Server: Receives requests from users.

[1840] Example: Purpose: Relaxation, Time required: 1 hour, Current location: Shinjuku Station, Emotion: "Slightly stressed."

[1841] Step 8:

[1842] Server: Sends a request to the weather API to get current weather information (e.g. sunny).

[1843] Step 9:

[1844] Server: Sends a request to the congestion API to obtain the local congestion status (e.g., the area around Shinjuku Station is slightly crowded).

[1845] Step 10:

[1846] Server: Calculates the optimal walking route based on user input, weather information, congestion status, and emotional information.

[1847] If the emotion is "stress," prioritize quieter routes and relaxing spots.

[1848] Step 11:

[1849] Server: Apply an algorithm that prioritizes exploring unusual routes and new stores, and adds points.

[1850] Step 12:

[1851] Server: Optimal route information (route) and points of interest (new shops and landmarks) are compiled in JSON format and sent to the terminal.

[1852] Step 13:

[1853] Terminal: Interprets the route information received from the server and displays the route on a map.

[1854] Step 14:

[1855] Device: Use the AR function to display markers and pop-ups at points of interest (e.g., new cafes or landmarks).

[1856] Step 15:

[1857] User: Check the route through the app and start the walk.

[1858] Step 16:

[1859] Device: Prepares to display AR ads when approaching a specific point on the route.

[1860] Example: When you approach a cafe, an AR ad with a special discount coupon will be displayed as a pop-up.

[1861] Step 17:

[1862] Users: Check out ads while walking and respond to ads that interest them.

[1863] Step 18:

[1864] Terminal: When a user takes an action in response to an advertisement (e.g., obtains a coupon), that information is sent to the server and stored as statistical data.

[1865] Example 2

[1866] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1867] Conventional walking route provision systems calculate routes by taking into account only weather information and congestion status, and therefore are unable to provide optimal routes that reflect the user's psychological state. Furthermore, there is a lack of means to provide a personalized experience that takes into account the user's emotions. This makes it difficult to provide walking routes that satisfy users, and there are also issues with limited contribution to local commercial activity.

[1868] 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 receiving user input information, a means for acquiring real-time weather information, a means for grasping the local congestion state, a means for recognizing the user's emotions, a means for calculating an optimal walking route based on the user's input information, weather information, congestion state, and emotion information, and a means for displaying the calculated walking route and points of interest to the user. This makes it possible to provide a personalized optimal walking route that takes into account the user's psychological state, real-time weather, and congestion state.

[1869] "User input information" refers to information such as the purpose of the walk and the required time provided by the user to the system.

[1870] "Real-time weather information" means data about current weather conditions in a specified area.

[1871] "Local congestion status" is information about the current level of congestion of people and vehicles at a specific location or route.

[1872] "Means for recognizing the user's emotions" refers to technology that analyzes the user's facial expressions and voice to determine their psychological state and emotions.

[1873] The "means for calculating the optimal walking route" is an algorithm or program for calculating the most suitable walking route for the user based on the user's input information and real-time weather information, congestion status, and emotional information.

[1874] The "calculated walking route" is a walking route derived by the means for calculating the optimal walking route described above.

[1875] "Points of interest" are places that are considered worth visiting by the user during a walk, such as new stores or landmarks.

[1876] "Augmented reality display means" is a technology that displays digital information overlaid on real-world scenery, and is a means of visually providing information such as points of interest on the user's device.

[1877] Overall system overview

[1878] This system provides optimal walking routes based on user input, real-time weather information, and local congestion status. The system also features an emotion engine that recognizes the user's emotions, and selects routes and suggests points of interest that match the user's psychological state.

[1879] System Components

[1880] 1. User device (smartphone or augmented reality device): The user inputs the purpose and duration of the walk, obtains the current location using GPS, and uses an emotion engine to recognize the user's emotions and displays the calculated walking route and points of interest.

[1881] 2. Server: Receives requests from users and obtains information such as weather and congestion status using external APIs. Based on this information and the user's emotional state, the server calculates the optimal walking route and sends it to the user's device.

[1882] 3. External API: An API that provides weather information and an API that provides congestion information.

[1883] 4. Emotion engine: Uses the user's camera or other sensors to recognize emotions from the user's facial expressions and voice.

[1884] Program processing overview

[1885] Enter and submit user information

[1886] The user opens the smartphone app and selects the purpose of their walk (e.g., relaxation, exercise, or discovering new stores). Next, they enter the desired duration (e.g., 1 hour), and the device uses its GPS function to obtain their current location. The device then activates an emotion engine that analyzes the user's facial expressions and voice to recognize their emotions. This information is then compiled in JSON format and sent to the server.

[1887] Obtaining weather and congestion information

[1888] The server receives a request from the user, sends a request to the weather API to get current weather information, and sends a request to the congestion API to get the local congestion status.

[1889] Walking route calculation

[1890] The server calculates the optimal walking route based on the user's input information, weather information, congestion status, and emotional information it has acquired so far. To reduce user stress, it prioritizes quiet areas and selects routes that include new shops and points of interest. This information is compiled in JSON format and sent to the user's device.

[1891] Route presentation and AR information display

[1892] The user's device interprets the route information received from the server and displays the route on a map. It also uses AR functionality to display markers and pop-ups at points of interest (new cafes and landmarks). The user checks the route through the app and begins their walk.

[1893] Specific actions

[1894] A user wants to take a relaxing walk, inputs the required time of one hour and their current location as Shinjuku Station, and the emotion engine recognizes the user as slightly stressed. The server retrieves "sunny" from the weather API and "somewhat crowded around Shinjuku Station" from the congestion API. The server then calculates a route to the cafe via Shinjuku Gyoen and sends it to the user.

[1895] Prompt Sentence Examples

[1896] "If the user selects "relaxation" as the purpose of the walk, the duration is one hour, the current location is Shinjuku Station, and the emotion is "slightly stressed," the system should calculate the optimal walking route via Shinjuku Gyoen."

[1897] "Recognize the user's emotional state and suggest optimal walking routes and points of interest based on that."

[1898] In this way, the system comprehensively considers the user's psychological state, real-time weather, and congestion, and provides the user with an optimal personalized walking route, which can also contribute to revitalizing local commercial activity.

[1899] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1900] Step 1:

[1901] User: Opens the smartphone app and selects the purpose of the walk. For example, the user selects "relaxation." This is the input information.

[1902] Step 2:

[1903] User: Enter the desired duration. For example, specify "1 hour." This input information will also be used in subsequent processing.

[1904] Step 3:

[1905] Device: Uses GPS to obtain current location. For example, obtain "Shinjuku Station." This is added to the input information.

[1906] Step 4:

[1907] Device: The emotion engine is activated and the smartphone's camera and microphone are used to recognize the user's emotions. As a result of emotion analysis, information such as "slightly stressed" is obtained. This emotional information also becomes part of the input data.

[1908] Step 5:

[1909] Device: The user's input information, current location, and emotion information are compiled into JSON format and sent to the server as an HTTP POST request. Specifically, the JSON structure shown below is generated.

[1910] json

[1911] {

[1912] "Purpose": "Relax",

[1913] "Duration": "1 hour",

[1914] "Current Location": "Shinjuku Station",

[1915] "Emotion": "Slightly stressed"

[1916] }

[1917] Step 6:

[1918] Server: Analyzes the request received from the user and sends a request to the weather API to obtain current weather information. For example, the information obtained is "sunny." This becomes the newly added input information.

[1919] Step 7:

[1920] Server: Next, a request is sent to the congestion API to obtain the local congestion status. For example, information such as "The area around Shinjuku Station is somewhat crowded" is obtained. This congestion information also becomes part of the input data.

[1921] Step 8:

[1922] Server: Calculates the optimal walking route based on the user's input information, weather information, congestion status, and emotional information acquired so far. For example, it calculates a route to reach a cafe via Shinjuku Gyoen. The calculated route information and points of interest are generated as output.

[1923] Step 9:

[1924] Server: The output walking route information and points of interest are compiled into JSON format and sent to the device. Specifically, the JSON structure shown below is generated.

[1925] json

[1926] {

[1927] "Route": "Route via Shinjuku Gyoen",

[1928] "Featured": "New Cafe"

[1929] }

[1930] Step 10:

[1931] Terminal: Analyzes the JSON data received from the server and displays the route in a map application. For example, it draws a "route to reach the cafe via Shinjuku Gyoen" on the map.

[1932] Step 11:

[1933] Device: Activate the AR function to display markers and pop-ups at points of interest along the route. For example, place AR markers at "new cafes" or "landmarks."

[1934] Step 12:

[1935] User: Check the route and points of interest on the app screen and start a walk. For example, execute "Go through Shinjuku Gyoen" and "Reach the cafe."

[1936] Step 13:

[1937] Device: Prepares to display AR advertisements when the user approaches a specific point on the route. For example, "approaching a cafe" and "displaying an AR advertisement with a special discount coupon."

[1938] Step 14:

[1939] User: Check out advertisements (e.g., special discount coupons) while walking and respond to advertisements that interest them.

[1940] Step 15:

[1941] Terminal: When a user takes an action on an advertisement (for example, obtains a coupon), the information is sent to the server in JSON format and stored in a database as statistical data.

[1942] (Application example 2)

[1943] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1944] Conventional walking route suggestion systems have limited means of taking into account weather information and local congestion, making it difficult to select an optimal route that reflects the user's psychological state. Furthermore, for certain tasks, such as delivery, it has not been possible to provide an optimal route that takes into account the psychological state of the delivery staff. This has resulted in a lack of routes that are comfortable and efficient for both users and delivery staff.

[1945] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user input information, means for acquiring real-time weather information, means for understanding the local congestion situation, means for recognizing the user's emotions, means for selecting a route and suggesting points of interest based on the user's psychological state, means for displaying the calculated walking route and points of interest to the user, means for providing the optimal delivery route taking into account the psychological state of the delivery staff, and means for displaying information and advertisements when approaching specific points. This makes it possible to provide the user and delivery staff with optimal routes and information that comprehensively take into account their psychological state and the external environment.

[1946] "User input information" refers to information sent by the user via the terminal, including the user's current location, destination, required travel time, and other requirements.

[1947] "Real-time weather information" refers to the latest weather data obtained from external APIs, etc., and includes current weather and forecast information.

[1948] "Regional congestion status" is information indicating the degree of concentration of people and vehicles in a specific area, and is obtained from external APIs, etc.

[1949] "User emotions" refers to analyzing the user's psychological state and mood using cameras, audio sensors, etc.

[1950] "Route selection based on psychological state" refers to the process of selecting the most suitable route for a user based on the user's emotional information.

[1951] "Points of interest" refer to places, stores, etc. that may catch the user's interest while walking or during delivery.

[1952] "The psychological state of delivery staff" refers to the mental state and stress level of the staff performing delivery work.

[1953] The "optimal delivery route" refers to the most efficient and comfortable route calculated by comprehensively taking into consideration the mental state of the delivery staff, weather information, and congestion conditions.

[1954] "Means for displaying information or advertisements" refers to a method for visually displaying information or advertisements related to a location to a user when the user approaches a specific point.

[1955] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to specific embodiments.

[1956] Overall system configuration

[1957] The system collects and analyzes user input, real-time weather information, local congestion status, and user sentiment information to provide the optimal walking or delivery route. The system includes the following main components:

[1958] 1. User device (smartphone or AR device)

[1959] It provides an interface for collecting and sending user input information, current location, and emotion information to the server.

[1960] It displays the optimal route and points of interest, and displays information and advertisements when you approach certain points.

[1961] 2. Server

[1962] Receive requests from users and obtain weather information and congestion status.

[1963] The optimal route is calculated based on the user's input information, weather information, congestion status, and emotional information, and transmitted to the user.

[1964] 3. External API

[1965] API for obtaining weather information (e.g. OpenWeatherMap API)

[1966] API to obtain congestion status (e.g., Google Maps Traffic API)

[1967] 4. Emotion Engine

[1968] APIs that utilize camera and audio sensors to recognize user emotions (e.g., Microsoft Azure Face API)

[1969] Program processing

[1970] The program in this system works as follows:

[1971] 1. Enter and submit user information

[1972] The user uses the user terminal to input the destination of the walk or delivery, the required time, the current location, etc.

[1973] The emotion engine is activated and recognizes emotions from the user's facial expressions and voice.

[1974] This information is compiled in JSON format and sent to the server.

[1975] 2. Obtaining weather information and congestion status

[1976] The server uses an external API to obtain current weather information and local congestion status.

[1977] 3. Route calculation

[1978] The server calculates the optimal walking or delivery route based on the user's input information, weather information, congestion status, and emotional information.

[1979] For delivery staff, the system takes into account their psychological state and provides routes that minimize stress, including points of interest that match the user's specified objectives.

[1980] 4. Route presentation and information display

[1981] The calculated route information and points of interest are transmitted to the user terminal.

[1982] The user terminal displays route information on a map, and also displays information and advertisements when the user approaches a specific point.

[1983] Specific examples

[1984] For example, if a delivery staff member inputs "Shinjuku Station" as their current location and their emotional information is recognized as "slightly stressed," the server will calculate the optimal route to the delivery destination, taking into account the current weather information (e.g., sunny) and congestion status (e.g., slightly crowded), prioritizing quieter routes. Additionally, when the delivery staff member approaches the delivery destination, specific information and advertisements will be displayed in AR.

[1985] The system can use a generative AI model with prompts like this:

[1986] "If the user is stressed, if the weather is bad, calculate the optimal delivery route with a focus on safety."

[1987] "If a user wants to discover new stores, calculate a walking route that reflects that desire."

[1988] In this way, the embodiments of the invention provide specific means for providing an optimal experience by comprehensively considering the psychology and environmental information of the user and delivery staff.

[1989] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1990] Step 1:

[1991] The user uses the device to input their current location, destination, purpose of walk or delivery, and required time. This information is formatted in JSON format. The device also uses the camera and microphone to collect the user's emotional data, which is analyzed by the emotion engine. The results of this analysis are also added to the JSON format. Input data: current location, destination, purpose of walk or delivery, required time, emotional data. Output data: input information and emotional data in JSON format.

[1992] Step 2:

[1993] The device sends formatted JSON formatted data to the server. The server receives this data and begins parsing it. Input data: Input information and emotion data in JSON format. Output data: None.

[1994] Step 3:

[1995] The server uses an external API to get real-time weather information based on the user's current location. It sends a request to the weather API (e.g., OpenWeatherMap API) and receives weather information as a response. Input data: current location. Output data: weather information.

[1996] Step 4:

[1997] The server also uses an external API to obtain the local congestion status based on the user's current location. It sends a request to the congestion status API (e.g., Google Maps Traffic API) and receives congestion status data as a response. Input data: current location. Output data: congestion status data.

[1998] Step 5:

[1999] The server integrates the received user input information, emotion data, weather information, and congestion status to calculate the optimal walking or delivery route. A route calculation algorithm is used to select a route that takes into account the user's psychological state and congestion status. Input data: User input information, emotion data, weather information, congestion status data. Output data: Optimal route information.

[2000] Step 6:

[2001] The server formats the calculated optimal route information and points of interest in JSON format and sends it to the terminal. Input data: optimal route information, points of interest information. Output data: route information and points of interest in JSON format.

[2002] Step 7:

[2003] The device analyzes the route information and points of interest in JSON format received from the server and displays them to the user through a map app or AR display. When the user approaches a specific point, related information or advertisements are displayed. Input data: Route information and points of interest in JSON format. Output data: Visual display to the user.

[2004] Step 8:

[2005] The user begins traveling along the route and reaches a specific point of interest or delivery destination. The user's behavior data and collected ad response data are then sent to the server and used for statistical analysis. Input data: user behavior data, ad response data. Output data: statistical data.

[2006] Through the above steps, a system is realized that provides optimal routes and information that comprehensively consider the user's emotional state and external environmental information.

[2007] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2008] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2009] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2010] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2011] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2012] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2013] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2014] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2015] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2016] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2017] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2018] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2019] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2020] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2021] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2022] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2023] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2024] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2025] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2026] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2027] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2028] The following is further disclosed regarding the above embodiment.

[2029] (Claim 1)

[2030] means for receiving user input information;

[2031] a means for obtaining real-time weather information;

[2032] A means of understanding the congestion situation in the area,

[2033] means for calculating an optimal walking route based on the user's input information, weather information, and congestion status;

[2034] means for displaying the calculated walking route and points of interest to the user;

[2035] A system including:

[2036] (Claim 2)

[2037] 2. The system according to claim 1, further comprising means for giving priority to routes that the user does not usually take and new stores in the calculation of the optimal walking route.

[2038] (Claim 3)

[2039] 2. The system according to claim 1, wherein the points of interest are displayed by an augmented reality display means.

[2040] "Example 1"

[2041] (Claim 1)

[2042] means for receiving user input information;

[2043] a means for obtaining real-time weather information;

[2044] A means of understanding the congestion situation in the area,

[2045] means for calculating an optimal walking route based on the user's input information, weather information, and congestion status;

[2046] means for displaying the calculated walking route and points of interest to the user;

[2047] A means to display advertisements when approaching points of interest,

[2048] A means for collecting and accumulating user responses to advertisements as statistical data;

[2049] A system including:

[2050] (Claim 2)

[2051] 2. The system according to claim 1, further comprising means for giving priority to routes that the user does not usually take and new stores in the calculation of the optimal walking route.

[2052] (Claim 3)

[2053] 2. The system according to claim 1, wherein the points of interest are displayed by an augmented reality display means.

[2054] "Application Example 1"

[2055] (Claim 1)

[2056] means for receiving user input information;

[2057] a means for obtaining real-time weather information;

[2058] A means of understanding the congestion situation in the area,

[2059] means for calculating an optimal walking route based on the user's input information, weather information, and congestion status;

[2060] means for displaying the calculated walking route and points of interest to the user;

[2061] A means to calculate and display purchase paths and recommended stores,

[2062] A system including:

[2063] (Claim 2)

[2064] 2. The system according to claim 1, further comprising means for giving priority to routes that the user does not usually take and new commercial facilities in calculating the optimal walking route.

[2065] (Claim 3)

[2066] 2. The system according to claim 1, wherein the points of interest and recommended stores are displayed by an augmented reality display means.

[2067] "Example 2: Combining Emotion Engines"

[2068] (Claim 1)

[2069] means for receiving user input information;

[2070] a means for obtaining real-time weather information;

[2071] A means of understanding the congestion situation in the area,

[2072] means for recognizing a user's emotion;

[2073] means for calculating an optimal walking route based on the user's input information, weather information, congestion status, and emotion information;

[2074] means for displaying the calculated walking route and points of interest to the user;

[2075] A system including:

[2076] (Claim 2)

[2077] 2. The system according to claim 1, further comprising means for giving priority to routes that the user does not usually take and new stores in the calculation of the optimal walking route.

[2078] (Claim 3)

[2079] 2. The system according to claim 1, wherein the points of interest are displayed by an augmented reality display means.

[2080] "Application example 2 when combining emotion engines"

[2081] (Claim 1)

[2082] means for receiving user input information;

[2083] a means for obtaining real-time weather information;

[2084] A means of understanding the congestion situation in the area,

[2085] means for calculating an optimal walking route based on the user's input information, weather information, and congestion status;

[2086] means for recognizing a user's emotion;

[2087] A means for selecting routes and suggesting points of interest according to the user's psychological state;

[2088] means for displaying the calculated walking route and points of interest to the user;

[2089] A means to provide the optimal delivery route taking into consideration the psychological state of delivery staff,

[2090] A means to display information and advertisements when approaching a specific point,

[2091] A system including:

[2092] (Claim 2)

[2093] 2. The system according to claim 1, further comprising means for giving priority to routes that the user does not usually take and new stores in the calculation of the optimal walking route.

[2094] (Claim 3)

[2095] 2. The system according to claim 1, wherein the points of interest are displayed by an augmented reality display means. [Explanation of symbols]

[2096] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving user input information; a means for obtaining real-time weather information; A means of understanding the congestion situation in the area, means for calculating an optimal walking route based on the user's input information, weather information, and congestion status; a means for displaying the calculated walking route and points of interest to the user; A system including:

2. The system according to claim 1 , further comprising means for giving priority to routes that the user does not usually take and new stores in the calculation of the optimal walking route.

3. The system according to claim 1 , wherein the points of interest are displayed by an augmented reality display means.

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