System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to input a starting location and a destination location; means for the user to input constraints; means for the user to input a location to visit en route and a visit time; means for receiving the input information and calculating an optimal route; and means for notifying the user of the calculated optimal route.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The present invention aims to propose an efficient and optimal route when travelling by car over medium distances and when time and budget are constraints. Conventional map applications have the problem that it is difficult to search for a route that meets specific budget and time constraints simply by setting the starting point and destination. Furthermore, when there are places you want to visit or a place you want to arrive at at a specific time, it is difficult to propose an optimal route that takes these into account. The present invention aims to solve these problems and provide a system that proposes an optimal route based on the constraints (time, fare, places to visit, arrival time) set by the user. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides a system having the following means: means for the user to input a starting location and a destination location, means for the user to input constraints, and means for the user to input places the user wants to visit along the way and the visiting time; means for receiving this input information and calculating an optimal route; means for notifying the user of the calculated optimal route; means for generating multiple routes that satisfy the time constraints and fare constraints specified by the user based on the received information, and selecting the route with the highest rating from among those routes; and means for predicting the stay time at places to be visited specified by the user and optimizing the overall visiting route.

[0006] The "starting location" is information indicating the point from which the user departs.

[0007] The "destination" is information indicating a location where the user aims to arrive.

[0008] "Constraints" are information that indicates conditions such as maximum travel time, fare, places to visit, and arrival time set by the user when traveling.

[0009] "Places to visit" is information indicating places that the user wishes to stop at along the way.

[0010] "Visiting time" is information that indicates the time a user stays at a particular location or the time at which the user wants to arrive at a particular time zone.

[0011] The "optimal route" is information that indicates a route that satisfies the constraints set by the user and realizes efficient and effective travel.

[0012] "Multiple routes" refers to information that indicates multiple options for different travel methods, means of travel, and routes from a departure point to a destination point.

[0013] "Route evaluation" refers to the criteria and methods for determining how well each route meets the user's constraints.

[0014] "Means for notifying the user" refers to the functions and devices within the system for providing information to the user about the calculated optimum route.

[0015] "Station duration prediction" refers to a method and means for calculating how long a user is expected to stay at a designated visit location.

[0016] "Means for streamlining the overall visiting route" refers to a system and algorithm for optimizing travel time and staying time between each visiting location, and making the overall movement efficient. [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] A system for implementing this invention calculates and proposes an optimal route to a user based on a starting point, destination, constraints, and places to visit set by the user. This system is realized through communication between a server and a terminal. A specific embodiment of the system is described below.

[0039] User Input

[0040] The user launches the application on the terminal and enters the following information:

[0041] 1. Enter your departure and destination.

[0042] Example: Departure point "Home", destination "Tokyo Tower"

[0043] 2. Enter the constraints.

[0044] Time it takes: Within 1 hour

[0045] Acceptable toll: Expressway tolls under 1,000 yen

[0046] 3. Enter the location you want to visit and a specific arrival time.

[0047] Example: Places to visit: "△△ Park", "◇◇ Cafe", "Arrive at Tokyo Tower at 4:00 PM"

[0048] Sending data

[0049] The terminal sends this input information to the server. The sent data is in the following format:

[0050] json

[0051] {

[0052] "Origin": "Home",

[0053] "Destination": "Tokyo Tower",

[0054] "Time Constraint": 60,

[0055] "Constraint Fee": 1000,

[0056] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[0057] "Arrival time": "16:00"

[0058] }

[0059] Server processing

[0060] The server receives the data sent from the terminal and performs the following processing.

[0061] 1. Analysis of received data

[0062] The server analyzes the received data and checks whether each piece of information has been entered correctly.

[0063] 2. Calculating the optimal route

[0064] The server generates multiple routes and calculates the travel time and cost for each route.

[0065] The server selects a route that fits within the time and cost constraints based on the user's constraints.

[0066] 3. Coordinating visit times

[0067] The server predicts the amount of time spent at desired destinations and streamlines the overall route.

[0068] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[0069] Sending and displaying results

[0070] The server sends the optimal route data to the terminal. The terminal displays the received data to the user. The specific display contents are as follows:

[0071] The best route from your starting point to your destination

[0072] Detailed directions on the map

[0073] Places visited along the way and duration of stay

[0074] Total travel time and estimated fare

[0075] User Review and Feedback

[0076] 1. The user checks the route displayed.

[0077] 2. If there are any further corrections the user would like to make, enter their feedback.

[0078] Example: "I'd like to go to Restaurant ☆☆ instead of Cafe ◇◇."

[0079] 3. The device sends the feedback to the server again, and the server reflects the feedback and recalculates a new optimal route.

[0080] 4. The recalculated route is re-notified and displayed to the user.

[0081] In this way, a system is realized that can effectively provide the optimal route within the time and budget set by the user.

[0082] The processing flow will be explained below.

[0083] Step 1:

[0084] The user starts the application on the terminal and inputs the departure point and destination.

[0085] The user inputs constraints (amount of time that can be spent, a fee).

[0086] The user inputs the location they wish to visit and a specific arrival time.

[0087] Step 2:

[0088] The terminal formats the user's input data and sends it to the server in JSON format or an appropriate data format.

[0089] example:

[0090] {

[0091] "Origin": "Home",

[0092] "Destination": "Tokyo Tower",

[0093] "Time Constraint": 60,

[0094] "Constraint Fee": 1000,

[0095] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[0096] "Arrival time": "16:00"

[0097] }

[0098] Step 3:

[0099] The server receives the data sent from the terminal and analyzes the received data.

[0100] The server checks the integrity of the data and makes sure there is no missing or incorrect information.

[0101] Step 4:

[0102] The server generates multiple candidate routes from the origin to the destination.

[0103] Calculate the travel time and cost for each candidate route.

[0104] Step 5:

[0105] The server incorporates the places the user wants to visit into the proposed route and reconstructs the route.

[0106] Add the estimated time spent at the places the user has specified to visit.

[0107] Step 6:

[0108] The server evaluates each candidate route to see if it satisfies the user's constraints (time, cost).

[0109] The route with the highest rating is selected from among the routes that satisfy the criteria.

[0110] Step 7:

[0111] The server sends the selected optimal route to the terminal in JSON format or other appropriate data format.

[0112] Step 8:

[0113] The terminal analyzes the optimum route data received from the server and displays it to the user.

[0114] The display includes detailed route information, time spent at each stop, total travel time, estimated fare, and more.

[0115] Step 9:

[0116] The user checks the displayed route and provides feedback on any corrections needed, if necessary.

[0117] Example: Enter "I want to go to Restaurant ☆☆ instead of Cafe ◇◇."

[0118] Step 10:

[0119] The terminal transmits the user's feedback to the server again.

[0120] Step 11:

[0121] The server receives the feedback and recalculates the optimal route based on the new conditions.

[0122] The server retransmits the recalculated route to the terminal.

[0123] Step 12:

[0124] The terminal displays the new optimal route to the user for final confirmation.

[0125] The above is the specific program processing flow in this system. By having the user, terminal, and server each fulfill their respective roles, the system can provide the optimal route within the time and budget set by the user.

[0126] Example 1

[0127] 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."

[0128] Conventional route calculation systems lack the functionality to verify the accuracy and completeness of data when calculating the optimal route based on multiple visit locations, arrival times, and constraints specified by the user. Furthermore, they are unable to efficiently select the optimal route and notify the user. As a result, users may not be satisfied with the route plan provided, which can be inconvenient.

[0129] 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.

[0130] In this invention, the server includes a means for the user to input a starting location and a destination location, a means for the user to input constraints, and a means for the user to input locations that the user wants to visit along the way and the visiting times.

[0131] 1. Efficiently select the optimal route based on constraints by verifying the accuracy and completeness of the data format of input information received from the user, generating multiple routes, and calculating the travel time and fare for each route;

[0132] 2. By providing a means to notify the user of the data on the selected optimal route, it becomes possible to present the optimal route.

[0133] This system allows users to easily receive efficient route plans based on specified destinations and constraints, providing a comfortable travel experience.

[0134] "Means for the user to input the starting location and destination" refers to an interface or function that allows the user to input information about the departure point and destination into the terminal.

[0135] "Means for users to input constraints" refers to interfaces and functions that allow users to input constraints such as travel time and travel costs into a terminal.

[0136] "Means for inputting the places the user wishes to visit along the way and the time of the visit" refers to an interface or function that allows the user to input the places the user wishes to visit and the time of arrival at them into the terminal.

[0137] "Means for receiving this input information and verifying the accuracy and completeness of the data format" refers to the function by which the server receives data sent from the terminal and verifies that the data is in the correct format and contains all the required information.

[0138] "Means for generating multiple routes and calculating the required time and cost for each route" refers to a function in which the server generates multiple candidates for efficient travel routes and calculates the required time and travel cost for each.

[0139] "Means for selecting the optimal route based on constraints" refers to a function that selects the most suitable route from the generated routes based on constraints such as time and fare set by the user.

[0140] "Means for notifying the user of data on the selected optimal route" refers to the function of sending information on the optimal route selected by the server to the terminal and notifying the user of its contents.

[0141] "Means for receiving feedback entered by the user, recalculating a new optimal route, and notifying the user again" refers to a function in which the server receives feedback information re-entered from the terminal, recalculates a new optimal route based on that information, and notifies the user again of the results.

[0142] A system for implementing this invention calculates an optimal route based on a starting location, a destination location, constraints, and places to visit set by a user, and proposes the route to the user. This system is realized through communication between a server and a terminal. Specific embodiments of the system are described below.

[0143] User Input

[0144] The user launches the application on the device and enters the following data:

[0145] 1. Starting and Destination Locations

[0146] Example: Start location "Home", destination location "Landmark"

[0147] 2. Constraints

[0148] Travel time: Less than 2 hours

[0149] Travel cost: Under 500 yen

[0150] 3. Places you want to visit and desired arrival time

[0151] Example: Visit locations: "Park", "Cafe", "Arrive at Landmark at 6pm"

[0152] Sending data

[0153] The device sends these inputs to the server, which structure the data as follows:

[0154] json

[0155] {

[0156] "Start Location": "Home",

[0157] "Destination": "Landmark",

[0158] "Time Constraint": 120,

[0159] "Constraint Fee": 500,

[0160] "visited place": ["park", "cafe"],

[0161] "Arrival time": "18:00"

[0162] }

[0163] Server analysis and processing

[0164] The server analyzes the data received from the device, verifies the accuracy and completeness of each piece of information, and then performs the following steps:

[0165] 1. Calculating the optimal route

[0166] The server generates multiple routes and calculates the travel time and cost for each route, using external services such as the Google Maps API.

[0167] Select the optimal route based on constraints.

[0168] 2. Coordinating visit times

[0169] The server takes into account the time spent at each desired visit location and efficiently adjusts the overall visit route.

[0170] Example: "Home → Park (stay 30 minutes) → Cafe (stay 30 minutes) → Landmark (arrive at 6pm)"

[0171] Sending and displaying results

[0172] The server sends the optimal route data in JSON format to the device. The device displays the received data to the user. The display contents are as follows:

[0173] The best route from the starting point to the destination

[0174] Detailed directions on the map

[0175] Places visited and duration of stay

[0176] Total travel time and estimated fare

[0177] User Review and Feedback

[0178] 1. The user checks the route

[0179] The user checks the route displayed.

[0180] 2. Enter your feedback

[0181] If the user is not satisfied with the route, he or she enters feedback.

[0182] Example: "I'd rather go to a different establishment than a cafe."

[0183] 3. Send feedback and recalculate

[0184] The device sends feedback to the server, which recalculates a new optimal route and sends it again.

[0185] Specific examples and prompts for generative AI models

[0186] For example, given the following user input:

[0187] Starting Location: Home

[0188] Destination: Landmark

[0189] Time limit: 2 hours

[0190] Restricted price: 500 yen or less

[0191] Places visited: parks, cafes

[0192] Desired arrival time: 18:00

[0193] Example prompts for generative AI models:

[0194] Please suggest the best route based on the following criteria:

[0195] 1. Starting location: Home

[0196] 2. Destination: Landmark

[0197] 3. Travel time: Within 2 hours

[0198] 4. Travel cost: Under 500 yen

[0199] 5. Places visited: parks, cafes

[0200] 6. Desired arrival time: Arrive at the landmark at 18:00

[0201] This system provides optimal route planning based on the places to visit and constraints specified by the user, thereby improving travel efficiency.

[0202] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0203] Step 1: User Input

[0204] This is a procedure in which a user starts an application on a terminal and inputs the starting location, destination location, constraints, visit locations, and visit time. The input information is structured in the following format.

[0205] Input: "Home" (starting location), "Landmark" (destination location), travel time within 120 minutes, travel fare within 500 yen, visit locations "park, cafe", arrival time "18:00"

[0206] Output: Structured data (e.g. JSON)

[0207] Step 2: Sending data

[0208] This is the procedure by which the terminal sends data entered by the user to the server. The HTTP protocol is used for communication, and structured data is sent in JSON format.

[0209] Input: Structured data (e.g. JSON)

[0210] Output: Data sent

[0211] Step 3: Data analysis by the server

[0212] This is the procedure in which the server analyzes the data received from the terminal and checks the accuracy and completeness of the data format. The analysis results are checked to see if all necessary information is included and if the data format is correct.

[0213] Input: Submitted data (e.g. JSON)

[0214] Data processing: Checking data format and information integrity

[0215] Output: Analysis results (data format and information integrity check)

[0216] Step 4: Calculate the optimal route

[0217] This is the procedure where the server generates multiple routes based on the received data and calculates the required time and fare for each route. Route generation and calculations are performed using an external map API (e.g., Google Maps API).

[0218] Input: Parsed data

[0219] Data processing: Route generation, travel time and fare calculation (using map API)

[0220] Output: Multiple candidate routes and their respective travel times and fares

[0221] Step 5: Selecting the optimal route

[0222] This is a procedure in which the server selects the optimal route from multiple generated routes that meets the user's constraints (time and cost). The most suitable route is selected based on evaluation criteria.

[0223] Input: Multiple candidate routes and their respective travel times and fares

[0224] Data calculation: Evaluation of candidate routes, selection of optimal route

[0225] Output: Optimal route

[0226] Step 6: Arrange visit times

[0227] This is a procedure in which the server further adjusts the optimal route, taking into account the time spent at desired destinations. It predicts the time spent at each destination and creates an overall travel schedule.

[0228] Input: Optimal route

[0229] Data calculation: Prediction of stay time, adjustment of travel schedule

[0230] Output: Optimal schedule (e.g., home → park (30 min stay) → cafe (30 min stay) → landmark)

[0231] Step 7: Send and view results

[0232] This is the procedure where the server sends the adjusted optimal route and schedule to the terminal in JSON format. The terminal displays the received information to the user.

[0233] Input: Optimal schedule and route

[0234] Output: Results displayed to the user (map, directions, duration, travel time, estimated fare)

[0235] Step 8: User review and feedback

[0236] This is the procedure where the user checks the displayed route and inputs feedback if necessary. If the user inputs a new request, the terminal sends the feedback to the server, which then recalculates.

[0237] Input: User feedback (e.g., "I'd rather go to a different establishment than the cafe")

[0238] Data processing: receiving feedback and recalculating

[0239] Output: New recalculated optimal route and schedule

[0240] In this way, the entire system is able to efficiently process user requests and provide optimal routes and schedules.

[0241] (Application example 1)

[0242] 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."

[0243] In the food delivery industry, maximizing delivery efficiency and improving customer satisfaction requires a system that enables delivery personnel to efficiently and quickly select the optimal route. However, conventional systems have difficulty calculating the optimal delivery route taking into account traffic conditions, time constraints, and multiple destinations. This leads to delivery delays and inefficient routes, resulting in a decline in service quality.

[0244] 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.

[0245] In this invention, the server includes means for the user to input a start location and a destination location, means for the user to input constraints, means for the user to input places the user wants to visit along the way and the visiting time, means for receiving this input information and calculating an optimal route, means for notifying the user of the calculated optimal route, means for the delivery person to input the start location and destination location, means for inputting delivery constraints, means for calculating an optimal delivery route taking traffic information into account, and means for notifying the delivery person of the optimal delivery route. This allows the delivery person to quickly obtain optimal route information taking traffic conditions into account in real time and make deliveries efficiently.

[0246] A "user" is a person or entity who uses the system to input the starting location, destination location, constraints, places to visit, and so on.

[0247] "Starting location / destination location" means the starting location and destination location entered by the user.

[0248] "Constraints" refer to conditions such as time constraints and fare constraints that the user takes into account when calculating a route.

[0249] "Visiting place and visiting time" refers to the places the user wants to visit along the way and the estimated time of arrival at those places.

[0250] "Input information" refers to information provided by the user to the system regarding the starting location, destination location, constraints, visit locations and their arrival times.

[0251] "Optimal route" refers to the most efficient route calculated based on input information that satisfies the user's constraints.

[0252] The "means for notifying" refers to a method or device for transmitting information about the calculated optimal route to the user.

[0253] A "delivery person" is a person or entity that uses the system to calculate the optimal delivery route in order to perform food delivery operations.

[0254] "Delivery constraints" refer to conditions such as time constraints and traffic conditions related to delivery that are input by the delivery person.

[0255] "Traffic information" refers to dynamic data on current road congestion conditions, traffic regulations, etc.

[0256] "Optimal delivery route" refers to the most efficient delivery route for a delivery person, calculated taking into account delivery constraints and traffic information.

[0257] The system according to the present invention allows users and delivery personnel to efficiently calculate and select routes and propose optimal routes to their destinations. Specific embodiments of the system are described below.

[0258] 1. Program Generation

[0259] This system includes a program that calculates the optimal route based on user input information and notifies the delivery person of the optimal delivery route, taking into account real-time traffic information. The specific functions and processing of the system are shown below.

[0260] 2. System processing explanation

[0261] The server receives information about the starting location, destination location, constraints, visiting locations and visiting times input by the user through the terminal, which is required when the user sets up a specific delivery scenario.

[0262] The received data is first verified for accuracy. The server then generates multiple routes and calculates the travel time and cost for each. An algorithm is used to select the optimal route, taking into account time and cost constraints.

[0263] This optimal route calculation utilizes traffic information APIs (e.g., Google Maps API), which allows the calculation of optimal routes taking into account real-time traffic conditions, and provides highly accurate route information to delivery personnel.

[0264] The delivery person's device displays the optimal route information received from the server on a map application, enabling the delivery person to carry out their delivery work smoothly and efficiently.

[0265] 3. Examples of concrete examples and prompts

[0266] For example, if a delivery person needs to deliver from a "food delivery shop" to a "customer's address" within 30 minutes, the delivery person will enter the following information into the system:

[0267] Starting point: Food delivery shop

[0268] Destination: Customer address

[0269] Restrictions: Arrive within 30 minutes

[0270] Traffic conditions: Congested

[0271] Based on this information, the server calculates the optimal route as follows and notifies the delivery person:

[0272] Starting point → Main road → Customer address

[0273] Example prompt sentence:

[0274] "Calculate the quickest route and show me the route that will get me to my customer's address in under 30 minutes."

[0275] As described above, this system can significantly improve the efficiency of food delivery operations by calculating the optimal route based on information input by the user and delivery person and providing accurate route information in real time.

[0276] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0277] Step 1:

[0278] The user uses a terminal to input the starting location, destination location, constraints, places to visit, and visiting times.

[0279] Input: Start location, Destination location, Constraints, Visit locations and visit times

[0280] Output: Input information is sent from the device to the server.

[0281] Step 2:

[0282] The server analyzes the input information received from the terminal and verifies the accuracy and completeness of the format.

[0283] Input: Starting location, destination location, constraints, visit locations and visit times sent from the terminal

[0284] Output: Validated input information

[0285] Step 3:

[0286] Based on the information received by the server, multiple routes are generated and the required time and cost for each route are calculated.

[0287] Input: Validated input information, data from traffic information API

[0288] Output: Multiple route information (including travel time and fare)

[0289] Step 4:

[0290] The server selects the optimal route from multiple route information based on the user's constraints.

[0291] Input: Multiple route information, user constraints

[0292] Output: Optimal route

[0293] Step 5:

[0294] The server generates optimal route information and adjusts visit locations and times, taking into account real-time data such as traffic conditions as needed.

[0295] Input: Optimal route, data from traffic information API

[0296] Output: The adjusted optimal path

[0297] Step 6:

[0298] The server sends the adjusted optimal route information to the terminal.

[0299] Input: Adjusted optimal route

[0300] Output: Optimal route information displayed on the user's device

[0301] Step 7:

[0302] The optimal route information received by the user terminal is displayed on a map application and notified to the user.

[0303] Input: Adjusted optimal route information sent from the server

[0304] Output: Optimal route displayed on a map application

[0305] Step 8:

[0306] The user checks the displayed route and provides feedback if necessary, which is then sent back to the server.

[0307] Input: Displayed optimal route, user feedback

[0308] Output: Feedback information resent to the server

[0309] Step 9:

[0310] The server recalculates the route based on the user's feedback, generates a new optimal route, and notifies the user.

[0311] Input: User feedback information

[0312] Output: Newly recalculated optimal route information

[0313] 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.

[0314] A system for implementing this invention calculates an optimal route based on the departure point, destination, constraints, and places to visit set by the user, and also uses an emotion engine that recognizes the user's emotions, and suggests the route to the user. This system is realized via communication between a server and a terminal. A specific embodiment of the system is described below.

[0315] User Input

[0316] The user launches the application on the terminal and enters the following information:

[0317] 1. Enter your departure and destination.

[0318] Example: Departure point "Home", destination "Tokyo Tower"

[0319] 2. Enter the constraints.

[0320] Time it takes: Within 1 hour

[0321] Acceptable toll: Expressway tolls under 1,000 yen

[0322] 3. Enter the location you want to visit and a specific arrival time.

[0323] Example: Places to visit: "△△ Park", "◇◇ Cafe", "Arrive at Tokyo Tower at 4:00 PM"

[0324] User Emotion Recognition

[0325] The device's built-in emotion engine analyzes the user's emotions in real time and determines their current emotional state based on their facial expressions, voice, and text input.

[0326] 1. Collect emotional data

[0327] The emotion engine collects information while the user is using the application.

[0328] Example: Judging whether a user is "having fun" or "tired" from their facial expression.

[0329] Sending data

[0330] The device formats the input data and emotion data and sends them to the server in JSON format or an appropriate data format.

[0331] example:

[0332] {

[0333] "Origin": "Home",

[0334] "Destination": "Tokyo Tower",

[0335] "Time Constraint": 60,

[0336] "Constraint Fee": 1000,

[0337] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[0338] "Arrival time": "16:00",

[0339] "emotion": {

[0340] "Status": "Having fun",

[0341] "Strength": 0.8

[0342] }

[0343] }

[0344] Server processing

[0345] The server receives the data sent from the terminal and performs the following processing.

[0346] 1. Analysis of received data

[0347] The server analyzes the received data and checks whether each piece of information has been entered correctly.

[0348] 2. Calculating the optimal route

[0349] The server generates multiple routes and calculates the travel time and cost for each route.

[0350] The server selects a route that fits within the time and cost constraints based on the user's constraints.

[0351] 3. Coordinating visit times

[0352] The server predicts the amount of time spent at desired destinations and streamlines the overall route.

[0353] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[0354] 4. Considering Emotional Data

[0355] The server adjusts the route based on the user's emotional state. For example, if the user is "having fun," it will suggest a route that takes a slightly longer route and passes through more enjoyable places, while if the user is "tired," it will prioritize the shortest route.

[0356] Sending and displaying results

[0357] The server sends the optimal route and emotion-based adjustment results data to the device. The device displays the received data to the user. The specific display content is as follows:

[0358] The best route from your starting point to your destination

[0359] Detailed directions on the map

[0360] Places visited along the way and duration of stay

[0361] Total travel time and estimated fare

[0362] Sentiment-based route recommendations

[0363] User Review and Feedback

[0364] 1. The user checks the route displayed.

[0365] 2. If there are any further corrections the user would like to make, enter their feedback.

[0366] Example: "I'd like to go to Restaurant ☆☆ instead of Cafe ◇◇."

[0367] 3. The device sends the feedback to the server again, and the server reflects the feedback and recalculates a new optimal route.

[0368] 4. The recalculated route is re-notified and displayed to the user.

[0369] In this way, a system is realized that can effectively provide an optimal route within a time and budget set by the user, taking into account the emotional state of the user.

[0370] The processing flow will be explained below.

[0371] Step 1:

[0372] The user starts the application on the terminal and inputs the departure point and destination.

[0373] The user inputs constraints (amount of time that can be spent, a fee).

[0374] The user inputs the location they wish to visit and a specific arrival time.

[0375] Example: Departure point "Home", destination "Tokyo Tower", time constraint "within 1 hour", toll constraint "highway toll less than 1,000 yen", visit locations "△△ Park", "◇◇ Cafe", arrival time "4:00 PM"

[0376] Step 2:

[0377] The terminal formats the input data and sends it to the server in JSON format.

[0378] The terminal sends the input data to the server.

[0379] example:

[0380] {

[0381] "Origin": "Home",

[0382] "Destination": "Tokyo Tower",

[0383] "Time Constraint": 60,

[0384] "Constraint Fee": 1000,

[0385] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[0386] "Arrival time": "16:00"

[0387] }

[0388] Step 3:

[0389] The emotion engine analyzes the user's emotions and understands their current emotional state.

[0390] The device collects emotional data from the user's facial expressions, voice, text input, etc.

[0391] Example: An emotion engine determines whether a user is "happy" or "tired" based on their facial expression.

[0392] Step 4:

[0393] The device analyzes the emotion data and transmits it to the server along with the starting point, destination, constraints, and places to be visited.

[0394] example:

[0395] {

[0396] "Origin": "Home",

[0397] "Destination": "Tokyo Tower",

[0398] "Time Constraint": 60,

[0399] "Constraint Fee": 1000,

[0400] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[0401] "Arrival time": "16:00",

[0402] "emotion": {

[0403] "Status": "Having fun",

[0404] "Strength": 0.8

[0405] }

[0406] }

[0407] Step 5:

[0408] The server receives and analyzes the data sent from the terminal.

[0409] The server verifies the integrity of each piece of information and checks for missing or incorrect information.

[0410] Step 6:

[0411] The server generates multiple candidate routes from the origin to the destination.

[0412] Calculate travel time and cost for the candidate routes.

[0413] Step 7:

[0414] The server incorporates the places the user wants to visit into the proposed route and reconstructs the route.

[0415] Add the estimated time spent at the places the user has specified to visit.

[0416] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[0417] Step 8:

[0418] The server evaluates each candidate route to see if it satisfies the constraints.

[0419] The route with the highest rating is selected from among the routes that satisfy the criteria.

[0420] Step 9:

[0421] The server takes into account the user's emotional state and adjusts the selected route.

[0422] For example, if you are "having fun," prioritize routes that include many tourist spots, and if you are "tired," prioritize the shortest route.

[0423] Step 10:

[0424] The server transmits the optimized route data to the terminal.

[0425] Step 11:

[0426] The terminal analyzes the optimum route data received from the server and displays it to the user.

[0427] The display includes detailed route information, places to visit and duration, total travel time, estimated fare, and more.

[0428] Step 12:

[0429] The user checks the displayed route and provides feedback on any corrections needed, if necessary.

[0430] The user inputs any parts that he / she wants to further correct as feedback.

[0431] Example: "I'd like to go to Restaurant ☆☆ instead of Cafe ◇◇."

[0432] Step 13:

[0433] The terminal transmits the user's feedback to the server again.

[0434] Step 14:

[0435] The server receives the feedback and recalculates based on the new conditions.

[0436] The recalculated route is retransmitted to the terminal.

[0437] Step 15:

[0438] The device displays the new optimal route to the user for final confirmation.

[0439] In this way, a system is realized that can effectively provide an optimal route within a time and budget set by the user, taking into account the emotional state of the user.

[0440] Example 2

[0441] 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."

[0442] Conventional route guidance systems calculate routes based on static information such as the departure point, destination, constraints, and places to visit, but are unable to provide route guidance that takes the user's emotional state into account. As a result, route guidance is not flexible enough to reflect the user's mood or physical condition, which can sometimes compromise the user experience. To solve this problem, a system that proposes optimal routes that also take the user's emotional information into account is needed.

[0443] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for the user to input a start location and a destination location, a means for the user to input constraints, a means for the user to input places the user wants to visit along the way and the visiting time, a means for recognizing the user's emotions in real time, a means for receiving the input information and emotion information and calculating an optimal route, and a means for notifying the user of the calculated optimal route. This makes it possible to provide flexible and optimal route guidance that also takes the user's emotional state into consideration.

[0444] A "user" is an entity that uses the system to input information such as the departure point, destination, constraints, and places to visit.

[0445] The "start location" is the point where the user starts moving.

[0446] A "destination" is a location that the user ultimately wants to reach.

[0447] "Constraints" are restrictions set by the user, such as travel time and fare.

[0448] A "place to visit" is a location where the user wants to stop during their travels.

[0449] "Visit time" is the time when the user will arrive at the visit location specified by the user.

[0450] "Emotion" refers to a psychological state that is recognized in real time from the user's facial expression, voice, etc.

[0451] The "optimal route" is the route that is judged to be the most efficient, taking into account factors such as travel time from the departure point to the destination, fare, and availability of places to visit.

[0452] "Notification" is the act of showing the calculated optimal route to the user.

[0453] The system for implementing this invention calculates the optimal route based on the starting point, destination, constraints, and places to visit set by the user, and further uses an emotion engine that recognizes the user's emotions, and proposes the route to the user. Specific embodiments of this system are described below.

[0454] First, the user launches the application on their device and inputs their starting location and destination. For example, they input "home" as the starting point and "Tokyo Tower" as the destination. Next, the user inputs constraints such as the amount of time and cost they are willing to spend. For example, they can set the required time to "within one hour" and the cost to "highway toll under 1,000 yen." Next, they input the places they want to visit and a specific arrival time. They can set "△△ Park" or "◇◇ Cafe" as places to visit and "arrive at 4:00 p.m." as the destination.

[0455] Furthermore, the emotion engine installed in the device analyzes the user's emotions in real time. The emotion engine determines the user's current emotional state based on the user's facial expressions, voice, and text input. For example, it can determine whether the user is "enjoyed" or "tired" based on the user's facial expressions. This emotional data is sensed and collected by the device.

[0456] The device formats the user's input data and emotion data and sends them to the server in JSON format or an appropriate data format.

[0457] {

[0458] "Origin": "Home",

[0459] "Destination": "Tokyo Tower",

[0460] "Time Constraint": 60,

[0461] "Constraint Fee": 1000,

[0462] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[0463] "Arrival time": "16:00",

[0464] "emotion": {

[0465] "Status": "Having fun",

[0466] "Strength": 0.8

[0467] }

[0468] }

[0469] Data like this is sent.

[0470] Next, the server receives the data sent from the terminal. After receiving the data, the server analyzes it and verifies that each piece of information has been entered correctly. The server then generates multiple routes and calculates the travel time and cost for each route. Based on the user's constraints, the server selects a route that fits within the time and cost constraints. Furthermore, the server predicts the length of stay at desired destinations and streamlines the overall route. For example, it may adjust the route to "Home → △△ Park (30-minute stay) → ◇◇ Cafe (20-minute stay) → Tokyo Tower (arrive at 4:00 p.m.)."

[0471] The server also adjusts the route based on the user's emotional state: for example, if the user is "having fun," it suggests a route that takes them through more enjoyable places, while if the user is "tired," it prioritizes the shortest route.

[0472] Finally, the server sends the optimal route and emotion-based adjustment results data to the device, which then displays the received data to the user. The display includes the optimal route from the origin to the destination, detailed directions on a map, stops along the way and their duration, total travel time and estimated fare, and an explanation of the emotion-based recommended route.

[0473] The user checks the displayed route and enters feedback if there are any parts they would like to correct. For example, if the user enters feedback such as "I would like to go to Restaurant ☆☆ instead of Cafe ◇◇," the device will send this to the server again. The server will reflect this feedback, recalculate a new optimal route, and notify and display it to the user again.

[0474] In this way, a system is realized that can effectively provide an optimal route within a time and budget set by the user, taking into account the emotional state of the user.

[0475] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0476] Step 1:

[0477] The user launches the application on their device and inputs the starting location, destination location, constraints, and places and times to visit. These inputs are saved on the device and used for subsequent data processing. For example, if a user inputs "home" as the starting point, "Tokyo Tower" as the destination, "within 1 hour" and "highway toll under 1,000 yen" as constraints, and "△△ Park," "◇◇ Cafe," and "arrive at Tokyo Tower at 4 p.m." as places to visit, the device will save this information as structured data.

[0478] input:

[0479] Start location, destination location, constraints, visit locations and visit times

[0480] output:

[0481] Structured Input Data

[0482] Step 2:

[0483] The emotion engine installed in the device recognizes the user's emotions in real time based on the user's facial expressions, voice, and text input. The emotion engine uses image recognition and voice analysis technologies to evaluate the user's state and generate corresponding emotion data. Specifically, analysis is performed using a camera and microphone, and the results are output as "enjoyed" or "tired," etc.

[0484] input:

[0485] User facial expressions, voice, and text input

[0486] output:

[0487] Real-time sentiment data

[0488] Step 3:

[0489] The device formats the user's input data and emotion data and sends them to the server in JSON format or other appropriate data format, where they are prepared for analysis.

[0490] input:

[0491] Structured input data, real-time sentiment data

[0492] output:

[0493] JSON format data to send to the server

[0494] Step 4:

[0495] The server receives and analyzes the data sent from the terminal. The received data includes the starting location, destination location, constraints, visited locations, visiting time, and emotion data. The server interprets this data and checks whether each piece of information has been entered correctly.

[0496] input:

[0497] JSON format data

[0498] output:

[0499] Analyzed data

[0500] Step 5:

[0501] The server generates multiple routes based on the analyzed data and calculates the travel time and fare for each route. Taking into account the user's constraints, it selects a route that fits within the time and fare constraints. The data is calculated using a route optimization algorithm using a map database and route information.

[0502] input:

[0503] Analyzed data

[0504] output:

[0505] Multiple calculated route candidates

[0506] Step 6:

[0507] The server predicts the amount of time spent at desired locations and optimizes the overall route. Taking into account the amount of time spent at each location, the server determines the optimal order of visits and stopovers. This allows for an efficient route that also takes into account the amount of time spent at each location.

[0508] input:

[0509] Multiple calculated route candidates

[0510] output:

[0511] Optimal route considering stay time

[0512] Step 7:

[0513] The server adjusts the route based on the user's emotional state. For example, if the user is "having fun," it will choose a route with a beautiful view, and if the user is "tired," it will choose the shortest route. Emotional data is also incorporated into the route calculation algorithm to generate optimal suggestions.

[0514] input:

[0515] Optimal route considering stay time, user emotion data

[0516] output:

[0517] Optimal route considering emotions

[0518] Step 8:

[0519] The server sends the calculated optimal route and emotion-based adjustment results data to the device, which then formats the results data and sends them back to the device in a format that is easy for the user to understand.

[0520] input:

[0521] Optimal route considering emotions

[0522] output:

[0523] Result data for display to the user

[0524] Step 9:

[0525] The device displays the data it receives to the user, including the optimal route from the departure point to the destination, detailed directions on a map, recommended routes based on locations visited along the way and their duration, total travel time and estimated fare, and sentiment. The information presented to the user allows them to review their travel plans in detail.

[0526] input:

[0527] Result data

[0528] output:

[0529] Optimal route and detailed information displayed to the user

[0530] Step 10:

[0531] The user checks the displayed route and inputs feedback if there are any corrections they would like to make. For example, they can input a request such as "I would like to go to Restaurant ☆☆ instead of Cafe ◇◇" into the device, and the device then sends this feedback data back to the server.

[0532] input:

[0533] User Feedback

[0534] output:

[0535] Feedback Data

[0536] Step 11:

[0537] The server recalculates a new optimal route based on the feedback and notifies the user again, with the new route suggestion adjusted to reflect the user's new preferences.

[0538] input:

[0539] Feedback Data

[0540] output:

[0541] Recalculated optimal route

[0542] In this way, we have created a system that proposes optimal routes that take the user's emotions into consideration through each step.

[0543] (Application example 2)

[0544] 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."

[0545] Current autonomous vehicle systems can calculate routes and provide driving instructions based on user settings, but they do not offer optimal route suggestions that take the user's emotional state into account. As a result, they are unable to flexibly respond to subtle changes in the user's emotions, which can lead to stress and frustration. The present invention aims to improve the user experience by calculating more personalized driving routes using user emotion recognition data and applying them to autonomous vehicles.

[0546] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input a start location and a destination location, means for the user to input constraints, means for the user to input places the user wants to visit along the way and the visiting time, means having a human emotion recognition engine for acquiring the user's emotional state, means for receiving the input information and emotional data and calculating an optimal route, means for notifying the user of the calculated optimal route, and means for transmitting driving instructions to the autonomously driven vehicle. This makes it possible to propose an optimal route and provide driving instructions that take the user's emotional state into consideration.

[0547] The "means for the user to input the starting point and the destination point" is an interface for the user to input the starting point and the destination point on the terminal.

[0548] The "means for the user to input constraints" is an interface for the user to input constraints such as time and cost during travel.

[0549] The "means for inputting the places the user wants to visit along the way and the time of visit" is an interface for inputting the places the user wants to stop at along the way and the time of arrival at those places.

[0550] A "human emotion recognition engine for acquiring a user's emotional state" is a system for acquiring emotional data in real time from a user's facial expressions, voice, etc.

[0551] The "means for receiving this input information and emotion data and calculating the optimal route" is a computer program for calculating the optimal travel route based on the information entered by the user and the acquired emotion data.

[0552] The "means for notifying the user of the calculated optimum route" is a communication means for notifying the user's terminal of the optimum route calculated by the server.

[0553] The "means for transmitting driving instructions to an autonomous vehicle" is a communication interface for transmitting driving instructions to an autonomous vehicle based on the calculated optimal route.

[0554] A system for implementing the present invention provides an optimal route for an autonomous vehicle that takes into account the emotional state of the user, and performs operational management. Detailed embodiments of this system will be described below.

[0555] User Input

[0556] The user enters the following information using a smartphone or vehicle interface:

[0557] 1. Origin and Destination

[0558] Example: Departure point "Home", destination "Tokyo Tower"

[0559] 2. Constraints

[0560] Example: Acceptable time: "within 1 hour", acceptable cost: "1,000 yen or less"

[0561] 3. The places you want to visit and the specific arrival time

[0562] Example: Visit locations: "△△ Park", "◇◇ Cafe", destination: "Arrival at 4:00 PM"

[0563] User Emotion Recognition

[0564] The device's built-in emotion engine analyzes the user's emotional state in real time. This emotion engine uses emotion recognition software such as "EmotionEngine" to determine the user's current emotional state based on facial expressions, voice, and text input.

[0565] Example: Judging whether a user is "having fun" or "tired" from their facial expression.

[0566] Sending data

[0567] The device formats the input data and emotion data and sends them to the server in JSON format or an appropriate data format, such as the following:

[0568] example:

[0569] json

[0570] {

[0571] "Origin": "Home",

[0572] "Destination": "Tokyo Tower",

[0573] "Time Constraint": 60,

[0574] "Constraint Fee": 1000,

[0575] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[0576] "Arrival time": "16:00",

[0577] "emotion": {

[0578] "Status": "Having fun",

[0579] "Strength": 0.8

[0580] }

[0581] }

[0582] Server processing

[0583] The server analyzes the received data and performs the following processing.

[0584] 1. Analysis of received data

[0585] Check that the data is entered correctly.

[0586] 2. Calculating the optimal route

[0587] Generate multiple routes and calculate the travel time and cost for each route.

[0588] The route with the highest evaluation within the constraints is selected.

[0589] 3. Coordinating visit times

[0590] Predict the amount of time spent at desired destinations and streamline the overall route.

[0591] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[0592] 4. Considering Emotional Data

[0593] The system adjusts the route based on the user's emotional state. For example, if the user is "having fun," it suggests a route that takes a slightly longer route and passes through more enjoyable places. If the user is "tired," it prioritizes the shortest route.

[0594] Sending and displaying results

[0595] The server sends the calculated optimal route information to the terminal, where the user can check the information through their smartphone or vehicle interface.

[0596] What it shows: The best route from origin to destination, stops along the way and duration, total travel time and estimated cost, and a sentiment-based explanation of the recommended route

[0597] Commanding autonomous vehicles

[0598] Based on the optimal route selected by the server, the autonomous vehicle will send driving instructions, which the autonomous vehicle will then follow to begin driving.

[0599] Specific prompt examples

[0600] The optimal route is calculated by inputting the following prompt sentence into the generative AI model:

[0601] markdown

[0602] You are the operator of a self-driving vehicle. Using the following information, provide the optimal route taking into account the user's specified conditions and emotional state:

[0603] Starting point: Home

[0604] Destination: Tokyo Tower

[0605] Constraints:

[0606] Time: 60 minutes or less

[0607] Price: Under 1,000 yen

[0608] Visited location: △△ Park, ◇◇ Cafe

[0609] Arrival time: 16:00

[0610] Emotional State: Enjoying (Intensity: 0.8)

[0611] Use this information to calculate the best route and suggest it to the user.

[0612] The above clearly shows how the system embodying the present invention operates in concrete terms.

[0613] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0614] Step 1: The user enters input information into the terminal

[0615] The user inputs the starting point, destination, constraints (such as time constraints and fare constraints), places to visit, and arrival time through the interface on the terminal. The user's input data is temporarily stored inside the terminal.

[0616] Input: Start point, Destination point, Constraints, Visit locations, Arrival time

[0617] Output: Saved user input data

[0618] Step 2: Collect user emotion data with an emotion recognition engine

[0619] The device's built-in emotion recognition engine analyzes the user's facial expressions, voice, and text input in real time to understand the user's emotional state. The necessary emotional data is extracted and stored on the device.

[0620] Input: User facial expression data, voice data, text input

[0621] Output: Emotion data (e.g., enjoying, intensity 0.8)

[0622] Step 3: Send input data and emotion data to the server

[0623] The device formats the user's input data and emotion data, converts it into an appropriate data format such as JSON, and sends it to the server.

[0624] Input: User input data, emotion data

[0625] Output: Formatted JSON data sent to the server

[0626] Step 4: The server parses the received data

[0627] The server analyzes the received data and checks its accuracy: it verifies that the starting point, destination, constraints, visit locations, arrival time, and emotional state are entered correctly.

[0628] Input: JSON data received by the server

[0629] Output: Parsed input data and sentiment data

[0630] Step 5: The server calculates the optimal route

[0631] The server generates multiple routes based on the analyzed input data and emotion data, calculates the travel time and cost for each route, and selects the route with the highest rating based on the user's constraints and emotional state.

[0632] Input: Parsed input data, emotion data

[0633] Output: Optimal route

[0634] Step 6: Adjust the time spent at each location

[0635] The server predicts the time spent at the places the user has designated to visit, and adjusts the overall route to make it more efficient.

[0636] Input: Visit location information, arrival time, constraints

[0637] Output: Adjusted itinerary

[0638] Step 7: The server sends the calculated route information to the terminal.

[0639] The server organizes the calculated and adjusted optimal route information and sends it to the terminal, where it is converted into an optimal format for the user to quickly check.

[0640] Input: Optimal route

[0641] Output: The organized route information is sent to the terminal.

[0642] Step 8: The device displays the route information to the user, and the user confirms it.

[0643] The device displays the optimal route information sent from the server to the user, who can then check it via their smartphone or in-car interface and make any necessary corrections.

[0644] Input: Organized route information

[0645] Output: Route information displayed to the user

[0646] Step 9: Send driving instructions to the autonomous vehicle

[0647] The server sends driving instructions to the autonomous vehicle based on the optimal route, and the autonomous vehicle then begins driving along the specified route.

[0648] Input: Optimal route instructions

[0649] Output: Driving instructions are sent to the autonomous vehicle.

[0650] 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.

[0651] 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.

[0652] 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.

[0653] [Second embodiment]

[0654] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0655] 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.

[0656] 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).

[0657] 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.

[0658] 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.

[0659] 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).

[0660] 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.

[0661] 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.

[0662] 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.

[0663] 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.

[0664] 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.

[0665] 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."

[0666] A system for implementing this invention calculates and proposes an optimal route to a user based on a starting point, destination, constraints, and places to visit set by the user. This system is realized through communication between a server and a terminal. A specific embodiment of the system is described below.

[0667] User Input

[0668] The user launches the application on the terminal and enters the following information:

[0669] 1. Enter your departure and destination.

[0670] Example: Departure point "Home", destination "Tokyo Tower"

[0671] 2. Enter the constraints.

[0672] Time it takes: Within 1 hour

[0673] Acceptable toll: Expressway tolls under 1,000 yen

[0674] 3. Enter the location you want to visit and a specific arrival time.

[0675] Example: Places to visit: "△△ Park", "◇◇ Cafe", "Arrive at Tokyo Tower at 4:00 PM"

[0676] Sending data

[0677] The terminal sends this input information to the server. The sent data is in the following format:

[0678] json

[0679] {

[0680] "Origin": "Home",

[0681] "Destination": "Tokyo Tower",

[0682] "Time Constraint": 60,

[0683] "Constraint Fee": 1000,

[0684] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[0685] "Arrival time": "16:00"

[0686] }

[0687] Server processing

[0688] The server receives the data sent from the terminal and performs the following processing.

[0689] 1. Analysis of received data

[0690] The server analyzes the received data and checks whether each piece of information has been entered correctly.

[0691] 2. Calculating the optimal route

[0692] The server generates multiple routes and calculates the travel time and cost for each route.

[0693] The server selects a route that fits within the time and cost constraints based on the user's constraints.

[0694] 3. Coordinating visit times

[0695] The server predicts the amount of time spent at desired destinations and streamlines the overall route.

[0696] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[0697] Sending and displaying results

[0698] The server sends the optimal route data to the terminal. The terminal displays the received data to the user. The specific display contents are as follows:

[0699] The best route from your starting point to your destination

[0700] Detailed directions on the map

[0701] Places visited along the way and duration of stay

[0702] Total travel time and estimated fare

[0703] User Review and Feedback

[0704] 1. The user checks the route displayed.

[0705] 2. If there are any further corrections the user would like to make, enter their feedback.

[0706] Example: "I'd like to go to Restaurant ☆☆ instead of Cafe ◇◇."

[0707] 3. The device sends the feedback to the server again, and the server reflects the feedback and recalculates a new optimal route.

[0708] 4. The recalculated route is re-notified and displayed to the user.

[0709] In this way, a system is realized that can effectively provide the optimal route within the time and budget set by the user.

[0710] The processing flow will be explained below.

[0711] Step 1:

[0712] The user starts the application on the terminal and inputs the departure point and destination.

[0713] The user inputs constraints (amount of time that can be spent, a fee).

[0714] The user inputs the location they wish to visit and a specific arrival time.

[0715] Step 2:

[0716] The terminal formats the user's input data and sends it to the server in JSON format or an appropriate data format.

[0717] example:

[0718] {

[0719] "Origin": "Home",

[0720] "Destination": "Tokyo Tower",

[0721] "Time Constraint": 60,

[0722] "Constraint Fee": 1000,

[0723] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[0724] "Arrival time": "16:00"

[0725] }

[0726] Step 3:

[0727] The server receives the data sent from the terminal and analyzes the received data.

[0728] The server checks the integrity of the data and makes sure there is no missing or incorrect information.

[0729] Step 4:

[0730] The server generates multiple candidate routes from the origin to the destination.

[0731] Calculate the travel time and cost for each candidate route.

[0732] Step 5:

[0733] The server incorporates the places the user wants to visit into the proposed route and reconstructs the route.

[0734] Add the estimated time spent at the places the user has specified to visit.

[0735] Step 6:

[0736] The server evaluates each candidate route to see if it satisfies the user's constraints (time, cost).

[0737] The route with the highest rating is selected from among the routes that satisfy the criteria.

[0738] Step 7:

[0739] The server sends the selected optimal route to the terminal in JSON format or other appropriate data format.

[0740] Step 8:

[0741] The terminal analyzes the optimum route data received from the server and displays it to the user.

[0742] The display includes detailed route information, time spent at each stop, total travel time, estimated fare, and more.

[0743] Step 9:

[0744] The user checks the displayed route and provides feedback on any corrections needed, if necessary.

[0745] Example: Enter "I want to go to Restaurant ☆☆ instead of Cafe ◇◇."

[0746] Step 10:

[0747] The terminal transmits the user's feedback to the server again.

[0748] Step 11:

[0749] The server receives the feedback and recalculates the optimal route based on the new conditions.

[0750] The server retransmits the recalculated route to the terminal.

[0751] Step 12:

[0752] The terminal displays the new optimal route to the user for final confirmation.

[0753] The above is the specific program processing flow in this system. By having the user, terminal, and server each fulfill their respective roles, the system can provide the optimal route within the time and budget set by the user.

[0754] Example 1

[0755] 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."

[0756] Conventional route calculation systems lack the functionality to verify the accuracy and completeness of data when calculating the optimal route based on multiple visit locations, arrival times, and constraints specified by the user. Furthermore, they are unable to efficiently select the optimal route and notify the user. As a result, users may not be satisfied with the route plan provided, which can be inconvenient.

[0757] 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.

[0758] In this invention, the server includes a means for the user to input a starting location and a destination location, a means for the user to input constraints, and a means for the user to input locations that the user wants to visit along the way and the visiting times.

[0759] 1. Efficiently select the optimal route based on constraints by verifying the accuracy and completeness of the data format of input information received from the user, generating multiple routes, and calculating the travel time and fare for each route;

[0760] 2. By providing a means to notify the user of the data on the selected optimal route, it becomes possible to present the optimal route.

[0761] This system allows users to easily receive efficient route plans based on specified destinations and constraints, providing a comfortable travel experience.

[0762] "Means for the user to input the starting location and destination" refers to an interface or function that allows the user to input information about the departure point and destination into the terminal.

[0763] "Means for users to input constraints" refers to interfaces and functions that allow users to input constraints such as travel time and travel costs into a terminal.

[0764] "Means for inputting the places the user wishes to visit along the way and the time of the visit" refers to an interface or function that allows the user to input the places the user wishes to visit and the time of arrival at them into the terminal.

[0765] "Means for receiving this input information and verifying the accuracy and completeness of the data format" refers to the function by which the server receives data sent from the terminal and verifies that the data is in the correct format and contains all the required information.

[0766] "Means for generating multiple routes and calculating the required time and cost for each route" refers to a function in which the server generates multiple candidates for efficient travel routes and calculates the required time and travel cost for each.

[0767] "Means for selecting the optimal route based on constraints" refers to a function that selects the most suitable route from the generated routes based on constraints such as time and fare set by the user.

[0768] "Means for notifying the user of data on the selected optimal route" refers to the function of sending information on the optimal route selected by the server to the terminal and notifying the user of its contents.

[0769] "Means for receiving feedback entered by the user, recalculating a new optimal route, and notifying the user again" refers to a function in which the server receives feedback information re-entered from the terminal, recalculates a new optimal route based on that information, and notifies the user again of the results.

[0770] A system for implementing this invention calculates an optimal route based on a starting location, a destination location, constraints, and places to visit set by a user, and proposes the route to the user. This system is realized through communication between a server and a terminal. Specific embodiments of the system are described below.

[0771] User Input

[0772] The user launches the application on the device and enters the following data:

[0773] 1. Starting and Destination Locations

[0774] Example: Start location "Home", destination location "Landmark"

[0775] 2. Constraints

[0776] Travel time: Less than 2 hours

[0777] Travel cost: Under 500 yen

[0778] 3. Places you want to visit and desired arrival time

[0779] Example: Visit locations: "Park", "Cafe", "Arrive at Landmark at 6pm"

[0780] Sending data

[0781] The device sends these inputs to the server, which structure the data as follows:

[0782] json

[0783] {

[0784] "Start Location": "Home",

[0785] "Destination": "Landmark",

[0786] "Time Constraint": 120,

[0787] "Constraint Fee": 500,

[0788] "visited place": ["park", "cafe"],

[0789] "Arrival time": "18:00"

[0790] }

[0791] Server analysis and processing

[0792] The server analyzes the data received from the device, verifies the accuracy and completeness of each piece of information, and then performs the following steps:

[0793] 1. Calculating the optimal route

[0794] The server generates multiple routes and calculates the travel time and cost for each route, using external services such as the Google Maps API.

[0795] Select the optimal route based on constraints.

[0796] 2. Coordinating visit times

[0797] The server takes into account the time spent at each desired visit location and efficiently adjusts the overall visit route.

[0798] Example: "Home → Park (stay 30 minutes) → Cafe (stay 30 minutes) → Landmark (arrive at 6pm)"

[0799] Sending and displaying results

[0800] The server sends the optimal route data in JSON format to the device. The device displays the received data to the user. The display contents are as follows:

[0801] The best route from the starting point to the destination

[0802] Detailed directions on the map

[0803] Places visited and duration of stay

[0804] Total travel time and estimated fare

[0805] User Review and Feedback

[0806] 1. The user checks the route

[0807] The user checks the route displayed.

[0808] 2. Enter your feedback

[0809] If the user is not satisfied with the route, he or she enters feedback.

[0810] Example: "I'd rather go to a different establishment than a cafe."

[0811] 3. Send feedback and recalculate

[0812] The device sends feedback to the server, which recalculates a new optimal route and sends it again.

[0813] Specific examples and prompts for generative AI models

[0814] For example, given the following user input:

[0815] Starting Location: Home

[0816] Destination: Landmark

[0817] Time limit: 2 hours

[0818] Restricted price: 500 yen or less

[0819] Places visited: parks, cafes

[0820] Desired arrival time: 18:00

[0821] Example prompts for generative AI models:

[0822] Please suggest the best route based on the following criteria:

[0823] 1. Starting location: Home

[0824] 2. Destination: Landmark

[0825] 3. Travel time: Within 2 hours

[0826] 4. Travel cost: Under 500 yen

[0827] 5. Places visited: parks, cafes

[0828] 6. Desired arrival time: Arrive at the landmark at 18:00

[0829] This system provides optimal route planning based on the places to visit and constraints specified by the user, thereby improving travel efficiency.

[0830] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0831] Step 1: User Input

[0832] This is a procedure in which a user starts an application on a terminal and inputs the starting location, destination location, constraints, visit locations, and visit time. The input information is structured in the following format.

[0833] Input: "Home" (starting location), "Landmark" (destination location), travel time within 120 minutes, travel fare within 500 yen, visit locations "park, cafe", arrival time "18:00"

[0834] Output: Structured data (e.g. JSON)

[0835] Step 2: Sending data

[0836] This is the procedure by which the terminal sends data entered by the user to the server. The HTTP protocol is used for communication, and structured data is sent in JSON format.

[0837] Input: Structured data (e.g. JSON)

[0838] Output: Data sent

[0839] Step 3: Data analysis by the server

[0840] This is the procedure in which the server analyzes the data received from the terminal and checks the accuracy and completeness of the data format. The analysis results are checked to see if all necessary information is included and if the data format is correct.

[0841] Input: Submitted data (e.g. JSON)

[0842] Data processing: Checking data format and information integrity

[0843] Output: Analysis results (data format and information integrity check)

[0844] Step 4: Calculate the optimal route

[0845] This is the procedure where the server generates multiple routes based on the received data and calculates the required time and fare for each route. Route generation and calculations are performed using an external map API (e.g., Google Maps API).

[0846] Input: Parsed data

[0847] Data processing: Route generation, travel time and fare calculation (using map API)

[0848] Output: Multiple candidate routes and their respective travel times and fares

[0849] Step 5: Selecting the optimal route

[0850] This is a procedure in which the server selects the optimal route from multiple generated routes that meets the user's constraints (time and cost). The most suitable route is selected based on evaluation criteria.

[0851] Input: Multiple candidate routes and their respective travel times and fares

[0852] Data calculation: Evaluation of candidate routes, selection of optimal route

[0853] Output: Optimal route

[0854] Step 6: Arrange visit times

[0855] This is a procedure in which the server further adjusts the optimal route, taking into account the time spent at desired destinations. It predicts the time spent at each destination and creates an overall travel schedule.

[0856] Input: Optimal route

[0857] Data calculation: Prediction of stay time, adjustment of travel schedule

[0858] Output: Optimal schedule (e.g., home → park (30 min stay) → cafe (30 min stay) → landmark)

[0859] Step 7: Send and view results

[0860] This is the procedure where the server sends the adjusted optimal route and schedule to the terminal in JSON format. The terminal displays the received information to the user.

[0861] Input: Optimal schedule and route

[0862] Output: Results displayed to the user (map, directions, duration, travel time, estimated fare)

[0863] Step 8: User review and feedback

[0864] This is the procedure where the user checks the displayed route and inputs feedback if necessary. If the user inputs a new request, the terminal sends the feedback to the server, which then recalculates.

[0865] Input: User feedback (e.g., "I'd rather go to a different establishment than the cafe")

[0866] Data processing: receiving feedback and recalculating

[0867] Output: New recalculated optimal route and schedule

[0868] In this way, the entire system is able to efficiently process user requests and provide optimal routes and schedules.

[0869] (Application example 1)

[0870] 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."

[0871] In the food delivery industry, maximizing delivery efficiency and improving customer satisfaction requires a system that enables delivery personnel to efficiently and quickly select the optimal route. However, conventional systems have difficulty calculating the optimal delivery route taking into account traffic conditions, time constraints, and multiple destinations. This leads to delivery delays and inefficient routes, resulting in a decline in service quality.

[0872] 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.

[0873] In this invention, the server includes means for the user to input a start location and a destination location, means for the user to input constraints, means for the user to input places the user wants to visit along the way and the visiting time, means for receiving this input information and calculating an optimal route, means for notifying the user of the calculated optimal route, means for the delivery person to input the start location and destination location, means for inputting delivery constraints, means for calculating an optimal delivery route taking traffic information into account, and means for notifying the delivery person of the optimal delivery route. This allows the delivery person to quickly obtain optimal route information taking traffic conditions into account in real time and make deliveries efficiently.

[0874] A "user" is a person or entity who uses the system to input the starting location, destination location, constraints, places to visit, and so on.

[0875] "Starting location / destination location" means the starting location and destination location entered by the user.

[0876] "Constraints" refer to conditions such as time constraints and fare constraints that the user takes into account when calculating a route.

[0877] "Visiting place and visiting time" refers to the places the user wants to visit along the way and the estimated time of arrival at those places.

[0878] "Input information" refers to information provided by the user to the system regarding the starting location, destination location, constraints, visit locations and their arrival times.

[0879] "Optimal route" refers to the most efficient route calculated based on input information that satisfies the user's constraints.

[0880] The "means for notifying" refers to a method or device for transmitting information about the calculated optimal route to the user.

[0881] A "delivery person" is a person or entity that uses the system to calculate the optimal delivery route in order to perform food delivery operations.

[0882] "Delivery constraints" refer to conditions such as time constraints and traffic conditions related to delivery that are input by the delivery person.

[0883] "Traffic information" refers to dynamic data on current road congestion conditions, traffic regulations, etc.

[0884] "Optimal delivery route" refers to the most efficient delivery route for a delivery person, calculated taking into account delivery constraints and traffic information.

[0885] The system according to the present invention allows users and delivery personnel to efficiently calculate and select routes and propose optimal routes to their destinations. Specific embodiments of the system are described below.

[0886] 1. Program Generation

[0887] This system includes a program that calculates the optimal route based on user input information and notifies the delivery person of the optimal delivery route, taking into account real-time traffic information. The specific functions and processing of the system are shown below.

[0888] 2. System processing explanation

[0889] The server receives information about the starting location, destination location, constraints, visiting locations and visiting times input by the user through the terminal, which is required when the user sets up a specific delivery scenario.

[0890] The received data is first verified for accuracy. The server then generates multiple routes and calculates the travel time and cost for each. An algorithm is used to select the optimal route, taking into account time and cost constraints.

[0891] This optimal route calculation utilizes traffic information APIs (e.g., Google Maps API), which allows the calculation of optimal routes taking into account real-time traffic conditions, and provides highly accurate route information to delivery personnel.

[0892] The delivery person's device displays the optimal route information received from the server on a map application, enabling the delivery person to carry out their delivery work smoothly and efficiently.

[0893] 3. Examples of concrete examples and prompts

[0894] For example, if a delivery person needs to deliver from a "food delivery shop" to a "customer's address" within 30 minutes, the delivery person will enter the following information into the system:

[0895] Starting point: Food delivery shop

[0896] Destination: Customer address

[0897] Restrictions: Arrive within 30 minutes

[0898] Traffic conditions: Congested

[0899] Based on this information, the server calculates the optimal route as follows and notifies the delivery person:

[0900] Starting point → Main road → Customer address

[0901] Example prompt sentence:

[0902] "Calculate the quickest route and show me the route that will get me to my customer's address in under 30 minutes."

[0903] As described above, this system can significantly improve the efficiency of food delivery operations by calculating the optimal route based on information input by the user and delivery person and providing accurate route information in real time.

[0904] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0905] Step 1:

[0906] The user uses a terminal to input the starting location, destination location, constraints, places to visit, and visiting times.

[0907] Input: Start location, Destination location, Constraints, Visit locations and visit times

[0908] Output: Input information is sent from the device to the server.

[0909] Step 2:

[0910] The server analyzes the input information received from the terminal and verifies the accuracy and completeness of the format.

[0911] Input: Starting location, destination location, constraints, visit locations and visit times sent from the terminal

[0912] Output: Validated input information

[0913] Step 3:

[0914] Based on the information received by the server, multiple routes are generated and the required time and cost for each route are calculated.

[0915] Input: Validated input information, data from traffic information API

[0916] Output: Multiple route information (including travel time and fare)

[0917] Step 4:

[0918] The server selects the optimal route from multiple route information based on the user's constraints.

[0919] Input: Multiple route information, user constraints

[0920] Output: Optimal route

[0921] Step 5:

[0922] The server generates optimal route information and adjusts visit locations and times, taking into account real-time data such as traffic conditions as needed.

[0923] Input: Optimal route, data from traffic information API

[0924] Output: The adjusted optimal path

[0925] Step 6:

[0926] The server sends the adjusted optimal route information to the terminal.

[0927] Input: Adjusted optimal route

[0928] Output: Optimal route information displayed on the user's device

[0929] Step 7:

[0930] The optimal route information received by the user terminal is displayed on a map application and notified to the user.

[0931] Input: Adjusted optimal route information sent from the server

[0932] Output: Optimal route displayed on a map application

[0933] Step 8:

[0934] The user checks the displayed route and provides feedback if necessary, which is then sent back to the server.

[0935] Input: Displayed optimal route, user feedback

[0936] Output: Feedback information resent to the server

[0937] Step 9:

[0938] The server recalculates the route based on the user's feedback, generates a new optimal route, and notifies the user.

[0939] Input: User feedback information

[0940] Output: Newly recalculated optimal route information

[0941] 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.

[0942] A system for implementing this invention calculates an optimal route based on the departure point, destination, constraints, and places to visit set by the user, and also uses an emotion engine that recognizes the user's emotions, and suggests the route to the user. This system is realized via communication between a server and a terminal. A specific embodiment of the system is described below.

[0943] User Input

[0944] The user launches the application on the terminal and enters the following information:

[0945] 1. Enter your departure and destination.

[0946] Example: Departure point "Home", destination "Tokyo Tower"

[0947] 2. Enter the constraints.

[0948] Time it takes: Within 1 hour

[0949] Acceptable toll: Expressway tolls under 1,000 yen

[0950] 3. Enter the location you want to visit and a specific arrival time.

[0951] Example: Places to visit: "△△ Park", "◇◇ Cafe", "Arrive at Tokyo Tower at 4:00 PM"

[0952] User Emotion Recognition

[0953] The device's built-in emotion engine analyzes the user's emotions in real time and determines their current emotional state based on their facial expressions, voice, and text input.

[0954] 1. Collect emotional data

[0955] The emotion engine collects information while the user is using the application.

[0956] Example: Judging whether a user is "having fun" or "tired" from their facial expression.

[0957] Sending data

[0958] The device formats the input data and emotion data and sends them to the server in JSON format or an appropriate data format.

[0959] example:

[0960] {

[0961] "Origin": "Home",

[0962] "Destination": "Tokyo Tower",

[0963] "Time Constraint": 60,

[0964] "Constraint Fee": 1000,

[0965] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[0966] "Arrival time": "16:00",

[0967] "emotion": {

[0968] "Status": "Having fun",

[0969] "Strength": 0.8

[0970] }

[0971] }

[0972] Server processing

[0973] The server receives the data sent from the terminal and performs the following processing.

[0974] 1. Analysis of received data

[0975] The server analyzes the received data and checks whether each piece of information has been entered correctly.

[0976] 2. Calculating the optimal route

[0977] The server generates multiple routes and calculates the travel time and cost for each route.

[0978] The server selects a route that fits within the time and cost constraints based on the user's constraints.

[0979] 3. Coordinating visit times

[0980] The server predicts the amount of time spent at desired destinations and streamlines the overall route.

[0981] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[0982] 4. Considering Emotional Data

[0983] The server adjusts the route based on the user's emotional state. For example, if the user is "having fun," it will suggest a route that takes a slightly longer route and passes through more enjoyable places, while if the user is "tired," it will prioritize the shortest route.

[0984] Sending and displaying results

[0985] The server sends the optimal route and emotion-based adjustment results data to the device. The device displays the received data to the user. The specific display content is as follows:

[0986] The best route from your starting point to your destination

[0987] Detailed directions on the map

[0988] Places visited along the way and duration of stay

[0989] Total travel time and estimated fare

[0990] Sentiment-based route recommendations

[0991] User Review and Feedback

[0992] 1. The user checks the route displayed.

[0993] 2. If there are any further corrections the user would like to make, enter their feedback.

[0994] Example: "I'd like to go to Restaurant ☆☆ instead of Cafe ◇◇."

[0995] 3. The device sends the feedback to the server again, and the server reflects the feedback and recalculates a new optimal route.

[0996] 4. The recalculated route is re-notified and displayed to the user.

[0997] In this way, a system is realized that can effectively provide an optimal route within a time and budget set by the user, taking into account the emotional state of the user.

[0998] The processing flow will be explained below.

[0999] Step 1:

[1000] The user starts the application on the terminal and inputs the departure point and destination.

[1001] The user inputs constraints (amount of time that can be spent, a fee).

[1002] The user inputs the location they wish to visit and a specific arrival time.

[1003] Example: Departure point "Home", destination "Tokyo Tower", time constraint "within 1 hour", toll constraint "highway toll less than 1,000 yen", visit locations "△△ Park", "◇◇ Cafe", arrival time "4:00 PM"

[1004] Step 2:

[1005] The terminal formats the input data and sends it to the server in JSON format.

[1006] The terminal sends the input data to the server.

[1007] example:

[1008] {

[1009] "Origin": "Home",

[1010] "Destination": "Tokyo Tower",

[1011] "Time Constraint": 60,

[1012] "Constraint Fee": 1000,

[1013] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[1014] "Arrival time": "16:00"

[1015] }

[1016] Step 3:

[1017] The emotion engine analyzes the user's emotions and understands their current emotional state.

[1018] The device collects emotional data from the user's facial expressions, voice, text input, etc.

[1019] Example: An emotion engine determines whether a user is "happy" or "tired" based on their facial expression.

[1020] Step 4:

[1021] The device analyzes the emotion data and transmits it to the server along with the starting point, destination, constraints, and places to be visited.

[1022] example:

[1023] {

[1024] "Origin": "Home",

[1025] "Destination": "Tokyo Tower",

[1026] "Time Constraint": 60,

[1027] "Constraint Fee": 1000,

[1028] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[1029] "Arrival time": "16:00",

[1030] "emotion": {

[1031] "Status": "Having fun",

[1032] "Strength": 0.8

[1033] }

[1034] }

[1035] Step 5:

[1036] The server receives and analyzes the data sent from the terminal.

[1037] The server verifies the integrity of each piece of information and checks for missing or incorrect information.

[1038] Step 6:

[1039] The server generates multiple candidate routes from the origin to the destination.

[1040] Calculate travel time and cost for the candidate routes.

[1041] Step 7:

[1042] The server incorporates the places the user wants to visit into the proposed route and reconstructs the route.

[1043] Add the estimated time spent at the places the user has specified to visit.

[1044] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[1045] Step 8:

[1046] The server evaluates each candidate route to see if it satisfies the constraints.

[1047] The route with the highest rating is selected from among the routes that satisfy the criteria.

[1048] Step 9:

[1049] The server takes into account the user's emotional state and adjusts the selected route.

[1050] For example, if you are "having fun," prioritize routes that include many tourist spots, and if you are "tired," prioritize the shortest route.

[1051] Step 10:

[1052] The server transmits the optimized route data to the terminal.

[1053] Step 11:

[1054] The terminal analyzes the optimum route data received from the server and displays it to the user.

[1055] The display includes detailed route information, places to visit and duration, total travel time, estimated fare, and more.

[1056] Step 12:

[1057] The user checks the displayed route and provides feedback on any corrections needed, if necessary.

[1058] The user inputs any parts that he / she wants to further correct as feedback.

[1059] Example: "I'd like to go to Restaurant ☆☆ instead of Cafe ◇◇."

[1060] Step 13:

[1061] The terminal transmits the user's feedback to the server again.

[1062] Step 14:

[1063] The server receives the feedback and recalculates based on the new conditions.

[1064] The recalculated route is retransmitted to the terminal.

[1065] Step 15:

[1066] The device displays the new optimal route to the user for final confirmation.

[1067] In this way, a system is realized that can effectively provide an optimal route within a time and budget set by the user, taking into account the emotional state of the user.

[1068] Example 2

[1069] 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."

[1070] Conventional route guidance systems calculate routes based on static information such as the departure point, destination, constraints, and places to visit, but are unable to provide route guidance that takes the user's emotional state into account. As a result, route guidance is not flexible enough to reflect the user's mood or physical condition, which can sometimes compromise the user experience. To solve this problem, a system that proposes optimal routes that also take the user's emotional information into account is needed.

[1071] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for the user to input a start location and a destination location, a means for the user to input constraints, a means for the user to input places the user wants to visit along the way and the visiting time, a means for recognizing the user's emotions in real time, a means for receiving the input information and emotion information and calculating an optimal route, and a means for notifying the user of the calculated optimal route. This makes it possible to provide flexible and optimal route guidance that also takes the user's emotional state into consideration.

[1072] A "user" is an entity that uses the system to input information such as the departure point, destination, constraints, and places to visit.

[1073] The "start location" is the point where the user starts moving.

[1074] A "destination" is a location that the user ultimately wants to reach.

[1075] "Constraints" are restrictions set by the user, such as travel time and fare.

[1076] A "place to visit" is a location where the user wants to stop during their travels.

[1077] "Visit time" is the time when the user will arrive at the visit location specified by the user.

[1078] "Emotion" refers to a psychological state that is recognized in real time from the user's facial expression, voice, etc.

[1079] The "optimal route" is the route that is judged to be the most efficient, taking into account factors such as travel time from the departure point to the destination, fare, and availability of places to visit.

[1080] "Notification" is the act of showing the calculated optimal route to the user.

[1081] The system for implementing this invention calculates the optimal route based on the starting point, destination, constraints, and places to visit set by the user, and further uses an emotion engine that recognizes the user's emotions, and proposes the route to the user. Specific embodiments of this system are described below.

[1082] First, the user launches the application on their device and inputs their starting location and destination. For example, they input "home" as the starting point and "Tokyo Tower" as the destination. Next, the user inputs constraints such as the amount of time and cost they are willing to spend. For example, they can set the required time to "within one hour" and the cost to "highway toll under 1,000 yen." Next, they input the places they want to visit and a specific arrival time. They can set "△△ Park" or "◇◇ Cafe" as places to visit and "arrive at 4:00 p.m." as the destination.

[1083] Furthermore, the emotion engine installed in the device analyzes the user's emotions in real time. The emotion engine determines the user's current emotional state based on the user's facial expressions, voice, and text input. For example, it can determine whether the user is "enjoyed" or "tired" based on the user's facial expressions. This emotional data is sensed and collected by the device.

[1084] The device formats the user's input data and emotion data and sends them to the server in JSON format or an appropriate data format.

[1085] {

[1086] "Origin": "Home",

[1087] "Destination": "Tokyo Tower",

[1088] "Time Constraint": 60,

[1089] "Constraint Fee": 1000,

[1090] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[1091] "Arrival time": "16:00",

[1092] "emotion": {

[1093] "Status": "Having fun",

[1094] "Strength": 0.8

[1095] }

[1096] }

[1097] Data like this is sent.

[1098] Next, the server receives the data sent from the terminal. After receiving the data, the server analyzes it and verifies that each piece of information has been entered correctly. The server then generates multiple routes and calculates the travel time and cost for each route. Based on the user's constraints, the server selects a route that fits within the time and cost constraints. Furthermore, the server predicts the length of stay at desired destinations and streamlines the overall route. For example, it may adjust the route to "Home → △△ Park (30-minute stay) → ◇◇ Cafe (20-minute stay) → Tokyo Tower (arrive at 4:00 p.m.)."

[1099] The server also adjusts the route based on the user's emotional state: for example, if the user is "having fun," it suggests a route that takes them through more enjoyable places, while if the user is "tired," it prioritizes the shortest route.

[1100] Finally, the server sends the optimal route and emotion-based adjustment results data to the device, which then displays the received data to the user. The display includes the optimal route from the origin to the destination, detailed directions on a map, stops along the way and their duration, total travel time and estimated fare, and an explanation of the emotion-based recommended route.

[1101] The user checks the displayed route and enters feedback if there are any parts they would like to correct. For example, if the user enters feedback such as "I would like to go to Restaurant ☆☆ instead of Cafe ◇◇," the device will send this to the server again. The server will reflect this feedback, recalculate a new optimal route, and notify and display it to the user again.

[1102] In this way, a system is realized that can effectively provide an optimal route within a time and budget set by the user, taking into account the emotional state of the user.

[1103] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1104] Step 1:

[1105] The user launches the application on their device and inputs the starting location, destination location, constraints, and places and times to visit. These inputs are saved on the device and used for subsequent data processing. For example, if a user inputs "home" as the starting point, "Tokyo Tower" as the destination, "within 1 hour" and "highway toll under 1,000 yen" as constraints, and "△△ Park," "◇◇ Cafe," and "arrive at Tokyo Tower at 4 p.m." as places to visit, the device will save this information as structured data.

[1106] input:

[1107] Start location, destination location, constraints, visit locations and visit times

[1108] output:

[1109] Structured Input Data

[1110] Step 2:

[1111] The emotion engine installed in the device recognizes the user's emotions in real time based on the user's facial expressions, voice, and text input. The emotion engine uses image recognition and voice analysis technologies to evaluate the user's state and generate corresponding emotion data. Specifically, analysis is performed using a camera and microphone, and the results are output as "enjoyed" or "tired," etc.

[1112] input:

[1113] User facial expressions, voice, and text input

[1114] output:

[1115] Real-time sentiment data

[1116] Step 3:

[1117] The device formats the user's input data and emotion data and sends them to the server in JSON format or other appropriate data format, where they are prepared for analysis.

[1118] input:

[1119] Structured input data, real-time sentiment data

[1120] output:

[1121] JSON format data to send to the server

[1122] Step 4:

[1123] The server receives and analyzes the data sent from the terminal. The received data includes the starting location, destination location, constraints, visited locations, visiting time, and emotion data. The server interprets this data and checks whether each piece of information has been entered correctly.

[1124] input:

[1125] JSON format data

[1126] output:

[1127] Analyzed data

[1128] Step 5:

[1129] The server generates multiple routes based on the analyzed data and calculates the travel time and fare for each route. Taking into account the user's constraints, it selects a route that fits within the time and fare constraints. The data is calculated using a route optimization algorithm using a map database and route information.

[1130] input:

[1131] Analyzed data

[1132] output:

[1133] Multiple calculated route candidates

[1134] Step 6:

[1135] The server predicts the amount of time spent at desired locations and optimizes the overall route. Taking into account the amount of time spent at each location, the server determines the optimal order of visits and stopovers. This allows for an efficient route that also takes into account the amount of time spent at each location.

[1136] input:

[1137] Multiple calculated route candidates

[1138] output:

[1139] Optimal route considering stay time

[1140] Step 7:

[1141] The server adjusts the route based on the user's emotional state. For example, if the user is "having fun," it will choose a route with a beautiful view, and if the user is "tired," it will choose the shortest route. Emotional data is also incorporated into the route calculation algorithm to generate optimal suggestions.

[1142] input:

[1143] Optimal route considering stay time, user emotion data

[1144] output:

[1145] Optimal route considering emotions

[1146] Step 8:

[1147] The server sends the calculated optimal route and emotion-based adjustment results data to the device, which then formats the results data and sends them back to the device in a format that is easy for the user to understand.

[1148] input:

[1149] Optimal route considering emotions

[1150] output:

[1151] Result data for display to the user

[1152] Step 9:

[1153] The device displays the data it receives to the user, including the optimal route from the departure point to the destination, detailed directions on a map, recommended routes based on locations visited along the way and their duration, total travel time and estimated fare, and sentiment. The information presented to the user allows them to review their travel plans in detail.

[1154] input:

[1155] Result data

[1156] output:

[1157] Optimal route and detailed information displayed to the user

[1158] Step 10:

[1159] The user checks the displayed route and inputs feedback if there are any corrections they would like to make. For example, they can input a request such as "I would like to go to Restaurant ☆☆ instead of Cafe ◇◇" into the device, and the device then sends this feedback data back to the server.

[1160] input:

[1161] User Feedback

[1162] output:

[1163] Feedback Data

[1164] Step 11:

[1165] The server recalculates a new optimal route based on the feedback and notifies the user again, with the new route suggestion adjusted to reflect the user's new preferences.

[1166] input:

[1167] Feedback Data

[1168] output:

[1169] Recalculated optimal route

[1170] In this way, we have created a system that proposes optimal routes that take the user's emotions into consideration through each step.

[1171] (Application example 2)

[1172] 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."

[1173] Current autonomous vehicle systems can calculate routes and provide driving instructions based on user settings, but they do not offer optimal route suggestions that take the user's emotional state into account. As a result, they are unable to flexibly respond to subtle changes in the user's emotions, which can lead to stress and frustration. The present invention aims to improve the user experience by calculating more personalized driving routes using user emotion recognition data and applying them to autonomous vehicles.

[1174] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input a start location and a destination location, means for the user to input constraints, means for the user to input places the user wants to visit along the way and the visiting time, means having a human emotion recognition engine for acquiring the user's emotional state, means for receiving the input information and emotional data and calculating an optimal route, means for notifying the user of the calculated optimal route, and means for transmitting driving instructions to the autonomously driven vehicle. This makes it possible to propose an optimal route and provide driving instructions that take the user's emotional state into consideration.

[1175] The "means for the user to input the starting point and the destination point" is an interface for the user to input the starting point and the destination point on the terminal.

[1176] The "means for the user to input constraints" is an interface for the user to input constraints such as time and cost during travel.

[1177] The "means for inputting the places the user wants to visit along the way and the time of visit" is an interface for inputting the places the user wants to stop at along the way and the time of arrival at those places.

[1178] A "human emotion recognition engine for acquiring a user's emotional state" is a system for acquiring emotional data in real time from a user's facial expressions, voice, etc.

[1179] The "means for receiving this input information and emotion data and calculating the optimal route" is a computer program for calculating the optimal travel route based on the information entered by the user and the acquired emotion data.

[1180] The "means for notifying the user of the calculated optimum route" is a communication means for notifying the user's terminal of the optimum route calculated by the server.

[1181] The "means for transmitting driving instructions to an autonomous vehicle" is a communication interface for transmitting driving instructions to an autonomous vehicle based on the calculated optimal route.

[1182] A system for implementing the present invention provides an optimal route for an autonomous vehicle that takes into account the emotional state of the user, and performs operational management. Detailed embodiments of this system will be described below.

[1183] User Input

[1184] The user enters the following information using a smartphone or vehicle interface:

[1185] 1. Origin and Destination

[1186] Example: Departure point "Home", destination "Tokyo Tower"

[1187] 2. Constraints

[1188] Example: Acceptable time: "within 1 hour", acceptable cost: "1,000 yen or less"

[1189] 3. The places you want to visit and the specific arrival time

[1190] Example: Visit locations: "△△ Park", "◇◇ Cafe", destination: "Arrival at 4:00 PM"

[1191] User Emotion Recognition

[1192] The device's built-in emotion engine analyzes the user's emotional state in real time. This emotion engine uses emotion recognition software such as "EmotionEngine" to determine the user's current emotional state based on facial expressions, voice, and text input.

[1193] Example: Judging whether a user is "having fun" or "tired" from their facial expression.

[1194] Sending data

[1195] The device formats the input data and emotion data and sends them to the server in JSON format or an appropriate data format, such as the following:

[1196] example:

[1197] json

[1198] {

[1199] "Origin": "Home",

[1200] "Destination": "Tokyo Tower",

[1201] "Time Constraint": 60,

[1202] "Constraint Fee": 1000,

[1203] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[1204] "Arrival time": "16:00",

[1205] "emotion": {

[1206] "Status": "Having fun",

[1207] "Strength": 0.8

[1208] }

[1209] }

[1210] Server processing

[1211] The server analyzes the received data and performs the following processing.

[1212] 1. Analysis of received data

[1213] Check that the data is entered correctly.

[1214] 2. Calculating the optimal route

[1215] Generate multiple routes and calculate the travel time and cost for each route.

[1216] The route with the highest evaluation within the constraints is selected.

[1217] 3. Coordinating visit times

[1218] Predict the amount of time spent at desired destinations and streamline the overall route.

[1219] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[1220] 4. Considering Emotional Data

[1221] The system adjusts the route based on the user's emotional state. For example, if the user is "having fun," it suggests a route that takes a slightly longer route and passes through more enjoyable places. If the user is "tired," it prioritizes the shortest route.

[1222] Sending and displaying results

[1223] The server sends the calculated optimal route information to the terminal, where the user can check the information through their smartphone or vehicle interface.

[1224] What it shows: The best route from origin to destination, stops along the way and duration, total travel time and estimated cost, and a sentiment-based explanation of the recommended route

[1225] Commanding autonomous vehicles

[1226] Based on the optimal route selected by the server, the autonomous vehicle will send driving instructions, which the autonomous vehicle will then follow to begin driving.

[1227] Specific prompt examples

[1228] The optimal route is calculated by inputting the following prompt sentence into the generative AI model:

[1229] markdown

[1230] You are the operator of a self-driving vehicle. Using the following information, provide the optimal route taking into account the user's specified conditions and emotional state:

[1231] Starting point: Home

[1232] Destination: Tokyo Tower

[1233] Constraints:

[1234] Time: 60 minutes or less

[1235] Price: Under 1,000 yen

[1236] Visited location: △△ Park, ◇◇ Cafe

[1237] Arrival time: 16:00

[1238] Emotional State: Enjoying (Intensity: 0.8)

[1239] Use this information to calculate the best route and suggest it to the user.

[1240] The above clearly shows how the system embodying the present invention operates in concrete terms.

[1241] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1242] Step 1: The user enters input information into the terminal

[1243] The user inputs the starting point, destination, constraints (such as time constraints and fare constraints), places to visit, and arrival time through the interface on the terminal. The user's input data is temporarily stored inside the terminal.

[1244] Input: Start point, Destination point, Constraints, Visit locations, Arrival time

[1245] Output: Saved user input data

[1246] Step 2: Collect user emotion data with an emotion recognition engine

[1247] The device's built-in emotion recognition engine analyzes the user's facial expressions, voice, and text input in real time to understand the user's emotional state. The necessary emotional data is extracted and stored on the device.

[1248] Input: User facial expression data, voice data, text input

[1249] Output: Emotion data (e.g., enjoying, intensity 0.8)

[1250] Step 3: Send input data and emotion data to the server

[1251] The device formats the user's input data and emotion data, converts it into an appropriate data format such as JSON, and sends it to the server.

[1252] Input: User input data, emotion data

[1253] Output: Formatted JSON data sent to the server

[1254] Step 4: The server parses the received data

[1255] The server analyzes the received data and checks its accuracy: it verifies that the starting point, destination, constraints, visit locations, arrival time, and emotional state are entered correctly.

[1256] Input: JSON data received by the server

[1257] Output: Parsed input data and sentiment data

[1258] Step 5: The server calculates the optimal route

[1259] The server generates multiple routes based on the analyzed input data and emotion data, calculates the travel time and cost for each route, and selects the route with the highest rating based on the user's constraints and emotional state.

[1260] Input: Parsed input data, emotion data

[1261] Output: Optimal route

[1262] Step 6: Adjust the time spent at each location

[1263] The server predicts the time spent at the places the user has designated to visit, and adjusts the overall route to make it more efficient.

[1264] Input: Visit location information, arrival time, constraints

[1265] Output: Adjusted itinerary

[1266] Step 7: The server sends the calculated route information to the terminal.

[1267] The server organizes the calculated and adjusted optimal route information and sends it to the terminal, where it is converted into an optimal format for the user to quickly check.

[1268] Input: Optimal route

[1269] Output: The organized route information is sent to the terminal.

[1270] Step 8: The device displays the route information to the user, and the user confirms it.

[1271] The device displays the optimal route information sent from the server to the user, who can then check it via their smartphone or in-car interface and make any necessary corrections.

[1272] Input: Organized route information

[1273] Output: Route information displayed to the user

[1274] Step 9: Send driving instructions to the autonomous vehicle

[1275] The server sends driving instructions to the autonomous vehicle based on the optimal route, and the autonomous vehicle then begins driving along the specified route.

[1276] Input: Optimal route instructions

[1277] Output: Driving instructions are sent to the autonomous vehicle.

[1278] 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.

[1279] 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.

[1280] 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.

[1281] [Third embodiment]

[1282] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1283] 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.

[1284] 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).

[1285] 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.

[1286] 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.

[1287] 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).

[1288] 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.

[1289] 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.

[1290] 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.

[1291] 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.

[1292] 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.

[1293] 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."

[1294] A system for implementing this invention calculates and proposes an optimal route to a user based on a starting point, destination, constraints, and places to visit set by the user. This system is realized through communication between a server and a terminal. A specific embodiment of the system is described below.

[1295] User Input

[1296] The user launches the application on the terminal and enters the following information:

[1297] 1. Enter your departure and destination.

[1298] Example: Departure point "Home", destination "Tokyo Tower"

[1299] 2. Enter the constraints.

[1300] Time it takes: Within 1 hour

[1301] Acceptable toll: Expressway tolls under 1,000 yen

[1302] 3. Enter the location you want to visit and a specific arrival time.

[1303] Example: Places to visit: "△△ Park", "◇◇ Cafe", "Arrive at Tokyo Tower at 4:00 PM"

[1304] Sending data

[1305] The terminal sends this input information to the server. The sent data is in the following format:

[1306] json

[1307] {

[1308] "Origin": "Home",

[1309] "Destination": "Tokyo Tower",

[1310] "Time Constraint": 60,

[1311] "Constraint Fee": 1000,

[1312] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[1313] "Arrival time": "16:00"

[1314] }

[1315] Server processing

[1316] The server receives the data sent from the terminal and performs the following processing.

[1317] 1. Analysis of received data

[1318] The server analyzes the received data and checks whether each piece of information has been entered correctly.

[1319] 2. Calculating the optimal route

[1320] The server generates multiple routes and calculates the travel time and cost for each route.

[1321] The server selects a route that fits within the time and cost constraints based on the user's constraints.

[1322] 3. Coordinating visit times

[1323] The server predicts the amount of time spent at desired destinations and streamlines the overall route.

[1324] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[1325] Sending and displaying results

[1326] The server sends the optimal route data to the terminal. The terminal displays the received data to the user. The specific display contents are as follows:

[1327] The best route from your starting point to your destination

[1328] Detailed directions on the map

[1329] Places visited along the way and duration of stay

[1330] Total travel time and estimated fare

[1331] User Review and Feedback

[1332] 1. The user checks the route displayed.

[1333] 2. If there are any further corrections the user would like to make, enter their feedback.

[1334] Example: "I'd like to go to Restaurant ☆☆ instead of Cafe ◇◇."

[1335] 3. The device sends the feedback to the server again, and the server reflects the feedback and recalculates a new optimal route.

[1336] 4. The recalculated route is re-notified and displayed to the user.

[1337] In this way, a system is realized that can effectively provide the optimal route within the time and budget set by the user.

[1338] The processing flow will be explained below.

[1339] Step 1:

[1340] The user starts the application on the terminal and inputs the departure point and destination.

[1341] The user inputs constraints (amount of time that can be spent, a fee).

[1342] The user inputs the location they wish to visit and a specific arrival time.

[1343] Step 2:

[1344] The terminal formats the user's input data and sends it to the server in JSON format or an appropriate data format.

[1345] example:

[1346] {

[1347] "Origin": "Home",

[1348] "Destination": "Tokyo Tower",

[1349] "Time Constraint": 60,

[1350] "Constraint Fee": 1000,

[1351] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[1352] "Arrival time": "16:00"

[1353] }

[1354] Step 3:

[1355] The server receives the data sent from the terminal and analyzes the received data.

[1356] The server checks the integrity of the data and makes sure there is no missing or incorrect information.

[1357] Step 4:

[1358] The server generates multiple candidate routes from the origin to the destination.

[1359] Calculate the travel time and cost for each candidate route.

[1360] Step 5:

[1361] The server incorporates the places the user wants to visit into the proposed route and reconstructs the route.

[1362] Add the estimated time spent at the places the user has specified to visit.

[1363] Step 6:

[1364] The server evaluates each candidate route to see if it satisfies the user's constraints (time, cost).

[1365] The route with the highest rating is selected from among the routes that satisfy the criteria.

[1366] Step 7:

[1367] The server sends the selected optimal route to the terminal in JSON format or other appropriate data format.

[1368] Step 8:

[1369] The terminal analyzes the optimum route data received from the server and displays it to the user.

[1370] The display includes detailed route information, time spent at each stop, total travel time, estimated fare, and more.

[1371] Step 9:

[1372] The user checks the displayed route and provides feedback on any corrections needed, if necessary.

[1373] Example: Enter "I want to go to Restaurant ☆☆ instead of Cafe ◇◇."

[1374] Step 10:

[1375] The terminal transmits the user's feedback to the server again.

[1376] Step 11:

[1377] The server receives the feedback and recalculates the optimal route based on the new conditions.

[1378] The server retransmits the recalculated route to the terminal.

[1379] Step 12:

[1380] The terminal displays the new optimal route to the user for final confirmation.

[1381] The above is the specific program processing flow in this system. By having the user, terminal, and server each fulfill their respective roles, the system can provide the optimal route within the time and budget set by the user.

[1382] Example 1

[1383] 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."

[1384] Conventional route calculation systems lack the functionality to verify the accuracy and completeness of data when calculating the optimal route based on multiple visit locations, arrival times, and constraints specified by the user. Furthermore, they are unable to efficiently select the optimal route and notify the user. As a result, users may not be satisfied with the route plan provided, which can be inconvenient.

[1385] 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.

[1386] In this invention, the server includes a means for the user to input a starting location and a destination location, a means for the user to input constraints, and a means for the user to input locations that the user wants to visit along the way and the visiting times.

[1387] 1. Efficiently select the optimal route based on constraints by verifying the accuracy and completeness of the data format of input information received from the user, generating multiple routes, and calculating the travel time and fare for each route;

[1388] 2. By providing a means to notify the user of the data on the selected optimal route, it becomes possible to present the optimal route.

[1389] This system allows users to easily receive efficient route plans based on specified destinations and constraints, providing a comfortable travel experience.

[1390] "Means for the user to input the starting location and destination" refers to an interface or function that allows the user to input information about the departure point and destination into the terminal.

[1391] "Means for users to input constraints" refers to interfaces and functions that allow users to input constraints such as travel time and travel costs into a terminal.

[1392] "Means for inputting the places the user wishes to visit along the way and the time of the visit" refers to an interface or function that allows the user to input the places the user wishes to visit and the time of arrival at them into the terminal.

[1393] "Means for receiving this input information and verifying the accuracy and completeness of the data format" refers to the function by which the server receives data sent from the terminal and verifies that the data is in the correct format and contains all the required information.

[1394] "Means for generating multiple routes and calculating the required time and cost for each route" refers to a function in which the server generates multiple candidates for efficient travel routes and calculates the required time and travel cost for each.

[1395] "Means for selecting the optimal route based on constraints" refers to a function that selects the most suitable route from the generated routes based on constraints such as time and fare set by the user.

[1396] "Means for notifying the user of data on the selected optimal route" refers to the function of sending information on the optimal route selected by the server to the terminal and notifying the user of its contents.

[1397] "Means for receiving feedback entered by the user, recalculating a new optimal route, and notifying the user again" refers to a function in which the server receives feedback information re-entered from the terminal, recalculates a new optimal route based on that information, and notifies the user again of the results.

[1398] A system for implementing this invention calculates an optimal route based on a starting location, a destination location, constraints, and places to visit set by a user, and proposes the route to the user. This system is realized through communication between a server and a terminal. Specific embodiments of the system are described below.

[1399] User Input

[1400] The user launches the application on the device and enters the following data:

[1401] 1. Starting and Destination Locations

[1402] Example: Start location "Home", destination location "Landmark"

[1403] 2. Constraints

[1404] Travel time: Less than 2 hours

[1405] Travel cost: Under 500 yen

[1406] 3. Places you want to visit and desired arrival time

[1407] Example: Visit locations: "Park", "Cafe", "Arrive at Landmark at 6pm"

[1408] Sending data

[1409] The device sends these inputs to the server, which structure the data as follows:

[1410] json

[1411] {

[1412] "Start Location": "Home",

[1413] "Destination": "Landmark",

[1414] "Time Constraint": 120,

[1415] "Constraint Fee": 500,

[1416] "visited place": ["park", "cafe"],

[1417] "Arrival time": "18:00"

[1418] }

[1419] Server analysis and processing

[1420] The server analyzes the data received from the device, verifies the accuracy and completeness of each piece of information, and then performs the following steps:

[1421] 1. Calculating the optimal route

[1422] The server generates multiple routes and calculates the travel time and cost for each route, using external services such as the Google Maps API.

[1423] Select the optimal route based on constraints.

[1424] 2. Coordinating visit times

[1425] The server takes into account the time spent at each desired visit location and efficiently adjusts the overall visit route.

[1426] Example: "Home → Park (stay 30 minutes) → Cafe (stay 30 minutes) → Landmark (arrive at 6pm)"

[1427] Sending and displaying results

[1428] The server sends the optimal route data in JSON format to the device. The device displays the received data to the user. The display contents are as follows:

[1429] The best route from the starting point to the destination

[1430] Detailed directions on the map

[1431] Places visited and duration of stay

[1432] Total travel time and estimated fare

[1433] User Review and Feedback

[1434] 1. The user checks the route

[1435] The user checks the route displayed.

[1436] 2. Enter your feedback

[1437] If the user is not satisfied with the route, he or she enters feedback.

[1438] Example: "I'd rather go to a different establishment than a cafe."

[1439] 3. Send feedback and recalculate

[1440] The device sends feedback to the server, which recalculates a new optimal route and sends it again.

[1441] Specific examples and prompts for generative AI models

[1442] For example, given the following user input:

[1443] Starting Location: Home

[1444] Destination: Landmark

[1445] Time limit: 2 hours

[1446] Restricted price: 500 yen or less

[1447] Places visited: parks, cafes

[1448] Desired arrival time: 18:00

[1449] Example prompts for generative AI models:

[1450] Please suggest the best route based on the following criteria:

[1451] 1. Starting location: Home

[1452] 2. Destination: Landmark

[1453] 3. Travel time: Within 2 hours

[1454] 4. Travel cost: Under 500 yen

[1455] 5. Places visited: parks, cafes

[1456] 6. Desired arrival time: Arrive at the landmark at 18:00

[1457] This system provides optimal route planning based on the places to visit and constraints specified by the user, thereby improving travel efficiency.

[1458] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1459] Step 1: User Input

[1460] This is a procedure in which a user starts an application on a terminal and inputs the starting location, destination location, constraints, visit locations, and visit time. The input information is structured in the following format.

[1461] Input: "Home" (starting location), "Landmark" (destination location), travel time within 120 minutes, travel fare within 500 yen, visit locations "park, cafe", arrival time "18:00"

[1462] Output: Structured data (e.g. JSON)

[1463] Step 2: Sending data

[1464] This is the procedure by which the terminal sends data entered by the user to the server. The HTTP protocol is used for communication, and structured data is sent in JSON format.

[1465] Input: Structured data (e.g. JSON)

[1466] Output: Data sent

[1467] Step 3: Data analysis by the server

[1468] This is the procedure in which the server analyzes the data received from the terminal and checks the accuracy and completeness of the data format. The analysis results are checked to see if all necessary information is included and if the data format is correct.

[1469] Input: Submitted data (e.g. JSON)

[1470] Data processing: Checking data format and information integrity

[1471] Output: Analysis results (data format and information integrity check)

[1472] Step 4: Calculate the optimal route

[1473] This is the procedure where the server generates multiple routes based on the received data and calculates the required time and fare for each route. Route generation and calculations are performed using an external map API (e.g., Google Maps API).

[1474] Input: Parsed data

[1475] Data processing: Route generation, travel time and fare calculation (using map API)

[1476] Output: Multiple candidate routes and their respective travel times and fares

[1477] Step 5: Selecting the optimal route

[1478] This is a procedure in which the server selects the optimal route from multiple generated routes that meets the user's constraints (time and cost). The most suitable route is selected based on evaluation criteria.

[1479] Input: Multiple candidate routes and their respective travel times and fares

[1480] Data calculation: Evaluation of candidate routes, selection of optimal route

[1481] Output: Optimal route

[1482] Step 6: Arrange visit times

[1483] This is a procedure in which the server further adjusts the optimal route, taking into account the time spent at desired destinations. It predicts the time spent at each destination and creates an overall travel schedule.

[1484] Input: Optimal route

[1485] Data calculation: Prediction of stay time, adjustment of travel schedule

[1486] Output: Optimal schedule (e.g., home → park (30 min stay) → cafe (30 min stay) → landmark)

[1487] Step 7: Send and view results

[1488] This is the procedure where the server sends the adjusted optimal route and schedule to the terminal in JSON format. The terminal displays the received information to the user.

[1489] Input: Optimal schedule and route

[1490] Output: Results displayed to the user (map, directions, duration, travel time, estimated fare)

[1491] Step 8: User review and feedback

[1492] This is the procedure where the user checks the displayed route and inputs feedback if necessary. If the user inputs a new request, the terminal sends the feedback to the server, which then recalculates.

[1493] Input: User feedback (e.g., "I'd rather go to a different establishment than the cafe")

[1494] Data processing: receiving feedback and recalculating

[1495] Output: New recalculated optimal route and schedule

[1496] In this way, the entire system is able to efficiently process user requests and provide optimal routes and schedules.

[1497] (Application example 1)

[1498] 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."

[1499] In the food delivery industry, maximizing delivery efficiency and improving customer satisfaction requires a system that enables delivery personnel to efficiently and quickly select the optimal route. However, conventional systems have difficulty calculating the optimal delivery route taking into account traffic conditions, time constraints, and multiple destinations. This leads to delivery delays and inefficient routes, resulting in a decline in service quality.

[1500] 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.

[1501] In this invention, the server includes means for the user to input a start location and a destination location, means for the user to input constraints, means for the user to input places the user wants to visit along the way and the visiting time, means for receiving this input information and calculating an optimal route, means for notifying the user of the calculated optimal route, means for the delivery person to input the start location and destination location, means for inputting delivery constraints, means for calculating an optimal delivery route taking traffic information into account, and means for notifying the delivery person of the optimal delivery route. This allows the delivery person to quickly obtain optimal route information taking traffic conditions into account in real time and make deliveries efficiently.

[1502] A "user" is a person or entity who uses the system to input the starting location, destination location, constraints, places to visit, and so on.

[1503] "Starting location / destination location" means the starting location and destination location entered by the user.

[1504] "Constraints" refer to conditions such as time constraints and fare constraints that the user takes into account when calculating a route.

[1505] "Visiting place and visiting time" refers to the places the user wants to visit along the way and the estimated time of arrival at those places.

[1506] "Input information" refers to information provided by the user to the system regarding the starting location, destination location, constraints, visit locations and their arrival times.

[1507] "Optimal route" refers to the most efficient route calculated based on input information that satisfies the user's constraints.

[1508] The "means for notifying" refers to a method or device for transmitting information about the calculated optimal route to the user.

[1509] A "delivery person" is a person or entity that uses the system to calculate the optimal delivery route in order to perform food delivery operations.

[1510] "Delivery constraints" refer to conditions such as time constraints and traffic conditions related to delivery that are input by the delivery person.

[1511] "Traffic information" refers to dynamic data on current road congestion conditions, traffic regulations, etc.

[1512] "Optimal delivery route" refers to the most efficient delivery route for a delivery person, calculated taking into account delivery constraints and traffic information.

[1513] The system according to the present invention allows users and delivery personnel to efficiently calculate and select routes and propose optimal routes to their destinations. Specific embodiments of the system are described below.

[1514] 1. Program Generation

[1515] This system includes a program that calculates the optimal route based on user input information and notifies the delivery person of the optimal delivery route, taking into account real-time traffic information. The specific functions and processing of the system are shown below.

[1516] 2. System processing explanation

[1517] The server receives information about the starting location, destination location, constraints, visiting locations and visiting times input by the user through the terminal, which is required when the user sets up a specific delivery scenario.

[1518] The received data is first verified for accuracy. The server then generates multiple routes and calculates the travel time and cost for each. An algorithm is used to select the optimal route, taking into account time and cost constraints.

[1519] This optimal route calculation utilizes traffic information APIs (e.g., Google Maps API), which allows the calculation of optimal routes taking into account real-time traffic conditions, and provides highly accurate route information to delivery personnel.

[1520] The delivery person's device displays the optimal route information received from the server on a map application, enabling the delivery person to carry out their delivery work smoothly and efficiently.

[1521] 3. Examples of concrete examples and prompts

[1522] For example, if a delivery person needs to deliver from a "food delivery shop" to a "customer's address" within 30 minutes, the delivery person will enter the following information into the system:

[1523] Starting point: Food delivery shop

[1524] Destination: Customer address

[1525] Restrictions: Arrive within 30 minutes

[1526] Traffic conditions: Congested

[1527] Based on this information, the server calculates the optimal route as follows and notifies the delivery person:

[1528] Starting point → Main road → Customer address

[1529] Example prompt sentence:

[1530] "Calculate the quickest route and show me the route that will get me to my customer's address in under 30 minutes."

[1531] As described above, this system can significantly improve the efficiency of food delivery operations by calculating the optimal route based on information input by the user and delivery person and providing accurate route information in real time.

[1532] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1533] Step 1:

[1534] The user uses a terminal to input the starting location, destination location, constraints, places to visit, and visiting times.

[1535] Input: Start location, Destination location, Constraints, Visit locations and visit times

[1536] Output: Input information is sent from the device to the server.

[1537] Step 2:

[1538] The server analyzes the input information received from the terminal and verifies the accuracy and completeness of the format.

[1539] Input: Starting location, destination location, constraints, visit locations and visit times sent from the terminal

[1540] Output: Validated input information

[1541] Step 3:

[1542] Based on the information received by the server, multiple routes are generated and the required time and cost for each route are calculated.

[1543] Input: Validated input information, data from traffic information API

[1544] Output: Multiple route information (including travel time and fare)

[1545] Step 4:

[1546] The server selects the optimal route from multiple route information based on the user's constraints.

[1547] Input: Multiple route information, user constraints

[1548] Output: Optimal route

[1549] Step 5:

[1550] The server generates optimal route information and adjusts visit locations and times, taking into account real-time data such as traffic conditions as needed.

[1551] Input: Optimal route, data from traffic information API

[1552] Output: The adjusted optimal path

[1553] Step 6:

[1554] The server sends the adjusted optimal route information to the terminal.

[1555] Input: Adjusted optimal route

[1556] Output: Optimal route information displayed on the user's device

[1557] Step 7:

[1558] The optimal route information received by the user terminal is displayed on a map application and notified to the user.

[1559] Input: Adjusted optimal route information sent from the server

[1560] Output: Optimal route displayed on a map application

[1561] Step 8:

[1562] The user checks the displayed route and provides feedback if necessary, which is then sent back to the server.

[1563] Input: Displayed optimal route, user feedback

[1564] Output: Feedback information resent to the server

[1565] Step 9:

[1566] The server recalculates the route based on the user's feedback, generates a new optimal route, and notifies the user.

[1567] Input: User feedback information

[1568] Output: Newly recalculated optimal route information

[1569] 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.

[1570] A system for implementing this invention calculates an optimal route based on the departure point, destination, constraints, and places to visit set by the user, and also uses an emotion engine that recognizes the user's emotions, and suggests the route to the user. This system is realized via communication between a server and a terminal. A specific embodiment of the system is described below.

[1571] User Input

[1572] The user launches the application on the terminal and enters the following information:

[1573] 1. Enter your departure and destination.

[1574] Example: Departure point "Home", destination "Tokyo Tower"

[1575] 2. Enter the constraints.

[1576] Time it takes: Within 1 hour

[1577] Acceptable toll: Expressway tolls under 1,000 yen

[1578] 3. Enter the location you want to visit and a specific arrival time.

[1579] Example: Places to visit: "△△ Park", "◇◇ Cafe", "Arrive at Tokyo Tower at 4:00 PM"

[1580] User Emotion Recognition

[1581] The device's built-in emotion engine analyzes the user's emotions in real time and determines their current emotional state based on their facial expressions, voice, and text input.

[1582] 1. Collect emotional data

[1583] The emotion engine collects information while the user is using the application.

[1584] Example: Judging whether a user is "having fun" or "tired" from their facial expression.

[1585] Sending data

[1586] The device formats the input data and emotion data and sends them to the server in JSON format or an appropriate data format.

[1587] example:

[1588] {

[1589] "Origin": "Home",

[1590] "Destination": "Tokyo Tower",

[1591] "Time Constraint": 60,

[1592] "Constraint Fee": 1000,

[1593] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[1594] "Arrival time": "16:00",

[1595] "emotion": {

[1596] "Status": "Having fun",

[1597] "Strength": 0.8

[1598] }

[1599] }

[1600] Server processing

[1601] The server receives the data sent from the terminal and performs the following processing.

[1602] 1. Analysis of received data

[1603] The server analyzes the received data and checks whether each piece of information has been entered correctly.

[1604] 2. Calculating the optimal route

[1605] The server generates multiple routes and calculates the travel time and cost for each route.

[1606] The server selects a route that fits within the time and cost constraints based on the user's constraints.

[1607] 3. Coordinating visit times

[1608] The server predicts the amount of time spent at desired destinations and streamlines the overall route.

[1609] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[1610] 4. Considering Emotional Data

[1611] The server adjusts the route based on the user's emotional state. For example, if the user is "having fun," it will suggest a route that takes a slightly longer route and passes through more enjoyable places, while if the user is "tired," it will prioritize the shortest route.

[1612] Sending and displaying results

[1613] The server sends the optimal route and emotion-based adjustment results data to the device. The device displays the received data to the user. The specific display content is as follows:

[1614] The best route from your starting point to your destination

[1615] Detailed directions on the map

[1616] Places visited along the way and duration of stay

[1617] Total travel time and estimated fare

[1618] Sentiment-based route recommendations

[1619] User Review and Feedback

[1620] 1. The user checks the route displayed.

[1621] 2. If there are any further corrections the user would like to make, enter their feedback.

[1622] Example: "I'd like to go to Restaurant ☆☆ instead of Cafe ◇◇."

[1623] 3. The device sends the feedback to the server again, and the server reflects the feedback and recalculates a new optimal route.

[1624] 4. The recalculated route is re-notified and displayed to the user.

[1625] In this way, a system is realized that can effectively provide an optimal route within a time and budget set by the user, taking into account the emotional state of the user.

[1626] The processing flow will be explained below.

[1627] Step 1:

[1628] The user starts the application on the terminal and inputs the departure point and destination.

[1629] The user inputs constraints (amount of time that can be spent, a fee).

[1630] The user inputs the location they wish to visit and a specific arrival time.

[1631] Example: Departure point "Home", destination "Tokyo Tower", time constraint "within 1 hour", toll constraint "highway toll less than 1,000 yen", visit locations "△△ Park", "◇◇ Cafe", arrival time "4:00 PM"

[1632] Step 2:

[1633] The terminal formats the input data and sends it to the server in JSON format.

[1634] The terminal sends the input data to the server.

[1635] example:

[1636] {

[1637] "Origin": "Home",

[1638] "Destination": "Tokyo Tower",

[1639] "Time Constraint": 60,

[1640] "Constraint Fee": 1000,

[1641] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[1642] "Arrival time": "16:00"

[1643] }

[1644] Step 3:

[1645] The emotion engine analyzes the user's emotions and understands their current emotional state.

[1646] The device collects emotional data from the user's facial expressions, voice, text input, etc.

[1647] Example: An emotion engine determines whether a user is "happy" or "tired" based on their facial expression.

[1648] Step 4:

[1649] The device analyzes the emotion data and transmits it to the server along with the starting point, destination, constraints, and places to be visited.

[1650] example:

[1651] {

[1652] "Origin": "Home",

[1653] "Destination": "Tokyo Tower",

[1654] "Time Constraint": 60,

[1655] "Constraint Fee": 1000,

[1656] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[1657] "Arrival time": "16:00",

[1658] "emotion": {

[1659] "Status": "Having fun",

[1660] "Strength": 0.8

[1661] }

[1662] }

[1663] Step 5:

[1664] The server receives and analyzes the data sent from the terminal.

[1665] The server verifies the integrity of each piece of information and checks for missing or incorrect information.

[1666] Step 6:

[1667] The server generates multiple candidate routes from the origin to the destination.

[1668] Calculate travel time and cost for the candidate routes.

[1669] Step 7:

[1670] The server incorporates the places the user wants to visit into the proposed route and reconstructs the route.

[1671] Add the estimated time spent at the places the user has specified to visit.

[1672] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[1673] Step 8:

[1674] The server evaluates each candidate route to see if it satisfies the constraints.

[1675] The route with the highest rating is selected from among the routes that satisfy the criteria.

[1676] Step 9:

[1677] The server takes into account the user's emotional state and adjusts the selected route.

[1678] For example, if you are "having fun," prioritize routes that include many tourist spots, and if you are "tired," prioritize the shortest route.

[1679] Step 10:

[1680] The server transmits the optimized route data to the terminal.

[1681] Step 11:

[1682] The terminal analyzes the optimum route data received from the server and displays it to the user.

[1683] The display includes detailed route information, places to visit and duration, total travel time, estimated fare, and more.

[1684] Step 12:

[1685] The user checks the displayed route and provides feedback on any corrections needed, if necessary.

[1686] The user inputs any parts that he / she wants to further correct as feedback.

[1687] Example: "I'd like to go to Restaurant ☆☆ instead of Cafe ◇◇."

[1688] Step 13:

[1689] The terminal transmits the user's feedback to the server again.

[1690] Step 14:

[1691] The server receives the feedback and recalculates based on the new conditions.

[1692] The recalculated route is retransmitted to the terminal.

[1693] Step 15:

[1694] The device displays the new optimal route to the user for final confirmation.

[1695] In this way, a system is realized that can effectively provide an optimal route within a time and budget set by the user, taking into account the emotional state of the user.

[1696] Example 2

[1697] 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."

[1698] Conventional route guidance systems calculate routes based on static information such as the departure point, destination, constraints, and places to visit, but are unable to provide route guidance that takes the user's emotional state into account. As a result, route guidance is not flexible enough to reflect the user's mood or physical condition, which can sometimes compromise the user experience. To solve this problem, a system that proposes optimal routes that also take the user's emotional information into account is needed.

[1699] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for the user to input a start location and a destination location, a means for the user to input constraints, a means for the user to input places the user wants to visit along the way and the visiting time, a means for recognizing the user's emotions in real time, a means for receiving the input information and emotion information and calculating an optimal route, and a means for notifying the user of the calculated optimal route. This makes it possible to provide flexible and optimal route guidance that also takes the user's emotional state into consideration.

[1700] A "user" is an entity that uses the system to input information such as the departure point, destination, constraints, and places to visit.

[1701] The "start location" is the point where the user starts moving.

[1702] A "destination" is a location that the user ultimately wants to reach.

[1703] "Constraints" are restrictions set by the user, such as travel time and fare.

[1704] A "place to visit" is a location where the user wants to stop during their travels.

[1705] "Visit time" is the time when the user will arrive at the visit location specified by the user.

[1706] "Emotion" refers to a psychological state that is recognized in real time from the user's facial expression, voice, etc.

[1707] The "optimal route" is the route that is judged to be the most efficient, taking into account factors such as travel time from the departure point to the destination, fare, and availability of places to visit.

[1708] "Notification" is the act of showing the calculated optimal route to the user.

[1709] The system for implementing this invention calculates the optimal route based on the starting point, destination, constraints, and places to visit set by the user, and further uses an emotion engine that recognizes the user's emotions, and proposes the route to the user. Specific embodiments of this system are described below.

[1710] First, the user launches the application on their device and inputs their starting location and destination. For example, they input "home" as the starting point and "Tokyo Tower" as the destination. Next, the user inputs constraints such as the amount of time and cost they are willing to spend. For example, they can set the required time to "within one hour" and the cost to "highway toll under 1,000 yen." Next, they input the places they want to visit and a specific arrival time. They can set "△△ Park" or "◇◇ Cafe" as places to visit and "arrive at 4:00 p.m." as the destination.

[1711] Furthermore, the emotion engine installed in the device analyzes the user's emotions in real time. The emotion engine determines the user's current emotional state based on the user's facial expressions, voice, and text input. For example, it can determine whether the user is "enjoyed" or "tired" based on the user's facial expressions. This emotional data is sensed and collected by the device.

[1712] The device formats the user's input data and emotion data and sends them to the server in JSON format or an appropriate data format.

[1713] {

[1714] "Origin": "Home",

[1715] "Destination": "Tokyo Tower",

[1716] "Time Constraint": 60,

[1717] "Constraint Fee": 1000,

[1718] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[1719] "Arrival time": "16:00",

[1720] "emotion": {

[1721] "Status": "Having fun",

[1722] "Strength": 0.8

[1723] }

[1724] }

[1725] Data like this is sent.

[1726] Next, the server receives the data sent from the terminal. After receiving the data, the server analyzes it and verifies that each piece of information has been entered correctly. The server then generates multiple routes and calculates the travel time and cost for each route. Based on the user's constraints, the server selects a route that fits within the time and cost constraints. Furthermore, the server predicts the length of stay at desired destinations and streamlines the overall route. For example, it may adjust the route to "Home → △△ Park (30-minute stay) → ◇◇ Cafe (20-minute stay) → Tokyo Tower (arrive at 4:00 p.m.)."

[1727] The server also adjusts the route based on the user's emotional state: for example, if the user is "having fun," it suggests a route that takes them through more enjoyable places, while if the user is "tired," it prioritizes the shortest route.

[1728] Finally, the server sends the optimal route and emotion-based adjustment results data to the device, which then displays the received data to the user. The display includes the optimal route from the origin to the destination, detailed directions on a map, stops along the way and their duration, total travel time and estimated fare, and an explanation of the emotion-based recommended route.

[1729] The user checks the displayed route and enters feedback if there are any parts they would like to correct. For example, if the user enters feedback such as "I would like to go to Restaurant ☆☆ instead of Cafe ◇◇," the device will send this to the server again. The server will reflect this feedback, recalculate a new optimal route, and notify and display it to the user again.

[1730] In this way, a system is realized that can effectively provide an optimal route within a time and budget set by the user, taking into account the emotional state of the user.

[1731] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1732] Step 1:

[1733] The user launches the application on their device and inputs the starting location, destination location, constraints, and places and times to visit. These inputs are saved on the device and used for subsequent data processing. For example, if a user inputs "home" as the starting point, "Tokyo Tower" as the destination, "within 1 hour" and "highway toll under 1,000 yen" as constraints, and "△△ Park," "◇◇ Cafe," and "arrive at Tokyo Tower at 4 p.m." as places to visit, the device will save this information as structured data.

[1734] input:

[1735] Start location, destination location, constraints, visit locations and visit times

[1736] output:

[1737] Structured Input Data

[1738] Step 2:

[1739] The emotion engine installed in the device recognizes the user's emotions in real time based on the user's facial expressions, voice, and text input. The emotion engine uses image recognition and voice analysis technologies to evaluate the user's state and generate corresponding emotion data. Specifically, analysis is performed using a camera and microphone, and the results are output as "enjoyed" or "tired," etc.

[1740] input:

[1741] User facial expressions, voice, and text input

[1742] output:

[1743] Real-time sentiment data

[1744] Step 3:

[1745] The device formats the user's input data and emotion data and sends them to the server in JSON format or other appropriate data format, where they are prepared for analysis.

[1746] input:

[1747] Structured input data, real-time sentiment data

[1748] output:

[1749] JSON format data to send to the server

[1750] Step 4:

[1751] The server receives and analyzes the data sent from the terminal. The received data includes the starting location, destination location, constraints, visited locations, visiting time, and emotion data. The server interprets this data and checks whether each piece of information has been entered correctly.

[1752] input:

[1753] JSON format data

[1754] output:

[1755] Analyzed data

[1756] Step 5:

[1757] The server generates multiple routes based on the analyzed data and calculates the travel time and fare for each route. Taking into account the user's constraints, it selects a route that fits within the time and fare constraints. The data is calculated using a route optimization algorithm using a map database and route information.

[1758] input:

[1759] Analyzed data

[1760] output:

[1761] Multiple calculated route candidates

[1762] Step 6:

[1763] The server predicts the amount of time spent at desired locations and optimizes the overall route. Taking into account the amount of time spent at each location, the server determines the optimal order of visits and stopovers. This allows for an efficient route that also takes into account the amount of time spent at each location.

[1764] input:

[1765] Multiple calculated route candidates

[1766] output:

[1767] Optimal route considering stay time

[1768] Step 7:

[1769] The server adjusts the route based on the user's emotional state. For example, if the user is "having fun," it will choose a route with a beautiful view, and if the user is "tired," it will choose the shortest route. Emotional data is also incorporated into the route calculation algorithm to generate optimal suggestions.

[1770] input:

[1771] Optimal route considering stay time, user emotion data

[1772] output:

[1773] Optimal route considering emotions

[1774] Step 8:

[1775] The server sends the calculated optimal route and emotion-based adjustment results data to the device, which then formats the results data and sends them back to the device in a format that is easy for the user to understand.

[1776] input:

[1777] Optimal route considering emotions

[1778] output:

[1779] Result data for display to the user

[1780] Step 9:

[1781] The device displays the data it receives to the user, including the optimal route from the departure point to the destination, detailed directions on a map, recommended routes based on locations visited along the way and their duration, total travel time and estimated fare, and sentiment. The information presented to the user allows them to review their travel plans in detail.

[1782] input:

[1783] Result data

[1784] output:

[1785] Optimal route and detailed information displayed to the user

[1786] Step 10:

[1787] The user checks the displayed route and inputs feedback if there are any corrections they would like to make. For example, they can input a request such as "I would like to go to Restaurant ☆☆ instead of Cafe ◇◇" into the device, and the device then sends this feedback data back to the server.

[1788] input:

[1789] User Feedback

[1790] output:

[1791] Feedback Data

[1792] Step 11:

[1793] The server recalculates a new optimal route based on the feedback and notifies the user again, with the new route suggestion adjusted to reflect the user's new preferences.

[1794] input:

[1795] Feedback Data

[1796] output:

[1797] Recalculated optimal route

[1798] In this way, we have created a system that proposes optimal routes that take the user's emotions into consideration through each step.

[1799] (Application example 2)

[1800] 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."

[1801] Current autonomous vehicle systems can calculate routes and provide driving instructions based on user settings, but they do not offer optimal route suggestions that take the user's emotional state into account. As a result, they are unable to flexibly respond to subtle changes in the user's emotions, which can lead to stress and frustration. The present invention aims to improve the user experience by calculating more personalized driving routes using user emotion recognition data and applying them to autonomous vehicles.

[1802] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input a start location and a destination location, means for the user to input constraints, means for the user to input places the user wants to visit along the way and the visiting time, means having a human emotion recognition engine for acquiring the user's emotional state, means for receiving the input information and emotional data and calculating an optimal route, means for notifying the user of the calculated optimal route, and means for transmitting driving instructions to the autonomously driven vehicle. This makes it possible to propose an optimal route and provide driving instructions that take the user's emotional state into consideration.

[1803] The "means for the user to input the starting point and the destination point" is an interface for the user to input the starting point and the destination point on the terminal.

[1804] The "means for the user to input constraints" is an interface for the user to input constraints such as time and cost during travel.

[1805] The "means for inputting the places the user wants to visit along the way and the time of visit" is an interface for inputting the places the user wants to stop at along the way and the time of arrival at those places.

[1806] A "human emotion recognition engine for acquiring a user's emotional state" is a system for acquiring emotional data in real time from a user's facial expressions, voice, etc.

[1807] The "means for receiving this input information and emotion data and calculating the optimal route" is a computer program for calculating the optimal travel route based on the information entered by the user and the acquired emotion data.

[1808] The "means for notifying the user of the calculated optimum route" is a communication means for notifying the user's terminal of the optimum route calculated by the server.

[1809] The "means for transmitting driving instructions to an autonomous vehicle" is a communication interface for transmitting driving instructions to an autonomous vehicle based on the calculated optimal route.

[1810] A system for implementing the present invention provides an optimal route for an autonomous vehicle that takes into account the emotional state of the user, and performs operational management. Detailed embodiments of this system will be described below.

[1811] User Input

[1812] The user enters the following information using a smartphone or vehicle interface:

[1813] 1. Origin and Destination

[1814] Example: Departure point "Home", destination "Tokyo Tower"

[1815] 2. Constraints

[1816] Example: Acceptable time: "within 1 hour", acceptable cost: "1,000 yen or less"

[1817] 3. The places you want to visit and the specific arrival time

[1818] Example: Visit locations: "△△ Park", "◇◇ Cafe", destination: "Arrival at 4:00 PM"

[1819] User Emotion Recognition

[1820] The device's built-in emotion engine analyzes the user's emotional state in real time. This emotion engine uses emotion recognition software such as "EmotionEngine" to determine the user's current emotional state based on facial expressions, voice, and text input.

[1821] Example: Judging whether a user is "having fun" or "tired" from their facial expression.

[1822] Sending data

[1823] The device formats the input data and emotion data and sends them to the server in JSON format or an appropriate data format, such as the following:

[1824] example:

[1825] json

[1826] {

[1827] "Origin": "Home",

[1828] "Destination": "Tokyo Tower",

[1829] "Time Constraint": 60,

[1830] "Constraint Fee": 1000,

[1831] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[1832] "Arrival time": "16:00",

[1833] "emotion": {

[1834] "Status": "Having fun",

[1835] "Strength": 0.8

[1836] }

[1837] }

[1838] Server processing

[1839] The server analyzes the received data and performs the following processing.

[1840] 1. Analysis of received data

[1841] Check that the data is entered correctly.

[1842] 2. Calculating the optimal route

[1843] Generate multiple routes and calculate the travel time and cost for each route.

[1844] The route with the highest evaluation within the constraints is selected.

[1845] 3. Coordinating visit times

[1846] Predict the amount of time spent at desired destinations and streamline the overall route.

[1847] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[1848] 4. Considering Emotional Data

[1849] The system adjusts the route based on the user's emotional state. For example, if the user is "having fun," it suggests a route that takes a slightly longer route and passes through more enjoyable places. If the user is "tired," it prioritizes the shortest route.

[1850] Sending and displaying results

[1851] The server sends the calculated optimal route information to the terminal, where the user can check the information through their smartphone or vehicle interface.

[1852] What it shows: The best route from origin to destination, stops along the way and duration, total travel time and estimated cost, and a sentiment-based explanation of the recommended route

[1853] Commanding autonomous vehicles

[1854] Based on the optimal route selected by the server, the autonomous vehicle will send driving instructions, which the autonomous vehicle will then follow to begin driving.

[1855] Specific prompt examples

[1856] The optimal route is calculated by inputting the following prompt sentence into the generative AI model:

[1857] markdown

[1858] You are the operator of a self-driving vehicle. Using the following information, provide the optimal route taking into account the user's specified conditions and emotional state:

[1859] Starting point: Home

[1860] Destination: Tokyo Tower

[1861] Constraints:

[1862] Time: 60 minutes or less

[1863] Price: Under 1,000 yen

[1864] Visited location: △△ Park, ◇◇ Cafe

[1865] Arrival time: 16:00

[1866] Emotional State: Enjoying (Intensity: 0.8)

[1867] Use this information to calculate the best route and suggest it to the user.

[1868] The above clearly shows how the system embodying the present invention operates in concrete terms.

[1869] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1870] Step 1: The user enters input information into the terminal

[1871] The user inputs the starting point, destination, constraints (such as time constraints and fare constraints), places to visit, and arrival time through the interface on the terminal. The user's input data is temporarily stored inside the terminal.

[1872] Input: Start point, Destination point, Constraints, Visit locations, Arrival time

[1873] Output: Saved user input data

[1874] Step 2: Collect user emotion data with an emotion recognition engine

[1875] The device's built-in emotion recognition engine analyzes the user's facial expressions, voice, and text input in real time to understand the user's emotional state. The necessary emotional data is extracted and stored on the device.

[1876] Input: User facial expression data, voice data, text input

[1877] Output: Emotion data (e.g., enjoying, intensity 0.8)

[1878] Step 3: Send input data and emotion data to the server

[1879] The device formats the user's input data and emotion data, converts it into an appropriate data format such as JSON, and sends it to the server.

[1880] Input: User input data, emotion data

[1881] Output: Formatted JSON data sent to the server

[1882] Step 4: The server parses the received data

[1883] The server analyzes the received data and checks its accuracy: it verifies that the starting point, destination, constraints, visit locations, arrival time, and emotional state are entered correctly.

[1884] Input: JSON data received by the server

[1885] Output: Parsed input data and sentiment data

[1886] Step 5: The server calculates the optimal route

[1887] The server generates multiple routes based on the analyzed input data and emotion data, calculates the travel time and cost for each route, and selects the route with the highest rating based on the user's constraints and emotional state.

[1888] Input: Parsed input data, emotion data

[1889] Output: Optimal route

[1890] Step 6: Adjust the time spent at each location

[1891] The server predicts the time spent at the places the user has designated to visit, and adjusts the overall route to make it more efficient.

[1892] Input: Visit location information, arrival time, constraints

[1893] Output: Adjusted itinerary

[1894] Step 7: The server sends the calculated route information to the terminal.

[1895] The server organizes the calculated and adjusted optimal route information and sends it to the terminal, where it is converted into an optimal format for the user to quickly check.

[1896] Input: Optimal route

[1897] Output: The organized route information is sent to the terminal.

[1898] Step 8: The device displays the route information to the user, and the user confirms it.

[1899] The device displays the optimal route information sent from the server to the user, who can then check it via their smartphone or in-car interface and make any necessary corrections.

[1900] Input: Organized route information

[1901] Output: Route information displayed to the user

[1902] Step 9: Send driving instructions to the autonomous vehicle

[1903] The server sends driving instructions to the autonomous vehicle based on the optimal route, and the autonomous vehicle then begins driving along the specified route.

[1904] Input: Optimal route instructions

[1905] Output: Driving instructions are sent to the autonomous vehicle.

[1906] 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.

[1907] 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.

[1908] 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.

[1909] [Fourth embodiment]

[1910] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1911] 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.

[1912] 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).

[1913] 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.

[1914] 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.

[1915] 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).

[1916] 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.

[1917] 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.

[1918] 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.

[1919] 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.

[1920] 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.

[1921] 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.

[1922] 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."

[1923] A system for implementing this invention calculates and proposes an optimal route to a user based on a starting point, destination, constraints, and places to visit set by the user. This system is realized through communication between a server and a terminal. A specific embodiment of the system is described below.

[1924] User Input

[1925] The user launches the application on the terminal and enters the following information:

[1926] 1. Enter your departure and destination.

[1927] Example: Departure point "Home", destination "Tokyo Tower"

[1928] 2. Enter the constraints.

[1929] Time it takes: Within 1 hour

[1930] Acceptable toll: Expressway tolls under 1,000 yen

[1931] 3. Enter the location you want to visit and a specific arrival time.

[1932] Example: Places to visit: "△△ Park", "◇◇ Cafe", "Arrive at Tokyo Tower at 4:00 PM"

[1933] Sending data

[1934] The terminal sends this input information to the server. The sent data is in the following format:

[1935] json

[1936] {

[1937] "Origin": "Home",

[1938] "Destination": "Tokyo Tower",

[1939] "Time Constraint": 60,

[1940] "Constraint Fee": 1000,

[1941] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[1942] "Arrival time": "16:00"

[1943] }

[1944] Server processing

[1945] The server receives the data sent from the terminal and performs the following processing.

[1946] 1. Analysis of received data

[1947] The server analyzes the received data and checks whether each piece of information has been entered correctly.

[1948] 2. Calculating the optimal route

[1949] The server generates multiple routes and calculates the travel time and cost for each route.

[1950] The server selects a route that fits within the time and cost constraints based on the user's constraints.

[1951] 3. Coordinating visit times

[1952] The server predicts the amount of time spent at desired destinations and streamlines the overall route.

[1953] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[1954] Sending and displaying results

[1955] The server sends the optimal route data to the terminal. The terminal displays the received data to the user. The specific display contents are as follows:

[1956] The best route from your starting point to your destination

[1957] Detailed directions on the map

[1958] Places visited along the way and duration of stay

[1959] Total travel time and estimated fare

[1960] User Review and Feedback

[1961] 1. The user checks the route displayed.

[1962] 2. If there are any further corrections the user would like to make, enter their feedback.

[1963] Example: "I'd like to go to Restaurant ☆☆ instead of Cafe ◇◇."

[1964] 3. The device sends the feedback to the server again, and the server reflects the feedback and recalculates a new optimal route.

[1965] 4. The recalculated route is re-notified and displayed to the user.

[1966] In this way, a system is realized that can effectively provide the optimal route within the time and budget set by the user.

[1967] The processing flow will be explained below.

[1968] Step 1:

[1969] The user starts the application on the terminal and inputs the departure point and destination.

[1970] The user inputs constraints (amount of time that can be spent, a fee).

[1971] The user inputs the location they wish to visit and a specific arrival time.

[1972] Step 2:

[1973] The terminal formats the user's input data and sends it to the server in JSON format or an appropriate data format.

[1974] example:

[1975] {

[1976] "Origin": "Home",

[1977] "Destination": "Tokyo Tower",

[1978] "Time Constraint": 60,

[1979] "Constraint Fee": 1000,

[1980] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[1981] "Arrival time": "16:00"

[1982] }

[1983] Step 3:

[1984] The server receives the data sent from the terminal and analyzes the received data.

[1985] The server checks the integrity of the data and makes sure there is no missing or incorrect information.

[1986] Step 4:

[1987] The server generates multiple candidate routes from the origin to the destination.

[1988] Calculate the travel time and cost for each candidate route.

[1989] Step 5:

[1990] The server incorporates the places the user wants to visit into the proposed route and reconstructs the route.

[1991] Add the estimated time spent at the places the user has specified to visit.

[1992] Step 6:

[1993] The server evaluates each candidate route to see if it satisfies the user's constraints (time, cost).

[1994] The route with the highest rating is selected from among the routes that satisfy the criteria.

[1995] Step 7:

[1996] The server sends the selected optimal route to the terminal in JSON format or other appropriate data format.

[1997] Step 8:

[1998] The terminal analyzes the optimum route data received from the server and displays it to the user.

[1999] The display includes detailed route information, time spent at each stop, total travel time, estimated fare, and more.

[2000] Step 9:

[2001] The user checks the displayed route and provides feedback on any corrections needed, if necessary.

[2002] Example: Enter "I want to go to Restaurant ☆☆ instead of Cafe ◇◇."

[2003] Step 10:

[2004] The terminal transmits the user's feedback to the server again.

[2005] Step 11:

[2006] The server receives the feedback and recalculates the optimal route based on the new conditions.

[2007] The server retransmits the recalculated route to the terminal.

[2008] Step 12:

[2009] The terminal displays the new optimal route to the user for final confirmation.

[2010] The above is the specific program processing flow in this system. By having the user, terminal, and server each fulfill their respective roles, the system can provide the optimal route within the time and budget set by the user.

[2011] Example 1

[2012] 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."

[2013] Conventional route calculation systems lack the functionality to verify the accuracy and completeness of data when calculating the optimal route based on multiple visit locations, arrival times, and constraints specified by the user. Furthermore, they are unable to efficiently select the optimal route and notify the user. As a result, users may not be satisfied with the route plan provided, which can be inconvenient.

[2014] 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.

[2015] In this invention, the server includes a means for the user to input a starting location and a destination location, a means for the user to input constraints, and a means for the user to input locations that the user wants to visit along the way and the visiting times.

[2016] 1. Efficiently select the optimal route based on constraints by verifying the accuracy and completeness of the data format of input information received from the user, generating multiple routes, and calculating the travel time and fare for each route;

[2017] 2. By providing a means to notify the user of the data on the selected optimal route, it becomes possible to present the optimal route.

[2018] This system allows users to easily receive efficient route plans based on specified destinations and constraints, providing a comfortable travel experience.

[2019] "Means for the user to input the starting location and destination" refers to an interface or function that allows the user to input information about the departure point and destination into the terminal.

[2020] "Means for users to input constraints" refers to interfaces and functions that allow users to input constraints such as travel time and travel costs into a terminal.

[2021] "Means for inputting the places the user wishes to visit along the way and the time of the visit" refers to an interface or function that allows the user to input the places the user wishes to visit and the time of arrival at them into the terminal.

[2022] "Means for receiving this input information and verifying the accuracy and completeness of the data format" refers to the function by which the server receives data sent from the terminal and verifies that the data is in the correct format and contains all the required information.

[2023] "Means for generating multiple routes and calculating the required time and cost for each route" refers to a function in which the server generates multiple candidates for efficient travel routes and calculates the required time and travel cost for each.

[2024] "Means for selecting the optimal route based on constraints" refers to a function that selects the most suitable route from the generated routes based on constraints such as time and fare set by the user.

[2025] "Means for notifying the user of data on the selected optimal route" refers to the function of sending information on the optimal route selected by the server to the terminal and notifying the user of its contents.

[2026] "Means for receiving feedback entered by the user, recalculating a new optimal route, and notifying the user again" refers to a function in which the server receives feedback information re-entered from the terminal, recalculates a new optimal route based on that information, and notifies the user again of the results.

[2027] A system for implementing this invention calculates an optimal route based on a starting location, a destination location, constraints, and places to visit set by a user, and proposes the route to the user. This system is realized through communication between a server and a terminal. Specific embodiments of the system are described below.

[2028] User Input

[2029] The user launches the application on the device and enters the following data:

[2030] 1. Starting and Destination Locations

[2031] Example: Start location "Home", destination location "Landmark"

[2032] 2. Constraints

[2033] Travel time: Less than 2 hours

[2034] Travel cost: Under 500 yen

[2035] 3. Places you want to visit and desired arrival time

[2036] Example: Visit locations: "Park", "Cafe", "Arrive at Landmark at 6pm"

[2037] Sending data

[2038] The device sends these inputs to the server, which structure the data as follows:

[2039] json

[2040] {

[2041] "Start Location": "Home",

[2042] "Destination": "Landmark",

[2043] "Time Constraint": 120,

[2044] "Constraint Fee": 500,

[2045] "visited place": ["park", "cafe"],

[2046] "Arrival time": "18:00"

[2047] }

[2048] Server analysis and processing

[2049] The server analyzes the data received from the device, verifies the accuracy and completeness of each piece of information, and then performs the following steps:

[2050] 1. Calculating the optimal route

[2051] The server generates multiple routes and calculates the travel time and cost for each route, using external services such as the Google Maps API.

[2052] Select the optimal route based on constraints.

[2053] 2. Coordinating visit times

[2054] The server takes into account the time spent at each desired visit location and efficiently adjusts the overall visit route.

[2055] Example: "Home → Park (stay 30 minutes) → Cafe (stay 30 minutes) → Landmark (arrive at 6pm)"

[2056] Sending and displaying results

[2057] The server sends the optimal route data in JSON format to the device. The device displays the received data to the user. The display contents are as follows:

[2058] The best route from the starting point to the destination

[2059] Detailed directions on the map

[2060] Places visited and duration of stay

[2061] Total travel time and estimated fare

[2062] User Review and Feedback

[2063] 1. The user checks the route

[2064] The user checks the route displayed.

[2065] 2. Enter your feedback

[2066] If the user is not satisfied with the route, he or she enters feedback.

[2067] Example: "I'd rather go to a different establishment than a cafe."

[2068] 3. Send feedback and recalculate

[2069] The device sends feedback to the server, which recalculates a new optimal route and sends it again.

[2070] Specific examples and prompts for generative AI models

[2071] For example, given the following user input:

[2072] Starting Location: Home

[2073] Destination: Landmark

[2074] Time limit: 2 hours

[2075] Restricted price: 500 yen or less

[2076] Places visited: parks, cafes

[2077] Desired arrival time: 18:00

[2078] Example prompts for generative AI models:

[2079] Please suggest the best route based on the following criteria:

[2080] 1. Starting location: Home

[2081] 2. Destination: Landmark

[2082] 3. Travel time: Within 2 hours

[2083] 4. Travel cost: Under 500 yen

[2084] 5. Places visited: parks, cafes

[2085] 6. Desired arrival time: Arrive at the landmark at 18:00

[2086] This system provides optimal route planning based on the places to visit and constraints specified by the user, thereby improving travel efficiency.

[2087] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2088] Step 1: User Input

[2089] This is a procedure in which a user starts an application on a terminal and inputs the starting location, destination location, constraints, visit locations, and visit time. The input information is structured in the following format.

[2090] Input: "Home" (starting location), "Landmark" (destination location), travel time within 120 minutes, travel fare within 500 yen, visit locations "park, cafe", arrival time "18:00"

[2091] Output: Structured data (e.g. JSON)

[2092] Step 2: Sending data

[2093] This is the procedure by which the terminal sends data entered by the user to the server. The HTTP protocol is used for communication, and structured data is sent in JSON format.

[2094] Input: Structured data (e.g. JSON)

[2095] Output: Data sent

[2096] Step 3: Data analysis by the server

[2097] This is the procedure in which the server analyzes the data received from the terminal and checks the accuracy and completeness of the data format. The analysis results are checked to see if all necessary information is included and if the data format is correct.

[2098] Input: Submitted data (e.g. JSON)

[2099] Data processing: Checking data format and information integrity

[2100] Output: Analysis results (data format and information integrity check)

[2101] Step 4: Calculate the optimal route

[2102] This is the procedure where the server generates multiple routes based on the received data and calculates the required time and fare for each route. Route generation and calculations are performed using an external map API (e.g., Google Maps API).

[2103] Input: Parsed data

[2104] Data processing: Route generation, travel time and fare calculation (using map API)

[2105] Output: Multiple candidate routes and their respective travel times and fares

[2106] Step 5: Selecting the optimal route

[2107] This is a procedure in which the server selects the optimal route from multiple generated routes that meets the user's constraints (time and cost). The most suitable route is selected based on evaluation criteria.

[2108] Input: Multiple candidate routes and their respective travel times and fares

[2109] Data calculation: Evaluation of candidate routes, selection of optimal route

[2110] Output: Optimal route

[2111] Step 6: Arrange visit times

[2112] This is a procedure in which the server further adjusts the optimal route, taking into account the time spent at desired destinations. It predicts the time spent at each destination and creates an overall travel schedule.

[2113] Input: Optimal route

[2114] Data calculation: Prediction of stay time, adjustment of travel schedule

[2115] Output: Optimal schedule (e.g., home → park (30 min stay) → cafe (30 min stay) → landmark)

[2116] Step 7: Send and view results

[2117] This is the procedure where the server sends the adjusted optimal route and schedule to the terminal in JSON format. The terminal displays the received information to the user.

[2118] Input: Optimal schedule and route

[2119] Output: Results displayed to the user (map, directions, duration, travel time, estimated fare)

[2120] Step 8: User review and feedback

[2121] This is the procedure where the user checks the displayed route and inputs feedback if necessary. If the user inputs a new request, the terminal sends the feedback to the server, which then recalculates.

[2122] Input: User feedback (e.g., "I'd rather go to a different establishment than the cafe")

[2123] Data processing: receiving feedback and recalculating

[2124] Output: New recalculated optimal route and schedule

[2125] In this way, the entire system is able to efficiently process user requests and provide optimal routes and schedules.

[2126] (Application example 1)

[2127] 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."

[2128] In the food delivery industry, maximizing delivery efficiency and improving customer satisfaction requires a system that enables delivery personnel to efficiently and quickly select the optimal route. However, conventional systems have difficulty calculating the optimal delivery route taking into account traffic conditions, time constraints, and multiple destinations. This leads to delivery delays and inefficient routes, resulting in a decline in service quality.

[2129] 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.

[2130] In this invention, the server includes means for the user to input a start location and a destination location, means for the user to input constraints, means for the user to input places the user wants to visit along the way and the visiting time, means for receiving this input information and calculating an optimal route, means for notifying the user of the calculated optimal route, means for the delivery person to input the start location and destination location, means for inputting delivery constraints, means for calculating an optimal delivery route taking traffic information into account, and means for notifying the delivery person of the optimal delivery route. This allows the delivery person to quickly obtain optimal route information taking traffic conditions into account in real time and make deliveries efficiently.

[2131] A "user" is a person or entity who uses the system to input the starting location, destination location, constraints, places to visit, and so on.

[2132] "Starting location / destination location" means the starting location and destination location entered by the user.

[2133] "Constraints" refer to conditions such as time constraints and fare constraints that the user takes into account when calculating a route.

[2134] "Visiting place and visiting time" refers to the places the user wants to visit along the way and the estimated time of arrival at those places.

[2135] "Input information" refers to information provided by the user to the system regarding the starting location, destination location, constraints, visit locations and their arrival times.

[2136] "Optimal route" refers to the most efficient route calculated based on input information that satisfies the user's constraints.

[2137] The "means for notifying" refers to a method or device for transmitting information about the calculated optimal route to the user.

[2138] A "delivery person" is a person or entity that uses the system to calculate the optimal delivery route in order to perform food delivery operations.

[2139] "Delivery constraints" refer to conditions such as time constraints and traffic conditions related to delivery that are input by the delivery person.

[2140] "Traffic information" refers to dynamic data on current road congestion conditions, traffic regulations, etc.

[2141] "Optimal delivery route" refers to the most efficient delivery route for a delivery person, calculated taking into account delivery constraints and traffic information.

[2142] The system according to the present invention allows users and delivery personnel to efficiently calculate and select routes and propose optimal routes to their destinations. Specific embodiments of the system are described below.

[2143] 1. Program Generation

[2144] This system includes a program that calculates the optimal route based on user input information and notifies the delivery person of the optimal delivery route, taking into account real-time traffic information. The specific functions and processing of the system are shown below.

[2145] 2. System processing explanation

[2146] The server receives information about the starting location, destination location, constraints, visiting locations and visiting times input by the user through the terminal, which is required when the user sets up a specific delivery scenario.

[2147] The received data is first verified for accuracy. The server then generates multiple routes and calculates the travel time and cost for each. An algorithm is used to select the optimal route, taking into account time and cost constraints.

[2148] This optimal route calculation utilizes traffic information APIs (e.g., Google Maps API), which allows the calculation of optimal routes taking into account real-time traffic conditions, and provides highly accurate route information to delivery personnel.

[2149] The delivery person's device displays the optimal route information received from the server on a map application, enabling the delivery person to carry out their delivery work smoothly and efficiently.

[2150] 3. Examples of concrete examples and prompts

[2151] For example, if a delivery person needs to deliver from a "food delivery shop" to a "customer's address" within 30 minutes, the delivery person will enter the following information into the system:

[2152] Starting point: Food delivery shop

[2153] Destination: Customer address

[2154] Restrictions: Arrive within 30 minutes

[2155] Traffic conditions: Congested

[2156] Based on this information, the server calculates the optimal route as follows and notifies the delivery person:

[2157] Starting point → Main road → Customer address

[2158] Example prompt sentence:

[2159] "Calculate the quickest route and show me the route that will get me to my customer's address in under 30 minutes."

[2160] As described above, this system can significantly improve the efficiency of food delivery operations by calculating the optimal route based on information input by the user and delivery person and providing accurate route information in real time.

[2161] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2162] Step 1:

[2163] The user uses a terminal to input the starting location, destination location, constraints, places to visit, and visiting times.

[2164] Input: Start location, Destination location, Constraints, Visit locations and visit times

[2165] Output: Input information is sent from the device to the server.

[2166] Step 2:

[2167] The server analyzes the input information received from the terminal and verifies the accuracy and completeness of the format.

[2168] Input: Starting location, destination location, constraints, visit locations and visit times sent from the terminal

[2169] Output: Validated input information

[2170] Step 3:

[2171] Based on the information received by the server, multiple routes are generated and the required time and cost for each route are calculated.

[2172] Input: Validated input information, data from traffic information API

[2173] Output: Multiple route information (including travel time and fare)

[2174] Step 4:

[2175] The server selects the optimal route from multiple route information based on the user's constraints.

[2176] Input: Multiple route information, user constraints

[2177] Output: Optimal route

[2178] Step 5:

[2179] The server generates optimal route information and adjusts visit locations and times, taking into account real-time data such as traffic conditions as needed.

[2180] Input: Optimal route, data from traffic information API

[2181] Output: The adjusted optimal path

[2182] Step 6:

[2183] The server sends the adjusted optimal route information to the terminal.

[2184] Input: Adjusted optimal route

[2185] Output: Optimal route information displayed on the user's device

[2186] Step 7:

[2187] The optimal route information received by the user terminal is displayed on a map application and notified to the user.

[2188] Input: Adjusted optimal route information sent from the server

[2189] Output: Optimal route displayed on a map application

[2190] Step 8:

[2191] The user checks the displayed route and provides feedback if necessary, which is then sent back to the server.

[2192] Input: Displayed optimal route, user feedback

[2193] Output: Feedback information resent to the server

[2194] Step 9:

[2195] The server recalculates the route based on the user's feedback, generates a new optimal route, and notifies the user.

[2196] Input: User feedback information

[2197] Output: Newly recalculated optimal route information

[2198] 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.

[2199] A system for implementing this invention calculates an optimal route based on the departure point, destination, constraints, and places to visit set by the user, and also uses an emotion engine that recognizes the user's emotions, and suggests the route to the user. This system is realized via communication between a server and a terminal. A specific embodiment of the system is described below.

[2200] User Input

[2201] The user launches the application on the terminal and enters the following information:

[2202] 1. Enter your departure and destination.

[2203] Example: Departure point "Home", destination "Tokyo Tower"

[2204] 2. Enter the constraints.

[2205] Time it takes: Within 1 hour

[2206] Acceptable toll: Expressway tolls under 1,000 yen

[2207] 3. Enter the location you want to visit and a specific arrival time.

[2208] Example: Places to visit: "△△ Park", "◇◇ Cafe", "Arrive at Tokyo Tower at 4:00 PM"

[2209] User Emotion Recognition

[2210] The device's built-in emotion engine analyzes the user's emotions in real time and determines their current emotional state based on their facial expressions, voice, and text input.

[2211] 1. Collect emotional data

[2212] The emotion engine collects information while the user is using the application.

[2213] Example: Judging whether a user is "having fun" or "tired" from their facial expression.

[2214] Sending data

[2215] The device formats the input data and emotion data and sends them to the server in JSON format or an appropriate data format.

[2216] example:

[2217] {

[2218] "Origin": "Home",

[2219] "Destination": "Tokyo Tower",

[2220] "Time Constraint": 60,

[2221] "Constraint Fee": 1000,

[2222] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[2223] "Arrival time": "16:00",

[2224] "emotion": {

[2225] "Status": "Having fun",

[2226] "Strength": 0.8

[2227] }

[2228] }

[2229] Server processing

[2230] The server receives the data sent from the terminal and performs the following processing.

[2231] 1. Analysis of received data

[2232] The server analyzes the received data and checks whether each piece of information has been entered correctly.

[2233] 2. Calculating the optimal route

[2234] The server generates multiple routes and calculates the travel time and cost for each route.

[2235] The server selects a route that fits within the time and cost constraints based on the user's constraints.

[2236] 3. Coordinating visit times

[2237] The server predicts the amount of time spent at desired destinations and streamlines the overall route.

[2238] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[2239] 4. Considering Emotional Data

[2240] The server adjusts the route based on the user's emotional state. For example, if the user is "having fun," it will suggest a route that takes a slightly longer route and passes through more enjoyable places, while if the user is "tired," it will prioritize the shortest route.

[2241] Sending and displaying results

[2242] The server sends the optimal route and emotion-based adjustment results data to the device. The device displays the received data to the user. The specific display content is as follows:

[2243] The best route from your starting point to your destination

[2244] Detailed directions on the map

[2245] Places visited along the way and duration of stay

[2246] Total travel time and estimated fare

[2247] Sentiment-based route recommendations

[2248] User Review and Feedback

[2249] 1. The user checks the route displayed.

[2250] 2. If there are any further corrections the user would like to make, enter their feedback.

[2251] Example: "I'd like to go to Restaurant ☆☆ instead of Cafe ◇◇."

[2252] 3. The device sends the feedback to the server again, and the server reflects the feedback and recalculates a new optimal route.

[2253] 4. The recalculated route is re-notified and displayed to the user.

[2254] In this way, a system is realized that can effectively provide an optimal route within a time and budget set by the user, taking into account the emotional state of the user.

[2255] The processing flow will be explained below.

[2256] Step 1:

[2257] The user starts the application on the terminal and inputs the departure point and destination.

[2258] The user inputs constraints (amount of time that can be spent, a fee).

[2259] The user inputs the location they wish to visit and a specific arrival time.

[2260] Example: Departure point "Home", destination "Tokyo Tower", time constraint "within 1 hour", toll constraint "highway toll less than 1,000 yen", visit locations "△△ Park", "◇◇ Cafe", arrival time "4:00 PM"

[2261] Step 2:

[2262] The terminal formats the input data and sends it to the server in JSON format.

[2263] The terminal sends the input data to the server.

[2264] example:

[2265] {

[2266] "Origin": "Home",

[2267] "Destination": "Tokyo Tower",

[2268] "Time Constraint": 60,

[2269] "Constraint Fee": 1000,

[2270] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[2271] "Arrival time": "16:00"

[2272] }

[2273] Step 3:

[2274] The emotion engine analyzes the user's emotions and understands their current emotional state.

[2275] The device collects emotional data from the user's facial expressions, voice, text input, etc.

[2276] Example: An emotion engine determines whether a user is "happy" or "tired" based on their facial expression.

[2277] Step 4:

[2278] The device analyzes the emotion data and transmits it to the server along with the starting point, destination, constraints, and places to be visited.

[2279] example:

[2280] {

[2281] "Origin": "Home",

[2282] "Destination": "Tokyo Tower",

[2283] "Time Constraint": 60,

[2284] "Constraint Fee": 1000,

[2285] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[2286] "Arrival time": "16:00",

[2287] "emotion": {

[2288] "Status": "Having fun",

[2289] "Strength": 0.8

[2290] }

[2291] }

[2292] Step 5:

[2293] The server receives and analyzes the data sent from the terminal.

[2294] The server verifies the integrity of each piece of information and checks for missing or incorrect information.

[2295] Step 6:

[2296] The server generates multiple candidate routes from the origin to the destination.

[2297] Calculate travel time and cost for the candidate routes.

[2298] Step 7:

[2299] The server incorporates the places the user wants to visit into the proposed route and reconstructs the route.

[2300] Add the estimated time spent at the places the user has specified to visit.

[2301] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[2302] Step 8:

[2303] The server evaluates each candidate route to see if it satisfies the constraints.

[2304] The route with the highest rating is selected from among the routes that satisfy the criteria.

[2305] Step 9:

[2306] The server takes into account the user's emotional state and adjusts the selected route.

[2307] For example, if you are "having fun," prioritize routes that include many tourist spots, and if you are "tired," prioritize the shortest route.

[2308] Step 10:

[2309] The server transmits the optimized route data to the terminal.

[2310] Step 11:

[2311] The terminal analyzes the optimum route data received from the server and displays it to the user.

[2312] The display includes detailed route information, places to visit and duration, total travel time, estimated fare, and more.

[2313] Step 12:

[2314] The user checks the displayed route and provides feedback on any corrections needed, if necessary.

[2315] The user inputs any parts that he / she wants to further correct as feedback.

[2316] Example: "I'd like to go to Restaurant ☆☆ instead of Cafe ◇◇."

[2317] Step 13:

[2318] The terminal transmits the user's feedback to the server again.

[2319] Step 14:

[2320] The server receives the feedback and recalculates based on the new conditions.

[2321] The recalculated route is retransmitted to the terminal.

[2322] Step 15:

[2323] The device displays the new optimal route to the user for final confirmation.

[2324] In this way, a system is realized that can effectively provide an optimal route within a time and budget set by the user, taking into account the emotional state of the user.

[2325] Example 2

[2326] 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."

[2327] Conventional route guidance systems calculate routes based on static information such as the departure point, destination, constraints, and places to visit, but are unable to provide route guidance that takes the user's emotional state into account. As a result, route guidance is not flexible enough to reflect the user's mood or physical condition, which can sometimes compromise the user experience. To solve this problem, a system that proposes optimal routes that also take the user's emotional information into account is needed.

[2328] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for the user to input a start location and a destination location, a means for the user to input constraints, a means for the user to input places the user wants to visit along the way and the visiting time, a means for recognizing the user's emotions in real time, a means for receiving the input information and emotion information and calculating an optimal route, and a means for notifying the user of the calculated optimal route. This makes it possible to provide flexible and optimal route guidance that also takes the user's emotional state into consideration.

[2329] A "user" is an entity that uses the system to input information such as the departure point, destination, constraints, and places to visit.

[2330] The "start location" is the point where the user starts moving.

[2331] A "destination" is a location that the user ultimately wants to reach.

[2332] "Constraints" are restrictions set by the user, such as travel time and fare.

[2333] A "place to visit" is a location where the user wants to stop during their travels.

[2334] "Visit time" is the time when the user will arrive at the visit location specified by the user.

[2335] "Emotion" refers to a psychological state that is recognized in real time from the user's facial expression, voice, etc.

[2336] The "optimal route" is the route that is judged to be the most efficient, taking into account factors such as travel time from the departure point to the destination, fare, and availability of places to visit.

[2337] "Notification" is the act of showing the calculated optimal route to the user.

[2338] The system for implementing this invention calculates the optimal route based on the starting point, destination, constraints, and places to visit set by the user, and further uses an emotion engine that recognizes the user's emotions, and proposes the route to the user. Specific embodiments of this system are described below.

[2339] First, the user launches the application on their device and inputs their starting location and destination. For example, they input "home" as the starting point and "Tokyo Tower" as the destination. Next, the user inputs constraints such as the amount of time and cost they are willing to spend. For example, they can set the required time to "within one hour" and the cost to "highway toll under 1,000 yen." Next, they input the places they want to visit and a specific arrival time. They can set "△△ Park" or "◇◇ Cafe" as places to visit and "arrive at 4:00 p.m." as the destination.

[2340] Furthermore, the emotion engine installed in the device analyzes the user's emotions in real time. The emotion engine determines the user's current emotional state based on the user's facial expressions, voice, and text input. For example, it can determine whether the user is "enjoyed" or "tired" based on the user's facial expressions. This emotional data is sensed and collected by the device.

[2341] The device formats the user's input data and emotion data and sends them to the server in JSON format or an appropriate data format.

[2342] {

[2343] "Origin": "Home",

[2344] "Destination": "Tokyo Tower",

[2345] "Time Constraint": 60,

[2346] "Constraint Fee": 1000,

[2347] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[2348] "Arrival time": "16:00",

[2349] "emotion": {

[2350] "Status": "Having fun",

[2351] "Strength": 0.8

[2352] }

[2353] }

[2354] Data like this is sent.

[2355] Next, the server receives the data sent from the terminal. After receiving the data, the server analyzes it and verifies that each piece of information has been entered correctly. The server then generates multiple routes and calculates the travel time and cost for each route. Based on the user's constraints, the server selects a route that fits within the time and cost constraints. Furthermore, the server predicts the length of stay at desired destinations and streamlines the overall route. For example, it may adjust the route to "Home → △△ Park (30-minute stay) → ◇◇ Cafe (20-minute stay) → Tokyo Tower (arrive at 4:00 p.m.)."

[2356] The server also adjusts the route based on the user's emotional state: for example, if the user is "having fun," it suggests a route that takes them through more enjoyable places, while if the user is "tired," it prioritizes the shortest route.

[2357] Finally, the server sends the optimal route and emotion-based adjustment results data to the device, which then displays the received data to the user. The display includes the optimal route from the origin to the destination, detailed directions on a map, stops along the way and their duration, total travel time and estimated fare, and an explanation of the emotion-based recommended route.

[2358] The user checks the displayed route and enters feedback if there are any parts they would like to correct. For example, if the user enters feedback such as "I would like to go to Restaurant ☆☆ instead of Cafe ◇◇," the device will send this to the server again. The server will reflect this feedback, recalculate a new optimal route, and notify and display it to the user again.

[2359] In this way, a system is realized that can effectively provide an optimal route within a time and budget set by the user, taking into account the emotional state of the user.

[2360] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2361] Step 1:

[2362] The user launches the application on their device and inputs the starting location, destination location, constraints, and places and times to visit. These inputs are saved on the device and used for subsequent data processing. For example, if a user inputs "home" as the starting point, "Tokyo Tower" as the destination, "within 1 hour" and "highway toll under 1,000 yen" as constraints, and "△△ Park," "◇◇ Cafe," and "arrive at Tokyo Tower at 4 p.m." as places to visit, the device will save this information as structured data.

[2363] input:

[2364] Start location, destination location, constraints, visit locations and visit times

[2365] output:

[2366] Structured Input Data

[2367] Step 2:

[2368] The emotion engine installed in the device recognizes the user's emotions in real time based on the user's facial expressions, voice, and text input. The emotion engine uses image recognition and voice analysis technologies to evaluate the user's state and generate corresponding emotion data. Specifically, analysis is performed using a camera and microphone, and the results are output as "enjoyed" or "tired," etc.

[2369] input:

[2370] User facial expressions, voice, and text input

[2371] output:

[2372] Real-time sentiment data

[2373] Step 3:

[2374] The device formats the user's input data and emotion data and sends them to the server in JSON format or other appropriate data format, where they are prepared for analysis.

[2375] input:

[2376] Structured input data, real-time sentiment data

[2377] output:

[2378] JSON format data to send to the server

[2379] Step 4:

[2380] The server receives and analyzes the data sent from the terminal. The received data includes the starting location, destination location, constraints, visited locations, visiting time, and emotion data. The server interprets this data and checks whether each piece of information has been entered correctly.

[2381] input:

[2382] JSON format data

[2383] output:

[2384] Analyzed data

[2385] Step 5:

[2386] The server generates multiple routes based on the analyzed data and calculates the travel time and fare for each route. Taking into account the user's constraints, it selects a route that fits within the time and fare constraints. The data is calculated using a route optimization algorithm using a map database and route information.

[2387] input:

[2388] Analyzed data

[2389] output:

[2390] Multiple calculated route candidates

[2391] Step 6:

[2392] The server predicts the amount of time spent at desired locations and optimizes the overall route. Taking into account the amount of time spent at each location, the server determines the optimal order of visits and stopovers. This allows for an efficient route that also takes into account the amount of time spent at each location.

[2393] input:

[2394] Multiple calculated route candidates

[2395] output:

[2396] Optimal route considering stay time

[2397] Step 7:

[2398] The server adjusts the route based on the user's emotional state. For example, if the user is "having fun," it will choose a route with a beautiful view, and if the user is "tired," it will choose the shortest route. Emotional data is also incorporated into the route calculation algorithm to generate optimal suggestions.

[2399] input:

[2400] Optimal route considering stay time, user emotion data

[2401] output:

[2402] Optimal route considering emotions

[2403] Step 8:

[2404] The server sends the calculated optimal route and emotion-based adjustment results data to the device, which then formats the results data and sends them back to the device in a format that is easy for the user to understand.

[2405] input:

[2406] Optimal route considering emotions

[2407] output:

[2408] Result data for display to the user

[2409] Step 9:

[2410] The device displays the data it receives to the user, including the optimal route from the departure point to the destination, detailed directions on a map, recommended routes based on locations visited along the way and their duration, total travel time and estimated fare, and sentiment. The information presented to the user allows them to review their travel plans in detail.

[2411] input:

[2412] Result data

[2413] output:

[2414] Optimal route and detailed information displayed to the user

[2415] Step 10:

[2416] The user checks the displayed route and inputs feedback if there are any corrections they would like to make. For example, they can input a request such as "I would like to go to Restaurant ☆☆ instead of Cafe ◇◇" into the device, and the device then sends this feedback data back to the server.

[2417] input:

[2418] User Feedback

[2419] output:

[2420] Feedback Data

[2421] Step 11:

[2422] The server recalculates a new optimal route based on the feedback and notifies the user again, with the new route suggestion adjusted to reflect the user's new preferences.

[2423] input:

[2424] Feedback Data

[2425] output:

[2426] Recalculated optimal route

[2427] In this way, we have created a system that proposes optimal routes that take the user's emotions into consideration through each step.

[2428] (Application example 2)

[2429] 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."

[2430] Current autonomous vehicle systems can calculate routes and provide driving instructions based on user settings, but they do not offer optimal route suggestions that take the user's emotional state into account. As a result, they are unable to flexibly respond to subtle changes in the user's emotions, which can lead to stress and frustration. The present invention aims to improve the user experience by calculating more personalized driving routes using user emotion recognition data and applying them to autonomous vehicles.

[2431] The identification processing by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input a start location and a destination location, means for the user to input constraints, means for the user to input places the user wants to visit along the way and the visiting time, means having a human emotion recognition engine for acquiring the user's emotional state, means for receiving the input information and emotional data and calculating an optimal route, means for notifying the user of the calculated optimal route, and means for transmitting driving instructions to the autonomously driven vehicle. This makes it possible to propose an optimal route and provide driving instructions that take the user's emotional state into consideration.

[2432] The "means for the user to input the starting point and the destination point" is an interface for the user to input the starting point and the destination point on the terminal.

[2433] The "means for the user to input constraints" is an interface for the user to input constraints such as time and cost during travel.

[2434] The "means for inputting the places the user wants to visit along the way and the time of visit" is an interface for inputting the places the user wants to stop at along the way and the time of arrival at those places.

[2435] A "human emotion recognition engine for acquiring a user's emotional state" is a system for acquiring emotional data in real time from a user's facial expressions, voice, etc.

[2436] The "means for receiving this input information and emotion data and calculating the optimal route" is a computer program for calculating the optimal travel route based on the information entered by the user and the acquired emotion data.

[2437] The "means for notifying the user of the calculated optimum route" is a communication means for notifying the user's terminal of the optimum route calculated by the server.

[2438] The "means for transmitting driving instructions to an autonomous vehicle" is a communication interface for transmitting driving instructions to an autonomous vehicle based on the calculated optimal route.

[2439] A system for implementing the present invention provides an optimal route for an autonomous vehicle that takes into account the emotional state of the user, and performs operational management. Detailed embodiments of this system will be described below.

[2440] User Input

[2441] The user enters the following information using a smartphone or vehicle interface:

[2442] 1. Origin and Destination

[2443] Example: Departure point "Home", destination "Tokyo Tower"

[2444] 2. Constraints

[2445] Example: Acceptable time: "within 1 hour", acceptable cost: "1,000 yen or less"

[2446] 3. The places you want to visit and the specific arrival time

[2447] Example: Visit locations: "△△ Park", "◇◇ Cafe", destination: "Arrival at 4:00 PM"

[2448] User Emotion Recognition

[2449] The device's built-in emotion engine analyzes the user's emotional state in real time. This emotion engine uses emotion recognition software such as "EmotionEngine" to determine the user's current emotional state based on facial expressions, voice, and text input.

[2450] Example: Judging whether a user is "having fun" or "tired" from their facial expression.

[2451] Sending data

[2452] The device formats the input data and emotion data and sends them to the server in JSON format or an appropriate data format, such as the following:

[2453] example:

[2454] json

[2455] {

[2456] "Origin": "Home",

[2457] "Destination": "Tokyo Tower",

[2458] "Time Constraint": 60,

[2459] "Constraint Fee": 1000,

[2460] "Visited Place": ["△△ Park", "◇◇ Cafe"],

[2461] "Arrival time": "16:00",

[2462] "emotion": {

[2463] "Status": "Having fun",

[2464] "Strength": 0.8

[2465] }

[2466] }

[2467] Server processing

[2468] The server analyzes the received data and performs the following processing.

[2469] 1. Analysis of received data

[2470] Check that the data is entered correctly.

[2471] 2. Calculating the optimal route

[2472] Generate multiple routes and calculate the travel time and cost for each route.

[2473] The route with the highest evaluation within the constraints is selected.

[2474] 3. Coordinating visit times

[2475] Predict the amount of time spent at desired destinations and streamline the overall route.

[2476] Example: "Home → △△ Park (30 minutes stay) → ◇◇ Cafe (20 minutes stay) → Tokyo Tower (arrival at 4pm)"

[2477] 4. Considering Emotional Data

[2478] The system adjusts the route based on the user's emotional state. For example, if the user is "having fun," it suggests a route that takes a slightly longer route and passes through more enjoyable places. If the user is "tired," it prioritizes the shortest route.

[2479] Sending and displaying results

[2480] The server sends the calculated optimal route information to the terminal, where the user can check the information through their smartphone or vehicle interface.

[2481] What it shows: The best route from origin to destination, stops along the way and duration, total travel time and estimated cost, and a sentiment-based explanation of the recommended route

[2482] Commanding autonomous vehicles

[2483] Based on the optimal route selected by the server, the autonomous vehicle will send driving instructions, which the autonomous vehicle will then follow to begin driving.

[2484] Specific prompt examples

[2485] The optimal route is calculated by inputting the following prompt sentence into the generative AI model:

[2486] markdown

[2487] You are the operator of a self-driving vehicle. Using the following information, provide the optimal route taking into account the user's specified conditions and emotional state:

[2488] Starting point: Home

[2489] Destination: Tokyo Tower

[2490] Constraints:

[2491] Time: 60 minutes or less

[2492] Price: Under 1,000 yen

[2493] Visited location: △△ Park, ◇◇ Cafe

[2494] Arrival time: 16:00

[2495] Emotional State: Enjoying (Intensity: 0.8)

[2496] Use this information to calculate the best route and suggest it to the user.

[2497] The above clearly shows how the system embodying the present invention operates in concrete terms.

[2498] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2499] Step 1: The user enters input information into the terminal

[2500] The user inputs the starting point, destination, constraints (such as time constraints and fare constraints), places to visit, and arrival time through the interface on the terminal. The user's input data is temporarily stored inside the terminal.

[2501] Input: Start point, Destination point, Constraints, Visit locations, Arrival time

[2502] Output: Saved user input data

[2503] Step 2: Collect user emotion data with an emotion recognition engine

[2504] The device's built-in emotion recognition engine analyzes the user's facial expressions, voice, and text input in real time to understand the user's emotional state. The necessary emotional data is extracted and stored on the device.

[2505] Input: User facial expression data, voice data, text input

[2506] Output: Emotion data (e.g., enjoying, intensity 0.8)

[2507] Step 3: Send input data and emotion data to the server

[2508] The device formats the user's input data and emotion data, converts it into an appropriate data format such as JSON, and sends it to the server.

[2509] Input: User input data, emotion data

[2510] Output: Formatted JSON data sent to the server

[2511] Step 4: The server parses the received data

[2512] The server analyzes the received data and checks its accuracy: it verifies that the starting point, destination, constraints, visit locations, arrival time, and emotional state are entered correctly.

[2513] Input: JSON data received by the server

[2514] Output: Parsed input data and sentiment data

[2515] Step 5: The server calculates the optimal route

[2516] The server generates multiple routes based on the analyzed input data and emotion data, calculates the travel time and cost for each route, and selects the route with the highest rating based on the user's constraints and emotional state.

[2517] Input: Parsed input data, emotion data

[2518] Output: Optimal route

[2519] Step 6: Adjust the time spent at each location

[2520] The server predicts the time spent at the places the user has designated to visit, and adjusts the overall route to make it more efficient.

[2521] Input: Visit location information, arrival time, constraints

[2522] Output: Adjusted itinerary

[2523] Step 7: The server sends the calculated route information to the terminal.

[2524] The server organizes the calculated and adjusted optimal route information and sends it to the terminal, where it is converted into an optimal format for the user to quickly check.

[2525] Input: Optimal route

[2526] Output: The organized route information is sent to the terminal.

[2527] Step 8: The device displays the route information to the user, and the user confirms it.

[2528] The device displays the optimal route information sent from the server to the user, who can then check it via their smartphone or in-car interface and make any necessary corrections.

[2529] Input: Organized route information

[2530] Output: Route information displayed to the user

[2531] Step 9: Send driving instructions to the autonomous vehicle

[2532] The server sends driving instructions to the autonomous vehicle based on the optimal route, and the autonomous vehicle then begins driving along the specified route.

[2533] Input: Optimal route instructions

[2534] Output: Driving instructions are sent to the autonomous vehicle.

[2535] 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.

[2536] 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.

[2537] 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.

[2538] 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.

[2539] 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.

[2540] 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.

[2541] 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).

[2542] 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.

[2543] 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."

[2544] 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.

[2545] 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).

[2546] 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.

[2547] 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.

[2548] 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.

[2549] 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.

[2550] 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.

[2551] 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.

[2552] 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.

[2553] 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.

[2554] 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.

[2555] 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.

[2556] The following is further disclosed regarding the above embodiment.

[2557] (Claim 1)

[2558] means for a user to input a start location and a destination location;

[2559] means for a user to input constraints;

[2560] means for the user to input the places and times of visits that the user wishes to visit along the way;

[2561] means for receiving these inputs and calculating an optimal route;

[2562] means for notifying a user of the calculated optimal route;

[2563] A system including:

[2564] (Claim 2)

[2565] generating a plurality of routes based on the received information that satisfy time and fare constraints specified by the user;

[2566] 10. The system of claim 1, further comprising means for selecting the route with the highest rating from among the routes.

[2567] (Claim 3)

[2568] Predict the duration of stay at a visit location designated by the user,

[2569] 10. The system of claim 1, further comprising means for streamlining an overall visit route.

[2570] "Example 1"

[2571] (Claim 1)

[2572] means for a user to input a start location and a destination location;

[2573] means for a user to input constraints;

[2574] means for the user to input the places and times of visits that the user wishes to make along the way;

[2575] a means for receiving these inputs and verifying the accuracy and completeness of the data format;

[2576] means for generating a plurality of routes and calculating the required time and fare for each route;

[2577] A means for selecting an optimal route based on constraints;

[2578] means for notifying a user of data on the selected optimal route;

[2579] A system including:

[2580] (Claim 2)

[2581] generating a plurality of routes based on the received information that satisfy time and fare constraints specified by the user;

[2582] A means for selecting the route with the highest rating from among those routes;

[2583] Further provided is a means for predicting the duration of stay at desired places to be visited and for streamlining the overall visiting route;

[2584] 10. The system of claim 1.

[2585] (Claim 3)

[2586] Receive user-entered feedback and recalculate a new optimal route.

[2587] further comprising means for re-notifying the user;

[2588] 10. The system of claim 1.

[2589] "Application Example 1"

[2590] (Claim 1)

[2591] means for a user to input a start location and a destination location;

[2592] means for a user to input constraints;

[2593] means for the user to input the places and times of visits that the user wishes to visit along the way;

[2594] means for receiving these inputs and calculating an optimal route;

[2595] means for notifying a user of the calculated optimal route;

[2596] means for a delivery person to input a starting location and a destination location;

[2597] means for inputting delivery constraints;

[2598] means for calculating an optimal delivery route taking into account traffic information;

[2599] a means for notifying a delivery person of an optimal delivery route;

[2600] A system including:

[2601] (Claim 2)

[2602] generating a plurality of routes based on the received information that satisfy time and fare constraints specified by the user;

[2603] 10. The system of claim 1, further comprising means for selecting the route with the highest rating from among the routes.

[2604] (Claim 3)

[2605] Predict the duration of stay at a visit location designated by the user,

[2606] 10. The system of claim 1, further comprising means for streamlining an overall visit route.

[2607] "Example 2: Combining Emotion Engines"

[2608] (Claim 1)

[2609] means for a user to input a start location and a destination location;

[2610] means for a user to input constraints;

[2611] means for the user to input the places and times of visits that the user wishes to visit along the way;

[2612] means for recognizing a user's emotions in real time;

[2613] means for receiving the input information and emotion information and calculating an optimal route;

[2614] means for notifying a user of the calculated optimal route;

[2615] A system including:

[2616] (Claim 2)

[2617] The system of claim 1, further comprising: means for generating a plurality of routes that satisfy time and fare constraints specified by the user based on the received information and the user's emotional information, and selecting the route with the highest rating from among the routes.

[2618] (Claim 3)

[2619] The system of claim 1, further comprising means for predicting a stay time at a visit location specified by a user and streamlining an overall visit route.

[2620] "Application example 2 when combining emotion engines"

[2621] (Claim 1)

[2622] means for a user to input a start location and a destination location;

[2623] means for a user to input constraints;

[2624] means for the user to input the places and times of visits that the user wishes to visit along the way;

[2625] means for acquiring an emotional state of a user, the means comprising a human emotion recognition engine;

[2626] A means for receiving the input information and emotion data and calculating an optimal route;

[2627] means for notifying a user of the calculated optimal route;

[2628] means for transmitting driving instructions to the autonomous vehicle;

[2629] A system including:

[2630] (Claim 2)

[2631] 10. The system of claim 1, further comprising: means for generating a plurality of routes for autonomous vehicle operation management that satisfy user-specified time and fare constraints based on the received information and emotion data, and selecting the route with the highest rating from among the routes.

[2632] (Claim 3)

[2633] The system of claim 1, further comprising means for predicting a stay time at a visit location specified by a user and streamlining an overall visit route. [Explanation of symbols]

[2634] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for a user to input a start location and a destination location; means for a user to input constraints; means for the user to input the places and times of visits that the user wishes to visit along the way; means for receiving these inputs and calculating an optimal route; means for notifying a user of the calculated optimal route; A system including:

2. generating a plurality of routes based on the received information that satisfy time and fare constraints specified by the user; The system of claim 1 further comprising means for selecting the route with the highest rating from among the routes.

3. Predict the duration of stay at a visit location designated by the user, The system of claim 1 , further comprising means for streamlining an overall visit route.

Images