system

Abstract

When driving a car or motorcycle alone, you can easily and appropriately obtain information such as road conditions, weather, and recommended routes from your current location to your destination. [Solution] A system including a means for determining a current location, a means for obtaining weather information using an external API, a means for obtaining road conditions using an external API, a means for transmitting these data to a server, a means for receiving analysis results from the server, and a means for providing the received analysis results to a user in the form of voice or text.

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] Drivers who drive cars or motorcycles alone face the challenge of finding appropriate information in real time. In particular, there is a lack of easy and appropriate ways to obtain information such as road conditions, weather, and recommended routes from the current location to the destination. This often leads to anxiety and stress for drivers, potentially hindering efficient travel and safe driving. [Means for solving the problem]

[0005] The present invention provides a system for providing necessary information in real time to a driver traveling alone. Specifically, the system includes the following components:

[0006] 1. Use the built-in GPS sensor as a means of determining your current location.

[0007] 2. Provide a means to obtain weather information for the current location or destination using an external API.

[0008] 3. Establish a means to obtain real-time road conditions using external APIs.

[0009] 4. It has a means for transmitting these data to a server and receiving the analysis results from the server again.

[0010] 5. The server analyzes this information and generates the optimal route and advice. The analysis results are provided to the driver via voice or text.

[0011] 6. A means for receiving a request for additional information from the driver, sending a data acquisition request to the server again, and providing the latest information is included.

[0012] This allows drivers to easily obtain the latest information in real time, enabling safe and efficient travel. In addition, the collected data can be used for business purposes, making it possible to generate profits.

[0013] A "location determining means" is a device or method that uses a built-in GPS sensor or other location information technology to determine a user's current location.

[0014] An "external API" is an application programming interface used to communicate with external systems and services, and can be used to obtain data such as weather information and road conditions.

[0015] "Means for acquiring weather information" refers to a method or device for acquiring weather information for the current location and destination via an external API, etc., and providing that information to the driver.

[0016] "Means of obtaining road conditions" refers to methods or devices for obtaining information on road congestion and traffic conditions between the current location and the destination using external APIs, etc.

[0017] A "server" is a computer system that receives data sent from a terminal, analyzes the data, and generates and transmits the information required by the driver.

[0018] The "means for receiving the analysis results" refers to a method or device for receiving the analyzed information sent from the server and providing the information to the driver.

[0019] "Means for providing to users" refers to methods and devices for conveying analysis results to users by voice or text, including speech synthesis functions and displays.

[0020] The "means for sending a request for additional information" refers to a method or device for receiving a new information request from a user, resubmitting the request to the server, and obtaining new analysis results. [Brief explanation of the drawings]

[0021] [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

[0022] 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.

[0023] First, the terms used in the following description will be explained.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 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.

[0032] 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).

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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."

[0042] The system of this invention is designed to provide real-time information and support to drivers when they are driving a car or motorcycle alone. The system consists of three main components: a terminal, a server, and a user.

[0043] 1. Terminal

[0044] The terminal is a navigation system installed in a car or motorcycle, and has the following functions:

[0045] Get current location

[0046] The device uses its built-in GPS sensor to determine the user's current location, which is then sent to a server and used as the basis for location information.

[0047] Obtaining weather and road conditions

[0048] The device will use external weather and traffic APIs to obtain weather and road conditions for the current location and destination, improving the accuracy of the information provided to users.

[0049] Sending and Receiving Data

[0050] The device sends the acquired data to the server and receives the analysis results from the server, which are then provided to the user using speech synthesis and text display functions.

[0051] 2. Server

[0052] The server receives data sent from the terminal and has the function of analyzing it. The specific functions of the server are as follows:

[0053] Data reception and analysis

[0054] The server receives data sent from the device, such as current location, weather information, road conditions, etc. It then analyzes this data and generates optimal routes and advice for the user.

[0055] Generating response data

[0056] The server generates response data based on the analysis results. For example, if there is traffic congestion, it generates data suggesting an alternative route.

[0057] Resend Data

[0058] The generated response data is sent back to the terminal and provided to the user.

[0059] 3. Users

[0060] Users can use this system to actually drive a car or motorcycle, and the system provides users with relevant information in real time.

[0061] Receiving information

[0062] The user receives information provided by the device. For example, if the device announces, "You are currently heading from Tokyo to Yokohama, but the expressway is congested. You will arrive faster if you use the local roads," the user can adjust their driving method accordingly.

[0063] Request for additional information

[0064] If the user needs more detailed information, they can ask a follow-up question, for example, "What's the weather like along that route?", and the device will again request the information from the server and provide the latest information.

[0065] Specific examples

[0066] For example, when a user travels from Tokyo to Yokohama, the device uses GPS to determine the user's current location and obtains weather information and road conditions from the API. This data is sent to the server, which analyzes it and returns the result, "The expressway is congested, so we recommend taking an ordinary road." The device notifies the user of the result by voice, and the user selects an ordinary road. If the user also asks, "What's the weather like on the ordinary road?", the device will query the server again and provide the latest weather information.

[0067] This system provides users with accurate information in real time, enabling them to travel efficiently and safely.

[0068] The processing flow will be explained below.

[0069] Step 1: Get your current location

[0070] Subject: Device

[0071] The device uses the built-in GPS sensor to determine the user's current location. Specifically, the GPS module obtains latitude and longitude information and stores this location data locally on the device.

[0072] Step 2: Get weather information

[0073] Subject: Device

[0074] The device sends a request to an external weather API to obtain weather information for the current location and destination. The request includes location information obtained by GPS. The device receives the response from the API, analyzes the weather information, and stores it.

[0075] Step 3: Obtaining road conditions

[0076] Subject: Device

[0077] The device sends a request to an external traffic API to obtain real-time road conditions, which also includes location information, receives a response from the API, analyzes the road condition data, and stores it.

[0078] Step 4: Sending data

[0079] Subject: Device

[0080] The device sends current location, weather, road conditions, and destination information to the server. Before sending, this data is formatted into a unified format. The data is sent over the Internet, and a confirmation message is received when the data has been successfully sent.

[0081] Step 5: Receiving and analyzing data

[0082] Subject: Server

[0083] The server receives the data sent from the device, analyzes it, and applies algorithms to generate the best route and advice for the user. The analysis process takes into account traffic conditions, weather, recommended routes, and more.

[0084] Step 6: Generate response data

[0085] Subject: Server

[0086] The server generates response data based on the analysis results, for example, a message such as "The current route is congested, so we recommend taking an open road." The generated data is then reformatted and prepared for transmission to the device.

[0087] Step 7: Sending response data

[0088] Subject: Server

[0089] The server sends the generated response data to the terminal. If the transmission is successful, the server goes into standby mode for the next data request.

[0090] Step 8: Receiving response data

[0091] Subject: Device

[0092] The device receives the response data from the server, analyzes the received data, and converts it into a format to be presented to the user. Specifically, it prepares for speech synthesis and text display.

[0093] Step 9: Provide information

[0094] Subject: Device

[0095] The device uses its voice synthesis function to notify the user, "The expressway is congested. You will arrive faster if you use the local road." It also displays text information on the display.

[0096] Step 10: Process requests for additional information

[0097] Subject: Device

[0098] When a user asks, "What's the weather like along that route?" the device parses this request and generates a new data request to ask the server for weather information again.

[0099] Step 11: Sending and Receiving New Data

[0100] Subject: Terminals and Servers

[0101] The device sends a new data request to the server, which receives the request and analyzes it again, and then sends the analysis results back to the device.

[0102] Step 12: Provide updates

[0103] Subject: Device

[0104] The device will provide the user with newly received weather information via voice and text, informing them that "The weather is currently clear on public roads and visibility is good."

[0105] Through the above steps, this system provides real-time information and support to drivers.

[0106] Example 1

[0107] 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."

[0108] Conventional driver assistance systems have faced challenges in providing users with appropriate information in real time. Providing timely updated data is particularly important given the frequently changing traffic and weather conditions. Furthermore, there is a lack of systems that can smoothly respond to additional requests for specific information that users require.

[0109] 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.

[0110] In this invention, the server includes means for identifying the current location, means for acquiring weather information using an external information system, means for acquiring road conditions using an external traffic information system, means for transmitting these data to the central control device, means for receiving analysis results from the central control device, and means for providing the received analysis results to the user as voice or text information, thereby enabling the user to obtain accurate information in real time and travel efficiently and safely.

[0111] "Means for determining current location" refers to a system that uses a location information acquisition device such as a GPS sensor to accurately determine the user's current location.

[0112] "Means of obtaining weather information using an external information system" refers to a mechanism for obtaining weather information for the current location and destination using external services such as weather information APIs.

[0113] "Means of obtaining road conditions using external traffic information systems" refers to a mechanism for obtaining road conditions at the current location and destination by utilizing external services such as traffic condition APIs.

[0114] The "means for transmitting these data to a central control device" refers to a communication means for transmitting the acquired current location, weather information, and road conditions to a central control device such as a server.

[0115] The "means for receiving the analysis results from the central control device" is a communication means for receiving the results of the data analyzed by the central control device such as a server.

[0116] "Means for providing the received analysis results to the user as voice or text information" refers to a mechanism for communicating the data analysis results received from the server to the user using voice synthesis technology or text display functions.

[0117] "Generating optimal route or advice" refers to the process in which the server analyzes the location, weather, and traffic data it receives and generates the most efficient and safe route or driving advice for the user.

[0118] The "means for receiving a request for additional information and again transmitting an information acquisition request to the central control device" is a mechanism for receiving a request for specific additional information from a user and again transmitting a data acquisition request to the central control device based on that request.

[0119] The system of the present invention consists of three main elements: the terminal, the server, and the user. Each element is described in detail below.

[0120] Terminal

[0121] The terminal consists of a navigation system installed in a car or motorcycle. Specific hardware includes a GPS sensor, a communication module (e.g., an LTE module), a voice synthesis device, a display, etc. Software includes an API client for obtaining weather information (e.g., an OpenWeatherMap API client) and an API client for obtaining traffic information (e.g., a Google (registered trademark) Maps API client). The terminal has the following functions:

[0122] 1. Get your current location

[0123] Your device will use the built-in GPS sensor to determine your current location. For example, your device may display "Getting location..." and go through the process of obtaining your GPS coordinates.

[0124] 2. Obtaining weather and road conditions

[0125] The device uses external weather APIs (e.g., OpenWeatherMap API) and traffic APIs (e.g., Google Maps API) to obtain weather information and road conditions for the current location and destination. For example, a message such as "Retrieving weather information and road conditions..." is displayed.

[0126] 3. Sending and Receiving Data

[0127] The device sends the acquired data to the server and receives the analysis results from the server. For example, when data is received from the server, the device displays "Data received."

[0128] server

[0129] The server acts as a central control unit, analyzing data sent from the terminals and generating response data. The server uses the following software and hardware:

[0130] 1. Data Reception and Analysis

[0131] The server receives data such as the current location, weather information, and road conditions sent from the device and begins analyzing it. For example, it calculates the optimal route using a generative AI model (e.g., a routing algorithm or traffic analysis model) based on the received data.

[0132] 2. Generating response data

[0133] The server generates response data for the user based on the analysis results. For example, the server may generate information such as "The highway is congested, so we recommend taking a regular road."

[0134] 3. Data retransmission

[0135] The server will retransmit the generated response data to the terminal. After this transmission process is successful, the server will record a message saying "Data transmission successful."

[0136] user

[0137] The user uses this system to actually drive a car or motorcycle. The user receives various information in real time via the terminal and can request additional information as needed. Specifically, the following operations are possible:

[0138] 1. Receiving information

[0139] The user receives information provided by the device. For example, the device may announce in voice, "You are currently traveling from Tokyo to Yokohama, but the expressway is congested. You will arrive faster if you use the local road."

[0140] 2. Request for additional information

[0141] If the user needs more detailed information, they can ask a follow-up question, for example, "What's the weather like along that route?", and the device will again request the information from the server and provide the latest information.

[0142] Specific examples

[0143] When a user travels from Tokyo to Yokohama, the following specific actions are taken:

[0144] 1. The device activates the GPS and obtains the current location (for example, near Tokyo Station).

[0145] 2. The device calls the OpenWeatherMap API to obtain weather information for Tokyo Station and Yokohama Station, and road conditions using the Google Maps API.

[0146] 3. The device sends this data to the server.

[0147] 4. The server receives the data and calculates the optimal route.

[0148] 5. The server generates data that says, "The highway is congested, so we recommend taking a regular road."

[0149] 6. The server sends the data to the device.

[0150] 7. The device notifies the user that "You'll arrive faster if you take the local road."

[0151] 8. The user requests additional information: "What's the weather like on the road?"

[0152] 9. The device sends the request to the server.

[0153] 10. The server analyzes the information and sends it to the device: "The weather on the public road is sunny."

[0154] 11. The device notifies the user that "The weather on the public road is clear."

[0155] Prompt Sentence Examples

[0156] 1. "What is the best route considering my current location and destination?"

[0157] 2. "If I use a public road, please let me know the weather information along the way."

[0158] 3. "Please provide traffic information on highways."

[0159] The overall flow of this system relies on the server for data processing, providing real-time information so users can reach their destinations comfortably and safely.

[0160] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0161] Step 1:

[0162] The device uses the GPS sensor to obtain the current location. Specifically, the device displays "Getting current location..." and obtains GPS coordinates (latitude and longitude). The input is data from the GPS sensor, and the output is the coordinate information of the current location.

[0163] Step 2:

[0164] The device obtains weather information and road conditions from an external API. Specifically, the device calls the OpenWeatherMap API to obtain weather information for the current location and destination, and calls the Google Maps API to obtain road conditions from the current location to the destination. The input is the coordinate information of the current location and destination, and the output is weather information and road condition information.

[0165] Step 3:

[0166] The device transmits the current location, weather information, and road conditions it has acquired to the server. Specifically, it displays "Sending data..." and sends all of this data to the server. The input is the current location, weather information, and road conditions data, and the output is the data transmitted to the server.

[0167] Step 4:

[0168] The server receives the data sent from the device and begins analyzing it. Specifically, the server stores it in a database and calculates the optimal route using a generative AI model. The input is the current location, weather information, and road condition data, and the output is the optimal route information.

[0169] Step 5:

[0170] The server generates response data based on the analysis results. Specifically, it creates response data such as "The highway is congested, so we recommend taking a local road." The input is optimal route information, and the output is response data.

[0171] Step 6:

[0172] The server sends the response data to the terminal. Specifically, it records the message "Data transmission successful" and sends the response data to the terminal. The input is the response data, and the output is the data sent to the terminal.

[0173] Step 7:

[0174] The response data received by the device is provided to the user as voice or text. Specifically, it notifies the user by voice that "You'll arrive faster if you use the public road." The input is the response data from the server, and the output is the information notified to the user.

[0175] Step 8:

[0176] If the user needs additional information, they ask the device a question. Specifically, the user asks aloud, "What's the weather like along that route?" The input is the question from the user, and the output is the question received by the device.

[0177] Step 9:

[0178] The device sends the user's question to the server. Specifically, it displays "Requesting additional information..." and sends the question to the server. The input is the question from the user, and the output is the question sent to the server.

[0179] Step 10:

[0180] The server analyzes the additional information and sends it back to the device. Specifically, it generates additional information such as "The weather on the public road is sunny." The input is the user's question, and the output is the additional information.

[0181] Step 11:

[0182] The terminal provides the received additional information to the user. Specifically, it notifies the user by voice, "The weather on the general road is sunny." The input is the additional information from the server, and the output is the additional information notified to the user.

[0183] (Application example 1)

[0184] 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."

[0185] A modern problem in car and motorcycle driving is the lack of real-time, accurate information. It is particularly difficult for drivers to understand the appropriate driving route, weather conditions, and traffic conditions while driving alone. This can result in reduced driving safety and efficiency. Furthermore, even when additional information is needed, it is dangerous for drivers to manually obtain the information while driving. There is a need to resolve these issues and improve driving safety and efficiency.

[0186] 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.

[0187] In this invention, the server includes a means for determining the current location, a means for acquiring weather information using an external API, a means for acquiring road conditions using an external API, a means for transmitting these data to the server, a means for receiving analysis results from the server, a means for providing the received analysis results to the user by voice or text, and a means for providing the driver with information they need by voice, thereby improving the safety and efficiency of automated driving. This allows the driver to understand appropriate driving routes, weather information, and traffic conditions in real time, significantly improving the safety and efficiency of driving. Furthermore, if additional information is requested, the information can be safely obtained through voice instructions, thereby reducing the burden on the driver and ensuring safety.

[0188] Key Word Definitions

[0189] "Means for determining current location" refers to a function that uses location information technology such as GPS to accurately determine the current location of the device.

[0190] "Means for obtaining weather information using an external API" is an interface for obtaining the latest weather information from an external weather information service.

[0191] "Means for obtaining road conditions using external APIs" refers to an interface for obtaining current road congestion conditions, accident information, etc. from external traffic information services.

[0192] "Means for transmitting these data to the server" refers to communication means for uploading acquired information such as current location, weather information, road conditions, etc. to the server.

[0193] The "means for receiving analysis results from the server" refers to a communication means for receiving analysis results and advice sent from the server at the terminal.

[0194] The "means for providing the received analysis results to the user by voice or text" refers to an interface for conveying the received information to the user by voice synthesis or text display.

[0195] "Means for providing the driver with the information they need via voice and improving the safety and efficiency of automated driving" refers to a function that provides the driver with the necessary information via voice in response to their request, thereby assisting in making the operation of automated vehicles safer and more efficient.

[0196] "Means for receiving a request for additional information from the user and sending a data acquisition request to the server again" is a function for accepting a request from a user for additional information and sending a data acquisition request to the server again.

[0197] MODE FOR CARRYING OUT THE INVENTION

[0198] The system of the present invention provides drivers with optimal information in real time when driving a vehicle, thereby improving safety and efficiency.

[0199] The system uses the following hardware and software:

[0200] Hardware

[0201] GPS module: Used to determine the vehicle's current location.

[0202] Smartphone or vehicle display: where system applications are installed and used to provide information.

[0203] Internet connection: Used to access external APIs and obtain necessary data.

[0204] Microphone and speaker: Used to provide information via voice and receive voice commands from the user.

[0205] software

[0206] Navigation software (e.g., Google Maps, Waze): used to provide route information and display analysis results.

[0207] Weather information API (e.g. OpenWeatherMap): Used to obtain weather information for your current location and destination.

[0208] Traffic information API (e.g., TomTom Traffic API): Used to obtain road congestion and accident information.

[0209] Description of the embodiment

[0210] The system's terminal first uses a GPS module to determine the driver's current location, then uses weather and traffic information APIs to obtain weather and road conditions for the current location and destination, and transmits this data to a server via an internet connection.

[0211] The server analyzes the transmitted data and generates the optimal route and advice for the driver. The analysis results are then sent back to the device. The device then notifies the user of the received analysis results in voice or text format. For example, it may say, "There is currently traffic congestion, so we recommend taking an ordinary road."

[0212] If the user needs more detailed information, they can ask additional questions by voice, such as "What's the weather like on the road?", and the device will request the information from the server again and provide the latest information. This allows the driver to always adjust their driving based on the latest information.

[0213] Specific examples

[0214] For example, suppose a user is driving from Tokyo to Yokohama. In this case, the device uses GPS to identify the user's current location and obtains weather and road information. This information is sent to the server, which analyzes it and generates the result, "The highway is congested, so it is recommended to take a regular road." The device then notifies the user of the result by voice.

[0215] When a user asks, "What's the weather like on the public road?", the device will again request weather information from the server and provide the latest weather information. This system allows users to obtain accurate information in real time, enabling them to travel efficiently and safely.

[0216] Prompt Sentence Examples

[0217] "What is the weather forecast for my current location?"

[0218] "Please provide traffic information."

[0219] "Calculate the best route."

[0220] "What's the weather like on the open road?"

[0221] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0222] Program processing steps

[0223] Step 1:

[0224] Get current location

[0225] The device uses the GPS module to determine the user's current location. At this time, it receives GPS data as input and outputs the latitude and longitude of the current location. Specifically, it obtains the numerical data of latitude and longitude from the GPS device and passes it to the system as the current location coordinates.

[0226] Step 2:

[0227] Get weather information

[0228] The device uses an external weather information API to obtain weather information for the current location and destination. At this time, the latitude and longitude obtained in step 1 are used as input, and the response data from the weather API is received as output. Specifically, the device sends an API request and parses the response in JSON format to extract the weather data.

[0229] Step 3:

[0230] Obtaining road conditions

[0231] The device uses an external traffic information API to obtain road conditions at the current location and destination. At this time, the latitude and longitude obtained in step 1 are used as input, and response data from the traffic API is received as output. Specifically, the device sends an API request, analyzes the response in JSON format, and extracts road condition data.

[0232] Step 4:

[0233] Sending data to the server

[0234] The device sends the acquired weather information, road conditions, and current location data to the server. At this time, the weather information, road condition data, latitude and longitude are sent together as input to the server, and a confirmation response is output. Specifically, the data is sent to the server using an HTTP POST request.

[0235] Step 5:

[0236] Data analysis by server

[0237] The server analyzes the received data and generates the optimal route and advice to provide to the driver. At this time, it analyzes the received input data (latitude and longitude, weather information, road conditions) and outputs the optimal route information. Specifically, it uses AI algorithms and routing algorithms to calculate the optimal driving route and recommended actions.

[0238] Step 6:

[0239] Resend analysis results

[0240] The server retransmits the analysis results to the terminal. At this time, it uses the optimal route information generated as input to construct the data to be sent to the terminal and actually sends it as output. Specifically, it returns the analysis results to the terminal in JSON format as an HTTP response.

[0241] Step 7:

[0242] User Notification

[0243] The device provides the analysis results received from the server to the user as voice or text. At this time, the optimal route information received from the server is used as input, and voice notification or text display is provided to the user as output. Specifically, voice notification is provided using speech synthesis software, or text data is displayed on the screen.

[0244] Step 8:

[0245] Processing requests for additional information

[0246] If the user requests additional information, the device retransmits the request to the server for further analysis and provision. The device receives the request for additional information via voice commands or button presses as input, constructs data to send to the server, and receives a response from the server as output. Specifically, the device analyzes the user's voice command using voice recognition software and sends a new request to the server.

[0247] 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.

[0248] The system of the present invention is designed to provide real-time information and appropriate support to drivers who are driving cars or motorcycles alone by recognizing their emotions. The system consists of four main components: a terminal, a server, a user, and an emotion engine.

[0249] 1. Terminal

[0250] The terminal is a navigation system installed in a car or motorcycle, and has the following functions:

[0251] Get current location

[0252] The device uses its built-in GPS sensor to determine the user's current location, which is then sent to a server and used as the basis for location information.

[0253] Obtaining weather and road conditions

[0254] The device will use external weather and traffic APIs to obtain weather and road conditions for the current location and destination, improving the accuracy of the information provided to users.

[0255] Sending and Receiving Data

[0256] The device sends the acquired data to the server and receives the analysis results from the server, which are then provided to the user using speech synthesis and text display functions.

[0257] Emotion engine included

[0258] The device is equipped with an emotion engine that recognizes emotions from the user's voice and facial expressions. The emotion engine analyzes the user's tone of voice and facial expressions to identify their emotional state.

[0259] 2. Server

[0260] The server receives data sent from the terminal and has the function of analyzing it. The specific functions of the server are as follows:

[0261] Data reception and analysis

[0262] The server receives the device's current location, weather information, road conditions, and the user's emotion data from the emotion engine. It then analyzes this data and applies algorithms to generate optimal routes and recommendations for the user. The analysis process comprehensively takes into account traffic conditions, weather, recommended routes, and the user's emotional state.

[0263] Generating response data

[0264] The server generates response data based on the analysis results. For example, if there is traffic congestion and the user is frustrated, it generates a message containing not only the best route but also advice on relaxation. The generated data is then reformatted and ready to be sent to the device.

[0265] Resend Data

[0266] The generated response data is sent back to the terminal and provided to the user.

[0267] 3. Users

[0268] Users can use this system to actually drive a car or motorcycle, and the system provides users with relevant information in real time.

[0269] Receiving information

[0270] The user receives information provided by the device. For example, if the device announces, "You are currently heading from Tokyo to Yokohama, but the expressway is congested. You will arrive faster if you use the local roads," the user can adjust their driving method accordingly.

[0271] Request for additional information

[0272] If the user needs more detailed information, they can ask a follow-up question, for example, "What's the weather like along that route?", and the device will again request the information from the server and provide the latest information.

[0273] Recognizing and Responding to Emotions

[0274] The user's tone of voice and facial expressions are analyzed to understand their emotional state. For example, if the user is feeling stressed, the device will provide support tailored to the user's mental state, such as by saying, "Relax. We'll guide you to the best route."

[0275] Specific examples

[0276] For example, when a user travels from Tokyo to Yokohama, the device uses GPS to determine their current location and obtains weather and road information from the API. This data is sent to a server, which analyzes it and returns the result, "The expressway is congested, so we recommend taking a regular road." The device then notifies the user of the result by voice, and the user selects a regular road. If the device determines that the user's voice tone sounds stressed, it will provide additional advice, such as, "Relax. We will guide you to the optimal route."

[0277] The system provides users with accurate, real-time, situation-specific information, enabling them to travel safely and efficiently. The adoption of an emotion engine also reduces stress and anxiety while driving, providing a safer and more comfortable driving environment.

[0278] The processing flow will be explained below.

[0279] Step 1: Get your current location

[0280] Subject: Device

[0281] The device uses the built-in GPS sensor to determine the user's current location. Specifically, the GPS module obtains latitude and longitude information and stores this location data locally on the device.

[0282] Step 2: Get weather information

[0283] Subject: Device

[0284] The device sends a request to an external weather API to obtain weather information for the current location and destination. The request includes location information obtained by GPS. The device receives the response from the API, analyzes the weather information, and stores it.

[0285] Step 3: Obtaining road conditions

[0286] Subject: Device

[0287] The device sends a request to an external traffic API to obtain real-time road conditions, which also includes location information, receives a response from the API, analyzes the road condition data, and stores it.

[0288] Step 4: Obtaining emotion data

[0289] Subject: Device

[0290] The device uses an emotion engine to obtain emotion data from the user's voice and facial expressions. The emotion engine uses voice tone and facial expression analysis algorithms to identify the user's emotional state (e.g., stressed, irritated, relaxed).

[0291] Step 5: Sending data

[0292] Subject: Device

[0293] The device transmits its current location, weather information, road conditions, and emotion data to the server, which then formats the data into a unified format. The transmission is done over the Internet, and the user receives a confirmation message when the data has been successfully sent.

[0294] Step 6: Receiving and analyzing data

[0295] Subject: Server

[0296] The server receives the data sent from the device, analyzes it, and applies algorithms to generate the best route and advice for the user. The analysis process takes into account factors such as traffic conditions, weather, and the user's emotional state.

[0297] Step 7: Generate response data

[0298] Subject: Server

[0299] The server generates response data based on the analysis results—for example, if the user is frustrated, it generates a message containing advice on relaxation as well as the best route—and the generated data is then reformatted and ready to be sent to the device.

[0300] Step 8: Sending response data

[0301] Subject: Server

[0302] The server sends the generated response data to the terminal. If the transmission is successful, the server goes into standby mode for the next data request.

[0303] Step 9: Receiving response data

[0304] Subject: Device

[0305] The device receives the response data from the server, analyzes the received data, and converts it into a format to be presented to the user. Specifically, it prepares for speech synthesis and text display.

[0306] Step 10: Provide information

[0307] Subject: Device

[0308] The device uses its voice synthesis function to notify the user, "The expressway is congested. You will arrive faster if you use the local road." It also displays text information on the display.

[0309] Step 11: Further emotional advice

[0310] Subject: Device

[0311] If the emotion engine determines that the user is feeling stressed, the device will notify them by saying, "Relax. We'll guide you to the best route," and provide additional advice tailored to the user's mental state.

[0312] Step 12: Process requests for additional information

[0313] Subject: Device

[0314] When a user asks, "What's the weather like along that route?" the device parses this request and generates a new data request to ask the server for weather information again.

[0315] Step 13: Sending and Receiving New Data

[0316] Subject: Terminals and Servers

[0317] The device sends a new data request to the server, which receives the request and analyzes it again, and then sends the analysis results back to the device.

[0318] Step 14: Provide updates

[0319] Subject: Device

[0320] The device will provide the user with newly received weather information via voice and text, informing them that "The weather is currently clear on public roads and visibility is good."

[0321] Through these steps, the system provides real-time information and support to drivers. The introduction of an emotion engine enables detailed support according to the user's emotional state, providing a safer and more comfortable driving environment.

[0322] Example 2

[0323] 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."

[0324] When a driver drives a car or motorcycle alone, they need not only real-time information but also the ability to recognize the driver's emotional state and provide appropriate support to reduce driving stress and anxiety, providing a safe and comfortable driving environment. However, current systems are unable to recognize the user's emotional state in real time and provide advice accordingly. To solve this problem, a new system is needed.

[0325] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0326] In this invention, the server includes a means for acquiring current location and weather information, a means for acquiring traffic information, and a means for recognizing the emotional state of the user, which makes it possible to acquire the user's current location and road conditions in real time, while also analyzing the user's emotional state, and provide optimal routes and advice.

[0327] "Means for determining current location" refers to a device or system that uses a GPS sensor to determine the current location of the driver's vehicle or motorcycle and obtains that information.

[0328] "Means for obtaining weather information using an external API" refers to a device or system for obtaining weather information for the current location and destination using the API of an external weather information service.

[0329] "Means for obtaining traffic information using an external API" refers to a device or system for obtaining road conditions and traffic congestion information using the API of an external traffic information service.

[0330] The "means for transmitting these data to the server" refers to a communication device or system for transmitting the driver's current location, weather information, traffic information, and the like to the server.

[0331] The "means for receiving the analysis results from the server" is a communication device or system for receiving the analysis results sent from the server.

[0332] The "means for analyzing acquired data and recognizing the user's emotional state" refers to an emotion recognition engine or analysis system that analyzes the user's voice and facial expressions and recognizes the user's emotional state.

[0333] The "means for generating response data based on the analysis results" refers to an algorithm or program for generating optimal routes and advice for users based on the data analyzed by the server.

[0334] "Means for providing the received analysis results to the user in voice or text" refers to a device or system for providing information to the user by synthesizing the analysis results received from the server as voice or displaying them as text.

[0335] This invention is a system that provides real-time information to drivers when they are driving a car or motorcycle alone, recognizes the driver's emotions, and provides appropriate support. This system mainly consists of four main components: a terminal, a server, a user, and an emotion engine.

[0336] Terminal

[0337] The terminal is a navigation system installed in a car or motorcycle, and specifically includes a GPS module, a communication module, a voice synthesizer, a text display device, and an emotion engine.

[0338] 1. Get your current location

[0339] The device uses a built-in GPS module (e.g., a Garmin GPS module) to determine the user's current location, which is then converted into JSON format and sent to the server.

[0340] 2. Obtaining weather and road conditions

[0341] The device uses external weather APIs (e.g., OpenWeatherMap API) and traffic APIs (e.g., Google Maps API) to obtain weather information and road conditions for the current location and destination. It sends an API request and sends the JSON-formatted data received as a response to the server.

[0342] 3. Sending and Receiving Data

[0343] The acquired data is sent to the server and the analysis results sent from the server are received. Communication is carried out using the HTTPS protocol.

[0344] 4. Equipped with an emotional engine

[0345] The device is equipped with an emotion engine (for example, Microsoft® Azure® Emotion API) that analyzes the user's voice and facial expressions. Specifically, it uses a camera and microphone to collect facial expression images and voice data, which are then sent to a server as emotion data.

[0346] server

[0347] The server has the function of receiving and analyzing data sent from the terminal.

[0348] 1. Data Analysis

[0349] The server comprehensively analyzes the received location, weather information, road conditions, and emotional data, and uses AI algorithms to generate optimal routes and advice, as well as generate response data based on the user's emotional state.

[0350] 2. Generate and send response data

[0351] Based on the analysis results, the engine generates response data for the user. For example, it creates a message such as, "The current weather is rainy. There is traffic congestion, so we recommend taking regular roads," and sends it to the device.

[0352] user

[0353] Users access the system through a terminal and actually drive a car or motorcycle.

[0354] 1. Receiving information

[0355] The user receives information provided by the device. For example, the device may use a voice synthesizer (e.g., Google Text-to-Speech) to notify the user that "the highway is congested. You will arrive faster if you take the local road," and the user can adjust their driving accordingly.

[0356] 2. Request for additional information

[0357] If the user needs more detailed information, they can request additional information using voice commands or touch operations. For example, if they ask, "What's the weather like along that route?", the device will again request the information from the server and provide the latest information.

[0358] 3. Recognizing and Responding to Emotions

[0359] If the user's tone of voice or facial expression is detected as stressed, the device will provide additional advice, such as "Relax. We'll guide you to the best route." This reduces stress and anxiety while driving, providing a safer and more comfortable driving environment.

[0360] Examples and prompts

[0361] For example, when a user travels from Tokyo to Yokohama, the following actions are performed:

[0362] The device uses GPS to determine its current location and obtains weather information and road conditions using the OpenWeatherMap API and Google Maps API.

[0363] The acquired data is sent to a server, which analyzes it and returns the result that "the highway is congested, so we recommend taking a regular road."

[0364] The device uses Google Text-to-Speech to notify the user via voice, "The highway is congested, so we recommend taking a regular road."

[0365] If the user's tone of voice is deemed stressful, the device will offer additional advice: "Relax. We'll guide you to the best route."

[0366] Example prompt sentence:

[0367] "Please provide the best route and weather information for traveling from Tokyo to Yokohama."

[0368] "Generate a message to a user who is currently stressed, with advice on how to relax."

[0369] In this way, the system of the present invention provides appropriate information in real time and optimal support according to the user's emotional state, providing a safe and comfortable driving experience.

[0370] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0371] Step 1:

[0372] The terminal uses a GPS module to determine the driver's current location.

[0373] Input: Satellite signal

[0374] Data processing: The GPS module receives signals from satellites and calculates latitude and longitude.

[0375] Output: Current location latitude and longitude data (JSON format)

[0376] Specific operation: The device's GPS sensor receives satellite signals, analyzes them to determine the current location, and obtains coordinate information.

[0377] Step 2:

[0378] The device uses weather and traffic APIs to obtain weather information and road conditions for the current location and destination.

[0379] Input: The latitude and longitude data determined by the device as its current location

[0380] Data processing: Constructing API requests, sending them to external weather and traffic APIs, and receiving responses in JSON format.

[0381] Output: Weather and road conditions for current and destination locations (JSON format)

[0382] What it does: The device sends requests to the OpenWeatherMap API and Google Maps API to obtain weather and road condition data for the current location and destination.

[0383] Step 3:

[0384] The terminal transmits data on the current location, weather information, and road conditions to the server.

[0385] Input: Weather information and road condition data acquired by the device (JSON format)

[0386] Data processing: The data is formatted in JSON format and sent to the server using the HTTPS protocol.

[0387] Output: Weather and road condition data sent to the server

[0388] Specific operation: The device collects the data and sends it to the server via HTTPS communication.

[0389] Step 4:

[0390] The terminal starts an emotion engine and acquires emotion data of the driver.

[0391] Input: Driver's voice and facial expression data

[0392] Data processing: Using speech recognition and facial expression analysis algorithms to identify emotional states.

[0393] Output: Emotion data (JSON format)

[0394] How it works: The emotion engine uses the camera and microphone to capture voice and facial expressions, which are then analyzed to determine the emotional state.

[0395] Step 5:

[0396] The terminal transmits the emotion data to the server.

[0397] Input: Emotion data acquired by the device (JSON format)

[0398] Data processing: The data is formatted in JSON format and sent to the server using the HTTPS protocol.

[0399] Output: Emotion data sent to the server

[0400] Specific operation: The device compiles emotion data and sends it to the server via HTTPS.

[0401] Step 6:

[0402] The server receives and analyzes the data sent from the terminal.

[0403] Input: Current location, weather information, road conditions, and emotion data (JSON format) sent from the device

[0404] Data processing: AI algorithms are used to analyze data and generate optimal routes and advice.

[0405] Output: Analysis result (JSON format)

[0406] Specific operation: The server comprehensively analyzes the received data and generates optimal route guidance and advice to provide to the driver.

[0407] Step 7:

[0408] The server generates response data based on the analysis results.

[0409] Input: Analyzed current location, weather information, road conditions, emotion data (JSON format)

[0410] Data processing: Construct a response message based on the analysis results.

[0411] Output: Response data (JSON format)

[0412] Specific operation: The server generates a response message from the analysis results and prepares to send it to the terminal.

[0413] Step 8:

[0414] The server transmits the response data to the terminal.

[0415] Input: Response data generated by the server (JSON format)

[0416] Data processing: The data is formatted in JSON format and sent to the terminal using the HTTPS protocol.

[0417] Output: Response data sent to the terminal

[0418] Specific operation: The server compiles the response data and sends it to the terminal via HTTPS communication.

[0419] Step 9:

[0420] The device receives the analysis results from the server and provides them to the user in voice or text format.

[0421] Input: Response data sent from the server (JSON format)

[0422] Data processing: Analyze the data and provide it to the user using speech synthesis or text display functions.

[0423] Output: Audio or text information provided to the user

[0424] Specific operation: The device analyzes the received data and notifies the user via voice using Google Text-to-Speech.

[0425] Step 10:

[0426] If the user requests additional information, the terminal again sends a data acquisition request to the server.

[0427] Input: Request for additional information from the user (voice command, touch action)

[0428] Data processing: Analyze the user's request and send a request to the server to retrieve the required information again.

[0429] Output: Request for more information sent to the server

[0430] Specific operation: The device sends a request to the server again based on the user's request, preparing to provide the latest information.

[0431] Step 11:

[0432] If the user's tone of voice or facial expression indicates stress, the device will offer additional emotional support advice.

[0433] Input: Detection results from the emotion recognition engine (emotion data such as stress, irritation, relaxation, etc.)

[0434] Data processing: Generate appropriate advice for stress reduction.

[0435] Output: Audio or text advice to the user to relax

[0436] What it does: The device analyzes emotional data and provides voice messages such as, "Relax. We'll guide you to the best route."

[0437] (Application example 2)

[0438] 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."

[0439] Conventional navigation systems are limited to providing information on the current location, weather, and road conditions, and are unable to provide appropriate support that takes into account the driver's psychological state. Therefore, the challenge is to reduce the stress and anxiety felt by drivers and provide a safe and comfortable driving environment.

[0440] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0441] In this invention, the server includes means for identifying the current location, means for acquiring weather information using an external API, means for acquiring road conditions using an external API, means for analyzing the emotional state of the driver using an emotion engine, means for providing additional advice based on the emotional state of the driver obtained from the emotion engine, and means for generating an appropriate voice or text message based on a prompt sentence of the generative AI model. This makes it possible to recognize the emotional state of the driver in real time and provide appropriate information and advice according to that state.

[0442] "Means for determining current location" refers to a function that obtains the user's location information using a GPS sensor.

[0443] "Means of obtaining weather information using external APIs" refers to a function that obtains weather information for the current location and destination using cloud services or publicly available APIs.

[0444] "Means of obtaining road conditions using external APIs" refers to a function that obtains traffic conditions and road congestion information using cloud services or publicly available APIs.

[0445] The "means for transmitting these data to the server" is a function for transmitting the acquired current location, weather information, and road condition information to the server via the network.

[0446] The "means for receiving analysis results from the server" is a function for receiving data analysis results sent from the server at the terminal.

[0447] "Means of providing the received analysis results to the user by voice or text" refers to a function that notifies the user of the analysis results through voice synthesis technology or a display.

[0448] The "emotion engine that analyzes the driver's emotional state" is a system that uses voice analysis and facial recognition technology to evaluate the driver's emotions and identify their state.

[0449] The "means for providing additional advice based on the driver's emotional state obtained from the emotion engine" is a function that provides appropriate advice or instructions to the driver based on the analysis results of the emotion engine.

[0450] "Means for generating appropriate voice or text messages based on prompt sentences from a generative AI model" refers to a function that uses a generative AI model to automatically create natural-sounding voice or text messages based on prompt sentences.

[0451] The system of the present invention is comprised of a device installed in an autonomous vehicle, a server, and a user, and provides real-time support and emotion recognition to the driver. Specifically, it has the following configuration and functions:

[0452] Terminal

[0453] The terminals used are navigation systems installed in vehicles, smartphones, etc. The main functions of the terminals are as follows:

[0454] Get current location:

[0455] The vehicle's GPS sensor is used to identify the user's current location, thereby obtaining location information.

[0456] Get weather and road conditions:

[0457] Use external weather APIs (e.g., OpenWeatherMap API) and traffic APIs (e.g., Google Maps API) to obtain weather information and road conditions for your current location and destination.

[0458] Sending and receiving data:

[0459] The device sends the acquired data to a server via the network, and receives the analysis results from the server and notifies the user using voice synthesis and text display functions.

[0460] Emotion engine included:

[0461] The emotion engine recognizes emotions from the driver's voice and facial expressions. For voice analysis, it uses IBM Watson (registered trademark) Tone Analyzer, and for facial recognition, it uses Microsoft Face API.

[0462] server

[0463] The server has the function of receiving and analyzing data sent from the terminal. The specific functions of the server are as follows:

[0464] Data reception and analysis:

[0465] The server receives and analyzes the current location data, weather information, road condition information, and emotion data from the emotion engine, using an algorithm that comprehensively considers traffic conditions, weather, recommended routes, and the user's emotional state.

[0466] Generate response data:

[0467] The server generates optimal routes and advice based on the analysis results. For example, if it detects that the driver is feeling stressed, it generates a message with relaxation suggestions.

[0468] Resend data:

[0469] The server transmits the generated response data to the terminal again and provides it to the user.

[0470] User

[0471] The user actually drives the vehicle using this system. The main functions are as follows:

[0472] Receiving information:

[0473] Users can receive information provided by the device and adjust their route and driving method.

[0474] Request for additional information:

[0475] If the user needs more information, they can ask additional questions and request the information from the server through the terminal.

[0476] Recognizing and Responding to Emotions:

[0477] The emotion engine analyzes the user's emotions and provides appropriate advice as needed, such as "Relax. We'll guide you to the best route."

[0478] Specific examples

[0479] When a user travels from Tokyo to Yokohama, the device uses GPS to determine their current location and obtains weather information and road conditions from an API. This data is sent to a server, which analyzes it and returns the result, "The expressway is congested, so we recommend taking an ordinary road." The device notifies the user of the result by voice, and the user selects an ordinary road. If the device determines that the user's tone of voice indicates stress, it provides additional advice, saying, "Please relax. We will guide you to the optimal route." An example of a prompt sentence from the generative AI model used in this case is, "Analyze the driver's emotions and guide them to the optimal route. If it determines that the driver is stressed, please also implement a function to play music for relaxation."

[0480] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0481] Step 1: Get your current location

[0482] The device uses the built-in GPS sensor to determine the user's current location. This location information provides the current latitude and longitude data, which is used in the next processing step.

[0483] Input: None (initial operation)

[0484] Output: Current location latitude and longitude data

[0485] Step 2: Get weather and road conditions

[0486] The device sends requests to external APIs (e.g., weather APIs and road traffic APIs) to obtain the latest weather and road conditions for the current location and destination, thereby providing information about the area the user plans to pass through.

[0487] Input: Latitude and longitude data of current location

[0488] Output: Weather and road conditions for current location and destination

[0489] Step 3: Sending data to the server

[0490] The terminal transmits the acquired current location data, weather information, and road condition information to the server, where the data is uploaded to the server via the network.

[0491] Input: current location latitude and longitude data, weather information, road condition information

[0492] Output: All data sent to the server

[0493] Step 4: Emotion analysis using the emotion engine

[0494] The device's built-in emotion engine analyzes the user's voice and facial expressions to identify their emotional state, using voice analysis and facial recognition technology to assess whether the user is relaxed or stressed.

[0495] Input: User's voice data, face image data

[0496] Output: User's emotional state data

[0497] Step 5: Receiving and analyzing data

[0498] The server receives and analyzes all data sent by the device (current location, weather information, road conditions, emotional state), and runs algorithms to generate optimal routes and additional advice.

[0499] Input: current location latitude and longitude data, weather information, road condition information, emotional state data

[0500] Output: Optimal route information, additional advice

[0501] Step 6: Generate and send response data

[0502] The server generates optimal routes and advice based on the analysis results, and uses a generative AI model to create voice or text messages based on the prompts, which are then sent back to the device.

[0503] Input: Optimal route information, additional advice

[0504] Output: Response data (route guidance, advice message)

[0505] Step 7: Notify users

[0506] The device then notifies the user of the response data received from the server. Using voice synthesis and display functions, the device provides guidance on the optimal route and emotional advice. This notification allows the user to adjust their driving style or take action to relax.

[0507] Input: Response data from the server

[0508] Output: Optimal route guidance, emotional advice notification

[0509] 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.

[0510] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0511] 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.

[0512] [Second embodiment]

[0513] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0514] 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.

[0515] 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).

[0516] 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.

[0517] 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.

[0518] 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).

[0519] 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.

[0520] 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.

[0521] 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.

[0522] 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.

[0523] 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.

[0524] 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."

[0525] The system of this invention is designed to provide real-time information and support to drivers when they are driving a car or motorcycle alone. The system consists of three main components: a terminal, a server, and a user.

[0526] 1. Terminal

[0527] The terminal is a navigation system installed in a car or motorcycle, and has the following functions:

[0528] Get current location

[0529] The device uses its built-in GPS sensor to determine the user's current location, which is then sent to a server and used as the basis for location information.

[0530] Obtaining weather and road conditions

[0531] The device will use external weather and traffic APIs to obtain weather and road conditions for the current location and destination, improving the accuracy of the information provided to users.

[0532] Sending and Receiving Data

[0533] The device sends the acquired data to the server and receives the analysis results from the server, which are then provided to the user using speech synthesis and text display functions.

[0534] 2. Server

[0535] The server receives data sent from the terminal and has the function of analyzing it. The specific functions of the server are as follows:

[0536] Data reception and analysis

[0537] The server receives data sent from the device, such as current location, weather information, road conditions, etc. It then analyzes this data and generates optimal routes and advice for the user.

[0538] Generating response data

[0539] The server generates response data based on the analysis results. For example, if there is traffic congestion, it generates data suggesting an alternative route.

[0540] Resend Data

[0541] The generated response data is sent back to the terminal and provided to the user.

[0542] 3. Users

[0543] Users can use this system to actually drive a car or motorcycle, and the system provides users with relevant information in real time.

[0544] Receiving information

[0545] The user receives information provided by the device. For example, if the device announces, "You are currently heading from Tokyo to Yokohama, but the expressway is congested. You will arrive faster if you use the local roads," the user can adjust their driving method accordingly.

[0546] Request for additional information

[0547] If the user needs more detailed information, they can ask a follow-up question, for example, "What's the weather like along the route?", and the device will again request the information from the server and provide the latest information.

[0548] Specific examples

[0549] For example, when a user travels from Tokyo to Yokohama, the device uses GPS to determine the user's current location and obtains weather information and road conditions from the API. This data is sent to the server, which analyzes it and returns the result, "The expressway is congested, so we recommend taking an ordinary road." The device notifies the user of the result by voice, and the user selects an ordinary road. If the user also asks, "What's the weather like on the ordinary road?", the device will query the server again and provide the latest weather information.

[0550] This system provides users with accurate information in real time, enabling them to travel efficiently and safely.

[0551] The processing flow will be explained below.

[0552] Step 1: Get your current location

[0553] Subject: Device

[0554] The device uses the built-in GPS sensor to determine the user's current location. Specifically, the GPS module obtains latitude and longitude information and stores this location data locally on the device.

[0555] Step 2: Get weather information

[0556] Subject: Device

[0557] The device sends a request to an external weather API to obtain weather information for the current location and destination. The request includes location information obtained by GPS. The device receives the response from the API, analyzes the weather information, and stores it.

[0558] Step 3: Obtaining road conditions

[0559] Subject: Device

[0560] The device sends a request to an external traffic API to obtain real-time road conditions, which also includes location information, receives a response from the API, analyzes the road condition data, and stores it.

[0561] Step 4: Sending data

[0562] Subject: Device

[0563] The device sends current location, weather, road conditions, and destination information to the server. Before sending, this data is formatted into a unified format. The data is sent over the Internet, and a confirmation message is received when the data has been successfully sent.

[0564] Step 5: Receiving and analyzing data

[0565] Subject: Server

[0566] The server receives the data sent from the device, analyzes it, and applies algorithms to generate the best route and advice for the user. The analysis process takes into account traffic conditions, weather, recommended routes, and more.

[0567] Step 6: Generate response data

[0568] Subject: Server

[0569] The server generates response data based on the analysis results, for example, a message such as "The current route is congested, so we recommend taking an open road." The generated data is then reformatted and prepared for transmission to the device.

[0570] Step 7: Sending response data

[0571] Subject: Server

[0572] The server sends the generated response data to the terminal. If the transmission is successful, the server goes into standby mode for the next data request.

[0573] Step 8: Receiving response data

[0574] Subject: Device

[0575] The device receives the response data from the server, analyzes the received data, and converts it into a format to be presented to the user. Specifically, it prepares for speech synthesis and text display.

[0576] Step 9: Provide information

[0577] Subject: Device

[0578] The device uses a voice synthesis function to notify the user, "The expressway is congested. You will arrive faster if you use the local road." It also displays text information on the display.

[0579] Step 10: Process requests for additional information

[0580] Subject: Device

[0581] When a user asks, "What's the weather like along that route?" the device parses this request and generates a new data request to ask the server for weather information again.

[0582] Step 11: Sending and Receiving New Data

[0583] Subject: Terminals and Servers

[0584] The device sends a new data request to the server, which receives the request and analyzes it again, and then sends the analysis results back to the device.

[0585] Step 12: Provide updates

[0586] Subject: Device

[0587] The device will provide the user with newly received weather information via voice and text, informing them that "The weather is currently clear on public roads and visibility is good."

[0588] Through the above steps, this system provides real-time information and support to drivers.

[0589] Example 1

[0590] 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."

[0591] Conventional driver assistance systems have faced challenges in providing users with appropriate information in real time. Providing timely updated data is particularly important given the frequently changing traffic and weather conditions. Furthermore, there is a lack of systems that can smoothly respond to additional requests for specific information that users require.

[0592] 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.

[0593] In this invention, the server includes means for identifying the current location, means for acquiring weather information using an external information system, means for acquiring road conditions using an external traffic information system, means for transmitting these data to the central control device, means for receiving analysis results from the central control device, and means for providing the received analysis results to the user as voice or text information, thereby enabling the user to obtain accurate information in real time and travel efficiently and safely.

[0594] "Means for determining current location" refers to a system that uses a location information acquisition device such as a GPS sensor to accurately determine the user's current location.

[0595] "Means of obtaining weather information using an external information system" refers to a mechanism for obtaining weather information for the current location and destination using external services such as weather information APIs.

[0596] "Means of obtaining road conditions using external traffic information systems" refers to a mechanism for obtaining road conditions at the current location and destination by utilizing external services such as traffic condition APIs.

[0597] The "means for transmitting these data to a central control device" refers to a communication means for transmitting the acquired current location, weather information, and road conditions to a central control device such as a server.

[0598] The "means for receiving the analysis results from the central control device" is a communication means for receiving the results of the data analyzed by the central control device such as a server.

[0599] "Means for providing the received analysis results to the user as voice or text information" refers to a mechanism for communicating the data analysis results received from the server to the user using voice synthesis technology or text display functions.

[0600] "Generating optimal route or advice" refers to the process in which the server analyzes the location, weather, and traffic data it receives and generates the most efficient and safe route or driving advice for the user.

[0601] The "means for receiving a request for additional information and again transmitting an information acquisition request to the central control device" is a mechanism for receiving a request for specific additional information from a user and again transmitting a data acquisition request to the central control device based on that request.

[0602] The system of the present invention consists of three main elements: the terminal, the server, and the user. Each element is described in detail below.

[0603] Terminal

[0604] The terminal consists of a navigation system installed in a car or motorcycle. Specific hardware includes a GPS sensor, a communication module (e.g., an LTE module), a voice synthesis device, a display, etc. The software also includes an API client for obtaining weather information (e.g., an OpenWeatherMap API client) and an API client for obtaining traffic information (e.g., a Google Maps API client). The terminal has the following functions:

[0605] 1. Obtaining your current location

[0606] Your device will use the built-in GPS sensor to determine your current location. For example, your device may display "Getting location..." and go through the process of obtaining GPS coordinates.

[0607] 2. Obtaining weather and road conditions

[0608] The device uses external weather APIs (e.g., OpenWeatherMap API) and traffic APIs (e.g., Google Maps API) to obtain weather information and road conditions for the current location and destination. For example, a message such as "Retrieving weather information and road conditions..." is displayed.

[0609] 3. Sending and Receiving Data

[0610] The device sends the acquired data to the server and receives the analysis results from the server. For example, when data is received from the server, the device displays "Data received."

[0611] server

[0612] The server acts as a central control unit, analyzing data sent from the terminals and generating response data. The server uses the following software and hardware:

[0613] 1. Data Reception and Analysis

[0614] The server receives data such as the current location, weather information, and road conditions sent from the device and begins analyzing it. For example, it calculates the optimal route using a generative AI model (e.g., a routing algorithm or traffic analysis model) based on the received data.

[0615] 2. Generating response data

[0616] The server generates response data for the user based on the analysis results. For example, the server may generate information such as "The highway is congested, so we recommend taking a regular road."

[0617] 3. Data retransmission

[0618] The server will retransmit the generated response data to the terminal. After this transmission process is successful, the server will record a message saying "Data transmission successful."

[0619] user

[0620] The user uses this system to actually drive a car or motorcycle. The user receives various information in real time via the terminal and can request additional information as needed. Specifically, the following operations are possible:

[0621] 1. Receiving information

[0622] The user receives information provided by the device. For example, the device may announce in voice, "You are currently traveling from Tokyo to Yokohama, but the expressway is congested. You will arrive faster if you use the local road."

[0623] 2. Request for additional information

[0624] If the user needs more detailed information, they can ask a follow-up question, for example, "What's the weather like along the route?", and the device will again request the information from the server and provide the latest information.

[0625] Specific examples

[0626] When a user travels from Tokyo to Yokohama, the following specific actions are taken:

[0627] 1. The device activates the GPS and obtains the current location (for example, near Tokyo Station).

[0628] 2. The device calls the OpenWeatherMap API to obtain weather information for Tokyo Station and Yokohama Station, and road conditions using the Google Maps API.

[0629] 3. The device sends this data to the server.

[0630] 4. The server receives the data and calculates the optimal route.

[0631] 5. The server generates data that says, "The highway is congested, so we recommend taking a regular road."

[0632] 6. The server sends the data to the device.

[0633] 7. The device notifies the user that "You'll arrive faster if you take the local road."

[0634] 8. The user requests additional information: "What's the weather like on the road?"

[0635] 9. The device sends the request to the server.

[0636] 10. The server analyzes the information and sends it to the device: "The weather on the public road is sunny."

[0637] 11. The device notifies the user that "The weather on the public road is clear."

[0638] Prompt Sentence Examples

[0639] 1. "What is the best route considering my current location and destination?"

[0640] 2. "If I use a public road, please let me know the weather information along the way."

[0641] 3. "Please provide traffic information on highways."

[0642] The overall flow of this system relies on the server for data processing, providing continuous real-time information, allowing users to reach their destinations comfortably and safely.

[0643] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0644] Step 1:

[0645] The device uses the GPS sensor to obtain the current location. Specifically, the device displays "Getting current location..." and obtains GPS coordinates (latitude and longitude). The input is data from the GPS sensor, and the output is the coordinate information of the current location.

[0646] Step 2:

[0647] The device obtains weather information and road conditions from an external API. Specifically, the device calls the OpenWeatherMap API to obtain weather information for the current location and destination, and calls the Google Maps API to obtain road conditions from the current location to the destination. The input is the coordinate information of the current location and destination, and the output is weather information and road condition information.

[0648] Step 3:

[0649] The device transmits the current location, weather information, and road conditions it has acquired to the server. Specifically, it displays "Sending data..." and sends all of this data to the server. The input is the current location, weather information, and road conditions data, and the output is the data transmitted to the server.

[0650] Step 4:

[0651] The server receives the data sent from the device and begins analyzing it. Specifically, the server stores it in a database and calculates the optimal route using a generative AI model. The input is the current location, weather information, and road condition data, and the output is the optimal route information.

[0652] Step 5:

[0653] The server generates response data based on the analysis results. Specifically, it creates response data such as "The highway is congested, so we recommend taking a local road." The input is optimal route information, and the output is response data.

[0654] Step 6:

[0655] The server sends the response data to the terminal. Specifically, it records the message "Data transmission successful" and sends the response data to the terminal. The input is the response data, and the output is the data sent to the terminal.

[0656] Step 7:

[0657] The response data received by the device is provided to the user as voice or text. Specifically, it notifies the user by voice that "You'll arrive faster if you use the public road." The input is the response data from the server, and the output is the information notified to the user.

[0658] Step 8:

[0659] If the user needs additional information, they ask the device a question. Specifically, the user asks aloud, "What's the weather like along that route?" The input is the question from the user, and the output is the question received by the device.

[0660] Step 9:

[0661] The device sends the user's question to the server. Specifically, it displays "Requesting additional information..." and sends the question to the server. The input is the question from the user, and the output is the question sent to the server.

[0662] Step 10:

[0663] The server analyzes the additional information and sends it back to the device. Specifically, it generates additional information such as "The weather on the public road is sunny." The input is the user's question, and the output is the additional information.

[0664] Step 11:

[0665] The terminal provides the received additional information to the user. Specifically, it notifies the user by voice, "The weather on the general road is sunny." The input is the additional information from the server, and the output is the additional information notified to the user.

[0666] (Application example 1)

[0667] 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."

[0668] A modern problem in car and motorcycle driving is the lack of real-time, accurate information. It is particularly difficult for drivers to understand the appropriate driving route, weather conditions, and traffic conditions while driving alone. This can result in reduced driving safety and efficiency. Furthermore, even when additional information is needed, it is dangerous for drivers to manually obtain the information while driving. There is a need to resolve these issues and improve driving safety and efficiency.

[0669] 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.

[0670] In this invention, the server includes a means for determining the current location, a means for acquiring weather information using an external API, a means for acquiring road conditions using an external API, a means for transmitting these data to the server, a means for receiving analysis results from the server, a means for providing the received analysis results to the user by voice or text, and a means for providing the driver with information they need by voice, thereby improving the safety and efficiency of automated driving. This allows the driver to understand appropriate driving routes, weather information, and traffic conditions in real time, significantly improving the safety and efficiency of driving. Furthermore, if additional information is requested, the information can be safely obtained through voice instructions, thereby reducing the burden on the driver and ensuring safety.

[0671] Key Word Definitions

[0672] "Means for determining current location" refers to a function that uses location information technology such as GPS to accurately determine the current location of the device.

[0673] "Means for obtaining weather information using an external API" is an interface for obtaining the latest weather information from an external weather information service.

[0674] "Means for obtaining road conditions using external APIs" refers to an interface for obtaining current road congestion conditions, accident information, etc. from external traffic information services.

[0675] "Means for transmitting these data to the server" refers to communication means for uploading acquired information such as current location, weather information, road conditions, etc. to the server.

[0676] The "means for receiving analysis results from the server" refers to a communication means for receiving analysis results and advice sent from the server at the terminal.

[0677] The "means for providing the received analysis results to the user by voice or text" refers to an interface for conveying the received information to the user by voice synthesis or text display.

[0678] "Means for providing the driver with the information they need via voice and improving the safety and efficiency of automated driving" refers to a function that provides the driver with the necessary information via voice in response to their request, thereby assisting in making the operation of automated vehicles safer and more efficient.

[0679] "Means for receiving a request for additional information from the user and sending a data acquisition request to the server again" is a function for accepting a request from a user for additional information and sending a data acquisition request to the server again.

[0680] MODE FOR CARRYING OUT THE INVENTION

[0681] The system of the present invention provides drivers with optimal information in real time when driving a vehicle, thereby improving safety and efficiency.

[0682] The system uses the following hardware and software:

[0683] Hardware

[0684] GPS module: Used to determine the vehicle's current location.

[0685] Smartphone or vehicle display: where system applications are installed and used to provide information.

[0686] Internet connection: Used to access external APIs and obtain necessary data.

[0687] Microphone and speaker: Used to provide information via voice and receive voice commands from the user.

[0688] software

[0689] Navigation software (e.g., Google Maps, Waze): used to provide route information and display analysis results.

[0690] Weather information API (e.g. OpenWeatherMap): Used to obtain weather information for your current location and destination.

[0691] Traffic information API (e.g., TomTom Traffic API): Used to obtain road congestion and accident information.

[0692] Description of the embodiment

[0693] The system's terminal first uses a GPS module to determine the driver's current location, then uses weather and traffic information APIs to obtain weather and road conditions for the current location and destination, and transmits this data to a server via an internet connection.

[0694] The server analyzes the transmitted data and generates the optimal route and advice for the driver. The analysis results are then sent back to the device. The device then notifies the user of the received analysis results in voice or text format. For example, it may say, "There is currently traffic congestion, so we recommend taking an ordinary road."

[0695] If the user needs more detailed information, they can ask additional questions by voice, such as "What's the weather like on the road?", and the device will request the information from the server again and provide the latest information. This allows the driver to always adjust their driving based on the latest information.

[0696] Specific examples

[0697] For example, suppose a user is driving from Tokyo to Yokohama. In this case, the device uses GPS to identify the user's current location and obtains weather and road information. This information is sent to the server, which analyzes it and generates the result, "The highway is congested, so it is recommended to take a regular road." The device then notifies the user of the result by voice.

[0698] When a user asks, "What's the weather like on the public road?", the device will again request weather information from the server and provide the latest weather information. This system allows users to obtain accurate information in real time, enabling them to travel efficiently and safely.

[0699] Prompt Sentence Examples

[0700] "What is the weather forecast for my current location?"

[0701] "Please provide traffic information."

[0702] "Calculate the best route."

[0703] "What's the weather like on the open road?"

[0704] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0705] Program processing steps

[0706] Step 1:

[0707] Get current location

[0708] The device uses the GPS module to determine the user's current location. At this time, it receives GPS data as input and outputs the latitude and longitude of the current location. Specifically, it obtains the numerical data of latitude and longitude from the GPS device and passes it to the system as the current location coordinates.

[0709] Step 2:

[0710] Get weather information

[0711] The device uses an external weather information API to obtain weather information for the current location and destination. At this time, the latitude and longitude obtained in step 1 are used as input, and the response data from the weather API is received as output. Specifically, the device sends an API request and parses the response in JSON format to extract the weather data.

[0712] Step 3:

[0713] Obtaining road conditions

[0714] The device uses an external traffic information API to obtain road conditions at the current location and destination. At this time, the latitude and longitude obtained in step 1 are used as input, and response data from the traffic API is received as output. Specifically, the device sends an API request, analyzes the response in JSON format, and extracts road condition data.

[0715] Step 4:

[0716] Sending data to the server

[0717] The device sends the acquired weather information, road conditions, and current location data to the server. At this time, the weather information, road condition data, latitude and longitude are sent together as input to the server, and a confirmation response is output. Specifically, the data is sent to the server using an HTTP POST request.

[0718] Step 5:

[0719] Data analysis by server

[0720] The server analyzes the received data and generates the optimal route and advice to provide to the driver. At this time, it analyzes the received input data (latitude and longitude, weather information, road conditions) and outputs the optimal route information. Specifically, it uses AI algorithms and routing algorithms to calculate the optimal driving route and recommended actions.

[0721] Step 6:

[0722] Resend analysis results

[0723] The server retransmits the analysis results to the terminal. At this time, it uses the optimal route information generated as input to construct the data to be sent to the terminal and actually sends it as output. Specifically, it returns the analysis results to the terminal in JSON format as an HTTP response.

[0724] Step 7:

[0725] User Notification

[0726] The device provides the analysis results received from the server to the user as voice or text. At this time, the optimal route information received from the server is used as input, and voice notification or text display is provided to the user as output. Specifically, voice notification is provided using speech synthesis software, or text data is displayed on the screen.

[0727] Step 8:

[0728] Processing requests for additional information

[0729] If the user requests additional information, the device retransmits the request to the server for further analysis and provision. The device receives the request for additional information via voice commands or button presses as input, constructs data to send to the server, and receives a response from the server as output. Specifically, the device analyzes the user's voice command using voice recognition software and sends a new request to the server.

[0730] 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.

[0731] The system of the present invention is designed to provide real-time information and appropriate support to drivers who are driving cars or motorcycles alone by recognizing their emotions. The system consists of four main components: a terminal, a server, a user, and an emotion engine.

[0732] 1. Terminal

[0733] The terminal is a navigation system installed in a car or motorcycle, and has the following functions:

[0734] Get current location

[0735] The device uses its built-in GPS sensor to determine the user's current location, which is then sent to a server and used as the basis for location information.

[0736] Obtaining weather and road conditions

[0737] The device will use external weather and traffic APIs to obtain weather and road conditions for the current location and destination, improving the accuracy of the information provided to users.

[0738] Sending and Receiving Data

[0739] The device sends the acquired data to the server and receives the analysis results from the server, which are then provided to the user using speech synthesis and text display functions.

[0740] Emotion engine included

[0741] The device is equipped with an emotion engine that recognizes emotions from the user's voice and facial expressions. The emotion engine analyzes the user's tone of voice and facial expressions to identify their emotional state.

[0742] 2. Server

[0743] The server receives data sent from the terminal and has the function of analyzing it. The specific functions of the server are as follows:

[0744] Data reception and analysis

[0745] The server receives the device's current location, weather information, road conditions, and the user's emotion data from the emotion engine. It then analyzes this data and applies algorithms to generate optimal routes and recommendations for the user. The analysis process comprehensively takes into account traffic conditions, weather, recommended routes, and the user's emotional state.

[0746] Generating response data

[0747] The server generates response data based on the analysis results. For example, if there is traffic congestion and the user is frustrated, it generates a message containing not only the best route but also advice on relaxation. The generated data is then reformatted and ready to be sent to the device.

[0748] Resend Data

[0749] The generated response data is sent back to the terminal and provided to the user.

[0750] 3. Users

[0751] Users can use this system to actually drive a car or motorcycle, and the system provides users with relevant information in real time.

[0752] Receiving information

[0753] The user receives information provided by the device. For example, if the device announces, "You are currently heading from Tokyo to Yokohama, but the expressway is congested. You will arrive faster if you use the local roads," the user can adjust their driving method accordingly.

[0754] Request for additional information

[0755] If the user needs more detailed information, they can ask a follow-up question, for example, "What's the weather like along that route?", and the device will again request the information from the server and provide the latest information.

[0756] Recognizing and Responding to Emotions

[0757] The user's tone of voice and facial expressions are analyzed to understand their emotional state. For example, if the user is feeling stressed, the device will provide support tailored to the user's mental state, such as by saying, "Relax. We'll guide you to the best route."

[0758] Specific examples

[0759] For example, when a user travels from Tokyo to Yokohama, the device uses GPS to determine their current location and obtains weather and road information from the API. This data is sent to a server, which analyzes it and returns the result, "The expressway is congested, so we recommend taking a regular road." The device then notifies the user of the result by voice, and the user selects a regular road. If the device determines that the user's voice tone sounds stressed, it will provide additional advice, such as, "Relax. We will guide you to the optimal route."

[0760] The system provides users with accurate, real-time, situation-specific information, enabling them to travel safely and efficiently. The adoption of an emotion engine also reduces stress and anxiety while driving, providing a safer and more comfortable driving environment.

[0761] The processing flow will be explained below.

[0762] Step 1: Get your current location

[0763] Subject: Device

[0764] The device uses the built-in GPS sensor to determine the user's current location. Specifically, the GPS module obtains latitude and longitude information and stores this location data locally on the device.

[0765] Step 2: Get weather information

[0766] Subject: Device

[0767] The device sends a request to an external weather API to obtain weather information for the current location and destination. The request includes location information obtained by GPS. The device receives the response from the API, analyzes the weather information, and stores it.

[0768] Step 3: Obtaining road conditions

[0769] Subject: Device

[0770] The device sends a request to an external traffic API to obtain real-time road conditions, which also includes location information, receives a response from the API, analyzes the road condition data, and stores it.

[0771] Step 4: Obtaining emotion data

[0772] Subject: Device

[0773] The device uses an emotion engine to obtain emotion data from the user's voice and facial expressions. The emotion engine uses voice tone and facial expression analysis algorithms to identify the user's emotional state (e.g., stressed, irritated, relaxed).

[0774] Step 5: Sending data

[0775] Subject: Device

[0776] The device transmits its current location, weather information, road conditions, and emotion data to the server, which then formats the data into a unified format. The transmission is done over the Internet, and the user receives a confirmation message when the data has been successfully sent.

[0777] Step 6: Receiving and analyzing data

[0778] Subject: Server

[0779] The server receives the data sent from the device, analyzes it, and applies algorithms to generate the best route and advice for the user. The analysis process takes into account factors such as traffic conditions, weather, and the user's emotional state.

[0780] Step 7: Generate response data

[0781] Subject: Server

[0782] The server generates response data based on the analysis results—for example, if the user is frustrated, it generates a message containing advice on relaxation as well as the best route—and the generated data is then reformatted and ready to be sent to the device.

[0783] Step 8: Sending response data

[0784] Subject: Server

[0785] The server sends the generated response data to the terminal. If the transmission is successful, the server goes into standby mode for the next data request.

[0786] Step 9: Receiving response data

[0787] Subject: Device

[0788] The device receives the response data from the server, analyzes the received data, and converts it into a format to be presented to the user. Specifically, it prepares for speech synthesis and text display.

[0789] Step 10: Provide information

[0790] Subject: Device

[0791] The device uses its voice synthesis function to notify the user, "The expressway is congested. You will arrive faster if you use the local road." It also displays text information on the display.

[0792] Step 11: Further emotional advice

[0793] Subject: Device

[0794] If the emotion engine determines that the user is feeling stressed, the device will notify them by saying, "Relax. We'll guide you to the best route," and provide additional advice tailored to the user's mental state.

[0795] Step 12: Process requests for additional information

[0796] Subject: Device

[0797] When a user asks, "What's the weather like along that route?" the device parses this request and generates a new data request to ask the server for weather information again.

[0798] Step 13: Sending and Receiving New Data

[0799] Subject: Terminals and Servers

[0800] The device sends a new data request to the server, which receives the request and analyzes it again, and then sends the analysis results back to the device.

[0801] Step 14: Provide updates

[0802] Subject: Device

[0803] The device will provide the user with newly received weather information via voice and text, informing them that "The weather is currently clear on public roads and visibility is good."

[0804] Through these steps, the system provides real-time information and support to drivers. The introduction of an emotion engine enables detailed support according to the user's emotional state, providing a safer and more comfortable driving environment.

[0805] Example 2

[0806] 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."

[0807] When a driver drives a car or motorcycle alone, they need not only real-time information but also the ability to recognize the driver's emotional state and provide appropriate support to reduce driving stress and anxiety, providing a safe and comfortable driving environment. However, current systems are unable to recognize the user's emotional state in real time and provide advice accordingly. To solve this problem, a new system is needed.

[0808] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0809] In this invention, the server includes a means for acquiring current location and weather information, a means for acquiring traffic information, and a means for recognizing the emotional state of the user, which makes it possible to acquire the user's current location and road conditions in real time, while also analyzing the user's emotional state, and provide optimal routes and advice.

[0810] "Means for determining current location" refers to a device or system that uses a GPS sensor to determine the current location of the driver's vehicle or motorcycle and obtains that information.

[0811] "Means for obtaining weather information using an external API" refers to a device or system for obtaining weather information for the current location and destination using the API of an external weather information service.

[0812] "Means for obtaining traffic information using an external API" refers to a device or system for obtaining road conditions and traffic congestion information using the API of an external traffic information service.

[0813] The "means for transmitting these data to the server" refers to a communication device or system for transmitting the driver's current location, weather information, traffic information, and the like to the server.

[0814] The "means for receiving the analysis results from the server" is a communication device or system for receiving the analysis results sent from the server.

[0815] The "means for analyzing acquired data and recognizing the user's emotional state" refers to an emotion recognition engine or analysis system that analyzes the user's voice and facial expressions and recognizes the user's emotional state.

[0816] The "means for generating response data based on the analysis results" refers to an algorithm or program for generating optimal routes and advice for users based on the data analyzed by the server.

[0817] "Means for providing the received analysis results to the user in voice or text" refers to a device or system for providing information to the user by synthesizing the analysis results received from the server as voice or displaying them as text.

[0818] This invention is a system that provides real-time information to drivers when they are driving a car or motorcycle alone, recognizes the driver's emotions, and provides appropriate support. This system mainly consists of four main components: a terminal, a server, a user, and an emotion engine.

[0819] Terminal

[0820] The terminal is a navigation system installed in a car or motorcycle, and specifically includes a GPS module, a communication module, a voice synthesizer, a text display device, and an emotion engine.

[0821] 1. Get your current location

[0822] The device uses a built-in GPS module (e.g., a Garmin GPS module) to determine the user's current location, which is then converted into JSON format and sent to the server.

[0823] 2. Obtaining weather and road conditions

[0824] The device uses external weather APIs (e.g., OpenWeatherMap API) and traffic APIs (e.g., Google Maps API) to obtain weather information and road conditions for the current location and destination. It sends an API request and sends the JSON-formatted data received as a response to the server.

[0825] 3. Sending and Receiving Data

[0826] The acquired data is sent to the server and the analysis results sent from the server are received. Communication is carried out using the HTTPS protocol.

[0827] 4. Equipped with an emotional engine

[0828] The device is equipped with an emotion engine (for example, Microsoft Azure Emotion API) that analyzes the user's voice and facial expressions. Specifically, it uses a camera and microphone to collect facial images and voice data, which are then sent to a server as emotion data.

[0829] server

[0830] The server has the function of receiving and analyzing data sent from the terminal.

[0831] 1. Data Analysis

[0832] The server comprehensively analyzes the received location, weather information, road conditions, and emotional data, and uses AI algorithms to generate optimal routes and advice, as well as generate response data based on the user's emotional state.

[0833] 2. Generate and send response data

[0834] Based on the analysis results, the engine generates response data for the user. For example, it creates a message such as, "The current weather is rainy. There is traffic congestion, so we recommend taking regular roads," and sends it to the device.

[0835] user

[0836] Users access the system through a terminal and actually drive a car or motorcycle.

[0837] 1. Receiving information

[0838] The user receives information provided by the device. For example, the device may use a voice synthesizer (e.g., Google Text-to-Speech) to notify the user that "the highway is congested. You will arrive faster if you take the local road," and the user can adjust their driving accordingly.

[0839] 2. Request for additional information

[0840] If the user needs more detailed information, they can request additional information using voice commands or touch operations. For example, if they ask, "What's the weather like along that route?", the device will again request the information from the server and provide the latest information.

[0841] 3. Recognizing and Responding to Emotions

[0842] If the user's tone of voice or facial expression is detected as stressed, the device will provide additional advice, such as "Relax. We'll guide you to the best route." This reduces stress and anxiety while driving, providing a safer and more comfortable driving environment.

[0843] Examples and prompts

[0844] For example, when a user travels from Tokyo to Yokohama, the following actions are performed:

[0845] The device uses GPS to determine its current location and obtains weather information and road conditions using the OpenWeatherMap API and Google Maps API.

[0846] The acquired data is sent to a server, which analyzes it and returns the result that "the highway is congested, so we recommend taking a regular road."

[0847] The device uses Google Text-to-Speech to notify the user via voice, "The highway is congested, so we recommend taking a regular road."

[0848] If the user's tone of voice is deemed stressful, the device will offer additional advice: "Relax. We'll guide you to the best route."

[0849] Example prompt sentence:

[0850] "Please provide the best route and weather information for traveling from Tokyo to Yokohama."

[0851] "Generate a message to a user who is currently stressed, with advice on how to relax."

[0852] In this way, the system of the present invention provides appropriate information in real time and optimal support according to the user's emotional state, providing a safe and comfortable driving experience.

[0853] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0854] Step 1:

[0855] The terminal uses a GPS module to determine the driver's current location.

[0856] Input: Satellite signal

[0857] Data processing: The GPS module receives signals from satellites and calculates latitude and longitude.

[0858] Output: Current location latitude and longitude data (JSON format)

[0859] Specific operation: The device's GPS sensor receives satellite signals, analyzes them to determine the current location, and obtains coordinate information.

[0860] Step 2:

[0861] The device uses weather and traffic APIs to obtain weather information and road conditions for the current location and destination.

[0862] Input: The latitude and longitude data determined by the device as its current location

[0863] Data processing: Constructing API requests, sending them to external weather and traffic APIs, and receiving responses in JSON format.

[0864] Output: Weather and road conditions for current and destination locations (JSON format)

[0865] What it does: The device sends requests to the OpenWeatherMap API and Google Maps API to obtain weather and road condition data for the current location and destination.

[0866] Step 3:

[0867] The terminal transmits data on the current location, weather information, and road conditions to the server.

[0868] Input: Weather information and road condition data acquired by the device (JSON format)

[0869] Data processing: The data is formatted in JSON format and sent to the server using the HTTPS protocol.

[0870] Output: Weather and road condition data sent to the server

[0871] Specific operation: The device collects the data and sends it to the server via HTTPS communication.

[0872] Step 4:

[0873] The terminal starts an emotion engine and acquires emotion data of the driver.

[0874] Input: Driver's voice and facial expression data

[0875] Data processing: Using speech recognition and facial expression analysis algorithms to identify emotional states.

[0876] Output: Emotion data (JSON format)

[0877] How it works: The emotion engine uses the camera and microphone to capture voice and facial expressions, which are then analyzed to determine the emotional state.

[0878] Step 5:

[0879] The terminal transmits the emotion data to the server.

[0880] Input: Emotion data acquired by the device (JSON format)

[0881] Data processing: The data is formatted in JSON format and sent to the server using the HTTPS protocol.

[0882] Output: Emotion data sent to the server

[0883] Specific operation: The device compiles emotion data and sends it to the server via HTTPS.

[0884] Step 6:

[0885] The server receives and analyzes the data sent from the terminal.

[0886] Input: Current location, weather information, road conditions, and emotion data (JSON format) sent from the device

[0887] Data processing: AI algorithms are used to analyze data and generate optimal routes and advice.

[0888] Output: Analysis result (JSON format)

[0889] Specific operation: The server comprehensively analyzes the received data and generates optimal route guidance and advice to provide to the driver.

[0890] Step 7:

[0891] The server generates response data based on the analysis results.

[0892] Input: Analyzed current location, weather information, road conditions, emotion data (JSON format)

[0893] Data processing: Construct a response message based on the analysis results.

[0894] Output: Response data (JSON format)

[0895] Specific operation: The server generates a response message from the analysis results and prepares to send it to the terminal.

[0896] Step 8:

[0897] The server transmits the response data to the terminal.

[0898] Input: Response data generated by the server (JSON format)

[0899] Data processing: The data is formatted in JSON format and sent to the terminal using the HTTPS protocol.

[0900] Output: Response data sent to the terminal

[0901] Specific operation: The server compiles the response data and sends it to the terminal via HTTPS communication.

[0902] Step 9:

[0903] The device receives the analysis results from the server and provides them to the user in voice or text format.

[0904] Input: Response data sent from the server (JSON format)

[0905] Data processing: Analyze the data and provide it to the user using speech synthesis or text display functions.

[0906] Output: Audio or text information provided to the user

[0907] Specific operation: The device analyzes the received data and notifies the user via voice using Google Text-to-Speech.

[0908] Step 10:

[0909] If the user requests additional information, the terminal again sends a data acquisition request to the server.

[0910] Input: Request for additional information from the user (voice command, touch action)

[0911] Data processing: Analyze the user's request and send a request to the server to retrieve the required information again.

[0912] Output: Request for more information sent to the server

[0913] Specific operation: The device sends a request to the server again based on the user's request, preparing to provide the latest information.

[0914] Step 11:

[0915] If the user's tone of voice or facial expression indicates stress, the device will offer additional emotional support advice.

[0916] Input: Detection results from the emotion recognition engine (emotion data such as stress, irritation, relaxation, etc.)

[0917] Data processing: Generate appropriate advice for stress reduction.

[0918] Output: Audio or text advice to the user to relax

[0919] What it does: The device analyzes emotional data and provides voice messages such as, "Relax. We'll guide you to the best route."

[0920] (Application example 2)

[0921] 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."

[0922] Conventional navigation systems are limited to providing information on the current location, weather, and road conditions, and are unable to provide appropriate support that takes into account the driver's psychological state. Therefore, the challenge is to reduce the stress and anxiety felt by drivers and provide a safe and comfortable driving environment.

[0923] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0924] In this invention, the server includes means for identifying the current location, means for acquiring weather information using an external API, means for acquiring road conditions using an external API, means for analyzing the emotional state of the driver using an emotion engine, means for providing additional advice based on the emotional state of the driver obtained from the emotion engine, and means for generating an appropriate voice or text message based on a prompt sentence of the generative AI model. This makes it possible to recognize the emotional state of the driver in real time and provide appropriate information and advice according to that state.

[0925] "Means for determining current location" refers to a function that obtains the user's location information using a GPS sensor.

[0926] "Means of obtaining weather information using external APIs" refers to a function that obtains weather information for the current location and destination using cloud services or publicly available APIs.

[0927] "Means of obtaining road conditions using external APIs" refers to a function that obtains traffic conditions and road congestion information using cloud services or publicly available APIs.

[0928] The "means for transmitting these data to the server" is a function for transmitting the acquired current location, weather information, and road condition information to the server via the network.

[0929] The "means for receiving analysis results from the server" is a function for receiving data analysis results sent from the server at the terminal.

[0930] "Means of providing the received analysis results to the user by voice or text" refers to a function that notifies the user of the analysis results through voice synthesis technology or a display.

[0931] The "emotion engine that analyzes the driver's emotional state" is a system that uses voice analysis and facial recognition technology to evaluate the driver's emotions and identify their state.

[0932] The "means for providing additional advice based on the driver's emotional state obtained from the emotion engine" is a function that provides appropriate advice or instructions to the driver based on the analysis results of the emotion engine.

[0933] "Means for generating appropriate voice or text messages based on prompt sentences from a generative AI model" refers to a function that uses a generative AI model to automatically create natural-sounding voice or text messages based on prompt sentences.

[0934] The system of the present invention is comprised of a device installed in an autonomous vehicle, a server, and a user, and provides real-time support and emotion recognition to the driver. Specifically, it has the following configuration and functions:

[0935] Terminal

[0936] The terminals used are navigation systems installed in vehicles, smartphones, etc. The main functions of the terminals are as follows:

[0937] Get current location:

[0938] The vehicle's GPS sensor is used to identify the user's current location, thereby obtaining location information.

[0939] Get weather and road conditions:

[0940] Use external weather APIs (e.g., OpenWeatherMap API) and traffic APIs (e.g., Google Maps API) to obtain weather information and road conditions for your current location and destination.

[0941] Sending and receiving data:

[0942] The device sends the acquired data to a server via the network, and receives the analysis results from the server and notifies the user using voice synthesis and text display functions.

[0943] Emotion engine included:

[0944] The emotion engine recognizes emotions from the driver's voice and facial expressions. It uses IBM Watson Tone Analyzer for voice analysis and Microsoft Face API for facial recognition.

[0945] server

[0946] The server has the function of receiving and analyzing data sent from the terminal. The specific functions of the server are as follows:

[0947] Data reception and analysis:

[0948] The server receives and analyzes the current location data, weather information, road condition information, and emotion data from the emotion engine, using an algorithm that comprehensively considers traffic conditions, weather, recommended routes, and the user's emotional state.

[0949] Generate response data:

[0950] The server generates optimal routes and advice based on the analysis results. For example, if it detects that the driver is feeling stressed, it generates a message with relaxation suggestions.

[0951] Resend data:

[0952] The server transmits the generated response data to the terminal again and provides it to the user.

[0953] User

[0954] The user actually drives the vehicle using this system. The main functions are as follows:

[0955] Receiving information:

[0956] Users can receive information provided by the device and adjust their route and driving method.

[0957] Request for additional information:

[0958] If the user needs more information, they can ask additional questions and request the information from the server through the terminal.

[0959] Recognizing and Responding to Emotions:

[0960] The emotion engine analyzes the user's emotions and provides appropriate advice as needed, such as "Relax. We'll guide you to the best route."

[0961] Specific examples

[0962] When a user travels from Tokyo to Yokohama, the device uses GPS to determine their current location and obtains weather information and road conditions from an API. This data is sent to a server, which analyzes it and returns the result, "The expressway is congested, so we recommend taking an ordinary road." The device notifies the user of the result by voice, and the user selects an ordinary road. If the device determines that the user's tone of voice indicates stress, it provides additional advice, saying, "Please relax. We will guide you to the optimal route." An example of a prompt sentence from the generative AI model used in this case is, "Analyze the driver's emotions and guide them to the optimal route. If it determines that the driver is stressed, please also implement a function to play music for relaxation."

[0963] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0964] Step 1: Get your current location

[0965] The device uses the built-in GPS sensor to determine the user's current location. This location information provides the current latitude and longitude data, which is used in the next processing step.

[0966] Input: None (initial operation)

[0967] Output: Current location latitude and longitude data

[0968] Step 2: Get weather and road conditions

[0969] The device sends requests to external APIs (e.g., weather APIs and road traffic APIs) to obtain the latest weather and road conditions for the current location and destination, thereby providing information about the area the user plans to pass through.

[0970] Input: Latitude and longitude data of current location

[0971] Output: Weather and road conditions for current location and destination

[0972] Step 3: Sending data to the server

[0973] The terminal transmits the acquired current location data, weather information, and road condition information to the server, where the data is uploaded to the server via the network.

[0974] Input: current location latitude and longitude data, weather information, road condition information

[0975] Output: All data sent to the server

[0976] Step 4: Emotion analysis using the emotion engine

[0977] The device's built-in emotion engine analyzes the user's voice and facial expressions to identify their emotional state, using voice analysis and facial recognition technology to assess whether the user is relaxed or stressed.

[0978] Input: User's voice data, face image data

[0979] Output: User's emotional state data

[0980] Step 5: Receiving and analyzing data

[0981] The server receives and analyzes all data sent by the device (current location, weather information, road conditions, emotional state), and runs algorithms to generate optimal routes and additional advice.

[0982] Input: current location latitude and longitude data, weather information, road condition information, emotional state data

[0983] Output: Optimal route information, additional advice

[0984] Step 6: Generate and send response data

[0985] The server generates optimal routes and advice based on the analysis results, and uses a generative AI model to create voice or text messages based on the prompts, which are then sent back to the device.

[0986] Input: Optimal route information, additional advice

[0987] Output: Response data (route guidance, advice message)

[0988] Step 7: Notify users

[0989] The device then notifies the user of the response data received from the server. Using voice synthesis and display functions, the device provides guidance on the optimal route and emotional advice. This notification allows the user to adjust their driving style or take action to relax.

[0990] Input: Response data from the server

[0991] Output: Optimal route guidance, emotional advice notification

[0992] 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.

[0993] 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.

[0994] 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.

[0995] [Third embodiment]

[0996] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0997] 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.

[0998] 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).

[0999] 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.

[1000] 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.

[1001] 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).

[1002] 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.

[1003] 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.

[1004] 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.

[1005] 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.

[1006] 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.

[1007] 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."

[1008] The system of this invention is designed to provide real-time information and support to drivers when they are driving a car or motorcycle alone. The system consists of three main components: a terminal, a server, and a user.

[1009] 1. Terminal

[1010] The terminal is a navigation system installed in a car or motorcycle, and has the following functions:

[1011] Get current location

[1012] The device uses its built-in GPS sensor to determine the user's current location, which is then sent to a server and used as the basis for location information.

[1013] Obtaining weather and road conditions

[1014] The device will use external weather and traffic APIs to obtain weather and road conditions for the current location and destination, improving the accuracy of the information provided to users.

[1015] Sending and Receiving Data

[1016] The device sends the acquired data to the server and receives the analysis results from the server, which are then provided to the user using speech synthesis and text display functions.

[1017] 2. Server

[1018] The server receives data sent from the terminal and has the function of analyzing it. The specific functions of the server are as follows:

[1019] Data reception and analysis

[1020] The server receives data sent from the device, such as current location, weather information, road conditions, etc. It then analyzes this data and generates optimal routes and advice for the user.

[1021] Generating response data

[1022] The server generates response data based on the analysis results. For example, if there is traffic congestion, it generates data suggesting an alternative route.

[1023] Resend Data

[1024] The generated response data is sent back to the terminal and provided to the user.

[1025] 3. Users

[1026] Users can use this system to actually drive a car or motorcycle, and the system provides users with relevant information in real time.

[1027] Receiving information

[1028] The user receives information provided by the device. For example, if the device announces, "You are currently heading from Tokyo to Yokohama, but the expressway is congested. You will arrive faster if you use the local roads," the user can adjust their driving method accordingly.

[1029] Request for additional information

[1030] If the user needs more detailed information, they can ask a follow-up question, for example, "What's the weather like along the route?", and the device will again request the information from the server and provide the latest information.

[1031] Specific examples

[1032] For example, when a user travels from Tokyo to Yokohama, the device uses GPS to determine the user's current location and obtains weather information and road conditions from the API. This data is sent to the server, which analyzes it and returns the result, "The expressway is congested, so we recommend taking an ordinary road." The device notifies the user of the result by voice, and the user selects an ordinary road. If the user also asks, "What's the weather like on the ordinary road?", the device will query the server again and provide the latest weather information.

[1033] This system provides users with accurate information in real time, enabling them to travel efficiently and safely.

[1034] The processing flow will be explained below.

[1035] Step 1: Get your current location

[1036] Subject: Device

[1037] The device uses the built-in GPS sensor to determine the user's current location. Specifically, the GPS module obtains latitude and longitude information and stores this location data locally on the device.

[1038] Step 2: Get weather information

[1039] Subject: Device

[1040] The device sends a request to an external weather API to obtain weather information for the current location and destination. The request includes location information obtained by GPS. The device receives the response from the API, analyzes the weather information, and stores it.

[1041] Step 3: Obtaining road conditions

[1042] Subject: Device

[1043] The device sends a request to an external traffic API to obtain real-time road conditions, which also includes location information, receives a response from the API, analyzes the road condition data, and stores it.

[1044] Step 4: Sending data

[1045] Subject: Device

[1046] The device sends current location, weather, road conditions, and destination information to the server. Before sending, this data is formatted into a unified format. The data is sent over the Internet, and a confirmation message is received when the data has been successfully sent.

[1047] Step 5: Receiving and analyzing data

[1048] Subject: Server

[1049] The server receives the data sent from the device, analyzes it, and applies algorithms to generate the best route and advice for the user. The analysis process takes into account traffic conditions, weather, recommended routes, and more.

[1050] Step 6: Generate response data

[1051] Subject: Server

[1052] The server generates response data based on the analysis results, for example, a message such as "The current route is congested, so we recommend taking an open road." The generated data is then reformatted and prepared for transmission to the device.

[1053] Step 7: Sending response data

[1054] Subject: Server

[1055] The server sends the generated response data to the terminal. If the transmission is successful, the server goes into standby mode for the next data request.

[1056] Step 8: Receiving response data

[1057] Subject: Device

[1058] The device receives the response data from the server, analyzes the received data, and converts it into a format to be presented to the user. Specifically, it prepares for speech synthesis and text display.

[1059] Step 9: Provide information

[1060] Subject: Device

[1061] The device uses a voice synthesis function to notify the user, "The expressway is congested. You will arrive faster if you use the local road." It also displays text information on the display.

[1062] Step 10: Process requests for additional information

[1063] Subject: Device

[1064] When a user asks, "What's the weather like along that route?" the device parses this request and generates a new data request to ask the server for weather information again.

[1065] Step 11: Sending and Receiving New Data

[1066] Subject: Terminals and Servers

[1067] The device sends a new data request to the server, which receives the request and analyzes it again, and then sends the analysis results back to the device.

[1068] Step 12: Provide updates

[1069] Subject: Device

[1070] The device will provide the user with newly received weather information via voice and text, informing them that "The weather is currently clear on public roads and visibility is good."

[1071] Through the above steps, this system provides real-time information and support to drivers.

[1072] Example 1

[1073] 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."

[1074] Conventional driver assistance systems have faced challenges in providing users with appropriate information in real time. Providing timely updated data is particularly important given the frequently changing traffic and weather conditions. Furthermore, there is a lack of systems that can smoothly respond to additional requests for specific information that users require.

[1075] 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.

[1076] In this invention, the server includes means for identifying the current location, means for acquiring weather information using an external information system, means for acquiring road conditions using an external traffic information system, means for transmitting these data to the central control device, means for receiving analysis results from the central control device, and means for providing the received analysis results to the user as voice or text information, thereby enabling the user to obtain accurate information in real time and travel efficiently and safely.

[1077] "Means for determining current location" refers to a system that uses a location information acquisition device such as a GPS sensor to accurately determine the user's current location.

[1078] "Means of obtaining weather information using an external information system" refers to a mechanism for obtaining weather information for the current location and destination using external services such as weather information APIs.

[1079] "Means of obtaining road conditions using external traffic information systems" refers to a mechanism for obtaining road conditions at the current location and destination by utilizing external services such as traffic condition APIs.

[1080] The "means for transmitting these data to a central control device" refers to a communication means for transmitting the acquired current location, weather information, and road conditions to a central control device such as a server.

[1081] The "means for receiving the analysis results from the central control device" is a communication means for receiving the results of the data analyzed by the central control device such as a server.

[1082] "Means for providing the received analysis results to the user as voice or text information" refers to a mechanism for communicating the data analysis results received from the server to the user using voice synthesis technology or text display functions.

[1083] "Generating optimal route or advice" refers to the process in which the server analyzes the location, weather, and traffic data it receives and generates the most efficient and safe route or driving advice for the user.

[1084] The "means for receiving a request for additional information and again transmitting an information acquisition request to the central control device" is a mechanism for receiving a request for specific additional information from a user and again transmitting a data acquisition request to the central control device based on that request.

[1085] The system of the present invention consists of three main elements: the terminal, the server, and the user. Each element is described in detail below.

[1086] Terminal

[1087] The terminal consists of a navigation system installed in a car or motorcycle. Specific hardware includes a GPS sensor, a communication module (e.g., an LTE module), a voice synthesis device, a display, etc. The software also includes an API client for obtaining weather information (e.g., an OpenWeatherMap API client) and an API client for obtaining traffic information (e.g., a Google Maps API client). The terminal has the following functions:

[1088] 1. Obtaining your current location

[1089] Your device will use the built-in GPS sensor to determine your current location. For example, your device may display "Getting location..." and go through the process of obtaining GPS coordinates.

[1090] 2. Obtaining weather and road conditions

[1091] The device uses external weather APIs (e.g., OpenWeatherMap API) and traffic APIs (e.g., Google Maps API) to obtain weather information and road conditions for the current location and destination. For example, a message such as "Retrieving weather information and road conditions..." is displayed.

[1092] 3. Sending and Receiving Data

[1093] The device sends the acquired data to the server and receives the analysis results from the server. For example, when data is received from the server, the device displays "Data received."

[1094] server

[1095] The server acts as a central control unit, analyzing data sent from the terminals and generating response data. The server uses the following software and hardware:

[1096] 1. Data Reception and Analysis

[1097] The server receives data such as the current location, weather information, and road conditions sent from the device and begins analyzing it. For example, it calculates the optimal route using a generative AI model (e.g., a routing algorithm or traffic analysis model) based on the received data.

[1098] 2. Generating response data

[1099] The server generates response data for the user based on the analysis results. For example, the server may generate information such as "The highway is congested, so we recommend taking a regular road."

[1100] 3. Data retransmission

[1101] The server will retransmit the generated response data to the terminal. After this transmission process is successful, the server will record a message saying "Data transmission successful."

[1102] user

[1103] The user uses this system to actually drive a car or motorcycle. The user receives various information in real time via the terminal and can request additional information as needed. Specifically, the following operations are possible:

[1104] 1. Receiving information

[1105] The user receives information provided by the device. For example, the device may announce in voice, "You are currently traveling from Tokyo to Yokohama, but the expressway is congested. You will arrive faster if you use the local road."

[1106] 2. Request for additional information

[1107] If the user needs more detailed information, they can ask a follow-up question, for example, "What's the weather like along the route?", and the device will again request the information from the server and provide the latest information.

[1108] Specific examples

[1109] When a user travels from Tokyo to Yokohama, the following specific actions are taken:

[1110] 1. The device activates the GPS and obtains the current location (for example, near Tokyo Station).

[1111] 2. The device calls the OpenWeatherMap API to obtain weather information for Tokyo Station and Yokohama Station, and road conditions using the Google Maps API.

[1112] 3. The device sends this data to the server.

[1113] 4. The server receives the data and calculates the optimal route.

[1114] 5. The server generates data that says, "The highway is congested, so we recommend taking a regular road."

[1115] 6. The server sends the data to the device.

[1116] 7. The device notifies the user that "You'll arrive faster if you take the local road."

[1117] 8. The user requests additional information: "What's the weather like on the road?"

[1118] 9. The device sends the request to the server.

[1119] 10. The server analyzes the information and sends it to the device: "The weather on the public road is sunny."

[1120] 11. The device notifies the user that "The weather on the public road is clear."

[1121] Prompt Sentence Examples

[1122] 1. "What is the best route considering my current location and destination?"

[1123] 2. "If I use a public road, please let me know the weather information along the way."

[1124] 3. "Please provide traffic information on highways."

[1125] The overall flow of this system relies on the server for data processing, providing continuous real-time information, allowing users to reach their destinations comfortably and safely.

[1126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1127] Step 1:

[1128] The device uses the GPS sensor to obtain the current location. Specifically, the device displays "Getting current location..." and obtains GPS coordinates (latitude and longitude). The input is data from the GPS sensor, and the output is the coordinate information of the current location.

[1129] Step 2:

[1130] The device obtains weather information and road conditions from an external API. Specifically, the device calls the OpenWeatherMap API to obtain weather information for the current location and destination, and calls the Google Maps API to obtain road conditions from the current location to the destination. The input is the coordinate information of the current location and destination, and the output is weather information and road condition information.

[1131] Step 3:

[1132] The device transmits the current location, weather information, and road conditions it has acquired to the server. Specifically, it displays "Sending data..." and sends all of this data to the server. The input is the current location, weather information, and road conditions data, and the output is the data transmitted to the server.

[1133] Step 4:

[1134] The server receives the data sent from the device and begins analyzing it. Specifically, the server stores it in a database and calculates the optimal route using a generative AI model. The input is the current location, weather information, and road condition data, and the output is the optimal route information.

[1135] Step 5:

[1136] The server generates response data based on the analysis results. Specifically, it creates response data such as "The highway is congested, so we recommend taking a local road." The input is optimal route information, and the output is response data.

[1137] Step 6:

[1138] The server sends the response data to the terminal. Specifically, it records the message "Data transmission successful" and sends the response data to the terminal. The input is the response data, and the output is the data sent to the terminal.

[1139] Step 7:

[1140] The response data received by the device is provided to the user as voice or text. Specifically, it notifies the user by voice that "You'll arrive faster if you use the public road." The input is the response data from the server, and the output is the information notified to the user.

[1141] Step 8:

[1142] If the user needs additional information, they ask the device a question. Specifically, the user asks aloud, "What's the weather like along that route?" The input is the question from the user, and the output is the question received by the device.

[1143] Step 9:

[1144] The device sends the user's question to the server. Specifically, it displays "Requesting additional information..." and sends the question to the server. The input is the question from the user, and the output is the question sent to the server.

[1145] Step 10:

[1146] The server analyzes the additional information and sends it back to the device. Specifically, it generates additional information such as "The weather on the public road is sunny." The input is the user's question, and the output is the additional information.

[1147] Step 11:

[1148] The terminal provides the received additional information to the user. Specifically, it notifies the user by voice, "The weather on the general road is sunny." The input is the additional information from the server, and the output is the additional information notified to the user.

[1149] (Application example 1)

[1150] 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."

[1151] A modern problem in car and motorcycle driving is the lack of real-time, accurate information. It is particularly difficult for drivers to understand the appropriate driving route, weather conditions, and traffic conditions while driving alone. This can result in reduced driving safety and efficiency. Furthermore, even when additional information is needed, it is dangerous for drivers to manually obtain the information while driving. There is a need to resolve these issues and improve driving safety and efficiency.

[1152] 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.

[1153] In this invention, the server includes a means for determining the current location, a means for acquiring weather information using an external API, a means for acquiring road conditions using an external API, a means for transmitting these data to the server, a means for receiving analysis results from the server, a means for providing the received analysis results to the user by voice or text, and a means for providing the driver with information they need by voice, thereby improving the safety and efficiency of automated driving. This allows the driver to understand appropriate driving routes, weather information, and traffic conditions in real time, significantly improving the safety and efficiency of driving. Furthermore, if additional information is requested, the information can be safely obtained through voice instructions, thereby reducing the burden on the driver and ensuring safety.

[1154] Key Word Definitions

[1155] "Means for determining current location" refers to a function that uses location information technology such as GPS to accurately determine the current location of the device.

[1156] "Means for obtaining weather information using an external API" is an interface for obtaining the latest weather information from an external weather information service.

[1157] "Means for obtaining road conditions using external APIs" refers to an interface for obtaining current road congestion status and accident information from external traffic information services.

[1158] "Means for transmitting these data to the server" refers to communication means for uploading acquired information such as current location, weather information, road conditions, etc. to the server.

[1159] The "means for receiving analysis results from the server" refers to a communication means for receiving analysis results and advice sent from the server at the terminal.

[1160] The "means for providing the received analysis results to the user by voice or text" refers to an interface for conveying the received information to the user by voice synthesis or text display.

[1161] "Means for providing the driver with the information they need via voice and improving the safety and efficiency of automated driving" refers to a function that provides the driver with the necessary information via voice in response to their request, thereby assisting in making the operation of automated vehicles safer and more efficient.

[1162] "Means for receiving a request for additional information from the user and sending a data acquisition request to the server again" is a function for accepting a request from a user for additional information and sending a data acquisition request to the server again.

[1163] MODE FOR CARRYING OUT THE INVENTION

[1164] The system of the present invention provides drivers with optimal information in real time when driving a vehicle, thereby improving safety and efficiency.

[1165] The system uses the following hardware and software:

[1166] Hardware

[1167] GPS module: Used to determine the vehicle's current location.

[1168] Smartphone or in-car display: where system applications are installed and used to provide information.

[1169] Internet connection: Used to access external APIs and obtain necessary data.

[1170] Microphone and speaker: Used to provide information via voice and receive voice commands from the user.

[1171] software

[1172] Navigation software (e.g., Google Maps, Waze): used to provide route information and display analysis results.

[1173] Weather information API (e.g. OpenWeatherMap): Used to obtain weather information for the current location and destination.

[1174] Traffic information API (e.g., TomTom Traffic API): Used to obtain road congestion and accident information.

[1175] Description of the embodiment

[1176] The system's terminal first uses a GPS module to determine the driver's current location, then uses weather and traffic information APIs to obtain weather and road conditions for the current location and destination, and transmits this data to a server via an internet connection.

[1177] The server analyzes the transmitted data and generates the optimal route and advice for the driver. The analysis results are then sent back to the device. The device then notifies the user of the received analysis results in voice or text format. For example, it may say, "There is currently traffic congestion, so we recommend taking an ordinary road."

[1178] If the user needs more detailed information, they can ask additional questions by voice, such as "What's the weather like on the road?", and the device will request the information from the server again and provide the latest information. This allows the driver to adjust their driving based on the latest information.

[1179] Specific examples

[1180] For example, suppose a user is driving from Tokyo to Yokohama. In this case, the device uses GPS to identify the user's current location and obtains weather and road information. This information is sent to the server, which analyzes it and generates the result, "The highway is congested, so it is recommended to take a regular road." The device then notifies the user of the result by voice.

[1181] When a user asks, "What's the weather like on the public road?", the device will again request weather information from the server and provide the latest weather information. This system allows users to obtain accurate information in real time, enabling them to travel efficiently and safely.

[1182] Prompt Sentence Examples

[1183] "What is the weather forecast for my current location?"

[1184] "Please provide traffic information."

[1185] "Calculate the best route."

[1186] "What's the weather like on the open road?"

[1187] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1188] Program processing steps

[1189] Step 1:

[1190] Get current location

[1191] The device uses the GPS module to determine the user's current location. At this time, it receives GPS data as input and outputs the latitude and longitude of the current location. Specifically, it obtains the numerical data of latitude and longitude from the GPS device and passes it to the system as the current location coordinates.

[1192] Step 2:

[1193] Get weather information

[1194] The device uses an external weather information API to obtain weather information for the current location and destination. At this time, the latitude and longitude obtained in step 1 are used as input, and the response data from the weather API is received as output. Specifically, the device sends an API request and parses the response in JSON format to extract the weather data.

[1195] Step 3:

[1196] Obtaining road conditions

[1197] The device uses an external traffic information API to obtain road conditions at the current location and destination. At this time, the latitude and longitude obtained in step 1 are used as input, and response data from the traffic API is received as output. Specifically, the device sends an API request, analyzes the response in JSON format, and extracts road condition data.

[1198] Step 4:

[1199] Sending data to the server

[1200] The device sends the acquired weather information, road conditions, and current location data to the server. At this time, the weather information, road condition data, latitude and longitude are sent together as input to the server, and a confirmation response is output. Specifically, the data is sent to the server using an HTTP POST request.

[1201] Step 5:

[1202] Data analysis by server

[1203] The server analyzes the received data and generates the optimal route and advice to provide to the driver. At this time, it analyzes the received input data (latitude and longitude, weather information, road conditions) and outputs the optimal route information. Specifically, it uses AI algorithms and routing algorithms to calculate the optimal driving route and recommended actions.

[1204] Step 6:

[1205] Resend analysis results

[1206] The server retransmits the analysis results to the terminal. At this time, it uses the optimal route information generated as input to construct the data to be sent to the terminal and actually sends it as output. Specifically, it returns the analysis results to the terminal in JSON format as an HTTP response.

[1207] Step 7:

[1208] User Notification

[1209] The device provides the analysis results received from the server to the user as voice or text. At this time, the optimal route information received from the server is used as input, and voice notification or text display is provided to the user as output. Specifically, voice notification is provided using speech synthesis software, or text data is displayed on the screen.

[1210] Step 8:

[1211] Processing requests for additional information

[1212] If the user requests additional information, the device retransmits the request to the server for further analysis and provision. The device receives the request for additional information via voice commands or button presses as input, constructs data to send to the server, and receives a response from the server as output. Specifically, the device analyzes the user's voice command using voice recognition software and sends a new request to the server.

[1213] 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.

[1214] The system of the present invention is designed to provide real-time information and appropriate support to drivers who are driving cars or motorcycles alone by recognizing their emotions. The system consists of four main components: a terminal, a server, a user, and an emotion engine.

[1215] 1. Terminal

[1216] The terminal is a navigation system installed in a car or motorcycle, and has the following functions:

[1217] Get current location

[1218] The device uses its built-in GPS sensor to determine the user's current location, which is then sent to a server and used as the basis for location information.

[1219] Obtaining weather and road conditions

[1220] The device will use external weather and traffic APIs to obtain weather and road conditions for the current location and destination, improving the accuracy of the information provided to users.

[1221] Sending and Receiving Data

[1222] The device sends the acquired data to the server and receives the analysis results from the server, which are then provided to the user using speech synthesis and text display functions.

[1223] Emotion engine included

[1224] The device is equipped with an emotion engine that recognizes emotions from the user's voice and facial expressions. The emotion engine analyzes the user's tone of voice and facial expressions to identify their emotional state.

[1225] 2. Server

[1226] The server receives data sent from the terminal and has the function of analyzing it. The specific functions of the server are as follows:

[1227] Data reception and analysis

[1228] The server receives the device's current location, weather information, road conditions, and the user's emotion data from the emotion engine. It then analyzes this data and applies algorithms to generate optimal routes and recommendations for the user. The analysis process comprehensively takes into account traffic conditions, weather, recommended routes, and the user's emotional state.

[1229] Generating response data

[1230] The server generates response data based on the analysis results. For example, if there is traffic congestion and the user is frustrated, it generates a message containing not only the best route but also advice on relaxation. The generated data is then reformatted and ready to be sent to the device.

[1231] Resend Data

[1232] The generated response data is sent back to the terminal and provided to the user.

[1233] 3. Users

[1234] Users can use this system to actually drive a car or motorcycle, and the system provides users with relevant information in real time.

[1235] Receiving information

[1236] The user receives information provided by the device. For example, if the device announces, "You are currently heading from Tokyo to Yokohama, but the expressway is congested. You will arrive faster if you use the local roads," the user can adjust their driving method accordingly.

[1237] Request for additional information

[1238] If the user needs more detailed information, they can ask a follow-up question, for example, "What's the weather like along the route?", and the device will again request the information from the server and provide the latest information.

[1239] Recognizing and Responding to Emotions

[1240] The user's tone of voice and facial expressions are analyzed to understand their emotional state. For example, if the user is feeling stressed, the device will provide support tailored to the user's mental state, such as by saying, "Relax. We'll guide you to the best route."

[1241] Specific examples

[1242] For example, when a user travels from Tokyo to Yokohama, the device uses GPS to determine their current location and obtains weather and road information from the API. This data is sent to a server, which analyzes it and returns the result, "The expressway is congested, so we recommend taking a regular road." The device then notifies the user of the result by voice, and the user selects a regular road. If the device determines that the user's voice tone sounds stressed, it will provide additional advice, such as, "Relax. We will guide you to the optimal route."

[1243] The system provides users with accurate, context-sensitive information in real time, enabling them to travel safely and efficiently. The adoption of an emotion engine also reduces stress and anxiety while driving, providing a safer and more comfortable driving environment.

[1244] The processing flow will be explained below.

[1245] Step 1: Get your current location

[1246] Subject: Device

[1247] The device uses the built-in GPS sensor to determine the user's current location. Specifically, the GPS module obtains latitude and longitude information and stores this location data locally on the device.

[1248] Step 2: Get weather information

[1249] Subject: Device

[1250] The device sends a request to an external weather API to obtain weather information for the current location and destination. The request includes location information obtained by GPS. The device receives the response from the API, analyzes the weather information, and stores it.

[1251] Step 3: Obtaining road conditions

[1252] Subject: Device

[1253] The device sends a request to an external traffic API to obtain real-time road conditions, which also includes location information, receives a response from the API, analyzes the road condition data, and stores it.

[1254] Step 4: Obtaining emotion data

[1255] Subject: Device

[1256] The device uses an emotion engine to obtain emotion data from the user's voice and facial expressions. The emotion engine uses voice tone and facial expression analysis algorithms to identify the user's emotional state (e.g., stressed, irritated, relaxed).

[1257] Step 5: Sending data

[1258] Subject: Device

[1259] The device transmits its current location, weather information, road conditions, and emotion data to the server, which then formats the data into a unified format. The transmission is done over the Internet, and the user receives a confirmation message when the data has been successfully sent.

[1260] Step 6: Receiving and analyzing data

[1261] Subject: Server

[1262] The server receives the data sent from the device, analyzes it, and applies algorithms to generate the best route and advice for the user. The analysis process takes into account factors such as traffic conditions, weather, and the user's emotional state.

[1263] Step 7: Generate response data

[1264] Subject: Server

[1265] The server generates response data based on the analysis results—for example, if the user is frustrated, it generates a message containing advice on relaxation as well as the best route—and the generated data is then reformatted and ready to be sent to the device.

[1266] Step 8: Sending response data

[1267] Subject: Server

[1268] The server sends the generated response data to the terminal. If the transmission is successful, the server goes into standby mode for the next data request.

[1269] Step 9: Receiving response data

[1270] Subject: Device

[1271] The device receives the response data from the server, analyzes the received data, and converts it into a format to be presented to the user. Specifically, it prepares for speech synthesis and text display.

[1272] Step 10: Provide information

[1273] Subject: Device

[1274] The device uses a voice synthesis function to notify the user, "The expressway is congested. You will arrive faster if you use the local road." It also displays text information on the display.

[1275] Step 11: Further emotional advice

[1276] Subject: Device

[1277] If the emotion engine determines that the user is feeling stressed, the device will notify them by saying, "Relax. We'll guide you to the best route," and provide additional advice tailored to the user's mental state.

[1278] Step 12: Process requests for additional information

[1279] Subject: Device

[1280] When a user asks, "What's the weather like along that route?" the device parses this request and generates a new data request to ask the server for weather information again.

[1281] Step 13: Sending and Receiving New Data

[1282] Subject: Terminals and Servers

[1283] The device sends a new data request to the server, which receives the request and analyzes it again, and then sends the analysis results back to the device.

[1284] Step 14: Provide updates

[1285] Subject: Device

[1286] The device will provide the user with newly received weather information via voice and text, informing them that "The weather is currently clear on public roads and visibility is good."

[1287] Through these steps, the system provides real-time information and support to drivers. The introduction of an emotion engine enables detailed support according to the user's emotional state, providing a safer and more comfortable driving environment.

[1288] Example 2

[1289] 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."

[1290] When a driver drives a car or motorcycle alone, they need not only real-time information but also the ability to recognize the driver's emotional state and provide appropriate support to reduce driving stress and anxiety, providing a safe and comfortable driving environment. However, current systems are unable to recognize the user's emotional state in real time and provide advice accordingly. To solve this problem, a new system is needed.

[1291] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1292] In this invention, the server includes a means for acquiring current location and weather information, a means for acquiring traffic information, and a means for recognizing the emotional state of the user, which makes it possible to acquire the user's current location and road conditions in real time, while also analyzing the user's emotional state, and provide optimal routes and advice.

[1293] "Means for determining current location" refers to a device or system that uses a GPS sensor to determine the current location of the driver's vehicle or motorcycle and obtains that information.

[1294] "Means for obtaining weather information using an external API" refers to a device or system for obtaining weather information for the current location and destination using the API of an external weather information service.

[1295] "Means for obtaining traffic information using an external API" refers to a device or system for obtaining road conditions and traffic congestion information using the API of an external traffic information service.

[1296] The "means for transmitting these data to the server" refers to a communication device or system for transmitting the driver's current location, weather information, traffic information, and the like to the server.

[1297] The "means for receiving the analysis results from the server" is a communication device or system for receiving the analysis results sent from the server.

[1298] The "means for analyzing acquired data and recognizing the user's emotional state" refers to an emotion recognition engine or analysis system that analyzes the user's voice and facial expressions and recognizes the user's emotional state.

[1299] The "means for generating response data based on the analysis results" refers to an algorithm or program for generating optimal routes and advice for users based on the data analyzed by the server.

[1300] "Means for providing the received analysis results to the user in voice or text" refers to a device or system for providing information to the user by synthesizing the analysis results received from the server as voice or displaying them as text.

[1301] This invention is a system that provides real-time information to drivers when they are driving a car or motorcycle alone, recognizes the driver's emotions, and provides appropriate support. This system mainly consists of four main components: a terminal, a server, a user, and an emotion engine.

[1302] Terminal

[1303] The terminal is a navigation system installed in a car or motorcycle, and specifically includes a GPS module, a communication module, a voice synthesizer, a text display device, and an emotion engine.

[1304] 1. Obtaining your current location

[1305] The device uses a built-in GPS module (e.g., a Garmin GPS module) to determine the user's current location, which is then converted into JSON format and sent to the server.

[1306] 2. Obtaining weather and road conditions

[1307] The device uses external weather APIs (e.g., OpenWeatherMap API) and traffic APIs (e.g., Google Maps API) to obtain weather information and road conditions for the current location and destination. It sends an API request and sends the JSON-formatted data received as a response to the server.

[1308] 3. Sending and Receiving Data

[1309] The acquired data is sent to the server and the analysis results sent from the server are received. Communication is carried out using the HTTPS protocol.

[1310] 4. Equipped with an emotional engine

[1311] The device is equipped with an emotion engine (for example, Microsoft Azure Emotion API) that analyzes the user's voice and facial expressions. Specifically, it uses a camera and microphone to collect facial images and voice data, which are then sent to a server as emotion data.

[1312] server

[1313] The server has the function of receiving and analyzing data sent from the terminal.

[1314] 1. Data Analysis

[1315] The server comprehensively analyzes the received location, weather information, road conditions, and emotional data, and uses AI algorithms to generate optimal routes and advice, as well as generate response data based on the user's emotional state.

[1316] 2. Generate and send response data

[1317] Based on the analysis results, the engine generates response data for the user. For example, it creates a message such as, "The current weather is rainy. There is traffic congestion, so we recommend taking regular roads," and sends it to the device.

[1318] user

[1319] Users access the system through a terminal and actually drive a car or motorcycle.

[1320] 1. Receiving information

[1321] The user receives information provided by the device. For example, the device may use a voice synthesizer (e.g., Google Text-to-Speech) to notify the user that "the highway is congested. You will arrive faster if you take the local road," and the user can adjust their driving accordingly.

[1322] 2. Request for additional information

[1323] If the user needs more detailed information, they can request additional information using voice commands or touch operations. For example, if they ask, "What's the weather like along that route?", the device will again request the information from the server and provide the latest information.

[1324] 3. Recognizing and Responding to Emotions

[1325] If the user's tone of voice or facial expression is detected as stressed, the device will provide additional advice, such as "Relax. We'll guide you to the best route." This reduces stress and anxiety while driving, providing a safer and more comfortable driving environment.

[1326] Examples and prompts

[1327] For example, when a user travels from Tokyo to Yokohama, the following actions are performed:

[1328] The device uses GPS to determine its current location and obtains weather information and road conditions using the OpenWeatherMap API and Google Maps API.

[1329] The acquired data is sent to a server, which analyzes it and returns the result that "the highway is congested, so we recommend taking a regular road."

[1330] The device uses Google Text-to-Speech to notify the user via voice, "The highway is congested, so we recommend taking a regular road."

[1331] If the user's tone of voice is deemed stressful, the device will offer additional advice: "Relax. We'll guide you to the best route."

[1332] Example prompt sentence:

[1333] "Please provide the best route and weather information for traveling from Tokyo to Yokohama."

[1334] "Generate a message to a user who is currently stressed, with advice on how to relax."

[1335] In this way, the system of the present invention provides appropriate information in real time and optimal support according to the user's emotional state, providing a safe and comfortable driving experience.

[1336] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1337] Step 1:

[1338] The terminal uses a GPS module to determine the driver's current location.

[1339] Input: Satellite signal

[1340] Data processing: The GPS module receives signals from satellites and calculates latitude and longitude.

[1341] Output: Current location latitude and longitude data (JSON format)

[1342] Specific operation: The device's GPS sensor receives satellite signals, analyzes them to determine the current location, and obtains coordinate information.

[1343] Step 2:

[1344] The device uses weather and traffic APIs to obtain weather information and road conditions for the current location and destination.

[1345] Input: The latitude and longitude data determined by the device as its current location

[1346] Data processing: Constructing API requests, sending them to external weather and traffic APIs, and receiving responses in JSON format.

[1347] Output: Weather and road conditions for current and destination locations (JSON format)

[1348] What it does: The device sends requests to the OpenWeatherMap API and Google Maps API to obtain weather and road condition data for the current location and destination.

[1349] Step 3:

[1350] The terminal transmits data on the current location, weather information, and road conditions to the server.

[1351] Input: Weather information and road condition data acquired by the device (JSON format)

[1352] Data processing: The data is formatted in JSON format and sent to the server using the HTTPS protocol.

[1353] Output: Weather and road condition data sent to the server

[1354] Specific operation: The device collects the data and sends it to the server via HTTPS communication.

[1355] Step 4:

[1356] The terminal starts an emotion engine and acquires emotion data of the driver.

[1357] Input: Driver's voice and facial expression data

[1358] Data processing: Using speech recognition and facial expression analysis algorithms to identify emotional states.

[1359] Output: Emotion data (JSON format)

[1360] How it works: The emotion engine uses the camera and microphone to capture voice and facial expressions, which are then analyzed to determine the emotional state.

[1361] Step 5:

[1362] The terminal transmits the emotion data to the server.

[1363] Input: Emotion data acquired by the device (JSON format)

[1364] Data processing: The data is formatted in JSON format and sent to the server using the HTTPS protocol.

[1365] Output: Emotion data sent to the server

[1366] Specific operation: The device compiles emotion data and sends it to the server via HTTPS.

[1367] Step 6:

[1368] The server receives and analyzes the data sent from the terminal.

[1369] Input: Current location, weather information, road conditions, and emotion data (JSON format) sent from the device

[1370] Data processing: AI algorithms are used to analyze data and generate optimal routes and advice.

[1371] Output: Analysis result (JSON format)

[1372] Specific operation: The server comprehensively analyzes the received data and generates optimal route guidance and advice to provide to the driver.

[1373] Step 7:

[1374] The server generates response data based on the analysis results.

[1375] Input: Analyzed current location, weather information, road conditions, emotion data (JSON format)

[1376] Data processing: Construct a response message based on the analysis results.

[1377] Output: Response data (JSON format)

[1378] Specific operation: The server generates a response message from the analysis results and prepares to send it to the terminal.

[1379] Step 8:

[1380] The server transmits the response data to the terminal.

[1381] Input: Response data generated by the server (JSON format)

[1382] Data processing: The data is formatted in JSON format and sent to the terminal using the HTTPS protocol.

[1383] Output: Response data sent to the terminal

[1384] Specific operation: The server compiles the response data and sends it to the terminal via HTTPS communication.

[1385] Step 9:

[1386] The device receives the analysis results from the server and provides them to the user in voice or text format.

[1387] Input: Response data sent from the server (JSON format)

[1388] Data processing: Analyze the data and provide it to the user using speech synthesis or text display functions.

[1389] Output: Audio or text information provided to the user

[1390] Specific operation: The device analyzes the received data and notifies the user via voice using Google Text-to-Speech.

[1391] Step 10:

[1392] If the user requests additional information, the terminal again sends a data acquisition request to the server.

[1393] Input: Request for additional information from the user (voice command, touch action)

[1394] Data processing: Analyze the user's request and send a request to the server to retrieve the required information again.

[1395] Output: Request for more information sent to the server

[1396] Specific operation: The device sends a request to the server again based on the user's request, preparing to provide the latest information.

[1397] Step 11:

[1398] If the user's tone of voice or facial expression indicates stress, the device will offer additional emotional support advice.

[1399] Input: Detection results from the emotion recognition engine (emotion data such as stress, irritation, relaxation, etc.)

[1400] Data processing: Generate appropriate advice for stress reduction.

[1401] Output: Audio or text advice to the user to relax

[1402] What it does: The device analyzes emotional data and provides voice messages such as, "Relax. We'll guide you to the best route."

[1403] (Application example 2)

[1404] 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."

[1405] Conventional navigation systems are limited to providing information on the current location, weather, and road conditions, and are unable to provide appropriate support that takes into account the driver's psychological state. Therefore, the challenge is to reduce the stress and anxiety felt by drivers and provide a safe and comfortable driving environment.

[1406] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1407] In this invention, the server includes means for identifying the current location, means for acquiring weather information using an external API, means for acquiring road conditions using an external API, means for analyzing the emotional state of the driver using an emotion engine, means for providing additional advice based on the emotional state of the driver obtained from the emotion engine, and means for generating an appropriate voice or text message based on a prompt sentence of the generative AI model. This makes it possible to recognize the emotional state of the driver in real time and provide appropriate information and advice according to that state.

[1408] "Means for determining current location" refers to a function that obtains the user's location information using a GPS sensor.

[1409] "Means of obtaining weather information using external APIs" refers to a function that obtains weather information for the current location and destination using cloud services or publicly available APIs.

[1410] "Means of obtaining road conditions using external APIs" refers to a function that obtains traffic conditions and road congestion information using cloud services or publicly available APIs.

[1411] The "means for transmitting these data to the server" is a function for transmitting the acquired current location, weather information, and road condition information to the server via the network.

[1412] The "means for receiving analysis results from the server" is a function for receiving data analysis results sent from the server at the terminal.

[1413] "Means of providing the received analysis results to the user by voice or text" refers to a function that notifies the user of the analysis results through voice synthesis technology or a display.

[1414] The "emotion engine that analyzes the driver's emotional state" is a system that uses voice analysis and facial recognition technology to evaluate the driver's emotions and identify their state.

[1415] The "means for providing additional advice based on the driver's emotional state obtained from the emotion engine" is a function that provides appropriate advice or instructions to the driver based on the analysis results of the emotion engine.

[1416] "Means for generating appropriate voice or text messages based on prompt sentences from a generative AI model" refers to a function that uses a generative AI model to automatically create natural-sounding voice or text messages based on prompt sentences.

[1417] The system of the present invention is comprised of a device installed in an autonomous vehicle, a server, and a user, and provides real-time support and emotion recognition to the driver. Specifically, it has the following configuration and functions:

[1418] Terminal

[1419] The terminals used are navigation systems installed in vehicles, smartphones, etc. The main functions of the terminals are as follows:

[1420] Get current location:

[1421] The vehicle's GPS sensor is used to identify the user's current location, thereby obtaining location information.

[1422] Get weather and road conditions:

[1423] Use external weather APIs (e.g., OpenWeatherMap API) and traffic APIs (e.g., Google Maps API) to obtain weather information and road conditions for your current location and destination.

[1424] Sending and receiving data:

[1425] The device sends the acquired data to a server via the network, and receives the analysis results from the server and notifies the user using voice synthesis and text display functions.

[1426] Emotion engine included:

[1427] The emotion engine recognizes emotions from the driver's voice and facial expressions. It uses IBM Watson Tone Analyzer for voice analysis and Microsoft Face API for facial recognition.

[1428] server

[1429] The server has the function of receiving and analyzing data sent from the terminal. The specific functions of the server are as follows:

[1430] Data reception and analysis:

[1431] The server receives and analyzes the current location data, weather information, road condition information, and emotion data from the emotion engine, using an algorithm that comprehensively considers traffic conditions, weather, recommended routes, and the user's emotional state.

[1432] Generate response data:

[1433] The server generates optimal routes and advice based on the analysis results. For example, if it detects that the driver is feeling stressed, it generates a message with relaxation suggestions.

[1434] Resend data:

[1435] The server transmits the generated response data to the terminal again and provides it to the user.

[1436] User

[1437] The user actually drives the vehicle using this system. The main functions are as follows:

[1438] Receiving information:

[1439] Users can receive information provided by the device and adjust their route and driving method.

[1440] Request for additional information:

[1441] If the user needs more information, they can ask additional questions and request the information from the server through the terminal.

[1442] Recognizing and Responding to Emotions:

[1443] The emotion engine analyzes the user's emotions and provides appropriate advice as needed, such as "Relax. We'll guide you to the best route."

[1444] Specific examples

[1445] When a user travels from Tokyo to Yokohama, the device uses GPS to determine their current location and obtains weather information and road conditions from an API. This data is sent to a server, which analyzes it and returns the result, "The expressway is congested, so we recommend taking an ordinary road." The device notifies the user of the result by voice, and the user selects an ordinary road. If the device determines that the user's tone of voice indicates stress, it provides additional advice, saying, "Please relax. We will guide you to the optimal route." An example of a prompt sentence from the generative AI model used in this case is, "Analyze the driver's emotions and guide them to the optimal route. If it determines that the driver is stressed, please also implement a function to play music for relaxation."

[1446] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1447] Step 1: Get your current location

[1448] The device uses the built-in GPS sensor to determine the user's current location. This location information provides the current latitude and longitude data, which is used in the next processing step.

[1449] Input: None (initial operation)

[1450] Output: Current location latitude and longitude data

[1451] Step 2: Get weather and road conditions

[1452] The device sends requests to external APIs (e.g., weather APIs and road traffic APIs) to obtain the latest weather and road conditions for the current location and destination, thereby providing information about the area the user plans to pass through.

[1453] Input: Latitude and longitude data of current location

[1454] Output: Weather and road conditions for current location and destination

[1455] Step 3: Sending data to the server

[1456] The terminal transmits the acquired current location data, weather information, and road condition information to the server, where the data is uploaded to the server via the network.

[1457] Input: current location latitude and longitude data, weather information, road condition information

[1458] Output: All data sent to the server

[1459] Step 4: Emotion analysis using the emotion engine

[1460] The device's built-in emotion engine analyzes the user's voice and facial expressions to identify their emotional state, using voice analysis and facial recognition technology to assess whether the user is relaxed or stressed.

[1461] Input: User's voice data, face image data

[1462] Output: User's emotional state data

[1463] Step 5: Receiving and analyzing data

[1464] The server receives and analyzes all data sent by the device (current location, weather information, road conditions, emotional state), and runs algorithms to generate optimal routes and additional advice.

[1465] Input: current location latitude and longitude data, weather information, road condition information, emotional state data

[1466] Output: Optimal route information, additional advice

[1467] Step 6: Generate and send response data

[1468] The server generates optimal routes and advice based on the analysis results, and uses a generative AI model to create voice or text messages based on the prompts. This response data is then sent back to the device.

[1469] Input: Optimal route information, additional advice

[1470] Output: Response data (route guidance, advice message)

[1471] Step 7: Notify users

[1472] The device then notifies the user of the response data received from the server. Using voice synthesis and display functions, the device provides guidance on the optimal route and emotional advice. This notification allows the user to adjust their driving style or take action to relax.

[1473] Input: Response data from the server

[1474] Output: Optimal route guidance, emotional advice notification

[1475] 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.

[1476] 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.

[1477] 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.

[1478] [Fourth embodiment]

[1479] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1480] 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.

[1481] 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).

[1482] 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.

[1483] 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.

[1484] 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).

[1485] 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.

[1486] 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.

[1487] 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.

[1488] 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.

[1489] 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.

[1490] 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.

[1491] 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."

[1492] The system of this invention is designed to provide real-time information and support to drivers when they are driving a car or motorcycle alone. The system consists of three main components: a terminal, a server, and a user.

[1493] 1. Terminal

[1494] The terminal is a navigation system installed in a car or motorcycle, and has the following functions:

[1495] Get current location

[1496] The device uses its built-in GPS sensor to determine the user's current location, which is then sent to a server and used as the basis for location information.

[1497] Obtaining weather and road conditions

[1498] The device will use external weather and traffic APIs to obtain weather and road conditions for the current location and destination, improving the accuracy of the information provided to users.

[1499] Sending and Receiving Data

[1500] The device sends the acquired data to the server and receives the analysis results from the server, which are then provided to the user using speech synthesis and text display functions.

[1501] 2. Server

[1502] The server receives data sent from the terminal and has the function of analyzing it. The specific functions of the server are as follows:

[1503] Data reception and analysis

[1504] The server receives data sent from the device, such as current location, weather information, road conditions, etc. It then analyzes this data and generates optimal routes and advice for the user.

[1505] Generating response data

[1506] The server generates response data based on the analysis results. For example, if there is traffic congestion, it generates data suggesting an alternative route.

[1507] Resend Data

[1508] The generated response data is sent back to the terminal and provided to the user.

[1509] 3. Users

[1510] Users can use this system to actually drive a car or motorcycle, and the system provides users with relevant information in real time.

[1511] Receiving information

[1512] The user receives information provided by the device. For example, if the device announces, "You are currently heading from Tokyo to Yokohama, but the expressway is congested. You will arrive faster if you use the local roads," the user can adjust their driving method accordingly.

[1513] Request for additional information

[1514] If the user needs more detailed information, they can ask a follow-up question, for example, "What's the weather like along the route?", and the device will again request the information from the server and provide the latest information.

[1515] Specific examples

[1516] For example, when a user travels from Tokyo to Yokohama, the device uses GPS to determine the user's current location and obtains weather information and road conditions from the API. This data is sent to the server, which analyzes it and returns the result, "The expressway is congested, so we recommend taking an ordinary road." The device notifies the user of the result by voice, and the user selects an ordinary road. If the user also asks, "What's the weather like on the ordinary road?", the device will query the server again and provide the latest weather information.

[1517] This system provides users with accurate information in real time, enabling them to travel efficiently and safely.

[1518] The processing flow will be explained below.

[1519] Step 1: Get your current location

[1520] Subject: Device

[1521] The device uses the built-in GPS sensor to determine the user's current location. Specifically, the GPS module obtains latitude and longitude information and stores this location data locally on the device.

[1522] Step 2: Get weather information

[1523] Subject: Device

[1524] The device sends a request to an external weather API to obtain weather information for the current location and destination. The request includes location information obtained by GPS. The device receives the response from the API, analyzes the weather information, and stores it.

[1525] Step 3: Obtaining road conditions

[1526] Subject: Device

[1527] The device sends a request to an external traffic API to obtain real-time road conditions, which also includes location information, receives a response from the API, analyzes the road condition data, and stores it.

[1528] Step 4: Sending data

[1529] Subject: Device

[1530] The device sends current location, weather, road conditions, and destination information to the server. Before sending, this data is formatted into a unified format. The data is sent over the Internet, and a confirmation message is received when the data has been successfully sent.

[1531] Step 5: Receiving and analyzing data

[1532] Subject: Server

[1533] The server receives the data sent from the device, analyzes it, and applies algorithms to generate the best route and advice for the user. The analysis process takes into account traffic conditions, weather, recommended routes, and more.

[1534] Step 6: Generate response data

[1535] Subject: Server

[1536] The server generates response data based on the analysis results, for example, a message such as "The current route is congested, so we recommend taking an open road." The generated data is then reformatted and prepared for transmission to the device.

[1537] Step 7: Sending response data

[1538] Subject: Server

[1539] The server sends the generated response data to the terminal. If the transmission is successful, the server goes into standby mode for the next data request.

[1540] Step 8: Receiving response data

[1541] Subject: Device

[1542] The device receives the response data from the server, analyzes the received data, and converts it into a format to be presented to the user. Specifically, it prepares for speech synthesis and text display.

[1543] Step 9: Provide information

[1544] Subject: Device

[1545] The device uses a voice synthesis function to notify the user, "The expressway is congested. You will arrive faster if you use the local road." It also displays text information on the display.

[1546] Step 10: Process requests for additional information

[1547] Subject: Device

[1548] When a user asks, "What's the weather like along that route?" the device parses this request and generates a new data request to ask the server for weather information again.

[1549] Step 11: Sending and Receiving New Data

[1550] Subject: Terminals and Servers

[1551] The device sends a new data request to the server, which receives the request and analyzes it again, and then sends the analysis results back to the device.

[1552] Step 12: Provide updates

[1553] Subject: Device

[1554] The device will provide the user with newly received weather information via voice and text, informing them that "The weather is currently clear on public roads and visibility is good."

[1555] Through the above steps, this system provides real-time information and support to drivers.

[1556] Example 1

[1557] 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."

[1558] Conventional driver assistance systems have faced challenges in providing users with appropriate information in real time. Providing timely updated data is particularly important given the frequently changing traffic and weather conditions. Furthermore, there is a lack of systems that can smoothly respond to additional requests for specific information that users require.

[1559] 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.

[1560] In this invention, the server includes means for identifying the current location, means for acquiring weather information using an external information system, means for acquiring road conditions using an external traffic information system, means for transmitting these data to the central control device, means for receiving analysis results from the central control device, and means for providing the received analysis results to the user as voice or text information, thereby enabling the user to obtain accurate information in real time and travel efficiently and safely.

[1561] "Means for determining current location" refers to a system that uses a location information acquisition device such as a GPS sensor to accurately determine the user's current location.

[1562] "Means of obtaining weather information using an external information system" refers to a mechanism for obtaining weather information for the current location and destination using external services such as weather information APIs.

[1563] "Means of obtaining road conditions using external traffic information systems" refers to a mechanism for obtaining road conditions at the current location and destination by utilizing external services such as traffic condition APIs.

[1564] The "means for transmitting these data to a central control device" refers to a communication means for transmitting the acquired current location, weather information, and road conditions to a central control device such as a server.

[1565] The "means for receiving the analysis results from the central control device" is a communication means for receiving the results of the data analyzed by the central control device such as a server.

[1566] "Means for providing the received analysis results to the user as voice or text information" refers to a mechanism for communicating the data analysis results received from the server to the user using voice synthesis technology or text display functions.

[1567] "Generating optimal route or advice" refers to the process in which the server analyzes the location, weather, and traffic data it receives and generates the most efficient and safe route or driving advice for the user.

[1568] The "means for receiving a request for additional information and again transmitting an information acquisition request to the central control device" is a mechanism for receiving a request for specific additional information from a user and again transmitting a data acquisition request to the central control device based on that request.

[1569] The system of the present invention consists of three main elements: the terminal, the server, and the user. Each element is described in detail below.

[1570] Terminal

[1571] The terminal consists of a navigation system installed in a car or motorcycle. Specific hardware includes a GPS sensor, a communication module (e.g., an LTE module), a voice synthesis device, a display, etc. The software also includes an API client for obtaining weather information (e.g., an OpenWeatherMap API client) and an API client for obtaining traffic information (e.g., a Google Maps API client). The terminal has the following functions:

[1572] 1. Obtaining your current location

[1573] Your device will use the built-in GPS sensor to determine your current location. For example, your device may display "Getting location..." and go through the process of obtaining GPS coordinates.

[1574] 2. Obtaining weather and road conditions

[1575] The device uses external weather APIs (e.g., OpenWeatherMap API) and traffic APIs (e.g., Google Maps API) to obtain weather information and road conditions for the current location and destination. For example, a message such as "Retrieving weather information and road conditions..." is displayed.

[1576] 3. Sending and Receiving Data

[1577] The device sends the acquired data to the server and receives the analysis results from the server. For example, when data is received from the server, the device displays "Data received."

[1578] server

[1579] The server acts as a central control unit, analyzing data sent from the terminals and generating response data. The server uses the following software and hardware:

[1580] 1. Data Reception and Analysis

[1581] The server receives data such as the current location, weather information, and road conditions sent from the device and begins analyzing it. For example, it calculates the optimal route using a generative AI model (e.g., a routing algorithm or traffic analysis model) based on the received data.

[1582] 2. Generating response data

[1583] The server generates response data for the user based on the analysis results. For example, the server may generate information such as "The highway is congested, so we recommend taking a regular road."

[1584] 3. Data retransmission

[1585] The server will retransmit the generated response data to the terminal. After this transmission process is successful, the server will record a message saying "Data transmission successful."

[1586] user

[1587] The user uses this system to actually drive a car or motorcycle. The user receives various information in real time via the terminal and can request additional information as needed. Specifically, the following operations are possible:

[1588] 1. Receiving information

[1589] The user receives information provided by the device. For example, the device may announce in voice, "You are currently traveling from Tokyo to Yokohama, but the expressway is congested. You will arrive faster if you use the local road."

[1590] 2. Request for additional information

[1591] If the user needs more detailed information, they can ask a follow-up question, for example, "What's the weather like along the route?", and the device will again request the information from the server and provide the latest information.

[1592] Specific examples

[1593] When a user travels from Tokyo to Yokohama, the following specific actions are taken:

[1594] 1. The device activates the GPS and obtains the current location (for example, near Tokyo Station).

[1595] 2. The device calls the OpenWeatherMap API to obtain weather information for Tokyo Station and Yokohama Station, and road conditions using the Google Maps API.

[1596] 3. The device sends this data to the server.

[1597] 4. The server receives the data and calculates the optimal route.

[1598] 5. The server generates data that says, "The highway is congested, so we recommend taking a regular road."

[1599] 6. The server sends the data to the device.

[1600] 7. The device notifies the user that "You'll arrive faster if you take the local road."

[1601] 8. The user requests additional information: "What's the weather like on the road?"

[1602] 9. The device sends the request to the server.

[1603] 10. The server analyzes the information and sends it to the device: "The weather on the public road is sunny."

[1604] 11. The device notifies the user that "The weather on the public road is clear."

[1605] Prompt Sentence Examples

[1606] 1. "What is the best route considering my current location and destination?"

[1607] 2. "If I use a public road, please let me know the weather information along the way."

[1608] 3. "Please provide traffic information on highways."

[1609] The overall flow of this system relies on the server for data processing, providing continuous real-time information, allowing users to reach their destinations comfortably and safely.

[1610] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1611] Step 1:

[1612] The device uses the GPS sensor to obtain the current location. Specifically, the device displays "Getting current location..." and obtains GPS coordinates (latitude and longitude). The input is data from the GPS sensor, and the output is the coordinate information of the current location.

[1613] Step 2:

[1614] The device obtains weather information and road conditions from an external API. Specifically, the device calls the OpenWeatherMap API to obtain weather information for the current location and destination, and calls the Google Maps API to obtain road conditions from the current location to the destination. The input is the coordinate information of the current location and destination, and the output is weather information and road condition information.

[1615] Step 3:

[1616] The device transmits the current location, weather information, and road conditions it has acquired to the server. Specifically, it displays "Sending data..." and sends all of this data to the server. The input is the current location, weather information, and road conditions data, and the output is the data transmitted to the server.

[1617] Step 4:

[1618] The server receives the data sent from the device and begins analyzing it. Specifically, the server stores it in a database and calculates the optimal route using a generative AI model. The input is the current location, weather information, and road condition data, and the output is the optimal route information.

[1619] Step 5:

[1620] The server generates response data based on the analysis results. Specifically, it creates response data such as "The highway is congested, so we recommend taking a local road." The input is optimal route information, and the output is response data.

[1621] Step 6:

[1622] The server sends the response data to the terminal. Specifically, it records the message "Data transmission successful" and sends the response data to the terminal. The input is the response data, and the output is the data sent to the terminal.

[1623] Step 7:

[1624] The response data received by the device is provided to the user as voice or text. Specifically, it notifies the user by voice that "You'll arrive faster if you use the public road." The input is the response data from the server, and the output is the information notified to the user.

[1625] Step 8:

[1626] If the user needs additional information, they ask the device a question. Specifically, the user asks aloud, "What's the weather like along that route?" The input is the question from the user, and the output is the question received by the device.

[1627] Step 9:

[1628] The device sends the user's question to the server. Specifically, it displays "Requesting additional information..." and sends the question to the server. The input is the question from the user, and the output is the question sent to the server.

[1629] Step 10:

[1630] The server analyzes the additional information and sends it back to the device. Specifically, it generates additional information such as "The weather on the public road is sunny." The input is the user's question, and the output is the additional information.

[1631] Step 11:

[1632] The terminal provides the received additional information to the user. Specifically, it notifies the user by voice, "The weather on the general road is sunny." The input is the additional information from the server, and the output is the additional information notified to the user.

[1633] (Application example 1)

[1634] 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."

[1635] A modern problem in car and motorcycle driving is the lack of real-time, accurate information. It is particularly difficult for drivers to understand the appropriate driving route, weather conditions, and traffic conditions while driving alone. This can result in reduced driving safety and efficiency. Furthermore, even when additional information is needed, it is dangerous for drivers to manually obtain the information while driving. There is a need to resolve these issues and improve driving safety and efficiency.

[1636] 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.

[1637] In this invention, the server includes a means for determining the current location, a means for acquiring weather information using an external API, a means for acquiring road conditions using an external API, a means for transmitting these data to the server, a means for receiving analysis results from the server, a means for providing the received analysis results to the user by voice or text, and a means for providing the driver with information they need by voice, thereby improving the safety and efficiency of automated driving. This allows the driver to understand appropriate driving routes, weather information, and traffic conditions in real time, significantly improving the safety and efficiency of driving. Furthermore, if additional information is requested, the information can be safely obtained through voice instructions, thereby reducing the burden on the driver and ensuring safety.

[1638] Key Word Definitions

[1639] "Means for determining current location" refers to a function that uses location information technology such as GPS to accurately determine the current location of the device.

[1640] "Means for obtaining weather information using an external API" is an interface for obtaining the latest weather information from an external weather information service.

[1641] "Means for obtaining road conditions using external APIs" refers to an interface for obtaining current road congestion status and accident information from external traffic information services.

[1642] "Means for transmitting these data to the server" refers to communication means for uploading acquired information such as current location, weather information, road conditions, etc. to the server.

[1643] The "means for receiving analysis results from the server" refers to a communication means for receiving analysis results and advice sent from the server at the terminal.

[1644] The "means for providing the received analysis results to the user by voice or text" refers to an interface for conveying the received information to the user by voice synthesis or text display.

[1645] "Means for providing the driver with the information they need via voice and improving the safety and efficiency of automated driving" refers to a function that provides the driver with the necessary information via voice in response to their request, thereby assisting in making the operation of automated vehicles safer and more efficient.

[1646] "Means for receiving a request for additional information from the user and sending a data acquisition request to the server again" is a function for accepting a request from a user for additional information and sending a data acquisition request to the server again.

[1647] MODE FOR CARRYING OUT THE INVENTION

[1648] The system of the present invention provides drivers with optimal information in real time when driving a vehicle, thereby improving safety and efficiency.

[1649] The system uses the following hardware and software:

[1650] Hardware

[1651] GPS module: Used to determine the vehicle's current location.

[1652] Smartphone or in-car display: where system applications are installed and used to provide information.

[1653] Internet connection: Used to access external APIs and obtain necessary data.

[1654] Microphone and speaker: Used to provide information via voice and receive voice commands from the user.

[1655] software

[1656] Navigation software (e.g., Google Maps, Waze): used to provide route information and display analysis results.

[1657] Weather information API (e.g. OpenWeatherMap): Used to obtain weather information for the current location and destination.

[1658] Traffic information API (e.g., TomTom Traffic API): Used to obtain road congestion and accident information.

[1659] Description of the embodiment

[1660] The system's terminal first uses a GPS module to determine the driver's current location, then uses weather and traffic information APIs to obtain weather and road conditions for the current location and destination, and transmits this data to a server via an internet connection.

[1661] The server analyzes the transmitted data and generates the optimal route and advice for the driver. The analysis results are then sent back to the device. The device then notifies the user of the received analysis results in voice or text format. For example, it may say, "There is currently traffic congestion, so we recommend taking an ordinary road."

[1662] If the user needs more detailed information, they can ask additional questions by voice, such as "What's the weather like on the road?", and the device will request the information from the server again and provide the latest information. This allows the driver to adjust their driving based on the latest information.

[1663] Specific examples

[1664] For example, suppose a user is driving from Tokyo to Yokohama. In this case, the device uses GPS to identify the user's current location and obtains weather and road information. This information is sent to the server, which analyzes it and generates the result, "The highway is congested, so it is recommended to take a regular road." The device then notifies the user of the result by voice.

[1665] When a user asks, "What's the weather like on the public road?", the device will again request weather information from the server and provide the latest weather information. This system allows users to obtain accurate information in real time, enabling them to travel efficiently and safely.

[1666] Prompt Sentence Examples

[1667] "What is the weather forecast for my current location?"

[1668] "Please provide traffic information."

[1669] "Calculate the best route."

[1670] "What's the weather like on the open road?"

[1671] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1672] Program processing steps

[1673] Step 1:

[1674] Get current location

[1675] The device uses the GPS module to determine the user's current location. At this time, it receives GPS data as input and outputs the latitude and longitude of the current location. Specifically, it obtains the numerical data of latitude and longitude from the GPS device and passes it to the system as the current location coordinates.

[1676] Step 2:

[1677] Get weather information

[1678] The device uses an external weather information API to obtain weather information for the current location and destination. At this time, the latitude and longitude obtained in step 1 are used as input, and the response data from the weather API is received as output. Specifically, the device sends an API request and parses the response in JSON format to extract the weather data.

[1679] Step 3:

[1680] Obtaining road conditions

[1681] The device uses an external traffic information API to obtain road conditions at the current location and destination. At this time, the latitude and longitude obtained in step 1 are used as input, and response data from the traffic API is received as output. Specifically, the device sends an API request, analyzes the response in JSON format, and extracts road condition data.

[1682] Step 4:

[1683] Sending data to the server

[1684] The device sends the acquired weather information, road conditions, and current location data to the server. At this time, the weather information, road condition data, latitude and longitude are sent together as input to the server, and a confirmation response is output. Specifically, the data is sent to the server using an HTTP POST request.

[1685] Step 5:

[1686] Data analysis by server

[1687] The server analyzes the received data and generates the optimal route and advice to provide to the driver. At this time, it analyzes the received input data (latitude and longitude, weather information, road conditions) and outputs the optimal route information. Specifically, it uses AI algorithms and routing algorithms to calculate the optimal driving route and recommended actions.

[1688] Step 6:

[1689] Resend analysis results

[1690] The server retransmits the analysis results to the terminal. At this time, it uses the optimal route information generated as input to construct the data to be sent to the terminal and actually sends it as output. Specifically, it returns the analysis results to the terminal in JSON format as an HTTP response.

[1691] Step 7:

[1692] User Notification

[1693] The device provides the analysis results received from the server to the user as voice or text. At this time, the optimal route information received from the server is used as input, and voice notification or text display is provided to the user as output. Specifically, voice notification is provided using speech synthesis software, or text data is displayed on the screen.

[1694] Step 8:

[1695] Processing requests for additional information

[1696] If the user requests additional information, the device retransmits the request to the server for further analysis and provision. The device receives the request for additional information via voice commands or button presses as input, constructs data to send to the server, and receives a response from the server as output. Specifically, the device analyzes the user's voice command using voice recognition software and sends a new request to the server.

[1697] 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.

[1698] The system of the present invention is designed to provide real-time information and appropriate support to drivers who are driving cars or motorcycles alone by recognizing their emotions. The system consists of four main components: a terminal, a server, a user, and an emotion engine.

[1699] 1. Terminal

[1700] The terminal is a navigation system installed in a car or motorcycle, and has the following functions:

[1701] Get current location

[1702] The device uses its built-in GPS sensor to determine the user's current location, which is then sent to a server and used as the basis for location information.

[1703] Obtaining weather and road conditions

[1704] The device will use external weather and traffic APIs to obtain weather and road conditions for the current location and destination, improving the accuracy of the information provided to users.

[1705] Sending and Receiving Data

[1706] The device sends the acquired data to the server and receives the analysis results from the server, which are then provided to the user using speech synthesis and text display functions.

[1707] Emotion engine included

[1708] The device is equipped with an emotion engine that recognizes emotions from the user's voice and facial expressions. The emotion engine analyzes the user's tone of voice and facial expressions to identify their emotional state.

[1709] 2. Server

[1710] The server receives data sent from the terminal and has the function of analyzing it. The specific functions of the server are as follows:

[1711] Data reception and analysis

[1712] The server receives the device's current location, weather information, road conditions, and the user's emotion data from the emotion engine. It then analyzes this data and applies algorithms to generate optimal routes and recommendations for the user. The analysis process comprehensively takes into account traffic conditions, weather, recommended routes, and the user's emotional state.

[1713] Generating response data

[1714] The server generates response data based on the analysis results. For example, if there is traffic congestion and the user is frustrated, it generates a message containing not only the best route but also advice on relaxation. The generated data is then reformatted and ready to be sent to the device.

[1715] Resend Data

[1716] The generated response data is sent back to the terminal and provided to the user.

[1717] 3. Users

[1718] Users can use this system to actually drive a car or motorcycle, and the system provides users with relevant information in real time.

[1719] Receiving information

[1720] The user receives information provided by the device. For example, if the device announces, "You are currently heading from Tokyo to Yokohama, but the expressway is congested. You will arrive faster if you use the local roads," the user can adjust their driving method accordingly.

[1721] Request for additional information

[1722] If the user needs more detailed information, they can ask a follow-up question, for example, "What's the weather like along the route?", and the device will again request the information from the server and provide the latest information.

[1723] Recognizing and Responding to Emotions

[1724] The user's tone of voice and facial expressions are analyzed to understand their emotional state. For example, if the user is feeling stressed, the device will provide support tailored to the user's mental state, such as by saying, "Relax. We'll guide you to the best route."

[1725] Specific examples

[1726] For example, when a user travels from Tokyo to Yokohama, the device uses GPS to determine their current location and obtains weather and road information from the API. This data is sent to a server, which analyzes it and returns the result, "The expressway is congested, so we recommend taking a regular road." The device then notifies the user of the result by voice, and the user selects a regular road. If the device determines that the user's voice tone sounds stressed, it will provide additional advice, such as, "Relax. We will guide you to the optimal route."

[1727] The system provides users with accurate, context-sensitive information in real time, enabling them to travel safely and efficiently. The adoption of an emotion engine also reduces stress and anxiety while driving, providing a safer and more comfortable driving environment.

[1728] The processing flow will be explained below.

[1729] Step 1: Get your current location

[1730] Subject: Device

[1731] The device uses the built-in GPS sensor to determine the user's current location. Specifically, the GPS module obtains latitude and longitude information and stores this location data locally on the device.

[1732] Step 2: Get weather information

[1733] Subject: Device

[1734] The device sends a request to an external weather API to obtain weather information for the current location and destination. The request includes location information obtained by GPS. The device receives the response from the API, analyzes the weather information, and stores it.

[1735] Step 3: Obtaining road conditions

[1736] Subject: Device

[1737] The device sends a request to an external traffic API to obtain real-time road conditions, which also includes location information, receives a response from the API, analyzes the road condition data, and stores it.

[1738] Step 4: Obtaining emotion data

[1739] Subject: Device

[1740] The device uses an emotion engine to obtain emotion data from the user's voice and facial expressions. The emotion engine uses voice tone and facial expression analysis algorithms to identify the user's emotional state (e.g., stressed, irritated, relaxed).

[1741] Step 5: Sending data

[1742] Subject: Device

[1743] The device transmits its current location, weather information, road conditions, and emotion data to the server, which then formats the data into a unified format. The transmission is done over the Internet, and the user receives a confirmation message when the data has been successfully sent.

[1744] Step 6: Receiving and analyzing data

[1745] Subject: Server

[1746] The server receives the data sent from the device, analyzes it, and applies algorithms to generate the best route and advice for the user. The analysis process takes into account factors such as traffic conditions, weather, and the user's emotional state.

[1747] Step 7: Generate response data

[1748] Subject: Server

[1749] The server generates response data based on the analysis results—for example, if the user is frustrated, it generates a message containing advice on relaxation as well as the best route—and the generated data is then reformatted and ready to be sent to the device.

[1750] Step 8: Sending response data

[1751] Subject: Server

[1752] The server sends the generated response data to the terminal. If the transmission is successful, the server goes into standby mode for the next data request.

[1753] Step 9: Receiving response data

[1754] Subject: Device

[1755] The device receives the response data from the server, analyzes the received data, and converts it into a format to be presented to the user. Specifically, it prepares for speech synthesis and text display.

[1756] Step 10: Provide information

[1757] Subject: Device

[1758] The device uses a voice synthesis function to notify the user, "The expressway is congested. You will arrive faster if you use the local road." It also displays text information on the display.

[1759] Step 11: Further emotional advice

[1760] Subject: Device

[1761] If the emotion engine determines that the user is feeling stressed, the device will notify them by saying, "Relax. We'll guide you to the best route," and provide additional advice tailored to the user's mental state.

[1762] Step 12: Process requests for additional information

[1763] Subject: Device

[1764] When a user asks, "What's the weather like along that route?" the device parses this request and generates a new data request to ask the server for weather information again.

[1765] Step 13: Sending and Receiving New Data

[1766] Subject: Terminals and Servers

[1767] The device sends a new data request to the server, which receives the request and analyzes it again, and then sends the analysis results back to the device.

[1768] Step 14: Provide updates

[1769] Subject: Device

[1770] The device will provide the user with newly received weather information via voice and text, informing them that "The weather is currently clear on public roads and visibility is good."

[1771] Through these steps, the system provides real-time information and support to drivers. The introduction of an emotion engine enables detailed support according to the user's emotional state, providing a safer and more comfortable driving environment.

[1772] Example 2

[1773] 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."

[1774] When a driver drives a car or motorcycle alone, they need not only real-time information but also the ability to recognize the driver's emotional state and provide appropriate support to reduce driving stress and anxiety, providing a safe and comfortable driving environment. However, current systems are unable to recognize the user's emotional state in real time and provide advice accordingly. To solve this problem, a new system is needed.

[1775] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1776] In this invention, the server includes a means for acquiring current location and weather information, a means for acquiring traffic information, and a means for recognizing the emotional state of the user, which makes it possible to acquire the user's current location and road conditions in real time, while also analyzing the user's emotional state, and provide optimal routes and advice.

[1777] "Means for determining current location" refers to a device or system that uses a GPS sensor to determine the current location of the driver's vehicle or motorcycle and obtains that information.

[1778] "Means for obtaining weather information using an external API" refers to a device or system for obtaining weather information for the current location and destination using the API of an external weather information service.

[1779] "Means for obtaining traffic information using an external API" refers to a device or system for obtaining road conditions and traffic congestion information using the API of an external traffic information service.

[1780] The "means for transmitting these data to the server" refers to a communication device or system for transmitting the driver's current location, weather information, traffic information, and the like to the server.

[1781] The "means for receiving the analysis results from the server" is a communication device or system for receiving the analysis results sent from the server.

[1782] The "means for analyzing acquired data and recognizing the user's emotional state" refers to an emotion recognition engine or analysis system that analyzes the user's voice and facial expressions and recognizes the user's emotional state.

[1783] The "means for generating response data based on the analysis results" refers to an algorithm or program for generating optimal routes and advice for users based on the data analyzed by the server.

[1784] "Means for providing the received analysis results to the user in voice or text" refers to a device or system for providing information to the user by synthesizing the analysis results received from the server as voice or displaying them as text.

[1785] This invention is a system that provides real-time information to drivers when they are driving a car or motorcycle alone, recognizes the driver's emotions, and provides appropriate support. This system mainly consists of four main components: a terminal, a server, a user, and an emotion engine.

[1786] Terminal

[1787] The terminal is a navigation system installed in a car or motorcycle, and specifically includes a GPS module, a communication module, a voice synthesizer, a text display device, and an emotion engine.

[1788] 1. Obtaining your current location

[1789] The device uses a built-in GPS module (e.g., a Garmin GPS module) to determine the user's current location, which is then converted into JSON format and sent to the server.

[1790] 2. Obtaining weather and road conditions

[1791] The device uses external weather APIs (e.g., OpenWeatherMap API) and traffic APIs (e.g., Google Maps API) to obtain weather information and road conditions for the current location and destination. It sends an API request and sends the JSON-formatted data received as a response to the server.

[1792] 3. Sending and Receiving Data

[1793] The acquired data is sent to the server and the analysis results sent from the server are received. Communication is carried out using the HTTPS protocol.

[1794] 4. Equipped with an emotional engine

[1795] The device is equipped with an emotion engine (for example, Microsoft Azure Emotion API) that analyzes the user's voice and facial expressions. Specifically, it uses a camera and microphone to collect facial images and voice data, which are then sent to a server as emotion data.

[1796] server

[1797] The server has the function of receiving and analyzing data sent from the terminal.

[1798] 1. Data Analysis

[1799] The server comprehensively analyzes the received location, weather information, road conditions, and emotional data, and uses AI algorithms to generate optimal routes and advice, as well as generate response data based on the user's emotional state.

[1800] 2. Generate and send response data

[1801] Based on the analysis results, the engine generates response data for the user. For example, it creates a message such as, "The current weather is rainy. There is traffic congestion, so we recommend taking regular roads," and sends it to the device.

[1802] user

[1803] Users access the system through a terminal and actually drive a car or motorcycle.

[1804] 1. Receiving information

[1805] The user receives information provided by the device. For example, the device may use a voice synthesizer (e.g., Google Text-to-Speech) to notify the user that "the highway is congested. You will arrive faster if you take the local road," and the user can adjust their driving accordingly.

[1806] 2. Request for additional information

[1807] If the user needs more detailed information, they can request additional information using voice commands or touch operations. For example, if they ask, "What's the weather like along that route?", the device will again request the information from the server and provide the latest information.

[1808] 3. Recognizing and Responding to Emotions

[1809] If the user's tone of voice or facial expression is detected as stressed, the device will provide additional advice, such as "Relax. We'll guide you to the best route." This reduces stress and anxiety while driving, providing a safer and more comfortable driving environment.

[1810] Examples and prompts

[1811] For example, when a user travels from Tokyo to Yokohama, the following actions are performed:

[1812] The device uses GPS to determine its current location and obtains weather information and road conditions using the OpenWeatherMap API and Google Maps API.

[1813] The acquired data is sent to a server, which analyzes it and returns the result that "the highway is congested, so we recommend taking a regular road."

[1814] The device uses Google Text-to-Speech to notify the user via voice, "The highway is congested, so we recommend taking a regular road."

[1815] If the user's tone of voice is deemed stressful, the device will offer additional advice: "Relax. We'll guide you to the best route."

[1816] Example prompt sentence:

[1817] "Please provide the best route and weather information for traveling from Tokyo to Yokohama."

[1818] "Generate a message to a user who is currently stressed, with advice on how to relax."

[1819] In this way, the system of the present invention provides appropriate information in real time and optimal support according to the user's emotional state, providing a safe and comfortable driving experience.

[1820] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1821] Step 1:

[1822] The terminal uses a GPS module to determine the driver's current location.

[1823] Input: Satellite signal

[1824] Data processing: The GPS module receives signals from satellites and calculates latitude and longitude.

[1825] Output: Current location latitude and longitude data (JSON format)

[1826] Specific operation: The device's GPS sensor receives satellite signals, analyzes them to determine the current location, and obtains coordinate information.

[1827] Step 2:

[1828] The device uses weather and traffic APIs to obtain weather information and road conditions for the current location and destination.

[1829] Input: The latitude and longitude data determined by the device as its current location

[1830] Data processing: Constructing API requests, sending them to external weather and traffic APIs, and receiving responses in JSON format.

[1831] Output: Weather and road conditions for current and destination locations (JSON format)

[1832] What it does: The device sends requests to the OpenWeatherMap API and Google Maps API to obtain weather and road condition data for the current location and destination.

[1833] Step 3:

[1834] The terminal transmits data on the current location, weather information, and road conditions to the server.

[1835] Input: Weather information and road condition data acquired by the device (JSON format)

[1836] Data processing: The data is formatted in JSON format and sent to the server using the HTTPS protocol.

[1837] Output: Weather and road condition data sent to the server

[1838] Specific operation: The device collects the data and sends it to the server via HTTPS communication.

[1839] Step 4:

[1840] The terminal starts an emotion engine and acquires emotion data of the driver.

[1841] Input: Driver's voice and facial expression data

[1842] Data processing: Using speech recognition and facial expression analysis algorithms to identify emotional states.

[1843] Output: Emotion data (JSON format)

[1844] How it works: The emotion engine uses the camera and microphone to capture voice and facial expressions, which are then analyzed to determine the emotional state.

[1845] Step 5:

[1846] The terminal transmits the emotion data to the server.

[1847] Input: Emotion data acquired by the device (JSON format)

[1848] Data processing: The data is formatted in JSON format and sent to the server using the HTTPS protocol.

[1849] Output: Emotion data sent to the server

[1850] Specific operation: The device compiles emotion data and sends it to the server via HTTPS.

[1851] Step 6:

[1852] The server receives and analyzes the data sent from the terminal.

[1853] Input: Current location, weather information, road conditions, and emotion data (JSON format) sent from the device

[1854] Data processing: AI algorithms are used to analyze data and generate optimal routes and advice.

[1855] Output: Analysis result (JSON format)

[1856] Specific operation: The server comprehensively analyzes the received data and generates optimal route guidance and advice to provide to the driver.

[1857] Step 7:

[1858] The server generates response data based on the analysis results.

[1859] Input: Analyzed current location, weather information, road conditions, emotion data (JSON format)

[1860] Data processing: Construct a response message based on the analysis results.

[1861] Output: Response data (JSON format)

[1862] Specific operation: The server generates a response message from the analysis results and prepares to send it to the terminal.

[1863] Step 8:

[1864] The server transmits the response data to the terminal.

[1865] Input: Response data generated by the server (JSON format)

[1866] Data processing: The data is formatted in JSON format and sent to the terminal using the HTTPS protocol.

[1867] Output: Response data sent to the terminal

[1868] Specific operation: The server compiles the response data and sends it to the terminal via HTTPS communication.

[1869] Step 9:

[1870] The device receives the analysis results from the server and provides them to the user in voice or text format.

[1871] Input: Response data sent from the server (JSON format)

[1872] Data processing: Analyze the data and provide it to the user using speech synthesis or text display functions.

[1873] Output: Audio or text information provided to the user

[1874] Specific operation: The device analyzes the received data and notifies the user via voice using Google Text-to-Speech.

[1875] Step 10:

[1876] If the user requests additional information, the terminal again sends a data acquisition request to the server.

[1877] Input: Request for additional information from the user (voice command, touch action)

[1878] Data processing: Analyze the user's request and send a request to the server to retrieve the required information again.

[1879] Output: Request for more information sent to the server

[1880] Specific operation: The device sends a request to the server again based on the user's request, preparing to provide the latest information.

[1881] Step 11:

[1882] If the user's tone of voice or facial expression indicates stress, the device will offer additional emotional support advice.

[1883] Input: Detection results from the emotion recognition engine (emotion data such as stress, irritation, relaxation, etc.)

[1884] Data processing: Generate appropriate advice for stress reduction.

[1885] Output: Audio or text advice to the user to relax

[1886] What it does: The device analyzes emotional data and provides voice messages such as, "Relax. We'll guide you to the best route."

[1887] (Application example 2)

[1888] 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."

[1889] Conventional navigation systems are limited to providing information on the current location, weather, and road conditions, and are unable to provide appropriate support that takes into account the driver's psychological state. Therefore, the challenge is to reduce the stress and anxiety felt by drivers and provide a safe and comfortable driving environment.

[1890] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1891] In this invention, the server includes means for identifying the current location, means for acquiring weather information using an external API, means for acquiring road conditions using an external API, means for analyzing the emotional state of the driver using an emotion engine, means for providing additional advice based on the emotional state of the driver obtained from the emotion engine, and means for generating an appropriate voice or text message based on a prompt sentence of the generative AI model. This makes it possible to recognize the emotional state of the driver in real time and provide appropriate information and advice according to that state.

[1892] "Means for determining current location" refers to a function that obtains the user's location information using a GPS sensor.

[1893] "Means of obtaining weather information using external APIs" refers to a function that obtains weather information for the current location and destination using cloud services or publicly available APIs.

[1894] "Means of obtaining road conditions using external APIs" refers to a function that obtains traffic conditions and road congestion information using cloud services or publicly available APIs.

[1895] The "means for transmitting these data to the server" is a function for transmitting the acquired current location, weather information, and road condition information to the server via the network.

[1896] The "means for receiving analysis results from the server" is a function for receiving data analysis results sent from the server at the terminal.

[1897] "Means of providing the received analysis results to the user by voice or text" refers to a function that notifies the user of the analysis results through voice synthesis technology or a display.

[1898] The "emotion engine that analyzes the driver's emotional state" is a system that uses voice analysis and facial recognition technology to evaluate the driver's emotions and identify their state.

[1899] The "means for providing additional advice based on the driver's emotional state obtained from the emotion engine" is a function that provides appropriate advice or instructions to the driver based on the analysis results of the emotion engine.

[1900] "Means for generating appropriate voice or text messages based on prompt sentences from a generative AI model" refers to a function that uses a generative AI model to automatically create natural-sounding voice or text messages based on prompt sentences.

[1901] The system of the present invention is comprised of a device installed in an autonomous vehicle, a server, and a user, and provides real-time support and emotion recognition to the driver. Specifically, it has the following configuration and functions:

[1902] Terminal

[1903] The terminals used are navigation systems installed in vehicles, smartphones, etc. The main functions of the terminals are as follows:

[1904] Get current location:

[1905] The vehicle's GPS sensor is used to identify the user's current location, thereby obtaining location information.

[1906] Get weather and road conditions:

[1907] Use external weather APIs (e.g., OpenWeatherMap API) and traffic APIs (e.g., Google Maps API) to obtain weather information and road conditions for your current location and destination.

[1908] Sending and receiving data:

[1909] The device sends the acquired data to a server via the network, and receives the analysis results from the server and notifies the user using voice synthesis and text display functions.

[1910] Emotion engine included:

[1911] The emotion engine recognizes emotions from the driver's voice and facial expressions. It uses IBM Watson Tone Analyzer for voice analysis and Microsoft Face API for facial recognition.

[1912] server

[1913] The server has the function of receiving and analyzing data sent from the terminal. The specific functions of the server are as follows:

[1914] Data reception and analysis:

[1915] The server receives and analyzes the current location data, weather information, road condition information, and emotion data from the emotion engine, using an algorithm that comprehensively considers traffic conditions, weather, recommended routes, and the user's emotional state.

[1916] Generate response data:

[1917] The server generates optimal routes and advice based on the analysis results. For example, if it detects that the driver is feeling stressed, it generates a message with relaxation suggestions.

[1918] Resend data:

[1919] The server transmits the generated response data to the terminal again and provides it to the user.

[1920] User

[1921] The user actually drives the vehicle using this system. The main functions are as follows:

[1922] Receiving information:

[1923] Users can receive information provided by the device and adjust their route and driving method.

[1924] Request for additional information:

[1925] If the user needs more information, they can ask additional questions and request the information from the server through the terminal.

[1926] Recognizing and Responding to Emotions:

[1927] The emotion engine analyzes the user's emotions and provides appropriate advice as needed, such as "Relax. We'll guide you to the best route."

[1928] Specific examples

[1929] When a user travels from Tokyo to Yokohama, the device uses GPS to determine their current location and obtains weather information and road conditions from an API. This data is sent to a server, which analyzes it and returns the result, "The expressway is congested, so we recommend taking an ordinary road." The device notifies the user of the result by voice, and the user selects an ordinary road. If the device determines that the user's tone of voice indicates stress, it provides additional advice, saying, "Please relax. We will guide you to the optimal route." An example of a prompt sentence from the generative AI model used in this case is, "Analyze the driver's emotions and guide them to the optimal route. If it determines that the driver is stressed, please also implement a function to play music for relaxation."

[1930] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1931] Step 1: Get your current location

[1932] The device uses the built-in GPS sensor to determine the user's current location. This location information provides the current latitude and longitude data, which is used in the next processing step.

[1933] Input: None (initial operation)

[1934] Output: Current location latitude and longitude data

[1935] Step 2: Get weather and road conditions

[1936] The device sends requests to external APIs (e.g., weather APIs and road traffic APIs) to obtain the latest weather and road conditions for the current location and destination, thereby providing information about the area the user plans to pass through.

[1937] Input: Latitude and longitude data of current location

[1938] Output: Weather and road conditions for current location and destination

[1939] Step 3: Sending data to the server

[1940] The terminal transmits the acquired current location data, weather information, and road condition information to the server, where the data is uploaded to the server via the network.

[1941] Input: current location latitude and longitude data, weather information, road condition information

[1942] Output: All data sent to the server

[1943] Step 4: Emotion analysis using the emotion engine

[1944] The device's built-in emotion engine analyzes the user's voice and facial expressions to identify their emotional state, using voice analysis and facial recognition technology to assess whether the user is relaxed or stressed.

[1945] Input: User's voice data, face image data

[1946] Output: User's emotional state data

[1947] Step 5: Receiving and analyzing data

[1948] The server receives and analyzes all data sent by the device (current location, weather information, road conditions, emotional state), and runs algorithms to generate optimal routes and additional advice.

[1949] Input: current location latitude and longitude data, weather information, road condition information, emotional state data

[1950] Output: Optimal route information, additional advice

[1951] Step 6: Generate and send response data

[1952] The server generates optimal routes and advice based on the analysis results, and uses a generative AI model to create voice or text messages based on the prompts. This response data is then sent back to the device.

[1953] Input: Optimal route information, additional advice

[1954] Output: Response data (route guidance, advice message)

[1955] Step 7: Notify users

[1956] The device then notifies the user of the response data received from the server. Using voice synthesis and display functions, the device provides guidance on the optimal route and emotional advice. This notification allows the user to adjust their driving style or take action to relax.

[1957] Input: Response data from the server

[1958] Output: Optimal route guidance, emotional advice notification

[1959] 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.

[1960] 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.

[1961] 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.

[1962] 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.

[1963] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1964] 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.

[1965] 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).

[1966] 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.

[1967] 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."

[1968] 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.

[1969] 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).

[1970] 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.

[1971] 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.

[1972] 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.

[1973] 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.

[1974] 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.

[1975] 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.

[1976] 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.

[1977] 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.

[1978] 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...

Claims

1. A means for determining the current location; A means of obtaining weather information using an external API; A means for acquiring road conditions using an external API; means for transmitting these data to a server; means for receiving the analysis results from the server; A means for providing the received analysis results to the user by voice or text; A system including:

2. The system according to claim 1, wherein the server analyzes data on the current location, weather information, and road condition information to generate an optimal route or advice.

3. 2. The system of claim 1, further comprising means for receiving a request for additional information from a user and again transmitting a data acquisition request to the server.

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