System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving distance-to-empty information; means for acquiring position information; means for receiving destination information; means for acquiring peripheral charging spot information based on the position information; means for acquiring peripheral sightseeing spot information based on the position information; AI means for integrating the charging spot information and the sightseeing spot information to generate a drive plan enjoyable during charging; means for transmitting the generated drive plan to a user device; and means for displaying the drive plan on the user device.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] Charging an electric vehicle (EV) typically takes 2-3 hours, so drivers need to plan how to spend this time while charging. However, finding a nearby spot where they can have fun while charging is time-consuming, and there are few spots that combine charging facilities with dining and drinking establishments, making it difficult to make effective use of the charging time overall. It is also time-consuming for EV owners to plan their own drive that will allow them to spend the time efficiently and comfortably while charging. Therefore, a system is needed that allows EV owners to spend the time while charging in an enjoyable and meaningful way. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for receiving and acquiring information on electric vehicle (EV) driving range, location, and destination, acquires information on nearby charging spots and tourist spots based on the location information, and uses AI means for integrating the charging spot information and tourist spot information to generate an optimal driving plan that can be enjoyed while charging. This system transmits the generated driving plan to a user's terminal and displays the driving plan on the user's terminal. Furthermore, the system can also acquire information on nearby dining facilities and propose dining plans that can be enjoyed while charging. Furthermore, the AI ​​means generates the optimal plan using information updated in real time, and the plan is displayed on the user's terminal using a map display function, making it easy for the user to intuitively understand.

[0006] "Drivable distance information" is data indicating the distance that an electric vehicle can travel with the current remaining battery charge.

[0007] "Location information" is data indicating your current location obtained by GPS or other positioning means.

[0008] "Destination information" is data indicating the location of a destination set by the user.

[0009] "Charging spot information" is data relating to the location and usage status of charging stations where electric vehicles can be charged.

[0010] "Tourist attraction information" is data about tourist attractions and entertainment facilities that users can visit.

[0011] "AI means" means means including an algorithm and a processing device that uses artificial intelligence to analyze data and generate an optimal driving plan.

[0012] A "drive plan" is a suggested plan that includes sightseeing routes and schedules that can be enjoyed while charging.

[0013] "User terminal" refers to a device such as a smartphone or tablet owned by a user, which is used to receive and display plans from the system.

[0014] The "map display function" is a function that displays a map on the user terminal and overlays information on it.

[0015] "Dining facility information" is data about dining facilities, such as restaurants and cafes, that can be used while charging. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of the time while charging and provides them with an enjoyable driving plan. This system is implemented through the following specific configuration and processing.

[0038] Users launch a dedicated app on their smartphone, tablet, or other user device and request the creation of a driving plan. At this time, the user device automatically obtains current location information using GPS. At the same time, destination information entered by the user is also obtained.

[0039] The user terminal receives information about the remaining driving distance from the electric vehicle, and transmits information about the current location, remaining driving distance, and destination to the server. The server receives this information and, based on the information provided by the user terminal, retrieves information about nearby charging spots and tourist spots from a database.

[0040] The server uses AI to integrate the acquired charging spot information and tourist spot information and generate an optimal driving plan for enjoying the ride while charging. Furthermore, if necessary, it also acquires information on nearby dining facilities and proposes an optimal dining plan. In this case, the AI ​​utilizes information updated in real time and generates a driving plan based on the most recent information.

[0041] The generated driving plan is sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. For example, the locations of charging spots, tourist spots, and suggested restaurants are displayed on the map, and the route to take while charging is also visually displayed.

[0042] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the user's device sends information about the current location in Tokyo, the remaining driving distance of 100 km, and the destination, Yokohama, to the server. Information provided by the in-vehicle system is also sent to the server.

[0043] The server selects the optimal charging spot between the user's current location and destination, and uses AI to generate a driving plan that includes nearby dining facilities (e.g., cafes and restaurants) and tourist attractions (e.g., museums, parks, etc.) that can be enjoyed while charging.

[0044] The generated plan is sent to the user's device, and the user can view it in the app. For example, the plan may suggest a stop for breakfast at a cafe while the user is charging, or a visit to a museum within walking distance.

[0045] In this way, the present invention provides electric vehicle owners with a system that proposes optimal driving plans that allow them to spend their charging time in a fun and meaningful way. As a result, EV owners can use their charging time efficiently and enjoy a more fulfilling driving experience.

[0046] The processing flow will be explained below.

[0047] Step 1:

[0048] A user requests a driving plan.

[0049] Operation: The user launches the dedicated app and presses the "Create a Drive Plan" button. The user inputs their destination and sets their current location and destination information.

[0050] Step 2:

[0051] The terminal transmits current location information, remaining driving distance, and destination information to the server.

[0052] How it works: The device uses GPS to determine its current location and receives driving range information from the in-vehicle system. It then sends this data, along with the destination information entered by the user, to the server.

[0053] Step 3:

[0054] The on-board system provides the terminal with information on the EV's driving range and estimated arrival time.

[0055] How it works: The onboard system monitors battery status and calculates the current driving range. It also calculates the estimated time of arrival based on current traffic conditions and sends it to the terminal.

[0056] Step 4:

[0057] The server acquires information about nearby charging spots and tourist spots based on user information and vehicle information.

[0058] Operation: The server searches a database based on the received current location information to obtain the latest information on nearby charging spots and tourist attractions. Charging spot information includes the location and availability of available charging stations. Tourist attraction information includes the location and business status of parks, museums, restaurants, etc.

[0059] Step 5:

[0060] The server uses AI to analyze charging spot information and tourist spot information and generate the optimal driving plan.

[0061] How it works: The server inputs the acquired charging spot information and tourist spot information into an AI algorithm, and creates an optimal driving plan based on the user's current location, destination, and available driving distance. The AI ​​makes suggestions by combining the location of charging spots, charging times, and the opening hours of nearby tourist spots and restaurants.

[0062] Step 6:

[0063] The server transmits the generated drive plan to the user terminal.

[0064] Operation: The server sends the generated driving plan to the user's device, which includes information on suggested charging spots and nearby tourist attractions and restaurants.

[0065] Step 7:

[0066] The terminal displays the received plan to the user.

[0067] How it works: The device displays the received driving plan in the app, and the user can use the map view to visually confirm the location of charging spots and tourist attractions, as well as the proposed route.

[0068] As a concrete example, if a user drives from Tokyo to Yokohama, the system will suggest the best charging spot (for example, a charging station with a cafe attached in Tokyo) and nearby tourist attractions (for example, a nearby art museum) when charging is required. The user can check the proposed plan in the app and spend the time while charging meaningfully.

[0069] Example 1

[0070] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0071] Electric vehicle (EV) owners must spend a certain amount of time charging their vehicles, but there are limited ways to make effective use of that time. In particular, how to spend time while charging has become a difficult issue, and there is a demand for efficient and meaningful ways to spend that time.

[0072] 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.

[0073] In this invention, the server includes means for acquiring current location information by an acquisition device, means for receiving destination information by an input device, means for receiving mileage information, means for acquiring information on surrounding charging facilities based on the location information, means for acquiring information on surrounding tourist facilities based on the location information, generation AI means for integrating the charging facility information and the tourist facility information to generate a driving plan that can be enjoyed while charging, means for transmitting the generated driving plan to an information processing device, and means for displaying the driving plan on a display device. This makes it possible to effectively utilize time while charging and provide a driving plan that is enjoyable for the user.

[0074] The "acquisition device" is a device for acquiring current location information.

[0075] An "input device" is a device for receiving destination information.

[0076] "Driving distance information" is information relating to the distance that an electric vehicle can travel.

[0077] "Location information" is information indicating the current geographical location obtained from a user terminal or an in-vehicle system.

[0078] "Charging facility information" is information about facilities for charging electric vehicles.

[0079] "Tourist facility information" is information about tourist spots that users can visit.

[0080] "Generative AI means" refers to a means that utilizes artificial intelligence technology to generate optimal driving plans based on acquired information.

[0081] The "information processing device" is a device for transmitting the generated driving plan to the user terminal.

[0082] A "display device" is a device for displaying a driving plan on a user terminal.

[0083] A "drive plan" is a plan for a travel route that includes tourist spots and dining facilities that can be enjoyed while charging.

[0084] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of their charging time and provide enjoyable driving plans. This system uses hardware and software to perform various data processing and calculations and generate driving plans that are meaningful to the user.

[0085] The user launches a dedicated app on a device such as a smartphone or tablet. The app automatically obtains the user's current location information using GPS. At the same time, it also obtains the destination information entered by the user. The device receives driving range information from the in-vehicle system and sends this information to the server.

[0086] Based on the received information and location information, the server retrieves information on nearby charging facilities and tourist facilities from a database. Detailed information on charging facilities and tourist facilities is stored in the database. The server then uses a generative AI model to integrate the retrieved charging facility information and tourist facility information to generate an optimal driving plan for enjoying the ride while charging. If necessary, the server also retrieves information on nearby dining facilities and suggests an optimal dining plan. This generative AI model generates driving plans based on information updated in real time.

[0087] The generated driving plan is sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. Specifically, the locations of charging stations, tourist facilities, and suggested restaurants are displayed on the map, and the route to take while charging is visually displayed.

[0088] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the device sends information about the current location in Tokyo, the remaining driving distance of 100 km, and the destination, Yokohama, to the server. Information provided by the in-vehicle system is also sent to the server.

[0089] The server selects the optimal charging facility between the user's current location and destination, and uses a generative AI model to generate a driving plan that can be enjoyed while charging, including nearby dining facilities (e.g., cafes and restaurants) and tourist facilities (e.g., museums and parks). An example of a prompt sentence to input into the generative AI model at this time is, "The user's current location is Tokyo, and the destination is Yokohama. The driving distance is 100 km. Please generate a driving plan between Tokyo and Yokohama that includes the optimal charging facility and nearby tourist facilities and dining facilities. Please also provide map information to visualize the generated plan."

[0090] The generated plan is sent to the user's device, where the user can view it in the app. For example, the plan may suggest a stop for breakfast at a cafe while the user is charging, or a visit to a museum within walking distance. In this way, the present invention provides a system that suggests optimal driving plans to electric vehicle owners that allow them to spend their charging time in a fun and meaningful way. As a result, EV owners can use their charging time efficiently and enjoy a more fulfilling driving experience.

[0091] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0092] Step 1:

[0093] The user launches the dedicated app and requests the creation of a driving plan.

[0094] Input: User launches app

[0095] Output: App launch screen

[0096] How it works: The user taps the dedicated app on their smartphone or tablet to launch it, then taps the "Create a driving plan" button to request the creation of a plan.

[0097] Step 2:

[0098] The device obtains current location and destination information

[0099] Input: User's current location and destination information

[0100] Output: Current location and destination information data

[0101] Operation: The device uses the built-in GPS to obtain the user's current location and simultaneously receives the destination (e.g. Yokohama) entered by the user in the app.

[0102] Step 3:

[0103] The device receives the driving range information.

[0104] Input: Range information from electric vehicle

[0105] Output: Driving distance information data

[0106] How it works: The device receives battery status and range information (e.g., 100km) from the vehicle's system via Bluetooth or Wi-Fi.

[0107] Step 4:

[0108] The device sends all information to the server

[0109] Input: current location information, destination information, remaining driving distance information

[0110] Output: Sending information to the server

[0111] Operation: The device compiles the collected current location information, destination information, and remaining driving distance information and sends it to a server via the Internet.

[0112] Step 5:

[0113] The server retrieves information about nearby charging facilities and tourist facilities from a database.

[0114] Input: current location information, destination information

[0115] Output: Charging facility information, tourist facility information data

[0116] Operation: Based on the received information, the server searches the database for and obtains information about charging facilities and tourist facilities located between the user's current location and the destination.

[0117] Step 6:

[0118] The server generates an optimal driving plan using the generative AI model

[0119] Input: current location information, destination information, driving range information, charging facility information, tourist facility information

[0120] Output: Data for optimal driving plans

[0121] Operation: The server inputs the acquired charging facility information and tourist facility information into the generative AI model. The generative AI model generates an optimal driving plan based on the prompt: "The user's current location is Tokyo, and their destination is Yokohama. The driving distance is 100 km. Please generate a driving plan between Tokyo and Yokohama that includes the optimal charging facilities and surrounding tourist facilities and restaurants. Please also provide map information to visualize the generated plan."

[0122] Step 7:

[0123] The server sends the generated driving plan to the terminal.

[0124] Input: Data for optimal drive planning

[0125] Output: Sending the driving plan to the user's terminal

[0126] Operation: The server transmits the generated drive plan data to the user terminal via the Internet.

[0127] Step 8:

[0128] The device displays the driving plan

[0129] Input: Data for optimal drive planning

[0130] Output: Drive plan display on the app

[0131] Operation: The device displays the received driving plan data on the screen of a dedicated app. Using a map API (e.g., Google Maps API), the locations of charging stations, tourist attractions, and restaurants are visualized on a map.

[0132] Step 9:

[0133] User confirms driving plan

[0134] Input: Drive plan display on the app

[0135] Output: User confirmation action

[0136] Operation: The user checks the driving plan displayed in the app, including a list of charging spots, a list of nearby tourist attractions and restaurants, and a map showing the location of the plan, allowing the user to intuitively understand the details of the driving plan.

[0137] (Application example 1)

[0138] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0139] Electric vehicle (EV) owners often have limited options for making effective use of the time while their vehicle is charging, which often prevents them from making the most of that time. It is also difficult to determine the need for charging and the current status of charging stations, making it difficult to plan appropriate trips. Therefore, there is a need for a system that allows EV owners to enjoy the time while charging safely and enjoyably.

[0140] 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.

[0141] In this invention, the server includes means for receiving driving range information, means for acquiring location information, means for receiving destination information, means for acquiring information on nearby charging spots based on the location information, means for acquiring information on nearby tourist spots based on the location information, AI means for integrating the charging spot information and the tourist spot information to generate a driving plan that can be enjoyed while charging, means for transmitting the generated driving plan to a user terminal, means for displaying the driving plan on the user terminal, means for determining whether charging is necessary using the location information and driving range information, means for acquiring information on nearby restaurants and tourist spots if charging is necessary based on the determination, and means for integrating the acquired information to generate an optimal driving plan. This allows electric vehicle owners to effectively utilize their time while charging and enjoy everything from selecting a charging spot to sightseeing and dining.

[0142] "Drivable distance information" is information that indicates the distance that an electric vehicle can travel using the power that is charged.

[0143] "Location information" is information that indicates the current geographical location of an electric vehicle or a user terminal.

[0144] "Destination information" is information that indicates the geographical location of the destination set by the user.

[0145] "Charging spot information" is data that indicates the locations and related information of spots where electric vehicles can be charged.

[0146] "Tourist spot information" is data that indicates the locations of tourist spots and tourist attractions and related information.

[0147] "AI means" refers to a means that uses artificial intelligence technology to integrate charging spot information and tourist spot information to generate an optimal driving plan.

[0148] "User terminal" refers to a computing device operated by a user, such as a smartphone or tablet.

[0149] The "means for determining whether charging is necessary" is a means for determining whether the electric vehicle needs additional charging based on the location information and the driving range information.

[0150] "Dining facility information" is data that indicates the location and related information of dining facilities such as restaurants and cafes.

[0151] The "means for generating an optimal driving plan" is a means for integrating the acquired charging spot information, tourist spot information, and dining facility information to create the most beneficial driving plan for the user.

[0152] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of the time while charging and provides them with an enjoyable driving plan. This system is implemented through the following specific configuration and processing.

[0153] The user launches a dedicated app using a user device such as a smartphone or tablet and requests the creation of a driving plan. At this time, the user device automatically obtains current location information using GPS. At the same time, destination information entered by the user is also obtained. The user device receives information about the remaining driving distance from the electric vehicle and transmits the current location, remaining driving distance, and destination information together to the server.

[0154] The server receives this information and, based on the information provided by the user's device, retrieves information on nearby charging spots and tourist spots from a database. Furthermore, using AI tools, the server integrates the retrieved charging spot information and tourist spot information to generate an optimal driving plan for enjoying while charging. In this process, it uses location information and driving range information to determine whether charging is necessary, and also retrieves information on nearby restaurants and other establishments as necessary.

[0155] The generated driving plan is then sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. For example, the locations of charging spots, tourist spots, and suggested dining facilities are displayed on the map, and the route to take while charging is visually displayed.

[0156] To implement this system, specific hardware and software are required on both the server and user devices. The server requires a computer with high processing power, as well as software for data processing using AI technology. On the other hand, smartphones or tablets with GPS functionality are suitable for user devices.

[0157] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the user's device sends information about the user's current location in Tokyo, the remaining driving distance of 100 km, and the destination, Yokohama, to the server. Information provided by the in-vehicle system is also sent to the server. The server selects the optimal charging spot between the user's current location and destination, and uses AI to generate a drive plan that can be enjoyed while charging, including nearby eating and drinking establishments (e.g., cafes and restaurants) and tourist spots (e.g., museums and parks). The generated plan is sent to the user's device, and the user can view it in the app.

[0158] In addition, by using a generative AI model, it is possible to generate even more sophisticated driving plans. For example, the following can be entered as a prompt to suggest the optimal driving plan taking into account the current location and destination of the autonomous vehicle.

[0159] "Please propose the optimal driving plan taking into account the current location and destination of the autonomous vehicle. The current location is Tokyo, latitude 35.6895, longitude 139.6917, and the destination is Yokohama. The electric vehicle has a range of 100 km. Please provide information on charging spots, tourist attractions, and dining facilities."

[0160] This will allow electric vehicle owners to make effective use of the time spent charging, and enjoy everything from choosing a charging location to sightseeing and dining.

[0161] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0162] Step 1:

[0163] The user launches the dedicated app and requests the creation of a driving plan. The user's device automatically acquires the current location information using the GPS function, and receives the destination information entered by the user as well as the driving range information from the electric vehicle.

[0164] Input: User operation, GPS location information, destination information, remaining driving distance information

[0165] Output: Current location information, destination information, and driving distance information sent to the server

[0166] Step 2:

[0167] The user terminal transmits the current location, remaining driving distance, and destination information to the server.

[0168] Input: current location information, destination information, driving distance information

[0169] Output: Consolidated data sent to the server

[0170] Step 3:

[0171] The server acquires information about nearby charging spots and tourist spots from a database based on the received information about the current location, remaining driving distance, and destination.

[0172] Input: current location information, destination information, driving distance information

[0173] Output: Charging spot information, tourist spot information

[0174] Step 4:

[0175] The server uses AI to integrate information on charging spots and tourist spots and generate an optimal driving plan. At this time, it determines whether charging is necessary based on location information and driving range information, and also obtains information on nearby restaurants and other establishments as needed.

[0176] Input: current location information, destination information, driving range information, charging spot information, tourist spot information

[0177] Output: Optimal driving plan

[0178] Step 5:

[0179] The server transmits the generated drive plan to the user terminal.

[0180] Input: Optimal driving plan

[0181] Output: Drive plan data sent to the user's device

[0182] Step 6:

[0183] The user device displays the received drive plan so that the user can intuitively understand it. The user device uses its map display function to display the locations of charging spots, tourist attractions, and suggested dining facilities.

[0184] Input: Drive plan data sent from the server

[0185] Output: Drive plan displayed on the user's device screen

[0186] Step 7:

[0187] The user checks the displayed drive plan and selects an action to enjoy while charging.

[0188] Input: Drive plan displayed on the user's device

[0189] Output: User's action choice

[0190] These steps will enable electric vehicle owners to make the most of their time while charging and enjoy a fulfilling driving experience.

[0191] 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.

[0192] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of their charging time and proposes more enjoyable driving plans. The system of the present invention incorporates emotion recognition technology to propose customized driving plans according to the user's emotional state.

[0193] The user launches a dedicated app using a user device such as a smartphone or tablet and requests the creation of a driving plan. At this time, the user device automatically obtains current location information using GPS. At the same time, destination information entered by the user is also obtained. Furthermore, the emotion engine uses a camera, microphone, and biometric sensors to analyze data such as facial expressions, voice, and heart rate in order to recognize the user's emotional state.

[0194] The user terminal receives information about the remaining driving distance from the electric vehicle and transmits data on the current location, remaining driving distance, destination information, and emotional state to the server. The server receives this information and, based on the information provided by the user terminal, retrieves information about nearby charging spots and tourist spots from a database.

[0195] The server uses AI means to integrate the acquired charging spot information, tourist spot information, and emotional state to generate an optimal driving plan suited to the user's emotional state. For example, if the emotional state indicates stress, it will suggest relaxing spots, and if the emotional state indicates excitement, it will suggest active spots. It also acquires information on nearby dining facilities and proposes an optimal dining plan. The AI ​​means utilizes information updated in real time to generate a driving plan based on the most recent information.

[0196] The generated driving plan is sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. For example, the locations of charging spots, tourist spots, and suggested restaurants are displayed on the map, and the route to take while charging is also visually displayed.

[0197] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the user's device sends to the server information about the user's current location in Tokyo, the remaining distance of 100 km, and the destination Yokohama, as well as emotional state data obtained through the emotion engine. Information provided by the in-vehicle system is also sent to the server.

[0198] The server selects the optimal charging spot between the user's current location and destination, and uses AI to generate a driving plan that includes suitable nearby tourist attractions and dining options to enjoy while charging based on the user's emotional state. For example, if the user indicates a desire to relax, the server will suggest a plan that includes a charging station with a quiet cafe attached and a nearby park.

[0199] In this way, the present invention provides a system that proposes optimal driving plans to electric vehicle owners, allowing them to spend their charging time in a fun and meaningful way. This allows EV owners to use their charging time efficiently and enjoy a more fulfilling driving experience. The introduction of an emotion engine allows for plans customized according to the user's emotional state, further increasing user satisfaction.

[0200] The processing flow will be explained below.

[0201] Step 1:

[0202] A user requests a driving plan.

[0203] How it works: The user launches the app and presses the "Create a Drive Plan" button. The user then enters their destination, and emotional state data is collected using a facial recognition camera, microphone, and biometric sensors.

[0204] Step 2:

[0205] The terminal transmits current location information, remaining driving distance, and destination information to the server.

[0206] Operation: The device obtains the user's current location using GPS and receives the driving range fetched from the in-vehicle system. It then sends this data along with the destination information entered by the user to the server. It also simultaneously sends the emotional state data obtained by the emotion engine.

[0207] Step 3:

[0208] An emotion engine analyzes the user's emotional state.

[0209] How it works: The emotion engine analyzes collected data such as the user's facial expressions, tone of voice, and heart rate to determine their current emotional state, such as stress, anxiety, or relaxation.

[0210] Step 4:

[0211] The server acquires information about nearby charging spots and tourist spots based on user information, vehicle information, and emotional state.

[0212] Operation: The server searches a database based on the received current location information to obtain the latest information on nearby charging spots and tourist attractions. Charging spot information includes the location and availability of available charging stations. Tourist attraction information includes the location and business status of parks, museums, restaurants, etc.

[0213] Step 5:

[0214] The server uses AI to analyze charging spot information and tourist spot information and generate the optimal driving plan.

[0215] How it works: The server inputs the acquired charging spot and tourist spot information into an AI algorithm, which then creates an optimal driving plan based on the user's current location, destination, driving range, and emotional state. The AI ​​makes suggestions by combining the location of charging spots, charging times, and the opening hours of nearby tourist spots and restaurants. For example, if the user is feeling anxious, it will suggest relaxing parks or spa facilities.

[0216] Step 6:

[0217] The server transmits the generated drive plan to the user terminal.

[0218] Operation: The server sends the generated driving plan to the user's device. This plan includes information on the proposed charging spots and nearby tourist attractions and dining options.

[0219] Step 7:

[0220] The terminal displays the received plan to the user.

[0221] How it works: The device displays the received driving plan in the app, and the user can use the map view to visually confirm the location of charging spots and tourist attractions, as well as the proposed route.

[0222] As a concrete example, if a user drives from Tokyo to Yokohama, the system will suggest the best charging spot (for example, a charging station with a cafe attached in Tokyo) and nearby tourist attractions (for example, a nearby temple or park) when charging is required. If the user indicates an emotional state that requires relaxation, the system will suggest nearby quiet cafes and relaxation facilities. The user can check the suggested plan in the app and spend the time while charging meaningfully.

[0223] Example 2

[0224] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0225] Electric vehicle (EV) owners often waste time while charging, and there is a need for a way to make efficient use of charging time. Furthermore, conventional drive plan suggestion systems only provide uniform information without considering the user's emotional state, which limits the improvement of user satisfaction.

[0226] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving driving range information, means for acquiring location information, means for receiving destination information, means for collecting emotion data, means for acquiring information on nearby charging spots based on the location information, means for acquiring information on nearby tourist spots based on the location information, means for acquiring information on nearby eating and drinking facilities, AI means for integrating the charging spot information, tourist spot information, eating and drinking facility information, and emotion data to generate a driving plan that can be enjoyed while charging, means for transmitting the generated driving plan to the user terminal, and means for displaying the driving plan on the user terminal. This allows the server to provide a driving plan customized according to the user's emotional state, making it possible to spend charging time meaningfully.

[0227] "Drivable distance information" is information that indicates the distance that the electric vehicle can travel with the current remaining battery charge.

[0228] "Location information" is information indicating the current geographical location of a user or vehicle obtained by GPS or other location measurement means.

[0229] "Destination information" is information that indicates the geographical location of the destination set by the user.

[0230] "Emotion data" is data that indicates the emotional state of a user, obtained by analyzing the user's facial expression, voice, biological information, and the like.

[0231] "Charging spot information" is information about locations where electric vehicles can be charged.

[0232] "Tourist attraction information" is information about tourist attractions that the user can visit.

[0233] "Dining facility information" is information about facilities where users can enjoy eating and drinking.

[0234] "AI means" refers to a means of analyzing data using artificial intelligence technology and generating a driving plan suitable for the user.

[0235] A "user terminal" is a smartphone, tablet, or other information device operated by a user.

[0236] A "drive plan" is a plan that suggests sightseeing, dining, and other activities that can be enjoyed while the user is traveling and charging.

[0237] This invention provides a system that enables electric vehicle (EV) owners to effectively utilize their charging time and provide a better driving experience. The system generates a customized driving plan that takes into account the user's emotional state and provides it to the user. Specific embodiments of the system are described below.

[0238] Hardware and Software Configuration

[0239] This system mainly uses the following hardware and software:

[0240] User device: Smartphone or tablet (e.g. iPhone, Android tablet)

[0241] GPS function: A location information acquisition function built into the user's device

[0242] Camera: A camera built into the user's device

[0243] Microphone: A microphone built into the user's device

[0244] Biometric sensors: sensors such as heart rate monitors

[0245] Dedicated app: Application software installed by the user

[0246] Server: A server running on a cloud service that processes data and runs AI models.

[0247] Database: A database that stores information about tourist spots and charging spots (e.g., Google Places API)

[0248] AI Methods: Analyze data and generate driving plans using artificial intelligence models (e.g., TensorFlow, PyTorch)

[0249] Specific operation of the system

[0250] The specific operations when a user requests a drive plan using a dedicated app are as follows.

[0251] 1. Start the user device

[0252] The user launches a dedicated app on their smartphone or tablet.

[0253] 2. Information gathering

[0254] Enter your current location and destination in the app. For example, the user enters their current location as "Tokyo" and their destination as "Yokohama."

[0255] The user device automatically obtains the user's current location using the built-in GPS function.

[0256] Collecting user emotional data using cameras, microphones, and biometric sensors, as well as facial recognition software (e.g., OpenFace) and voice analysis software (e.g., Praat).

[0257] 3. Information Transmission

[0258] The collected data on the current location, destination, driving range (data obtained from the in-vehicle system), and emotion data are sent to the server. The communication module is used to assemble this data into packets and send them to the server.

[0259] 4. Data processing and drive plan generation

[0260] Based on the received data, the server retrieves information about nearby charging spots and tourist spots from a database.

[0261] Using an AI model, the system generates optimal driving plans based on the collected information and the user's emotional state. For example, if the user is in a state of "wanting to relax," it will suggest plans that include quiet cafes and parks.

[0262] 5. Send and display drive plans

[0263] The generated driving plan is sent to the user's terminal. The driving plan is packaged into packets using the communication module and sent to the terminal.

[0264] The user device analyzes the drive plan received from the server and displays it using a map display function (e.g., Google Maps SDK), visually showing the locations of charging spots, tourist attractions, restaurants, etc.

[0265] Specific examples

[0266] For example, if a user plans a drive from Tokyo to Yokohama, they make a request using a dedicated app. The user inputs their current location (Tokyo), destination (Yokohama), remaining driving distance (100km), and emotional state (want to relax) into the system. The device sends this data to the server, which analyzes the information and generates an optimal driving plan. The generated plan includes a charging station with a quiet cafe and a nearby park. This plan is sent to the device, and the user can check the plan in the app and enjoy the drive.

[0267] Prompt Sentence Examples

[0268] As an example of a prompt, the following text is input to the generative AI model:

[0269] "Current location is Tokyo, destination is Yokohama, and remaining driving distance is 100km. The user's emotional state is that they want to relax. Please suggest the optimal driving plan based on these conditions."

[0270] The above is a specific embodiment for carrying out the present invention. This system allows the user to spend time during charging meaningfully and enjoy a driving plan that is optimized for the user's emotional state.

[0271] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0272] Step 1:

[0273] The user launches the dedicated app and requests a driving plan. The user operates the app's interface to input their current location and destination. The user provides information on their current location (e.g., Tokyo) and destination (e.g., Yokohama) as input. The device automatically obtains the current location using its built-in GPS function. This results in the current location (Tokyo) and the input destination (Yokohama) being obtained as output.

[0274] Step 2:

[0275] Collects user emotional data. The device uses a camera, microphone, and biometric sensors to collect the user's facial expressions, voice, heart rate, and other data in real time. Specifically, the camera captures the user's facial expressions, the microphone collects voice data, and the sensor acquires heart rate data. This results in the acquired emotional data being output.

[0276] Step 3:

[0277] The device obtains remaining driving range information from the in-vehicle system. The input is the remaining battery capacity reported by the in-vehicle system, and the output is the calculated remaining driving range information. Specifically, the device communicates with the in-vehicle system via a dedicated protocol or API to query the remaining driving range.

[0278] Step 4:

[0279] The device sends the current location, destination, remaining driving distance, and emotion data together to the server. The input data includes the current location (Tokyo), destination (Yokohama), remaining driving distance, and emotion data. This includes the operation of sending this data to the server using the communication module. This allows the server to receive all the necessary data.

[0280] Step 5:

[0281] The server retrieves information on nearby charging spots, tourist spots, and restaurants from a database based on the received current location, destination, remaining driving distance, and emotion data. The received data (current location, destination, remaining driving distance, emotion data) is used as input, and the server queries the database based on this. As a result, information on charging spots, tourist spots, and restaurants is obtained as output.

[0282] Step 6:

[0283] The server uses an AI model to process and analyze the received and acquired data and generate an optimal driving plan based on the user's emotional state. Input data includes charging spot information, tourist spot information, restaurant information, and emotional data. Analysis and plan generation are performed using an AI model (e.g., TensorFlow, PyTorch). This results in an optimized driving plan being obtained as output.

[0284] Step 7:

[0285] The generated drive plan is sent from the server to the user terminal. The input is the generated drive plan, and the operation of sending this to the user terminal via the communication module is included. As a result, the user terminal receives the drive plan.

[0286] Step 8:

[0287] The user device analyzes the received drive plan and displays it visually. The input is the received drive plan, and the device uses a map display function (e.g., Google Maps SDK) to display charging spots, tourist attractions, dining facilities, and other information on a map. Specifically, the device displays the planned route and spots on the map in a format that is intuitively easy for the user to understand. The output is a visually organized drive plan that is provided to the user.

[0288] The above is the specific processing flow of this system.

[0289] (Application example 2)

[0290] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0291] There is a need for electric vehicle (EV) owners to be able to make effective use of their charging time and enjoy a more enjoyable driving experience. Current charging stations simply charge their vehicles and are unable to provide customized services that reflect the user's emotional state, making the waiting time less meaningful. For this reason, there is a need for a system that can automatically suggest optimal charging spots and tourist spots based on the user's emotional state, allowing them to enjoy their charging time.

[0292] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring emotional state information, means for receiving drivable distance information, means for acquiring location information, means for receiving destination information, means for acquiring information on nearby charging spots based on the location information, means for acquiring information on nearby tourist spots based on the location information, AI means for integrating the charging spot information and the tourist spot information to generate a driving plan that can be enjoyed while charging according to the emotional state, means for transmitting the generated driving plan to a user terminal, and means for displaying the driving plan on the user terminal. This allows the user to enjoy a driving plan customized according to their emotional state, allowing them to spend their waiting time while charging meaningfully and enjoyably.

[0293] "Emotional state information" is data that indicates the emotional state of the user, and includes information such as facial expressions, voice, and heart rate obtained from a camera, microphone, biometric sensor, etc.

[0294] "Drivable distance information" is data indicating the distance that an electric vehicle can travel with the current remaining battery charge.

[0295] "Location Information" means current geographic location data obtained using GPS or other location-determining technology.

[0296] "Destination information" is data relating to a specific destination set by a user.

[0297] "Charging spot information" is data about locations where electric vehicles can be charged.

[0298] "Tourist attraction information" is data about places that travelers aim to visit.

[0299] "AI means" refers to algorithms and software that use artificial intelligence to analyze data and generate optimal driving plans.

[0300] A "user terminal" is an electronic device operated by a user, such as a smartphone, tablet, or in-vehicle system.

[0301] A "drive plan" is a plan of routes and activities that includes charging spots, tourist spots, dining facilities, and other things that can be enjoyed while charging.

[0302] This invention provides a specific system that enables electric vehicle (EV) owners to make effective use of the time spent charging, using user terminals such as smartphones and tablets, in-vehicle systems, and emotion recognition sensors (cameras, microphones, biometric sensors).

[0303] By combining data such as emotional state information, driving range information, location information, destination information, charging spot information, and tourist spot information, an optimal driving plan is generated based on the user's emotional state using AI means. The generated driving plan is sent to the user's device and displayed for visual confirmation.

[0304] The server works as follows:

[0305] 1. Means of acquiring emotional state information

[0306] The system uses cameras, microphones, and biometric sensors installed on user devices and in-vehicle systems to analyze the user's facial expressions, voice, and heart rate to recognize their emotional state, thereby obtaining information in real time about whether the user is relaxed or excited.

[0307] 2. Means for receiving driving range information

[0308] The in-vehicle system receives information about the remaining battery charge of the electric vehicle and sends it to the server via the user's terminal.

[0309] 3. How to obtain location information

[0310] The current location information is obtained using the GPS function of the user's device, and this information is also sent to the server in real time.

[0311] 4. Means of receiving destination information

[0312] The destination information entered by the user through a dedicated app is obtained and sent to the server.

[0313] 5. A method for obtaining information about nearby charging spots based on location information

[0314] Based on the acquired location information, the server retrieves information about nearby charging spots from a database.

[0315] 6. A way to obtain information about nearby tourist spots based on location information

[0316] Similarly, the server retrieves information about nearby tourist spots from a database based on the location information.

[0317] 7. AI method for integrating charging spot information and tourist spot information to generate driving plans that are enjoyable while charging according to the driver's emotional state

[0318] The AI ​​in the server integrates information on the user's emotional state, driving range, charging spots, tourist spots, and dining facilities to generate the optimal driving plan according to the user's emotional state. For example, if the user wants to relax, it will suggest quiet cafes and parks, and if the user wants to be active, it will suggest spots with plenty of activities.

[0319] 8. Means for sending the generated driving plan to the user terminal

[0320] The generated drive plan is transmitted from the server to the user terminal.

[0321] 9. Means for displaying the driving plan on the user's device

[0322] The user terminal displays the received drive plan and also uses a map display function to enable visual confirmation.

[0323] Examples:

[0324] For example, if a user plans a drive from Tokyo to Yokohama, they can request a driving plan through a dedicated app. The user's device will then send the user's current location in Tokyo, the remaining 100km driving distance, information about the destination Yokohama, and their emotional state obtained through the emotion engine to the server. The server will then generate a driving plan that includes the best charging spots and sightseeing spots and dining options according to the user's emotional state, and provide it to the user.

[0325] Example prompt sentence:

[0326] "The user is in Tokyo and planning to travel to Yokohama. The driving range is 100km. The user feels like relaxing. Please suggest charging spots and tourist spots where they can relax."

[0327] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0328] Step 1:

[0329] The user launches the dedicated app and requests the creation of a driving plan.

[0330] Input: A request from a user device (such as a smartphone or tablet).

[0331] Output: Start collecting emotional state information, location information, and destination information.

[0332] Step 2:

[0333] The device automatically obtains the current location information using GPS.

[0334] Input: GPS data from the user device.

[0335] Data processing: Convert to current location coordinates.

[0336] Output: Coordinate data of the user's current location.

[0337] Step 3:

[0338] The user enters destination information into a dedicated app, and the device retrieves it.

[0339] Input: User text entry of destination.

[0340] Data processing: Convert to geographic coordinates of destination.

[0341] Output: Destination coordinate data.

[0342] Step 4:

[0343] The terminal receives the range information from the in-vehicle system.

[0344] Input: Battery level information from the in-car system.

[0345] Data processing: Converted into driving distance.

[0346] Output: Driving distance data.

[0347] Step 5:

[0348] Emotion recognition sensors analyze the user's facial expressions, voice, and heart rate to obtain emotional state information.

[0349] Input: Data from camera, microphone, and biometric sensors.

[0350] Data calculation: Emotional state is estimated through facial expression analysis, voice analysis, and biometric information analysis.

[0351] Output: User's emotional state data.

[0352] Step 6:

[0353] The location information, destination information, remaining driving distance information, and emotional state information acquired by the terminal are transmitted to the server.

[0354] Input: location information, destination information, driving range information, emotional state information.

[0355] Output: Data sent to the server.

[0356] Step 7:

[0357] The server retrieves information about nearby charging spots and tourist spots from a database based on the location information.

[0358] Input: Location.

[0359] Data processing: Extract charging spot information and tourist spot information through database queries.

[0360] Output: Information on nearby charging spots and tourist spots.

[0361] Step 8:

[0362] The server uses AI to select appropriate charging spots and tourist spots based on emotional state information and generates a driving plan.

[0363] Input: charging spot information, tourist spot information, emotional state information.

[0364] Data calculation: Select spots that adapt to your emotional state and create optimal routes.

[0365] Output: The generated drive plan.

[0366] Step 9:

[0367] The server transmits the generated drive plan to the user terminal.

[0368] Input: The generated drive plan.

[0369] Output: Data sent to the user's terminal.

[0370] Step 10:

[0371] The terminal visually displays the received drive plan to the user using a map display function.

[0372] Input: The received drive plan.

[0373] Output: A visual drive plan displayed on the user's terminal screen.

[0374] 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.

[0375] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0376] 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.

[0377] [Second embodiment]

[0378] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0379] 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.

[0380] 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).

[0381] 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.

[0382] 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.

[0383] 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).

[0384] 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.

[0385] 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.

[0386] 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.

[0387] 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.

[0388] 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.

[0389] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0390] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of the time while charging and provides them with an enjoyable driving plan. This system is implemented through the following specific configuration and processing.

[0391] Users launch a dedicated app on their smartphone, tablet, or other user device and request the creation of a driving plan. At this time, the user device automatically obtains current location information using GPS. At the same time, destination information entered by the user is also obtained.

[0392] The user terminal receives information about the remaining driving distance from the electric vehicle, and transmits information about the current location, remaining driving distance, and destination to the server. The server receives this information and, based on the information provided by the user terminal, retrieves information about nearby charging spots and tourist spots from a database.

[0393] The server uses AI to integrate the acquired charging spot information and tourist spot information and generate an optimal driving plan for enjoying the ride while charging. Furthermore, if necessary, it also acquires information on nearby dining facilities and proposes an optimal dining plan. In this case, the AI ​​utilizes information updated in real time and generates a driving plan based on the most recent information.

[0394] The generated driving plan is sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. For example, the locations of charging spots, tourist spots, and suggested restaurants are displayed on the map, and the route to take while charging is also visually displayed.

[0395] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the user's device sends information about the current location in Tokyo, the remaining driving distance of 100 km, and the destination, Yokohama, to the server. Information provided by the in-vehicle system is also sent to the server.

[0396] The server selects the optimal charging spot between the user's current location and destination, and uses AI to generate a driving plan that includes nearby dining facilities (e.g., cafes and restaurants) and tourist attractions (e.g., museums, parks, etc.) that can be enjoyed while charging.

[0397] The generated plan is sent to the user's device, and the user can view it in the app. For example, the plan may suggest a stop for breakfast at a cafe while the user is charging, or a visit to a museum within walking distance.

[0398] In this way, the present invention provides electric vehicle owners with a system that proposes optimal driving plans that allow them to spend their charging time in a fun and meaningful way. As a result, EV owners can use their charging time efficiently and enjoy a more fulfilling driving experience.

[0399] The processing flow will be explained below.

[0400] Step 1:

[0401] A user requests a driving plan.

[0402] Operation: The user launches the dedicated app and presses the "Create a Drive Plan" button. The user inputs their destination and sets their current location and destination information.

[0403] Step 2:

[0404] The terminal transmits current location information, remaining driving distance, and destination information to the server.

[0405] How it works: The device uses GPS to determine its current location and receives driving range information from the in-vehicle system. It then sends this data, along with the destination information entered by the user, to the server.

[0406] Step 3:

[0407] The on-board system provides the terminal with information on the EV's driving range and estimated arrival time.

[0408] How it works: The onboard system monitors battery status and calculates the current driving range. It also calculates the estimated time of arrival based on current traffic conditions and sends it to the terminal.

[0409] Step 4:

[0410] The server acquires information about nearby charging spots and tourist spots based on user information and vehicle information.

[0411] Operation: The server searches a database based on the received current location information to obtain the latest information on nearby charging spots and tourist attractions. Charging spot information includes the location and availability of available charging stations. Tourist attraction information includes the location and business status of parks, museums, restaurants, etc.

[0412] Step 5:

[0413] The server uses AI to analyze charging spot information and tourist spot information and generate the optimal driving plan.

[0414] How it works: The server inputs the acquired charging spot information and tourist spot information into an AI algorithm, and creates an optimal driving plan based on the user's current location, destination, and available driving distance. The AI ​​makes suggestions by combining the location of charging spots, charging times, and the opening hours of nearby tourist spots and restaurants.

[0415] Step 6:

[0416] The server transmits the generated drive plan to the user terminal.

[0417] Operation: The server sends the generated driving plan to the user's device, which includes information on suggested charging spots and nearby tourist attractions and restaurants.

[0418] Step 7:

[0419] The terminal displays the received plan to the user.

[0420] How it works: The device displays the received driving plan in the app, and the user can use the map view to visually confirm the location of charging spots and tourist attractions, as well as the proposed route.

[0421] As a concrete example, if a user drives from Tokyo to Yokohama, the system will suggest the best charging spot (for example, a charging station with a cafe attached in Tokyo) and nearby tourist attractions (for example, a nearby art museum) when charging is required. The user can check the proposed plan in the app and spend the time while charging meaningfully.

[0422] Example 1

[0423] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0424] Electric vehicle (EV) owners must spend a certain amount of time charging their vehicles, but there are limited ways to make effective use of that time. In particular, how to spend time while charging has become a difficult issue, and there is a demand for efficient and meaningful ways to spend that time.

[0425] 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.

[0426] In this invention, the server includes means for acquiring current location information by an acquisition device, means for receiving destination information by an input device, means for receiving mileage information, means for acquiring information on surrounding charging facilities based on the location information, means for acquiring information on surrounding tourist facilities based on the location information, generation AI means for integrating the charging facility information and the tourist facility information to generate a driving plan that can be enjoyed while charging, means for transmitting the generated driving plan to an information processing device, and means for displaying the driving plan on a display device. This makes it possible to effectively utilize time while charging and provide a driving plan that is enjoyable for the user.

[0427] The "acquisition device" is a device for acquiring current location information.

[0428] An "input device" is a device for receiving destination information.

[0429] "Driving distance information" is information relating to the distance that an electric vehicle can travel.

[0430] "Location information" is information indicating the current geographical location obtained from a user terminal or an in-vehicle system.

[0431] "Charging facility information" is information about facilities for charging electric vehicles.

[0432] "Tourist facility information" is information about tourist spots that users can visit.

[0433] "Generative AI means" refers to a means that utilizes artificial intelligence technology to generate optimal driving plans based on acquired information.

[0434] The "information processing device" is a device for transmitting the generated driving plan to the user terminal.

[0435] A "display device" is a device for displaying a driving plan on a user terminal.

[0436] A "drive plan" is a plan for a travel route that includes tourist spots and dining facilities that can be enjoyed while charging.

[0437] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of their charging time and provide enjoyable driving plans. This system uses hardware and software to perform various data processing and calculations and generate driving plans that are meaningful to the user.

[0438] The user launches a dedicated app on a device such as a smartphone or tablet. The app automatically obtains the user's current location information using GPS. At the same time, it also obtains the destination information entered by the user. The device receives driving range information from the in-vehicle system and sends this information to the server.

[0439] Based on the received information and location information, the server retrieves information on nearby charging facilities and tourist facilities from a database. Detailed information on charging facilities and tourist facilities is stored in the database. The server then uses a generative AI model to integrate the retrieved charging facility information and tourist facility information to generate an optimal driving plan for enjoying the ride while charging. If necessary, the server also retrieves information on nearby dining facilities and suggests an optimal dining plan. This generative AI model generates driving plans based on information updated in real time.

[0440] The generated driving plan is sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. Specifically, the locations of charging stations, tourist facilities, and suggested restaurants are displayed on the map, and the route to take while charging is visually displayed.

[0441] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the device sends information about the current location in Tokyo, the remaining driving distance of 100 km, and the destination, Yokohama, to the server. Information provided by the in-vehicle system is also sent to the server.

[0442] The server selects the optimal charging facility between the user's current location and destination, and uses a generative AI model to generate a driving plan that can be enjoyed while charging, including nearby dining facilities (e.g., cafes and restaurants) and tourist facilities (e.g., museums and parks). An example of a prompt sentence to input into the generative AI model at this time is, "The user's current location is Tokyo, and the destination is Yokohama. The driving distance is 100 km. Please generate a driving plan between Tokyo and Yokohama that includes the optimal charging facility and nearby tourist facilities and dining facilities. Please also provide map information to visualize the generated plan."

[0443] The generated plan is sent to the user's device, where the user can view it in the app. For example, the plan may suggest a stop for breakfast at a cafe while the user is charging, or a visit to a museum within walking distance. In this way, the present invention provides a system that suggests optimal driving plans to electric vehicle owners that allow them to spend their charging time in a fun and meaningful way. As a result, EV owners can use their charging time efficiently and enjoy a more fulfilling driving experience.

[0444] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0445] Step 1:

[0446] The user launches the dedicated app and requests the creation of a driving plan.

[0447] Input: User launches app

[0448] Output: App launch screen

[0449] How it works: The user taps the dedicated app on their smartphone or tablet to launch it, then taps the "Create a driving plan" button to request the creation of a plan.

[0450] Step 2:

[0451] The device obtains current location and destination information

[0452] Input: User's current location and destination information

[0453] Output: Current location and destination information data

[0454] Operation: The device uses the built-in GPS to obtain the user's current location and simultaneously receives the destination (e.g. Yokohama) entered by the user in the app.

[0455] Step 3:

[0456] The device receives the driving range information.

[0457] Input: Range information from electric vehicle

[0458] Output: Driving distance information data

[0459] How it works: The device receives battery status and range information (e.g., 100km) from the vehicle's system via Bluetooth or Wi-Fi.

[0460] Step 4:

[0461] The device sends all information to the server

[0462] Input: current location information, destination information, remaining driving distance information

[0463] Output: Sending information to the server

[0464] Operation: The device compiles the collected current location information, destination information, and remaining driving distance information and sends it to a server via the Internet.

[0465] Step 5:

[0466] The server retrieves information about nearby charging facilities and tourist facilities from a database.

[0467] Input: current location information, destination information

[0468] Output: Charging facility information, tourist facility information data

[0469] Operation: Based on the received information, the server searches the database for and obtains information about charging facilities and tourist facilities located between the user's current location and the destination.

[0470] Step 6:

[0471] The server generates an optimal driving plan using the generative AI model

[0472] Input: current location information, destination information, driving range information, charging facility information, tourist facility information

[0473] Output: Data for optimal driving plans

[0474] Operation: The server inputs the acquired charging facility information and tourist facility information into the generative AI model. The generative AI model generates an optimal driving plan based on the prompt: "The user's current location is Tokyo, and their destination is Yokohama. The driving distance is 100 km. Please generate a driving plan between Tokyo and Yokohama that includes the optimal charging facilities and surrounding tourist facilities and restaurants. Please also provide map information to visualize the generated plan."

[0475] Step 7:

[0476] The server sends the generated driving plan to the terminal.

[0477] Input: Data for optimal drive planning

[0478] Output: Sending the driving plan to the user's terminal

[0479] Operation: The server transmits the generated drive plan data to the user terminal via the Internet.

[0480] Step 8:

[0481] The device displays the driving plan

[0482] Input: Data for optimal drive planning

[0483] Output: Drive plan display on the app

[0484] Operation: The device displays the received driving plan data on the screen of a dedicated app. Using a map API (e.g., Google Maps API), the locations of charging stations, tourist attractions, and restaurants are visualized on a map.

[0485] Step 9:

[0486] User confirms driving plan

[0487] Input: Drive plan display on the app

[0488] Output: User confirmation action

[0489] Operation: The user checks the driving plan displayed in the app, including a list of charging spots, a list of nearby tourist attractions and restaurants, and a map showing the location of the plan, allowing the user to intuitively understand the details of the driving plan.

[0490] (Application example 1)

[0491] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0492] Electric vehicle (EV) owners often have limited options for making effective use of the time while their vehicle is charging, which often prevents them from making the most of that time. It is also difficult to determine the need for charging and the current status of charging stations, making it difficult to plan appropriate trips. Therefore, there is a need for a system that allows EV owners to enjoy the time while charging safely and enjoyably.

[0493] 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.

[0494] In this invention, the server includes means for receiving driving range information, means for acquiring location information, means for receiving destination information, means for acquiring information on nearby charging spots based on the location information, means for acquiring information on nearby tourist spots based on the location information, AI means for integrating the charging spot information and the tourist spot information to generate a driving plan that can be enjoyed while charging, means for transmitting the generated driving plan to a user terminal, means for displaying the driving plan on the user terminal, means for determining whether charging is necessary using the location information and driving range information, means for acquiring information on nearby restaurants and tourist spots if charging is necessary based on the determination, and means for integrating the acquired information to generate an optimal driving plan. This allows electric vehicle owners to effectively utilize their time while charging and enjoy everything from selecting a charging spot to sightseeing and dining.

[0495] "Drivable distance information" is information that indicates the distance that an electric vehicle can travel using the power that is charged.

[0496] "Location information" is information that indicates the current geographical location of an electric vehicle or a user terminal.

[0497] "Destination information" is information that indicates the geographical location of the destination set by the user.

[0498] "Charging spot information" is data that indicates the locations and related information of spots where electric vehicles can be charged.

[0499] "Tourist spot information" is data that indicates the locations of tourist spots and tourist attractions and related information.

[0500] "AI means" refers to a means that uses artificial intelligence technology to integrate charging spot information and tourist spot information to generate an optimal driving plan.

[0501] "User terminal" refers to a computing device operated by a user, such as a smartphone or tablet.

[0502] The "means for determining whether charging is necessary" is a means for determining whether the electric vehicle needs additional charging based on the location information and the driving range information.

[0503] "Dining facility information" is data that indicates the location and related information of dining facilities such as restaurants and cafes.

[0504] The "means for generating an optimal driving plan" is a means for integrating the acquired charging spot information, tourist spot information, and dining facility information to create the most beneficial driving plan for the user.

[0505] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of the time while charging and provides them with an enjoyable driving plan. This system is implemented through the following specific configuration and processing.

[0506] The user launches a dedicated app using a user device such as a smartphone or tablet and requests the creation of a driving plan. At this time, the user device automatically obtains current location information using GPS. At the same time, destination information entered by the user is also obtained. The user device receives information about the remaining driving distance from the electric vehicle and transmits the current location, remaining driving distance, and destination information together to the server.

[0507] The server receives this information and, based on the information provided by the user's device, retrieves information on nearby charging spots and tourist spots from a database. Furthermore, using AI tools, the server integrates the retrieved charging spot information and tourist spot information to generate an optimal driving plan for enjoying while charging. In this process, it uses location information and driving range information to determine whether charging is necessary, and also retrieves information on nearby restaurants and other establishments as necessary.

[0508] The generated driving plan is then sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. For example, the locations of charging spots, tourist spots, and suggested dining facilities are displayed on the map, and the route to take while charging is visually displayed.

[0509] To implement this system, specific hardware and software are required on both the server and user devices. The server requires a computer with high processing power, as well as software for data processing using AI technology. On the other hand, smartphones or tablets with GPS functionality are suitable for user devices.

[0510] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the user's device sends information about the user's current location in Tokyo, the remaining driving distance of 100 km, and the destination, Yokohama, to the server. Information provided by the in-vehicle system is also sent to the server. The server selects the optimal charging spot between the user's current location and destination, and uses AI to generate a drive plan that can be enjoyed while charging, including nearby eating and drinking establishments (e.g., cafes and restaurants) and tourist spots (e.g., museums and parks). The generated plan is sent to the user's device, and the user can view it in the app.

[0511] In addition, by using a generative AI model, it is possible to generate even more sophisticated driving plans. For example, the following can be entered as a prompt to suggest the optimal driving plan taking into account the current location and destination of the autonomous vehicle.

[0512] "Please propose the optimal driving plan taking into account the current location and destination of the autonomous vehicle. The current location is Tokyo, latitude 35.6895, longitude 139.6917, and the destination is Yokohama. The electric vehicle has a range of 100 km. Please provide information on charging spots, tourist attractions, and dining facilities."

[0513] This will allow electric vehicle owners to make effective use of the time spent charging, and enjoy everything from choosing a charging location to sightseeing and dining.

[0514] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0515] Step 1:

[0516] The user launches the dedicated app and requests the creation of a driving plan. The user's device automatically acquires the current location information using the GPS function, and receives the destination information entered by the user as well as the driving range information from the electric vehicle.

[0517] Input: User operation, GPS location information, destination information, remaining driving distance information

[0518] Output: Current location information, destination information, and driving distance information sent to the server

[0519] Step 2:

[0520] The user terminal transmits the current location, remaining driving distance, and destination information to the server.

[0521] Input: current location information, destination information, driving distance information

[0522] Output: Consolidated data sent to the server

[0523] Step 3:

[0524] The server acquires information about nearby charging spots and tourist spots from a database based on the received information about the current location, remaining driving distance, and destination.

[0525] Input: current location information, destination information, driving distance information

[0526] Output: Charging spot information, tourist spot information

[0527] Step 4:

[0528] The server uses AI to integrate information on charging spots and tourist spots and generate an optimal driving plan. At this time, it determines whether charging is necessary based on location information and driving range information, and also obtains information on nearby restaurants and other establishments as needed.

[0529] Input: current location information, destination information, driving range information, charging spot information, tourist spot information

[0530] Output: Optimal driving plan

[0531] Step 5:

[0532] The server transmits the generated drive plan to the user terminal.

[0533] Input: Optimal driving plan

[0534] Output: Drive plan data sent to the user's device

[0535] Step 6:

[0536] The user device displays the received drive plan so that the user can intuitively understand it. The user device uses its map display function to display the locations of charging spots, tourist attractions, and suggested dining facilities.

[0537] Input: Drive plan data sent from the server

[0538] Output: Drive plan displayed on the user's device screen

[0539] Step 7:

[0540] The user checks the displayed drive plan and selects an action to enjoy while charging.

[0541] Input: Drive plan displayed on the user's device

[0542] Output: User's action choice

[0543] These steps will enable electric vehicle owners to make the most of their time while charging and enjoy a fulfilling driving experience.

[0544] 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.

[0545] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of their charging time and proposes more enjoyable driving plans. The system of the present invention incorporates emotion recognition technology to propose customized driving plans according to the user's emotional state.

[0546] The user launches a dedicated app using a user device such as a smartphone or tablet and requests the creation of a driving plan. At this time, the user device automatically obtains current location information using GPS. At the same time, destination information entered by the user is also obtained. Furthermore, the emotion engine uses a camera, microphone, and biometric sensors to analyze data such as facial expressions, voice, and heart rate in order to recognize the user's emotional state.

[0547] The user terminal receives information about the remaining driving distance from the electric vehicle and transmits data on the current location, remaining driving distance, destination information, and emotional state to the server. The server receives this information and, based on the information provided by the user terminal, retrieves information about nearby charging spots and tourist spots from a database.

[0548] The server uses AI means to integrate the acquired charging spot information, tourist spot information, and emotional state to generate an optimal driving plan suited to the user's emotional state. For example, if the emotional state indicates stress, it will suggest relaxing spots, and if the emotional state indicates excitement, it will suggest active spots. It also acquires information on nearby dining facilities and proposes an optimal dining plan. The AI ​​means utilizes information updated in real time to generate a driving plan based on the most recent information.

[0549] The generated driving plan is sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. For example, the locations of charging spots, tourist spots, and suggested restaurants are displayed on the map, and the route to take while charging is also visually displayed.

[0550] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the user's device sends to the server information about the user's current location in Tokyo, the remaining distance of 100 km, and the destination Yokohama, as well as emotional state data obtained through the emotion engine. Information provided by the in-vehicle system is also sent to the server.

[0551] The server selects the optimal charging spot between the user's current location and destination, and uses AI to generate a driving plan that includes suitable nearby tourist attractions and dining options to enjoy while charging based on the user's emotional state. For example, if the user indicates a desire to relax, the server will suggest a plan that includes a charging station with a quiet cafe attached and a nearby park.

[0552] In this way, the present invention provides a system that proposes optimal driving plans to electric vehicle owners, allowing them to spend their charging time in a fun and meaningful way. This allows EV owners to use their charging time efficiently and enjoy a more fulfilling driving experience. The introduction of an emotion engine allows for plans customized according to the user's emotional state, further increasing user satisfaction.

[0553] The processing flow will be explained below.

[0554] Step 1:

[0555] A user requests a driving plan.

[0556] How it works: The user launches the app and presses the "Create a Drive Plan" button. The user then enters their destination, and emotional state data is collected using a facial recognition camera, microphone, and biometric sensors.

[0557] Step 2:

[0558] The terminal transmits current location information, remaining driving distance, and destination information to the server.

[0559] Operation: The device obtains the user's current location using GPS and receives the driving range fetched from the in-vehicle system. It then sends this data along with the destination information entered by the user to the server. It also simultaneously sends the emotional state data obtained by the emotion engine.

[0560] Step 3:

[0561] An emotion engine analyzes the user's emotional state.

[0562] How it works: The emotion engine analyzes collected data such as the user's facial expressions, tone of voice, and heart rate to determine their current emotional state, such as stress, anxiety, or relaxation.

[0563] Step 4:

[0564] The server acquires information about nearby charging spots and tourist spots based on user information, vehicle information, and emotional state.

[0565] Operation: The server searches a database based on the received current location information to obtain the latest information on nearby charging spots and tourist attractions. Charging spot information includes the location and availability of available charging stations. Tourist attraction information includes the location and business status of parks, museums, restaurants, etc.

[0566] Step 5:

[0567] The server uses AI to analyze charging spot information and tourist spot information and generate the optimal driving plan.

[0568] How it works: The server inputs the acquired charging spot and tourist spot information into an AI algorithm, which then creates an optimal driving plan based on the user's current location, destination, driving range, and emotional state. The AI ​​makes suggestions by combining the location of charging spots, charging times, and the opening hours of nearby tourist spots and restaurants. For example, if the user is feeling anxious, it will suggest relaxing parks or spa facilities.

[0569] Step 6:

[0570] The server transmits the generated drive plan to the user terminal.

[0571] Operation: The server sends the generated driving plan to the user's device. This plan includes information on the proposed charging spots and nearby tourist attractions and dining options.

[0572] Step 7:

[0573] The terminal displays the received plan to the user.

[0574] How it works: The device displays the received driving plan in the app, and the user can use the map view to visually confirm the location of charging spots and tourist attractions, as well as the proposed route.

[0575] As a concrete example, if a user drives from Tokyo to Yokohama, the system will suggest the best charging spot (for example, a charging station with a cafe attached in Tokyo) and nearby tourist attractions (for example, a nearby temple or park) when charging is required. If the user indicates an emotional state that requires relaxation, the system will suggest nearby quiet cafes and relaxation facilities. The user can check the suggested plan in the app and spend the time while charging meaningfully.

[0576] Example 2

[0577] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0578] Electric vehicle (EV) owners often waste time while charging, and there is a need for a way to make efficient use of charging time. Furthermore, conventional drive plan suggestion systems only provide uniform information without considering the user's emotional state, which limits the improvement of user satisfaction.

[0579] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving driving range information, means for acquiring location information, means for receiving destination information, means for collecting emotion data, means for acquiring information on nearby charging spots based on the location information, means for acquiring information on nearby tourist spots based on the location information, means for acquiring information on nearby eating and drinking facilities, AI means for integrating the charging spot information, tourist spot information, eating and drinking facility information, and emotion data to generate a driving plan that can be enjoyed while charging, means for transmitting the generated driving plan to the user terminal, and means for displaying the driving plan on the user terminal. This allows the server to provide a driving plan customized according to the user's emotional state, making it possible to spend charging time meaningfully.

[0580] "Drivable distance information" is information that indicates the distance that the electric vehicle can travel with the current remaining battery charge.

[0581] "Location information" is information indicating the current geographical location of a user or vehicle obtained by GPS or other location measurement means.

[0582] "Destination information" is information that indicates the geographical location of the destination set by the user.

[0583] "Emotion data" is data that indicates the emotional state of a user, obtained by analyzing the user's facial expression, voice, biological information, and the like.

[0584] "Charging spot information" is information about locations where electric vehicles can be charged.

[0585] "Tourist attraction information" is information about tourist attractions that the user can visit.

[0586] "Dining facility information" is information about facilities where users can enjoy eating and drinking.

[0587] "AI means" refers to a means of analyzing data using artificial intelligence technology and generating a driving plan suitable for the user.

[0588] A "user terminal" is a smartphone, tablet, or other information device operated by a user.

[0589] A "drive plan" is a plan that suggests sightseeing, dining, and other activities that can be enjoyed while the user is traveling and charging.

[0590] This invention provides a system that enables electric vehicle (EV) owners to effectively utilize their charging time and provide a better driving experience. The system generates a customized driving plan that takes into account the user's emotional state and provides it to the user. Specific embodiments of the system are described below.

[0591] Hardware and Software Configuration

[0592] This system mainly uses the following hardware and software:

[0593] User device: Smartphone or tablet (e.g. iPhone, Android tablet)

[0594] GPS function: A location information acquisition function built into the user's device

[0595] Camera: A camera built into the user's device

[0596] Microphone: A microphone built into the user's device

[0597] Biometric sensors: sensors such as heart rate monitors

[0598] Dedicated app: Application software installed by the user

[0599] Server: A server running on a cloud service that processes data and runs AI models.

[0600] Database: A database that stores information about tourist spots and charging spots (e.g., Google Places API)

[0601] AI Methods: Analyze data and generate driving plans using artificial intelligence models (e.g., TensorFlow, PyTorch)

[0602] Specific operation of the system

[0603] The specific operations when a user requests a drive plan using a dedicated app are as follows.

[0604] 1. Start the user device

[0605] The user launches a dedicated app on their smartphone or tablet.

[0606] 2. Information gathering

[0607] Enter your current location and destination in the app. For example, the user enters their current location as "Tokyo" and their destination as "Yokohama."

[0608] The user device automatically obtains the user's current location using the built-in GPS function.

[0609] Collecting user emotional data using cameras, microphones, and biometric sensors, as well as facial recognition software (e.g., OpenFace) and voice analysis software (e.g., Praat).

[0610] 3. Information Transmission

[0611] The collected data on the current location, destination, driving range (data obtained from the in-vehicle system), and emotion data are sent to the server. The communication module is used to assemble this data into packets and send them to the server.

[0612] 4. Data processing and drive plan generation

[0613] Based on the received data, the server retrieves information about nearby charging spots and tourist spots from a database.

[0614] Using an AI model, the system generates optimal driving plans based on the collected information and the user's emotional state. For example, if the user is in a state of "wanting to relax," it will suggest plans that include quiet cafes and parks.

[0615] 5. Send and display drive plans

[0616] The generated driving plan is sent to the user's terminal. The driving plan is packaged into packets using the communication module and sent to the terminal.

[0617] The user device analyzes the drive plan received from the server and displays it using a map display function (e.g., Google Maps SDK), visually showing the locations of charging spots, tourist attractions, restaurants, etc.

[0618] Specific examples

[0619] For example, if a user plans a drive from Tokyo to Yokohama, they make a request using a dedicated app. The user inputs their current location (Tokyo), destination (Yokohama), remaining driving distance (100km), and emotional state (want to relax) into the system. The device sends this data to the server, which analyzes the information and generates an optimal driving plan. The generated plan includes a charging station with a quiet cafe and a nearby park. This plan is sent to the device, and the user can check the plan in the app and enjoy the drive.

[0620] Prompt Sentence Examples

[0621] As an example of a prompt, the following text is input to the generative AI model:

[0622] "Current location is Tokyo, destination is Yokohama, and remaining driving distance is 100km. The user's emotional state is that they want to relax. Please suggest the optimal driving plan based on these conditions."

[0623] The above is a specific embodiment for carrying out the present invention. This system allows the user to spend time during charging meaningfully and enjoy a driving plan that is optimized for the user's emotional state.

[0624] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0625] Step 1:

[0626] The user launches the dedicated app and requests a driving plan. The user operates the app's interface to input their current location and destination. The user provides information on their current location (e.g., Tokyo) and destination (e.g., Yokohama) as input. The device automatically obtains the current location using its built-in GPS function. This results in the current location (Tokyo) and the input destination (Yokohama) being obtained as output.

[0627] Step 2:

[0628] Collects user emotional data. The device uses a camera, microphone, and biometric sensors to collect the user's facial expressions, voice, heart rate, and other data in real time. Specifically, the camera captures the user's facial expressions, the microphone collects voice data, and the sensor acquires heart rate data. This results in the acquired emotional data being output.

[0629] Step 3:

[0630] The device obtains remaining driving range information from the in-vehicle system. The input is the remaining battery capacity reported by the in-vehicle system, and the output is the calculated remaining driving range information. Specifically, the device communicates with the in-vehicle system via a dedicated protocol or API to query the remaining driving range.

[0631] Step 4:

[0632] The device sends the current location, destination, remaining driving distance, and emotion data together to the server. The input data includes the current location (Tokyo), destination (Yokohama), remaining driving distance, and emotion data. This includes the operation of sending this data to the server using the communication module. This allows the server to receive all the necessary data.

[0633] Step 5:

[0634] The server retrieves information on nearby charging spots, tourist spots, and restaurants from a database based on the received current location, destination, remaining driving distance, and emotion data. The received data (current location, destination, remaining driving distance, emotion data) is used as input, and the server queries the database based on this. As a result, information on charging spots, tourist spots, and restaurants is obtained as output.

[0635] Step 6:

[0636] The server uses an AI model to process and analyze the received and acquired data and generate an optimal driving plan based on the user's emotional state. Input data includes charging spot information, tourist spot information, restaurant information, and emotional data. Analysis and plan generation are performed using an AI model (e.g., TensorFlow, PyTorch). This results in an optimized driving plan being obtained as output.

[0637] Step 7:

[0638] The generated drive plan is sent from the server to the user terminal. The input is the generated drive plan, and the operation of sending this to the user terminal via the communication module is included. As a result, the user terminal receives the drive plan.

[0639] Step 8:

[0640] The user device analyzes the received drive plan and displays it visually. The input is the received drive plan, and the device uses a map display function (e.g., Google Maps SDK) to display charging spots, tourist attractions, dining facilities, and other information on a map. Specifically, the device displays the planned route and spots on the map in a format that is intuitively easy for the user to understand. The output is a visually organized drive plan that is provided to the user.

[0641] The above is the specific processing flow of this system.

[0642] (Application example 2)

[0643] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0644] There is a need for electric vehicle (EV) owners to be able to make effective use of their charging time and enjoy a more enjoyable driving experience. Current charging stations simply charge their vehicles and are unable to provide customized services that reflect the user's emotional state, making the waiting time less meaningful. For this reason, there is a need for a system that can automatically suggest optimal charging spots and tourist spots based on the user's emotional state, allowing them to enjoy their charging time.

[0645] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring emotional state information, means for receiving drivable distance information, means for acquiring location information, means for receiving destination information, means for acquiring information on nearby charging spots based on the location information, means for acquiring information on nearby tourist spots based on the location information, AI means for integrating the charging spot information and the tourist spot information to generate a driving plan that can be enjoyed while charging according to the emotional state, means for transmitting the generated driving plan to a user terminal, and means for displaying the driving plan on the user terminal. This allows the user to enjoy a driving plan customized according to their emotional state, allowing them to spend their waiting time while charging meaningfully and enjoyably.

[0646] "Emotional state information" is data that indicates the emotional state of the user, and includes information such as facial expressions, voice, and heart rate obtained from a camera, microphone, biometric sensor, etc.

[0647] "Drivable distance information" is data indicating the distance that an electric vehicle can travel with the current remaining battery charge.

[0648] "Location Information" means current geographic location data obtained using GPS or other location-determining technology.

[0649] "Destination information" is data relating to a specific destination set by a user.

[0650] "Charging spot information" is data about locations where electric vehicles can be charged.

[0651] "Tourist attraction information" is data about places that travelers aim to visit.

[0652] "AI means" refers to algorithms and software that use artificial intelligence to analyze data and generate optimal driving plans.

[0653] A "user terminal" is an electronic device operated by a user, such as a smartphone, tablet, or in-vehicle system.

[0654] A "drive plan" is a plan of routes and activities that includes charging spots, tourist spots, dining facilities, and other things that can be enjoyed while charging.

[0655] This invention provides a specific system that enables electric vehicle (EV) owners to make effective use of the time spent charging, using user terminals such as smartphones and tablets, in-vehicle systems, and emotion recognition sensors (cameras, microphones, biometric sensors).

[0656] By combining data such as emotional state information, driving range information, location information, destination information, charging spot information, and tourist spot information, an optimal driving plan is generated based on the user's emotional state using AI means. The generated driving plan is sent to the user's device and displayed for visual confirmation.

[0657] The server works as follows:

[0658] 1. Means of acquiring emotional state information

[0659] The system uses cameras, microphones, and biometric sensors installed on user devices and in-vehicle systems to analyze the user's facial expressions, voice, and heart rate to recognize their emotional state, thereby obtaining information in real time about whether the user is relaxed or excited.

[0660] 2. Means for receiving driving range information

[0661] The in-vehicle system receives information about the remaining battery charge of the electric vehicle and sends it to the server via the user's terminal.

[0662] 3. How to obtain location information

[0663] The current location information is obtained using the GPS function of the user's device, and this information is also sent to the server in real time.

[0664] 4. Means of receiving destination information

[0665] The destination information entered by the user through a dedicated app is obtained and sent to the server.

[0666] 5. A method for obtaining information about nearby charging spots based on location information

[0667] Based on the acquired location information, the server retrieves information about nearby charging spots from a database.

[0668] 6. A way to obtain information about nearby tourist spots based on location information

[0669] Similarly, the server retrieves information about nearby tourist spots from a database based on the location information.

[0670] 7. AI method for integrating charging spot information and tourist spot information to generate driving plans that are enjoyable while charging according to the driver's emotional state

[0671] The AI ​​in the server integrates information on the user's emotional state, driving range, charging spots, tourist spots, and dining facilities to generate the optimal driving plan according to the user's emotional state. For example, if the user wants to relax, it will suggest quiet cafes and parks, and if the user wants to be active, it will suggest spots with plenty of activities.

[0672] 8. Means for sending the generated driving plan to the user terminal

[0673] The generated drive plan is transmitted from the server to the user terminal.

[0674] 9. Means for displaying the driving plan on the user's device

[0675] The user terminal displays the received drive plan and also uses a map display function to enable visual confirmation.

[0676] Examples:

[0677] For example, if a user plans a drive from Tokyo to Yokohama, they can request a driving plan through a dedicated app. The user's device will then send the user's current location in Tokyo, the remaining 100km driving distance, information about the destination Yokohama, and their emotional state obtained through the emotion engine to the server. The server will then generate a driving plan that includes the best charging spots and sightseeing spots and dining options according to the user's emotional state, and provide it to the user.

[0678] Example prompt sentence:

[0679] "The user is in Tokyo and planning to travel to Yokohama. The driving range is 100km. The user feels like relaxing. Please suggest charging spots and tourist spots where they can relax."

[0680] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0681] Step 1:

[0682] The user launches the dedicated app and requests the creation of a driving plan.

[0683] Input: A request from a user device (such as a smartphone or tablet).

[0684] Output: Start collecting emotional state information, location information, and destination information.

[0685] Step 2:

[0686] The device automatically obtains the current location information using GPS.

[0687] Input: GPS data from the user device.

[0688] Data processing: Convert to current location coordinates.

[0689] Output: Coordinate data of the user's current location.

[0690] Step 3:

[0691] The user enters destination information into a dedicated app, and the device retrieves it.

[0692] Input: User text entry of destination.

[0693] Data processing: Convert to geographic coordinates of destination.

[0694] Output: Destination coordinate data.

[0695] Step 4:

[0696] The terminal receives the range information from the in-vehicle system.

[0697] Input: Battery level information from the in-car system.

[0698] Data processing: Converted into driving distance.

[0699] Output: Driving distance data.

[0700] Step 5:

[0701] Emotion recognition sensors analyze the user's facial expressions, voice, and heart rate to obtain emotional state information.

[0702] Input: Data from camera, microphone, and biometric sensors.

[0703] Data calculation: Emotional state is estimated through facial expression analysis, voice analysis, and biometric information analysis.

[0704] Output: User's emotional state data.

[0705] Step 6:

[0706] The location information, destination information, remaining driving distance information, and emotional state information acquired by the terminal are transmitted to the server.

[0707] Input: location information, destination information, driving range information, emotional state information.

[0708] Output: Data sent to the server.

[0709] Step 7:

[0710] The server retrieves information about nearby charging spots and tourist spots from a database based on the location information.

[0711] Input: Location.

[0712] Data processing: Extract charging spot information and tourist spot information through database queries.

[0713] Output: Information on nearby charging spots and tourist spots.

[0714] Step 8:

[0715] The server uses AI to select appropriate charging spots and tourist spots based on emotional state information and generates a driving plan.

[0716] Input: charging spot information, tourist spot information, emotional state information.

[0717] Data calculation: Select spots that adapt to your emotional state and create optimal routes.

[0718] Output: The generated drive plan.

[0719] Step 9:

[0720] The server transmits the generated drive plan to the user terminal.

[0721] Input: The generated drive plan.

[0722] Output: Data sent to the user's terminal.

[0723] Step 10:

[0724] The terminal visually displays the received drive plan to the user using a map display function.

[0725] Input: The received drive plan.

[0726] Output: A visual drive plan displayed on the user's terminal screen.

[0727] 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.

[0728] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0729] 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.

[0730] [Third embodiment]

[0731] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0732] 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.

[0733] 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).

[0734] 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.

[0735] 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.

[0736] 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).

[0737] 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.

[0738] 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.

[0739] 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.

[0740] 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.

[0741] 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.

[0742] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0743] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of the time while charging and provides them with an enjoyable driving plan. This system is implemented through the following specific configuration and processing.

[0744] Users launch a dedicated app on their smartphone, tablet, or other user device and request the creation of a driving plan. At this time, the user device automatically obtains current location information using GPS. At the same time, destination information entered by the user is also obtained.

[0745] The user terminal receives information about the remaining driving distance from the electric vehicle, and transmits information about the current location, remaining driving distance, and destination to the server. The server receives this information and, based on the information provided by the user terminal, retrieves information about nearby charging spots and tourist spots from a database.

[0746] The server uses AI to integrate the acquired charging spot information and tourist spot information and generate an optimal driving plan for enjoying the ride while charging. Furthermore, if necessary, it also acquires information on nearby dining facilities and proposes an optimal dining plan. In this case, the AI ​​utilizes information updated in real time and generates a driving plan based on the most recent information.

[0747] The generated driving plan is sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. For example, the locations of charging spots, tourist spots, and suggested restaurants are displayed on the map, and the route to take while charging is also visually displayed.

[0748] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the user's device sends information about the current location in Tokyo, the remaining driving distance of 100 km, and the destination, Yokohama, to the server. Information provided by the in-vehicle system is also sent to the server.

[0749] The server selects the optimal charging spot between the user's current location and destination, and uses AI to generate a driving plan that includes nearby dining facilities (e.g., cafes and restaurants) and tourist attractions (e.g., museums, parks, etc.) that can be enjoyed while charging.

[0750] The generated plan is sent to the user's device, and the user can view it in the app. For example, the plan may suggest a stop for breakfast at a cafe while the user is charging, or a visit to a museum within walking distance.

[0751] In this way, the present invention provides electric vehicle owners with a system that proposes optimal driving plans that allow them to spend their charging time in a fun and meaningful way. As a result, EV owners can use their charging time efficiently and enjoy a more fulfilling driving experience.

[0752] The processing flow will be explained below.

[0753] Step 1:

[0754] A user requests a driving plan.

[0755] Operation: The user launches the dedicated app and presses the "Create a Drive Plan" button. The user inputs their destination and sets their current location and destination information.

[0756] Step 2:

[0757] The terminal transmits current location information, remaining driving distance, and destination information to the server.

[0758] How it works: The device uses GPS to determine its current location and receives driving range information from the in-vehicle system. It then sends this data, along with the destination information entered by the user, to the server.

[0759] Step 3:

[0760] The on-board system provides the terminal with information on the EV's driving range and estimated arrival time.

[0761] How it works: The onboard system monitors battery status and calculates the current driving range. It also calculates the estimated time of arrival based on current traffic conditions and sends it to the terminal.

[0762] Step 4:

[0763] The server acquires information about nearby charging spots and tourist spots based on user information and vehicle information.

[0764] Operation: The server searches a database based on the received current location information to obtain the latest information on nearby charging spots and tourist attractions. Charging spot information includes the location and availability of available charging stations. Tourist attraction information includes the location and business status of parks, museums, restaurants, etc.

[0765] Step 5:

[0766] The server uses AI to analyze charging spot information and tourist spot information and generate the optimal driving plan.

[0767] How it works: The server inputs the acquired charging spot information and tourist spot information into an AI algorithm, and creates an optimal driving plan based on the user's current location, destination, and available driving distance. The AI ​​makes suggestions by combining the location of charging spots, charging times, and the opening hours of nearby tourist spots and restaurants.

[0768] Step 6:

[0769] The server transmits the generated drive plan to the user terminal.

[0770] Operation: The server sends the generated driving plan to the user's device, which includes information on suggested charging spots and nearby tourist attractions and restaurants.

[0771] Step 7:

[0772] The terminal displays the received plan to the user.

[0773] How it works: The device displays the received driving plan in the app, and the user can use the map view to visually confirm the location of charging spots and tourist attractions, as well as the proposed route.

[0774] As a concrete example, if a user drives from Tokyo to Yokohama, the system will suggest the best charging spot (for example, a charging station with a cafe attached in Tokyo) and nearby tourist attractions (for example, a nearby art museum) when charging is required. The user can check the proposed plan in the app and spend the time while charging meaningfully.

[0775] Example 1

[0776] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0777] Electric vehicle (EV) owners must spend a certain amount of time charging their vehicles, but there are limited ways to make effective use of that time. In particular, how to spend time while charging has become a difficult issue, and there is a demand for efficient and meaningful ways to spend that time.

[0778] 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.

[0779] In this invention, the server includes means for acquiring current location information by an acquisition device, means for receiving destination information by an input device, means for receiving mileage information, means for acquiring information on surrounding charging facilities based on the location information, means for acquiring information on surrounding tourist facilities based on the location information, generation AI means for integrating the charging facility information and the tourist facility information to generate a driving plan that can be enjoyed while charging, means for transmitting the generated driving plan to an information processing device, and means for displaying the driving plan on a display device. This makes it possible to effectively utilize time while charging and provide a driving plan that is enjoyable for the user.

[0780] The "acquisition device" is a device for acquiring current location information.

[0781] An "input device" is a device for receiving destination information.

[0782] "Driving distance information" is information relating to the distance that an electric vehicle can travel.

[0783] "Location information" is information indicating the current geographical location obtained from a user terminal or an in-vehicle system.

[0784] "Charging facility information" is information about facilities for charging electric vehicles.

[0785] "Tourist facility information" is information about tourist spots that users can visit.

[0786] "Generative AI means" refers to a means that utilizes artificial intelligence technology to generate optimal driving plans based on acquired information.

[0787] The "information processing device" is a device for transmitting the generated driving plan to the user terminal.

[0788] A "display device" is a device for displaying a driving plan on a user terminal.

[0789] A "drive plan" is a plan for a travel route that includes tourist spots and dining facilities that can be enjoyed while charging.

[0790] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of their charging time and provide enjoyable driving plans. This system uses hardware and software to perform various data processing and calculations and generate driving plans that are meaningful to the user.

[0791] The user launches a dedicated app on a device such as a smartphone or tablet. The app automatically obtains the user's current location information using GPS. At the same time, it also obtains the destination information entered by the user. The device receives driving range information from the in-vehicle system and sends this information to the server.

[0792] Based on the received information and location information, the server retrieves information on nearby charging facilities and tourist facilities from a database. Detailed information on charging facilities and tourist facilities is stored in the database. The server then uses a generative AI model to integrate the retrieved charging facility information and tourist facility information to generate an optimal driving plan for enjoying the ride while charging. If necessary, the server also retrieves information on nearby dining facilities and suggests an optimal dining plan. This generative AI model generates driving plans based on information updated in real time.

[0793] The generated driving plan is sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. Specifically, the locations of charging stations, tourist facilities, and suggested restaurants are displayed on the map, and the route to take while charging is visually displayed.

[0794] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the device sends information about the current location in Tokyo, the remaining driving distance of 100 km, and the destination, Yokohama, to the server. Information provided by the in-vehicle system is also sent to the server.

[0795] The server selects the optimal charging facility between the user's current location and destination, and uses a generative AI model to generate a driving plan that can be enjoyed while charging, including nearby dining facilities (e.g., cafes and restaurants) and tourist facilities (e.g., museums and parks). An example of a prompt sentence to input into the generative AI model at this time is, "The user's current location is Tokyo, and the destination is Yokohama. The driving distance is 100 km. Please generate a driving plan between Tokyo and Yokohama that includes the optimal charging facility and nearby tourist facilities and dining facilities. Please also provide map information to visualize the generated plan."

[0796] The generated plan is sent to the user's device, where the user can view it in the app. For example, the plan may suggest a stop for breakfast at a cafe while the user is charging, or a visit to a museum within walking distance. In this way, the present invention provides a system that suggests optimal driving plans to electric vehicle owners that allow them to spend their charging time in a fun and meaningful way. As a result, EV owners can use their charging time efficiently and enjoy a more fulfilling driving experience.

[0797] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0798] Step 1:

[0799] The user launches the dedicated app and requests the creation of a driving plan.

[0800] Input: User launches app

[0801] Output: App launch screen

[0802] How it works: The user taps the dedicated app on their smartphone or tablet to launch it, then taps the "Create a driving plan" button to request the creation of a plan.

[0803] Step 2:

[0804] The device obtains current location and destination information

[0805] Input: User's current location and destination information

[0806] Output: Current location and destination information data

[0807] Operation: The device uses the built-in GPS to obtain the user's current location and simultaneously receives the destination (e.g. Yokohama) entered by the user in the app.

[0808] Step 3:

[0809] The device receives the driving range information.

[0810] Input: Range information from electric vehicle

[0811] Output: Driving distance information data

[0812] How it works: The device receives battery status and range information (e.g., 100km) from the vehicle's system via Bluetooth or Wi-Fi.

[0813] Step 4:

[0814] The device sends all information to the server

[0815] Input: current location information, destination information, remaining driving distance information

[0816] Output: Sending information to the server

[0817] Operation: The device compiles the collected current location information, destination information, and remaining driving distance information and sends it to a server via the Internet.

[0818] Step 5:

[0819] The server retrieves information about nearby charging facilities and tourist facilities from a database.

[0820] Input: current location information, destination information

[0821] Output: Charging facility information, tourist facility information data

[0822] Operation: Based on the received information, the server searches the database for and obtains information about charging facilities and tourist facilities located between the user's current location and the destination.

[0823] Step 6:

[0824] The server generates an optimal driving plan using the generative AI model

[0825] Input: current location information, destination information, driving range information, charging facility information, tourist facility information

[0826] Output: Data for optimal driving plans

[0827] Operation: The server inputs the acquired charging facility information and tourist facility information into the generative AI model. The generative AI model generates an optimal driving plan based on the prompt: "The user's current location is Tokyo, and their destination is Yokohama. The driving distance is 100 km. Please generate a driving plan between Tokyo and Yokohama that includes the optimal charging facilities and surrounding tourist facilities and restaurants. Please also provide map information to visualize the generated plan."

[0828] Step 7:

[0829] The server sends the generated driving plan to the terminal.

[0830] Input: Data for optimal drive planning

[0831] Output: Sending the driving plan to the user's terminal

[0832] Operation: The server transmits the generated drive plan data to the user terminal via the Internet.

[0833] Step 8:

[0834] The device displays the driving plan

[0835] Input: Data for optimal drive planning

[0836] Output: Drive plan display on the app

[0837] Operation: The device displays the received driving plan data on the screen of a dedicated app. Using a map API (e.g., Google Maps API), the locations of charging stations, tourist attractions, and restaurants are visualized on a map.

[0838] Step 9:

[0839] User confirms driving plan

[0840] Input: Drive plan display on the app

[0841] Output: User confirmation action

[0842] Operation: The user checks the driving plan displayed in the app, including a list of charging spots, a list of nearby tourist attractions and restaurants, and a map showing the location of the plan, allowing the user to intuitively understand the details of the driving plan.

[0843] (Application example 1)

[0844] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0845] Electric vehicle (EV) owners often have limited options for making effective use of the time while their vehicle is charging, which often prevents them from making the most of that time. It is also difficult to determine the need for charging and the current status of charging stations, making it difficult to plan appropriate trips. Therefore, there is a need for a system that allows EV owners to enjoy the time while charging safely and enjoyably.

[0846] 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.

[0847] In this invention, the server includes means for receiving driving range information, means for acquiring location information, means for receiving destination information, means for acquiring information on nearby charging spots based on the location information, means for acquiring information on nearby tourist spots based on the location information, AI means for integrating the charging spot information and the tourist spot information to generate a driving plan that can be enjoyed while charging, means for transmitting the generated driving plan to a user terminal, means for displaying the driving plan on the user terminal, means for determining whether charging is necessary using the location information and driving range information, means for acquiring information on nearby restaurants and tourist spots if charging is necessary based on the determination, and means for integrating the acquired information to generate an optimal driving plan. This allows electric vehicle owners to effectively utilize their time while charging and enjoy everything from selecting a charging spot to sightseeing and dining.

[0848] "Drivable distance information" is information that indicates the distance that an electric vehicle can travel using the power that is charged.

[0849] "Location information" is information that indicates the current geographical location of an electric vehicle or a user terminal.

[0850] "Destination information" is information that indicates the geographical location of the destination set by the user.

[0851] "Charging spot information" is data that indicates the locations and related information of spots where electric vehicles can be charged.

[0852] "Tourist spot information" is data that indicates the locations of tourist spots and tourist attractions and related information.

[0853] "AI means" refers to a means that uses artificial intelligence technology to integrate charging spot information and tourist spot information to generate an optimal driving plan.

[0854] "User terminal" refers to a computing device operated by a user, such as a smartphone or tablet.

[0855] The "means for determining whether charging is necessary" is a means for determining whether the electric vehicle needs additional charging based on the location information and the driving range information.

[0856] "Dining facility information" is data that indicates the location and related information of dining facilities such as restaurants and cafes.

[0857] The "means for generating an optimal driving plan" is a means for integrating the acquired charging spot information, tourist spot information, and dining facility information to create the most beneficial driving plan for the user.

[0858] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of the time while charging and provides them with an enjoyable driving plan. This system is implemented through the following specific configuration and processing.

[0859] The user launches a dedicated app using a user device such as a smartphone or tablet and requests the creation of a driving plan. At this time, the user device automatically obtains current location information using GPS. At the same time, destination information entered by the user is also obtained. The user device receives information about the remaining driving distance from the electric vehicle and transmits the current location, remaining driving distance, and destination information together to the server.

[0860] The server receives this information and, based on the information provided by the user's device, retrieves information on nearby charging spots and tourist spots from a database. Furthermore, using AI tools, the server integrates the retrieved charging spot information and tourist spot information to generate an optimal driving plan for enjoying while charging. In this process, it uses location information and driving range information to determine whether charging is necessary, and also retrieves information on nearby restaurants and other establishments as necessary.

[0861] The generated driving plan is then sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. For example, the locations of charging spots, tourist spots, and suggested dining facilities are displayed on the map, and the route to take while charging is visually displayed.

[0862] To implement this system, specific hardware and software are required on both the server and user devices. The server requires a computer with high processing power, as well as software for data processing using AI technology. On the other hand, smartphones or tablets with GPS functionality are suitable for user devices.

[0863] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the user's device sends information about the user's current location in Tokyo, the remaining driving distance of 100 km, and the destination, Yokohama, to the server. Information provided by the in-vehicle system is also sent to the server. The server selects the optimal charging spot between the user's current location and destination, and uses AI to generate a drive plan that can be enjoyed while charging, including nearby eating and drinking establishments (e.g., cafes and restaurants) and tourist spots (e.g., museums and parks). The generated plan is sent to the user's device, and the user can view it in the app.

[0864] In addition, by using a generative AI model, it is possible to generate even more sophisticated driving plans. For example, the following can be entered as a prompt to suggest the optimal driving plan taking into account the current location and destination of the autonomous vehicle.

[0865] "Please propose the optimal driving plan taking into account the current location and destination of the autonomous vehicle. The current location is Tokyo, latitude 35.6895, longitude 139.6917, and the destination is Yokohama. The electric vehicle has a range of 100 km. Please provide information on charging spots, tourist attractions, and dining facilities."

[0866] This will allow electric vehicle owners to make effective use of the time spent charging, and enjoy everything from choosing a charging location to sightseeing and dining.

[0867] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0868] Step 1:

[0869] The user launches the dedicated app and requests the creation of a driving plan. The user's device automatically acquires the current location information using the GPS function, and receives the destination information entered by the user as well as the driving range information from the electric vehicle.

[0870] Input: User operation, GPS location information, destination information, remaining driving distance information

[0871] Output: Current location information, destination information, and driving distance information sent to the server

[0872] Step 2:

[0873] The user terminal transmits the current location, remaining driving distance, and destination information to the server.

[0874] Input: current location information, destination information, driving distance information

[0875] Output: Consolidated data sent to the server

[0876] Step 3:

[0877] The server acquires information about nearby charging spots and tourist spots from a database based on the received information about the current location, remaining driving distance, and destination.

[0878] Input: current location information, destination information, driving distance information

[0879] Output: Charging spot information, tourist spot information

[0880] Step 4:

[0881] The server uses AI to integrate information on charging spots and tourist spots and generate an optimal driving plan. At this time, it determines whether charging is necessary based on location information and driving range information, and also obtains information on nearby restaurants and other establishments as needed.

[0882] Input: current location information, destination information, driving range information, charging spot information, tourist spot information

[0883] Output: Optimal driving plan

[0884] Step 5:

[0885] The server transmits the generated drive plan to the user terminal.

[0886] Input: Optimal driving plan

[0887] Output: Drive plan data sent to the user's device

[0888] Step 6:

[0889] The user device displays the received drive plan so that the user can intuitively understand it. The user device uses its map display function to display the locations of charging spots, tourist attractions, and suggested dining facilities.

[0890] Input: Drive plan data sent from the server

[0891] Output: Drive plan displayed on the user's device screen

[0892] Step 7:

[0893] The user checks the displayed drive plan and selects an action to enjoy while charging.

[0894] Input: Drive plan displayed on the user's device

[0895] Output: User's action choice

[0896] These steps will enable electric vehicle owners to make the most of their time while charging and enjoy a fulfilling driving experience.

[0897] 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.

[0898] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of their charging time and proposes more enjoyable driving plans. The system of the present invention incorporates emotion recognition technology to propose customized driving plans according to the user's emotional state.

[0899] The user launches a dedicated app using a user device such as a smartphone or tablet and requests the creation of a driving plan. At this time, the user device automatically obtains current location information using GPS. At the same time, destination information entered by the user is also obtained. Furthermore, the emotion engine uses a camera, microphone, and biometric sensors to analyze data such as facial expressions, voice, and heart rate in order to recognize the user's emotional state.

[0900] The user terminal receives information about the remaining driving distance from the electric vehicle and transmits data on the current location, remaining driving distance, destination information, and emotional state to the server. The server receives this information and, based on the information provided by the user terminal, retrieves information about nearby charging spots and tourist spots from a database.

[0901] The server uses AI means to integrate the acquired charging spot information, tourist spot information, and emotional state to generate an optimal driving plan suited to the user's emotional state. For example, if the emotional state indicates stress, it will suggest relaxing spots, and if the emotional state indicates excitement, it will suggest active spots. It also acquires information on nearby dining facilities and proposes an optimal dining plan. The AI ​​means utilizes information updated in real time to generate a driving plan based on the most recent information.

[0902] The generated driving plan is sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. For example, the locations of charging spots, tourist spots, and suggested restaurants are displayed on the map, and the route to take while charging is also visually displayed.

[0903] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the user's device sends to the server information about the user's current location in Tokyo, the remaining distance of 100 km, and the destination Yokohama, as well as emotional state data obtained through the emotion engine. Information provided by the in-vehicle system is also sent to the server.

[0904] The server selects the optimal charging spot between the user's current location and destination, and uses AI to generate a driving plan that includes suitable nearby tourist attractions and dining options to enjoy while charging based on the user's emotional state. For example, if the user indicates a desire to relax, the server will suggest a plan that includes a charging station with a quiet cafe attached and a nearby park.

[0905] In this way, the present invention provides a system that proposes optimal driving plans to electric vehicle owners, allowing them to spend their charging time in a fun and meaningful way. This allows EV owners to use their charging time efficiently and enjoy a more fulfilling driving experience. The introduction of an emotion engine allows for plans customized according to the user's emotional state, further increasing user satisfaction.

[0906] The processing flow will be explained below.

[0907] Step 1:

[0908] A user requests a driving plan.

[0909] How it works: The user launches the app and presses the "Create a Drive Plan" button. The user then enters their destination, and emotional state data is collected using a facial recognition camera, microphone, and biometric sensors.

[0910] Step 2:

[0911] The terminal transmits current location information, remaining driving distance, and destination information to the server.

[0912] Operation: The device obtains the user's current location using GPS and receives the driving range fetched from the in-vehicle system. It then sends this data along with the destination information entered by the user to the server. It also simultaneously sends the emotional state data obtained by the emotion engine.

[0913] Step 3:

[0914] An emotion engine analyzes the user's emotional state.

[0915] How it works: The emotion engine analyzes collected data such as the user's facial expressions, tone of voice, and heart rate to determine their current emotional state, such as stress, anxiety, or relaxation.

[0916] Step 4:

[0917] The server acquires information about nearby charging spots and tourist spots based on user information, vehicle information, and emotional state.

[0918] Operation: The server searches a database based on the received current location information to obtain the latest information on nearby charging spots and tourist attractions. Charging spot information includes the location and availability of available charging stations. Tourist attraction information includes the location and business status of parks, museums, restaurants, etc.

[0919] Step 5:

[0920] The server uses AI to analyze charging spot information and tourist spot information and generate the optimal driving plan.

[0921] How it works: The server inputs the acquired charging spot and tourist spot information into an AI algorithm, which then creates an optimal driving plan based on the user's current location, destination, driving range, and emotional state. The AI ​​makes suggestions by combining the location of charging spots, charging times, and the opening hours of nearby tourist spots and restaurants. For example, if the user is feeling anxious, it will suggest relaxing parks or spa facilities.

[0922] Step 6:

[0923] The server transmits the generated drive plan to the user terminal.

[0924] Operation: The server sends the generated driving plan to the user's device. This plan includes information on the proposed charging spots and nearby tourist attractions and dining options.

[0925] Step 7:

[0926] The terminal displays the received plan to the user.

[0927] How it works: The device displays the received driving plan in the app, and the user can use the map view to visually confirm the location of charging spots and tourist attractions, as well as the proposed route.

[0928] As a concrete example, if a user drives from Tokyo to Yokohama, the system will suggest the best charging spot (for example, a charging station with a cafe attached in Tokyo) and nearby tourist attractions (for example, a nearby temple or park) when charging is required. If the user indicates an emotional state that requires relaxation, the system will suggest nearby quiet cafes and relaxation facilities. The user can check the suggested plan in the app and spend the time while charging meaningfully.

[0929] Example 2

[0930] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0931] Electric vehicle (EV) owners often waste time while charging, and there is a need for a way to make efficient use of charging time. Furthermore, conventional drive plan suggestion systems only provide uniform information without considering the user's emotional state, which limits the improvement of user satisfaction.

[0932] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving driving range information, means for acquiring location information, means for receiving destination information, means for collecting emotion data, means for acquiring information on nearby charging spots based on the location information, means for acquiring information on nearby tourist spots based on the location information, means for acquiring information on nearby eating and drinking facilities, AI means for integrating the charging spot information, tourist spot information, eating and drinking facility information, and emotion data to generate a driving plan that can be enjoyed while charging, means for transmitting the generated driving plan to the user terminal, and means for displaying the driving plan on the user terminal. This allows the server to provide a driving plan customized according to the user's emotional state, making it possible to spend charging time meaningfully.

[0933] "Drivable distance information" is information that indicates the distance that the electric vehicle can travel with the current remaining battery charge.

[0934] "Location information" is information indicating the current geographical location of a user or vehicle obtained by GPS or other location measurement means.

[0935] "Destination information" is information that indicates the geographical location of the destination set by the user.

[0936] "Emotion data" is data that indicates the emotional state of a user, obtained by analyzing the user's facial expression, voice, biological information, and the like.

[0937] "Charging spot information" is information about locations where electric vehicles can be charged.

[0938] "Tourist attraction information" is information about tourist attractions that the user can visit.

[0939] "Dining facility information" is information about facilities where users can enjoy eating and drinking.

[0940] "AI means" refers to a means of analyzing data using artificial intelligence technology and generating a driving plan suitable for the user.

[0941] A "user terminal" is a smartphone, tablet, or other information device operated by a user.

[0942] A "drive plan" is a plan that suggests sightseeing, dining, and other activities that can be enjoyed while the user is traveling and charging.

[0943] This invention provides a system that enables electric vehicle (EV) owners to effectively utilize their charging time and provide a better driving experience. The system generates a customized driving plan that takes into account the user's emotional state and provides it to the user. Specific embodiments of the system are described below.

[0944] Hardware and Software Configuration

[0945] This system mainly uses the following hardware and software:

[0946] User device: Smartphone or tablet (e.g. iPhone, Android tablet)

[0947] GPS function: A location information acquisition function built into the user's device

[0948] Camera: A camera built into the user's device

[0949] Microphone: A microphone built into the user's device

[0950] Biometric sensors: sensors such as heart rate monitors

[0951] Dedicated app: Application software installed by the user

[0952] Server: A server running on a cloud service that processes data and runs AI models.

[0953] Database: A database that stores information about tourist spots and charging spots (e.g., Google Places API)

[0954] AI Methods: Analyze data and generate driving plans using artificial intelligence models (e.g., TensorFlow, PyTorch)

[0955] Specific operation of the system

[0956] The specific operations when a user requests a drive plan using a dedicated app are as follows.

[0957] 1. Start the user device

[0958] The user launches a dedicated app on their smartphone or tablet.

[0959] 2. Information gathering

[0960] Enter your current location and destination in the app. For example, the user enters their current location as "Tokyo" and their destination as "Yokohama."

[0961] The user device automatically obtains the user's current location using the built-in GPS function.

[0962] Collecting user emotional data using cameras, microphones, and biometric sensors, as well as facial recognition software (e.g., OpenFace) and voice analysis software (e.g., Praat).

[0963] 3. Information Transmission

[0964] The collected data on the current location, destination, driving range (data obtained from the in-vehicle system), and emotion data are sent to the server. The communication module is used to assemble this data into packets and send them to the server.

[0965] 4. Data processing and drive plan generation

[0966] Based on the received data, the server retrieves information about nearby charging spots and tourist spots from a database.

[0967] Using an AI model, the system generates optimal driving plans based on the collected information and the user's emotional state. For example, if the user is in a state of "wanting to relax," it will suggest plans that include quiet cafes and parks.

[0968] 5. Send and display drive plans

[0969] The generated driving plan is sent to the user's terminal. The driving plan is packaged into packets using the communication module and sent to the terminal.

[0970] The user device analyzes the drive plan received from the server and displays it using a map display function (e.g., Google Maps SDK), visually showing the locations of charging spots, tourist attractions, restaurants, etc.

[0971] Specific examples

[0972] For example, if a user plans a drive from Tokyo to Yokohama, they make a request using a dedicated app. The user inputs their current location (Tokyo), destination (Yokohama), remaining driving distance (100km), and emotional state (want to relax) into the system. The device sends this data to the server, which analyzes the information and generates an optimal driving plan. The generated plan includes a charging station with a quiet cafe and a nearby park. This plan is sent to the device, and the user can check the plan in the app and enjoy the drive.

[0973] Prompt Sentence Examples

[0974] As an example of a prompt, the following text is input to the generative AI model:

[0975] "Current location is Tokyo, destination is Yokohama, and remaining driving distance is 100km. The user's emotional state is that they want to relax. Please suggest the optimal driving plan based on these conditions."

[0976] The above is a specific embodiment for carrying out the present invention. This system allows the user to spend time during charging meaningfully and enjoy a driving plan that is optimized for the user's emotional state.

[0977] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0978] Step 1:

[0979] The user launches the dedicated app and requests a driving plan. The user operates the app's interface to input their current location and destination. The user provides information on their current location (e.g., Tokyo) and destination (e.g., Yokohama) as input. The device automatically obtains the current location using its built-in GPS function. This results in the current location (Tokyo) and the input destination (Yokohama) being obtained as output.

[0980] Step 2:

[0981] Collects user emotional data. The device uses a camera, microphone, and biometric sensors to collect the user's facial expressions, voice, heart rate, and other data in real time. Specifically, the camera captures the user's facial expressions, the microphone collects voice data, and the sensor acquires heart rate data. This results in the acquired emotional data being output.

[0982] Step 3:

[0983] The device obtains remaining driving range information from the in-vehicle system. The input is the remaining battery capacity reported by the in-vehicle system, and the output is the calculated remaining driving range information. Specifically, the device communicates with the in-vehicle system via a dedicated protocol or API to query the remaining driving range.

[0984] Step 4:

[0985] The device sends the current location, destination, remaining driving distance, and emotion data together to the server. The input data includes the current location (Tokyo), destination (Yokohama), remaining driving distance, and emotion data. This includes the operation of sending this data to the server using the communication module. This allows the server to receive all the necessary data.

[0986] Step 5:

[0987] The server retrieves information on nearby charging spots, tourist spots, and restaurants from a database based on the received current location, destination, remaining driving distance, and emotion data. The received data (current location, destination, remaining driving distance, emotion data) is used as input, and the server queries the database based on this. As a result, information on charging spots, tourist spots, and restaurants is obtained as output.

[0988] Step 6:

[0989] The server uses an AI model to process and analyze the received and acquired data and generate an optimal driving plan based on the user's emotional state. Input data includes charging spot information, tourist spot information, restaurant information, and emotional data. Analysis and plan generation are performed using an AI model (e.g., TensorFlow, PyTorch). This results in an optimized driving plan being obtained as output.

[0990] Step 7:

[0991] The generated drive plan is sent from the server to the user terminal. The input is the generated drive plan, and the operation of sending this to the user terminal via the communication module is included. As a result, the user terminal receives the drive plan.

[0992] Step 8:

[0993] The user device analyzes the received drive plan and displays it visually. The input is the received drive plan, and the device uses a map display function (e.g., Google Maps SDK) to display charging spots, tourist attractions, dining facilities, and other information on a map. Specifically, the device displays the planned route and spots on the map in a format that is intuitively easy for the user to understand. The output is a visually organized drive plan that is provided to the user.

[0994] The above is the specific processing flow of this system.

[0995] (Application example 2)

[0996] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0997] There is a need for electric vehicle (EV) owners to be able to make effective use of their charging time and enjoy a more enjoyable driving experience. Current charging stations simply charge their vehicles and are unable to provide customized services that reflect the user's emotional state, making the waiting time less meaningful. For this reason, there is a need for a system that can automatically suggest optimal charging spots and tourist spots based on the user's emotional state, allowing them to enjoy their charging time.

[0998] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring emotional state information, means for receiving drivable distance information, means for acquiring location information, means for receiving destination information, means for acquiring information on nearby charging spots based on the location information, means for acquiring information on nearby tourist spots based on the location information, AI means for integrating the charging spot information and the tourist spot information to generate a driving plan that can be enjoyed while charging according to the emotional state, means for transmitting the generated driving plan to a user terminal, and means for displaying the driving plan on the user terminal. This allows the user to enjoy a driving plan customized according to their emotional state, allowing them to spend their waiting time while charging meaningfully and enjoyably.

[0999] "Emotional state information" is data that indicates the emotional state of the user, and includes information such as facial expressions, voice, and heart rate obtained from a camera, microphone, biometric sensor, etc.

[1000] "Drivable distance information" is data indicating the distance that an electric vehicle can travel with the current remaining battery charge.

[1001] "Location Information" means current geographic location data obtained using GPS or other location-determining technology.

[1002] "Destination information" is data relating to a specific destination set by a user.

[1003] "Charging spot information" is data about locations where electric vehicles can be charged.

[1004] "Tourist attraction information" is data about places that travelers aim to visit.

[1005] "AI means" refers to algorithms and software that use artificial intelligence to analyze data and generate optimal driving plans.

[1006] A "user terminal" is an electronic device operated by a user, such as a smartphone, tablet, or in-vehicle system.

[1007] A "drive plan" is a plan of routes and activities that includes charging spots, tourist spots, dining facilities, and other things that can be enjoyed while charging.

[1008] This invention provides a specific system that enables electric vehicle (EV) owners to make effective use of the time spent charging, using user terminals such as smartphones and tablets, in-vehicle systems, and emotion recognition sensors (cameras, microphones, biometric sensors).

[1009] By combining data such as emotional state information, driving range information, location information, destination information, charging spot information, and tourist spot information, an optimal driving plan is generated based on the user's emotional state using AI means. The generated driving plan is sent to the user's device and displayed for visual confirmation.

[1010] The server works as follows:

[1011] 1. Means of acquiring emotional state information

[1012] The system uses cameras, microphones, and biometric sensors installed on user devices and in-vehicle systems to analyze the user's facial expressions, voice, and heart rate to recognize their emotional state, thereby obtaining information in real time about whether the user is relaxed or excited.

[1013] 2. Means for receiving driving range information

[1014] The in-vehicle system receives information about the remaining battery charge of the electric vehicle and sends it to the server via the user's terminal.

[1015] 3. How to obtain location information

[1016] The current location information is obtained using the GPS function of the user's device, and this information is also sent to the server in real time.

[1017] 4. Means of receiving destination information

[1018] The destination information entered by the user through a dedicated app is obtained and sent to the server.

[1019] 5. A method for obtaining information about nearby charging spots based on location information

[1020] Based on the acquired location information, the server retrieves information about nearby charging spots from a database.

[1021] 6. A way to obtain information about nearby tourist spots based on location information

[1022] Similarly, the server retrieves information about nearby tourist spots from a database based on the location information.

[1023] 7. AI method for integrating charging spot information and tourist spot information to generate driving plans that are enjoyable while charging according to the driver's emotional state

[1024] The AI ​​in the server integrates information on the user's emotional state, driving range, charging spots, tourist spots, and dining facilities to generate the optimal driving plan according to the user's emotional state. For example, if the user wants to relax, it will suggest quiet cafes and parks, and if the user wants to be active, it will suggest spots with plenty of activities.

[1025] 8. Means for sending the generated driving plan to the user terminal

[1026] The generated drive plan is transmitted from the server to the user terminal.

[1027] 9. Means for displaying the driving plan on the user's device

[1028] The user terminal displays the received drive plan and also uses a map display function to enable visual confirmation.

[1029] Examples:

[1030] For example, if a user plans a drive from Tokyo to Yokohama, they can request a driving plan through a dedicated app. The user's device will then send the user's current location in Tokyo, the remaining 100km driving distance, information about the destination Yokohama, and their emotional state obtained through the emotion engine to the server. The server will then generate a driving plan that includes the best charging spots and sightseeing spots and dining options according to the user's emotional state, and provide it to the user.

[1031] Example prompt sentence:

[1032] "The user is in Tokyo and planning to travel to Yokohama. The driving range is 100km. The user feels like relaxing. Please suggest charging spots and tourist spots where they can relax."

[1033] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1034] Step 1:

[1035] The user launches the dedicated app and requests the creation of a driving plan.

[1036] Input: A request from a user device (such as a smartphone or tablet).

[1037] Output: Start collecting emotional state information, location information, and destination information.

[1038] Step 2:

[1039] The device automatically obtains the current location information using GPS.

[1040] Input: GPS data from the user device.

[1041] Data processing: Convert to current location coordinates.

[1042] Output: Coordinate data of the user's current location.

[1043] Step 3:

[1044] The user enters destination information into a dedicated app, and the device retrieves it.

[1045] Input: User text entry of destination.

[1046] Data processing: Convert to geographic coordinates of destination.

[1047] Output: Destination coordinate data.

[1048] Step 4:

[1049] The terminal receives the range information from the in-vehicle system.

[1050] Input: Battery level information from the in-car system.

[1051] Data processing: Converted into driving distance.

[1052] Output: Driving distance data.

[1053] Step 5:

[1054] Emotion recognition sensors analyze the user's facial expressions, voice, and heart rate to obtain emotional state information.

[1055] Input: Data from camera, microphone, and biometric sensors.

[1056] Data calculation: Emotional state is estimated through facial expression analysis, voice analysis, and biometric information analysis.

[1057] Output: User's emotional state data.

[1058] Step 6:

[1059] The location information, destination information, remaining driving distance information, and emotional state information acquired by the terminal are transmitted to the server.

[1060] Input: location information, destination information, driving range information, emotional state information.

[1061] Output: Data sent to the server.

[1062] Step 7:

[1063] The server retrieves information about nearby charging spots and tourist spots from a database based on the location information.

[1064] Input: Location.

[1065] Data processing: Extract charging spot information and tourist spot information through database queries.

[1066] Output: Information on nearby charging spots and tourist spots.

[1067] Step 8:

[1068] The server uses AI to select appropriate charging spots and tourist spots based on emotional state information and generates a driving plan.

[1069] Input: charging spot information, tourist spot information, emotional state information.

[1070] Data calculation: Select spots that adapt to your emotional state and create optimal routes.

[1071] Output: The generated drive plan.

[1072] Step 9:

[1073] The server transmits the generated drive plan to the user terminal.

[1074] Input: The generated drive plan.

[1075] Output: Data sent to the user's terminal.

[1076] Step 10:

[1077] The terminal visually displays the received drive plan to the user using a map display function.

[1078] Input: The received drive plan.

[1079] Output: A visual drive plan displayed on the user's terminal screen.

[1080] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1081] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1082] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1083] [Fourth embodiment]

[1084] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1085] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1086] 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).

[1087] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1088] 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.

[1089] 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).

[1090] 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.

[1091] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1092] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1093] 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.

[1094] 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.

[1095] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1096] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1097] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of the time while charging and provides them with an enjoyable driving plan. This system is implemented through the following specific configuration and processing.

[1098] Users launch a dedicated app on their smartphone, tablet, or other user device and request the creation of a driving plan. At this time, the user device automatically obtains current location information using GPS. At the same time, destination information entered by the user is also obtained.

[1099] The user terminal receives information about the remaining driving distance from the electric vehicle, and transmits information about the current location, remaining driving distance, and destination to the server. The server receives this information and, based on the information provided by the user terminal, retrieves information about nearby charging spots and tourist spots from a database.

[1100] The server uses AI to integrate the acquired charging spot information and tourist spot information and generate an optimal driving plan for enjoying the ride while charging. Furthermore, if necessary, it also acquires information on nearby dining facilities and proposes an optimal dining plan. In this case, the AI ​​utilizes information updated in real time and generates a driving plan based on the most recent information.

[1101] The generated driving plan is sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. For example, the locations of charging spots, tourist spots, and suggested restaurants are displayed on the map, and the route to take while charging is also visually displayed.

[1102] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the user's device sends information about the current location in Tokyo, the remaining driving distance of 100 km, and the destination, Yokohama, to the server. Information provided by the in-vehicle system is also sent to the server.

[1103] The server selects the optimal charging spot between the user's current location and destination, and uses AI to generate a driving plan that includes nearby dining facilities (e.g., cafes and restaurants) and tourist attractions (e.g., museums, parks, etc.) that can be enjoyed while charging.

[1104] The generated plan is sent to the user's device, and the user can view it in the app. For example, the plan may suggest a stop for breakfast at a cafe while the user is charging, or a visit to a museum within walking distance.

[1105] In this way, the present invention provides electric vehicle owners with a system that proposes optimal driving plans that allow them to spend their charging time in a fun and meaningful way. As a result, EV owners can use their charging time efficiently and enjoy a more fulfilling driving experience.

[1106] The processing flow will be explained below.

[1107] Step 1:

[1108] A user requests a driving plan.

[1109] Operation: The user launches the dedicated app and presses the "Create a Drive Plan" button. The user inputs their destination and sets their current location and destination information.

[1110] Step 2:

[1111] The terminal transmits current location information, remaining driving distance, and destination information to the server.

[1112] How it works: The device uses GPS to determine its current location and receives driving range information from the in-vehicle system. It then sends this data, along with the destination information entered by the user, to the server.

[1113] Step 3:

[1114] The on-board system provides the terminal with information on the EV's driving range and estimated arrival time.

[1115] How it works: The onboard system monitors battery status and calculates the current driving range. It also calculates the estimated time of arrival based on current traffic conditions and sends it to the terminal.

[1116] Step 4:

[1117] The server acquires information about nearby charging spots and tourist spots based on user information and vehicle information.

[1118] Operation: The server searches a database based on the received current location information to obtain the latest information on nearby charging spots and tourist attractions. Charging spot information includes the location and availability of available charging stations. Tourist attraction information includes the location and business status of parks, museums, restaurants, etc.

[1119] Step 5:

[1120] The server uses AI to analyze charging spot information and tourist spot information and generate the optimal driving plan.

[1121] How it works: The server inputs the acquired charging spot information and tourist spot information into an AI algorithm, and creates an optimal driving plan based on the user's current location, destination, and available driving distance. The AI ​​makes suggestions by combining the location of charging spots, charging times, and the opening hours of nearby tourist spots and restaurants.

[1122] Step 6:

[1123] The server transmits the generated drive plan to the user terminal.

[1124] Operation: The server sends the generated driving plan to the user's device, which includes information on suggested charging spots and nearby tourist attractions and restaurants.

[1125] Step 7:

[1126] The terminal displays the received plan to the user.

[1127] How it works: The device displays the received driving plan in the app, and the user can use the map view to visually confirm the location of charging spots and tourist attractions, as well as the proposed route.

[1128] As a concrete example, if a user drives from Tokyo to Yokohama, the system will suggest the best charging spot (for example, a charging station with a cafe attached in Tokyo) and nearby tourist attractions (for example, a nearby art museum) when charging is required. The user can check the proposed plan in the app and spend the time while charging meaningfully.

[1129] Example 1

[1130] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1131] Electric vehicle (EV) owners must spend a certain amount of time charging their vehicles, but there are limited ways to make effective use of that time. In particular, how to spend time while charging has become a difficult issue, and there is a demand for efficient and meaningful ways to spend that time.

[1132] 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.

[1133] In this invention, the server includes means for acquiring current location information by an acquisition device, means for receiving destination information by an input device, means for receiving mileage information, means for acquiring information on surrounding charging facilities based on the location information, means for acquiring information on surrounding tourist facilities based on the location information, generation AI means for integrating the charging facility information and the tourist facility information to generate a driving plan that can be enjoyed while charging, means for transmitting the generated driving plan to an information processing device, and means for displaying the driving plan on a display device. This makes it possible to effectively utilize time while charging and provide a driving plan that is enjoyable for the user.

[1134] The "acquisition device" is a device for acquiring current location information.

[1135] An "input device" is a device for receiving destination information.

[1136] "Driving distance information" is information relating to the distance that an electric vehicle can travel.

[1137] "Location information" is information indicating the current geographical location obtained from a user terminal or an in-vehicle system.

[1138] "Charging facility information" is information about facilities for charging electric vehicles.

[1139] "Tourist facility information" is information about tourist spots that users can visit.

[1140] "Generative AI means" refers to a means that utilizes artificial intelligence technology to generate optimal driving plans based on acquired information.

[1141] The "information processing device" is a device for transmitting the generated driving plan to the user terminal.

[1142] A "display device" is a device for displaying a driving plan on a user terminal.

[1143] A "drive plan" is a plan for a travel route that includes tourist spots and dining facilities that can be enjoyed while charging.

[1144] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of their charging time and provide enjoyable driving plans. This system uses hardware and software to perform various data processing and calculations and generate driving plans that are meaningful to the user.

[1145] The user launches a dedicated app on a device such as a smartphone or tablet. The app automatically obtains the user's current location information using GPS. At the same time, it also obtains the destination information entered by the user. The device receives driving range information from the in-vehicle system and sends this information to the server.

[1146] Based on the received information and location information, the server retrieves information on nearby charging facilities and tourist facilities from a database. Detailed information on charging facilities and tourist facilities is stored in the database. The server then uses a generative AI model to integrate the retrieved charging facility information and tourist facility information to generate an optimal driving plan for enjoying the ride while charging. If necessary, the server also retrieves information on nearby dining facilities and suggests an optimal dining plan. This generative AI model generates driving plans based on information updated in real time.

[1147] The generated driving plan is sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. Specifically, the locations of charging stations, tourist facilities, and suggested restaurants are displayed on the map, and the route to take while charging is visually displayed.

[1148] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the device sends information about the current location in Tokyo, the remaining driving distance of 100 km, and the destination, Yokohama, to the server. Information provided by the in-vehicle system is also sent to the server.

[1149] The server selects the optimal charging facility between the user's current location and destination, and uses a generative AI model to generate a driving plan that can be enjoyed while charging, including nearby dining facilities (e.g., cafes and restaurants) and tourist facilities (e.g., museums and parks). An example of a prompt sentence to input into the generative AI model at this time is, "The user's current location is Tokyo, and the destination is Yokohama. The driving distance is 100 km. Please generate a driving plan between Tokyo and Yokohama that includes the optimal charging facility and nearby tourist facilities and dining facilities. Please also provide map information to visualize the generated plan."

[1150] The generated plan is sent to the user's device, where the user can view it in the app. For example, the plan may suggest a stop for breakfast at a cafe while the user is charging, or a visit to a museum within walking distance. In this way, the present invention provides a system that suggests optimal driving plans to electric vehicle owners that allow them to spend their charging time in a fun and meaningful way. As a result, EV owners can use their charging time efficiently and enjoy a more fulfilling driving experience.

[1151] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1152] Step 1:

[1153] The user launches the dedicated app and requests the creation of a driving plan.

[1154] Input: User launches app

[1155] Output: App launch screen

[1156] How it works: The user taps the dedicated app on their smartphone or tablet to launch it, then taps the "Create a driving plan" button to request the creation of a plan.

[1157] Step 2:

[1158] The device obtains current location and destination information

[1159] Input: User's current location and destination information

[1160] Output: Current location and destination information data

[1161] Operation: The device uses the built-in GPS to obtain the user's current location and simultaneously receives the destination (e.g. Yokohama) entered by the user in the app.

[1162] Step 3:

[1163] The device receives the driving range information.

[1164] Input: Range information from electric vehicle

[1165] Output: Driving distance information data

[1166] How it works: The device receives battery status and range information (e.g., 100km) from the vehicle's system via Bluetooth or Wi-Fi.

[1167] Step 4:

[1168] The device sends all information to the server

[1169] Input: current location information, destination information, remaining driving distance information

[1170] Output: Sending information to the server

[1171] Operation: The device compiles the collected current location information, destination information, and remaining driving distance information and sends it to a server via the Internet.

[1172] Step 5:

[1173] The server retrieves information about nearby charging facilities and tourist facilities from a database.

[1174] Input: current location information, destination information

[1175] Output: Charging facility information, tourist facility information data

[1176] Operation: Based on the received information, the server searches the database for and obtains information about charging facilities and tourist facilities located between the user's current location and the destination.

[1177] Step 6:

[1178] The server generates an optimal driving plan using the generative AI model

[1179] Input: current location information, destination information, driving range information, charging facility information, tourist facility information

[1180] Output: Data for optimal driving plans

[1181] Operation: The server inputs the acquired charging facility information and tourist facility information into the generative AI model. The generative AI model generates an optimal driving plan based on the prompt: "The user's current location is Tokyo, and their destination is Yokohama. The driving distance is 100 km. Please generate a driving plan between Tokyo and Yokohama that includes the optimal charging facilities and surrounding tourist facilities and restaurants. Please also provide map information to visualize the generated plan."

[1182] Step 7:

[1183] The server sends the generated driving plan to the terminal.

[1184] Input: Data for optimal drive planning

[1185] Output: Sending the driving plan to the user's terminal

[1186] Operation: The server transmits the generated drive plan data to the user terminal via the Internet.

[1187] Step 8:

[1188] The device displays the driving plan

[1189] Input: Data for optimal drive planning

[1190] Output: Drive plan display on the app

[1191] Operation: The device displays the received driving plan data on the screen of a dedicated app. Using a map API (e.g., Google Maps API), the locations of charging stations, tourist attractions, and restaurants are visualized on a map.

[1192] Step 9:

[1193] User confirms driving plan

[1194] Input: Drive plan display on the app

[1195] Output: User confirmation action

[1196] Operation: The user checks the driving plan displayed in the app, including a list of charging spots, a list of nearby tourist attractions and restaurants, and a map showing the location of the plan, allowing the user to intuitively understand the details of the driving plan.

[1197] (Application example 1)

[1198] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1199] Electric vehicle (EV) owners often have limited options for making effective use of the time while their vehicle is charging, which often prevents them from making the most of that time. It is also difficult to determine the need for charging and the current status of charging stations, making it difficult to plan appropriate trips. Therefore, there is a need for a system that allows EV owners to enjoy the time while charging safely and enjoyably.

[1200] 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.

[1201] In this invention, the server includes means for receiving driving range information, means for acquiring location information, means for receiving destination information, means for acquiring information on nearby charging spots based on the location information, means for acquiring information on nearby tourist spots based on the location information, AI means for integrating the charging spot information and the tourist spot information to generate a driving plan that can be enjoyed while charging, means for transmitting the generated driving plan to a user terminal, means for displaying the driving plan on the user terminal, means for determining whether charging is necessary using the location information and driving range information, means for acquiring information on nearby restaurants and tourist spots if charging is necessary based on the determination, and means for integrating the acquired information to generate an optimal driving plan. This allows electric vehicle owners to effectively utilize their time while charging and enjoy everything from selecting a charging spot to sightseeing and dining.

[1202] "Drivable distance information" is information that indicates the distance that an electric vehicle can travel using the power that is charged.

[1203] "Location information" is information that indicates the current geographical location of an electric vehicle or a user terminal.

[1204] "Destination information" is information that indicates the geographical location of the destination set by the user.

[1205] "Charging spot information" is data that indicates the locations and related information of spots where electric vehicles can be charged.

[1206] "Tourist spot information" is data that indicates the locations of tourist spots and tourist attractions and related information.

[1207] "AI means" refers to a means that uses artificial intelligence technology to integrate charging spot information and tourist spot information to generate an optimal driving plan.

[1208] "User terminal" refers to a computing device operated by a user, such as a smartphone or tablet.

[1209] The "means for determining whether charging is necessary" is a means for determining whether the electric vehicle needs additional charging based on the location information and the driving range information.

[1210] "Dining facility information" is data that indicates the location and related information of dining facilities such as restaurants and cafes.

[1211] The "means for generating an optimal driving plan" is a means for integrating the acquired charging spot information, tourist spot information, and dining facility information to create the most beneficial driving plan for the user.

[1212] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of the time while charging and provides them with an enjoyable driving plan. This system is implemented through the following specific configuration and processing.

[1213] The user launches a dedicated app using a user device such as a smartphone or tablet and requests the creation of a driving plan. At this time, the user device automatically obtains current location information using GPS. At the same time, destination information entered by the user is also obtained. The user device receives information about the remaining driving distance from the electric vehicle and transmits the current location, remaining driving distance, and destination information together to the server.

[1214] The server receives this information and, based on the information provided by the user's device, retrieves information on nearby charging spots and tourist spots from a database. Furthermore, using AI tools, the server integrates the retrieved charging spot information and tourist spot information to generate an optimal driving plan for enjoying while charging. In this process, it uses location information and driving range information to determine whether charging is necessary, and also retrieves information on nearby restaurants and other establishments as necessary.

[1215] The generated driving plan is then sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. For example, the locations of charging spots, tourist spots, and suggested dining facilities are displayed on the map, and the route to take while charging is visually displayed.

[1216] To implement this system, specific hardware and software are required on both the server and user devices. The server requires a computer with high processing power, as well as software for data processing using AI technology. On the other hand, smartphones or tablets with GPS functionality are suitable for user devices.

[1217] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the user's device sends information about the user's current location in Tokyo, the remaining driving distance of 100 km, and the destination, Yokohama, to the server. Information provided by the in-vehicle system is also sent to the server. The server selects the optimal charging spot between the user's current location and destination, and uses AI to generate a drive plan that can be enjoyed while charging, including nearby eating and drinking establishments (e.g., cafes and restaurants) and tourist spots (e.g., museums and parks). The generated plan is sent to the user's device, and the user can view it in the app.

[1218] In addition, by using a generative AI model, it is possible to generate even more sophisticated driving plans. For example, the following can be entered as a prompt to suggest the optimal driving plan taking into account the current location and destination of the autonomous vehicle.

[1219] "Please propose the optimal driving plan taking into account the current location and destination of the autonomous vehicle. The current location is Tokyo, latitude 35.6895, longitude 139.6917, and the destination is Yokohama. The electric vehicle has a range of 100 km. Please provide information on charging spots, tourist attractions, and dining facilities."

[1220] This will allow electric vehicle owners to make effective use of the time spent charging, and enjoy everything from choosing a charging location to sightseeing and dining.

[1221] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1222] Step 1:

[1223] The user launches the dedicated app and requests the creation of a driving plan. The user's device automatically acquires the current location information using the GPS function, and receives the destination information entered by the user as well as the driving range information from the electric vehicle.

[1224] Input: User operation, GPS location information, destination information, remaining driving distance information

[1225] Output: Current location information, destination information, and driving distance information sent to the server

[1226] Step 2:

[1227] The user terminal transmits the current location, remaining driving distance, and destination information to the server.

[1228] Input: current location information, destination information, driving distance information

[1229] Output: Consolidated data sent to the server

[1230] Step 3:

[1231] The server acquires information about nearby charging spots and tourist spots from a database based on the received information about the current location, remaining driving distance, and destination.

[1232] Input: current location information, destination information, driving distance information

[1233] Output: Charging spot information, tourist spot information

[1234] Step 4:

[1235] The server uses AI to integrate information on charging spots and tourist spots and generate an optimal driving plan. At this time, it determines whether charging is necessary based on location information and driving range information, and also obtains information on nearby restaurants and other establishments as needed.

[1236] Input: current location information, destination information, driving range information, charging spot information, tourist spot information

[1237] Output: Optimal driving plan

[1238] Step 5:

[1239] The server transmits the generated drive plan to the user terminal.

[1240] Input: Optimal driving plan

[1241] Output: Drive plan data sent to the user's device

[1242] Step 6:

[1243] The user device displays the received drive plan so that the user can intuitively understand it. The user device uses its map display function to display the locations of charging spots, tourist attractions, and suggested dining facilities.

[1244] Input: Drive plan data sent from the server

[1245] Output: Drive plan displayed on the user's device screen

[1246] Step 7:

[1247] The user checks the displayed drive plan and selects an action to enjoy while charging.

[1248] Input: Drive plan displayed on the user's device

[1249] Output: User's action choice

[1250] These steps will enable electric vehicle owners to make the most of their time while charging and enjoy a fulfilling driving experience.

[1251] 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.

[1252] The present invention relates to a system that allows electric vehicle (EV) owners to make effective use of their charging time and proposes more enjoyable driving plans. The system of the present invention incorporates emotion recognition technology to propose customized driving plans according to the user's emotional state.

[1253] The user launches a dedicated app using a user device such as a smartphone or tablet and requests the creation of a driving plan. At this time, the user device automatically obtains current location information using GPS. At the same time, destination information entered by the user is also obtained. Furthermore, the emotion engine uses a camera, microphone, and biometric sensors to analyze data such as facial expressions, voice, and heart rate in order to recognize the user's emotional state.

[1254] The user terminal receives information about the remaining driving distance from the electric vehicle and transmits data on the current location, remaining driving distance, destination information, and emotional state to the server. The server receives this information and, based on the information provided by the user terminal, retrieves information about nearby charging spots and tourist spots from a database.

[1255] The server uses AI means to integrate the acquired charging spot information, tourist spot information, and emotional state to generate an optimal driving plan suited to the user's emotional state. For example, if the emotional state indicates stress, it will suggest relaxing spots, and if the emotional state indicates excitement, it will suggest active spots. It also acquires information on nearby dining facilities and proposes an optimal dining plan. The AI ​​means utilizes information updated in real time to generate a driving plan based on the most recent information.

[1256] The generated driving plan is sent from the server to the user's device, which receives and displays it. The user can check the driving plan on the app and intuitively understand the plan's contents using the map display function. For example, the locations of charging spots, tourist spots, and suggested restaurants are displayed on the map, and the route to take while charging is also visually displayed.

[1257] As a concrete example, consider the case where a user is planning a drive from Tokyo to Yokohama. When the user requests a drive plan using a dedicated app, the user's device sends to the server information about the user's current location in Tokyo, the remaining distance of 100 km, and the destination Yokohama, as well as emotional state data obtained through the emotion engine. Information provided by the in-vehicle system is also sent to the server.

[1258] The server selects the optimal charging spot between the user's current location and destination, and uses AI to generate a driving plan that includes suitable nearby tourist attractions and dining options to enjoy while charging based on the user's emotional state. For example, if the user indicates a desire to relax, the server will suggest a plan that includes a charging station with a quiet cafe attached and a nearby park.

[1259] In this way, the present invention provides a system that proposes optimal driving plans to electric vehicle owners, allowing them to spend their charging time in a fun and meaningful way. This allows EV owners to use their charging time efficiently and enjoy a more fulfilling driving experience. The introduction of an emotion engine allows for plans customized according to the user's emotional state, further increasing user satisfaction.

[1260] The processing flow will be explained below.

[1261] Step 1:

[1262] A user requests a driving plan.

[1263] How it works: The user launches the app and presses the "Create a Drive Plan" button. The user then enters their destination, and emotional state data is collected using a facial recognition camera, microphone, and biometric sensors.

[1264] Step 2:

[1265] The terminal transmits current location information, remaining driving distance, and destination information to the server.

[1266] Operation: The device obtains the user's current location using GPS and receives the driving range fetched from the in-vehicle system. It then sends this data along with the destination information entered by the user to the server. It also simultaneously sends the emotional state data obtained by the emotion engine.

[1267] Step 3:

[1268] An emotion engine analyzes the user's emotional state.

[1269] How it works: The emotion engine analyzes collected data such as the user's facial expressions, tone of voice, and heart rate to determine their current emotional state, such as stress, anxiety, or relaxation.

[1270] Step 4:

[1271] The server acquires information about nearby charging spots and tourist spots based on user information, vehicle information, and emotional state.

[1272] Operation: The server searches a database based on the received current location information to obtain the latest information on nearby charging spots and tourist attractions. Charging spot information includes the location and availability of available charging stations. Tourist attraction information includes the location and business status of parks, museums, restaurants, etc.

[1273] Step 5:

[1274] The server uses AI to analyze charging spot information and tourist spot information and generate the optimal driving plan.

[1275] How it works: The server inputs the acquired charging spot and tourist spot information into an AI algorithm, which then creates an optimal driving plan based on the user's current location, destination, driving range, and emotional state. The AI ​​makes suggestions by combining the location of charging spots, charging times, and the opening hours of nearby tourist spots and restaurants. For example, if the user is feeling anxious, it will suggest relaxing parks or spa facilities.

[1276] Step 6:

[1277] The server transmits the generated drive plan to the user terminal.

[1278] Operation: The server sends the generated driving plan to the user's device. This plan includes information on the proposed charging spots and nearby tourist attractions and dining options.

[1279] Step 7:

[1280] The terminal displays the received plan to the user.

[1281] How it works: The device displays the received driving plan in the app, and the user can use the map view to visually confirm the location of charging spots and tourist attractions, as well as the proposed route.

[1282] As a concrete example, if a user drives from Tokyo to Yokohama, the system will suggest the best charging spot (for example, a charging station with a cafe attached in Tokyo) and nearby tourist attractions (for example, a nearby temple or park) when charging is required. If the user indicates an emotional state that requires relaxation, the system will suggest nearby quiet cafes and relaxation facilities. The user can check the suggested plan in the app and spend the time while charging meaningfully.

[1283] Example 2

[1284] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1285] Electric vehicle (EV) owners often waste time while charging, and there is a need for a way to make efficient use of charging time. Furthermore, conventional drive plan suggestion systems only provide uniform information without considering the user's emotional state, which limits the improvement of user satisfaction.

[1286] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving driving range information, means for acquiring location information, means for receiving destination information, means for collecting emotion data, means for acquiring information on nearby charging spots based on the location information, means for acquiring information on nearby tourist spots based on the location information, means for acquiring information on nearby eating and drinking facilities, AI means for integrating the charging spot information, tourist spot information, eating and drinking facility information, and emotion data to generate a driving plan that can be enjoyed while charging, means for transmitting the generated driving plan to the user terminal, and means for displaying the driving plan on the user terminal. This allows the server to provide a driving plan customized according to the user's emotional state, making it possible to spend charging time meaningfully.

[1287] "Drivable distance information" is information that indicates the distance that the electric vehicle can travel with the current remaining battery charge.

[1288] "Location information" is information indicating the current geographical location of a user or vehicle obtained by GPS or other location measurement means.

[1289] "Destination information" is information that indicates the geographical location of the destination set by the user.

[1290] "Emotion data" is data that indicates the emotional state of a user, obtained by analyzing the user's facial expression, voice, biological information, and the like.

[1291] "Charging spot information" is information about locations where electric vehicles can be charged.

[1292] "Tourist attraction information" is information about tourist attractions that the user can visit.

[1293] "Dining facility information" is information about facilities where users can enjoy eating and drinking.

[1294] "AI means" refers to a means of analyzing data using artificial intelligence technology and generating a driving plan suitable for the user.

[1295] A "user terminal" is a smartphone, tablet, or other information device operated by a user.

[1296] A "drive plan" is a plan that suggests sightseeing, dining, and other activities that can be enjoyed while the user is traveling and charging.

[1297] This invention provides a system that enables electric vehicle (EV) owners to effectively utilize their charging time and provide a better driving experience. The system generates a customized driving plan that takes into account the user's emotional state and provides it to the user. Specific embodiments of the system are described below.

[1298] Hardware and Software Configuration

[1299] This system mainly uses the following hardware and software:

[1300] User device: Smartphone or tablet (e.g. iPhone, Android tablet)

[1301] GPS function: A location information acquisition function built into the user's device

[1302] Camera: A camera built into the user's device

[1303] Microphone: A microphone built into the user's device

[1304] Biometric sensors: sensors such as heart rate monitors

[1305] Dedicated app: Application software installed by the user

[1306] Server: A server running on a cloud service that processes data and runs AI models.

[1307] Database: A database that stores information about tourist spots and charging spots (e.g., Google Places API)

[1308] AI Methods: Analyze data and generate driving plans using artificial intelligence models (e.g., TensorFlow, PyTorch)

[1309] Specific operation of the system

[1310] The specific operations when a user requests a drive plan using a dedicated app are as follows.

[1311] 1. Start the user device

[1312] The user launches a dedicated app on their smartphone or tablet.

[1313] 2. Information gathering

[1314] Enter your current location and destination in the app. For example, the user enters their current location as "Tokyo" and their destination as "Yokohama."

[1315] The user device automatically obtains the user's current location using the built-in GPS function.

[1316] Collecting user emotional data using cameras, microphones, and biometric sensors, as well as facial recognition software (e.g., OpenFace) and voice analysis software (e.g., Praat).

[1317] 3. Information Transmission

[1318] The collected data on the current location, destination, driving range (data obtained from the in-vehicle system), and emotion data are sent to the server. The communication module is used to assemble this data into packets and send them to the server.

[1319] 4. Data processing and drive plan generation

[1320] Based on the received data, the server retrieves information about nearby charging spots and tourist spots from a database.

[1321] Using an AI model, the system generates optimal driving plans based on the collected information and the user's emotional state. For example, if the user is in a state of "wanting to relax," it will suggest plans that include quiet cafes and parks.

[1322] 5. Send and display drive plans

[1323] The generated driving plan is sent to the user's terminal. The driving plan is packaged into packets using the communication module and sent to the terminal.

[1324] The user device analyzes the drive plan received from the server and displays it using a map display function (e.g., Google Maps SDK), visually showing the locations of charging spots, tourist attractions, restaurants, etc.

[1325] Specific examples

[1326] For example, if a user plans a drive from Tokyo to Yokohama, they make a request using a dedicated app. The user inputs their current location (Tokyo), destination (Yokohama), remaining driving distance (100km), and emotional state (want to relax) into the system. The device sends this data to the server, which analyzes the information and generates an optimal driving plan. The generated plan includes a charging station with a quiet cafe and a nearby park. This plan is sent to the device, and the user can check the plan in the app and enjoy the drive.

[1327] Prompt Sentence Examples

[1328] As an example of a prompt, the following text is input to the generative AI model:

[1329] "Current location is Tokyo, destination is Yokohama, and remaining driving distance is 100km. The user's emotional state is that they want to relax. Please suggest the optimal driving plan based on these conditions."

[1330] The above is a specific embodiment for carrying out the present invention. This system allows the user to spend time during charging meaningfully and enjoy a driving plan that is optimized for the user's emotional state.

[1331] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1332] Step 1:

[1333] The user launches the dedicated app and requests a driving plan. The user operates the app's interface to input their current location and destination. The user provides information on their current location (e.g., Tokyo) and destination (e.g., Yokohama) as input. The device automatically obtains the current location using its built-in GPS function. This results in the current location (Tokyo) and the input destination (Yokohama) being obtained as output.

[1334] Step 2:

[1335] Collects user emotional data. The device uses a camera, microphone, and biometric sensors to collect the user's facial expressions, voice, heart rate, and other data in real time. Specifically, the camera captures the user's facial expressions, the microphone collects voice data, and the sensor acquires heart rate data. This results in the acquired emotional data being output.

[1336] Step 3:

[1337] The device obtains remaining driving range information from the in-vehicle system. The input is the remaining battery capacity reported by the in-vehicle system, and the output is the calculated remaining driving range information. Specifically, the device communicates with the in-vehicle system via a dedicated protocol or API to query the remaining driving range.

[1338] Step 4:

[1339] The device sends the current location, destination, remaining driving distance, and emotion data together to the server. The input data includes the current location (Tokyo), destination (Yokohama), remaining driving distance, and emotion data. This includes the operation of sending this data to the server using the communication module. This allows the server to receive all the necessary data.

[1340] Step 5:

[1341] The server retrieves information on nearby charging spots, tourist spots, and restaurants from a database based on the received current location, destination, remaining driving distance, and emotion data. The received data (current location, destination, remaining driving distance, emotion data) is used as input, and the server queries the database based on this. As a result, information on charging spots, tourist spots, and restaurants is obtained as output.

[1342] Step 6:

[1343] The server uses an AI model to process and analyze the received and acquired data and generate an optimal driving plan based on the user's emotional state. Input data includes charging spot information, tourist spot information, restaurant information, and emotional data. Analysis and plan generation are performed using an AI model (e.g., TensorFlow, PyTorch). This results in an optimized driving plan being obtained as output.

[1344] Step 7:

[1345] The generated drive plan is sent from the server to the user terminal. The input is the generated drive plan, and the operation of sending this to the user terminal via the communication module is included. As a result, the user terminal receives the drive plan.

[1346] Step 8:

[1347] The user device analyzes the received drive plan and displays it visually. The input is the received drive plan, and the device uses a map display function (e.g., Google Maps SDK) to display charging spots, tourist attractions, dining facilities, and other information on a map. Specifically, the device displays the planned route and spots on the map in a format that is intuitively easy for the user to understand. The output is a visually organized drive plan that is provided to the user.

[1348] The above is the specific processing flow of this system.

[1349] (Application example 2)

[1350] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1351] There is a need for electric vehicle (EV) owners to be able to make effective use of their charging time and enjoy a more enjoyable driving experience. Current charging stations simply charge their vehicles and are unable to provide customized services that reflect the user's emotional state, making the waiting time less meaningful. For this reason, there is a need for a system that can automatically suggest optimal charging spots and tourist spots based on the user's emotional state, allowing them to enjoy their charging time.

[1352] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring emotional state information, means for receiving drivable distance information, means for acquiring location information, means for receiving destination information, means for acquiring information on nearby charging spots based on the location information, means for acquiring information on nearby tourist spots based on the location information, AI means for integrating the charging spot information and the tourist spot information to generate a driving plan that can be enjoyed while charging according to the emotional state, means for transmitting the generated driving plan to a user terminal, and means for displaying the driving plan on the user terminal. This allows the user to enjoy a driving plan customized according to their emotional state, allowing them to spend their waiting time while charging meaningfully and enjoyably.

[1353] "Emotional state information" is data that indicates the emotional state of the user, and includes information such as facial expressions, voice, and heart rate obtained from a camera, microphone, biometric sensor, etc.

[1354] "Drivable distance information" is data indicating the distance that an electric vehicle can travel with the current remaining battery charge.

[1355] "Location Information" means current geographic location data obtained using GPS or other location-determining technology.

[1356] "Destination information" is data relating to a specific destination set by a user.

[1357] "Charging spot information" is data about locations where electric vehicles can be charged.

[1358] "Tourist attraction information" is data about places that travelers aim to visit.

[1359] "AI means" refers to algorithms and software that use artificial intelligence to analyze data and generate optimal driving plans.

[1360] A "user terminal" is an electronic device operated by a user, such as a smartphone, tablet, or in-vehicle system.

[1361] A "drive plan" is a plan of routes and activities that includes charging spots, tourist spots, dining facilities, and other things that can be enjoyed while charging.

[1362] This invention provides a specific system that enables electric vehicle (EV) owners to make effective use of the time spent charging, using user terminals such as smartphones and tablets, in-vehicle systems, and emotion recognition sensors (cameras, microphones, biometric sensors).

[1363] By combining data such as emotional state information, driving range information, location information, destination information, charging spot information, and tourist spot information, an optimal driving plan is generated based on the user's emotional state using AI means. The generated driving plan is sent to the user's device and displayed for visual confirmation.

[1364] The server works as follows:

[1365] 1. Means of acquiring emotional state information

[1366] The system uses cameras, microphones, and biometric sensors installed on user devices and in-vehicle systems to analyze the user's facial expressions, voice, and heart rate to recognize their emotional state, thereby obtaining information in real time about whether the user is relaxed or excited.

[1367] 2. Means for receiving driving range information

[1368] The in-vehicle system receives information about the remaining battery charge of the electric vehicle and sends it to the server via the user's terminal.

[1369] 3. How to obtain location information

[1370] The current location information is obtained using the GPS function of the user's device, and this information is also sent to the server in real time.

[1371] 4. Means of receiving destination information

[1372] The destination information entered by the user through a dedicated app is obtained and sent to the server.

[1373] 5. A method for obtaining information about nearby charging spots based on location information

[1374] Based on the acquired location information, the server retrieves information about nearby charging spots from a database.

[1375] 6. A way to obtain information about nearby tourist spots based on location information

[1376] Similarly, the server retrieves information about nearby tourist spots from a database based on the location information.

[1377] 7. AI method for integrating charging spot information and tourist spot information to generate driving plans that are enjoyable while charging according to the driver's emotional state

[1378] The AI ​​in the server integrates information on the user's emotional state, driving range, charging spots, tourist spots, and dining facilities to generate the optimal driving plan according to the user's emotional state. For example, if the user wants to relax, it will suggest quiet cafes and parks, and if the user wants to be active, it will suggest spots with plenty of activities.

[1379] 8. Means for sending the generated driving plan to the user terminal

[1380] The generated drive plan is transmitted from the server to the user terminal.

[1381] 9. Means for displaying the driving plan on the user's device

[1382] The user terminal displays the received drive plan and also uses a map display function to enable visual confirmation.

[1383] Examples:

[1384] For example, if a user plans a drive from Tokyo to Yokohama, they can request a driving plan through a dedicated app. The user's device will then send the user's current location in Tokyo, the remaining 100km driving distance, information about the destination Yokohama, and their emotional state obtained through the emotion engine to the server. The server will then generate a driving plan that includes the best charging spots and sightseeing spots and dining options according to the user's emotional state, and provide it to the user.

[1385] Example prompt sentence:

[1386] "The user is in Tokyo and planning to travel to Yokohama. The driving range is 100km. The user feels like relaxing. Please suggest charging spots and tourist spots where they can relax."

[1387] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1388] Step 1:

[1389] The user launches the dedicated app and requests the creation of a driving plan.

[1390] Input: A request from a user device (such as a smartphone or tablet).

[1391] Output: Start collecting emotional state information, location information, and destination information.

[1392] Step 2:

[1393] The device automatically obtains the current location information using GPS.

[1394] Input: GPS data from the user device.

[1395] Data processing: Convert to current location coordinates.

[1396] Output: Coordinate data of the user's current location.

[1397] Step 3:

[1398] The user enters destination information into a dedicated app, and the device retrieves it.

[1399] Input: User text entry of destination.

[1400] Data processing: Convert to geographic coordinates of destination.

[1401] Output: Destination coordinate data.

[1402] Step 4:

[1403] The terminal receives the range information from the in-vehicle system.

[1404] Input: Battery level information from the in-car system.

[1405] Data processing: Converted into driving distance.

[1406] Output: Driving distance data.

[1407] Step 5:

[1408] Emotion recognition sensors analyze the user's facial expressions, voice, and heart rate to obtain emotional state information.

[1409] Input: Data from camera, microphone, and biometric sensors.

[1410] Data calculation: Emotional state is estimated through facial expression analysis, voice analysis, and biometric information analysis.

[1411] Output: User's emotional state data.

[1412] Step 6:

[1413] The location information, destination information, remaining driving distance information, and emotional state information acquired by the terminal are transmitted to the server.

[1414] Input: location information, destination information, driving range information, emotional state information.

[1415] Output: Data sent to the server.

[1416] Step 7:

[1417] The server retrieves information about nearby charging spots and tourist spots from a database based on the location information.

[1418] Input: Location.

[1419] Data processing: Extract charging spot information and tourist spot information through database queries.

[1420] Output: Information on nearby charging spots and tourist spots.

[1421] Step 8:

[1422] The server uses AI to select appropriate charging spots and tourist spots based on emotional state information and generates a driving plan.

[1423] Input: charging spot information, tourist spot information, emotional state information.

[1424] Data calculation: Select spots that adapt to your emotional state and create optimal routes.

[1425] Output: The generated drive plan.

[1426] Step 9:

[1427] The server transmits the generated drive plan to the user terminal.

[1428] Input: The generated drive plan.

[1429] Output: Data sent to the user's terminal.

[1430] Step 10:

[1431] The terminal visually displays the received drive plan to the user using a map display function.

[1432] Input: The received drive plan.

[1433] Output: A visual drive plan displayed on the user's terminal screen.

[1434] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1435] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1436] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1437] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1438] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1439] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1440] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1441] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1442] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1443] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1444] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1445] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1446] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1447] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1448] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1449] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1450] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1451] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1452] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1453] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1454] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1455] The following is further disclosed regarding the above embodiment.

[1456] (Claim 1)

[1457] means for receiving mileage information;

[1458] A means for acquiring location information;

[1459] means for receiving destination information;

[1460] A means for acquiring information about nearby charging spots based on location information;

[1461] A means for acquiring information about nearby tourist spots based on the location information;

[1462] An AI means for integrating the charging spot information and tourist spot information to generate a driving plan that can be enjoyed while charging;

[1463] means for transmitting the generated drive plan to a user terminal;

[1464] means for displaying the drive plan on a user terminal;

[1465] A system including:

[1466] (Claim 2)

[1467] 2. The system according to claim 1, wherein the drive plan generating means also acquires information about nearby eating and drinking establishments and proposes a dining plan that can be enjoyed while charging.

[1468] (Claim 3)

[1469] 2. The system according to claim 1, wherein the AI ​​means generates a driving plan using charging spot information and tourist spot information that are updated in real time.

[1470] (Claim 4)

[1471] 2. The system according to claim 1, wherein the user terminal has a map display function, and the generated drive plan is displayed on a map.

[1472] "Example 1"

[1473] (Claim 1)

[1474] means for acquiring current location information by an acquisition device;

[1475] means for receiving destination information by an input device;

[1476] means for receiving mileage information;

[1477] A means for acquiring information about surrounding charging facilities based on location information;

[1478] A means for acquiring information about surrounding tourist facilities based on the location information;

[1479] A generation AI means for integrating the charging facility information and the tourist facility information to generate a driving plan that can be enjoyed while charging;

[1480] means for transmitting the generated driving plan to an information processing device;

[1481] means for displaying the drive plan on a display device;

[1482] A system including:

[1483] (Claim 2)

[1484] 2. The system according to claim 1, wherein the drive plan generation means also acquires information about nearby eating and drinking establishments and proposes a dining plan that can be enjoyed while charging.

[1485] (Claim 3)

[1486] The system according to claim 1, wherein the generating AI means generates a driving plan using charging facility information and tourist facility information that are updated in real time.

[1487] "Application Example 1"

[1488] (Claim 1)

[1489] means for receiving mileage information;

[1490] A means for acquiring location information;

[1491] means for receiving destination information;

[1492] A means for acquiring information about nearby charging spots based on location information;

[1493] A means for acquiring information about nearby tourist spots based on the location information;

[1494] An AI means for integrating the charging spot information and tourist spot information to generate a driving plan that can be enjoyed while charging;

[1495] means for transmitting the generated drive plan to a user terminal;

[1496] means for displaying the drive plan on a user terminal;

[1497] a means for determining whether charging is necessary using the location information and the available driving distance information;

[1498] When charging is necessary based on the determination, a means for acquiring information on nearby eating and drinking establishments and tourist spots;

[1499] means for integrating the acquired information to generate an optimal drive plan;

[1500] A system including:

[1501] (Claim 2)

[1502] 2. The system according to claim 1, wherein the drive plan generating means also acquires information about nearby eating and drinking establishments and proposes a dining plan that can be enjoyed while charging.

[1503] (Claim 3)

[1504] 2. The system according to claim 1, wherein the AI ​​means generates a driving plan using charging spot information and tourist spot information that are updated in real time.

[1505] "Example 2: Combining Emotion Engines"

[1506] (Claim 1)

[1507] means for receiving mileage information;

[1508] A means for acquiring location information;

[1509] means for receiving destination information;

[1510] a means for collecting emotion data;

[1511] A means for acquiring information about nearby charging spots based on location information;

[1512] A means for acquiring information about nearby tourist spots based on the location information;

[1513] A means for obtaining information about nearby dining establishments;

[1514] An AI method for integrating charging spot information, tourist spot information, restaurant information, and emotional data to generate a driving plan that can be enjoyed while charging;

[1515] means for transmitting the generated drive plan to a user terminal;

[1516] A means for displaying the drive plan on the user's terminal

[1517] A system including:

[1518] (Claim 2)

[1519] The system of claim 1, wherein the AI ​​means generates a driving plan using charging spot information and tourist spot information that are updated in real time.

[1520] (Claim 3)

[1521] 2. The system according to claim 1, wherein a driving plan is generated based on the emotional data and adapted to the emotional state of the user.

[1522] "Application example 2 when combining emotion engines"

[1523] (Claim 1)

[1524] a means for obtaining emotional state information;

[1525] means for receiving mileage information;

[1526] A means for acquiring location information;

[1527] means for receiving destination information;

[1528] A means for acquiring information about nearby charging spots based on location information;

[1529] A means for acquiring information about nearby tourist spots based on the location information;

[1530] An AI means for integrating the charging spot information and tourist spot information to generate a driving plan that can be enjoyed while charging according to the emotional state;

[1531] means for transmitting the generated drive plan to a user terminal;

[1532] means for displaying the drive plan on a user terminal;

[1533] A system including:

[1534] (Claim 2)

[1535] The system according to claim 1, wherein the drive plan generation means also acquires information about nearby dining facilities and proposes a dining plan that can be enjoyed while charging according to the emotional state.

[1536] (Claim 3)

[1537] 2. The system according to claim 1, wherein the AI ​​means generates a driving plan using charging spot information and tourist spot information that are updated in real time. [Explanation of symbols]

[1538] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving mileage information; A means for acquiring location information; means for receiving destination information; A means for acquiring information about nearby charging spots based on location information; A means for acquiring information about nearby tourist spots based on the location information; An AI means for integrating the charging spot information and tourist spot information to generate a driving plan that can be enjoyed while charging; means for transmitting the generated drive plan to a user terminal; means for displaying the drive plan on a user terminal; A system including:

2. The system according to claim 1, wherein the drive plan generating means also acquires information about nearby eating and drinking establishments and proposes a dining plan that can be enjoyed while charging.

3. The system according to claim 1, wherein the AI ​​means generates a driving plan using charging spot information and tourist spot information that are updated in real time.

4. 2. The system according to claim 1, wherein the user terminal has a map display function, and the generated drive plan is displayed on the map.

Images