system

Abstract

We provide the system. [Solution] In order to generate the optimal route for a moving object, means for acquiring and analyzing traffic information and weather information, A means for communicating with a terminal device that accepts user input and manages reservations for mobile vehicles, A system including communication means for controlling and monitoring reserved mobile objects in real time.

Description

Technical Field

[0001] The technology of this disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Currently, in the field of logistics and transportation, the shortage of labor is intensifying, and the provision of efficient and safe movement is required. Also, there is a problem that it is difficult to provide flexible services according to various needs of users. As a result, in the conventional system, it is difficult to smoothly integrate vehicle dispatching and delivery, and an improvement in service quality is required.

Means for Solving the Problems

[0005] This invention provides a means for acquiring traffic and weather information in real time and generating an optimal route. This means enables flexible service provision by communicating with a terminal device that accepts user input and manages travel reservations. Furthermore, by using a communication means for controlling and monitoring reserved travel destinations in real time, safe and efficient travel is ensured. In addition, by analyzing the user's past travel history and predicting trends, it enables advanced services tailored to individual needs.

[0006] A "mobile device" refers to a mechanical device or vehicle used to transport users to their destination.

[0007] The "optimal route" refers to the route selected to allow a vehicle to travel efficiently, taking into account traffic conditions and the time it will take to reach its destination.

[0008] "Traffic information" refers to data related to road conditions, such as real-time road congestion and traffic accident information.

[0009] "Weather information" refers to real-time data on meteorological conditions such as weather, temperature, precipitation, and wind speed.

[0010] A "terminal device" refers to a digital device that users operate to make travel reservations and complete payment procedures.

[0011] "Communication means" refers to digital network technology used for sending and receiving information, and is used for controlling mobile devices and managing reservation information. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3]It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

MODE FOR CARRYING OUT THE INVENTION

[0013] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described according to the accompanying drawings.

[0014] First, the language used in the following description will be explained.

[0015] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. 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), or Bluetooth (registered trademark), and the like.

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the 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.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0026] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] This invention is a system that realizes an integrated mobility platform for providing efficient transportation services to users using artificial intelligence and autonomous driving technology. This system optimizes vehicle dispatch and delivery by optimizing routes based on traffic and weather information, and by analyzing users' travel patterns. The operation of the system is described below in natural language.

[0034] The server manages and analyzes the data.

[0035] The server collects traffic and weather data in real time and analyzes this data to select the most efficient route. Furthermore, it analyzes the user's past travel history to suggest a personalized route.

[0036] For example, if the server has a history of a specific user leaving for the office at 8:00 AM every Monday, it will calculate the optimal departure time and route based on weather and traffic conditions and notify the user in advance.

[0037] The device provides an interface with the user.

[0038] The terminal receives information such as destinations from users and manages reservations. Users can easily make travel reservations through an interface that operates within the LINE app. Based on information obtained from the server, the terminal displays travel suggestions and the next available reservation times.

[0039] User-friendly operation

[0040] Users can easily book travel by entering their departure and destination points through their device. The app's interactive interface allows users to arrange the most suitable transportation without complex operations.

[0041] Real-time control and payment completion

[0042] The server controls the mobile device in real time and operates while receiving environmental information using 5G communication. After the user completes their movement, the terminal quickly and easily completes the payment process using PayPay.

[0043] Through these processes, the present invention realizes efficient and user-friendly transportation services. Furthermore, it addresses the problem of labor shortages in logistics and delivery, and builds a system that is highly safe and convenient.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The server collects traffic and weather information in real time. This allows for an accurate understanding of current road conditions and weather conditions, which helps in the efficient operation of mobile vehicles.

[0047] Step 2:

[0048] The server retrieves the user's past travel history from a database and analyzes their movement trends. Based on this information, it prepares to provide personalized services to the user.

[0049] Step 3:

[0050] The user enters their departure point, destination, and departure time through their device. The device receives this information and sends it to the server.

[0051] Step 4:

[0052] The server calculates the optimal route based on information received from the terminal. It selects the best route from multiple options, taking into account traffic conditions and user travel patterns.

[0053] Step 5:

[0054] The server checks the current location and status of the moving object and selects an available vehicle. Based on this information, the server creates a dispatch plan.

[0055] Step 6:

[0056] The server sends information about available vehicles and the optimal route to the terminal. The terminal displays this information to the user and prompts them to confirm the vehicle assignment.

[0057] Step 7:

[0058] The user confirms the ride request via their terminal. After confirmation, the terminal sets the payment method and verifies the pre-registered payment method.

[0059] Step 8:

[0060] Once the transfer is complete, the terminal receives a payment request from the server and executes the payment using the pre-configured payment method. This completes all processes related to the transfer.

[0061] (Example 1)

[0062] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0063] In modern urban environments, traffic congestion and unpredictable weather conditions make efficient travel difficult. Furthermore, there is a need to provide safe and convenient services that meet the diverse travel needs of users. Additionally, labor shortages pose challenges to achieving smooth transportation and logistics.

[0064] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0065] In this invention, the server includes means for acquiring and analyzing traffic condition information and environmental condition information, means for receiving user input and communicating with a terminal device for managing reservations for mobile devices, and communication means for controlling reserved mobile devices and monitoring them in real time. This enables optimized route selection for individual users and allows for the provision of efficient and safe mobility services.

[0066] "Traffic information" refers to data showing road congestion levels, travel times, and real-time traffic flow.

[0067] "Environmental condition information" refers to information that includes data on weather, temperature, precipitation, and other meteorological conditions.

[0068] "User" refers to an individual or group that wishes to receive mobility services using this system.

[0069] "Mobile devices" refer to devices including vehicles and delivery equipment that are operated autonomously or remotely.

[0070] "Terminal device" refers to electronic devices or interfaces that users use to input data and communicate with the system.

[0071] "Communication methods" refer to communication technologies and infrastructure used to send and receive information in real time.

[0072] A "processing device" refers to a device that handles information processing to analyze data and calculate the optimal path.

[0073] A "unified communication network" refers to a network infrastructure that can handle information centrally without using multiple communication protocols.

[0074] This invention is an integrated system that utilizes traffic and environmental information to optimize the routes of moving objects efficiently and provide mobility services to users. The main components of the system allow each function to operate as follows:

[0075] First, the server acquires and analyzes traffic and environmental information. Specifically, it collects real-time data using an API service and calculates the optimal route using an analysis engine. This analysis engine implements an AI algorithm using deep learning to calculate the optimized travel route.

[0076] Next, the terminal provides an electronic interface to receive user input. For example, via a smartphone app, users can enter their departure point, destination, and desired departure time. This terminal interacts with a server to present a plan suitable for the user. It also includes payment processing functionality, allowing users to make electronic payments after completing their journey.

[0077] Finally, the user books their desired journey via the terminal. The user easily enters information through an interactive interface and reviews the optimal route and travel plan provided by the server.

[0078] For example, the server can suggest an optimal departure time, different from the usual route, based on the weather and traffic conditions, using the past travel history of a specific user heading to the office on Monday mornings.

[0079] An example of an input prompt for a generating AI model is: "For a user who goes to the office every Monday, please suggest the optimal departure time and route, taking weather and traffic conditions into consideration."

[0080] The implementation of this system will enable the provision of innovative mobility services that combine safety and convenience, from individual users to logistics operations.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The server acquires traffic and environmental information. The server receives current traffic and weather information via traffic data APIs and weather data APIs. The latest traffic speed data, congestion information, temperature, and precipitation probability are provided as input from each API. The server uses this information to update a database that monitors environmental conditions in real time.

[0084] Step 2:

[0085] The server analyzes the acquired data and calculates the optimal travel route. The server inputs the collected traffic and weather data into an AI algorithm to generate the best route for the user. As part of data processing, a machine learning model is used to predict traffic, and the output generates optimal route information including current and predicted routes.

[0086] Step 3:

[0087] The terminal receives input from the user. The user enters their departure point, destination, and desired travel time into the terminal via a smartphone app. The input is directly from the user in text data format, and the app converts this data into a format and sends it to the server. After sending, the terminal waits to receive optimal route data from the server.

[0088] Step 4:

[0089] The server integrates user input with optimal travel route information and sends an optimized travel plan to the device. Input includes the user's destination and departure time information, as well as analyzed optimal route information. The server returns the integrated result to the device as JSON data.

[0090] Step 5:

[0091] The device displays information received from the server to the user. The device receives a response from the server and visualizes the suggested optimal route, departure time, and estimated arrival time on the app screen for the user. As output, the user receives a visually verifiable travel plan.

[0092] Step 6:

[0093] The user books their travel through their device. The user reviews the proposed travel plan and completes the booking by tapping the "Make Arrangement" button. Based on the user's input, the device sends the booking data to the server for approval within the system.

[0094] Step 7:

[0095] The server monitors and controls movement. The server acquires location data of the moving object in real time, and if any changes in the situation are anticipated, it recalculates the route and sends instructions to the terminal. The input is GPS information of the moving object, and the output is instructions based on that information.

[0096] Step 8:

[0097] The terminal completes the payment process. After the transfer is complete, the terminal prompts the user to confirm payment and processes the electronic payment. Payment information is sent to the terminal as input, and a payment completion notification is sent to the user as output.

[0098] (Application Example 1)

[0099] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0100] In mobility services utilizing autonomous driving technology, there is a need to provide route guidance that constantly reflects optimal traffic and weather conditions, as well as a personalized travel experience that takes into account the user's past travel history. Furthermore, smooth payment processing after the completion of the journey is also a crucial challenge.

[0101] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0102] In this invention, the server includes means for acquiring and analyzing traffic and weather information; means for receiving user input and communicating with an information terminal for managing reservations for mobile vehicles; means for controlling and monitoring reserved mobile vehicles in real time; means for notifying users of recommended routes and departure times; means for processing payment information after the completion of travel; and means for updating routes as needed based on traffic and weather conditions. This enables a smart travel service that provides users with an efficient and personalized travel experience and allows for quick payment.

[0103] "Traffic information" refers to information on roads that affects the movement of vehicles, such as road congestion, accidents, and traffic jams.

[0104] "Weather information" refers to information about the natural environment that affects the operation of moving objects, such as weather, temperature, precipitation, and wind speed.

[0105] An "information terminal" refers to a device that receives user input and performs tasks such as outputting various types of information and managing reservations for mobile devices.

[0106] "Communication means" refers to the technical means for exchanging information between a server and an information terminal or mobile device. These means include network lines and protocols.

[0107] A "recommended route" refers to a path calculated based on traffic conditions and weather conditions to efficiently reach the destination.

[0108] "Payment information" refers to data and procedures related to paying for the use of mobility services.

[0109] "Real-time route updates" means dynamically recalculating and optimizing travel routes in response to changes in current traffic conditions and weather.

[0110] The system for realizing this invention involves running a program on a server that acquires and analyzes traffic and weather information in real time. The server analyzes this data and calculates the optimal route. The hardware used includes a server machine capable of high-speed computing and a communication network. The software implements data analysis algorithms and communication protocols. The server also analyzes the user's past travel history to provide personalized travel guidance.

[0111] Information terminals receive information such as destinations from users and, in cooperation with a server, make reservations for travel and suggest routes. Smartphones, which are portable communication devices, are primarily used. These terminals incorporate application software that facilitates interface design. The terminal displays the information received from the server and notifies the user of recommended travel routes and optimal departure times.

[0112] Users can book transportation through their terminals with simple operations. To enhance usability, an interactive interface is provided within the app. Furthermore, after the journey is complete, the terminal processes payment information, enabling quick and convenient payment. A digital payment platform is used as the payment method here.

[0113] For example, if a user plans to travel from a city to the suburbs over the weekend, the server will consider expected congestion and weather conditions, calculate the optimal route in advance, and notify the user. Even if sudden weather changes occur at the time of departure, the route will be adjusted to the optimal direction thanks to a real-time route update function. Furthermore, payment will be automatically completed upon completion of the trip, enhancing user convenience.

[0114] Example prompt: "Please provide instructions necessary for the user to travel efficiently to the city center using autonomous driving. Suggest the optimal route, taking into account time, weather, and traffic, and provide explanations that allow for changes during the journey."

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The server acquires traffic and weather information in real time. It receives the latest road and weather data through various APIs as input and generates analyzable datasets as output. This prepares the data for use in the next step.

[0118] Step 2:

[0119] The server calculates the optimal route based on the acquired information. It uses an algorithm (e.g., Dijkstra's algorithm) to solve the shortest path problem by analyzing the dataset obtained in Step 1 as input. The output calculates the recommended route to the destination and the required departure time. This operation is designed to handle real-time information updates.

[0120] Step 3:

[0121] The server analyzes the user's past travel history. It references a database of past travel data as input and applies a pattern recognition algorithm. As output, it generates personalized travel suggestions that take into account the user's preferred routes and departure times.

[0122] Step 4:

[0123] The terminal accepts destination input from the user. It handles geographical information received through the user interface as input and generates a request for communication with the server as output. This operation is performed simply using an interactive interface.

[0124] Step 5:

[0125] The terminal notifies the user of the recommended route and departure time received from the server. It interprets the communication content from the server as input and converts it into a format that can be displayed on the screen as output. In this way, the user can receive optimal travel suggestions based on real-time traffic information.

[0126] Step 6:

[0127] The user makes a reservation for travel using their device. The user confirms the departure and destination based on recommended information as input, and confirms the reservation details as output. This process is completed with simple user operation.

[0128] Step 7:

[0129] The server recalculates the route if traffic or weather conditions change during travel. It uses the latest newly acquired information as input and sends the improved route information to the terminal as output. This achieves real-time optimization.

[0130] Step 8:

[0131] The terminal processes payment information after the move is complete and completes the payment using the user's account. It sends the amount spent and credit card information to the server as input and receives confirmation of transaction completion as output. This process is fast and secure through the payment platform.

[0132] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0133] This invention is an integrated mobility system for achieving efficient dispatch and delivery of mobile vehicles, and has the function of recognizing user emotions and dynamically changing its response. This system generates optimal routes based on traffic and weather information, and not only reserves and controls mobile vehicles, but also provides services while taking user emotions into consideration.

[0134] The server analyzes the data.

[0135] The server analyzes traffic information, weather information, and the user's travel history. Based on this analysis, it plans the optimal route for the mobile device to efficiently reach its destination. The server also uses an emotion engine to analyze voice and text data received from the terminal device to identify the user's emotional state.

[0136] For example, if the server detects stress from the user's voice, it can prioritize a more comfortable route that shortens the travel time to the destination when selecting a route.

[0137] The terminal provides an interface with the user.

[0138] The terminal receives input from the user and sends travel reservations and sentiment data to the server. Through an interactive interface, the terminal allows users to easily set destinations and collects data required by the sentiment engine from the user's voice and text.

[0139] The user operates the system

[0140] Users input their travel preferences through the terminal interface, while their emotional state is communicated to the system via voice or text. This allows for the provision of customized services tailored to the user's emotional state.

[0141] Real-time control and service coordination

[0142] The server has the ability to automatically adjust the in-vehicle environment settings (e.g., music selection and air conditioning adjustment) according to the user's emotional state. This allows the emotion engine to optimize the environment during travel, improving the user's comfort.

[0143] Through these processes, the present invention improves the accuracy and satisfaction of services for individual users by combining emotion recognition technology with conventional mobility services.

[0144] The following describes the processing flow.

[0145] Step 1:

[0146] The server collects and analyzes traffic and weather information in real time, constantly monitoring various road and weather conditions. This updates the database related to the operation of mobile vehicles.

[0147] Step 2:

[0148] The terminal accepts input from the user, such as destination and departure time. Based on the user's requested conditions, the terminal sends a request to the server.

[0149] Step 3:

[0150] The device sends the user's voice or text to an emotion engine, which analyzes their emotional state. The engine identifies emotions such as stress, joy, and anxiety.

[0151] Step 4:

[0152] The server calculates the optimal route based on the travel conditions and emotional state it receives. Depending on the emotional state, it selects a more comfortable route or option and sends it to the terminal.

[0153] Step 5:

[0154] The user confirms the vehicle assignment on their terminal. Once the assignment is confirmed, the server adjusts the vehicle's schedule and sends the necessary instructions to the vehicle.

[0155] Step 6:

[0156] Once the mobile device begins operation, the server controls it in real time, making environmental adjustments (such as controlling lighting and music) in response to the user's emotional state.

[0157] Step 7:

[0158] Upon arrival at the destination, the terminal initiates the payment process. If the sentiment engine's results affect the price, the server may apply special pricing options.

[0159] Step 8:

[0160] The user completes the payment via the LINE app, and the entire process is finished. Payment information and travel history are stored in a database and used to improve future services.

[0161] (Example 2)

[0162] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0163] Modern transportation systems utilize traffic and weather information to select the optimal route for travelers, but they lack the flexibility to take into account the emotional state of users. Furthermore, there is a need to improve convenience by linking users' travel history with their immediate emotional state. Additionally, there is a lack of personalized service tailored to users' emotional states. Solving these challenges is essential.

[0164] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0165] In this invention, the server includes means for acquiring and analyzing traffic and weather information to generate an optimal route for a mobile object; means for analyzing the user's emotional state and adjusting the mobile object's environmental settings based on the user's emotions; and means for dynamically changing the optimal route based on the results of the user's emotional analysis. This makes it possible to provide an optimal travel experience that reflects the user's emotional state.

[0166] A "mobile entity" refers to a vehicle or device used to transport users or goods to a destination, and is controlled autonomously or manually.

[0167] The "optimal route" is the route selected to ensure that a moving object reaches its destination safely and efficiently, and is dynamically adjusted based on traffic information, weather information, and user requests.

[0168] "Traffic information" refers to data that affects travel, such as road conditions, congestion levels, and construction information.

[0169] "Weather information" refers to data on meteorological conditions that affect travel, such as weather, temperature, precipitation, and wind speed.

[0170] "Terminal devices" refer to electronic devices used by users to input information and interface with a system, and include smartphones and tablets.

[0171] "Emotional state" refers to the user's psychological condition and mood, and is identified through the analysis of voice and text data.

[0172] "Environmental settings" refer to conditions such as temperature, lighting, and sound inside the mobile vehicle, and are adjusted to improve user comfort.

[0173] "Dynamic modification" refers to the process of updating and optimizing pre-determined settings and conditions in real time.

[0174] "Emotional analysis results" refer to data obtained after identifying the user's emotional state, and are used for service provision and route selection.

[0175] This invention is an integrated mobility system for achieving efficient dispatching and delivery of mobile vehicles, and has the function of providing dynamic responses that take into account the emotional state of the user. In this embodiment of the system, the server, terminal, and user components communicate with each other to provide the optimal mobility service.

[0176] The server uses external data sources such as traffic information APIs and weather information APIs to acquire data in real time. This allows the server to calculate the most efficient route and provide instructions to the moving object. Furthermore, the server uses an emotion engine to analyze voice and text data transmitted from the terminal to determine the user's emotional state. The emotion engine utilizes natural language processing libraries and sentiment analysis APIs.

[0177] The terminal transmits destination and reservation information entered by the user to the server. The terminal is equipped with an interface that allows for both voice and text input, making it easy for users to access the system. Through this interface, the terminal collects user sentiment data and transmits it to the server.

[0178] Users can input their travel preferences through the terminal interface and communicate their emotional state to the system using voice or text. This allows for the provision of travel services optimized for each individual user.

[0179] As a concrete example, suppose a user verbally instructs their device to "arrive quickly and quietly." The device sends this information to the server, and based on the data collected in real time, the server can select the optimal route with less congestion. Furthermore, if the server determines that the user's emotional state is one of high stress levels, it will play relaxing music during the journey to improve the user's comfort.

[0180] As a concrete example of a prompt given to a generating AI model, one could input, "Please tell me how to suggest services that are appropriate when the user wants to relax." This prompt allows the system to adaptively adjust the services it provides.

[0181] This invention integrates these functions to realize advanced mobility services that take into account the user's emotions.

[0182] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0183] Step 1:

[0184] The device collects user input information.

[0185] When a user enters their destination or travel preferences into the device's interface, the device receives this information as voice or text data. The input information also includes the user's emotional state, which is then used to organize the necessary data for subsequent processing. For example, if a user says, "I want to get to work early," this information is converted into digital data through speech recognition and natural language processing.

[0186] Step 2:

[0187] The terminal sends data to the server.

[0188] The device sends the collected user destination information and sentiment data to the server using HTTPS. At this stage, the data is encrypted and sent to the server's API in a secure format. Specifically, the device sends "Destination: Workplace, Priority: Arrive quickly, Sentiment: Urgent" to the server.

[0189] Step 3:

[0190] The server calculates the optimal route.

[0191] The server uses traffic information APIs and weather information APIs based on the received data to calculate the optimal route. As an example of data processing, it calculates the estimated arrival time based on traffic information and extracts the optimal route. Specifically, the server decides to "select Route C, which is the shortest route to the destination and has less congestion."

[0192] Step 4:

[0193] The server adjusts the service based on the emotional state.

[0194] The server uses an emotion analysis engine to analyze the user's emotional state and issues commands to adjust the mobile device's environment settings based on that analysis. If the emotion indicates stress, the device will be set to play relaxing music. Specifically, the server issues commands such as "stress detection, route C selection, and play relaxation music."

[0195] Step 5:

[0196] The server sends the results to the terminal, and the terminal notifies the user.

[0197] The server sends the final route and service coordination information back to the terminal, which then notifies the user of that information. As a concrete example of output, the terminal might tell the user, "Using Route C, travel time is 15 minutes. Starting relaxation music."

[0198] Step 6:

[0199] The user boards the mobile vehicle and receives the provided service.

[0200] The user boards the vehicle following instructions from their terminal. During the journey, they enjoy a comfortable travel experience through environmental settings instructed by the server. For example, the user travels along a designated route and listens to relaxation music.

[0201] (Application Example 2)

[0202] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0203] To achieve efficient dispatching and delivery of mobile vehicles, route optimization that takes traffic and weather information into account is necessary. However, conventional systems cannot provide services that take into account the emotional state of users, resulting in a lack of customized services for individual users. Therefore, to improve user satisfaction, an advanced mobile vehicle control system incorporating emotion recognition is required.

[0204] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0205] In this invention, the server includes means for acquiring and analyzing traffic and weather information, means for communicating with a terminal device that accepts user input, and means for controlling and monitoring reserved mobile objects in real time. This enables route optimization and dynamic adjustment of environmental settings that take into account the user's emotional state.

[0206] A "mobile device" refers to a machine or vehicle whose role is to move people or objects from one place to another.

[0207] The "optimal route" refers to the path chosen to maximize the efficiency of travel and minimize time and fuel consumption.

[0208] "Traffic information" refers to data on road congestion, accidents, road closures, and other related information.

[0209] "Weather information" refers to data related to meteorological conditions, such as weather, temperature, and precipitation.

[0210] A "terminal device" refers to an electronic device used by a user to input information or communicate with a system.

[0211] "Communication methods" refer to the methods and technologies for sending and receiving data between different devices within a system.

[0212] "Emotional state" refers to the psychological state a user experiences, such as stress or relaxation.

[0213] "Route optimization" refers to the process of selecting and adjusting routes to improve the efficiency of travel, taking into account traffic conditions and the state of users.

[0214] "Environmental settings" refers to adjustments made to the music, air conditioning, lighting, and other elements within the vehicle to enhance user comfort.

[0215] The system implementing the present invention has an advanced control mechanism for achieving efficient and personalized dispatching and delivery of mobile vehicles.

[0216] The server uses traffic information APIs and weather information APIs to acquire traffic and weather conditions in real time, and analyzes this data using Python libraries such as NumPy and Pandas. This allows it to calculate the optimal route and help select a route for the moving object. Furthermore, it can use an emotion engine (e.g., Affectiva) to analyze voice data transmitted from the user's terminal device and identify the user's emotional state. Based on this identified emotional state, it automatically adjusts the environment settings during travel (music, lighting, air conditioning, etc.) to enhance the user's comfort.

[0217] The terminal device provides an interface for users to input destinations and other information. Information entered by the user via voice or text is transmitted to the server as emotional data referenced by the emotion engine. This allows the user's travel experience to be customized to their individual emotional state, thereby improving user satisfaction.

[0218] As a concrete example, if a user is caught in traffic and stress is detected, the system can quickly select the optimal alternative route. It can also provide a user-friendly travel experience by playing relaxing music and adjusting the in-car temperature appropriately.

[0219] In this way, the present invention takes mobility services a step further and provides added value through emotion recognition.

[0220] An example of a prompt is: "Explain how, when a user is wearing smart glasses, the AI ​​combines traffic congestion data with the user's stress level to optimize route selection."

[0221] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0222] Step 1:

[0223] The server retrieves data from traffic and weather information APIs. The input is real-time traffic and weather data, which is then analyzed using NumPy and Pandas to calculate the optimal travel route. The output is the calculated optimal route information.

[0224] Step 2:

[0225] The terminal receives destination and reservation information from the user in text or voice format. Input is the user's destination information, which is transmitted to the system via the user interface. Output is the reservation information sent to the system.

[0226] Step 3:

[0227] The server uses an emotion engine to analyze voice data transmitted from the terminal. The input is the user's voice data, and the analysis identifies the user's emotional state. The output is the identified emotional state.

[0228] Step 4:

[0229] The server optimizes the environment settings of a mobile object based on its emotional state. The input consists of the identified emotional state and route information based on traffic data, and the system generates data to adjust the environment settings. The output is the adjusted environment settings.

[0230] Step 5:

[0231] Users experience a customized environment for their mobile device. As a result, the user's travel experience adapts to their individual emotional state, leading to improved comfort.

[0232] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0233] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0234] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0235] [Second Embodiment]

[0236] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0237] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0238] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0239] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0240] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0241] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0242] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0243] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0244] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0245] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0246] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0247] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0248] This invention is a system that realizes an integrated mobility platform for providing efficient transportation services to users using artificial intelligence and autonomous driving technology. This system optimizes vehicle dispatch and delivery by optimizing routes based on traffic and weather information, and by analyzing users' travel patterns. The operation of the system is described below in natural language.

[0249] The server manages and analyzes the data.

[0250] The server collects traffic and weather data in real time and analyzes this data to select the most efficient route. Furthermore, it analyzes the user's past travel history to suggest a personalized route.

[0251] For example, if the server has a history of a specific user leaving for the office at 8:00 AM every Monday, it will calculate the optimal departure time and route based on weather and traffic conditions and notify the user in advance.

[0252] The device provides an interface with the user.

[0253] The terminal receives information such as destinations from users and manages reservations. Users can easily make travel reservations through an interface that operates within the LINE app. Based on information obtained from the server, the terminal displays travel suggestions and the next available reservation times.

[0254] User-friendly operation

[0255] Users can easily book travel by entering their departure and destination points through their device. The app's interactive interface allows users to arrange the most suitable transportation without complex operations.

[0256] Real-time control and payment completion

[0257] The server controls the mobile device in real time and operates while receiving environmental information using 5G communication. After the user completes their movement, the terminal quickly and easily completes the payment process using PayPay.

[0258] Through these processes, the present invention realizes efficient and user-friendly transportation services. Furthermore, it addresses the problem of labor shortages in logistics and delivery, and builds a system that is highly safe and convenient.

[0259] The following describes the processing flow.

[0260] Step 1:

[0261] The server collects traffic and weather information in real time. This allows for an accurate understanding of current road conditions and weather conditions, which helps in the efficient operation of mobile vehicles.

[0262] Step 2:

[0263] The server retrieves the user's past travel history from a database and analyzes their movement trends. Based on this information, it prepares to provide personalized services to the user.

[0264] Step 3:

[0265] The user enters their departure point, destination, and departure time through their device. The device receives this information and sends it to the server.

[0266] Step 4:

[0267] The server calculates the optimal route based on information received from the terminal. It selects the best route from multiple options, taking into account traffic conditions and user travel patterns.

[0268] Step 5:

[0269] The server checks the current location and status of the moving object and selects an available vehicle. Based on this information, the server creates a dispatch plan.

[0270] Step 6:

[0271] The server sends information about available vehicles and the optimal route to the terminal. The terminal displays this information to the user and prompts them to confirm the vehicle assignment.

[0272] Step 7:

[0273] The user confirms the ride request via their terminal. After confirmation, the terminal sets the payment method and verifies the pre-registered payment method.

[0274] Step 8:

[0275] Once the transfer is complete, the terminal receives a payment request from the server and executes the payment using the pre-configured payment method. This completes all processes related to the transfer.

[0276] (Example 1)

[0277] Next, we will describe Example 1. 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."

[0278] In modern urban environments, traffic congestion and unpredictable weather conditions make efficient travel difficult. Furthermore, there is a need to provide safe and convenient services that meet the diverse travel needs of users. Additionally, labor shortages pose challenges to achieving smooth transportation and logistics.

[0279] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0280] In this invention, the server includes means for acquiring and analyzing traffic condition information and environmental condition information, means for receiving user input and communicating with a terminal device for managing reservations for mobile devices, and communication means for controlling reserved mobile devices and monitoring them in real time. This enables optimized route selection for individual users and allows for the provision of efficient and safe mobility services.

[0281] "Traffic information" refers to data showing road congestion levels, travel times, and real-time traffic flow.

[0282] "Environmental condition information" refers to information that includes data on weather, temperature, precipitation, and other meteorological conditions.

[0283] "User" refers to an individual person or group who wishes to receive mobility services using this system.

[0284] "Mobility device" refers to a device that includes vehicles and delivery equipment that operate autonomously or remotely.

[0285] "Terminal device" refers to an electronic device or interface through which a user inputs and communicates with the system.

[0286] "Communication means" refers to communication technologies and infrastructure used to transmit and receive information in real time.

[0287] "Processing device" refers to a device responsible for information processing to analyze data and calculate an optimal route.

[0288] "Integrated communication network" refers to a network infrastructure that can handle information in a unified manner without using multiple communication protocols.

[0289] The present invention is an integrated system that uses traffic situation information and environmental condition information to provide efficient route optimization for moving objects and mobility services for users. Each function operates as follows according to the main components of the system.

[0290] First, the server acquires and analyzes traffic situation information and environmental condition information. Specifically, it collects real-time data using an API service and calculates an optimal route using an analysis engine. This analysis engine implements an AI algorithm using deep learning to calculate an optimized movement route.

[0291] Next, the terminal provides an electronic interface to receive user input. For example, through a smartphone app, the user can input the departure location, destination, and desired departure time. This terminal cooperates with the server and presents a plan suitable for the user. It also includes a payment processing function, and after the movement is completed, the user can perform electronic payment.

[0292] Finally, the user books their desired journey via the terminal. The user easily enters information through an interactive interface and reviews the optimal route and travel plan provided by the server.

[0293] For example, the server can suggest an optimal departure time, different from the usual route, based on the weather and traffic conditions, using the past travel history of a specific user heading to the office on Monday mornings.

[0294] An example of an input prompt for a generating AI model is: "For a user who goes to the office every Monday, please suggest the optimal departure time and route, taking weather and traffic conditions into consideration."

[0295] The implementation of this system will enable the provision of innovative mobility services that combine safety and convenience, from individual users to logistics operations.

[0296] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0297] Step 1:

[0298] The server acquires traffic and environmental information. The server receives current traffic and weather information via traffic data APIs and weather data APIs. The latest traffic speed data, congestion information, temperature, and precipitation probability are provided as input from each API. The server uses this information to update a database that monitors environmental conditions in real time.

[0299] Step 2:

[0300] The server analyzes the acquired data and calculates the optimal travel route. The server inputs the collected traffic and weather data into an AI algorithm to generate the best route for the user. As part of data processing, a machine learning model is used to predict traffic, and the output generates optimal route information including current and predicted routes.

[0301] Step 3:

[0302] The terminal receives an input from the user. The user inputs the departure location, destination, and desired departure time into the terminal via a smartphone app. The input is in the form of text data directly from the user, and the app converts this data into a format and sends it to the server. After sending, the terminal waits to receive the optimal route data from the server.

[0303] Step 4:

[0304] The server integrates the user's input and the optimal travel route information and sends an optimized travel plan to the terminal. The inputs include the destination and departure time information from the user and the analyzed optimal route information. The server returns the integrated result to the terminal as JSON data.

[0305] Step 5:

[0306] The terminal displays the information received from the server to the user. The terminal receives the response from the server and visualizes the proposed optimal route, departure time, and expected arrival time on the app screen for the user. As output, the user obtains a visually confirmable travel plan.

[0307] Step 6:

[0308] The user reserves the travel through the terminal. The user confirms the proposed travel plan and completes the reservation by tapping the button for arrangements. Based on the user's input, the terminal sends the reservation data to the server and obtains approval within the system.

[0309] Step 7:

[0310] The server monitors and controls the travel. The server obtains the real-time position data of the moving body, and if a situation change is predicted in case of an emergency, recalculates the route and sends an instruction to the terminal. The input is the GPS information of the moving body, and the output is the instruction based on it.

[0311] Step 8:

[0312] The terminal completes the payment process. After the transfer is complete, the terminal prompts the user to confirm payment and processes the electronic payment. Payment information is sent to the terminal as input, and a payment completion notification is sent to the user as output.

[0313] (Application Example 1)

[0314] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0315] In mobility services utilizing autonomous driving technology, there is a need to provide route guidance that constantly reflects optimal traffic and weather conditions, as well as a personalized travel experience that takes into account the user's past travel history. Furthermore, smooth payment processing after the completion of the journey is also a crucial challenge.

[0316] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0317] In this invention, the server includes means for acquiring and analyzing traffic and weather information; means for receiving user input and communicating with an information terminal for managing reservations for mobile vehicles; means for controlling and monitoring reserved mobile vehicles in real time; means for notifying users of recommended routes and departure times; means for processing payment information after the completion of travel; and means for updating routes as needed based on traffic and weather conditions. This enables a smart travel service that provides users with an efficient and personalized travel experience and allows for quick payment.

[0318] "Traffic information" refers to information on roads that affects the movement of vehicles, such as road congestion, accidents, and traffic jams.

[0319] "Weather information" refers to information about the natural environment that affects the operation of moving objects, such as weather, temperature, precipitation, and wind speed.

[0320] An "information terminal" refers to a device that receives user input and performs tasks such as outputting various types of information and managing reservations for mobile devices.

[0321] "Communication means" refers to the technical means for exchanging information between a server and an information terminal or mobile device. These means include network lines and protocols.

[0322] A "recommended route" refers to a path calculated based on traffic conditions and weather conditions to efficiently reach the destination.

[0323] "Payment information" refers to data and procedures related to paying for the use of mobility services.

[0324] "Real-time route updates" means dynamically recalculating and optimizing travel routes in response to changes in current traffic conditions and weather.

[0325] The system for realizing this invention involves running a program on a server that acquires and analyzes traffic and weather information in real time. The server analyzes this data and calculates the optimal route. The hardware used includes a server machine capable of high-speed computing and a communication network. The software implements data analysis algorithms and communication protocols. The server also analyzes the user's past travel history to provide personalized travel guidance.

[0326] Information terminals receive information such as destinations from users and, in cooperation with a server, make reservations for travel and suggest routes. Smartphones, which are portable communication devices, are primarily used. These terminals incorporate application software that facilitates interface design. The terminal displays the information received from the server and notifies the user of recommended travel routes and optimal departure times.

[0327] Users can book transportation through their terminals with simple operations. To enhance usability, an interactive interface is provided within the app. Furthermore, after the journey is complete, the terminal processes payment information, enabling quick and convenient payment. A digital payment platform is used as the payment method here.

[0328] For example, if a user plans to travel from a city to the suburbs over the weekend, the server will consider expected congestion and weather conditions, calculate the optimal route in advance, and notify the user. Even if sudden weather changes occur at the time of departure, the route will be adjusted to the optimal direction thanks to a real-time route update function. Furthermore, payment will be automatically completed upon completion of the trip, enhancing user convenience.

[0329] Example prompt: "Please provide instructions necessary for the user to travel efficiently to the city center using autonomous driving. Suggest the optimal route, taking into account time, weather, and traffic, and provide explanations that allow for changes during the journey."

[0330] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0331] Step 1:

[0332] The server acquires traffic and weather information in real time. It receives the latest road and weather data through various APIs as input and generates analyzable datasets as output. This prepares the data for use in the next step.

[0333] Step 2:

[0334] The server calculates the optimal route based on the acquired information. It uses an algorithm (e.g., Dijkstra's algorithm) to solve the shortest path problem by analyzing the dataset obtained in Step 1 as input. The output calculates the recommended route to the destination and the required departure time. This operation is designed to handle real-time information updates.

[0335] Step 3:

[0336] The server analyzes the user's past travel history. It references a database of past travel data as input and applies a pattern recognition algorithm. As output, it generates personalized travel suggestions that take into account the user's preferred routes and departure times.

[0337] Step 4:

[0338] The terminal accepts destination input from the user. It handles geographical information received through the user interface as input and generates a request for communication with the server as output. This operation is performed simply using an interactive interface.

[0339] Step 5:

[0340] The terminal notifies the user of the recommended route and departure time received from the server. It interprets the communication content from the server as input and converts it into a format that can be displayed on the screen as output. In this way, the user can receive optimal travel suggestions based on real-time traffic information.

[0341] Step 6:

[0342] The user makes a reservation for travel using their device. The user confirms the departure and destination based on recommended information as input, and confirms the reservation details as output. This process is completed with simple user operation.

[0343] Step 7:

[0344] The server recalculates the route if traffic or weather conditions change during travel. It uses the latest newly acquired information as input and sends the improved route information to the terminal as output. This achieves real-time optimization.

[0345] Step 8:

[0346] The terminal processes payment information after the move is complete and completes the payment using the user's account. It sends the amount spent and credit card information to the server as input and receives confirmation of transaction completion as output. This process is fast and secure through the payment platform.

[0347] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0348] This invention is an integrated mobility system for achieving efficient dispatch and delivery of mobile vehicles, and has the function of recognizing user emotions and dynamically changing its response. This system generates optimal routes based on traffic and weather information, and not only reserves and controls mobile vehicles, but also provides services while taking user emotions into consideration.

[0349] The server analyzes the data.

[0350] The server analyzes traffic information, weather information, and the user's travel history. Based on this analysis, it plans the optimal route for the mobile device to efficiently reach its destination. The server also uses an emotion engine to analyze voice and text data received from the terminal device to identify the user's emotional state.

[0351] For example, if the server detects stress from the user's voice, it can prioritize a more comfortable route that shortens the travel time to the destination when selecting a route.

[0352] The terminal provides an interface with the user.

[0353] The terminal receives input from the user and sends travel reservations and sentiment data to the server. Through an interactive interface, the terminal allows users to easily set destinations and collects data required by the sentiment engine from the user's voice and text.

[0354] The user operates the system

[0355] Users input their travel preferences through the terminal interface, while their emotional state is communicated to the system via voice or text. This allows for the provision of customized services tailored to the user's emotional state.

[0356] Real-time control and service coordination

[0357] The server has the ability to automatically adjust the in-vehicle environment settings (e.g., music selection and air conditioning adjustment) according to the user's emotional state. This allows the emotion engine to optimize the environment during travel, improving the user's comfort.

[0358] Through these processes, the present invention improves the accuracy and satisfaction of services for individual users by combining emotion recognition technology with conventional mobility services.

[0359] The following describes the processing flow.

[0360] Step 1:

[0361] The server collects and analyzes traffic and weather information in real time, constantly monitoring various road and weather conditions. This updates the database related to the operation of mobile vehicles.

[0362] Step 2:

[0363] The terminal accepts input from the user, such as destination and departure time. Based on the user's requested conditions, the terminal sends a request to the server.

[0364] Step 3:

[0365] The device sends the user's voice or text to an emotion engine, which analyzes their emotional state. The engine identifies emotions such as stress, joy, and anxiety.

[0366] Step 4:

[0367] The server calculates the optimal route based on the travel conditions and emotional state it receives. Depending on the emotional state, it selects a more comfortable route or option and sends it to the terminal.

[0368] Step 5:

[0369] The user confirms the vehicle assignment on their terminal. Once the assignment is confirmed, the server adjusts the vehicle's schedule and sends the necessary instructions to the vehicle.

[0370] Step 6:

[0371] Once the mobile device begins operation, the server controls it in real time, making environmental adjustments (such as controlling lighting and music) in response to the user's emotional state.

[0372] Step 7:

[0373] Upon arrival at the destination, the terminal initiates the payment process. If the sentiment engine's results affect the price, the server may apply special pricing options.

[0374] Step 8:

[0375] The user completes the payment via the LINE app, and the entire process is finished. Payment information and travel history are stored in a database and used to improve future services.

[0376] (Example 2)

[0377] Next, we will describe Example 2. 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".

[0378] Modern transportation systems utilize traffic and weather information to select the optimal route for travelers, but they lack the flexibility to take into account the emotional state of users. Furthermore, there is a need to improve convenience by linking users' travel history with their immediate emotional state. Additionally, there is a lack of personalized service tailored to users' emotional states. Solving these challenges is essential.

[0379] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0380] In this invention, the server includes means for acquiring and analyzing traffic and weather information to generate an optimal route for a mobile object; means for analyzing the user's emotional state and adjusting the mobile object's environmental settings based on the user's emotions; and means for dynamically changing the optimal route based on the results of the user's emotional analysis. This makes it possible to provide an optimal travel experience that reflects the user's emotional state.

[0381] A "mobile entity" refers to a vehicle or device used to transport users or goods to a destination, and is controlled autonomously or manually.

[0382] The "optimal route" is the route selected to ensure that a moving object reaches its destination safely and efficiently, and is dynamically adjusted based on traffic information, weather information, and user requests.

[0383] "Traffic information" refers to data that affects travel, such as road conditions, congestion levels, and construction information.

[0384] "Weather information" refers to data on meteorological conditions that affect travel, such as weather, temperature, precipitation, and wind speed.

[0385] "Terminal devices" refer to electronic devices used by users to input information and interface with a system, and include smartphones and tablets.

[0386] "Emotional state" refers to the user's psychological condition and mood, and is identified through the analysis of voice and text data.

[0387] "Environmental settings" refer to conditions such as temperature, lighting, and sound inside the mobile vehicle, and are adjusted to improve user comfort.

[0388] "Dynamic modification" refers to the process of updating and optimizing pre-determined settings and conditions in real time.

[0389] "Emotional analysis results" refer to data obtained after identifying the user's emotional state, and are used for service provision and route selection.

[0390] This invention is an integrated mobility system for achieving efficient dispatching and delivery of mobile vehicles, and has the function of providing dynamic responses that take into account the emotional state of the user. In this embodiment of the system, the server, terminal, and user components communicate with each other to provide the optimal mobility service.

[0391] The server uses external data sources such as traffic information APIs and weather information APIs to acquire data in real time. This allows the server to calculate the most efficient route and provide instructions to the moving object. Furthermore, the server uses an emotion engine to analyze voice and text data transmitted from the terminal to determine the user's emotional state. The emotion engine utilizes natural language processing libraries and sentiment analysis APIs.

[0392] The terminal transmits destination and reservation information entered by the user to the server. The terminal is equipped with an interface that allows for both voice and text input, making it easy for users to access the system. Through this interface, the terminal collects user sentiment data and transmits it to the server.

[0393] Users can input their travel preferences through the terminal interface and communicate their emotional state to the system using voice or text. This allows for the provision of travel services optimized for each individual user.

[0394] As a concrete example, suppose a user verbally instructs their device to "arrive quickly and quietly." The device sends this information to the server, and based on the data collected in real time, the server can select the optimal route with less congestion. Furthermore, if the server determines that the user's emotional state is one of high stress levels, it will play relaxing music during the journey to improve the user's comfort.

[0395] As a concrete example of a prompt given to a generating AI model, one could input, "Please tell me how to suggest services that are appropriate when the user wants to relax." This prompt allows the system to adaptively adjust the services it provides.

[0396] This invention integrates these functions to realize advanced mobility services that take into account the user's emotions.

[0397] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0398] Step 1:

[0399] The device collects user input information.

[0400] When a user enters their destination or travel preferences into the device's interface, the device receives this information as voice or text data. The input information also includes the user's emotional state, which is then used to organize the necessary data for subsequent processing. For example, if a user says, "I want to get to work early," this information is converted into digital data through speech recognition and natural language processing.

[0401] Step 2:

[0402] The terminal sends data to the server.

[0403] The device sends the collected user destination information and sentiment data to the server using HTTPS. At this stage, the data is encrypted and sent to the server's API in a secure format. Specifically, the device sends "Destination: Workplace, Priority: Arrive quickly, Sentiment: Urgent" to the server.

[0404] Step 3:

[0405] The server calculates the optimal route.

[0406] The server uses traffic information APIs and weather information APIs based on the received data to calculate the optimal route. As an example of data processing, it calculates the estimated arrival time based on traffic information and extracts the optimal route. Specifically, the server decides to "select Route C, which is the shortest route to the destination and has less congestion."

[0407] Step 4:

[0408] The server adjusts the service based on the emotional state.

[0409] The server uses an emotion analysis engine to analyze the user's emotional state and issues commands to adjust the mobile device's environment settings based on that analysis. If the emotion indicates stress, the device will be set to play relaxing music. Specifically, the server issues commands such as "stress detection, route C selection, and play relaxation music."

[0410] Step 5:

[0411] The server sends the results to the terminal, and the terminal notifies the user.

[0412] The server sends the final route and service coordination information back to the terminal, which then notifies the user of that information. As a concrete example of output, the terminal might tell the user, "Using Route C, travel time is 15 minutes. Starting relaxation music."

[0413] Step 6:

[0414] The user boards the mobile vehicle and receives the provided service.

[0415] The user boards the vehicle following instructions from their terminal. During the journey, they enjoy a comfortable travel experience through environmental settings instructed by the server. For example, the user travels along a designated route and listens to relaxation music.

[0416] (Application Example 2)

[0417] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0418] To achieve efficient dispatching and delivery of mobile vehicles, route optimization that takes traffic and weather information into account is necessary. However, conventional systems cannot provide services that take into account the emotional state of users, resulting in a lack of customized services for individual users. Therefore, to improve user satisfaction, an advanced mobile vehicle control system incorporating emotion recognition is required.

[0419] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0420] In this invention, the server includes means for acquiring and analyzing traffic and weather information, means for communicating with a terminal device that accepts user input, and means for controlling and monitoring reserved mobile objects in real time. This enables route optimization and dynamic adjustment of environmental settings that take into account the user's emotional state.

[0421] A "mobile device" refers to a machine or vehicle whose role is to move people or objects from one place to another.

[0422] The "optimal route" refers to the path chosen to maximize the efficiency of travel and minimize time and fuel consumption.

[0423] "Traffic information" refers to data on road congestion, accidents, road closures, and other related information.

[0424] "Weather information" refers to data related to meteorological conditions, such as weather, temperature, and precipitation.

[0425] A "terminal device" refers to an electronic device used by a user to input information or communicate with a system.

[0426] "Communication methods" refer to the methods and technologies for sending and receiving data between different devices within a system.

[0427] "Emotional state" refers to the psychological state a user experiences, such as stress or relaxation.

[0428] "Route optimization" refers to the process of selecting and adjusting routes to improve the efficiency of travel, taking into account traffic conditions and the state of users.

[0429] "Environmental settings" refers to adjustments made to the music, air conditioning, lighting, and other elements within the vehicle to enhance user comfort.

[0430] The system implementing the present invention has an advanced control mechanism for achieving efficient and personalized dispatching and delivery of mobile vehicles.

[0431] The server uses traffic information APIs and weather information APIs to acquire traffic and weather conditions in real time, and analyzes this data using Python libraries such as NumPy and Pandas. This allows it to calculate the optimal route and help select a route for the moving object. Furthermore, it can use an emotion engine (e.g., Affectiva) to analyze voice data transmitted from the user's terminal device and identify the user's emotional state. Based on this identified emotional state, it automatically adjusts the environment settings during travel (music, lighting, air conditioning, etc.) to enhance the user's comfort.

[0432] The terminal device provides an interface for users to input destinations and other information. Information entered by the user via voice or text is transmitted to the server as emotional data referenced by the emotion engine. This allows the user's travel experience to be customized to their individual emotional state, thereby improving user satisfaction.

[0433] As a concrete example, if a user is caught in traffic and stress is detected, the system can quickly select the optimal alternative route. It can also provide a user-friendly travel experience by playing relaxing music and adjusting the in-car temperature appropriately.

[0434] In this way, the present invention takes mobility services a step further and provides added value through emotion recognition.

[0435] An example of a prompt is: "Explain how, when a user is wearing smart glasses, the AI ​​combines traffic congestion data with the user's stress level to optimize route selection."

[0436] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0437] Step 1:

[0438] The server retrieves data from traffic and weather information APIs. The input is real-time traffic and weather data, which is then analyzed using NumPy and Pandas to calculate the optimal travel route. The output is the calculated optimal route information.

[0439] Step 2:

[0440] The terminal receives destination and reservation information from the user in text or voice format. Input is the user's destination information, which is transmitted to the system via the user interface. Output is the reservation information sent to the system.

[0441] Step 3:

[0442] The server uses an emotion engine to analyze voice data transmitted from the terminal. The input is the user's voice data, and the analysis identifies the user's emotional state. The output is the identified emotional state.

[0443] Step 4:

[0444] The server optimizes the environment settings of a mobile object based on its emotional state. The input consists of the identified emotional state and route information based on traffic data, and the system generates data to adjust the environment settings. The output is the adjusted environment settings.

[0445] Step 5:

[0446] Users experience a customized environment for their mobile device. As a result, the user's travel experience adapts to their individual emotional state, leading to improved comfort.

[0447] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0448] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0449] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0450] [Third Embodiment]

[0451] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0452] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0453] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0454] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0455] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0456] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0457] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0458] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0459] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0460] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0461] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0462] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0463] This invention is a system that realizes an integrated mobility platform for providing efficient transportation services to users using artificial intelligence and autonomous driving technology. This system optimizes vehicle dispatch and delivery by optimizing routes based on traffic and weather information, and by analyzing users' travel patterns. The operation of the system is described below in natural language.

[0464] The server manages and analyzes the data.

[0465] The server collects traffic and weather data in real time and analyzes this data to select the most efficient route. Furthermore, it analyzes the user's past travel history to suggest a personalized route.

[0466] For example, if the server has a history of a specific user leaving for the office at 8:00 AM every Monday, it will calculate the optimal departure time and route based on weather and traffic conditions and notify the user in advance.

[0467] The device provides an interface with the user.

[0468] The terminal receives information such as destinations from users and manages reservations. Users can easily make travel reservations through an interface that operates within the LINE app. Based on information obtained from the server, the terminal displays travel suggestions and the next available reservation times.

[0469] User-friendly operation

[0470] Users can easily book travel by entering their departure and destination points through their device. The app's interactive interface allows users to arrange the most suitable transportation without complex operations.

[0471] Real-time control and payment completion

[0472] The server controls the mobile device in real time and operates while receiving environmental information using 5G communication. After the user completes their movement, the terminal quickly and easily completes the payment process using PayPay.

[0473] Through these processes, the present invention realizes efficient and user-friendly transportation services. Furthermore, it addresses the problem of labor shortages in logistics and delivery, and builds a system that is highly safe and convenient.

[0474] The following describes the processing flow.

[0475] Step 1:

[0476] The server collects traffic and weather information in real time. This allows for an accurate understanding of current road conditions and weather conditions, which helps in the efficient operation of mobile vehicles.

[0477] Step 2:

[0478] The server retrieves the user's past travel history from a database and analyzes their movement trends. Based on this information, it prepares to provide personalized services to the user.

[0479] Step 3:

[0480] The user enters their departure point, destination, and departure time through their device. The device receives this information and sends it to the server.

[0481] Step 4:

[0482] The server calculates the optimal route based on information received from the terminal. It selects the best route from multiple options, taking into account traffic conditions and user travel patterns.

[0483] Step 5:

[0484] The server checks the current location and status of the moving object and selects an available vehicle. Based on this information, the server creates a dispatch plan.

[0485] Step 6:

[0486] The server sends information about available vehicles and the optimal route to the terminal. The terminal displays this information to the user and prompts them to confirm the vehicle assignment.

[0487] Step 7:

[0488] The user confirms the ride request via their terminal. After confirmation, the terminal sets the payment method and verifies the pre-registered payment method.

[0489] Step 8:

[0490] Once the transfer is complete, the terminal receives a payment request from the server and executes the payment using the pre-configured payment method. This completes all processes related to the transfer.

[0491] (Example 1)

[0492] Next, we will describe Example 1. 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."

[0493] In modern urban environments, traffic congestion and unpredictable weather conditions make efficient travel difficult. Furthermore, there is a need to provide safe and convenient services that meet the diverse travel needs of users. Additionally, labor shortages pose challenges to achieving smooth transportation and logistics.

[0494] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0495] In this invention, the server includes means for acquiring and analyzing traffic condition information and environmental condition information, means for receiving user input and communicating with a terminal device for managing reservations for mobile devices, and communication means for controlling reserved mobile devices and monitoring them in real time. This enables optimized route selection for individual users and allows for the provision of efficient and safe mobility services.

[0496] "Traffic information" refers to data showing road congestion levels, travel times, and real-time traffic flow.

[0497] "Environmental condition information" refers to information that includes data on weather, temperature, precipitation, and other meteorological conditions.

[0498] "User" refers to an individual or group that wishes to receive mobility services using this system.

[0499] "Mobile devices" refer to devices including vehicles and delivery equipment that are operated autonomously or remotely.

[0500] "Terminal device" refers to electronic devices or interfaces that users use to input data and communicate with the system.

[0501] "Communication methods" refer to communication technologies and infrastructure used to send and receive information in real time.

[0502] A "processing device" refers to a device that handles information processing to analyze data and calculate the optimal path.

[0503] A "unified communication network" refers to a network infrastructure that can handle information centrally without using multiple communication protocols.

[0504] This invention is an integrated system that utilizes traffic and environmental information to optimize the routes of moving objects efficiently and provide mobility services to users. The main components of the system allow each function to operate as follows:

[0505] First, the server acquires and analyzes traffic and environmental information. Specifically, it collects real-time data using an API service and calculates the optimal route using an analysis engine. This analysis engine implements an AI algorithm using deep learning to calculate the optimized travel route.

[0506] Next, the terminal provides an electronic interface to receive user input. For example, via a smartphone app, users can enter their departure point, destination, and desired departure time. This terminal interacts with a server to present a plan suitable for the user. It also includes payment processing functionality, allowing users to make electronic payments after completing their journey.

[0507] Finally, the user books their desired journey via the terminal. The user easily enters information through an interactive interface and reviews the optimal route and travel plan provided by the server.

[0508] For example, the server can suggest an optimal departure time, different from the usual route, based on the weather and traffic conditions, using the past travel history of a specific user heading to the office on Monday mornings.

[0509] An example of an input prompt for a generating AI model is: "For a user who goes to the office every Monday, please suggest the optimal departure time and route, taking weather and traffic conditions into consideration."

[0510] The implementation of this system will enable the provision of innovative mobility services that combine safety and convenience, from individual users to logistics operations.

[0511] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0512] Step 1:

[0513] The server acquires traffic and environmental information. The server receives current traffic and weather information via traffic data APIs and weather data APIs. The latest traffic speed data, congestion information, temperature, and precipitation probability are provided as input from each API. The server uses this information to update a database that monitors environmental conditions in real time.

[0514] Step 2:

[0515] The server analyzes the acquired data and calculates the optimal travel route. The server inputs the collected traffic and weather data into an AI algorithm to generate the best route for the user. As part of data processing, a machine learning model is used to predict traffic, and the output generates optimal route information including current and predicted routes.

[0516] Step 3:

[0517] The terminal receives input from the user. The user enters their departure point, destination, and desired travel time into the terminal via a smartphone app. The input is directly from the user in text data format, and the app converts this data into a format and sends it to the server. After sending, the terminal waits to receive optimal route data from the server.

[0518] Step 4:

[0519] The server integrates user input with optimal travel route information and sends an optimized travel plan to the device. Input includes the user's destination and departure time information, as well as analyzed optimal route information. The server returns the integrated result to the device as JSON data.

[0520] Step 5:

[0521] The device displays information received from the server to the user. The device receives a response from the server and visualizes the suggested optimal route, departure time, and estimated arrival time on the app screen for the user. As output, the user receives a visually verifiable travel plan.

[0522] Step 6:

[0523] The user books their travel through their device. The user reviews the proposed travel plan and completes the booking by tapping the "Make Arrangement" button. Based on the user's input, the device sends the booking data to the server for approval within the system.

[0524] Step 7:

[0525] The server monitors and controls movement. The server acquires location data of the moving object in real time, and if any changes in the situation are anticipated, it recalculates the route and sends instructions to the terminal. The input is GPS information of the moving object, and the output is instructions based on that information.

[0526] Step 8:

[0527] The terminal completes the payment process. After the transfer is complete, the terminal prompts the user to confirm payment and processes the electronic payment. Payment information is sent to the terminal as input, and a payment completion notification is sent to the user as output.

[0528] (Application Example 1)

[0529] Next, we will explain Application Example 1. In the following explanation, 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."

[0530] In mobility services utilizing autonomous driving technology, there is a need to provide route guidance that constantly reflects optimal traffic and weather conditions, as well as a personalized travel experience that takes into account the user's past travel history. Furthermore, smooth payment processing after the completion of the journey is also a crucial challenge.

[0531] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0532] In this invention, the server includes means for acquiring and analyzing traffic and weather information; means for receiving user input and communicating with an information terminal for managing reservations for mobile vehicles; means for controlling and monitoring reserved mobile vehicles in real time; means for notifying users of recommended routes and departure times; means for processing payment information after the completion of travel; and means for updating routes as needed based on traffic and weather conditions. This enables a smart travel service that provides users with an efficient and personalized travel experience and allows for quick payment.

[0533] "Traffic information" refers to information on roads that affects the movement of vehicles, such as road congestion, accidents, and traffic jams.

[0534] "Weather information" refers to information about the natural environment that affects the operation of moving objects, such as weather, temperature, precipitation, and wind speed.

[0535] An "information terminal" refers to a device that receives user input and performs tasks such as outputting various types of information and managing reservations for mobile devices.

[0536] "Communication means" refers to the technical means for exchanging information between a server and an information terminal or mobile device. These means include network lines and protocols.

[0537] A "recommended route" refers to a path calculated based on traffic conditions and weather conditions to efficiently reach the destination.

[0538] "Payment information" refers to data and procedures related to paying for the use of mobility services.

[0539] "Real-time route updates" means dynamically recalculating and optimizing travel routes in response to changes in current traffic conditions and weather.

[0540] The system for realizing this invention involves running a program on a server that acquires and analyzes traffic and weather information in real time. The server analyzes this data and calculates the optimal route. The hardware used includes a server machine capable of high-speed computing and a communication network. The software implements data analysis algorithms and communication protocols. The server also analyzes the user's past travel history to provide personalized travel guidance.

[0541] Information terminals receive information such as destinations from users and, in cooperation with a server, make reservations for travel and suggest routes. Smartphones, which are portable communication devices, are primarily used. These terminals incorporate application software that facilitates interface design. The terminal displays the information received from the server and notifies the user of recommended travel routes and optimal departure times.

[0542] Users can book transportation through their terminals with simple operations. To enhance usability, an interactive interface is provided within the app. Furthermore, after the journey is complete, the terminal processes payment information, enabling quick and convenient payment. A digital payment platform is used as the payment method here.

[0543] For example, if a user plans to travel from a city to the suburbs over the weekend, the server will consider expected congestion and weather conditions, calculate the optimal route in advance, and notify the user. Even if sudden weather changes occur at the time of departure, the route will be adjusted to the optimal direction thanks to a real-time route update function. Furthermore, payment will be automatically completed upon completion of the trip, enhancing user convenience.

[0544] Example prompt: "Please provide instructions necessary for the user to travel efficiently to the city center using autonomous driving. Suggest the optimal route, taking into account time, weather, and traffic, and provide explanations that allow for changes during the journey."

[0545] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0546] Step 1:

[0547] The server acquires traffic and weather information in real time. It receives the latest road and weather data through various APIs as input and generates analyzable datasets as output. This prepares the data for use in the next step.

[0548] Step 2:

[0549] The server calculates the optimal route based on the acquired information. It uses an algorithm (e.g., Dijkstra's algorithm) to solve the shortest path problem by analyzing the dataset obtained in Step 1 as input. The output calculates the recommended route to the destination and the required departure time. This operation is designed to handle real-time information updates.

[0550] Step 3:

[0551] The server analyzes the user's past travel history. It references a database of past travel data as input and applies a pattern recognition algorithm. As output, it generates personalized travel suggestions that take into account the user's preferred routes and departure times.

[0552] Step 4:

[0553] The terminal accepts destination input from the user. It handles geographical information received through the user interface as input and generates a request for communication with the server as output. This operation is performed simply using an interactive interface.

[0554] Step 5:

[0555] The terminal notifies the user of the recommended route and departure time received from the server. It interprets the communication content from the server as input and converts it into a format that can be displayed on the screen as output. In this way, the user can receive optimal travel suggestions based on real-time traffic information.

[0556] Step 6:

[0557] The user makes a reservation for travel using their device. The user confirms the departure and destination based on recommended information as input, and confirms the reservation details as output. This process is completed with simple user operation.

[0558] Step 7:

[0559] The server recalculates the route if traffic or weather conditions change during travel. It uses the latest newly acquired information as input and sends the improved route information to the terminal as output. This achieves real-time optimization.

[0560] Step 8:

[0561] The terminal processes payment information after the move is complete and completes the payment using the user's account. It sends the amount spent and credit card information to the server as input and receives confirmation of transaction completion as output. This process is fast and secure through the payment platform.

[0562] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0563] This invention is an integrated mobility system for achieving efficient dispatch and delivery of mobile vehicles, and has the function of recognizing user emotions and dynamically changing its response. This system generates optimal routes based on traffic and weather information, and not only reserves and controls mobile vehicles, but also provides services while taking user emotions into consideration.

[0564] The server analyzes the data.

[0565] The server analyzes traffic information, weather information, and the user's travel history. Based on this analysis, it plans the optimal route for the mobile device to efficiently reach its destination. The server also uses an emotion engine to analyze voice and text data received from the terminal device to identify the user's emotional state.

[0566] For example, if the server detects stress from the user's voice, it can prioritize a more comfortable route that shortens the travel time to the destination when selecting a route.

[0567] The terminal provides an interface with the user.

[0568] The terminal receives input from the user and sends travel reservations and sentiment data to the server. Through an interactive interface, the terminal allows users to easily set destinations and collects data required by the sentiment engine from the user's voice and text.

[0569] The user operates the system

[0570] Users input their travel preferences through the terminal interface, while their emotional state is communicated to the system via voice or text. This allows for the provision of customized services tailored to the user's emotional state.

[0571] Real-time control and service coordination

[0572] The server has the ability to automatically adjust the in-vehicle environment settings (e.g., music selection and air conditioning adjustment) according to the user's emotional state. This allows the emotion engine to optimize the environment during travel, improving the user's comfort.

[0573] Through these processes, the present invention improves the accuracy and satisfaction of services for individual users by combining emotion recognition technology with conventional mobility services.

[0574] The following describes the processing flow.

[0575] Step 1:

[0576] The server collects and analyzes traffic and weather information in real time, constantly monitoring various road and weather conditions. This updates the database related to the operation of mobile vehicles.

[0577] Step 2:

[0578] The terminal accepts input from the user, such as destination and departure time. Based on the user's requested conditions, the terminal sends a request to the server.

[0579] Step 3:

[0580] The device sends the user's voice or text to an emotion engine, which analyzes their emotional state. The engine identifies emotions such as stress, joy, and anxiety.

[0581] Step 4:

[0582] The server calculates the optimal route based on the travel conditions and emotional state it receives. Depending on the emotional state, it selects a more comfortable route or option and sends it to the terminal.

[0583] Step 5:

[0584] The user confirms the vehicle assignment on their terminal. Once the assignment is confirmed, the server adjusts the vehicle's schedule and sends the necessary instructions to the vehicle.

[0585] Step 6:

[0586] Once the mobile device begins operation, the server controls it in real time, making environmental adjustments (such as controlling lighting and music) in response to the user's emotional state.

[0587] Step 7:

[0588] Upon arrival at the destination, the terminal initiates the payment process. If the sentiment engine's results affect the price, the server may apply special pricing options.

[0589] Step 8:

[0590] The user completes the payment via the LINE app, and the entire process is finished. Payment information and travel history are stored in a database and used to improve future services.

[0591] (Example 2)

[0592] Next, we will describe Example 2. 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."

[0593] Modern transportation systems utilize traffic and weather information to select the optimal route for travelers, but they lack the flexibility to take into account the emotional state of users. Furthermore, there is a need to improve convenience by linking users' travel history with their immediate emotional state. Additionally, there is a lack of personalized service tailored to users' emotional states. Solving these challenges is essential.

[0594] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0595] In this invention, the server includes means for acquiring and analyzing traffic and weather information to generate an optimal route for a mobile object; means for analyzing the user's emotional state and adjusting the mobile object's environmental settings based on the user's emotions; and means for dynamically changing the optimal route based on the results of the user's emotional analysis. This makes it possible to provide an optimal travel experience that reflects the user's emotional state.

[0596] A "mobile entity" refers to a vehicle or device used to transport users or goods to a destination, and is controlled autonomously or manually.

[0597] The "optimal route" is the route selected to ensure that a moving object reaches its destination safely and efficiently, and is dynamically adjusted based on traffic information, weather information, and user requests.

[0598] "Traffic information" refers to data that affects travel, such as road conditions, congestion levels, and construction information.

[0599] "Weather information" refers to data on meteorological conditions that affect travel, such as weather, temperature, precipitation, and wind speed.

[0600] "Terminal devices" refer to electronic devices used by users to input information and interface with a system, and include smartphones and tablets.

[0601] "Emotional state" refers to the user's psychological condition and mood, and is identified through the analysis of voice and text data.

[0602] "Environmental settings" refer to conditions such as temperature, lighting, and sound inside the mobile vehicle, and are adjusted to improve user comfort.

[0603] "Dynamic modification" refers to the process of updating and optimizing pre-determined settings and conditions in real time.

[0604] "Emotional analysis results" refer to data obtained after identifying the user's emotional state, and are used for service provision and route selection.

[0605] This invention is an integrated mobility system for achieving efficient dispatching and delivery of mobile vehicles, and has the function of providing dynamic responses that take into account the emotional state of the user. In this embodiment of the system, the server, terminal, and user components communicate with each other to provide the optimal mobility service.

[0606] The server uses external data sources such as traffic information APIs and weather information APIs to acquire data in real time. This allows the server to calculate the most efficient route and provide instructions to the moving object. Furthermore, the server uses an emotion engine to analyze voice and text data transmitted from the terminal to determine the user's emotional state. The emotion engine utilizes natural language processing libraries and sentiment analysis APIs.

[0607] The terminal transmits destination and reservation information entered by the user to the server. The terminal is equipped with an interface that allows for both voice and text input, making it easy for users to access the system. Through this interface, the terminal collects user sentiment data and transmits it to the server.

[0608] Users can input their travel preferences through the terminal interface and communicate their emotional state to the system using voice or text. This allows for the provision of travel services optimized for each individual user.

[0609] As a concrete example, suppose a user verbally instructs their device to "arrive quickly and quietly." The device sends this information to the server, and based on the data collected in real time, the server can select the optimal route with less congestion. Furthermore, if the server determines that the user's emotional state is one of high stress levels, it will play relaxing music during the journey to improve the user's comfort.

[0610] As a concrete example of a prompt given to a generating AI model, one could input, "Please tell me how to suggest services that are appropriate when the user wants to relax." This prompt allows the system to adaptively adjust the services it provides.

[0611] This invention integrates these functions to realize advanced mobility services that take into account the user's emotions.

[0612] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0613] Step 1:

[0614] The device collects user input information.

[0615] When a user enters their destination or travel preferences into the device's interface, the device receives this information as voice or text data. The input information also includes the user's emotional state, which is then used to organize the necessary data for subsequent processing. For example, if a user says, "I want to get to work early," this information is converted into digital data through speech recognition and natural language processing.

[0616] Step 2:

[0617] The terminal sends data to the server.

[0618] The device sends the collected user destination information and sentiment data to the server using HTTPS. At this stage, the data is encrypted and sent to the server's API in a secure format. Specifically, the device sends "Destination: Workplace, Priority: Arrive quickly, Sentiment: Urgent" to the server.

[0619] Step 3:

[0620] The server calculates the optimal route.

[0621] The server uses traffic information APIs and weather information APIs based on the received data to calculate the optimal route. As an example of data processing, it calculates the estimated arrival time based on traffic information and extracts the optimal route. Specifically, the server decides to "select Route C, which is the shortest route to the destination and has less congestion."

[0622] Step 4:

[0623] The server adjusts the service based on the emotional state.

[0624] The server uses an emotion analysis engine to analyze the user's emotional state and issues commands to adjust the mobile device's environment settings based on that analysis. If the emotion indicates stress, the device will be set to play relaxing music. Specifically, the server issues commands such as "stress detection, route C selection, and play relaxation music."

[0625] Step 5:

[0626] The server sends the results to the terminal, and the terminal notifies the user.

[0627] The server sends the final route and service coordination information back to the terminal, which then notifies the user of that information. As a concrete example of output, the terminal might tell the user, "Using Route C, travel time is 15 minutes. Starting relaxation music."

[0628] Step 6:

[0629] The user boards the mobile vehicle and receives the provided service.

[0630] The user boards the vehicle following instructions from their terminal. During the journey, they enjoy a comfortable travel experience through environmental settings instructed by the server. For example, the user travels along a designated route and listens to relaxation music.

[0631] (Application Example 2)

[0632] Next, we will explain application example 2. In the following explanation, 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."

[0633] To achieve efficient dispatching and delivery of mobile vehicles, route optimization that takes traffic and weather information into account is necessary. However, conventional systems cannot provide services that take into account the emotional state of users, resulting in a lack of customized services for individual users. Therefore, to improve user satisfaction, an advanced mobile vehicle control system incorporating emotion recognition is required.

[0634] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0635] In this invention, the server includes means for acquiring and analyzing traffic and weather information, means for communicating with a terminal device that accepts user input, and means for controlling and monitoring reserved mobile objects in real time. This enables route optimization and dynamic adjustment of environmental settings that take into account the user's emotional state.

[0636] A "mobile device" refers to a machine or vehicle whose role is to move people or objects from one place to another.

[0637] The "optimal route" refers to the path chosen to maximize the efficiency of travel and minimize time and fuel consumption.

[0638] "Traffic information" refers to data on road congestion, accidents, road closures, and other related information.

[0639] "Weather information" refers to data related to meteorological conditions, such as weather, temperature, and precipitation.

[0640] A "terminal device" refers to an electronic device used by a user to input information or communicate with a system.

[0641] "Communication methods" refer to the methods and technologies for sending and receiving data between different devices within a system.

[0642] "Emotional state" refers to the psychological state a user experiences, such as stress or relaxation.

[0643] "Route optimization" refers to the process of selecting and adjusting routes to improve the efficiency of travel, taking into account traffic conditions and the state of users.

[0644] "Environmental settings" refers to adjustments made to the music, air conditioning, lighting, and other elements within the vehicle to enhance user comfort.

[0645] The system implementing the present invention has an advanced control mechanism for achieving efficient and personalized dispatching and delivery of mobile vehicles.

[0646] The server uses traffic information APIs and weather information APIs to acquire traffic and weather conditions in real time, and analyzes this data using Python libraries such as NumPy and Pandas. This allows it to calculate the optimal route and help select a route for the moving object. Furthermore, it can use an emotion engine (e.g., Affectiva) to analyze voice data transmitted from the user's terminal device and identify the user's emotional state. Based on this identified emotional state, it automatically adjusts the environment settings during travel (music, lighting, air conditioning, etc.) to enhance the user's comfort.

[0647] The terminal device provides an interface for users to input destinations and other information. Information entered by the user via voice or text is transmitted to the server as emotional data referenced by the emotion engine. This allows the user's travel experience to be customized to their individual emotional state, thereby improving user satisfaction.

[0648] As a concrete example, if a user is caught in traffic and stress is detected, the system can quickly select the optimal alternative route. It can also provide a user-friendly travel experience by playing relaxing music and adjusting the in-car temperature appropriately.

[0649] In this way, the present invention takes mobility services a step further and provides added value through emotion recognition.

[0650] An example of a prompt is: "Explain how, when a user is wearing smart glasses, the AI ​​combines traffic congestion data with the user's stress level to optimize route selection."

[0651] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0652] Step 1:

[0653] The server retrieves data from traffic and weather information APIs. The input is real-time traffic and weather data, which is then analyzed using NumPy and Pandas to calculate the optimal travel route. The output is the calculated optimal route information.

[0654] Step 2:

[0655] The terminal receives destination and reservation information from the user in text or voice format. Input is the user's destination information, which is transmitted to the system via the user interface. Output is the reservation information sent to the system.

[0656] Step 3:

[0657] The server uses an emotion engine to analyze voice data transmitted from the terminal. The input is the user's voice data, and the analysis identifies the user's emotional state. The output is the identified emotional state.

[0658] Step 4:

[0659] The server optimizes the environment settings of a mobile object based on its emotional state. The input consists of the identified emotional state and route information based on traffic data, and the system generates data to adjust the environment settings. The output is the adjusted environment settings.

[0660] Step 5:

[0661] Users experience a customized environment for their mobile device. As a result, the user's travel experience adapts to their individual emotional state, leading to improved comfort.

[0662] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0663] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0664] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0665] [Fourth Embodiment]

[0666] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0667] As shown in Figure 7, the 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.

[0668] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0669] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0670] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0671] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0672] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0673] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0674] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0675] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0676] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0677] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0678] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0679] This invention is a system that realizes an integrated mobility platform for providing efficient transportation services to users using artificial intelligence and autonomous driving technology. This system optimizes vehicle dispatch and delivery by optimizing routes based on traffic and weather information, and by analyzing users' travel patterns. The operation of the system is described below in natural language.

[0680] The server manages and analyzes the data.

[0681] The server collects traffic and weather data in real time and analyzes this data to select the most efficient route. Furthermore, it analyzes the user's past travel history to suggest a personalized route.

[0682] For example, if the server has a history of a specific user leaving for the office at 8:00 AM every Monday, it will calculate the optimal departure time and route based on weather and traffic conditions and notify the user in advance.

[0683] The device provides an interface with the user.

[0684] The terminal receives information such as destinations from users and manages reservations. Users can easily make travel reservations through an interface that operates within the LINE app. Based on information obtained from the server, the terminal displays travel suggestions and the next available reservation times.

[0685] User-friendly operation

[0686] Users can easily book travel by entering their departure and destination points through their device. The app's interactive interface allows users to arrange the most suitable transportation without complex operations.

[0687] Real-time control and payment completion

[0688] The server controls the mobile device in real time and operates while receiving environmental information using 5G communication. After the user completes their movement, the terminal quickly and easily completes the payment process using PayPay.

[0689] Through these processes, the present invention realizes efficient and user-friendly transportation services. Furthermore, it addresses the problem of labor shortages in logistics and delivery, and builds a system that is highly safe and convenient.

[0690] The following describes the processing flow.

[0691] Step 1:

[0692] The server collects traffic and weather information in real time. This allows for an accurate understanding of current road conditions and weather conditions, which helps in the efficient operation of mobile vehicles.

[0693] Step 2:

[0694] The server retrieves the user's past travel history from a database and analyzes their movement trends. Based on this information, it prepares to provide personalized services to the user.

[0695] Step 3:

[0696] The user enters their departure point, destination, and departure time through their device. The device receives this information and sends it to the server.

[0697] Step 4:

[0698] The server calculates the optimal route based on information received from the terminal. It selects the best route from multiple options, taking into account traffic conditions and user travel patterns.

[0699] Step 5:

[0700] The server checks the current location and status of the moving object and selects an available vehicle. Based on this information, the server creates a dispatch plan.

[0701] Step 6:

[0702] The server sends information about available vehicles and the optimal route to the terminal. The terminal displays this information to the user and prompts them to confirm the vehicle assignment.

[0703] Step 7:

[0704] The user confirms the ride request via their terminal. After confirmation, the terminal sets the payment method and verifies the pre-registered payment method.

[0705] Step 8:

[0706] Once the transfer is complete, the terminal receives a payment request from the server and executes the payment using the pre-configured payment method. This completes all processes related to the transfer.

[0707] (Example 1)

[0708] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0709] In modern urban environments, traffic congestion and unpredictable weather conditions make efficient travel difficult. Furthermore, there is a need to provide safe and convenient services that meet the diverse travel needs of users. Additionally, labor shortages pose challenges to achieving smooth transportation and logistics.

[0710] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0711] In this invention, the server includes means for acquiring and analyzing traffic condition information and environmental condition information, means for receiving user input and communicating with a terminal device for managing reservations for mobile devices, and communication means for controlling reserved mobile devices and monitoring them in real time. This enables optimized route selection for individual users and allows for the provision of efficient and safe mobility services.

[0712] "Traffic information" refers to data showing road congestion levels, travel times, and real-time traffic flow.

[0713] "Environmental condition information" refers to information that includes data on weather, temperature, precipitation, and other meteorological conditions.

[0714] "User" refers to an individual or group that wishes to receive mobility services using this system.

[0715] "Mobile devices" refer to devices including vehicles and delivery equipment that are operated autonomously or remotely.

[0716] "Terminal device" refers to electronic devices or interfaces that users use to input data and communicate with the system.

[0717] "Communication methods" refer to communication technologies and infrastructure used to send and receive information in real time.

[0718] A "processing device" refers to a device that handles information processing to analyze data and calculate the optimal path.

[0719] A "unified communication network" refers to a network infrastructure that can handle information centrally without using multiple communication protocols.

[0720] This invention is an integrated system that utilizes traffic and environmental information to optimize the routes of moving objects efficiently and provide mobility services to users. The main components of the system allow each function to operate as follows:

[0721] First, the server acquires and analyzes traffic and environmental information. Specifically, it collects real-time data using an API service and calculates the optimal route using an analysis engine. This analysis engine implements an AI algorithm using deep learning to calculate the optimized travel route.

[0722] Next, the terminal provides an electronic interface to receive user input. For example, via a smartphone app, users can enter their departure point, destination, and desired departure time. This terminal interacts with a server to present a plan suitable for the user. It also includes payment processing functionality, allowing users to make electronic payments after completing their journey.

[0723] Finally, the user books their desired journey via the terminal. The user easily enters information through an interactive interface and reviews the optimal route and travel plan provided by the server.

[0724] For example, the server can suggest an optimal departure time, different from the usual route, based on the weather and traffic conditions, using the past travel history of a specific user heading to the office on Monday mornings.

[0725] An example of an input prompt for a generating AI model is: "For a user who goes to the office every Monday, please suggest the optimal departure time and route, taking weather and traffic conditions into consideration."

[0726] The implementation of this system will enable the provision of innovative mobility services that combine safety and convenience, from individual users to logistics operations.

[0727] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0728] Step 1:

[0729] The server acquires traffic and environmental information. The server receives current traffic and weather information via traffic data APIs and weather data APIs. The latest traffic speed data, congestion information, temperature, and precipitation probability are provided as input from each API. The server uses this information to update a database that monitors environmental conditions in real time.

[0730] Step 2:

[0731] The server analyzes the acquired data and calculates the optimal travel route. The server inputs the collected traffic and weather data into an AI algorithm to generate the best route for the user. As part of data processing, a machine learning model is used to predict traffic, and the output generates optimal route information including current and predicted routes.

[0732] Step 3:

[0733] The terminal receives input from the user. The user enters their departure point, destination, and desired travel time into the terminal via a smartphone app. The input is directly from the user in text data format, and the app converts this data into a format and sends it to the server. After sending, the terminal waits to receive optimal route data from the server.

[0734] Step 4:

[0735] The server integrates user input with optimal travel route information and sends an optimized travel plan to the device. Input includes the user's destination and departure time information, as well as analyzed optimal route information. The server returns the integrated result to the device as JSON data.

[0736] Step 5:

[0737] The device displays information received from the server to the user. The device receives a response from the server and visualizes the suggested optimal route, departure time, and estimated arrival time on the app screen for the user. As output, the user receives a visually verifiable travel plan.

[0738] Step 6:

[0739] The user books their travel through their device. The user reviews the proposed travel plan and completes the booking by tapping the "Make Arrangement" button. Based on the user's input, the device sends the booking data to the server for approval within the system.

[0740] Step 7:

[0741] The server monitors and controls movement. The server acquires location data of the moving object in real time, and if any changes in the situation are anticipated, it recalculates the route and sends instructions to the terminal. The input is GPS information of the moving object, and the output is instructions based on that information.

[0742] Step 8:

[0743] The terminal completes the payment process. After the transfer is complete, the terminal prompts the user to confirm payment and processes the electronic payment. Payment information is sent to the terminal as input, and a payment completion notification is sent to the user as output.

[0744] (Application Example 1)

[0745] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0746] In mobility services utilizing autonomous driving technology, there is a need to provide route guidance that constantly reflects optimal traffic and weather conditions, as well as a personalized travel experience that takes into account the user's past travel history. Furthermore, smooth payment processing after the completion of the journey is also a crucial challenge.

[0747] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0748] In this invention, the server includes means for acquiring and analyzing traffic and weather information; means for receiving user input and communicating with an information terminal for managing reservations for mobile vehicles; means for controlling and monitoring reserved mobile vehicles in real time; means for notifying users of recommended routes and departure times; means for processing payment information after the completion of travel; and means for updating routes as needed based on traffic and weather conditions. This enables a smart travel service that provides users with an efficient and personalized travel experience and allows for quick payment.

[0749] "Traffic information" refers to information on roads that affects the movement of vehicles, such as road congestion, accidents, and traffic jams.

[0750] "Weather information" refers to information about the natural environment that affects the operation of moving objects, such as weather, temperature, precipitation, and wind speed.

[0751] An "information terminal" refers to a device that receives user input and performs tasks such as outputting various types of information and managing reservations for mobile devices.

[0752] "Communication means" refers to the technical means for exchanging information between a server and an information terminal or mobile device. These means include network lines and protocols.

[0753] A "recommended route" refers to a path calculated based on traffic conditions and weather conditions to efficiently reach the destination.

[0754] "Payment information" refers to data and procedures related to paying for the use of mobility services.

[0755] "Real-time route updates" means dynamically recalculating and optimizing travel routes in response to changes in current traffic conditions and weather.

[0756] The system for realizing this invention involves running a program on a server that acquires and analyzes traffic and weather information in real time. The server analyzes this data and calculates the optimal route. The hardware used includes a server machine capable of high-speed computing and a communication network. The software implements data analysis algorithms and communication protocols. The server also analyzes the user's past travel history to provide personalized travel guidance.

[0757] Information terminals receive information such as destinations from users and, in cooperation with a server, make reservations for travel and suggest routes. Smartphones, which are portable communication devices, are primarily used. These terminals incorporate application software that facilitates interface design. The terminal displays the information received from the server and notifies the user of recommended travel routes and optimal departure times.

[0758] Users can book transportation through their terminals with simple operations. To enhance usability, an interactive interface is provided within the app. Furthermore, after the journey is complete, the terminal processes payment information, enabling quick and convenient payment. A digital payment platform is used as the payment method here.

[0759] For example, if a user plans to travel from a city to the suburbs over the weekend, the server will consider expected congestion and weather conditions, calculate the optimal route in advance, and notify the user. Even if sudden weather changes occur at the time of departure, the route will be adjusted to the optimal direction thanks to a real-time route update function. Furthermore, payment will be automatically completed upon completion of the trip, enhancing user convenience.

[0760] Example prompt: "Please provide instructions necessary for the user to travel efficiently to the city center using autonomous driving. Suggest the optimal route, taking into account time, weather, and traffic, and provide explanations that allow for changes during the journey."

[0761] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0762] Step 1:

[0763] The server acquires traffic and weather information in real time. It receives the latest road and weather data through various APIs as input and generates analyzable datasets as output. This prepares the data for use in the next step.

[0764] Step 2:

[0765] The server calculates the optimal route based on the acquired information. It uses an algorithm (e.g., Dijkstra's algorithm) to solve the shortest path problem by analyzing the dataset obtained in Step 1 as input. The output calculates the recommended route to the destination and the required departure time. This operation is designed to handle real-time information updates.

[0766] Step 3:

[0767] The server analyzes the user's past travel history. It references a database of past travel data as input and applies a pattern recognition algorithm. As output, it generates personalized travel suggestions that take into account the user's preferred routes and departure times.

[0768] Step 4:

[0769] The terminal accepts destination input from the user. It handles geographical information received through the user interface as input and generates a request for communication with the server as output. This operation is performed simply using an interactive interface.

[0770] Step 5:

[0771] The terminal notifies the user of the recommended route and departure time received from the server. It interprets the communication content from the server as input and converts it into a format that can be displayed on the screen as output. In this way, the user can receive optimal travel suggestions based on real-time traffic information.

[0772] Step 6:

[0773] The user makes a reservation for travel using their device. The user confirms the departure and destination based on recommended information as input, and confirms the reservation details as output. This process is completed with simple user operation.

[0774] Step 7:

[0775] The server recalculates the route if traffic or weather conditions change during travel. It uses the latest newly acquired information as input and sends the improved route information to the terminal as output. This achieves real-time optimization.

[0776] Step 8:

[0777] The terminal processes payment information after the move is complete and completes the payment using the user's account. It sends the amount spent and credit card information to the server as input and receives confirmation of transaction completion as output. This process is fast and secure through the payment platform.

[0778] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0779] This invention is an integrated mobility system for achieving efficient dispatch and delivery of mobile vehicles, and has the function of recognizing user emotions and dynamically changing its response. This system generates optimal routes based on traffic and weather information, and not only reserves and controls mobile vehicles, but also provides services while taking user emotions into consideration.

[0780] The server analyzes the data.

[0781] The server analyzes traffic information, weather information, and the user's travel history. Based on this analysis, it plans the optimal route for the mobile device to efficiently reach its destination. The server also uses an emotion engine to analyze voice and text data received from the terminal device to identify the user's emotional state.

[0782] For example, if the server detects stress from the user's voice, it can prioritize a more comfortable route that shortens the travel time to the destination when selecting a route.

[0783] The terminal provides an interface with the user.

[0784] The terminal receives input from the user and sends travel reservations and sentiment data to the server. Through an interactive interface, the terminal allows users to easily set destinations and collects data required by the sentiment engine from the user's voice and text.

[0785] The user operates the system

[0786] Users input their travel preferences through the terminal interface, while their emotional state is communicated to the system via voice or text. This allows for the provision of customized services tailored to the user's emotional state.

[0787] Real-time control and service coordination

[0788] The server has the ability to automatically adjust the in-vehicle environment settings (e.g., music selection and air conditioning adjustment) according to the user's emotional state. This allows the emotion engine to optimize the environment during travel, improving the user's comfort.

[0789] Through these processes, the present invention improves the accuracy and satisfaction of services for individual users by combining emotion recognition technology with conventional mobility services.

[0790] The following describes the processing flow.

[0791] Step 1:

[0792] The server collects and analyzes traffic and weather information in real time, constantly monitoring various road and weather conditions. This updates the database related to the operation of mobile vehicles.

[0793] Step 2:

[0794] The terminal accepts input from the user, such as destination and departure time. Based on the user's requested conditions, the terminal sends a request to the server.

[0795] Step 3:

[0796] The device sends the user's voice or text to an emotion engine, which analyzes their emotional state. The engine identifies emotions such as stress, joy, and anxiety.

[0797] Step 4:

[0798] The server calculates the optimal route based on the travel conditions and emotional state it receives. Depending on the emotional state, it selects a more comfortable route or option and sends it to the terminal.

[0799] Step 5:

[0800] The user confirms the vehicle assignment on their terminal. Once the assignment is confirmed, the server adjusts the vehicle's schedule and sends the necessary instructions to the vehicle.

[0801] Step 6:

[0802] Once the mobile device begins operation, the server controls it in real time, making environmental adjustments (such as controlling lighting and music) in response to the user's emotional state.

[0803] Step 7:

[0804] Upon arrival at the destination, the terminal initiates the payment process. If the sentiment engine's results affect the price, the server may apply special pricing options.

[0805] Step 8:

[0806] The user completes the payment via the LINE app, and the entire process is finished. Payment information and travel history are stored in a database and used to improve future services.

[0807] (Example 2)

[0808] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0809] Modern transportation systems utilize traffic and weather information to select the optimal route for travelers, but they lack the flexibility to take into account the emotional state of users. Furthermore, there is a need to improve convenience by linking users' travel history with their immediate emotional state. Additionally, there is a lack of personalized service tailored to users' emotional states. Solving these challenges is essential.

[0810] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0811] In this invention, the server includes means for acquiring and analyzing traffic and weather information to generate an optimal route for a mobile object; means for analyzing the user's emotional state and adjusting the mobile object's environmental settings based on the user's emotions; and means for dynamically changing the optimal route based on the results of the user's emotional analysis. This makes it possible to provide an optimal travel experience that reflects the user's emotional state.

[0812] A "mobile entity" refers to a vehicle or device used to transport users or goods to a destination, and is controlled autonomously or manually.

[0813] The "optimal route" is the route selected to ensure that a moving object reaches its destination safely and efficiently, and is dynamically adjusted based on traffic information, weather information, and user requests.

[0814] "Traffic information" refers to data that affects travel, such as road conditions, congestion levels, and construction information.

[0815] "Weather information" refers to data on meteorological conditions that affect travel, such as weather, temperature, precipitation, and wind speed.

[0816] "Terminal devices" refer to electronic devices used by users to input information and interface with a system, and include smartphones and tablets.

[0817] "Emotional state" refers to the user's psychological condition and mood, and is identified through the analysis of voice and text data.

[0818] "Environmental settings" refer to conditions such as temperature, lighting, and sound inside the mobile vehicle, and are adjusted to improve user comfort.

[0819] "Dynamic modification" refers to the process of updating and optimizing pre-determined settings and conditions in real time.

[0820] "Emotional analysis results" refer to data obtained after identifying the user's emotional state, and are used for service provision and route selection.

[0821] This invention is an integrated mobility system for achieving efficient dispatching and delivery of mobile vehicles, and has the function of providing dynamic responses that take into account the emotional state of the user. In this embodiment of the system, the server, terminal, and user components communicate with each other to provide the optimal mobility service.

[0822] The server uses external data sources such as traffic information APIs and weather information APIs to acquire data in real time. This allows the server to calculate the most efficient route and provide instructions to the moving object. Furthermore, the server uses an emotion engine to analyze voice and text data transmitted from the terminal to determine the user's emotional state. The emotion engine utilizes natural language processing libraries and sentiment analysis APIs.

[0823] The terminal transmits destination and reservation information entered by the user to the server. The terminal is equipped with an interface that allows for both voice and text input, making it easy for users to access the system. Through this interface, the terminal collects user sentiment data and transmits it to the server.

[0824] Users can input their travel preferences through the terminal interface and communicate their emotional state to the system using voice or text. This allows for the provision of travel services optimized for each individual user.

[0825] As a concrete example, suppose a user verbally instructs their device to "arrive quickly and quietly." The device sends this information to the server, and based on the data collected in real time, the server can select the optimal route with less congestion. Furthermore, if the server determines that the user's emotional state is one of high stress levels, it will play relaxing music during the journey to improve the user's comfort.

[0826] As a concrete example of a prompt given to a generating AI model, one could input, "Please tell me how to suggest services that are appropriate when the user wants to relax." This prompt allows the system to adaptively adjust the services it provides.

[0827] This invention integrates these functions to realize advanced mobility services that take into account the user's emotions.

[0828] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0829] Step 1:

[0830] The device collects user input information.

[0831] When a user enters their destination or travel preferences into the device's interface, the device receives this information as voice or text data. The input information also includes the user's emotional state, which is then used to organize the necessary data for subsequent processing. For example, if a user says, "I want to get to work early," this information is converted into digital data through speech recognition and natural language processing.

[0832] Step 2:

[0833] The terminal sends data to the server.

[0834] The device sends the collected user destination information and sentiment data to the server using HTTPS. At this stage, the data is encrypted and sent to the server's API in a secure format. Specifically, the device sends "Destination: Workplace, Priority: Arrive quickly, Sentiment: Urgent" to the server.

[0835] Step 3:

[0836] The server calculates the optimal route.

[0837] The server uses traffic information APIs and weather information APIs based on the received data to calculate the optimal route. As an example of data processing, it calculates the estimated arrival time based on traffic information and extracts the optimal route. Specifically, the server decides to "select Route C, which is the shortest route to the destination and has less congestion."

[0838] Step 4:

[0839] The server adjusts the service based on the emotional state.

[0840] The server uses an emotion analysis engine to analyze the user's emotional state and issues commands to adjust the mobile device's environment settings based on that analysis. If the emotion indicates stress, the device will be set to play relaxing music. Specifically, the server issues commands such as "stress detection, route C selection, and play relaxation music."

[0841] Step 5:

[0842] The server sends the results to the terminal, and the terminal notifies the user.

[0843] The server sends the final route and service coordination information back to the terminal, which then notifies the user of that information. As a concrete example of output, the terminal might tell the user, "Using Route C, travel time is 15 minutes. Starting relaxation music."

[0844] Step 6:

[0845] The user boards the mobile vehicle and receives the provided service.

[0846] The user boards the vehicle following instructions from their terminal. During the journey, they enjoy a comfortable travel experience through environmental settings instructed by the server. For example, the user travels along a designated route and listens to relaxation music.

[0847] (Application Example 2)

[0848] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0849] To achieve efficient dispatching and delivery of mobile vehicles, route optimization that takes traffic and weather information into account is necessary. However, conventional systems cannot provide services that take into account the emotional state of users, resulting in a lack of customized services for individual users. Therefore, to improve user satisfaction, an advanced mobile vehicle control system incorporating emotion recognition is required.

[0850] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0851] In this invention, the server includes means for acquiring and analyzing traffic and weather information, means for communicating with a terminal device that accepts user input, and means for controlling and monitoring reserved mobile objects in real time. This enables route optimization and dynamic adjustment of environmental settings that take into account the user's emotional state.

[0852] A "mobile device" refers to a machine or vehicle whose role is to move people or objects from one place to another.

[0853] The "optimal route" refers to the path chosen to maximize the efficiency of travel and minimize time and fuel consumption.

[0854] "Traffic information" refers to data on road congestion, accidents, road closures, and other related information.

[0855] "Weather information" refers to data related to meteorological conditions, such as weather, temperature, and precipitation.

[0856] A "terminal device" refers to an electronic device used by a user to input information or communicate with a system.

[0857] "Communication methods" refer to the methods and technologies for sending and receiving data between different devices within a system.

[0858] "Emotional state" refers to the psychological state a user experiences, such as stress or relaxation.

[0859] "Route optimization" refers to the process of selecting and adjusting routes to improve the efficiency of travel, taking into account traffic conditions and the state of users.

[0860] "Environmental settings" refers to adjustments made to the music, air conditioning, lighting, and other elements within the vehicle to enhance user comfort.

[0861] The system implementing the present invention has an advanced control mechanism for achieving efficient and personalized dispatching and delivery of mobile vehicles.

[0862] The server uses traffic information APIs and weather information APIs to acquire traffic and weather conditions in real time, and analyzes this data using Python libraries such as NumPy and Pandas. This allows it to calculate the optimal route and help select a route for the moving object. Furthermore, it can use an emotion engine (e.g., Affectiva) to analyze voice data transmitted from the user's terminal device and identify the user's emotional state. Based on this identified emotional state, it automatically adjusts the environment settings during travel (music, lighting, air conditioning, etc.) to enhance the user's comfort.

[0863] The terminal device provides an interface for users to input destinations and other information. Information entered by the user via voice or text is transmitted to the server as emotional data referenced by the emotion engine. This allows the user's travel experience to be customized to their individual emotional state, thereby improving user satisfaction.

[0864] As a concrete example, if a user is caught in traffic and stress is detected, the system can quickly select the optimal alternative route. It can also provide a user-friendly travel experience by playing relaxing music and adjusting the in-car temperature appropriately.

[0865] In this way, the present invention takes mobility services a step further and provides added value through emotion recognition.

[0866] An example of a prompt is: "Explain how, when a user is wearing smart glasses, the AI ​​combines traffic congestion data with the user's stress level to optimize route selection."

[0867] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0868] Step 1:

[0869] The server retrieves data from traffic and weather information APIs. The input is real-time traffic and weather data, which is then analyzed using NumPy and Pandas to calculate the optimal travel route. The output is the calculated optimal route information.

[0870] Step 2:

[0871] The terminal receives destination and reservation information from the user in text or voice format. Input is the user's destination information, which is transmitted to the system via the user interface. Output is the reservation information sent to the system.

[0872] Step 3:

[0873] The server uses an emotion engine to analyze voice data transmitted from the terminal. The input is the user's voice data, and the analysis identifies the user's emotional state. The output is the identified emotional state.

[0874] Step 4:

[0875] The server optimizes the environment settings of a mobile object based on its emotional state. The input consists of the identified emotional state and route information based on traffic data, and the system generates data to adjust the environment settings. The output is the adjusted environment settings.

[0876] Step 5:

[0877] Users experience a customized environment for their mobile device. As a result, the user's travel experience adapts to their individual emotional state, leading to improved comfort.

[0878] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0879] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0880] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0881] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0882] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0883] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0884] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0885] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0886] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0887] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0888] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0889] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0890] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0891] 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.

[0892] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0893] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0894] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0895] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0896] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0897] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0898] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0899] The following is further disclosed regarding the embodiments described above.

[0900] (Claim 1)

[0901] In order to generate the optimal route for a moving object, means for acquiring and analyzing traffic information and weather information,

[0902] A means for communicating with a terminal device that accepts user input and manages reservations for mobile vehicles,

[0903] A system including communication means for controlling and monitoring reserved mobile objects in real time.

[0904] (Claim 2)

[0905] The system according to claim 1, further comprising means for analyzing a user's past travel history and predicting travel trends.

[0906] (Claim 3)

[0907] The system according to claim 1, further comprising means for the terminal device to process payment information and complete the payment via communication means.

[0908] "Example 1"

[0909] (Claim 1)

[0910] A means for acquiring and analyzing traffic condition information and environmental condition information,

[0911] A means for receiving user input and communicating with a terminal device for managing reservations for mobile devices,

[0912] A communication means for controlling and monitoring reserved mobile devices in real time,

[0913] A means for calculating an efficient path via a processing device and generating individually optimized travel paths,

[0914] A means of transmitting information and processing and completing payment information using a unified communication network,

[0915] A system that includes this.

[0916] (Claim 2)

[0917] The system according to claim 1, further comprising means for analyzing the user's past travel history and predicting travel trends.

[0918] (Claim 3)

[0919] The system according to claim 1, further comprising communication means for adjusting the behavior of a mobile device in real time according to an instructed route.

[0920] "Application Example 1"

[0921] (Claim 1)

[0922] A means of acquiring and analyzing traffic and weather information,

[0923] A means of communicating with an information terminal for receiving user input and managing reservations for mobile vehicles,

[0924] A communication means for controlling and monitoring reserved mobile objects in real time,

[0925] A means of notifying users of recommended routes and departure times,

[0926] A means for processing payment information after the transfer is complete,

[0927] A system that includes this.

[0928] (Claim 2)

[0929] The system according to claim 1, further comprising means for analyzing a user's past travel history and predicting travel trends.

[0930] (Claim 3)

[0931] The system according to claim 1, further comprising means for updating the route in real time based on traffic conditions and weather conditions.

[0932] "Example 2 of combining an emotion engine"

[0933] (Claim 1)

[0934] In order to generate the optimal route for a moving object, means for acquiring and analyzing traffic information and weather information,

[0935] A means of communicating with terminal equipment for receiving user input and managing reservations for mobile vehicles,

[0936] A means for analyzing the user's emotional state and adjusting the environment settings of a mobile device based on the user's emotions,

[0937] A communication means for controlling and monitoring reserved mobile objects in real time,

[0938] A means for dynamically changing the optimal route based on the results of user sentiment analysis,

[0939] A system that includes this.

[0940] (Claim 2)

[0941] The system according to claim 1, further comprising means for analyzing a user's past travel history and emotional data to predict travel trends and emotional changes.

[0942] (Claim 3)

[0943] The system according to claim 1, further comprising means for the terminal device to process payment information and complete the payment via communication means, and further comprising means for adjusting the provision of services based on the emotional state of the user.

[0944] "Application example 2 when combining with an emotional engine"

[0945] (Claim 1)

[0946] In order to generate the optimal route for a moving object, means for acquiring and analyzing traffic information and weather information,

[0947] A means for communicating with a terminal device that accepts user input and manages reservations for mobile vehicles,

[0948] A communication means for controlling and monitoring reserved mobile objects in real time,

[0949] A means of recognizing the emotional state of the user from their voice or text and dynamically adjusting the environment settings while they are on the move,

[0950] A system that includes means for optimizing routes while taking into account the emotional state of the user.

[0951] (Claim 2)

[0952] The system according to claim 1, further comprising means for analyzing a user's past travel history and predicting travel trends.

[0953] (Claim 3)

[0954] The system according to claim 1, further comprising means for the terminal device to process payment information and complete the payment via communication means. [Explanation of Symbols]

[0955] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. In order to generate the optimal route for a moving object, means for acquiring and analyzing traffic information and weather information, A means for communicating with a terminal device that accepts user input and manages reservations for mobile vehicles, A system including communication means for controlling and monitoring reserved mobile objects in real time.

2. The system according to claim 1, further comprising means for analyzing a user's past travel history and predicting travel trends.

3. The system according to claim 1, further comprising means for the terminal device to process payment information and complete the payment via communication means.

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