System

Abstract

To provide a system.SOLUTION: A system includes: means for receiving a customer request; means for storing the customer request received with the receiving means to a database; means for executing an algorithm for selecting optimal transportation means on the basis of the request stored to the storing means; means for transmitting a prompt statement to a generative AI model and acquiring optimal transportation means on the basis of a result executed by the means for executing an algorithm; means for suggesting to the customer the transportation means acquired by the acquisition means; and means for settling the transportation on the basis of the suggestion of the transportation means suggested by the suggesting means.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] When people move with a purpose, "travel" is always involved, but there is a problem of frustration when the desired travel is not possible due to delays or traffic jams. [Means for solving the problem]

[0005] To solve this problem, we provide a system that accepts customer requests, performs AI / video analysis of the requests, utilizes MaaS based on the results, and pays for travel using MaaS. Furthermore, based on the results of the AI / video analysis, we propose the optimal route to the customer's destination and use ONEID payment as the payment method. [Brief explanation of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

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

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

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

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

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

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

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

[0014] [First embodiment]

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

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

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

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

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

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

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0023] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

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

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

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

[0027] "Example 1"

[0028] According to an embodiment of the present invention, there is provided a transportation service platform system, which includes a means for receiving requests from customers, for example, customers can send transportation requests through a smartphone application.

[0029] "Example 2"

[0030] The received request is processed by AI / video analytics, which analyzes the request and determines the optimal means of transportation. For example, based on the request, it can select public transportation, taxis, bike sharing, or other MaaS services.

[0031] "Example 3"

[0032] Based on the results of AI analysis / video analysis, a means of utilizing MaaS is provided. This means provides the selected MaaS service to the customer and realizes transportation. For example, if the customer selects a taxi, the system calls the nearest taxi and transports the customer to their destination. "Example 4"

[0033] Finally, a means of payment for MaaS journeys is provided, which allows customers to pay for the MaaS services they use, for example by automatically debiting the customer's account using the ONEID payment system.

[0034] The processing flow of each embodiment will be described below.

[0035] "Example 1"

[0036] Step 1: A customer accesses the transportation service platform system and submits a transportation request, which includes information such as the origin, destination, and desired departure time.

[0037] Step 2: The system sends the received request to the AI ​​analysis / video analysis means.

[0038] "Example 2"

[0039] Step 1: AI analytics / video analytics analyzes the request and determines the optimal mode of transportation, taking into account current traffic conditions, weather, and the customer's past usage history.

[0040] Step 2: Based on the analysis results, the optimal MaaS service is selected and notified to the customer. "Example 3"

[0041] Step 1: If the customer accepts the proposed MaaS service, the system will provide the service. For example, if a taxi is selected, the system will call the nearest taxi and take the customer to their destination.

[0042] Step 2: Once the customer arrives at their destination, the system confirms the trip is complete.

[0043] "Example 4"

[0044] Step 1: Once the transfer is complete, the system accepts payment from the customer.

[0045] Step 2: The customer pays through the ONEID payment system, which confirms the payment is complete and provides the customer with a receipt.

[0046] Example 1

[0047] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0048] Conventional mobility service platform systems have difficulty quickly and accurately proposing the optimal means of transportation in response to customer requests. Furthermore, there was a lack of standardized payment methods for the proposed means of transportation, which resulted in poor customer convenience. Furthermore, the lack of advanced analysis using AI models meant that the accuracy of the proposals was low.

[0049] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0050] In this invention, the server includes means for accepting customer requests, means for storing the accepted customer requests in a database, means for executing an algorithm for selecting the optimal means of transportation based on the stored requests, means for sending a prompt message to the generative AI model to obtain the optimal means of transportation, means for responding to the customer with the obtained means of transportation, and means for paying for transportation based on the proposed means of transportation. This makes it possible to quickly and accurately propose the optimal means of transportation in response to a customer request and provide a unified payment method.

[0051] The "means for accepting customer requests" is a function that provides an interface for customers to input their departure and destination points to use transportation services and transmit that information to the system.

[0052] The "means for storing received customer requests in a database" is a function for storing request information received from a customer in a database and making it available for subsequent processing.

[0053] "Means for executing an algorithm to select the most suitable means of transportation based on the stored requests" refers to a function that analyzes the request information stored in the database and performs calculations to select the most suitable means of transportation.

[0054] "Means for sending prompts to a generative AI model and obtaining the optimal means of transportation" refers to a function that sends prompts containing specific questions or instructions to a generative AI model and receives suggestions for the optimal means of transportation in response.

[0055] "Means of responding to customers about the acquired transportation method" is a function that notifies customers of the optimal transportation method information acquired from the generative AI model.

[0056] The "means for settling travel based on proposed means of transportation" is a function for carrying out a payment process for the customer to pay for the travel service based on the proposed means of transportation.

[0057] A "unified payment system" is a system that centrally manages multiple payment methods and allows customers to complete payments using any payment method they choose.

[0058] This invention relates to a mobility service platform system that accepts customer requests, proposes optimal means of transportation, and processes payments. This system is composed of a server, terminals, and user elements.

[0059] The server provides an API for accepting customer requests. This API is built using Python and Flask, and has the ability to store received requests in a MySQL® database. The server runs an algorithm for selecting the optimal transportation mode based on the stored requests. This algorithm is implemented in Python and uses a generative AI model (e.g., a generative AI model) to suggest the optimal transportation mode.

[0060] The terminal provides an interface for customers to submit travel requests. Specifically, it uses a smartphone application developed with React Native. Users input their departure and destination points through this application and submit their requests. The terminal then sends the input information to the server as an HTTP request.

[0061] A user submits a trip request using a smartphone application. After the user enters their origin and destination and presses the send button, the application sends this information to a server. The server receives the request and stores it in a database. The server then runs an algorithm to select the optimal mode of transportation based on the stored request. The algorithm uses a generative AI model to suggest the optimal mode of transportation to the user.

[0062] For example, consider the case where a user uses a smartphone application to send a "travel request from Shinjuku Station to Shibuya Station." When the user enters "Shinjuku Station" as the departure point and "Shibuya Station" as the destination and presses the send button, the application sends this information to a server. The server receives this request and stores it in a database. The server then runs an algorithm to select the optimal mode of transportation based on the stored request. This algorithm uses a generative AI model to make a suggestion to the user, such as "Traveling by train is the best option."

[0063] Examples of prompts to input to a generative AI model might include:

[0064] "A user has requested a trip from Shinjuku Station to Shibuya Station. Please suggest the best means of transportation."

[0065] By inputting this prompt into the generative AI model, the model will suggest the optimal means of transportation. For example, it may give an answer such as, "Traveling by train is best. The journey will take about 10 minutes." The server receives this response and sends it back to the user. The user can then confirm the suggested means of transportation through the application and actually begin traveling.

[0066] In this way, the mobility service platform system can propose the most suitable means of transportation for a user's mobility request and provide a unified payment method.

[0067] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0068] Step 1:

[0069] The user launches the smartphone application.

[0070] Input: User actions

[0071] Output: Application launch

[0072] Specific operation: The user taps the smartphone icon to launch the application. The application is developed with React Native and the initial screen is displayed.

[0073] Step 2:

[0074] The user enters the origin and destination and submits a travel request.

[0075] Input: Origin and destination information

[0076] Output: Move request sent

[0077] Specific operation: The user enters "Shinjuku Station" as the departure point and "Shibuya Station" as the destination in the application interface and presses the send button.

[0078] Step 3:

[0079] The device sends a request to the server.

[0080] Input: User-entered origin and destination information

[0081] Output: HTTP request to the server

[0082] Specific operation: The device sends the input information to the server as an HTTP request. This communication uses the HTTPS protocol.

[0083] Step 4:

[0084] The server receives the request and stores it in a database.

[0085] Input: HTTP request from the terminal

[0086] Output: Save to database

[0087] Specific operation: The server receives requests through an API built using Flask and saves a "travel request from Shinjuku Station to Shibuya Station" in a MySQL database.

[0088] Step 5:

[0089] The server runs an algorithm based on the stored requests to select the most suitable mode of transportation.

[0090] Input: Request information stored in the database

[0091] Output: Selection of optimal transportation mode

[0092] Specific operation: The server runs an algorithm implemented in Python and selects the optimal means of transportation, taking into account past data and current traffic conditions.

[0093] Step 6:

[0094] The server sends a prompt to the generative AI model to obtain the optimal means of transportation.

[0095] Input: Prompt text (e.g., "The user requests to travel from Shinjuku Station to Shibuya Station. Please suggest the best mode of transportation.")

[0096] Output: The response from the generative AI model

[0097] Specific operation: The server sends a prompt to the generative AI model and receives a response from the model such as, "Traveling by train is best. The journey takes about 10 minutes."

[0098] Step 7:

[0099] The server returns the acquired means of transportation to the user.

[0100] Input: Response from a generative AI model

[0101] Output: Reply to the user

[0102] Specific operation: The server receives the response from the generative AI model and notifies the user of the content. The user then confirms the proposed transportation method through the application.

[0103] Step 8:

[0104] The user confirms the proposed transportation options.

[0105] Input: Response from the server

[0106] Output: Check transportation method

[0107] Specific operation: The user confirms the proposed means of transportation through the application and actually starts traveling.

[0108] (Application example 1)

[0109] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0110] Conventional mobility service platform systems have had the problem of making it difficult to quickly and efficiently summon the most suitable autonomous vehicle when a customer submits a travel request. Furthermore, they lack the functionality to accurately input the customer's current location and destination and suggest the optimal route, which reduces the efficiency of travel.

[0111] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0112] In this invention, the server includes means for accepting customer requests, means for performing AI analysis / video analysis of the accepted customer requests, means for utilizing transportation services based on the results of the AI ​​analysis / video analysis, means for paying for transportation using the transportation services, means for inputting the customer's current location and destination, and means for calling the optimal self-driving vehicle, thereby enabling customers to quickly and efficiently call an autonomous vehicle using their smartphone and reach their destination via the optimal route.

[0113] "Customer Request" means a request submitted by a Customer to utilize the Mobility Services.

[0114] "AI analytics" is the process of using artificial intelligence to analyze data and extract meaningful information.

[0115] "Video analysis" is a technology that analyzes video data obtained from cameras and sensors and extracts specific information.

[0116] "Transportation services" refers to transportation means and services provided to customers to travel to their destinations.

[0117] "Payment method" refers to a method or system for paying for the service.

[0118] "Current location" refers to the location where the customer is currently located.

[0119] A "destination" is where a customer wants to go.

[0120] An "autonomous vehicle" is a vehicle that is driven automatically using artificial intelligence and sensors.

[0121] An "optimal route" is the most efficient route from a departure point to a destination, taking into account factors such as time, distance, and traffic conditions.

[0122] "Unified authentication and payment" refers to an authentication and payment system that can be used across multiple services and platforms.

[0123] A system for implementing this invention is configured as follows: First, a user sends a travel request using a smartphone. A dedicated application is installed on the smartphone, and the user can input their current location and destination through this application.

[0124] When the server receives a request from a user, it performs AI analysis and video analysis of the received request. Software such as Python and TENSORFLOW (registered trademark) is used for the AI ​​analysis, and libraries such as OpenCV are used for the video analysis. This allows the server to analyze data such as the user's current location, destination, and traffic conditions, and select the optimal autonomous vehicle.

[0125] Next, the server will call the most suitable self-driving vehicle based on the analysis results. The self-driving vehicle is equipped with GPS and various sensors, and collects data in real time to drive the optimal route to the destination.

[0126] After the transfer is complete, the server settles the transfer service fee. The payment method is a unified authentication payment system. This allows users to use multiple services with a single authentication, improving convenience.

[0127] As a concrete example, consider the case where a user requests an autonomous taxi from Tokyo Station to Tokyo Tower. The user opens a smartphone app and enters the latitude and longitude of Tokyo Station (35.6895, 139.6917) as their current location and the latitude and longitude of Tokyo Tower (35.6586, 139.7454) as their destination. The server receives this information, selects the most suitable autonomous vehicle, and dispatches it to the user.

[0128] An example of a prompt is as follows:

[0129] Consider a scenario where a user requests a self-driving taxi using a smartphone app. The user enters their current location and destination and calls the best available self-driving taxi. Write a Python program to send a request to the taxi service using an API key and receive the response.

[0130] In this way, users can quickly and efficiently summon an autonomous vehicle using their smartphone to reach their destination along the optimal route.

[0131] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0132] Step 1:

[0133] The user starts the smartphone app and inputs their current location and destination. The input data of the current location and destination is sent to the application as latitude and longitude information, which generates a travel request for the user.

[0134] Step 2:

[0135] The device sends the user's travel request to the server. The server analyzes the received request and obtains the latitude and longitude information of the current location and destination. Based on this information, the travel request processing begins.

[0136] Step 3:

[0137] The server then performs AI and video analysis on the received latitude and longitude information, using TensorFlow for the AI ​​analysis and OpenCV for the video analysis. This allows the server to analyze data such as traffic and road conditions and calculate the optimal route.

[0138] Step 4:

[0139] The server selects the most suitable autonomous vehicle based on the results of AI analysis and video analysis. Information about the selected autonomous vehicle is then sent from the server to the device, allowing the user to know which vehicle will respond to their request.

[0140] Step 5:

[0141] The terminal displays the information about the autonomous vehicle received from the server to the user. The user confirms the displayed information and confirms the request. This confirmation information is then sent back to the server.

[0142] Step 6:

[0143] The server receives the user's request confirmation and issues instructions to the self-driving vehicle. The self-driving vehicle uses GPS and various sensors to head to the user's current location. This allows the self-driving vehicle to be dispatched to the user's location.

[0144] Step 7:

[0145] When the autonomous vehicle arrives at the user's current location, the user gets in the vehicle and starts traveling toward the destination. The vehicle travels according to the optimal route provided by the server.

[0146] Step 8:

[0147] Once the transfer is complete, the server calculates the transfer service fee and charges the fee via the payment method. The payment is made using a unified authentication payment system, which allows the user to pay the fee with a single authentication.

[0148] Step 9:

[0149] The server notifies the terminal that the payment has been completed. The terminal then displays a notification of the payment completion to the user, allowing the user to confirm that the use of the mobile service has been completed.

[0150] Example 2

[0151] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0152] Conventional transportation suggestion systems have difficulty quickly and accurately suggesting the optimal transportation method in response to a user's request. Furthermore, when using multiple transportation methods in an integrated manner, payment methods are complicated, reducing user convenience.

[0153] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0154] In this invention, the server includes means for accepting customer requests, means for performing AI analysis / video analysis of the accepted customer requests, means for determining a means of transportation based on the results of the AI ​​analysis / video analysis, means for providing information on the determined means of transportation to the customer, and means for paying for the use of the means of transportation. This makes it possible to quickly and accurately propose the most suitable means of transportation in response to a user's request and to simplify payment methods when using multiple means of transportation in an integrated manner.

[0155] The "means for accepting customer requests" is an interface for receiving requests and information regarding travel from users.

[0156] "AI analysis / video analysis means" is a system that uses artificial intelligence and video analysis technology to analyze received customer requests and identify the optimal means of transportation.

[0157] "Means for determining the means of transportation" refers to the algorithms and processes for selecting the most suitable means of transportation for the user based on the results of AI analysis / video analysis.

[0158] The "means for providing the customer with information about the selected transportation means" refers to an interface or communication means for notifying the user of detailed information about the selected transportation means.

[0159] The "means for paying for the use of transportation" refers to a payment system that allows a user to pay the fee when using the selected transportation.

[0160] An "integrated payment system" is a payment platform for processing fees for multiple means of transportation in one go.

[0161] MODE FOR CARRYING OUT THE INVENTION

[0162] The present invention is a system for making optimal suggestions when a user selects a means of transportation and for easily paying for the use of that means of transportation. Specific embodiments of this system are described below.

[0163] System configuration

[0164] The system consists of the following major components:

[0165] 1. How we receive customer requests

[0166] Users use devices such as smartphones or PCs to input travel requests, such as "I want the fastest way from Shinjuku to Shibuya."

[0167] 2. AI analysis / video analysis methods

[0168] The server passes the received customer request to an AI analytics / video analysis method, which analyzes the request content using a machine learning model implemented in Python (e.g., TensorFlow or PyTorch).

[0169] 3. How to decide on transportation

[0170] AI analytics / video analytics analyzes the request content and identifies the transportation method that best suits the user's needs. For example, it references public transportation timetable databases (e.g., GTFS data) to calculate the optimal train or bus route. It also uses APIs for taxi and bike-sharing services (e.g., taxi API and bike-sharing API) to obtain real-time availability and fare information.

[0171] 4. Means of providing customers with information about their chosen transportation options

[0172] The server then sends information about the selected transportation method to the terminal, including the specific route, travel time, and fare.

[0173] 5. Means of payment for transportation

[0174] The server provides a payment system for the user to pay for the transportation means selected by the user, which uses an integrated payment system to process the fees for multiple transportation means in a single transaction.

[0175] Specific examples

[0176] For example, if a user requests "the fastest way to get from Shinjuku to Shibuya," the process proceeds as follows:

[0177] 1. The user types "I want to travel from Shinjuku to Shibuya the fastest" into their smartphone and presses the send button.

[0178] 2. The device sends this request to the server.

[0179] 3. The server receives the request and passes it to the AI ​​analysis / video analysis method.

[0180] 4. AI analytics / video analytics analyzes the request and identifies the best means of transportation, for example, by consulting train timetables and calculating the optimal route.

[0181] 5. Based on the analysis results, the server determines which train is the fastest and determines the route information.

[0182] 6. The server sends the determined route information to the terminal.

[0183] 7. The device displays to the user, "The best route from Shinjuku to Shibuya is the 15:10 train."

[0184] 8. The user selects a means of transportation based on the displayed information and begins traveling.

[0185] 9. The server uses an integrated payment system to process the user's transportation fees in one lump sum.

[0186] Prompt Sentence Examples

[0187] "I want to get from Shinjuku to Shibuya as quickly as possible. It's currently 3:00 PM. What is the best way to get there?"

[0188] By inputting this prompt into a generative AI model, the system suggests the most optimal means of transportation for the user.

[0189] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0190] Step 1:

[0191] The user submits a request.

[0192] A user uses a device such as a smartphone or PC to input a travel request and press the send button. The input includes information such as the current location, destination, and desired mode of transportation. The output is the request data sent from the device to the server.

[0193] Step 2:

[0194] The device sends a request to the server.

[0195] The terminal sends the request entered by the user to the server as an HTTP request. The input is the request data entered by the user, and the output is the request data sent to the server.

[0196] Step 3:

[0197] The server receives the request and passes it to the AI ​​analysis / video analysis means.

[0198] The server passes the request received from the terminal to the AI ​​analysis / video analysis means for analysis. The input is the request data received from the terminal, and the output is the request data passed to the AI ​​analysis / video analysis means.

[0199] Step 4:

[0200] AI analysis / video analysis tools analyze the request.

[0201] The AI ​​analysis / video analysis method analyzes the content of the request using a machine learning model implemented in Python (e.g., TensorFlow or PyTorch). The input is the request data passed from the server, and the output is the analysis results. Specifically, it analyzes the content of the request and identifies the transportation method that best suits the user's needs.

[0202] Step 5:

[0203] The server determines the optimal means of transportation based on the analysis results.

[0204] The server receives the analysis results from the AI ​​analysis / video analysis means and determines the optimal means of transportation for the user. The input is the analysis results from the AI ​​analysis / video analysis means, and the output is information on the determined means of transportation. Specifically, it refers to a public transportation timetable database (e.g., GTFS data) to calculate the optimal train or bus route. It also uses the APIs of taxi and bicycle sharing services (e.g., taxi API and bicycle sharing API) to obtain real-time availability and fare information.

[0205] Step 6:

[0206] The server transmits information about the determined means of transportation to the terminal.

[0207] The server sends information about the selected transportation mode to the terminal. The input is the information about the selected transportation mode, and the output is the information about the transportation mode sent to the terminal. Specific operations include information about the specific route, required time, fare, etc.

[0208] Step 7:

[0209] The device displays the most suitable means of transportation for the user.

[0210] The terminal displays the information received from the server to the user. The input is the information about the means of transportation received from the server, and the output is the information about the means of transportation displayed to the user. In concrete terms, the user can select the most suitable means of transportation based on the displayed information and start traveling.

[0211] Step 8:

[0212] The server settles the transportation fee.

[0213] The server provides a payment system for users to pay for the transportation they select. The input is the user's transportation usage information, and the output is confirmation of payment completion. Specifically, the integrated payment system is used to process the fees for multiple transportation methods in a lump sum.

[0214] (Application example 2)

[0215] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0216] In modern society, the variety of transportation methods is increasing, but users need to collect and compare a lot of information to choose the most suitable transportation method. This requires users to spend time and effort, making it difficult to travel efficiently. In addition, the complexity of reserving and paying for transportation methods reduces user convenience. Furthermore, if real-time route guidance is not provided, users may get lost during their trip.

[0217] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0218] In this invention, the server includes means for accepting customer requests, means for performing AI analysis / video analysis of the accepted customer requests, means for utilizing MaaS based on the results of the AI ​​analysis / video analysis, means for paying for travel using MaaS, means for proposing the optimal means of transportation, means for providing real-time route guidance based on the proposed means of transportation, and means for checking reservations and usage status of autonomous vehicles. This allows users to easily select the optimal means of transportation and enables efficient travel. Furthermore, by simplifying reservations and payments for transportation and providing real-time route guidance, user convenience is greatly improved.

[0219] "Customer Request" means a travel request or desire entered into the System by a User.

[0220] "AI analysis / video analysis" is the process of using artificial intelligence technology to analyze customer requests and related video data to determine the most appropriate means of transportation.

[0221] "MaaS" stands for Mobility as a Service and refers to a service that integrates and provides multiple means of transportation.

[0222] "Payment method" means a method or system by which a user pays for the use of a mobility service.

[0223] "Optimal transportation" refers to the most efficient and convenient way of transportation based on the user's request and circumstances.

[0224] "Means for providing route guidance in real time" refers to a system that provides real-time guidance on the optimal route based on the user's current location information while they are traveling.

[0225] "Means for checking reservations and usage status of self-driving vehicles" refers to a system that allows users to reserve self-driving vehicles and check their usage status.

[0226] "Unified authentication payment" is a payment method that integrates multiple payment methods into a single authentication system, allowing users to make payments easily.

[0227] A system for implementing this invention has the following configuration: First, a user inputs a destination and a request for travel using a terminal such as a smartphone. The terminal then transmits this request to a server.

[0228] The server analyzes the received customer requests using AI analysis / video analysis methods. This analysis is achieved by using Python and the Requests library and calling the AI ​​analysis API. Based on the analysis results, the server determines the optimal means of transportation and suggests it to the user.

[0229] The server then provides real-time route guidance based on the proposed transportation options, using GPS data and map information to calculate the optimal route from the user's current location to their destination. The server also provides a way to reserve and check the availability of autonomous vehicles, allowing users to easily reserve an autonomous vehicle and check its availability in real time.

[0230] The payment method used is unified authentication payment, which allows users to integrate multiple payment methods into a single authentication system and make payments easily.

[0231] For example, if a user requests to go to Tokyo Station, the server will suggest that the best way to get from Shibuya Station to Tokyo Station is by train and provide real-time route guidance. If the user wants to use an autonomous vehicle, the server will support the reservation and confirmation of its usage status.

[0232] An example of a prompt sentence is as follows:

[0233] "Create an application where the user inputs their destination and the AI ​​suggests the best means of transportation and provides real-time route guidance. Include a function that determines the best means of transportation by taking into account the user's current location, destination, and transportation preferences (cost, time, etc.)."

[0234] This allows users to easily select the most suitable means of transportation, enabling efficient travel. It also simplifies travel reservations and payments, and provides real-time route guidance, greatly improving user convenience.

[0235] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0236] Step 1:

[0237] The user inputs a destination and a travel request using a device such as a smartphone.

[0238] Input: User's destination, current location, transportation preferences (cost, time, etc.)

[0239] Output: Request data (e.g., JSON format)

[0240] Specific operation: The user enters their destination and preferred mode of transportation into the application's input form and presses the submit button.

[0241] Step 2:

[0242] The terminal transmits the request data to the server.

[0243] Input: Request data

[0244] Output: Request data sent to the server

[0245] Specific operation: The terminal uses an HTTP POST request to send request data to the server.

[0246] Step 3:

[0247] The request data received by the server is analyzed using AI analysis / video analysis methods.

[0248] Input: Request data

[0249] Output: Analysis results (optimal means of transportation)

[0250] How it works: The server calls the AI ​​analytics API and analyzes the request data using Python and the Requests library.

[0251] Step 4:

[0252] The server determines the optimal means of transportation based on the analysis results and suggests it to the user.

[0253] Input: Analysis results

[0254] Output: Recommendation of optimal transportation method

[0255] Specific operation: Based on the analysis results, the server determines the optimal means of transportation (e.g., train, self-driving vehicle, etc.) and notifies the user.

[0256] Step 5:

[0257] The server provides real-time route guidance based on the proposed means of travel.

[0258] Input: Best mode of transportation, current user location

[0259] Output: Real-time directions

[0260] Specific operation: The server uses GPS data and map information to calculate the optimal route from the user's current location to their destination and provides real-time guidance.

[0261] Step 6:

[0262] The server provides a means to check reservations and usage status of autonomous vehicles.

[0263] Input: User's booking request

[0264] Output: Reservation confirmation, usage status notification

[0265] Specific operation: The server accesses the autonomous vehicle reservation system, processes the user's reservation request, checks the usage status, and notifies the user.

[0266] Step 7:

[0267] The server settles the mobile service fee using unified authentication and settlement.

[0268] Input: User's payment information

[0269] Output: Payment completion notification

[0270] Specific operation: The server uses the unified authentication and payment system to process the user's payment information and pay the usage fee. After the payment is completed, the server notifies the user.

[0271] Example 3

[0272] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0273] Conventional mobility service systems have difficulty responding quickly and appropriately to customer requests, particularly in accurately determining the customer's current location and the optimal means of transportation. Furthermore, payment methods are complicated, making them inconvenient for customers. This has led to issues such as lower customer satisfaction and a decrease in the frequency of service use.

[0274] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0275] In this invention, the server includes means for accepting customer requests, means for performing artificial intelligence analysis and video analysis of the accepted customer requests, means for utilizing transportation services based on the results of the artificial intelligence analysis and video analysis, means for paying for transportation using the transportation services, means for analyzing the customer's current location, means for calling the nearest transportation means, and means for displaying a notification of payment completion to the customer. This makes it possible to respond quickly and appropriately to customer requests and provide the most optimal transportation means. In addition, the payment method is simple, providing high convenience for customers.

[0276] "Means for accepting customer requests" refers to equipment or software for receiving requests for mobility services from customers.

[0277] "Means for artificial intelligence analysis and video analysis" refers to devices or software that use artificial intelligence technology and video analysis technology to process data based on received customer requests and analyze the customer's current location and situation.

[0278] "Means for utilizing transportation services" refers to devices or software that select the optimal means of transportation and provide it to customers based on the results of artificial intelligence analysis and video analysis.

[0279] "Means for settling travel for the use of mobility services" means a device or software for automatically settling the charges for the mobility services used by the customer.

[0280] "Means for analyzing the customer's current location" refers to a device or software for identifying and analyzing the customer's current location.

[0281] A "nearest transportation call means" is a device or software that identifies and calls the transportation closest to the customer's current location.

[0282] The "means for displaying a notice of payment completion to the customer" is a device or software for notifying the customer that the fee for the mobile service has been paid.

[0283] MODE FOR CARRYING OUT THE INVENTION

[0284] The present invention relates to a system that accepts customer requests, performs artificial intelligence analysis and video analysis, provides optimal transportation services, and performs payment. Specific embodiments of this system are described below.

[0285] System configuration

[0286] The system consists of the following major components:

[0287] 1. How we receive customer requests

[0288] The terminal (smartphone or tablet) receives requests for transportation services from customers, who then submit requests using a dedicated application.

[0289] 2. AI analysis and video analysis methods

[0290] Based on the received customer request, the server processes the data using artificial intelligence technology (e.g., machine learning models) and video analysis technology (e.g., image recognition software), specifically using Google® Cloud Vision API and Amazon Rekognition.

[0291] 3. Ways to utilize transportation services

[0292] The server selects the optimal transportation method based on the results of AI analysis and video analysis, and provides it to the customer. For example, it uses the Uber API to call the nearest taxi.

[0293] 4. Means of payment for travel using transportation services

[0294] The server automatically settles the mobile service fee, specifically using an automatic settlement system (for example, the ONEID settlement system).

[0295] 5. A way to analyze customer location

[0296] The server uses the Google Cloud Vision API to analyze the customer's location, returning the results in the form of latitude and longitude.

[0297] 6. How to call the nearest transportation

[0298] The server calls the Uber API to dispatch the nearest taxi to the customer's location, and the API call returns the taxi's vehicle information and estimated arrival time.

[0299] 7. How to notify customers that payment has been completed

[0300] The terminal will display a notification to the customer that the payment has been completed, and the customer can view a receipt within the app.

[0301] Specific examples

[0302] For example, the specific steps for a user to call a taxi using a smartphone are as follows.

[0303] 1. The user opens the app on their smartphone and selects a taxi.

[0304] 2. The device sends the user's request to the server.

[0305] 3. The server uses the Google Cloud Vision API to analyze the user's current location.

[0306] 4. The server uses Amazon Rekognition to analyze the surrounding video data and collect information to suggest the best means of transportation.

[0307] 5. The server calls the Uber API and dispatches the nearest taxi to the user's current location.

[0308] 6. The device notifies the user of the taxi's estimated arrival time and vehicle information.

[0309] 7. The taxi arrives and takes the user to their destination. During the journey, the device displays their current location and estimated arrival time in real time.

[0310] 8. Once the transfer is complete, the server calls the ONEID payment system and debits the user's account.

[0311] 9. The terminal will display a notification to the user that the payment has been completed, and the user can view the receipt within the app.

[0312] Prompt Sentence Examples

[0313] "Please explain the steps a user would take to call a taxi using their smartphone and get to their destination. Please include names of any specific software or hardware."

[0314] In this way, by explaining the specific embodiment of the system, the details of the invention can be easily understood and can serve as a reference for other people to practice the invention accurately. The flow of the specific processing in Example 3 will be explained using Figure 15.

[0315] Step 1:

[0316] The user opens the app on their smartphone and selects a transportation service (e.g., a taxi).

[0317] Input: User request (selection of travel service)

[0318] Output: Request data (selected travel service)

[0319] Specific operation: When a user selects a taxi within the app and presses the request button, request data is generated.

[0320] Step 2:

[0321] The terminal transmits the user's request to the server.

[0322] Input: Request data

[0323] Output: Request sent to server

[0324] Specific operation: The terminal performs network communication to send the request data to the server.

[0325] Step 3:

[0326] The server uses the Google Cloud Vision API to analyze the user's current location.

[0327] Input: Request data, user location information

[0328] Output: Analysis results (latitude and longitude)

[0329] Specific operation: The server sends the user's location information to the Google Cloud Vision API and obtains the current location in the form of latitude and longitude.

[0330] Step 4:

[0331] The server uses Amazon Rekognition to analyze surrounding video data and collect information to suggest the best means of transportation.

[0332] Input: User's location information, surrounding video data

[0333] Output: Analysis results (traffic conditions and weather information)

[0334] Specific operation: The server sends surrounding video data to Amazon Rekognition to obtain traffic and weather information.

[0335] Step 5:

[0336] Based on the analysis results, the server calls the Uber API to call the nearest taxi.

[0337] Input: Analysis results (latitude and longitude, traffic conditions, weather information)

[0338] Output: Taxi vehicle information, estimated arrival time

[0339] Specific operation: The server calls the Uber API to dispatch the nearest taxi to the user's current location. The API call returns the taxi's vehicle information and estimated arrival time.

[0340] Step 6:

[0341] The terminal notifies the user of the taxi's estimated arrival time and vehicle information.

[0342] Input: Taxi vehicle information, estimated arrival time

[0343] Output: Notification message

[0344] Specific operation: The terminal generates a notification message and displays the estimated arrival time of the taxi and vehicle information to the user.

[0345] Step 7:

[0346] The taxi arrives and takes the user to their destination.

[0347] Input: current location and destination information

[0348] Output: Providing transportation services

[0349] Specific operation: The taxi picks up the user and takes them to their destination. During the trip, the device displays their current location and estimated arrival time in real time.

[0350] Step 8:

[0351] The server confirms the transfer is complete and automatically debits the fee using the ONEID payment system.

[0352] Input: Movement completion information, fee information

[0353] Output: Payment completion notification

[0354] Specific operation: The server receives the transfer completion information and calls the ONEID payment system to deduct the fee.

[0355] Step 9:

[0356] The terminal displays a notice to the user that the payment has been completed.

[0357] Input: Payment completion notification

[0358] Output: Payment completion message

[0359] Specific behavior: The terminal generates a payment completion message and displays it to the user, who can then view the receipt in the app.

[0360] (Application example 3)

[0361] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0362] Conventional mobility service systems have difficulty in providing optimal transportation methods in response to customer requests, and safety and efficiency are not sufficiently ensured, especially when using autonomous vehicles. Furthermore, payment for the transportation service fee requires manual operation, which is inconvenient. There is a need to solve these issues and provide safer and more efficient mobility services.

[0363] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0364] In this invention, the server includes means for accepting customer requests, means for performing artificial intelligence analysis / video analysis of the accepted customer requests, means for utilizing a transportation service based on the results of the artificial intelligence analysis / video analysis, means for paying for transportation using the transportation service, means for analyzing the surrounding situation in real time using a smartphone camera, means for selecting the optimal autonomous vehicle based on the analysis results, means for calling the autonomous vehicle and navigating the route to the destination, and means for automatically withdrawing the usage fee. This enables customers to use autonomous vehicles safely and efficiently, and the usage fee for the transportation service is also automatically paid, improving convenience.

[0365] "Customer Request" means a request submitted by a Customer to utilize the Mobility Services.

[0366] "Artificial intelligence analysis" is the process of using artificial intelligence technology to analyze data and support decision-making.

[0367] "Video analysis" is a technology that analyzes video data from cameras and other sources and extracts specific information.

[0368] "Mobility services" is a general term for transportation methods and services that assist customers in their mobility.

[0369] "Payment method" refers to a method or system for paying for service usage fees.

[0370] A "smartphone camera" is a photographic device built into a smartphone.

[0371] "Real-time analysis" is the process of analyzing data immediately at the moment it is acquired.

[0372] An "autonomous vehicle" is a vehicle that drives autonomously using artificial intelligence and sensor technology.

[0373] "Navigation" means guiding the user to the optimal route to their destination.

[0374] "Usage Fee" means the fee paid to use the Service.

[0375] "Automatic debit" is the process by which fees are paid automatically without manual intervention.

[0376] A system for implementing this invention includes means for accepting customer requests, means for performing artificial intelligence analysis / video analysis of the accepted customer requests, means for utilizing a transportation service based on the results of the artificial intelligence analysis / video analysis, means for paying for transportation using the transportation service, means for analyzing the surrounding situation in real time using a smartphone camera, means for selecting the most suitable autonomous vehicle based on the analysis results, means for calling an autonomous vehicle and navigating the route to the destination, and means for automatically deducting the usage fee.

[0377] Program processing explanation

[0378] The server receives customer requests through a smartphone application. The received requests are sent to the server for artificial intelligence analysis and video analysis. The server analyzes the surrounding situation in real time using the smartphone's camera and selects the most suitable autonomous vehicle based on the analysis results. The selected autonomous vehicle navigates the route to the customer's specified destination.

[0379] Hardware and software used

[0380] Hardware: Smartphones (with cameras), autonomous vehicles, servers

[0381] Software: Smartphone applications, artificial intelligence analysis software, video analysis software, payment systems (automatic payment systems)

[0382] Data processing and calculation

[0383] Data processing: Video data captured by the smartphone camera is sent to a server in real time, where it is analyzed by artificial intelligence and video analysis is performed.

[0384] Data calculation: Based on the analysis results, the optimal self-driving vehicle is selected, the route to the destination is calculated, and payment processing is performed to automatically deduct the usage fee.

[0385] Specific examples

[0386] The user opens the smartphone app and enters "Tokyo Station" as their destination. The app uses the smartphone's camera to analyze the surrounding situation in real time, and once it is confirmed to be safe, it calls the nearest self-driving vehicle. The vehicle arrives and takes the user to their destination. After arrival, the fare is automatically deducted using an automated payment system.

[0387] Prompt Sentence Examples

[0388] The user opens the smartphone app and enters "Tokyo Station" as their destination. The app uses the smartphone's camera to analyze the surrounding situation in real time, and once it is confirmed to be safe, it calls the nearest self-driving vehicle. The vehicle arrives and takes the user to their destination. After arrival, the fare is automatically deducted using an automated payment system.

[0389] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0390] Step 1:

[0391] The user opens the smartphone app and enters their destination.

[0392] Input: Destination information entered by the user into the smartphone app.

[0393] Output: The destination information is sent to the server.

[0394] Specific operation: The user enters a destination, such as "Tokyo Station," into the app's input form and presses the submit button. The app sends this information to the server.

[0395] Step 2:

[0396] The server accepts the customer request.

[0397] Input: Destination information sent from the smartphone app.

[0398] Output: The accepted request is saved in the database.

[0399] Specific operation: The server saves the received destination information in the database and generates a request ID.

[0400] Step 3:

[0401] The server uses the smartphone's camera to analyze the surrounding situation in real time.

[0402] Input: Smartphone camera image data.

[0403] Output: Surrounding safety information as an analysis result.

[0404] How it works: The smartphone camera captures video of the surrounding area and sends the video data to a server, which then uses video analysis software to evaluate the safety of the surrounding area.

[0405] Step 4:

[0406] The server performs artificial intelligence analysis and selects the most suitable self-driving vehicle.

[0407] Input: Surrounding safety information and destination information.

[0408] Output: The optimal autonomous vehicle selection result.

[0409] Specific operation: The server uses artificial intelligence analysis software to select the most suitable autonomous vehicle based on surrounding safety information and destination information, and outputs the selection result as a vehicle ID.

[0410] Step 5:

[0411] The server calls the self-driving vehicle and navigates the route to the destination.

[0412] Input: Optimal autonomous vehicle selection results and destination information.

[0413] Output: Autonomous vehicle invocation and navigation information.

[0414] Specific operation: The server sends destination information to the selected autonomous vehicle and instructs the vehicle to head to the user's location. The vehicle then navigates the route to the destination.

[0415] Step 6:

[0416] The user gets into an autonomous vehicle and travels to their destination.

[0417] Input: User's ride and navigation information.

[0418] Output: Destination arrival information.

[0419] Specific operation: The user gets into the autonomous vehicle, and the vehicle travels to the destination according to the navigation information. Upon arrival, the destination arrival information is sent to the server.

[0420] Step 7:

[0421] The server will automatically deduct the fee.

[0422] Input: Destination arrival information and user payment information.

[0423] Output: Payment completion information.

[0424] Specific operation: The server receives the destination arrival information, deducts the usage fee using the automatic payment system based on the user's payment information, and notifies the user that payment has been completed.

[0425] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0426] "Example 1"

[0427] In one embodiment of the present invention, the emotion engine recognizes the customer's emotions and adjusts the transportation method based on the emotions. Specifically, if the emotion engine recognizes that the customer is stressed, it may suggest a more relaxing transportation method, such as suggesting scenic public transportation instead of a taxi.

[0428] "Example 2"

[0429] The emotion engine also adjusts the route based on the customer's emotions. Specifically, if the emotion engine recognizes that the customer is feeling happy, it will suggest a more enjoyable route, such as one that passes through parks or tourist spots.

[0430] "Example 3"

[0431] Furthermore, the emotion engine simultaneously adjusts the means of transportation and route based on the customer's emotions. Specifically, if the emotion engine recognizes that the customer is feeling angry, it will suggest a smoother, more stress-free means of transportation and route. For example, it will suggest the shortest route to avoid congestion and the fastest means of transportation along that route.

[0432] "Example 4"

[0433] The emotion engine also recognizes the customer's emotions in real time, and if their emotions change during the journey, it will readjust the means of transportation and route accordingly. Specifically, if it recognizes that the customer is starting to feel bored during the journey, the emotion engine will suggest more entertaining means of transportation and routes. For example, it will suggest means of transportation that include music and video, or routes that are visually appealing.

[0434] The processing flow of each embodiment will be described below.

[0435] "Example 1"

[0436] Step 1: The emotion engine recognizes customer emotions in real time.

[0437] Step 2: If the emotion engine recognizes that the customer is stressed, it will choose a more relaxing mode of transportation.

[0438] Step 3: Specifically, suggest scenic public transportation instead of taxis.

[0439] "Example 2"

[0440] Step 1: The emotion engine recognizes customer emotions in real time.

[0441] Step 2: If the emotion engine recognizes that the customer is feeling happy, it will choose a more enjoyable route.

[0442] Step 3: Specifically, suggest a route that passes through parks and tourist spots.

[0443] "Example 3"

[0444] Step 1: The emotion engine recognizes customer emotions in real time.

[0445] Step 2: If the emotion engine recognizes that the customer is angry, it selects a smoother, more stress-free mode of transportation and route.

[0446] Step 3: Specifically, we propose the shortest route to avoid congestion and the fastest means of transportation along that route.

[0447] "Example 4"

[0448] Step 1: The emotion engine recognizes customer emotions in real time.

[0449] Step 2: If the emotion engine detects that the customer is starting to feel bored during the journey, it will rearrange the journey or route to make it more entertaining.

[0450] Step 3: Specifically, we suggest transportation methods that allow you to enjoy music and video, and routes that are visually appealing.

[0451] Example 1

[0452] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0453] Conventional mobility service platform systems often suggest transportation methods without considering the customer's feelings, which can lead to lower customer satisfaction. Furthermore, there is a lack of technology to select the optimal transportation method based on the customer's feelings, making it difficult to provide services that meet customer needs. Furthermore, there is also the issue of low convenience due to limited payment methods.

[0454] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0455] In this invention, the server includes means for accepting customer requests, means for analyzing the accepted customer requests using natural language processing technology, means for recognizing the customer's emotions based on the analysis results, means for selecting the optimal means of transportation based on the recognized emotions, means for notifying the customer of information about the selected means of transportation, and means for paying for the use of the means of transportation. This makes it possible to suggest the optimal means of transportation based on the customer's emotions and improve customer satisfaction. Furthermore, convenience can be improved by introducing a payment method using biometric authentication.

[0456] "Customer Request" means a travel request or wish that a customer submits to the travel service platform system.

[0457] "Natural language processing technology" is a technology that allows computers to analyze and understand human language.

[0458] "Analysis results" refers to the data and information obtained after analyzing a customer request using natural language processing technology.

[0459] "Means for recognizing emotions" refers to technologies and methods for identifying customer emotions based on analysis results.

[0460] "Transportation" refers to the means of transportation used by the customer to travel to their destination.

[0461] A "selection tool" is a method or technique for determining the best option based on specific conditions or criteria.

[0462] "Means of notification" refers to the methods or techniques used to communicate selected information to customers.

[0463] "Payment instruments" refers to methods and technologies for making payments for the use of transportation means.

[0464] "Biometric authentication" is a technology that identifies individuals using biometric information such as fingerprints or facial recognition.

[0465] This invention relates to a transportation service platform system that proposes the most suitable transportation method based on customer emotions. This system accepts customer requests, analyzes them using natural language processing technology, recognizes the customer's emotions based on the analysis results, selects the most suitable transportation method based on the recognized emotions, notifies the customer of the selected transportation method, and performs a series of processes to settle the use of the transportation method.

[0466] Hardware and software used

[0467] Hardware:

[0468] Server: Use a server machine with a powerful processor and sufficient memory.

[0469] Device: The customer uses a smartphone (iOS or ANDROID (registered trademark)).

[0470] software:

[0471] Server: Runs programs written in Python.

[0472] Natural language processing libraries: Use NLTK, spaCy, etc.

[0473] Machine learning models: Use TensorFlow, PyTorch, etc.

[0474] Explanation of program processing

[0475] Accepting requests:

[0476] The terminal (customer's smartphone) sends a travel request through a dedicated application. For example, a user might enter, "I want to travel from Shinjuku to Shibuya. I'm very tired today," and press the send button. The server receives the request sent from the terminal and stores it in a database.

[0477] Emotion Recognition:

[0478] The server analyzes the text data of the received request and uses natural language processing technology to recognize the customer's emotions. For example, it recognizes "fatigue" from the text "I'm very tired today." The server tokenizes the text using a natural language processing library (e.g., spaCy) and inputs it into a sentiment analysis model (e.g., a model trained with TensorFlow). The model extracts emotions from the text and returns the result "fatigue."

[0479] Transportation options:

[0480] The server selects the optimal transportation method based on the recognized emotion. For example, if "fatigue" is recognized, the server will suggest a public transportation method with a good view. The server searches the database of transportation methods for transportation tagged with "relaxing," and from the search results, selects the public transportation method that is optimal for the user's current location and destination.

[0481] Notification of results:

[0482] The server generates information about the selected transportation method and sends it to the device. For example, it generates information such as, "The public transportation with the best scenery from Shinjuku to Shibuya is the Yamanote Line." The device then displays the received message to the user through the application's notification function.

[0483] settlement:

[0484] The server provides a means of payment for transportation. By introducing a payment method using biometric authentication, convenience can be improved. For example, payment can be made using fingerprint authentication or face authentication.

[0485] Examples of specific examples and prompts

[0486] As a concrete example, consider the following scenario.

[0487] Scenario: A user types into the app, "I'm very tired today and I'm looking for a relaxing ride."

[0488] Prompt: "If the customer is feeling tired, suggest a relaxing mode of transportation."

[0489] By inputting this prompt sentence into the generative AI model, the following output is obtained:

[0490] Example output: "The customer feels tired, so suggest scenic public transport."

[0491] In this way, the mobility service platform system provides optimal transportation based on customer sentiment.

[0492] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0493] Step 1: Accepting the request

[0494] Input: The user inputs a travel request through the smartphone application and presses the send button.

[0495] What happens: The user types into the app, "I want to travel from Shinjuku to Shibuya. I'm very tired today."

[0496] Data processing: The terminal sends the entered text data to the server.

[0497] Output: The server stores the received request in a database.

[0498] Step 2: Recognize emotions

[0499] Input: The text data of the request received by the server.

[0500] What it does: The server uses a natural language processing library (e.g., spaCy) to tokenize the text and feed it into a sentiment analysis model (e.g., a model trained in TensorFlow).

[0501] Data processing: The model extracts emotions from the text and returns the result "fatigue."

[0502] Output: The server gets the emotion recognition result "fatigue".

[0503] Step 3: Choose your transportation

[0504] Input: Emotion recognition result from the server (e.g., tiredness).

[0505] What happens: The server searches its database of transportation options for options tagged as "relaxing."

[0506] Data processing: From the search results, select the public transport that best suits the user's current location and destination.

[0507] Output: The server generates the information "The best scenic public transport from Shinjuku to Shibuya is the Yamanote Line."

[0508] Step 4: Notification of results

[0509] Input: Information about the transportation method selected by the server.

[0510] Specific operation: The server generates a message containing detailed information about the selected transportation method (e.g., route name, travel time, and fare).

[0511] Data processing: The server sends the generated message to the terminal.

[0512] Output: The device displays the received message to the user through the application's notification function.

[0513] Step 5: Payment

[0514] Input: The user indicates their intention to use the selected mode of transportation.

[0515] Specific operation: The user makes a payment using biometric authentication (e.g., fingerprint authentication or facial authentication).

[0516] Data processing: The server verifies the biometric data and processes the payment.

[0517] Output: The server sends a notification of payment completion to the terminal, which displays it to the user.

[0518] In this way, the mobility service platform system provides optimal transportation based on customer sentiment, improving convenience.

[0519] (Application example 1)

[0520] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0521] Conventional mobility service platform systems provide transportation without considering the emotional state of the customer, which can cause stress for the customer. Furthermore, the system does not adjust the optimal route or in-car environment, which can lead to a decrease in customer satisfaction. This creates a problem of not improving the quality of the customer experience.

[0522] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for accepting a customer request, means for performing artificial intelligence analysis / video analysis of the accepted customer request, means for utilizing a transportation service based on the results of the artificial intelligence analysis / video analysis, means for paying for transportation using the transportation service, and means for recognizing the customer's emotions and adjusting the transportation means based on the emotions. This makes it possible to provide the optimal transportation means according to the customer's emotional state, thereby improving the quality of the customer experience.

[0523] "Customer Request" means a request submitted by a Customer to utilize mobility services.

[0524] "Artificial intelligence analysis" is the process of using artificial intelligence techniques to analyze data and extract meaningful information.

[0525] "Video analysis" is a technology that analyzes video data acquired by cameras and other devices and extracts specific information.

[0526] "Transportation services" refers to the transportation and related services provided to customers to travel to their destinations.

[0527] "Payment method" refers to a method or system for paying for the service.

[0528] "Means for recognizing emotions" refers to technology that detects a customer's emotional state from their facial expressions, voice, etc.

[0529] "Means to adjust transportation" refers to technology that selects and provides the optimal transportation means and route based on the customer's emotional state.

[0530] "Uniform identification payment" is a payment method that uses uniform identification information.

[0531] The following system configuration and processing procedure will be described as an embodiment of the present invention.

[0532] System Configuration

[0533] The system consists of the following major components:

[0534] 1. Customer terminal: A device such as a smartphone or tablet through which a customer submits a travel request.

[0535] 2. Server: A central processing unit that accepts customer requests and performs artificial intelligence analysis and video analysis.

[0536] 3. Self-driving vehicles: Vehicles equipped with self-driving technology to transport customers to their destinations.

[0537] Program processing explanation

[0538] Customer terminal

[0539] The customer terminal sends a request for movement via a smartphone application, which then captures a picture of the customer's face with a camera and sends the video data to the server.

[0540] server

[0541] The server performs the following process.

[0542] 1. Artificial intelligence analysis: The received video data is analyzed using the EmotionRecognizer library to recognize the customer's emotions.

[0543] 2. Video analysis: Analyze the customer's facial expressions and voice from video data to detect their emotional state.

[0544] 3. Trip adjustment: Based on the recognized emotion, plan the optimal route using the RoutePlanner library. For example, if the customer is stressed, choose a scenic route and play relaxing music.

[0545] Autonomous vehicles

[0546] The autonomous vehicle operates based on optimal route information sent from the server, and the audio system in the vehicle plays music specified by the server.

[0547] Specific examples

[0548] For example, a customer opens a smartphone app to request a self-driving vehicle. The app uses a camera to capture the customer's face and recognize their emotions. If the app detects that the customer is stressed, the server will select a scenic route and play relaxing music.

[0549] Prompt Sentence Examples

[0550] A customer requests a self-driving vehicle through a smartphone app. The app uses a camera to capture the customer's face and recognize their emotions. If the customer is feeling stressed, the app will select a scenic route and play relaxing music.

[0551] In this way, it is possible to provide the most suitable transportation method according to the customer's emotional state, improving the quality of the customer experience.

[0552] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0553] Step 1:

[0554] The customer device sends a travel request through a smartphone application. The input is the travel request information that the customer enters into the application. The output is the request data that is sent to the server. Specifically, the customer enters their destination and desired means of transportation into the app and presses the send button.

[0555] Step 2:

[0556] The customer device uses a camera to capture a picture of the customer's face and sends the video data to the server. The input is the video of the customer's face captured by the camera. The output is the video data sent to the server. Specifically, the app automatically starts the camera and captures the customer's face.

[0557] Step 3:

[0558] The server analyzes the video data it receives using the EmotionRecognizer library to recognize the customer's emotions. The input is video data of the customer's face. The output is the recognized emotion data. Specifically, the server passes the video data to EmotionRecognizer and obtains the emotion recognition results.

[0559] Step 4:

[0560] The server uses the RoutePlanner library to plan the optimal route based on the emotional data it recognizes. The input is the recognized emotional data and the customer's destination information. The output is the optimal route information. Specifically, the server analyzes the emotional data and, for example, if the customer is feeling stressed, selects a route with a good view.

[0561] Step 5:

[0562] The server sends optimal route information and instructions to play relaxing music to the autonomous vehicle. The input is the optimal route information and music playback instructions. The output is instruction data sent to the autonomous vehicle. Specifically, the server sends the route information and the path to the music file to the vehicle's control system.

[0563] Step 6:

[0564] The autonomous vehicle operates based on optimal route information sent from the server, and the in-car audio system plays the specified music. The input is the route information and music playback instructions received from the server. The output is the driving and music playback until the customer reaches their destination. The specific operation is that the vehicle drives the specified route and plays relaxing music from the in-car speakers.

[0565] Example 2

[0566] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0567] Conventional transportation service systems can provide optimal transportation methods based on customer requests, but they have the problem of not being able to propose routes that take into account the customer's emotional state. This makes it difficult to improve customer satisfaction.

[0568] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting a customer request, means for performing artificial intelligence analysis and video analysis of the accepted customer request, means for utilizing a transportation service based on the results of the artificial intelligence analysis and video analysis, means for settling a trip using the transportation service, means for analyzing customer emotions, and means for adjusting a transportation route based on the customer emotions. This makes it possible to provide the optimal transportation means and route taking into account the emotional state of the customer.

[0569] The "means for accepting customer requests" is an interface for receiving information such as the departure point, destination, and desired means of transportation from the customer.

[0570] "Means for artificial intelligence analysis and video analysis" refers to means for analyzing received customer requests and using artificial intelligence technology and video analysis technology to determine the optimal means of transportation and route.

[0571] "Means for utilizing transportation services" refers to the means of selecting transportation services such as public transportation, taxis, and bicycle sharing based on the analysis results and providing them to customers.

[0572] "Means for paying for travel using a mobile service" refers to means for paying for the use of the selected mobile service.

[0573] "Means for analyzing customer emotions" refers to technology for analyzing the emotional state of a customer, such as using an emotion analysis API.

[0574] The "means for adjusting a travel route based on the customer's emotions" is a means for proposing a more enjoyable or comfortable travel route based on the analyzed emotional state of the customer.

[0575] The "means for proposing the optimal route" is a means for proposing the optimal travel route to the customer's destination.

[0576] "Means using unified identification payment" refers to means for making payments using unified identification information.

[0577] This invention is a system that accepts customer requests, determines the optimal means of transportation using artificial intelligence analysis and video analysis, and further adjusts the travel route based on the customer's emotional state. Specific embodiments of this system are described below.

[0578] System configuration

[0579] Hardware and Software

[0580] The server plays a central role in accepting customer requests, analyzing them, and returning results. It has artificial intelligence and video analysis libraries such as TensorFlow and OpenCV installed.

[0581] A terminal is a device through which a user inputs a request and receives the results, such as a smartphone or a computer.

[0582] The emotion engine is software for analyzing customer emotions, and uses, for example, IBM Watson (registered trademark) emotion analysis API.

[0583] Program processing

[0584] Accepting customer requests

[0585] Users submit requests through a smartphone app or web interface, which include information such as origin, destination, and preferred mode of transportation.

[0586] The terminal receives the user's request and sends it to the server.

[0587] Request content analysis

[0588] The server converts the received request into JSON format and passes it to the artificial intelligence analysis and video analysis means.

[0589] The AI ​​analysis method uses libraries such as TensorFlow and OpenCV to analyze the request content. For example, it obtains the coordinates of the departure and destination and lists possible transportation options.

[0590] Determining the best mode of transportation

[0591] The server receives the analysis results from the AI ​​analysis means and determines the optimal transportation method, such as public transportation, taxi, or bicycle sharing.

[0592] The server prepares the data to return the selected mode of transportation to the user.

[0593] Emotion analysis using an emotion engine

[0594] The server passes the user's emotional data to the emotion engine, including the user's past movement history and current emotional state.

[0595] The emotion engine uses IBM Watson's emotion analysis API to analyze the user's emotions, for example, to determine whether the user is feeling happy.

[0596] Adjusting travel routes

[0597] If the emotion engine recognizes that the user is feeling joy, it will suggest more enjoyable routes, for example, routes that pass through parks and tourist spots.

[0598] The server receives suggestions from the emotion engine and determines the final travel route.

[0599] Returning the results

[0600] The server formats the data to return the final trip and route to the user.

[0601] The device displays the data received from the server to the user, for example, displaying the means of transportation and route on a map on the screen of a smartphone app.

[0602] Specific examples

[0603] The user types "How do I get from Shinjuku to Shibuya?" into a smartphone app and presses the send button.

[0604] The terminal sends this request to the server.

[0605] The server receives the request, converts it into JSON format, and passes it to the AI ​​analysis tool.

[0606] The AI ​​analysis tool obtains the coordinates of the departure and destination and lists possible means of transportation.

[0607] The server receives the analysis results from the AI ​​analysis means and selects "train" as the optimal means of transportation.

[0608] The server prepares the data to return this information to the user.

[0609] The server passes the user's emotional data to the emotion engine, including, for example, the places the user has visited in the past and their current emotional state.

[0610] The emotion engine determines that the user is feeling happy.

[0611] The emotion engine suggests a route that passes through Yoyogi Park because the user feels joy.

[0612] The server receives this proposal and determines the final travel route.

[0613] The server formats the data to return the final trip and route to the user.

[0614] The device displays the data received from the server to the user. For example, a smartphone app screen might show a map showing a route from Shinjuku to Shibuya by train, passing through Yoyogi Park.

[0615] Prompt Sentence Examples

[0616] "Tell me the best way to get from Shinjuku to Shibuya. If it makes users happy, suggest fun routes too."

[0617] In this way, the system provides the optimal means of transportation and route based on the user's request.

[0618] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0619] Step 1:

[0620] Users submit requests through a smartphone app or web interface, which include information such as origin, destination, and preferred mode of transportation.

[0621] Input: User request information (starting point, destination, desired means of transportation)

[0622] Output: Request information is sent to the terminal

[0623] Specific behavior: The user enters information into the app's input form and presses the submit button.

[0624] Step 2:

[0625] The terminal receives the user's request and sends it to the server.

[0626] Input: User request information

[0627] Output: Request information is sent to the server

[0628] Specific operation: The terminal converts the request information into JSON format and sends it to the server as an HTTP request.

[0629] Step 3:

[0630] The server passes the received request to the artificial intelligence analysis and video analysis means.

[0631] Input: Request information sent from the terminal

[0632] Output: Request information passed to the parser

[0633] Specific operation: The server converts the request information into an internal data structure to pass it to the analysis means.

[0634] Step 4:

[0635] The AI ​​analysis tool analyzes the request content and determines the most suitable means of transportation.

[0636] Input: Request information passed from the server

[0637] Output: A list of optimal transportation options

[0638] Specific operation: The AI ​​analysis means uses TensorFlow and OpenCV to obtain the coordinates of the departure and destination and list possible means of transportation.

[0639] Step 5:

[0640] The server receives the analysis results from the AI ​​analysis means and determines the optimal means of transportation.

[0641] Input: Candidate list from AI analysis method

[0642] Output: Determine the best mode of transportation

[0643] Specific operation: The server selects the best mode of transportation from the candidate list and prepares the data to return to the user.

[0644] Step 6:

[0645] The server passes the user's emotion data to the emotion engine.

[0646] Input: User's emotional data (past movement history, current emotional state)

[0647] Output: Emotion data passed to the emotion engine

[0648] Specific operation: The server collects the user's emotion data and sends it to the emotion engine.

[0649] Step 7:

[0650] The emotion engine analyzes the user's emotions.

[0651] Input: Emotion data passed from the server

[0652] Output: User's emotional state (happy, sad, etc.)

[0653] Specific operation: The emotion engine uses the emotion analysis API to analyze the user's emotions.

[0654] Step 8:

[0655] The emotion engine adjusts the travel route based on the user's emotional state.

[0656] Input: User's emotional state

[0657] Output: Adjusted travel route suggestions

[0658] Specific operation: The emotion engine generates a route, for example passing through parks and tourist spots, based on the user's emotional state.

[0659] Step 9:

[0660] The server receives suggestions from the emotion engine and determines the final travel route.

[0661] Input: Adjusted travel route from the emotion engine

[0662] Output: Final travel route determination

[0663] Specific operation: The server determines the final movement route based on suggestions from the emotion engine.

[0664] Step 10:

[0665] The server formats the data to return the final trip and route to the user.

[0666] Input: Final travel route and mode

[0667] Output: Data to return to the user

[0668] Specific operation: The server converts the final means of travel and route into JSON format and sends it to the device.

[0669] Step 11:

[0670] The terminal displays the data received from the server to the user.

[0671] Input: Data sent from the server

[0672] Output: The trip and route displayed to the user

[0673] Specific operation: The device analyzes the data received and displays the means of transportation and route on a map on the smartphone app screen.

[0674] (Application example 2)

[0675] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0676] Conventional transportation suggestion systems did not consider customer emotions when proposing routes, and were unable to sufficiently increase customer satisfaction. Furthermore, they lacked convenience due to insufficient selection of optimal transportation methods and insufficient integration of payment methods. This made it difficult to respond to diverse customer needs.

[0677] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0678] In this invention, the server includes means for accepting customer requests, means for performing AI analysis / video analysis of the accepted customer requests, means for utilizing MaaS based on the results of the AI ​​analysis / video analysis, means for paying for travel using MaaS, and means for analyzing customer emotions and adjusting travel routes based on the emotions. This makes it possible to propose optimal means of travel and routes that take customer emotions into consideration, thereby increasing customer satisfaction.

[0679] "Customer Request" refers to a request or wish that a customer enters into the system.

[0680] "AI analysis" refers to the technology of using artificial intelligence to analyze data and extract meaning and patterns.

[0681] "Video analysis" refers to the technology of analyzing video data and extracting information.

[0682] "MaaS" stands for Mobility as a Service and refers to a service that integrates multiple means of transportation.

[0683] "Payment method" refers to the method or system for paying the service fee.

[0684] "Means for analyzing emotions" refers to technology that analyzes customer emotions and determines their state.

[0685] "Means for adjusting travel routes" refers to technology that suggests optimal travel routes based on customer sentiment and other factors.

[0686] The "optimal route" refers to the most efficient and satisfying route to a customer's destination.

[0687] "Electronic payment" refers to a payment method that uses the Internet or electronic devices.

[0688] A system for implementing this invention includes means for accepting customer requests, means for performing AI analysis / video analysis of the accepted customer requests, means for utilizing MaaS based on the results of the AI ​​analysis / video analysis, means for paying for travel using MaaS, and means for analyzing customer emotions and adjusting travel routes based on the emotions.

[0689] Explanation of program processing

[0690] 1. Accepting Customer Requests:

[0691] The server receives requests from customers via a smartphone application, which includes information such as the destination and desired arrival time.

[0692] 2. AI analysis / video analysis:

[0693] The server analyzes the received request using AI analysis / video analysis methods. Specifically, it analyzes the request content using natural language processing technology to determine the travel distance and type of destination. This analysis is performed using software such as Python and TensorFlow.

[0694] 3. Utilizing MaaS:

[0695] The server determines the optimal means of transportation based on the results of AI analysis and video analysis. For example, it selects bicycle sharing for short distances, public transportation for medium distances, and a taxi for long distances. This selection is made using the MaaS platform's API.

[0696] 4. Payment Methods:

[0697] The server then processes the payment for the selected transportation option, completing the payment via the customer's credit card details or electronic wallet using an electronic payment gateway such as Stripe or PayPal.

[0698] 5. Sentiment analysis and route adjustment:

[0699] The server analyzes the customer's facial expressions and tone of voice using the smartphone's camera and microphone to analyze their emotions. Software such as OpenCV and Emotion API is used for emotion analysis. Based on the analysis results, the server suggests a scenic route if the customer is happy, or a quiet route if they want to relax.

[0700] Specific examples

[0701] For example, if the user requests "I want to go to the city center" and the emotion is "joy", the server will do the following:

[0702] 1. Analyze the request and determine that a trip to the city center is required.

[0703] 2. Determine that the trip is a medium distance and choose public transportation.

[0704] 3. Suggest scenic routes because users love them.

[0705] Prompt Sentence Examples

[0706] "If the user requests 'I want to go to the city center' and the emotion is 'joy', generate a Python program that suggests the best mode of transportation and route."

[0707] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0708] Step 1:

[0709] The server accepts requests from users through a smartphone application. As input, the user provides information such as the destination and desired arrival time. As output, this information is sent to the server. Specifically, the user enters the destination into the application and presses the send button.

[0710] Step 2:

[0711] The server analyzes the received request using AI analysis / video analysis methods. The user's request information is used as input. For data processing, natural language processing technology is used to analyze the request content and determine the travel distance and type of destination. The analysis results are obtained as output. Specifically, the request content is analyzed using Python and TensorFlow.

[0712] Step 3:

[0713] The server determines the optimal means of transportation based on the results of AI analysis / video analysis. The analysis results are used as input. Data calculations involve selecting bicycle sharing for short distances, public transportation for medium distances, and taxis for long distances, depending on the distance traveled and the type of destination. The selected means of transportation is obtained as output. The specific operation involves selecting the means of transportation using the MaaS platform's API.

[0714] Step 4:

[0715] The server processes the payment for the selected mode of transport. As input, the selected mode of transport and the user's payment information are used. As a data operation, the payment is completed using an electronic payment method. As an output, a confirmation of the completion of the payment is obtained. As a specific operation, the payment is processed using a payment gateway such as Stripe or PayPal.

[0716] Step 5:

[0717] To analyze the user's emotions, the server uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice. The user's facial expression and voice data are used as input. OpenCV and Emotion API are used to process the data and analyze emotions. The analyzed emotional information is obtained as output. Specifically, the system works by capturing a photo of the user's facial expression with the smartphone camera and analyzing it.

[0718] Step 6:

[0719] The server adjusts the travel route based on the analyzed emotion information. The emotion information and destination information are used as input. The data calculation suggests a scenic route if the user is happy, or a quiet route if the user wants to relax. The output is the adjusted travel route. The specific operation is to use a route suggestion algorithm to calculate the optimal route.

[0720] Example 3

[0721] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0722] Conventional mobility service systems did not propose transportation methods or routes that took into account the customer's emotional state, which prevented them from fully increasing customer satisfaction. Furthermore, they lacked the ability to readjust transportation methods and routes in real time if the customer's emotions changed during the trip, making it difficult to provide a comfortable transportation experience for customers. Furthermore, payment methods were not standardized, requiring the use of multiple payment methods, which reduced convenience.

[0723] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0724] In this invention, the server includes means for accepting customer requests, means for performing artificial intelligence analysis / video analysis of the accepted customer requests, means for utilizing transportation services based on the results of the artificial intelligence analysis / video analysis, means for paying for transportation using the transportation services, means for recognizing customer emotions in real time and adjusting the transportation method and route, and means for readjusting the transportation method and route if the customer's emotions change during the trip. This makes it possible to propose the optimal transportation method and route based on the customer's emotional state, and to provide a comfortable transportation experience that responds to emotional changes during the trip. In addition, the use of unified authentication payment also improves payment convenience.

[0725] "Customer Request" means a request made by a Customer to the System to use a mobility service.

[0726] "Artificial intelligence analysis" refers to the process of using machine learning and data analysis techniques to analyze input data and extract meaningful information.

[0727] "Video analytics" refers to the technology of analyzing video data obtained from cameras and other image capture devices and extracting specific information.

[0728] "Transportation service" refers to a service that provides transportation of a customer's choice and enables the customer to travel to their destination.

[0729] "Payment method" refers to a method or system for customers to pay for the services they use.

[0730] "Emotion recognition" refers to technology that analyzes data such as a customer's facial expressions and voice to identify their emotional state.

[0731] "Transportation" refers to the means of transportation used by the Customer to travel to their destination.

[0732] "Route adjustment" refers to the process of calculating and suggesting the optimal route to a customer's destination.

[0733] "Real-time" refers to data acquisition and processing occurring immediately.

[0734] "Unified authentication payment" refers to a method of integrating multiple payment methods into a single authentication system to make payments easier.

[0735] MODE FOR CARRYING OUT THE INVENTION

[0736] This invention is a system that accepts customer requests, performs artificial intelligence analysis and video analysis, provides transportation services based on the results, and further recognizes customer emotions in real time to adjust transportation methods and routes. Specific embodiments of this system are described below.

[0737] Hardware and software used

[0738] 1. Server

[0739] It uses servers with high-performance data processing capabilities, which handle key processes such as accepting customer requests, AI analysis, video analysis, providing mobility services, payment processing, emotion recognition, and route adjustment.

[0740] The software used may include artificial intelligence models (e.g., machine learning algorithms), video analytics software, payment systems (e.g., unified authentication payment systems), and emotion recognition engines.

[0741] 2. Terminal

[0742] This refers to devices such as smartphones and PCs used by customers. The devices input customer requests, communicate with the server, capture and send emotional data, and display suggested transportation methods and routes.

[0743] The software used includes dedicated applications, camera and microphone control software, and communication modules.

[0744] 3. Users

[0745] This refers to customers who use transportation services. Users operate a terminal to input requests and receive suggestions for transportation methods and routes.

[0746] Data processing and calculation

[0747] 1. Acceptance of Customer Requests

[0748] A user uses a terminal to access a dedicated application and input a request for a transportation service, including information such as the origin, destination, and desired mode of transportation.

[0749] The terminal transmits the input request information to the server.

[0750] 2. Artificial intelligence and video analysis

[0751] Based on the received request information, the server uses an artificial intelligence model to calculate the optimal means of transportation and route.

[0752] The server uses video analytics software to analyze the video data sent from the terminal to identify the customer's emotional state.

[0753] 3. Provision of transportation services

[0754] The server identifies the optimal means of transportation and route and transmits the necessary information to the transportation service provider to provide the transportation service.

[0755] For example, if a taxi is selected, the server searches for the nearest taxi and sends a pickup request.

[0756] 4. Payment Processing

[0757] The server calculates the cost of the mobile service and automatically debits the customer's account using a unified authentication and payment system.

[0758] 5. Emotion recognition and route adjustment

[0759] The server uses an emotion recognition engine to analyze the customer's facial and voice data sent from the device and identify their emotional state in real time.

[0760] The server suggests the optimal means of transportation and route based on the customer's emotional state, and makes readjustments if necessary.

[0761] Specific examples

[0762] When the user selects a taxi and wishes to travel to the destination, the terminal transmits the information to the server.

[0763] The server calls the taxi company's API, searches for the nearest taxi, and calls it.

[0764] The server debits the user's account using a unified authentication and payment system.

[0765] The server activates an emotion engine and recognizes emotions by analyzing the user's facial expressions and voice data sent from the terminal.

[0766] If the server recognizes that the user is feeling angry, it will suggest the shortest route to avoid congestion and the fastest way to travel that route.

[0767] If the user begins to feel bored during the journey, the server will re-suggest a means of transportation that allows for enjoyment of music and video, or a visually appealing route.

[0768] Prompt Sentence Examples

[0769] If the user selects a taxi, how does the system call the nearest taxi and take them to their destination?

[0770] "Please explain in detail how the emotion engine recognizes the user's emotions in real time and adjusts the mode of travel and route."

[0771] "Please explain the procedure for debiting the user's account using the unified authentication and payment system." The flow of the specific process in the third embodiment will be explained with reference to FIG.

[0772] Step 1:

[0773] The user accesses a dedicated application using a device such as a smartphone or PC. The user selects the desired means of transportation (e.g., taxi) from a list of transportation services provided within the application and enters the departure point and destination. The device then sends the entered request information to the server. The input data is the departure point, destination, and desired means of transportation, and the output data is the request information sent to the server.

[0774] Step 2:

[0775] The server uses an artificial intelligence model to calculate the optimal means of transportation and route based on the received request information. The input data is the user's request information, and the output data is information on the optimal means of transportation and route. Specifically, the server analyzes the user's current location information and destination information, and calls the taxi company's API to search for the nearest taxi. The server identifies the nearest taxi and sends the user's pickup request to that taxi.

[0776] Step 3:

[0777] The server calculates the fee for the transportation service and automatically deducts it from the customer's account using a unified authentication payment system. The input data is the transportation service usage information and data for fee calculation, and the output data is a notification of payment completion. Specifically, the server calculates the fee based on the travel distance and time, and deducts the fee from the user's account through the unified authentication payment system. The server then sends a notification of payment completion to the user's terminal.

[0778] Step 4:

[0779] The server activates the emotion engine and recognizes the user's emotions in real time. The input data is the user's facial expression and voice data sent from the device, and the output data is the analyzed emotional state. Specifically, the device uses a camera and microphone to capture the user's facial expression and voice and sends the data to the server. The server analyzes the received data and identifies the user's emotional state.

[0780] Step 5:

[0781] The server proposes the optimal means of transportation and route based on the user's emotional state. The input data is the analyzed emotional state and current means of transportation and route information, and the output data is a proposal of an adjusted means of transportation and route. Specifically, if the server recognizes that the user is feeling angry, it proposes the shortest route to avoid congestion and the fastest way to travel that route. The server notifies the user's device of the proposal.

[0782] Step 6:

[0783] The server continuously monitors the user's emotions while traveling. The input data is continuous emotional data sent from the device, and the output data is a readjusted transportation method and route proposal. Specifically, the device continuously sends the user's emotional data to the server using a camera and microphone. If the user's emotions change, the server readjusts the transportation method and route accordingly. For example, if the user begins to feel bored, the server will suggest transportation methods that include music and video, or a visually appealing route. The server notifies the user's device of the readjusted proposal.

[0784] (Application example 3)

[0785] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0786] Conventional mobility service systems have difficulty responding flexibly to customer emotions and situations, often resulting in stress and dissatisfaction. Another issue is the inability to respond appropriately when a customer's emotions change during a trip. Furthermore, limited payment methods mean low convenience.

[0787] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0788] In this invention, the server includes means for accepting customer requests, means for performing artificial intelligence analysis / video analysis of the accepted customer requests, means for utilizing transportation services based on the results of the artificial intelligence analysis / video analysis, means for paying for transportation using the transportation services, means for recognizing customer emotions and adjusting the transportation method and route based on the emotions, and means for readjusting the transportation method and route if the customer's emotions change. This enables flexible responses according to the customer's emotions and circumstances, reducing stress and dissatisfaction. Furthermore, appropriate responses can be made even if the customer's emotions change during transportation, improving convenience.

[0789] "Customer Request" means any request or request submitted by a Customer when using the Mobility Services.

[0790] "Artificial intelligence analysis" is the process of using artificial intelligence techniques to analyze data and extract meaningful information.

[0791] "Video analysis" is a technology that analyzes video data from cameras and other sources and extracts specific information.

[0792] "Transportation services" refers to transportation means and services provided to customers to travel to their destinations.

[0793] "Payment method" refers to a method or system for paying for the service.

[0794] "Means of recognizing emotions" refers to technologies and systems that can determine emotions from customers' facial expressions, voice, etc.

[0795] "Means for adjusting transportation methods and routes based on emotions" refers to technologies and systems that select the optimal transportation method and route based on the customer's emotional state.

[0796] "Means for readjusting transportation methods and routes when emotions change" refers to technologies and systems that reselect transportation methods and routes in response to changes in a customer's emotions during travel.

[0797] "Uniform identification payment" refers to a payment method that uses uniform identification information.

[0798] The following system configuration and processing procedure will be described as an embodiment of the present invention.

[0799] System Configuration

[0800] The system consists of the following major components:

[0801] 1. Customer request acceptance means: Customer travel requests are accepted using a smartphone application.

[0802] 2. Artificial intelligence analysis / video analysis method: Using the smartphone camera and sensors, the customer's facial expressions and voice are analyzed to recognize emotions.

[0803] 3. Transportation service utilization: Call the nearest autonomous vehicle to transport the customer to their destination.

[0804] 4. Payment method: The usage fee will be automatically deducted using a unified identification payment system.

[0805] 5. Emotion recognition: Recognize customer emotions in real time and adjust transportation methods and routes based on emotions.

[0806] 6. Readjustment: Readjust the mode of travel or route if the customer's emotions change during the journey.

[0807] Hardware and software used

[0808] Hardware: Smartphone (camera, microphone, GPS sensor)

[0809] Software: OpenCV (video analysis), EmotionRecognizer (emotion recognition), MaaSService (mobility service provision), ONEIDPayment (payment processing)

[0810] Data processing and calculation

[0811] 1. Accepting customer request: The smartphone application accepts the customer's request for transportation.

[0812] 2. Video analysis and emotion recognition: Using the smartphone camera and microphone, the customer's facial expressions and voice are analyzed in real time to recognize their emotions.

[0813] 3. Trip and route adjustment: Select the optimal trip and route based on the recognized emotion. For example, if the customer is angry, suggest the shortest route to avoid congestion.

[0814] 4. Providing transportation services: Calling the nearest autonomous vehicle to take customers to their destination.

[0815] 5. Payment processing: The usage fee will be automatically deducted using a unified identification payment system.

[0816] 6. Readjustment in response to emotional changes: If a customer's emotions change during the journey, re-acknowledge the emotion and readjust the mode of travel or route accordingly.

[0817] Specific examples

[0818] For example, if a user calls a taxi through a smartphone application, the application can analyze the user's facial expressions and voice and determine that the user is angry. In this case, the system will suggest the shortest route to avoid congestion and call the nearest self-driving vehicle. If the user begins to feel bored during the trip, the system will suggest transportation options that include music and video, or routes that are visually appealing.

[0819] Prompt Sentence Examples

[0820] "Develop a smartphone app that suggests optimal modes of transport and routes based on the user's emotions. If the user is angry, suggest the shortest route to avoid congestion. If the user is bored, suggest modes of transport and routes that are more entertaining."

[0821] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0822] Step 1:

[0823] Accepting customer requests

[0824] The device (smartphone application) accepts a travel request from the user. As input, the user enters their destination and desired mode of transportation into the application. As output, the accepted request information is sent to the server. In concrete terms, the user operates the application interface to select their destination and mode of transportation.

[0825] Step 2:

[0826] Video analysis and emotion recognition

[0827] The device (smartphone) uses a camera and microphone to capture the user's facial expressions and voice in real time. Camera video and audio data are acquired as input. Emotion recognition results are obtained as output. Specifically, the device performs video analysis using OpenCV and recognizes emotions using EmotionRecognizer.

[0828] Step 3:

[0829] Coordinating transportation and routes

[0830] The server selects the optimal means of transportation and route based on the recognized emotion. The emotion recognition results and user request information are sent to the server as input. The optimal means of transportation and route information are determined as output. Specifically, the server uses the MaaSService to suggest the shortest route to avoid congestion if the user is feeling angry, for example.

[0831] Step 4:

[0832] Providing transportation services

[0833] The server calls the nearest autonomous vehicle and arranges for it to transport the user to their destination. The determined transportation method and route information are used as input. The output is that the transportation arrangement has been completed and the user is notified. Specifically, the server sends a request to the autonomous vehicle system, and the vehicle heads to the user's location.

[0834] Step 5:

[0835] Payment Processing

[0836] The server automatically deducts the usage fee using the unified identity payment system. The input is the usage fee information for the mobile service. The output is that the payment has been completed and the user is notified. Specifically, the server deducts the fee from the user's account using ONEIDPayment.

[0837] Step 6:

[0838] Recalibrating as emotions change

[0839] If the user's emotions change while traveling, the device will recognize the emotions again and readjust the means of transportation and route accordingly. Camera footage and audio data from the journey are acquired as input. The readjusted means of transportation and route information are determined as output. Specifically, the device will recognize the emotions again using OpenCV and EmotionRecognizer, and the server will use the MaaSService to suggest new means of transportation and routes.

[0840] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0841] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0842] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[0843] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0844] [Second embodiment]

[0845] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0846] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0847] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0848] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0849] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0850] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0851] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0852] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0853] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0854] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0855] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0856] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0857] "Example 1"

[0858] According to an embodiment of the present invention, there is provided a transportation service platform system, which includes a means for receiving requests from customers, for example, customers can send transportation requests through a smartphone application.

[0859] "Example 2"

[0860] The received request is processed by AI / video analytics, which analyzes the request and determines the optimal means of transportation. For example, based on the request, it can select public transportation, taxis, bike sharing, or other MaaS services.

[0861] "Example 3"

[0862] Based on the results of AI analysis / video analysis, a means of utilizing MaaS is provided. This means provides the selected MaaS service to the customer and realizes transportation. For example, if the customer selects a taxi, the system calls the nearest taxi and transports the customer to their destination. "Example 4"

[0863] Finally, a means of payment for MaaS journeys is provided, which allows customers to pay for the MaaS services they use, for example by automatically debiting the customer's account using the ONEID payment system.

[0864] The processing flow of each embodiment will be described below.

[0865] "Example 1"

[0866] Step 1: A customer accesses the transportation service platform system and submits a transportation request, which includes information such as the origin, destination, and desired departure time.

[0867] Step 2: The system sends the received request to the AI ​​analysis / video analysis means.

[0868] "Example 2"

[0869] Step 1: AI analytics / video analytics analyzes the request and determines the optimal mode of transportation, taking into account current traffic conditions, weather, and the customer's past usage history.

[0870] Step 2: Based on the analysis results, the optimal MaaS service is selected and notified to the customer. "Example 3"

[0871] Step 1: If the customer accepts the proposed MaaS service, the system will provide the service. For example, if a taxi is selected, the system will call the nearest taxi and take the customer to their destination.

[0872] Step 2: Once the customer arrives at their destination, the system confirms the trip is complete.

[0873] "Example 4"

[0874] Step 1: Once the transfer is complete, the system accepts payment from the customer.

[0875] Step 2: The customer pays through the ONEID payment system, which confirms the payment is complete and provides the customer with a receipt.

[0876] Example 1

[0877] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0878] Conventional mobility service platform systems have difficulty quickly and accurately proposing the optimal means of transportation in response to customer requests. Furthermore, there was a lack of standardized payment methods for the proposed means of transportation, which resulted in poor customer convenience. Furthermore, the lack of advanced analysis using AI models meant that the accuracy of the proposals was low.

[0879] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0880] In this invention, the server includes means for accepting customer requests, means for storing the accepted customer requests in a database, means for executing an algorithm for selecting the optimal means of transportation based on the stored requests, means for sending a prompt message to the generative AI model to obtain the optimal means of transportation, means for responding to the customer with the obtained means of transportation, and means for paying for transportation based on the proposed means of transportation. This makes it possible to quickly and accurately propose the optimal means of transportation in response to a customer request and provide a unified payment method.

[0881] The "means for accepting customer requests" is a function that provides an interface for customers to input their departure and destination points to use transportation services and transmit that information to the system.

[0882] The "means for storing received customer requests in a database" is a function for storing request information received from a customer in a database and making it available for subsequent processing.

[0883] "Means for executing an algorithm to select the most suitable means of transportation based on the stored requests" refers to a function that analyzes the request information stored in the database and performs calculations to select the most suitable means of transportation.

[0884] "Means for sending prompts to a generative AI model and obtaining the optimal means of transportation" refers to a function that sends prompts containing specific questions or instructions to a generative AI model and receives suggestions for the optimal means of transportation in response.

[0885] "Means of responding to customers about the acquired transportation method" is a function that notifies customers of the optimal transportation method information acquired from the generative AI model.

[0886] The "means for settling travel based on proposed means of transportation" is a function for carrying out a payment process for the customer to pay for the travel service based on the proposed means of transportation.

[0887] A "unified payment system" is a system that centrally manages multiple payment methods and allows customers to complete payments using any payment method they choose.

[0888] This invention relates to a mobility service platform system that accepts customer requests, proposes optimal means of transportation, and processes payments. This system is composed of a server, terminals, and user elements.

[0889] The server provides an API for accepting customer requests. This API is built using Python and Flask, and has the ability to store received requests in a MySQL database. The server then runs an algorithm to select the optimal transportation mode based on the stored requests. This algorithm is implemented in Python and uses a generative AI model (e.g., a generative AI model) to suggest the optimal transportation mode.

[0890] The terminal provides an interface for customers to submit travel requests. Specifically, it uses a smartphone application developed with React Native. Users input their departure and destination points through this application and submit their requests. The terminal then sends the input information to the server as an HTTP request.

[0891] A user submits a trip request using a smartphone application. After the user enters their origin and destination and presses the send button, the application sends this information to a server. The server receives the request and stores it in a database. The server then runs an algorithm to select the optimal mode of transportation based on the stored request. The algorithm uses a generative AI model to suggest the optimal mode of transportation to the user.

[0892] For example, consider the case where a user uses a smartphone application to send a "travel request from Shinjuku Station to Shibuya Station." When the user enters "Shinjuku Station" as the departure point and "Shibuya Station" as the destination and presses the send button, the application sends this information to a server. The server receives this request and stores it in a database. The server then runs an algorithm to select the optimal mode of transportation based on the stored request. This algorithm uses a generative AI model to make a suggestion to the user, such as "Traveling by train is the best option."

[0893] Examples of prompts to input to a generative AI model might include:

[0894] "A user has requested a trip from Shinjuku Station to Shibuya Station. Please suggest the best means of transportation."

[0895] By inputting this prompt into the generative AI model, the model will suggest the optimal means of transportation. For example, it may give an answer such as, "Traveling by train is best. The journey will take about 10 minutes." The server receives this response and sends it back to the user. The user can then confirm the suggested means of transportation through the application and actually begin traveling.

[0896] In this way, the mobility service platform system can propose the most suitable means of transportation for a user's mobility request and provide a unified payment method.

[0897] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0898] Step 1:

[0899] The user launches the smartphone application.

[0900] Input: User actions

[0901] Output: Application launch

[0902] Specific operation: The user taps the smartphone icon to launch the application. The application is developed with React Native and the initial screen is displayed.

[0903] Step 2:

[0904] The user enters the origin and destination and submits a travel request.

[0905] Input: Origin and destination information

[0906] Output: Move request sent

[0907] Specific operation: The user enters "Shinjuku Station" as the departure point and "Shibuya Station" as the destination in the application interface and presses the send button.

[0908] Step 3:

[0909] The device sends a request to the server.

[0910] Input: User-entered origin and destination information

[0911] Output: HTTP request to the server

[0912] Specific operation: The device sends the input information to the server as an HTTP request. This communication uses the HTTPS protocol.

[0913] Step 4:

[0914] The server receives the request and stores it in a database.

[0915] Input: HTTP request from the terminal

[0916] Output: Save to database

[0917] Specific operation: The server receives requests through an API built using Flask and saves a "travel request from Shinjuku Station to Shibuya Station" in a MySQL database.

[0918] Step 5:

[0919] The server runs an algorithm based on the stored requests to select the most suitable mode of transportation.

[0920] Input: Request information stored in the database

[0921] Output: Selection of optimal transportation mode

[0922] Specific operation: The server runs an algorithm implemented in Python and selects the optimal means of transportation, taking into account past data and current traffic conditions.

[0923] Step 6:

[0924] The server sends a prompt to the generative AI model to obtain the optimal means of transportation.

[0925] Input: Prompt text (e.g., "The user requests to travel from Shinjuku Station to Shibuya Station. Please suggest the best mode of transportation.")

[0926] Output: The response from the generative AI model

[0927] Specific operation: The server sends a prompt to the generative AI model and receives a response from the model such as, "Traveling by train is best. The journey takes about 10 minutes."

[0928] Step 7:

[0929] The server returns the acquired means of transportation to the user.

[0930] Input: Response from a generative AI model

[0931] Output: Reply to the user

[0932] Specific operation: The server receives the response from the generative AI model and notifies the user of the content. The user then confirms the proposed transportation method through the application.

[0933] Step 8:

[0934] The user confirms the proposed transportation options.

[0935] Input: Response from the server

[0936] Output: Check transportation method

[0937] Specific operation: The user confirms the proposed means of transportation through the application and actually starts traveling.

[0938] (Application example 1)

[0939] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0940] Conventional mobility service platform systems have had the problem of making it difficult to quickly and efficiently summon the most suitable autonomous vehicle when a customer submits a travel request. Furthermore, they lack the functionality to accurately input the customer's current location and destination and suggest the optimal route, which reduces the efficiency of travel.

[0941] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0942] In this invention, the server includes means for accepting customer requests, means for performing AI analysis / video analysis of the accepted customer requests, means for utilizing transportation services based on the results of the AI ​​analysis / video analysis, means for paying for transportation using the transportation services, means for inputting the customer's current location and destination, and means for calling the optimal self-driving vehicle, thereby enabling customers to quickly and efficiently call an autonomous vehicle using their smartphone and reach their destination via the optimal route.

[0943] "Customer Request" means a request submitted by a Customer to utilize the Mobility Services.

[0944] "AI analytics" is the process of using artificial intelligence to analyze data and extract meaningful information.

[0945] "Video analysis" is a technology that analyzes video data obtained from cameras and sensors and extracts specific information.

[0946] "Transportation services" refers to transportation means and services provided to customers to travel to their destinations.

[0947] "Payment method" refers to a method or system for paying for the service.

[0948] "Current location" refers to the location where the customer is currently located.

[0949] A "destination" is where a customer wants to go.

[0950] An "autonomous vehicle" is a vehicle that is driven automatically using artificial intelligence and sensors.

[0951] An "optimal route" is the most efficient route from a departure point to a destination, taking into account factors such as time, distance, and traffic conditions.

[0952] "Unified authentication and payment" refers to an authentication and payment system that can be used across multiple services and platforms.

[0953] A system for implementing this invention is configured as follows: First, a user sends a travel request using a smartphone. A dedicated application is installed on the smartphone, and the user can input their current location and destination through this application.

[0954] When the server receives a request from a user, it performs AI analysis and video analysis of the request. Software such as Python and TensorFlow is used for AI analysis, and libraries such as OpenCV are used for video analysis. This allows the server to analyze data such as the user's current location, destination, and traffic conditions, and select the optimal autonomous vehicle.

[0955] Next, the server will call the most suitable self-driving vehicle based on the analysis results. The self-driving vehicle is equipped with GPS and various sensors, and collects data in real time to drive the optimal route to the destination.

[0956] After the transfer is complete, the server settles the transfer service fee. The payment method is a unified authentication payment system. This allows users to use multiple services with a single authentication, improving convenience.

[0957] As a concrete example, consider the case where a user requests an autonomous taxi from Tokyo Station to Tokyo Tower. The user opens a smartphone app and enters the latitude and longitude of Tokyo Station (35.6895, 139.6917) as their current location and the latitude and longitude of Tokyo Tower (35.6586, 139.7454) as their destination. The server receives this information, selects the most suitable autonomous vehicle, and dispatches it to the user.

[0958] An example of a prompt is as follows:

[0959] Consider a scenario where a user requests a self-driving taxi using a smartphone app. The user enters their current location and destination and calls the best available self-driving taxi. Write a Python program to send a request to the taxi service using an API key and receive the response.

[0960] In this way, users can quickly and efficiently summon an autonomous vehicle using their smartphone to reach their destination along the optimal route.

[0961] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0962] Step 1:

[0963] The user starts the smartphone app and inputs their current location and destination. The input data of the current location and destination is sent to the application as latitude and longitude information, which generates a travel request for the user.

[0964] Step 2:

[0965] The device sends the user's travel request to the server. The server analyzes the received request and obtains the latitude and longitude information of the current location and destination. Based on this information, the travel request processing begins.

[0966] Step 3:

[0967] The server then performs AI and video analysis on the received latitude and longitude information, using TensorFlow for the AI ​​analysis and OpenCV for the video analysis. This allows the server to analyze data such as traffic and road conditions and calculate the optimal route.

[0968] Step 4:

[0969] The server selects the most suitable autonomous vehicle based on the results of AI analysis and video analysis. Information about the selected autonomous vehicle is then sent from the server to the device, allowing the user to know which vehicle will respond to their request.

[0970] Step 5:

[0971] The terminal displays the information about the autonomous vehicle received from the server to the user. The user confirms the displayed information and confirms the request. This confirmation information is then sent back to the server.

[0972] Step 6:

[0973] The server receives the user's request confirmation and issues instructions to the self-driving vehicle. The self-driving vehicle uses GPS and various sensors to head to the user's current location. This allows the self-driving vehicle to be dispatched to the user's location.

[0974] Step 7:

[0975] When the autonomous vehicle arrives at the user's current location, the user gets in the vehicle and starts traveling toward the destination. The vehicle travels according to the optimal route provided by the server.

[0976] Step 8:

[0977] Once the transfer is complete, the server calculates the transfer service fee and charges the fee via the payment method. The payment is made using a unified authentication payment system, which allows the user to pay the fee with a single authentication.

[0978] Step 9:

[0979] The server notifies the terminal that the payment has been completed. The terminal then displays a notification of the payment completion to the user, allowing the user to confirm that the use of the mobile service has been completed.

[0980] Example 2

[0981] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0982] Conventional transportation suggestion systems have difficulty quickly and accurately suggesting the optimal transportation method in response to a user's request. Furthermore, when using multiple transportation methods in an integrated manner, payment methods are complicated, reducing user convenience.

[0983] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0984] In this invention, the server includes means for accepting customer requests, means for performing AI analysis / video analysis of the accepted customer requests, means for determining a means of transportation based on the results of the AI ​​analysis / video analysis, means for providing information on the determined means of transportation to the customer, and means for paying for the use of the means of transportation. This makes it possible to quickly and accurately propose the most suitable means of transportation in response to a user's request and to simplify payment methods when using multiple means of transportation in an integrated manner.

[0985] The "means for accepting customer requests" is an interface for receiving requests and information regarding travel from users.

[0986] "AI analysis / video analysis means" is a system that uses artificial intelligence and video analysis technology to analyze received customer requests and identify the optimal means of transportation.

[0987] "Means for determining the means of transportation" refers to the algorithms and processes for selecting the most suitable means of transportation for the user based on the results of AI analysis / video analysis.

[0988] The "means for providing the customer with information about the selected transportation means" refers to an interface or communication means for notifying the user of detailed information about the selected transportation means.

[0989] The "means for paying for the use of transportation" refers to a payment system that allows a user to pay the fee when using the selected transportation.

[0990] An "integrated payment system" is a payment platform for processing fees for multiple means of transportation in one go.

[0991] MODE FOR CARRYING OUT THE INVENTION

[0992] The present invention is a system for making optimal suggestions when a user selects a means of transportation and for easily paying for the use of that means of transportation. Specific embodiments of this system are described below.

[0993] System configuration

[0994] The system consists of the following major components:

[0995] 1. How we receive customer requests

[0996] Users use devices such as smartphones or PCs to input travel requests, such as "I want the fastest way from Shinjuku to Shibuya."

[0997] 2. AI analysis / video analysis methods

[0998] The server passes the received customer request to an AI analytics / video analysis method, which analyzes the request content using a machine learning model implemented in Python (e.g., TensorFlow or PyTorch).

[0999] 3. How to decide on transportation

[1000] AI analytics / video analytics analyzes the request content and identifies the transportation method that best suits the user's needs. For example, it references public transportation timetable databases (e.g., GTFS data) to calculate the optimal train or bus route. It also uses APIs for taxi and bike-sharing services (e.g., taxi API and bike-sharing API) to obtain real-time availability and fare information.

[1001] 4. Means of providing customers with information about their chosen transportation options

[1002] The server then sends information about the selected transportation method to the terminal, including the specific route, travel time, and fare.

[1003] 5. Means of payment for transportation

[1004] The server provides a payment system for the user to pay for the transportation means selected by the user, which uses an integrated payment system to process the fees for multiple transportation means in a single transaction.

[1005] Specific examples

[1006] For example, if a user requests "the fastest way to get from Shinjuku to Shibuya," the process proceeds as follows:

[1007] 1. The user types "I want to travel from Shinjuku to Shibuya the fastest" into their smartphone and presses the send button.

[1008] 2. The device sends this request to the server.

[1009] 3. The server receives the request and passes it to the AI ​​analysis / video analysis method.

[1010] 4. AI analytics / video analytics analyzes the request and identifies the best means of transportation, for example, by consulting train timetables and calculating the optimal route.

[1011] 5. Based on the analysis results, the server determines which train is the fastest and determines the route information.

[1012] 6. The server sends the determined route information to the terminal.

[1013] 7. The device displays to the user, "The best route from Shinjuku to Shibuya is the 15:10 train."

[1014] 8. The user selects a means of transportation based on the displayed information and begins traveling.

[1015] 9. The server uses an integrated payment system to process the user's transportation fees in one lump sum.

[1016] Prompt Sentence Examples

[1017] "I want to get from Shinjuku to Shibuya as quickly as possible. It's currently 3:00 PM. What is the best way to get there?"

[1018] By inputting this prompt into a generative AI model, the system suggests the most optimal means of transportation for the user.

[1019] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1020] Step 1:

[1021] The user submits a request.

[1022] A user uses a device such as a smartphone or PC to input a travel request and press the send button. The input includes information such as the current location, destination, and desired mode of transportation. The output is the request data sent from the device to the server.

[1023] Step 2:

[1024] The device sends a request to the server.

[1025] The terminal sends the request entered by the user to the server as an HTTP request. The input is the request data entered by the user, and the output is the request data sent to the server.

[1026] Step 3:

[1027] The server receives the request and passes it to the AI ​​analysis / video analysis means.

[1028] The server passes the request received from the terminal to the AI ​​analysis / video analysis means for analysis. The input is the request data received from the terminal, and the output is the request data passed to the AI ​​analysis / video analysis means.

[1029] Step 4:

[1030] AI analysis / video analysis tools analyze the request.

[1031] The AI ​​analysis / video analysis method analyzes the content of the request using a machine learning model implemented in Python (e.g., TensorFlow or PyTorch). The input is the request data passed from the server, and the output is the analysis results. Specifically, it analyzes the content of the request and identifies the transportation method that best suits the user's needs.

[1032] Step 5:

[1033] The server determines the optimal means of transportation based on the analysis results.

[1034] The server receives the analysis results from the AI ​​analysis / video analysis means and determines the optimal means of transportation for the user. The input is the analysis results from the AI ​​analysis / video analysis means, and the output is information on the determined means of transportation. Specifically, it refers to a public transportation timetable database (e.g., GTFS data) to calculate the optimal train or bus route. It also uses the APIs of taxi and bicycle sharing services (e.g., taxi API and bicycle sharing API) to obtain real-time availability and fare information.

[1035] Step 6:

[1036] The server transmits information about the determined means of transportation to the terminal.

[1037] The server sends information about the selected transportation mode to the terminal. The input is the information about the selected transportation mode, and the output is the information about the transportation mode sent to the terminal. Specific operations include information about the specific route, required time, fare, etc.

[1038] Step 7:

[1039] The device displays the most suitable means of transportation for the user.

[1040] The terminal displays the information received from the server to the user. The input is the information about the means of transportation received from the server, and the output is the information about the means of transportation displayed to the user. In concrete terms, the user can select the most suitable means of transportation based on the displayed information and start traveling.

[1041] Step 8:

[1042] The server settles the transportation fee.

[1043] The server provides a payment system for users to pay for the transportation they select. The input is the user's transportation usage information, and the output is confirmation of payment completion. Specifically, the integrated payment system is used to process the fees for multiple transportation methods in a lump sum.

[1044] (Application example 2)

[1045] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1046] In modern society, the variety of transportation methods is increasing, but users need to collect and compare a lot of information to choose the most suitable transportation method. This requires users to spend time and effort, making it difficult to travel efficiently. In addition, the complexity of reserving and paying for transportation methods reduces user convenience. Furthermore, if real-time route guidance is not provided, users may get lost during their trip.

[1047] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1048] In this invention, the server includes means for accepting customer requests, means for performing AI analysis / video analysis of the accepted customer requests, means for utilizing MaaS based on the results of the AI ​​analysis / video analysis, means for paying for travel using MaaS, means for proposing the optimal means of transportation, means for providing real-time route guidance based on the proposed means of transportation, and means for checking reservations and usage status of autonomous vehicles. This allows users to easily select the optimal means of transportation and enables efficient travel. Furthermore, by simplifying reservations and payments for transportation and providing real-time route guidance, user convenience is greatly improved.

[1049] "Customer Request" means a travel request or desire entered into the System by a User.

[1050] "AI analysis / video analysis" is the process of using artificial intelligence technology to analyze customer requests and related video data to determine the most appropriate means of transportation.

[1051] "MaaS" stands for Mobility as a Service and refers to a service that integrates and provides multiple means of transportation.

[1052] "Payment method" means a method or system by which a user pays for the use of a mobility service.

[1053] "Optimal transportation" refers to the most efficient and convenient way of transportation based on the user's request and circumstances.

[1054] "Means for providing route guidance in real time" refers to a system that provides real-time guidance on the optimal route based on the user's current location information while they are traveling.

[1055] "Means for checking reservations and usage status of self-driving vehicles" refers to a system that allows users to reserve self-driving vehicles and check their usage status.

[1056] "Unified authentication payment" is a payment method that integrates multiple payment methods into a single authentication system, allowing users to make payments easily.

[1057] A system for implementing this invention has the following configuration: First, a user inputs a destination and a request for travel using a terminal such as a smartphone. The terminal then transmits this request to a server.

[1058] The server analyzes the received customer requests using AI analysis / video analysis methods. This analysis is achieved by using Python and the Requests library and calling the AI ​​analysis API. Based on the analysis results, the server determines the optimal means of transportation and suggests it to the user.

[1059] The server then provides real-time route guidance based on the proposed transportation options, using GPS data and map information to calculate the optimal route from the user's current location to their destination. The server also provides a way to reserve and check the availability of autonomous vehicles, allowing users to easily reserve an autonomous vehicle and check its availability in real time.

[1060] The payment method used is unified authentication payment, which allows users to integrate multiple payment methods into a single authentication system and make payments easily.

[1061] For example, if a user requests to go to Tokyo Station, the server will suggest that the best way to get from Shibuya Station to Tokyo Station is by train and provide real-time route guidance. If the user wants to use an autonomous vehicle, the server will support the reservation and confirmation of its usage status.

[1062] An example of a prompt sentence is as follows:

[1063] "Create an application where the user inputs their destination and the AI ​​suggests the best means of transportation and provides real-time route guidance. Include a function that determines the best means of transportation by taking into account the user's current location, destination, and transportation preferences (cost, time, etc.)."

[1064] This allows users to easily select the most suitable means of transportation, enabling efficient travel. It also simplifies travel reservations and payments, and provides real-time route guidance, greatly improving user convenience.

[1065] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1066] Step 1:

[1067] The user inputs a destination and a travel request using a device such as a smartphone.

[1068] Input: User's destination, current location, transportation preferences (cost, time, etc.)

[1069] Output: Request data (e.g., JSON format)

[1070] Specific operation: The user enters their destination and preferred mode of transportation into the application's input form and presses the submit button.

[1071] Step 2:

[1072] The terminal transmits the request data to the server.

[1073] Input: Request data

[1074] Output: Request data sent to the server

[1075] Specific operation: The terminal uses an HTTP POST request to send request data to the server.

[1076] Step 3:

[1077] The request data received by the server is analyzed using AI analysis / video analysis methods.

[1078] Input: Request data

[1079] Output: Analysis results (optimal means of transportation)

[1080] How it works: The server calls the AI ​​analytics API and analyzes the request data using Python and the Requests library.

[1081] Step 4:

[1082] The server determines the optimal means of transportation based on the analysis results and suggests it to the user.

[1083] Input: Analysis results

[1084] Output: Recommendation of optimal transportation method

[1085] Specific operation: Based on the analysis results, the server determines the optimal means of transportation (e.g., train, self-driving vehicle, etc.) and notifies the user.

[1086] Step 5:

[1087] The server provides real-time route guidance based on the proposed means of travel.

[1088] Input: Best mode of transportation, current user location

[1089] Output: Real-time directions

[1090] Specific operation: The server uses GPS data and map information to calculate the optimal route from the user's current location to their destination and provides real-time guidance.

[1091] Step 6:

[1092] The server provides a means to check reservations and usage status of autonomous vehicles.

[1093] Input: User's booking request

[1094] Output: Reservation confirmation, usage status notification

[1095] Specific operation: The server accesses the autonomous vehicle reservation system, processes the user's reservation request, checks the usage status, and notifies the user.

[1096] Step 7:

[1097] The server settles the mobile service fee using unified authentication and settlement.

[1098] Input: User's payment information

[1099] Output: Payment completion notification

[1100] Specific operation: The server uses the unified authentication and payment system to process the user's payment information and pay the usage fee. After the payment is completed, the server notifies the user.

[1101] Example 3

[1102] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1103] Conventional mobility service systems have difficulty responding quickly and appropriately to customer requests, particularly in accurately determining the customer's current location and the optimal means of transportation. Furthermore, payment methods are complicated, making them inconvenient for customers. This has led to issues such as lower customer satisfaction and a decrease in the frequency of service use.

[1104] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1105] In this invention, the server includes means for accepting customer requests, means for performing artificial intelligence analysis and video analysis of the accepted customer requests, means for utilizing transportation services based on the results of the artificial intelligence analysis and video analysis, means for paying for transportation using the transportation services, means for analyzing the customer's current location, means for calling the nearest transportation means, and means for displaying a notification of payment completion to the customer. This makes it possible to respond quickly and appropriately to customer requests and provide the most optimal transportation means. In addition, the payment method is simple, providing high convenience for customers.

[1106] "Means for accepting customer requests" refers to equipment or software for receiving requests for mobility services from customers.

[1107] "Means for artificial intelligence analysis and video analysis" refers to devices or software that use artificial intelligence technology and video analysis technology to process data based on received customer requests and analyze the customer's current location and situation.

[1108] "Means for utilizing transportation services" refers to devices or software that select the optimal means of transportation and provide it to customers based on the results of artificial intelligence analysis and video analysis.

[1109] "Means for settling travel for the use of mobility services" means a device or software for automatically settling the charges for the mobility services used by the customer.

[1110] "Means for analyzing the customer's current location" refers to a device or software for identifying and analyzing the customer's current location.

[1111] A "nearest transportation call means" is a device or software that identifies and calls the transportation closest to the customer's current location.

[1112] The "means for displaying a notice of payment completion to the customer" is a device or software for notifying the customer that the fee for the mobile service has been paid.

[1113] MODE FOR CARRYING OUT THE INVENTION

[1114] The present invention relates to a system that accepts customer requests, performs artificial intelligence analysis and video analysis, provides optimal transportation services, and performs payment. Specific embodiments of this system are described below.

[1115] System configuration

[1116] The system consists of the following major components:

[1117] 1. How we receive customer requests

[1118] The terminal (smartphone or tablet) receives requests for transportation services from customers, who then submit requests using a dedicated application.

[1119] 2. AI analysis and video analysis methods

[1120] Based on the received customer request, the server processes the data using artificial intelligence technology (e.g., machine learning models) and video analysis technology (e.g., image recognition software), specifically, Google Cloud Vision API and Amazon Rekognition.

[1121] 3. Ways to utilize transportation services

[1122] The server selects the optimal transportation method based on the results of AI analysis and video analysis, and provides it to the customer. For example, it uses the Uber API to call the nearest taxi.

[1123] 4. Means of payment for travel using transportation services

[1124] The server automatically settles the mobile service fee, specifically using an automatic settlement system (for example, the ONEID settlement system).

[1125] 5. A way to analyze customer location

[1126] The server uses the Google Cloud Vision API to analyze the customer's location, returning the results in the form of latitude and longitude.

[1127] 6. How to call the nearest transportation

[1128] The server calls the Uber API to dispatch the nearest taxi to the customer's location, and the API call returns the taxi's vehicle information and estimated arrival time.

[1129] 7. How to notify customers that payment has been completed

[1130] The terminal will display a notification to the customer that the payment has been completed, and the customer can view a receipt within the app.

[1131] Specific examples

[1132] For example, the specific steps for a user to call a taxi using a smartphone are as follows.

[1133] 1. The user opens the app on their smartphone and selects a taxi.

[1134] 2. The device sends the user's request to the server.

[1135] 3. The server uses the Google Cloud Vision API to analyze the user's current location.

[1136] 4. The server uses Amazon Rekognition to analyze the surrounding video data and collect information to suggest the best means of transportation.

[1137] 5. The server calls the Uber API and dispatches the nearest taxi to the user's current location.

[1138] 6. The device notifies the user of the taxi's estimated arrival time and vehicle information.

[1139] 7. The taxi arrives and takes the user to their destination. During the journey, the device displays their current location and estimated arrival time in real time.

[1140] 8. Once the transfer is complete, the server calls the ONEID payment system and debits the user's account.

[1141] 9. The terminal will display a notification to the user that the payment has been completed, and the user can view the receipt within the app.

[1142] Prompt Sentence Examples

[1143] "Please explain the steps a user would take to call a taxi using their smartphone and get to their destination. Please include names of any specific software or hardware."

[1144] In this way, by explaining the specific embodiment of the system, the details of the invention can be easily understood and can serve as a reference for other people to practice the invention accurately. The flow of the specific processing in Example 3 will be explained using Figure 15.

[1145] Step 1:

[1146] The user opens the app on their smartphone and selects a transportation service (e.g., a taxi).

[1147] Input: User request (selection of travel service)

[1148] Output: Request data (selected travel service)

[1149] Specific operation: When a user selects a taxi within the app and presses the request button, request data is generated.

[1150] Step 2:

[1151] The terminal transmits the user's request to the server.

[1152] Input: Request data

[1153] Output: Request sent to server

[1154] Specific operation: The terminal performs network communication to send the request data to the server.

[1155] Step 3:

[1156] The server uses the Google Cloud Vision API to analyze the user's current location.

[1157] Input: Request data, user location information

[1158] Output: Analysis results (latitude and longitude)

[1159] Specific operation: The server sends the user's location information to the Google Cloud Vision API and obtains the current location in the form of latitude and longitude.

[1160] Step 4:

[1161] The server uses Amazon Rekognition to analyze surrounding video data and collect information to suggest the best means of transportation.

[1162] Input: User's location information, surrounding video data

[1163] Output: Analysis results (traffic conditions and weather information)

[1164] Specific operation: The server sends surrounding video data to Amazon Rekognition to obtain traffic and weather information.

[1165] Step 5:

[1166] Based on the analysis results, the server calls the Uber API to call the nearest taxi.

[1167] Input: Analysis results (latitude and longitude, traffic conditions, weather information)

[1168] Output: Taxi vehicle information, estimated arrival time

[1169] Specific operation: The server calls the Uber API to dispatch the nearest taxi to the user's current location. The API call returns the taxi's vehicle information and estimated arrival time.

[1170] Step 6:

[1171] The terminal notifies the user of the taxi's estimated arrival time and vehicle information.

[1172] Input: Taxi vehicle information, estimated arrival time

[1173] Output: Notification message

[1174] Specific operation: The terminal generates a notification message and displays the estimated arrival time of the taxi and vehicle information to the user.

[1175] Step 7:

[1176] The taxi arrives and takes the user to their destination.

[1177] Input: current location and destination information

[1178] Output: Providing transportation services

[1179] Specific operation: The taxi picks up the user and takes them to their destination. During the trip, the device displays their current location and estimated arrival time in real time.

[1180] Step 8:

[1181] The server confirms the transfer is complete and automatically debits the fee using the ONEID payment system.

[1182] Input: Movement completion information, fee information

[1183] Output: Payment completion notification

[1184] Specific operation: The server receives the transfer completion information and calls the ONEID payment system to deduct the fee.

[1185] Step 9:

[1186] The terminal displays a notice to the user that the payment has been completed.

[1187] Input: Payment completion notification

[1188] Output: Payment completion message

[1189] Specific behavior: The terminal generates a payment completion message and displays it to the user, who can then view the receipt in the app.

[1190] (Application example 3)

[1191] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1192] Conventional mobility service systems have difficulty in providing optimal transportation methods in response to customer requests, and safety and efficiency are not sufficiently ensured, especially when using autonomous vehicles. Furthermore, payment for the transportation service fee requires manual operation, which is inconvenient. There is a need to solve these issues and provide safer and more efficient mobility services.

[1193] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1194] In this invention, the server includes means for accepting customer requests, means for performing artificial intelligence analysis / video analysis of the accepted customer requests, means for utilizing a transportation service based on the results of the artificial intelligence analysis / video analysis, means for paying for transportation using the transportation service, means for analyzing the surrounding situation in real time using a smartphone camera, means for selecting the optimal autonomous vehicle based on the analysis results, means for calling the autonomous vehicle and navigating the route to the destination, and means for automatically withdrawing the usage fee. This enables customers to use autonomous vehicles safely and efficiently, and the usage fee for the transportation service is also automatically paid, improving convenience.

[1195] "Customer Request" means a request submitted by a Customer to utilize the Mobility Services.

[1196] "Artificial intelligence analysis" is the process of using artificial intelligence technology to analyze data and support decision-making.

[1197] "Video analysis" is a technology that analyzes video data from cameras and other sources and extracts specific information.

[1198] "Mobility services" is a general term for transportation methods and services that assist customers in their mobility.

[1199] "Payment method" refers to a method or system for paying for service usage fees.

[1200] A "smartphone camera" is a photographic device built into a smartphone.

[1201] "Real-time analysis" is the process of analyzing data immediately at the moment it is acquired.

[1202] An "autonomous vehicle" is a vehicle that drives autonomously using artificial intelligence and sensor technology.

[1203] "Navigation" means guiding the user to the optimal route to their destination.

[1204] "Usage Fee" means the fee paid to use the Service.

[1205] "Automatic debit" is the process by which fees are paid automatically without manual intervention.

[1206] A system for implementing this invention includes means for accepting customer requests, means for performing artificial intelligence analysis / video analysis of the accepted customer requests, means for utilizing a transportation service based on the results of the artificial intelligence analysis / video analysis, means for paying for transportation using the transportation service, means for analyzing the surrounding situation in real time using a smartphone camera, means for selecting the most suitable autonomous vehicle based on the analysis results, means for calling an autonomous vehicle and navigating the route to the destination, and means for automatically deducting the usage fee.

[1207] Program processing explanation

[1208] The server receives customer requests through a smartphone application. The received requests are sent to the server for artificial intelligence analysis and video analysis. The server analyzes the surrounding situation in real time using the smartphone's camera and selects the most suitable autonomous vehicle based on the analysis results. The selected autonomous vehicle navigates the route to the customer's specified destination.

[1209] Hardware and software used

[1210] Hardware: Smartphones (with cameras), autonomous vehicles, servers

[1211] Software: Smartphone applications, artificial intelligence analysis software, video analysis software, payment systems (automatic payment systems)

[1212] Data processing and calculation

[1213] Data processing: Video data captured by the smartphone camera is sent to a server in real time, where it is analyzed by artificial intelligence and video analysis is performed.

[1214] Data calculation: Based on the analysis results, the optimal self-driving vehicle is selected, the route to the destination is calculated, and payment processing is performed to automatically deduct the usage fee.

[1215] Specific examples

[1216] The user opens the smartphone app and enters "Tokyo Station" as their destination. The app uses the smartphone's camera to analyze the surrounding situation in real time, and once it is confirmed to be safe, it calls the nearest self-driving vehicle. The vehicle arrives and takes the user to their destination. After arrival, the fare is automatically deducted using an automated payment system.

[1217] Prompt Sentence Examples

[1218] The user opens the smartphone app and enters "Tokyo Station" as their destination. The app uses the smartphone's camera to analyze the surrounding situation in real time, and once it is confirmed to be safe, it calls the nearest self-driving vehicle. The vehicle arrives and takes the user to their destination. After arrival, the fare is automatically deducted using an automated payment system.

[1219] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1220] Step 1:

[1221] The user opens the smartphone app and enters their destination.

[1222] Input: Destination information entered by the user into the smartphone app.

[1223] Output: The destination information is sent to the server.

[1224] Specific operation: The user enters a destination, such as "Tokyo Station," into the app's input form and presses the submit button. The app sends this information to the server.

[1225] Step 2:

[1226] The server accepts the customer request.

[1227] Input: Destination information sent from the smartphone app.

[1228] Output: The accepted request is saved in the database.

[1229] Specific operation: The server saves the received destination information in the database and generates a request ID.

[1230] Step 3:

[1231] The server uses the smartphone's camera to analyze the surrounding situation in real time.

[1232] Input: Smartphone camera image data.

[1233] Output: Surrounding safety information as an analysis result.

[1234] How it works: The smartphone camera captures video of the surrounding area and sends the video data to a server, which then uses video analysis software to evaluate the safety of the surrounding area.

[1235] Step 4:

[1236] The server performs artificial intelligence analysis and selects the most suitable self-driving vehicle.

[1237] Input: Surrounding safety information and destination information.

[1238] Output: The optimal autonomous vehicle selection result.

[1239] Specific operation: The server uses artificial intelligence analysis software to select the most suitable autonomous vehicle based on surrounding safety information and destination information, and outputs the selection result as a vehicle ID.

[1240] Step 5:

[1241] The server calls the self-driving vehicle and navigates the route to the destination.

[1242] Input: Optimal autonomous vehicle selection results and destination information.

[1243] Output: Autonomous vehicle invocation and navigation information.

[1244] Specific operation: The server sends destination information to the selected autonomous vehicle and instructs the vehicle to head to the user's location. The vehicle then navigates the route to the destination.

[1245] Step 6:

[1246] The user gets into an autonomous vehicle and travels to their destination.

[1247] Input: User's ride and navigation information.

[1248] Output: Destination arrival information.

[1249] Specific operation: The user gets into the autonomous vehicle, and the vehicle travels to the destination according to the navigation information. Upon arrival, the destination arrival information is sent to the server.

[1250] Step 7:

[1251] The server will automatically deduct the fee.

[1252] Input: Destination arrival information and user payment information.

[1253] Output: Payment completion information.

[1254] Specific operation: The server receives the destination arrival information, deducts the usage fee using the automatic payment system based on the user's payment information, and notifies the user that payment has been completed.

[1255] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1256] "Example 1"

[1257] In one embodiment of the present invention, the emotion engine recognizes the customer's emotions and adjusts the transportation method based on the emotions. Specifically, if the emotion engine recognizes that the customer is stressed, it may suggest a more relaxing transportation method, such as suggesting scenic public transportation instead of a taxi.

[1258] "Example 2"

[1259] The emotion engine also adjusts the route based on the customer's emotions. Specifically, if the emotion engine recognizes that the customer is feeling happy, it will suggest a more enjoyable route, such as one that passes through parks or tourist spots.

[1260] "Example 3"

[1261] Furthermore, the emotion engine simultaneously adjusts the means of transportation and route based on the customer's emotions. Specifically, if the emotion engine recognizes that the customer is feeling angry, it will suggest a smoother, more stress-free means of transportation and route. For example, it will suggest the shortest route to avoid congestion and the fastest means of transportation along that route.

[1262] "Example 4"

[1263] The emotion engine also recognizes the customer's emotions in real time, and if their emotions change during the journey, it will readjust the means of transportation and route accordingly. Specifically, if it recognizes that the customer is starting to feel bored during the journey, the emotion engine will suggest more entertaining means of transportation and routes. For example, it will suggest means of transportation that include music and video, or routes that are visually appealing.

[1264] The processing flow of each embodiment will be described below.

[1265] "Example 1"

[1266] Step 1: The emotion engine recognizes customer emotions in real time.

[1267] Step 2: If the emotion engine recognizes that the customer is stressed, it will choose a more relaxing mode of transportation.

[1268] Step 3: Specifically, suggest scenic public transportation instead of taxis.

[1269] "Example 2"

[1270] Step 1: The emotion engine recognizes customer emotions in real time.

[1271] Step 2: If the emotion engine recognizes that the customer is feeling happy, it will choose a more enjoyable route.

[1272] Step 3: Specifically, suggest a route that passes through parks and tourist spots.

[1273] "Example 3"

[1274] Step 1: The emotion engine recognizes customer emotions in real time.

[1275] Step 2: If the emotion engine recognizes that the customer is angry, it selects a smoother, more stress-free mode of transportation and route.

[1276] Step 3: Specifically, we propose the shortest route to avoid congestion and the fastest means of transportation along that route.

[1277] "Example 4"

[1278] Step 1: The emotion engine recognizes customer emotions in real time.

[1279] Step 2: If the emotion engine detects that the customer is starting to feel bored during the journey, it will rearrange the journey or route to make it more entertaining.

[1280] Step 3: Specifically, we suggest transportation methods that allow you to enjoy music and video, and routes that are visually appealing.

[1281] Example 1

[1282] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1283] Conventional mobility service platform systems often suggest transportation methods without considering the customer's feelings, which can lead to lower customer satisfaction. Furthermore, there is a lack of technology to select the optimal transportation method based on the customer's feelings, making it difficult to provide services that meet customer needs. Furthermore, there is also the issue of low convenience due to limited payment methods.

[1284] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1285] In this invention, the server includes means for accepting customer requests, means for analyzing the accepted customer requests using natural language processing technology, means for recognizing the customer's emotions based on the analysis results, means for selecting the optimal means of transportation based on the recognized emotions, means for notifying the customer of information about the selected means of transportation, and means for paying for the use of the means of transportation. This makes it possible to suggest the optimal means of transportation based on the customer's emotions and improve customer satisfaction. Furthermore, convenience can be improved by introducing a payment method using biometric authentication.

[1286] "Customer Request" means a travel request or wish that a customer submits to the travel service platform system.

[1287] "Natural language processing technology" is a technology that allows computers to analyze and understand human language.

[1288] "Analysis results" refers to the data and information obtained after analyzing a customer request using natural language processing technology.

[1289] "Means for recognizing emotions" refers to technologies and methods for identifying customer emotions based on analysis results.

[1290] "Transportation" refers to the means of transportation used by the customer to travel to their destination.

[1291] A "selection tool" is a method or technique for determining the best option based on specific conditions or criteria.

[1292] "Means of notification" refers to the methods or techniques used to communicate selected information to customers.

[1293] "Payment instruments" refers to methods and technologies for making payments for the use of transportation means.

[1294] "Biometric authentication" is a technology that identifies individuals using biometric information such as fingerprints or facial recognition.

[1295] This invention relates to a transportation service platform system that proposes the most suitable transportation method based on customer emotions. This system accepts customer requests, analyzes them using natural language processing technology, recognizes the customer's emotions based on the analysis results, selects the most suitable transportation method based on the recognized emotions, notifies the customer of the selected transportation method, and performs a series of processes to settle the use of the transportation method.

[1296] Hardware and software used

[1297] Hardware:

[1298] Server: Use a server machine with a powerful processor and sufficient memory.

[1299] Device: Customers use smartphones (iOS or Android).

[1300] software:

[1301] Server: Runs programs written in Python.

[1302] Natural language processing libraries: Use NLTK, spaCy, etc.

[1303] Machine learning models: Use TensorFlow, PyTorch, etc.

[1304] Explanation of program processing

[1305] Accepting requests:

[1306] The terminal (customer's smartphone) sends a travel request through a dedicated application. For example, a user might enter, "I want to travel from Shinjuku to Shibuya. I'm very tired today," and press the send button. The server receives the request sent from the terminal and stores it in a database.

[1307] Emotion Recognition:

[1308] The server analyzes the text data of the received request and uses natural language processing technology to recognize the customer's emotions. For example, it recognizes "fatigue" from the text "I'm very tired today." The server tokenizes the text using a natural language processing library (e.g., spaCy) and inputs it into a sentiment analysis model (e.g., a model trained with TensorFlow). The model extracts emotions from the text and returns the result "fatigue."

[1309] Transportation options:

[1310] The server selects the optimal transportation method based on the recognized emotion. For example, if "fatigue" is recognized, the server will suggest a public transportation method with a good view. The server searches the database of transportation methods for transportation tagged with "relaxing," and from the search results, selects the public transportation method that is optimal for the user's current location and destination.

[1311] Notification of results:

[1312] The server generates information about the selected transportation method and sends it to the device. For example, it generates information such as, "The public transportation with the best scenery from Shinjuku to Shibuya is the Yamanote Line." The device then displays the received message to the user through the application's notification function.

[1313] settlement:

[1314] The server provides a means of payment for transportation. By introducing a payment method using biometric authentication, convenience can be improved. For example, payment can be made using fingerprint authentication or face authentication.

[1315] Examples of specific examples and prompts

[1316] As a concrete example, consider the following scenario.

[1317] Scenario: A user types into the app, "I'm very tired today and I'm looking for a relaxing ride."

[1318] Prompt: "If the customer is feeling tired, suggest a relaxing mode of transportation."

[1319] By inputting this prompt sentence into the generative AI model, the following output is obtained:

[1320] Example output: "The customer feels tired, so suggest scenic public transport."

[1321] In this way, the mobility service platform system provides optimal transportation based on customer sentiment.

[1322] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1323] Step 1: Accepting the request

[1324] Input: The user inputs a travel request through the smartphone application and presses the send button.

[1325] What happens: The user types into the app, "I want to travel from Shinjuku to Shibuya. I'm very tired today."

[1326] Data processing: The terminal sends the entered text data to the server.

[1327] Output: The server stores the received request in a database.

[1328] Step 2: Recognize emotions

[1329] Input: The text data of the request received by the server.

[1330] What it does: The server uses a natural language processing library (e.g., spaCy) to tokenize the text and feed it into a sentiment analysis model (e.g., a model trained in TensorFlow).

[1331] Data processing: The model extracts emotions from the text and returns the result "fatigue."

[1332] Output: The server gets the emotion recognition result "fatigue".

[1333] Step 3: Choose your transportation

[1334] Input: Emotion recognition result from the server (e.g., tiredness).

[1335] What happens: The server searches its database of transportation options for options tagged as "relaxing."

[1336] Data processing: From the search results, select the public transport that best suits the user's current location and destination.

[1337] Output: The server generates the information "The best scenic public transport from Shinjuku to Shibuya is the Yamanote Line."

[1338] Step 4: Notification of results

[1339] Input: Information about the transportation method selected by the server.

[1340] Specific operation: The server generates a message containing detailed information about the selected transportation method (e.g., route name, travel time, and fare).

[1341] Data processing: The server sends the generated message to the terminal.

[1342] Output: The device displays the received message to the user through the application's notification function.

[1343] Step 5: Payment

[1344] Input: The user indicates their intention to use the selected mode of transportation.

[1345] Specific operation: The user makes a payment using biometric authentication (e.g., fingerprint authentication or facial authentication).

[1346] Data processing: The server verifies the biometric data and processes the payment.

[1347] Output: The server sends a notification of payment completion to the terminal, which displays it to the user.

[1348] In this way, the mobility service platform system provides optimal transportation based on customer sentiment, improving convenience.

[1349] (Application example 1)

[1350] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1351] Conventional mobility service platform systems provide transportation without considering the emotional state of the customer, which can cause stress for the customer. Furthermore, the system does not adjust the optimal route or in-car environment, which can lead to a decrease in customer satisfaction. This creates a problem of not improving the quality of the customer experience.

[1352] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for accepting a customer request, means for performing artificial intelligence analysis / video analysis of the accepted customer request, means for utilizing a transportation service based on the results of the artificial intelligence analysis / video analysis, means for paying for transportation using the transportation service, and means for recognizing the customer's emotions and adjusting the transportation means based on the emotions. This makes it possible to provide the optimal transportation means according to the customer's emotional state, thereby improving the quality of the customer experience.

[1353] "Customer Request" means a request submitted by a Customer to utilize mobility services.

[1354] "Artificial intelligence analysis" is the process of using artificial intelligence techniques to analyze data and extract meaningful information.

[1355] "Video analysis" is a technology that analyzes video data acquired by cameras and other devices and extracts specific information.

[1356] "Transportation services" refers to the transportation and related services provided to customers to travel to their destinations.

[1357] "Payment method" refers to a method or system for paying for the service.

[1358] "Means for recognizing emotions" refers to technology that detects a customer's emotional state from their facial expressions, voice, etc.

[1359] "Means to adjust transportation" refers to technology that selects and provides the optimal transportation means and route based on the customer's emotional state.

[1360] "Uniform identification payment" is a payment method that uses uniform identification information.

[1361] The following system configuration and processing procedure will be described as an embodiment of the present invention.

[1362] System Configuration

[1363] The system consists of the following major components:

[1364] 1. Customer terminal: A device such as a smartphone or tablet through which a customer submits a travel request.

[1365] 2. Server: A central processing unit that accepts customer requests and performs artificial intelligence analysis and video analysis.

[1366] 3. Self-driving vehicles: Vehicles equipped with self-driving technology to transport customers to their destinations.

[1367] Program processing explanation

[1368] Customer terminal

[1369] The customer terminal sends a request for movement via a smartphone application, which then captures a picture of the customer's face with a camera and sends the video data to the server.

[1370] server

[1371] The server performs the following process.

[1372] 1. Artificial intelligence analysis: The received video data is analyzed using the EmotionRecognizer library to recognize the customer's emotions.

[1373] 2. Video analysis: Analyze the customer's facial expressions and voice from video data to detect their emotional state.

[1374] 3. Trip adjustment: Based on the recognized emotion, plan the optimal route using the RoutePlanner library. For example, if the customer is stressed, choose a scenic route and play relaxing music.

[1375] Autonomous vehicles

[1376] The autonomous vehicle operates based on optimal route information sent from the server, and the audio system in the vehicle plays music specified by the server.

[1377] Specific examples

[1378] For example, a customer opens a smartphone app to request a self-driving vehicle. The app uses a camera to capture the customer's face and recognize their emotions. If the app detects that the customer is stressed, the server will select a scenic route and play relaxing music.

[1379] Prompt Sentence Examples

[1380] A customer requests a self-driving vehicle through a smartphone app. The app uses a camera to capture the customer's face and recognize their emotions. If the customer is feeling stressed, the app will select a scenic route and play relaxing music.

[1381] In this way, it is possible to provide the most suitable transportation method according to the customer's emotional state, improving the quality of the customer experience.

[1382] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1383] Step 1:

[1384] The customer device sends a travel request through a smartphone application. The input is the travel request information that the customer enters into the application. The output is the request data that is sent to the server. Specifically, the customer enters their destination and desired means of transportation into the app and presses the send button.

[1385] Step 2:

[1386] The customer device uses a camera to capture a picture of the customer's face and sends the video data to the server. The input is the video of the customer's face captured by the camera. The output is the video data sent to the server. Specifically, the app automatically starts the camera and captures the customer's face.

[1387] Step 3:

[1388] The server analyzes the video data it receives using the EmotionRecognizer library to recognize the customer's emotions. The input is video data of the customer's face. The output is the recognized emotion data. Specifically, the server passes the video data to EmotionRecognizer and obtains the emotion recognition results.

[1389] Step 4:

[1390] The server uses the RoutePlanner library to plan the optimal route based on the emotional data it recognizes. The input is the recognized emotional data and the customer's destination information. The output is the optimal route information. Specifically, the server analyzes the emotional data and, for example, if the customer is feeling stressed, selects a route with a good view.

[1391] Step 5:

[1392] The server sends optimal route information and instructions to play relaxing music to the autonomous vehicle. The input is the optimal route information and music playback instructions. The output is instruction data sent to the autonomous vehicle. Specifically, the server sends the route information and the path to the music file to the vehicle's control system.

[1393] Step 6:

[1394] The autonomous vehicle operates based on optimal route information sent from the server, and the in-car audio system plays the specified music. The input is the route information and music playback instructions received from the server. The output is the driving and music playback until the customer reaches their destination. The specific operation is that the vehicle drives the specified route and plays relaxing music from the in-car speakers.

[1395] Example 2

[1396] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1397] Conventional transportation service systems can provide optimal transportation methods based on customer requests, but they have the problem of not being able to propose routes that take into account the customer's emotional state. This makes it difficult to improve customer satisfaction.

[1398] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for accepting a customer request, means for performing artificial intelligence analysis and video analysis of the accepted customer request, means for utilizing a transportation service based on the results of the artificial intelligence analysis and video analysis, means for settling a trip using the transportation service, means for analyzing customer emotions, and means for adjusting a transportation route based on the customer emotions. This makes it possible to provide the optimal transportation means and route taking into account the emotional state of the customer.

[1399] The "means for accepting customer requests" is an interface for receiving information such as the departure point, destination, and desired means of transportation from the customer.

[1400] "Means for artificial intelligence analysis and video analysis" refers to means for analyzing received customer requests and using artificial intelligence technology and video analysis technology to determine the optimal means of transportation and route.

[1401] "Means for utilizing transportation services" refers to the means of selecting transportation services such as public transportation, taxis, and bicycle sharing based on the analysis results and providing them to customers.

[1402] "Means for paying for travel using a mobile service" refers to means for paying for the use of the selected mobile service.

[1403] "Means for analyzing customer emotions" refers to technology for analyzing the emotional state of a customer, such as using an emotion analysis API.

[1404] The "means for adjusting a travel route based on the customer's emotions" is a means for proposing a more enjoyable or comfortable travel route based on the analyzed emotional state of the customer.

[1405] The "means for proposing the optimal route" is a means for proposing the optimal travel route to the customer's destination.

[1406] "Means using unified identification payment" refers to means for making payments using unified identification information.

[1407] This invention is a system that accepts customer requests, determines the optimal means of transportation using artificial intelligence analysis and video analysis, and further adjusts the travel route based on the customer's emotional state. Specific embodiments of this system are described below.

[1408] System configuration

[1409] Hardware and Software

[1410] The server plays a central role in accepting customer requests, analyzing them, and returning results. It has artificial intelligence and video analysis libraries such as TensorFlow and OpenCV installed.

[1411] A terminal is a device through which a user inputs a request and receives the results, such as a smartphone or a computer.

[1412] An emotion engine is software for analyzing customer emotions, and uses, for example, IBM Watson's emotion analysis API.

[1413] Program processing

[1414] Accepting customer requests

[1415] Users submit requests through a smartphone app or web interface, which include information such as origin, destination, and preferred mode of transportation.

[1416] The terminal receives the user's request and sends it to the server.

[1417] Request content analysis

[1418] The server converts the received request into JSON format and passes it to the artificial intelligence analysis and video analysis means.

[1419] The AI ​​analysis method uses libraries such as TensorFlow and OpenCV to analyze the request content. For example, it obtains the coordinates of the departure and destination and lists possible transportation options.

[1420] Determining the best mode of transportation

[1421] The server receives the analysis results from the AI ​​analysis means and determines the optimal transportation method, such as public transportation, taxi, or bicycle sharing.

[1422] The server prepares the data to return the selected mode of transportation to the user.

[1423] Emotion analysis using an emotion engine

[1424] The server passes the user's emotional data to the emotion engine, including the user's past movement history and current emotional state.

[1425] The emotion engine uses IBM Watson's emotion analysis API to analyze the user's emotions, for example, to determine whether the user is feeling happy.

[1426] Adjusting travel routes

[1427] If the emotion engine recognizes that the user is feeling joy, it will suggest more enjoyable routes, for example, routes that pass through parks and tourist spots.

[1428] The server receives suggestions from the emotion engine and determines the final travel route.

[1429] Returning the results

[1430] The server formats the data to return the final trip and route to the user.

[1431] The device displays the data received from the server to the user, for example, displaying the means of transportation and route on a map on the screen of a smartphone app.

[1432] Specific examples

[1433] The user types "How do I get from Shinjuku to Shibuya?" into a smartphone app and presses the send button.

[1434] The terminal sends this request to the server.

[1435] The server receives the request, converts it into JSON format, and passes it to the AI ​​analysis tool.

[1436] The AI ​​analysis tool obtains the coordinates of the departure and destination and lists possible means of transportation.

[1437] The server receives the analysis results from the AI ​​analysis means and selects "train" as the optimal means of transportation.

[1438] The server prepares the data to return this information to the user.

[1439] The server passes the user's emotional data to the emotion engine, including, for example, the places the user has visited in the past and their current emotional state.

[1440] The emotion engine determines that the user is feeling happy.

[1441] The emotion engine suggests a route that passes through Yoyogi Park because the user feels joy.

[1442] The server receives this proposal and determines the final travel route.

[1443] The server formats the data to return the final trip and route to the user.

[1444] The device displays the data received from the server to the user. For example, a smartphone app screen might show a map showing a route from Shinjuku to Shibuya by train, passing through Yoyogi Park.

[1445] Prompt Sentence Examples

[1446] "Tell me the best way to get from Shinjuku to Shibuya. If it makes users happy, suggest fun routes too."

[1447] In this way, the system provides the optimal means of transportation and route based on the user's request.

[1448] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1449] Step 1:

[1450] Users submit requests through a smartphone app or web interface, which include information such as origin, destination, and preferred mode of transportation.

[1451] Input: User request information (starting point, destination, desired means of transportation)

[1452] Output: Request information is sent to the terminal

[1453] Specific behavior: The user enters information into the app's input form and presses the submit button.

[1454] Step 2:

[1455] The terminal receives the user's request and sends it to the server.

[1456] Input: User request information

[1457] Output: Request information is sent to the server

[1458] Specific operation: The terminal converts the request information into JSON format and sends it to the server as an HTTP request.

[1459] Step 3:

[1460] The server passes the received request to the artificial intelligence analysis and video analysis means.

[1461] Input: Request information sent from the terminal

[1462] Output: Request information passed to the parser

[1463] Specific operation: The server converts the request information into an internal data structure to pass it to the analysis means.

[1464] Step 4:

[1465] The AI ​​analysis tool analyzes the request content and determines the most suitable means of transportation.

[1466] Input: Request information passed from the server

[1467] Output: A list of optimal transportation options

[1468] Specific operation: The AI ​​analysis means uses TensorFlow and OpenCV to obtain the coordinates of the departure and destination and list possible means of transportation.

[1469] Step 5:

[1470] The server receives the analysis results from the AI ​​analysis means and determines the optimal means of transportation.

[1471] Input: Candidate list from AI analysis method

[1472] Output: Determine the best mode of transportation

[1473] Specific operation: The server selects the best mode of transportation from the candidate list and prepares the data to return to the user.

[1474] Step 6:

[1475] The server passes the user's emotion data to the emotion engine.

[1476] Input: User's emotional data (past movement history, current emotional state)

[1477] Output: Emotion data passed to the emotion engine

[1478] Specific operation: The server collects the user's emotion data and sends it to the emotion engine.

[1479] Step 7:

[1480] The emotion engine analyzes the user's emotions.

[1481] Input: Emotion data passed from the server

[1482] Output: User's emotional state (happy, sad, etc.)

[1483] Specific operation: The emotion engine uses the emotion analysis API to analyze the user's emotions.

[1484] Step 8:

[1485] The emotion engine adjusts the travel route based on the user's emotional state.

[1486] Input: User's emotional state

[1487] Output: Adjusted travel route suggestions

[1488] Specific operation: The emotion engine generates a route, for example passing through parks and tourist spots, based on the user's emotional state.

[1489] Step 9:

[1490] The server receives suggestions from the emotion engine and determines the final travel route.

[1491] Input: Adjusted travel route from the emotion engine

[1492] Output: Final travel route determination

[1493] Specific operation: The server determines the final movement route based on suggestions from the emotion engine.

[1494] Step 10:

[1495] The server formats the data to return the final trip and route to the user.

[1496] Input: Final travel route and mode

[1497] Output: Data to return to the user

[1498] Specific operation: The server converts the final means of travel and route into JSON format and sends it to the device.

[1499] Step 11:

[1500] The terminal displays the data received from the server to the user.

[1501] Input: Data sent from the server

[1502] Output: The trip and route displayed to the user

[1503] Specific operation: The device analyzes the data received and displays the means of transportation and route on a map on the smartphone app screen.

[1504] (Application example 2)

[1505] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1506] Conventional transportation suggestion systems did not consider customer emotions when proposing routes, and were unable to sufficiently increase customer satisfaction. Furthermore, they lacked convenience due to insufficient selection of optimal transportation methods and insufficient integration of payment methods. This made it difficult to respond to diverse customer needs.

[1507] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1508] In this invention, the server includes means for accepting customer requests, means for performing AI analysis / video analysis of the accepted customer requests, means for utilizing MaaS based on the results of the AI ​​analysis / video analysis, means for paying for travel using MaaS, and means for analyzing customer emotions and adjusting travel routes based on the emotions. This makes it possible to propose optimal means of travel and routes that take customer emotions into consideration, thereby increasing customer satisfaction.

[1509] "Customer Request" refers to a request or wish that a customer enters into the system.

[1510] "AI analysis" refers to the technology of using artificial intelligence to analyze data and extract meaning and patterns.

[1511] "Video analysis" refers to the technology of analyzing video data and extracting information.

[1512] "MaaS" stands for Mobility as a Service and refers to a service that integrates multiple means of transportation.

[1513] "Payment method" refers to the method or system for paying the service fee.

[1514] "Means for analyzing emotions" refers to technology that analyzes customer emotions and determines their state.

[1515] "Means for adjusting travel routes" refers to technology that suggests optimal travel routes based on customer sentiment and other factors.

[1516] The "optimal route" refers to the most efficient and satisfying route to a customer's destination.

[1517] "Electronic payment" refers to a payment method that uses the Internet or electronic devices.

[1518] A system for implementing this invention includes means for accepting customer requests, means for performing AI analysis / video analysis of the accepted customer requests, means for utilizing MaaS based on the results of the AI ​​analysis / video analysis, means for paying for travel using MaaS, and means for analyzing customer emotions and adjusting travel routes based on the emotions.

[1519] Explanation of program processing

[1520] 1. Accepting Customer Requests:

[1521] The server receives requests from customers via a smartphone application, which includes information such as the destination and desired arrival time.

[1522] 2. AI analysis / video analysis:

[1523] The server analyzes the received request using AI analysis / video analysis methods. Specifically, it analyzes the request content using natural language processing technology to determine the travel distance and type of destination. This analysis is performed using software such as Python and TensorFlow.

[1524] 3. Utilizing MaaS:

[1525] The server determines the optimal means of transportation based on the results of AI analysis and video analysis. For example, it selects bicycle sharing for short distances, public transportation for medium distances, and a taxi for long distances. This selection is made using the MaaS platform's API.

[1526] 4. Payment Methods:

[1527] The server then processes the payment for the selected transportation option, completing the payment via the customer's credit card details or electronic wallet using an electronic payment gateway such as Stripe or PayPal.

[1528] 5. Sentiment analysis and route adjustment:

[1529] The server analyzes the customer's facial expressions and tone of voice using the smartphone's camera and microphone to analyze their emotions. Software such as OpenCV and Emotion API is used for emotion analysis. Based on the analysis results, the server suggests a scenic route if the customer is happy, or a quiet route if they want to relax.

[1530] Specific examples

[1531] For example, if the user requests "I want to go to the city center" and the emotion is "joy", the server will do the following:

[1532] 1. Analyze the request and determine that a trip to the city center is required.

[1533] 2. Determine that the trip is a medium distance and choose public transportation.

[1534] 3. Suggest scenic routes because users love them.

[1535] Prompt Sentence Examples

[1536] "If the user requests 'I want to go to the city center' and the emotion is 'joy', generate a Python program that suggests the best mode of transportation and route."

[1537] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1538] Step 1:

[1539] The server accepts requests from users through a smartphone application. As input, the user provides information such as the destination and desired arrival time. As output, this information is sent to the server. Specifically, the user enters the destination into the application and presses the send button.

[1540] Step 2:

[1541] The server analyzes the received request using AI analysis / video analysis methods. The user's request information is used as input. For data processing, natural language processing technology is used to analyze the request content and determine the travel distance and type of destination. The analysis results are obtained as output. Specifically, the request content is analyzed using Python and TensorFlow.

[1542] Step 3:

[1543] The server determines the optimal means of transportation based on the results of AI analysis / video analysis. The analysis results are used as input. Data calculations involve selecting bicycle sharing for short distances, public transportation for medium distances, and taxis for long distances, depending on the distance traveled and the type of destination. The selected means of transportation is obtained as output. The specific operation involves selecting the means of transportation using the MaaS platform's API.

[1544] Step 4:

[1545] The server processes the payment for the selected mode of transport. As input, the selected mode of transport and the user's payment information are used. As a data operation, the payment is completed using an electronic payment method. As an output, a confirmation of the completion of the payment is obtained. As a specific operation, the payment is processed using a payment gateway such as Stripe or PayPal.

[1546] Step 5:

[1547] To analyze the user's emotions, the server uses the smartphone's camera and microphone to analyze the user's facial expressions and tone of voice. The user's facial expression and voice data are used as input. OpenCV and Emotion API are used to process the data and analyze emotions. The analyzed emotional information is obtained as output. Specifically, the system works by capturing a photo of the user's facial expression with the smartphone camera and analyzing it.

[1548] Step 6:

[1549] The server adjusts the travel route based on the analyzed emotion information. The emotion information and destination information are used as input. The data calculation suggests a scenic route if the user is happy, or a quiet route if the user wants to relax. The output is the adjusted travel route. The specific operation is to use a route suggestion algorithm to calculate the optimal route.

[1550] Example 3

[1551] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1552] Conventional mobility service systems did not propose transportation methods or routes that took into account the customer's emotional state, which prevented them from fully increasing customer satisfaction. Furthermore, they lacked the ability to readjust transportation methods and routes in real time if the customer's emotions changed during the trip, making it difficult to provide a comfortable transportation experience for customers. Furthermore, payment methods were not standardized, requiring the use of multiple payment methods, which reduced convenience.

[1553] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1554] In this invention, the server includes means for accepting customer requests, means for performing artificial intelligence analysis / video analysis of the accepted customer requests, means for utilizing transportation services based on the results of the artificial intelligence analysis / video analysis, means for paying for transportation using the transportation services, means for recognizing customer emotions in real time and adjusting the transportation method and route, and means for readjusting the transportation method and route if the customer's emotions change during the trip. This makes it possible to propose the optimal transportation method and route based on the customer's emotional state, and to provide a comfortable transportation experience that responds to emotional changes during the trip. In addition, the use of unified authentication payment also improves payment convenience.

[1555] "Customer Request" means a request made by a Customer to the System to use a mobility service.

[1556] "Artificial intelligence analysis" refers to the process of using machine learning and data analysis techniques to analyze input data and extract meaningful information.

[1557] "Video analytics" refers to the technology of analyzing video data obtained from cameras and other image capture devices and extracting specific information.

[1558] "Transportation service" refers to a service that provides transportation of a customer's choice and enables the customer to travel to their destination.

[1559] "Payment method" refers to a method or system for customers to pay for the services they use.

[1560] "Emotion recognition" refers to technology that analyzes data such as a customer's facial expressions and voice to identify their emotional state.

[1561] "Transportation" refers to the means of transportation used by the Customer to travel to their destination.

[1562] "Route adjustment" refers to the process of calculating and suggesting the optimal route to a customer's destination.

[1563] "Real-time" refers to data acquisition and processing occurring immediately.

[1564] "Unified authentication payment" refers to a method of integrating multiple payment methods into a single authentication system to make payments easier.

[1565] MODE FOR CARRYING OUT THE INVENTION

[1566] This invention is a system that accepts customer requests, performs artificial intelligence analysis and video analysis, provides transportation services based on the results, and further recognizes customer emotions in real time to adjust transportation methods and routes. Specific embodiments of this system are described below.

[1567] Hardware and software used

[1568] 1. Server

[1569] It uses servers with high-performance data processing capabilities, which handle key processes such as accepting customer requests, AI analysis, video analysis, providing mobility services, payment processing, emotion recognition, and route adjustment.

[1570] The software used may include artificial intelligence models (e.g., machine learning algorithms), video analytics software, payment systems (e.g., unified authentication payment systems), and emotion recognition engines.

[1571] 2. Terminal

[1572] This refers to devices such as smartphones and PCs used by customers. The devices input customer requests, communicate with the server, capture and send emotional data, and display suggested transportation methods and routes.

[1573] The software used includes dedicated applications, camera and microphone control software, and communication modules.

[1574] 3. Users

[1575] This refers to customers who use transportation services. Users operate a terminal to input requests and receive suggestions for transportation methods and routes.

[1576] Data processing and calculation

[1577] 1. Acceptance of Customer Requests

[1578] A user uses a terminal to access a dedicated application and input a request for a transportation service, including information such as the origin, destination, and desired mode of transportation.

[1579] The terminal transmits the input request information to the server.

[1580] 2. Artificial intelligence and video analysis

[1581] Based on the received request information, the server uses an artificial intelligence model to calculate the optimal means of transportation and route.

[1582] The server uses video analytics software to analyze the video data sent from the terminal to identify the customer's emotional state.

[1583] 3. Provision of transportation services

[1584] The server identifies the optimal means of transportation and route and transmits the necessary information to the transportation service provider to provide the transportation service.

[1585] For example, if a taxi is selected, the server searches for the nearest taxi and sends a pickup request.

[1586] 4. Payment Processing

[1587] The server calculates the cost of the mobile service and automatically debits the customer's account using a unified authentication and payment system.

[1588] 5. Emotion recognition and route adjustment

[1589] The server uses an emotion recognition engine to analyze the customer's facial and voice data sent from the device and identify their emotional state in real time.

[1590] The server suggests the optimal means of transportation and route based on the customer's emotional state, and makes readjustments if necessary.

[1591] Specific examples

[1592] When the user selects a taxi and wishes to travel to the destination, the terminal transmits the information to the server.

[1593] The server calls the taxi company's API, searches for the nearest taxi, and calls it.

[1594] The server debits the user's account using a unified authentication and payment system.

[1595] The server activates an emotion engine and recognizes emotions by analyzing the user's facial expressions and voice data sent from the terminal.

[1596] If the server recognizes that the user is feeling angry, it will suggest the shortest route to avoid congestion and the fastest way to travel that route.

[1597] If the user begins to feel bored during the journey, the server will re-suggest a means of transportation that allows for enjoyment of music and video, or a visually appealing route.

[1598] Prompt Sentence Examples

[1599] If the user selects a taxi, how does the system call the nearest taxi and take them to their destination?

[1600] "Please explain in detail how the emotion engine recognizes the user's emotions in real time and adjusts the mode of travel and route."

[1601] "Please explain the procedure for debiting the user's account using the unified authentication and payment system." The flow of the specific process in the third embodiment will be explained with reference to FIG.

[1602] Step 1:

[1603] The user accesses a dedicated application using a device such as a smartphone or PC. The user selects the desired means of transportation (e.g., taxi) from a list of transportation services provided within the application and enters the departure point and destination. The device then sends the entered request information to the server. The input data is the departure point, destination, and desired means of transportation, and the output data is the request information sent to the server.

[1604] Step 2:

[1605] The server uses an artificial intelligence model to calculate the optimal means of transportation and route based on the received request information. The input data is the user's request information, and the output data is information on the optimal means of transportation and route. Specifically, the server analyzes the user's current location information and destination information, and calls the taxi company's API to search for the nearest taxi. The server identifies the nearest taxi and sends the user's pickup request to that taxi.

[1606] Step 3:

[1607] The server calculates the fee for the transportation service and automatically deducts it from the customer's account using a unified authentication payment system. The input data is the transportation service usage information and data for fee calculation, and the output data is a notification of payment completion. Specifically, the server calculates the fee based on the travel distance and time, and deducts the fee from the user's account through the unified authentication payment system. The server then sends a notification of payment completion to the user's terminal.

[1608] Step 4:

[1609] The server activates the emotion engine and recognizes the user's emotions in real time. The input data is the user's facial expression and voice data sent from the device, and the output data is the analyzed emotional state. Specifically, the device uses a camera and microphone to capture the user's facial expression and voice and sends the data to the server. The server analyzes the received data and identifies the user's emotional state.

[1610] Step 5:

[1611] The server proposes the optimal means of transportation and route based on the user's emotional state. The input data is the analyzed emotional state and current means of transportation and route information, and the output data is a proposal of an adjusted means of transportation and route. Specifically, if the server recognizes that the user is feeling angry, it proposes the shortest route to avoid congestion and the fastest way to travel that route. The server notifies the user's device of the proposal.

[1612] Step 6:

[1613] The server continuously monitors the user's emotions while traveling. The input data is continuous emotional data sent from the device, and the output data is a readjusted transportation method and route proposal. Specifically, the device continuously sends the user's emotional data to the server using a camera and microphone. If the user's emotions change, the server readjusts the transportation method and route accordingly. For example, if the user begins to feel bored, the server will suggest transportation methods that include music and video, or a visually appealing route. The server notifies the user's device of the readjusted proposal.

[1614] (Application example 3)

[1615] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1616] Conventional mobility service systems have difficulty responding flexibly to customer emotions and situations, often resulting in stress and dissatisfaction. Another issue is the inability to respond appropriately when a customer's emotions change during a trip. Furthermore, limited payment methods mean low convenience.

[1617] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1618] In this invention, the server includes means for accepting customer requests, means for performing artificial intelligence analysis / video analysis of the accepted customer requests, means for utilizing transportation services based on the results of the artificial intelligence analysis / video analysis, means for paying for transportation using the transportation services, means for recognizing customer emotions and adjusting the transportation method and route based on the emotions, and means for readjusting the transportation method and route if the customer's emotions change. This enables flexible responses according to the customer's emotions and circumstances, reducing stress and dissatisfaction. Furthermore, appropriate responses can be made even if the customer's emotions change during transportation, improving convenience.

[1619] "Customer Request" means any request or request submitted by a Customer when using the Mobility Services.

[1620] "Artificial intelligence analysis" is the process of using artificial intelligence techniques to analyze data and extract meaningful information.

[1621] "Video analysis" is a technology that analyzes video data from cameras and other sources and extracts specific information.

[1622] "Transportation services" refers to transportation means and services provided to customers to travel to their destinations.

[1623] "Payment method" refers to a method or system for paying for the service.

[1624] "Means of recognizing emotions" refers to technologies and systems that can determine emotions from customers' facial expressions, voice, etc.

[1625] "Means for adjusting transportation methods and routes based on emotions" refers to technologies and systems that select the optimal transportation method and route based on the customer's emotional state.

[1626] "Means for readjusting transportation methods and routes when emotions change" refers to technologies and systems that reselect transportation methods and routes in response to changes in a customer's emotions during travel.

[1627] "Uniform identification payment" refers to a payment method that uses uniform identification information.

[1628] The following system configuration and processing procedure will be described as an embodiment of the present invention.

[1629] System Configuration

[1630] The system consists of the following major components:

[1631] 1. Customer request acceptance means: Customer travel requests are accepted using a smartphone application.

[1632] 2. Artificial intelligence analysis / video analysis method: Using the smartphone camera and sensors, the customer's facial expressions and voice are analyzed to recognize emotions.

[1633] 3. Transportation service utilization: Call the nearest autonomous vehicle to transport the customer to their destination.

[1634] 4. Payment method: The usage fee will be automatically deducted using a unified identification payment system.

[1635] 5. Emotion recognition: Recognize customer emotions in real time and adjust transportation methods and routes based on emotions.

[1636] 6. Readjustment: Readjust the mode of travel or route if the customer's emotions change during the journey.

[1637] Hardware and software used

[1638] Hardware: Smartphone (camera, microphone, GPS sensor)

[1639] Software: OpenCV (video analysis), EmotionRecognizer (emotion recognition), MaaSService (mobility service provision), ONEIDPayment (payment processing)

[1640] Data processing and calculation

[1641] 1. Accepting customer request: The smartphone application accepts the customer's request for transportation.

[1642] 2. Video analysis and emotion recognition: Using the smartphone camera and microphone, the customer's facial expressions and voice are analyzed in real time to recognize their emotions.

[1643] 3. Trip and route adjustment: Select the optimal trip and route based on the recognized emotion. For example, if the customer is angry, suggest the shortest route to avoid congestion.

[1644] 4. Providing transportation services: Calling the nearest autonomous vehicle to take customers to their destination.

[1645] 5. Payment processing: The usage fee will be automatically deducted using a unified identification payment system.

[1646] 6. Readjustment in response to emotional changes: If a customer's emotions change during the journey, re-acknowledge the emotion and readjust the mode of travel or route accordingly.

[1647] Specific examples

[1648] For example, if a user calls a taxi through a smartphone application, the application can analyze the user's facial expressions and voice and determine that the user is angry. In this case, the system will suggest the shortest route to avoid congestion and call the nearest self-driving vehicle. If the user begins to feel bored during the trip, the system will suggest transportation options that include music and video, or routes that are visually appealing.

[1649] Prompt Sentence Examples

[1650] "Develop a smartphone app that suggests optimal modes of transport and routes based on the user's emotions. If the user is angry, suggest the shortest route to avoid congestion. If the user is bored, suggest modes of transport and routes that are more entertaining."

[1651] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1652] Step 1:

[1653] Accepting customer requests

[1654] The device (smartphone application) accepts a travel request from the user. As input, the user enters their destination and desired mode of transportation into the application. As output, the accepted request information is sent to the server. In concrete terms, the user operates the application interface to select their destination and mode of transportation.

[1655] Step 2:

[1656] Video analysis and emotion recognition

[1657] The device (smartphone) uses a camera and microphone to capture the user's facial expressions and voice in real time. Camera video and audio data are acquired as input. Emotion recognition results are obtained as output. Specifically, the device performs video analysis using OpenCV and recognizes emotions using EmotionRecognizer.

[1658] Step 3:

[1659] Coordinating transportation and routes

[1660] The server selects the optimal means of transportation and route based on the recognized emotion. The emotion recognition results and user request information are sent to the server as input. The optimal means of transportation and route information are determined as output. Specifically, the server uses the MaaSService to suggest the shortest route to avoid congestion if the user is feeling angry, for example.

[1661] Step 4:

[1662] Providing transportation services

[1663] The server calls the nearest autonomous vehicle and arranges for it to transport the user to their destination. The determined transportation method and route information are used as input. The output is that the transportation arrangement has been completed and the user is notified. Specifically, the server sends a request to the autonomous vehicle system, and the vehicle heads to the user's location.

[1664] Step 5:

[1665] Payment Processing

[1666] The server automatically deducts the usage fee using the unified identity payment system. The input is the usage fee information for the mobile service. The output is that the payment has been completed and the user is notified. Specifically, the server deducts the fee from the user's account using ONEIDPayment.

[1667] Step 6:

[1668] Recalibrating as emotions change

[1669] If the user's emotions change while traveling, the device will recognize the emotions again and readjust the means of transportation and route accordingly. Camera footage and audio data from the journey are acquired as input. The readjusted means of transportation and route information are determined as output. Specifically, the device will recognize the emotions again using OpenCV and EmotionRecognizer, and the server will use the MaaSService to suggest new means of transportation and routes.

[1670] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1671] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1672] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[1673] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1674] [Third embodiment]

[1675] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1676] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1677] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1678] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1679] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1680] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1681] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1682] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1683] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1684] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1685] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1686] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1687] "Example 1"

[1688] According to an embodiment of the present invention, there is provided a transportation service platform system, which includes a means for receiving requests from customers, for example, customers can send transportation requests through a smartphone application.

[1689] "Example 2"

[1690] The received request is processed by AI / video analytics, which analyzes the request and determines the optimal means of transportation. For example, based on the request, it can select public transportation, taxis, bike sharing, or other MaaS services.

[1691] "Example 3"

[1692] Based on the results of AI analysis / video analysis, a means of utilizing MaaS is provided. This means provides the selected MaaS service to the customer and realizes transportation. For example, if the customer selects a taxi, the system calls the nearest taxi and transports the customer to their destination. "Example 4"

[1693] Finally, a means of payment for MaaS journeys is provided, which allows customers to pay for the MaaS services they use, for example by automatically debiting the customer's account using the ONEID payment system.

[1694] The processing flow of each embodiment will be described below.

[1695] "Example 1"

[1696] Step 1: A customer accesses the transportation service platform system and submits a transportation request, which includes information such as the origin, destination, and desired departure time.

[1697] Step 2: The system sends the received request to the AI ​​analysis / video analysis means.

[1698] "Example 2"

[1699] Step 1: AI analytics / video analytics analyzes the request and determines the optimal mode of transportation, taking into account current traffic conditions, weather, and the customer's past usage history.

[1700] Step 2: Based on the analysis results, the optimal MaaS service is selected and notified to the customer. "Example 3"

[1701] Step 1: If the customer accepts the proposed MaaS service, the system will provide the service. For example, if a taxi is selected, the system will call the nearest taxi and take the customer to their destination.

[1702] Step 2: Once the customer arrives at their destination, the system confirms the trip is complete.

[1703] "Example 4"

[1704] Step 1: Once the transfer is complete, the system accepts payment from the customer.

[1705] Step 2: The customer pays through the ONEID payment system, which confirms the payment is complete and provides the customer with a receipt.

[1706] Example 1

[1707] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1708] Conventional mobility service platform systems have difficulty quickly and accurately proposing the optimal means of transportation in response to customer requests. Furthermore, there was a lack of standardized payment methods for the proposed means of transportation, which resulted in poor customer convenience. Furthermore, the lack of advanced analysis using AI models meant that the accuracy of the proposals was low.

[1709] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1710] In this invention, the server includes means for accepting customer requests, means for storing the accepted customer requests in a database, means for executing an algorithm for selecting the optimal means of transportation based on the stored requests, means for sending a prompt message to the generative AI model to obtain the optimal means of transportation, means for responding to the customer with the obtained means of transportation, and means for paying for transportation based on the proposed means of transportation. This makes it possible to quickly and accurately propose the optimal means of transportation in response to a customer request and provide a unified payment method.

[1711] The "means for accepting customer requests" is a function that provides an interface for customers to input their departure and destination points to use transportation services and transmit that information to the system.

[1712] The "means for storing received customer requests in a database" is a function for storing request information received from a customer in a database and making it available for subsequent processing.

[1713] "Means for executing an algorithm to select the most suitable means of transportation based on the stored requests" refers to a function that analyzes the request information stored in the database and performs calculations to select the most suitable means of transportation.

[1714] "Means for sending prompts to a generative AI model and obtaining the optimal means of transportation" refers to a function that sends prompts containing specific questions or instructions to a generative AI model and receives suggestions for the optimal means of transportation in response.

[1715] "Means of responding to customers about the acquired transportation method" is a function that notifies customers of the optimal transportation method information acquired from the generative AI model.

[1716] The "means for settling travel based on proposed means of transportation" is a function for carrying out a payment process for the customer to pay for the travel service based on the proposed means of transportation.

[1717] A "unified payment system" is a system that centrally manages multiple payment methods and allows customers to complete payments using any payment method they choose.

[1718] This invention relates to a mobility service platform system that accepts customer requests, proposes optimal means of transportation, and processes payments. This system is composed of a server, terminals, and user elements.

[1719] The server provides an API for accepting customer requests. This API is built using Python and Flask, and has the ability to store received requests in a MySQL database. The server then runs an algorithm to select the optimal transportation mode based on the stored requests. This algorithm is implemented in Python and uses a generative AI model (e.g., a generative AI model) to suggest the optimal transportation mode.

[1720] The terminal provides an interface for customers to submit travel requests. Specifically, it uses a smartphone application developed with React Native. Users input their departure and destination points through this application and submit their requests. The terminal then sends the input information to the server as an HTTP request.

[1721] A user submits a trip request using a smartphone application. After the user enters their origin and destination and presses the send button, the application sends this information to a server. The server receives the request and stores it in a database. The server then runs an algorithm to select the optimal mode of transportation based on the stored request. The algorithm uses a generative AI model to suggest the optimal mode of transportation to the user.

[1722] For example, consider the case where a user uses a smartphone application to send a "travel request from Shinjuku Station to Shibuya Station." When the user enters "Shinjuku Station" as the departure point and "Shibuya Station" as the destination and presses the send button, the application sends this information to a server. The server receives this request and stores it in a database. The server then runs an algorithm to select the optimal mode of transportation based on the stored request. This algorithm uses a generative AI model to make a suggestion to the user, such as "Traveling by train is the best option."

[1723] Examples of prompts to input to a generative AI model might include:

[1724] "A user has requested a trip from Shinjuku Station to Shibuya Station. Please suggest the best means of transportation."

[1725] By inputting this prompt into the generative AI model, the model will suggest the optimal means of transportation. For example, it may give an answer such as, "Traveling by train is best. The journey will take about 10 minutes." The server receives this response and sends it back to the user. The user can then confirm the suggested means of transportation through the application and actually begin traveling.

[1726] In this way, the mobility service platform system can propose the most suitable means of transportation for a user's mobility request and provide a unified payment method.

[1727] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1728] Step 1:

[1729] The user launches the smartphone application.

[1730] Input: User actions

[1731] Output: Application launch

[1732] Specific operation: The user taps the smartphone icon to launch the application. The application is developed with React Native and the initial screen is displayed.

[1733] Step 2:

[1734] The user enters the origin and destination and submits a travel request.

[1735] Input: Origin and destination information

[1736] Output: Move request sent

[1737] Specific operation: The user enters "Shinjuku Station" as the departure point and "Shibuya Station" as the destination in the application interface and presses the send button.

[1738] Step 3:

[1739] The device sends a request to the server.

[1740] Input: User-entered origin and destination information

[1741] Output: HTTP request to the server

[1742] Specific operation: The device sends the input information to the server as an HTTP request. This communication uses the HTTPS protocol.

[1743] Step 4:

[1744] The server receives the request and stores it in a database.

[1745] Input: HTTP request from the terminal

[1746] Output: Save to database

[1747] Specific operation: The server receives requests through an API built using Flask and saves a "travel request from Shinjuku Station to Shibuya Station" in a MySQL database.

[1748] Step 5:

[1749] The server runs an algorithm based on the stored requests to select the most suitable mode of transportation.

[1750] Input: Request information stored in the database

[1751] Output: Selection of optimal transportation mode

[1752] Specific operation: The server runs an algorithm implemented in Python and selects the optimal means of transportation, taking into account past data and current traffic conditions.

[1753] Step 6:

[1754] The server sends a prompt to the generative AI model to obtain the optimal means of transportation.

[1755] Input: Prompt text (e.g., "The user requests to travel from Shinjuku Station to Shibuya Station. Please suggest the best mode of transportation.")

[1756] Output: The response from the generative AI model

[1757] Specific operation: The server sends a prompt to the generative AI model and receives a response from the model such as, "Traveling by train is best. The journey takes about 10 minutes."

[1758] Step 7:

[1759] The server returns the acquired means of transportation to the user.

[1760] Input: Response from a generative AI model

[1761] Output: Reply to the user

[1762] Specific operation: The server receives the response from the generative AI model and notifies the user of the content. The user then confirms the proposed transportation method through the application.

[1763] Step 8:

[1764] The user confirms the proposed transportation options.

[1765] Input: Response from the server

[1766] Output: Check transportation method

[1767] Specific operation: The user confirms the proposed means of transportation through the application and actually starts traveling.

[1768] (Application example 1)

[1769] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1770] Conventional mobility service platform systems have had the problem of making it difficult to quickly and efficiently summon the most suitable autonomous vehicle when a customer submits a travel request. Furthermore, they lack the functionality to accurately input the customer's current location and destination and suggest the optimal route, which reduces the efficiency of travel.

[1771] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1772] In this invention, the server includes means for accepting customer requests, means for performing AI analysis / video analysis of the accepted customer requests, means for utilizing transportation services based on the results of the AI ​​analysis / video analysis, means for paying for transportation using the transportation services, means for inputting the customer's current location and destination, and means for calling the optimal self-driving vehicle, thereby enabling customers to quickly and efficiently call an autonomous vehicle using their smartphone and reach their destination via the optimal route.

[1773] "Customer Request" means a request submitted by a Customer to utilize the Mobility Services.

[1774] "AI analytics" is the process of using artificial intelligence to analyze data and extract meaningful information.

[1775] "Video analysis" is a technology that analyzes video data obtained from cameras and sensors and extracts specific information.

[1776] "Transportation services" refers to transportation means and services provided to customers to travel to their destinations.

[1777] "Payment method" refers to a method or system for paying for the service.

[1778] "Current location" refers to the location where the customer is currently located.

[1779] A "destination" is where a customer wants to go.

[1780] An "autonomous vehicle" is a vehicle that is driven automatically using artificial intelligence and sensors.

[1781] An "optimal route" is the most efficient route from a departure point to a destination, taking into account factors such as time, distance, and traffic conditions.

[1782] "Unified authentication and payment" refers to an authentication and payment system that can be used across multiple services and platforms.

[1783] A system for implementing this invention is configured as follows: First, a user sends a travel request using a smartphone. A dedicated application is installed on the smartphone, and the user can input their current location and destination through this application.

[1784] When the server receives a request from a user, it performs AI analysis and video analysis of the request. Software such as Python and TensorFlow is used for AI analysis, and libraries such as OpenCV are used for video analysis. This allows the server to analyze data such as the user's current location, destination, and traffic conditions, and select the optimal autonomous vehicle.

[1785] Next, the server will call the most suitable self-driving vehicle based on the analysis results. The self-driving vehicle is equipped with GPS and various sensors, and collects data in real time to drive the optimal route to the destination.

[1786] After the transfer is complete, the server settles the transfer service fee. The payment method is a unified authentication payment system. This allows users to use multiple services with a single authentication, improving convenience.

[1787] As a concrete example, consider the case where a user requests an autonomous taxi from Tokyo Station to Tokyo Tower. The user opens a smartphone app and enters the latitude and longitude of Tokyo Station (35.6895, 139.6917) as their current location and the latitude and longitude of Tokyo Tower (35.6586, 139.7454) as their destination. The server receives this information, selects the most suitable autonomous vehicle, and dispatches it to the user.

[1788] An example of a prompt is as follows:

[1789] Consider a scenario where a user requests a self-driving taxi using a smartphone app. The user enters their current location and destination and calls the best available self-driving taxi. Write a Python program to send a request to the taxi service using an API key and receive the response.

[1790] In this way, users can quickly and efficiently summon an autonomous vehicle using their smartphone to reach their destination along the optimal route.

[1791] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1792] Step 1:

[1793] The user starts the smartphone app and inputs their current location and destination. The input data of the current location and destination is sent to the application as latitude and longitude information, which generates a travel request for the user.

[1794] Step 2:

[1795] The device sends the user's travel request to the server. The server analyzes the received request and obtains the latitude and longitude information of the current location and destination. Based on this information, the travel request processing begins.

[1796] Step 3:

[1797] The server then performs AI and video analysis on the received latitude and longitude information, using TensorFlow for the AI ​​analysis and OpenCV for the video analysis. This allows the server to analyze data such as traffic and road conditions and calculate the optimal route.

[1798] Step 4:

[1799] The server selects the most suitable autonomous vehicle based on the results of AI analysis and video analysis. Information about the selected autonomous vehicle is then sent from the server to the device, allowing the user to know which vehicle will respond to their request.

[1800] Step 5:

[1801] The terminal displays the information about the autonomous vehicle received from the server to the user. The user confirms the displayed information and confirms the request. This confirmation information is then sent back to the server.

[1802] Step 6:

[1803] The server receives the user's request confirmation and issues instructions to the self-driving vehicle. The self-driving vehicle uses GPS and various sensors to head to the user's current location. This allows the self-driving vehicle to be dispatched to the user's location.

[1804] Step 7:

[1805] When the autonomous vehicle arrives at the user's current location, the user gets in the vehicle and starts traveling toward the destination. The vehicle travels according to the optimal route provided by the server.

[1806] Step 8:

[1807] Once the transfer is complete, the server calculates the transfer service fee and charges the fee via the payment method. The payment is made using a unified authentication payment system, which allows the user to pay the fee with a single authentication.

[1808] Step 9:

[1809] The server notifies the terminal that the payment has been completed. The terminal then displays a notification of the payment completion to the user, allowing the user to confirm that the use of the mobile service has been completed.

[1810] Example 2

[1811] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1812] Conventional transportation suggestion systems have difficulty quickly and accurately suggesting the optimal transportation method in response to a user's request. Furthermore, when using multiple transportation methods in an integrated manner, payment methods are complicated, reducing user convenience.

[1813] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1814] In this invention, the server includes means for accepting customer requests, means for performing AI analysis / video analysis of the accepted customer requests, means for determining a means of transportation based on the results of the AI ​​analysis / video analysis, means for providing information on the determined means of transportation to the customer, and means for paying for the use of the means of transportation. This makes it possible to quickly and accurately propose the most suitable means of transportation in response to a user's request and to simplify payment methods when using multiple means of transportation in an integrated manner.

[1815] The "means for accepting customer requests" is an interface for receiving requests and information regarding travel from users.

[1816] "AI analysis / video analysis means" is a system that uses artificial intelligence and video analysis technology to analyze received customer requests and identify the optimal means of transportation.

[1817] "Means for determining the means of transportation" refers to the algorithms and processes for selecting the most suitable means of transportation for the user based on the results of AI analysis / video analysis.

[1818] The "means for providing the customer with information about the selected transportation means" refers to an interface or communication means for notifying the user of detailed information about the selected transportation means.

[1819] The "means for paying for the use of transportation" refers to a payment system that allows a user to pay the fee when using the selected transportation.

[1820] An "integrated payment system" is a payment platform for processing fees for multiple means of transportation in one go.

[1821] MODE FOR CARRYING OUT THE INVENTION

[1822] The present invention is a system for making optimal suggestions when a user selects a means of transportation and for easily paying for the use of that means of transportation. Specific embodiments of this system are described below.

[1823] System configuration

[1824] The system consists of the following major components:

[1825] 1. How we receive customer requests

[1826] Users use devices such as smartphones or PCs to input travel requests, such as "I want the fastest way from Shinjuku to Shibuya."

[1827] 2. AI analysis / video analysis methods

[1828] The server passes the received customer request to an AI analytics / video analysis method, which analyzes the request content using a machine learning model implemented in Python (e.g., TensorFlow or PyTorch).

[1829] 3. How to decide on transportation

[1830] AI analytics / video analytics analyzes the request content and identifies the transportation method that best suits the user's needs. For example, it references public transportation timetable databases (e.g., GTFS data) to calculate the optimal train or bus route. It also uses APIs for taxi and bike-sharing services (e.g., taxi API and bike-sharing API) to obtain real-time availability and fare information.

[1831] 4. Means of providing customers with information about their chosen transportation options

[1832] The server then sends information about the selected transportation method to the terminal, including the specific route, travel time, and fare.

[1833] 5. Means of payment for transportation

[1834] The server provides a payment system for the user to pay for the transportation means selected by the user, which uses an integrated payment system to process the fees for multiple transportation means in a single transaction.

[1835] Specific examples

[1836] For example, if a user requests "the fastest way to get from Shinjuku to Shibuya," the process proceeds as follows:

[1837] 1. The user types "I want to travel from Shinjuku to Shibuya the fastest" into their smartphone and presses the send button.

[1838] 2. The device sends this request to the server.

[1839] 3. The server receives the request and passes it to the AI ​​analysis / video analysis method.

[1840] 4. AI analytics / video analytics analyzes the request and identifies the best means of transportation, for example, by consulting train timetables and calculating the optimal route.

[1841] 5. Based on the analysis results, the server determines which train is the fastest and determines the route information.

[1842] 6. The server sends the determined route information to the terminal.

[1843] 7. The device displays to the user, "The best route from Shinjuku to Shibuya is the 15:10 train."

[1844] 8. The user selects a means of transportation based on the displayed information and begins traveling.

[1845] 9. The server uses an integrated payment system to process the user's transportation fees in one lump sum.

[1846] Prompt Sentence Examples

[1847] "I want to get from Shinjuku to Shibuya as quickly as possible. It's currently 3:00 PM. What is the best way to get there?"

[1848] By inputting this prompt into a generative AI model, the system suggests the most optimal means of transportation for the user.

[1849] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1850] Step 1:

[1851] The user submits a request.

[1852] A user uses a device such as a smartphone or PC to input a travel request and press the send button. The input includes information such as the current location, destination, and desired mode of transportation. The output is the request data sent from the device to the server.

[1853] Step 2:

[1854] The device sends a request to the server.

[1855] The terminal sends the request entered by the user to the server as an HTTP request. The input is the request data entered by the user, and the output is the request data sent to the server.

[1856] Step 3:

[1857] The server receives the request and passes it to the AI ​​analysis / video analysis means.

[1858] The server passes the request received from the terminal to the AI ​​analysis / video analysis means for analysis. The input is the request data received from the terminal, and the output is the request data passed to the AI ​​analysis / video analysis means.

[1859] Step 4:

[1860] AI analysis / video analysis tools analyze the request.

[1861] The AI ​​analysis / video analysis method analyzes the content of the request using a machine learning model implemented in Python (e.g., TensorFlow or PyTorch). The input is the request data passed from the server, and the output is the analysis results. Specifically, it analyzes the content of the request and identifies the transportation method that best suits the user's needs.

[1862] Step 5:

[1863] The server determines the optimal means of transportation based on the analysis results.

[1864] The server receives the analysis results from the AI ​​analysis / video analysis means and determines the optimal means of transportation for the user. The input is the analysis results from the AI ​​analysis / video analysis means, and the output is information on the determined means of transportation. Specifically, it refers to a public transportation timetable database (e.g., GTFS data) to calculate the optimal train or bus route. It also uses the APIs of taxi and bicycle sharing services (e.g., taxi API and bicycle sharing API) to obtain real-time availability and fare information.

[1865] Step 6:

[1866] The server transmits information about the determined means of transportation to the terminal.

[1867] The server sends information about the selected transportation mode to the terminal. The input is the information about the selected transportation mode, and the output is the information about the transportation mode sent to the terminal. Specific operations include information about the specific route, required time, fare, etc.

[1868] Step 7:

[1869] The device displays the most suitable means of transportation for the user.

[1870] The terminal displays the information received from the server to the user. The input is the information about the means of transportation received from the server, and the output is the information about the means of transportation displayed to the user. In concrete terms, the user can select the most suitable means of transportation based on the displayed information and start traveling.

[1871] Step 8:

[1872] The server settles the transportation fee.

[1873] The server provides a payment system for users to pay for the transportation they select. The input is the user's transportation usage information, and the output is confirmation of payment completion. Specifically, the integrated payment system is used to process the fees for multiple transportation methods in a lump sum.

[1874] (Application example 2)

[1875] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1876] In modern society, the variety of transportation methods is increasing, but users need to collect and compare a lot of information to choose the most suitable transportation method. This requires users to spend time and effort, making it difficult to travel efficiently. In addition, the complexity of reserving and paying for transportation methods reduces user convenience. Furthermore, if real-time route guidance is not provided, users may get lost during their trip.

[1877] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1878] In this invention, the server includes means for accepting customer requests, means for performing AI analysis / video analysis of the accepted customer requests, means for utilizing MaaS based on the results of the AI ​​analysis / video analysis, means for paying for travel using MaaS, means for proposing the optimal means of transportation, means for providing real-time route guidance based on the proposed means of transportation, and means for checking reservations and usage status of autonomous vehicles. This allows users to easily select the optimal means of transportation and enables efficient travel. Furthermore, by simplifying reservations and payments for transportation and providing real-time route guidance, user convenience is greatly improved.

[1879] "Customer Request" means a travel request or desire entered into the System by a User.

[1880] "AI analysis / video analysis" is the process of using artificial intelligence technology to analyze customer requests and related video data to determine the most appropriate means of transportation.

[1881] "MaaS" stands for Mobility as a Service and refers to a service that integrates and provides multiple means of transportation.

[1882] "Payment method" means a method or system by which a user pays for the use of a mobility service.

[1883] "Optimal transportation" refers to the most efficient and convenient way of transportation based on the user's request and circumstances.

[1884] "Means for providing route guidance in real time" refers to a system that provides real-time guidance on the optimal route based on the user's current location information while they are traveling.

[1885] "Means for checking reservations and usage status of self-driving vehicles" refers to a system that allows users to reserve self-driving vehicles and check their usage status.

[1886] "Unified authentication payment" is a payment method that integrates multiple payment methods into a single authentication system, allowing users to make payments easily.

[1887] A system for implementing this invention has the following configuration: First, a user inputs a destination and a request for travel using a terminal such as a smartphone. The terminal then transmits this request to a server.

[1888] The server analyzes the received customer requests using AI analysis / video analysis methods. This analysis is achieved by using Python and the Requests library and calling the AI ​​analysis API. Based on the analysis results, the server determines the optimal means of transportation and suggests it to the user.

[1889] The server then provides real-time route guidance based on the proposed transportation options, using GPS data and map information to calculate the optimal route from the user's current location to their destination. The server also provides a way to reserve and check the availability of autonomous vehicles, allowing users to easily reserve an autonomous vehicle and check its availability in real time.

[1890] The payment method used is unified authentication payment, which allows users to integrate multiple payment methods into a single authentication system and make payments easily.

[1891] For example, if a user requests to go to Tokyo Station, the server will suggest that the best way to get from Shibuya Station to Tokyo Station is by train and provide real-time route guidance. If the user wants to use an autonomous vehicle, the server will support the reservation and confirmation of its usage status.

[1892] An example of a prompt sentence is as follows:

[1893] "Create an application where the user inputs their destination and the AI ​​suggests the best means of transportation and provides real-time route guidance. Include a function that determines the best means of transportation by taking into account the user's current location, destination, and transportation preferences (cost, time, etc.)."

[1894] This allows users to easily select the most suitable means of transportation, enabling efficient travel. It also simplifies travel reservations and payments, and provides real-time route guidance, greatly improving user convenience.

[1895] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1896] Step 1:

[1897] The user inputs a destination and a travel request using a device such as a smartphone.

[1898] Input: User's destination, current location, transportation preferences (cost, time, etc.)

[1899] Output: Request data (e.g., JSON format)

[1900] Specific operation: The user enters their destination and preferred mode of transportation into the application's input form and presses the submit button.

[1901] Step 2:

[1902] The terminal transmits the request data to the server.

[1903] Input: Request data

[1904] Output: Request data sent to the server

[1905] Specific operation: The terminal uses an HTTP POST request to send request data to the server.

[1906] Step 3:

[1907] The request data received by the server is analyzed using AI analysis / video analysis methods.

[1908] Input: Request data

[1909] Output: Analysis results (optimal means of transportation)

[1910] How it works: The server calls the AI ​​analytics API and analyzes the request data using Python and the Requests library.

[1911] Step 4:

[1912] The server determines the optimal means of transportation based on the analysis results and suggests it to the user.

[1913] Input: Analysis results

[1914] Output: Recommendation of optimal transportation method

[1915] Specific operation: Based on the analysis results, the server determines the optimal means of transportation (e.g., train, self-driving vehicle, etc.) and notifies the user.

[1916] Step 5:

[1917] The server provides real-time route guidance based on the proposed means of travel.

[1918] Input: Best mode of transportation, current user location

[1919] Output: Real-time directions

[1920] Specific operation: The server uses GPS data and map information to calculate the optimal route from the user's current location to their destination and provides real-time guidance.

[1921] Step 6:

[1922] The server provides a means to check reservations and usage status of autonomous vehicles.

[1923] Input: User's booking request

[1924] Output: Reservation confirmation, usage status notification

[1925] Specific operation: The server accesses the autonomous vehicle reservation system, processes the user's reservation request, checks the usage status, and notifies the user.

[1926] Step 7:

[1927] The server settles the mobile service fee using unified authentication and settlement.

[1928] Input: User's payment information

[1929] Output: Payment completion notification

[1930] Specific operation: The server uses the unified authentication and payment system to process the user's payment information and pay the usage fee. After the payment is completed, the server notifies the user.

[1931] Example 3

[1932] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1933] Conventional mobility service systems have difficulty responding quickly and appropriately to customer requests, particularly in accurately determining the customer's current location and the optimal means of transportation. Furthermore, payment methods are complicated, making them inconvenient for customers. This has led to issues such as lower customer satisfaction and a decrease in the frequency of service use.

[1934] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1935] In this invention, the server includes means for accepting customer requests, means for performing artificial intelligence analysis and video analysis of the accepted customer requests, means for utilizing transportation services based on the results of the artificial i...

Claims

1. a means for accepting customer requests; means for storing the customer request received by the receiving means in a database; means for executing an algorithm for selecting an optimal transportation mode based on the requests stored in said storing means; A means for sending a prompt sentence to a generative AI model based on a result of execution by the means for executing the algorithm, and obtaining an optimal means of transportation; A means for proposing the transportation means acquired by the acquiring means to a customer; means for settling travel based on the travel means proposal proposed by said proposing means; A system including:

2. The system of claim 1 , further comprising: means for suggesting an optimal route to a customer's destination based on the optimal means of transportation obtained from the generative AI model.

3. The system of claim 1 , wherein the means for settling the transfer further comprises means for using a unified payment system.

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