system

Abstract

Provide a system. [Solution] An input means for inputting cargo quantity, delivery destination, and schedule; a transmitting means for transmitting the information inputted via the input means to a server; a search means for searching a database for available vehicles based on the transmitted information; a transmitting means for transmitting the available vehicle information obtained by the searching means to a terminal; a reservation means for allowing a user to select a vehicle based on the search results and transmit reservation information to a server; A route calculation means for calculating an optimal vehicle dispatch route based on reservation information; a transmitting means for transmitting the calculation result and reservation confirmation information to a terminal; A system including:

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] In the current logistics industry, searching for and reserving the appropriate vehicle based on cargo volume, delivery destination, and delivery date is complex and time-consuming. Furthermore, the calculation of the optimal vehicle dispatch route is often done manually, making efficient delivery difficult. This makes it difficult to effectively utilize available vehicles and optimally allocate resources. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that searches for and reserves the optimal available vehicle based on the cargo volume, delivery destination, and schedule entered by the user. This system includes an input means for inputting the cargo volume, delivery destination, and schedule, a transmission means for transmitting the input information to a server, a search means for searching a database for available vehicles based on the transmitted information, a transmission means for transmitting the search results to a terminal, a reservation means for the user to select a vehicle from the search results and transmit the reservation information to the server, a route calculation means for calculating the optimal vehicle dispatch route based on the reservation information, and a transmission means for transmitting the calculation results to the terminal. This system efficiently searches for and reserves available vehicles and automates the calculation of the optimal vehicle dispatch route, thereby improving the efficiency of logistics operations.

[0006] "Load" is a value indicating the weight or volume of cargo.

[0007] "Delivery point" refers to the location to which cargo is ultimately delivered.

[0008] "Date" means a specific date for delivery of a shipment.

[0009] An "input means" is a device or interface through which a user provides data to a system.

[0010] The "transmission means" is a method or device for transmitting input data to a server.

[0011] A "server" is a computer system that processes and stores data and provides services to clients.

[0012] A "database" is a system for systematically storing and managing data.

[0013] A "search tool" is a method or device for retrieving information from a database based on specific criteria.

[0014] "Terminal" refers to a device such as a computer or smartphone that is directly operated by a user.

[0015] A "reservation means" is a method or device for reserving a vehicle selected by a user.

[0016] A "route calculation means" is a method or device for calculating an optimal route from a starting point to a destination point. [Brief explanation of the drawings]

[0017] [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 illustrating 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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The present invention is a system for searching for and reserving available vehicles based on cargo volume, delivery destination, and schedule, and also creates optimal vehicle dispatch routes. This makes it possible to improve the efficiency of logistics operations. Specific embodiments of the system of the present invention are described below.

[0039] A dedicated web form or mobile application is provided on the terminal to allow users to input the cargo amount, delivery destination, and schedule. This form has fields for inputting the cargo amount, delivery destination, and the user's schedule, making it easy to enter the required data. After that, when the user presses the "Search" button, the terminal sends this information to the server.

[0040] The server analyzes the received information, accesses the database, and searches for available vehicles. Specifically, it extracts vehicles that can transport the input load on the specified date. If a suitable vehicle is found, it returns the vehicle information to the terminal.

[0041] The terminal receives the reply from the server and displays a list of available vehicles to the user. The user selects the desired vehicle from the displayed list and presses the "Reserve" button, which sends the reservation information for that vehicle to the server.

[0042] Once the server receives the reservation information, it processes the reservation, including updating the vehicle's status to "reserved." At the same time, the server calculates the optimal route from the departure point to the delivery destination. This calculation is performed using a map service such as Google® Maps API. The calculation results include distance, travel time, and a recommended route.

[0043] Finally, the server sends the confirmed reservation information and details of the vehicle dispatch route to the terminal. The terminal displays this information to the user, who can confirm that the reservation has been confirmed and the optimal vehicle dispatch route. As a specific example, if the user enters "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01," the system will search for available vehicles that match these conditions and present them to the user. When the user selects one of the suggested vehicles and makes a reservation, the server calculates the optimal route and notifies the user of the results.

[0044] In this way, a system is realized that can efficiently search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and also create optimal vehicle dispatch routes. This system improves the efficiency of the entire logistics operation and reduces resource waste.

[0045] The processing flow will be explained below.

[0046] Step 1:

[0047] The user accesses the web form or mobile application on their device and enters the cargo amount, delivery destination, and delivery date. The user enters the necessary information, such as "Cargo amount: 1000 kg," "Delivery destination: Tokyo," and "Date: 2023-12-01."

[0048] Step 2:

[0049] The terminal acquires the information entered in the input form, converts it to JSON format, and sends an HTTP POST request to the server. The request payload contains the information entered by the user: cargo quantity, delivery destination, and delivery date.

[0050] Step 3:

[0051] The server receives the request from the terminal. The server analyzes the received information and creates a database query based on the load, destination, and delivery date. The query contains criteria for finding available vehicles that can transport the specified load on a specific date.

[0052] Step 4:

[0053] The server queries the database to retrieve information about available vehicles that match the criteria, including the vehicle's ID, maximum load capacity, and status (e.g., "available").

[0054] Step 5:

[0055] The server generates search results in JSON format and returns this information to the device, including a list of all available vehicles that match the search criteria.

[0056] Step 6:

[0057] The terminal receives the reply from the server and displays the results in a user interface that displays a list of all the vehicles provided as search results, each with a "Book Now" button.

[0058] Step 7:

[0059] The user selects the appropriate vehicle from the displayed list of vehicles and presses the "Reserve" button. The selected vehicle's ID and the necessary reservation information are sent back to the server from the terminal.

[0060] Step 8:

[0061] The server receives the reservation information and updates the status of the corresponding vehicle to "reserved." The server also calculates the optimal route from the departure point to the delivery destination, using a map API (e.g., Google Maps API) to determine the distance, travel time, and recommended route.

[0062] Step 9:

[0063] The server generates the reservation confirmation information and the calculated vehicle route in JSON format and sends it to the terminal.

[0064] Step 10:

[0065] The terminal receives the reply from the server and displays the reservation confirmation information and the optimal route information to the user, allowing the user to confirm that the reservation has been confirmed and the delivery route.

[0066] Through these specific processing steps, a system is realized that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and provides the optimal vehicle dispatch route.

[0067] Example 1

[0068] 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."

[0069] In the past, it was difficult to search for and reserve an appropriate available vehicle based on cargo volume, delivery destination, and schedule, and then create an optimal vehicle dispatch route in logistics operations. Furthermore, manual information management and vehicle dispatch plan creation required time and cost, resulting in a decrease in the efficiency of the entire logistics operation. Furthermore, if an appropriate available vehicle cannot be found or an optimal vehicle dispatch route cannot be calculated, resources are wasted. Thus, a system that can improve the efficiency of logistics operations and optimize the use of resources is needed.

[0070] 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.

[0071] In this invention, the server includes input means for inputting the cargo amount, delivery destination, and schedule, transmission means for transmitting the information input via the input means to the server, search means for searching for available vehicles from the information management device based on the transmitted information, transmission means for transmitting available vehicle information obtained by the search means to the terminal, reservation means for the user to select a vehicle based on the search result and transmit reservation information to the server, route calculation means for calculating the optimal vehicle dispatch route based on the reservation information, and transmission means for transmitting the calculation result and reservation confirmation information to the terminal. This makes it possible to improve the efficiency of the entire logistics operation and reduce waste of resources.

[0072] "Input means" refers to a device or software that allows a user to input the cargo amount, delivery destination, and schedule.

[0073] The "transmission means" refers to a device or mechanism that transmits information input via the input means to the server.

[0074] The "information management device" refers to a database that holds information about available vehicles and the management system for that database.

[0075] The "search means" refers to a device or software for searching for available vehicles from the information management device based on the transmitted information.

[0076] The "reservation means" refers to a device or software that allows the user to select a vehicle based on the search results and transmit the reservation information to the server.

[0077] The "route calculation means" refers to a device or software for calculating the optimal vehicle dispatch route based on reservation information.

[0078] A "terminal" is an electronic device or computer through which a user enters information and receives results.

[0079] The present invention is a system for searching for and reserving available vehicles based on cargo volume, delivery destination, and schedule, and also creates optimal vehicle dispatch routes. This system can improve the efficiency of logistics operations. Specific embodiments of the present invention are described below.

[0080] A dedicated web form or mobile application is provided on the terminal so that the user can enter the load amount, delivery destination, and delivery date. This form has fields for entering the load amount, delivery destination, and delivery date, allowing the user to easily enter the required data. For example, the user enters "Load amount: 1000 kg," "Delivery destination: Tokyo," and "Date: 2023-12-01."

[0081] After that, when the user presses the "Search" button, the terminal sends this information to the server as an HTTP request. The server receives the request and extracts information such as the cargo amount, delivery destination, and delivery date by parsing the JSON data. Based on the parsed information, the server executes an SQL query against a database (for example, a general SQL database) to search for available vehicles that can transport the entered cargo amount on the specified date. As a result, a list of available vehicles is obtained.

[0082] If a matching vehicle is found, the server generates information about that vehicle in JSON format and returns it to the terminal. The terminal receives the response, parses the JSON data, and displays it to the user. For example, a list containing information such as "Vehicle 1: Truck A, Load Capacity: 1500 kg, Current Location: Osaka" is displayed. The user selects the desired vehicle from the displayed list and presses the "Reserve" button. The terminal then sends the reservation information selected by the user to the server.

[0083] Based on the received reservation information, the server updates the status of the corresponding vehicle in its database to "reserved." The server then uses a map service such as Google Maps API to calculate the optimal route from the departure point to the delivery destination. The calculation results include the distance, required time, and recommended route. The server generates the calculation results in JSON format and returns them to the terminal. The terminal parses the information and displays it to the user, allowing them to confirm that the reservation has been confirmed and the details of the vehicle dispatch route. For example, the terminal may display information such as "Reservation confirmed. Recommended route: total distance 500 km, required time 6 hours, route A, route B."

[0084] This allows you to efficiently search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and also create optimal vehicle dispatch routes, improving the efficiency of overall logistics operations and reducing resource waste.

[0085] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0086] Step 1:

[0087] The user inputs the cargo amount, delivery destination, and delivery date.

[0088] The user uses a terminal to access a dedicated web form or mobile application and enters the load amount (e.g., 1,000 kg), delivery destination (e.g., Tokyo), and delivery date (e.g., 2023-12-01). This data is captured as text entered into the form.

[0089] Input: cargo amount, delivery destination, date (e.g. 1000kg, Tokyo, 2023-12-01)

[0090] Output: Data entered into the form

[0091] Step 2:

[0092] The terminal transmits the input information to the server.

[0093] When the user presses the "Search" button, the device converts the entered information into JSON format data and sends it to the server as an HTTP request.

[0094] Input: Data entered into a form

[0095] Output: JSON format data (e.g., { "Load": "1000kg", "Delivery destination": "Tokyo", "Date": "2023-12-01"})

[0096] Step 3:

[0097] The server receives and analyzes the data.

[0098] The server analyzes the HTTP request received from the terminal, parses the JSON data, and extracts the fields for cargo quantity, delivery destination, and schedule.

[0099] Input: JSON format data

[0100] Output: Extracted cargo volume, delivery destination, and schedule

[0101] Step 4:

[0102] The server searches for available vehicles from the information management device.

[0103] Based on the analyzed information, the server executes an SQL query against the database to search for available vehicles that can transport the input load on the specified date. For example, it executes a query such as "SELECT FROM vehicle WHERE date = '2023-12-01' AND maximum load capacity >= 1000kg".

[0104] Input: Extracted cargo volume, delivery destination, schedule

[0105] Output: A list of available vehicles as a result of the search.

[0106] Step 5:

[0107] The server returns the search results to the device.

[0108] If a matching vehicle is found, the server generates the vehicle information in JSON format and returns it to the terminal. For example, it generates data like "{ Vehicle ID: 1, Vehicle name: 'Truck A', Maximum load capacity: '1500kg', Current location: 'Osaka'}".

[0109] Input: A list of available vehicles as search results

[0110] Output: Vehicle information in JSON format

[0111] Step 6:

[0112] Your device will display the search results.

[0113] The terminal parses the JSON data received from the server and displays a list of available vehicles suggested to the user. For example, it displays information such as "Truck A, Load Capacity: 1500 kg, Current Location: Osaka."

[0114] Input: Vehicle information in JSON format

[0115] Output: A list of vehicles displayed to the user

[0116] Step 7:

[0117] The user selects and reserves a vehicle.

[0118] The user selects the desired vehicle from the displayed list and presses the "Reserve" button. The user's selection data is acquired by the terminal as reservation information.

[0119] Input: User selected vehicle information

[0120] Output: Reservation information

[0121] Step 8:

[0122] The terminal transmits the reservation information to the server.

[0123] The terminal converts the reservation information selected by the user into JSON format data and sends it to the server as an HTTP request.

[0124] Input: Reservation information

[0125] Output: Reservation information in JSON format

[0126] Step 9:

[0127] The server confirms the reservation based on the reservation information.

[0128] Based on the received reservation information, the server updates the status of the corresponding vehicle in the database to "reserved." For example, it executes an SQL query such as "UPDATE VEHICLE SET STATUS = 'RESERVED' WHERE VEHICLE ID = 1."

[0129] Input: Reservation information in JSON format

[0130] Output: Database update results

[0131] Step 10:

[0132] The server calculates the route.

[0133] The server uses a map service such as Google Maps API to calculate the optimal route from the starting point to the delivery destination, including distance, time required, and a recommended route.

[0134] Input: Departure point, delivery destination

[0135] Output: Calculated vehicle routing (e.g., distance 500 km, travel time 6 hours, route A)

[0136] Step 11:

[0137] The server returns the details of the vehicle route to the terminal.

[0138] The server generates the calculation results in JSON format and sends them to the terminal. For example, it generates data like "{ distance: '500km', required time: '6 hours', recommended route: 'Route A'}".

[0139] Input: Calculated vehicle routing route

[0140] Output: JSON formatted route information

[0141] Step 12:

[0142] The terminal displays the final information.

[0143] The device parses the JSON data received from the server and displays to the user that the reservation has been confirmed and details of the optimal route. For example, it displays "Reservation confirmed. Recommended route: total distance 500 km, required time 6 hours, route A."

[0144] Input: JSON formatted route information

[0145] Output: Confirmed booking information and route details displayed to the user

[0146] (Application example 1)

[0147] 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."

[0148] In the modern logistics industry, optimal vehicle allocation and route planning is required based on cargo volume, delivery destination, and schedule. However, doing this manually is extremely inefficient and wastes time and resources. Furthermore, it is difficult to check available vehicles in real time or propose optimal routes, making efficient vehicle allocation difficult. Therefore, a system is needed to improve the efficiency of logistics operations overall.

[0149] 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.

[0150] In this invention, the server includes an input means for inputting the cargo amount, delivery destination, and schedule, a transmission means for transmitting the information input via the input means to the server, a search means for searching a database for available vehicles based on the transmitted information, a transmission means for transmitting available vehicle information obtained by the search means to a terminal, a reservation means for a user to select a vehicle based on the search result and transmit reservation information to the server, a route calculation means for calculating an optimal vehicle dispatch route based on the reservation information, a transmission means for transmitting the calculation result and reservation confirmation information to the terminal, a means operated via a smartphone application used in the logistics center, a means for providing a web form for a user to easily input the cargo amount, delivery destination, and schedule, a means for calculating the route using a Google Maps API, and a means for analyzing prompts input by a user using a generative AI model and making optimal suggestions, thereby enabling efficient and real-time vehicle dispatch and route suggestions for logistics operations.

[0151] "Load volume" refers to the weight and volume of cargo or luggage, and is information that serves as the basis for determining the capacity of the vehicle required for transportation.

[0152] "Delivery destination" refers to the location or address where the package or product is to be delivered, and is important destination information in the logistic procedure.

[0153] "Schedule" refers to the schedule for shipping and arrival of packages, and is information for time management in the logistics process.

[0154] "Input means" refers to a device or interface (e.g., a web form or application) that allows a user to enter required information into a system.

[0155] "Transmission means" refers to a system or device that has the function of transmitting input information to a server.

[0156] A "search means" is a system or device that has the function of searching for relevant information (e.g., available vehicle information) from a database based on received information.

[0157] A "reservation vehicle" is a system or device that has the functionality to reserve a product or service (in this case, a vehicle) selected by a user.

[0158] "Route calculation means" refers to a system or device that has the function of calculating the optimal vehicle dispatch route from the departure point to the arrival point.

[0159] "Smartphone applications used within logistics centers" refers to mobile applications used by logistics center staff to manage cargo and arrange vehicle dispatches.

[0160] "Web Form" refers to an online form that allows a user to enter required information in a browser.

[0161] "Google Maps API" is a program interface for the map service provided by Google, and is a tool that provides functions such as map display and route calculation.

[0162] A "generative AI model" refers to an artificial intelligence system that learns from large amounts of data and provides optimal responses and suggestions for specified tasks or questions.

[0163] A "prompt" is an instruction or question entered by a user to instruct a generative AI model on a specific task.

[0164] This invention is a system that includes a smartphone application that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule at a logistics center. It also creates optimal vehicle dispatch routes, improving the efficiency of logistics operations.

[0165] Users input the cargo amount, delivery destination, and delivery date using a smartphone application installed in the logistics center. The smartphone application used in the logistics center has an intuitive user interface and provides a web form, allowing users to easily enter the necessary information.

[0166] The entered information is sent to the server via the smartphone application's transmission means. The server analyzes the received information and accesses the database to search for available vehicles. Specifically, the search means extracts available vehicles with a load capacity equal to or greater than the transmitted load capacity. If a suitable vehicle is found, the vehicle's information is sent to the terminal, and a list of suggested available vehicles is displayed to the user.

[0167] The user selects the desired vehicle from the displayed list and presses the "Reserve" button, and the reservation information is sent to the server. The server receives the reservation information and performs the reservation confirmation process, which includes updating the status of the corresponding vehicle to "Reserved."

[0168] At the same time, the server calculates the optimal route from the starting point to the delivery destination. This calculation is performed using the Google Maps API, and the calculation results include distance, travel time, and recommended route. Furthermore, using a generative AI model, the system makes optimal suggestions when the user inputs a prompt. The generative AI model is trained based on a large amount of data and returns the most appropriate result for the user's input.

[0169] Finally, the server sends the reservation confirmation and route details to the smartphone application, which displays this information to the user, who can confirm that the reservation has been confirmed and the optimal route.

[0170] For example, if a user enters "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01," the system can search for available vehicles that match these conditions and present them to the user. When the user reserves the suggested vehicle, the server uses the Google Maps API to calculate the optimal vehicle dispatch route and notify the user of the results.

[0171] An example of a prompt is:

[0172] "Search for available vehicles to deliver a 1000kg package to Tokyo on December 1, 2023, and suggest the best route."

[0173] In this way, a system is realized that efficiently searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and also creates optimal vehicle dispatch routes, thereby improving the efficiency of the entire logistics operation and reducing resource waste.

[0174] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0175] Step 1:

[0176] The user launches the smartphone application and inputs the cargo amount, delivery destination, and delivery date. The web form has an intuitive interface, making it easy to enter information. The input data (cargo amount, delivery destination, delivery date) obtained using the input means is temporarily stored in the smartphone's memory.

[0177] Step 2:

[0178] When the user presses the "Search" button, the terminal transmits the input data to the server via the transmission means. The transmitted data is in a format that includes information on the input amount, delivery destination, and schedule.

[0179] Step 3:

[0180] The server analyzes the received data and searches the database for available vehicles. Using the search means, the server extracts available vehicles from the database that can transport the input load for the specified date and time. This search process reads the ID of the vehicle that matches the conditions, its future usage schedule, and the load capacity.

[0181] Step 4:

[0182] The available vehicle information obtained by the search means is transmitted to a smartphone application using a transmission means, and the user can check a list of suggested available vehicles on the smartphone display.

[0183] Step 5:

[0184] The user selects the desired vehicle from the displayed list and presses the "Reserve" button. The terminal then sends the reservation information for the selected vehicle to the server. This reservation information includes the vehicle ID, reservation date and time, user ID, etc.

[0185] Step 6:

[0186] The server receives the reservation information and processes the reservation. It updates the status of the corresponding vehicle to "reserved" and records this information in the database. At the same time, the server calculates the optimal vehicle route from the departure point to the delivery destination. It uses the Google Maps API to calculate the optimal route, including the shortest distance and required time.

[0187] Step 7:

[0188] The generative AI model is used to analyze prompts entered by users. For example, the generative AI model analyzes a prompt such as, "Please search for available vehicles to deliver a 1,000 kg package to Tokyo on December 1, 2023, and suggest the optimal route," and makes appropriate suggestions. Based on this analysis, the optimal route information and vehicle information are reevaluated.

[0189] Step 8:

[0190] The server sends the route calculation results and reservation confirmation information to the smartphone application via the transmission means. The terminal receives this and displays to the user that the reservation has been confirmed and the optimal vehicle dispatch route. The user can check the details of the vehicle dispatch route on the smartphone screen and efficiently proceed with the vehicle dispatch operation.

[0191] In this way, the system efficiently executes a series of processes, from inputting the cargo volume, delivery destination, and schedule to searching for available vehicles, making reservations, and calculating routes, providing the user with the information they need.

[0192] 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.

[0193] This invention combines a system that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and creates optimal vehicle dispatch routes with an emotion engine that recognizes user emotions. This system not only improves the efficiency of logistics operations, but also enhances the user experience.

[0194] The interface for users to input cargo volume, delivery destination, and schedule is provided as a web form or mobile application. Users enter the cargo volume, delivery destination, and schedule and then press the "Search" button to start the search.

[0195] The terminal converts the input information into JSON format and sends it to the server via a transmission means. The server analyzes the received information and searches the database based on the cargo amount, delivery destination, and schedule. After obtaining information on the corresponding available vehicle, the server returns this information to the terminal.

[0196] The terminal receives the response from the server and displays the results to the user. The user selects the desired vehicle from the displayed results and presses the "Reserve" button, which sends reservation information such as the selected vehicle's ID to the server.

[0197] After receiving the reservation information, the server updates the vehicle's status to "reserved." The server then calculates the optimal route from the departure point to the delivery destination and returns the results to the terminal.

[0198] The emotion engine analyzes the input information and operations performed by the user while using the system, and determines the user's emotional state in real time. For example, it recognizes emotional states such as stress or decreased attention based on the user's input speed, mouse movements, and touchscreen operation patterns.

[0199] Based on the analysis results of the emotion engine, the system provides the following functions:

[0200] 1. Adjust search results and notifications:

[0201] If the emotion engine determines that you are stressed, it will simplify search results, highlight important information, and phrase notifications in more user-friendly language.

[0202] 2. Changes in how vehicle routing is suggested:

[0203] If the emotion engine determines that the user is in a hurry, it will prioritize the shortest route, while if the user is relaxed, it can suggest a scenic route that is a comfortable drive.

[0204] As a concrete example, suppose a user inputs "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01" and executes "search." The device sends this information to the server, which searches the database for available vehicles that match the criteria. The server then sends the search results to the device, which displays them to the user. Once the user selects the desired vehicle and confirms the reservation, the server calculates a vehicle dispatch route that takes into account the user's current emotional state based on the analysis results of the emotion engine, and sends this information to the device.

[0205] In this way, a system is realized that not only efficiently searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and provides the optimal vehicle dispatch route, but also improves the user experience by taking into account the user's emotional state.

[0206] The processing flow will be explained below.

[0207] Step 1:

[0208] The user accesses the web form or mobile application on their device and enters the cargo amount, delivery destination, and delivery date. For example, they enter information such as "Cargo amount: 1000 kg," "Delivery destination: Tokyo," and "Date: 2023-12-01."

[0209] Step 2:

[0210] The terminal receives the input information, converts it to JSON format, and sends an HTTP POST request to the server, which includes the input information on the load, delivery destination, and delivery date.

[0211] Step 3:

[0212] The server receives the request from the terminal. The server analyzes the received information and creates a database query based on the load, destination, and delivery date. The query contains criteria for finding available vehicles that can transport the specified load on a specific date.

[0213] Step 4:

[0214] The server queries the database to retrieve information about available vehicles that match the criteria, including the vehicle's ID, maximum load capacity, and status (e.g., "available").

[0215] Step 5:

[0216] The server generates search results in JSON format and sends this information to the device, which returns a list of all available vehicles that match the search criteria.

[0217] Step 6:

[0218] The terminal receives the reply from the server and displays a list of available vehicles to the user. The user selects the desired vehicle from the list and presses the "Reserve" button.

[0219] Step 7:

[0220] When the user presses the "Reserve" button, the ID of the selected vehicle and the necessary reservation information are sent from the terminal to the server. The reservation information includes the ID of the selected vehicle.

[0221] Step 8:

[0222] The server receives the reservation information and updates the status of the corresponding vehicle to "reserved." The server then calculates the optimal route from the departure point to the delivery destination. This calculation uses a map API (e.g., Google Maps API) to find the distance, travel time, and recommended route.

[0223] Step 9:

[0224] The server generates the reservation confirmation information and the calculated vehicle route in JSON format and sends it to the terminal.

[0225] Step 10:

[0226] The terminal receives the reply from the server and displays the reservation confirmation information and the optimal route information to the user, allowing the user to confirm that the reservation has been confirmed and the delivery route.

[0227] Step 11:

[0228] The emotion engine analyzes the user's input speed, operation patterns, mouse movements, and touchscreen operations to determine the user's emotional state in real time.

[0229] Step 12:

[0230] Based on the analysis results of the emotion engine, the server adjusts search results taking into account the user's emotional state. Specifically, if it determines that the user is feeling stressed, it condenses search results and highlights important information.

[0231] Step 13:

[0232] The emotion engine suggests optimal routes based on the user's emotional state. For example, it suggests the shortest route for a user in a hurry, and a scenic route for a user who is relaxed.

[0233] In this way, the system can efficiently search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and provide optimal vehicle dispatch routes that take the user's emotional state into consideration, simultaneously improving the user experience and streamlining logistics operations.

[0234] Example 2

[0235] 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."

[0236] Conventional logistics systems can search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and provide optimal vehicle dispatch routes, but they lack the ability to provide services that take into account the user's emotional state. Therefore, improvements are needed to reduce user stress and provide a better user experience.

[0237] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0238] In this invention, the server includes input means for inputting the cargo amount, delivery destination, and schedule, transmission means for transmitting the information input via the input means to a central device, search means for searching a storage device for available vehicles based on the transmitted information, transmission means for transmitting available vehicle information obtained by the search means to a terminal, reservation means for a user to select a vehicle based on the search results and transmit reservation information to the central device, route calculation means for calculating an optimal vehicle dispatch route based on the reservation information, transmission means for transmitting the calculation result and reservation confirmation information to the terminal, emotion analysis means for analyzing the user's operation and input information and determining the user's emotional state, result adjustment means for adjusting the search results and notification content based on the result of the emotion analysis means, and route suggestion means for changing the method of suggesting vehicle dispatch routes based on the result of the emotion analysis means. This makes it possible to provide logistics services that take the user's emotional state into consideration, which was not possible with conventional systems.

[0239] "Cargo volume" refers to the total weight of cargo transported in logistics.

[0240] "Delivery point" means the final receiving location to which the shipment is delivered.

[0241] "Schedule" refers to the scheduled delivery date or delivery period in logistics.

[0242] "Input means" refers to a device or interface used by a user to input cargo quantity, delivery destination, and delivery date into the system.

[0243] "Transmission means" refers to a means for transmitting input information to another device or system.

[0244] "Central device" refers to the main device that controls the entire system and processes and manages various types of information.

[0245] "Storage device" refers to a hardware or software component used to store information as data.

[0246] "Search means" refers to a device or program that has the function of searching for information from a database or the like based on certain conditions.

[0247] "Terminal" refers to a device that a user accesses and uses to perform various operations such as inputting and displaying information.

[0248] "Reservation means" refers to an interface that allows a user to select a desired vehicle and transmit that information to the system.

[0249] "Route calculation means" refers to a device or program that has the function of calculating the optimal vehicle dispatch route from the departure point to the delivery destination.

[0250] "Emotion analysis means" refers to a system that analyzes the user's input speed, operation patterns, etc., and determines the user's emotional state.

[0251] "Result adjustment means" refers to a device or program that has the function of adjusting search results or notification content based on the results of the emotion analysis means.

[0252] The "route suggestion means" refers to a device or program that has the function of changing the method of suggesting the optimal vehicle dispatch route based on the results of the emotion analysis means.

[0253] The present invention is directed to a system that aims to improve the efficiency of a logistics system and the user experience. Hereinafter, an embodiment of the present invention will be described in detail.

[0254] The interface for users to input cargo volume, delivery destination, and schedule is provided as a web form or mobile application. Users enter the necessary information through these interfaces and start the operation by pressing the "Search" button. This input method works on platforms such as web browsers and mobile apps.

[0255] The terminal converts the input information into JSON format and sends it to the central server using an HTTP request. The HTTPS protocol is used for transmission. The server parses the received JSON data and analyzes the information on the load, delivery destination, and schedule.

[0256] The server uses a relational database management system (RDBMS) such as MySQL (registered trademark) to search the database stored in the storage device. For example, the following SQL query is used as a search method:

[0257] SELECT FROM Vehicle WHERE Load >= '1000kg' AND Delivery Destination = 'Tokyo' AND Available Date >= '2023-12-01'

[0258] This allows you to obtain available vehicles that meet the conditions.

[0259] The search results are converted to JSON format and sent from the server to the terminal. The transmission method is again HTTPS protocol. The terminal analyzes the results and displays them visually to the user. The user selects the desired vehicle from the displayed search results and clicks the "Reserve" button.

[0260] The device converts the reservation information, including the ID of the selected vehicle, into JSON format and sends it to the server using an HTTP request. The server parses the received reservation information and executes an SQL query to update the vehicle's status to "reserved":

[0261] UPDATE VEHICLE SET STATE = 'RESERVED' WHERE ID = '123'

[0262] After the reservation is completed, the server uses the Google Maps API to calculate the optimal route from the departure point to the delivery destination. The calculation result is converted into JSON format and sent from the server to the terminal. The terminal receives it and displays it visually to the user.

[0263] Additionally, the app is equipped with an emotion engine that analyzes the user's typing speed, mouse movements, touch patterns, etc. to determine the user's emotional state. The emotion engine uses machine learning models to assess stress levels, attention deficits, etc. in real time. Depending on the emotional state, the app offers the following features:

[0264] 1. Adjust search results and notifications:

[0265] If the system detects that a user is stressed, it will simplify search results, highlight important information, and present notifications in user-friendly language.

[0266] 2. Changes in how vehicle routing is suggested:

[0267] If the system determines that the user is in a hurry, it will prioritize showing the shortest route, while if the user is relaxed, it will suggest a scenic route that will provide a comfortable drive.

[0268] As a concrete example, consider the case where a user inputs "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01" and executes "search." The terminal sends this information to the server, which searches the database for available vehicles that match the criteria. The server then sends the search results to the terminal, which displays them to the user. Once the user selects the desired vehicle and confirms the reservation, the server calculates the optimal vehicle dispatch route based on the analysis results of the emotion engine, taking into account the user's current emotional state, and sends this information to the terminal.

[0269] Examples of prompts for generative AI models include:

[0270] "We want to build a system that allows users to input their cargo volume, delivery destination, and delivery date, search for available vehicles, and reserve them. We also want to be able to analyze the user's emotional state and adjust the display content and route suggestions accordingly."

[0271] In this way, the system can search for the most suitable available vehicle based on the cargo volume, delivery destination, and schedule, and provide an efficient logistics service that takes into account the user's emotional state.

[0272] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0273] Step 1:

[0274] The user uses a web form or mobile app to input the load, delivery destination, and delivery date. The user enters the load (e.g., 1000 kg), delivery destination (e.g., Tokyo), and delivery date (e.g., 2023-12-01) into each field in the form and clicks the "Search" button. This input is received by the terminal.

[0275] Step 2:

[0276] The terminal converts the information entered by the user, such as the amount of cargo, delivery destination, and delivery date, into JSON format. For example, the following JSON data is generated:

[0277] {"Load": "1000kg", "Delivery destination": "Tokyo", "Date": "2023-12-01"}

[0278] The converted JSON data is sent to the server via an HTTP request, which is part of the transmission method.

[0279] Step 3:

[0280] The server parses the received JSON data and extracts the necessary information (cargo volume, delivery destination, schedule). Specifically, it uses a JSON parser to extract the following data:

[0281] Load: 1000kg, Delivery location: Tokyo, Date: 2023-12-01

[0282] Based on this data, the server searches for available vehicles using a relational database such as MySQL.

[0283] Step 4:

[0284] The server generates and executes the SQL query to search the database:

[0285] SELECT FROM Vehicle WHERE Load >= '1000kg' AND Delivery Destination = 'Tokyo' AND Available Date >= '2023-12-01'

[0286] The information about available vehicles obtained through this search is converted into JSON format and returned to the terminal via an HTTP response.

[0287] Step 5:

[0288] The device receives the search results in JSON format from the server and parses them. For example, it parses the following results:

[0289] {"Vehicle": [{"ID": "123", "Vehicle Type": "Large Truck", "Status": "Available"}]}

[0290] The terminal visually displays the analyzed data to the user, specifically, the search results in a table format.

[0291] Step 6:

[0292] The user selects the desired vehicle from the displayed search results and clicks the "Reserve" button. This operation records the ID of the selected vehicle in the terminal. For example, the user selects a large truck with ID 123.

[0293] Step 7:

[0294] The device converts the reservation information, such as the vehicle ID selected by the user and the user ID, into JSON format. Specifically, the following data is generated:

[0295] {"Vehicle ID": "123", "User ID": "456"}

[0296] The converted JSON data is again sent to the server via an HTTP request.

[0297] Step 8:

[0298] The server parses the received reservation information and executes a SQL query to update the vehicle status to "reserved":

[0299] UPDATE VEHICLE SET STATE = 'RESERVED' WHERE ID = '123'

[0300] After the update is complete, the server uses the Google Maps API or similar to calculate the optimal route from the starting point to the delivery destination.

[0301] Step 9:

[0302] The server converts the calculated route into JSON format and sends it to the device via an HTTP response. For example, the following data is generated:

[0303] {"Route": "Detailed directions from the starting point to the delivery destination"}

[0304] The terminal receives this and displays it visually to the user.

[0305] Step 10:

[0306] The terminal collects data such as the user's input speed and operation patterns and sends it to the emotion analysis means, which analyzes this data and determines the user's emotional state, for example, whether the user is in a hurry or relaxed.

[0307] Step 11:

[0308] Based on the results of the emotion analysis, the server adjusts search results and notification content. For example, if it determines that the user is feeling stressed, it simplifies search results, highlights important information, and phrases notifications in more user-friendly language.

[0309] Step 12:

[0310] Based on the results of the emotion analysis, the server changes the way it suggests routes. For example, if it determines that the user is in a hurry, it will prioritize the shortest route. On the other hand, if the user is relaxed, it will suggest a route with a nice view.

[0311] This allows the system to not only search for and reserve the most suitable available vehicle based on cargo volume, delivery destination, and schedule, but also to provide logistics services that take into account the user's emotional state.

[0312] (Application example 2)

[0313] 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."

[0314] In conventional logistics systems, it is common to search for available vehicles based on conditions such as cargo volume, delivery destination, and schedule, and then provide the optimal vehicle dispatch route, but this alone has problems such as reducing user stress and not being able to support efficient input. In particular, there is a problem that information provided without considering the user's emotional state is insufficient to improve the user experience and is likely to reduce the user's work efficiency.

[0315] 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: input means for inputting the cargo amount, delivery destination, and schedule; transmission means for transmitting the information input via the input means to the server; search means for searching a database for available vehicles based on the transmitted information; transmission means for transmitting available vehicle information obtained by the search means to a terminal; reservation means for allowing the user to select a vehicle based on the search results and transmit reservation information to the server; route calculation means for calculating an optimal vehicle dispatch route based on the reservation information; transmission means for transmitting the calculation result and reservation confirmation information to the terminal; emotion recognition means for analyzing the user's emotional state; adjustment means for adjusting the search results and notification content based on the analysis result of the emotion recognition means; and route suggestion means for suggesting an optimal vehicle dispatch route in accordance with the user's emotional state. This enables efficient vehicle search and optimal vehicle dispatch route suggestion based on the cargo amount, delivery destination, and schedule while taking the user's emotional state into consideration in real time.

[0316] "Input means" refers to a device or system that provides an interface for inputting the cargo amount, delivery destination, and schedule.

[0317] The "transmission means" is a device or program for transmitting the input information to the server.

[0318] The "search means" is a device or program for searching for available vehicles from a database based on the transmitted information.

[0319] The "reservation means" is a device or program that allows the user to select a vehicle based on the search results and transmit reservation information to the server.

[0320] The "route calculation means" is a device or program for calculating the optimum vehicle dispatch route based on reservation information.

[0321] "Emotion recognition means" is a device or program for analyzing the user's emotional state.

[0322] The "adjustment means" is a device or program for adjusting search results and notification content based on the analysis results of the emotion recognition means.

[0323] The "route suggestion means" is a device or program for suggesting an optimal vehicle dispatch route according to the emotional state of the user.

[0324] This invention integrates an emotion engine that recognizes user emotions into a system that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and proposes optimal vehicle dispatch routes. This system can improve the efficiency of logistics operations and the user experience.

[0325] The main components of the system are:

[0326] 1. Input method: Smart glasses, smartphones, and other mobile devices are used as interfaces for users to input cargo quantities, delivery destinations, and delivery dates. For example, they support voice input and touch operation.

[0327] 2. Transmission means: Equipped with a communication function for transmitting input information to a server. This includes the communication module inside the smart glasses and the network function of the smartphone.

[0328] 3. Searching method: A search algorithm implemented on the server searches the database for available vehicles based on the received information, using a Python program and a database management system (e.g., MySQL).

[0329] 4. Reservation method: This includes a function to send reservation information for the vehicle selected by the user to the server. After the selection, the reservation process is performed on the server side.

[0330] 5. Route calculation method: The server runs an algorithm to calculate the optimal route based on the reservation information. In this case, a geographic information system (GIS) may be used.

[0331] 6. Emotion Recognition: This includes an emotion engine to analyze the user's emotional state. For example, it evaluates the user's emotional state in real time based on the user's input speed and touch strength. This is achieved by software called EmotionEngine.

[0332] 7. Adjustment: This includes programs to adjust search results and notification content based on the results of emotion recognition. For example, it may provide a simpler display to a stressed user and more detailed information to a calm user.

[0333] 8. Route suggestion: This includes an algorithm to suggest the optimal route based on the user's emotional state. For a relaxed user, it suggests a scenic route, while for a user in a hurry, it suggests the shortest route.

[0334] Examples:

[0335] The user uses the smart glasses to input "Load: 1000kg," "Delivery destination: Tokyo," and "Date: 2023-12-01." The input information is sent to the server via the smart glasses' communication function, and the server searches its database for available vehicles that match the criteria. The search results are then displayed on the smart glasses, and the reservation information for the vehicle selected by the user is sent to the server. The server uses an emotion engine to analyze the user's emotional state and suggests the optimal vehicle dispatch route based on the analysis results. The prompt is set as follows:

[0336] "Please create a program that uses smart glasses to acquire the cargo volume, delivery destination, and schedule information entered by the user, and displays the optimal vehicle search results according to the user's emotional state. A virtual emotion engine will be used for emotion recognition, and operation will be assumed to be via smart glasses."

[0337] In this way, the system is not only able to efficiently search for and reserve available vehicles based on the cargo volume, delivery destination, and schedule information entered by the user, but is also able to grasp the user's emotional state and respond flexibly accordingly.

[0338] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0339] Step 1:

[0340] The user uses smart glasses to input the cargo amount, delivery destination, and delivery date.

[0341] Input: cargo quantity, delivery destination, and schedule information.

[0342] Output: The input information displayed on the UI within the smart glasses.

[0343] Specific operation: The user uses the smart glasses' voice input function or touch operation to input the cargo quantity, delivery destination, and delivery date, and the input information is displayed on the smart glasses' display in real time.

[0344] Step 2:

[0345] The terminal transmits the input information to the server.

[0346] Input: User input information (JSON format).

[0347] Output: The data sent to the server.

[0348] Specific operation: The transmission means in the smart glasses converts the input information into JSON format and sends it to the server via the Internet.

[0349] Step 3:

[0350] The server searches the database based on the received information.

[0351] Input: User input information.

[0352] Output: A list of available vehicles.

[0353] Specific operation: The server analyzes the received information and searches the database for available vehicles that match the criteria, for example, by executing an SQL query using a Python program.

[0354] Step 4:

[0355] The server transmits available vehicle information to the terminal.

[0356] Input: A list of available vehicles.

[0357] Output: Data on which available vehicle information is sent.

[0358] Specific operation: The server sends the search result of the available vehicle list to the smart glasses, which then displays the information on their display.

[0359] Step 5:

[0360] The user selects the desired available vehicle and transmits the reservation information to the server.

[0361] Input: Available vehicle selection information.

[0362] Output: The reservation information sent to the server.

[0363] Specific operation: The user selects the desired vehicle using the interface of the smart glasses, and this selection information is sent to the server as reservation information.

[0364] Step 6:

[0365] The server calculates the optimal vehicle route based on the reservation information.

[0366] Input: Reservation information.

[0367] Output: Optimal vehicle routing.

[0368] How it works: The server uses the reservation information to calculate the optimal route using a geographic information system (GIS) and other algorithms.

[0369] Step 7:

[0370] The server sends the calculation results and reservation confirmation information to the terminal.

[0371] Input: Optimal route and reservation confirmation information.

[0372] Output: Data sent to the terminal.

[0373] Specific operation: The server sends the calculated route and reservation confirmation information to the smart glasses, allowing the user to view detailed information on the smart glasses display.

[0374] Step 8:

[0375] The server analyzes the user's emotional state.

[0376] Input: User operation logs (such as input speed and touch strength).

[0377] Output: The user's emotional state.

[0378] Specific operation: The emotion recognition means analyzes the user's operation log and evaluates the user's emotional state (such as changes in stress and attention) in real time.

[0379] Step 9:

[0380] The server adjusts search results and notification content based on the emotional state.

[0381] Input: User's emotional state, available vehicle information.

[0382] Output: Tailored search results and notifications.

[0383] Specific behavior: Search results and notification content are adjusted based on the analysis results of the emotion recognition method. For example, for users who are feeling stressed, search results are simplified and important information is highlighted.

[0384] Step 10:

[0385] The server proposes the optimal vehicle dispatch route according to the user's emotional state.

[0386] Input: User's emotional state, optimal vehicle routing.

[0387] Output: Vehicle routing suggestions based on emotional state.

[0388] Specific operation: The route suggestion means suggests the optimal vehicle dispatch route, such as the shortest distance or the most scenic route, based on the user's emotional state.

[0389] 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.

[0390] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0391] 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.

[0392] [Second embodiment]

[0393] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0394] 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.

[0395] 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).

[0396] 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.

[0397] 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.

[0398] 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).

[0399] 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.

[0400] 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.

[0401] 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.

[0402] 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.

[0403] 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.

[0404] 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."

[0405] The present invention is a system for searching for and reserving available vehicles based on cargo volume, delivery destination, and schedule, and also creates optimal vehicle dispatch routes. This makes it possible to improve the efficiency of logistics operations. Specific embodiments of the system of the present invention are described below.

[0406] A dedicated web form or mobile application is provided on the terminal to allow users to input the cargo amount, delivery destination, and schedule. This form has fields for inputting the cargo amount, delivery destination, and the user's schedule, making it easy to enter the required data. After that, when the user presses the "Search" button, the terminal sends this information to the server.

[0407] The server analyzes the received information, accesses the database, and searches for available vehicles. Specifically, it extracts vehicles that can transport the input load on the specified date. If a suitable vehicle is found, it returns the vehicle information to the terminal.

[0408] The terminal receives the reply from the server and displays a list of available vehicles to the user. The user selects the desired vehicle from the displayed list and presses the "Reserve" button, which sends the reservation information for that vehicle to the server.

[0409] Once the server receives the reservation information, it processes the reservation, which includes updating the vehicle's status to "reserved." At the same time, the server calculates the optimal route from the departure point to the delivery destination. This calculation is performed using a map service, such as Google Maps API. The calculation results include distance, travel time, and a recommended route.

[0410] Finally, the server sends the confirmed reservation information and details of the vehicle dispatch route to the terminal. The terminal displays this information to the user, who can confirm that the reservation has been confirmed and the optimal vehicle dispatch route. As a specific example, if the user enters "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01," the system will search for available vehicles that match these conditions and present them to the user. When the user selects one of the suggested vehicles and makes a reservation, the server calculates the optimal route and notifies the user of the results.

[0411] In this way, a system is realized that can efficiently search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and also create optimal vehicle dispatch routes. This system improves the efficiency of the entire logistics operation and reduces resource waste.

[0412] The processing flow will be explained below.

[0413] Step 1:

[0414] The user accesses the web form or mobile application on their device and enters the cargo amount, delivery destination, and delivery date. The user enters the necessary information, such as "Cargo amount: 1000 kg," "Delivery destination: Tokyo," and "Date: 2023-12-01."

[0415] Step 2:

[0416] The terminal acquires the information entered in the input form, converts it to JSON format, and sends an HTTP POST request to the server. The request payload contains the information entered by the user: cargo quantity, delivery destination, and delivery date.

[0417] Step 3:

[0418] The server receives the request from the terminal. The server analyzes the received information and creates a database query based on the load, destination, and delivery date. The query contains criteria for finding available vehicles that can transport the specified load on a specific date.

[0419] Step 4:

[0420] The server queries the database to retrieve information about available vehicles that match the criteria, including the vehicle's ID, maximum load capacity, and status (e.g., "available").

[0421] Step 5:

[0422] The server generates search results in JSON format and returns this information to the device, including a list of all available vehicles that match the search criteria.

[0423] Step 6:

[0424] The terminal receives the reply from the server and displays the results in a user interface that displays a list of all the vehicles provided as search results, each with a "Book Now" button.

[0425] Step 7:

[0426] The user selects the appropriate vehicle from the displayed list of vehicles and presses the "Reserve" button. The selected vehicle's ID and the necessary reservation information are sent back to the server from the terminal.

[0427] Step 8:

[0428] The server receives the reservation information and updates the status of the corresponding vehicle to "reserved." The server also calculates the optimal route from the departure point to the delivery destination, using a map API (e.g., Google Maps API) to determine the distance, travel time, and recommended route.

[0429] Step 9:

[0430] The server generates the reservation confirmation information and the calculated vehicle route in JSON format and sends it to the terminal.

[0431] Step 10:

[0432] The terminal receives the reply from the server and displays the reservation confirmation information and the optimal route information to the user, allowing the user to confirm that the reservation has been confirmed and the delivery route.

[0433] Through these specific processing steps, a system is realized that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and provides the optimal vehicle dispatch route.

[0434] Example 1

[0435] 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."

[0436] In the past, it was difficult to search for and reserve an appropriate available vehicle based on cargo volume, delivery destination, and schedule, and then create an optimal vehicle dispatch route in logistics operations. Furthermore, manual information management and vehicle dispatch plan creation required time and cost, resulting in a decrease in the efficiency of the entire logistics operation. Furthermore, if an appropriate available vehicle cannot be found or an optimal vehicle dispatch route cannot be calculated, resources are wasted. Thus, a system that can improve the efficiency of logistics operations and optimize the use of resources is needed.

[0437] 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.

[0438] In this invention, the server includes input means for inputting the cargo amount, delivery destination, and schedule, transmission means for transmitting the information input via the input means to the server, search means for searching for available vehicles from the information management device based on the transmitted information, transmission means for transmitting available vehicle information obtained by the search means to the terminal, reservation means for the user to select a vehicle based on the search result and transmit reservation information to the server, route calculation means for calculating the optimal vehicle dispatch route based on the reservation information, and transmission means for transmitting the calculation result and reservation confirmation information to the terminal. This makes it possible to improve the efficiency of the entire logistics operation and reduce waste of resources.

[0439] "Input means" refers to a device or software that allows a user to input the cargo amount, delivery destination, and schedule.

[0440] The "transmission means" refers to a device or mechanism that transmits information input via the input means to the server.

[0441] The "information management device" refers to a database that holds information about available vehicles and the management system for that database.

[0442] The "search means" refers to a device or software for searching for available vehicles from the information management device based on the transmitted information.

[0443] The "reservation means" refers to a device or software that allows the user to select a vehicle based on the search results and transmit the reservation information to the server.

[0444] The "route calculation means" refers to a device or software for calculating the optimal vehicle dispatch route based on reservation information.

[0445] A "terminal" is an electronic device or computer through which a user enters information and receives results.

[0446] The present invention is a system for searching for and reserving available vehicles based on cargo volume, delivery destination, and schedule, and also creates optimal vehicle dispatch routes. This system can improve the efficiency of logistics operations. Specific embodiments of the present invention are described below.

[0447] A dedicated web form or mobile application is provided on the terminal so that the user can enter the load amount, delivery destination, and delivery date. This form has fields for entering the load amount, delivery destination, and delivery date, allowing the user to easily enter the required data. For example, the user enters "Load amount: 1000 kg," "Delivery destination: Tokyo," and "Date: 2023-12-01."

[0448] After that, when the user presses the "Search" button, the terminal sends this information to the server as an HTTP request. The server receives the request and extracts information such as the cargo amount, delivery destination, and delivery date by parsing the JSON data. Based on the parsed information, the server executes an SQL query against a database (for example, a general SQL database) to search for available vehicles that can transport the entered cargo amount on the specified date. As a result, a list of available vehicles is obtained.

[0449] If a matching vehicle is found, the server generates information about that vehicle in JSON format and returns it to the terminal. The terminal receives the response, parses the JSON data, and displays it to the user. For example, a list containing information such as "Vehicle 1: Truck A, Load Capacity: 1500 kg, Current Location: Osaka" is displayed. The user selects the desired vehicle from the displayed list and presses the "Reserve" button. The terminal then sends the reservation information selected by the user to the server.

[0450] Based on the received reservation information, the server updates the status of the corresponding vehicle in its database to "reserved." The server then uses a map service such as Google Maps API to calculate the optimal route from the departure point to the delivery destination. The calculation results include the distance, required time, and recommended route. The server generates the calculation results in JSON format and returns them to the terminal. The terminal parses the information and displays it to the user, allowing them to confirm that the reservation has been confirmed and the details of the vehicle dispatch route. For example, the terminal may display information such as "Reservation confirmed. Recommended route: total distance 500 km, required time 6 hours, route A, route B."

[0451] This allows you to efficiently search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and also create optimal vehicle dispatch routes, improving the efficiency of overall logistics operations and reducing resource waste.

[0452] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0453] Step 1:

[0454] The user inputs the cargo amount, delivery destination, and delivery date.

[0455] The user uses a terminal to access a dedicated web form or mobile application and enters the load amount (e.g., 1,000 kg), delivery destination (e.g., Tokyo), and delivery date (e.g., 2023-12-01). This data is captured as text entered into the form.

[0456] Input: cargo amount, delivery destination, date (e.g. 1000kg, Tokyo, 2023-12-01)

[0457] Output: Data entered into the form

[0458] Step 2:

[0459] The terminal transmits the input information to the server.

[0460] When the user presses the "Search" button, the device converts the entered information into JSON format data and sends it to the server as an HTTP request.

[0461] Input: Data entered into a form

[0462] Output: JSON format data (e.g., { "Load": "1000kg", "Delivery destination": "Tokyo", "Date": "2023-12-01"})

[0463] Step 3:

[0464] The server receives and analyzes the data.

[0465] The server analyzes the HTTP request received from the terminal, parses the JSON data, and extracts the fields for cargo quantity, delivery destination, and schedule.

[0466] Input: JSON format data

[0467] Output: Extracted cargo volume, delivery destination, and schedule

[0468] Step 4:

[0469] The server searches for available vehicles from the information management device.

[0470] Based on the analyzed information, the server executes an SQL query against the database to search for available vehicles that can transport the input load on the specified date. For example, it executes a query such as "SELECT FROM vehicle WHERE date = '2023-12-01' AND maximum load capacity >= 1000kg".

[0471] Input: Extracted cargo volume, delivery destination, schedule

[0472] Output: A list of available vehicles as a result of the search.

[0473] Step 5:

[0474] The server returns the search results to the device.

[0475] If a matching vehicle is found, the server generates the vehicle information in JSON format and returns it to the terminal. For example, it generates data like "{ Vehicle ID: 1, Vehicle name: 'Truck A', Maximum load capacity: '1500kg', Current location: 'Osaka'}".

[0476] Input: A list of available vehicles as search results

[0477] Output: Vehicle information in JSON format

[0478] Step 6:

[0479] Your device will display the search results.

[0480] The terminal parses the JSON data received from the server and displays a list of available vehicles suggested to the user. For example, it displays information such as "Truck A, Load Capacity: 1500 kg, Current Location: Osaka."

[0481] Input: Vehicle information in JSON format

[0482] Output: A list of vehicles displayed to the user

[0483] Step 7:

[0484] The user selects and reserves a vehicle.

[0485] The user selects the desired vehicle from the displayed list and presses the "Reserve" button. The user's selection data is acquired by the terminal as reservation information.

[0486] Input: User selected vehicle information

[0487] Output: Reservation information

[0488] Step 8:

[0489] The terminal transmits the reservation information to the server.

[0490] The terminal converts the reservation information selected by the user into JSON format data and sends it to the server as an HTTP request.

[0491] Input: Reservation information

[0492] Output: Reservation information in JSON format

[0493] Step 9:

[0494] The server confirms the reservation based on the reservation information.

[0495] Based on the received reservation information, the server updates the status of the corresponding vehicle in the database to "reserved." For example, it executes an SQL query such as "UPDATE VEHICLE SET STATUS = 'RESERVED' WHERE VEHICLE ID = 1."

[0496] Input: Reservation information in JSON format

[0497] Output: Database update results

[0498] Step 10:

[0499] The server calculates the route.

[0500] The server uses a map service such as Google Maps API to calculate the optimal route from the starting point to the delivery destination, including distance, time required, and a recommended route.

[0501] Input: Departure point, delivery destination

[0502] Output: Calculated vehicle routing (e.g., distance 500 km, travel time 6 hours, route A)

[0503] Step 11:

[0504] The server returns the details of the vehicle route to the terminal.

[0505] The server generates the calculation results in JSON format and sends them to the terminal. For example, it generates data like "{ distance: '500km', required time: '6 hours', recommended route: 'Route A'}".

[0506] Input: Calculated vehicle routing route

[0507] Output: JSON formatted route information

[0508] Step 12:

[0509] The terminal displays the final information.

[0510] The device parses the JSON data received from the server and displays to the user that the reservation has been confirmed and details of the optimal route. For example, it displays "Reservation confirmed. Recommended route: total distance 500 km, required time 6 hours, route A."

[0511] Input: JSON formatted route information

[0512] Output: Confirmed booking information and route details displayed to the user

[0513] (Application example 1)

[0514] 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."

[0515] In the modern logistics industry, optimal vehicle allocation and route planning is required based on cargo volume, delivery destination, and schedule. However, doing this manually is extremely inefficient and wastes time and resources. Furthermore, it is difficult to check available vehicles in real time or propose optimal routes, making efficient vehicle allocation difficult. Therefore, a system is needed to improve the efficiency of logistics operations overall.

[0516] 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.

[0517] In this invention, the server includes an input means for inputting the cargo amount, delivery destination, and schedule, a transmission means for transmitting the information input via the input means to the server, a search means for searching a database for available vehicles based on the transmitted information, a transmission means for transmitting available vehicle information obtained by the search means to a terminal, a reservation means for a user to select a vehicle based on the search result and transmit reservation information to the server, a route calculation means for calculating an optimal vehicle dispatch route based on the reservation information, a transmission means for transmitting the calculation result and reservation confirmation information to the terminal, a means operated via a smartphone application used in the logistics center, a means for providing a web form for a user to easily input the cargo amount, delivery destination, and schedule, a means for calculating the route using a Google Maps API, and a means for analyzing prompts input by a user using a generative AI model and making optimal suggestions, thereby enabling efficient and real-time vehicle dispatch and route suggestions for logistics operations.

[0518] "Load volume" refers to the weight and volume of cargo or luggage, and is information that serves as the basis for determining the capacity of the vehicle required for transportation.

[0519] "Delivery destination" refers to the location or address where the package or product is to be delivered, and is important destination information in the logistic procedure.

[0520] "Schedule" refers to the schedule for shipping and arrival of packages, and is information for time management in the logistics process.

[0521] "Input means" refers to a device or interface (e.g., a web form or application) that allows a user to enter required information into a system.

[0522] "Transmission means" refers to a system or device that has the function of transmitting input information to a server.

[0523] A "search means" is a system or device that has the function of searching for relevant information (e.g., available vehicle information) from a database based on received information.

[0524] A "reservation vehicle" is a system or device that has the functionality to reserve a product or service (in this case, a vehicle) selected by a user.

[0525] "Route calculation means" refers to a system or device that has the function of calculating the optimal vehicle dispatch route from the departure point to the arrival point.

[0526] "Smartphone applications used within logistics centers" refers to mobile applications used by logistics center staff to manage cargo and arrange vehicle dispatches.

[0527] "Web Form" refers to an online form that allows a user to enter required information in a browser.

[0528] "Google Maps API" is a program interface for the map service provided by Google, and is a tool that provides functions such as map display and route calculation.

[0529] A "generative AI model" refers to an artificial intelligence system that learns from large amounts of data and provides optimal responses and suggestions for specified tasks or questions.

[0530] A "prompt" is an instruction or question entered by a user to instruct a generative AI model on a specific task.

[0531] This invention is a system that includes a smartphone application that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule at a logistics center. It also creates optimal vehicle dispatch routes, improving the efficiency of logistics operations.

[0532] Users input the cargo amount, delivery destination, and delivery date using a smartphone application installed in the logistics center. The smartphone application used in the logistics center has an intuitive user interface and provides a web form, allowing users to easily enter the necessary information.

[0533] The entered information is sent to the server via the smartphone application's transmission means. The server analyzes the received information and accesses the database to search for available vehicles. Specifically, the search means extracts available vehicles with a load capacity equal to or greater than the transmitted load capacity. If a suitable vehicle is found, the vehicle's information is sent to the terminal, and a list of suggested available vehicles is displayed to the user.

[0534] The user selects the desired vehicle from the displayed list and presses the "Reserve" button, and the reservation information is sent to the server. The server receives the reservation information and performs the reservation confirmation process, which includes updating the status of the corresponding vehicle to "Reserved."

[0535] At the same time, the server calculates the optimal route from the starting point to the delivery destination. This calculation is performed using the Google Maps API, and the calculation results include distance, travel time, and recommended route. Furthermore, using a generative AI model, the system makes optimal suggestions when the user inputs a prompt. The generative AI model is trained based on a large amount of data and returns the most appropriate result for the user's input.

[0536] Finally, the server sends the reservation confirmation and route details to the smartphone application, which displays this information to the user, who can confirm that the reservation has been confirmed and the optimal route.

[0537] For example, if a user enters "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01," the system can search for available vehicles that match these conditions and present them to the user. When the user reserves the suggested vehicle, the server uses the Google Maps API to calculate the optimal vehicle dispatch route and notify the user of the results.

[0538] An example of a prompt is:

[0539] "Search for available vehicles to deliver a 1000kg package to Tokyo on December 1, 2023, and suggest the best route."

[0540] In this way, a system is realized that efficiently searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and also creates optimal vehicle dispatch routes, thereby improving the efficiency of the entire logistics operation and reducing resource waste.

[0541] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0542] Step 1:

[0543] The user launches the smartphone application and inputs the cargo amount, delivery destination, and delivery date. The web form has an intuitive interface, making it easy to enter information. The input data (cargo amount, delivery destination, delivery date) obtained using the input means is temporarily stored in the smartphone's memory.

[0544] Step 2:

[0545] When the user presses the "Search" button, the terminal transmits the input data to the server via the transmission means. The transmitted data is in a format that includes information on the input amount, delivery destination, and schedule.

[0546] Step 3:

[0547] The server analyzes the received data and searches the database for available vehicles. Using the search means, the server extracts available vehicles from the database that can transport the input load for the specified date and time. This search process reads the ID of the vehicle that matches the conditions, its future usage schedule, and the load capacity.

[0548] Step 4:

[0549] The available vehicle information obtained by the search means is transmitted to a smartphone application using a transmission means, and the user can check a list of suggested available vehicles on the smartphone display.

[0550] Step 5:

[0551] The user selects the desired vehicle from the displayed list and presses the "Reserve" button. The terminal then sends the reservation information for the selected vehicle to the server. This reservation information includes the vehicle ID, reservation date and time, user ID, etc.

[0552] Step 6:

[0553] The server receives the reservation information and processes the reservation. It updates the status of the corresponding vehicle to "reserved" and records this information in the database. At the same time, the server calculates the optimal vehicle route from the departure point to the delivery destination. It uses the Google Maps API to calculate the optimal route, including the shortest distance and required time.

[0554] Step 7:

[0555] The generative AI model is used to analyze prompts entered by users. For example, the generative AI model analyzes a prompt such as, "Please search for available vehicles to deliver a 1,000 kg package to Tokyo on December 1, 2023, and suggest the optimal route," and makes appropriate suggestions. Based on this analysis, the optimal route information and vehicle information are reevaluated.

[0556] Step 8:

[0557] The server sends the route calculation results and reservation confirmation information to the smartphone application via the transmission means. The terminal receives this and displays to the user that the reservation has been confirmed and the optimal vehicle dispatch route. The user can check the details of the vehicle dispatch route on the smartphone screen and efficiently proceed with the vehicle dispatch operation.

[0558] In this way, the system efficiently executes a series of processes, from inputting the cargo volume, delivery destination, and schedule to searching for available vehicles, making reservations, and calculating routes, providing the user with the information they need.

[0559] 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.

[0560] This invention combines a system that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and creates optimal vehicle dispatch routes with an emotion engine that recognizes user emotions. This system not only improves the efficiency of logistics operations, but also enhances the user experience.

[0561] The interface for users to input cargo volume, delivery destination, and schedule is provided as a web form or mobile application. Users enter the cargo volume, delivery destination, and schedule and then press the "Search" button to start the search.

[0562] The terminal converts the input information into JSON format and sends it to the server via a transmission means. The server analyzes the received information and searches the database based on the cargo amount, delivery destination, and schedule. After obtaining information on the corresponding available vehicle, the server returns this information to the terminal.

[0563] The terminal receives the response from the server and displays the results to the user. The user selects the desired vehicle from the displayed results and presses the "Reserve" button, which sends reservation information such as the selected vehicle's ID to the server.

[0564] After receiving the reservation information, the server updates the vehicle's status to "reserved." The server then calculates the optimal route from the departure point to the delivery destination and returns the results to the terminal.

[0565] The emotion engine analyzes the input information and operations performed by the user while using the system, and determines the user's emotional state in real time. For example, it recognizes emotional states such as stress or decreased attention based on the user's input speed, mouse movements, and touchscreen operation patterns.

[0566] Based on the analysis results of the emotion engine, the system provides the following functions:

[0567] 1. Adjust search results and notifications:

[0568] If the emotion engine determines that you are stressed, it will simplify search results, highlight important information, and phrase notifications in more user-friendly language.

[0569] 2. Changes in how vehicle routing is suggested:

[0570] If the emotion engine determines that the user is in a hurry, it will prioritize the shortest route, while if the user is relaxed, it can suggest a scenic route that is a comfortable drive.

[0571] As a concrete example, suppose a user inputs "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01" and executes "search." The device sends this information to the server, which searches the database for available vehicles that match the criteria. The server then sends the search results to the device, which displays them to the user. Once the user selects the desired vehicle and confirms the reservation, the server calculates a vehicle dispatch route that takes into account the user's current emotional state based on the analysis results of the emotion engine, and sends this information to the device.

[0572] In this way, a system is realized that not only efficiently searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and provides the optimal vehicle dispatch route, but also improves the user experience by taking into account the user's emotional state.

[0573] The processing flow will be explained below.

[0574] Step 1:

[0575] The user accesses the web form or mobile application on their device and enters the cargo amount, delivery destination, and delivery date. For example, they enter information such as "Cargo amount: 1000 kg," "Delivery destination: Tokyo," and "Date: 2023-12-01."

[0576] Step 2:

[0577] The terminal receives the input information, converts it to JSON format, and sends an HTTP POST request to the server, which includes the input information on the load, delivery destination, and delivery date.

[0578] Step 3:

[0579] The server receives the request from the terminal. The server analyzes the received information and creates a database query based on the load, destination, and delivery date. The query contains criteria for finding available vehicles that can transport the specified load on a specific date.

[0580] Step 4:

[0581] The server queries the database to retrieve information about available vehicles that match the criteria, including the vehicle's ID, maximum load capacity, and status (e.g., "available").

[0582] Step 5:

[0583] The server generates search results in JSON format and sends this information to the device, which returns a list of all available vehicles that match the search criteria.

[0584] Step 6:

[0585] The terminal receives the reply from the server and displays a list of available vehicles to the user. The user selects the desired vehicle from the list and presses the "Reserve" button.

[0586] Step 7:

[0587] When the user presses the "Reserve" button, the ID of the selected vehicle and the necessary reservation information are sent from the terminal to the server. The reservation information includes the ID of the selected vehicle.

[0588] Step 8:

[0589] The server receives the reservation information and updates the status of the corresponding vehicle to "reserved." The server then calculates the optimal route from the departure point to the delivery destination. This calculation uses a map API (e.g., Google Maps API) to find the distance, travel time, and recommended route.

[0590] Step 9:

[0591] The server generates the reservation confirmation information and the calculated vehicle route in JSON format and sends it to the terminal.

[0592] Step 10:

[0593] The terminal receives the reply from the server and displays the reservation confirmation information and the optimal route information to the user, allowing the user to confirm that the reservation has been confirmed and the delivery route.

[0594] Step 11:

[0595] The emotion engine analyzes the user's input speed, operation patterns, mouse movements, and touchscreen operations to determine the user's emotional state in real time.

[0596] Step 12:

[0597] Based on the analysis results of the emotion engine, the server adjusts search results taking into account the user's emotional state. Specifically, if it determines that the user is feeling stressed, it condenses search results and highlights important information.

[0598] Step 13:

[0599] The emotion engine suggests optimal routes based on the user's emotional state. For example, it suggests the shortest route for a user in a hurry, and a scenic route for a user who is relaxed.

[0600] In this way, the system can efficiently search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and provide optimal vehicle dispatch routes that take the user's emotional state into consideration, simultaneously improving the user experience and streamlining logistics operations.

[0601] Example 2

[0602] 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."

[0603] Conventional logistics systems can search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and provide optimal vehicle dispatch routes, but they lack the ability to provide services that take into account the user's emotional state. Therefore, improvements are needed to reduce user stress and provide a better user experience.

[0604] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0605] In this invention, the server includes input means for inputting the cargo amount, delivery destination, and schedule, transmission means for transmitting the information input via the input means to a central device, search means for searching a storage device for available vehicles based on the transmitted information, transmission means for transmitting available vehicle information obtained by the search means to a terminal, reservation means for a user to select a vehicle based on the search results and transmit reservation information to the central device, route calculation means for calculating an optimal vehicle dispatch route based on the reservation information, transmission means for transmitting the calculation result and reservation confirmation information to the terminal, emotion analysis means for analyzing the user's operation and input information and determining the user's emotional state, result adjustment means for adjusting the search results and notification content based on the result of the emotion analysis means, and route suggestion means for changing the method of suggesting vehicle dispatch routes based on the result of the emotion analysis means. This makes it possible to provide logistics services that take the user's emotional state into consideration, which was not possible with conventional systems.

[0606] "Cargo volume" refers to the total weight of cargo transported in logistics.

[0607] "Delivery point" means the final receiving location to which the shipment is delivered.

[0608] "Schedule" refers to the scheduled delivery date or delivery period in logistics.

[0609] "Input means" refers to a device or interface used by a user to input cargo quantity, delivery destination, and delivery date into the system.

[0610] "Transmission means" refers to a means for transmitting input information to another device or system.

[0611] "Central device" refers to the main device that controls the entire system and processes and manages various types of information.

[0612] "Storage device" refers to a hardware or software component used to store information as data.

[0613] "Search means" refers to a device or program that has the function of searching for information from a database or the like based on certain conditions.

[0614] "Terminal" refers to a device that a user accesses and uses to perform various operations such as inputting and displaying information.

[0615] "Reservation means" refers to an interface that allows a user to select a desired vehicle and transmit that information to the system.

[0616] "Route calculation means" refers to a device or program that has the function of calculating the optimal vehicle dispatch route from the departure point to the delivery destination.

[0617] "Emotion analysis means" refers to a system that analyzes the user's input speed, operation patterns, etc., and determines the user's emotional state.

[0618] "Result adjustment means" refers to a device or program that has the function of adjusting search results or notification content based on the results of the emotion analysis means.

[0619] The "route suggestion means" refers to a device or program that has the function of changing the method of suggesting the optimal vehicle dispatch route based on the results of the emotion analysis means.

[0620] The present invention is directed to a system that aims to improve the efficiency of a logistics system and the user experience. Hereinafter, an embodiment of the present invention will be described in detail.

[0621] The interface for users to input cargo volume, delivery destination, and schedule is provided as a web form or mobile application. Users enter the necessary information through these interfaces and start the operation by pressing the "Search" button. This input method works on platforms such as web browsers and mobile apps.

[0622] The terminal converts the input information into JSON format and sends it to the central server using an HTTP request. The HTTPS protocol is used for transmission. The server parses the received JSON data and analyzes the information on the load, delivery destination, and schedule.

[0623] The server uses a relational database management system (RDBMS) such as MySQL to search the database stored in the storage device, using, for example, the following SQL query:

[0624] SELECT FROM Vehicle WHERE Load >= '1000kg' AND Delivery Destination = 'Tokyo' AND Available Date >= '2023-12-01'

[0625] This allows you to obtain available vehicles that meet the conditions.

[0626] The search results are converted to JSON format and sent from the server to the terminal. The transmission method is again HTTPS protocol. The terminal analyzes the results and displays them visually to the user. The user selects the desired vehicle from the displayed search results and clicks the "Reserve" button.

[0627] The device converts the reservation information, including the ID of the selected vehicle, into JSON format and sends it to the server using an HTTP request. The server parses the received reservation information and executes an SQL query to update the vehicle's status to "reserved":

[0628] UPDATE VEHICLE SET STATE = 'RESERVED' WHERE ID = '123'

[0629] After the reservation is completed, the server uses the Google Maps API to calculate the optimal route from the departure point to the delivery destination. The calculation result is converted into JSON format and sent from the server to the terminal. The terminal receives it and displays it visually to the user.

[0630] Additionally, the app is equipped with an emotion engine that analyzes the user's typing speed, mouse movements, touch patterns, etc. to determine the user's emotional state. The emotion engine uses machine learning models to assess stress levels, attention deficits, etc. in real time. Depending on the emotional state, the app offers the following features:

[0631] 1. Adjust search results and notifications:

[0632] If the system detects that a user is stressed, it will simplify search results, highlight important information, and present notifications in user-friendly language.

[0633] 2. Changes in how vehicle routing is suggested:

[0634] If the system determines that the user is in a hurry, it will prioritize showing the shortest route, while if the user is relaxed, it will suggest a scenic route that will provide a comfortable drive.

[0635] As a concrete example, consider the case where a user inputs "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01" and executes "search." The terminal sends this information to the server, which searches the database for available vehicles that match the criteria. The server then sends the search results to the terminal, which displays them to the user. Once the user selects the desired vehicle and confirms the reservation, the server calculates the optimal vehicle dispatch route based on the analysis results of the emotion engine, taking into account the user's current emotional state, and sends this information to the terminal.

[0636] Examples of prompts for generative AI models include:

[0637] "We want to build a system that allows users to input their cargo volume, delivery destination, and delivery date, search for available vehicles, and reserve them. We also want to be able to analyze the user's emotional state and adjust the display content and route suggestions accordingly."

[0638] In this way, the system can search for the most suitable available vehicle based on the cargo volume, delivery destination, and schedule, and provide an efficient logistics service that takes into account the user's emotional state.

[0639] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0640] Step 1:

[0641] The user uses a web form or mobile app to input the load, delivery destination, and delivery date. The user enters the load (e.g., 1000 kg), delivery destination (e.g., Tokyo), and delivery date (e.g., 2023-12-01) into each field in the form and clicks the "Search" button. This input is received by the terminal.

[0642] Step 2:

[0643] The terminal converts the information entered by the user, such as the amount of cargo, delivery destination, and delivery date, into JSON format. For example, the following JSON data is generated:

[0644] {"Load": "1000kg", "Delivery destination": "Tokyo", "Date": "2023-12-01"}

[0645] The converted JSON data is sent to the server via an HTTP request, which is part of the transmission method.

[0646] Step 3:

[0647] The server parses the received JSON data and extracts the necessary information (cargo volume, delivery destination, schedule). Specifically, it uses a JSON parser to extract the following data:

[0648] Load: 1000kg, Delivery location: Tokyo, Date: 2023-12-01

[0649] Based on this data, the server searches for available vehicles using a relational database such as MySQL.

[0650] Step 4:

[0651] The server generates and executes the SQL query to search the database:

[0652] SELECT FROM Vehicle WHERE Load >= '1000kg' AND Delivery Destination = 'Tokyo' AND Available Date >= '2023-12-01'

[0653] The information about available vehicles obtained through this search is converted into JSON format and returned to the terminal via an HTTP response.

[0654] Step 5:

[0655] The device receives the search results in JSON format from the server and parses them. For example, it parses the following results:

[0656] {"Vehicle": [{"ID": "123", "Vehicle Type": "Large Truck", "Status": "Available"}]}

[0657] The terminal visually displays the analyzed data to the user, specifically, the search results in a table format.

[0658] Step 6:

[0659] The user selects the desired vehicle from the displayed search results and clicks the "Reserve" button. This operation records the ID of the selected vehicle in the terminal. For example, the user selects a large truck with ID 123.

[0660] Step 7:

[0661] The device converts the reservation information, such as the vehicle ID selected by the user and the user ID, into JSON format. Specifically, the following data is generated:

[0662] {"Vehicle ID": "123", "User ID": "456"}

[0663] The converted JSON data is again sent to the server via an HTTP request.

[0664] Step 8:

[0665] The server parses the received reservation information and executes a SQL query to update the vehicle status to "reserved":

[0666] UPDATE VEHICLE SET STATE = 'RESERVED' WHERE ID = '123'

[0667] After the update is complete, the server uses the Google Maps API or similar to calculate the optimal route from the starting point to the delivery destination.

[0668] Step 9:

[0669] The server converts the calculated route into JSON format and sends it to the device via an HTTP response. For example, the following data is generated:

[0670] {"Route": "Detailed directions from the starting point to the delivery destination"}

[0671] The terminal receives this and displays it visually to the user.

[0672] Step 10:

[0673] The terminal collects data such as the user's input speed and operation patterns and sends it to the emotion analysis means, which analyzes this data and determines the user's emotional state, for example, whether the user is in a hurry or relaxed.

[0674] Step 11:

[0675] Based on the results of the emotion analysis, the server adjusts search results and notification content. For example, if it determines that the user is feeling stressed, it simplifies search results, highlights important information, and phrases notifications in more user-friendly language.

[0676] Step 12:

[0677] Based on the results of the emotion analysis, the server changes the way it suggests routes. For example, if it determines that the user is in a hurry, it will prioritize the shortest route. On the other hand, if the user is relaxed, it will suggest a route with a nice view.

[0678] This allows the system to not only search for and reserve the most suitable available vehicle based on cargo volume, delivery destination, and schedule, but also to provide logistics services that take into account the user's emotional state.

[0679] (Application example 2)

[0680] 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."

[0681] In conventional logistics systems, it is common to search for available vehicles based on conditions such as cargo volume, delivery destination, and schedule, and then provide the optimal vehicle dispatch route, but this alone has problems such as reducing user stress and not being able to support efficient input. In particular, there is a problem that information provided without considering the user's emotional state is insufficient to improve the user experience and is likely to reduce the user's work efficiency.

[0682] 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: input means for inputting the cargo amount, delivery destination, and schedule; transmission means for transmitting the information input via the input means to the server; search means for searching a database for available vehicles based on the transmitted information; transmission means for transmitting available vehicle information obtained by the search means to a terminal; reservation means for allowing the user to select a vehicle based on the search results and transmit reservation information to the server; route calculation means for calculating an optimal vehicle dispatch route based on the reservation information; transmission means for transmitting the calculation result and reservation confirmation information to the terminal; emotion recognition means for analyzing the user's emotional state; adjustment means for adjusting the search results and notification content based on the analysis result of the emotion recognition means; and route suggestion means for suggesting an optimal vehicle dispatch route in accordance with the user's emotional state. This enables efficient vehicle search and optimal vehicle dispatch route suggestion based on the cargo amount, delivery destination, and schedule while taking the user's emotional state into consideration in real time.

[0683] "Input means" refers to a device or system that provides an interface for inputting the cargo amount, delivery destination, and schedule.

[0684] The "transmission means" is a device or program for transmitting the input information to the server.

[0685] The "search means" is a device or program for searching for available vehicles from a database based on the transmitted information.

[0686] The "reservation means" is a device or program that allows the user to select a vehicle based on the search results and transmit reservation information to the server.

[0687] The "route calculation means" is a device or program for calculating the optimum vehicle dispatch route based on reservation information.

[0688] "Emotion recognition means" is a device or program for analyzing the user's emotional state.

[0689] The "adjustment means" is a device or program for adjusting search results and notification content based on the analysis results of the emotion recognition means.

[0690] The "route suggestion means" is a device or program for suggesting an optimal vehicle dispatch route according to the emotional state of the user.

[0691] This invention integrates an emotion engine that recognizes user emotions into a system that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and proposes optimal vehicle dispatch routes. This system can improve the efficiency of logistics operations and the user experience.

[0692] The main components of the system are:

[0693] 1. Input method: Smart glasses, smartphones, and other mobile devices are used as interfaces for users to input cargo quantities, delivery destinations, and delivery dates. For example, they support voice input and touch operation.

[0694] 2. Transmission means: Equipped with a communication function for transmitting input information to a server. This includes the communication module inside the smart glasses and the network function of the smartphone.

[0695] 3. Searching method: A search algorithm implemented on the server searches the database for available vehicles based on the received information, using a Python program and a database management system (e.g., MySQL).

[0696] 4. Reservation method: This includes a function to send reservation information for the vehicle selected by the user to the server. After the selection, the reservation process is performed on the server side.

[0697] 5. Route calculation method: The server runs an algorithm to calculate the optimal route based on the reservation information. In this case, a geographic information system (GIS) may be used.

[0698] 6. Emotion Recognition: This includes an emotion engine to analyze the user's emotional state. For example, it evaluates the user's emotional state in real time based on the user's input speed and touch strength. This is achieved by software called EmotionEngine.

[0699] 7. Adjustment: This includes programs to adjust search results and notification content based on the results of emotion recognition. For example, it may provide a simpler display to a stressed user and more detailed information to a calm user.

[0700] 8. Route suggestion: This includes an algorithm to suggest the optimal route based on the user's emotional state. For a relaxed user, it suggests a scenic route, while for a user in a hurry, it suggests the shortest route.

[0701] Examples:

[0702] The user uses the smart glasses to input "Load: 1000kg," "Delivery destination: Tokyo," and "Date: 2023-12-01." The input information is sent to the server via the smart glasses' communication function, and the server searches its database for available vehicles that match the criteria. The search results are then displayed on the smart glasses, and the reservation information for the vehicle selected by the user is sent to the server. The server uses an emotion engine to analyze the user's emotional state and suggests the optimal vehicle dispatch route based on the analysis results. The prompt is set as follows:

[0703] "Please create a program that uses smart glasses to acquire the cargo volume, delivery destination, and schedule information entered by the user, and displays the optimal vehicle search results according to the user's emotional state. A virtual emotion engine will be used for emotion recognition, and operation will be assumed to be via smart glasses."

[0704] In this way, the system is not only able to efficiently search for and reserve available vehicles based on the cargo volume, delivery destination, and schedule information entered by the user, but is also able to grasp the user's emotional state and respond flexibly accordingly.

[0705] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0706] Step 1:

[0707] The user uses smart glasses to input the cargo amount, delivery destination, and delivery date.

[0708] Input: cargo quantity, delivery destination, and schedule information.

[0709] Output: The input information displayed on the UI within the smart glasses.

[0710] Specific operation: The user uses the smart glasses' voice input function or touch operation to input the cargo quantity, delivery destination, and delivery date, and the input information is displayed on the smart glasses' display in real time.

[0711] Step 2:

[0712] The terminal transmits the input information to the server.

[0713] Input: User input information (JSON format).

[0714] Output: The data sent to the server.

[0715] Specific operation: The transmission means in the smart glasses converts the input information into JSON format and sends it to the server via the Internet.

[0716] Step 3:

[0717] The server searches the database based on the received information.

[0718] Input: User input information.

[0719] Output: A list of available vehicles.

[0720] Specific operation: The server analyzes the received information and searches the database for available vehicles that match the criteria, for example, by executing an SQL query using a Python program.

[0721] Step 4:

[0722] The server transmits available vehicle information to the terminal.

[0723] Input: A list of available vehicles.

[0724] Output: Data on which available vehicle information is sent.

[0725] Specific operation: The server sends the search result of the available vehicle list to the smart glasses, which then displays the information on their display.

[0726] Step 5:

[0727] The user selects the desired available vehicle and transmits the reservation information to the server.

[0728] Input: Available vehicle selection information.

[0729] Output: The reservation information sent to the server.

[0730] Specific operation: The user selects the desired vehicle using the interface of the smart glasses, and this selection information is sent to the server as reservation information.

[0731] Step 6:

[0732] The server calculates the optimal vehicle route based on the reservation information.

[0733] Input: Reservation information.

[0734] Output: Optimal vehicle routing.

[0735] How it works: The server uses the reservation information to calculate the optimal route using a geographic information system (GIS) and other algorithms.

[0736] Step 7:

[0737] The server sends the calculation results and reservation confirmation information to the terminal.

[0738] Input: Optimal route and reservation confirmation information.

[0739] Output: Data sent to the terminal.

[0740] Specific operation: The server sends the calculated route and reservation confirmation information to the smart glasses, allowing the user to view detailed information on the smart glasses display.

[0741] Step 8:

[0742] The server analyzes the user's emotional state.

[0743] Input: User operation logs (such as input speed and touch strength).

[0744] Output: The user's emotional state.

[0745] Specific operation: The emotion recognition means analyzes the user's operation log and evaluates the user's emotional state (such as changes in stress and attention) in real time.

[0746] Step 9:

[0747] The server adjusts search results and notification content based on the emotional state.

[0748] Input: User's emotional state, available vehicle information.

[0749] Output: Tailored search results and notifications.

[0750] Specific behavior: Search results and notification content are adjusted based on the analysis results of the emotion recognition method. For example, for users who are feeling stressed, search results are simplified and important information is highlighted.

[0751] Step 10:

[0752] The server proposes the optimal vehicle dispatch route according to the user's emotional state.

[0753] Input: User's emotional state, optimal vehicle routing.

[0754] Output: Vehicle routing suggestions based on emotional state.

[0755] Specific operation: The route suggestion means suggests the optimal vehicle dispatch route, such as the shortest distance or the most scenic route, based on the user's emotional state.

[0756] 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.

[0757] 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.

[0758] 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.

[0759] [Third embodiment]

[0760] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0761] 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.

[0762] 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).

[0763] 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.

[0764] 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.

[0765] 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).

[0766] 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.

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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.

[0771] 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."

[0772] The present invention is a system for searching for and reserving available vehicles based on cargo volume, delivery destination, and schedule, and also creates optimal vehicle dispatch routes. This makes it possible to improve the efficiency of logistics operations. Specific embodiments of the system of the present invention are described below.

[0773] A dedicated web form or mobile application is provided on the terminal to allow users to input the cargo amount, delivery destination, and schedule. This form has fields for inputting the cargo amount, delivery destination, and the user's schedule, making it easy to enter the required data. After that, when the user presses the "Search" button, the terminal sends this information to the server.

[0774] The server analyzes the received information, accesses the database, and searches for available vehicles. Specifically, it extracts vehicles that can transport the input load on the specified date. If a suitable vehicle is found, it returns the vehicle information to the terminal.

[0775] The terminal receives the reply from the server and displays a list of available vehicles to the user. The user selects the desired vehicle from the displayed list and presses the "Reserve" button, which sends the reservation information for that vehicle to the server.

[0776] Once the server receives the reservation information, it processes the reservation, which includes updating the vehicle's status to "reserved." At the same time, the server calculates the optimal route from the departure point to the delivery destination. This calculation is performed using a map service, such as Google Maps API. The calculation results include distance, travel time, and a recommended route.

[0777] Finally, the server sends the confirmed reservation information and details of the vehicle dispatch route to the terminal. The terminal displays this information to the user, who can confirm that the reservation has been confirmed and the optimal vehicle dispatch route. As a specific example, if the user enters "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01," the system will search for available vehicles that match these conditions and present them to the user. When the user selects one of the suggested vehicles and makes a reservation, the server calculates the optimal route and notifies the user of the results.

[0778] In this way, a system is realized that can efficiently search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and also create optimal vehicle dispatch routes. This system improves the efficiency of the entire logistics operation and reduces resource waste.

[0779] The processing flow will be explained below.

[0780] Step 1:

[0781] The user accesses the web form or mobile application on their device and enters the cargo amount, delivery destination, and delivery date. The user enters the necessary information, such as "Cargo amount: 1000 kg," "Delivery destination: Tokyo," and "Date: 2023-12-01."

[0782] Step 2:

[0783] The terminal acquires the information entered in the input form, converts it to JSON format, and sends an HTTP POST request to the server. The request payload contains the information entered by the user: cargo quantity, delivery destination, and delivery date.

[0784] Step 3:

[0785] The server receives the request from the terminal. The server analyzes the received information and creates a database query based on the load, destination, and delivery date. The query contains criteria for finding available vehicles that can transport the specified load on a specific date.

[0786] Step 4:

[0787] The server queries the database to retrieve information about available vehicles that match the criteria, including the vehicle's ID, maximum load capacity, and status (e.g., "available").

[0788] Step 5:

[0789] The server generates search results in JSON format and returns this information to the device, including a list of all available vehicles that match the search criteria.

[0790] Step 6:

[0791] The terminal receives the reply from the server and displays the results in a user interface that displays a list of all the vehicles provided as search results, each with a "Book Now" button.

[0792] Step 7:

[0793] The user selects the appropriate vehicle from the displayed list of vehicles and presses the "Reserve" button. The selected vehicle's ID and the necessary reservation information are sent back to the server from the terminal.

[0794] Step 8:

[0795] The server receives the reservation information and updates the status of the corresponding vehicle to "reserved." The server also calculates the optimal route from the departure point to the delivery destination, using a map API (e.g., Google Maps API) to determine the distance, travel time, and recommended route.

[0796] Step 9:

[0797] The server generates the reservation confirmation information and the calculated vehicle route in JSON format and sends it to the terminal.

[0798] Step 10:

[0799] The terminal receives the reply from the server and displays the reservation confirmation information and the optimal route information to the user, allowing the user to confirm that the reservation has been confirmed and the delivery route.

[0800] Through these specific processing steps, a system is realized that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and provides the optimal vehicle dispatch route.

[0801] Example 1

[0802] 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."

[0803] In the past, it was difficult to search for and reserve an appropriate available vehicle based on cargo volume, delivery destination, and schedule, and then create an optimal vehicle dispatch route in logistics operations. Furthermore, manual information management and vehicle dispatch plan creation required time and cost, resulting in a decrease in the efficiency of the entire logistics operation. Furthermore, if an appropriate available vehicle cannot be found or an optimal vehicle dispatch route cannot be calculated, resources are wasted. Thus, a system that can improve the efficiency of logistics operations and optimize the use of resources is needed.

[0804] 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.

[0805] In this invention, the server includes input means for inputting the cargo amount, delivery destination, and schedule, transmission means for transmitting the information input via the input means to the server, search means for searching for available vehicles from the information management device based on the transmitted information, transmission means for transmitting available vehicle information obtained by the search means to the terminal, reservation means for the user to select a vehicle based on the search result and transmit reservation information to the server, route calculation means for calculating the optimal vehicle dispatch route based on the reservation information, and transmission means for transmitting the calculation result and reservation confirmation information to the terminal. This makes it possible to improve the efficiency of the entire logistics operation and reduce waste of resources.

[0806] "Input means" refers to a device or software that allows a user to input the cargo amount, delivery destination, and schedule.

[0807] The "transmission means" refers to a device or mechanism that transmits information input via the input means to the server.

[0808] The "information management device" refers to a database that holds information about available vehicles and the management system for that database.

[0809] The "search means" refers to a device or software for searching for available vehicles from the information management device based on the transmitted information.

[0810] The "reservation means" refers to a device or software that allows the user to select a vehicle based on the search results and transmit the reservation information to the server.

[0811] The "route calculation means" refers to a device or software for calculating the optimal vehicle dispatch route based on reservation information.

[0812] A "terminal" is an electronic device or computer through which a user enters information and receives results.

[0813] The present invention is a system for searching for and reserving available vehicles based on cargo volume, delivery destination, and schedule, and also creates optimal vehicle dispatch routes. This system can improve the efficiency of logistics operations. Specific embodiments of the present invention are described below.

[0814] A dedicated web form or mobile application is provided on the terminal so that the user can enter the load amount, delivery destination, and delivery date. This form has fields for entering the load amount, delivery destination, and delivery date, allowing the user to easily enter the required data. For example, the user enters "Load amount: 1000 kg," "Delivery destination: Tokyo," and "Date: 2023-12-01."

[0815] After that, when the user presses the "Search" button, the terminal sends this information to the server as an HTTP request. The server receives the request and extracts information such as the cargo amount, delivery destination, and delivery date by parsing the JSON data. Based on the parsed information, the server executes an SQL query against a database (for example, a general SQL database) to search for available vehicles that can transport the entered cargo amount on the specified date. As a result, a list of available vehicles is obtained.

[0816] If a matching vehicle is found, the server generates information about that vehicle in JSON format and returns it to the terminal. The terminal receives the response, parses the JSON data, and displays it to the user. For example, a list containing information such as "Vehicle 1: Truck A, Load Capacity: 1500 kg, Current Location: Osaka" is displayed. The user selects the desired vehicle from the displayed list and presses the "Reserve" button. The terminal then sends the reservation information selected by the user to the server.

[0817] Based on the received reservation information, the server updates the status of the corresponding vehicle in its database to "reserved." The server then uses a map service such as Google Maps API to calculate the optimal route from the departure point to the delivery destination. The calculation results include the distance, required time, and recommended route. The server generates the calculation results in JSON format and returns them to the terminal. The terminal parses the information and displays it to the user, allowing them to confirm that the reservation has been confirmed and the details of the vehicle dispatch route. For example, the terminal may display information such as "Reservation confirmed. Recommended route: total distance 500 km, required time 6 hours, route A, route B."

[0818] This allows you to efficiently search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and also create optimal vehicle dispatch routes, improving the efficiency of overall logistics operations and reducing resource waste.

[0819] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0820] Step 1:

[0821] The user inputs the cargo amount, delivery destination, and delivery date.

[0822] The user uses a terminal to access a dedicated web form or mobile application and enters the load amount (e.g., 1,000 kg), delivery destination (e.g., Tokyo), and delivery date (e.g., 2023-12-01). This data is captured as text entered into the form.

[0823] Input: cargo amount, delivery destination, date (e.g. 1000kg, Tokyo, 2023-12-01)

[0824] Output: Data entered into the form

[0825] Step 2:

[0826] The terminal transmits the input information to the server.

[0827] When the user presses the "Search" button, the device converts the entered information into JSON format data and sends it to the server as an HTTP request.

[0828] Input: Data entered into a form

[0829] Output: JSON format data (e.g., { "Load": "1000kg", "Delivery destination": "Tokyo", "Date": "2023-12-01"})

[0830] Step 3:

[0831] The server receives and analyzes the data.

[0832] The server analyzes the HTTP request received from the terminal, parses the JSON data, and extracts the fields for cargo quantity, delivery destination, and schedule.

[0833] Input: JSON format data

[0834] Output: Extracted cargo volume, delivery destination, and schedule

[0835] Step 4:

[0836] The server searches for available vehicles from the information management device.

[0837] Based on the analyzed information, the server executes an SQL query against the database to search for available vehicles that can transport the input load on the specified date. For example, it executes a query such as "SELECT FROM vehicle WHERE date = '2023-12-01' AND maximum load capacity >= 1000kg".

[0838] Input: Extracted cargo volume, delivery destination, schedule

[0839] Output: A list of available vehicles as a result of the search.

[0840] Step 5:

[0841] The server returns the search results to the device.

[0842] If a matching vehicle is found, the server generates the vehicle information in JSON format and returns it to the terminal. For example, it generates data like "{ Vehicle ID: 1, Vehicle name: 'Truck A', Maximum load capacity: '1500kg', Current location: 'Osaka'}".

[0843] Input: A list of available vehicles as search results

[0844] Output: Vehicle information in JSON format

[0845] Step 6:

[0846] Your device will display the search results.

[0847] The terminal parses the JSON data received from the server and displays a list of available vehicles suggested to the user. For example, it displays information such as "Truck A, Load Capacity: 1500 kg, Current Location: Osaka."

[0848] Input: Vehicle information in JSON format

[0849] Output: A list of vehicles displayed to the user

[0850] Step 7:

[0851] The user selects and reserves a vehicle.

[0852] The user selects the desired vehicle from the displayed list and presses the "Reserve" button. The user's selection data is acquired by the terminal as reservation information.

[0853] Input: User selected vehicle information

[0854] Output: Reservation information

[0855] Step 8:

[0856] The terminal transmits the reservation information to the server.

[0857] The terminal converts the reservation information selected by the user into JSON format data and sends it to the server as an HTTP request.

[0858] Input: Reservation information

[0859] Output: Reservation information in JSON format

[0860] Step 9:

[0861] The server confirms the reservation based on the reservation information.

[0862] Based on the received reservation information, the server updates the status of the corresponding vehicle in the database to "reserved." For example, it executes an SQL query such as "UPDATE VEHICLE SET STATUS = 'RESERVED' WHERE VEHICLE ID = 1."

[0863] Input: Reservation information in JSON format

[0864] Output: Database update results

[0865] Step 10:

[0866] The server calculates the route.

[0867] The server uses a map service such as Google Maps API to calculate the optimal route from the starting point to the delivery destination, including distance, time required, and a recommended route.

[0868] Input: Departure point, delivery destination

[0869] Output: Calculated vehicle routing (e.g., distance 500 km, travel time 6 hours, route A)

[0870] Step 11:

[0871] The server returns the details of the vehicle route to the terminal.

[0872] The server generates the calculation results in JSON format and sends them to the terminal. For example, it generates data like "{ distance: '500km', required time: '6 hours', recommended route: 'Route A'}".

[0873] Input: Calculated vehicle routing route

[0874] Output: JSON formatted route information

[0875] Step 12:

[0876] The terminal displays the final information.

[0877] The device parses the JSON data received from the server and displays to the user that the reservation has been confirmed and details of the optimal route. For example, it displays "Reservation confirmed. Recommended route: total distance 500 km, required time 6 hours, route A."

[0878] Input: JSON formatted route information

[0879] Output: Confirmed booking information and route details displayed to the user

[0880] (Application example 1)

[0881] 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."

[0882] In the modern logistics industry, optimal vehicle allocation and route planning is required based on cargo volume, delivery destination, and schedule. However, doing this manually is extremely inefficient and wastes time and resources. Furthermore, it is difficult to check available vehicles in real time or propose optimal routes, making efficient vehicle allocation difficult. Therefore, a system is needed to improve the efficiency of logistics operations overall.

[0883] 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.

[0884] In this invention, the server includes an input means for inputting the cargo amount, delivery destination, and schedule, a transmission means for transmitting the information input via the input means to the server, a search means for searching a database for available vehicles based on the transmitted information, a transmission means for transmitting available vehicle information obtained by the search means to a terminal, a reservation means for a user to select a vehicle based on the search result and transmit reservation information to the server, a route calculation means for calculating an optimal vehicle dispatch route based on the reservation information, a transmission means for transmitting the calculation result and reservation confirmation information to the terminal, a means operated via a smartphone application used in the logistics center, a means for providing a web form for a user to easily input the cargo amount, delivery destination, and schedule, a means for calculating the route using a Google Maps API, and a means for analyzing prompts input by a user using a generative AI model and making optimal suggestions, thereby enabling efficient and real-time vehicle dispatch and route suggestions for logistics operations.

[0885] "Load volume" refers to the weight and volume of cargo or luggage, and is information that serves as the basis for determining the capacity of the vehicle required for transportation.

[0886] "Delivery destination" refers to the location or address where the package or product is to be delivered, and is important destination information in the logistic procedure.

[0887] "Schedule" refers to the schedule for shipping and arrival of packages, and is information for time management in the logistics process.

[0888] "Input means" refers to a device or interface (e.g., a web form or application) that allows a user to enter required information into a system.

[0889] "Transmission means" refers to a system or device that has the function of transmitting input information to a server.

[0890] A "search means" is a system or device that has the function of searching for relevant information (e.g., available vehicle information) from a database based on received information.

[0891] A "reservation vehicle" is a system or device that has the functionality to reserve a product or service (in this case, a vehicle) selected by a user.

[0892] "Route calculation means" refers to a system or device that has the function of calculating the optimal vehicle dispatch route from the departure point to the arrival point.

[0893] "Smartphone applications used within logistics centers" refers to mobile applications used by logistics center staff to manage cargo and arrange vehicle dispatches.

[0894] "Web Form" refers to an online form that allows a user to enter required information in a browser.

[0895] "Google Maps API" is a program interface for the map service provided by Google, and is a tool that provides functions such as map display and route calculation.

[0896] A "generative AI model" refers to an artificial intelligence system that learns from large amounts of data and provides optimal responses and suggestions for specified tasks or questions.

[0897] A "prompt" is an instruction or question entered by a user to instruct a generative AI model on a specific task.

[0898] This invention is a system that includes a smartphone application that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule at a logistics center. It also creates optimal vehicle dispatch routes, improving the efficiency of logistics operations.

[0899] Users input the cargo amount, delivery destination, and delivery date using a smartphone application installed in the logistics center. The smartphone application used in the logistics center has an intuitive user interface and provides a web form, allowing users to easily enter the necessary information.

[0900] The entered information is sent to the server via the smartphone application's transmission means. The server analyzes the received information and accesses the database to search for available vehicles. Specifically, the search means extracts available vehicles with a load capacity equal to or greater than the transmitted load capacity. If a suitable vehicle is found, the vehicle's information is sent to the terminal, and a list of suggested available vehicles is displayed to the user.

[0901] The user selects the desired vehicle from the displayed list and presses the "Reserve" button, and the reservation information is sent to the server. The server receives the reservation information and performs the reservation confirmation process, which includes updating the status of the corresponding vehicle to "Reserved."

[0902] At the same time, the server calculates the optimal route from the starting point to the delivery destination. This calculation is performed using the Google Maps API, and the calculation results include distance, travel time, and recommended route. Furthermore, using a generative AI model, the system makes optimal suggestions when the user inputs a prompt. The generative AI model is trained based on a large amount of data and returns the most appropriate result for the user's input.

[0903] Finally, the server sends the reservation confirmation and route details to the smartphone application, which displays this information to the user, who can confirm that the reservation has been confirmed and the optimal route.

[0904] For example, if a user enters "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01," the system can search for available vehicles that match these conditions and present them to the user. When the user reserves the suggested vehicle, the server uses the Google Maps API to calculate the optimal vehicle dispatch route and notify the user of the results.

[0905] An example of a prompt is:

[0906] "Search for available vehicles to deliver a 1000kg package to Tokyo on December 1, 2023, and suggest the best route."

[0907] In this way, a system is realized that efficiently searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and also creates optimal vehicle dispatch routes, thereby improving the efficiency of the entire logistics operation and reducing resource waste.

[0908] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0909] Step 1:

[0910] The user launches the smartphone application and inputs the cargo amount, delivery destination, and delivery date. The web form has an intuitive interface, making it easy to enter information. The input data (cargo amount, delivery destination, delivery date) obtained using the input means is temporarily stored in the smartphone's memory.

[0911] Step 2:

[0912] When the user presses the "Search" button, the terminal transmits the input data to the server via the transmission means. The transmitted data is in a format that includes information on the input amount, delivery destination, and schedule.

[0913] Step 3:

[0914] The server analyzes the received data and searches the database for available vehicles. Using the search means, the server extracts available vehicles from the database that can transport the input load for the specified date and time. This search process reads the ID of the vehicle that matches the conditions, its future usage schedule, and the load capacity.

[0915] Step 4:

[0916] The available vehicle information obtained by the search means is transmitted to a smartphone application using a transmission means, and the user can check a list of suggested available vehicles on the smartphone display.

[0917] Step 5:

[0918] The user selects the desired vehicle from the displayed list and presses the "Reserve" button. The terminal then sends the reservation information for the selected vehicle to the server. This reservation information includes the vehicle ID, reservation date and time, user ID, etc.

[0919] Step 6:

[0920] The server receives the reservation information and processes the reservation. It updates the status of the corresponding vehicle to "reserved" and records this information in the database. At the same time, the server calculates the optimal vehicle route from the departure point to the delivery destination. It uses the Google Maps API to calculate the optimal route, including the shortest distance and required time.

[0921] Step 7:

[0922] The generative AI model is used to analyze prompts entered by users. For example, the generative AI model analyzes a prompt such as, "Please search for available vehicles to deliver a 1,000 kg package to Tokyo on December 1, 2023, and suggest the optimal route," and makes appropriate suggestions. Based on this analysis, the optimal route information and vehicle information are reevaluated.

[0923] Step 8:

[0924] The server sends the route calculation results and reservation confirmation information to the smartphone application via the transmission means. The terminal receives this and displays to the user that the reservation has been confirmed and the optimal vehicle dispatch route. The user can check the details of the vehicle dispatch route on the smartphone screen and efficiently proceed with the vehicle dispatch operation.

[0925] In this way, the system efficiently executes a series of processes, from inputting the cargo volume, delivery destination, and schedule to searching for available vehicles, making reservations, and calculating routes, providing the user with the information they need.

[0926] 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.

[0927] This invention combines a system that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and creates optimal vehicle dispatch routes with an emotion engine that recognizes user emotions. This system not only improves the efficiency of logistics operations, but also enhances the user experience.

[0928] The interface for users to input cargo volume, delivery destination, and schedule is provided as a web form or mobile application. Users enter the cargo volume, delivery destination, and schedule and then press the "Search" button to start the search.

[0929] The terminal converts the input information into JSON format and sends it to the server via a transmission means. The server analyzes the received information and searches the database based on the cargo amount, delivery destination, and schedule. After obtaining information on the corresponding available vehicle, the server returns this information to the terminal.

[0930] The terminal receives the response from the server and displays the results to the user. The user selects the desired vehicle from the displayed results and presses the "Reserve" button, which sends reservation information such as the selected vehicle's ID to the server.

[0931] After receiving the reservation information, the server updates the vehicle's status to "reserved." The server then calculates the optimal route from the departure point to the delivery destination and returns the results to the terminal.

[0932] The emotion engine analyzes the input information and operations performed by the user while using the system, and determines the user's emotional state in real time. For example, it recognizes emotional states such as stress or decreased attention based on the user's input speed, mouse movements, and touchscreen operation patterns.

[0933] Based on the analysis results of the emotion engine, the system provides the following functions:

[0934] 1. Adjust search results and notifications:

[0935] If the emotion engine determines that you are stressed, it will simplify search results, highlight important information, and phrase notifications in more user-friendly language.

[0936] 2. Changes in how vehicle routing is suggested:

[0937] If the emotion engine determines that the user is in a hurry, it will prioritize the shortest route, while if the user is relaxed, it can suggest a scenic route that is a comfortable drive.

[0938] As a concrete example, suppose a user inputs "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01" and executes "search." The device sends this information to the server, which searches the database for available vehicles that match the criteria. The server then sends the search results to the device, which displays them to the user. Once the user selects the desired vehicle and confirms the reservation, the server calculates a vehicle dispatch route that takes into account the user's current emotional state based on the analysis results of the emotion engine, and sends this information to the device.

[0939] In this way, a system is realized that not only efficiently searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and provides the optimal vehicle dispatch route, but also improves the user experience by taking into account the user's emotional state.

[0940] The processing flow will be explained below.

[0941] Step 1:

[0942] The user accesses the web form or mobile application on their device and enters the cargo amount, delivery destination, and delivery date. For example, they enter information such as "Cargo amount: 1000 kg," "Delivery destination: Tokyo," and "Date: 2023-12-01."

[0943] Step 2:

[0944] The terminal receives the input information, converts it to JSON format, and sends an HTTP POST request to the server, which includes the input information on the load, delivery destination, and delivery date.

[0945] Step 3:

[0946] The server receives the request from the terminal. The server analyzes the received information and creates a database query based on the load, destination, and delivery date. The query contains criteria for finding available vehicles that can transport the specified load on a specific date.

[0947] Step 4:

[0948] The server queries the database to retrieve information about available vehicles that match the criteria, including the vehicle's ID, maximum load capacity, and status (e.g., "available").

[0949] Step 5:

[0950] The server generates search results in JSON format and sends this information to the device, which returns a list of all available vehicles that match the search criteria.

[0951] Step 6:

[0952] The terminal receives the reply from the server and displays a list of available vehicles to the user. The user selects the desired vehicle from the list and presses the "Reserve" button.

[0953] Step 7:

[0954] When the user presses the "Reserve" button, the ID of the selected vehicle and the necessary reservation information are sent from the terminal to the server. The reservation information includes the ID of the selected vehicle.

[0955] Step 8:

[0956] The server receives the reservation information and updates the status of the corresponding vehicle to "reserved." The server then calculates the optimal route from the departure point to the delivery destination. This calculation uses a map API (e.g., Google Maps API) to find the distance, travel time, and recommended route.

[0957] Step 9:

[0958] The server generates the reservation confirmation information and the calculated vehicle route in JSON format and sends it to the terminal.

[0959] Step 10:

[0960] The terminal receives the reply from the server and displays the reservation confirmation information and the optimal route information to the user, allowing the user to confirm that the reservation has been confirmed and the delivery route.

[0961] Step 11:

[0962] The emotion engine analyzes the user's input speed, operation patterns, mouse movements, and touchscreen operations to determine the user's emotional state in real time.

[0963] Step 12:

[0964] Based on the analysis results of the emotion engine, the server adjusts search results taking into account the user's emotional state. Specifically, if it determines that the user is feeling stressed, it condenses search results and highlights important information.

[0965] Step 13:

[0966] The emotion engine suggests optimal routes based on the user's emotional state. For example, it suggests the shortest route for a user in a hurry, and a scenic route for a user who is relaxed.

[0967] In this way, the system can efficiently search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and provide optimal vehicle dispatch routes that take the user's emotional state into consideration, simultaneously improving the user experience and streamlining logistics operations.

[0968] Example 2

[0969] 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."

[0970] Conventional logistics systems can search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and provide optimal vehicle dispatch routes, but they lack the ability to provide services that take into account the user's emotional state. Therefore, improvements are needed to reduce user stress and provide a better user experience.

[0971] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0972] In this invention, the server includes input means for inputting the cargo amount, delivery destination, and schedule, transmission means for transmitting the information input via the input means to a central device, search means for searching a storage device for available vehicles based on the transmitted information, transmission means for transmitting available vehicle information obtained by the search means to a terminal, reservation means for a user to select a vehicle based on the search results and transmit reservation information to the central device, route calculation means for calculating an optimal vehicle dispatch route based on the reservation information, transmission means for transmitting the calculation result and reservation confirmation information to the terminal, emotion analysis means for analyzing the user's operation and input information and determining the user's emotional state, result adjustment means for adjusting the search results and notification content based on the result of the emotion analysis means, and route suggestion means for changing the method of suggesting vehicle dispatch routes based on the result of the emotion analysis means. This makes it possible to provide logistics services that take the user's emotional state into consideration, which was not possible with conventional systems.

[0973] "Cargo volume" refers to the total weight of cargo transported in logistics.

[0974] "Delivery point" means the final receiving location to which the shipment is delivered.

[0975] "Schedule" refers to the scheduled delivery date or delivery period in logistics.

[0976] "Input means" refers to a device or interface used by a user to input cargo quantity, delivery destination, and delivery date into the system.

[0977] "Transmission means" refers to a means for transmitting input information to another device or system.

[0978] "Central device" refers to the main device that controls the entire system and processes and manages various types of information.

[0979] "Storage device" refers to a hardware or software component used to store information as data.

[0980] "Search means" refers to a device or program that has the function of searching for information from a database or the like based on certain conditions.

[0981] "Terminal" refers to a device that a user accesses and uses to perform various operations such as inputting and displaying information.

[0982] "Reservation means" refers to an interface that allows a user to select a desired vehicle and transmit that information to the system.

[0983] "Route calculation means" refers to a device or program that has the function of calculating the optimal vehicle dispatch route from the departure point to the delivery destination.

[0984] "Emotion analysis means" refers to a system that analyzes the user's input speed, operation patterns, etc., and determines the user's emotional state.

[0985] "Result adjustment means" refers to a device or program that has the function of adjusting search results or notification content based on the results of the emotion analysis means.

[0986] The "route suggestion means" refers to a device or program that has the function of changing the method of suggesting the optimal vehicle dispatch route based on the results of the emotion analysis means.

[0987] The present invention is directed to a system that aims to improve the efficiency of a logistics system and the user experience. Hereinafter, an embodiment of the present invention will be described in detail.

[0988] The interface for users to input cargo volume, delivery destination, and schedule is provided as a web form or mobile application. Users enter the necessary information through these interfaces and start the operation by pressing the "Search" button. This input method works on platforms such as web browsers and mobile apps.

[0989] The terminal converts the input information into JSON format and sends it to the central server using an HTTP request. The HTTPS protocol is used for transmission. The server parses the received JSON data and analyzes the information on the load, delivery destination, and schedule.

[0990] The server uses a relational database management system (RDBMS) such as MySQL to search the database stored in the storage device, using, for example, the following SQL query:

[0991] SELECT FROM Vehicle WHERE Load >= '1000kg' AND Delivery Destination = 'Tokyo' AND Available Date >= '2023-12-01'

[0992] This allows you to obtain available vehicles that meet the conditions.

[0993] The search results are converted to JSON format and sent from the server to the terminal. The transmission method is again HTTPS protocol. The terminal analyzes the results and displays them visually to the user. The user selects the desired vehicle from the displayed search results and clicks the "Reserve" button.

[0994] The device converts the reservation information, including the ID of the selected vehicle, into JSON format and sends it to the server using an HTTP request. The server parses the received reservation information and executes an SQL query to update the vehicle's status to "reserved":

[0995] UPDATE VEHICLE SET STATE = 'RESERVED' WHERE ID = '123'

[0996] After the reservation is completed, the server uses the Google Maps API to calculate the optimal route from the departure point to the delivery destination. The calculation result is converted into JSON format and sent from the server to the terminal. The terminal receives it and displays it visually to the user.

[0997] Additionally, the app is equipped with an emotion engine that analyzes the user's typing speed, mouse movements, touch patterns, etc. to determine the user's emotional state. The emotion engine uses machine learning models to assess stress levels, attention deficits, etc. in real time. Depending on the emotional state, the app offers the following features:

[0998] 1. Adjust search results and notifications:

[0999] If the system detects that a user is stressed, it will simplify search results, highlight important information, and present notifications in user-friendly language.

[1000] 2. Changes in how vehicle routing is suggested:

[1001] If the system determines that the user is in a hurry, it will prioritize showing the shortest route, while if the user is relaxed, it will suggest a scenic route that will provide a comfortable drive.

[1002] As a concrete example, consider the case where a user inputs "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01" and executes "search." The terminal sends this information to the server, which searches the database for available vehicles that match the criteria. The server then sends the search results to the terminal, which displays them to the user. Once the user selects the desired vehicle and confirms the reservation, the server calculates the optimal vehicle dispatch route based on the analysis results of the emotion engine, taking into account the user's current emotional state, and sends this information to the terminal.

[1003] Examples of prompts for generative AI models include:

[1004] "We want to build a system that allows users to input their cargo volume, delivery destination, and delivery date, search for available vehicles, and reserve them. We also want to be able to analyze the user's emotional state and adjust the display content and route suggestions accordingly."

[1005] In this way, the system can search for the most suitable available vehicle based on the cargo volume, delivery destination, and schedule, and provide an efficient logistics service that takes into account the user's emotional state.

[1006] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1007] Step 1:

[1008] The user uses a web form or mobile app to input the load, delivery destination, and delivery date. The user enters the load (e.g., 1000 kg), delivery destination (e.g., Tokyo), and delivery date (e.g., 2023-12-01) into each field in the form and clicks the "Search" button. This input is received by the terminal.

[1009] Step 2:

[1010] The terminal converts the information entered by the user, such as the amount of cargo, delivery destination, and delivery date, into JSON format. For example, the following JSON data is generated:

[1011] {"Load": "1000kg", "Delivery destination": "Tokyo", "Date": "2023-12-01"}

[1012] The converted JSON data is sent to the server via an HTTP request, which is part of the transmission method.

[1013] Step 3:

[1014] The server parses the received JSON data and extracts the necessary information (cargo volume, delivery destination, schedule). Specifically, it uses a JSON parser to extract the following data:

[1015] Load: 1000kg, Delivery location: Tokyo, Date: 2023-12-01

[1016] Based on this data, the server searches for available vehicles using a relational database such as MySQL.

[1017] Step 4:

[1018] The server generates and executes the SQL query to search the database:

[1019] SELECT FROM Vehicle WHERE Load >= '1000kg' AND Delivery Destination = 'Tokyo' AND Available Date >= '2023-12-01'

[1020] The information about available vehicles obtained through this search is converted into JSON format and returned to the terminal via an HTTP response.

[1021] Step 5:

[1022] The device receives the search results in JSON format from the server and parses them. For example, it parses the following results:

[1023] {"Vehicle": [{"ID": "123", "Vehicle Type": "Large Truck", "Status": "Available"}]}

[1024] The terminal visually displays the analyzed data to the user, specifically, the search results in a table format.

[1025] Step 6:

[1026] The user selects the desired vehicle from the displayed search results and clicks the "Reserve" button. This operation records the ID of the selected vehicle in the terminal. For example, the user selects a large truck with ID 123.

[1027] Step 7:

[1028] The device converts the reservation information, such as the vehicle ID selected by the user and the user ID, into JSON format. Specifically, the following data is generated:

[1029] {"Vehicle ID": "123", "User ID": "456"}

[1030] The converted JSON data is again sent to the server via an HTTP request.

[1031] Step 8:

[1032] The server parses the received reservation information and executes a SQL query to update the vehicle status to "reserved":

[1033] UPDATE VEHICLE SET STATE = 'RESERVED' WHERE ID = '123'

[1034] After the update is complete, the server uses the Google Maps API or similar to calculate the optimal route from the starting point to the delivery destination.

[1035] Step 9:

[1036] The server converts the calculated route into JSON format and sends it to the device via an HTTP response. For example, the following data is generated:

[1037] {"Route": "Detailed directions from the starting point to the delivery destination"}

[1038] The terminal receives this and displays it visually to the user.

[1039] Step 10:

[1040] The terminal collects data such as the user's input speed and operation patterns and sends it to the emotion analysis means, which analyzes this data and determines the user's emotional state, for example, whether the user is in a hurry or relaxed.

[1041] Step 11:

[1042] Based on the results of the emotion analysis, the server adjusts search results and notification content. For example, if it determines that the user is feeling stressed, it simplifies search results, highlights important information, and phrases notifications in more user-friendly language.

[1043] Step 12:

[1044] Based on the results of the emotion analysis, the server changes the way it suggests routes. For example, if it determines that the user is in a hurry, it will prioritize the shortest route. On the other hand, if the user is relaxed, it will suggest a route with a nice view.

[1045] This allows the system to not only search for and reserve the most suitable available vehicle based on cargo volume, delivery destination, and schedule, but also to provide logistics services that take into account the user's emotional state.

[1046] (Application example 2)

[1047] 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."

[1048] In conventional logistics systems, it is common to search for available vehicles based on conditions such as cargo volume, delivery destination, and schedule, and then provide the optimal vehicle dispatch route, but this alone has problems such as reducing user stress and not being able to support efficient input. In particular, there is a problem that information provided without considering the user's emotional state is insufficient to improve the user experience and is likely to reduce the user's work efficiency.

[1049] 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: input means for inputting the cargo amount, delivery destination, and schedule; transmission means for transmitting the information input via the input means to the server; search means for searching a database for available vehicles based on the transmitted information; transmission means for transmitting available vehicle information obtained by the search means to a terminal; reservation means for allowing the user to select a vehicle based on the search results and transmit reservation information to the server; route calculation means for calculating an optimal vehicle dispatch route based on the reservation information; transmission means for transmitting the calculation result and reservation confirmation information to the terminal; emotion recognition means for analyzing the user's emotional state; adjustment means for adjusting the search results and notification content based on the analysis result of the emotion recognition means; and route suggestion means for suggesting an optimal vehicle dispatch route in accordance with the user's emotional state. This enables efficient vehicle search and optimal vehicle dispatch route suggestion based on the cargo amount, delivery destination, and schedule while taking the user's emotional state into consideration in real time.

[1050] "Input means" refers to a device or system that provides an interface for inputting the cargo amount, delivery destination, and schedule.

[1051] The "transmission means" is a device or program for transmitting the input information to the server.

[1052] The "search means" is a device or program for searching for available vehicles from a database based on the transmitted information.

[1053] The "reservation means" is a device or program that allows the user to select a vehicle based on the search results and transmit reservation information to the server.

[1054] The "route calculation means" is a device or program for calculating the optimum vehicle dispatch route based on reservation information.

[1055] "Emotion recognition means" is a device or program for analyzing the user's emotional state.

[1056] The "adjustment means" is a device or program for adjusting search results and notification content based on the analysis results of the emotion recognition means.

[1057] The "route suggestion means" is a device or program for suggesting an optimal vehicle dispatch route according to the emotional state of the user.

[1058] This invention integrates an emotion engine that recognizes user emotions into a system that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and proposes optimal vehicle dispatch routes. This system can improve the efficiency of logistics operations and the user experience.

[1059] The main components of the system are:

[1060] 1. Input method: Smart glasses, smartphones, and other mobile devices are used as interfaces for users to input cargo quantities, delivery destinations, and delivery dates. For example, they support voice input and touch operation.

[1061] 2. Transmission means: Equipped with a communication function for transmitting input information to a server. This includes the communication module inside the smart glasses and the network function of the smartphone.

[1062] 3. Searching method: A search algorithm implemented on the server searches the database for available vehicles based on the received information, using a Python program and a database management system (e.g., MySQL).

[1063] 4. Reservation method: This includes a function to send reservation information for the vehicle selected by the user to the server. After the selection, the reservation process is performed on the server side.

[1064] 5. Route calculation method: The server runs an algorithm to calculate the optimal route based on the reservation information. In this case, a geographic information system (GIS) may be used.

[1065] 6. Emotion Recognition: This includes an emotion engine to analyze the user's emotional state. For example, it evaluates the user's emotional state in real time based on the user's input speed and touch strength. This is achieved by software called EmotionEngine.

[1066] 7. Adjustment: This includes programs to adjust search results and notification content based on the results of emotion recognition. For example, it may provide a simpler display to a stressed user and more detailed information to a calm user.

[1067] 8. Route suggestion: This includes an algorithm to suggest the optimal route based on the user's emotional state. For a relaxed user, it suggests a scenic route, while for a user in a hurry, it suggests the shortest route.

[1068] Examples:

[1069] The user uses the smart glasses to input "Load: 1000kg," "Delivery destination: Tokyo," and "Date: 2023-12-01." The input information is sent to the server via the smart glasses' communication function, and the server searches its database for available vehicles that match the criteria. The search results are then displayed on the smart glasses, and the reservation information for the vehicle selected by the user is sent to the server. The server uses an emotion engine to analyze the user's emotional state and suggests the optimal vehicle dispatch route based on the analysis results. The prompt is set as follows:

[1070] "Please create a program that uses smart glasses to acquire the cargo volume, delivery destination, and schedule information entered by the user, and displays the optimal vehicle search results according to the user's emotional state. A virtual emotion engine will be used for emotion recognition, and operation will be assumed to be via smart glasses."

[1071] In this way, the system is not only able to efficiently search for and reserve available vehicles based on the cargo volume, delivery destination, and schedule information entered by the user, but is also able to grasp the user's emotional state and respond flexibly accordingly.

[1072] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1073] Step 1:

[1074] The user uses smart glasses to input the cargo amount, delivery destination, and delivery date.

[1075] Input: cargo quantity, delivery destination, and schedule information.

[1076] Output: The input information displayed on the UI within the smart glasses.

[1077] Specific operation: The user uses the smart glasses' voice input function or touch operation to input the cargo quantity, delivery destination, and delivery date, and the input information is displayed on the smart glasses' display in real time.

[1078] Step 2:

[1079] The terminal transmits the input information to the server.

[1080] Input: User input information (JSON format).

[1081] Output: The data sent to the server.

[1082] Specific operation: The transmission means in the smart glasses converts the input information into JSON format and sends it to the server via the Internet.

[1083] Step 3:

[1084] The server searches the database based on the received information.

[1085] Input: User input information.

[1086] Output: A list of available vehicles.

[1087] Specific operation: The server analyzes the received information and searches the database for available vehicles that match the criteria, for example, by executing an SQL query using a Python program.

[1088] Step 4:

[1089] The server transmits available vehicle information to the terminal.

[1090] Input: A list of available vehicles.

[1091] Output: Data on which available vehicle information is sent.

[1092] Specific operation: The server sends the search result of the available vehicle list to the smart glasses, which then displays the information on their display.

[1093] Step 5:

[1094] The user selects the desired available vehicle and transmits the reservation information to the server.

[1095] Input: Available vehicle selection information.

[1096] Output: The reservation information sent to the server.

[1097] Specific operation: The user selects the desired vehicle using the interface of the smart glasses, and this selection information is sent to the server as reservation information.

[1098] Step 6:

[1099] The server calculates the optimal vehicle route based on the reservation information.

[1100] Input: Reservation information.

[1101] Output: Optimal vehicle routing.

[1102] How it works: The server uses the reservation information to calculate the optimal route using a geographic information system (GIS) and other algorithms.

[1103] Step 7:

[1104] The server sends the calculation results and reservation confirmation information to the terminal.

[1105] Input: Optimal route and reservation confirmation information.

[1106] Output: Data sent to the terminal.

[1107] Specific operation: The server sends the calculated route and reservation confirmation information to the smart glasses, allowing the user to view detailed information on the smart glasses display.

[1108] Step 8:

[1109] The server analyzes the user's emotional state.

[1110] Input: User operation logs (such as input speed and touch strength).

[1111] Output: The user's emotional state.

[1112] Specific operation: The emotion recognition means analyzes the user's operation log and evaluates the user's emotional state (such as changes in stress and attention) in real time.

[1113] Step 9:

[1114] The server adjusts search results and notification content based on the emotional state.

[1115] Input: User's emotional state, available vehicle information.

[1116] Output: Tailored search results and notifications.

[1117] Specific behavior: Search results and notification content are adjusted based on the analysis results of the emotion recognition method. For example, for users who are feeling stressed, search results are simplified and important information is highlighted.

[1118] Step 10:

[1119] The server proposes the optimal vehicle dispatch route according to the user's emotional state.

[1120] Input: User's emotional state, optimal vehicle routing.

[1121] Output: Vehicle routing suggestions based on emotional state.

[1122] Specific operation: The route suggestion means suggests the optimal vehicle dispatch route, such as the shortest distance or the most scenic route, based on the user's emotional state.

[1123] 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.

[1124] 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.

[1125] 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.

[1126] [Fourth embodiment]

[1127] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1128] 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.

[1129] 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).

[1130] 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.

[1131] 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.

[1132] 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).

[1133] 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.

[1134] 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.

[1135] 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.

[1136] 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.

[1137] 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.

[1138] 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.

[1139] 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."

[1140] The present invention is a system for searching for and reserving available vehicles based on cargo volume, delivery destination, and schedule, and also creates optimal vehicle dispatch routes. This makes it possible to improve the efficiency of logistics operations. Specific embodiments of the system of the present invention are described below.

[1141] A dedicated web form or mobile application is provided on the terminal to allow users to input the cargo amount, delivery destination, and schedule. This form has fields for inputting the cargo amount, delivery destination, and the user's schedule, making it easy to enter the required data. After that, when the user presses the "Search" button, the terminal sends this information to the server.

[1142] The server analyzes the received information, accesses the database, and searches for available vehicles. Specifically, it extracts vehicles that can transport the input load on the specified date. If a suitable vehicle is found, it returns the vehicle information to the terminal.

[1143] The terminal receives the reply from the server and displays a list of available vehicles to the user. The user selects the desired vehicle from the displayed list and presses the "Reserve" button, which sends the reservation information for that vehicle to the server.

[1144] Once the server receives the reservation information, it processes the reservation, which includes updating the vehicle's status to "reserved." At the same time, the server calculates the optimal route from the departure point to the delivery destination. This calculation is performed using a map service, such as Google Maps API. The calculation results include distance, travel time, and a recommended route.

[1145] Finally, the server sends the confirmed reservation information and details of the vehicle dispatch route to the terminal. The terminal displays this information to the user, who can confirm that the reservation has been confirmed and the optimal vehicle dispatch route. As a specific example, if the user enters "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01," the system will search for available vehicles that match these conditions and present them to the user. When the user selects one of the suggested vehicles and makes a reservation, the server calculates the optimal route and notifies the user of the results.

[1146] In this way, a system is realized that can efficiently search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and also create optimal vehicle dispatch routes. This system improves the efficiency of the entire logistics operation and reduces resource waste.

[1147] The processing flow will be explained below.

[1148] Step 1:

[1149] The user accesses the web form or mobile application on their device and enters the cargo amount, delivery destination, and delivery date. The user enters the necessary information, such as "Cargo amount: 1000 kg," "Delivery destination: Tokyo," and "Date: 2023-12-01."

[1150] Step 2:

[1151] The terminal acquires the information entered in the input form, converts it to JSON format, and sends an HTTP POST request to the server. The request payload contains the information entered by the user: cargo quantity, delivery destination, and delivery date.

[1152] Step 3:

[1153] The server receives the request from the terminal. The server analyzes the received information and creates a database query based on the load, destination, and delivery date. The query contains criteria for finding available vehicles that can transport the specified load on a specific date.

[1154] Step 4:

[1155] The server queries the database to retrieve information about available vehicles that match the criteria, including the vehicle's ID, maximum load capacity, and status (e.g., "available").

[1156] Step 5:

[1157] The server generates search results in JSON format and returns this information to the device, including a list of all available vehicles that match the search criteria.

[1158] Step 6:

[1159] The terminal receives the reply from the server and displays the results in a user interface that displays a list of all the vehicles provided as search results, each with a "Book Now" button.

[1160] Step 7:

[1161] The user selects the appropriate vehicle from the displayed list of vehicles and presses the "Reserve" button. The selected vehicle's ID and the necessary reservation information are sent back to the server from the terminal.

[1162] Step 8:

[1163] The server receives the reservation information and updates the status of the corresponding vehicle to "reserved." The server also calculates the optimal route from the departure point to the delivery destination, using a map API (e.g., Google Maps API) to determine the distance, travel time, and recommended route.

[1164] Step 9:

[1165] The server generates the reservation confirmation information and the calculated vehicle route in JSON format and sends it to the terminal.

[1166] Step 10:

[1167] The terminal receives the reply from the server and displays the reservation confirmation information and the optimal route information to the user, allowing the user to confirm that the reservation has been confirmed and the delivery route.

[1168] Through these specific processing steps, a system is realized that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and provides the optimal vehicle dispatch route.

[1169] Example 1

[1170] 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."

[1171] In the past, it was difficult to search for and reserve an appropriate available vehicle based on cargo volume, delivery destination, and schedule, and then create an optimal vehicle dispatch route in logistics operations. Furthermore, manual information management and vehicle dispatch plan creation required time and cost, resulting in a decrease in the efficiency of the entire logistics operation. Furthermore, if an appropriate available vehicle cannot be found or an optimal vehicle dispatch route cannot be calculated, resources are wasted. Thus, a system that can improve the efficiency of logistics operations and optimize the use of resources is needed.

[1172] 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.

[1173] In this invention, the server includes input means for inputting the cargo amount, delivery destination, and schedule, transmission means for transmitting the information input via the input means to the server, search means for searching for available vehicles from the information management device based on the transmitted information, transmission means for transmitting available vehicle information obtained by the search means to the terminal, reservation means for the user to select a vehicle based on the search result and transmit reservation information to the server, route calculation means for calculating the optimal vehicle dispatch route based on the reservation information, and transmission means for transmitting the calculation result and reservation confirmation information to the terminal. This makes it possible to improve the efficiency of the entire logistics operation and reduce waste of resources.

[1174] "Input means" refers to a device or software that allows a user to input the cargo amount, delivery destination, and schedule.

[1175] The "transmission means" refers to a device or mechanism that transmits information input via the input means to the server.

[1176] The "information management device" refers to a database that holds information about available vehicles and the management system for that database.

[1177] The "search means" refers to a device or software for searching for available vehicles from the information management device based on the transmitted information.

[1178] The "reservation means" refers to a device or software that allows the user to select a vehicle based on the search results and transmit the reservation information to the server.

[1179] The "route calculation means" refers to a device or software for calculating the optimal vehicle dispatch route based on reservation information.

[1180] A "terminal" is an electronic device or computer through which a user enters information and receives results.

[1181] The present invention is a system for searching for and reserving available vehicles based on cargo volume, delivery destination, and schedule, and also creates optimal vehicle dispatch routes. This system can improve the efficiency of logistics operations. Specific embodiments of the present invention are described below.

[1182] A dedicated web form or mobile application is provided on the terminal so that the user can enter the load amount, delivery destination, and delivery date. This form has fields for entering the load amount, delivery destination, and delivery date, allowing the user to easily enter the required data. For example, the user enters "Load amount: 1000 kg," "Delivery destination: Tokyo," and "Date: 2023-12-01."

[1183] After that, when the user presses the "Search" button, the terminal sends this information to the server as an HTTP request. The server receives the request and extracts information such as the cargo amount, delivery destination, and delivery date by parsing the JSON data. Based on the parsed information, the server executes an SQL query against a database (for example, a general SQL database) to search for available vehicles that can transport the entered cargo amount on the specified date. As a result, a list of available vehicles is obtained.

[1184] If a matching vehicle is found, the server generates information about that vehicle in JSON format and returns it to the terminal. The terminal receives the response, parses the JSON data, and displays it to the user. For example, a list containing information such as "Vehicle 1: Truck A, Load Capacity: 1500 kg, Current Location: Osaka" is displayed. The user selects the desired vehicle from the displayed list and presses the "Reserve" button. The terminal then sends the reservation information selected by the user to the server.

[1185] Based on the received reservation information, the server updates the status of the corresponding vehicle in its database to "reserved." The server then uses a map service such as Google Maps API to calculate the optimal route from the departure point to the delivery destination. The calculation results include the distance, required time, and recommended route. The server generates the calculation results in JSON format and returns them to the terminal. The terminal parses the information and displays it to the user, allowing them to confirm that the reservation has been confirmed and the details of the vehicle dispatch route. For example, the terminal may display information such as "Reservation confirmed. Recommended route: total distance 500 km, required time 6 hours, route A, route B."

[1186] This allows you to efficiently search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and also create optimal vehicle dispatch routes, improving the efficiency of overall logistics operations and reducing resource waste.

[1187] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1188] Step 1:

[1189] The user inputs the cargo amount, delivery destination, and delivery date.

[1190] The user uses a terminal to access a dedicated web form or mobile application and enters the load amount (e.g., 1,000 kg), delivery destination (e.g., Tokyo), and delivery date (e.g., 2023-12-01). This data is captured as text entered into the form.

[1191] Input: cargo amount, delivery destination, date (e.g. 1000kg, Tokyo, 2023-12-01)

[1192] Output: Data entered into the form

[1193] Step 2:

[1194] The terminal transmits the input information to the server.

[1195] When the user presses the "Search" button, the device converts the entered information into JSON format data and sends it to the server as an HTTP request.

[1196] Input: Data entered into a form

[1197] Output: JSON format data (e.g., { "Load": "1000kg", "Delivery destination": "Tokyo", "Date": "2023-12-01"})

[1198] Step 3:

[1199] The server receives and analyzes the data.

[1200] The server analyzes the HTTP request received from the terminal, parses the JSON data, and extracts the fields for cargo quantity, delivery destination, and schedule.

[1201] Input: JSON format data

[1202] Output: Extracted cargo volume, delivery destination, and schedule

[1203] Step 4:

[1204] The server searches for available vehicles from the information management device.

[1205] Based on the analyzed information, the server executes an SQL query against the database to search for available vehicles that can transport the input load on the specified date. For example, it executes a query such as "SELECT FROM vehicle WHERE date = '2023-12-01' AND maximum load capacity >= 1000kg".

[1206] Input: Extracted cargo volume, delivery destination, schedule

[1207] Output: A list of available vehicles as a result of the search.

[1208] Step 5:

[1209] The server returns the search results to the device.

[1210] If a matching vehicle is found, the server generates the vehicle information in JSON format and returns it to the terminal. For example, it generates data like "{ Vehicle ID: 1, Vehicle name: 'Truck A', Maximum load capacity: '1500kg', Current location: 'Osaka'}".

[1211] Input: A list of available vehicles as search results

[1212] Output: Vehicle information in JSON format

[1213] Step 6:

[1214] Your device will display the search results.

[1215] The terminal parses the JSON data received from the server and displays a list of available vehicles suggested to the user. For example, it displays information such as "Truck A, Load Capacity: 1500 kg, Current Location: Osaka."

[1216] Input: Vehicle information in JSON format

[1217] Output: A list of vehicles displayed to the user

[1218] Step 7:

[1219] The user selects and reserves a vehicle.

[1220] The user selects the desired vehicle from the displayed list and presses the "Reserve" button. The user's selection data is acquired by the terminal as reservation information.

[1221] Input: User selected vehicle information

[1222] Output: Reservation information

[1223] Step 8:

[1224] The terminal transmits the reservation information to the server.

[1225] The terminal converts the reservation information selected by the user into JSON format data and sends it to the server as an HTTP request.

[1226] Input: Reservation information

[1227] Output: Reservation information in JSON format

[1228] Step 9:

[1229] The server confirms the reservation based on the reservation information.

[1230] Based on the received reservation information, the server updates the status of the corresponding vehicle in the database to "reserved." For example, it executes an SQL query such as "UPDATE VEHICLE SET STATUS = 'RESERVED' WHERE VEHICLE ID = 1."

[1231] Input: Reservation information in JSON format

[1232] Output: Database update results

[1233] Step 10:

[1234] The server calculates the route.

[1235] The server uses a map service such as Google Maps API to calculate the optimal route from the starting point to the delivery destination, including distance, time required, and a recommended route.

[1236] Input: Departure point, delivery destination

[1237] Output: Calculated vehicle routing (e.g., distance 500 km, travel time 6 hours, route A)

[1238] Step 11:

[1239] The server returns the details of the vehicle route to the terminal.

[1240] The server generates the calculation results in JSON format and sends them to the terminal. For example, it generates data like "{ distance: '500km', required time: '6 hours', recommended route: 'Route A'}".

[1241] Input: Calculated vehicle routing route

[1242] Output: JSON formatted route information

[1243] Step 12:

[1244] The terminal displays the final information.

[1245] The device parses the JSON data received from the server and displays to the user that the reservation has been confirmed and details of the optimal route. For example, it displays "Reservation confirmed. Recommended route: total distance 500 km, required time 6 hours, route A."

[1246] Input: JSON formatted route information

[1247] Output: Confirmed booking information and route details displayed to the user

[1248] (Application example 1)

[1249] 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."

[1250] In the modern logistics industry, optimal vehicle allocation and route planning is required based on cargo volume, delivery destination, and schedule. However, doing this manually is extremely inefficient and wastes time and resources. Furthermore, it is difficult to check available vehicles in real time or propose optimal routes, making efficient vehicle allocation difficult. Therefore, a system is needed to improve the efficiency of logistics operations overall.

[1251] 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.

[1252] In this invention, the server includes an input means for inputting the cargo amount, delivery destination, and schedule, a transmission means for transmitting the information input via the input means to the server, a search means for searching a database for available vehicles based on the transmitted information, a transmission means for transmitting available vehicle information obtained by the search means to a terminal, a reservation means for a user to select a vehicle based on the search result and transmit reservation information to the server, a route calculation means for calculating an optimal vehicle dispatch route based on the reservation information, a transmission means for transmitting the calculation result and reservation confirmation information to the terminal, a means operated via a smartphone application used in the logistics center, a means for providing a web form for a user to easily input the cargo amount, delivery destination, and schedule, a means for calculating the route using a Google Maps API, and a means for analyzing prompts input by a user using a generative AI model and making optimal suggestions, thereby enabling efficient and real-time vehicle dispatch and route suggestions for logistics operations.

[1253] "Load volume" refers to the weight and volume of cargo or luggage, and is information that serves as the basis for determining the capacity of the vehicle required for transportation.

[1254] "Delivery destination" refers to the location or address where the package or product is to be delivered, and is important destination information in the logistic procedure.

[1255] "Schedule" refers to the schedule for shipping and arrival of packages, and is information for time management in the logistics process.

[1256] "Input means" refers to a device or interface (e.g., a web form or application) that allows a user to enter required information into a system.

[1257] "Transmission means" refers to a system or device that has the function of transmitting input information to a server.

[1258] A "search means" is a system or device that has the function of searching for relevant information (e.g., available vehicle information) from a database based on received information.

[1259] A "reservation vehicle" is a system or device that has the functionality to reserve a product or service (in this case, a vehicle) selected by a user.

[1260] "Route calculation means" refers to a system or device that has the function of calculating the optimal vehicle dispatch route from the departure point to the arrival point.

[1261] "Smartphone applications used within logistics centers" refers to mobile applications used by logistics center staff to manage cargo and arrange vehicle dispatches.

[1262] "Web Form" refers to an online form that allows a user to enter required information in a browser.

[1263] "Google Maps API" is a program interface for the map service provided by Google, and is a tool that provides functions such as map display and route calculation.

[1264] A "generative AI model" refers to an artificial intelligence system that learns from large amounts of data and provides optimal responses and suggestions for specified tasks or questions.

[1265] A "prompt" is an instruction or question entered by a user to instruct a generative AI model on a specific task.

[1266] This invention is a system that includes a smartphone application that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule at a logistics center. It also creates optimal vehicle dispatch routes, improving the efficiency of logistics operations.

[1267] Users input the cargo amount, delivery destination, and delivery date using a smartphone application installed in the logistics center. The smartphone application used in the logistics center has an intuitive user interface and provides a web form, allowing users to easily enter the necessary information.

[1268] The entered information is sent to the server via the smartphone application's transmission means. The server analyzes the received information and accesses the database to search for available vehicles. Specifically, the search means extracts available vehicles with a load capacity equal to or greater than the transmitted load capacity. If a suitable vehicle is found, the vehicle's information is sent to the terminal, and a list of suggested available vehicles is displayed to the user.

[1269] The user selects the desired vehicle from the displayed list and presses the "Reserve" button, and the reservation information is sent to the server. The server receives the reservation information and performs the reservation confirmation process, which includes updating the status of the corresponding vehicle to "Reserved."

[1270] At the same time, the server calculates the optimal route from the starting point to the delivery destination. This calculation is performed using the Google Maps API, and the calculation results include distance, travel time, and recommended route. Furthermore, using a generative AI model, the system makes optimal suggestions when the user inputs a prompt. The generative AI model is trained based on a large amount of data and returns the most appropriate result for the user's input.

[1271] Finally, the server sends the reservation confirmation and route details to the smartphone application, which displays this information to the user, who can confirm that the reservation has been confirmed and the optimal route.

[1272] For example, if a user enters "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01," the system can search for available vehicles that match these conditions and present them to the user. When the user reserves the suggested vehicle, the server uses the Google Maps API to calculate the optimal vehicle dispatch route and notify the user of the results.

[1273] An example of a prompt is:

[1274] "Search for available vehicles to deliver a 1000kg package to Tokyo on December 1, 2023, and suggest the best route."

[1275] In this way, a system is realized that efficiently searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and also creates optimal vehicle dispatch routes, thereby improving the efficiency of the entire logistics operation and reducing resource waste.

[1276] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1277] Step 1:

[1278] The user launches the smartphone application and inputs the cargo amount, delivery destination, and delivery date. The web form has an intuitive interface, making it easy to enter information. The input data (cargo amount, delivery destination, delivery date) obtained using the input means is temporarily stored in the smartphone's memory.

[1279] Step 2:

[1280] When the user presses the "Search" button, the terminal transmits the input data to the server via the transmission means. The transmitted data is in a format that includes information on the input amount, delivery destination, and schedule.

[1281] Step 3:

[1282] The server analyzes the received data and searches the database for available vehicles. Using the search means, the server extracts available vehicles from the database that can transport the input load for the specified date and time. This search process reads the ID of the vehicle that matches the conditions, its future usage schedule, and the load capacity.

[1283] Step 4:

[1284] The available vehicle information obtained by the search means is transmitted to a smartphone application using a transmission means, and the user can check a list of suggested available vehicles on the smartphone display.

[1285] Step 5:

[1286] The user selects the desired vehicle from the displayed list and presses the "Reserve" button. The terminal then sends the reservation information for the selected vehicle to the server. This reservation information includes the vehicle ID, reservation date and time, user ID, etc.

[1287] Step 6:

[1288] The server receives the reservation information and processes the reservation. It updates the status of the corresponding vehicle to "reserved" and records this information in the database. At the same time, the server calculates the optimal vehicle route from the departure point to the delivery destination. It uses the Google Maps API to calculate the optimal route, including the shortest distance and required time.

[1289] Step 7:

[1290] The generative AI model is used to analyze prompts entered by users. For example, the generative AI model analyzes a prompt such as, "Please search for available vehicles to deliver a 1,000 kg package to Tokyo on December 1, 2023, and suggest the optimal route," and makes appropriate suggestions. Based on this analysis, the optimal route information and vehicle information are reevaluated.

[1291] Step 8:

[1292] The server sends the route calculation results and reservation confirmation information to the smartphone application via the transmission means. The terminal receives this and displays to the user that the reservation has been confirmed and the optimal vehicle dispatch route. The user can check the details of the vehicle dispatch route on the smartphone screen and efficiently proceed with the vehicle dispatch operation.

[1293] In this way, the system efficiently executes a series of processes, from inputting the cargo volume, delivery destination, and schedule to searching for available vehicles, making reservations, and calculating routes, providing the user with the information they need.

[1294] 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.

[1295] This invention combines a system that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and creates optimal vehicle dispatch routes with an emotion engine that recognizes user emotions. This system not only improves the efficiency of logistics operations, but also enhances the user experience.

[1296] The interface for users to input cargo volume, delivery destination, and schedule is provided as a web form or mobile application. Users enter the cargo volume, delivery destination, and schedule and then press the "Search" button to start the search.

[1297] The terminal converts the input information into JSON format and sends it to the server via a transmission means. The server analyzes the received information and searches the database based on the cargo amount, delivery destination, and schedule. After obtaining information on the corresponding available vehicle, the server returns this information to the terminal.

[1298] The terminal receives the response from the server and displays the results to the user. The user selects the desired vehicle from the displayed results and presses the "Reserve" button, which sends reservation information such as the selected vehicle's ID to the server.

[1299] After receiving the reservation information, the server updates the vehicle's status to "reserved." The server then calculates the optimal route from the departure point to the delivery destination and returns the results to the terminal.

[1300] The emotion engine analyzes the input information and operations performed by the user while using the system, and determines the user's emotional state in real time. For example, it recognizes emotional states such as stress or decreased attention based on the user's input speed, mouse movements, and touchscreen operation patterns.

[1301] Based on the analysis results of the emotion engine, the system provides the following functions:

[1302] 1. Adjust search results and notifications:

[1303] If the emotion engine determines that you are stressed, it will simplify search results, highlight important information, and phrase notifications in more user-friendly language.

[1304] 2. Changes in how vehicle routing is suggested:

[1305] If the emotion engine determines that the user is in a hurry, it will prioritize the shortest route, while if the user is relaxed, it can suggest a scenic route that is a comfortable drive.

[1306] As a concrete example, suppose a user inputs "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01" and executes "search." The device sends this information to the server, which searches the database for available vehicles that match the criteria. The server then sends the search results to the device, which displays them to the user. Once the user selects the desired vehicle and confirms the reservation, the server calculates a vehicle dispatch route that takes into account the user's current emotional state based on the analysis results of the emotion engine, and sends this information to the device.

[1307] In this way, a system is realized that not only efficiently searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and provides the optimal vehicle dispatch route, but also improves the user experience by taking into account the user's emotional state.

[1308] The processing flow will be explained below.

[1309] Step 1:

[1310] The user accesses the web form or mobile application on their device and enters the cargo amount, delivery destination, and delivery date. For example, they enter information such as "Cargo amount: 1000 kg," "Delivery destination: Tokyo," and "Date: 2023-12-01."

[1311] Step 2:

[1312] The terminal receives the input information, converts it to JSON format, and sends an HTTP POST request to the server, which includes the input information on the load, delivery destination, and delivery date.

[1313] Step 3:

[1314] The server receives the request from the terminal. The server analyzes the received information and creates a database query based on the load, destination, and delivery date. The query contains criteria for finding available vehicles that can transport the specified load on a specific date.

[1315] Step 4:

[1316] The server queries the database to retrieve information about available vehicles that match the criteria, including the vehicle's ID, maximum load capacity, and status (e.g., "available").

[1317] Step 5:

[1318] The server generates search results in JSON format and sends this information to the device, which returns a list of all available vehicles that match the search criteria.

[1319] Step 6:

[1320] The terminal receives the reply from the server and displays a list of available vehicles to the user. The user selects the desired vehicle from the list and presses the "Reserve" button.

[1321] Step 7:

[1322] When the user presses the "Reserve" button, the ID of the selected vehicle and the necessary reservation information are sent from the terminal to the server. The reservation information includes the ID of the selected vehicle.

[1323] Step 8:

[1324] The server receives the reservation information and updates the status of the corresponding vehicle to "reserved." The server then calculates the optimal route from the departure point to the delivery destination. This calculation uses a map API (e.g., Google Maps API) to find the distance, travel time, and recommended route.

[1325] Step 9:

[1326] The server generates the reservation confirmation information and the calculated vehicle route in JSON format and sends it to the terminal.

[1327] Step 10:

[1328] The terminal receives the reply from the server and displays the reservation confirmation information and the optimal route information to the user, allowing the user to confirm that the reservation has been confirmed and the delivery route.

[1329] Step 11:

[1330] The emotion engine analyzes the user's input speed, operation patterns, mouse movements, and touchscreen operations to determine the user's emotional state in real time.

[1331] Step 12:

[1332] Based on the analysis results of the emotion engine, the server adjusts search results taking into account the user's emotional state. Specifically, if it determines that the user is feeling stressed, it condenses search results and highlights important information.

[1333] Step 13:

[1334] The emotion engine suggests optimal routes based on the user's emotional state. For example, it suggests the shortest route for a user in a hurry, and a scenic route for a user who is relaxed.

[1335] In this way, the system can efficiently search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and provide optimal vehicle dispatch routes that take the user's emotional state into consideration, simultaneously improving the user experience and streamlining logistics operations.

[1336] Example 2

[1337] 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."

[1338] Conventional logistics systems can search for and reserve available vehicles based on cargo volume, delivery destination, and schedule, and provide optimal vehicle dispatch routes, but they lack the ability to provide services that take into account the user's emotional state. Therefore, improvements are needed to reduce user stress and provide a better user experience.

[1339] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1340] In this invention, the server includes input means for inputting the cargo amount, delivery destination, and schedule, transmission means for transmitting the information input via the input means to a central device, search means for searching a storage device for available vehicles based on the transmitted information, transmission means for transmitting available vehicle information obtained by the search means to a terminal, reservation means for a user to select a vehicle based on the search results and transmit reservation information to the central device, route calculation means for calculating an optimal vehicle dispatch route based on the reservation information, transmission means for transmitting the calculation result and reservation confirmation information to the terminal, emotion analysis means for analyzing the user's operation and input information and determining the user's emotional state, result adjustment means for adjusting the search results and notification content based on the result of the emotion analysis means, and route suggestion means for changing the method of suggesting vehicle dispatch routes based on the result of the emotion analysis means. This makes it possible to provide logistics services that take the user's emotional state into consideration, which was not possible with conventional systems.

[1341] "Cargo volume" refers to the total weight of cargo transported in logistics.

[1342] "Delivery point" means the final receiving location to which the shipment is delivered.

[1343] "Schedule" refers to the scheduled delivery date or delivery period in logistics.

[1344] "Input means" refers to a device or interface used by a user to input cargo quantity, delivery destination, and delivery date into the system.

[1345] "Transmission means" refers to a means for transmitting input information to another device or system.

[1346] "Central device" refers to the main device that controls the entire system and processes and manages various types of information.

[1347] "Storage device" refers to a hardware or software component used to store information as data.

[1348] "Search means" refers to a device or program that has the function of searching for information from a database or the like based on certain conditions.

[1349] "Terminal" refers to a device that a user accesses and uses to perform various operations such as inputting and displaying information.

[1350] "Reservation means" refers to an interface that allows a user to select a desired vehicle and transmit that information to the system.

[1351] "Route calculation means" refers to a device or program that has the function of calculating the optimal vehicle dispatch route from the departure point to the delivery destination.

[1352] "Emotion analysis means" refers to a system that analyzes the user's input speed, operation patterns, etc., and determines the user's emotional state.

[1353] "Result adjustment means" refers to a device or program that has the function of adjusting search results or notification content based on the results of the emotion analysis means.

[1354] The "route suggestion means" refers to a device or program that has the function of changing the method of suggesting the optimal vehicle dispatch route based on the results of the emotion analysis means.

[1355] The present invention is directed to a system that aims to improve the efficiency of a logistics system and the user experience. Hereinafter, an embodiment of the present invention will be described in detail.

[1356] The interface for users to input cargo volume, delivery destination, and schedule is provided as a web form or mobile application. Users enter the necessary information through these interfaces and start the operation by pressing the "Search" button. This input method works on platforms such as web browsers and mobile apps.

[1357] The terminal converts the input information into JSON format and sends it to the central server using an HTTP request. The HTTPS protocol is used for transmission. The server parses the received JSON data and analyzes the information on the load, delivery destination, and schedule.

[1358] The server uses a relational database management system (RDBMS) such as MySQL to search the database stored in the storage device, using, for example, the following SQL query:

[1359] SELECT FROM Vehicle WHERE Load >= '1000kg' AND Delivery Destination = 'Tokyo' AND Available Date >= '2023-12-01'

[1360] This allows you to obtain available vehicles that meet the conditions.

[1361] The search results are converted to JSON format and sent from the server to the terminal. The transmission method is again HTTPS protocol. The terminal analyzes the results and displays them visually to the user. The user selects the desired vehicle from the displayed search results and clicks the "Reserve" button.

[1362] The device converts the reservation information, including the ID of the selected vehicle, into JSON format and sends it to the server using an HTTP request. The server parses the received reservation information and executes an SQL query to update the vehicle's status to "reserved":

[1363] UPDATE VEHICLE SET STATE = 'RESERVED' WHERE ID = '123'

[1364] After the reservation is completed, the server uses the Google Maps API to calculate the optimal route from the departure point to the delivery destination. The calculation result is converted into JSON format and sent from the server to the terminal. The terminal receives it and displays it visually to the user.

[1365] Additionally, the app is equipped with an emotion engine that analyzes the user's typing speed, mouse movements, touch patterns, etc. to determine the user's emotional state. The emotion engine uses machine learning models to assess stress levels, attention deficits, etc. in real time. Depending on the emotional state, the app offers the following features:

[1366] 1. Adjust search results and notifications:

[1367] If the system detects that a user is stressed, it will simplify search results, highlight important information, and present notifications in user-friendly language.

[1368] 2. Changes in how vehicle routing is suggested:

[1369] If the system determines that the user is in a hurry, it will prioritize showing the shortest route, while if the user is relaxed, it will suggest a scenic route that will provide a comfortable drive.

[1370] As a concrete example, consider the case where a user inputs "load: 1000 kg," "delivery destination: Tokyo," and "date: 2023-12-01" and executes "search." The terminal sends this information to the server, which searches the database for available vehicles that match the criteria. The server then sends the search results to the terminal, which displays them to the user. Once the user selects the desired vehicle and confirms the reservation, the server calculates the optimal vehicle dispatch route based on the analysis results of the emotion engine, taking into account the user's current emotional state, and sends this information to the terminal.

[1371] Examples of prompts for generative AI models include:

[1372] "We want to build a system that allows users to input their cargo volume, delivery destination, and delivery date, search for available vehicles, and reserve them. We also want to be able to analyze the user's emotional state and adjust the display content and route suggestions accordingly."

[1373] In this way, the system can search for the most suitable available vehicle based on the cargo volume, delivery destination, and schedule, and provide an efficient logistics service that takes into account the user's emotional state.

[1374] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1375] Step 1:

[1376] The user uses a web form or mobile app to input the load, delivery destination, and delivery date. The user enters the load (e.g., 1000 kg), delivery destination (e.g., Tokyo), and delivery date (e.g., 2023-12-01) into each field in the form and clicks the "Search" button. This input is received by the terminal.

[1377] Step 2:

[1378] The terminal converts the information entered by the user, such as the amount of cargo, delivery destination, and delivery date, into JSON format. For example, the following JSON data is generated:

[1379] {"Load": "1000kg", "Delivery destination": "Tokyo", "Date": "2023-12-01"}

[1380] The converted JSON data is sent to the server via an HTTP request, which is part of the transmission method.

[1381] Step 3:

[1382] The server parses the received JSON data and extracts the necessary information (cargo volume, delivery destination, schedule). Specifically, it uses a JSON parser to extract the following data:

[1383] Load: 1000kg, Delivery location: Tokyo, Date: 2023-12-01

[1384] Based on this data, the server searches for available vehicles using a relational database such as MySQL.

[1385] Step 4:

[1386] The server generates and executes the SQL query to search the database:

[1387] SELECT FROM Vehicle WHERE Load >= '1000kg' AND Delivery Destination = 'Tokyo' AND Available Date >= '2023-12-01'

[1388] The information about available vehicles obtained through this search is converted into JSON format and returned to the terminal via an HTTP response.

[1389] Step 5:

[1390] The device receives the search results in JSON format from the server and parses them. For example, it parses the following results:

[1391] {"Vehicle": [{"ID": "123", "Vehicle Type": "Large Truck", "Status": "Available"}]}

[1392] The terminal visually displays the analyzed data to the user, specifically, the search results in a table format.

[1393] Step 6:

[1394] The user selects the desired vehicle from the displayed search results and clicks the "Reserve" button. This operation records the ID of the selected vehicle in the terminal. For example, the user selects a large truck with ID 123.

[1395] Step 7:

[1396] The device converts the reservation information, such as the vehicle ID selected by the user and the user ID, into JSON format. Specifically, the following data is generated:

[1397] {"Vehicle ID": "123", "User ID": "456"}

[1398] The converted JSON data is again sent to the server via an HTTP request.

[1399] Step 8:

[1400] The server parses the received reservation information and executes a SQL query to update the vehicle status to "reserved":

[1401] UPDATE VEHICLE SET STATE = 'RESERVED' WHERE ID = '123'

[1402] After the update is complete, the server uses the Google Maps API or similar to calculate the optimal route from the starting point to the delivery destination.

[1403] Step 9:

[1404] The server converts the calculated route into JSON format and sends it to the device via an HTTP response. For example, the following data is generated:

[1405] {"Route": "Detailed directions from the starting point to the delivery destination"}

[1406] The terminal receives this and displays it visually to the user.

[1407] Step 10:

[1408] The terminal collects data such as the user's input speed and operation patterns and sends it to the emotion analysis means, which analyzes this data and determines the user's emotional state, for example, whether the user is in a hurry or relaxed.

[1409] Step 11:

[1410] Based on the results of the emotion analysis, the server adjusts search results and notification content. For example, if it determines that the user is feeling stressed, it simplifies search results, highlights important information, and phrases notifications in more user-friendly language.

[1411] Step 12:

[1412] Based on the results of the emotion analysis, the server changes the way it suggests routes. For example, if it determines that the user is in a hurry, it will prioritize the shortest route. On the other hand, if the user is relaxed, it will suggest a route with a nice view.

[1413] This allows the system to not only search for and reserve the most suitable available vehicle based on cargo volume, delivery destination, and schedule, but also to provide logistics services that take into account the user's emotional state.

[1414] (Application example 2)

[1415] 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."

[1416] In conventional logistics systems, it is common to search for available vehicles based on conditions such as cargo volume, delivery destination, and schedule, and then provide the optimal vehicle dispatch route, but this alone has problems such as reducing user stress and not being able to support efficient input. In particular, there is a problem that information provided without considering the user's emotional state is insufficient to improve the user experience and is likely to reduce the user's work efficiency.

[1417] 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: input means for inputting the cargo amount, delivery destination, and schedule; transmission means for transmitting the information input via the input means to the server; search means for searching a database for available vehicles based on the transmitted information; transmission means for transmitting available vehicle information obtained by the search means to a terminal; reservation means for allowing the user to select a vehicle based on the search results and transmit reservation information to the server; route calculation means for calculating an optimal vehicle dispatch route based on the reservation information; transmission means for transmitting the calculation result and reservation confirmation information to the terminal; emotion recognition means for analyzing the user's emotional state; adjustment means for adjusting the search results and notification content based on the analysis result of the emotion recognition means; and route suggestion means for suggesting an optimal vehicle dispatch route in accordance with the user's emotional state. This enables efficient vehicle search and optimal vehicle dispatch route suggestion based on the cargo amount, delivery destination, and schedule while taking the user's emotional state into consideration in real time.

[1418] "Input means" refers to a device or system that provides an interface for inputting the cargo amount, delivery destination, and schedule.

[1419] The "transmission means" is a device or program for transmitting the input information to the server.

[1420] The "search means" is a device or program for searching for available vehicles from a database based on the transmitted information.

[1421] The "reservation means" is a device or program that allows the user to select a vehicle based on the search results and transmit reservation information to the server.

[1422] The "route calculation means" is a device or program for calculating the optimum vehicle dispatch route based on reservation information.

[1423] "Emotion recognition means" is a device or program for analyzing the user's emotional state.

[1424] The "adjustment means" is a device or program for adjusting search results and notification content based on the analysis results of the emotion recognition means.

[1425] The "route suggestion means" is a device or program for suggesting an optimal vehicle dispatch route according to the emotional state of the user.

[1426] This invention integrates an emotion engine that recognizes user emotions into a system that searches for and reserves available vehicles based on cargo volume, delivery destination, and schedule, and proposes optimal vehicle dispatch routes. This system can improve the efficiency of logistics operations and the user experience.

[1427] The main components of the system are:

[1428] 1. Input method: Smart glasses, smartphones, and other mobile devices are used as interfaces for users to input cargo quantities, delivery destinations, and delivery dates. For example, they support voice input and touch operation.

[1429] 2. Transmission means: Equipped with a communication function for transmitting input information to a server. This includes the communication module inside the smart glasses and the network function of the smartphone.

[1430] 3. Searching method: A search algorithm implemented on the server searches the database for available vehicles based on the received information, using a Python program and a database management system (e.g., MySQL).

[1431] 4. Reservation method: This includes a function to send reservation information for the vehicle selected by the user to the server. After the selection, the reservation process is performed on the server side.

[1432] 5. Route calculation method: The server runs an algorithm to calculate the optimal route based on the reservation information. In this case, a geographic information system (GIS) may be used.

[1433] 6. Emotion Recognition: This includes an emotion engine to analyze the user's emotional state. For example, it evaluates the user's emotional state in real time based on the user's input speed and touch strength. This is achieved by software called EmotionEngine.

[1434] 7. Adjustment: This includes programs to adjust search results and notification content based on the results of emotion recognition. For example, it may provide a simpler display to a stressed user and more detailed information to a calm user.

[1435] 8. Route suggestion: This includes an algorithm to suggest the optimal route based on the user's emotional state. For a relaxed user, it suggests a scenic route, while for a user in a hurry, it suggests the shortest route.

[1436] Examples:

[1437] The user uses the smart glasses to input "Load: 1000kg," "Delivery destination: Tokyo," and "Date: 2023-12-01." The input information is sent to the server via the smart glasses' communication function, and the server searches its database for available vehicles that match the criteria. The search results are then displayed on the smart glasses, and the reservation information for the vehicle selected by the user is sent to the server. The server uses an emotion engine to analyze the user's emotional state and suggests the optimal vehicle dispatch route based on the analysis results. The prompt is set as follows:

[1438] "Please create a program that uses smart glasses to acquire the cargo volume, delivery destination, and schedule information entered by the user, and displays the optimal vehicle search results according to the user's emotional state. A virtual emotion engine will be used for emotion recognition, and operation will be assumed to be via smart glasses."

[1439] In this way, the system is not only able to efficiently search for and reserve available vehicles based on the cargo volume, delivery destination, and schedule information entered by the user, but is also able to grasp the user's emotional state and respond flexibly accordingly.

[1440] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1441] Step 1:

[1442] The user uses smart glasses to input the cargo amount, delivery destination, and delivery date.

[1443] Input: cargo quantity, delivery destination, and schedule information.

[1444] Output: The input information displayed on the UI within the smart glasses.

[1445] Specific operation: The user uses the smart glasses' voice input function or touch operation to input the cargo quantity, delivery destination, and delivery date, and the input information is displayed on the smart glasses' display in real time.

[1446] Step 2:

[1447] The terminal transmits the input information to the server.

[1448] Input: User input information (JSON format).

[1449] Output: The data sent to the server.

[1450] Specific operation: The transmission means in the smart glasses converts the input information into JSON format and sends it to the server via the Internet.

[1451] Step 3:

[1452] The server searches the database based on the received information.

[1453] Input: User input information.

[1454] Output: A list of available vehicles.

[1455] Specific operation: The server analyzes the received information and searches the database for available vehicles that match the criteria, for example, by executing an SQL query using a Python program.

[1456] Step 4:

[1457] The server transmits available vehicle information to the terminal.

[1458] Input: A list of available vehicles.

[1459] Output: Data on which available vehicle information is sent.

[1460] Specific operation: The server sends the search result of the available vehicle list to the smart glasses, which then displays the information on their display.

[1461] Step 5:

[1462] The user selects the desired available vehicle and transmits the reservation information to the server.

[1463] Input: Available vehicle selection information.

[1464] Output: The reservation information sent to the server.

[1465] Specific operation: The user selects the desired vehicle using the interface of the smart glasses, and this selection information is sent to the server as reservation information.

[1466] Step 6:

[1467] The server calculates the optimal vehicle route based on the reservation information.

[1468] Input: Reservation information.

[1469] Output: Optimal vehicle routing.

[1470] How it works: The server uses the reservation information to calculate the optimal route using a geographic information system (GIS) and other algorithms.

[1471] Step 7:

[1472] The server sends the calculation results and reservation confirmation information to the terminal.

[1473] Input: Optimal route and reservation confirmation information.

[1474] Output: Data sent to the terminal.

[1475] Specific operation: The server sends the calculated route and reservation confirmation information to the smart glasses, allowing the user to view detailed information on the smart glasses display.

[1476] Step 8:

[1477] The server analyzes the user's emotional state.

[1478] Input: User operation logs (such as input speed and touch strength).

[1479] Output: The user's emotional state.

[1480] Specific operation: The emotion recognition means analyzes the user's operation log and evaluates the user's emotional state (such as changes in stress and attention) in real time.

[1481] Step 9:

[1482] The server adjusts search results and notification content based on the emotional state.

[1483] Input: User's emotional state, available vehicle information.

[1484] Output: Tailored search results and notifications.

[1485] Specific behavior: Search results and notification content are adjusted based on the analysis results of the emotion recognition method. For example, for users who are feeling stressed, search results are simplified and important information is highlighted.

[1486] Step 10:

[1487] The server proposes the optimal vehicle dispatch route according to the user's emotional state.

[1488] Input: User's emotional state, optimal vehicle routing.

[1489] Output: Vehicle routing suggestions based on emotional state.

[1490] Specific operation: The route suggestion means suggests the optimal vehicle dispatch route, such as the shortest distance or the most scenic route, based on the user's emotional state.

[1491] 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.

[1492] 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.

[1493] 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.

[1494] 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.

[1495] 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.

[1496] 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.

[1497] 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).

[1498] 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.

[1499] 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."

[1500] 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.

[1501] 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).

[1502] 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.

[1503] 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.

[1504] 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.

[1505] 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.

[1506] 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.

[1507] 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.

[1508] 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.

[1509] 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.

[1510] 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.

[1511] 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.

[1512] The following is further disclosed regarding the above embodiment.

[1513] (Claim 1)

[1514] an input means for inputting the cargo amount, delivery destination, and schedule;

[1515] a transmitting means for transmitting the information inputted via the input means to a server;

[1516] a search means for searching a database for available vehicles based on the transmitted information;

[1517] a transmitting means for transmitting the available vehicle information obtained by the searching means to a terminal;

[1518] a reservation means for allowing a user to select a vehicle based on the search results and transmit reservation information to a server;

[1519] A route calculation means for calculating an optimal vehicle dispatch route based on reservation information;

[1520] a transmitting means for transmitting the calculation result and reservation confirmation information to a terminal;

[1521] A system including:

[1522] (Claim 2)

[1523] 2. The system of claim 1, wherein the means for searching the database searches for available vehicles with a load equal to or greater than the transmitted load.

[1524] (Claim 3)

[1525] 2. The system according to claim 1, wherein the route calculation means calculates an optimal route between the departure point and the destination point and transmits the result to the terminal.

[1526] "Example 1"

[1527] (Claim 1)

[1528] an input means for inputting the cargo amount, delivery destination, and schedule;

[1529] a transmitting means for transmitting the information inputted via the input means to a server;

[1530] a search means for searching for available vehicles from the information management device based on the transmitted information;

[1531] a transmitting means for transmitting the available vehicle information obtained by the searching means to a terminal;

[1532] a reservation means for allowing a user to select a vehicle based on the search results and transmit reservation information to a server;

[1533] A route calculation means for calculating an optimal vehicle dispatch route based on reservation information;

[1534] a transmitting means for transmitting the calculation result and reservation confirmation information to a terminal;

[1535] A system including:

[1536] (Claim 2)

[1537] 2. The system according to claim 1, wherein the means for searching the information management device searches for an available vehicle having a load equal to or greater than the transmitted load.

[1538] (Claim 3)

[1539] 2. The system according to claim 1, wherein the route calculation means calculates an optimal transportation route between the departure point and the arrival point and transmits the result to the terminal.

[1540] "Application Example 1"

[1541] (Claim 1)

[1542] an input means for inputting the cargo amount, delivery destination, and schedule;

[1543] a transmitting means for transmitting the information inputted via the input means to a server;

[1544] a search means for searching a database for available vehicles based on the transmitted information;

[1545] a transmitting means for transmitting the available vehicle information obtained by the searching means to a terminal;

[1546] a reservation means for allowing a user to select a vehicle based on the search results and transmit reservation information to a server;

[1547] A route calculation means for calculating an optimal vehicle dispatch route based on reservation information;

[1548] a transmitting means for transmitting the calculation result and reservation confirmation information to a terminal;

[1549] A means operated via a smartphone application used in the logistics center;

[1550] A means for providing a web form that allows users to easily input the amount of cargo, delivery destination, and delivery date;

[1551] A way to calculate routes using the Google Maps API,

[1552] A means to analyze user-entered prompts using a generative AI model and provide optimal suggestions;

[1553] A system including:

[1554] (Claim 2)

[1555] 2. The system of claim 1, wherein the means for searching the database searches for available vehicles with a load equal to or greater than the transmitted load.

[1556] (Claim 3)

[1557] 2. The system according to claim 1, wherein the route calculation means calculates an optimal route between the departure point and the destination point and transmits the result to the terminal.

[1558] "Example 2: Combining Emotion Engines"

[1559] (Claim 1)

[1560] an input means for inputting the cargo amount, delivery destination, and schedule;

[1561] a transmitting means for transmitting the information inputted via the input means to a central device;

[1562] a search means for searching for an available vehicle from a storage device based on the transmitted information;

[1563] a transmitting means for transmitting the available vehicle information obtained by the searching means to a terminal;

[1564] a reservation means for allowing a user to select a vehicle based on the search results and transmit reservation information to a central device;

[1565] A route calculation means for calculating an optimal vehicle dispatch route based on reservation information;

[1566] a transmitting means for transmitting the calculation result and reservation confirmation information to a terminal;

[1567] emotion analysis means for analyzing a user's operation and input information to determine the user's emotional state;

[1568] a result adjustment means for adjusting search results and notification content based on the result of the sentiment analysis means;

[1569] a route suggestion means for changing a method for suggesting a vehicle dispatch route based on a result of the emotion analysis means;

[1570] A system including:

[1571] (Claim 2)

[1572] 2. The system of claim 1, wherein the means for searching the storage device searches for an available vehicle having a load equal to or greater than the transmitted load.

[1573] (Claim 3)

[1574] 2. The system according to claim 1, wherein the route calculation means calculates an optimal route between the departure point and the destination point and transmits the result to the terminal.

[1575] "Application example 2 when combining emotion engines"

[1576] (Claim 1)

[1577] an input means for inputting the cargo amount, delivery destination, and schedule;

[1578] a transmitting means for transmitting the information inputted via the input means to a server;

[1579] a search means for searching a database for available vehicles based on the transmitted information;

[1580] a transmitting means for transmitting the available vehicle information obtained by the searching means to a terminal;

[1581] a reservation means for allowing a user to select a vehicle based on the search results and transmit reservation information to a server;

[1582] A route calculation means for calculating an optimal vehicle dispatch route based on reservation information;

[1583] a transmitting means for transmitting the calculation result and reservation confirmation information to a terminal;

[1584] emotion recognition means for analyzing the emotional state of a user;

[1585] an adjustment means for adjusting search results and notification contents based on the analysis result of the emotion recognition means;

[1586] a route suggestion means for suggesting an optimal vehicle dispatch route according to the emotional state of the user;

[1587] A system including:

[1588] (Claim 2)

[1589] 2. The system of claim 1, wherein the means for searching the database searches for available vehicles with a load equal to or greater than the transmitted load.

[1590] (Claim 3)

[1591] 2. The system according to claim 1, wherein the route calculation means calculates an optimal route between the departure point and the destination point and transmits the result to the terminal. [Explanation of symbols]

[1592] 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. an input means for inputting the cargo amount, delivery destination, and schedule; a transmitting means for transmitting the information inputted via the input means to a server; a search means for searching a database for available vehicles based on the transmitted information; a transmitting means for transmitting the available vehicle information obtained by the searching means to a terminal; a reservation means for allowing a user to select a vehicle based on the search results and transmit reservation information to a server; A route calculation means for calculating an optimal vehicle dispatch route based on reservation information; a transmitting means for transmitting the calculation result and reservation confirmation information to a terminal; A system including:

2. 2. The system of claim 1, wherein the means for searching the database searches for available vehicles having a load equal to or greater than the transmitted load.

3. 2. The system according to claim 1, wherein the route calculation means calculates an optimum route between the departure point and the destination point and transmits the result to the terminal.

Images