System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting personal information of a user; means for analyzing the collected personal information and grasping preferences of the user; means for generating a plurality of routes including a stop-by spot based on information of a current location and a destination of the user; means for proposing an optimal route from the generated routes according to an option selected by the user; and means for displaying the provided route on a user interface.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] When choosing a modern mode of transportation, arrival time and cost are often the primary factors to consider. However, when it comes to leisure and sightseeing, the travel process itself is part of the experience, so simply being provided with the shortest distance or cheapest price is not enough. Until now, users have had to gather information and make plans themselves, which takes time and effort, and finding the optimal route is often difficult. Therefore, a system is needed that can automatically generate and suggest routes that include stopover spots tailored to the user's preferences. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means. First, a means for collecting personal information of a user is provided. Next, a means for analyzing the collected personal information and understanding the user's preferences is provided. Also, a means for generating multiple routes including stop-off spots based on information about the user's current location and destination is provided. Furthermore, a means for proposing an optimal route according to an option selected by the user from among the generated routes and a means for displaying the provided route on a user interface are provided. This allows the user to easily find a travel route that suits their preferences and spend their travel time meaningfully. Furthermore, by updating the route generation means using the user's personal information, which is continuously updated, more accurate suggestions are possible. Furthermore, by providing a means for the user to select an option that prioritizes exercise or fun, flexible route suggestions tailored to the needs of individual users are realized.

[0006] "User's personal information" refers to data about the user, including the user's hobbies and preferences, behavioral history, health care data, search history, favorite location information, etc.

[0007] "Means of collection" is a term that refers to the software or hardware features that record and store information entered by users.

[0008] "Means of analysis" refers to the process of analyzing collected personal information about users and using algorithms and statistical methods to identify their preferences and behavioral patterns.

[0009] "Taste" refers to a user's preferences and interests, and refers to a preference for a particular category or theme.

[0010] "Current Location" means the User's current physical location, as determined by GPS data or other positioning technology.

[0011] "Destination" refers to the final destination to which the user wishes to travel, and is the point that the user inputs into the application.

[0012] "Route generation means" refers to the process of calculating and proposing multiple travel routes to reach a destination from a current location.

[0013] A "stop-off spot" refers to a specific location or facility that the user can visit during their travels, and is a place selected based on the user's preferences.

[0014] "Means for proposing the optimal route" refers to the process of selecting the optimal route from the generated routes based on the user's selections and options and presenting it to the user.

[0015] "User interface display means" refers to the screen display technology and software functionality used to visually display the proposed route to the user.

[0016] "Continuously updated" means that a user's personal information and behavioral data is periodically replaced with new information over time.

[0017] "Exercise priority" refers to an option that users select when choosing a route to get more exercise.

[0018] "Fun-first" refers to an option that prioritizes fun and entertainment when a user selects a travel route. [Brief explanation of the drawings]

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

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

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

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

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

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0040] This invention is a system that generates and proposes optimal travel routes based on the user's preferences. This system is mainly composed of three elements: a server, a terminal, and a user.

[0041] Overall Overview

[0042] 1. Collection of User's Personal Information

[0043] Users enter personal information such as their favorite cafes, frequently visited spots, and events they are interested in through a smartphone app.

[0044] The device collects this information and sends it to the server in encrypted form.

[0045] The server stores the received information in a database.

[0046] 2. Analysis of user information

[0047] The server retrieves the user's personal information from the database, cleans the data, and then analyzes the user's preferences and behavioral patterns.

[0048] The server generates an AI model based on these analysis results and identifies each user's preferences.

[0049] 3. Route Generation

[0050] The user enters their current location and destination into the application.

[0051] The terminal sends the input data to the server.

[0052] The server generates multiple routes based on the user's current location, destination, and preferences, including stopovers that the user may be interested in.

[0053] The device displays the generated route to the user and allows the user to select the option of "exercise first" or "fun first."

[0054] 4. Optimal route suggestions

[0055] When the user selects an option, the terminal sends the information to the server.

[0056] The server will re-evaluate the routes based on the options and choose the best one.

[0057] The server sends the optimized route to the terminal, which displays it to the user.

[0058] Processing details and examples

[0059] Collection of Personal Information

[0060] Information users enter includes their favorite cafe (e.g., Blue Bottle Coffee), the gym they frequently visit, and upcoming music events.

[0061] The terminal receives these inputs, encrypts them, and sends them to the server.

[0062] The server decrypts the received information and stores it in a database.

[0063] User information analysis

[0064] The server retrieves user information from the database and performs data cleaning to remove outliers and missing values.

[0065] The server analyzes the user's preferences (e.g., cafe hopping, running, music) and reflects them in the AI ​​model.

[0066] The server continually updates the analysis results, keeping track of the user's latest preferences.

[0067] Route generation

[0068] The user inputs the destination "from home to the station."

[0069] The terminal sends the information to the server.

[0070] The server generates multiple routes including stopover spots (e.g., cafes, jogging courses) based on the user's current location, destination, and preference information.

[0071] The device displays the generated route on a user interface and allows the user to select options such as "exercise first" or "fun first."

[0072] Optimal route suggestions

[0073] When the user selects, for example, "Enjoyment Priority," the terminal transmits the selection to the server.

[0074] The server re-evaluates multiple routes based on the selection and selects the best route.

[0075] The server sends the optimized route to the terminal, which displays it to the user.

[0076] Ad business applications

[0077] The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[0078] The terminal displays the route with advertisements on a user interface.

[0079] The user may be interested in the displayed advertisement and may select a stop-off spot based on this interest.

[0080] As described above, the system of the present invention utilizes user preference information to optimize travel routes, thereby enabling users to spend their travel time meaningfully.

[0081] The processing flow will be explained below.

[0082] Step 1:

[0083] Users open the smartphone app and enter personal information such as their favorite cafes, frequently visited places, and events they are interested in through a registration profile.

[0084] Step 2:

[0085] The terminal collects personal information entered by the user and encrypts the data.

[0086] Step 3:

[0087] The terminal transmits the encrypted personal information to the server.

[0088] Step 4:

[0089] The server receives the encrypted data, decrypts it, and stores it in a database.

[0090] Step 5:

[0091] The server retrieves the user's personal information from the database and cleans the data, specifically by detecting and processing outliers and missing values.

[0092] Step 6:

[0093] The server uses the cleaned data to run algorithms that analyze user preferences and behavioral patterns.

[0094] Step 7:

[0095] Based on the analysis results, the server generates and trains a different AI model for each user.

[0096] Step 8:

[0097] The user inputs their current location and destination into the application (e.g., from home to the train station).

[0098] Step 9:

[0099] The terminal transmits the current location and destination information input by the user to the server.

[0100] Step 10:

[0101] The server generates multiple routes based on the user's current location, destination, and analyzed user preferences, including stopovers that may be of interest to the user.

[0102] Step 11:

[0103] The server transmits the generated routes to the terminal.

[0104] Step 12:

[0105] The device displays the generated route on a user interface, and the user can select options such as "exercise first" or "fun first."

[0106] Step 13:

[0107] The user selects an option (e.g., "Fun First").

[0108] Step 14:

[0109] The terminal sends the user's selected option to the server.

[0110] Step 15:

[0111] Based on the selected option, the server re-evaluates multiple routes and selects the best one.

[0112] Step 16:

[0113] The server sends the optimal route information to the terminal.

[0114] Step 17:

[0115] The terminal displays the optimal route on the user interface.

[0116] Step 18:

[0117] The user checks the displayed route and selects the route that best suits their preferences.

[0118] Step 19:

[0119] The device activates the navigation function and guides the user along the optimal route.

[0120] Step 20:

[0121] (Advertising business as an example)

[0122] The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[0123] Step 21:

[0124] The terminal displays the route with advertisements on a user interface.

[0125] Step 22:

[0126] The user is interested in the displayed advertisement and selects a stopover spot.

[0127] Example 1

[0128] 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."

[0129] Conventional travel route generation systems are limited to basic route search without fully considering the user's personal information and preferences. This makes it difficult to provide an optimal route that matches the user's interests and preferences. In addition, when a user's interests change, the system is unable to quickly reflect those changes, making it difficult to propose a route based on the latest information. Furthermore, from a commercial perspective, advertisements based on the user's preferences are not effectively displayed. To solve these problems, a system is needed that can understand and dynamically update the user's preferences to generate a more optimal travel route while also effectively providing related advertising information.

[0130] 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.

[0131] In this invention, the server includes a means for encrypting the user's personal information and transmitting it to the server, a means for storing the personal information received by the server in a database, and a means for retrieving the user's personal information from the database and performing data cleaning. This makes it possible to analyze the user's preferences and propose an optimal route based on dynamically updated information. Furthermore, the system has a function for selecting an option to prioritize exercise or fun in the user interface and a function for displaying related advertising information, providing a travel route that reflects the user's latest interests.

[0132] "User" refers to a person who uses the system to optimize their travel route.

[0133] "Personal information" refers to personal information such as a user's hobbies and interests, favorite spots, and frequently visited places.

[0134] "Terminal" refers to an electronic device such as a smartphone or tablet operated by a user.

[0135] "Server" means the central processing unit that receives, stores, and analyzes User's personal information.

[0136] "Database" means an electronic storage device for storing collected personal information about users.

[0137] "Data cleaning" refers to the process of removing irrelevant data and missing values ​​from a dataset and preparing it for analysis.

[0138] An "AI model" refers to a mathematical model that uses machine learning algorithms to analyze and predict user preferences.

[0139] "Route" refers to information showing the route from the user's current location to the destination.

[0140] The "route generation means" refers to a mechanism for calculating multiple routes based on the user's current location, destination, and user preference information.

[0141] "Route suggestion means" refers to a mechanism that selects and suggests the optimal route from multiple generated routes according to the user's selection.

[0142] "User interface" refers to the display screen and input means that users use to operate the system through a terminal.

[0143] "Option selection means" refers to a mechanism that allows users to select options such as "exercise priority" or "fun priority."

[0144] "Advertising information" refers to commercial information displayed based on the user's preferences.

[0145] "Encryption" refers to the process of converting data, such as personal information, for security purposes, making it unavailable to third parties.

[0146] A "generative AI model" refers to an algorithm that uses artificial intelligence technology to analyze user behavior and preferences and generate new data patterns.

[0147] A "prompt" is a command or question entered into a system to request a specific action or piece of information.

[0148] This invention is a system that generates and proposes optimal travel routes based on the user's preferences. This system is mainly composed of three elements: a server, a terminal, and a user. Each element and its role are explained in detail below.

[0149] server

[0150] The server plays an important role in receiving, storing, and analyzing the user's personal information and generating the optimal travel route.

[0151] Data Receipt and Decryption: Personal information sent by users arrives at the server in encrypted form. The server decrypts the information and stores it securely in a database. Specifically, encryption algorithms such as AES-256 can be used.

[0152] Database management: The server stores the received personal information in a database (e.g., MySQL or PostgreSQL). The database assigns a unique ID to each user and manages each user's information.

[0153] Data cleaning: Data cleaning is performed to remove inappropriate data and missing values ​​from the information obtained from the database.

[0154] Creation and analysis of AI models: To analyze user preferences, the server creates an AI model using machine learning libraries (e.g., TensorFlow or PyTorch). This model is used to identify and analyze individual user behavior patterns and preferences.

[0155] Route generation: The server generates multiple routes using a route search algorithm (e.g., Dijkstra or A algorithm) based on the user's current location, destination, and preference information.

[0156] Route proposal: From the generated routes, the optimal route is selected and proposed based on the user's selection (e.g., "exercise first" or "fun first").

[0157] Generating advertising information: The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[0158] Terminal

[0159] The terminal is an electronic device such as a smartphone or tablet that is operated by a user.

[0160] Information collection and transmission: Personal information entered by the user is collected, encrypted, and transmitted to the server. An encryption library (e.g., OpenSSL) can be embedded in the terminal.

[0161] User interface: The device displays the generated route on the user interface and presents the user with options such as "exercise priority" or "fun priority."

[0162] Sending selection information: The options selected by the user are encrypted and sent to the server.

[0163] Display Advertisements: Displays advertising information sent from the server and allows users to access more information.

[0164] User

[0165] A user is a person who uses the system to optimize a travel route.

[0166] Information input: Users input their preferences and interests (such as their favorite cafe, frequently visited gym, upcoming music events, etc.) through a smartphone app.

[0167] Setting current location and destination: The user sets their current location and destination within the app and sends them to the server via their device.

[0168] Select an option: Select the option you want from the options displayed on your device (e.g., "Prioritize exercise" or "Prioritize fun").

[0169] Examples of concrete examples and prompts

[0170] Specific examples

[0171] A user enters into the app, "I like Blue Bottle Coffee," "I go to the gym every weekend," and "I'll attend the next music festival."

[0172] The device encrypts the information and sends it to the server.

[0173] The server decrypts the received personal information and stores it in a database.

[0174] The server retrieves information from the database and analyzes that "cafe hopping" is a hobby.

[0175] When the user enters "from home to the station," the device sends the information to the server.

[0176] The server generates a route based on the user's preferences and suggests a route that includes "Blue Bottle Coffee."

[0177] The terminal displays the route and the user selects "Enjoyment priority."

[0178] The server selects the optimal route and the device displays it.

[0179] The server generates advertisements related to "cafe hopping" and the device displays them.

[0180] Prompt Sentence Examples

[0181] "Please tell me the route from your house to the station, including recommended cafes and jogging courses. Please also include options for routes that prioritize exercise."

[0182] As described above, this system utilizes user preference information to optimize travel routes, allowing users to spend their travel time meaningfully.

[0183] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0184] Step 1:

[0185] The user launches the smartphone app and enters their personal information (e.g., favorite cafe, frequently visited spots).

[0186] Input: Personal information such as the user's hobbies and interests

[0187] Action: The user performs an action to enter information into a form within the app.

[0188] Output: The personal information entered is saved on the device.

[0189] Step 2:

[0190] The terminal encrypts the user's personal information and sends it to the server.

[0191] Input: User's personal information

[0192] Processing: The device encrypts the data using an encryption algorithm such as AES-256 and sends it to the server in a secure HTTP request.

[0193] Output: Encrypted personal information is sent to the server.

[0194] Step 3:

[0195] The server receives the encrypted personal information, decrypts it, and stores it in a database.

[0196] Input: Encrypted personal information

[0197] Processing: The server decrypts the received data and stores it in a database, where each user is assigned a unique ID.

[0198] Output: Personal information decrypted and stored in a database

[0199] Step 4:

[0200] The server retrieves user information from the database and performs data cleaning.

[0201] Input: Personal information stored in the database

[0202] Processing: The server executes database queries to retrieve information and then performs a data cleaning process to remove irrelevant data and missing values.

[0203] Output: Cleaned user information

[0204] Step 5:

[0205] The server analyzes the user's preferences and generates an AI model.

[0206] Input: Cleaned user information

[0207] Processing: The server uses machine learning libraries such as TensorFlow and PyTorch to generate an AI model to analyze user preferences and perform the analysis.

[0208] Output: User preference information

[0209] Step 6:

[0210] The user enters their current location and destination through the app.

[0211] Input: Current location and destination information

[0212] Action: The user performs an action to enter information into an input field in the app.

[0213] Output: Current location and destination information is saved on the device.

[0214] Step 7:

[0215] The device encrypts the current location and destination information entered and sends it to the server.

[0216] Input: Current location and destination information

[0217] Processing: The device encrypts the information and sends it to the server in a secure HTTP request.

[0218] Output: Encrypted current location and destination information is sent to the server.

[0219] Step 8:

[0220] The server generates a route based on the user's current location, destination, and preference information.

[0221] Input: Encrypted current location and destination information, user preferences

[0222] Processing: The server interprets the information and generates multiple possible routes using a geographic information system (GIS) and route planning algorithms.

[0223] Output: Multiple route candidates

[0224] Step 9:

[0225] The device displays the generated route on a user interface and allows the user to select options such as "exercise first" or "fun first."

[0226] Input: Multiple route candidates

[0227] Processing: The terminal displays the route information received from the server on the user interface and presents options to the user.

[0228] Output: Route information and option choices displayed to the user

[0229] Step 10:

[0230] The user selects an option.

[0231] Input: The option selected by the user (e.g., "Enjoyment first")

[0232] Processing: The user selects an option through the terminal interface.

[0233] Output: Selected option information

[0234] Step 11:

[0235] The terminal encrypts the selected option information and transmits it to the server.

[0236] Input: The option selected by the user

[0237] Processing: The terminal encrypts the selected information and sends it to the server.

[0238] Output: The encrypted selection information is sent to the server.

[0239] Step 12:

[0240] The server reevaluates based on the selection information and selects the optimal route.

[0241] Input: Encrypted selection information, route candidates

[0242] Processing: The server decodes the selection information and uses AI models to re-evaluate route options and select the optimal route.

[0243] Output: Information on the best route

[0244] Step 13:

[0245] The server transmits optimal route information to the terminal, which then displays it to the user.

[0246] Input: Optimal route information

[0247] Processing: The server sends the optimal route information to the terminal, which displays it on the user interface.

[0248] Output: The optimal route is displayed on the user's device.

[0249] Step 14:

[0250] The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[0251] Input: User preferences

[0252] Processing: The server generates relevant advertising information based on the preference information and incorporates it into the selected route.

[0253] Output: Route information incorporating advertising information

[0254] Step 15:

[0255] The terminal displays the optimal route with advertisements on the user interface.

[0256] Input: Optimal route incorporating advertising information

[0257] Processing: The terminal displays the displayed information on the user interface.

[0258] Output: The optimal route information with advertisements is displayed to the user.

[0259] (Application example 1)

[0260] 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."

[0261] Conventional travel route generation systems simply provide the shortest or fastest route without fully utilizing the user's personal information and preferences. This makes it difficult to provide an optimal route that includes attractions and other interesting stops that the user wants to enjoy during their trip. Furthermore, even in autonomous vehicles, personalized navigation based on the user's preferences has not been provided.

[0262] 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.

[0263] In this invention, the server includes means for collecting personal information of a user, means for analyzing the collected personal information and understanding the user's preferences, means for generating multiple routes including stop-off spots based on information on the user's current location and destination, means for proposing an optimal route from the generated routes in accordance with an option selected by the user, means for displaying the provided route on a user interface, means for providing the above route in a navigation system for an autonomous vehicle, and means for generating an AI model for route proposals based on the user's preferences. This allows the user to not only reach their destination but also enjoy a personalized travel experience, and enables flexible navigation based on the user's preferences even in autonomous vehicles.

[0264] "User's personal information" is information that represents individual characteristics of the user, such as the user's tastes, interests, and past behavioral history.

[0265] A "user interface" is the part of a system that includes display and input devices through which a user interacts with the system.

[0266] An "autonomous vehicle" is a vehicle that uses systems or algorithms to drive itself automatically without a human driver.

[0267] A "navigation system" is a device or system that provides a user with the optimal route to reach their destination.

[0268] An "AI model" is a mathematical model that uses artificial intelligence technology to analyze data and apply the results.

[0269] "Route proposal" is the act of generating multiple routes from the user's current location to the destination, selecting the most suitable one, and presenting it.

[0270] A "stop-off spot" is a place or facility that a user can visit on the way while traveling.

[0271] "Selectable options" are route conditions and characteristics that a user can choose depending on their preferences and purpose.

[0272] "Collection means" refers to the functions and methods for acquiring user information.

[0273] "Analysis tools" are functions and methods for processing collected data and extracting meaningful information.

[0274] "Generation means" refers to functions or methods for creating new data or results based on user information or conditions.

[0275] "Display means" refers to a device or method for visually conveying generated information or results to a user.

[0276] The present invention relates to a system for generating and proposing optimal travel routes based on user preferences, which is targeted at autonomous vehicles and provides a personalized travel experience.

[0277] System configuration

[0278] This system mainly consists of three elements: a server, a terminal (smartphone or in-vehicle device), and a user.

[0279] 1. Collection of User's Personal Information:

[0280] Users enter personal information such as their favorite cafes, frequently visited spots, and events they are interested in through a smartphone app. The device collects this information and sends it in a securely encrypted format to a server, which then stores the information in a database.

[0281] 2. Analysis of User Information:

[0282] The server retrieves the user's personal information from the database, cleans the data, and then analyzes the user's preferences and behavioral patterns. Based on this, an AI model is generated to identify each user's preferences.

[0283] 3. Pathway Generation:

[0284] The user inputs their current location and destination into the application. The device then sends this input data to the server. The server generates multiple routes based on the current location, destination, and the user's preferences, including stopovers that the user may be interested in. The device displays the generated routes on a user interface, allowing the user to select options such as "exercise priority" or "fun priority."

[0285] 4. Optimal route suggestions:

[0286] Once the user selects an option, the device sends that information to the server, which reevaluates routes based on the options and selects the best one. The server then sends the optimized route to the device, which displays it to the user.

[0287] Hardware and software used

[0288] Hardware:

[0289] In-Vehicle Information System (IVI)

[0290] Smartphone

[0291] Autonomous vehicle sensors (GPS, LiDAR, cameras, etc.)

[0292] software:

[0293] Server applications (AWS, GCP)

[0294] Database (MySQL, Postgres)

[0295] Cryptography library (PyCryptodome)

[0296] HTTP client (requests)

[0297] Specific examples

[0298] For example, if the user selects "Strolling first," the server can suggest multiple routes that include the following spots:

[0299] Recently opened cafes and restaurants

[0300] Highly rated parks

[0301] Historical Attractions

[0302] Example prompts to input to a generative AI model:

[0303] text

[0304] Design a system that suggests optimal routes for autonomous vehicles based on the user's preferences. Based on the following information, generate routes that allow the user to select the "Stroll first" option and display them in the navigation system. The user's personal information includes their favorite cafes and events of interest.

[0305] 1. User preferences (cafes, tourist spots, parks)

[0306] 2. Current location (starting point) and destination

[0307] 3. Route options (exercise first, fun first)

[0308] As described above, this system utilizes user preference information to personalize the travel experience even in autonomous vehicles.

[0309] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0310] Step 1:

[0311] Users use a smartphone app to input personal information such as their favorite cafes, frequently visited spots, and events they are interested in. The device collects this information, encrypts it, and sends it to a server. The input data includes the user's interests and behavioral history, and encrypted data is generated as output.

[0312] Step 2:

[0313] The server receives the encrypted data sent from the terminal, decrypts it, and stores it in the database. The server checks the integrity of the initial data and stores it in the database. The input data is encrypted user information, and the output is user personal information stored in the database.

[0314] Step 3:

[0315] The server retrieves the user's personal information from the database and performs data cleaning. After eliminating outliers and missing data, it performs analysis to identify the user's preferences and behavioral patterns. An AI model is generated based on the analysis results, and a new user profile is created. The input data is the user's personal information, and the output is the generated AI model and user profile.

[0316] Step 4:

[0317] The user inputs their current location and destination into a smartphone app or on the in-car display. The device then sends this information to the server. The input data is the current location and destination information, and the output is the route request data sent to the server.

[0318] Step 5:

[0319] The server generates multiple routes based on the user's current location, destination, and preference information. The server uses an AI model to calculate a route that includes stops that the user may be interested in. After the route is generated, the result is sent to the device. The input data is the route request data and the user's preference information, and the output is the multiple routes generated.

[0320] Step 6:

[0321] The device displays multiple generated routes on a user interface, and the user selects options such as "exercise priority" or "fun priority." The input data is the generated route, and the output is the route options presented to the user.

[0322] Step 7:

[0323] When a user selects an option, the terminal sends the option information to the server. The server reevaluates routes based on the selected option and selects the optimal route. The input data is the option information selected by the user, and the output is the reevaluated optimal route.

[0324] Step 8:

[0325] The server sends the optimal route to the terminal, which then displays it to the user. The optimized route is reflected in the navigation system of the autonomous vehicle. The input data is the re-evaluated optimal route, and the output is the optimized route presented to the user.

[0326] Through the above processing steps, the system can utilize user preference information to provide a personalized travel experience in an autonomous vehicle.

[0327] 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.

[0328] The present invention is a system that generates and proposes optimal travel routes based on the user's preferences and emotions. It is mainly composed of a server, a terminal, a user, and an emotion engine.

[0329] Overall Overview

[0330] 1. Collection of User's Personal Information

[0331] Users enter personal information such as their hobbies, favorite cafes, frequently visited places, and events they are interested in through a smartphone app.

[0332] The device collects this information, encrypts it, and sends it to the server.

[0333] The server stores the received information in a database.

[0334] 2. Analysis of user information

[0335] The server retrieves the user's personal information from the database and performs data cleaning, handling outliers and missing values, and preparing the data in a format suitable for analysis.

[0336] The server analyzes the user's preferences and behavioral patterns based on the cleaned data.

[0337] The server uses the analysis results to generate and train a different AI model for each user.

[0338] 3. Emotional Engine Activation

[0339] It activates an emotion engine that recognizes emotions in real time using the user's facial expressions, voice data, touch input, etc.

[0340] The device collects emotion data and sends it to the server.

[0341] The server analyzes this emotional data to determine the current emotional state (e.g., happy, stressed).

[0342] 4. Route Generation

[0343] The user enters their current location and destination into the application.

[0344] The terminal transmits this information to the server.

[0345] The server generates multiple routes based on the user's current location, destination, and data on the user's preferences and emotional state. The generated routes include stopover spots that are likely to interest the user.

[0346] 5. Option selection and optimal route suggestions

[0347] The device displays the generated route on a user interface and allows the user to select options such as "exercise first" or "fun first."

[0348] When the user selects an option, the selection is sent to the server.

[0349] The server re-evaluates multiple routes depending on the selected options and the current emotional state and selects the optimal route.

[0350] The server transmits the optimized route information to the terminal.

[0351] The terminal displays the optimal route on the user interface, allowing the user to review and select.

[0352] Processing details and examples

[0353] Collection and analysis of personal information

[0354] Users enter their favorite cafes and spots (e.g., movie theaters, running courses, restaurants) through the app.

[0355] The device encrypts this, and the server receives the data and stores it in a database.

[0356] The server cleans the data and analyzes user behavior patterns, and the analysis results are reflected in the AI ​​model.

[0357] Example of the Emotion Engine in action

[0358] The user uses their smartphone camera to recognize their facial expressions (e.g., smiling, tired).

[0359] The device collects emotional data and sends it to a server.

[0360] The server analyzes the data using an emotion engine to identify the user's current emotional state. For example, if the user is feeling stressed, the server suggests a route that passes through a relaxing cafe or park.

[0361] Route generation

[0362] The user enters the destination as "from home to the station."

[0363] The device sends information to a server, which then generates multiple routes based on the information. The routes include stops based on the user's preferences (e.g., cafe hopping) and emotional state (e.g., needing to relax).

[0364] Option selection and optimal route suggestions

[0365] The device displays the route and allows the user to select "exercise priority" or "fun priority" (e.g., select "fun priority").

[0366] The device sends the selection information to the server, which then reevaluates the route based on the options and emotional state.

[0367] The server sends the optimal route to the terminal, which then displays it to the user.

[0368] The user checks the optimal route and prepares to depart.

[0369] Ad business applications

[0370] The server generates relevant advertisements (e.g., spas that are effective for relieving stress) based on the user's preferences and emotional state and incorporates them into the route.

[0371] The terminal displays a route with advertisements, and the user selects stop-off spots based on the advertisements.

[0372] In this way, the system of the present invention can utilize the user's preference information and emotional state to suggest more appropriate and meaningful travel routes.

[0373] The processing flow will be explained below.

[0374] Step 1:

[0375] Users open the smartphone app and enter personal information such as hobbies, favorite cafes, frequently visited places, and events they are interested in on the profile screen.

[0376] Step 2:

[0377] The terminal collects personal information entered by the user and encrypts the data.

[0378] Step 3:

[0379] The terminal transmits the encrypted personal information to the server.

[0380] Step 4:

[0381] The server receives the encrypted data, decrypts it, and stores it in a database.

[0382] Step 5:

[0383] The server retrieves the user's personal information from the database and performs data cleaning, specifically detecting and formatting outliers and missing data.

[0384] Step 6:

[0385] The server analyzes the cleaned data to identify the user's preferences and behavioral patterns.

[0386] Step 7:

[0387] The server generates an AI model based on the analysis results and trains a model personalized for each user.

[0388] Step 8:

[0389] The user uses the app to show their face to the camera, and the emotion engine recognizes their facial expressions.

[0390] Step 9:

[0391] The device transmits emotion data to the emotion engine in real time.

[0392] Step 10:

[0393] The server analyzes the data sent from the emotion engine and recognizes the current emotional state. For example, it recognizes that the user is "feeling stressed."

[0394] Step 11:

[0395] The user inputs their current location and destination into the application (e.g., from home to the train station).

[0396] Step 12:

[0397] The terminal transmits the entered current location and destination information to the server.

[0398] Step 13:

[0399] The server generates multiple routes including stopover spots based on the current location, destination, user preference information, and emotion data.

[0400] Step 14:

[0401] The server transmits the generated routes to the terminal.

[0402] Step 15:

[0403] The device displays the generated route in a user interface, where the user can select options such as "exercise first" or "fun first."

[0404] Step 16:

[0405] When the user selects an option, the terminal transmits the selection to the server.

[0406] Step 17:

[0407] The server re-evaluates multiple routes based on the selected options and the current emotional state and selects the optimal route.

[0408] Step 18:

[0409] The server transmits the optimized route information to the terminal.

[0410] Step 19:

[0411] The terminal displays the optimal route on the user interface, and the user confirms it and prepares to depart.

[0412] Step 20:

[0413] The device activates the navigation function and guides the user along the optimal route.

[0414] Step 21:

[0415] (Application of advertising business)

[0416] The server generates relevant advertising information based on the user's preference information and emotional state and incorporates it into the route.

[0417] Step 22:

[0418] The terminal displays the route with advertisements on a user interface.

[0419] Step 23:

[0420] The user selects stops of interest based on the advertisements displayed.

[0421] Through the above processing steps, the system can utilize the user's personal information and emotional state to provide the optimal route to make the travel process more meaningful and enjoyable.

[0422] Example 2

[0423] 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."

[0424] Conventional travel route generation systems do not take into account the user's personal information or emotional state, making it difficult to propose optimal travel routes that suit the user's preferences and current mood. Furthermore, they lack real-time emotion recognition and adaptation, making it difficult to improve user satisfaction. The present invention aims to solve these problems by providing a system that generates and proposes optimal travel routes based on the user's personal information and emotional state.

[0425] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting personal information of a user, means for encrypting the collected personal information and transmitting it via a network, means for storing the encrypted information in a database, means for acquiring the personal information from the database and performing data cleaning, means for analyzing the user's preferences and behavioral patterns based on the cleaned data, means for generating and training different artificial intelligence models based on the analysis results, means for recognizing emotions using the user's facial expressions, voice, and touch input, means for analyzing the recognized emotion data and identifying the user's current emotional state, means for generating multiple routes including stop-off spots based on information about the user's current location and destination, means for proposing an optimal route from the generated routes in accordance with an option selected by the user, and means for displaying the provided route on a user interface. This makes it possible to generate and suggest travel routes suited to the user's preferences and emotional state.

[0426] "User's personal information" means information relating to the User personally, such as the User's hobbies, interests, favorite places, frequently visited places and events of interest.

[0427] "Encryption" refers to a security technology that converts data so that it cannot be viewed illegally by third parties.

[0428] "Transmitting over a network" means the act of sending data over a communications network, including the Internet.

[0429] "Storing in a database" means storing data in a data storage system that systematically accumulates and manages information.

[0430] "Data cleaning" refers to the process of detecting outliers and missing values ​​in data and then performing processes such as deletion, completion, and correction to improve the quality of the data.

[0431] "Analysis of preferences and behavioral patterns" refers to the process of analyzing a user's preferences and behavioral patterns based on the user's personal information.

[0432] "Generating and training an artificial intelligence model" refers to the process of building an AI model based on data and then applying a learning algorithm to that model to improve its performance.

[0433] "Emotion recognition" refers to technology that determines a user's emotional state based on information such as the user's facial expressions, voice, and touch input.

[0434] "Analyzing emotional data and identifying emotional state" refers to the process of analyzing the data obtained from emotion recognition and identifying the emotion the user is currently feeling.

[0435] "Generating a route based on information about the current location and destination" refers to the operation of calculating the optimal travel route based on information about the departure point and arrival point set by the user.

[0436] "Spots to stop off at" refer to points along the way or potential destinations that are likely to interest the user.

[0437] "Proposing the best route based on options" refers to the process of recommending the most suitable route from among multiple route candidates based on setting options that the user can select.

[0438] "Displaying on the user interface" means the operation of displaying the generated route information on the display screen of the application.

[0439] The present invention is a system that generates and proposes optimal travel routes based on the user's preferences and emotions. This system is mainly composed of a server, a terminal, a user, and an emotion engine.

[0440] First, a user enters their hobbies and places of interest (e.g., cafes, movie theaters, running courses) through a smartphone application. This information is collected by the device and encrypted using an encryption algorithm (e.g., AES-256). The device then sends the encrypted data to a server. The server receives this data and stores it in a database (e.g., MySQL).

[0441] Next, the server retrieves personal information from the database and performs data cleaning. Data cleaning includes outlier detection and completion, and missing data handling. Specifically, an outlier detection algorithm is used to complete missing data with the mean or median. Based on this cleaned data, the server analyzes the user's preferences and behavioral patterns using machine learning algorithms (e.g., k-means clustering and collaborative filtering). The analysis results are used to generate different artificial intelligence models (e.g., using TensorFlow), which the AI ​​uses to learn.

[0442] For the emotion engine, the user inputs facial expressions and voice using the smartphone's camera and microphone. The device collects this emotion data and sends it to the server. The server then uses the emotion engine (using OpenCV or Pytorch, for example) to analyze the data and identify the user's current emotional state. For example, if the user is feeling stressed, the system will prioritize suggestions for relaxing cafes or parks.

[0443] To generate a route, the user inputs information about the starting point and destination through the application. For example, the input might be "from home to the station." The device then sends this information to the server, which then uses a map database (e.g., Google Maps API) to generate multiple routes. These routes include interesting stops (e.g., cafes, movie theaters, running courses) based on the user's preferences and emotional state.

[0444] The generated route is displayed on the user interface by the device. The user selects an option such as "exercise priority" or "fun priority." The option information selected by the user is sent back from the device to the server, and the server reevaluates the route based on the selected option and the user's current emotional state, selecting the optimal route. The server then sends the optimized route information to the device, which displays it on the user interface.

[0445] Examples of specific prompts include:

[0446] "Please enter places of interest or hobbies of the user (e.g., cafes, movie theaters, running trails)."

[0447] "Please enter your current location and destination (e.g. from home to the station)."

[0448] "Choose the exercise-first or fun-first option."

[0449] These procedures make it possible to generate and suggest travel routes that suit the user's preferences and emotional state.

[0450] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0451] Step 1: Collecting User Personal Information

[0452] A user starts a smartphone application and enters their hobbies and places of interest, such as their favorite cafe, movie theater, or running course, into an input box.

[0453] Input: User's hobbies and places of interest

[0454] Output: Raw personal information data

[0455] The device collects personal information entered, which is then encrypted using an encryption algorithm (e.g., AES-256).

[0456] Input: Raw personal information data

[0457] Output: Encrypted personal information data

[0458] The terminal transmits the encrypted personal information data to the server.

[0459] Input: Encrypted personal information data

[0460] Output: Encrypted data sent to the server

[0461] Step 2: Saving and cleaning user information

[0462] The server receives the encrypted data and stores it in a database (e.g. MySQL).

[0463] Input: Encrypted personal information data

[0464] Output: Information stored in the database

[0465] The server retrieves personal information from the database and performs data cleaning, detecting outliers and filling in missing data.

[0466] Input: Personal information retrieved from a database

[0467] Output: Cleaned personal information data

[0468] Step 3: Analyze preferences and behavioral patterns

[0469] The server analyzes user preferences and behavioral patterns based on the cleaned data, using machine learning algorithms (e.g., k-means clustering, collaborative filtering).

[0470] Input: Cleaned personal information data

[0471] Output: Analysis results of user preferences and behavior patterns

[0472] The server generates and trains a different artificial intelligence model (e.g., using TensorFlow) based on the analysis results.

[0473] Input: Analysis results of user preferences and behavior patterns

[0474] Output: A trained AI model

[0475] Step 4: Activate the Emotion Engine

[0476] The user uses the smartphone's camera and microphone to input facial expressions and voice data into the emotion engine.

[0477] Input: User's facial expression data and voice data

[0478] Output: Collected emotion data

[0479] The device collects emotional data and transmits it to a server in real time.

[0480] Input: Collected emotion data

[0481] Output: Emotion data sent to the server

[0482] The server analyzes the received emotion data and identifies the user's current emotional state (e.g., using OpenCV or Pytorch).

[0483] Input: Emotion data sent to the server

[0484] Output: The user's current emotional state

[0485] Step 5: Generate a path

[0486] The user inputs the departure and arrival points through a smartphone application (e.g., "from home to the station").

[0487] Input: Current location and destination information

[0488] Output: Location information entered into the device

[0489] The device transmits the input location information to the server.

[0490] Input: Location information entered on the device

[0491] Output: Location information sent to the server

[0492] The server generates multiple routes based on all data (personal information, emotional state) including the above information, using a map database (e.g., Google Maps API).

[0493] Input: current location, destination, personal information, emotional state

[0494] Output: Multiple generated routes

[0495] Step 6: Optimal Route Suggestion

[0496] The terminal displays the generated route on a user interface, and the user selects an option such as "exercise priority" or "fun priority."

[0497] Input: Multiple generated routes

[0498] Output: The route displayed in the user interface

[0499] The user selects the desired option and transmits the selection information from the terminal to the server.

[0500] Input: User's selection information (exercise priority, fun priority)

[0501] Output: Selections sent to the server

[0502] The server re-evaluates multiple routes and selects the best route based on the selected options and current emotional state.

[0503] Input: Selection information, emotional state

[0504] Output: Re-evaluated optimal path

[0505] The server sends the optimized route information to the terminal, which displays it on a user interface.

[0506] Input: Re-evaluated optimal path

[0507] Output: The optimal route displayed in the user interface

[0508] (Application example 2)

[0509] 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."

[0510] Conventional navigation systems mainly propose the shortest route to a destination based on the user's basic behavioral patterns. However, they do not offer optimal route suggestions that take into account the user's emotional state and preferences, making it difficult for users to have a travel experience that matches their mood and interests at the time. Therefore, there is a demand for a system that provides a comfortable and enjoyable travel experience based on the user's emotional state and preferences while traveling.

[0511] The identification processing 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 collecting personal information of the user, means for analyzing the collected personal information and understanding the user's preferences, means for generating multiple routes including stop-off spots based on information about the user's current location and destination, means for proposing an optimal route from the generated routes in accordance with an option selected by the user, means for displaying the provided route on a user interface, means for detecting the user's facial expressions and voice in real time using a camera and microphone mounted in the vehicle and collecting emotional data, means for identifying the user's current emotional state based on the collected emotional data, and means for optimizing the generated route based on the user's emotional state and preferences. This allows the server to provide an optimal travel route based on the user's emotional state and preferences, enabling a comfortable and enjoyable travel experience.

[0512] "User's personal information" is personal information about the user, such as the user's hobbies, favorite places, places that the user frequently visits, and events that interest the user.

[0513] "Tastes" refer to the preferences and tastes that are expressed by the things that a user likes or has interests.

[0514] A "stop-off spot" is a place or facility where a user can stop off during their travels.

[0515] "Current location" refers to the physical location where the user is currently located.

[0516] A "destination" is a location that a user is trying to reach.

[0517] "Options" are multiple choices or settings that a user can choose from.

[0518] The "route" refers to the route from the current location to the destination.

[0519] A "user interface" refers to a screen or device that allows a user to operate a system.

[0520] A "camera" is a device for taking images or videos.

[0521] A "microphone" is a device for recording sound.

[0522] "Emotion data" is information that indicates the user's emotional state, and is data collected from facial expressions and voice.

[0523] "Emotional state" refers to the mood or emotion that a user is currently experiencing.

[0524] "Optimization" means taking multiple conditions into consideration to derive the most suitable result.

[0525] The system that realizes this application example is an "emotional navigation system" installed in an autonomous vehicle. This system generates and suggests optimal routes based on the user's preferences and emotional state. The following describes an embodiment of this system.

[0526] The server collects and analyzes personal information about the user, who uses the in-vehicle interface to input information such as hobbies, favorite places, and events of interest. This information is stored in the vehicle system, encrypted, and synchronized to a cloud server.

[0527] The cloud server cleans the collected user information, analyzes the user's behavioral patterns and preferences, and generates and trains an AI model for each user based on that information.The data analysis tools used are Python's Pandas and Numpy, and the AI ​​models are TensorFlow and PyTorch.

[0528] Next, cameras and microphones mounted on the vehicle capture the user's facial expressions and voice in real time to collect emotional data, which is then analyzed using an emotion recognition engine (e.g., Affectiva SDK) to identify the user's current emotional state (e.g., enjoying, stressed).

[0529] When a user inputs their current location and destination into the vehicle's interface or smartphone app, the information is sent to a cloud server, which then generates an optimal route based on the user's information and emotional state, taking into account stopovers based on the user's preferences.

[0530] For example, if a user specifies a route from home to the station and wishes to relax, the cloud server will suggest a route that passes through cafes and parks where the user can relax. An example of a prompt sentence for a generative AI model is as follows:

[0531] "Please suggest routes that pass through recommended cafes and parks when the user wants to relax. The user's hobby is visiting cafes."

[0532] Finally, the generated routes are displayed on the user interface, and the user can select options such as "exercise first" or "relaxation first." The cloud server reevaluates the optimal route based on the selected option and the latest emotional state data, and sends the updated route information to the vehicle, providing a travel route that best suits the user's current emotional state and interests.

[0533] This system allows users to have a comfortable and enjoyable experience while traveling, and can provide added value not available in conventional navigation systems.

[0534] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0535] Step 1:

[0536] The user uses the in-vehicle interface to input personal information such as their hobbies, favorite places, and events of interest. The input information is stored in the vehicle system, encrypted, and synchronized to a cloud server, where the user's personal information is securely transmitted.

[0537] Step 2:

[0538] The server stores the user's personal information sent to the cloud server in a database. After storing the information, the server cleans the data, removing outliers and missing values, and converting it into a format suitable for analysis. This results in clean data that can be analyzed.

[0539] Step 3:

[0540] The server processes the cleaned data to analyze the user's behavioral patterns and preferences. For example, it uses Python's Pandas or Numpy to organize the data. After this, it generates an AI model for each user based on the data and trains it using TensorFlow or PyTorch. The analysis results in an individual AI model that reflects each user's preferences.

[0541] Step 4:

[0542] Cameras and microphones installed in the vehicle capture the user's facial expressions and voice in real time to collect emotional data. An emotion recognition engine (e.g., Affectiva SDK) is used to analyze the collected data and identify the user's current emotional state, resulting in real-time emotional state data.

[0543] Step 5:

[0544] The user inputs their current location and destination into the vehicle's interface or smartphone app. This information is sent to a cloud server, which then generates multiple routes based on the user's information and emotional state. Multiple routes, including stopovers, are calculated based on the user's preferences.

[0545] Step 6:

[0546] The server generates multiple routes and proposes the optimal route based on the user's selection. When the user selects an option such as "exercise priority" or "relaxation priority," the server reevaluates and optimizes the route based on the selected option and the user's latest emotional state data. The optimized route information is stored on the cloud server.

[0547] Step 7:

[0548] The device displays the optimized route on the vehicle's user interface. The user can confirm the proposed optimal route and, if they agree, the vehicle will begin autonomous driving according to that route. This allows the vehicle to travel along a route that best suits the user's emotional state and preferences.

[0549] Through these steps, the user can have a comfortable and enjoyable travel experience. An example of a prompt sentence for the generative AI model is, "Please suggest a route that passes through recommended cafes and parks when the user wants to relax. The user's hobby is visiting cafes."

[0550] 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.

[0551] 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.

[0552] 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.

[0553] [Second embodiment]

[0554] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0555] 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.

[0556] 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).

[0557] 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.

[0558] 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.

[0559] 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).

[0560] 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.

[0561] 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.

[0562] 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.

[0563] 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.

[0564] 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.

[0565] 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."

[0566] This invention is a system that generates and proposes optimal travel routes based on the user's preferences. This system is mainly composed of three elements: a server, a terminal, and a user.

[0567] Overall Overview

[0568] 1. Collection of User's Personal Information

[0569] Users enter personal information such as their favorite cafes, frequently visited spots, and events they are interested in through a smartphone app.

[0570] The device collects this information and sends it to the server in encrypted form.

[0571] The server stores the received information in a database.

[0572] 2. Analysis of user information

[0573] The server retrieves the user's personal information from the database, cleans the data, and then analyzes the user's preferences and behavioral patterns.

[0574] The server generates an AI model based on these analysis results and identifies each user's preferences.

[0575] 3. Route Generation

[0576] The user enters their current location and destination into the application.

[0577] The terminal sends the input data to the server.

[0578] The server generates multiple routes based on the user's current location, destination, and preferences, including stopovers that the user may be interested in.

[0579] The device displays the generated route to the user and allows the user to select the option of "exercise first" or "fun first."

[0580] 4. Optimal route suggestions

[0581] When the user selects an option, the terminal sends the information to the server.

[0582] The server will re-evaluate the routes based on the options and choose the best one.

[0583] The server sends the optimized route to the terminal, which displays it to the user.

[0584] Processing details and examples

[0585] Collection of Personal Information

[0586] Information users enter includes their favorite cafe (e.g., Blue Bottle Coffee), the gym they frequently visit, and upcoming music events.

[0587] The terminal receives these inputs, encrypts them, and sends them to the server.

[0588] The server decrypts the received information and stores it in a database.

[0589] User information analysis

[0590] The server retrieves user information from the database and performs data cleaning to remove outliers and missing values.

[0591] The server analyzes the user's preferences (e.g., cafe hopping, running, music) and reflects them in the AI ​​model.

[0592] The server continually updates the analysis results, keeping track of the user's latest preferences.

[0593] Route generation

[0594] The user inputs the destination "from home to the station."

[0595] The terminal sends the information to the server.

[0596] The server generates multiple routes including stopover spots (e.g., cafes, jogging courses) based on the user's current location, destination, and preference information.

[0597] The device displays the generated route on a user interface and allows the user to select options such as "exercise first" or "fun first."

[0598] Optimal route suggestions

[0599] When the user selects, for example, "Enjoyment Priority," the terminal transmits the selection to the server.

[0600] The server re-evaluates multiple routes based on the selection and selects the best route.

[0601] The server sends the optimized route to the terminal, which displays it to the user.

[0602] Ad business applications

[0603] The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[0604] The terminal displays the route with advertisements on a user interface.

[0605] The user may be interested in the displayed advertisement and may select a stop-off spot based on this interest.

[0606] As described above, the system of the present invention utilizes user preference information to optimize travel routes, thereby enabling users to spend their travel time meaningfully.

[0607] The processing flow will be explained below.

[0608] Step 1:

[0609] Users open the smartphone app and enter personal information such as their favorite cafes, frequently visited places, and events they are interested in through a registration profile.

[0610] Step 2:

[0611] The terminal collects personal information entered by the user and encrypts the data.

[0612] Step 3:

[0613] The terminal transmits the encrypted personal information to the server.

[0614] Step 4:

[0615] The server receives the encrypted data, decrypts it, and stores it in a database.

[0616] Step 5:

[0617] The server retrieves the user's personal information from the database and cleans the data, specifically by detecting and processing outliers and missing values.

[0618] Step 6:

[0619] The server uses the cleaned data to run algorithms that analyze user preferences and behavioral patterns.

[0620] Step 7:

[0621] Based on the analysis results, the server generates and trains a different AI model for each user.

[0622] Step 8:

[0623] The user inputs their current location and destination into the application (e.g., from home to the train station).

[0624] Step 9:

[0625] The terminal transmits the current location and destination information input by the user to the server.

[0626] Step 10:

[0627] The server generates multiple routes based on the user's current location, destination, and analyzed user preferences, including stopovers that may be of interest to the user.

[0628] Step 11:

[0629] The server transmits the generated routes to the terminal.

[0630] Step 12:

[0631] The device displays the generated route on a user interface, and the user can select options such as "exercise first" or "fun first."

[0632] Step 13:

[0633] The user selects an option (e.g., "Fun First").

[0634] Step 14:

[0635] The terminal sends the user's selected option to the server.

[0636] Step 15:

[0637] Based on the selected option, the server re-evaluates multiple routes and selects the best one.

[0638] Step 16:

[0639] The server sends the optimal route information to the terminal.

[0640] Step 17:

[0641] The terminal displays the optimal route on the user interface.

[0642] Step 18:

[0643] The user checks the displayed route and selects the route that best suits their preferences.

[0644] Step 19:

[0645] The device activates the navigation function and guides the user along the optimal route.

[0646] Step 20:

[0647] (Advertising business as an example)

[0648] The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[0649] Step 21:

[0650] The terminal displays the route with advertisements on a user interface.

[0651] Step 22:

[0652] The user is interested in the displayed advertisement and selects a stopover spot.

[0653] Example 1

[0654] 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."

[0655] Conventional travel route generation systems are limited to basic route search without fully considering the user's personal information and preferences. This makes it difficult to provide an optimal route that matches the user's interests and preferences. In addition, when a user's interests change, the system is unable to quickly reflect those changes, making it difficult to propose a route based on the latest information. Furthermore, from a commercial perspective, advertisements based on the user's preferences are not effectively displayed. To solve these problems, a system is needed that can understand and dynamically update the user's preferences to generate a more optimal travel route while also effectively providing related advertising information.

[0656] 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.

[0657] In this invention, the server includes a means for encrypting the user's personal information and transmitting it to the server, a means for storing the personal information received by the server in a database, and a means for retrieving the user's personal information from the database and performing data cleaning. This makes it possible to analyze the user's preferences and propose an optimal route based on dynamically updated information. Furthermore, the system has a function for selecting an option to prioritize exercise or fun in the user interface and a function for displaying related advertising information, providing a travel route that reflects the user's latest interests.

[0658] "User" refers to a person who uses the system to optimize their travel route.

[0659] "Personal information" refers to personal information such as a user's hobbies and interests, favorite spots, and frequently visited places.

[0660] "Terminal" refers to an electronic device such as a smartphone or tablet operated by a user.

[0661] "Server" means the central processing unit that receives, stores, and analyzes User's personal information.

[0662] "Database" means an electronic storage device for storing collected personal information about users.

[0663] "Data cleaning" refers to the process of removing irrelevant data and missing values ​​from a dataset and preparing it for analysis.

[0664] An "AI model" refers to a mathematical model that uses machine learning algorithms to analyze and predict user preferences.

[0665] "Route" refers to information showing the route from the user's current location to the destination.

[0666] The "route generation means" refers to a mechanism for calculating multiple routes based on the user's current location, destination, and user preference information.

[0667] "Route suggestion means" refers to a mechanism that selects and suggests the optimal route from multiple generated routes according to the user's selection.

[0668] "User interface" refers to the display screen and input means that users use to operate the system through a terminal.

[0669] "Option selection means" refers to a mechanism that allows users to select options such as "exercise priority" or "fun priority."

[0670] "Advertising information" refers to commercial information displayed based on the user's preferences.

[0671] "Encryption" refers to the process of converting data, such as personal information, for security purposes, making it unavailable to third parties.

[0672] A "generative AI model" refers to an algorithm that uses artificial intelligence technology to analyze user behavior and preferences and generate new data patterns.

[0673] A "prompt" is a command or question entered into a system to request a specific action or piece of information.

[0674] This invention is a system that generates and proposes optimal travel routes based on the user's preferences. This system is mainly composed of three elements: a server, a terminal, and a user. Each element and its role are explained in detail below.

[0675] server

[0676] The server plays an important role in receiving, storing, and analyzing the user's personal information and generating the optimal travel route.

[0677] Data Receipt and Decryption: Personal information sent by users arrives at the server in encrypted form. The server decrypts the information and stores it securely in a database. Specifically, encryption algorithms such as AES-256 can be used.

[0678] Database management: The server stores the received personal information in a database (e.g., MySQL or PostgreSQL). The database assigns a unique ID to each user and manages each user's information.

[0679] Data cleaning: Data cleaning is performed to remove inappropriate data and missing values ​​from the information obtained from the database.

[0680] Creation and analysis of AI models: To analyze user preferences, the server creates an AI model using machine learning libraries (e.g., TensorFlow or PyTorch). This model is used to identify and analyze individual user behavior patterns and preferences.

[0681] Route generation: The server generates multiple routes using a route search algorithm (e.g., Dijkstra or A algorithm) based on the user's current location, destination, and preference information.

[0682] Route proposal: From the generated routes, the optimal route is selected and proposed based on the user's selection (e.g., "exercise first" or "fun first").

[0683] Generating advertising information: The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[0684] Terminal

[0685] The terminal is an electronic device such as a smartphone or tablet that is operated by a user.

[0686] Information collection and transmission: Personal information entered by the user is collected, encrypted, and transmitted to the server. An encryption library (e.g., OpenSSL) can be embedded in the terminal.

[0687] User interface: The device displays the generated route on the user interface and presents the user with options such as "exercise priority" or "fun priority."

[0688] Sending selection information: The options selected by the user are encrypted and sent to the server.

[0689] Display Advertisements: Displays advertising information sent from the server and allows users to access more information.

[0690] User

[0691] A user is a person who uses the system to optimize a travel route.

[0692] Information input: Users input their preferences and interests (such as their favorite cafe, frequently visited gym, upcoming music events, etc.) through a smartphone app.

[0693] Setting current location and destination: The user sets their current location and destination within the app and sends them to the server via their device.

[0694] Select an option: Select the option you want from the options displayed on your device (e.g., "Prioritize exercise" or "Prioritize fun").

[0695] Examples of concrete examples and prompts

[0696] Specific examples

[0697] A user enters into the app, "I like Blue Bottle Coffee," "I go to the gym every weekend," and "I'll attend the next music festival."

[0698] The device encrypts the information and sends it to the server.

[0699] The server decrypts the received personal information and stores it in a database.

[0700] The server retrieves information from the database and analyzes that "cafe hopping" is a hobby.

[0701] When the user enters "from home to the station," the device sends the information to the server.

[0702] The server generates a route based on the user's preferences and suggests a route that includes "Blue Bottle Coffee."

[0703] The terminal displays the route and the user selects "Enjoyment priority."

[0704] The server selects the optimal route and the device displays it.

[0705] The server generates advertisements related to "cafe hopping" and the device displays them.

[0706] Prompt Sentence Examples

[0707] "Please tell me the route from your house to the station, including recommended cafes and jogging courses. Please also include options for routes that prioritize exercise."

[0708] As described above, this system utilizes user preference information to optimize travel routes, allowing users to spend their travel time meaningfully.

[0709] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0710] Step 1:

[0711] The user launches the smartphone app and enters their personal information (e.g., favorite cafe, frequently visited spots).

[0712] Input: Personal information such as the user's hobbies and interests

[0713] Action: The user performs an action to enter information into a form within the app.

[0714] Output: The personal information entered is saved on the device.

[0715] Step 2:

[0716] The terminal encrypts the user's personal information and sends it to the server.

[0717] Input: User's personal information

[0718] Processing: The device encrypts the data using an encryption algorithm such as AES-256 and sends it to the server in a secure HTTP request.

[0719] Output: Encrypted personal information is sent to the server.

[0720] Step 3:

[0721] The server receives the encrypted personal information, decrypts it, and stores it in a database.

[0722] Input: Encrypted personal information

[0723] Processing: The server decrypts the received data and stores it in a database, where each user is assigned a unique ID.

[0724] Output: Personal information decrypted and stored in a database

[0725] Step 4:

[0726] The server retrieves user information from the database and performs data cleaning.

[0727] Input: Personal information stored in the database

[0728] Processing: The server executes database queries to retrieve information and then performs a data cleaning process to remove irrelevant data and missing values.

[0729] Output: Cleaned user information

[0730] Step 5:

[0731] The server analyzes the user's preferences and generates an AI model.

[0732] Input: Cleaned user information

[0733] Processing: The server uses machine learning libraries such as TensorFlow and PyTorch to generate an AI model to analyze user preferences and perform the analysis.

[0734] Output: User preference information

[0735] Step 6:

[0736] The user enters their current location and destination through the app.

[0737] Input: Current location and destination information

[0738] Action: The user performs an action to enter information into an input field in the app.

[0739] Output: Current location and destination information is saved on the device.

[0740] Step 7:

[0741] The device encrypts the current location and destination information entered and sends it to the server.

[0742] Input: Current location and destination information

[0743] Processing: The device encrypts the information and sends it to the server in a secure HTTP request.

[0744] Output: Encrypted current location and destination information is sent to the server.

[0745] Step 8:

[0746] The server generates a route based on the user's current location, destination, and preference information.

[0747] Input: Encrypted current location and destination information, user preferences

[0748] Processing: The server interprets the information and generates multiple possible routes using a geographic information system (GIS) and route planning algorithms.

[0749] Output: Multiple route candidates

[0750] Step 9:

[0751] The device displays the generated route on a user interface and allows the user to select options such as "exercise first" or "fun first."

[0752] Input: Multiple route candidates

[0753] Processing: The terminal displays the route information received from the server on the user interface and presents options to the user.

[0754] Output: Route information and option choices displayed to the user

[0755] Step 10:

[0756] The user selects an option.

[0757] Input: The option selected by the user (e.g., "Enjoyment first")

[0758] Processing: The user selects an option through the terminal interface.

[0759] Output: Selected option information

[0760] Step 11:

[0761] The terminal encrypts the selected option information and transmits it to the server.

[0762] Input: The option selected by the user

[0763] Processing: The terminal encrypts the selected information and sends it to the server.

[0764] Output: The encrypted selection information is sent to the server.

[0765] Step 12:

[0766] The server reevaluates based on the selection information and selects the optimal route.

[0767] Input: Encrypted selection information, route candidates

[0768] Processing: The server decodes the selection information and uses AI models to re-evaluate route options and select the optimal route.

[0769] Output: Information on the best route

[0770] Step 13:

[0771] The server transmits optimal route information to the terminal, which then displays it to the user.

[0772] Input: Optimal route information

[0773] Processing: The server sends the optimal route information to the terminal, which displays it on the user interface.

[0774] Output: The optimal route is displayed on the user's device.

[0775] Step 14:

[0776] The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[0777] Input: User preferences

[0778] Processing: The server generates relevant advertising information based on the preference information and incorporates it into the selected route.

[0779] Output: Route information incorporating advertising information

[0780] Step 15:

[0781] The terminal displays the optimal route with advertisements on the user interface.

[0782] Input: Optimal route incorporating advertising information

[0783] Processing: The terminal displays the displayed information on the user interface.

[0784] Output: The optimal route information with advertisements is displayed to the user.

[0785] (Application example 1)

[0786] 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."

[0787] Conventional travel route generation systems simply provide the shortest or fastest route without fully utilizing the user's personal information and preferences. This makes it difficult to provide an optimal route that includes attractions and other interesting stops that the user wants to enjoy during their trip. Furthermore, even in autonomous vehicles, personalized navigation based on the user's preferences has not been provided.

[0788] 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.

[0789] In this invention, the server includes means for collecting personal information of a user, means for analyzing the collected personal information and understanding the user's preferences, means for generating multiple routes including stop-off spots based on information on the user's current location and destination, means for proposing an optimal route from the generated routes in accordance with an option selected by the user, means for displaying the provided route on a user interface, means for providing the above route in a navigation system for an autonomous vehicle, and means for generating an AI model for route proposals based on the user's preferences. This allows the user to not only reach their destination but also enjoy a personalized travel experience, and enables flexible navigation based on the user's preferences even in autonomous vehicles.

[0790] "User's personal information" is information that represents individual characteristics of the user, such as the user's tastes, interests, and past behavioral history.

[0791] A "user interface" is the part of a system that includes display and input devices through which a user interacts with the system.

[0792] An "autonomous vehicle" is a vehicle that uses systems or algorithms to drive itself automatically without a human driver.

[0793] A "navigation system" is a device or system that provides a user with the optimal route to reach their destination.

[0794] An "AI model" is a mathematical model that uses artificial intelligence technology to analyze data and apply the results.

[0795] "Route proposal" is the act of generating multiple routes from the user's current location to the destination, selecting the most suitable one, and presenting it.

[0796] A "stop-off spot" is a place or facility that a user can visit on the way while traveling.

[0797] "Selectable options" are route conditions and characteristics that a user can choose depending on their preferences and purpose.

[0798] "Collection means" refers to the functions and methods for acquiring user information.

[0799] "Analysis tools" are functions and methods for processing collected data and extracting meaningful information.

[0800] "Generation means" refers to functions or methods for creating new data or results based on user information or conditions.

[0801] "Display means" refers to a device or method for visually conveying generated information or results to a user.

[0802] The present invention relates to a system for generating and proposing optimal travel routes based on user preferences, which is targeted at autonomous vehicles and provides a personalized travel experience.

[0803] System configuration

[0804] This system mainly consists of three elements: a server, a terminal (smartphone or in-vehicle device), and a user.

[0805] 1. Collection of User's Personal Information:

[0806] Users enter personal information such as their favorite cafes, frequently visited spots, and events they are interested in through a smartphone app. The device collects this information and sends it in a securely encrypted format to a server, which then stores the information in a database.

[0807] 2. Analysis of User Information:

[0808] The server retrieves the user's personal information from the database, cleans the data, and then analyzes the user's preferences and behavioral patterns. Based on this, an AI model is generated to identify each user's preferences.

[0809] 3. Pathway Generation:

[0810] The user inputs their current location and destination into the application. The device then sends this input data to the server. The server generates multiple routes based on the current location, destination, and the user's preferences, including stopovers that the user may be interested in. The device displays the generated routes on a user interface, allowing the user to select options such as "exercise priority" or "fun priority."

[0811] 4. Optimal route suggestions:

[0812] Once the user selects an option, the device sends that information to the server, which reevaluates routes based on the options and selects the best one. The server then sends the optimized route to the device, which displays it to the user.

[0813] Hardware and software used

[0814] Hardware:

[0815] In-Vehicle Information System (IVI)

[0816] Smartphone

[0817] Autonomous vehicle sensors (GPS, LiDAR, cameras, etc.)

[0818] software:

[0819] Server applications (AWS, GCP)

[0820] Database (MySQL, Postgres)

[0821] Cryptography library (PyCryptodome)

[0822] HTTP client (requests)

[0823] Specific examples

[0824] For example, if the user selects "Strolling first," the server can suggest multiple routes that include the following spots:

[0825] Recently opened cafes and restaurants

[0826] Highly rated parks

[0827] Historical Attractions

[0828] Example prompts to input to a generative AI model:

[0829] text

[0830] Design a system that suggests optimal routes for autonomous vehicles based on the user's preferences. Based on the following information, generate routes that allow the user to select the "Stroll first" option and display them in the navigation system. The user's personal information includes their favorite cafes and events of interest.

[0831] 1. User preferences (cafes, tourist spots, parks)

[0832] 2. Current location (starting point) and destination

[0833] 3. Route options (exercise first, fun first)

[0834] As described above, this system utilizes user preference information to personalize the travel experience even in autonomous vehicles.

[0835] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0836] Step 1:

[0837] Users use a smartphone app to input personal information such as their favorite cafes, frequently visited spots, and events they are interested in. The device collects this information, encrypts it, and sends it to a server. The input data includes the user's interests and behavioral history, and encrypted data is generated as output.

[0838] Step 2:

[0839] The server receives the encrypted data sent from the terminal, decrypts it, and stores it in the database. The server checks the integrity of the initial data and stores it in the database. The input data is encrypted user information, and the output is user personal information stored in the database.

[0840] Step 3:

[0841] The server retrieves the user's personal information from the database and performs data cleaning. After eliminating outliers and missing data, it performs analysis to identify the user's preferences and behavioral patterns. An AI model is generated based on the analysis results, and a new user profile is created. The input data is the user's personal information, and the output is the generated AI model and user profile.

[0842] Step 4:

[0843] The user inputs their current location and destination into a smartphone app or on the in-car display. The device then sends this information to the server. The input data is the current location and destination information, and the output is the route request data sent to the server.

[0844] Step 5:

[0845] The server generates multiple routes based on the user's current location, destination, and preference information. The server uses an AI model to calculate a route that includes stops that the user may be interested in. After the route is generated, the result is sent to the device. The input data is the route request data and the user's preference information, and the output is the multiple routes generated.

[0846] Step 6:

[0847] The device displays multiple generated routes on a user interface, and the user selects options such as "exercise priority" or "fun priority." The input data is the generated route, and the output is the route options presented to the user.

[0848] Step 7:

[0849] When a user selects an option, the terminal sends the option information to the server. The server reevaluates routes based on the selected option and selects the optimal route. The input data is the option information selected by the user, and the output is the reevaluated optimal route.

[0850] Step 8:

[0851] The server sends the optimal route to the terminal, which then displays it to the user. The optimized route is reflected in the navigation system of the autonomous vehicle. The input data is the re-evaluated optimal route, and the output is the optimized route presented to the user.

[0852] Through the above processing steps, the system can utilize user preference information to provide a personalized travel experience in an autonomous vehicle.

[0853] 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.

[0854] The present invention is a system that generates and proposes optimal travel routes based on the user's preferences and emotions. It is mainly composed of a server, a terminal, a user, and an emotion engine.

[0855] Overall Overview

[0856] 1. Collection of User's Personal Information

[0857] Users enter personal information such as their hobbies, favorite cafes, frequently visited places, and events they are interested in through a smartphone app.

[0858] The device collects this information, encrypts it, and sends it to the server.

[0859] The server stores the received information in a database.

[0860] 2. Analysis of user information

[0861] The server retrieves the user's personal information from the database and performs data cleaning, handling outliers and missing values, and preparing the data in a format suitable for analysis.

[0862] The server analyzes the user's preferences and behavioral patterns based on the cleaned data.

[0863] The server uses the analysis results to generate and train a different AI model for each user.

[0864] 3. Emotional Engine Activation

[0865] It activates an emotion engine that recognizes emotions in real time using the user's facial expressions, voice data, touch input, etc.

[0866] The device collects emotion data and sends it to the server.

[0867] The server analyzes this emotional data to determine the current emotional state (e.g., happy, stressed).

[0868] 4. Route Generation

[0869] The user enters their current location and destination into the application.

[0870] The terminal transmits this information to the server.

[0871] The server generates multiple routes based on the user's current location, destination, and data on the user's preferences and emotional state. The generated routes include stopover spots that are likely to interest the user.

[0872] 5. Option selection and optimal route suggestions

[0873] The device displays the generated route on a user interface and allows the user to select options such as "exercise first" or "fun first."

[0874] When the user selects an option, the selection is sent to the server.

[0875] The server re-evaluates multiple routes depending on the selected options and the current emotional state and selects the optimal route.

[0876] The server transmits the optimized route information to the terminal.

[0877] The terminal displays the optimal route on the user interface, allowing the user to review and select.

[0878] Processing details and examples

[0879] Collection and analysis of personal information

[0880] Users enter their favorite cafes and spots (e.g., movie theaters, running courses, restaurants) through the app.

[0881] The device encrypts this, and the server receives the data and stores it in a database.

[0882] The server cleans the data and analyzes user behavior patterns, and the analysis results are reflected in the AI ​​model.

[0883] Example of the Emotion Engine in action

[0884] The user uses their smartphone camera to recognize their facial expressions (e.g., smiling, tired).

[0885] The device collects emotional data and sends it to a server.

[0886] The server analyzes the data using an emotion engine to identify the user's current emotional state. For example, if the user is feeling stressed, the server suggests a route that passes through a relaxing cafe or park.

[0887] Route generation

[0888] The user enters the destination as "from home to the station."

[0889] The device sends information to a server, which then generates multiple routes based on the information. The routes include stops based on the user's preferences (e.g., cafe hopping) and emotional state (e.g., needing to relax).

[0890] Option selection and optimal route suggestions

[0891] The device displays the route and allows the user to select "exercise priority" or "fun priority" (e.g., select "fun priority").

[0892] The device sends the selection information to the server, which then reevaluates the route based on the options and emotional state.

[0893] The server sends the optimal route to the terminal, which then displays it to the user.

[0894] The user checks the optimal route and prepares to depart.

[0895] Ad business applications

[0896] The server generates relevant advertisements (e.g., spas that are effective for relieving stress) based on the user's preferences and emotional state and incorporates them into the route.

[0897] The terminal displays a route with advertisements, and the user selects stop-off spots based on the advertisements.

[0898] In this way, the system of the present invention can utilize the user's preference information and emotional state to suggest more appropriate and meaningful travel routes.

[0899] The processing flow will be explained below.

[0900] Step 1:

[0901] Users open the smartphone app and enter personal information such as hobbies, favorite cafes, frequently visited places, and events they are interested in on the profile screen.

[0902] Step 2:

[0903] The terminal collects personal information entered by the user and encrypts the data.

[0904] Step 3:

[0905] The terminal transmits the encrypted personal information to the server.

[0906] Step 4:

[0907] The server receives the encrypted data, decrypts it, and stores it in a database.

[0908] Step 5:

[0909] The server retrieves the user's personal information from the database and performs data cleaning, specifically detecting and formatting outliers and missing data.

[0910] Step 6:

[0911] The server analyzes the cleaned data to identify the user's preferences and behavioral patterns.

[0912] Step 7:

[0913] The server generates an AI model based on the analysis results and trains a model personalized for each user.

[0914] Step 8:

[0915] The user uses the app to show their face to the camera, and the emotion engine recognizes their facial expressions.

[0916] Step 9:

[0917] The device transmits emotion data to the emotion engine in real time.

[0918] Step 10:

[0919] The server analyzes the data sent from the emotion engine and recognizes the current emotional state. For example, it recognizes that the user is "feeling stressed."

[0920] Step 11:

[0921] The user inputs their current location and destination into the application (e.g., from home to the train station).

[0922] Step 12:

[0923] The terminal transmits the entered current location and destination information to the server.

[0924] Step 13:

[0925] The server generates multiple routes including stopover spots based on the current location, destination, user preference information, and emotion data.

[0926] Step 14:

[0927] The server transmits the generated routes to the terminal.

[0928] Step 15:

[0929] The device displays the generated route in a user interface, where the user can select options such as "exercise first" or "fun first."

[0930] Step 16:

[0931] When the user selects an option, the terminal transmits the selection to the server.

[0932] Step 17:

[0933] The server re-evaluates multiple routes based on the selected options and the current emotional state and selects the optimal route.

[0934] Step 18:

[0935] The server transmits the optimized route information to the terminal.

[0936] Step 19:

[0937] The terminal displays the optimal route on the user interface, and the user confirms it and prepares to depart.

[0938] Step 20:

[0939] The device activates the navigation function and guides the user along the optimal route.

[0940] Step 21:

[0941] (Application of advertising business)

[0942] The server generates relevant advertising information based on the user's preference information and emotional state and incorporates it into the route.

[0943] Step 22:

[0944] The terminal displays the route with advertisements on a user interface.

[0945] Step 23:

[0946] The user selects stops of interest based on the advertisements displayed.

[0947] Through the above processing steps, the system can utilize the user's personal information and emotional state to provide the optimal route to make the travel process more meaningful and enjoyable.

[0948] Example 2

[0949] 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."

[0950] Conventional travel route generation systems do not take into account the user's personal information or emotional state, making it difficult to propose optimal travel routes that suit the user's preferences and current mood. Furthermore, they lack real-time emotion recognition and adaptation, making it difficult to improve user satisfaction. The present invention aims to solve these problems by providing a system that generates and proposes optimal travel routes based on the user's personal information and emotional state.

[0951] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting personal information of a user, means for encrypting the collected personal information and transmitting it via a network, means for storing the encrypted information in a database, means for acquiring the personal information from the database and performing data cleaning, means for analyzing the user's preferences and behavioral patterns based on the cleaned data, means for generating and training different artificial intelligence models based on the analysis results, means for recognizing emotions using the user's facial expressions, voice, and touch input, means for analyzing the recognized emotion data and identifying the user's current emotional state, means for generating multiple routes including stop-off spots based on information about the user's current location and destination, means for proposing an optimal route from the generated routes in accordance with an option selected by the user, and means for displaying the provided route on a user interface. This makes it possible to generate and suggest travel routes suited to the user's preferences and emotional state.

[0952] "User's personal information" means information relating to the User personally, such as the User's hobbies, interests, favorite places, frequently visited places and events of interest.

[0953] "Encryption" refers to a security technology that converts data so that it cannot be viewed illegally by third parties.

[0954] "Transmitting over a network" means the act of sending data over a communications network, including the Internet.

[0955] "Storing in a database" means storing data in a data storage system that systematically accumulates and manages information.

[0956] "Data cleaning" refers to the process of detecting outliers and missing values ​​in data and then performing processes such as deletion, completion, and correction to improve the quality of the data.

[0957] "Analysis of preferences and behavioral patterns" refers to the process of analyzing a user's preferences and behavioral patterns based on the user's personal information.

[0958] "Generating and training an artificial intelligence model" refers to the process of building an AI model based on data and then applying a learning algorithm to that model to improve its performance.

[0959] "Emotion recognition" refers to technology that determines a user's emotional state based on information such as the user's facial expressions, voice, and touch input.

[0960] "Analyzing emotional data and identifying emotional state" refers to the process of analyzing the data obtained from emotion recognition and identifying the emotion the user is currently feeling.

[0961] "Generating a route based on information about the current location and destination" refers to the operation of calculating the optimal travel route based on information about the departure point and arrival point set by the user.

[0962] "Spots to stop off at" refer to points along the way or potential destinations that are likely to interest the user.

[0963] "Proposing the best route based on options" refers to the process of recommending the most suitable route from among multiple route candidates based on setting options that the user can select.

[0964] "Displaying on the user interface" means the operation of displaying the generated route information on the display screen of the application.

[0965] The present invention is a system that generates and proposes optimal travel routes based on the user's preferences and emotions. This system is mainly composed of a server, a terminal, a user, and an emotion engine.

[0966] First, a user enters their hobbies and places of interest (e.g., cafes, movie theaters, running courses) through a smartphone application. This information is collected by the device and encrypted using an encryption algorithm (e.g., AES-256). The device then sends the encrypted data to a server. The server receives this data and stores it in a database (e.g., MySQL).

[0967] Next, the server retrieves personal information from the database and performs data cleaning. Data cleaning includes outlier detection and completion, and missing data handling. Specifically, an outlier detection algorithm is used to complete missing data with the mean or median. Based on this cleaned data, the server analyzes the user's preferences and behavioral patterns using machine learning algorithms (e.g., k-means clustering and collaborative filtering). The analysis results are used to generate different artificial intelligence models (e.g., using TensorFlow), which the AI ​​uses to learn.

[0968] For the emotion engine, the user inputs facial expressions and voice using the smartphone's camera and microphone. The device collects this emotion data and sends it to the server. The server then uses the emotion engine (using OpenCV or Pytorch, for example) to analyze the data and identify the user's current emotional state. For example, if the user is feeling stressed, the system will prioritize suggestions for relaxing cafes or parks.

[0969] To generate a route, the user inputs information about the starting point and destination through the application. For example, the input might be "from home to the station." The device then sends this information to the server, which then uses a map database (e.g., Google Maps API) to generate multiple routes. These routes include interesting stops (e.g., cafes, movie theaters, running courses) based on the user's preferences and emotional state.

[0970] The generated route is displayed on the user interface by the device. The user selects an option such as "exercise priority" or "fun priority." The option information selected by the user is sent back from the device to the server, and the server reevaluates the route based on the selected option and the user's current emotional state, selecting the optimal route. The server then sends the optimized route information to the device, which displays it on the user interface.

[0971] Examples of specific prompts include:

[0972] "Please enter places of interest or hobbies of the user (e.g., cafes, movie theaters, running trails)."

[0973] "Please enter your current location and destination (e.g. from home to the station)."

[0974] "Choose the exercise-first or fun-first option."

[0975] These procedures make it possible to generate and suggest travel routes that suit the user's preferences and emotional state.

[0976] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0977] Step 1: Collecting User Personal Information

[0978] A user starts a smartphone application and enters their hobbies and places of interest, such as their favorite cafe, movie theater, or running course, into an input box.

[0979] Input: User's hobbies and places of interest

[0980] Output: Raw personal information data

[0981] The device collects personal information entered, which is then encrypted using an encryption algorithm (e.g., AES-256).

[0982] Input: Raw personal information data

[0983] Output: Encrypted personal information data

[0984] The terminal transmits the encrypted personal information data to the server.

[0985] Input: Encrypted personal information data

[0986] Output: Encrypted data sent to the server

[0987] Step 2: Saving and cleaning user information

[0988] The server receives the encrypted data and stores it in a database (e.g. MySQL).

[0989] Input: Encrypted personal information data

[0990] Output: Information stored in the database

[0991] The server retrieves personal information from the database and performs data cleaning, detecting outliers and filling in missing data.

[0992] Input: Personal information retrieved from a database

[0993] Output: Cleaned personal information data

[0994] Step 3: Analyze preferences and behavioral patterns

[0995] The server analyzes user preferences and behavioral patterns based on the cleaned data, using machine learning algorithms (e.g., k-means clustering, collaborative filtering).

[0996] Input: Cleaned personal information data

[0997] Output: Analysis results of user preferences and behavior patterns

[0998] The server generates and trains a different artificial intelligence model (e.g., using TensorFlow) based on the analysis results.

[0999] Input: Analysis results of user preferences and behavior patterns

[1000] Output: A trained AI model

[1001] Step 4: Activate the Emotion Engine

[1002] The user uses the smartphone's camera and microphone to input facial expressions and voice data into the emotion engine.

[1003] Input: User's facial expression data and voice data

[1004] Output: Collected emotion data

[1005] The device collects emotional data and transmits it to a server in real time.

[1006] Input: Collected emotion data

[1007] Output: Emotion data sent to the server

[1008] The server analyzes the received emotion data and identifies the user's current emotional state (e.g., using OpenCV or Pytorch).

[1009] Input: Emotion data sent to the server

[1010] Output: The user's current emotional state

[1011] Step 5: Generate a path

[1012] The user inputs the departure and arrival points through a smartphone application (e.g., "from home to the station").

[1013] Input: Current location and destination information

[1014] Output: Location information entered into the device

[1015] The device transmits the input location information to the server.

[1016] Input: Location information entered on the device

[1017] Output: Location information sent to the server

[1018] The server generates multiple routes based on all data (personal information, emotional state) including the above information, using a map database (e.g., Google Maps API).

[1019] Input: current location, destination, personal information, emotional state

[1020] Output: Multiple generated routes

[1021] Step 6: Optimal Route Suggestion

[1022] The terminal displays the generated route on a user interface, and the user selects an option such as "exercise priority" or "fun priority."

[1023] Input: Multiple generated routes

[1024] Output: The route displayed in the user interface

[1025] The user selects the desired option and transmits the selection information from the terminal to the server.

[1026] Input: User's selection information (exercise priority, fun priority)

[1027] Output: Selections sent to the server

[1028] The server re-evaluates multiple routes and selects the best route based on the selected options and current emotional state.

[1029] Input: Selection information, emotional state

[1030] Output: Re-evaluated optimal path

[1031] The server sends the optimized route information to the terminal, which displays it on a user interface.

[1032] Input: Re-evaluated optimal path

[1033] Output: The optimal route displayed in the user interface

[1034] (Application example 2)

[1035] 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."

[1036] Conventional navigation systems mainly propose the shortest route to a destination based on the user's basic behavioral patterns. However, they do not offer optimal route suggestions that take into account the user's emotional state and preferences, making it difficult for users to have a travel experience that matches their mood and interests at the time. Therefore, there is a demand for a system that provides a comfortable and enjoyable travel experience based on the user's emotional state and preferences while traveling.

[1037] The identification processing 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 collecting personal information of the user, means for analyzing the collected personal information and understanding the user's preferences, means for generating multiple routes including stop-off spots based on information about the user's current location and destination, means for proposing an optimal route from the generated routes in accordance with an option selected by the user, means for displaying the provided route on a user interface, means for detecting the user's facial expressions and voice in real time using a camera and microphone mounted in the vehicle and collecting emotional data, means for identifying the user's current emotional state based on the collected emotional data, and means for optimizing the generated route based on the user's emotional state and preferences. This allows the server to provide an optimal travel route based on the user's emotional state and preferences, enabling a comfortable and enjoyable travel experience.

[1038] "User's personal information" is personal information about the user, such as the user's hobbies, favorite places, places that the user frequently visits, and events that interest the user.

[1039] "Tastes" refer to the preferences and tastes that are expressed by the things that a user likes or has interests.

[1040] A "stop-off spot" is a place or facility where a user can stop off during their travels.

[1041] "Current location" refers to the physical location where the user is currently located.

[1042] A "destination" is a location that a user is trying to reach.

[1043] "Options" are multiple choices or settings that a user can choose from.

[1044] The "route" refers to the route from the current location to the destination.

[1045] A "user interface" refers to a screen or device that allows a user to operate a system.

[1046] A "camera" is a device for taking images or videos.

[1047] A "microphone" is a device for recording sound.

[1048] "Emotion data" is information that indicates the user's emotional state, and is data collected from facial expressions and voice.

[1049] "Emotional state" refers to the mood or emotion that a user is currently experiencing.

[1050] "Optimization" means taking multiple conditions into consideration to derive the most suitable result.

[1051] The system that realizes this application example is an "emotional navigation system" installed in an autonomous vehicle. This system generates and suggests optimal routes based on the user's preferences and emotional state. The following describes an embodiment of this system.

[1052] The server collects and analyzes personal information about the user, who uses the in-vehicle interface to input information such as hobbies, favorite places, and events of interest. This information is stored in the vehicle system, encrypted, and synchronized to a cloud server.

[1053] The cloud server cleans the collected user information, analyzes the user's behavioral patterns and preferences, and generates and trains an AI model for each user based on that information.The data analysis tools used are Python's Pandas and Numpy, and the AI ​​models are TensorFlow and PyTorch.

[1054] Next, cameras and microphones mounted on the vehicle capture the user's facial expressions and voice in real time to collect emotional data, which is then analyzed using an emotion recognition engine (e.g., Affectiva SDK) to identify the user's current emotional state (e.g., enjoying, stressed).

[1055] When a user inputs their current location and destination into the vehicle's interface or smartphone app, the information is sent to a cloud server, which then generates an optimal route based on the user's information and emotional state, taking into account stopovers based on the user's preferences.

[1056] For example, if a user specifies a route from home to the station and wishes to relax, the cloud server will suggest a route that passes through cafes and parks where the user can relax. An example of a prompt sentence for a generative AI model is as follows:

[1057] "Please suggest routes that pass through recommended cafes and parks when the user wants to relax. The user's hobby is visiting cafes."

[1058] Finally, the generated routes are displayed on the user interface, and the user can select options such as "exercise first" or "relaxation first." The cloud server reevaluates the optimal route based on the selected option and the latest emotional state data, and sends the updated route information to the vehicle, providing a travel route that best suits the user's current emotional state and interests.

[1059] This system allows users to have a comfortable and enjoyable experience while traveling, and can provide added value not available in conventional navigation systems.

[1060] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1061] Step 1:

[1062] The user uses the in-vehicle interface to input personal information such as their hobbies, favorite places, and events of interest. The input information is stored in the vehicle system, encrypted, and synchronized to a cloud server, where the user's personal information is securely transmitted.

[1063] Step 2:

[1064] The server stores the user's personal information sent to the cloud server in a database. After storing the information, the server cleans the data, removing outliers and missing values, and converting it into a format suitable for analysis. This results in clean data that can be analyzed.

[1065] Step 3:

[1066] The server processes the cleaned data to analyze the user's behavioral patterns and preferences. For example, it uses Python's Pandas or Numpy to organize the data. After this, it generates an AI model for each user based on the data and trains it using TensorFlow or PyTorch. The analysis results in an individual AI model that reflects each user's preferences.

[1067] Step 4:

[1068] Cameras and microphones installed in the vehicle capture the user's facial expressions and voice in real time to collect emotional data. An emotion recognition engine (e.g., Affectiva SDK) is used to analyze the collected data and identify the user's current emotional state, resulting in real-time emotional state data.

[1069] Step 5:

[1070] The user inputs their current location and destination into the vehicle's interface or smartphone app. This information is sent to a cloud server, which then generates multiple routes based on the user's information and emotional state. Multiple routes, including stopovers, are calculated based on the user's preferences.

[1071] Step 6:

[1072] The server generates multiple routes and proposes the optimal route based on the user's selection. When the user selects an option such as "exercise priority" or "relaxation priority," the server reevaluates and optimizes the route based on the selected option and the user's latest emotional state data. The optimized route information is stored on the cloud server.

[1073] Step 7:

[1074] The device displays the optimized route on the vehicle's user interface. The user can confirm the proposed optimal route and, if they agree, the vehicle will begin autonomous driving according to that route. This allows the vehicle to travel along a route that best suits the user's emotional state and preferences.

[1075] Through these steps, the user can have a comfortable and enjoyable travel experience. An example of a prompt sentence for the generative AI model is, "Please suggest a route that passes through recommended cafes and parks when the user wants to relax. The user's hobby is visiting cafes."

[1076] 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.

[1077] 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.

[1078] 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.

[1079] [Third embodiment]

[1080] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1081] 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.

[1082] 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).

[1083] 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.

[1084] 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.

[1085] 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).

[1086] 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.

[1087] 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.

[1088] 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.

[1089] 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.

[1090] 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.

[1091] 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."

[1092] This invention is a system that generates and proposes optimal travel routes based on the user's preferences. This system is mainly composed of three elements: a server, a terminal, and a user.

[1093] Overall Overview

[1094] 1. Collection of User's Personal Information

[1095] Users enter personal information such as their favorite cafes, frequently visited spots, and events they are interested in through a smartphone app.

[1096] The device collects this information and sends it to the server in encrypted form.

[1097] The server stores the received information in a database.

[1098] 2. Analysis of user information

[1099] The server retrieves the user's personal information from the database, cleans the data, and then analyzes the user's preferences and behavioral patterns.

[1100] The server generates an AI model based on these analysis results and identifies each user's preferences.

[1101] 3. Route Generation

[1102] The user enters their current location and destination into the application.

[1103] The terminal sends the input data to the server.

[1104] The server generates multiple routes based on the user's current location, destination, and preferences, including stopovers that the user may be interested in.

[1105] The device displays the generated route to the user and allows the user to select the option of "exercise first" or "fun first."

[1106] 4. Optimal route suggestions

[1107] When the user selects an option, the terminal sends the information to the server.

[1108] The server will re-evaluate the routes based on the options and choose the best one.

[1109] The server sends the optimized route to the terminal, which displays it to the user.

[1110] Processing details and examples

[1111] Collection of Personal Information

[1112] Information users enter includes their favorite cafe (e.g., Blue Bottle Coffee), the gym they frequently visit, and upcoming music events.

[1113] The terminal receives these inputs, encrypts them, and sends them to the server.

[1114] The server decrypts the received information and stores it in a database.

[1115] User information analysis

[1116] The server retrieves user information from the database and performs data cleaning to remove outliers and missing values.

[1117] The server analyzes the user's preferences (e.g., cafe hopping, running, music) and reflects them in the AI ​​model.

[1118] The server continually updates the analysis results, keeping track of the user's latest preferences.

[1119] Route generation

[1120] The user inputs the destination "from home to the station."

[1121] The terminal sends the information to the server.

[1122] The server generates multiple routes including stopover spots (e.g., cafes, jogging courses) based on the user's current location, destination, and preference information.

[1123] The device displays the generated route on a user interface and allows the user to select options such as "exercise first" or "fun first."

[1124] Optimal route suggestions

[1125] When the user selects, for example, "Enjoyment Priority," the terminal transmits the selection to the server.

[1126] The server re-evaluates multiple routes based on the selection and selects the best route.

[1127] The server sends the optimized route to the terminal, which displays it to the user.

[1128] Ad business applications

[1129] The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[1130] The terminal displays the route with advertisements on a user interface.

[1131] The user may be interested in the displayed advertisement and may select a stop-off spot based on this interest.

[1132] As described above, the system of the present invention utilizes user preference information to optimize travel routes, thereby enabling users to spend their travel time meaningfully.

[1133] The processing flow will be explained below.

[1134] Step 1:

[1135] Users open the smartphone app and enter personal information such as their favorite cafes, frequently visited places, and events they are interested in through a registration profile.

[1136] Step 2:

[1137] The terminal collects personal information entered by the user and encrypts the data.

[1138] Step 3:

[1139] The terminal transmits the encrypted personal information to the server.

[1140] Step 4:

[1141] The server receives the encrypted data, decrypts it, and stores it in a database.

[1142] Step 5:

[1143] The server retrieves the user's personal information from the database and cleans the data, specifically by detecting and processing outliers and missing values.

[1144] Step 6:

[1145] The server uses the cleaned data to run algorithms that analyze user preferences and behavioral patterns.

[1146] Step 7:

[1147] Based on the analysis results, the server generates and trains a different AI model for each user.

[1148] Step 8:

[1149] The user inputs their current location and destination into the application (e.g., from home to the train station).

[1150] Step 9:

[1151] The terminal transmits the current location and destination information input by the user to the server.

[1152] Step 10:

[1153] The server generates multiple routes based on the user's current location, destination, and analyzed user preferences, including stopovers that may be of interest to the user.

[1154] Step 11:

[1155] The server transmits the generated routes to the terminal.

[1156] Step 12:

[1157] The device displays the generated route on a user interface, and the user can select options such as "exercise first" or "fun first."

[1158] Step 13:

[1159] The user selects an option (e.g., "Fun First").

[1160] Step 14:

[1161] The terminal sends the user's selected option to the server.

[1162] Step 15:

[1163] Based on the selected option, the server re-evaluates multiple routes and selects the best one.

[1164] Step 16:

[1165] The server sends the optimal route information to the terminal.

[1166] Step 17:

[1167] The terminal displays the optimal route on the user interface.

[1168] Step 18:

[1169] The user checks the displayed route and selects the route that best suits their preferences.

[1170] Step 19:

[1171] The device activates the navigation function and guides the user along the optimal route.

[1172] Step 20:

[1173] (Advertising business as an example)

[1174] The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[1175] Step 21:

[1176] The terminal displays the route with advertisements on a user interface.

[1177] Step 22:

[1178] The user is interested in the displayed advertisement and selects a stopover spot.

[1179] Example 1

[1180] 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."

[1181] Conventional travel route generation systems are limited to basic route search without fully considering the user's personal information and preferences. This makes it difficult to provide an optimal route that matches the user's interests and preferences. In addition, when a user's interests change, the system is unable to quickly reflect those changes, making it difficult to propose a route based on the latest information. Furthermore, from a commercial perspective, advertisements based on the user's preferences are not effectively displayed. To solve these problems, a system is needed that can understand and dynamically update the user's preferences to generate a more optimal travel route while also effectively providing related advertising information.

[1182] 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.

[1183] In this invention, the server includes a means for encrypting the user's personal information and transmitting it to the server, a means for storing the personal information received by the server in a database, and a means for retrieving the user's personal information from the database and performing data cleaning. This makes it possible to analyze the user's preferences and propose an optimal route based on dynamically updated information. Furthermore, the system has a function for selecting an option to prioritize exercise or fun in the user interface and a function for displaying related advertising information, providing a travel route that reflects the user's latest interests.

[1184] "User" refers to a person who uses the system to optimize their travel route.

[1185] "Personal information" refers to personal information such as a user's hobbies and interests, favorite spots, and frequently visited places.

[1186] "Terminal" refers to an electronic device such as a smartphone or tablet operated by a user.

[1187] "Server" means the central processing unit that receives, stores, and analyzes User's personal information.

[1188] "Database" means an electronic storage device for storing collected personal information about users.

[1189] "Data cleaning" refers to the process of removing irrelevant data and missing values ​​from a dataset and preparing it for analysis.

[1190] An "AI model" refers to a mathematical model that uses machine learning algorithms to analyze and predict user preferences.

[1191] "Route" refers to information showing the route from the user's current location to the destination.

[1192] The "route generation means" refers to a mechanism for calculating multiple routes based on the user's current location, destination, and user preference information.

[1193] "Route suggestion means" refers to a mechanism that selects and suggests the optimal route from multiple generated routes according to the user's selection.

[1194] "User interface" refers to the display screen and input means that users use to operate the system through a terminal.

[1195] "Option selection means" refers to a mechanism that allows users to select options such as "exercise priority" or "fun priority."

[1196] "Advertising information" refers to commercial information displayed based on the user's preferences.

[1197] "Encryption" refers to the process of converting data, such as personal information, for security purposes, making it unavailable to third parties.

[1198] A "generative AI model" refers to an algorithm that uses artificial intelligence technology to analyze user behavior and preferences and generate new data patterns.

[1199] A "prompt" is a command or question entered into a system to request a specific action or piece of information.

[1200] This invention is a system that generates and proposes optimal travel routes based on the user's preferences. This system is mainly composed of three elements: a server, a terminal, and a user. Each element and its role are explained in detail below.

[1201] server

[1202] The server plays an important role in receiving, storing, and analyzing the user's personal information and generating the optimal travel route.

[1203] Data Receipt and Decryption: Personal information sent by users arrives at the server in encrypted form. The server decrypts the information and stores it securely in a database. Specifically, encryption algorithms such as AES-256 can be used.

[1204] Database management: The server stores the received personal information in a database (e.g., MySQL or PostgreSQL). The database assigns a unique ID to each user and manages each user's information.

[1205] Data cleaning: Data cleaning is performed to remove inappropriate data and missing values ​​from the information obtained from the database.

[1206] Creation and analysis of AI models: To analyze user preferences, the server creates an AI model using machine learning libraries (e.g., TensorFlow or PyTorch). This model is used to identify and analyze individual user behavior patterns and preferences.

[1207] Route generation: The server generates multiple routes using a route search algorithm (e.g., Dijkstra or A algorithm) based on the user's current location, destination, and preference information.

[1208] Route proposal: From the generated routes, the optimal route is selected and proposed based on the user's selection (e.g., "exercise first" or "fun first").

[1209] Generating advertising information: The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[1210] Terminal

[1211] The terminal is an electronic device such as a smartphone or tablet that is operated by a user.

[1212] Information collection and transmission: Personal information entered by the user is collected, encrypted, and transmitted to the server. An encryption library (e.g., OpenSSL) can be embedded in the terminal.

[1213] User interface: The device displays the generated route on the user interface and presents the user with options such as "exercise priority" or "fun priority."

[1214] Sending selection information: The options selected by the user are encrypted and sent to the server.

[1215] Display Advertisements: Displays advertising information sent from the server and allows users to access more information.

[1216] User

[1217] A user is a person who uses the system to optimize a travel route.

[1218] Information input: Users input their preferences and interests (such as their favorite cafe, frequently visited gym, upcoming music events, etc.) through a smartphone app.

[1219] Setting current location and destination: The user sets their current location and destination within the app and sends them to the server via their device.

[1220] Select an option: Select the option you want from the options displayed on your device (e.g., "Prioritize exercise" or "Prioritize fun").

[1221] Examples of concrete examples and prompts

[1222] Specific examples

[1223] A user enters into the app, "I like Blue Bottle Coffee," "I go to the gym every weekend," and "I'll attend the next music festival."

[1224] The device encrypts the information and sends it to the server.

[1225] The server decrypts the received personal information and stores it in a database.

[1226] The server retrieves information from the database and analyzes that "cafe hopping" is a hobby.

[1227] When the user enters "from home to the station," the device sends the information to the server.

[1228] The server generates a route based on the user's preferences and suggests a route that includes "Blue Bottle Coffee."

[1229] The terminal displays the route and the user selects "Enjoyment priority."

[1230] The server selects the optimal route and the device displays it.

[1231] The server generates advertisements related to "cafe hopping" and the device displays them.

[1232] Prompt Sentence Examples

[1233] "Please tell me the route from your house to the station, including recommended cafes and jogging courses. Please also include options for routes that prioritize exercise."

[1234] As described above, this system utilizes user preference information to optimize travel routes, allowing users to spend their travel time meaningfully.

[1235] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1236] Step 1:

[1237] The user launches the smartphone app and enters their personal information (e.g., favorite cafe, frequently visited spots).

[1238] Input: Personal information such as the user's hobbies and interests

[1239] Action: The user performs an action to enter information into a form within the app.

[1240] Output: The personal information entered is saved on the device.

[1241] Step 2:

[1242] The terminal encrypts the user's personal information and sends it to the server.

[1243] Input: User's personal information

[1244] Processing: The device encrypts the data using an encryption algorithm such as AES-256 and sends it to the server in a secure HTTP request.

[1245] Output: Encrypted personal information is sent to the server.

[1246] Step 3:

[1247] The server receives the encrypted personal information, decrypts it, and stores it in a database.

[1248] Input: Encrypted personal information

[1249] Processing: The server decrypts the received data and stores it in a database, where each user is assigned a unique ID.

[1250] Output: Personal information decrypted and stored in a database

[1251] Step 4:

[1252] The server retrieves user information from the database and performs data cleaning.

[1253] Input: Personal information stored in the database

[1254] Processing: The server executes database queries to retrieve information and then performs a data cleaning process to remove irrelevant data and missing values.

[1255] Output: Cleaned user information

[1256] Step 5:

[1257] The server analyzes the user's preferences and generates an AI model.

[1258] Input: Cleaned user information

[1259] Processing: The server uses machine learning libraries such as TensorFlow and PyTorch to generate an AI model to analyze user preferences and perform the analysis.

[1260] Output: User preference information

[1261] Step 6:

[1262] The user enters their current location and destination through the app.

[1263] Input: Current location and destination information

[1264] Action: The user performs an action to enter information into an input field in the app.

[1265] Output: Current location and destination information is saved on the device.

[1266] Step 7:

[1267] The device encrypts the current location and destination information entered and sends it to the server.

[1268] Input: Current location and destination information

[1269] Processing: The device encrypts the information and sends it to the server in a secure HTTP request.

[1270] Output: Encrypted current location and destination information is sent to the server.

[1271] Step 8:

[1272] The server generates a route based on the user's current location, destination, and preference information.

[1273] Input: Encrypted current location and destination information, user preferences

[1274] Processing: The server interprets the information and generates multiple possible routes using a geographic information system (GIS) and route planning algorithms.

[1275] Output: Multiple route candidates

[1276] Step 9:

[1277] The device displays the generated route on a user interface and allows the user to select options such as "exercise first" or "fun first."

[1278] Input: Multiple route candidates

[1279] Processing: The terminal displays the route information received from the server on the user interface and presents options to the user.

[1280] Output: Route information and option choices displayed to the user

[1281] Step 10:

[1282] The user selects an option.

[1283] Input: The option selected by the user (e.g., "Enjoyment first")

[1284] Processing: The user selects an option through the terminal interface.

[1285] Output: Selected option information

[1286] Step 11:

[1287] The terminal encrypts the selected option information and transmits it to the server.

[1288] Input: The option selected by the user

[1289] Processing: The terminal encrypts the selected information and sends it to the server.

[1290] Output: The encrypted selection information is sent to the server.

[1291] Step 12:

[1292] The server reevaluates based on the selection information and selects the optimal route.

[1293] Input: Encrypted selection information, route candidates

[1294] Processing: The server decodes the selection information and uses AI models to re-evaluate route options and select the optimal route.

[1295] Output: Information on the best route

[1296] Step 13:

[1297] The server transmits optimal route information to the terminal, which then displays it to the user.

[1298] Input: Optimal route information

[1299] Processing: The server sends the optimal route information to the terminal, which displays it on the user interface.

[1300] Output: The optimal route is displayed on the user's device.

[1301] Step 14:

[1302] The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[1303] Input: User preferences

[1304] Processing: The server generates relevant advertising information based on the preference information and incorporates it into the selected route.

[1305] Output: Route information incorporating advertising information

[1306] Step 15:

[1307] The terminal displays the optimal route with advertisements on the user interface.

[1308] Input: Optimal route incorporating advertising information

[1309] Processing: The terminal displays the displayed information on the user interface.

[1310] Output: The optimal route information with advertisements is displayed to the user.

[1311] (Application example 1)

[1312] 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."

[1313] Conventional travel route generation systems simply provide the shortest or fastest route without fully utilizing the user's personal information and preferences. This makes it difficult to provide an optimal route that includes attractions and other interesting stops that the user wants to enjoy during their trip. Furthermore, even in autonomous vehicles, personalized navigation based on the user's preferences has not been provided.

[1314] 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.

[1315] In this invention, the server includes means for collecting personal information of a user, means for analyzing the collected personal information and understanding the user's preferences, means for generating multiple routes including stop-off spots based on information on the user's current location and destination, means for proposing an optimal route from the generated routes in accordance with an option selected by the user, means for displaying the provided route on a user interface, means for providing the above route in a navigation system for an autonomous vehicle, and means for generating an AI model for route proposals based on the user's preferences. This allows the user to not only reach their destination but also enjoy a personalized travel experience, and enables flexible navigation based on the user's preferences even in autonomous vehicles.

[1316] "User's personal information" is information that represents individual characteristics of the user, such as the user's tastes, interests, and past behavioral history.

[1317] A "user interface" is the part of a system that includes display and input devices through which a user interacts with the system.

[1318] An "autonomous vehicle" is a vehicle that uses systems or algorithms to drive itself automatically without a human driver.

[1319] A "navigation system" is a device or system that provides a user with the optimal route to reach their destination.

[1320] An "AI model" is a mathematical model that uses artificial intelligence technology to analyze data and apply the results.

[1321] "Route proposal" is the act of generating multiple routes from the user's current location to the destination, selecting the most suitable one, and presenting it.

[1322] A "stop-off spot" is a place or facility that a user can visit on the way while traveling.

[1323] "Selectable options" are route conditions and characteristics that a user can choose depending on their preferences and purpose.

[1324] "Collection means" refers to the functions and methods for acquiring user information.

[1325] "Analysis tools" are functions and methods for processing collected data and extracting meaningful information.

[1326] "Generation means" refers to functions or methods for creating new data or results based on user information or conditions.

[1327] "Display means" refers to a device or method for visually conveying generated information or results to a user.

[1328] The present invention relates to a system for generating and proposing optimal travel routes based on user preferences, which is targeted at autonomous vehicles and provides a personalized travel experience.

[1329] System configuration

[1330] This system mainly consists of three elements: a server, a terminal (smartphone or in-vehicle device), and a user.

[1331] 1. Collection of User's Personal Information:

[1332] Users enter personal information such as their favorite cafes, frequently visited spots, and events they are interested in through a smartphone app. The device collects this information and sends it in a securely encrypted format to a server, which then stores the information in a database.

[1333] 2. Analysis of User Information:

[1334] The server retrieves the user's personal information from the database, cleans the data, and then analyzes the user's preferences and behavioral patterns. Based on this, an AI model is generated to identify each user's preferences.

[1335] 3. Pathway Generation:

[1336] The user inputs their current location and destination into the application. The device then sends this input data to the server. The server generates multiple routes based on the current location, destination, and the user's preferences, including stopovers that the user may be interested in. The device displays the generated routes on a user interface, allowing the user to select options such as "exercise priority" or "fun priority."

[1337] 4. Optimal route suggestions:

[1338] Once the user selects an option, the device sends that information to the server, which reevaluates routes based on the options and selects the best one. The server then sends the optimized route to the device, which displays it to the user.

[1339] Hardware and software used

[1340] Hardware:

[1341] In-Vehicle Information System (IVI)

[1342] Smartphone

[1343] Autonomous vehicle sensors (GPS, LiDAR, cameras, etc.)

[1344] software:

[1345] Server applications (AWS, GCP)

[1346] Database (MySQL, Postgres)

[1347] Cryptography library (PyCryptodome)

[1348] HTTP client (requests)

[1349] Specific examples

[1350] For example, if the user selects "Strolling first," the server can suggest multiple routes that include the following spots:

[1351] Recently opened cafes and restaurants

[1352] Highly rated parks

[1353] Historical Attractions

[1354] Example prompts to input to a generative AI model:

[1355] text

[1356] Design a system that suggests optimal routes for autonomous vehicles based on the user's preferences. Based on the following information, generate routes that allow the user to select the "Stroll first" option and display them in the navigation system. The user's personal information includes their favorite cafes and events of interest.

[1357] 1. User preferences (cafes, tourist spots, parks)

[1358] 2. Current location (starting point) and destination

[1359] 3. Route options (exercise first, fun first)

[1360] As described above, this system utilizes user preference information to personalize the travel experience even in autonomous vehicles.

[1361] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1362] Step 1:

[1363] Users use a smartphone app to input personal information such as their favorite cafes, frequently visited spots, and events they are interested in. The device collects this information, encrypts it, and sends it to a server. The input data includes the user's interests and behavioral history, and encrypted data is generated as output.

[1364] Step 2:

[1365] The server receives the encrypted data sent from the terminal, decrypts it, and stores it in the database. The server checks the integrity of the initial data and stores it in the database. The input data is encrypted user information, and the output is user personal information stored in the database.

[1366] Step 3:

[1367] The server retrieves the user's personal information from the database and performs data cleaning. After eliminating outliers and missing data, it performs analysis to identify the user's preferences and behavioral patterns. An AI model is generated based on the analysis results, and a new user profile is created. The input data is the user's personal information, and the output is the generated AI model and user profile.

[1368] Step 4:

[1369] The user inputs their current location and destination into a smartphone app or on the in-car display. The device then sends this information to the server. The input data is the current location and destination information, and the output is the route request data sent to the server.

[1370] Step 5:

[1371] The server generates multiple routes based on the user's current location, destination, and preference information. The server uses an AI model to calculate a route that includes stops that the user may be interested in. After the route is generated, the result is sent to the device. The input data is the route request data and the user's preference information, and the output is the multiple routes generated.

[1372] Step 6:

[1373] The device displays multiple generated routes on a user interface, and the user selects options such as "exercise priority" or "fun priority." The input data is the generated route, and the output is the route options presented to the user.

[1374] Step 7:

[1375] When a user selects an option, the terminal sends the option information to the server. The server reevaluates routes based on the selected option and selects the optimal route. The input data is the option information selected by the user, and the output is the reevaluated optimal route.

[1376] Step 8:

[1377] The server sends the optimal route to the terminal, which then displays it to the user. The optimized route is reflected in the navigation system of the autonomous vehicle. The input data is the re-evaluated optimal route, and the output is the optimized route presented to the user.

[1378] Through the above processing steps, the system can utilize user preference information to provide a personalized travel experience in an autonomous vehicle.

[1379] 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.

[1380] The present invention is a system that generates and proposes optimal travel routes based on the user's preferences and emotions. It is mainly composed of a server, a terminal, a user, and an emotion engine.

[1381] Overall Overview

[1382] 1. Collection of User's Personal Information

[1383] Users enter personal information such as their hobbies, favorite cafes, frequently visited places, and events they are interested in through a smartphone app.

[1384] The device collects this information, encrypts it, and sends it to the server.

[1385] The server stores the received information in a database.

[1386] 2. Analysis of user information

[1387] The server retrieves the user's personal information from the database and performs data cleaning, handling outliers and missing values, and preparing the data in a format suitable for analysis.

[1388] The server analyzes the user's preferences and behavioral patterns based on the cleaned data.

[1389] The server uses the analysis results to generate and train a different AI model for each user.

[1390] 3. Emotional Engine Activation

[1391] It activates an emotion engine that recognizes emotions in real time using the user's facial expressions, voice data, touch input, etc.

[1392] The device collects emotion data and sends it to the server.

[1393] The server analyzes this emotional data to determine the current emotional state (e.g., happy, stressed).

[1394] 4. Route Generation

[1395] The user enters their current location and destination into the application.

[1396] The terminal transmits this information to the server.

[1397] The server generates multiple routes based on the user's current location, destination, and data on the user's preferences and emotional state. The generated routes include stopover spots that are likely to interest the user.

[1398] 5. Option selection and optimal route suggestions

[1399] The device displays the generated route on a user interface and allows the user to select options such as "exercise first" or "fun first."

[1400] When the user selects an option, the selection is sent to the server.

[1401] The server re-evaluates multiple routes depending on the selected options and the current emotional state and selects the optimal route.

[1402] The server transmits the optimized route information to the terminal.

[1403] The terminal displays the optimal route on the user interface, allowing the user to review and select.

[1404] Processing details and examples

[1405] Collection and analysis of personal information

[1406] Users enter their favorite cafes and spots (e.g., movie theaters, running courses, restaurants) through the app.

[1407] The device encrypts this, and the server receives the data and stores it in a database.

[1408] The server cleans the data and analyzes user behavior patterns, and the analysis results are reflected in the AI ​​model.

[1409] Example of the Emotion Engine in action

[1410] The user uses their smartphone camera to recognize their facial expressions (e.g., smiling, tired).

[1411] The device collects emotional data and sends it to a server.

[1412] The server analyzes the data using an emotion engine to identify the user's current emotional state. For example, if the user is feeling stressed, the server suggests a route that passes through a relaxing cafe or park.

[1413] Route generation

[1414] The user enters the destination as "from home to the station."

[1415] The device sends information to a server, which then generates multiple routes based on the information. The routes include stops based on the user's preferences (e.g., cafe hopping) and emotional state (e.g., needing to relax).

[1416] Option selection and optimal route suggestions

[1417] The device displays the route and allows the user to select "exercise priority" or "fun priority" (e.g., select "fun priority").

[1418] The device sends the selection information to the server, which then reevaluates the route based on the options and emotional state.

[1419] The server sends the optimal route to the terminal, which then displays it to the user.

[1420] The user checks the optimal route and prepares to depart.

[1421] Ad business applications

[1422] The server generates relevant advertisements (e.g., spas that are effective for relieving stress) based on the user's preferences and emotional state and incorporates them into the route.

[1423] The terminal displays a route with advertisements, and the user selects stop-off spots based on the advertisements.

[1424] In this way, the system of the present invention can utilize the user's preference information and emotional state to suggest more appropriate and meaningful travel routes.

[1425] The processing flow will be explained below.

[1426] Step 1:

[1427] Users open the smartphone app and enter personal information such as hobbies, favorite cafes, frequently visited places, and events they are interested in on the profile screen.

[1428] Step 2:

[1429] The terminal collects personal information entered by the user and encrypts the data.

[1430] Step 3:

[1431] The terminal transmits the encrypted personal information to the server.

[1432] Step 4:

[1433] The server receives the encrypted data, decrypts it, and stores it in a database.

[1434] Step 5:

[1435] The server retrieves the user's personal information from the database and performs data cleaning, specifically detecting and formatting outliers and missing data.

[1436] Step 6:

[1437] The server analyzes the cleaned data to identify the user's preferences and behavioral patterns.

[1438] Step 7:

[1439] The server generates an AI model based on the analysis results and trains a model personalized for each user.

[1440] Step 8:

[1441] The user uses the app to show their face to the camera, and the emotion engine recognizes their facial expressions.

[1442] Step 9:

[1443] The device transmits emotion data to the emotion engine in real time.

[1444] Step 10:

[1445] The server analyzes the data sent from the emotion engine and recognizes the current emotional state. For example, it recognizes that the user is "feeling stressed."

[1446] Step 11:

[1447] The user inputs their current location and destination into the application (e.g., from home to the train station).

[1448] Step 12:

[1449] The terminal transmits the entered current location and destination information to the server.

[1450] Step 13:

[1451] The server generates multiple routes including stopover spots based on the current location, destination, user preference information, and emotion data.

[1452] Step 14:

[1453] The server transmits the generated routes to the terminal.

[1454] Step 15:

[1455] The device displays the generated route in a user interface, where the user can select options such as "exercise first" or "fun first."

[1456] Step 16:

[1457] When the user selects an option, the terminal transmits the selection to the server.

[1458] Step 17:

[1459] The server re-evaluates multiple routes based on the selected options and the current emotional state and selects the optimal route.

[1460] Step 18:

[1461] The server transmits the optimized route information to the terminal.

[1462] Step 19:

[1463] The terminal displays the optimal route on the user interface, and the user confirms it and prepares to depart.

[1464] Step 20:

[1465] The device activates the navigation function and guides the user along the optimal route.

[1466] Step 21:

[1467] (Application of advertising business)

[1468] The server generates relevant advertising information based on the user's preference information and emotional state and incorporates it into the route.

[1469] Step 22:

[1470] The terminal displays the route with advertisements on a user interface.

[1471] Step 23:

[1472] The user selects stops of interest based on the advertisements displayed.

[1473] Through the above processing steps, the system can utilize the user's personal information and emotional state to provide the optimal route to make the travel process more meaningful and enjoyable.

[1474] Example 2

[1475] 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."

[1476] Conventional travel route generation systems do not take into account the user's personal information or emotional state, making it difficult to propose optimal travel routes that suit the user's preferences and current mood. Furthermore, they lack real-time emotion recognition and adaptation, making it difficult to improve user satisfaction. The present invention aims to solve these problems by providing a system that generates and proposes optimal travel routes based on the user's personal information and emotional state.

[1477] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting personal information of a user, means for encrypting the collected personal information and transmitting it via a network, means for storing the encrypted information in a database, means for acquiring the personal information from the database and performing data cleaning, means for analyzing the user's preferences and behavioral patterns based on the cleaned data, means for generating and training different artificial intelligence models based on the analysis results, means for recognizing emotions using the user's facial expressions, voice, and touch input, means for analyzing the recognized emotion data and identifying the user's current emotional state, means for generating multiple routes including stop-off spots based on information about the user's current location and destination, means for proposing an optimal route from the generated routes in accordance with an option selected by the user, and means for displaying the provided route on a user interface. This makes it possible to generate and suggest travel routes suited to the user's preferences and emotional state.

[1478] "User's personal information" means information relating to the User personally, such as the User's hobbies, interests, favorite places, frequently visited places and events of interest.

[1479] "Encryption" refers to a security technology that converts data so that it cannot be viewed illegally by third parties.

[1480] "Transmitting over a network" means the act of sending data over a communications network, including the Internet.

[1481] "Storing in a database" means storing data in a data storage system that systematically accumulates and manages information.

[1482] "Data cleaning" refers to the process of detecting outliers and missing values ​​in data and then performing processes such as deletion, completion, and correction to improve the quality of the data.

[1483] "Analysis of preferences and behavioral patterns" refers to the process of analyzing a user's preferences and behavioral patterns based on the user's personal information.

[1484] "Generating and training an artificial intelligence model" refers to the process of building an AI model based on data and then applying a learning algorithm to that model to improve its performance.

[1485] "Emotion recognition" refers to technology that determines a user's emotional state based on information such as the user's facial expressions, voice, and touch input.

[1486] "Analyzing emotional data and identifying emotional state" refers to the process of analyzing the data obtained from emotion recognition and identifying the emotion the user is currently feeling.

[1487] "Generating a route based on information about the current location and destination" refers to the operation of calculating the optimal travel route based on information about the departure point and arrival point set by the user.

[1488] "Spots to stop off at" refer to points along the way or potential destinations that are likely to interest the user.

[1489] "Proposing the best route based on options" refers to the process of recommending the most suitable route from among multiple route candidates based on setting options that the user can select.

[1490] "Displaying on the user interface" means the operation of displaying the generated route information on the display screen of the application.

[1491] The present invention is a system that generates and proposes optimal travel routes based on the user's preferences and emotions. This system is mainly composed of a server, a terminal, a user, and an emotion engine.

[1492] First, a user enters their hobbies and places of interest (e.g., cafes, movie theaters, running courses) through a smartphone application. This information is collected by the device and encrypted using an encryption algorithm (e.g., AES-256). The device then sends the encrypted data to a server. The server receives this data and stores it in a database (e.g., MySQL).

[1493] Next, the server retrieves personal information from the database and performs data cleaning. Data cleaning includes outlier detection and completion, and missing data handling. Specifically, an outlier detection algorithm is used to complete missing data with the mean or median. Based on this cleaned data, the server analyzes the user's preferences and behavioral patterns using machine learning algorithms (e.g., k-means clustering and collaborative filtering). The analysis results are used to generate different artificial intelligence models (e.g., using TensorFlow), which the AI ​​uses to learn.

[1494] For the emotion engine, the user inputs facial expressions and voice using the smartphone's camera and microphone. The device collects this emotion data and sends it to the server. The server then uses the emotion engine (using OpenCV or Pytorch, for example) to analyze the data and identify the user's current emotional state. For example, if the user is feeling stressed, the system will prioritize suggestions for relaxing cafes or parks.

[1495] To generate a route, the user inputs information about the starting point and destination through the application. For example, the input might be "from home to the station." The device then sends this information to the server, which then uses a map database (e.g., Google Maps API) to generate multiple routes. These routes include interesting stops (e.g., cafes, movie theaters, running courses) based on the user's preferences and emotional state.

[1496] The generated route is displayed on the user interface by the device. The user selects an option such as "exercise priority" or "fun priority." The option information selected by the user is sent back from the device to the server, and the server reevaluates the route based on the selected option and the user's current emotional state, selecting the optimal route. The server then sends the optimized route information to the device, which displays it on the user interface.

[1497] Examples of specific prompts include:

[1498] "Please enter places of interest or hobbies of the user (e.g., cafes, movie theaters, running trails)."

[1499] "Please enter your current location and destination (e.g. from home to the station)."

[1500] "Choose the exercise-first or fun-first option."

[1501] These procedures make it possible to generate and suggest travel routes that suit the user's preferences and emotional state.

[1502] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1503] Step 1: Collecting User Personal Information

[1504] A user starts a smartphone application and enters their hobbies and places of interest, such as their favorite cafe, movie theater, or running course, into an input box.

[1505] Input: User's hobbies and places of interest

[1506] Output: Raw personal information data

[1507] The device collects personal information entered, which is then encrypted using an encryption algorithm (e.g., AES-256).

[1508] Input: Raw personal information data

[1509] Output: Encrypted personal information data

[1510] The terminal transmits the encrypted personal information data to the server.

[1511] Input: Encrypted personal information data

[1512] Output: Encrypted data sent to the server

[1513] Step 2: Saving and cleaning user information

[1514] The server receives the encrypted data and stores it in a database (e.g. MySQL).

[1515] Input: Encrypted personal information data

[1516] Output: Information stored in the database

[1517] The server retrieves personal information from the database and performs data cleaning, detecting outliers and filling in missing data.

[1518] Input: Personal information retrieved from a database

[1519] Output: Cleaned personal information data

[1520] Step 3: Analyze preferences and behavioral patterns

[1521] The server analyzes user preferences and behavioral patterns based on the cleaned data, using machine learning algorithms (e.g., k-means clustering, collaborative filtering).

[1522] Input: Cleaned personal information data

[1523] Output: Analysis results of user preferences and behavior patterns

[1524] The server generates and trains a different artificial intelligence model (e.g., using TensorFlow) based on the analysis results.

[1525] Input: Analysis results of user preferences and behavior patterns

[1526] Output: A trained AI model

[1527] Step 4: Activate the Emotion Engine

[1528] The user uses the smartphone's camera and microphone to input facial expressions and voice data into the emotion engine.

[1529] Input: User's facial expression data and voice data

[1530] Output: Collected emotion data

[1531] The device collects emotional data and transmits it to a server in real time.

[1532] Input: Collected emotion data

[1533] Output: Emotion data sent to the server

[1534] The server analyzes the received emotion data and identifies the user's current emotional state (e.g., using OpenCV or Pytorch).

[1535] Input: Emotion data sent to the server

[1536] Output: The user's current emotional state

[1537] Step 5: Generate a path

[1538] The user inputs the departure and arrival points through a smartphone application (e.g., "from home to the station").

[1539] Input: Current location and destination information

[1540] Output: Location information entered into the device

[1541] The device transmits the input location information to the server.

[1542] Input: Location information entered on the device

[1543] Output: Location information sent to the server

[1544] The server generates multiple routes based on all data (personal information, emotional state) including the above information, using a map database (e.g., Google Maps API).

[1545] Input: current location, destination, personal information, emotional state

[1546] Output: Multiple generated routes

[1547] Step 6: Optimal Route Suggestion

[1548] The terminal displays the generated route on a user interface, and the user selects an option such as "exercise priority" or "fun priority."

[1549] Input: Multiple generated routes

[1550] Output: The route displayed in the user interface

[1551] The user selects the desired option and transmits the selection information from the terminal to the server.

[1552] Input: User's selection information (exercise priority, fun priority)

[1553] Output: Selections sent to the server

[1554] The server re-evaluates multiple routes and selects the best route based on the selected options and current emotional state.

[1555] Input: Selection information, emotional state

[1556] Output: Re-evaluated optimal path

[1557] The server sends the optimized route information to the terminal, which displays it on a user interface.

[1558] Input: Re-evaluated optimal path

[1559] Output: The optimal route displayed in the user interface

[1560] (Application example 2)

[1561] 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."

[1562] Conventional navigation systems mainly propose the shortest route to a destination based on the user's basic behavioral patterns. However, they do not offer optimal route suggestions that take into account the user's emotional state and preferences, making it difficult for users to have a travel experience that matches their mood and interests at the time. Therefore, there is a demand for a system that provides a comfortable and enjoyable travel experience based on the user's emotional state and preferences while traveling.

[1563] The identification processing 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 collecting personal information of the user, means for analyzing the collected personal information and understanding the user's preferences, means for generating multiple routes including stop-off spots based on information about the user's current location and destination, means for proposing an optimal route from the generated routes in accordance with an option selected by the user, means for displaying the provided route on a user interface, means for detecting the user's facial expressions and voice in real time using a camera and microphone mounted in the vehicle and collecting emotional data, means for identifying the user's current emotional state based on the collected emotional data, and means for optimizing the generated route based on the user's emotional state and preferences. This allows the server to provide an optimal travel route based on the user's emotional state and preferences, enabling a comfortable and enjoyable travel experience.

[1564] "User's personal information" is personal information about the user, such as the user's hobbies, favorite places, places that the user frequently visits, and events that interest the user.

[1565] "Tastes" refer to the preferences and tastes that are expressed by the things that a user likes or has interests.

[1566] A "stop-off spot" is a place or facility where a user can stop off during their travels.

[1567] "Current location" refers to the physical location where the user is currently located.

[1568] A "destination" is a location that a user is trying to reach.

[1569] "Options" are multiple choices or settings that a user can choose from.

[1570] The "route" refers to the route from the current location to the destination.

[1571] A "user interface" refers to a screen or device that allows a user to operate a system.

[1572] A "camera" is a device for taking images or videos.

[1573] A "microphone" is a device for recording sound.

[1574] "Emotion data" is information that indicates the user's emotional state, and is data collected from facial expressions and voice.

[1575] "Emotional state" refers to the mood or emotion that a user is currently experiencing.

[1576] "Optimization" means taking multiple conditions into consideration to derive the most suitable result.

[1577] The system that realizes this application example is an "emotional navigation system" installed in an autonomous vehicle. This system generates and suggests optimal routes based on the user's preferences and emotional state. The following describes an embodiment of this system.

[1578] The server collects and analyzes personal information about the user, who uses the in-vehicle interface to input information such as hobbies, favorite places, and events of interest. This information is stored in the vehicle system, encrypted, and synchronized to a cloud server.

[1579] The cloud server cleans the collected user information, analyzes the user's behavioral patterns and preferences, and generates and trains an AI model for each user based on that information.The data analysis tools used are Python's Pandas and Numpy, and the AI ​​models are TensorFlow and PyTorch.

[1580] Next, cameras and microphones mounted on the vehicle capture the user's facial expressions and voice in real time to collect emotional data, which is then analyzed using an emotion recognition engine (e.g., Affectiva SDK) to identify the user's current emotional state (e.g., enjoying, stressed).

[1581] When a user inputs their current location and destination into the vehicle's interface or smartphone app, the information is sent to a cloud server, which then generates an optimal route based on the user's information and emotional state, taking into account stopovers based on the user's preferences.

[1582] For example, if a user specifies a route from home to the station and wishes to relax, the cloud server will suggest a route that passes through cafes and parks where the user can relax. An example of a prompt sentence for a generative AI model is as follows:

[1583] "Please suggest routes that pass through recommended cafes and parks when the user wants to relax. The user's hobby is visiting cafes."

[1584] Finally, the generated routes are displayed on the user interface, and the user can select options such as "exercise first" or "relaxation first." The cloud server reevaluates the optimal route based on the selected option and the latest emotional state data, and sends the updated route information to the vehicle, providing a travel route that best suits the user's current emotional state and interests.

[1585] This system allows users to have a comfortable and enjoyable experience while traveling, and can provide added value not available in conventional navigation systems.

[1586] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1587] Step 1:

[1588] The user uses the in-vehicle interface to input personal information such as their hobbies, favorite places, and events of interest. The input information is stored in the vehicle system, encrypted, and synchronized to a cloud server, where the user's personal information is securely transmitted.

[1589] Step 2:

[1590] The server stores the user's personal information sent to the cloud server in a database. After storing the information, the server cleans the data, removing outliers and missing values, and converting it into a format suitable for analysis. This results in clean data that can be analyzed.

[1591] Step 3:

[1592] The server processes the cleaned data to analyze the user's behavioral patterns and preferences. For example, it uses Python's Pandas or Numpy to organize the data. After this, it generates an AI model for each user based on the data and trains it using TensorFlow or PyTorch. The analysis results in an individual AI model that reflects each user's preferences.

[1593] Step 4:

[1594] Cameras and microphones installed in the vehicle capture the user's facial expressions and voice in real time to collect emotional data. An emotion recognition engine (e.g., Affectiva SDK) is used to analyze the collected data and identify the user's current emotional state, resulting in real-time emotional state data.

[1595] Step 5:

[1596] The user inputs their current location and destination into the vehicle's interface or smartphone app. This information is sent to a cloud server, which then generates multiple routes based on the user's information and emotional state. Multiple routes, including stopovers, are calculated based on the user's preferences.

[1597] Step 6:

[1598] The server generates multiple routes and proposes the optimal route based on the user's selection. When the user selects an option such as "exercise priority" or "relaxation priority," the server reevaluates and optimizes the route based on the selected option and the user's latest emotional state data. The optimized route information is stored on the cloud server.

[1599] Step 7:

[1600] The device displays the optimized route on the vehicle's user interface. The user can confirm the proposed optimal route and, if they agree, the vehicle will begin autonomous driving according to that route. This allows the vehicle to travel along a route that best suits the user's emotional state and preferences.

[1601] Through these steps, the user can have a comfortable and enjoyable travel experience. An example of a prompt sentence for the generative AI model is, "Please suggest a route that passes through recommended cafes and parks when the user wants to relax. The user's hobby is visiting cafes."

[1602] 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.

[1603] 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.

[1604] 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.

[1605] [Fourth embodiment]

[1606] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1607] 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.

[1608] 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).

[1609] 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.

[1610] 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.

[1611] 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).

[1612] 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.

[1613] 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.

[1614] 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.

[1615] 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.

[1616] 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.

[1617] 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.

[1618] 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."

[1619] This invention is a system that generates and proposes optimal travel routes based on the user's preferences. This system is mainly composed of three elements: a server, a terminal, and a user.

[1620] Overall Overview

[1621] 1. Collection of User's Personal Information

[1622] Users enter personal information such as their favorite cafes, frequently visited spots, and events they are interested in through a smartphone app.

[1623] The device collects this information and sends it to the server in encrypted form.

[1624] The server stores the received information in a database.

[1625] 2. Analysis of user information

[1626] The server retrieves the user's personal information from the database, cleans the data, and then analyzes the user's preferences and behavioral patterns.

[1627] The server generates an AI model based on these analysis results and identifies each user's preferences.

[1628] 3. Route Generation

[1629] The user enters their current location and destination into the application.

[1630] The terminal sends the input data to the server.

[1631] The server generates multiple routes based on the user's current location, destination, and preferences, including stopovers that the user may be interested in.

[1632] The device displays the generated route to the user and allows the user to select the option of "exercise first" or "fun first."

[1633] 4. Optimal route suggestions

[1634] When the user selects an option, the terminal sends the information to the server.

[1635] The server will re-evaluate the routes based on the options and choose the best one.

[1636] The server sends the optimized route to the terminal, which displays it to the user.

[1637] Processing details and examples

[1638] Collection of Personal Information

[1639] Information users enter includes their favorite cafe (e.g., Blue Bottle Coffee), the gym they frequently visit, and upcoming music events.

[1640] The terminal receives these inputs, encrypts them, and sends them to the server.

[1641] The server decrypts the received information and stores it in a database.

[1642] User information analysis

[1643] The server retrieves user information from the database and performs data cleaning to remove outliers and missing values.

[1644] The server analyzes the user's preferences (e.g., cafe hopping, running, music) and reflects them in the AI ​​model.

[1645] The server continually updates the analysis results, keeping track of the user's latest preferences.

[1646] Route generation

[1647] The user inputs the destination "from home to the station."

[1648] The terminal sends the information to the server.

[1649] The server generates multiple routes including stopover spots (e.g., cafes, jogging courses) based on the user's current location, destination, and preference information.

[1650] The device displays the generated route on a user interface and allows the user to select options such as "exercise first" or "fun first."

[1651] Optimal route suggestions

[1652] When the user selects, for example, "Enjoyment Priority," the terminal transmits the selection to the server.

[1653] The server re-evaluates multiple routes based on the selection and selects the best route.

[1654] The server sends the optimized route to the terminal, which displays it to the user.

[1655] Ad business applications

[1656] The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[1657] The terminal displays the route with advertisements on a user interface.

[1658] The user may be interested in the displayed advertisement and may select a stop-off spot based on this interest.

[1659] As described above, the system of the present invention utilizes user preference information to optimize travel routes, thereby enabling users to spend their travel time meaningfully.

[1660] The processing flow will be explained below.

[1661] Step 1:

[1662] Users open the smartphone app and enter personal information such as their favorite cafes, frequently visited places, and events they are interested in through a registration profile.

[1663] Step 2:

[1664] The terminal collects personal information entered by the user and encrypts the data.

[1665] Step 3:

[1666] The terminal transmits the encrypted personal information to the server.

[1667] Step 4:

[1668] The server receives the encrypted data, decrypts it, and stores it in a database.

[1669] Step 5:

[1670] The server retrieves the user's personal information from the database and cleans the data, specifically by detecting and processing outliers and missing values.

[1671] Step 6:

[1672] The server uses the cleaned data to run algorithms that analyze user preferences and behavioral patterns.

[1673] Step 7:

[1674] Based on the analysis results, the server generates and trains a different AI model for each user.

[1675] Step 8:

[1676] The user inputs their current location and destination into the application (e.g., from home to the train station).

[1677] Step 9:

[1678] The terminal transmits the current location and destination information input by the user to the server.

[1679] Step 10:

[1680] The server generates multiple routes based on the user's current location, destination, and analyzed user preferences, including stopovers that may be of interest to the user.

[1681] Step 11:

[1682] The server transmits the generated routes to the terminal.

[1683] Step 12:

[1684] The device displays the generated route on a user interface, and the user can select options such as "exercise first" or "fun first."

[1685] Step 13:

[1686] The user selects an option (e.g., "Fun First").

[1687] Step 14:

[1688] The terminal sends the user's selected option to the server.

[1689] Step 15:

[1690] Based on the selected option, the server re-evaluates multiple routes and selects the best one.

[1691] Step 16:

[1692] The server sends the optimal route information to the terminal.

[1693] Step 17:

[1694] The terminal displays the optimal route on the user interface.

[1695] Step 18:

[1696] The user checks the displayed route and selects the route that best suits their preferences.

[1697] Step 19:

[1698] The device activates the navigation function and guides the user along the optimal route.

[1699] Step 20:

[1700] (Advertising business as an example)

[1701] The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[1702] Step 21:

[1703] The terminal displays the route with advertisements on a user interface.

[1704] Step 22:

[1705] The user is interested in the displayed advertisement and selects a stopover spot.

[1706] Example 1

[1707] 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."

[1708] Conventional travel route generation systems are limited to basic route search without fully considering the user's personal information and preferences. This makes it difficult to provide an optimal route that matches the user's interests and preferences. In addition, when a user's interests change, the system is unable to quickly reflect those changes, making it difficult to propose a route based on the latest information. Furthermore, from a commercial perspective, advertisements based on the user's preferences are not effectively displayed. To solve these problems, a system is needed that can understand and dynamically update the user's preferences to generate a more optimal travel route while also effectively providing related advertising information.

[1709] 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.

[1710] In this invention, the server includes a means for encrypting the user's personal information and transmitting it to the server, a means for storing the personal information received by the server in a database, and a means for retrieving the user's personal information from the database and performing data cleaning. This makes it possible to analyze the user's preferences and propose an optimal route based on dynamically updated information. Furthermore, the system has a function for selecting an option to prioritize exercise or fun in the user interface and a function for displaying related advertising information, providing a travel route that reflects the user's latest interests.

[1711] "User" refers to a person who uses the system to optimize their travel route.

[1712] "Personal information" refers to personal information such as a user's hobbies and interests, favorite spots, and frequently visited places.

[1713] "Terminal" refers to an electronic device such as a smartphone or tablet operated by a user.

[1714] "Server" means the central processing unit that receives, stores, and analyzes User's personal information.

[1715] "Database" means an electronic storage device for storing collected personal information about users.

[1716] "Data cleaning" refers to the process of removing irrelevant data and missing values ​​from a dataset and preparing it for analysis.

[1717] An "AI model" refers to a mathematical model that uses machine learning algorithms to analyze and predict user preferences.

[1718] "Route" refers to information showing the route from the user's current location to the destination.

[1719] The "route generation means" refers to a mechanism for calculating multiple routes based on the user's current location, destination, and user preference information.

[1720] "Route suggestion means" refers to a mechanism that selects and suggests the optimal route from multiple generated routes according to the user's selection.

[1721] "User interface" refers to the display screen and input means that users use to operate the system through a terminal.

[1722] "Option selection means" refers to a mechanism that allows users to select options such as "exercise priority" or "fun priority."

[1723] "Advertising information" refers to commercial information displayed based on the user's preferences.

[1724] "Encryption" refers to the process of converting data, such as personal information, for security purposes, making it unavailable to third parties.

[1725] A "generative AI model" refers to an algorithm that uses artificial intelligence technology to analyze user behavior and preferences and generate new data patterns.

[1726] A "prompt" is a command or question entered into a system to request a specific action or piece of information.

[1727] This invention is a system that generates and proposes optimal travel routes based on the user's preferences. This system is mainly composed of three elements: a server, a terminal, and a user. Each element and its role are explained in detail below.

[1728] server

[1729] The server plays an important role in receiving, storing, and analyzing the user's personal information and generating the optimal travel route.

[1730] Data Receipt and Decryption: Personal information sent by users arrives at the server in encrypted form. The server decrypts the information and stores it securely in a database. Specifically, encryption algorithms such as AES-256 can be used.

[1731] Database management: The server stores the received personal information in a database (e.g., MySQL or PostgreSQL). The database assigns a unique ID to each user and manages each user's information.

[1732] Data cleaning: Data cleaning is performed to remove inappropriate data and missing values ​​from the information obtained from the database.

[1733] Creation and analysis of AI models: To analyze user preferences, the server creates an AI model using machine learning libraries (e.g., TensorFlow or PyTorch). This model is used to identify and analyze individual user behavior patterns and preferences.

[1734] Route generation: The server generates multiple routes using a route search algorithm (e.g., Dijkstra or A algorithm) based on the user's current location, destination, and preference information.

[1735] Route proposal: From the generated routes, the optimal route is selected and proposed based on the user's selection (e.g., "exercise first" or "fun first").

[1736] Generating advertising information: The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[1737] Terminal

[1738] The terminal is an electronic device such as a smartphone or tablet that is operated by a user.

[1739] Information collection and transmission: Personal information entered by the user is collected, encrypted, and transmitted to the server. An encryption library (e.g., OpenSSL) can be embedded in the terminal.

[1740] User interface: The device displays the generated route on the user interface and presents the user with options such as "exercise priority" or "fun priority."

[1741] Sending selection information: The options selected by the user are encrypted and sent to the server.

[1742] Display Advertisements: Displays advertising information sent from the server and allows users to access more information.

[1743] User

[1744] A user is a person who uses the system to optimize a travel route.

[1745] Information input: Users input their preferences and interests (such as their favorite cafe, frequently visited gym, upcoming music events, etc.) through a smartphone app.

[1746] Setting current location and destination: The user sets their current location and destination within the app and sends them to the server via their device.

[1747] Select an option: Select the option you want from the options displayed on your device (e.g., "Prioritize exercise" or "Prioritize fun").

[1748] Examples of concrete examples and prompts

[1749] Specific examples

[1750] A user enters into the app, "I like Blue Bottle Coffee," "I go to the gym every weekend," and "I'll attend the next music festival."

[1751] The device encrypts the information and sends it to the server.

[1752] The server decrypts the received personal information and stores it in a database.

[1753] The server retrieves information from the database and analyzes that "cafe hopping" is a hobby.

[1754] When the user enters "from home to the station," the device sends the information to the server.

[1755] The server generates a route based on the user's preferences and suggests a route that includes "Blue Bottle Coffee."

[1756] The terminal displays the route and the user selects "Enjoyment priority."

[1757] The server selects the optimal route and the device displays it.

[1758] The server generates advertisements related to "cafe hopping" and the device displays them.

[1759] Prompt Sentence Examples

[1760] "Please tell me the route from your house to the station, including recommended cafes and jogging courses. Please also include options for routes that prioritize exercise."

[1761] As described above, this system utilizes user preference information to optimize travel routes, allowing users to spend their travel time meaningfully.

[1762] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1763] Step 1:

[1764] The user launches the smartphone app and enters their personal information (e.g., favorite cafe, frequently visited spots).

[1765] Input: Personal information such as the user's hobbies and interests

[1766] Action: The user performs an action to enter information into a form within the app.

[1767] Output: The personal information entered is saved on the device.

[1768] Step 2:

[1769] The terminal encrypts the user's personal information and sends it to the server.

[1770] Input: User's personal information

[1771] Processing: The device encrypts the data using an encryption algorithm such as AES-256 and sends it to the server in a secure HTTP request.

[1772] Output: Encrypted personal information is sent to the server.

[1773] Step 3:

[1774] The server receives the encrypted personal information, decrypts it, and stores it in a database.

[1775] Input: Encrypted personal information

[1776] Processing: The server decrypts the received data and stores it in a database, where each user is assigned a unique ID.

[1777] Output: Personal information decrypted and stored in a database

[1778] Step 4:

[1779] The server retrieves user information from the database and performs data cleaning.

[1780] Input: Personal information stored in the database

[1781] Processing: The server executes database queries to retrieve information and then performs a data cleaning process to remove irrelevant data and missing values.

[1782] Output: Cleaned user information

[1783] Step 5:

[1784] The server analyzes the user's preferences and generates an AI model.

[1785] Input: Cleaned user information

[1786] Processing: The server uses machine learning libraries such as TensorFlow and PyTorch to generate an AI model to analyze user preferences and perform the analysis.

[1787] Output: User preference information

[1788] Step 6:

[1789] The user enters their current location and destination through the app.

[1790] Input: Current location and destination information

[1791] Action: The user performs an action to enter information into an input field in the app.

[1792] Output: Current location and destination information is saved on the device.

[1793] Step 7:

[1794] The device encrypts the current location and destination information entered and sends it to the server.

[1795] Input: Current location and destination information

[1796] Processing: The device encrypts the information and sends it to the server in a secure HTTP request.

[1797] Output: Encrypted current location and destination information is sent to the server.

[1798] Step 8:

[1799] The server generates a route based on the user's current location, destination, and preference information.

[1800] Input: Encrypted current location and destination information, user preferences

[1801] Processing: The server interprets the information and generates multiple possible routes using a geographic information system (GIS) and route planning algorithms.

[1802] Output: Multiple route candidates

[1803] Step 9:

[1804] The device displays the generated route on a user interface and allows the user to select options such as "exercise first" or "fun first."

[1805] Input: Multiple route candidates

[1806] Processing: The terminal displays the route information received from the server on the user interface and presents options to the user.

[1807] Output: Route information and option choices displayed to the user

[1808] Step 10:

[1809] The user selects an option.

[1810] Input: The option selected by the user (e.g., "Enjoyment first")

[1811] Processing: The user selects an option through the terminal interface.

[1812] Output: Selected option information

[1813] Step 11:

[1814] The terminal encrypts the selected option information and transmits it to the server.

[1815] Input: The option selected by the user

[1816] Processing: The terminal encrypts the selected information and sends it to the server.

[1817] Output: The encrypted selection information is sent to the server.

[1818] Step 12:

[1819] The server reevaluates based on the selection information and selects the optimal route.

[1820] Input: Encrypted selection information, route candidates

[1821] Processing: The server decodes the selection information and uses AI models to re-evaluate route options and select the optimal route.

[1822] Output: Information on the best route

[1823] Step 13:

[1824] The server transmits optimal route information to the terminal, which then displays it to the user.

[1825] Input: Optimal route information

[1826] Processing: The server sends the optimal route information to the terminal, which displays it on the user interface.

[1827] Output: The optimal route is displayed on the user's device.

[1828] Step 14:

[1829] The server generates relevant advertising information based on the user's preferences and incorporates it into the route.

[1830] Input: User preferences

[1831] Processing: The server generates relevant advertising information based on the preference information and incorporates it into the selected route.

[1832] Output: Route information incorporating advertising information

[1833] Step 15:

[1834] The terminal displays the optimal route with advertisements on the user interface.

[1835] Input: Optimal route incorporating advertising information

[1836] Processing: The terminal displays the displayed information on the user interface.

[1837] Output: The optimal route information with advertisements is displayed to the user.

[1838] (Application example 1)

[1839] 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."

[1840] Conventional travel route generation systems simply provide the shortest or fastest route without fully utilizing the user's personal information and preferences. This makes it difficult to provide an optimal route that includes attractions and other interesting stops that the user wants to enjoy during their trip. Furthermore, even in autonomous vehicles, personalized navigation based on the user's preferences has not been provided.

[1841] 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.

[1842] In this invention, the server includes means for collecting personal information of a user, means for analyzing the collected personal information and understanding the user's preferences, means for generating multiple routes including stop-off spots based on information on the user's current location and destination, means for proposing an optimal route from the generated routes in accordance with an option selected by the user, means for displaying the provided route on a user interface, means for providing the above route in a navigation system for an autonomous vehicle, and means for generating an AI model for route proposals based on the user's preferences. This allows the user to not only reach their destination but also enjoy a personalized travel experience, and enables flexible navigation based on the user's preferences even in autonomous vehicles.

[1843] "User's personal information" is information that represents individual characteristics of the user, such as the user's tastes, interests, and past behavioral history.

[1844] A "user interface" is the part of a system that includes display and input devices through which a user interacts with the system.

[1845] An "autonomous vehicle" is a vehicle that uses systems or algorithms to drive itself automatically without a human driver.

[1846] A "navigation system" is a device or system that provides a user with the optimal route to reach their destination.

[1847] An "AI model" is a mathematical model that uses artificial intelligence technology to analyze data and apply the results.

[1848] "Route proposal" is the act of generating multiple routes from the user's current location to the destination, selecting the most suitable one, and presenting it.

[1849] A "stop-off spot" is a place or facility that a user can visit on the way while traveling.

[1850] "Selectable options" are route conditions and characteristics that a user can choose depending on their preferences and purpose.

[1851] "Collection means" refers to the functions and methods for acquiring user information.

[1852] "Analysis tools" are functions and methods for processing collected data and extracting meaningful information.

[1853] "Generation means" refers to functions or methods for creating new data or results based on user information or conditions.

[1854] "Display means" refers to a device or method for visually conveying generated information or results to a user.

[1855] The present invention relates to a system for generating and proposing optimal travel routes based on user preferences, which is targeted at autonomous vehicles and provides a personalized travel experience.

[1856] System configuration

[1857] This system mainly consists of three elements: a server, a terminal (smartphone or in-vehicle device), and a user.

[1858] 1. Collection of User's Personal Information:

[1859] Users enter personal information such as their favorite cafes, frequently visited spots, and events they are interested in through a smartphone app. The device collects this information and sends it in a securely encrypted format to a server, which then stores the information in a database.

[1860] 2. Analysis of User Information:

[1861] The server retrieves the user's personal information from the database, cleans the data, and then analyzes the user's preferences and behavioral patterns. Based on this, an AI model is generated to identify each user's preferences.

[1862] 3. Pathway Generation:

[1863] The user inputs their current location and destination into the application. The device then sends this input data to the server. The server generates multiple routes based on the current location, destination, and the user's preferences, including stopovers that the user may be interested in. The device displays the generated routes on a user interface, allowing the user to select options such as "exercise priority" or "fun priority."

[1864] 4. Optimal route suggestions:

[1865] Once the user selects an option, the device sends that information to the server, which reevaluates routes based on the options and selects the best one. The server then sends the optimized route to the device, which displays it to the user.

[1866] Hardware and software used

[1867] Hardware:

[1868] In-Vehicle Information System (IVI)

[1869] Smartphone

[1870] Autonomous vehicle sensors (GPS, LiDAR, cameras, etc.)

[1871] software:

[1872] Server applications (AWS, GCP)

[1873] Database (MySQL, Postgres)

[1874] Cryptography library (PyCryptodome)

[1875] HTTP client (requests)

[1876] Specific examples

[1877] For example, if the user selects "Strolling first," the server can suggest multiple routes that include the following spots:

[1878] Recently opened cafes and restaurants

[1879] Highly rated parks

[1880] Historical Attractions

[1881] Example prompts to input to a generative AI model:

[1882] text

[1883] Design a system that suggests optimal routes for autonomous vehicles based on the user's preferences. Based on the following information, generate routes that allow the user to select the "Stroll first" option and display them in the navigation system. The user's personal information includes their favorite cafes and events of interest.

[1884] 1. User preferences (cafes, tourist spots, parks)

[1885] 2. Current location (starting point) and destination

[1886] 3. Route options (exercise first, fun first)

[1887] As described above, this system utilizes user preference information to personalize the travel experience even in autonomous vehicles.

[1888] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1889] Step 1:

[1890] Users use a smartphone app to input personal information such as their favorite cafes, frequently visited spots, and events they are interested in. The device collects this information, encrypts it, and sends it to a server. The input data includes the user's interests and behavioral history, and encrypted data is generated as output.

[1891] Step 2:

[1892] The server receives the encrypted data sent from the terminal, decrypts it, and stores it in the database. The server checks the integrity of the initial data and stores it in the database. The input data is encrypted user information, and the output is user personal information stored in the database.

[1893] Step 3:

[1894] The server retrieves the user's personal information from the database and performs data cleaning. After eliminating outliers and missing data, it performs analysis to identify the user's preferences and behavioral patterns. An AI model is generated based on the analysis results, and a new user profile is created. The input data is the user's personal information, and the output is the generated AI model and user profile.

[1895] Step 4:

[1896] The user inputs their current location and destination into a smartphone app or on the in-car display. The device then sends this information to the server. The input data is the current location and destination information, and the output is the route request data sent to the server.

[1897] Step 5:

[1898] The server generates multiple routes based on the user's current location, destination, and preference information. The server uses an AI model to calculate a route that includes stops that the user may be interested in. After the route is generated, the result is sent to the device. The input data is the route request data and the user's preference information, and the output is the multiple routes generated.

[1899] Step 6:

[1900] The device displays multiple generated routes on a user interface, and the user selects options such as "exercise priority" or "fun priority." The input data is the generated route, and the output is the route options presented to the user.

[1901] Step 7:

[1902] When a user selects an option, the terminal sends the option information to the server. The server reevaluates routes based on the selected option and selects the optimal route. The input data is the option information selected by the user, and the output is the reevaluated optimal route.

[1903] Step 8:

[1904] The server sends the optimal route to the terminal, which then displays it to the user. The optimized route is reflected in the navigation system of the autonomous vehicle. The input data is the re-evaluated optimal route, and the output is the optimized route presented to the user.

[1905] Through the above processing steps, the system can utilize user preference information to provide a personalized travel experience in an autonomous vehicle.

[1906] 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.

[1907] The present invention is a system that generates and proposes optimal travel routes based on the user's preferences and emotions. It is mainly composed of a server, a terminal, a user, and an emotion engine.

[1908] Overall Overview

[1909] 1. Collection of User's Personal Information

[1910] Users enter personal information such as their hobbies, favorite cafes, frequently visited places, and events they are interested in through a smartphone app.

[1911] The device collects this information, encrypts it, and sends it to the server.

[1912] The server stores the received information in a database.

[1913] 2. Analysis of user information

[1914] The server retrieves the user's personal information from the database and performs data cleaning, handling outliers and missing values, and preparing the data in a format suitable for analysis.

[1915] The server analyzes the user's preferences and behavioral patterns based on the cleaned data.

[1916] The server uses the analysis results to generate and train a different AI model for each user.

[1917] 3. Emotional Engine Activation

[1918] It activates an emotion engine that recognizes emotions in real time using the user's facial expressions, voice data, touch input, etc.

[1919] The device collects emotion data and sends it to the server.

[1920] The server analyzes this emotional data to determine the current emotional state (e.g., happy, stressed).

[1921] 4. Route Generation

[1922] The user enters their current location and destination into the application.

[1923] The terminal transmits this information to the server.

[1924] The server generates multiple routes based on the user's current location, destination, and data on the user's preferences and emotional state. The generated routes include stopover spots that are likely to interest the user.

[1925] 5. Option selection and optimal route suggestions

[1926] The device displays the generated route on a user interface and allows the user to select options such as "exercise first" or "fun first."

[1927] When the user selects an option, the selection is sent to the server.

[1928] The server re-evaluates multiple routes depending on the selected options and the current emotional state and selects the optimal route.

[1929] The server transmits the optimized route information to the terminal.

[1930] The terminal displays the optimal route on the user interface, allowing the user to review and select.

[1931] Processing details and examples

[1932] Collection and analysis of personal information

[1933] Users enter their favorite cafes and spots (e.g., movie theaters, running courses, restaurants) through the app.

[1934] The device encrypts this, and the server receives the data and stores it in a database.

[1935] The server cleans the data and analyzes user behavior patterns, and the analysis results are reflected in the AI ​​model.

[1936] Example of the Emotion Engine in action

[1937] The user uses their smartphone camera to recognize their facial expressions (e.g., smiling, tired).

[1938] The device collects emotional data and sends it to a server.

[1939] The server analyzes the data using an emotion engine to identify the user's current emotional state. For example, if the user is feeling stressed, the server suggests a route that passes through a relaxing cafe or park.

[1940] Route generation

[1941] The user enters the destination as "from home to the station."

[1942] The device sends information to a server, which then generates multiple routes based on the information. The routes include stops based on the user's preferences (e.g., cafe hopping) and emotional state (e.g., needing to relax).

[1943] Option selection and optimal route suggestions

[1944] The device displays the route and allows the user to select "exercise priority" or "fun priority" (e.g., select "fun priority").

[1945] The device sends the selection information to the server, which then reevaluates the route based on the options and emotional state.

[1946] The server sends the optimal route to the terminal, which then displays it to the user.

[1947] The user checks the optimal route and prepares to depart.

[1948] Ad business applications

[1949] The server generates relevant advertisements (e.g., spas that are effective for relieving stress) based on the user's preferences and emotional state and incorporates them into the route.

[1950] The terminal displays a route with advertisements, and the user selects stop-off spots based on the advertisements.

[1951] In this way, the system of the present invention can utilize the user's preference information and emotional state to suggest more appropriate and meaningful travel routes.

[1952] The processing flow will be explained below.

[1953] Step 1:

[1954] Users open the smartphone app and enter personal information such as hobbies, favorite cafes, frequently visited places, and events they are interested in on the profile screen.

[1955] Step 2:

[1956] The terminal collects personal information entered by the user and encrypts the data.

[1957] Step 3:

[1958] The terminal transmits the encrypted personal information to the server.

[1959] Step 4:

[1960] The server receives the encrypted data, decrypts it, and stores it in a database.

[1961] Step 5:

[1962] The server retrieves the user's personal information from the database and performs data cleaning, specifically detecting and formatting outliers and missing data.

[1963] Step 6:

[1964] The server analyzes the cleaned data to identify the user's preferences and behavioral patterns.

[1965] Step 7:

[1966] The server generates an AI model based on the analysis results and trains a model personalized for each user.

[1967] Step 8:

[1968] The user uses the app to show their face to the camera, and the emotion engine recognizes their facial expressions.

[1969] Step 9:

[1970] The device transmits emotion data to the emotion engine in real time.

[1971] Step 10:

[1972] The server analyzes the data sent from the emotion engine and recognizes the current emotional state. For example, it recognizes that the user is "feeling stressed."

[1973] Step 11:

[1974] The user inputs their current location and destination into the application (e.g., from home to the train station).

[1975] Step 12:

[1976] The terminal transmits the entered current location and destination information to the server.

[1977] Step 13:

[1978] The server generates multiple routes including stopover spots based on the current location, destination, user preference information, and emotion data.

[1979] Step 14:

[1980] The server transmits the generated routes to the terminal.

[1981] Step 15:

[1982] The device displays the generated route in a user interface, where the user can select options such as "exercise first" or "fun first."

[1983] Step 16:

[1984] When the user selects an option, the terminal transmits the selection to the server.

[1985] Step 17:

[1986] The server re-evaluates multiple routes based on the selected options and the current emotional state and selects the optimal route.

[1987] Step 18:

[1988] The server transmits the optimized route information to the terminal.

[1989] Step 19:

[1990] The terminal displays the optimal route on the user interface, and the user confirms it and prepares to depart.

[1991] Step 20:

[1992] The device activates the navigation function and guides the user along the optimal route.

[1993] Step 21:

[1994] (Application of advertising business)

[1995] The server generates relevant advertising information based on the user's preference information and emotional state and incorporates it into the route.

[1996] Step 22:

[1997] The terminal displays the route with advertisements on a user interface.

[1998] Step 23:

[1999] The user selects stops of interest based on the advertisements displayed.

[2000] Through the above processing steps, the system can utilize the user's personal information and emotional state to provide the optimal route to make the travel process more meaningful and enjoyable.

[2001] Example 2

[2002] 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."

[2003] Conventional travel route generation systems do not take into account the user's personal information or emotional state, making it difficult to propose optimal travel routes that suit the user's preferences and current mood. Furthermore, they lack real-time emotion recognition and adaptation, making it difficult to improve user satisfaction. The present invention aims to solve these problems by providing a system that generates and proposes optimal travel routes based on the user's personal information and emotional state.

[2004] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for collecting personal information of a user, means for encrypting the collected personal information and transmitting it via a network, means for storing the encrypted information in a database, means for acquiring the personal information from the database and performing data cleaning, means for analyzing the user's preferences and behavioral patterns based on the cleaned data, means for generating and training different artificial intelligence models based on the analysis results, means for recognizing emotions using the user's facial expressions, voice, and touch input, means for analyzing the recognized emotion data and identifying the user's current emotional state, means for generating multiple routes including stop-off spots based on information about the user's current location and destination, means for proposing an optimal route from the generated routes in accordance with an option selected by the user, and means for displaying the provided route on a user interface. This makes it possible to generate and suggest travel routes suited to the user's preferences and emotional state.

[2005] "User's personal information" means information relating to the User personally, such as the User's hobbies, interests, favorite places, frequently visited places and events of interest.

[2006] "Encryption" refers to a security technology that converts data so that it cannot be viewed illegally by third parties.

[2007] "Transmitting over a network" means the act of sending data over a communications network, including the Internet.

[2008] "Storing in a database" means storing data in a data storage system that systematically accumulates and manages information.

[2009] "Data cleaning" refers to the process of detecting outliers and missing values ​​in data and then performing processes such as deletion, completion, and correction to improve the quality of the data.

[2010] "Analysis of preferences and behavioral patterns" refers to the process of analyzing a user's preferences and behavioral patterns based on the user's personal information.

[2011] "Generating and training an artificial intelligence model" refers to the process of building an AI model based on data and then applying a learning algorithm to that model to improve its performance.

[2012] "Emotion recognition" refers to technology that determines a user's emotional state based on information such as the user's facial expressions, voice, and touch input.

[2013] "Analyzing emotional data and identifying emotional state" refers to the process of analyzing the data obtained from emotion recognition and identifying the emotion the user is currently feeling.

[2014] "Generating a route based on information about the current location and destination" refers to the operation of calculating the optimal travel route based on information about the departure point and arrival point set by the user.

[2015] "Spots to stop off at" refer to points along the way or potential destinations that are likely to interest the user.

[2016] "Proposing the best route based on options" refers to the process of recommending the most suitable route from among multiple route candidates based on setting options that the user can select.

[2017] "Displaying on the user interface" means the operation of displaying the generated route information on the display screen of the application.

[2018] The present invention is a system that generates and proposes optimal travel routes based on the user's preferences and emotions. This system is mainly composed of a server, a terminal, a user, and an emotion engine.

[2019] First, a user enters their hobbies and places of interest (e.g., cafes, movie theaters, running courses) through a smartphone application. This information is collected by the device and encrypted using an encryption algorithm (e.g., AES-256). The device then sends the encrypted data to a server. The server receives this data and stores it in a database (e.g., MySQL).

[2020] Next, the server retrieves personal information from the database and performs data cleaning. Data cleaning includes outlier detection and completion, and missing data handling. Specifically, an outlier detection algorithm is used to complete missing data with the mean or median. Based on this cleaned data, the server analyzes the user's preferences and behavioral patterns using machine learning algorithms (e.g., k-means clustering and collaborative filtering). The analysis results are used to generate different artificial intelligence models (e.g., using TensorFlow), which the AI ​​uses to learn.

[2021] For the emotion engine, the user inputs facial expressions and voice using the smartphone's camera and microphone. The device collects this emotion data and sends it to the server. The server then uses the emotion engine (using OpenCV or Pytorch, for example) to analyze the data and identify the user's current emotional state. For example, if the user is feeling stressed, the system will prioritize suggestions for relaxing cafes or parks.

[2022] To generate a route, the user inputs information about the starting point and destination through the application. For example, the input might be "from home to the station." The device then sends this information to the server, which then uses a map database (e.g., Google Maps API) to generate multiple routes. These routes include interesting stops (e.g., cafes, movie theaters, running courses) based on the user's preferences and emotional state.

[2023] The generated route is displayed on the user interface by the device. The user selects an option such as "exercise priority" or "fun priority." The option information selected by the user is sent back from the device to the server, and the server reevaluates the route based on the selected option and the user's current emotional state, selecting the optimal route. The server then sends the optimized route information to the device, which displays it on the user interface.

[2024] Examples of specific prompts include:

[2025] "Please enter places of interest or hobbies of the user (e.g., cafes, movie theaters, running trails)."

[2026] "Please enter your current location and destination (e.g. from home to the station)."

[2027] "Choose the exercise-first or fun-first option."

[2028] These procedures make it possible to generate and suggest travel routes that suit the user's preferences and emotional state.

[2029] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2030] Step 1: Collecting User Personal Information

[2031] A user starts a smartphone application and enters their hobbies and places of interest, such as their favorite cafe, movie theater, or running course, into an input box.

[2032] Input: User's hobbies and places of interest

[2033] Output: Raw personal information data

[2034] The device collects personal information entered, which is then encrypted using an encryption algorithm (e.g., AES-256).

[2035] Input: Raw personal information data

[2036] Output: Encrypted personal information data

[2037] The terminal transmits the encrypted personal information data to the server.

[2038] Input: Encrypted personal information data

[2039] Output: Encrypted data sent to the server

[2040] Step 2: Saving and cleaning user information

[2041] The server receives the encrypted data and stores it in a database (e.g. MySQL).

[2042] Input: Encrypted personal information data

[2043] Output: Information stored in the database

[2044] The server retrieves personal information from the database and performs data cleaning, detecting outliers and filling in missing data.

[2045] Input: Personal information retrieved from a database

[2046] Output: Cleaned personal information data

[2047] Step 3: Analyze preferences and behavioral patterns

[2048] The server analyzes user preferences and behavioral patterns based on the cleaned data, using machine learning algorithms (e.g., k-means clustering, collaborative filtering).

[2049] Input: Cleaned personal information data

[2050] Output: Analysis results of user preferences and behavior patterns

[2051] The server generates and trains a different artificial intelligence model (e.g., using TensorFlow) based on the analysis results.

[2052] Input: Analysis results of user preferences and behavior patterns

[2053] Output: A trained AI model

[2054] Step 4: Activate the Emotion Engine

[2055] The user uses the smartphone's camera and microphone to input facial expressions and voice data into the emotion engine.

[2056] Input: User's facial expression data and voice data

[2057] Output: Collected emotion data

[2058] The device collects emotional data and transmits it to a server in real time.

[2059] Input: Collected emotion data

[2060] Output: Emotion data sent to the server

[2061] The server analyzes the received emotion data and identifies the user's current emotional state (e.g., using OpenCV or Pytorch).

[2062] Input: Emotion data sent to the server

[2063] Output: The user's current emotional state

[2064] Step 5: Generate a path

[2065] The user inputs the departure and arrival points through a smartphone application (e.g., "from home to the station").

[2066] Input: Current location and destination information

[2067] Output: Location information entered into the device

[2068] The device transmits the input location information to the server.

[2069] Input: Location information entered on the device

[2070] Output: Location information sent to the server

[2071] The server generates multiple routes based on all data (personal information, emotional state) including the above information, using a map database (e.g., Google Maps API).

[2072] Input: current location, destination, personal information, emotional state

[2073] Output: Multiple generated routes

[2074] Step 6: Optimal Route Suggestion

[2075] The terminal displays the generated route on a user interface, and the user selects an option such as "exercise priority" or "fun priority."

[2076] Input: Multiple generated routes

[2077] Output: The route displayed in the user interface

[2078] The user selects the desired option and transmits the selection information from the terminal to the server.

[2079] Input: User's selection information (exercise priority, fun priority)

[2080] Output: Selections sent to the server

[2081] The server re-evaluates multiple routes and selects the best route based on the selected options and current emotional state.

[2082] Input: Selection information, emotional state

[2083] Output: Re-evaluated optimal path

[2084] The server sends the optimized route information to the terminal, which displays it on a user interface.

[2085] Input: Re-evaluated optimal path

[2086] Output: The optimal route displayed in the user interface

[2087] (Application example 2)

[2088] 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."

[2089] Conventional navigation systems mainly propose the shortest route to a destination based on the user's basic behavioral patterns. However, they do not offer optimal route suggestions that take into account the user's emotional state and preferences, making it difficult for users to have a travel experience that matches their mood and interests at the time. Therefore, there is a demand for a system that provides a comfortable and enjoyable travel experience based on the user's emotional state and preferences while traveling.

[2090] The identification processing 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 collecting personal information of the user, means for analyzing the collected personal information and understanding the user's preferences, means for generating multiple routes including stop-off spots based on information about the user's current location and destination, means for proposing an optimal route from the generated routes in accordance with an option selected by the user, means for displaying the provided route on a user interface, means for detecting the user's facial expressions and voice in real time using a camera and microphone mounted in the vehicle and collecting emotional data, means for identifying the user's current emotional state based on the collected emotional data, and means for optimizing the generated route based on the user's emotional state and preferences. This allows the server to provide an optimal travel route based on the user's emotional state and preferences, enabling a comfortable and enjoyable travel experience.

[2091] "User's personal information" is personal information about the user, such as the user's hobbies, favorite places, places that the user frequently visits, and events that interest the user.

[2092] "Tastes" refer to the preferences and tastes that are expressed by the things that a user likes or has interests.

[2093] A "stop-off spot" is a place or facility where a user can stop off during their travels.

[2094] "Current location" refers to the physical location where the user is currently located.

[2095] A "destination" is a location that a user is trying to reach.

[2096] "Options" are multiple choices or settings that a user can choose from.

[2097] The "route" refers to the route from the current location to the destination.

[2098] A "user interface" refers to a screen or device that allows a user to operate a system.

[2099] A "camera" is a device for taking images or videos.

[2100] A "microphone" is a device for recording sound.

[2101] "Emotion data" is information that indicates the user's emotional state, and is data collected from facial expressions and voice.

[2102] "Emotional state" refers to the mood or emotion that a user is currently experiencing.

[2103] "Optimization" means taking multiple conditions into consideration to derive the most suitable result.

[2104] The system that realizes this application example is an "emotional navigation system" installed in an autonomous vehicle. This system generates and suggests optimal routes based on the user's preferences and emotional state. The following describes an embodiment of this system.

[2105] The server collects and analyzes personal information about the user, who uses the in-vehicle interface to input information such as hobbies, favorite places, and events of interest. This information is stored in the vehicle system, encrypted, and synchronized to a cloud server.

[2106] The cloud server cleans the collected user information, analyzes the user's behavioral patterns and preferences, and generates and trains an AI model for each user based on that information.The data analysis tools used are Python's Pandas and Numpy, and the AI ​​models are TensorFlow and PyTorch.

[2107] Next, cameras and microphones mounted on the vehicle capture the user's facial expressions and voice in real time to collect emotional data, which is then analyzed using an emotion recognition engine (e.g., Affectiva SDK) to identify the user's current emotional state (e.g., enjoying, stressed).

[2108] When a user inputs their current location and destination into the vehicle's interface or smartphone app, the information is sent to a cloud server, which then generates an optimal route based on the user's information and emotional state, taking into account stopovers based on the user's preferences.

[2109] For example, if a user specifies a route from home to the station and wishes to relax, the cloud server will suggest a route that passes through cafes and parks where the user can relax. An example of a prompt sentence for a generative AI model is as follows:

[2110] "Please suggest routes that pass through recommended cafes and parks when the user wants to relax. The user's hobby is visiting cafes."

[2111] Finally, the generated routes are displayed on the user interface, and the user can select options such as "exercise first" or "relaxation first." The cloud server reevaluates the optimal route based on the selected option and the latest emotional state data, and sends the updated route information to the vehicle, providing a travel route that best suits the user's current emotional state and interests.

[2112] This system allows users to have a comfortable and enjoyable experience while traveling, and can provide added value not available in conventional navigation systems.

[2113] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2114] Step 1:

[2115] The user uses the in-vehicle interface to input personal information such as their hobbies, favorite places, and events of interest. The input information is stored in the vehicle system, encrypted, and synchronized to a cloud server, where the user's personal information is securely transmitted.

[2116] Step 2:

[2117] The server stores the user's personal information sent to the cloud server in a database. After storing the information, the server cleans the data, removing outliers and missing values, and converting it into a format suitable for analysis. This results in clean data that can be analyzed.

[2118] Step 3:

[2119] The server processes the cleaned data to analyze the user's behavioral patterns and preferences. For example, it uses Python's Pandas or Numpy to organize the data. After this, it generates an AI model for each user based on the data and trains it using TensorFlow or PyTorch. The analysis results in an individual AI model that reflects each user's preferences.

[2120] Step 4:

[2121] Cameras and microphones installed in the vehicle capture the user's facial expressions and voice in real time to collect emotional data. An emotion recognition engine (e.g., Affectiva SDK) is used to analyze the collected data and identify the user's current emotional state, resulting in real-time emotional state data.

[2122] Step 5:

[2123] The user inputs their current location and destination into the vehicle's interface or smartphone app. This information is sent to a cloud server, which then generates multiple routes based on the user's information and emotional state. Multiple routes, including stopovers, are calculated based on the user's preferences.

[2124] Step 6:

[2125] The server generates multiple routes and proposes the optimal route based on the user's selection. When the user selects an option such as "exercise priority" or "relaxation priority," the server reevaluates and optimizes the route based on the selected option and the user's latest emotional state data. The optimized route information is stored on the cloud server.

[2126] Step 7:

[2127] The device displays the optimized route on the vehicle's user interface. The user can confirm the proposed optimal route and, if they agree, the vehicle will begin autonomous driving according to that route. This allows the vehicle to travel along a route that best suits the user's emotional state and preferences.

[2128] Through these steps, the user can have a comfortable and enjoyable travel experience. An example of a prompt sentence for the generative AI model is, "Please suggest a route that passes through recommended cafes and parks when the user wants to relax. The user's hobby is visiting cafes."

[2129] 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.

[2130] 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.

[2131] 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.

[2132] 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.

[2133] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2134] 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.

[2135] 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).

[2136] 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.

[2137] 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."

[2138] 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.

[2139] 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).

[2140] 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.

[2141] 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.

[2142] 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.

[2143] 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.

[2144] 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.

[2145] 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.

[2146] 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.

[2147] 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.

[2148] 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.

[2149] 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.

[2150] The following is further disclosed regarding the above embodiment.

[2151] (Claim 1)

[2152] means for collecting personal information of users;

[2153] A means for analyzing the collected personal information and understanding the user's preferences;

[2154] A means for generating a plurality of routes including stop-off spots based on information of a user's current location and destination;

[2155] A means for proposing an optimal route from the generated routes according to an option selected by the user;

[2156] means for displaying the provided route on a user interface;

[2157] A system including:

[2158] (Claim 2)

[2159] 10. The system of claim 1, further comprising means for updating the route generation means with the user's personal information, which is updated sequentially.

[2160] (Claim 3)

[2161] 10. The system of claim 1, further comprising means for selecting an exercise-first or fun-first option based on user input.

[2162] "Example 1"

[2163] (Claim 1)

[2164] means for collecting personal information of users;

[2165] A means for encrypting the collected personal information and transmitting it to a server;

[2166] means for storing the received personal information in a database by the server;

[2167] A means for retrieving user personal information from a database and performing data cleaning;

[2168] A means for analyzing user preferences and generating an AI model;

[2169] A means for generating a route based on information of a user's current location and destination;

[2170] means for displaying the generated route on a user interface;

[2171] a means for a user to select either an exercise-first or a fun-first option;

[2172] A means for suggesting the best route depending on the options selected by the user;

[2173] means for displaying advertising information related to the provided route;

[2174] A system including:

[2175] (Claim 2)

[2176] 10. The system of claim 1, further comprising means for reevaluating and updating the AI ​​model using the user's personal information, which is updated sequentially.

[2177] (Claim 3)

[2178] 10. The system of claim 1, further comprising means for selecting an exercise-first or fun-first option based on user input.

[2179] "Application Example 1"

[2180] (Claim 1)

[2181] means for collecting personal information of users;

[2182] A means for analyzing the collected personal information and understanding the user's preferences;

[2183] A means for generating a plurality of routes including stop-off spots based on information of a user's current location and destination;

[2184] A means for proposing an optimal route from the generated routes according to an option selected by the user;

[2185] means for displaying the provided route on a user interface;

[2186] means for providing said route in a navigation system of an autonomous vehicle;

[2187] A means for generating an AI model for route suggestions based on user preferences;

[2188] A system including:

[2189] (Claim 2)

[2190] 10. The system of claim 1, further comprising means for updating the route generation means with the user's personal information, which is updated sequentially.

[2191] (Claim 3)

[2192] 10. The system of claim 1, further comprising means for selecting an exercise-first or fun-first option based on user input.

[2193] "Example 2: Combining Emotion Engines"

[2194] (Claim 1)

[2195] means for collecting personal information of users;

[2196] A means for encrypting the collected personal information and transmitting it over a network;

[2197] a means for storing the encrypted information in a database;

[2198] A means for retrieving personal information from the database and performing data cleaning;

[2199] A means of analyzing user preferences and behavioral patterns based on the cleaned data;

[2200] A means for generating and training different artificial intelligence models based on the analysis results;

[2201] means for recognizing emotions using a user's facial expressions, voice, and touch input;

[2202] means for analyzing the recognized emotion data to identify a current emotional state of the user;

[2203] A means for generating a plurality of routes including stop-off spots based on information of a user's current location and destination;

[2204] A means for proposing an optimal route from the generated routes according to an option selected by the user;

[2205] means for displaying the provided route on a user interface;

[2206] A system including:

[2207] (Claim 2)

[2208] 10. The system of claim 1, further comprising means for updating the route generation means based on successively updated personal information and emotional state of the user.

[2209] (Claim 3)

[2210] 10. The system of claim 1, further comprising means for selecting an exercise-first or fun-first option based on user input.

[2211] "Application example 2 when combining emotion engines"

[2212] (Claim 1)

[2213] means for collecting personal information of users;

[2214] A means for analyzing the collected personal information and understanding the user's preferences;

[2215] A means for generating a plurality of routes including stop-off spots based on information of a user's current location and destination;

[2216] A means for proposing an optimal route from the generated routes according to an option selected by the user;

[2217] means for displaying the provided route on a user interface;

[2218] A means for detecting the user's facial expressions and voice in real time using a camera and microphone installed in the vehicle to collect emotion data;

[2219] a means for identifying a current emotional state based on the collected emotional data;

[2220] means for optimizing the generated route based on the user's emotional state and preferences;

[2221] A system including:

[2222] (Claim 2)

[2223] 10. The system of claim 1, further comprising means for updating the route generation means with the user's personal information and emotion data, which are updated sequentially.

[2224] (Claim 3)

[2225] 10. The system of claim 1, further comprising means for selecting an exercise-first or fun-first option based on user input. [Explanation ...

Claims

1. means for collecting personal information of users; A means for analyzing the collected personal information and understanding the user's preferences; A means for generating a plurality of routes including stop-off spots based on information of a user's current location and destination; A means for proposing an optimal route from the generated routes according to an option selected by the user; means for displaying the provided route on a user interface; A system including:

2. 2. The system of claim 1, further comprising means for updating the route generating means with continuously updated user personal information.

3. 10. The system of claim 1, further comprising means for selecting an exercise-first or fun-first option based on user input.

Images