System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving current location information and destination information of a user; means for instantaneously generating an optimal route from the current location information to the destination information using a generative AI model; and means for transmitting the generated optimal route information to a user device for display on the user device.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] At large-scale events, participants concentrating in one place can cause problems such as congestion, safety risks, and rising security costs. It can also make it difficult for local explorers to enjoy the event comfortably and safely. These issues place a heavy burden on government agencies, event organizers, and participants, so effective methods of controlling people flow are needed. [Means for solving the problem]

[0005] The present invention provides a system that receives a user's current location information and destination information and instantly generates an optimal route using a generative AI model. Specifically, the system includes (1) a means for receiving the user's current location information and destination information, (2) a means for generating an optimal route from the current location information to the destination information using a generative AI model, and (3) a means for transmitting the generated optimal route information to a user terminal and making it displayable on the user terminal. The system also includes a means for transmitting the user's current location information to a server in real time and updating the optimal route, as well as a means for calculating passing points and awarding points to the user. This enables safe and comfortable travel during events and local exploration, alleviating congestion, and contributing to reduced security costs.

[0006] "User" refers to a person who travels using this system.

[0007] "Current location information" refers to data that indicates the geographic location where a user is located at a particular time.

[0008] "Destination information" refers to data that indicates a geographic location to which a user wishes to travel.

[0009] A "server" refers to a computer system that receives and processes data sent from a user terminal.

[0010] A "generative AI model" refers to an artificial intelligence algorithm that generates optimal routes based on historical data and real-time information.

[0011] The "optimal route" refers to the most efficient and safe route for a user to travel from their current location to their destination.

[0012] "User terminal" refers to a device with GPS functionality, such as a smartphone or tablet owned by the user.

[0013] "Points" refer to a type of reward or benefit given to a user when the user passes through a specific route.

[0014] "Real-time" refers to processing and providing current information with little delay.

[0015] An "event" is a large gathering or activity that involves many people.

[0016] A "local explorer" is someone who explores a particular area and participates in local events and activities.

[0017] "Congestion reduction" refers to preventing people from gathering in one place by dispersing them.

[0018] "People flow control" refers to the effective management of people's movements in a specific area or space.

[0019] "Safety risks" refer to safety issues and dangers that arise from crowding.

[0020] "Security costs" refers to the costs incurred to ensure safety at events and gatherings. [Brief explanation of the drawings]

[0021] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0022] 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.

[0023] First, the terms used in the following description will be explained.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 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.

[0032] 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).

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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."

[0042] The present invention describes a specific embodiment of a digital tool, "digital checkpoint," aimed at congestion relief and people flow management.

[0043] Collecting and transmitting user location information

[0044] A user inputs their current location and destination information using a device with GPS functionality, such as a smartphone or tablet. For example, if a user is participating in a large-scale event, their current location may be "latitude 35.6895 degrees, longitude 139.6917 degrees" (Tokyo) and their destination may be "latitude 35.7100 degrees, longitude 139.8107 degrees" (Skytree). The device then sends this location information to the server.

[0045] Server generates optimal route

[0046] The server analyzes the received user's current location and destination information and instantly generates the optimal route using a generative AI model. The generative AI model suggests the optimal route for the user to choose based on past event data and real-time people flow data. For example, it generates specific routes such as "Route A: via Asakusa Street" and "Route B: via Kuramae Street."

[0047] Providing and displaying the best route

[0048] The server then formats the generated optimal route information in JSON format and sends it to the device, which then visually displays the received optimal route to the user, allowing the user to travel safely and efficiently according to the optimal route.

[0049] Real-time location tracking and route updates

[0050] While moving, the device periodically acquires GPS data and sends its current location information to the server. The server then recalculates and adjusts the optimal route as needed based on the received location information. Real-time location tracking makes it possible to avoid dynamically changing pedestrian flows and crowds.

[0051] Points and evaluation

[0052] The device sends the pass point information to the server each time the user passes through a checkpoint area. The server analyzes the pass data and adds points to the user's account if the user has passed through the appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons.

[0053] Specific examples

[0054] The following is a specific example of an event using this invention. For example, suppose a user participating in a summer festival is currently located at Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees) and has set their destination as Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The user enters this information into a smartphone app and submits it.

[0055] Based on the received data, the server uses a generative AI model to generate optimal routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori." The generated route information is returned to the device in JSON format, and the device then provides the displayed route to the user.

[0056] When a user selects Route A and starts moving, the current location information is updated periodically during the movement, and the route is recalculated to avoid congestion. When a user passes through a specific checkpoint, the server calculates the passing points and gives the user points.

[0057] This system allows users to travel safely and comfortably, and event organizers can alleviate congestion and reduce security costs. The above is a detailed description of the embodiment of the present invention.

[0058] The processing flow will be explained below.

[0059] Step 1:

[0060] The user launches the smartphone app, obtains their current location information, enters their destination, and presses the send button.

[0061] Step 2:

[0062] The device uses the built-in GPS to obtain the latitude and longitude of its current location, and then sends the current location and destination information to the server in JSON format.

[0063] Step 3:

[0064] The server receives the current location information and destination information transmitted from the user terminal.

[0065] Step 4:

[0066] The server analyzes the received location information and uses a generative AI model to instantly generate the optimal route from the current location to the destination.

[0067] Step 5:

[0068] The server constructs a response in JSON format containing the generated optimal route information and sends it to the terminal.

[0069] Step 6:

[0070] The device receives the response from the server and visually displays the optimal route to the user, providing specific route details using a map.

[0071] Step 7:

[0072] The user starts moving according to the displayed optimal route. The device periodically acquires GPS data and sends the current location to the server.

[0073] Step 8:

[0074] The server recalculates and adjusts the optimal route as needed based on the current location information received in real time.

[0075] Step 9:

[0076] When a user passes through a checkpoint area, the terminal transmits the passing data to the server, which calculates the passing points and adds them to the user's account.

[0077] Step 10:

[0078] Users can check the points they have earned within the app and exchange them for rewards and coupons.

[0079] Example 1

[0080] 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."

[0081] Conventional people flow management systems not only provide optimal routes while avoiding congestion in real time, but also lack the ability to collect and analyze data during events to proactively propose optimal routes that will be effective for future events. Furthermore, they lack incentive functions that not only provide users with a safe and efficient way to travel, but also track their location information during travel and provide appropriate points. This requires improving user convenience and optimizing people flow management for organizers.

[0082] 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.

[0083] In this invention, the server includes: a means for receiving a user's current location information and destination information; a means for instantly generating an optimal route from the current location information to the destination information based on past and real-time data using a generative AI model; a means for configuring the generated optimal route information, transmitting it to the user's terminal, and visually displaying it on the user's terminal; a means for periodically transmitting current location information from the user's terminal to the server; and a means for recalculating and adjusting the optimal route as needed based on the current location information periodically received by the server. This not only enables users to travel safely and efficiently, but also avoids real-time congestion during travel, allowing organizers to achieve more effective people flow management. It also provides incentives by awarding passing points and collecting data during the event, contributing to the generation of optimal routes for the next event.

[0084] "User" refers to an individual user who uses the system to input location information, check routes, and earn points.

[0085] "Server" refers to the central processing unit that analyzes the data received from the user and generates, recalculates, and adjusts the optimal route using the generative AI model.

[0086] A "generative AI model" refers to an artificial intelligence algorithm that instantly generates the optimal route from a user's location information to their destination information based on past and real-time data.

[0087] "Current location information" refers to latitude and longitude data obtained using the GPS function of the user's device, and indicates the user's current location.

[0088] "Destination information" refers to the latitude and longitude data of the destination that the user inputs into the system.

[0089] An "optimal route" refers to a recommended route that is analyzed and calculated by a generative AI model to help users reach their destination efficiently and safely.

[0090] "User device" refers to a mobile information terminal equipped with GPS functionality used by a user, such as a smartphone or tablet.

[0091] "Data" refers to all types of information used and analyzed by the system, such as user location information, destination information, past event data, and real-time people flow data.

[0092] "Passage point information" refers to information and data recorded each time a user passes through a specific checkpoint area.

[0093] "Points" refer to virtual rewards given to users when they follow a proper route.

[0094] "Benefits and coupons" refer to items that improve convenience, such as rewards and discount coupons that can be exchanged using points earned by users.

[0095] A specific embodiment of the present invention will be described, which provides a digital tool for congestion reduction and people flow management, specifically for enabling users to move around efficiently and safely at events and large gatherings.

[0096] Collecting and transmitting user location information

[0097] A user uses a device with GPS functionality, such as a smartphone or tablet, to input current location information and destination information. The application used in this case provides an interface for inputting location information. Specific information is assumed to be the current location is "latitude 35.6581, longitude 139.7017" (Shibuya Station), and the destination is "latitude 35.6717, longitude 139.6949" (Yoyogi Park). The device sends the input location information to the server as an HTTP request.

[0098] Server generates optimal route

[0099] The server receives the current location and destination information sent by the user and uses a generative AI model to analyze it. This generative AI model instantly generates the optimal travel route based on past event data and real-time people flow data. For example, it generates specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori."

[0100] Providing and displaying the best route

[0101] The server generates optimal route information in JSON format and sends it to the device. The device analyzes the received optimal route information and visually displays it to the user. The user can then select the optimal route from the displayed routes.

[0102] Real-time location tracking and route updates

[0103] When the user starts moving, the device periodically acquires GPS data and sends the current location information to the server. The server recalculates and adjusts the optimal route as needed based on the received current location information. For example, if new congestion occurs during movement, the server generates a new route, sends it to the device, and notifies the user.

[0104] Points and evaluation

[0105] Each time a user passes through a checkpoint area (specific location), the device sends the passing point information to the server. The server analyzes this passing data and awards points to the user if the user has passed through the appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons.

[0106] Specific examples

[0107] The following is a concrete example of an event using this system. For example, suppose a user participating in a summer festival is currently located at Shibuya Station (latitude 35.6581, longitude 139.7017) and has set their destination as Yoyogi Park (latitude 35.6717, longitude 139.6949). The user enters this information into a smartphone app and submits it. Based on the received data, the server uses a generative AI model to generate an optimal route, such as "Route A: via Harajuku" or "Route B: via Meiji Dori." The generated route information is returned to the device in JSON format, and the device provides the displayed route to the user. If the user selects Route A and begins traveling, their current location information is updated periodically during the trip, and the route is recalculated to avoid congestion. When the user passes through a specific checkpoint, the server calculates the passing points and awards the user points.

[0108] Prompt Sentence Examples

[0109] Current location: 35.6581, 139.7017 (Shibuya Station)

[0110] Destination: 35.6717, 139.6949 (Yoyogi Park)

[0111] The above is a specific embodiment for carrying out the invention.

[0112] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0113] Step 1:

[0114] The user launches the application on a device with GPS functionality, such as a smartphone or tablet, and inputs their current location and destination information. Specifically, the current location is "latitude 35.6581, longitude 139.7017" (Shibuya Station), and the destination is "latitude 35.6717, longitude 139.6949" (Yoyogi Park). The device sends this input information to the server as an HTTP request. Input: Current location and destination information entered by the user, Output: Location data in JSON format.

[0115] Step 2:

[0116] The server receives the current location information and destination information sent by the user. To analyze the received location information, the server uses a generative AI model. This generative AI model generates the optimal travel route using past event data and real-time people flow data. For example, specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori" are generated. Input: JSON data of location information from the user, Output: JSON data containing optimal route information.

[0117] Step 3:

[0118] The server composes the generated optimal route information in JSON format and sends it to the terminal. The terminal analyzes the received optimal route information and displays it visually to the user. The user selects the best route from the displayed routes. Input: JSON data containing optimal route information from the server, Output: Data returning the selection result to the user.

[0119] Step 4:

[0120] When the user starts moving, the device periodically acquires GPS data and sends current location information to the server. The server recalculates and adjusts the optimal route as needed based on the received current location information. For example, if unexpected congestion occurs during movement, the server generates a new route and sends it to the device to notify the user. Input: Data on the user's location while moving, Output: Optimal route information recalculated as needed.

[0121] Step 5:

[0122] Each time the user passes through a checkpoint area (specific point), the device sends the passing point information to the server. The server analyzes this passing data and adds points to the user's account if the user has passed through the appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons. Input: Passing points and timestamp information, Output: Passing points and associated reward data.

[0123] (Application example 1)

[0124] 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."

[0125] Conventional logistics centers lacked real-time route optimization for efficient movement of employees and autonomous vehicles, resulting in congestion and delays. This reduced delivery efficiency, increased overall costs, and inefficient operations. Furthermore, there was a need for a system that could dynamically recalculate routes based on on-site congestion and provide appropriate instructions to employees.

[0126] 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.

[0127] In this invention, the server includes a means for receiving a user's current location information and destination information, a means for instantly generating an optimal route from the current location information to the destination information using a generative AI model, a means for transmitting the generated optimal route information to a user terminal and making it displayable on the user terminal, and a means for providing the optimal route to employees or automated vehicles in the logistics center. This enables employees and automated vehicles in the logistics center to travel safely and quickly via the optimal route efficiently. Real-time route updates and congestion avoidance can improve the efficiency of the entire logistics center.

[0128] "User's current location information" refers to data on the geographic coordinates of the user's current location, obtained using GPS or other location information technology.

[0129] "Destination information" is data on the final geographical destination to which the user wishes to travel.

[0130] A "generative AI model" is an artificial intelligence model that automatically generates optimal routes and suggestions based on past and real-time data.

[0131] "Means for updating the optimal route in real time" refers to a mechanism that periodically sends the user's current location information to a server and dynamically recalculates the route based on the latest information.

[0132] The "means for calculating passing points on the optimum route and giving points to the user" is a function that records the user's passing through a specific route and adds up points.

[0133] "Means for providing optimal routes to employees or automated vehicles within a logistics center" refers to a system that provides efficient route instructions to employees and automated vehicles working within a logistics center.

[0134] "Real-time people flow data within a logistics center" is data collected by observing the movement of people and vehicles within the logistics center in real time.

[0135] "Means for informing a delivery robot of the optimal route by voice or visual display" refers to technology for instructing a delivery robot on the optimal route by voice announcement or visual display.

[0136] An "incentive" is a reward or benefit given for passing a specific route.

[0137] The present invention describes a specific embodiment of a digital tool called a "Logistics Optimization Navigator" that aims to alleviate congestion and efficiently manage people flow within logistics centers.

[0138] 1. Collecting and transmitting user location information

[0139] Users use a device with GPS functionality, such as a smartphone or smart glasses, to obtain current location information and input destination information. The delivery robot automatically obtains its current location using its built-in GPS, and delivery destination information is pre-registered in the system. For example, assume the current location is "latitude 35.6581 degrees, longitude 139.7017 degrees" and the destination is "latitude 35.6717 degrees, longitude 139.6949 degrees." The device then sends this location information to the server.

[0140] 2. Server generates optimal route

[0141] The server analyzes the received user's current location and destination information and instantly generates an optimal route using a generative AI model (for example, OpenAI's GPT-4). This generative AI model suggests the optimal route for the user to choose based on past delivery data and real-time people flow data. For example, it generates specific routes such as "Route A: via Asakusa Street" and "Route B: via Kuramae Street."

[0142] 3. Providing and displaying the optimal route

[0143] The server composes the generated optimal route information in JSON format and sends it to the terminal. The terminal visually displays the received optimal route to the user, allowing the user to travel safely and efficiently according to the optimal route. The delivery robot is informed of the route by voice and light display.

[0144] 4. Real-time location tracking and route updates

[0145] While moving, the device periodically acquires GPS data and sends its current location information to the server. The server then recalculates and adjusts the optimal route as needed based on the received location information. Real-time location tracking makes it possible to avoid dynamically changing pedestrian flows and crowds.

[0146] 5. Points and Evaluation

[0147] The device sends passing point information to the server each time the user passes through a specific route. The server analyzes the passing data and adds points to the user's account if the user passes through an appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons. In addition, evaluation data is collected and analyzed after delivery is completed and used to generate the next route.

[0148] Specific examples

[0149] The following is a concrete example of a logistics center using this invention. For example, suppose a delivery staff member is currently located at "latitude 35.6581 degrees, longitude 139.7017 degrees" and has set the destination to "latitude 35.6717 degrees, longitude 139.6949 degrees." The user enters this information into a smartphone app and submits it. Based on the received data, the server uses a generative AI model to generate an optimal route, such as "Route A: via Route 1" or "Route B: via Route 2." The generated route information is returned to the terminal in JSON format, and the terminal provides the displayed route to the user. If the user selects Route A and begins traveling, the current location information is updated periodically during the trip, and the route is recalculated to avoid congestion.

[0150] Generative AI model prompt example

[0151] Below are some example prompts that can be input to a generative AI model to generate an optimal route:

[0152] The user's current location is "Latitude 35.6581°, Longitude 139.7017°." The destination is "Latitude 35.6717°, Longitude 139.6949°." According to past delivery data, Kuramae Street was the least crowded at a particular time. Also, real-time people flow data shows that the Asakusa Street route is very congested. Based on this information, please suggest the optimal delivery route.

[0153] This system allows users to travel safely and comfortably, and logistics center managers can achieve efficient people flow management and cost reduction. In this way, the invention can be embodied.

[0154] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0155] Step 1: Enter and send your current location and destination information

[0156] Input: The user inputs their current location and destination information using a smartphone or smart glasses. In the case of a delivery robot, the current location information is obtained from the built-in GPS, and the destination information is pre-registered.

[0157] Specific operation: The user operates the application UI to input and send the current location and destination. The delivery robot automatically obtains the current location and sends the destination information to the server.

[0158] Output: Location and destination information is sent to the server in JSON format.

[0159] Step 2: Data reception and analysis by the server

[0160] Input: Current location and destination information in JSON format.

[0161] Specific operation: The server parses the received JSON data and prepares a dataset to input into the generative AI model.

[0162] Output: Parsed location and destination information.

[0163] Step 3: Generative AI model calculates optimal route

[0164] Input: Parsed location and destination information.

[0165] How it works: The server uses a generative AI model (e.g., GPT-4) to generate prompts and calculate the optimal route. The prompts include the current location, destination, past performance data, and real-time people flow data.

[0166] Output: Optimal route information.

[0167] Step 4: Providing and displaying optimal route information

[0168] Input: Optimal route information.

[0169] Specific operation: The server creates optimal route information in JSON format and sends it to the user's device. The device visually displays the received optimal route. The delivery robot is informed of the route through voice guidance and light displays.

[0170] Output: Optimal route information displayed on the user's device or delivery robot.

[0171] Step 5: Real-time location tracking and route updates

[0172] Input: GPS data acquired while moving.

[0173] How it works: The device periodically sends its current location information to the server, which then uses the generated AI model again based on the received real-time location information to recalculate and adjust the route as needed.

[0174] Output: Updated optimal route information.

[0175] Step 6: Points and evaluation

[0176] Input: location information, passing point information.

[0177] Specific operation: Each time a user passes through a specific route, the device sends the passing point information to the server. The server analyzes the passing data and assigns points to the appropriate user's account. Evaluation data is also collected and used to generate the next route.

[0178] Output: Points earned and rating data.

[0179] Example of a generative AI model prompt

[0180] Here is an example prompt:

[0181] plain text

[0182] The user's current location is "Latitude 35.6581°, Longitude 139.7017°." The destination is "Latitude 35.6717°, Longitude 139.6949°." According to past delivery data, Kuramae Street was the least crowded at a particular time. Also, real-time people flow data shows that the Asakusa Street route is very congested. Based on this information, please suggest the optimal delivery route.

[0183] 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.

[0184] The present invention describes a specific embodiment in which an emotion engine is combined with a digital tool called a "digital checkpoint" for the purpose of congestion relief and people flow management.

[0185] Collecting and transmitting user location information

[0186] A user inputs their current location and destination information using a device with GPS functionality, such as a smartphone or tablet. For example, if a user is participating in a large-scale event, their current location may be "latitude 35.6895 degrees, longitude 139.6917 degrees" (Tokyo) and their destination may be "latitude 35.7100 degrees, longitude 139.8107 degrees" (Skytree). The device then sends this location information to the server.

[0187] Server generates optimal route

[0188] The server analyzes the received user's current location and destination information and instantly generates the optimal route using a generative AI model. The generative AI model suggests the optimal route for the user to choose based on past event data and real-time people flow data. For example, it generates specific routes such as "Route A: via Asakusa Street" and "Route B: via Kuramae Street."

[0189] Combining Emotion Engines

[0190] A distinctive feature of the present invention is that the terminal is equipped with an emotion engine that recognizes the user's emotions. The emotion engine recognizes the user's real-time emotional state by analyzing the user's facial expressions, tone of voice, and other biometric information.

[0191] Real-time emotional information transmission and route adjustment

[0192] The device transmits the user's emotional information recognized by the emotion engine to the server. For example, the server can obtain emotional information such as whether the user is "nervous" or "enjoyed." The server receives this emotional information and adjusts the optimal route based on the user's emotional state.

[0193] Providing and displaying the best route

[0194] The server then formats the generated optimal route information in JSON format and sends it to the device, which then visually displays the received optimal route to the user, allowing the user to travel safely and efficiently according to the optimal route.

[0195] Real-time location tracking and route updates

[0196] While moving, the device periodically acquires GPS data and sends its current location and emotion information to the server. The server recalculates and adjusts the optimal route as needed based on the received location and emotion information. Real-time tracking of location and emotion information enables movement that takes into account dynamically changing pedestrian flow and congestion, as well as the user's emotional state.

[0197] Points and evaluation

[0198] The device sends the passing point information to the server each time the user passes through a checkpoint area. The server analyzes the passing data and emotional information, and if the user passes through the appropriate route, points are added to the user's account. Users can check the points they have earned within the app and exchange them for rewards or coupons.

[0199] Specific examples

[0200] The following is a specific example of an event using this invention. For example, suppose a user participating in a summer festival is currently located at Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees) and has set their destination as Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The user enters this information into a smartphone app and submits it.

[0201] Based on the received data, the server uses a generative AI model and emotion engine to generate optimal routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori." If the user is feeling nervous about a particular route, the server will suggest a route that is less crowded, based on the user's emotions. The generated route information is returned to the device in JSON format, and the device then displays the route to the user.

[0202] When a user selects Route A and starts moving, their current location and emotion information are periodically updated during the movement, and the route is recalculated to avoid congestion and emotional states. When a user passes through a specific checkpoint, the server calculates the passing points, and if the user's emotion is positive, additional points are awarded.

[0203] This system allows users to travel safely and comfortably, and event organizers can reduce congestion and security costs. Furthermore, emotion recognition can increase user satisfaction. This concludes the detailed description of the embodiment of the present invention.

[0204] The processing flow will be explained below.

[0205] Step 1:

[0206] The user starts the app on their smartphone and inputs their current location and destination information. For example, they input their current location as "Shibuya Station" and their destination as "Yoyogi Park."

[0207] Step 2:

[0208] The device uses the GPS function to obtain the latitude and longitude of its current location. The device then sends the current location information and destination information to the server in JSON format.

[0209] Step 3:

[0210] The server receives the current location information and destination information transmitted from the user terminal.

[0211] Step 4:

[0212] The server analyzes the received location information and uses a generative AI model to instantly generate the optimal route from the current location to the destination.

[0213] Step 5:

[0214] The server constructs a response in JSON format containing the generated optimal route information and sends it to the terminal.

[0215] Step 6:

[0216] The device receives the response from the server and visually displays the optimal route to the user, providing specific route details using a map.

[0217] Step 7:

[0218] The user starts moving according to the displayed optimal route. The device periodically acquires GPS data and sends the current location to the server.

[0219] Step 8:

[0220] The device's emotion engine analyzes the user's facial expressions and tone of voice to obtain real-time emotional information, such as whether they are "nervous" or "enjoyed."

[0221] Step 9:

[0222] The device transmits the acquired emotion information to the server, which then receives the user's current location information and emotion information at the same time.

[0223] Step 10:

[0224] The server recalculates or adjusts the optimal route as needed based on the current location and emotion information received in real time. For example, if the user is "nervous," it will suggest a less congested route.

[0225] Step 11:

[0226] When a user passes through a checkpoint area, the device sends the pass point information to the server, which analyzes the pass data and adds points to the user's account if the user passes through the appropriate route.

[0227] Step 12:

[0228] The server also calculates and credits additional points to the user's account when the user is in a positive emotional state, allowing the user to receive rewards according to their emotions.

[0229] Step 13:

[0230] Users can check the points they have earned within the app, which can be exchanged for rewards and coupons.

[0231] In this way, a digital checkpoint system combined with an emotion engine enables users to travel safely and comfortably, and event organizers can reduce congestion and security costs. It also improves the travel experience based on user emotion recognition, increasing satisfaction.

[0232] Example 2

[0233] 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."

[0234] Conventional location information services are limited to basic route suggestions based on the user's current location and destination information, making it difficult to suggest optimal routes that take into account the user's real-time emotional state and dynamically changing people flow information.In addition, there has been a lack of effective people flow management methods, including the use of emotional information to improve event participant satisfaction and the awarding of reward points.

[0235] 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 collecting and transmitting user location information, a means for instantly generating an optimal route from current location information to destination information using a generative AI model, a means for analyzing user emotion information using an emotion engine, a means for adjusting the route based on the user emotion information, and a means for transmitting the generated optimal route information to a user terminal and making it displayable on the user terminal. This makes it possible to propose an optimal route taking into account the user's real-time emotional state and dynamically changing people flow information, thereby improving user satisfaction and reducing congestion at events.

[0236] "User" refers to a person who uses the system.

[0237] "Location information" refers to the latitude and longitude information of the user's current location and destination.

[0238] A "generative AI model" refers to an artificial intelligence model that generates optimal routes based on past data and real-time information.

[0239] "Emotion engine" refers to a function that recognizes a user's emotional state by analyzing their facial expressions, tone of voice, and other biometric information.

[0240] The "optimal route" refers to the optimal travel route from the user's current location to the destination.

[0241] "Server" refers to the central system that analyzes the received data, generates optimal routes using generative AI models and emotion engines, and provides information to user devices.

[0242] "User terminal" refers to a mobile device such as a smartphone or tablet used by a user.

[0243] "Passing points" refer to points awarded when a user passes through a specific checkpoint or route.

[0244] "People flow data" refers to information on people's movements and congestion within a specific area.

[0245] "Optimal route information" refers to data containing details of the generated optimal travel route.

[0246] "JSON format" refers to a format for structuring data and expressing it in a format that is easy to read and write.

[0247] The present invention is a system that combines an emotion engine with digital tools for congestion relief and people flow management. A specific embodiment of this system will be described.

[0248] First, the user launches the dedicated app using a device with GPS functionality, such as a smartphone or tablet. On the app screen, the user enters their current location and destination information. For example, if a user attending a summer festival is currently located at Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees), they can set their destination as Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The entered information is obtained by the device using its GPS function, and this location information is sent to the server.

[0249] The server uses a generative AI model based on the received user's current location and destination information to instantly generate an optimal route. The generative AI model references past event data and real-time people flow data to suggest the optimal route to avoid congestion. For example, it generates specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori."

[0250] Another distinctive feature of this invention is that the device is equipped with an emotion engine that analyzes the user's emotions. The emotion engine uses the smartphone's camera, microphone, and other sensors (heart rate, body temperature, etc.) to analyze the user's real-time emotional state. For example, it can recognize emotions such as "enjoying" or "tense."

[0251] The device periodically sends emotional information analyzed by the emotion engine to the server, which then recalculates the optimal route based on the emotional information and makes adjustments according to the user's emotional state. The server then compiles the generated optimal route information in JSON format and sends it to the device. The device then displays the received information on the screen of a map app or dedicated app, providing the user with the optimal route.

[0252] While moving, the device periodically acquires GPS data and sends its current location and emotion information to the server. This allows the server to monitor dynamically changing pedestrian flow and congestion conditions in real time, recalculating the optimal route as needed. The user's emotion information is also updated, so the optimal route is always based on the latest information.

[0253] When a user passes through a specific checkpoint, the device sends the passage data and emotional information to the server. The server analyzes this information and awards points based on evaluation criteria such as "following the specified route" or "maintaining a positive emotional state." Users can view these points within the app and exchange them for rewards or coupons.

[0254] For example, the following prompts can be used:

[0255] "Please use GPS information to suggest the optimal route between the user's current location and destination. Also, please adjust the route and notify the user based on their emotional state."

[0256] The above is a detailed description of the embodiment of the present invention.

[0257] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0258] Step 1:

[0259] The user launches a dedicated app on their smartphone or tablet device and inputs their current location and destination information. In this case, the user inputs information from "Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees)" to "Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees)." The input information is confirmed using the GPS function of the user's device, and the latitude and longitude data of the current location and destination are collected. The input data is sent to the server.

[0260] Input: Current location and destination information entered by the user

[0261] Output: Location data sent to the server

[0262] Step 2:

[0263] The server uses a generative AI model based on the user's current location and destination information, and references past event data and real-time people flow data. This allows the system to instantly generate the optimal route. For example, the system may suggest specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori."

[0264] Input: current location information, destination information

[0265] Output: Optimal route information (Route A, Route B, etc.)

[0266] Step 3:

[0267] The device is equipped with an emotion engine that analyzes the user's emotions. The user uses the smartphone's camera, microphone, and other sensors, and the emotion engine analyzes the user's facial expressions, tone of voice, and biometric information. For example, the device can recognize the user's emotional state, such as "enjoying" or "tension," in real time.

[0268] Input: User's facial expression, voice, biometric information

[0269] Output: User's emotional information

[0270] Step 4:

[0271] The device sends the user's emotional information collected and analyzed by the emotion engine to the server. The server then uses the received emotional information to recalculate the optimal route. For example, if the server receives information that the user is "nervous," it will adjust the route to suggest a quieter route to avoid congestion.

[0272] Input: User's emotional information

[0273] Output: Re-adjusted optimal route information

[0274] Step 5:

[0275] The server creates the generated optimal route information in JSON format and sends it to the user's device. The device visually displays the received route information on the screen of a dedicated app or map app, notifying the user of the optimal route.

[0276] Input: Optimal route information

[0277] Output: Route information in JSON format sent to the device

[0278] Step 6:

[0279] As the user begins to move along the displayed route, the device periodically acquires GPS data. The device then transmits this current location and emotion information to the server. The server then monitors the dynamically changing pedestrian flow situation based on the real-time location and emotion information, and recalculates and adjusts the optimal route as necessary.

[0280] Input: current location information, emotional information

[0281] Output: Updated optimal route information

[0282] Step 7:

[0283] When a user passes through a certain checkpoint, the device transmits the passing data and emotional information to the server. The server analyzes this information and awards points to the user's account based on appropriate evaluation criteria. At the same time, the user can check the points they have earned within the app and exchange them for rewards or coupons.

[0284] Input: Transit data, emotional information

[0285] Output: Points awarded and evaluation results

[0286] The above is the specific flow of program processing for this system.

[0287] (Application example 2)

[0288] 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."

[0289] Conventional navigation systems were able to provide the optimal route to a destination, but it was difficult to adjust the route taking into account the user's real-time emotional state and dynamically changing surrounding conditions. Therefore, there is a need for a system that allows users to arrive at their destination more comfortably and efficiently, without feeling nervous or anxious.

[0290] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving the user's current location information and destination information; means for instantaneously generating an optimal route from the current location information to the destination information using a generative AI model; means for transmitting the generated optimal route information to the user terminal and making it displayable on the user terminal; a user terminal incorporating an emotion engine that analyzes the user's emotional information in real time; and means for transmitting the user's emotional information to the server and adjusting the optimal route based on the user's emotional state. This allows the user's emotional state to be reflected in real time, enabling more comfortable and safer travel.

[0291] (definition)

[0292] "User's current location information" is digital data that indicates the latitude and longitude of the user's current location.

[0293] "Destination information" is digital data that indicates the latitude and longitude of the location the user is heading for.

[0294] A "generative AI model" is an artificial intelligence model that generates optimal routes based on past and real-time data.

[0295] The "optimal route" refers to a route that allows the user to travel from the current location to the destination efficiently and safely.

[0296] A "user terminal" is an information device used by a user, such as a smartphone, tablet, smart glasses, head-mounted display, or robot.

[0297] An "emotion engine" is an algorithm or software that analyzes a user's emotional state in real time.

[0298] A "server" is a computer system for receiving, analyzing, and transmitting data.

[0299] "Means for real-time adjustment" is a function that instantly recalculates and provides the optimal route based on the user's current situation and emotions.

[0300] This invention relates to a navigation system for an autonomous vehicle, which provides and adjusts an optimal route using location information and emotion information of a user. Specific embodiments are described below.

[0301] System Configuration

[0302] This system consists of a user terminal and a server.

[0303] The user device can be a smartphone or tablet equipped with a GPS module, camera, and microphone, smart glasses, a head-mounted display, or an embedded device in an autonomous vehicle. The user device collects the user's current location information and emotion information and transmits them to the server.

[0304] The server is a computer system that receives, analyzes, and transmits data, and uses web frameworks such as Flask or Django and generative AI models such as TensorFlow or PyTorch.

[0305] Data collection and transmission

[0306] The user device uses a GPS module to collect the user's current location information. The emotion engine also analyzes the user's emotional state in real time based on data acquired by the camera and microphone. This data is then sent to the server at regular intervals.

[0307] Generate and adjust optimal routes

[0308] The server analyzes the received user's current location and destination information and uses a generative AI model to instantly generate an optimal route, which is then sent to the user's display device and displayed visually.

[0309] While traveling, the server continuously receives real-time location and emotion information from the user's device and recalculates and adjusts the optimal route as needed. For example, if the user is nervous, it will suggest a route with fewer crowds.

[0310] Points System

[0311] The server calculates the passing points each time the user passes through a specific route, and if the user's emotional state is positive, the server awards additional points, thereby increasing the user's satisfaction.

[0312] Specific examples

[0313] Consider the case where a user travels from Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees) to Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The user first enters their current location and destination information into a smartphone application. The server then uses the received data to generate an optimal route using a generative AI model and emotion engine. If the emotion engine determines that the user is "nervous," the server will suggest a route that avoids crowded areas.

[0314] Prompt Sentence Examples

[0315] Here are some examples of prompts the server might give to a generative AI model:

[0316] "The user's location information is 'Latitude 35.6581°, Longitude 139.7017°' and the destination is 'Latitude 35.6717°, Longitude 139.6949°'. The user's real-time emotion is 'Tension'. Please suggest three optimal routes with minimal congestion."

[0317] This system allows autonomous vehicles to dynamically adjust their routes according to the user's emotional state, providing a comfortable and safe journey.

[0318] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0319] Step 1:

[0320] The user terminal acquires the current location information (latitude and longitude) using the GPS module. The user inputs the destination information (latitude and longitude) into the terminal.

[0321] Input: User's current location information, destination information

[0322] Output: Current location and destination information are saved on the device.

[0323] Step 2:

[0324] The user device uses a camera and microphone to collect data on the user's facial expressions and voice, and sends it to an emotion engine to analyze the user's emotional state.

[0325] Input: User's facial expression data, voice data

[0326] Output: Analyzed user's emotional information (e.g., nervousness, excitement)

[0327] Step 3:

[0328] The user terminal transmits current location information, destination information, and emotion information to the server.

[0329] Input: current location information, destination information, emotion information

[0330] Output: Data sent to the server

[0331] Step 4:

[0332] The server generates the optimal route by sending prompts to the generative AI model based on the received location and destination information. The prompts include location, destination, and emotion information.

[0333] Input: current location information, destination information, emotion information

[0334] Output: The optimal route generated by the generative AI model

[0335] Step 5:

[0336] The server generates the optimal route in JSON format and sends it to the user's device, which then displays the received optimal route on its screen.

[0337] Input: Optimal route information

[0338] Output: The optimal route displayed on the user's device

[0339] Step 6:

[0340] While moving, the user's device periodically obtains its current location information via GPS and analyzes the emotion information using the emotion engine. This data is then sent back to the server, which then recalculates the optimal route as necessary.

[0341] Input: Real-time location information, emotional information

[0342] Output: Newly adjusted optimal route information

[0343] Step 7:

[0344] The server calculates the user's passing points based on their passing points and emotional information, and adds the points to the user's account. The user's device can then check the point information.

[0345] Input: Passing points, emotional information

[0346] Output: Points awarded to the user

[0347] 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.

[0348] 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.

[0349] 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.

[0350] [Second embodiment]

[0351] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0352] 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.

[0353] 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).

[0354] 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.

[0355] 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.

[0356] 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).

[0357] 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.

[0358] 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.

[0359] 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.

[0360] 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.

[0361] 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.

[0362] 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."

[0363] The present invention describes a specific embodiment of a digital tool, "digital checkpoint," aimed at congestion relief and people flow management.

[0364] Collecting and transmitting user location information

[0365] A user inputs their current location and destination information using a device with GPS functionality, such as a smartphone or tablet. For example, if a user is participating in a large-scale event, their current location may be "latitude 35.6895 degrees, longitude 139.6917 degrees" (Tokyo) and their destination may be "latitude 35.7100 degrees, longitude 139.8107 degrees" (Skytree). The device then sends this location information to the server.

[0366] Server generates optimal route

[0367] The server analyzes the received user's current location and destination information and instantly generates the optimal route using a generative AI model. The generative AI model suggests the optimal route for the user to choose based on past event data and real-time people flow data. For example, it generates specific routes such as "Route A: via Asakusa Street" and "Route B: via Kuramae Street."

[0368] Providing and displaying the best route

[0369] The server then formats the generated optimal route information in JSON format and sends it to the device, which then visually displays the received optimal route to the user, allowing the user to travel safely and efficiently according to the optimal route.

[0370] Real-time location tracking and route updates

[0371] While moving, the device periodically acquires GPS data and sends its current location information to the server. The server then recalculates and adjusts the optimal route as needed based on the received location information. Real-time location tracking makes it possible to avoid dynamically changing pedestrian flows and crowds.

[0372] Points and evaluation

[0373] The device sends the pass point information to the server each time the user passes through a checkpoint area. The server analyzes the pass data and adds points to the user's account if the user has passed through the appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons.

[0374] Specific examples

[0375] The following is a specific example of an event using this invention. For example, suppose a user participating in a summer festival is currently located at Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees) and has set their destination as Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The user enters this information into a smartphone app and submits it.

[0376] Based on the received data, the server uses a generative AI model to generate optimal routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori." The generated route information is returned to the device in JSON format, and the device then provides the displayed route to the user.

[0377] When a user selects Route A and starts moving, the current location information is updated periodically during the movement, and the route is recalculated to avoid congestion. When a user passes through a specific checkpoint, the server calculates the passing points and gives the user points.

[0378] This system allows users to travel safely and comfortably, and event organizers can alleviate congestion and reduce security costs. The above is a detailed description of the embodiment of the present invention.

[0379] The processing flow will be explained below.

[0380] Step 1:

[0381] The user launches the smartphone app, obtains their current location information, enters their destination, and presses the send button.

[0382] Step 2:

[0383] The device uses the built-in GPS to obtain the latitude and longitude of its current location, and then sends the current location and destination information to the server in JSON format.

[0384] Step 3:

[0385] The server receives the current location information and destination information transmitted from the user terminal.

[0386] Step 4:

[0387] The server analyzes the received location information and uses a generative AI model to instantly generate the optimal route from the current location to the destination.

[0388] Step 5:

[0389] The server constructs a response in JSON format containing the generated optimal route information and sends it to the terminal.

[0390] Step 6:

[0391] The device receives the response from the server and visually displays the optimal route to the user, providing specific route details using a map.

[0392] Step 7:

[0393] The user starts moving according to the displayed optimal route. The device periodically acquires GPS data and sends the current location to the server.

[0394] Step 8:

[0395] The server recalculates and adjusts the optimal route as needed based on the current location information received in real time.

[0396] Step 9:

[0397] When a user passes through a checkpoint area, the terminal transmits the passing data to the server, which calculates the passing points and adds them to the user's account.

[0398] Step 10:

[0399] Users can check the points they have earned within the app and exchange them for rewards and coupons.

[0400] Example 1

[0401] 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."

[0402] Conventional people flow management systems not only provide optimal routes while avoiding congestion in real time, but also lack the ability to collect and analyze data during events to proactively propose optimal routes that will be effective for future events. Furthermore, they lack incentive functions that not only provide users with a safe and efficient way to travel, but also track their location information during travel and provide appropriate points. This requires improving user convenience and optimizing people flow management for organizers.

[0403] 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.

[0404] In this invention, the server includes: a means for receiving a user's current location information and destination information; a means for instantly generating an optimal route from the current location information to the destination information based on past and real-time data using a generative AI model; a means for configuring the generated optimal route information, transmitting it to the user's terminal, and visually displaying it on the user's terminal; a means for periodically transmitting current location information from the user's terminal to the server; and a means for recalculating and adjusting the optimal route as needed based on the current location information periodically received by the server. This not only enables users to travel safely and efficiently, but also avoids real-time congestion during travel, allowing organizers to achieve more effective people flow management. It also provides incentives by awarding passing points and collecting data during the event, contributing to the generation of optimal routes for the next event.

[0405] "User" refers to an individual user who uses the system to input location information, check routes, and earn points.

[0406] "Server" refers to the central processing unit that analyzes the data received from the user and generates, recalculates, and adjusts the optimal route using the generative AI model.

[0407] A "generative AI model" refers to an artificial intelligence algorithm that instantly generates the optimal route from a user's location information to their destination information based on past and real-time data.

[0408] "Current location information" refers to latitude and longitude data obtained using the GPS function of the user's device, and indicates the user's current location.

[0409] "Destination information" refers to the latitude and longitude data of the destination that the user inputs into the system.

[0410] An "optimal route" refers to a recommended route that is analyzed and calculated by a generative AI model to help users reach their destination efficiently and safely.

[0411] "User device" refers to a mobile information terminal equipped with GPS functionality used by a user, such as a smartphone or tablet.

[0412] "Data" refers to all types of information used and analyzed by the system, such as user location information, destination information, past event data, and real-time people flow data.

[0413] "Passage point information" refers to information and data recorded each time a user passes through a specific checkpoint area.

[0414] "Points" refer to virtual rewards given to users when they follow a proper route.

[0415] "Benefits and coupons" refer to items that improve convenience, such as rewards and discount coupons that can be exchanged using points earned by users.

[0416] A specific embodiment of the present invention will be described, which provides a digital tool for congestion reduction and people flow management, specifically for enabling users to move around efficiently and safely at events and large gatherings.

[0417] Collecting and transmitting user location information

[0418] A user uses a device with GPS functionality, such as a smartphone or tablet, to input current location information and destination information. The application used in this case provides an interface for inputting location information. Specific information is assumed to be the current location is "latitude 35.6581, longitude 139.7017" (Shibuya Station), and the destination is "latitude 35.6717, longitude 139.6949" (Yoyogi Park). The device sends the input location information to the server as an HTTP request.

[0419] Server generates optimal route

[0420] The server receives the current location and destination information sent by the user and uses a generative AI model to analyze it. This generative AI model instantly generates the optimal travel route based on past event data and real-time people flow data. For example, it generates specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori."

[0421] Providing and displaying the best route

[0422] The server generates optimal route information in JSON format and sends it to the device. The device analyzes the received optimal route information and visually displays it to the user. The user can then select the optimal route from the displayed routes.

[0423] Real-time location tracking and route updates

[0424] When the user starts moving, the device periodically acquires GPS data and sends the current location information to the server. The server recalculates and adjusts the optimal route as needed based on the received current location information. For example, if new congestion occurs during movement, the server generates a new route, sends it to the device, and notifies the user.

[0425] Points and evaluation

[0426] Each time a user passes through a checkpoint area (specific location), the device sends the passing point information to the server. The server analyzes this passing data and awards points to the user if the user has passed through the appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons.

[0427] Specific examples

[0428] The following is a concrete example of an event using this system. For example, suppose a user participating in a summer festival is currently located at Shibuya Station (latitude 35.6581, longitude 139.7017) and has set their destination as Yoyogi Park (latitude 35.6717, longitude 139.6949). The user enters this information into a smartphone app and submits it. Based on the received data, the server uses a generative AI model to generate an optimal route, such as "Route A: via Harajuku" or "Route B: via Meiji Dori." The generated route information is returned to the device in JSON format, and the device provides the displayed route to the user. If the user selects Route A and begins traveling, their current location information is updated periodically during the trip, and the route is recalculated to avoid congestion. When the user passes through a specific checkpoint, the server calculates the passing points and awards the user points.

[0429] Prompt Sentence Examples

[0430] Current location: 35.6581, 139.7017 (Shibuya Station)

[0431] Destination: 35.6717, 139.6949 (Yoyogi Park)

[0432] The above is a specific embodiment for carrying out the invention.

[0433] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0434] Step 1:

[0435] The user launches the application on a device with GPS functionality, such as a smartphone or tablet, and inputs their current location and destination information. Specifically, the current location is "latitude 35.6581, longitude 139.7017" (Shibuya Station), and the destination is "latitude 35.6717, longitude 139.6949" (Yoyogi Park). The device sends this input information to the server as an HTTP request. Input: Current location and destination information entered by the user, Output: Location data in JSON format.

[0436] Step 2:

[0437] The server receives the current location information and destination information sent by the user. To analyze the received location information, the server uses a generative AI model. This generative AI model generates the optimal travel route using past event data and real-time people flow data. For example, specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori" are generated. Input: JSON data of location information from the user, Output: JSON data containing optimal route information.

[0438] Step 3:

[0439] The server composes the generated optimal route information in JSON format and sends it to the terminal. The terminal analyzes the received optimal route information and displays it visually to the user. The user selects the best route from the displayed routes. Input: JSON data containing optimal route information from the server, Output: Data returning the selection result to the user.

[0440] Step 4:

[0441] When the user starts moving, the device periodically acquires GPS data and sends current location information to the server. The server recalculates and adjusts the optimal route as needed based on the received current location information. For example, if unexpected congestion occurs during movement, the server generates a new route and sends it to the device to notify the user. Input: Data on the user's location while moving, Output: Optimal route information recalculated as needed.

[0442] Step 5:

[0443] Each time the user passes through a checkpoint area (specific point), the device sends the passing point information to the server. The server analyzes this passing data and adds points to the user's account if the user has passed through the appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons. Input: Passing points and timestamp information, Output: Passing points and associated reward data.

[0444] (Application example 1)

[0445] 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."

[0446] Conventional logistics centers lacked real-time route optimization for efficient movement of employees and autonomous vehicles, resulting in congestion and delays. This reduced delivery efficiency, increased overall costs, and inefficient operations. Furthermore, there was a need for a system that could dynamically recalculate routes based on on-site congestion and provide appropriate instructions to employees.

[0447] 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.

[0448] In this invention, the server includes a means for receiving a user's current location information and destination information, a means for instantly generating an optimal route from the current location information to the destination information using a generative AI model, a means for transmitting the generated optimal route information to a user terminal and making it displayable on the user terminal, and a means for providing the optimal route to employees or automated vehicles in the logistics center. This enables employees and automated vehicles in the logistics center to travel safely and quickly via the optimal route efficiently. Real-time route updates and congestion avoidance can improve the efficiency of the entire logistics center.

[0449] "User's current location information" refers to data on the geographic coordinates of the user's current location, obtained using GPS or other location information technology.

[0450] "Destination information" is data on the final geographical destination to which the user wishes to travel.

[0451] A "generative AI model" is an artificial intelligence model that automatically generates optimal routes and suggestions based on past and real-time data.

[0452] "Means for updating the optimal route in real time" refers to a mechanism that periodically sends the user's current location information to a server and dynamically recalculates the route based on the latest information.

[0453] The "means for calculating passing points on the optimum route and giving points to the user" is a function that records the user's passing through a specific route and adds up points.

[0454] "Means for providing optimal routes to employees or automated vehicles within a logistics center" refers to a system that provides efficient route instructions to employees and automated vehicles working within a logistics center.

[0455] "Real-time people flow data within a logistics center" is data collected by observing the movement of people and vehicles within the logistics center in real time.

[0456] "Means for informing a delivery robot of the optimal route by voice or visual display" refers to technology for instructing a delivery robot on the optimal route by voice announcement or visual display.

[0457] An "incentive" is a reward or benefit given for passing a specific route.

[0458] The present invention describes a specific embodiment of a digital tool called a "Logistics Optimization Navigator" that aims to alleviate congestion and efficiently manage people flow within logistics centers.

[0459] 1. Collecting and transmitting user location information

[0460] Users use a device with GPS functionality, such as a smartphone or smart glasses, to obtain current location information and input destination information. The delivery robot automatically obtains its current location using its built-in GPS, and delivery destination information is pre-registered in the system. For example, assume the current location is "latitude 35.6581 degrees, longitude 139.7017 degrees" and the destination is "latitude 35.6717 degrees, longitude 139.6949 degrees." The device then sends this location information to the server.

[0461] 2. Server generates optimal route

[0462] The server analyzes the received user's current location and destination information and instantly generates an optimal route using a generative AI model (for example, OpenAI's GPT-4). This generative AI model suggests the optimal route for the user to choose based on past delivery data and real-time people flow data. For example, it generates specific routes such as "Route A: via Asakusa Street" and "Route B: via Kuramae Street."

[0463] 3. Providing and displaying the optimal route

[0464] The server composes the generated optimal route information in JSON format and sends it to the terminal. The terminal visually displays the received optimal route to the user, allowing the user to travel safely and efficiently according to the optimal route. The delivery robot is informed of the route by voice and light display.

[0465] 4. Real-time location tracking and route updates

[0466] While moving, the device periodically acquires GPS data and sends its current location information to the server. The server then recalculates and adjusts the optimal route as needed based on the received location information. Real-time location tracking makes it possible to avoid dynamically changing pedestrian flows and crowds.

[0467] 5. Points and Evaluation

[0468] The device sends passing point information to the server each time the user passes through a specific route. The server analyzes the passing data and adds points to the user's account if the user passes through an appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons. In addition, evaluation data is collected and analyzed after delivery is completed and used to generate the next route.

[0469] Specific examples

[0470] The following is a concrete example of a logistics center using this invention. For example, suppose a delivery staff member is currently located at "latitude 35.6581 degrees, longitude 139.7017 degrees" and has set the destination to "latitude 35.6717 degrees, longitude 139.6949 degrees." The user enters this information into a smartphone app and submits it. Based on the received data, the server uses a generative AI model to generate an optimal route, such as "Route A: via Route 1" or "Route B: via Route 2." The generated route information is returned to the terminal in JSON format, and the terminal provides the displayed route to the user. If the user selects Route A and begins traveling, the current location information is updated periodically during the trip, and the route is recalculated to avoid congestion.

[0471] Generative AI model prompt example

[0472] Below are some example prompts that can be input to a generative AI model to generate an optimal route:

[0473] The user's current location is "Latitude 35.6581°, Longitude 139.7017°." The destination is "Latitude 35.6717°, Longitude 139.6949°." According to past delivery data, Kuramae Street was the least crowded at a particular time. Also, real-time people flow data shows that the Asakusa Street route is very congested. Based on this information, please suggest the optimal delivery route.

[0474] This system allows users to travel safely and comfortably, and logistics center managers can achieve efficient people flow management and cost reduction. In this way, the invention can be embodied.

[0475] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0476] Step 1: Enter and send your current location and destination information

[0477] Input: The user inputs their current location and destination information using a smartphone or smart glasses. In the case of a delivery robot, the current location information is obtained from the built-in GPS, and the destination information is pre-registered.

[0478] Specific operation: The user operates the application UI to input and send the current location and destination. The delivery robot automatically obtains the current location and sends the destination information to the server.

[0479] Output: Location and destination information is sent to the server in JSON format.

[0480] Step 2: Data reception and analysis by the server

[0481] Input: Current location and destination information in JSON format.

[0482] Specific operation: The server parses the received JSON data and prepares a dataset to input into the generative AI model.

[0483] Output: Parsed location and destination information.

[0484] Step 3: Generative AI model calculates optimal route

[0485] Input: Parsed location and destination information.

[0486] How it works: The server uses a generative AI model (e.g., GPT-4) to generate prompts and calculate the optimal route. The prompts include the current location, destination, past performance data, and real-time people flow data.

[0487] Output: Optimal route information.

[0488] Step 4: Providing and displaying optimal route information

[0489] Input: Optimal route information.

[0490] Specific operation: The server creates optimal route information in JSON format and sends it to the user's device. The device visually displays the received optimal route. The delivery robot is informed of the route through voice guidance and light displays.

[0491] Output: Optimal route information displayed on the user's device or delivery robot.

[0492] Step 5: Real-time location tracking and route updates

[0493] Input: GPS data acquired while moving.

[0494] How it works: The device periodically sends its current location information to the server, which then uses the generated AI model again based on the received real-time location information to recalculate and adjust the route as needed.

[0495] Output: Updated optimal route information.

[0496] Step 6: Points and evaluation

[0497] Input: location information, passing point information.

[0498] Specific operation: Each time a user passes through a specific route, the device sends the passing point information to the server. The server analyzes the passing data and assigns points to the appropriate user's account. Evaluation data is also collected and used to generate the next route.

[0499] Output: Points earned and rating data.

[0500] Example of a generative AI model prompt

[0501] Here is an example prompt:

[0502] plain text

[0503] The user's current location is "Latitude 35.6581°, Longitude 139.7017°." The destination is "Latitude 35.6717°, Longitude 139.6949°." According to past delivery data, Kuramae Street was the least crowded at a particular time. Also, real-time people flow data shows that the Asakusa Street route is very congested. Based on this information, please suggest the optimal delivery route.

[0504] 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.

[0505] The present invention describes a specific embodiment in which an emotion engine is combined with a digital tool called a "digital checkpoint" for the purpose of congestion relief and people flow management.

[0506] Collecting and transmitting user location information

[0507] A user inputs their current location and destination information using a device with GPS functionality, such as a smartphone or tablet. For example, if a user is participating in a large-scale event, their current location may be "latitude 35.6895 degrees, longitude 139.6917 degrees" (Tokyo) and their destination may be "latitude 35.7100 degrees, longitude 139.8107 degrees" (Skytree). The device then sends this location information to the server.

[0508] Server generates optimal route

[0509] The server analyzes the received user's current location and destination information and instantly generates the optimal route using a generative AI model. The generative AI model suggests the optimal route for the user to choose based on past event data and real-time people flow data. For example, it generates specific routes such as "Route A: via Asakusa Street" and "Route B: via Kuramae Street."

[0510] Combining Emotion Engines

[0511] A distinctive feature of the present invention is that the terminal is equipped with an emotion engine that recognizes the user's emotions. The emotion engine recognizes the user's real-time emotional state by analyzing the user's facial expressions, tone of voice, and other biometric information.

[0512] Real-time emotional information transmission and route adjustment

[0513] The device transmits the user's emotional information recognized by the emotion engine to the server. For example, the server can obtain emotional information such as whether the user is "nervous" or "enjoyed." The server receives this emotional information and adjusts the optimal route based on the user's emotional state.

[0514] Providing and displaying the best route

[0515] The server then formats the generated optimal route information in JSON format and sends it to the device, which then visually displays the received optimal route to the user, allowing the user to travel safely and efficiently according to the optimal route.

[0516] Real-time location tracking and route updates

[0517] While moving, the device periodically acquires GPS data and sends its current location and emotion information to the server. The server recalculates and adjusts the optimal route as needed based on the received location and emotion information. Real-time tracking of location and emotion information enables movement that takes into account dynamically changing pedestrian flow and congestion, as well as the user's emotional state.

[0518] Points and evaluation

[0519] The device sends the passing point information to the server each time the user passes through a checkpoint area. The server analyzes the passing data and emotional information, and if the user passes through the appropriate route, points are added to the user's account. Users can check the points they have earned within the app and exchange them for rewards or coupons.

[0520] Specific examples

[0521] The following is a specific example of an event using this invention. For example, suppose a user participating in a summer festival is currently located at Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees) and has set their destination as Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The user enters this information into a smartphone app and submits it.

[0522] Based on the received data, the server uses a generative AI model and emotion engine to generate optimal routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori." If the user is feeling nervous about a particular route, the server will suggest a route that is less crowded, based on the user's emotions. The generated route information is returned to the device in JSON format, and the device then displays the route to the user.

[0523] When a user selects Route A and starts moving, their current location and emotion information are periodically updated during the movement, and the route is recalculated to avoid congestion and emotional states. When a user passes through a specific checkpoint, the server calculates the passing points, and if the user's emotion is positive, additional points are awarded.

[0524] This system allows users to travel safely and comfortably, and event organizers can reduce congestion and security costs. Furthermore, emotion recognition can increase user satisfaction. This concludes the detailed description of the embodiment of the present invention.

[0525] The processing flow will be explained below.

[0526] Step 1:

[0527] The user starts the app on their smartphone and inputs their current location and destination information. For example, they input their current location as "Shibuya Station" and their destination as "Yoyogi Park."

[0528] Step 2:

[0529] The device uses the GPS function to obtain the latitude and longitude of its current location. The device then sends the current location information and destination information to the server in JSON format.

[0530] Step 3:

[0531] The server receives the current location information and destination information transmitted from the user terminal.

[0532] Step 4:

[0533] The server analyzes the received location information and uses a generative AI model to instantly generate the optimal route from the current location to the destination.

[0534] Step 5:

[0535] The server constructs a response in JSON format containing the generated optimal route information and sends it to the terminal.

[0536] Step 6:

[0537] The device receives the response from the server and visually displays the optimal route to the user, providing specific route details using a map.

[0538] Step 7:

[0539] The user starts moving according to the displayed optimal route. The device periodically acquires GPS data and sends the current location to the server.

[0540] Step 8:

[0541] The device's emotion engine analyzes the user's facial expressions and tone of voice to obtain real-time emotional information, such as whether they are "nervous" or "enjoyed."

[0542] Step 9:

[0543] The device transmits the acquired emotion information to the server, which then receives the user's current location information and emotion information at the same time.

[0544] Step 10:

[0545] The server recalculates or adjusts the optimal route as needed based on the current location and emotion information received in real time. For example, if the user is "nervous," it will suggest a less congested route.

[0546] Step 11:

[0547] When a user passes through a checkpoint area, the device sends the pass point information to the server, which analyzes the pass data and adds points to the user's account if the user passes through the appropriate route.

[0548] Step 12:

[0549] The server also calculates and credits additional points to the user's account when the user is in a positive emotional state, allowing the user to receive rewards according to their emotions.

[0550] Step 13:

[0551] Users can check the points they have earned within the app, which can be exchanged for rewards and coupons.

[0552] In this way, a digital checkpoint system combined with an emotion engine enables users to travel safely and comfortably, and event organizers can reduce congestion and security costs. It also improves the travel experience based on user emotion recognition, increasing satisfaction.

[0553] Example 2

[0554] 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."

[0555] Conventional location information services are limited to basic route suggestions based on the user's current location and destination information, making it difficult to suggest optimal routes that take into account the user's real-time emotional state and dynamically changing people flow information.In addition, there has been a lack of effective people flow management methods, including the use of emotional information to improve event participant satisfaction and the awarding of reward points.

[0556] 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 collecting and transmitting user location information, a means for instantly generating an optimal route from current location information to destination information using a generative AI model, a means for analyzing user emotion information using an emotion engine, a means for adjusting the route based on the user emotion information, and a means for transmitting the generated optimal route information to a user terminal and making it displayable on the user terminal. This makes it possible to propose an optimal route taking into account the user's real-time emotional state and dynamically changing people flow information, thereby improving user satisfaction and reducing congestion at events.

[0557] "User" refers to a person who uses the system.

[0558] "Location information" refers to the latitude and longitude information of the user's current location and destination.

[0559] A "generative AI model" refers to an artificial intelligence model that generates optimal routes based on past data and real-time information.

[0560] "Emotion engine" refers to a function that recognizes a user's emotional state by analyzing their facial expressions, tone of voice, and other biometric information.

[0561] The "optimal route" refers to the optimal travel route from the user's current location to the destination.

[0562] "Server" refers to the central system that analyzes the received data, generates optimal routes using generative AI models and emotion engines, and provides information to user devices.

[0563] "User terminal" refers to a mobile device such as a smartphone or tablet used by a user.

[0564] "Passing points" refer to points awarded when a user passes through a specific checkpoint or route.

[0565] "People flow data" refers to information on people's movements and congestion within a specific area.

[0566] "Optimal route information" refers to data containing details of the generated optimal travel route.

[0567] "JSON format" refers to a format for structuring data and expressing it in a format that is easy to read and write.

[0568] The present invention is a system that combines an emotion engine with digital tools for congestion relief and people flow management. A specific embodiment of this system will be described.

[0569] First, the user launches the dedicated app using a device with GPS functionality, such as a smartphone or tablet. On the app screen, the user enters their current location and destination information. For example, if a user attending a summer festival is currently located at Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees), they can set their destination as Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The entered information is obtained by the device using its GPS function, and this location information is sent to the server.

[0570] The server uses a generative AI model based on the received user's current location and destination information to instantly generate an optimal route. The generative AI model references past event data and real-time people flow data to suggest the optimal route to avoid congestion. For example, it generates specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori."

[0571] Another distinctive feature of this invention is that the device is equipped with an emotion engine that analyzes the user's emotions. The emotion engine uses the smartphone's camera, microphone, and other sensors (heart rate, body temperature, etc.) to analyze the user's real-time emotional state. For example, it can recognize emotions such as "enjoying" or "tense."

[0572] The device periodically sends emotional information analyzed by the emotion engine to the server, which then recalculates the optimal route based on the emotional information and makes adjustments according to the user's emotional state. The server then compiles the generated optimal route information in JSON format and sends it to the device. The device then displays the received information on the screen of a map app or dedicated app, providing the user with the optimal route.

[0573] While moving, the device periodically acquires GPS data and sends its current location and emotion information to the server. This allows the server to monitor dynamically changing pedestrian flow and congestion conditions in real time, recalculating the optimal route as needed. The user's emotion information is also updated, so the optimal route is always based on the latest information.

[0574] When a user passes through a specific checkpoint, the device sends the passage data and emotional information to the server. The server analyzes this information and awards points based on evaluation criteria such as "following the specified route" or "maintaining a positive emotional state." Users can view these points within the app and exchange them for rewards or coupons.

[0575] For example, the following prompts can be used:

[0576] "Please use GPS information to suggest the optimal route between the user's current location and destination. Also, please adjust the route and notify the user based on their emotional state."

[0577] The above is a detailed description of the embodiment of the present invention.

[0578] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0579] Step 1:

[0580] The user launches a dedicated app on their smartphone or tablet device and inputs their current location and destination information. In this case, the user inputs information from "Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees)" to "Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees)." The input information is confirmed using the GPS function of the user's device, and the latitude and longitude data of the current location and destination are collected. The input data is sent to the server.

[0581] Input: Current location and destination information entered by the user

[0582] Output: Location data sent to the server

[0583] Step 2:

[0584] The server uses a generative AI model based on the user's current location and destination information, and references past event data and real-time people flow data. This allows the system to instantly generate the optimal route. For example, the system may suggest specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori."

[0585] Input: current location information, destination information

[0586] Output: Optimal route information (Route A, Route B, etc.)

[0587] Step 3:

[0588] The device is equipped with an emotion engine that analyzes the user's emotions. The user uses the smartphone's camera, microphone, and other sensors, and the emotion engine analyzes the user's facial expressions, tone of voice, and biometric information. For example, the device can recognize the user's emotional state, such as "enjoying" or "tension," in real time.

[0589] Input: User's facial expression, voice, biometric information

[0590] Output: User's emotional information

[0591] Step 4:

[0592] The device sends the user's emotional information collected and analyzed by the emotion engine to the server. The server then uses the received emotional information to recalculate the optimal route. For example, if the server receives information that the user is "nervous," it will adjust the route to suggest a quieter route to avoid congestion.

[0593] Input: User's emotional information

[0594] Output: Re-adjusted optimal route information

[0595] Step 5:

[0596] The server creates the generated optimal route information in JSON format and sends it to the user's device. The device visually displays the received route information on the screen of a dedicated app or map app, notifying the user of the optimal route.

[0597] Input: Optimal route information

[0598] Output: Route information in JSON format sent to the device

[0599] Step 6:

[0600] As the user begins to move along the displayed route, the device periodically acquires GPS data. The device then transmits this current location and emotion information to the server. The server then monitors the dynamically changing pedestrian flow situation based on the real-time location and emotion information, and recalculates and adjusts the optimal route as necessary.

[0601] Input: current location information, emotional information

[0602] Output: Updated optimal route information

[0603] Step 7:

[0604] When a user passes through a certain checkpoint, the device transmits the passing data and emotional information to the server. The server analyzes this information and awards points to the user's account based on appropriate evaluation criteria. At the same time, the user can check the points they have earned within the app and exchange them for rewards or coupons.

[0605] Input: Transit data, emotional information

[0606] Output: Points awarded and evaluation results

[0607] The above is the specific flow of program processing for this system.

[0608] (Application example 2)

[0609] 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."

[0610] Conventional navigation systems were able to provide the optimal route to a destination, but it was difficult to adjust the route taking into account the user's real-time emotional state and dynamically changing surrounding conditions. Therefore, there is a need for a system that allows users to arrive at their destination more comfortably and efficiently, without feeling nervous or anxious.

[0611] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving the user's current location information and destination information; means for instantaneously generating an optimal route from the current location information to the destination information using a generative AI model; means for transmitting the generated optimal route information to the user terminal and making it displayable on the user terminal; a user terminal incorporating an emotion engine that analyzes the user's emotional information in real time; and means for transmitting the user's emotional information to the server and adjusting the optimal route based on the user's emotional state. This allows the user's emotional state to be reflected in real time, enabling more comfortable and safer travel.

[0612] (definition)

[0613] "User's current location information" is digital data that indicates the latitude and longitude of the user's current location.

[0614] "Destination information" is digital data that indicates the latitude and longitude of the location the user is heading for.

[0615] A "generative AI model" is an artificial intelligence model that generates optimal routes based on past and real-time data.

[0616] The "optimal route" refers to a route that allows the user to travel from the current location to the destination efficiently and safely.

[0617] A "user terminal" is an information device used by a user, such as a smartphone, tablet, smart glasses, head-mounted display, or robot.

[0618] An "emotion engine" is an algorithm or software that analyzes a user's emotional state in real time.

[0619] A "server" is a computer system for receiving, analyzing, and transmitting data.

[0620] "Means for real-time adjustment" is a function that instantly recalculates and provides the optimal route based on the user's current situation and emotions.

[0621] This invention relates to a navigation system for an autonomous vehicle, which provides and adjusts an optimal route using location information and emotion information of a user. Specific embodiments are described below.

[0622] System Configuration

[0623] This system consists of a user terminal and a server.

[0624] The user device can be a smartphone or tablet equipped with a GPS module, camera, and microphone, smart glasses, a head-mounted display, or an embedded device in an autonomous vehicle. The user device collects the user's current location information and emotion information and transmits them to the server.

[0625] The server is a computer system that receives, analyzes, and transmits data, and uses web frameworks such as Flask or Django and generative AI models such as TensorFlow or PyTorch.

[0626] Data collection and transmission

[0627] The user device uses a GPS module to collect the user's current location information. The emotion engine also analyzes the user's emotional state in real time based on data acquired by the camera and microphone. This data is then sent to the server at regular intervals.

[0628] Generate and adjust optimal routes

[0629] The server analyzes the received user's current location and destination information and uses a generative AI model to instantly generate an optimal route, which is then sent to the user's display device and displayed visually.

[0630] While traveling, the server continuously receives real-time location and emotion information from the user's device and recalculates and adjusts the optimal route as needed. For example, if the user is nervous, it will suggest a route with fewer crowds.

[0631] Points System

[0632] The server calculates the passing points each time the user passes through a specific route, and if the user's emotional state is positive, the server awards additional points, thereby increasing the user's satisfaction.

[0633] Specific examples

[0634] Consider the case where a user travels from Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees) to Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The user first enters their current location and destination information into a smartphone application. The server then uses the received data to generate an optimal route using a generative AI model and emotion engine. If the emotion engine determines that the user is "nervous," the server will suggest a route that avoids crowded areas.

[0635] Prompt Sentence Examples

[0636] Here are some examples of prompts the server might give to a generative AI model:

[0637] "The user's location information is 'Latitude 35.6581°, Longitude 139.7017°' and the destination is 'Latitude 35.6717°, Longitude 139.6949°'. The user's real-time emotion is 'Tension'. Please suggest three optimal routes with minimal congestion."

[0638] This system allows autonomous vehicles to dynamically adjust their routes according to the user's emotional state, providing a comfortable and safe journey.

[0639] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0640] Step 1:

[0641] The user terminal acquires the current location information (latitude and longitude) using the GPS module. The user inputs the destination information (latitude and longitude) into the terminal.

[0642] Input: User's current location information, destination information

[0643] Output: Current location and destination information are saved on the device.

[0644] Step 2:

[0645] The user device uses a camera and microphone to collect data on the user's facial expressions and voice, and sends it to an emotion engine to analyze the user's emotional state.

[0646] Input: User's facial expression data, voice data

[0647] Output: Analyzed user's emotional information (e.g., nervousness, excitement)

[0648] Step 3:

[0649] The user terminal transmits current location information, destination information, and emotion information to the server.

[0650] Input: current location information, destination information, emotion information

[0651] Output: Data sent to the server

[0652] Step 4:

[0653] The server generates the optimal route by sending prompts to the generative AI model based on the received location and destination information. The prompts include location, destination, and emotion information.

[0654] Input: current location information, destination information, emotion information

[0655] Output: The optimal route generated by the generative AI model

[0656] Step 5:

[0657] The server generates the optimal route in JSON format and sends it to the user's device, which then displays the received optimal route on its screen.

[0658] Input: Optimal route information

[0659] Output: The optimal route displayed on the user's device

[0660] Step 6:

[0661] While moving, the user's device periodically obtains its current location information via GPS and analyzes the emotion information using the emotion engine. This data is then sent back to the server, which then recalculates the optimal route as necessary.

[0662] Input: Real-time location information, emotional information

[0663] Output: Newly adjusted optimal route information

[0664] Step 7:

[0665] The server calculates the user's passing points based on their passing points and emotional information, and adds the points to the user's account. The user's device can then check the point information.

[0666] Input: Passing points, emotional information

[0667] Output: Points awarded to the user

[0668] 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.

[0669] 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.

[0670] 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.

[0671] [Third embodiment]

[0672] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0673] 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.

[0674] 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).

[0675] 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.

[0676] 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.

[0677] 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).

[0678] 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.

[0679] 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.

[0680] 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.

[0681] 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.

[0682] 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.

[0683] 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."

[0684] The present invention describes a specific embodiment of a digital tool, "digital checkpoint," aimed at congestion relief and people flow management.

[0685] Collecting and transmitting user location information

[0686] A user inputs their current location and destination information using a device with GPS functionality, such as a smartphone or tablet. For example, if a user is participating in a large-scale event, their current location may be "latitude 35.6895 degrees, longitude 139.6917 degrees" (Tokyo) and their destination may be "latitude 35.7100 degrees, longitude 139.8107 degrees" (Skytree). The device then sends this location information to the server.

[0687] Server generates optimal route

[0688] The server analyzes the received user's current location and destination information and instantly generates the optimal route using a generative AI model. The generative AI model suggests the optimal route for the user to choose based on past event data and real-time people flow data. For example, it generates specific routes such as "Route A: via Asakusa Street" and "Route B: via Kuramae Street."

[0689] Providing and displaying the best route

[0690] The server then formats the generated optimal route information in JSON format and sends it to the device, which then visually displays the received optimal route to the user, allowing the user to travel safely and efficiently according to the optimal route.

[0691] Real-time location tracking and route updates

[0692] While moving, the device periodically acquires GPS data and sends its current location information to the server. The server then recalculates and adjusts the optimal route as needed based on the received location information. Real-time location tracking makes it possible to avoid dynamically changing pedestrian flows and crowds.

[0693] Points and evaluation

[0694] The device sends the pass point information to the server each time the user passes through a checkpoint area. The server analyzes the pass data and adds points to the user's account if the user has passed through the appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons.

[0695] Specific examples

[0696] The following is a specific example of an event using this invention. For example, suppose a user participating in a summer festival is currently located at Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees) and has set their destination as Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The user enters this information into a smartphone app and submits it.

[0697] Based on the received data, the server uses a generative AI model to generate optimal routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori." The generated route information is returned to the device in JSON format, and the device then provides the displayed route to the user.

[0698] When a user selects Route A and starts moving, the current location information is updated periodically during the movement, and the route is recalculated to avoid congestion. When a user passes through a specific checkpoint, the server calculates the passing points and gives the user points.

[0699] This system allows users to travel safely and comfortably, and event organizers can alleviate congestion and reduce security costs. The above is a detailed description of the embodiment of the present invention.

[0700] The processing flow will be explained below.

[0701] Step 1:

[0702] The user launches the smartphone app, obtains their current location information, enters their destination, and presses the send button.

[0703] Step 2:

[0704] The device uses the built-in GPS to obtain the latitude and longitude of its current location, and then sends the current location and destination information to the server in JSON format.

[0705] Step 3:

[0706] The server receives the current location information and destination information transmitted from the user terminal.

[0707] Step 4:

[0708] The server analyzes the received location information and uses a generative AI model to instantly generate the optimal route from the current location to the destination.

[0709] Step 5:

[0710] The server constructs a response in JSON format containing the generated optimal route information and sends it to the terminal.

[0711] Step 6:

[0712] The device receives the response from the server and visually displays the optimal route to the user, providing specific route details using a map.

[0713] Step 7:

[0714] The user starts moving according to the displayed optimal route. The device periodically acquires GPS data and sends the current location to the server.

[0715] Step 8:

[0716] The server recalculates and adjusts the optimal route as needed based on the current location information received in real time.

[0717] Step 9:

[0718] When a user passes through a checkpoint area, the terminal transmits the passing data to the server, which calculates the passing points and adds them to the user's account.

[0719] Step 10:

[0720] Users can check the points they have earned within the app and exchange them for rewards and coupons.

[0721] Example 1

[0722] 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."

[0723] Conventional people flow management systems not only provide optimal routes while avoiding congestion in real time, but also lack the ability to collect and analyze data during events to proactively propose optimal routes that will be effective for future events. Furthermore, they lack incentive functions that not only provide users with a safe and efficient way to travel, but also track their location information during travel and provide appropriate points. This requires improving user convenience and optimizing people flow management for organizers.

[0724] 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.

[0725] In this invention, the server includes: a means for receiving a user's current location information and destination information; a means for instantly generating an optimal route from the current location information to the destination information based on past and real-time data using a generative AI model; a means for configuring the generated optimal route information, transmitting it to the user's terminal, and visually displaying it on the user's terminal; a means for periodically transmitting current location information from the user's terminal to the server; and a means for recalculating and adjusting the optimal route as needed based on the current location information periodically received by the server. This not only enables users to travel safely and efficiently, but also avoids real-time congestion during travel, allowing organizers to achieve more effective people flow management. It also provides incentives by awarding passing points and collecting data during the event, contributing to the generation of optimal routes for the next event.

[0726] "User" refers to an individual user who uses the system to input location information, check routes, and earn points.

[0727] "Server" refers to the central processing unit that analyzes the data received from the user and generates, recalculates, and adjusts the optimal route using the generative AI model.

[0728] A "generative AI model" refers to an artificial intelligence algorithm that instantly generates the optimal route from a user's location information to their destination information based on past and real-time data.

[0729] "Current location information" refers to latitude and longitude data obtained using the GPS function of the user's device, and indicates the user's current location.

[0730] "Destination information" refers to the latitude and longitude data of the destination that the user inputs into the system.

[0731] An "optimal route" refers to a recommended route that is analyzed and calculated by a generative AI model to help users reach their destination efficiently and safely.

[0732] "User device" refers to a mobile information terminal equipped with GPS functionality used by a user, such as a smartphone or tablet.

[0733] "Data" refers to all types of information used and analyzed by the system, such as user location information, destination information, past event data, and real-time people flow data.

[0734] "Passage point information" refers to information and data recorded each time a user passes through a specific checkpoint area.

[0735] "Points" refer to virtual rewards given to users when they follow a proper route.

[0736] "Benefits and coupons" refer to items that improve convenience, such as rewards and discount coupons that can be exchanged using points earned by users.

[0737] A specific embodiment of the present invention will be described, which provides a digital tool for congestion reduction and people flow management, specifically for enabling users to move around efficiently and safely at events and large gatherings.

[0738] Collecting and transmitting user location information

[0739] A user uses a device with GPS functionality, such as a smartphone or tablet, to input current location information and destination information. The application used in this case provides an interface for inputting location information. Specific information is assumed to be the current location is "latitude 35.6581, longitude 139.7017" (Shibuya Station), and the destination is "latitude 35.6717, longitude 139.6949" (Yoyogi Park). The device sends the input location information to the server as an HTTP request.

[0740] Server generates optimal route

[0741] The server receives the current location and destination information sent by the user and uses a generative AI model to analyze it. This generative AI model instantly generates the optimal travel route based on past event data and real-time people flow data. For example, it generates specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori."

[0742] Providing and displaying the best route

[0743] The server generates optimal route information in JSON format and sends it to the device. The device analyzes the received optimal route information and visually displays it to the user. The user can then select the optimal route from the displayed routes.

[0744] Real-time location tracking and route updates

[0745] When the user starts moving, the device periodically acquires GPS data and sends the current location information to the server. The server recalculates and adjusts the optimal route as needed based on the received current location information. For example, if new congestion occurs during movement, the server generates a new route, sends it to the device, and notifies the user.

[0746] Points and evaluation

[0747] Each time a user passes through a checkpoint area (specific location), the device sends the passing point information to the server. The server analyzes this passing data and awards points to the user if the user has passed through the appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons.

[0748] Specific examples

[0749] The following is a concrete example of an event using this system. For example, suppose a user participating in a summer festival is currently located at Shibuya Station (latitude 35.6581, longitude 139.7017) and has set their destination as Yoyogi Park (latitude 35.6717, longitude 139.6949). The user enters this information into a smartphone app and submits it. Based on the received data, the server uses a generative AI model to generate an optimal route, such as "Route A: via Harajuku" or "Route B: via Meiji Dori." The generated route information is returned to the device in JSON format, and the device provides the displayed route to the user. If the user selects Route A and begins traveling, their current location information is updated periodically during the trip, and the route is recalculated to avoid congestion. When the user passes through a specific checkpoint, the server calculates the passing points and awards the user points.

[0750] Prompt Sentence Examples

[0751] Current location: 35.6581, 139.7017 (Shibuya Station)

[0752] Destination: 35.6717, 139.6949 (Yoyogi Park)

[0753] The above is a specific embodiment for carrying out the invention.

[0754] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0755] Step 1:

[0756] The user launches the application on a device with GPS functionality, such as a smartphone or tablet, and inputs their current location and destination information. Specifically, the current location is "latitude 35.6581, longitude 139.7017" (Shibuya Station), and the destination is "latitude 35.6717, longitude 139.6949" (Yoyogi Park). The device sends this input information to the server as an HTTP request. Input: Current location and destination information entered by the user, Output: Location data in JSON format.

[0757] Step 2:

[0758] The server receives the current location information and destination information sent by the user. To analyze the received location information, the server uses a generative AI model. This generative AI model generates the optimal travel route using past event data and real-time people flow data. For example, specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori" are generated. Input: JSON data of location information from the user, Output: JSON data containing optimal route information.

[0759] Step 3:

[0760] The server composes the generated optimal route information in JSON format and sends it to the terminal. The terminal analyzes the received optimal route information and displays it visually to the user. The user selects the best route from the displayed routes. Input: JSON data containing optimal route information from the server, Output: Data returning the selection result to the user.

[0761] Step 4:

[0762] When the user starts moving, the device periodically acquires GPS data and sends current location information to the server. The server recalculates and adjusts the optimal route as needed based on the received current location information. For example, if unexpected congestion occurs during movement, the server generates a new route and sends it to the device to notify the user. Input: Data on the user's location while moving, Output: Optimal route information recalculated as needed.

[0763] Step 5:

[0764] Each time the user passes through a checkpoint area (specific point), the device sends the passing point information to the server. The server analyzes this passing data and adds points to the user's account if the user has passed through the appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons. Input: Passing points and timestamp information, Output: Passing points and associated reward data.

[0765] (Application example 1)

[0766] 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."

[0767] Conventional logistics centers lacked real-time route optimization for efficient movement of employees and autonomous vehicles, resulting in congestion and delays. This reduced delivery efficiency, increased overall costs, and inefficient operations. Furthermore, there was a need for a system that could dynamically recalculate routes based on on-site congestion and provide appropriate instructions to employees.

[0768] 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.

[0769] In this invention, the server includes a means for receiving a user's current location information and destination information, a means for instantly generating an optimal route from the current location information to the destination information using a generative AI model, a means for transmitting the generated optimal route information to a user terminal and making it displayable on the user terminal, and a means for providing the optimal route to employees or automated vehicles in the logistics center. This enables employees and automated vehicles in the logistics center to travel safely and quickly via the optimal route efficiently. Real-time route updates and congestion avoidance can improve the efficiency of the entire logistics center.

[0770] "User's current location information" refers to data on the geographic coordinates of the user's current location, obtained using GPS or other location information technology.

[0771] "Destination information" is data on the final geographical destination to which the user wishes to travel.

[0772] A "generative AI model" is an artificial intelligence model that automatically generates optimal routes and suggestions based on past and real-time data.

[0773] "Means for updating the optimal route in real time" refers to a mechanism that periodically sends the user's current location information to a server and dynamically recalculates the route based on the latest information.

[0774] The "means for calculating passing points on the optimum route and giving points to the user" is a function that records the user's passing through a specific route and adds up points.

[0775] "Means for providing optimal routes to employees or automated vehicles within a logistics center" refers to a system that provides efficient route instructions to employees and automated vehicles working within a logistics center.

[0776] "Real-time people flow data within a logistics center" is data collected by observing the movement of people and vehicles within the logistics center in real time.

[0777] "Means for informing a delivery robot of the optimal route by voice or visual display" refers to technology for instructing a delivery robot on the optimal route by voice announcement or visual display.

[0778] An "incentive" is a reward or benefit given for passing a specific route.

[0779] The present invention describes a specific embodiment of a digital tool called a "Logistics Optimization Navigator" that aims to alleviate congestion and efficiently manage people flow within logistics centers.

[0780] 1. Collecting and transmitting user location information

[0781] Users use a device with GPS functionality, such as a smartphone or smart glasses, to obtain current location information and input destination information. The delivery robot automatically obtains its current location using its built-in GPS, and delivery destination information is pre-registered in the system. For example, assume the current location is "latitude 35.6581 degrees, longitude 139.7017 degrees" and the destination is "latitude 35.6717 degrees, longitude 139.6949 degrees." The device then sends this location information to the server.

[0782] 2. Server generates optimal route

[0783] The server analyzes the received user's current location and destination information and instantly generates an optimal route using a generative AI model (for example, OpenAI's GPT-4). This generative AI model suggests the optimal route for the user to choose based on past delivery data and real-time people flow data. For example, it generates specific routes such as "Route A: via Asakusa Street" and "Route B: via Kuramae Street."

[0784] 3. Providing and displaying the optimal route

[0785] The server composes the generated optimal route information in JSON format and sends it to the terminal. The terminal visually displays the received optimal route to the user, allowing the user to travel safely and efficiently according to the optimal route. The delivery robot is informed of the route by voice and light display.

[0786] 4. Real-time location tracking and route updates

[0787] While moving, the device periodically acquires GPS data and sends its current location information to the server. The server then recalculates and adjusts the optimal route as needed based on the received location information. Real-time location tracking makes it possible to avoid dynamically changing pedestrian flows and crowds.

[0788] 5. Points and Evaluation

[0789] The device sends passing point information to the server each time the user passes through a specific route. The server analyzes the passing data and adds points to the user's account if the user passes through an appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons. In addition, evaluation data is collected and analyzed after delivery is completed and used to generate the next route.

[0790] Specific examples

[0791] The following is a concrete example of a logistics center using this invention. For example, suppose a delivery staff member is currently located at "latitude 35.6581 degrees, longitude 139.7017 degrees" and has set the destination to "latitude 35.6717 degrees, longitude 139.6949 degrees." The user enters this information into a smartphone app and submits it. Based on the received data, the server uses a generative AI model to generate an optimal route, such as "Route A: via Route 1" or "Route B: via Route 2." The generated route information is returned to the terminal in JSON format, and the terminal provides the displayed route to the user. If the user selects Route A and begins traveling, the current location information is updated periodically during the trip, and the route is recalculated to avoid congestion.

[0792] Generative AI model prompt example

[0793] Below are some example prompts that can be input to a generative AI model to generate an optimal route:

[0794] The user's current location is "Latitude 35.6581°, Longitude 139.7017°." The destination is "Latitude 35.6717°, Longitude 139.6949°." According to past delivery data, Kuramae Street was the least crowded at a particular time. Also, real-time people flow data shows that the Asakusa Street route is very congested. Based on this information, please suggest the optimal delivery route.

[0795] This system allows users to travel safely and comfortably, and logistics center managers can achieve efficient people flow management and cost reduction. In this way, the invention can be embodied.

[0796] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0797] Step 1: Enter and send your current location and destination information

[0798] Input: The user inputs their current location and destination information using a smartphone or smart glasses. In the case of a delivery robot, the current location information is obtained from the built-in GPS, and the destination information is pre-registered.

[0799] Specific operation: The user operates the application UI to input and send the current location and destination. The delivery robot automatically obtains the current location and sends the destination information to the server.

[0800] Output: Location and destination information is sent to the server in JSON format.

[0801] Step 2: Data reception and analysis by the server

[0802] Input: Current location and destination information in JSON format.

[0803] Specific operation: The server parses the received JSON data and prepares a dataset to input into the generative AI model.

[0804] Output: Parsed location and destination information.

[0805] Step 3: Generative AI model calculates optimal route

[0806] Input: Parsed location and destination information.

[0807] How it works: The server uses a generative AI model (e.g., GPT-4) to generate prompts and calculate the optimal route. The prompts include the current location, destination, past performance data, and real-time people flow data.

[0808] Output: Optimal route information.

[0809] Step 4: Providing and displaying optimal route information

[0810] Input: Optimal route information.

[0811] Specific operation: The server creates optimal route information in JSON format and sends it to the user's device. The device visually displays the received optimal route. The delivery robot is informed of the route through voice guidance and light displays.

[0812] Output: Optimal route information displayed on the user's device or delivery robot.

[0813] Step 5: Real-time location tracking and route updates

[0814] Input: GPS data acquired while moving.

[0815] How it works: The device periodically sends its current location information to the server, which then uses the generated AI model again based on the received real-time location information to recalculate and adjust the route as needed.

[0816] Output: Updated optimal route information.

[0817] Step 6: Points and evaluation

[0818] Input: location information, passing point information.

[0819] Specific operation: Each time a user passes through a specific route, the device sends the passing point information to the server. The server analyzes the passing data and assigns points to the appropriate user's account. Evaluation data is also collected and used to generate the next route.

[0820] Output: Points earned and rating data.

[0821] Example of a generative AI model prompt

[0822] Here is an example prompt:

[0823] plain text

[0824] The user's current location is "Latitude 35.6581°, Longitude 139.7017°." The destination is "Latitude 35.6717°, Longitude 139.6949°." According to past delivery data, Kuramae Street was the least crowded at a particular time. Also, real-time people flow data shows that the Asakusa Street route is very congested. Based on this information, please suggest the optimal delivery route.

[0825] 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.

[0826] The present invention describes a specific embodiment in which an emotion engine is combined with a digital tool called a "digital checkpoint" for the purpose of congestion relief and people flow management.

[0827] Collecting and transmitting user location information

[0828] A user inputs their current location and destination information using a device with GPS functionality, such as a smartphone or tablet. For example, if a user is participating in a large-scale event, their current location may be "latitude 35.6895 degrees, longitude 139.6917 degrees" (Tokyo) and their destination may be "latitude 35.7100 degrees, longitude 139.8107 degrees" (Skytree). The device then sends this location information to the server.

[0829] Server generates optimal route

[0830] The server analyzes the received user's current location and destination information and instantly generates the optimal route using a generative AI model. The generative AI model suggests the optimal route for the user to choose based on past event data and real-time people flow data. For example, it generates specific routes such as "Route A: via Asakusa Street" and "Route B: via Kuramae Street."

[0831] Combining Emotion Engines

[0832] A distinctive feature of the present invention is that the terminal is equipped with an emotion engine that recognizes the user's emotions. The emotion engine recognizes the user's real-time emotional state by analyzing the user's facial expressions, tone of voice, and other biometric information.

[0833] Real-time emotional information transmission and route adjustment

[0834] The device transmits the user's emotional information recognized by the emotion engine to the server. For example, the server can obtain emotional information such as whether the user is "nervous" or "enjoyed." The server receives this emotional information and adjusts the optimal route based on the user's emotional state.

[0835] Providing and displaying the best route

[0836] The server then formats the generated optimal route information in JSON format and sends it to the device, which then visually displays the received optimal route to the user, allowing the user to travel safely and efficiently according to the optimal route.

[0837] Real-time location tracking and route updates

[0838] While moving, the device periodically acquires GPS data and sends its current location and emotion information to the server. The server recalculates and adjusts the optimal route as needed based on the received location and emotion information. Real-time tracking of location and emotion information enables movement that takes into account dynamically changing pedestrian flow and congestion, as well as the user's emotional state.

[0839] Points and evaluation

[0840] The device sends the passing point information to the server each time the user passes through a checkpoint area. The server analyzes the passing data and emotional information, and if the user passes through the appropriate route, points are added to the user's account. Users can check the points they have earned within the app and exchange them for rewards or coupons.

[0841] Specific examples

[0842] The following is a specific example of an event using this invention. For example, suppose a user participating in a summer festival is currently located at Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees) and has set their destination as Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The user enters this information into a smartphone app and submits it.

[0843] Based on the received data, the server uses a generative AI model and emotion engine to generate optimal routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori." If the user is feeling nervous about a particular route, the server will suggest a route that is less crowded, based on the user's emotions. The generated route information is returned to the device in JSON format, and the device then displays the route to the user.

[0844] When a user selects Route A and starts moving, their current location and emotion information are periodically updated during the movement, and the route is recalculated to avoid congestion and emotional states. When a user passes through a specific checkpoint, the server calculates the passing points, and if the user's emotion is positive, additional points are awarded.

[0845] This system allows users to travel safely and comfortably, and event organizers can reduce congestion and security costs. Furthermore, emotion recognition can increase user satisfaction. This concludes the detailed description of the embodiment of the present invention.

[0846] The processing flow will be explained below.

[0847] Step 1:

[0848] The user starts the app on their smartphone and inputs their current location and destination information. For example, they input their current location as "Shibuya Station" and their destination as "Yoyogi Park."

[0849] Step 2:

[0850] The device uses the GPS function to obtain the latitude and longitude of its current location. The device then sends the current location information and destination information to the server in JSON format.

[0851] Step 3:

[0852] The server receives the current location information and destination information transmitted from the user terminal.

[0853] Step 4:

[0854] The server analyzes the received location information and uses a generative AI model to instantly generate the optimal route from the current location to the destination.

[0855] Step 5:

[0856] The server constructs a response in JSON format containing the generated optimal route information and sends it to the terminal.

[0857] Step 6:

[0858] The device receives the response from the server and visually displays the optimal route to the user, providing specific route details using a map.

[0859] Step 7:

[0860] The user starts moving according to the displayed optimal route. The device periodically acquires GPS data and sends the current location to the server.

[0861] Step 8:

[0862] The device's emotion engine analyzes the user's facial expressions and tone of voice to obtain real-time emotional information, such as whether they are "nervous" or "enjoyed."

[0863] Step 9:

[0864] The device transmits the acquired emotion information to the server, which then receives the user's current location information and emotion information at the same time.

[0865] Step 10:

[0866] The server recalculates or adjusts the optimal route as needed based on the current location and emotion information received in real time. For example, if the user is "nervous," it will suggest a less congested route.

[0867] Step 11:

[0868] When a user passes through a checkpoint area, the device sends the pass point information to the server, which analyzes the pass data and adds points to the user's account if the user passes through the appropriate route.

[0869] Step 12:

[0870] The server also calculates and credits additional points to the user's account when the user is in a positive emotional state, allowing the user to receive rewards according to their emotions.

[0871] Step 13:

[0872] Users can check the points they have earned within the app, which can be exchanged for rewards and coupons.

[0873] In this way, a digital checkpoint system combined with an emotion engine enables users to travel safely and comfortably, and event organizers can reduce congestion and security costs. It also improves the travel experience based on user emotion recognition, increasing satisfaction.

[0874] Example 2

[0875] 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."

[0876] Conventional location information services are limited to basic route suggestions based on the user's current location and destination information, making it difficult to suggest optimal routes that take into account the user's real-time emotional state and dynamically changing people flow information.In addition, there has been a lack of effective people flow management methods, including the use of emotional information to improve event participant satisfaction and the awarding of reward points.

[0877] 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 collecting and transmitting user location information, a means for instantly generating an optimal route from current location information to destination information using a generative AI model, a means for analyzing user emotion information using an emotion engine, a means for adjusting the route based on the user emotion information, and a means for transmitting the generated optimal route information to a user terminal and making it displayable on the user terminal. This makes it possible to propose an optimal route taking into account the user's real-time emotional state and dynamically changing people flow information, thereby improving user satisfaction and reducing congestion at events.

[0878] "User" refers to a person who uses the system.

[0879] "Location information" refers to the latitude and longitude information of the user's current location and destination.

[0880] A "generative AI model" refers to an artificial intelligence model that generates optimal routes based on past data and real-time information.

[0881] "Emotion engine" refers to a function that recognizes a user's emotional state by analyzing their facial expressions, tone of voice, and other biometric information.

[0882] The "optimal route" refers to the optimal travel route from the user's current location to the destination.

[0883] "Server" refers to the central system that analyzes the received data, generates optimal routes using generative AI models and emotion engines, and provides information to user devices.

[0884] "User terminal" refers to a mobile device such as a smartphone or tablet used by a user.

[0885] "Passing points" refer to points awarded when a user passes through a specific checkpoint or route.

[0886] "People flow data" refers to information on people's movements and congestion within a specific area.

[0887] "Optimal route information" refers to data containing details of the generated optimal travel route.

[0888] "JSON format" refers to a format for structuring data and expressing it in a format that is easy to read and write.

[0889] The present invention is a system that combines an emotion engine with digital tools for congestion relief and people flow management. A specific embodiment of this system will be described.

[0890] First, the user launches the dedicated app using a device with GPS functionality, such as a smartphone or tablet. On the app screen, the user enters their current location and destination information. For example, if a user attending a summer festival is currently located at Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees), they can set their destination as Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The entered information is obtained by the device using its GPS function, and this location information is sent to the server.

[0891] The server uses a generative AI model based on the received user's current location and destination information to instantly generate an optimal route. The generative AI model references past event data and real-time people flow data to suggest the optimal route to avoid congestion. For example, it generates specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori."

[0892] Another distinctive feature of this invention is that the device is equipped with an emotion engine that analyzes the user's emotions. The emotion engine uses the smartphone's camera, microphone, and other sensors (heart rate, body temperature, etc.) to analyze the user's real-time emotional state. For example, it can recognize emotions such as "enjoying" or "tense."

[0893] The device periodically sends emotional information analyzed by the emotion engine to the server, which then recalculates the optimal route based on the emotional information and makes adjustments according to the user's emotional state. The server then compiles the generated optimal route information in JSON format and sends it to the device. The device then displays the received information on the screen of a map app or dedicated app, providing the user with the optimal route.

[0894] While moving, the device periodically acquires GPS data and sends its current location and emotion information to the server. This allows the server to monitor dynamically changing pedestrian flow and congestion conditions in real time, recalculating the optimal route as needed. The user's emotion information is also updated, so the optimal route is always based on the latest information.

[0895] When a user passes through a specific checkpoint, the device sends the passage data and emotional information to the server. The server analyzes this information and awards points based on evaluation criteria such as "following the specified route" or "maintaining a positive emotional state." Users can view these points within the app and exchange them for rewards or coupons.

[0896] For example, the following prompts can be used:

[0897] "Please use GPS information to suggest the optimal route between the user's current location and destination. Also, please adjust the route and notify the user based on their emotional state."

[0898] The above is a detailed description of the embodiment of the present invention.

[0899] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0900] Step 1:

[0901] The user launches a dedicated app on their smartphone or tablet device and inputs their current location and destination information. In this case, the user inputs information from "Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees)" to "Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees)." The input information is confirmed using the GPS function of the user's device, and the latitude and longitude data of the current location and destination are collected. The input data is sent to the server.

[0902] Input: Current location and destination information entered by the user

[0903] Output: Location data sent to the server

[0904] Step 2:

[0905] The server uses a generative AI model based on the user's current location and destination information, and references past event data and real-time people flow data. This allows the system to instantly generate the optimal route. For example, the system may suggest specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori."

[0906] Input: current location information, destination information

[0907] Output: Optimal route information (Route A, Route B, etc.)

[0908] Step 3:

[0909] The device is equipped with an emotion engine that analyzes the user's emotions. The user uses the smartphone's camera, microphone, and other sensors, and the emotion engine analyzes the user's facial expressions, tone of voice, and biometric information. For example, the device can recognize the user's emotional state, such as "enjoying" or "tension," in real time.

[0910] Input: User's facial expression, voice, biometric information

[0911] Output: User's emotional information

[0912] Step 4:

[0913] The device sends the user's emotional information collected and analyzed by the emotion engine to the server. The server then uses the received emotional information to recalculate the optimal route. For example, if the server receives information that the user is "nervous," it will adjust the route to suggest a quieter route to avoid congestion.

[0914] Input: User's emotional information

[0915] Output: Re-adjusted optimal route information

[0916] Step 5:

[0917] The server creates the generated optimal route information in JSON format and sends it to the user's device. The device visually displays the received route information on the screen of a dedicated app or map app, notifying the user of the optimal route.

[0918] Input: Optimal route information

[0919] Output: Route information in JSON format sent to the device

[0920] Step 6:

[0921] As the user begins to move along the displayed route, the device periodically acquires GPS data. The device then transmits this current location and emotion information to the server. The server then monitors the dynamically changing pedestrian flow situation based on the real-time location and emotion information, and recalculates and adjusts the optimal route as necessary.

[0922] Input: current location information, emotional information

[0923] Output: Updated optimal route information

[0924] Step 7:

[0925] When a user passes through a certain checkpoint, the device transmits the passing data and emotional information to the server. The server analyzes this information and awards points to the user's account based on appropriate evaluation criteria. At the same time, the user can check the points they have earned within the app and exchange them for rewards or coupons.

[0926] Input: Transit data, emotional information

[0927] Output: Points awarded and evaluation results

[0928] The above is the specific flow of program processing for this system.

[0929] (Application example 2)

[0930] 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."

[0931] Conventional navigation systems were able to provide the optimal route to a destination, but it was difficult to adjust the route taking into account the user's real-time emotional state and dynamically changing surrounding conditions. Therefore, there is a need for a system that allows users to arrive at their destination more comfortably and efficiently, without feeling nervous or anxious.

[0932] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving the user's current location information and destination information; means for instantaneously generating an optimal route from the current location information to the destination information using a generative AI model; means for transmitting the generated optimal route information to the user terminal and making it displayable on the user terminal; a user terminal incorporating an emotion engine that analyzes the user's emotional information in real time; and means for transmitting the user's emotional information to the server and adjusting the optimal route based on the user's emotional state. This allows the user's emotional state to be reflected in real time, enabling more comfortable and safer travel.

[0933] (definition)

[0934] "User's current location information" is digital data that indicates the latitude and longitude of the user's current location.

[0935] "Destination information" is digital data that indicates the latitude and longitude of the location the user is heading for.

[0936] A "generative AI model" is an artificial intelligence model that generates optimal routes based on past and real-time data.

[0937] The "optimal route" refers to a route that allows the user to travel from the current location to the destination efficiently and safely.

[0938] A "user terminal" is an information device used by a user, such as a smartphone, tablet, smart glasses, head-mounted display, or robot.

[0939] An "emotion engine" is an algorithm or software that analyzes a user's emotional state in real time.

[0940] A "server" is a computer system for receiving, analyzing, and transmitting data.

[0941] "Means for real-time adjustment" is a function that instantly recalculates and provides the optimal route based on the user's current situation and emotions.

[0942] This invention relates to a navigation system for an autonomous vehicle, which provides and adjusts an optimal route using location information and emotion information of a user. Specific embodiments are described below.

[0943] System Configuration

[0944] This system consists of a user terminal and a server.

[0945] The user device can be a smartphone or tablet equipped with a GPS module, camera, and microphone, smart glasses, a head-mounted display, or an embedded device in an autonomous vehicle. The user device collects the user's current location information and emotion information and transmits them to the server.

[0946] The server is a computer system that receives, analyzes, and transmits data, and uses web frameworks such as Flask or Django and generative AI models such as TensorFlow or PyTorch.

[0947] Data collection and transmission

[0948] The user device uses a GPS module to collect the user's current location information. The emotion engine also analyzes the user's emotional state in real time based on data acquired by the camera and microphone. This data is then sent to the server at regular intervals.

[0949] Generate and adjust optimal routes

[0950] The server analyzes the received user's current location and destination information and uses a generative AI model to instantly generate an optimal route, which is then sent to the user's display device and displayed visually.

[0951] While traveling, the server continuously receives real-time location and emotion information from the user's device and recalculates and adjusts the optimal route as needed. For example, if the user is nervous, it will suggest a route with fewer crowds.

[0952] Points System

[0953] The server calculates the passing points each time the user passes through a specific route, and if the user's emotional state is positive, the server awards additional points, thereby increasing the user's satisfaction.

[0954] Specific examples

[0955] Consider the case where a user travels from Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees) to Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The user first enters their current location and destination information into a smartphone application. The server then uses the received data to generate an optimal route using a generative AI model and emotion engine. If the emotion engine determines that the user is "nervous," the server will suggest a route that avoids crowded areas.

[0956] Prompt Sentence Examples

[0957] Here are some examples of prompts the server might give to a generative AI model:

[0958] "The user's location information is 'Latitude 35.6581°, Longitude 139.7017°' and the destination is 'Latitude 35.6717°, Longitude 139.6949°'. The user's real-time emotion is 'Tension'. Please suggest three optimal routes with minimal congestion."

[0959] This system allows autonomous vehicles to dynamically adjust their routes according to the user's emotional state, providing a comfortable and safe journey.

[0960] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0961] Step 1:

[0962] The user terminal acquires the current location information (latitude and longitude) using the GPS module. The user inputs the destination information (latitude and longitude) into the terminal.

[0963] Input: User's current location information, destination information

[0964] Output: Current location and destination information are saved on the device.

[0965] Step 2:

[0966] The user device uses a camera and microphone to collect data on the user's facial expressions and voice, and sends it to an emotion engine to analyze the user's emotional state.

[0967] Input: User's facial expression data, voice data

[0968] Output: Analyzed user's emotional information (e.g., nervousness, excitement)

[0969] Step 3:

[0970] The user terminal transmits current location information, destination information, and emotion information to the server.

[0971] Input: current location information, destination information, emotion information

[0972] Output: Data sent to the server

[0973] Step 4:

[0974] The server generates the optimal route by sending prompts to the generative AI model based on the received location and destination information. The prompts include location, destination, and emotion information.

[0975] Input: current location information, destination information, emotion information

[0976] Output: The optimal route generated by the generative AI model

[0977] Step 5:

[0978] The server generates the optimal route in JSON format and sends it to the user's device, which then displays the received optimal route on its screen.

[0979] Input: Optimal route information

[0980] Output: The optimal route displayed on the user's device

[0981] Step 6:

[0982] While moving, the user's device periodically obtains its current location information via GPS and analyzes the emotion information using the emotion engine. This data is then sent back to the server, which then recalculates the optimal route as necessary.

[0983] Input: Real-time location information, emotional information

[0984] Output: Newly adjusted optimal route information

[0985] Step 7:

[0986] The server calculates the user's passing points based on their passing points and emotional information, and adds the points to the user's account. The user's device can then check the point information.

[0987] Input: Passing points, emotional information

[0988] Output: Points awarded to the user

[0989] 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.

[0990] 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.

[0991] 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.

[0992] [Fourth embodiment]

[0993] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0994] 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.

[0995] 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).

[0996] 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.

[0997] 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.

[0998] 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).

[0999] 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.

[1000] 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.

[1001] 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.

[1002] 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.

[1003] 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.

[1004] 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.

[1005] 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."

[1006] The present invention describes a specific embodiment of a digital tool, "digital checkpoint," aimed at congestion relief and people flow management.

[1007] Collecting and transmitting user location information

[1008] A user inputs their current location and destination information using a device with GPS functionality, such as a smartphone or tablet. For example, if a user is participating in a large-scale event, their current location may be "latitude 35.6895 degrees, longitude 139.6917 degrees" (Tokyo) and their destination may be "latitude 35.7100 degrees, longitude 139.8107 degrees" (Skytree). The device then sends this location information to the server.

[1009] Server generates optimal route

[1010] The server analyzes the received user's current location and destination information and instantly generates the optimal route using a generative AI model. The generative AI model suggests the optimal route for the user to choose based on past event data and real-time people flow data. For example, it generates specific routes such as "Route A: via Asakusa Street" and "Route B: via Kuramae Street."

[1011] Providing and displaying the best route

[1012] The server then formats the generated optimal route information in JSON format and sends it to the device, which then visually displays the received optimal route to the user, allowing the user to travel safely and efficiently according to the optimal route.

[1013] Real-time location tracking and route updates

[1014] While moving, the device periodically acquires GPS data and sends its current location information to the server. The server then recalculates and adjusts the optimal route as needed based on the received location information. Real-time location tracking makes it possible to avoid dynamically changing pedestrian flows and crowds.

[1015] Points and evaluation

[1016] The device sends the pass point information to the server each time the user passes through a checkpoint area. The server analyzes the pass data and adds points to the user's account if the user has passed through the appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons.

[1017] Specific examples

[1018] The following is a specific example of an event using this invention. For example, suppose a user participating in a summer festival is currently located at Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees) and has set their destination as Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The user enters this information into a smartphone app and submits it.

[1019] Based on the received data, the server uses a generative AI model to generate optimal routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori." The generated route information is returned to the device in JSON format, and the device then provides the displayed route to the user.

[1020] When a user selects Route A and starts moving, the current location information is updated periodically during the movement, and the route is recalculated to avoid congestion. When a user passes through a specific checkpoint, the server calculates the passing points and gives the user points.

[1021] This system allows users to travel safely and comfortably, and event organizers can alleviate congestion and reduce security costs. The above is a detailed description of the embodiment of the present invention.

[1022] The processing flow will be explained below.

[1023] Step 1:

[1024] The user launches the smartphone app, obtains their current location information, enters their destination, and presses the send button.

[1025] Step 2:

[1026] The device uses the built-in GPS to obtain the latitude and longitude of its current location, and then sends the current location and destination information to the server in JSON format.

[1027] Step 3:

[1028] The server receives the current location information and destination information transmitted from the user terminal.

[1029] Step 4:

[1030] The server analyzes the received location information and uses a generative AI model to instantly generate the optimal route from the current location to the destination.

[1031] Step 5:

[1032] The server constructs a response in JSON format containing the generated optimal route information and sends it to the terminal.

[1033] Step 6:

[1034] The device receives the response from the server and visually displays the optimal route to the user, providing specific route details using a map.

[1035] Step 7:

[1036] The user starts moving according to the displayed optimal route. The device periodically acquires GPS data and sends the current location to the server.

[1037] Step 8:

[1038] The server recalculates and adjusts the optimal route as needed based on the current location information received in real time.

[1039] Step 9:

[1040] When a user passes through a checkpoint area, the terminal transmits the passing data to the server, which calculates the passing points and adds them to the user's account.

[1041] Step 10:

[1042] Users can check the points they have earned within the app and exchange them for rewards and coupons.

[1043] Example 1

[1044] 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."

[1045] Conventional people flow management systems not only provide optimal routes while avoiding congestion in real time, but also lack the ability to collect and analyze data during events to proactively propose optimal routes that will be effective for future events. Furthermore, they lack incentive functions that not only provide users with a safe and efficient way to travel, but also track their location information during travel and provide appropriate points. This requires improving user convenience and optimizing people flow management for organizers.

[1046] 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.

[1047] In this invention, the server includes: a means for receiving a user's current location information and destination information; a means for instantly generating an optimal route from the current location information to the destination information based on past and real-time data using a generative AI model; a means for configuring the generated optimal route information, transmitting it to the user's terminal, and visually displaying it on the user's terminal; a means for periodically transmitting current location information from the user's terminal to the server; and a means for recalculating and adjusting the optimal route as needed based on the current location information periodically received by the server. This not only enables users to travel safely and efficiently, but also avoids real-time congestion during travel, allowing organizers to achieve more effective people flow management. It also provides incentives by awarding passing points and collecting data during the event, contributing to the generation of optimal routes for the next event.

[1048] "User" refers to an individual user who uses the system to input location information, check routes, and earn points.

[1049] "Server" refers to the central processing unit that analyzes the data received from the user and generates, recalculates, and adjusts the optimal route using the generative AI model.

[1050] A "generative AI model" refers to an artificial intelligence algorithm that instantly generates the optimal route from a user's location information to their destination information based on past and real-time data.

[1051] "Current location information" refers to latitude and longitude data obtained using the GPS function of the user's device, and indicates the user's current location.

[1052] "Destination information" refers to the latitude and longitude data of the destination that the user inputs into the system.

[1053] An "optimal route" refers to a recommended route that is analyzed and calculated by a generative AI model to help users reach their destination efficiently and safely.

[1054] "User device" refers to a mobile information terminal equipped with GPS functionality used by a user, such as a smartphone or tablet.

[1055] "Data" refers to all types of information used and analyzed by the system, such as user location information, destination information, past event data, and real-time people flow data.

[1056] "Passage point information" refers to information and data recorded each time a user passes through a specific checkpoint area.

[1057] "Points" refer to virtual rewards given to users when they follow a proper route.

[1058] "Benefits and coupons" refer to items that improve convenience, such as rewards and discount coupons that can be exchanged using points earned by users.

[1059] A specific embodiment of the present invention will be described, which provides a digital tool for congestion reduction and people flow management, specifically for enabling users to move around efficiently and safely at events and large gatherings.

[1060] Collecting and transmitting user location information

[1061] A user uses a device with GPS functionality, such as a smartphone or tablet, to input current location information and destination information. The application used in this case provides an interface for inputting location information. Specific information is assumed to be the current location is "latitude 35.6581, longitude 139.7017" (Shibuya Station), and the destination is "latitude 35.6717, longitude 139.6949" (Yoyogi Park). The device sends the input location information to the server as an HTTP request.

[1062] Server generates optimal route

[1063] The server receives the current location and destination information sent by the user and uses a generative AI model to analyze it. This generative AI model instantly generates the optimal travel route based on past event data and real-time people flow data. For example, it generates specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori."

[1064] Providing and displaying the best route

[1065] The server generates optimal route information in JSON format and sends it to the device. The device analyzes the received optimal route information and visually displays it to the user. The user can then select the optimal route from the displayed routes.

[1066] Real-time location tracking and route updates

[1067] When the user starts moving, the device periodically acquires GPS data and sends the current location information to the server. The server recalculates and adjusts the optimal route as needed based on the received current location information. For example, if new congestion occurs during movement, the server generates a new route, sends it to the device, and notifies the user.

[1068] Points and evaluation

[1069] Each time a user passes through a checkpoint area (specific location), the device sends the passing point information to the server. The server analyzes this passing data and awards points to the user if the user has passed through the appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons.

[1070] Specific examples

[1071] The following is a concrete example of an event using this system. For example, suppose a user participating in a summer festival is currently located at Shibuya Station (latitude 35.6581, longitude 139.7017) and has set their destination as Yoyogi Park (latitude 35.6717, longitude 139.6949). The user enters this information into a smartphone app and submits it. Based on the received data, the server uses a generative AI model to generate an optimal route, such as "Route A: via Harajuku" or "Route B: via Meiji Dori." The generated route information is returned to the device in JSON format, and the device provides the displayed route to the user. If the user selects Route A and begins traveling, their current location information is updated periodically during the trip, and the route is recalculated to avoid congestion. When the user passes through a specific checkpoint, the server calculates the passing points and awards the user points.

[1072] Prompt Sentence Examples

[1073] Current location: 35.6581, 139.7017 (Shibuya Station)

[1074] Destination: 35.6717, 139.6949 (Yoyogi Park)

[1075] The above is a specific embodiment for carrying out the invention.

[1076] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1077] Step 1:

[1078] The user launches the application on a device with GPS functionality, such as a smartphone or tablet, and inputs their current location and destination information. Specifically, the current location is "latitude 35.6581, longitude 139.7017" (Shibuya Station), and the destination is "latitude 35.6717, longitude 139.6949" (Yoyogi Park). The device sends this input information to the server as an HTTP request. Input: Current location and destination information entered by the user, Output: Location data in JSON format.

[1079] Step 2:

[1080] The server receives the current location information and destination information sent by the user. To analyze the received location information, the server uses a generative AI model. This generative AI model generates the optimal travel route using past event data and real-time people flow data. For example, specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori" are generated. Input: JSON data of location information from the user, Output: JSON data containing optimal route information.

[1081] Step 3:

[1082] The server composes the generated optimal route information in JSON format and sends it to the terminal. The terminal analyzes the received optimal route information and displays it visually to the user. The user selects the best route from the displayed routes. Input: JSON data containing optimal route information from the server, Output: Data returning the selection result to the user.

[1083] Step 4:

[1084] When the user starts moving, the device periodically acquires GPS data and sends current location information to the server. The server recalculates and adjusts the optimal route as needed based on the received current location information. For example, if unexpected congestion occurs during movement, the server generates a new route and sends it to the device to notify the user. Input: Data on the user's location while moving, Output: Optimal route information recalculated as needed.

[1085] Step 5:

[1086] Each time the user passes through a checkpoint area (specific point), the device sends the passing point information to the server. The server analyzes this passing data and adds points to the user's account if the user has passed through the appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons. Input: Passing points and timestamp information, Output: Passing points and associated reward data.

[1087] (Application example 1)

[1088] 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."

[1089] Conventional logistics centers lacked real-time route optimization for efficient movement of employees and autonomous vehicles, resulting in congestion and delays. This reduced delivery efficiency, increased overall costs, and inefficient operations. Furthermore, there was a need for a system that could dynamically recalculate routes based on on-site congestion and provide appropriate instructions to employees.

[1090] 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.

[1091] In this invention, the server includes a means for receiving a user's current location information and destination information, a means for instantly generating an optimal route from the current location information to the destination information using a generative AI model, a means for transmitting the generated optimal route information to a user terminal and making it displayable on the user terminal, and a means for providing the optimal route to employees or automated vehicles in the logistics center. This enables employees and automated vehicles in the logistics center to travel safely and quickly via the optimal route efficiently. Real-time route updates and congestion avoidance can improve the efficiency of the entire logistics center.

[1092] "User's current location information" refers to data on the geographic coordinates of the user's current location, obtained using GPS or other location information technology.

[1093] "Destination information" is data on the final geographical destination to which the user wishes to travel.

[1094] A "generative AI model" is an artificial intelligence model that automatically generates optimal routes and suggestions based on past and real-time data.

[1095] "Means for updating the optimal route in real time" refers to a mechanism that periodically sends the user's current location information to a server and dynamically recalculates the route based on the latest information.

[1096] The "means for calculating passing points on the optimum route and giving points to the user" is a function that records the user's passing through a specific route and adds up points.

[1097] "Means for providing optimal routes to employees or automated vehicles within a logistics center" refers to a system that provides efficient route instructions to employees and automated vehicles working within a logistics center.

[1098] "Real-time people flow data within a logistics center" is data collected by observing the movement of people and vehicles within the logistics center in real time.

[1099] "Means for informing a delivery robot of the optimal route by voice or visual display" refers to technology for instructing a delivery robot on the optimal route by voice announcement or visual display.

[1100] An "incentive" is a reward or benefit given for passing a specific route.

[1101] The present invention describes a specific embodiment of a digital tool called a "Logistics Optimization Navigator" that aims to alleviate congestion and efficiently manage people flow within logistics centers.

[1102] 1. Collecting and transmitting user location information

[1103] Users use a device with GPS functionality, such as a smartphone or smart glasses, to obtain current location information and input destination information. The delivery robot automatically obtains its current location using its built-in GPS, and delivery destination information is pre-registered in the system. For example, assume the current location is "latitude 35.6581 degrees, longitude 139.7017 degrees" and the destination is "latitude 35.6717 degrees, longitude 139.6949 degrees." The device then sends this location information to the server.

[1104] 2. Server generates optimal route

[1105] The server analyzes the received user's current location and destination information and instantly generates an optimal route using a generative AI model (for example, OpenAI's GPT-4). This generative AI model suggests the optimal route for the user to choose based on past delivery data and real-time people flow data. For example, it generates specific routes such as "Route A: via Asakusa Street" and "Route B: via Kuramae Street."

[1106] 3. Providing and displaying the optimal route

[1107] The server composes the generated optimal route information in JSON format and sends it to the terminal. The terminal visually displays the received optimal route to the user, allowing the user to travel safely and efficiently according to the optimal route. The delivery robot is informed of the route by voice and light display.

[1108] 4. Real-time location tracking and route updates

[1109] While moving, the device periodically acquires GPS data and sends its current location information to the server. The server then recalculates and adjusts the optimal route as needed based on the received location information. Real-time location tracking makes it possible to avoid dynamically changing pedestrian flows and crowds.

[1110] 5. Points and Evaluation

[1111] The device sends passing point information to the server each time the user passes through a specific route. The server analyzes the passing data and adds points to the user's account if the user passes through an appropriate route. Users can check the points they have earned within the app and exchange them for rewards or coupons. In addition, evaluation data is collected and analyzed after delivery is completed and used to generate the next route.

[1112] Specific examples

[1113] The following is a concrete example of a logistics center using this invention. For example, suppose a delivery staff member is currently located at "latitude 35.6581 degrees, longitude 139.7017 degrees" and has set the destination to "latitude 35.6717 degrees, longitude 139.6949 degrees." The user enters this information into a smartphone app and submits it. Based on the received data, the server uses a generative AI model to generate an optimal route, such as "Route A: via Route 1" or "Route B: via Route 2." The generated route information is returned to the terminal in JSON format, and the terminal provides the displayed route to the user. If the user selects Route A and begins traveling, the current location information is updated periodically during the trip, and the route is recalculated to avoid congestion.

[1114] Generative AI model prompt example

[1115] Below are some example prompts that can be input to a generative AI model to generate an optimal route:

[1116] The user's current location is "Latitude 35.6581°, Longitude 139.7017°." The destination is "Latitude 35.6717°, Longitude 139.6949°." According to past delivery data, Kuramae Street was the least crowded at a particular time. Also, real-time people flow data shows that the Asakusa Street route is very congested. Based on this information, please suggest the optimal delivery route.

[1117] This system allows users to travel safely and comfortably, and logistics center managers can achieve efficient people flow management and cost reduction. In this way, the invention can be embodied.

[1118] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1119] Step 1: Enter and send your current location and destination information

[1120] Input: The user inputs their current location and destination information using a smartphone or smart glasses. In the case of a delivery robot, the current location information is obtained from the built-in GPS, and the destination information is pre-registered.

[1121] Specific operation: The user operates the application UI to input and send the current location and destination. The delivery robot automatically obtains the current location and sends the destination information to the server.

[1122] Output: Location and destination information is sent to the server in JSON format.

[1123] Step 2: Data reception and analysis by the server

[1124] Input: Current location and destination information in JSON format.

[1125] Specific operation: The server parses the received JSON data and prepares a dataset to input into the generative AI model.

[1126] Output: Parsed location and destination information.

[1127] Step 3: Generative AI model calculates optimal route

[1128] Input: Parsed location and destination information.

[1129] How it works: The server uses a generative AI model (e.g., GPT-4) to generate prompts and calculate the optimal route. The prompts include the current location, destination, past performance data, and real-time people flow data.

[1130] Output: Optimal route information.

[1131] Step 4: Providing and displaying optimal route information

[1132] Input: Optimal route information.

[1133] Specific operation: The server creates optimal route information in JSON format and sends it to the user's device. The device visually displays the received optimal route. The delivery robot is informed of the route through voice guidance and light displays.

[1134] Output: Optimal route information displayed on the user's device or delivery robot.

[1135] Step 5: Real-time location tracking and route updates

[1136] Input: GPS data acquired while moving.

[1137] How it works: The device periodically sends its current location information to the server, which then uses the generated AI model again based on the received real-time location information to recalculate and adjust the route as needed.

[1138] Output: Updated optimal route information.

[1139] Step 6: Points and evaluation

[1140] Input: location information, passing point information.

[1141] Specific operation: Each time a user passes through a specific route, the device sends the passing point information to the server. The server analyzes the passing data and assigns points to the appropriate user's account. Evaluation data is also collected and used to generate the next route.

[1142] Output: Points earned and rating data.

[1143] Example of a generative AI model prompt

[1144] Here is an example prompt:

[1145] plain text

[1146] The user's current location is "Latitude 35.6581°, Longitude 139.7017°." The destination is "Latitude 35.6717°, Longitude 139.6949°." According to past delivery data, Kuramae Street was the least crowded at a particular time. Also, real-time people flow data shows that the Asakusa Street route is very congested. Based on this information, please suggest the optimal delivery route.

[1147] 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.

[1148] The present invention describes a specific embodiment in which an emotion engine is combined with a digital tool called a "digital checkpoint" for the purpose of congestion relief and people flow management.

[1149] Collecting and transmitting user location information

[1150] A user inputs their current location and destination information using a device with GPS functionality, such as a smartphone or tablet. For example, if a user is participating in a large-scale event, their current location may be "latitude 35.6895 degrees, longitude 139.6917 degrees" (Tokyo) and their destination may be "latitude 35.7100 degrees, longitude 139.8107 degrees" (Skytree). The device then sends this location information to the server.

[1151] Server generates optimal route

[1152] The server analyzes the received user's current location and destination information and instantly generates the optimal route using a generative AI model. The generative AI model suggests the optimal route for the user to choose based on past event data and real-time people flow data. For example, it generates specific routes such as "Route A: via Asakusa Street" and "Route B: via Kuramae Street."

[1153] Combining Emotion Engines

[1154] A distinctive feature of the present invention is that the terminal is equipped with an emotion engine that recognizes the user's emotions. The emotion engine recognizes the user's real-time emotional state by analyzing the user's facial expressions, tone of voice, and other biometric information.

[1155] Real-time emotional information transmission and route adjustment

[1156] The device transmits the user's emotional information recognized by the emotion engine to the server. For example, the server can obtain emotional information such as whether the user is "nervous" or "enjoyed." The server receives this emotional information and adjusts the optimal route based on the user's emotional state.

[1157] Providing and displaying the best route

[1158] The server then formats the generated optimal route information in JSON format and sends it to the device, which then visually displays the received optimal route to the user, allowing the user to travel safely and efficiently according to the optimal route.

[1159] Real-time location tracking and route updates

[1160] While moving, the device periodically acquires GPS data and sends its current location and emotion information to the server. The server recalculates and adjusts the optimal route as needed based on the received location and emotion information. Real-time tracking of location and emotion information enables movement that takes into account dynamically changing pedestrian flow and congestion, as well as the user's emotional state.

[1161] Points and evaluation

[1162] The device sends the passing point information to the server each time the user passes through a checkpoint area. The server analyzes the passing data and emotional information, and if the user passes through the appropriate route, points are added to the user's account. Users can check the points they have earned within the app and exchange them for rewards or coupons.

[1163] Specific examples

[1164] The following is a specific example of an event using this invention. For example, suppose a user participating in a summer festival is currently located at Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees) and has set their destination as Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The user enters this information into a smartphone app and submits it.

[1165] Based on the received data, the server uses a generative AI model and emotion engine to generate optimal routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori." If the user is feeling nervous about a particular route, the server will suggest a route that is less crowded, based on the user's emotions. The generated route information is returned to the device in JSON format, and the device then displays the route to the user.

[1166] When a user selects Route A and starts moving, their current location and emotion information are periodically updated during the movement, and the route is recalculated to avoid congestion and emotional states. When a user passes through a specific checkpoint, the server calculates the passing points, and if the user's emotion is positive, additional points are awarded.

[1167] This system allows users to travel safely and comfortably, and event organizers can reduce congestion and security costs. Furthermore, emotion recognition can increase user satisfaction. This concludes the detailed description of the embodiment of the present invention.

[1168] The processing flow will be explained below.

[1169] Step 1:

[1170] The user starts the app on their smartphone and inputs their current location and destination information. For example, they input their current location as "Shibuya Station" and their destination as "Yoyogi Park."

[1171] Step 2:

[1172] The device uses the GPS function to obtain the latitude and longitude of its current location. The device then sends the current location information and destination information to the server in JSON format.

[1173] Step 3:

[1174] The server receives the current location information and destination information transmitted from the user terminal.

[1175] Step 4:

[1176] The server analyzes the received location information and uses a generative AI model to instantly generate the optimal route from the current location to the destination.

[1177] Step 5:

[1178] The server constructs a response in JSON format containing the generated optimal route information and sends it to the terminal.

[1179] Step 6:

[1180] The device receives the response from the server and visually displays the optimal route to the user, providing specific route details using a map.

[1181] Step 7:

[1182] The user starts moving according to the displayed optimal route. The device periodically acquires GPS data and sends the current location to the server.

[1183] Step 8:

[1184] The device's emotion engine analyzes the user's facial expressions and tone of voice to obtain real-time emotional information, such as whether they are "nervous" or "enjoyed."

[1185] Step 9:

[1186] The device transmits the acquired emotion information to the server, which then receives the user's current location information and emotion information at the same time.

[1187] Step 10:

[1188] The server recalculates or adjusts the optimal route as needed based on the current location and emotion information received in real time. For example, if the user is "nervous," it will suggest a less congested route.

[1189] Step 11:

[1190] When a user passes through a checkpoint area, the device sends the pass point information to the server, which analyzes the pass data and adds points to the user's account if the user passes through the appropriate route.

[1191] Step 12:

[1192] The server also calculates and credits additional points to the user's account when the user is in a positive emotional state, allowing the user to receive rewards according to their emotions.

[1193] Step 13:

[1194] Users can check the points they have earned within the app, which can be exchanged for rewards and coupons.

[1195] In this way, a digital checkpoint system combined with an emotion engine enables users to travel safely and comfortably, and event organizers can reduce congestion and security costs. It also improves the travel experience based on user emotion recognition, increasing satisfaction.

[1196] Example 2

[1197] 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."

[1198] Conventional location information services are limited to basic route suggestions based on the user's current location and destination information, making it difficult to suggest optimal routes that take into account the user's real-time emotional state and dynamically changing people flow information.In addition, there has been a lack of effective people flow management methods, including the use of emotional information to improve event participant satisfaction and the awarding of reward points.

[1199] 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 collecting and transmitting user location information, a means for instantly generating an optimal route from current location information to destination information using a generative AI model, a means for analyzing user emotion information using an emotion engine, a means for adjusting the route based on the user emotion information, and a means for transmitting the generated optimal route information to a user terminal and making it displayable on the user terminal. This makes it possible to propose an optimal route taking into account the user's real-time emotional state and dynamically changing people flow information, thereby improving user satisfaction and reducing congestion at events.

[1200] "User" refers to a person who uses the system.

[1201] "Location information" refers to the latitude and longitude information of the user's current location and destination.

[1202] A "generative AI model" refers to an artificial intelligence model that generates optimal routes based on past data and real-time information.

[1203] "Emotion engine" refers to a function that recognizes a user's emotional state by analyzing their facial expressions, tone of voice, and other biometric information.

[1204] The "optimal route" refers to the optimal travel route from the user's current location to the destination.

[1205] "Server" refers to the central system that analyzes the received data, generates optimal routes using generative AI models and emotion engines, and provides information to user devices.

[1206] "User terminal" refers to a mobile device such as a smartphone or tablet used by a user.

[1207] "Passing points" refer to points awarded when a user passes through a specific checkpoint or route.

[1208] "People flow data" refers to information on people's movements and congestion within a specific area.

[1209] "Optimal route information" refers to data containing details of the generated optimal travel route.

[1210] "JSON format" refers to a format for structuring data and expressing it in a format that is easy to read and write.

[1211] The present invention is a system that combines an emotion engine with digital tools for congestion relief and people flow management. A specific embodiment of this system will be described.

[1212] First, the user launches the dedicated app using a device with GPS functionality, such as a smartphone or tablet. On the app screen, the user enters their current location and destination information. For example, if a user attending a summer festival is currently located at Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees), they can set their destination as Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The entered information is obtained by the device using its GPS function, and this location information is sent to the server.

[1213] The server uses a generative AI model based on the received user's current location and destination information to instantly generate an optimal route. The generative AI model references past event data and real-time people flow data to suggest the optimal route to avoid congestion. For example, it generates specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori."

[1214] Another distinctive feature of this invention is that the device is equipped with an emotion engine that analyzes the user's emotions. The emotion engine uses the smartphone's camera, microphone, and other sensors (heart rate, body temperature, etc.) to analyze the user's real-time emotional state. For example, it can recognize emotions such as "enjoying" or "tense."

[1215] The device periodically sends emotional information analyzed by the emotion engine to the server, which then recalculates the optimal route based on the emotional information and makes adjustments according to the user's emotional state. The server then compiles the generated optimal route information in JSON format and sends it to the device. The device then displays the received information on the screen of a map app or dedicated app, providing the user with the optimal route.

[1216] While moving, the device periodically acquires GPS data and sends its current location and emotion information to the server. This allows the server to monitor dynamically changing pedestrian flow and congestion conditions in real time, recalculating the optimal route as needed. The user's emotion information is also updated, so the optimal route is always based on the latest information.

[1217] When a user passes through a specific checkpoint, the device sends the passage data and emotional information to the server. The server analyzes this information and awards points based on evaluation criteria such as "following the specified route" or "maintaining a positive emotional state." Users can view these points within the app and exchange them for rewards or coupons.

[1218] For example, the following prompts can be used:

[1219] "Please use GPS information to suggest the optimal route between the user's current location and destination. Also, please adjust the route and notify the user based on their emotional state."

[1220] The above is a detailed description of the embodiment of the present invention.

[1221] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1222] Step 1:

[1223] The user launches a dedicated app on their smartphone or tablet device and inputs their current location and destination information. In this case, the user inputs information from "Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees)" to "Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees)." The input information is confirmed using the GPS function of the user's device, and the latitude and longitude data of the current location and destination are collected. The input data is sent to the server.

[1224] Input: Current location and destination information entered by the user

[1225] Output: Location data sent to the server

[1226] Step 2:

[1227] The server uses a generative AI model based on the user's current location and destination information, and references past event data and real-time people flow data. This allows the system to instantly generate the optimal route. For example, the system may suggest specific routes such as "Route A: via Harajuku" and "Route B: via Meiji Dori."

[1228] Input: current location information, destination information

[1229] Output: Optimal route information (Route A, Route B, etc.)

[1230] Step 3:

[1231] The device is equipped with an emotion engine that analyzes the user's emotions. The user uses the smartphone's camera, microphone, and other sensors, and the emotion engine analyzes the user's facial expressions, tone of voice, and biometric information. For example, the device can recognize the user's emotional state, such as "enjoying" or "tension," in real time.

[1232] Input: User's facial expression, voice, biometric information

[1233] Output: User's emotional information

[1234] Step 4:

[1235] The device sends the user's emotional information collected and analyzed by the emotion engine to the server. The server then uses the received emotional information to recalculate the optimal route. For example, if the server receives information that the user is "nervous," it will adjust the route to suggest a quieter route to avoid congestion.

[1236] Input: User's emotional information

[1237] Output: Re-adjusted optimal route information

[1238] Step 5:

[1239] The server creates the generated optimal route information in JSON format and sends it to the user's device. The device visually displays the received route information on the screen of a dedicated app or map app, notifying the user of the optimal route.

[1240] Input: Optimal route information

[1241] Output: Route information in JSON format sent to the device

[1242] Step 6:

[1243] As the user begins to move along the displayed route, the device periodically acquires GPS data. The device then transmits this current location and emotion information to the server. The server then monitors the dynamically changing pedestrian flow situation based on the real-time location and emotion information, and recalculates and adjusts the optimal route as necessary.

[1244] Input: current location information, emotional information

[1245] Output: Updated optimal route information

[1246] Step 7:

[1247] When a user passes through a certain checkpoint, the device transmits the passing data and emotional information to the server. The server analyzes this information and awards points to the user's account based on appropriate evaluation criteria. At the same time, the user can check the points they have earned within the app and exchange them for rewards or coupons.

[1248] Input: Transit data, emotional information

[1249] Output: Points awarded and evaluation results

[1250] The above is the specific flow of program processing for this system.

[1251] (Application example 2)

[1252] 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."

[1253] Conventional navigation systems were able to provide the optimal route to a destination, but it was difficult to adjust the route taking into account the user's real-time emotional state and dynamically changing surrounding conditions. Therefore, there is a need for a system that allows users to arrive at their destination more comfortably and efficiently, without feeling nervous or anxious.

[1254] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving the user's current location information and destination information; means for instantaneously generating an optimal route from the current location information to the destination information using a generative AI model; means for transmitting the generated optimal route information to the user terminal and making it displayable on the user terminal; a user terminal incorporating an emotion engine that analyzes the user's emotional information in real time; and means for transmitting the user's emotional information to the server and adjusting the optimal route based on the user's emotional state. This allows the user's emotional state to be reflected in real time, enabling more comfortable and safer travel.

[1255] (definition)

[1256] "User's current location information" is digital data that indicates the latitude and longitude of the user's current location.

[1257] "Destination information" is digital data that indicates the latitude and longitude of the location the user is heading for.

[1258] A "generative AI model" is an artificial intelligence model that generates optimal routes based on past and real-time data.

[1259] The "optimal route" refers to a route that allows the user to travel from the current location to the destination efficiently and safely.

[1260] A "user terminal" is an information device used by a user, such as a smartphone, tablet, smart glasses, head-mounted display, or robot.

[1261] An "emotion engine" is an algorithm or software that analyzes a user's emotional state in real time.

[1262] A "server" is a computer system for receiving, analyzing, and transmitting data.

[1263] "Means for real-time adjustment" is a function that instantly recalculates and provides the optimal route based on the user's current situation and emotions.

[1264] This invention relates to a navigation system for an autonomous vehicle, which provides and adjusts an optimal route using location information and emotion information of a user. Specific embodiments are described below.

[1265] System Configuration

[1266] This system consists of a user terminal and a server.

[1267] The user device can be a smartphone or tablet equipped with a GPS module, camera, and microphone, smart glasses, a head-mounted display, or an embedded device in an autonomous vehicle. The user device collects the user's current location information and emotion information and transmits them to the server.

[1268] The server is a computer system that receives, analyzes, and transmits data, and uses web frameworks such as Flask or Django and generative AI models such as TensorFlow or PyTorch.

[1269] Data collection and transmission

[1270] The user device uses a GPS module to collect the user's current location information. The emotion engine also analyzes the user's emotional state in real time based on data acquired by the camera and microphone. This data is then sent to the server at regular intervals.

[1271] Generate and adjust optimal routes

[1272] The server analyzes the received user's current location and destination information and uses a generative AI model to instantly generate an optimal route, which is then sent to the user's display device and displayed visually.

[1273] While traveling, the server continuously receives real-time location and emotion information from the user's device and recalculates and adjusts the optimal route as needed. For example, if the user is nervous, it will suggest a route with fewer crowds.

[1274] Points System

[1275] The server calculates the passing points each time the user passes through a specific route, and if the user's emotional state is positive, the server awards additional points, thereby increasing the user's satisfaction.

[1276] Specific examples

[1277] Consider the case where a user travels from Shibuya Station (latitude 35.6581 degrees, longitude 139.7017 degrees) to Yoyogi Park (latitude 35.6717 degrees, longitude 139.6949 degrees). The user first enters their current location and destination information into a smartphone application. The server then uses the received data to generate an optimal route using a generative AI model and emotion engine. If the emotion engine determines that the user is "nervous," the server will suggest a route that avoids crowded areas.

[1278] Prompt Sentence Examples

[1279] Here are some examples of prompts the server might give to a generative AI model:

[1280] "The user's location information is 'Latitude 35.6581°, Longitude 139.7017°' and the destination is 'Latitude 35.6717°, Longitude 139.6949°'. The user's real-time emotion is 'Tension'. Please suggest three optimal routes with minimal congestion."

[1281] This system allows autonomous vehicles to dynamically adjust their routes according to the user's emotional state, providing a comfortable and safe journey.

[1282] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1283] Step 1:

[1284] The user terminal acquires the current location information (latitude and longitude) using the GPS module. The user inputs the destination information (latitude and longitude) into the terminal.

[1285] Input: User's current location information, destination information

[1286] Output: Current location and destination information are saved on the device.

[1287] Step 2:

[1288] The user device uses a camera and microphone to collect data on the user's facial expressions and voice, and sends it to an emotion engine to analyze the user's emotional state.

[1289] Input: User's facial expression data, voice data

[1290] Output: Analyzed user's emotional information (e.g., nervousness, excitement)

[1291] Step 3:

[1292] The user terminal transmits current location information, destination information, and emotion information to the server.

[1293] Input: current location information, destination information, emotion information

[1294] Output: Data sent to the server

[1295] Step 4:

[1296] The server generates the optimal route by sending prompts to the generative AI model based on the received location and destination information. The prompts include location, destination, and emotion information.

[1297] Input: current location information, destination information, emotion information

[1298] Output: The optimal route generated by the generative AI model

[1299] Step 5:

[1300] The server generates the optimal route in JSON format and sends it to the user's device, which then displays the received optimal route on its screen.

[1301] Input: Optimal route information

[1302] Output: The optimal route displayed on the user's device

[1303] Step 6:

[1304] While moving, the user's device periodically obtains its current location information via GPS and analyzes the emotion information using the emotion engine. This data is then sent back to the server, which then recalculates the optimal route as necessary.

[1305] Input: Real-time location information, emotional information

[1306] Output: Newly adjusted optimal route information

[1307] Step 7:

[1308] The server calculates the user's passing points based on their passing points and emotional information, and adds the points to the user's account. The user's device can then check the point information.

[1309] Input: Passing points, emotional information

[1310] Output: Points awarded to the user

[1311] 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.

[1312] 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.

[1313] 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.

[1314] 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.

[1315] 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.

[1316] 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.

[1317] 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).

[1318] 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.

[1319] 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."

[1320] 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.

[1321] 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).

[1322] 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.

[1323] 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.

[1324] 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.

[1325] 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.

[1326] 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.

[1327] 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.

[1328] 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.

[1329] 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.

[1330] 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.

[1331] 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.

[1332] The following is further disclosed regarding the above embodiment.

[1333] (Claim 1)

[1334] means for receiving user's current location information and destination information;

[1335] A means to instantly generate the optimal route from current location information to destination information using a generative AI model;

[1336] means for transmitting the generated optimum route information to a user terminal and enabling it to be displayed on the user terminal;

[1337] A system including:

[1338] (Claim 2)

[1339] A means for periodically transmitting the user's current location information to a server and updating the optimal route in real time;

[1340] means for calculating passing points on the optimum route and awarding points to the user;

[1341] The system of claim 1 further comprising:

[1342] (Claim 3)

[1343] A means to collect and analyze people flow data during an event and use it to generate optimal routes for the next event.

[1344] Rewards when users take a specific route

[1345] "Example 1"

[1346] (Claim 1)

[1347] means for receiving user's current location information and destination information;

[1348] A means to instantly generate the optimal route from current location information to destination information based on past data and real-time data using generative AI models, and

[1349] means for configuring the generated optimum route information, transmitting the same to a user terminal, and making the same visually displayable on the user terminal;

[1350] means for periodically transmitting current location information from the user terminal to a server;

[1351] A means for recalculating and adjusting the optimal route as necessary based on the current location information periodically received by the server;

[1352] A system including:

[1353] (Claim 2)

[1354] A means for the server to analyze the passing point information and grant points to the user's account when the user passes through an appropriate route;

[1355] A way for users to check their points within the app and exchange them for rewards and coupons.

[1356] The system of claim 1 further comprising:

[1357] (Claim 3)

[1358] A means to collect and analyze data during the event and use it to generate optimal routes for the next event.

[1359] A means for providing a reward based on a prompt sent when the user passes a specific route;

[1360] The system of claim 1 further comprising:

[1361] "Application Example 1"

[1362] (Claim 1)

[1363] means for receiving user's current location information and destination information;

[1364] A means to instantly generate the optimal route from current location information to destination information using a generative AI model;

[1365] means for transmitting the generated optimum route information to a user terminal and enabling it to be displayed on the user terminal;

[1366] A means for providing an optimal route to employees or automated vehicles within a logistics center;

[1367] A system including:

[1368] (Claim 2)

[1369] A means for periodically transmitting the user's current location information to a server and updating the optimal route in real time;

[1370] means for calculating passing points on the optimum route and awarding points to the user;

[1371] A means of recalculating routes taking into account real-time people flow data within the logistics center;

[1372] The system of claim 1 further comprising:

[1373] (Claim 3)

[1374] A means to collect and analyze people flow data during an event and use it to generate optimal routes for the next event.

[1375] A means for communicating the optimal route to the delivery robot by voice or visual display;

[1376] Including a means of providing incentives when a specific route is taken within the logistics center;

[1377] 10. The system of claim 1.

[1378] "Example 2: Combining Emotion Engines"

[1379] (Claim 1)

[1380] A means for collecting and transmitting user location information;

[1381] A means to instantly generate the optimal route from current location information to destination information using a generative AI model;

[1382] means for analyzing user emotion information using an emotion engine;

[1383] A means for adjusting a route based on user emotion information;

[1384] means for transmitting the generated optimum route information to a user terminal and enabling it to be displayed on the user terminal;

[1385] A system including:

[1386] (Claim 2)

[1387] a means for periodically transmitting current location information and emotion information of the user to a server and updating an optimal route in real time;

[1388] a means for transmitting passage point information and awarding points each time a user passes through a specific checkpoint;

[1389] The system of claim 1 further comprising:

[1390] (Claim 3)

[1391] A means to collect and analyze people flow data during an event and use it to generate optimal routes for the next event.

[1392] A means for evaluating and awarding points when a user passes through a designated route;

[1393] The system of claim 1 further comprising:

[1394] "Application example 2 when combining emotion engines"

[1395] (Claim 1)

[1396] means for receiving user's current location information and destination information;

[1397] A means to instantly generate the optimal route from current location information to destination information using a generative AI model;

[1398] means for transmitting the generated optimum route information to a user terminal and enabling it to be displayed on the user terminal;

[1399] A user terminal incorporating an emotion engine that analyzes the user's emotion information in real time;

[1400] means for transmitting the user's emotional information to a server and adjusting the optimal route based on the user's emotional state;

[1401] A system including:

[1402] (Claim 2)

[1403] A means for periodically transmitting the user's current location information to a server and updating the optimal route in real time;

[1404] means for calculating passing points on the optimum route and awarding points to the user;

[1405] The system of claim 1 further comprising:

[1406] (Claim 3)

[1407] A means to collect and analyze people flow data during an event and use it to generate optimal routes for the next event.

[1408] A means to adjust the optimal route in real time based on the user's emotions;

[1409] The system of claim 1 further comprising: [Explanation of symbols]

[1410] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving user's current location information and destination information; A means to instantly generate the optimal route from current location information to destination information using a generative AI model; means for transmitting the generated optimum route information to a user terminal and enabling it to be displayed on the user terminal; A system including:

2. A means for periodically transmitting the user's current location information to a server and updating the optimal route in real time; means for calculating passing points on the optimum route and awarding points to the user; The system of claim 1 further comprising:

3. A means to collect and analyze people flow data during an event and use it to generate optimal routes for the next event. Rewards when users take a specific route

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