system

Abstract

Provide a system. [Solution] means for receiving a travel planning request from a user; means for generating accommodation and tourist destination suggestions based on the requested information; a means of optimizing travel routes between proposed tourist destinations; A means for generating a packing list based on weather information and activities at the travel destination and providing a purchasing link; A means to obtain real-time traffic conditions and congestion information at tourist spots and re-propose routes and schedules; A means of providing emergency response to travel issues; A system including:

Description

[Technical Field]

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

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

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

[0004] Modern travel planning requires consideration of numerous factors, including selecting accommodation and sightseeing spots, optimizing travel routes, preparing travel luggage, understanding real-time congestion conditions, and responding to emergencies, placing a significant burden on travelers. Furthermore, manually organizing this information and creating an optimal plan is difficult and requires time and effort. Given these issues, there is a need for a system that allows travelers to easily and effectively plan their trips and enjoy peace of mind while they are on the go. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for receiving a travel plan request from a user and generating suggested accommodation and sightseeing spots based on the request. It also includes a means for optimizing travel routes between the suggested sightseeing spots, generating a packing list based on weather information and activities at the travel destination, and providing purchasing links. It also includes a means for acquiring real-time traffic conditions and congestion information at sightseeing spots, re-suggesting routes and schedules, and providing emergency response for problems encountered during the trip. This allows the system to easily and effectively plan a trip and enjoy it with peace of mind.

[0006] "Travel planning" refers to a series of travel-related activities and preparations, including travel destinations, itineraries, accommodations, sightseeing spots, means of transportation, and schedules.

[0007] "Request" refers to information a User submits to the System regarding their travel planning wishes and requests.

[0008] "Accommodation" refers to accommodation facilities for travelers, including hotels, inns, and guesthouses.

[0009] "Tourist destination" refers to tourist attractions and tourist destinations that are visited by tourists, including historical sites, natural landscapes, theme parks, etc.

[0010] "Suggestions" refers to information that shows options for accommodation and tourist destinations generated by the system based on user requests.

[0011] "Travel Route" refers to the route for travel between proposed tourist destinations, including the means of transportation and travel time.

[0012] "Optimization" refers to the process of finding the most efficient solution based on multiple options and conditions.

[0013] "Weather Information" refers to data about weather conditions at a travel destination, including factors such as temperature, precipitation, and wind speed.

[0014] "Activities" refers to specific activities or events planned at a travel destination, including sports, sightseeing tours, and dinner parties.

[0015] A "packing list" refers to a list of items and equipment you will need while traveling.

[0016] "Purchase Link" means a hyperlink to an online shopping site for purchasing recommended items based on the inventory list.

[0017] "Real-time" refers to information and data that reflects the current situation as soon as it is collected, providing ongoing information immediately.

[0018] "Traffic conditions" refers to information about the operation status of roads and transportation, including factors such as congestion, accidents, and delays.

[0019] "Crowd information" refers to data on the number of users and degree of congestion at tourist destinations and public transport.

[0020] "Emergency response" refers to the means and processes for responding promptly to problems or issues that arise during travel. [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 illustrating a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[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 system of the present invention is designed to enable users to smoothly carry out their travel plans and to quickly respond to any problems that may arise during the trip. Each component of the present invention and its function will be described in detail below.

[0043] 1. Receiving a travel planning request

[0044] A user sends a travel request to the LINE Official Account. For example, the user sends a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[0045] The server receives this message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[0046] 2. Accommodation and sightseeing suggestions

[0047] The server searches a database of affiliated accommodations and tourist destinations, for example, to extract suitable options from hotels and tourist attractions in Okinawa Prefecture, taking into account criteria such as the user's preferences, budget, and popularity.

[0048] The server then sends the user information about the selected accommodation and sightseeing spots via LINE message, such as "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium."

[0049] 3. Optimizing travel routes

[0050] The server uses external services such as Google® Maps API to calculate travel routes between the suggested tourist spots, generating an optimal travel schedule for the user, taking into account the travel time and transportation method (public transportation, rental car, etc.) to each tourist spot.

[0051] The server then sends the generated route and schedule information to the user via LINE message. For example, it suggests a schedule such as "Day 1: From Hotel A to Shuri Castle, 30 minutes by rental car, dinner on Kokusai Street."

[0052] 4. Inventory list and purchase suggestions

[0053] The server creates a packing list based on the weather and planned activities of the destination. For example, if traveling to Okinawa in the summer, the list might include sunscreen, light clothing, and flip-flops.

[0054] In addition, the server provides a purchasing link based on the inventory list. For example, it adds information to the inventory list such as "Flip-flops, sunscreen, and beach towels can be purchased at the online shop" and sends it to the user via LINE message.

[0055] 5. Route re-proposal based on congestion

[0056] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and then re-proposes optimal routes and schedules to users based on the day's congestion forecast and traffic conditions.

[0057] For example, if Shuri Castle is crowded, the server sends the user a message such as "Shuri Castle is crowded, so we suggest you reschedule your visit to the afternoon."

[0058] 6. Emergency Response

[0059] While traveling, users can request emergency response through the LINE Official Account. For example, if their rental car breaks down, they can send a message saying, "My rental car has broken down."

[0060] The server analyzes this message and arranges for an emergency response from an affiliated support center or service, then sends the user a LINE message with instructions on how to resolve the problem and the contact details of the nearest repair service.

[0061] In this way, the system of the present invention provides consistent support from travel planning to the actual travel, allowing users to enjoy their trip with peace of mind.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] A user sends a travel request to the LINE Official Account. For example, they send a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[0065] Step 2:

[0066] The server receives the user's message and uses natural language processing (NLP) technology to analyze the message content and extract information such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[0067] Step 3:

[0068] The server then uses the analysis results to search a database of affiliated accommodations and tourist destinations using SQL queries and API requests to extract options that match the user's preferences, budget, popularity, and other criteria.

[0069] Step 4:

[0070] The server lists information on selected accommodations and tourist spots and generates suggestions for the user. Example suggestion: "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium."

[0071] Step 5:

[0072] The server sends a proposal message to the user via LINE, who can then receive and confirm the proposal.

[0073] Step 6:

[0074] The server uses external services such as Google Maps API to calculate the travel routes between the proposed tourist spots. The API request specifies the departure point and destination, and obtains the optimal travel route and travel time between each tourist spot.

[0075] Step 7:

[0076] The server creates an optimal schedule for the user based on the travel route information it has acquired. Schedule example: "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle. Dinner at Kokusai Street."

[0077] Step 8:

[0078] The server generates schedule information and sends it to the user via LINE message. The user can check the schedule and get a detailed understanding of their travel plans.

[0079] Step 9:

[0080] The server retrieves weather information for the destination and planned activities, and creates a packing list based on that information. It uses a weather information API and an activity database.

[0081] Step 10:

[0082] The server generates links to purchase the items you need based on your inventory list, such as "You can buy flip-flops, sunscreen, and beach towels from our online store."

[0083] Step 11:

[0084] The server sends the user a list of items and a link to purchase them via LINE. The user can then check the list and purchase the items they need online.

[0085] Step 12:

[0086] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, periodically querying the traffic information API and congestion status database.

[0087] Step 13:

[0088] Based on the latest information obtained by the server, the server re-proposes the user's travel route and schedule as necessary. Example of re-proposition: "Shuri Castle is crowded, so we suggest visiting it in the afternoon."

[0089] Step 14:

[0090] The server sends a re-proposal message to the user via LINE, and the user receives the new proposal and can adjust their schedule.

[0091] Step 15:

[0092] If a user encounters a problem during their trip, they can send a support request through LINE. Example: "My rental car broke down."

[0093] Step 16:

[0094] The server receives the support request, analyzes the message content, and searches for and arranges for the appropriate affiliated support center or repair service depending on the type of problem.

[0095] Step 17:

[0096] The server will send a LINE message to the user with instructions on how to resolve the issue and contact details. Example: "If your rental car is broken, we will direct you to the nearest repair service."

[0097] In this way, the system of the present invention provides a consistent service from travel planning to support during the trip, allowing users to enjoy their trip with peace of mind.

[0098] Example 1

[0099] 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."

[0100] When planning a trip, users must consider a wide range of factors, including destination, accommodation, tourist spots, transportation, and belongings, which can be time-consuming and stressful. Furthermore, the lack of prompt support to deal with unexpected problems or crowded conditions during the trip makes it difficult for users to enjoy their trip with peace of mind. There is a need for a system that can solve these problems and enable users to plan and execute trips smoothly and stress-free.

[0101] 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.

[0102] In this invention, the server includes means for receiving a travel plan request from a user, means for generating suggestions for accommodations and tourist spots based on the requested information, means for optimizing travel routes between the suggested tourist spots using external services, means for generating a packing list based on weather information and activities at the travel destination and providing links to purchase items, means for obtaining real-time traffic conditions and congestion information at tourist spots and re-suggesting routes and schedules, and means for providing emergency responses to problems that occur during the trip. This allows users to smoothly plan their trip and quickly respond to unexpected situations that arise during the trip.

[0103] Ok, I've created definitions for some important words below.

[0104] "User" means an individual or organization that uses the System to make travel plans.

[0105] A "request" is a message about travel wishes and conditions that a user sends to the system.

[0106] "Accommodation" refers to facilities for staying overnight during a trip, including hotels, inns, and guesthouses.

[0107] "Tourist destinations" refer to tourist attractions and famous places that can be visited at a travel destination.

[0108] An "external service" is a service provided by a third party that the system uses to obtain data in cooperation with, and includes, for example, a map service or a weather information service.

[0109] "Weather information" is information about the weather at the travel destination, including weather forecasts, temperature, and the probability of precipitation.

[0110] "Activities" refers to specific activities or events that can be undertaken during a trip.

[0111] A "packing list" is a list of items you will need for your trip.

[0112] A "purchase link" is a link on the Internet to purchase an item included in the inventory list.

[0113] "Real-time" refers to the immediate availability of information at that time and place.

[0114] "Traffic conditions" refers to information indicating the degree of congestion and passability of roads and public transportation.

[0115] "Congestion information" is information that indicates the degree of congestion at tourist spots, roads, etc.

[0116] "Emergency response" refers to quickly dealing with unexpected problems that arise during travel.

[0117] A "server" is a computer system that controls the entire system, processes data, and provides services.

[0118] The system of the present invention is designed to enable users to smoothly carry out their travel plans and to quickly respond to any problems that may arise during the trip. Each component of the present invention and its function will be described in detail below.

[0119] Accepting travel planning requests

[0120] A user sends a travel request to the dedicated application or LINE official account. For example, a user sends a message saying, "I would like to take a five-day trip to Okinawa for my family of four."

[0121] The server receives this message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination, duration of the trip, and number of participants. Specifically, it uses an NLP library (e.g., spaCy) to perform the analysis.

[0122] Selection of accommodation and sightseeing spots

[0123] The server searches a database of affiliated accommodations and tourist destinations (for example, a PostgreSQL database). Using the keywords extracted earlier, "Okinawa," "5 days," and "family of four," the server searches for accommodations and tourist destinations that meet the criteria. For example, the server might list "Hotel A near Kokusai Street," "Beach Resort Hotel B," "Shuri Castle," and "Okinawa Churaumi Aquarium."

[0124] Based on the selection results, the server generates a list of accommodation and tourist spot suggestions and notifies the user via LINE message.

[0125] Optimizing travel routes

[0126] The server uses the Google Maps API to calculate travel routes between the suggested tourist spots. It sends a request to the Google Maps API to obtain the distances and travel times between the tourist spots. Based on this, it generates an optimal travel schedule. The generated schedule is put together taking into account the travel time to each tourist spot and the means of transportation (public transportation, rental car, etc.). This schedule is sent to the user via LINE message.

[0127] For example, a suggestion might be, "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street."

[0128] Inventory list and purchase suggestions

[0129] The server uses a weather information API (e.g., OpenWeatherMap API) to obtain weather information for the travel destination. A packing list is created based on the obtained weather information and planned activity information. Examples of packing list items include "sunscreen," "light clothing," and "beach sandals." A corresponding purchase link is also generated along with the packing list and provided to the user via LINE message.

[0130] For example, a link might say, "Buy sunscreen, flip flops and beach towels from our online store."

[0131] Checking congestion status and re-proposing

[0132] The server periodically accesses external APIs such as the Google Maps API to obtain real-time traffic conditions and congestion information at tourist spots. Based on the expected congestion and traffic conditions for the day, the server re-suggests optimal routes and schedules for users. For example, it might suggest, "Shuri Castle is crowded, so change your visit to the afternoon."

[0133] Emergency response

[0134] If a user requests an emergency response through the LINE Official Account while traveling, they can send a message saying, for example, "My rental car has broken down."

[0135] The server receives this message and uses NLP technology to analyze the problem. It then arranges for an emergency response from a partner support center or service. This provides the user with the steps to resolve the problem and the contact information for the nearest repair service. For example, it provides the user with information such as, "The nearest repair service is XX company, and their contact number is YYY."

[0136] Examples of concrete examples and prompts

[0137] As an example showing the operation of a specific system, we will show an example of inputting the following prompt sentence into a generative AI model (e.g., ChatGPT (registered trademark)).

[0138] Specific examples

[0139] 1. A user sends a message to the LINE Official Account saying, "We are planning a three-day trip to Okinawa. Please recommend accommodations and tourist spots for our family of four."

[0140] 2. The server receives the message and uses NLP technology to extract the information "Okinawa," "3 days," and "family of four."

[0141] 3. The server searches its partner accommodation database to find accommodations that meet the criteria. For example, it finds "Hotel A, Hotel B."

[0142] 4. Next, the main tourist spots in Okinawa are searched for, and "Shuri Castle, Okinawa Churaumi Aquarium, and Kokusai Street" are selected.

[0143] 5. The server generates a list based on the selection results and suggests to the user, "You can stay at Hotel A or Hotel B and visit Shuri Castle, Okinawa Churaumi Aquarium, and Kokusai Street."

[0144] Prompt Sentence Examples

[0145] We are building an AI assistant to help you plan your trip. Plan a trip that meets the following criteria:

[0146] Travel destination: Okinawa

[0147] Duration: 3 days

[0148] Participants: 4 family members

[0149] Please suggest accommodation and sightseeing spots, travel routes, and a recommended packing list.

[0150] This concludes the explanation of the program processing of the system of the present invention in natural language, including specific examples.

[0151] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0152] Step 1:

[0153] A user sends a travel request to the LINE Official Account. For example, they send a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[0154] Input: User request message

[0155] Output: RAW message data

[0156] Step 2:

[0157] The server receives the user's request message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination, trip duration, and number of participants, for example, using an NLP library (spaCy).

[0158] Input: RAW message data

[0159] Output: Extracted keywords (e.g., Okinawa, 5 days, family of 4)

[0160] Step 3:

[0161] The server searches a database of affiliated accommodations and tourist destinations based on the extracted keywords, for example, using a PostgreSQL database.

[0162] Input: Extracted keywords

[0163] Output: List of accommodations and tourist attractions (e.g., Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium)

[0164] Step 4:

[0165] The server will send suggestions to the user via LINE message based on a list of accommodations and tourist spots.

[0166] Input: List of accommodations and tourist attractions

[0167] Output: LINE message (Example: Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium)

[0168] Step 5:

[0169] The server uses the Google Maps API to calculate routes between tourist attractions, including distances and travel times between the attractions.

[0170] Input: List of accommodations and tourist attractions

[0171] Output: Distance and travel time data between tourist spots

[0172] Step 6:

[0173] The server generates an optimal travel schedule based on the travel data it acquires, including the travel time and means of transportation to each tourist spot.

[0174] Input: Distance and travel time data between tourist spots

[0175] Output: Optimal schedule (Example: Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street)

[0176] Step 7:

[0177] The server sends the generated schedule to the user via LINE message.

[0178] Input: Optimal schedule

[0179] Output: LINE message (Example: Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street)

[0180] Step 8:

[0181] The server uses a weather information API (OpenWeatherMap API) to obtain weather information for the travel destination.

[0182] Input: Travel destination information (e.g. Okinawa)

[0183] Output: Weather data

[0184] Step 9:

[0185] The server creates a list of items to bring based on weather and activity information obtained, and also generates corresponding purchase links.

[0186] Input: Weather data, activity information

[0187] Output: Packing list and purchase links (e.g. sunscreen, light clothing, flip-flops)

[0188] Step 10:

[0189] The server sends the user a LINE message with the list of items and a link to purchase them.

[0190] Input: Inventory list and purchase links

[0191] Output: LINE message (e.g., sunscreen, flip-flops, and beach towels are available for purchase at the online store)

[0192] Step 11:

[0193] The server uses external APIs such as Google Maps API to periodically obtain real-time traffic conditions and congestion information at tourist spots.

[0194] Input: Current travel schedule, traffic data

[0195] Output: Updated schedule (if necessary)

[0196] Step 12:

[0197] The server sends the updated schedule to the user via LINE message, which may include, for example, "Shuri Castle is crowded, so we will reschedule our visit to the afternoon."

[0198] Input: Updated Schedule

[0199] Output: LINE message

[0200] Step 13:

[0201] While traveling, a user requests an emergency response through the LINE Official Account. For example, they can send a message saying, "My rental car has broken down."

[0202] Input: Emergency response message

[0203] Output: RAW emergency message data

[0204] Step 14:

[0205] The server receives the emergency message and uses NLP technology to analyze the nature of the problem.

[0206] Input: RAW emergency message data

[0207] Output: Extracted problem keywords (e.g., rental car, breakdown)

[0208] Step 15:

[0209] Based on the analyzed problem, the server will dispatch emergency response to partner support centers or services, for example, dispatching the nearest repair service and obtaining contact information.

[0210] Input: Extracted problem keywords

[0211] Output: Repair service contact information

[0212] Step 16:

[0213] The server will send a LINE message to the user with instructions on how to resolve the problem and the contact information for the nearest repair service.

[0214] Input: Repair service contact information

[0215] Output: LINE message (e.g., the nearest repair service is XX company, contact number is YYY)

[0216] The above are the specific processing steps and contents of the program for this system.

[0217] (Application example 1)

[0218] 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."

[0219] Systems that provide consistent support, from planning a trip to troubleshooting during the trip, require a wide range of information, and are often complex and difficult for users to use. Arranging meals during a trip and responding to sudden changes in circumstances are also difficult challenges. These challenges make it difficult for users to enjoy their trip comfortably.

[0220] 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.

[0221] In this invention, the server includes means for receiving a travel plan request from a user, means for generating suggestions for accommodations and sightseeing spots based on the requested information, means for optimizing travel routes between the suggested sightseeing spots, means for generating a packing list based on weather information and activities at the travel destination and providing links to purchases, means for obtaining real-time traffic conditions and congestion information at sightseeing spots and re-proposing routes and schedules, means for receiving a request for meal delivery at the travel destination and searching for and suggesting affiliated restaurants, means for tracking delivery progress in real time and notifying the user, and means for providing emergency responses to problems during the trip. This makes it possible to efficiently perform everything from travel planning to dealing with problems during the trip, as well as arranging meals and responding to changes in the situation, all in one system.

[0222] A "user" is a person who utilizes the system to submit travel planning requests and receive suggestions and assistance.

[0223] A "travel plan" refers to a series of activities including travel destinations, accommodations, sightseeing spots, travel routes, packing list, meal delivery, and emergency response.

[0224] A "request" is information that a user submits to the system to communicate their travel planning wishes and desires.

[0225] An "accommodation" is a place where a user stays during a trip, such as a hotel or resort.

[0226] A "tourist spot" is a tourist spot in a travel destination that the user intends to visit.

[0227] A "travel route" is a route for efficiently traveling between the proposed tourist destinations.

[0228] "Weather information" is data about the weather at the travel destination, and is used to generate a packing list.

[0229] An "activity" is a planned action or event during a trip.

[0230] A "packing list" is a list of items necessary for a trip, and is generated based on weather information and activities.

[0231] A "purchase link" is a URL for online purchase of recommended items based on the inventory list.

[0232] "Traffic conditions" refers to data on traffic flow between travel destinations and tourist spots.

[0233] "Crowding information" is real-time information about the degree of congestion at tourist spots and travel routes.

[0234] "Meal delivery" is a service that allows users to order meals while traveling and have them delivered to their destination.

[0235] "Eating and drinking establishments" are establishments such as restaurants and cafes that serve meals and offer delivery services.

[0236] "Delivery progress" is information about the stage at which the ordered meal is and when it will arrive to the user.

[0237] "Emergency response" means assistance to provide a quick solution to unexpected problems that arise during travel.

[0238] A "support center" is a base for responding to emergency requests from users.

[0239] A specific embodiment of the travel planning and travel assistance system will be described in detail below.

[0240] Components and Functions

[0241] 1. Receiving a travel planning request from a user

[0242] The system receives a travel planning request from the user, such as a basic request like "Please deliver sushi for two in Okinawa" via a device like a smartphone or smart glasses, and then sends information such as the trip destination, number of people, and desired services to the server.

[0243] 2. Request analysis using natural language processing

[0244] The server then uses natural language processing (NLP) technology to analyze the incoming request and determine the destination, number of people, and desired services, using an NLP engine such as Google Cloud Natural Language API.

[0245] 3. Accommodation and sightseeing suggestions

[0246] Based on the analyzed request information, the server generates appropriate suggestions from a database of affiliated accommodation and tourist destinations. For example, if a user inputs "I'm planning a five-day trip to Okinawa for my family of four," the system will search for hotels and tourist attractions in Okinawa Prefecture and make suggestions based on the user's preferences and budget.

[0247] 4. Generate inventory list and purchase links

[0248] The server generates a list of necessary items to bring based on the weather information and activities of the destination. For example, if you are traveling to Okinawa in the summer, it will list light clothing and beach sandals, and provide a purchasing link. This link is designed so that the user can easily purchase the items on an online shopping site.

[0249] 5. Optimizing travel routes

[0250] The server uses external services such as Google Maps API to optimize travel routes between tourist spots. It generates an optimal travel schedule by taking into account the travel time and transportation means to each tourist spot. For example, it suggests a schedule such as "30 minutes by rental car from Hotel A to Shuri Castle."

[0251] 6. Get real-time traffic and congestion information

[0252] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and re-proposes routes and schedules as necessary. For example, congestion information is used to suggest, "Shuri Castle is crowded, so let's change our visit to the afternoon."

[0253] 7. Arrange for meal delivery

[0254] The server arranges meal delivery to the travel destination based on the user's request. It searches a database of affiliated restaurants to suggest appropriate menus and restaurants to the user. It then arranges delivery based on the user's selection. Delivery progress information is tracked in real time and notified to the user.

[0255] 8. Providing emergency response

[0256] If a problem occurs during a trip, such as a breakdown in a rental car, the user sends an emergency request to the system. The server analyzes the request, coordinates with affiliated support centers and the necessary emergency response, and provides the user with instructions on how to resolve the issue.

[0257] Hardware and software used

[0258] Smartphones / Smart Glasses: Used as an interface for the user.

[0259] Server: Receives, analyzes, proposes, arranges and notifies requests.

[0260] Natural language processing engine: Analyzes user requests using the Google Cloud Natural Language API, etc.

[0261] Database: Stores information about affiliated accommodations, tourist spots, and restaurants (MySQL (registered trademark), etc.).

[0262] External API service: Uses Google Maps API to optimize travel routes and obtain traffic information.

[0263] Delivery management system: Use APIs such as Uber Eats to schedule and track food deliveries.

[0264] Specific examples and input prompts for generative AI models

[0265] Example: "Sushi delivery for two in Okinawa."

[0266] Prompt statement:

[0267] Message: "Sushi delivery for two in Okinawa"

[0268] Destination: Okinawa

[0269] Type of cuisine: Sushi

[0270] Number of people: 2 people

[0271] Analyze the request details.

[0272] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0273] Step 1:

[0274] A user submits a travel planning request.

[0275] The user uses a smartphone or smart glasses to input and send a request message such as "Please deliver sushi for two in Okinawa," which is then sent to the server.

[0276] Input: Request message (e.g. "Please deliver sushi for two in Okinawa")

[0277] Output: The server receives the request message.

[0278] Step 2:

[0279] The server receives the request and performs analysis using natural language processing (NLP).

[0280] The server uses an NLP engine such as Google Cloud Natural Language API to analyze the request message and extract information such as the destination (Okinawa), number of people (2), and desired service (sushi delivery).

[0281] Input: Request message

[0282] Output: Extracted information (destination, number of people, desired services)

[0283] Step 3:

[0284] The server generates suggestions for accommodation and sightseeing spots.

[0285] Based on the user's request, the server searches its database of affiliated accommodation and tourist destinations and generates suggestions suitable for the user. For example, it searches for hotels and tourist attractions in Okinawa Prefecture and makes suggestions based on the user's preferences and budget.

[0286] Input: Request details (destination, number of people, desired service)

[0287] Output: Accommodation and sightseeing suggestions

[0288] Step 4:

[0289] The server generates the inventory list and purchase links.

[0290] The server generates a packing list based on the weather information of the destination and the planned activities. For example, if traveling to Okinawa in the summer, the list may include sunscreen, light clothing, beach sandals, etc. Then, based on the packing list, it generates a purchase link to an online shopping site and provides it to the user.

[0291] Input: Weather information, activity information

[0292] Output: Inventory list and purchase links

[0293] Step 5:

[0294] The server optimizes the travel route.

[0295] The server uses external services such as Google Maps API to calculate travel routes between the proposed tourist spots and generate an optimal travel schedule, taking into account the travel time to each tourist spot and the means of transportation (e.g., public transportation, rental car, etc.).

[0296] Input: tourist destination information, transportation data

[0297] Output: Travel routes and schedules

[0298] Step 6:

[0299] The server retrieves real-time traffic and congestion information and re-suggests routes and schedules.

[0300] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and based on that information, it re-proposes optimal routes and schedules to users. For example, if Shuri Castle is crowded, it will re-propose a visit to the castle in the afternoon.

[0301] Input: Real-time traffic information, congestion information

[0302] Output: Reproposed route and schedule

[0303] Step 7:

[0304] The server proposes and arranges meal delivery at the travel destination.

[0305] Based on the user's request, the server searches a database of affiliated restaurants and suggests appropriate menus and restaurants to the user. It also arranges delivery from the restaurant selected by the user and tracks the delivery progress in real time.

[0306] Input: Request details, partner restaurant data

[0307] Output: Suggested restaurant and ordering information, tracking information

[0308] Step 8:

[0309] The server provides emergency response for travel issues.

[0310] If a user encounters a problem during their trip, they send an emergency request to the server, which analyzes the request, coordinates with affiliated support centers and necessary emergency response, and provides the user with a solution and contact information.

[0311] Input: Urgent Request

[0312] Output: Emergency response arrangements and solution proposals

[0313] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0314] The system of the present invention is designed to enable users to smoothly execute their travel plans and quickly respond to any problems that may arise during the trip. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions and adjusts the content of the suggestions based on those emotions. Each component of the present invention and its function will be described in detail below.

[0315] 1. Receiving a travel planning request

[0316] A user sends a travel request to the LINE Official Account. For example, the user sends a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[0317] The server receives this message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[0318] 2. Accommodation and sightseeing suggestions

[0319] The server searches a database of affiliated accommodations and tourist destinations, for example, to extract suitable options from hotels and tourist attractions in Okinawa Prefecture, taking into account criteria such as the user's preferences, budget, and popularity.

[0320] Next, the server will suggest information about the selected accommodations and sightseeing spots to the user. For example, suggestions such as "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium" will be sent via LINE message.

[0321] The server uses an emotion engine to recognize the user's feelings toward these suggestions. For example, if a user sends a message saying "Hotel A is too expensive," the emotion engine recognizes that the user has a negative feeling toward the suggestion.

[0322] 3. Optimizing travel routes

[0323] The server uses external services such as Google Maps API to calculate travel routes between the proposed tourist spots, generating an optimal travel schedule for the user, taking into account the travel time and transportation method (public transportation, rental car, etc.) to each tourist spot.

[0324] For example, schedule information such as "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street" is sent to the user via LINE message. If the user expresses dissatisfaction by saying "the travel time is too long," the emotion engine will pick up on the user's emotions, and the server will recalculate the travel route based on this.

[0325] 4. Inventory list and purchase suggestions

[0326] The server creates a packing list based on the weather and planned activities of the destination. For example, if traveling to Okinawa in the summer, the list might include sunscreen, light clothing, and flip-flops.

[0327] The server provides a purchasing link based on the list of belongings, for example, "Flip-flops, sunscreen, and beach towels are available for purchase at the online shop," and sends the link to the user via LINE message.

[0328] 5. Route re-proposal based on congestion

[0329] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and then re-proposes optimal routes and schedules to users based on the day's congestion forecast and traffic conditions.

[0330] For example, if Shuri Castle is crowded, the server sends the user a message such as "Shuri Castle is crowded, so we suggest you reschedule your visit to the afternoon."

[0331] 6. Emergency Response

[0332] If a user encounters a problem during their trip, they can send a support request through the LINE official account. For example, if their rental car breaks down, they can send a message saying, "My rental car has broken down."

[0333] The server analyzes this message and arranges for an emergency response from an affiliated support center or service, then sends the user a LINE message with instructions on how to resolve the problem and the contact details of the nearest repair service.

[0334] 7. Use of Emotion Engines

[0335] The server uses an emotion engine to recognize emotions from the user's message. For example, if the user feels that they "don't like" the proposed accommodation, the emotion engine captures that negative emotion.

[0336] The server adjusts its suggestions based on the captured emotions. If the user expresses positive emotions, it stores the emotion information to use it in future suggestions. This ensures that the next time the user submits a request, suggestions will take into account their previous emotional history.

[0337] By combining this emotion engine, the system can make suggestions that are in line with the user's emotions and provide a comprehensive service, from travel planning to support during the trip.

[0338] The processing flow will be explained below.

[0339] Step 1:

[0340] A user sends a travel request through the LINE official account. For example, they send a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[0341] Step 2:

[0342] The server analyzes the received message and uses natural language processing (NLP) technology to extract information from the request, such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[0343] Step 3:

[0344] The server searches a database of affiliated accommodations and tourist destinations, extracting appropriate options based on the user's preferences, budget, popularity, and other criteria.

[0345] Step 4:

[0346] The server selects and suggests information about accommodation and sightseeing spots to the user. Example of suggestion: Send information such as "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium" via LINE message.

[0347] Step 5:

[0348] The user reviews the suggestions and provides feedback, for example, a message saying "Hotel A is too expensive."

[0349] Step 6:

[0350] The emotion engine analyzes the user feedback and recognizes emotions. In this case, the emotion engine catches negative emotions (felt too high).

[0351] Step 7:

[0352] The server then adjusts the recommendation based on the emotion engine's analysis, for example by finding another hotel within the customer's budget and suggesting, "How about Hotel B?"

[0353] Step 8:

[0354] The server calculates the travel routes between the proposed tourist spots using the Google Maps API, etc., and obtains the optimal travel route and travel time between each tourist spot.

[0355] Step 9:

[0356] The server creates an optimal schedule for the user based on the route information it obtains. Schedule example: "Day 1: 30 minutes by rental car from Hotel B to Shuri Castle, dinner at Kokusai Street" is sent via LINE message.

[0357] Step 10:

[0358] Users can review the schedule and provide feedback, such as "travel time is too long."

[0359] Step 11:

[0360] The emotion engine again analyzes the user feedback and recognizes emotions, in this case catching the negative emotion (travel time is too long).

[0361] Step 12:

[0362] The server again adjusts the suggestion, for example, calculating a new route to shorten the travel time, such as "leave in the afternoon instead."

[0363] Step 13:

[0364] The server creates a packing list based on weather information and planned activities. For example, the list might include "sunscreen, light clothing, and flip-flops."

[0365] Step 14:

[0366] The server provides a link to purchase items based on the list. For example, it sends a LINE message containing information such as "Flip-flops, sunscreen, and beach towels can be purchased from the online shop."

[0367] Step 15:

[0368] The server periodically retrieves real-time traffic information and congestion information for tourist spots, e.g., makes an API request every 15 minutes.

[0369] Step 16:

[0370] The server will re-suggest routes and schedules for the user based on the latest information as needed. For example, a LINE message will be sent saying, "Shuri Castle is crowded, so we suggest visiting in the afternoon."

[0371] Step 17:

[0372] If a user encounters a problem during their trip, they can send a support request through LINE, for example, by sending a message saying, "My rental car has broken down."

[0373] Step 18:

[0374] The server analyzes the support request and dispatches affiliated support centers or emergency response services depending on the type of problem.

[0375] Step 19:

[0376] The server will send a LINE message to the user with instructions on how to resolve the issue and the contact information for the nearest repair service. For example, it might say, "The nearest repair service is here."

[0377] By combining this emotion engine, the system can make suggestions that are in line with the user's emotions and provide a comprehensive service, from travel planning to support during the trip.

[0378] Example 2

[0379] 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."

[0380] Conventional travel planning support systems make suggestions based on the user's preferences, but they have the problem of being unable to respond flexibly to the user's emotions and real-time circumstances. Furthermore, they lack functionality that consistently supports the entire travel plan, such as packing lists, route optimization, and emergency response.

[0381] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving a travel plan request from a user, means for analyzing the requested information and extracting the destination, travel period, and participating members, means for generating suggestions of accommodation and sightseeing spots based on the extracted information, means for analyzing the user's feelings about the proposed accommodation and sightseeing spots, means for adjusting the suggestions based on the user's feelings, means for optimizing travel routes between the proposed sightseeing spots, means for generating a packing list based on weather information and activities at the travel destination and providing a purchasing link, means for obtaining real-time traffic conditions and congestion information at sightseeing spots and re-proposing routes and schedules, and means for providing emergency response for problems encountered during the trip. This allows users to receive comprehensive services from travel planning to support during the trip.

[0382] "User" refers to an individual or organization that uses the System to plan and execute travel plans.

[0383] "Travel plan request" refers to the act of a user sending information about a travel plan, such as destination, travel period, and participating members, to the server.

[0384] "Means" refers to a method, apparatus, or component in a system for achieving a particular purpose.

[0385] "Requested Information" means the data provided by a User to a Server in a Travel Planning Request.

[0386] "Analyzing information" refers to the process of analyzing received data and understanding or classifying its content.

[0387] "Destination" refers to the final destination or place of stay of a trip.

[0388] "Travel Period" refers to the time span from the start to the end of a trip.

[0389] "Participating Member" means an individual person participating in a trip.

[0390] "Accommodation" refers to the place where you stay during your trip.

[0391] "Tourist destinations" refer to tourist attractions and places of interest that are planned to be visited during a trip.

[0392] "Emotion analysis" refers to the process of reading a user's emotional state from their messages and feedback.

[0393] "Adjusting suggestions based on emotions" refers to the act of changing or optimizing the system's suggestions by taking into account the user's emotional information.

[0394] "Route optimization" refers to the process of adjusting travel routes during a planned trip to make them more efficient and effective.

[0395] "Weather Information" refers to data regarding weather conditions at a travel destination.

[0396] "Activities" refers to events or activities planned to take place during a trip.

[0397] A "packing list" is a list of items that should be brought on a trip.

[0398] "Purchase Link" means an online link to purchase an item included in the inventory list.

[0399] "Real-time traffic conditions" refers to information about current traffic conditions and status.

[0400] "Crowding information for tourist spots" refers to information on the current level of congestion at tourist spots and famous places.

[0401] "Route and schedule re-proposal" refers to the act of reevaluating travel plans based on real-time information and providing optimal travel routes and time allocations.

[0402] "Emergency response" refers to dealing with and providing support in the event of an unexpected problem occurring during travel.

[0403] The system of the present invention provides users with a consistent service from planning a trip to support during the trip. Each component of the present invention and its function will be described in detail below.

[0404] 1. Receiving and analyzing travel planning requests

[0405] A user sends a travel request to a LINE official account. For example, a message such as "I'm looking for a five-day trip to Okinawa for a family of four" is sent. The server receives this message and uses natural language processing (NLP) technology to extract key information from the request (destination, trip duration, and participating members). A common natural language processing API (such as Google Cloud Natural Language API) is used as the NLP engine.

[0406] 2. Accommodation and sightseeing suggestions

[0407] The server searches a database of affiliated accommodations and tourist destinations. For example, it executes SQL queries using a database management system (e.g., MySQL) to select accommodations and tourist destinations that fit the user's preferences and budget. The server then suggests information about the selected accommodations and tourist destinations to the user. Examples of suggestions could include "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, and Okinawa Churaumi Aquarium."

[0408] 3. Analyzing user sentiment and adjusting suggestions

[0409] When a user sends a LINE message with their opinion or thoughts about a suggestion, the server uses an emotion engine to analyze the user's emotions. The emotion engine uses a machine learning model (e.g., BERT), for example. Based on the results of this emotion analysis, the server adjusts the suggestion. For example, if a user sends negative feedback such as "Hotel A is too expensive," the server will reconsider the accommodation options and make a new suggestion.

[0410] 4. Optimizing travel routes

[0411] The server uses the Google Maps API to calculate travel routes between the suggested tourist spots. It generates the optimal travel schedule for the user, taking into account public transportation, rental cars, and other means of transportation. For example, it sends the user a LINE message with schedule information such as "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street."

[0412] 5. Create a packing list and get purchase suggestions

[0413] The server creates a packing list based on the weather information for the destination and the planned activities. It uses a weather API (e.g., OpenWeatherMap API) to obtain weather information. It also provides links to purchase specific products based on the packing list. For example, it sends a LINE message to the user with links to purchase beach sandals and sunscreen.

[0414] 6. Re-suggestions based on real-time information

[0415] The server periodically obtains real-time traffic conditions and congestion information at tourist spots, and based on this information, re-proposes optimal routes and schedules. It obtains information using traffic APIs (e.g., Google Maps Traffic) and congestion information services (e.g., Tourist Information API) and makes appropriate suggestions to the user. For example, it sends a message such as, "Shuri Castle is crowded, so we suggest you change your visit to the afternoon."

[0416] 7. Emergency Response

[0417] If a user encounters a problem during their trip, they can send a support request through their official LINE account. For example, if they send a message like "My rental car has broken down," the server will analyze the message and arrange for an emergency response from an affiliated support center. The server will then send a LINE message to the user with instructions on how to resolve the problem and the contact details of the nearest repair service.

[0418] Specific examples

[0419] Below is a concrete example of how the system works.

[0420] Start planning your trip

[0421] 1. A user sends a message to the LINE official account saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[0422] 2. The server receives the message and extracts the information using NLP techniques.

[0423] Destination: Okinawa

[0424] Trip duration: 5 days

[0425] Participants: Family of 4

[0426] Accommodation suggestions

[0427] 1. The server searches the accommodation database and selects hotels that meet the user's criteria.

[0428] 2. Send a LINE message with suggestions such as "Hotel A near Kokusai Street, Beach Resort Hotel B."

[0429] Use of emotion engine

[0430] 1. The user replies, "Hotel A is too expensive."

[0431] 2. The emotion engine captures the user's negative emotions, and the server uses this to re-suggest other hotels.

[0432] Optimizing travel routes

[0433] 1. The server calculates the route using the Google Maps API and sends the schedule to the user.

[0434] "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle"

[0435] Creating a packing list

[0436] 1. The server creates an inventory list based on weather information and activity.

[0437] "Flip flops, sunscreen, beach towels."

[0438] Re-proposal depending on congestion situation

[0439] 1. On the day, the server obtains real-time congestion information.

[0440] 2. Send a message saying, "Shuri Castle is crowded, so we suggest changing your visit to the afternoon."

[0441] Emergency response

[0442] 1. A user reports a malfunction in their rental car.

[0443] 2. The server will arrange for an emergency response from the partner service and provide contact information for the repair service.

[0444] Example prompts

[0445] "We are a family of four looking for a five-day trip. Destination: Okinawa. Please give us some suggestions for accommodation and sightseeing spots."

[0446] "I'd like to stay at Hotel A near Kokusai Street, but it's over my budget. Can you suggest another hotel?"

[0447] "What transportation options and routes are available during my trip?"

[0448] "Make a packing list and provide links to purchase the items you need."

[0449] This will clarify how users will utilize the system and what benefits they will gain.

[0450] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0451] Step 1:

[0452] A user sends a travel planning request to the LINE Official Account. For example, the user sends a message saying, "I'm looking for a five-day trip to Okinawa for a family of four." This message is the input data.

[0453] The server receives this message and analyzes the request using natural language processing (NLP) technology. Specifically, it uses an NLP engine (e.g., Google Cloud Natural Language API) to extract key information from the text, such as the destination, trip duration, and participating members. The extracted destination, trip duration, and participating members are the output data.

[0454] Step 2:

[0455] The server uses the extracted information to search a database of affiliated accommodations and tourist destinations, for example, by executing an SQL query using a database management system (e.g., MySQL). This SQL query is the input data.

[0456] The server selects appropriate accommodation and tourist destinations based on the user's desired conditions and budget. Information on the selected accommodation and tourist destinations is the output data. The server then sends this information to the user via LINE message. Examples of suggestions include "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle."

[0457] Step 3:

[0458] The user sends a LINE message with their opinion or feedback on the proposal. For example, they might send a message saying, "Hotel A is too expensive." This message is the input data.

[0459] The server uses an emotion engine to analyze the message and determine the user's emotion. The emotion engine uses a common machine learning model (e.g., BERT). The emotion analysis result is the output data. Based on the analysis result, the server adjusts the suggestions. For example, if the user expresses negative emotions, it will re-suggest other accommodations.

[0460] Step 4:

[0461] The server then optimizes the travel route between the proposed tourist spots. Specifically, it calculates the travel route using the Google Maps API. To calculate the route, the location information of the tourist spots and the means of transportation (public transportation, rental car, etc.) are input data.

[0462] The server generates an optimal travel schedule based on this input data. The generated schedule is the output data. For example, it generates schedule information such as "Day 1: From Hotel A to Shuri Castle, 30 minutes by rental car, dinner at Kokusai Street," and sends it to the user via LINE message.

[0463] Step 5:

[0464] The server creates a packing list based on the weather information of the destination and the planned activities. Specifically, weather information retrieval API (e.g., OpenWeatherMap API) and activity information are input data.

[0465] The server combines these input data and generates a list of necessary items. The generated list is the output data. It also provides links to purchase specific products based on the list. The provided purchase links are the output data. For example, a "purchase link for beach sandals and sunscreen" is sent to the user via LINE message.

[0466] Step 6:

[0467] The server periodically obtains real-time traffic conditions and congestion information at tourist spots. This information is input from traffic APIs (e.g., Google Maps Traffic API) and congestion information providers (e.g., Tourist Information API).

[0468] Based on the acquired information, the server re-proposes the optimal route and schedule for the day's conditions. The re-proposed route and schedule are the output data. For example, a message such as "Shuri Castle is crowded, so we suggest changing your visit to the afternoon" is sent to the user.

[0469] Step 7:

[0470] If a user encounters a problem during their trip, they can send a support request through their LINE official account. For example, they can send a message such as "My rental car has broken down." This message is the input data.

[0471] The server analyzes this message and arranges for an emergency response from an affiliated support center. The server then provides the user with instructions on how to resolve the problem and the contact information for the nearest repair service. The instructions and contact information are output data.

[0472] (Application example 2)

[0473] 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."

[0474] Current planning support systems and recommendation systems lack the ability to adjust proposal content taking into account the user's emotions, making it difficult to increase user satisfaction. This can result in inappropriate proposals received by users, leading to dissatisfaction with the plans and recommendations. Furthermore, the lack of a function for re-proposals based on real-time conditions can lead to a lack of flexibility in planning.

[0475] The specific processing by the specific 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 a plan request from a user; means for generating suggestions for places to stay and places to visit based on the requested information; means for optimizing travel routes between the suggested places to visit; means for generating a packing list based on destination condition information and activities and providing purchasing links; means for acquiring real-time situation information and congestion information for places to visit and re-proposing routes and schedules; means for providing emergency responses to problems during planning; means for receiving a text message input by the user and detecting emotions from the text; and means for adjusting the content of the next suggestion to be provided based on the detected emotions. This enables suggestions that take the user's emotions into consideration, improves user satisfaction, and enables flexible responses in real time.

[0476] "User" refers to the people who use a system or application.

[0477] A "planning request" is a request for information submitted by a user based on a specific purpose or preference.

[0478] "Place of stay" refers to a place or facility where a user temporarily stays.

[0479] "Places to visit" refers to places or tourist attractions that users wish to visit.

[0480] A "travel route" refers to the route or means of travel from one point to another.

[0481] "Condition information" refers to information about the environment or situation associated with a particular place or time.

[0482] "Activities" refers to the activities or events that you plan to take place at your planned visit or stay.

[0483] A "packing list" is a list of items needed for a particular project or situation.

[0484] "Purchase Link" refers to a website URL or link to purchase an item included in your inventory.

[0485] "Situation information" refers to information such as traffic conditions and congestion at places visited or stayed that is obtained in real time.

[0486] A "schedule" refers to the allocation or planning of time for carrying out a particular activity.

[0487] "Emergency response" refers to the means and methods for quickly dealing with problems or troubles that arise during planning.

[0488] "Input text message" refers to textual information that a user sends to a system or application.

[0489] "Emotion" refers to the user's psychological state or mood detected from the input text message.

[0490] "Suggestions" refers to specific recommendations and advice provided by the system based on the user's plans and preferences.

[0491] MODE FOR CARRYING OUT THE INVENTION

[0492] The present invention is a system designed to enable users to smoothly execute various plans and quickly respond to any problems that arise during the process. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the content of suggestions based on those emotions. Below, we will explain how this system is configured and how it is operated.

[0493] System Configuration

[0494] This system consists of a server and the devices used by users (smartphones, PCs, etc.). The main hardware and software includes the following:

[0495] Server: High-performance data processing server (e.g., AWS (registered trademark) or Google Cloud Platform)

[0496] Terminal: User device such as a smartphone or computer

[0497] Sentiment Engine: A library that performs sentiment analysis on text messages (e.g., TextBlob)

[0498] API: Integration with external services (e.g., Google Maps API, OpenWeather API)

[0499] Database: Data store for managing accommodations, places to visit, and belongings lists

[0500] Program processing

[0501] 1. Receiving a planning request

[0502] When a user sends a request from their device, the server receives the request, analyzes the content, and uses natural language processing technology to extract information such as the destination, itinerary, and participants from the request.

[0503] 2. Proposal Generation

[0504] The server generates suggestions based on the user's request. When suggesting places to stay or visit, it compares the user's preferences, budget, and reputation with a pre-prepared database to select appropriate locations.

[0505] 3. Optimizing travel routes

[0506] To optimize travel routes between the proposed destinations, we use external services such as Google Maps API to calculate transportation modes and travel times, and generate an optimal schedule for the user.

[0507] 4. Generate a list of items

[0508] The server generates a packing list based on destination conditions and activities, using data from a weather API and planned activities, and provides relevant shopping links for online shopping.

[0509] 5. Obtaining context information and re-proposing

[0510] It obtains real-time situational information (e.g., traffic conditions, congestion information) and re-proposes routes and schedules if the user's plans are affected, allowing users to respond flexibly to changing conditions.

[0511] 6. Emergency Response

[0512] If a problem occurs during the planning process, the user can request an emergency response from the server via their terminal. The server receives this request and promptly makes arrangements with affiliated support centers and services.

[0513] 7. Emotion detection and suggestion adjustment

[0514] The system receives a text message from the user and detects the emotion using the TextBlob library. Based on the emotion detected, the system adjusts the next suggestions provided. For example, if the user types "This documentary really moved me," the system detects a positive emotion and recommends content that will move them next.

[0515] Examples and prompts

[0516] Specific examples

[0517] 1. Receiving a planning request: A user sends a message saying, "I want to take my family on a 5-day trip to Kyoto."

[0518] 2. Proposal generation: The server proposes "Hotel A in Arashiyama" and "Hotel B in Gion," as well as "Kinkaku-ji Temple" and "Kiyomizu-dera Temple" as places to visit.

[0519] 3. Route optimization: The server uses the Google Maps API to calculate the optimal route from Kinkaku-ji Temple to Kiyomizu-dera Temple.

[0520] 4. Generate a list of items to bring: The server generates a list of items such as rain gear and comfortable walking shoes based on weather and activity information, and provides a link to purchase them.

[0521] 5. Obtaining situation information and re-suggestion: If Kinkaku-ji Temple is crowded on the day of your visit, the server will suggest "changing your visit to the afternoon."

[0522] 6. Emergency response: If the rental car breaks down during the plan, the server will arrange to contact the nearest repair service.

[0523] 7. Emotion detection and suggestion tailoring: If a user types, "This documentary really moved me," next time we'll recommend a different documentary or a heartwarming anime that will move them.

[0524] Prompt Sentence Examples

[0525] "User input text: "This documentary was really moving." Sentiment analysis detects a positive sentiment, so we recommend the following positive videos. Recommended video list: 1. Heartwarming anime 2. Funny comedy"

[0526] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0527] Step 1:

[0528] A user sends a planning request using a device such as a smartphone. The input includes information such as the destination, itinerary, and participants. The device then sends this information to the server via LINE messages or a dedicated app.

[0529] Step 2:

[0530] The server analyzes requests received from users using natural language processing (NLP) technology. Specifically, it extracts information such as destination, schedule, and participants. The input is the user message, and the output is the analysis results (destination, schedule, participants, etc.).

[0531] Step 3:

[0532] The server generates suggestions for places to stay and visit based on the analysis results. It accesses a database of accommodations and tourist destinations and extracts the best options based on the user's preferences, budget, and reputation. The input is the analysis results, and the output is suggested places to stay and visit.

[0533] Step 4:

[0534] The server optimizes the proposed travel routes between the destinations. It uses the Google Maps API to calculate the optimal route and transportation. The input is a list of destinations, and the output is the optimal travel route and travel time.

[0535] Step 5:

[0536] The server generates an inventory list based on destination condition information and activities, for example, using data from a weather information API or planned activity information, and provides purchase links for items related to the inventory list. The input is destination condition information and activity information, and the output is the inventory list and purchase links.

[0537] Step 6:

[0538] The server obtains real-time situation information and congestion information for destinations and re-proposes routes and schedules. If necessary, it recalculates based on traffic condition data and congestion information obtained from the API. The input is real-time situation information, and the output is the re-proposed route or schedule.

[0539] Step 7:

[0540] If a user needs emergency response during planning, they send an emergency response request to the server via their terminal. The server receives this request and promptly arranges for it to be sent to a support center or service that it is affiliated with. The input is the emergency response request, and the output is the procedure for resolving the problem and the contact information for the nearest support service.

[0541] Step 8:

[0542] The server receives an input text message from a user and detects the emotion using an emotion engine (e.g., TextBlob library). Specifically, it analyzes the text for positive or negative emotion. The input is the text message, and the output is the detected emotion (e.g., emotion score).

[0543] Step 9:

[0544] The server then adjusts the next suggestions it provides based on the detected emotion. For example, if a positive emotion is detected, it recommends content that is likely to further inspire the user. The input is the detected emotion, and the output is the adjusted suggestions.

[0545] 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.

[0546] 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 (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0547] 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.

[0548] [Second embodiment]

[0549] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0550] 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.

[0551] 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).

[0552] 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.

[0553] 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.

[0554] 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).

[0555] 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.

[0556] 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.

[0557] 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.

[0558] 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.

[0559] 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.

[0560] 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."

[0561] The system of the present invention is designed to enable users to smoothly carry out their travel plans and to quickly respond to any problems that may arise during the trip. Each component of the present invention and its function will be described in detail below.

[0562] 1. Receiving a travel planning request

[0563] A user sends a travel request to the LINE Official Account. For example, the user sends a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[0564] The server receives this message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[0565] 2. Accommodation and sightseeing suggestions

[0566] The server searches a database of affiliated accommodations and tourist destinations, for example, to extract suitable options from hotels and tourist attractions in Okinawa Prefecture, taking into account criteria such as the user's preferences, budget, and popularity.

[0567] The server then sends the user information about the selected accommodation and sightseeing spots via LINE message, such as "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium."

[0568] 3. Optimizing travel routes

[0569] The server uses external services such as Google Maps API to calculate travel routes between the proposed tourist spots, generating an optimal travel schedule for the user, taking into account the travel time and transportation method (public transportation, rental car, etc.) to each tourist spot.

[0570] The server then sends the generated route and schedule information to the user via LINE message. For example, it suggests a schedule such as "Day 1: From Hotel A to Shuri Castle, 30 minutes by rental car, dinner on Kokusai Street."

[0571] 4. Inventory list and purchase suggestions

[0572] The server creates a packing list based on the weather and planned activities of the destination. For example, if traveling to Okinawa in the summer, the list might include sunscreen, light clothing, and flip-flops.

[0573] In addition, the server provides a purchasing link based on the inventory list. For example, it adds information to the inventory list such as "Flip-flops, sunscreen, and beach towels can be purchased at the online shop" and sends it to the user via LINE message.

[0574] 5. Route re-proposal based on congestion

[0575] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and then re-proposes optimal routes and schedules to users based on the day's congestion forecast and traffic conditions.

[0576] For example, if Shuri Castle is crowded, the server sends the user a message such as "Shuri Castle is crowded, so we suggest you reschedule your visit to the afternoon."

[0577] 6. Emergency Response

[0578] While traveling, users can request emergency response through the LINE Official Account. For example, if their rental car breaks down, they can send a message saying, "My rental car has broken down."

[0579] The server analyzes this message and arranges for an emergency response from an affiliated support center or service, then sends the user a LINE message with instructions on how to resolve the problem and the contact details of the nearest repair service.

[0580] In this way, the system of the present invention provides consistent support from travel planning to the actual travel, allowing users to enjoy their trip with peace of mind.

[0581] The processing flow will be explained below.

[0582] Step 1:

[0583] A user sends a travel request to the LINE Official Account. For example, they send a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[0584] Step 2:

[0585] The server receives the user's message and uses natural language processing (NLP) technology to analyze the message content and extract information such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[0586] Step 3:

[0587] The server then uses the analysis results to search a database of affiliated accommodations and tourist destinations using SQL queries and API requests to extract options that match the user's preferences, budget, popularity, and other criteria.

[0588] Step 4:

[0589] The server lists information on selected accommodations and tourist spots and generates suggestions for the user. Example suggestion: "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium."

[0590] Step 5:

[0591] The server sends a proposal message to the user via LINE, who can then receive and confirm the proposal.

[0592] Step 6:

[0593] The server uses external services such as Google Maps API to calculate the travel routes between the proposed tourist spots. The API request specifies the departure point and destination, and obtains the optimal travel route and travel time between each tourist spot.

[0594] Step 7:

[0595] The server creates an optimal schedule for the user based on the travel route information it has acquired. Schedule example: "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle. Dinner at Kokusai Street."

[0596] Step 8:

[0597] The server generates schedule information and sends it to the user via LINE message. The user can check the schedule and get a detailed understanding of their travel plans.

[0598] Step 9:

[0599] The server retrieves weather information for the destination and planned activities, and creates a packing list based on that information. It uses a weather information API and an activity database.

[0600] Step 10:

[0601] The server generates links to purchase the items you need based on your inventory list, such as "You can buy flip-flops, sunscreen, and beach towels from our online store."

[0602] Step 11:

[0603] The server sends the user a list of items and a link to purchase them via LINE. The user can then check the list and purchase the items they need online.

[0604] Step 12:

[0605] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, periodically querying the traffic information API and congestion status database.

[0606] Step 13:

[0607] Based on the latest information obtained by the server, the server re-proposes the user's travel route and schedule as necessary. Example of re-proposition: "Shuri Castle is crowded, so we suggest visiting it in the afternoon."

[0608] Step 14:

[0609] The server sends a re-proposal message to the user via LINE, and the user receives the new proposal and can adjust their schedule.

[0610] Step 15:

[0611] If a user encounters a problem during their trip, they can send a support request through LINE. Example: "My rental car broke down."

[0612] Step 16:

[0613] The server receives the support request, analyzes the message content, and searches for and arranges for the appropriate affiliated support center or repair service depending on the type of problem.

[0614] Step 17:

[0615] The server will send a LINE message to the user with instructions on how to resolve the issue and contact details. Example: "If your rental car is broken, we will direct you to the nearest repair service."

[0616] In this way, the system of the present invention provides a consistent service from travel planning to support during the trip, allowing users to enjoy their trip with peace of mind.

[0617] Example 1

[0618] 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."

[0619] When planning a trip, users must consider a wide range of factors, including destination, accommodation, tourist spots, transportation, and belongings, which can be time-consuming and stressful. Furthermore, the lack of prompt support to deal with unexpected problems or crowded conditions during the trip makes it difficult for users to enjoy their trip with peace of mind. There is a need for a system that can solve these problems and enable users to plan and execute trips smoothly and stress-free.

[0620] 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.

[0621] In this invention, the server includes means for receiving a travel plan request from a user, means for generating suggestions for accommodations and tourist spots based on the requested information, means for optimizing travel routes between the suggested tourist spots using external services, means for generating a packing list based on weather information and activities at the travel destination and providing links to purchase items, means for obtaining real-time traffic conditions and congestion information at tourist spots and re-suggesting routes and schedules, and means for providing emergency responses to problems that occur during the trip. This allows users to smoothly plan their trip and quickly respond to unexpected situations that arise during the trip.

[0622] Ok, I've created definitions for some important words below.

[0623] "User" means an individual or organization that uses the System to make travel plans.

[0624] A "request" is a message about travel wishes and conditions that a user sends to the system.

[0625] "Accommodation" refers to facilities for staying overnight during a trip, including hotels, inns, and guesthouses.

[0626] "Tourist destinations" refer to tourist attractions and famous places that can be visited at a travel destination.

[0627] An "external service" is a service provided by a third party that the system uses to obtain data in cooperation with, and includes, for example, a map service or a weather information service.

[0628] "Weather information" is information about the weather at the travel destination, including weather forecasts, temperature, and the probability of precipitation.

[0629] "Activities" refers to specific activities or events that can be undertaken during a trip.

[0630] A "packing list" is a list of items you will need for your trip.

[0631] A "purchase link" is a link on the Internet to purchase an item included in the inventory list.

[0632] "Real-time" refers to the immediate availability of information at that time and place.

[0633] "Traffic conditions" refers to information indicating the degree of congestion and passability of roads and public transportation.

[0634] "Congestion information" is information that indicates the degree of congestion at tourist spots, roads, etc.

[0635] "Emergency response" refers to quickly dealing with unexpected problems that arise during travel.

[0636] A "server" is a computer system that controls the entire system, processes data, and provides services.

[0637] The system of the present invention is designed to enable users to smoothly carry out their travel plans and to quickly respond to any problems that may arise during the trip. Each component of the present invention and its function will be described in detail below.

[0638] Accepting travel planning requests

[0639] A user sends a travel request to the dedicated application or LINE official account. For example, a user sends a message saying, "I would like to take a five-day trip to Okinawa for my family of four."

[0640] The server receives this message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination, duration of the trip, and number of participants. Specifically, it uses an NLP library (e.g., spaCy) to perform the analysis.

[0641] Selection of accommodation and sightseeing spots

[0642] The server searches a database of affiliated accommodations and tourist destinations (for example, a PostgreSQL database). Using the keywords extracted earlier, "Okinawa," "5 days," and "family of four," the server searches for accommodations and tourist destinations that meet the criteria. For example, the server might list "Hotel A near Kokusai Street," "Beach Resort Hotel B," "Shuri Castle," and "Okinawa Churaumi Aquarium."

[0643] Based on the selection results, the server generates a list of accommodation and tourist spot suggestions and notifies the user via LINE message.

[0644] Optimizing travel routes

[0645] The server uses the Google Maps API to calculate travel routes between the suggested tourist spots. It sends a request to the Google Maps API to obtain the distances and travel times between the tourist spots. Based on this, it generates an optimal travel schedule. The generated schedule is put together taking into account the travel time to each tourist spot and the means of transportation (public transportation, rental car, etc.). This schedule is sent to the user via LINE message.

[0646] For example, a suggestion might be, "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street."

[0647] Inventory list and purchase suggestions

[0648] The server uses a weather information API (e.g., OpenWeatherMap API) to obtain weather information for the travel destination. A packing list is created based on the obtained weather information and planned activity information. Examples of packing list items include "sunscreen," "light clothing," and "beach sandals." A corresponding purchase link is also generated along with the packing list and provided to the user via LINE message.

[0649] For example, a link might say, "Buy sunscreen, flip flops and beach towels from our online store."

[0650] Checking congestion status and re-proposing

[0651] The server periodically accesses external APIs such as the Google Maps API to obtain real-time traffic conditions and congestion information at tourist spots. Based on the expected congestion and traffic conditions for the day, the server re-suggests optimal routes and schedules for users. For example, it might suggest, "Shuri Castle is crowded, so change your visit to the afternoon."

[0652] Emergency response

[0653] If a user requests an emergency response through the LINE Official Account while traveling, they can send a message saying, for example, "My rental car has broken down."

[0654] The server receives this message and uses NLP technology to analyze the problem. It then arranges for an emergency response from a partner support center or service. This provides the user with the steps to resolve the problem and the contact information for the nearest repair service. For example, it provides the user with information such as, "The nearest repair service is XX company, and their contact number is YYY."

[0655] Examples of concrete examples and prompts

[0656] As an example showing the operation of the specific system, we will show an example of inputting the following prompt sentence into a generative AI model (e.g., ChatGPT).

[0657] Specific examples

[0658] 1. A user sends a message to the LINE Official Account saying, "We are planning a three-day trip to Okinawa. Please recommend accommodations and tourist spots for our family of four."

[0659] 2. The server receives the message and uses NLP technology to extract the information "Okinawa," "3 days," and "family of four."

[0660] 3. The server searches its partner accommodation database to find accommodations that meet the criteria. For example, it finds "Hotel A, Hotel B."

[0661] 4. Next, the main tourist spots in Okinawa are searched for, and "Shuri Castle, Okinawa Churaumi Aquarium, and Kokusai Street" are selected.

[0662] 5. The server generates a list based on the selection results and suggests to the user, "You can stay at Hotel A or Hotel B and visit Shuri Castle, Okinawa Churaumi Aquarium, and Kokusai Street."

[0663] Prompt Sentence Examples

[0664] We are building an AI assistant to help you plan your trip. Plan a trip that meets the following criteria:

[0665] Travel destination: Okinawa

[0666] Duration: 3 days

[0667] Participants: 4 family members

[0668] Please suggest accommodation and sightseeing spots, travel routes, and a recommended packing list.

[0669] This concludes the explanation of the program processing of the system of the present invention in natural language, including specific examples.

[0670] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0671] Step 1:

[0672] A user sends a travel request to the LINE Official Account. For example, they send a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[0673] Input: User request message

[0674] Output: RAW message data

[0675] Step 2:

[0676] The server receives the user's request message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination, trip duration, and number of participants, for example, using an NLP library (spaCy).

[0677] Input: RAW message data

[0678] Output: Extracted keywords (e.g., Okinawa, 5 days, family of 4)

[0679] Step 3:

[0680] The server searches a database of affiliated accommodations and tourist destinations based on the extracted keywords, for example, using a PostgreSQL database.

[0681] Input: Extracted keywords

[0682] Output: List of accommodations and tourist attractions (e.g., Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium)

[0683] Step 4:

[0684] The server will send suggestions to the user via LINE message based on a list of accommodations and tourist spots.

[0685] Input: List of accommodations and tourist attractions

[0686] Output: LINE message (Example: Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium)

[0687] Step 5:

[0688] The server uses the Google Maps API to calculate routes between tourist attractions, including distances and travel times between the attractions.

[0689] Input: List of accommodations and tourist attractions

[0690] Output: Distance and travel time data between tourist spots

[0691] Step 6:

[0692] The server generates an optimal travel schedule based on the travel data it acquires, including the travel time and means of transportation to each tourist spot.

[0693] Input: Distance and travel time data between tourist spots

[0694] Output: Optimal schedule (Example: Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street)

[0695] Step 7:

[0696] The server sends the generated schedule to the user via LINE message.

[0697] Input: Optimal schedule

[0698] Output: LINE message (Example: Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street)

[0699] Step 8:

[0700] The server uses a weather information API (OpenWeatherMap API) to obtain weather information for the travel destination.

[0701] Input: Travel destination information (e.g. Okinawa)

[0702] Output: Weather data

[0703] Step 9:

[0704] The server creates a list of items to bring based on weather and activity information obtained, and also generates corresponding purchase links.

[0705] Input: Weather data, activity information

[0706] Output: Packing list and purchase links (e.g. sunscreen, light clothing, flip-flops)

[0707] Step 10:

[0708] The server sends the user a LINE message with the list of items and a link to purchase them.

[0709] Input: Inventory list and purchase links

[0710] Output: LINE message (e.g., sunscreen, flip-flops, and beach towels are available for purchase at the online store)

[0711] Step 11:

[0712] The server uses external APIs such as Google Maps API to periodically obtain real-time traffic conditions and congestion information at tourist spots.

[0713] Input: Current travel schedule, traffic data

[0714] Output: Updated schedule (if necessary)

[0715] Step 12:

[0716] The server sends the updated schedule to the user via LINE message, which may include, for example, "Shuri Castle is crowded, so we will reschedule our visit to the afternoon."

[0717] Input: Updated Schedule

[0718] Output: LINE message

[0719] Step 13:

[0720] While traveling, a user requests an emergency response through the LINE Official Account. For example, they can send a message saying, "My rental car has broken down."

[0721] Input: Emergency response message

[0722] Output: RAW emergency message data

[0723] Step 14:

[0724] The server receives the emergency message and uses NLP technology to analyze the nature of the problem.

[0725] Input: RAW emergency message data

[0726] Output: Extracted problem keywords (e.g., rental car, breakdown)

[0727] Step 15:

[0728] Based on the analyzed problem, the server will dispatch emergency response to partner support centers or services, for example, dispatching the nearest repair service and obtaining contact information.

[0729] Input: Extracted problem keywords

[0730] Output: Repair service contact information

[0731] Step 16:

[0732] The server will send a LINE message to the user with instructions on how to resolve the problem and the contact information for the nearest repair service.

[0733] Input: Repair service contact information

[0734] Output: LINE message (e.g., the nearest repair service is XX company, contact number is YYY)

[0735] The above are the specific processing steps and contents of the program for this system.

[0736] (Application example 1)

[0737] 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."

[0738] Systems that provide consistent support, from planning a trip to troubleshooting during the trip, require a wide range of information, and are often complex and difficult for users to use. Arranging meals during a trip and responding to sudden changes in circumstances are also difficult challenges. These challenges make it difficult for users to enjoy their trip comfortably.

[0739] 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.

[0740] In this invention, the server includes means for receiving a travel plan request from a user, means for generating suggestions for accommodations and sightseeing spots based on the requested information, means for optimizing travel routes between the suggested sightseeing spots, means for generating a packing list based on weather information and activities at the travel destination and providing links to purchases, means for obtaining real-time traffic conditions and congestion information at sightseeing spots and re-proposing routes and schedules, means for receiving a request for meal delivery at the travel destination and searching for and suggesting affiliated restaurants, means for tracking delivery progress in real time and notifying the user, and means for providing emergency responses to problems during the trip. This makes it possible to efficiently perform everything from travel planning to dealing with problems during the trip, as well as arranging meals and responding to changes in the situation, all in one system.

[0741] A "user" is a person who utilizes the system to submit travel planning requests and receive suggestions and assistance.

[0742] A "travel plan" refers to a series of activities including travel destinations, accommodations, sightseeing spots, travel routes, packing list, meal delivery, and emergency response.

[0743] A "request" is information that a user submits to the system to communicate their travel planning wishes and desires.

[0744] An "accommodation" is a place where a user stays during a trip, such as a hotel or resort.

[0745] A "tourist spot" is a tourist spot in a travel destination that the user intends to visit.

[0746] A "travel route" is a route for efficiently traveling between the proposed tourist destinations.

[0747] "Weather information" is data about the weather at the travel destination, and is used to generate a packing list.

[0748] An "activity" is a planned action or event during a trip.

[0749] A "packing list" is a list of items necessary for a trip, and is generated based on weather information and activities.

[0750] A "purchase link" is a URL for online purchase of recommended items based on the inventory list.

[0751] "Traffic conditions" refers to data on traffic flow between travel destinations and tourist spots.

[0752] "Crowding information" is real-time information about the degree of congestion at tourist spots and travel routes.

[0753] "Meal delivery" is a service that allows users to order meals while traveling and have them delivered to their destination.

[0754] "Eating and drinking establishments" are establishments such as restaurants and cafes that serve meals and offer delivery services.

[0755] "Delivery progress" is information about the stage at which the ordered meal is and when it will arrive to the user.

[0756] "Emergency response" means assistance to provide a quick solution to unexpected problems that arise during travel.

[0757] A "support center" is a base for responding to emergency requests from users.

[0758] A specific embodiment of the travel planning and travel assistance system will be described in detail below.

[0759] Components and Functions

[0760] 1. Receiving a travel planning request from a user

[0761] The system receives a travel planning request from the user, such as a basic request like "Please deliver sushi for two in Okinawa" via a device like a smartphone or smart glasses, and then sends information such as the trip destination, number of people, and desired services to the server.

[0762] 2. Request analysis using natural language processing

[0763] The server then uses natural language processing (NLP) technology to analyze the incoming request and determine the destination, number of people, and desired services, using an NLP engine such as Google Cloud Natural Language API.

[0764] 3. Accommodation and sightseeing suggestions

[0765] Based on the analyzed request information, the server generates appropriate suggestions from a database of affiliated accommodation and tourist destinations. For example, if a user inputs "I'm planning a five-day trip to Okinawa for my family of four," the system will search for hotels and tourist attractions in Okinawa Prefecture and make suggestions based on the user's preferences and budget.

[0766] 4. Generate inventory list and purchase links

[0767] The server generates a list of necessary items to bring based on the weather information and activities of the destination. For example, if you are traveling to Okinawa in the summer, it will list light clothing and beach sandals, and provide a purchasing link. This link is designed so that the user can easily purchase the items on an online shopping site.

[0768] 5. Optimizing travel routes

[0769] The server uses external services such as Google Maps API to optimize travel routes between tourist spots. It generates an optimal travel schedule by taking into account the travel time and transportation means to each tourist spot. For example, it suggests a schedule such as "30 minutes by rental car from Hotel A to Shuri Castle."

[0770] 6. Get real-time traffic and congestion information

[0771] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and re-proposes routes and schedules as necessary. For example, congestion information is used to suggest, "Shuri Castle is crowded, so let's change our visit to the afternoon."

[0772] 7. Arrange for meal delivery

[0773] The server arranges meal delivery to the travel destination based on the user's request. It searches a database of affiliated restaurants to suggest appropriate menus and restaurants to the user. It then arranges delivery based on the user's selection. Delivery progress information is tracked in real time and notified to the user.

[0774] 8. Providing emergency response

[0775] If a problem occurs during a trip, such as a breakdown in a rental car, the user sends an emergency request to the system. The server analyzes the request, coordinates with affiliated support centers and the necessary emergency response, and provides the user with instructions on how to resolve the issue.

[0776] Hardware and software used

[0777] Smartphones / Smart Glasses: Used as an interface for the user.

[0778] Server: Receives, analyzes, proposes, arranges and notifies requests.

[0779] Natural language processing engine: Analyzes user requests using the Google Cloud Natural Language API, etc.

[0780] Database: Stores information about affiliated accommodations, tourist spots, and restaurants (MySQL, etc.).

[0781] External API service: Uses Google Maps API to optimize travel routes and obtain traffic information.

[0782] Delivery management system: Use APIs such as Uber Eats to schedule and track food deliveries.

[0783] Specific examples and input prompts for generative AI models

[0784] Example: "Sushi delivery for two in Okinawa."

[0785] Prompt statement:

[0786] Message: "Sushi delivery for two in Okinawa"

[0787] Destination: Okinawa

[0788] Type of cuisine: Sushi

[0789] Number of people: 2 people

[0790] Analyze the request details.

[0791] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0792] Step 1:

[0793] A user submits a travel planning request.

[0794] The user uses a smartphone or smart glasses to input and send a request message such as "Please deliver sushi for two in Okinawa," which is then sent to the server.

[0795] Input: Request message (e.g. "Please deliver sushi for two in Okinawa")

[0796] Output: The server receives the request message.

[0797] Step 2:

[0798] The server receives the request and performs analysis using natural language processing (NLP).

[0799] The server uses an NLP engine such as Google Cloud Natural Language API to analyze the request message and extract information such as the destination (Okinawa), number of people (2), and desired service (sushi delivery).

[0800] Input: Request message

[0801] Output: Extracted information (destination, number of people, desired services)

[0802] Step 3:

[0803] The server generates suggestions for accommodation and sightseeing spots.

[0804] Based on the user's request, the server searches its database of affiliated accommodation and tourist destinations and generates suggestions suitable for the user. For example, it searches for hotels and tourist attractions in Okinawa Prefecture and makes suggestions based on the user's preferences and budget.

[0805] Input: Request details (destination, number of people, desired service)

[0806] Output: Accommodation and sightseeing suggestions

[0807] Step 4:

[0808] The server generates the inventory list and purchase links.

[0809] The server generates a packing list based on the weather information of the destination and the planned activities. For example, if traveling to Okinawa in the summer, the list may include sunscreen, light clothing, beach sandals, etc. Then, based on the packing list, it generates a purchase link to an online shopping site and provides it to the user.

[0810] Input: Weather information, activity information

[0811] Output: Inventory list and purchase links

[0812] Step 5:

[0813] The server optimizes the travel route.

[0814] The server uses external services such as Google Maps API to calculate travel routes between the proposed tourist spots and generate an optimal travel schedule, taking into account the travel time to each tourist spot and the means of transportation (e.g., public transportation, rental car, etc.).

[0815] Input: tourist destination information, transportation data

[0816] Output: Travel routes and schedules

[0817] Step 6:

[0818] The server retrieves real-time traffic and congestion information and re-suggests routes and schedules.

[0819] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and based on that information, it re-proposes optimal routes and schedules to users. For example, if Shuri Castle is crowded, it will re-propose a visit to the castle in the afternoon.

[0820] Input: Real-time traffic information, congestion information

[0821] Output: Reproposed route and schedule

[0822] Step 7:

[0823] The server proposes and arranges meal delivery at the travel destination.

[0824] Based on the user's request, the server searches a database of affiliated restaurants and suggests appropriate menus and restaurants to the user. It also arranges delivery from the restaurant selected by the user and tracks the delivery progress in real time.

[0825] Input: Request details, partner restaurant data

[0826] Output: Suggested restaurant and ordering information, tracking information

[0827] Step 8:

[0828] The server provides emergency response for travel issues.

[0829] If a user encounters a problem during their trip, they send an emergency request to the server, which analyzes the request, coordinates with affiliated support centers and necessary emergency response, and provides the user with a solution and contact information.

[0830] Input: Urgent Request

[0831] Output: Emergency response arrangements and solution proposals

[0832] 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.

[0833] The system of the present invention is designed to enable users to smoothly execute their travel plans and quickly respond to any problems that may arise during the trip. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions and adjusts the content of the suggestions based on those emotions. Each component of the present invention and its function will be described in detail below.

[0834] 1. Receiving a travel planning request

[0835] A user sends a travel request to the LINE Official Account. For example, the user sends a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[0836] The server receives this message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[0837] 2. Accommodation and sightseeing suggestions

[0838] The server searches a database of affiliated accommodations and tourist destinations, for example, to extract suitable options from hotels and tourist attractions in Okinawa Prefecture, taking into account criteria such as the user's preferences, budget, and popularity.

[0839] Next, the server will suggest information about the selected accommodations and sightseeing spots to the user. For example, suggestions such as "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium" will be sent via LINE message.

[0840] The server uses an emotion engine to recognize the user's feelings toward these suggestions. For example, if a user sends a message saying "Hotel A is too expensive," the emotion engine recognizes that the user has a negative feeling toward the suggestion.

[0841] 3. Optimizing travel routes

[0842] The server uses external services such as Google Maps API to calculate travel routes between the proposed tourist spots, generating an optimal travel schedule for the user, taking into account the travel time and transportation method (public transportation, rental car, etc.) to each tourist spot.

[0843] For example, schedule information such as "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street" is sent to the user via LINE message. If the user expresses dissatisfaction by saying "the travel time is too long," the emotion engine will pick up on the user's emotions, and the server will recalculate the travel route based on this.

[0844] 4. Inventory list and purchase suggestions

[0845] The server creates a packing list based on the weather and planned activities of the destination. For example, if traveling to Okinawa in the summer, the list might include sunscreen, light clothing, and flip-flops.

[0846] The server provides a purchasing link based on the list of belongings, for example, "Flip-flops, sunscreen, and beach towels are available for purchase at the online shop," and sends the link to the user via LINE message.

[0847] 5. Route re-proposal based on congestion

[0848] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and then re-proposes optimal routes and schedules to users based on the day's congestion forecast and traffic conditions.

[0849] For example, if Shuri Castle is crowded, the server sends the user a message such as "Shuri Castle is crowded, so we suggest you reschedule your visit to the afternoon."

[0850] 6. Emergency Response

[0851] If a user encounters a problem during their trip, they can send a support request through the LINE official account. For example, if their rental car breaks down, they can send a message saying, "My rental car has broken down."

[0852] The server analyzes this message and arranges for an emergency response from an affiliated support center or service, then sends the user a LINE message with instructions on how to resolve the problem and the contact details of the nearest repair service.

[0853] 7. Use of Emotion Engines

[0854] The server uses an emotion engine to recognize emotions from the user's message. For example, if the user feels that they "don't like" the proposed accommodation, the emotion engine captures that negative emotion.

[0855] The server adjusts its suggestions based on the captured emotions. If the user expresses positive emotions, it stores the emotion information to use it in future suggestions. This ensures that the next time the user submits a request, suggestions will take into account their previous emotional history.

[0856] By combining this emotion engine, the system can make suggestions that are in line with the user's emotions and provide a comprehensive service, from travel planning to support during the trip.

[0857] The processing flow will be explained below.

[0858] Step 1:

[0859] A user sends a travel request through the LINE official account. For example, they send a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[0860] Step 2:

[0861] The server analyzes the received message and uses natural language processing (NLP) technology to extract information from the request, such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[0862] Step 3:

[0863] The server searches a database of affiliated accommodations and tourist destinations, extracting appropriate options based on the user's preferences, budget, popularity, and other criteria.

[0864] Step 4:

[0865] The server selects and suggests information about accommodation and sightseeing spots to the user. Example of suggestion: Send information such as "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium" via LINE message.

[0866] Step 5:

[0867] The user reviews the suggestions and provides feedback, for example, a message saying "Hotel A is too expensive."

[0868] Step 6:

[0869] The emotion engine analyzes the user feedback and recognizes emotions. In this case, the emotion engine catches negative emotions (felt too high).

[0870] Step 7:

[0871] The server then adjusts the recommendation based on the emotion engine's analysis, for example by finding another hotel within the customer's budget and suggesting, "How about Hotel B?"

[0872] Step 8:

[0873] The server calculates the travel routes between the proposed tourist spots using the Google Maps API, etc., and obtains the optimal travel route and travel time between each tourist spot.

[0874] Step 9:

[0875] The server creates an optimal schedule for the user based on the route information it obtains. Schedule example: "Day 1: 30 minutes by rental car from Hotel B to Shuri Castle, dinner at Kokusai Street" is sent via LINE message.

[0876] Step 10:

[0877] Users can review the schedule and provide feedback, such as "travel time is too long."

[0878] Step 11:

[0879] The emotion engine again analyzes the user feedback and recognizes emotions, in this case catching the negative emotion (travel time is too long).

[0880] Step 12:

[0881] The server again adjusts the suggestion, for example, calculating a new route to shorten the travel time, such as "leave in the afternoon instead."

[0882] Step 13:

[0883] The server creates a packing list based on weather information and planned activities. For example, the list might include "sunscreen, light clothing, and flip-flops."

[0884] Step 14:

[0885] The server provides a link to purchase items based on the list. For example, it sends a LINE message containing information such as "Flip-flops, sunscreen, and beach towels can be purchased from the online shop."

[0886] Step 15:

[0887] The server periodically retrieves real-time traffic information and congestion information for tourist spots, e.g., makes an API request every 15 minutes.

[0888] Step 16:

[0889] The server will re-suggest routes and schedules for the user based on the latest information as needed. For example, a LINE message will be sent saying, "Shuri Castle is crowded, so we suggest visiting in the afternoon."

[0890] Step 17:

[0891] If a user encounters a problem during their trip, they can send a support request through LINE, for example, by sending a message saying, "My rental car has broken down."

[0892] Step 18:

[0893] The server analyzes the support request and dispatches affiliated support centers or emergency response services depending on the type of problem.

[0894] Step 19:

[0895] The server will send a LINE message to the user with instructions on how to resolve the issue and the contact information for the nearest repair service. For example, it might say, "The nearest repair service is here."

[0896] By combining this emotion engine, the system can make suggestions that are in line with the user's emotions and provide a comprehensive service, from travel planning to support during the trip.

[0897] Example 2

[0898] 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."

[0899] Conventional travel planning support systems make suggestions based on the user's preferences, but they have the problem of being unable to respond flexibly to the user's emotions and real-time circumstances. Furthermore, they lack functionality that consistently supports the entire travel plan, such as packing lists, route optimization, and emergency response.

[0900] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving a travel plan request from a user, means for analyzing the requested information and extracting the destination, travel period, and participating members, means for generating suggestions of accommodation and sightseeing spots based on the extracted information, means for analyzing the user's feelings about the proposed accommodation and sightseeing spots, means for adjusting the suggestions based on the user's feelings, means for optimizing travel routes between the proposed sightseeing spots, means for generating a packing list based on weather information and activities at the travel destination and providing a purchasing link, means for obtaining real-time traffic conditions and congestion information at sightseeing spots and re-proposing routes and schedules, and means for providing emergency response for problems encountered during the trip. This allows users to receive comprehensive services from travel planning to support during the trip.

[0901] "User" refers to an individual or organization that uses the System to plan and execute travel plans.

[0902] "Travel plan request" refers to the act of a user sending information about a travel plan, such as destination, travel period, and participating members, to the server.

[0903] "Means" refers to a method, apparatus, or component in a system for achieving a particular purpose.

[0904] "Requested Information" means the data provided by a User to a Server in a Travel Planning Request.

[0905] "Analyzing information" refers to the process of analyzing received data and understanding or classifying its content.

[0906] "Destination" refers to the final destination or place of stay of a trip.

[0907] "Travel Period" refers to the time span from the start to the end of a trip.

[0908] "Participating Member" means an individual person participating in a trip.

[0909] "Accommodation" refers to the place where you stay during your trip.

[0910] "Tourist destinations" refer to tourist attractions and places of interest that are planned to be visited during a trip.

[0911] "Emotion analysis" refers to the process of reading a user's emotional state from their messages and feedback.

[0912] "Adjusting suggestions based on emotions" refers to the act of changing or optimizing the system's suggestions by taking into account the user's emotional information.

[0913] "Route optimization" refers to the process of adjusting travel routes during a planned trip to make them more efficient and effective.

[0914] "Weather Information" refers to data regarding weather conditions at a travel destination.

[0915] "Activities" refers to events or activities planned to take place during a trip.

[0916] A "packing list" is a list of items that should be brought on a trip.

[0917] "Purchase Link" means an online link to purchase an item included in the inventory list.

[0918] "Real-time traffic conditions" refers to information about current traffic conditions and status.

[0919] "Crowding information for tourist spots" refers to information on the current level of congestion at tourist spots and famous places.

[0920] "Route and schedule re-proposal" refers to the act of reevaluating travel plans based on real-time information and providing optimal travel routes and time allocations.

[0921] "Emergency response" refers to dealing with and providing support in the event of an unexpected problem occurring during travel.

[0922] The system of the present invention provides users with a consistent service from planning a trip to support during the trip. Each component of the present invention and its function will be described in detail below.

[0923] 1. Receiving and analyzing travel planning requests

[0924] A user sends a travel request to a LINE official account. For example, a message such as "I'm looking for a five-day trip to Okinawa for a family of four" is sent. The server receives this message and uses natural language processing (NLP) technology to extract key information from the request (destination, trip duration, and participating members). A common natural language processing API (such as Google Cloud Natural Language API) is used as the NLP engine.

[0925] 2. Accommodation and sightseeing suggestions

[0926] The server searches a database of affiliated accommodations and tourist destinations. For example, it executes SQL queries using a database management system (e.g., MySQL) to select accommodations and tourist destinations that fit the user's preferences and budget. The server then suggests information about the selected accommodations and tourist destinations to the user. Examples of suggestions could include "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, and Okinawa Churaumi Aquarium."

[0927] 3. Analyzing user sentiment and adjusting suggestions

[0928] When a user sends a LINE message with their opinion or thoughts about a suggestion, the server uses an emotion engine to analyze the user's emotions. The emotion engine uses a machine learning model (e.g., BERT), for example. Based on the results of this emotion analysis, the server adjusts the suggestion. For example, if a user sends negative feedback such as "Hotel A is too expensive," the server will reconsider the accommodation options and make a new suggestion.

[0929] 4. Optimizing travel routes

[0930] The server uses the Google Maps API to calculate travel routes between the suggested tourist spots. It generates the optimal travel schedule for the user, taking into account public transportation, rental cars, and other means of transportation. For example, it sends the user a LINE message with schedule information such as "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street."

[0931] 5. Create a packing list and get purchase suggestions

[0932] The server creates a packing list based on the weather information for the destination and the planned activities. It uses a weather API (e.g., OpenWeatherMap API) to obtain weather information. It also provides links to purchase specific products based on the packing list. For example, it sends a LINE message to the user with links to purchase beach sandals and sunscreen.

[0933] 6. Re-suggestions based on real-time information

[0934] The server periodically obtains real-time traffic conditions and congestion information at tourist spots, and based on this information, re-proposes optimal routes and schedules. It obtains information using traffic APIs (e.g., Google Maps Traffic) and congestion information services (e.g., Tourist Information API) and makes appropriate suggestions to the user. For example, it sends a message such as, "Shuri Castle is crowded, so we suggest you change your visit to the afternoon."

[0935] 7. Emergency Response

[0936] If a user encounters a problem during their trip, they can send a support request through their official LINE account. For example, if they send a message like "My rental car has broken down," the server will analyze the message and arrange for an emergency response from an affiliated support center. The server will then send a LINE message to the user with instructions on how to resolve the problem and the contact details of the nearest repair service.

[0937] Specific examples

[0938] Below is a concrete example of how the system works.

[0939] Start planning your trip

[0940] 1. A user sends a message to the LINE official account saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[0941] 2. The server receives the message and extracts the information using NLP techniques.

[0942] Destination: Okinawa

[0943] Trip duration: 5 days

[0944] Participants: Family of 4

[0945] Accommodation suggestions

[0946] 1. The server searches the accommodation database and selects hotels that meet the user's criteria.

[0947] 2. Send a LINE message with suggestions such as "Hotel A near Kokusai Street, Beach Resort Hotel B."

[0948] Use of emotion engine

[0949] 1. The user replies, "Hotel A is too expensive."

[0950] 2. The emotion engine captures the user's negative emotions, and the server uses this to re-suggest other hotels.

[0951] Optimizing travel routes

[0952] 1. The server calculates the route using the Google Maps API and sends the schedule to the user.

[0953] "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle"

[0954] Creating a packing list

[0955] 1. The server creates an inventory list based on weather information and activity.

[0956] "Flip flops, sunscreen, beach towels."

[0957] Re-proposal depending on congestion situation

[0958] 1. On the day, the server obtains real-time congestion information.

[0959] 2. Send a message saying, "Shuri Castle is crowded, so we suggest changing your visit to the afternoon."

[0960] Emergency response

[0961] 1. A user reports a malfunction in their rental car.

[0962] 2. The server will arrange for an emergency response from the partner service and provide contact information for the repair service.

[0963] Example prompts

[0964] "We are a family of four looking for a five-day trip. Destination: Okinawa. Please give us some suggestions for accommodation and sightseeing spots."

[0965] "I'd like to stay at Hotel A near Kokusai Street, but it's over my budget. Can you suggest another hotel?"

[0966] "What transportation options and routes are available during my trip?"

[0967] "Make a packing list and provide links to purchase the items you need."

[0968] This will clarify how users will utilize the system and what benefits they will gain.

[0969] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0970] Step 1:

[0971] A user sends a travel planning request to the LINE Official Account. For example, the user sends a message saying, "I'm looking for a five-day trip to Okinawa for a family of four." This message is the input data.

[0972] The server receives this message and analyzes the request using natural language processing (NLP) technology. Specifically, it uses an NLP engine (e.g., Google Cloud Natural Language API) to extract key information from the text, such as the destination, trip duration, and participating members. The extracted destination, trip duration, and participating members are the output data.

[0973] Step 2:

[0974] The server uses the extracted information to search a database of affiliated accommodations and tourist destinations, for example, by executing an SQL query using a database management system (e.g., MySQL). This SQL query is the input data.

[0975] The server selects appropriate accommodation and tourist destinations based on the user's desired conditions and budget. Information on the selected accommodation and tourist destinations is the output data. The server then sends this information to the user via LINE message. Examples of suggestions include "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle."

[0976] Step 3:

[0977] The user sends a LINE message with their opinion or feedback on the proposal. For example, they might send a message saying, "Hotel A is too expensive." This message is the input data.

[0978] The server uses an emotion engine to analyze the message and determine the user's emotion. The emotion engine uses a common machine learning model (e.g., BERT). The emotion analysis result is the output data. Based on the analysis result, the server adjusts the suggestions. For example, if the user expresses negative emotions, it will re-suggest other accommodations.

[0979] Step 4:

[0980] The server then optimizes the travel route between the proposed tourist spots. Specifically, it calculates the travel route using the Google Maps API. To calculate the route, the location information of the tourist spots and the means of transportation (public transportation, rental car, etc.) are input data.

[0981] The server generates an optimal travel schedule based on this input data. The generated schedule is the output data. For example, it generates schedule information such as "Day 1: From Hotel A to Shuri Castle, 30 minutes by rental car, dinner at Kokusai Street," and sends it to the user via LINE message.

[0982] Step 5:

[0983] The server creates a packing list based on the weather information of the destination and the planned activities. Specifically, weather information retrieval API (e.g., OpenWeatherMap API) and activity information are input data.

[0984] The server combines these input data and generates a list of necessary items. The generated list is the output data. It also provides links to purchase specific products based on the list. The provided purchase links are the output data. For example, a "purchase link for beach sandals and sunscreen" is sent to the user via LINE message.

[0985] Step 6:

[0986] The server periodically obtains real-time traffic conditions and congestion information at tourist spots. This information is input from traffic APIs (e.g., Google Maps Traffic API) and congestion information providers (e.g., Tourist Information API).

[0987] Based on the acquired information, the server re-proposes the optimal route and schedule for the day's conditions. The re-proposed route and schedule are the output data. For example, a message such as "Shuri Castle is crowded, so we suggest changing your visit to the afternoon" is sent to the user.

[0988] Step 7:

[0989] If a user encounters a problem during their trip, they can send a support request through their LINE official account. For example, they can send a message such as "My rental car has broken down." This message is the input data.

[0990] The server analyzes this message and arranges for an emergency response from an affiliated support center. The server then provides the user with instructions on how to resolve the problem and the contact information for the nearest repair service. The instructions and contact information are output data.

[0991] (Application example 2)

[0992] 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."

[0993] Current planning support systems and recommendation systems lack the ability to adjust proposal content taking into account the user's emotions, making it difficult to increase user satisfaction. This can result in inappropriate proposals received by users, leading to dissatisfaction with the plans and recommendations. Furthermore, the lack of a function for re-proposals based on real-time conditions can lead to a lack of flexibility in planning.

[0994] The specific processing by the specific 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 a plan request from a user; means for generating suggestions for places to stay and places to visit based on the requested information; means for optimizing travel routes between the suggested places to visit; means for generating a packing list based on destination condition information and activities and providing purchasing links; means for acquiring real-time situation information and congestion information for places to visit and re-proposing routes and schedules; means for providing emergency responses to problems during planning; means for receiving a text message input by the user and detecting emotions from the text; and means for adjusting the content of the next suggestion to be provided based on the detected emotions. This enables suggestions that take the user's emotions into consideration, improves user satisfaction, and enables flexible responses in real time.

[0995] "User" refers to the people who use a system or application.

[0996] A "planning request" is a request for information submitted by a user based on a specific purpose or preference.

[0997] "Place of stay" refers to a place or facility where a user temporarily stays.

[0998] "Places to visit" refers to places or tourist attractions that users wish to visit.

[0999] A "travel route" refers to the route or means of travel from one point to another.

[1000] "Condition information" refers to information about the environment or situation associated with a particular place or time.

[1001] "Activities" refers to the activities or events that you plan to take place at your planned visit or stay.

[1002] A "packing list" is a list of items needed for a particular project or situation.

[1003] "Purchase Link" refers to a website URL or link to purchase an item included in your inventory.

[1004] "Situation information" refers to information such as traffic conditions and congestion at places visited or stayed that is obtained in real time.

[1005] A "schedule" refers to the allocation or planning of time for carrying out a particular activity.

[1006] "Emergency response" refers to the means and methods for quickly dealing with problems or troubles that arise during planning.

[1007] "Input text message" refers to textual information that a user sends to a system or application.

[1008] "Emotion" refers to the user's psychological state or mood detected from the input text message.

[1009] "Suggestions" refers to specific recommendations and advice provided by the system based on the user's plans and preferences.

[1010] MODE FOR CARRYING OUT THE INVENTION

[1011] The present invention is a system designed to enable users to smoothly execute various plans and quickly respond to any problems that arise during the process. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the content of suggestions based on those emotions. Below, we will explain how this system is configured and how it is operated.

[1012] System Configuration

[1013] This system consists of a server and the devices used by users (smartphones, PCs, etc.). The main hardware and software includes the following:

[1014] Server: High-performance data processing server (e.g., AWS or Google Cloud Platform)

[1015] Terminal: User device such as a smartphone or computer

[1016] Sentiment Engine: A library that performs sentiment analysis on text messages (e.g., TextBlob)

[1017] API: Integration with external services (e.g., Google Maps API, OpenWeather API)

[1018] Database: Data store for managing accommodations, places to visit, and belongings lists

[1019] Program processing

[1020] 1. Receiving a planning request

[1021] When a user sends a request from their device, the server receives the request, analyzes the content, and uses natural language processing technology to extract information such as the destination, itinerary, and participants from the request.

[1022] 2. Proposal Generation

[1023] The server generates suggestions based on the user's request. When suggesting places to stay or visit, it compares the user's preferences, budget, and reputation with a pre-prepared database to select appropriate locations.

[1024] 3. Optimizing travel routes

[1025] To optimize travel routes between the proposed destinations, we use external services such as Google Maps API to calculate transportation modes and travel times, and generate an optimal schedule for the user.

[1026] 4. Generate a list of items

[1027] The server generates a packing list based on destination conditions and activities, using data from a weather API and planned activities, and provides relevant shopping links for online shopping.

[1028] 5. Obtaining context information and re-proposing

[1029] It obtains real-time situational information (e.g., traffic conditions, congestion information) and re-proposes routes and schedules if the user's plans are affected, allowing users to respond flexibly to changing conditions.

[1030] 6. Emergency Response

[1031] If a problem occurs during the planning process, the user can request an emergency response from the server via their terminal. The server receives this request and promptly makes arrangements with affiliated support centers and services.

[1032] 7. Emotion detection and suggestion adjustment

[1033] The system receives a text message from the user and detects the emotion using the TextBlob library. Based on the emotion detected, the system adjusts the next suggestions provided. For example, if the user types "This documentary really moved me," the system detects a positive emotion and recommends content that will move them next.

[1034] Examples and prompts

[1035] Specific examples

[1036] 1. Receiving a planning request: A user sends a message saying, "I want to take my family on a 5-day trip to Kyoto."

[1037] 2. Proposal generation: The server proposes "Hotel A in Arashiyama" and "Hotel B in Gion," as well as "Kinkaku-ji Temple" and "Kiyomizu-dera Temple" as places to visit.

[1038] 3. Route optimization: The server uses the Google Maps API to calculate the optimal route from Kinkaku-ji Temple to Kiyomizu-dera Temple.

[1039] 4. Generate a list of items to bring: The server generates a list of items such as rain gear and comfortable walking shoes based on weather and activity information, and provides a link to purchase them.

[1040] 5. Obtaining situation information and re-suggestion: If Kinkaku-ji Temple is crowded on the day of your visit, the server will suggest "changing your visit to the afternoon."

[1041] 6. Emergency response: If the rental car breaks down during the plan, the server will arrange to contact the nearest repair service.

[1042] 7. Emotion detection and suggestion tailoring: If a user types, "This documentary really moved me," next time we'll recommend a different documentary or a heartwarming anime that will move them.

[1043] Prompt Sentence Examples

[1044] "User input text: "This documentary was really moving." Sentiment analysis detects a positive sentiment, so we recommend the following positive videos. Recommended video list: 1. Heartwarming anime 2. Funny comedy"

[1045] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1046] Step 1:

[1047] A user sends a planning request using a device such as a smartphone. The input includes information such as the destination, itinerary, and participants. The device then sends this information to the server via LINE messages or a dedicated app.

[1048] Step 2:

[1049] The server analyzes requests received from users using natural language processing (NLP) technology. Specifically, it extracts information such as destination, schedule, and participants. The input is the user message, and the output is the analysis results (destination, schedule, participants, etc.).

[1050] Step 3:

[1051] The server generates suggestions for places to stay and visit based on the analysis results. It accesses a database of accommodations and tourist destinations and extracts the best options based on the user's preferences, budget, and reputation. The input is the analysis results, and the output is suggested places to stay and visit.

[1052] Step 4:

[1053] The server optimizes the proposed travel routes between the destinations. It uses the Google Maps API to calculate the optimal route and transportation. The input is a list of destinations, and the output is the optimal travel route and travel time.

[1054] Step 5:

[1055] The server generates an inventory list based on destination condition information and activities, for example, using data from a weather information API or planned activity information, and provides purchase links for items related to the inventory list. The input is destination condition information and activity information, and the output is the inventory list and purchase links.

[1056] Step 6:

[1057] The server obtains real-time situation information and congestion information for destinations and re-proposes routes and schedules. If necessary, it recalculates based on traffic condition data and congestion information obtained from the API. The input is real-time situation information, and the output is the re-proposed route or schedule.

[1058] Step 7:

[1059] If a user needs emergency response during planning, they send an emergency response request to the server via their terminal. The server receives this request and promptly arranges for it to be sent to a support center or service that it is affiliated with. The input is the emergency response request, and the output is the procedure for resolving the problem and the contact information for the nearest support service.

[1060] Step 8:

[1061] The server receives an input text message from a user and detects the emotion using an emotion engine (e.g., TextBlob library). Specifically, it analyzes the text for positive or negative emotion. The input is the text message, and the output is the detected emotion (e.g., emotion score).

[1062] Step 9:

[1063] The server then adjusts the next suggestions it provides based on the detected emotion. For example, if a positive emotion is detected, it recommends content that is likely to further inspire the user. The input is the detected emotion, and the output is the adjusted suggestions.

[1064] 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.

[1065] 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.

[1066] 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.

[1067] [Third embodiment]

[1068] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1069] 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.

[1070] 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).

[1071] 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.

[1072] 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.

[1073] 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).

[1074] 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.

[1075] 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.

[1076] 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.

[1077] 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.

[1078] 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.

[1079] 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."

[1080] The system of the present invention is designed to enable users to smoothly carry out their travel plans and to quickly respond to any problems that may arise during the trip. Each component of the present invention and its function will be described in detail below.

[1081] 1. Receiving a travel planning request

[1082] A user sends a travel request to the LINE Official Account. For example, the user sends a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[1083] The server receives this message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[1084] 2. Accommodation and sightseeing suggestions

[1085] The server searches a database of affiliated accommodations and tourist destinations, for example, to extract suitable options from hotels and tourist attractions in Okinawa Prefecture, taking into account criteria such as the user's preferences, budget, and popularity.

[1086] The server then sends the user information about the selected accommodation and sightseeing spots via LINE message, such as "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium."

[1087] 3. Optimizing travel routes

[1088] The server uses external services such as Google Maps API to calculate travel routes between the proposed tourist spots, generating an optimal travel schedule for the user, taking into account the travel time and transportation method (public transportation, rental car, etc.) to each tourist spot.

[1089] The server then sends the generated route and schedule information to the user via LINE message. For example, it suggests a schedule such as "Day 1: From Hotel A to Shuri Castle, 30 minutes by rental car, dinner on Kokusai Street."

[1090] 4. Inventory list and purchase suggestions

[1091] The server creates a packing list based on the weather and planned activities of the destination. For example, if traveling to Okinawa in the summer, the list might include sunscreen, light clothing, and flip-flops.

[1092] In addition, the server provides a purchasing link based on the inventory list. For example, it adds information to the inventory list such as "Flip-flops, sunscreen, and beach towels can be purchased at the online shop" and sends it to the user via LINE message.

[1093] 5. Route re-proposal based on congestion

[1094] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and then re-proposes optimal routes and schedules to users based on the day's congestion forecast and traffic conditions.

[1095] For example, if Shuri Castle is crowded, the server sends the user a message such as "Shuri Castle is crowded, so we suggest you reschedule your visit to the afternoon."

[1096] 6. Emergency Response

[1097] While traveling, users can request emergency response through the LINE Official Account. For example, if their rental car breaks down, they can send a message saying, "My rental car has broken down."

[1098] The server analyzes this message and arranges for an emergency response from an affiliated support center or service, then sends the user a LINE message with instructions on how to resolve the problem and the contact details of the nearest repair service.

[1099] In this way, the system of the present invention provides consistent support from travel planning to the actual travel, allowing users to enjoy their trip with peace of mind.

[1100] The processing flow will be explained below.

[1101] Step 1:

[1102] A user sends a travel request to the LINE Official Account. For example, they send a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[1103] Step 2:

[1104] The server receives the user's message and uses natural language processing (NLP) technology to analyze the message content and extract information such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[1105] Step 3:

[1106] The server then uses the analysis results to search a database of affiliated accommodations and tourist destinations using SQL queries and API requests to extract options that match the user's preferences, budget, popularity, and other criteria.

[1107] Step 4:

[1108] The server lists information on selected accommodations and tourist spots and generates suggestions for the user. Example suggestion: "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium."

[1109] Step 5:

[1110] The server sends a proposal message to the user via LINE, who can then receive and confirm the proposal.

[1111] Step 6:

[1112] The server uses external services such as Google Maps API to calculate the travel routes between the proposed tourist spots. The API request specifies the departure point and destination, and obtains the optimal travel route and travel time between each tourist spot.

[1113] Step 7:

[1114] The server creates an optimal schedule for the user based on the travel route information it has acquired. Schedule example: "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle. Dinner at Kokusai Street."

[1115] Step 8:

[1116] The server generates schedule information and sends it to the user via LINE message. The user can check the schedule and get a detailed understanding of their travel plans.

[1117] Step 9:

[1118] The server retrieves weather information for the destination and planned activities, and creates a packing list based on that information. It uses a weather information API and an activity database.

[1119] Step 10:

[1120] The server generates links to purchase the items you need based on your inventory list, such as "You can buy flip-flops, sunscreen, and beach towels from our online store."

[1121] Step 11:

[1122] The server sends the user a list of items and a link to purchase them via LINE. The user can then check the list and purchase the items they need online.

[1123] Step 12:

[1124] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, periodically querying the traffic information API and congestion status database.

[1125] Step 13:

[1126] Based on the latest information obtained by the server, the server re-proposes the user's travel route and schedule as necessary. Example of re-proposition: "Shuri Castle is crowded, so we suggest visiting it in the afternoon."

[1127] Step 14:

[1128] The server sends a re-proposal message to the user via LINE, and the user receives the new proposal and can adjust their schedule.

[1129] Step 15:

[1130] If a user encounters a problem during their trip, they can send a support request through LINE. Example: "My rental car broke down."

[1131] Step 16:

[1132] The server receives the support request, analyzes the message content, and searches for and arranges for the appropriate affiliated support center or repair service depending on the type of problem.

[1133] Step 17:

[1134] The server will send a LINE message to the user with instructions on how to resolve the issue and contact details. Example: "If your rental car is broken, we will direct you to the nearest repair service."

[1135] In this way, the system of the present invention provides a consistent service from travel planning to support during the trip, allowing users to enjoy their trip with peace of mind.

[1136] Example 1

[1137] 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."

[1138] When planning a trip, users must consider a wide range of factors, including destination, accommodation, tourist spots, transportation, and belongings, which can be time-consuming and stressful. Furthermore, the lack of prompt support to deal with unexpected problems or crowded conditions during the trip makes it difficult for users to enjoy their trip with peace of mind. There is a need for a system that can solve these problems and enable users to plan and execute trips smoothly and stress-free.

[1139] 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.

[1140] In this invention, the server includes means for receiving a travel plan request from a user, means for generating suggestions for accommodations and tourist spots based on the requested information, means for optimizing travel routes between the suggested tourist spots using external services, means for generating a packing list based on weather information and activities at the travel destination and providing links to purchase items, means for obtaining real-time traffic conditions and congestion information at tourist spots and re-suggesting routes and schedules, and means for providing emergency responses to problems that occur during the trip. This allows users to smoothly plan their trip and quickly respond to unexpected situations that arise during the trip.

[1141] Ok, I've created definitions for some important words below.

[1142] "User" means an individual or organization that uses the System to make travel plans.

[1143] A "request" is a message about travel wishes and conditions that a user sends to the system.

[1144] "Accommodation" refers to facilities for staying overnight during a trip, including hotels, inns, and guesthouses.

[1145] "Tourist destinations" refer to tourist attractions and famous places that can be visited at a travel destination.

[1146] An "external service" is a service provided by a third party that the system uses to obtain data in cooperation with, and includes, for example, a map service or a weather information service.

[1147] "Weather information" is information about the weather at the travel destination, including weather forecasts, temperature, and the probability of precipitation.

[1148] "Activities" refers to specific activities or events that can be undertaken during a trip.

[1149] A "packing list" is a list of items you will need for your trip.

[1150] A "purchase link" is a link on the Internet to purchase an item included in the inventory list.

[1151] "Real-time" refers to the immediate availability of information at that time and place.

[1152] "Traffic conditions" refers to information indicating the degree of congestion and passability of roads and public transportation.

[1153] "Congestion information" is information that indicates the degree of congestion at tourist spots, roads, etc.

[1154] "Emergency response" refers to quickly dealing with unexpected problems that arise during travel.

[1155] A "server" is a computer system that controls the entire system, processes data, and provides services.

[1156] The system of the present invention is designed to enable users to smoothly carry out their travel plans and to quickly respond to any problems that may arise during the trip. Each component of the present invention and its function will be described in detail below.

[1157] Accepting travel planning requests

[1158] A user sends a travel request to the dedicated application or LINE official account. For example, a user sends a message saying, "I would like to take a five-day trip to Okinawa for my family of four."

[1159] The server receives this message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination, duration of the trip, and number of participants. Specifically, it uses an NLP library (e.g., spaCy) to perform the analysis.

[1160] Selection of accommodation and sightseeing spots

[1161] The server searches a database of affiliated accommodations and tourist destinations (for example, a PostgreSQL database). Using the keywords extracted earlier, "Okinawa," "5 days," and "family of four," the server searches for accommodations and tourist destinations that meet the criteria. For example, the server might list "Hotel A near Kokusai Street," "Beach Resort Hotel B," "Shuri Castle," and "Okinawa Churaumi Aquarium."

[1162] Based on the selection results, the server generates a list of accommodation and tourist spot suggestions and notifies the user via LINE message.

[1163] Optimizing travel routes

[1164] The server uses the Google Maps API to calculate travel routes between the suggested tourist spots. It sends a request to the Google Maps API to obtain the distances and travel times between the tourist spots. Based on this, it generates an optimal travel schedule. The generated schedule is put together taking into account the travel time to each tourist spot and the means of transportation (public transportation, rental car, etc.). This schedule is sent to the user via LINE message.

[1165] For example, a suggestion might be, "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street."

[1166] Inventory list and purchase suggestions

[1167] The server uses a weather information API (e.g., OpenWeatherMap API) to obtain weather information for the travel destination. A packing list is created based on the obtained weather information and planned activity information. Examples of packing list items include "sunscreen," "light clothing," and "beach sandals." A corresponding purchase link is also generated along with the packing list and provided to the user via LINE message.

[1168] For example, a link might say, "Buy sunscreen, flip flops and beach towels from our online store."

[1169] Checking congestion status and re-proposing

[1170] The server periodically accesses external APIs such as the Google Maps API to obtain real-time traffic conditions and congestion information at tourist spots. Based on the expected congestion and traffic conditions for the day, the server re-suggests optimal routes and schedules for users. For example, it might suggest, "Shuri Castle is crowded, so change your visit to the afternoon."

[1171] Emergency response

[1172] If a user requests an emergency response through the LINE Official Account while traveling, they can send a message saying, for example, "My rental car has broken down."

[1173] The server receives this message and uses NLP technology to analyze the problem. It then arranges for an emergency response from a partner support center or service. This provides the user with the steps to resolve the problem and the contact information for the nearest repair service. For example, it provides the user with information such as, "The nearest repair service is XX company, and their contact number is YYY."

[1174] Examples of concrete examples and prompts

[1175] As an example showing the operation of the specific system, we will show an example of inputting the following prompt sentence into a generative AI model (e.g., ChatGPT).

[1176] Specific examples

[1177] 1. A user sends a message to the LINE Official Account saying, "We are planning a three-day trip to Okinawa. Please recommend accommodations and tourist spots for our family of four."

[1178] 2. The server receives the message and uses NLP technology to extract the information "Okinawa," "3 days," and "family of four."

[1179] 3. The server searches its partner accommodation database to find accommodations that meet the criteria. For example, it finds "Hotel A, Hotel B."

[1180] 4. Next, the main tourist spots in Okinawa are searched for, and "Shuri Castle, Okinawa Churaumi Aquarium, and Kokusai Street" are selected.

[1181] 5. The server generates a list based on the selection results and suggests to the user, "You can stay at Hotel A or Hotel B and visit Shuri Castle, Okinawa Churaumi Aquarium, and Kokusai Street."

[1182] Prompt Sentence Examples

[1183] We are building an AI assistant to help you plan your trip. Plan a trip that meets the following criteria:

[1184] Travel destination: Okinawa

[1185] Duration: 3 days

[1186] Participants: 4 family members

[1187] Please suggest accommodation and sightseeing spots, travel routes, and a recommended packing list.

[1188] This concludes the explanation of the program processing of the system of the present invention in natural language, including specific examples.

[1189] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1190] Step 1:

[1191] A user sends a travel request to the LINE Official Account. For example, they send a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[1192] Input: User request message

[1193] Output: RAW message data

[1194] Step 2:

[1195] The server receives the user's request message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination, trip duration, and number of participants, for example, using an NLP library (spaCy).

[1196] Input: RAW message data

[1197] Output: Extracted keywords (e.g., Okinawa, 5 days, family of 4)

[1198] Step 3:

[1199] The server searches a database of affiliated accommodations and tourist destinations based on the extracted keywords, for example, using a PostgreSQL database.

[1200] Input: Extracted keywords

[1201] Output: List of accommodations and tourist attractions (e.g., Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium)

[1202] Step 4:

[1203] The server will send suggestions to the user via LINE message based on a list of accommodations and tourist spots.

[1204] Input: List of accommodations and tourist attractions

[1205] Output: LINE message (Example: Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium)

[1206] Step 5:

[1207] The server uses the Google Maps API to calculate routes between tourist attractions, including distances and travel times between the attractions.

[1208] Input: List of accommodations and tourist attractions

[1209] Output: Distance and travel time data between tourist spots

[1210] Step 6:

[1211] The server generates an optimal travel schedule based on the travel data it acquires, including the travel time and means of transportation to each tourist spot.

[1212] Input: Distance and travel time data between tourist spots

[1213] Output: Optimal schedule (Example: Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street)

[1214] Step 7:

[1215] The server sends the generated schedule to the user via LINE message.

[1216] Input: Optimal schedule

[1217] Output: LINE message (Example: Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street)

[1218] Step 8:

[1219] The server uses a weather information API (OpenWeatherMap API) to obtain weather information for the travel destination.

[1220] Input: Travel destination information (e.g. Okinawa)

[1221] Output: Weather data

[1222] Step 9:

[1223] The server creates a list of items to bring based on weather and activity information obtained, and also generates corresponding purchase links.

[1224] Input: Weather data, activity information

[1225] Output: Packing list and purchase links (e.g. sunscreen, light clothing, flip-flops)

[1226] Step 10:

[1227] The server sends the user a LINE message with the list of items and a link to purchase them.

[1228] Input: Inventory list and purchase links

[1229] Output: LINE message (e.g., sunscreen, flip-flops, and beach towels are available for purchase at the online store)

[1230] Step 11:

[1231] The server uses external APIs such as Google Maps API to periodically obtain real-time traffic conditions and congestion information at tourist spots.

[1232] Input: Current travel schedule, traffic data

[1233] Output: Updated schedule (if necessary)

[1234] Step 12:

[1235] The server sends the updated schedule to the user via LINE message, which may include, for example, "Shuri Castle is crowded, so we will reschedule our visit to the afternoon."

[1236] Input: Updated Schedule

[1237] Output: LINE message

[1238] Step 13:

[1239] While traveling, a user requests an emergency response through the LINE Official Account. For example, they can send a message saying, "My rental car has broken down."

[1240] Input: Emergency response message

[1241] Output: RAW emergency message data

[1242] Step 14:

[1243] The server receives the emergency message and uses NLP technology to analyze the nature of the problem.

[1244] Input: RAW emergency message data

[1245] Output: Extracted problem keywords (e.g., rental car, breakdown)

[1246] Step 15:

[1247] Based on the analyzed problem, the server will dispatch emergency response to partner support centers or services, for example, dispatching the nearest repair service and obtaining contact information.

[1248] Input: Extracted problem keywords

[1249] Output: Repair service contact information

[1250] Step 16:

[1251] The server will send a LINE message to the user with instructions on how to resolve the problem and the contact information for the nearest repair service.

[1252] Input: Repair service contact information

[1253] Output: LINE message (e.g., the nearest repair service is XX company, contact number is YYY)

[1254] The above are the specific processing steps and contents of the program for this system.

[1255] (Application example 1)

[1256] 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."

[1257] Systems that provide consistent support, from planning a trip to troubleshooting during the trip, require a wide range of information, and are often complex and difficult for users to use. Arranging meals during a trip and responding to sudden changes in circumstances are also difficult challenges. These challenges make it difficult for users to enjoy their trip comfortably.

[1258] 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.

[1259] In this invention, the server includes means for receiving a travel plan request from a user, means for generating suggestions for accommodations and sightseeing spots based on the requested information, means for optimizing travel routes between the suggested sightseeing spots, means for generating a packing list based on weather information and activities at the travel destination and providing links to purchases, means for obtaining real-time traffic conditions and congestion information at sightseeing spots and re-proposing routes and schedules, means for receiving a request for meal delivery at the travel destination and searching for and suggesting affiliated restaurants, means for tracking delivery progress in real time and notifying the user, and means for providing emergency responses to problems during the trip. This makes it possible to efficiently perform everything from travel planning to dealing with problems during the trip, as well as arranging meals and responding to changes in the situation, all in one system.

[1260] A "user" is a person who utilizes the system to submit travel planning requests and receive suggestions and assistance.

[1261] A "travel plan" refers to a series of activities including travel destinations, accommodations, sightseeing spots, travel routes, packing list, meal delivery, and emergency response.

[1262] A "request" is information that a user submits to the system to communicate their travel planning wishes and desires.

[1263] An "accommodation" is a place where a user stays during a trip, such as a hotel or resort.

[1264] A "tourist spot" is a tourist spot in a travel destination that the user intends to visit.

[1265] A "travel route" is a route for efficiently traveling between the proposed tourist destinations.

[1266] "Weather information" is data about the weather at the travel destination, and is used to generate a packing list.

[1267] An "activity" is a planned action or event during a trip.

[1268] A "packing list" is a list of items necessary for a trip, and is generated based on weather information and activities.

[1269] A "purchase link" is a URL for online purchase of recommended items based on the inventory list.

[1270] "Traffic conditions" refers to data on traffic flow between travel destinations and tourist spots.

[1271] "Crowding information" is real-time information about the degree of congestion at tourist spots and travel routes.

[1272] "Meal delivery" is a service that allows users to order meals while traveling and have them delivered to their destination.

[1273] "Eating and drinking establishments" are establishments such as restaurants and cafes that serve meals and offer delivery services.

[1274] "Delivery progress" is information about the stage at which the ordered meal is and when it will arrive to the user.

[1275] "Emergency response" means assistance to provide a quick solution to unexpected problems that arise during travel.

[1276] A "support center" is a base for responding to emergency requests from users.

[1277] A specific embodiment of the travel planning and travel assistance system will be described in detail below.

[1278] Components and Functions

[1279] 1. Receiving a travel planning request from a user

[1280] The system receives a travel planning request from the user, such as a basic request like "Please deliver sushi for two in Okinawa" via a device like a smartphone or smart glasses, and then sends information such as the trip destination, number of people, and desired services to the server.

[1281] 2. Request analysis using natural language processing

[1282] The server then uses natural language processing (NLP) technology to analyze the incoming request and determine the destination, number of people, and desired services, using an NLP engine such as Google Cloud Natural Language API.

[1283] 3. Accommodation and sightseeing suggestions

[1284] Based on the analyzed request information, the server generates appropriate suggestions from a database of affiliated accommodation and tourist destinations. For example, if a user inputs "I'm planning a five-day trip to Okinawa for my family of four," the system will search for hotels and tourist attractions in Okinawa Prefecture and make suggestions based on the user's preferences and budget.

[1285] 4. Generate inventory list and purchase links

[1286] The server generates a list of necessary items to bring based on the weather information and activities of the destination. For example, if you are traveling to Okinawa in the summer, it will list light clothing and beach sandals, and provide a purchasing link. This link is designed so that the user can easily purchase the items on an online shopping site.

[1287] 5. Optimizing travel routes

[1288] The server uses external services such as Google Maps API to optimize travel routes between tourist spots. It generates an optimal travel schedule by taking into account the travel time and transportation means to each tourist spot. For example, it suggests a schedule such as "30 minutes by rental car from Hotel A to Shuri Castle."

[1289] 6. Get real-time traffic and congestion information

[1290] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and re-proposes routes and schedules as necessary. For example, congestion information is used to suggest, "Shuri Castle is crowded, so let's change our visit to the afternoon."

[1291] 7. Arrange for meal delivery

[1292] The server arranges meal delivery to the travel destination based on the user's request. It searches a database of affiliated restaurants to suggest appropriate menus and restaurants to the user. It then arranges delivery based on the user's selection. Delivery progress information is tracked in real time and notified to the user.

[1293] 8. Providing emergency response

[1294] If a problem occurs during a trip, such as a breakdown in a rental car, the user sends an emergency request to the system. The server analyzes the request, coordinates with affiliated support centers and the necessary emergency response, and provides the user with instructions on how to resolve the issue.

[1295] Hardware and software used

[1296] Smartphones / Smart Glasses: Used as an interface for the user.

[1297] Server: Receives, analyzes, proposes, arranges and notifies requests.

[1298] Natural language processing engine: Analyzes user requests using the Google Cloud Natural Language API, etc.

[1299] Database: Stores information about affiliated accommodations, tourist spots, and restaurants (MySQL, etc.).

[1300] External API service: Uses Google Maps API to optimize travel routes and obtain traffic information.

[1301] Delivery management system: Use APIs such as Uber Eats to schedule and track food deliveries.

[1302] Specific examples and input prompts for generative AI models

[1303] Example: "Sushi delivery for two in Okinawa."

[1304] Prompt statement:

[1305] Message: "Sushi delivery for two in Okinawa"

[1306] Destination: Okinawa

[1307] Type of cuisine: Sushi

[1308] Number of people: 2 people

[1309] Analyze the request details.

[1310] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1311] Step 1:

[1312] A user submits a travel planning request.

[1313] The user uses a smartphone or smart glasses to input and send a request message such as "Please deliver sushi for two in Okinawa," which is then sent to the server.

[1314] Input: Request message (e.g. "Please deliver sushi for two in Okinawa")

[1315] Output: The server receives the request message.

[1316] Step 2:

[1317] The server receives the request and performs analysis using natural language processing (NLP).

[1318] The server uses an NLP engine such as Google Cloud Natural Language API to analyze the request message and extract information such as the destination (Okinawa), number of people (2), and desired service (sushi delivery).

[1319] Input: Request message

[1320] Output: Extracted information (destination, number of people, desired services)

[1321] Step 3:

[1322] The server generates suggestions for accommodation and sightseeing spots.

[1323] Based on the user's request, the server searches its database of affiliated accommodation and tourist destinations and generates suggestions suitable for the user. For example, it searches for hotels and tourist attractions in Okinawa Prefecture and makes suggestions based on the user's preferences and budget.

[1324] Input: Request details (destination, number of people, desired service)

[1325] Output: Accommodation and sightseeing suggestions

[1326] Step 4:

[1327] The server generates the inventory list and purchase links.

[1328] The server generates a packing list based on the weather information of the destination and the planned activities. For example, if traveling to Okinawa in the summer, the list may include sunscreen, light clothing, beach sandals, etc. Then, based on the packing list, it generates a purchase link to an online shopping site and provides it to the user.

[1329] Input: Weather information, activity information

[1330] Output: Inventory list and purchase links

[1331] Step 5:

[1332] The server optimizes the travel route.

[1333] The server uses external services such as Google Maps API to calculate travel routes between the proposed tourist spots and generate an optimal travel schedule, taking into account the travel time to each tourist spot and the means of transportation (e.g., public transportation, rental car, etc.).

[1334] Input: tourist destination information, transportation data

[1335] Output: Travel routes and schedules

[1336] Step 6:

[1337] The server retrieves real-time traffic and congestion information and re-suggests routes and schedules.

[1338] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and based on that information, it re-proposes optimal routes and schedules to users. For example, if Shuri Castle is crowded, it will re-propose a visit to the castle in the afternoon.

[1339] Input: Real-time traffic information, congestion information

[1340] Output: Reproposed route and schedule

[1341] Step 7:

[1342] The server proposes and arranges meal delivery at the travel destination.

[1343] Based on the user's request, the server searches a database of affiliated restaurants and suggests appropriate menus and restaurants to the user. It also arranges delivery from the restaurant selected by the user and tracks the delivery progress in real time.

[1344] Input: Request details, partner restaurant data

[1345] Output: Suggested restaurant and ordering information, tracking information

[1346] Step 8:

[1347] The server provides emergency response for travel issues.

[1348] If a user encounters a problem during their trip, they send an emergency request to the server, which analyzes the request, coordinates with affiliated support centers and necessary emergency response, and provides the user with a solution and contact information.

[1349] Input: Urgent Request

[1350] Output: Emergency response arrangements and solution proposals

[1351] 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.

[1352] The system of the present invention is designed to enable users to smoothly execute their travel plans and quickly respond to any problems that may arise during the trip. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions and adjusts the content of the suggestions based on those emotions. Each component of the present invention and its function will be described in detail below.

[1353] 1. Receiving a travel planning request

[1354] A user sends a travel request to the LINE Official Account. For example, the user sends a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[1355] The server receives this message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[1356] 2. Accommodation and sightseeing suggestions

[1357] The server searches a database of affiliated accommodations and tourist destinations, for example, to extract suitable options from hotels and tourist attractions in Okinawa Prefecture, taking into account criteria such as the user's preferences, budget, and popularity.

[1358] Next, the server will suggest information about the selected accommodations and sightseeing spots to the user. For example, suggestions such as "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium" will be sent via LINE message.

[1359] The server uses an emotion engine to recognize the user's feelings toward these suggestions. For example, if a user sends a message saying "Hotel A is too expensive," the emotion engine recognizes that the user has a negative feeling toward the suggestion.

[1360] 3. Optimizing travel routes

[1361] The server uses external services such as Google Maps API to calculate travel routes between the proposed tourist spots, generating an optimal travel schedule for the user, taking into account the travel time and transportation method (public transportation, rental car, etc.) to each tourist spot.

[1362] For example, schedule information such as "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street" is sent to the user via LINE message. If the user expresses dissatisfaction by saying "the travel time is too long," the emotion engine will pick up on the user's emotions, and the server will recalculate the travel route based on this.

[1363] 4. Inventory list and purchase suggestions

[1364] The server creates a packing list based on the weather and planned activities of the destination. For example, if traveling to Okinawa in the summer, the list might include sunscreen, light clothing, and flip-flops.

[1365] The server provides a purchasing link based on the list of belongings, for example, "Flip-flops, sunscreen, and beach towels are available for purchase at the online shop," and sends the link to the user via LINE message.

[1366] 5. Route re-proposal based on congestion

[1367] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and then re-proposes optimal routes and schedules to users based on the day's congestion forecast and traffic conditions.

[1368] For example, if Shuri Castle is crowded, the server sends the user a message such as "Shuri Castle is crowded, so we suggest you reschedule your visit to the afternoon."

[1369] 6. Emergency Response

[1370] If a user encounters a problem during their trip, they can send a support request through the LINE official account. For example, if their rental car breaks down, they can send a message saying, "My rental car has broken down."

[1371] The server analyzes this message and arranges for an emergency response from an affiliated support center or service, then sends the user a LINE message with instructions on how to resolve the problem and the contact details of the nearest repair service.

[1372] 7. Use of Emotion Engines

[1373] The server uses an emotion engine to recognize emotions from the user's message. For example, if the user feels that they "don't like" the proposed accommodation, the emotion engine captures that negative emotion.

[1374] The server adjusts its suggestions based on the captured emotions. If the user expresses positive emotions, it stores the emotion information to use it in future suggestions. This ensures that the next time the user submits a request, suggestions will take into account their previous emotional history.

[1375] By combining this emotion engine, the system can make suggestions that are in line with the user's emotions and provide a comprehensive service, from travel planning to support during the trip.

[1376] The processing flow will be explained below.

[1377] Step 1:

[1378] A user sends a travel request through the LINE official account. For example, they send a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[1379] Step 2:

[1380] The server analyzes the received message and uses natural language processing (NLP) technology to extract information from the request, such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[1381] Step 3:

[1382] The server searches a database of affiliated accommodations and tourist destinations, extracting appropriate options based on the user's preferences, budget, popularity, and other criteria.

[1383] Step 4:

[1384] The server selects and suggests information about accommodation and sightseeing spots to the user. Example of suggestion: Send information such as "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium" via LINE message.

[1385] Step 5:

[1386] The user reviews the suggestions and provides feedback, for example, a message saying "Hotel A is too expensive."

[1387] Step 6:

[1388] The emotion engine analyzes the user feedback and recognizes emotions. In this case, the emotion engine catches negative emotions (felt too high).

[1389] Step 7:

[1390] The server then adjusts the recommendation based on the emotion engine's analysis, for example by finding another hotel within the customer's budget and suggesting, "How about Hotel B?"

[1391] Step 8:

[1392] The server calculates the travel routes between the proposed tourist spots using the Google Maps API, etc., and obtains the optimal travel route and travel time between each tourist spot.

[1393] Step 9:

[1394] The server creates an optimal schedule for the user based on the route information it obtains. Schedule example: "Day 1: 30 minutes by rental car from Hotel B to Shuri Castle, dinner at Kokusai Street" is sent via LINE message.

[1395] Step 10:

[1396] Users can review the schedule and provide feedback, such as "travel time is too long."

[1397] Step 11:

[1398] The emotion engine again analyzes the user feedback and recognizes emotions, in this case catching the negative emotion (travel time is too long).

[1399] Step 12:

[1400] The server again adjusts the suggestion, for example, calculating a new route to shorten the travel time, such as "leave in the afternoon instead."

[1401] Step 13:

[1402] The server creates a packing list based on weather information and planned activities. For example, the list might include "sunscreen, light clothing, and flip-flops."

[1403] Step 14:

[1404] The server provides a link to purchase items based on the list. For example, it sends a LINE message containing information such as "Flip-flops, sunscreen, and beach towels can be purchased from the online shop."

[1405] Step 15:

[1406] The server periodically retrieves real-time traffic information and congestion information for tourist spots, e.g., makes an API request every 15 minutes.

[1407] Step 16:

[1408] The server will re-suggest routes and schedules for the user based on the latest information as needed. For example, a LINE message will be sent saying, "Shuri Castle is crowded, so we suggest visiting in the afternoon."

[1409] Step 17:

[1410] If a user encounters a problem during their trip, they can send a support request through LINE, for example, by sending a message saying, "My rental car has broken down."

[1411] Step 18:

[1412] The server analyzes the support request and dispatches affiliated support centers or emergency response services depending on the type of problem.

[1413] Step 19:

[1414] The server will send a LINE message to the user with instructions on how to resolve the issue and the contact information for the nearest repair service. For example, it might say, "The nearest repair service is here."

[1415] By combining this emotion engine, the system can make suggestions that are in line with the user's emotions and provide a comprehensive service, from travel planning to support during the trip.

[1416] Example 2

[1417] 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."

[1418] Conventional travel planning support systems make suggestions based on the user's preferences, but they have the problem of being unable to respond flexibly to the user's emotions and real-time circumstances. Furthermore, they lack functionality that consistently supports the entire travel plan, such as packing lists, route optimization, and emergency response.

[1419] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving a travel plan request from a user, means for analyzing the requested information and extracting the destination, travel period, and participating members, means for generating suggestions of accommodation and sightseeing spots based on the extracted information, means for analyzing the user's feelings about the proposed accommodation and sightseeing spots, means for adjusting the suggestions based on the user's feelings, means for optimizing travel routes between the proposed sightseeing spots, means for generating a packing list based on weather information and activities at the travel destination and providing a purchasing link, means for obtaining real-time traffic conditions and congestion information at sightseeing spots and re-proposing routes and schedules, and means for providing emergency response for problems encountered during the trip. This allows users to receive comprehensive services from travel planning to support during the trip.

[1420] "User" refers to an individual or organization that uses the System to plan and execute travel plans.

[1421] "Travel plan request" refers to the act of a user sending information about a travel plan, such as destination, travel period, and participating members, to the server.

[1422] "Means" refers to a method, apparatus, or component in a system for achieving a particular purpose.

[1423] "Requested Information" means the data provided by a User to a Server in a Travel Planning Request.

[1424] "Analyzing information" refers to the process of analyzing received data and understanding or classifying its content.

[1425] "Destination" refers to the final destination or place of stay of a trip.

[1426] "Travel Period" refers to the time span from the start to the end of a trip.

[1427] "Participating Member" means an individual person participating in a trip.

[1428] "Accommodation" refers to the place where you stay during your trip.

[1429] "Tourist destinations" refer to tourist attractions and places of interest that are planned to be visited during a trip.

[1430] "Emotion analysis" refers to the process of reading a user's emotional state from their messages and feedback.

[1431] "Adjusting suggestions based on emotions" refers to the act of changing or optimizing the system's suggestions by taking into account the user's emotional information.

[1432] "Route optimization" refers to the process of adjusting travel routes during a planned trip to make them more efficient and effective.

[1433] "Weather Information" refers to data regarding weather conditions at a travel destination.

[1434] "Activities" refers to events or activities planned to take place during a trip.

[1435] A "packing list" is a list of items that should be brought on a trip.

[1436] "Purchase Link" means an online link to purchase an item included in the inventory list.

[1437] "Real-time traffic conditions" refers to information about current traffic conditions and status.

[1438] "Crowding information for tourist spots" refers to information on the current level of congestion at tourist spots and famous places.

[1439] "Route and schedule re-proposal" refers to the act of reevaluating travel plans based on real-time information and providing optimal travel routes and time allocations.

[1440] "Emergency response" refers to dealing with and providing support in the event of an unexpected problem occurring during travel.

[1441] The system of the present invention provides users with a consistent service from planning a trip to support during the trip. Each component of the present invention and its function will be described in detail below.

[1442] 1. Receiving and analyzing travel planning requests

[1443] A user sends a travel request to a LINE official account. For example, a message such as "I'm looking for a five-day trip to Okinawa for a family of four" is sent. The server receives this message and uses natural language processing (NLP) technology to extract key information from the request (destination, trip duration, and participating members). A common natural language processing API (such as Google Cloud Natural Language API) is used as the NLP engine.

[1444] 2. Accommodation and sightseeing suggestions

[1445] The server searches a database of affiliated accommodations and tourist destinations. For example, it executes SQL queries using a database management system (e.g., MySQL) to select accommodations and tourist destinations that fit the user's preferences and budget. The server then suggests information about the selected accommodations and tourist destinations to the user. Examples of suggestions could include "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, and Okinawa Churaumi Aquarium."

[1446] 3. Analyzing user sentiment and adjusting suggestions

[1447] When a user sends a LINE message with their opinion or thoughts about a suggestion, the server uses an emotion engine to analyze the user's emotions. The emotion engine uses a machine learning model (e.g., BERT), for example. Based on the results of this emotion analysis, the server adjusts the suggestion. For example, if a user sends negative feedback such as "Hotel A is too expensive," the server will reconsider the accommodation options and make a new suggestion.

[1448] 4. Optimizing travel routes

[1449] The server uses the Google Maps API to calculate travel routes between the suggested tourist spots. It generates the optimal travel schedule for the user, taking into account public transportation, rental cars, and other means of transportation. For example, it sends the user a LINE message with schedule information such as "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street."

[1450] 5. Create a packing list and get purchase suggestions

[1451] The server creates a packing list based on the weather information for the destination and the planned activities. It uses a weather API (e.g., OpenWeatherMap API) to obtain weather information. It also provides links to purchase specific products based on the packing list. For example, it sends a LINE message to the user with links to purchase beach sandals and sunscreen.

[1452] 6. Re-suggestions based on real-time information

[1453] The server periodically obtains real-time traffic conditions and congestion information at tourist spots, and based on this information, re-proposes optimal routes and schedules. It obtains information using traffic APIs (e.g., Google Maps Traffic) and congestion information services (e.g., Tourist Information API) and makes appropriate suggestions to the user. For example, it sends a message such as, "Shuri Castle is crowded, so we suggest you change your visit to the afternoon."

[1454] 7. Emergency Response

[1455] If a user encounters a problem during their trip, they can send a support request through their official LINE account. For example, if they send a message like "My rental car has broken down," the server will analyze the message and arrange for an emergency response from an affiliated support center. The server will then send a LINE message to the user with instructions on how to resolve the problem and the contact details of the nearest repair service.

[1456] Specific examples

[1457] Below is a concrete example of how the system works.

[1458] Start planning your trip

[1459] 1. A user sends a message to the LINE official account saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[1460] 2. The server receives the message and extracts the information using NLP techniques.

[1461] Destination: Okinawa

[1462] Trip duration: 5 days

[1463] Participants: Family of 4

[1464] Accommodation suggestions

[1465] 1. The server searches the accommodation database and selects hotels that meet the user's criteria.

[1466] 2. Send a LINE message with suggestions such as "Hotel A near Kokusai Street, Beach Resort Hotel B."

[1467] Use of emotion engine

[1468] 1. The user replies, "Hotel A is too expensive."

[1469] 2. The emotion engine captures the user's negative emotions, and the server uses this to re-suggest other hotels.

[1470] Optimizing travel routes

[1471] 1. The server calculates the route using the Google Maps API and sends the schedule to the user.

[1472] "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle"

[1473] Creating a packing list

[1474] 1. The server creates an inventory list based on weather information and activity.

[1475] "Flip flops, sunscreen, beach towels."

[1476] Re-proposal depending on congestion situation

[1477] 1. On the day, the server obtains real-time congestion information.

[1478] 2. Send a message saying, "Shuri Castle is crowded, so we suggest changing your visit to the afternoon."

[1479] Emergency response

[1480] 1. A user reports a malfunction in their rental car.

[1481] 2. The server will arrange for an emergency response from the partner service and provide contact information for the repair service.

[1482] Example prompts

[1483] "We are a family of four looking for a five-day trip. Destination: Okinawa. Please give us some suggestions for accommodation and sightseeing spots."

[1484] "I'd like to stay at Hotel A near Kokusai Street, but it's over my budget. Can you suggest another hotel?"

[1485] "What transportation options and routes are available during my trip?"

[1486] "Make a packing list and provide links to purchase the items you need."

[1487] This will clarify how users will utilize the system and what benefits they will gain.

[1488] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1489] Step 1:

[1490] A user sends a travel planning request to the LINE Official Account. For example, the user sends a message saying, "I'm looking for a five-day trip to Okinawa for a family of four." This message is the input data.

[1491] The server receives this message and analyzes the request using natural language processing (NLP) technology. Specifically, it uses an NLP engine (e.g., Google Cloud Natural Language API) to extract key information from the text, such as the destination, trip duration, and participating members. The extracted destination, trip duration, and participating members are the output data.

[1492] Step 2:

[1493] The server uses the extracted information to search a database of affiliated accommodations and tourist destinations, for example, by executing an SQL query using a database management system (e.g., MySQL). This SQL query is the input data.

[1494] The server selects appropriate accommodation and tourist destinations based on the user's desired conditions and budget. Information on the selected accommodation and tourist destinations is the output data. The server then sends this information to the user via LINE message. Examples of suggestions include "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle."

[1495] Step 3:

[1496] The user sends a LINE message with their opinion or feedback on the proposal. For example, they might send a message saying, "Hotel A is too expensive." This message is the input data.

[1497] The server uses an emotion engine to analyze the message and determine the user's emotion. The emotion engine uses a common machine learning model (e.g., BERT). The emotion analysis result is the output data. Based on the analysis result, the server adjusts the suggestions. For example, if the user expresses negative emotions, it will re-suggest other accommodations.

[1498] Step 4:

[1499] The server then optimizes the travel route between the proposed tourist spots. Specifically, it calculates the travel route using the Google Maps API. To calculate the route, the location information of the tourist spots and the means of transportation (public transportation, rental car, etc.) are input data.

[1500] The server generates an optimal travel schedule based on this input data. The generated schedule is the output data. For example, it generates schedule information such as "Day 1: From Hotel A to Shuri Castle, 30 minutes by rental car, dinner at Kokusai Street," and sends it to the user via LINE message.

[1501] Step 5:

[1502] The server creates a packing list based on the weather information of the destination and the planned activities. Specifically, weather information retrieval API (e.g., OpenWeatherMap API) and activity information are input data.

[1503] The server combines these input data and generates a list of necessary items. The generated list is the output data. It also provides links to purchase specific products based on the list. The provided purchase links are the output data. For example, a "purchase link for beach sandals and sunscreen" is sent to the user via LINE message.

[1504] Step 6:

[1505] The server periodically obtains real-time traffic conditions and congestion information at tourist spots. This information is input from traffic APIs (e.g., Google Maps Traffic API) and congestion information providers (e.g., Tourist Information API).

[1506] Based on the acquired information, the server re-proposes the optimal route and schedule for the day's conditions. The re-proposed route and schedule are the output data. For example, a message such as "Shuri Castle is crowded, so we suggest changing your visit to the afternoon" is sent to the user.

[1507] Step 7:

[1508] If a user encounters a problem during their trip, they can send a support request through their LINE official account. For example, they can send a message such as "My rental car has broken down." This message is the input data.

[1509] The server analyzes this message and arranges for an emergency response from an affiliated support center. The server then provides the user with instructions on how to resolve the problem and the contact information for the nearest repair service. The instructions and contact information are output data.

[1510] (Application example 2)

[1511] 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."

[1512] Current planning support systems and recommendation systems lack the ability to adjust proposal content taking into account the user's emotions, making it difficult to increase user satisfaction. This can result in inappropriate proposals received by users, leading to dissatisfaction with the plans and recommendations. Furthermore, the lack of a function for re-proposals based on real-time conditions can lead to a lack of flexibility in planning.

[1513] The specific processing by the specific 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 a plan request from a user; means for generating suggestions for places to stay and places to visit based on the requested information; means for optimizing travel routes between the suggested places to visit; means for generating a packing list based on destination condition information and activities and providing purchasing links; means for acquiring real-time situation information and congestion information for places to visit and re-proposing routes and schedules; means for providing emergency responses to problems during planning; means for receiving a text message input by the user and detecting emotions from the text; and means for adjusting the content of the next suggestion to be provided based on the detected emotions. This enables suggestions that take the user's emotions into consideration, improves user satisfaction, and enables flexible responses in real time.

[1514] "User" refers to the people who use a system or application.

[1515] A "planning request" is a request for information submitted by a user based on a specific purpose or preference.

[1516] "Place of stay" refers to a place or facility where a user temporarily stays.

[1517] "Places to visit" refers to places or tourist attractions that users wish to visit.

[1518] A "travel route" refers to the route or means of travel from one point to another.

[1519] "Condition information" refers to information about the environment or situation associated with a particular place or time.

[1520] "Activities" refers to the activities or events that you plan to take place at your planned visit or stay.

[1521] A "packing list" is a list of items needed for a particular project or situation.

[1522] "Purchase Link" refers to a website URL or link to purchase an item included in your inventory.

[1523] "Situation information" refers to information such as traffic conditions and congestion at places visited or stayed that is obtained in real time.

[1524] A "schedule" refers to the allocation or planning of time for carrying out a particular activity.

[1525] "Emergency response" refers to the means and methods for quickly dealing with problems or troubles that arise during planning.

[1526] "Input text message" refers to textual information that a user sends to a system or application.

[1527] "Emotion" refers to the user's psychological state or mood detected from the input text message.

[1528] "Suggestions" refers to specific recommendations and advice provided by the system based on the user's plans and preferences.

[1529] MODE FOR CARRYING OUT THE INVENTION

[1530] The present invention is a system designed to enable users to smoothly execute various plans and quickly respond to any problems that arise during the process. It also incorporates an emotion engine that recognizes the user's emotions and adjusts the content of suggestions based on those emotions. Below, we will explain how this system is configured and how it is operated.

[1531] System Configuration

[1532] This system consists of a server and the devices used by users (smartphones, PCs, etc.). The main hardware and software includes the following:

[1533] Server: High-performance data processing server (e.g., AWS or Google Cloud Platform)

[1534] Terminal: User device such as a smartphone or computer

[1535] Sentiment Engine: A library that performs sentiment analysis on text messages (e.g., TextBlob)

[1536] API: Integration with external services (e.g., Google Maps API, OpenWeather API)

[1537] Database: Data store for managing accommodations, places to visit, and belongings lists

[1538] Program processing

[1539] 1. Receiving a planning request

[1540] When a user sends a request from their device, the server receives the request, analyzes the content, and uses natural language processing technology to extract information such as the destination, itinerary, and participants from the request.

[1541] 2. Proposal Generation

[1542] The server generates suggestions based on the user's request. When suggesting places to stay or visit, it compares the user's preferences, budget, and reputation with a pre-prepared database to select appropriate locations.

[1543] 3. Optimizing travel routes

[1544] To optimize travel routes between the proposed destinations, we use external services such as Google Maps API to calculate transportation modes and travel times, and generate an optimal schedule for the user.

[1545] 4. Generate a list of items

[1546] The server generates a packing list based on destination conditions and activities, using data from a weather API and planned activities, and provides relevant shopping links for online shopping.

[1547] 5. Obtaining context information and re-proposing

[1548] It obtains real-time situational information (e.g., traffic conditions, congestion information) and re-proposes routes and schedules if the user's plans are affected, allowing users to respond flexibly to changing conditions.

[1549] 6. Emergency Response

[1550] If a problem occurs during the planning process, the user can request an emergency response from the server via their terminal. The server receives this request and promptly makes arrangements with affiliated support centers and services.

[1551] 7. Emotion detection and suggestion adjustment

[1552] The system receives a text message from the user and detects the emotion using the TextBlob library. Based on the emotion detected, the system adjusts the next suggestions provided. For example, if the user types "This documentary really moved me," the system detects a positive emotion and recommends content that will move them next.

[1553] Examples and prompts

[1554] Specific examples

[1555] 1. Receiving a planning request: A user sends a message saying, "I want to take my family on a 5-day trip to Kyoto."

[1556] 2. Proposal generation: The server proposes "Hotel A in Arashiyama" and "Hotel B in Gion," as well as "Kinkaku-ji Temple" and "Kiyomizu-dera Temple" as places to visit.

[1557] 3. Route optimization: The server uses the Google Maps API to calculate the optimal route from Kinkaku-ji Temple to Kiyomizu-dera Temple.

[1558] 4. Generate a list of items to bring: The server generates a list of items such as rain gear and comfortable walking shoes based on weather and activity information, and provides a link to purchase them.

[1559] 5. Obtaining situation information and re-suggestion: If Kinkaku-ji Temple is crowded on the day of your visit, the server will suggest "changing your visit to the afternoon."

[1560] 6. Emergency response: If the rental car breaks down during the plan, the server will arrange to contact the nearest repair service.

[1561] 7. Emotion detection and suggestion tailoring: If a user types, "This documentary really moved me," next time we'll recommend a different documentary or a heartwarming anime that will move them.

[1562] Prompt Sentence Examples

[1563] "User input text: "This documentary was really moving." Sentiment analysis detects a positive sentiment, so we recommend the following positive videos. Recommended video list: 1. Heartwarming anime 2. Funny comedy"

[1564] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1565] Step 1:

[1566] A user sends a planning request using a device such as a smartphone. The input includes information such as the destination, itinerary, and participants. The device then sends this information to the server via LINE messages or a dedicated app.

[1567] Step 2:

[1568] The server analyzes requests received from users using natural language processing (NLP) technology. Specifically, it extracts information such as destination, schedule, and participants. The input is the user message, and the output is the analysis results (destination, schedule, participants, etc.).

[1569] Step 3:

[1570] The server generates suggestions for places to stay and visit based on the analysis results. It accesses a database of accommodations and tourist destinations and extracts the best options based on the user's preferences, budget, and reputation. The input is the analysis results, and the output is suggested places to stay and visit.

[1571] Step 4:

[1572] The server optimizes the proposed travel routes between the destinations. It uses the Google Maps API to calculate the optimal route and transportation. The input is a list of destinations, and the output is the optimal travel route and travel time.

[1573] Step 5:

[1574] The server generates an inventory list based on destination condition information and activities, for example, using data from a weather information API or planned activity information, and provides purchase links for items related to the inventory list. The input is destination condition information and activity information, and the output is the inventory list and purchase links.

[1575] Step 6:

[1576] The server obtains real-time situation information and congestion information for destinations and re-proposes routes and schedules. If necessary, it recalculates based on traffic condition data and congestion information obtained from the API. The input is real-time situation information, and the output is the re-proposed route or schedule.

[1577] Step 7:

[1578] If a user needs emergency response during planning, they send an emergency response request to the server via their terminal. The server receives this request and promptly arranges for it to be sent to a support center or service that it is affiliated with. The input is the emergency response request, and the output is the procedure for resolving the problem and the contact information for the nearest support service.

[1579] Step 8:

[1580] The server receives an input text message from a user and detects the emotion using an emotion engine (e.g., TextBlob library). Specifically, it analyzes the text for positive or negative emotion. The input is the text message, and the output is the detected emotion (e.g., emotion score).

[1581] Step 9:

[1582] The server then adjusts the next suggestions it provides based on the detected emotion. For example, if a positive emotion is detected, it recommends content that is likely to further inspire the user. The input is the detected emotion, and the output is the adjusted suggestions.

[1583] 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.

[1584] 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.

[1585] 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.

[1586] [Fourth embodiment]

[1587] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1588] 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.

[1589] 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).

[1590] 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.

[1591] 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.

[1592] 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).

[1593] 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.

[1594] 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.

[1595] 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.

[1596] 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.

[1597] 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.

[1598] 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.

[1599] 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."

[1600] The system of the present invention is designed to enable users to smoothly carry out their travel plans and to quickly respond to any problems that may arise during the trip. Each component of the present invention and its function will be described in detail below.

[1601] 1. Receiving a travel planning request

[1602] A user sends a travel request to the LINE Official Account. For example, the user sends a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[1603] The server receives this message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[1604] 2. Accommodation and sightseeing suggestions

[1605] The server searches a database of affiliated accommodations and tourist destinations, for example, to extract suitable options from hotels and tourist attractions in Okinawa Prefecture, taking into account criteria such as the user's preferences, budget, and popularity.

[1606] The server then sends the user information about the selected accommodation and sightseeing spots via LINE message, such as "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium."

[1607] 3. Optimizing travel routes

[1608] The server uses external services such as Google Maps API to calculate travel routes between the proposed tourist spots, generating an optimal travel schedule for the user, taking into account the travel time and transportation method (public transportation, rental car, etc.) to each tourist spot.

[1609] The server then sends the generated route and schedule information to the user via LINE message. For example, it suggests a schedule such as "Day 1: From Hotel A to Shuri Castle, 30 minutes by rental car, dinner on Kokusai Street."

[1610] 4. Inventory list and purchase suggestions

[1611] The server creates a packing list based on the weather and planned activities of the destination. For example, if traveling to Okinawa in the summer, the list might include sunscreen, light clothing, and flip-flops.

[1612] In addition, the server provides a purchasing link based on the inventory list. For example, it adds information to the inventory list such as "Flip-flops, sunscreen, and beach towels can be purchased at the online shop" and sends it to the user via LINE message.

[1613] 5. Route re-proposal based on congestion

[1614] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and then re-proposes optimal routes and schedules to users based on the day's congestion forecast and traffic conditions.

[1615] For example, if Shuri Castle is crowded, the server sends the user a message such as "Shuri Castle is crowded, so we suggest you reschedule your visit to the afternoon."

[1616] 6. Emergency Response

[1617] While traveling, users can request emergency response through the LINE Official Account. For example, if their rental car breaks down, they can send a message saying, "My rental car has broken down."

[1618] The server analyzes this message and arranges for an emergency response from an affiliated support center or service, then sends the user a LINE message with instructions on how to resolve the problem and the contact details of the nearest repair service.

[1619] In this way, the system of the present invention provides consistent support from travel planning to the actual travel, allowing users to enjoy their trip with peace of mind.

[1620] The processing flow will be explained below.

[1621] Step 1:

[1622] A user sends a travel request to the LINE Official Account. For example, they send a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[1623] Step 2:

[1624] The server receives the user's message and uses natural language processing (NLP) technology to analyze the message content and extract information such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[1625] Step 3:

[1626] The server then uses the analysis results to search a database of affiliated accommodations and tourist destinations using SQL queries and API requests to extract options that match the user's preferences, budget, popularity, and other criteria.

[1627] Step 4:

[1628] The server lists information on selected accommodations and tourist spots and generates suggestions for the user. Example suggestion: "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium."

[1629] Step 5:

[1630] The server sends a proposal message to the user via LINE, who can then receive and confirm the proposal.

[1631] Step 6:

[1632] The server uses external services such as Google Maps API to calculate the travel routes between the proposed tourist spots. The API request specifies the departure point and destination, and obtains the optimal travel route and travel time between each tourist spot.

[1633] Step 7:

[1634] The server creates an optimal schedule for the user based on the travel route information it has acquired. Schedule example: "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle. Dinner at Kokusai Street."

[1635] Step 8:

[1636] The server generates schedule information and sends it to the user via LINE message. The user can check the schedule and get a detailed understanding of their travel plans.

[1637] Step 9:

[1638] The server retrieves weather information for the destination and planned activities, and creates a packing list based on that information. It uses a weather information API and an activity database.

[1639] Step 10:

[1640] The server generates links to purchase the items you need based on your inventory list, such as "You can buy flip-flops, sunscreen, and beach towels from our online store."

[1641] Step 11:

[1642] The server sends the user a list of items and a link to purchase them via LINE. The user can then check the list and purchase the items they need online.

[1643] Step 12:

[1644] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, periodically querying the traffic information API and congestion status database.

[1645] Step 13:

[1646] Based on the latest information obtained by the server, the server re-proposes the user's travel route and schedule as necessary. Example of re-proposition: "Shuri Castle is crowded, so we suggest visiting it in the afternoon."

[1647] Step 14:

[1648] The server sends a re-proposal message to the user via LINE, and the user receives the new proposal and can adjust their schedule.

[1649] Step 15:

[1650] If a user encounters a problem during their trip, they can send a support request through LINE. Example: "My rental car broke down."

[1651] Step 16:

[1652] The server receives the support request, analyzes the message content, and searches for and arranges for the appropriate affiliated support center or repair service depending on the type of problem.

[1653] Step 17:

[1654] The server will send a LINE message to the user with instructions on how to resolve the issue and contact details. Example: "If your rental car is broken, we will direct you to the nearest repair service."

[1655] In this way, the system of the present invention provides a consistent service from travel planning to support during the trip, allowing users to enjoy their trip with peace of mind.

[1656] Example 1

[1657] 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."

[1658] When planning a trip, users must consider a wide range of factors, including destination, accommodation, tourist spots, transportation, and belongings, which can be time-consuming and stressful. Furthermore, the lack of prompt support to deal with unexpected problems or crowded conditions during the trip makes it difficult for users to enjoy their trip with peace of mind. There is a need for a system that can solve these problems and enable users to plan and execute trips smoothly and stress-free.

[1659] 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.

[1660] In this invention, the server includes means for receiving a travel plan request from a user, means for generating suggestions for accommodations and tourist spots based on the requested information, means for optimizing travel routes between the suggested tourist spots using external services, means for generating a packing list based on weather information and activities at the travel destination and providing links to purchase items, means for obtaining real-time traffic conditions and congestion information at tourist spots and re-suggesting routes and schedules, and means for providing emergency responses to problems that occur during the trip. This allows users to smoothly plan their trip and quickly respond to unexpected situations that arise during the trip.

[1661] Ok, I've created definitions for some important words below.

[1662] "User" means an individual or organization that uses the System to make travel plans.

[1663] A "request" is a message about travel wishes and conditions that a user sends to the system.

[1664] "Accommodation" refers to facilities for staying overnight during a trip, including hotels, inns, and guesthouses.

[1665] "Tourist destinations" refer to tourist attractions and famous places that can be visited at a travel destination.

[1666] An "external service" is a service provided by a third party that the system uses to obtain data in cooperation with, and includes, for example, a map service or a weather information service.

[1667] "Weather information" is information about the weather at the travel destination, including weather forecasts, temperature, and the probability of precipitation.

[1668] "Activities" refers to specific activities or events that can be undertaken during a trip.

[1669] A "packing list" is a list of items you will need for your trip.

[1670] A "purchase link" is a link on the Internet to purchase an item included in the inventory list.

[1671] "Real-time" refers to the immediate availability of information at that time and place.

[1672] "Traffic conditions" refers to information indicating the degree of congestion and passability of roads and public transportation.

[1673] "Congestion information" is information that indicates the degree of congestion at tourist spots, roads, etc.

[1674] "Emergency response" refers to quickly dealing with unexpected problems that arise during travel.

[1675] A "server" is a computer system that controls the entire system, processes data, and provides services.

[1676] The system of the present invention is designed to enable users to smoothly carry out their travel plans and to quickly respond to any problems that may arise during the trip. Each component of the present invention and its function will be described in detail below.

[1677] Accepting travel planning requests

[1678] A user sends a travel request to the dedicated application or LINE official account. For example, a user sends a message saying, "I would like to take a five-day trip to Okinawa for my family of four."

[1679] The server receives this message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination, duration of the trip, and number of participants. Specifically, it uses an NLP library (e.g., spaCy) to perform the analysis.

[1680] Selection of accommodation and sightseeing spots

[1681] The server searches a database of affiliated accommodations and tourist destinations (for example, a PostgreSQL database). Using the keywords extracted earlier, "Okinawa," "5 days," and "family of four," the server searches for accommodations and tourist destinations that meet the criteria. For example, the server might list "Hotel A near Kokusai Street," "Beach Resort Hotel B," "Shuri Castle," and "Okinawa Churaumi Aquarium."

[1682] Based on the selection results, the server generates a list of accommodation and tourist spot suggestions and notifies the user via LINE message.

[1683] Optimizing travel routes

[1684] The server uses the Google Maps API to calculate travel routes between the suggested tourist spots. It sends a request to the Google Maps API to obtain the distances and travel times between the tourist spots. Based on this, it generates an optimal travel schedule. The generated schedule is put together taking into account the travel time to each tourist spot and the means of transportation (public transportation, rental car, etc.). This schedule is sent to the user via LINE message.

[1685] For example, a suggestion might be, "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street."

[1686] Inventory list and purchase suggestions

[1687] The server uses a weather information API (e.g., OpenWeatherMap API) to obtain weather information for the travel destination. A packing list is created based on the obtained weather information and planned activity information. Examples of packing list items include "sunscreen," "light clothing," and "beach sandals." A corresponding purchase link is also generated along with the packing list and provided to the user via LINE message.

[1688] For example, a link might say, "Buy sunscreen, flip flops and beach towels from our online store."

[1689] Checking congestion status and re-proposing

[1690] The server periodically accesses external APIs such as the Google Maps API to obtain real-time traffic conditions and congestion information at tourist spots. Based on the expected congestion and traffic conditions for the day, the server re-suggests optimal routes and schedules for users. For example, it might suggest, "Shuri Castle is crowded, so change your visit to the afternoon."

[1691] Emergency response

[1692] If a user requests an emergency response through the LINE Official Account while traveling, they can send a message saying, for example, "My rental car has broken down."

[1693] The server receives this message and uses NLP technology to analyze the problem. It then arranges for an emergency response from a partner support center or service. This provides the user with the steps to resolve the problem and the contact information for the nearest repair service. For example, it provides the user with information such as, "The nearest repair service is XX company, and their contact number is YYY."

[1694] Examples of concrete examples and prompts

[1695] As an example showing the operation of the specific system, we will show an example of inputting the following prompt sentence into a generative AI model (e.g., ChatGPT).

[1696] Specific examples

[1697] 1. A user sends a message to the LINE Official Account saying, "We are planning a three-day trip to Okinawa. Please recommend accommodations and tourist spots for our family of four."

[1698] 2. The server receives the message and uses NLP technology to extract the information "Okinawa," "3 days," and "family of four."

[1699] 3. The server searches its partner accommodation database to find accommodations that meet the criteria. For example, it finds "Hotel A, Hotel B."

[1700] 4. Next, the main tourist spots in Okinawa are searched for, and "Shuri Castle, Okinawa Churaumi Aquarium, and Kokusai Street" are selected.

[1701] 5. The server generates a list based on the selection results and suggests to the user, "You can stay at Hotel A or Hotel B and visit Shuri Castle, Okinawa Churaumi Aquarium, and Kokusai Street."

[1702] Prompt Sentence Examples

[1703] We are building an AI assistant to help you plan your trip. Plan a trip that meets the following criteria:

[1704] Travel destination: Okinawa

[1705] Duration: 3 days

[1706] Participants: 4 family members

[1707] Please suggest accommodation and sightseeing spots, travel routes, and a recommended packing list.

[1708] This concludes the explanation of the program processing of the system of the present invention in natural language, including specific examples.

[1709] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1710] Step 1:

[1711] A user sends a travel request to the LINE Official Account. For example, they send a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[1712] Input: User request message

[1713] Output: RAW message data

[1714] Step 2:

[1715] The server receives the user's request message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination, trip duration, and number of participants, for example, using an NLP library (spaCy).

[1716] Input: RAW message data

[1717] Output: Extracted keywords (e.g., Okinawa, 5 days, family of 4)

[1718] Step 3:

[1719] The server searches a database of affiliated accommodations and tourist destinations based on the extracted keywords, for example, using a PostgreSQL database.

[1720] Input: Extracted keywords

[1721] Output: List of accommodations and tourist attractions (e.g., Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium)

[1722] Step 4:

[1723] The server will send suggestions to the user via LINE message based on a list of accommodations and tourist spots.

[1724] Input: List of accommodations and tourist attractions

[1725] Output: LINE message (Example: Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium)

[1726] Step 5:

[1727] The server uses the Google Maps API to calculate routes between tourist attractions, including distances and travel times between the attractions.

[1728] Input: List of accommodations and tourist attractions

[1729] Output: Distance and travel time data between tourist spots

[1730] Step 6:

[1731] The server generates an optimal travel schedule based on the travel data it acquires, including the travel time and means of transportation to each tourist spot.

[1732] Input: Distance and travel time data between tourist spots

[1733] Output: Optimal schedule (Example: Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street)

[1734] Step 7:

[1735] The server sends the generated schedule to the user via LINE message.

[1736] Input: Optimal schedule

[1737] Output: LINE message (Example: Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street)

[1738] Step 8:

[1739] The server uses a weather information API (OpenWeatherMap API) to obtain weather information for the travel destination.

[1740] Input: Travel destination information (e.g. Okinawa)

[1741] Output: Weather data

[1742] Step 9:

[1743] The server creates a list of items to bring based on weather and activity information obtained, and also generates corresponding purchase links.

[1744] Input: Weather data, activity information

[1745] Output: Packing list and purchase links (e.g. sunscreen, light clothing, flip-flops)

[1746] Step 10:

[1747] The server sends the user a LINE message with the list of items and a link to purchase them.

[1748] Input: Inventory list and purchase links

[1749] Output: LINE message (e.g., sunscreen, flip-flops, and beach towels are available for purchase at the online store)

[1750] Step 11:

[1751] The server uses external APIs such as Google Maps API to periodically obtain real-time traffic conditions and congestion information at tourist spots.

[1752] Input: Current travel schedule, traffic data

[1753] Output: Updated schedule (if necessary)

[1754] Step 12:

[1755] The server sends the updated schedule to the user via LINE message, which may include, for example, "Shuri Castle is crowded, so we will reschedule our visit to the afternoon."

[1756] Input: Updated Schedule

[1757] Output: LINE message

[1758] Step 13:

[1759] While traveling, a user requests an emergency response through the LINE Official Account. For example, they can send a message saying, "My rental car has broken down."

[1760] Input: Emergency response message

[1761] Output: RAW emergency message data

[1762] Step 14:

[1763] The server receives the emergency message and uses NLP technology to analyze the nature of the problem.

[1764] Input: RAW emergency message data

[1765] Output: Extracted problem keywords (e.g., rental car, breakdown)

[1766] Step 15:

[1767] Based on the analyzed problem, the server will dispatch emergency response to partner support centers or services, for example, dispatching the nearest repair service and obtaining contact information.

[1768] Input: Extracted problem keywords

[1769] Output: Repair service contact information

[1770] Step 16:

[1771] The server will send a LINE message to the user with instructions on how to resolve the problem and the contact information for the nearest repair service.

[1772] Input: Repair service contact information

[1773] Output: LINE message (e.g., the nearest repair service is XX company, contact number is YYY)

[1774] The above are the specific processing steps and contents of the program for this system.

[1775] (Application example 1)

[1776] 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."

[1777] Systems that provide consistent support, from planning a trip to troubleshooting during the trip, require a wide range of information, and are often complex and difficult for users to use. Arranging meals during a trip and responding to sudden changes in circumstances are also difficult challenges. These challenges make it difficult for users to enjoy their trip comfortably.

[1778] 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.

[1779] In this invention, the server includes means for receiving a travel plan request from a user, means for generating suggestions for accommodations and sightseeing spots based on the requested information, means for optimizing travel routes between the suggested sightseeing spots, means for generating a packing list based on weather information and activities at the travel destination and providing links to purchases, means for obtaining real-time traffic conditions and congestion information at sightseeing spots and re-proposing routes and schedules, means for receiving a request for meal delivery at the travel destination and searching for and suggesting affiliated restaurants, means for tracking delivery progress in real time and notifying the user, and means for providing emergency responses to problems during the trip. This makes it possible to efficiently perform everything from travel planning to dealing with problems during the trip, as well as arranging meals and responding to changes in the situation, all in one system.

[1780] A "user" is a person who utilizes the system to submit travel planning requests and receive suggestions and assistance.

[1781] A "travel plan" refers to a series of activities including travel destinations, accommodations, sightseeing spots, travel routes, packing list, meal delivery, and emergency response.

[1782] A "request" is information that a user submits to the system to communicate their travel planning wishes and desires.

[1783] An "accommodation" is a place where a user stays during a trip, such as a hotel or resort.

[1784] A "tourist spot" is a tourist spot in a travel destination that the user intends to visit.

[1785] A "travel route" is a route for efficiently traveling between the proposed tourist destinations.

[1786] "Weather information" is data about the weather at the travel destination, and is used to generate a packing list.

[1787] An "activity" is a planned action or event during a trip.

[1788] A "packing list" is a list of items necessary for a trip, and is generated based on weather information and activities.

[1789] A "purchase link" is a URL for online purchase of recommended items based on the inventory list.

[1790] "Traffic conditions" refers to data on traffic flow between travel destinations and tourist spots.

[1791] "Crowding information" is real-time information about the degree of congestion at tourist spots and travel routes.

[1792] "Meal delivery" is a service that allows users to order meals while traveling and have them delivered to their destination.

[1793] "Eating and drinking establishments" are establishments such as restaurants and cafes that serve meals and offer delivery services.

[1794] "Delivery progress" is information about the stage at which the ordered meal is and when it will arrive to the user.

[1795] "Emergency response" means assistance to provide a quick solution to unexpected problems that arise during travel.

[1796] A "support center" is a base for responding to emergency requests from users.

[1797] A specific embodiment of the travel planning and travel assistance system will be described in detail below.

[1798] Components and Functions

[1799] 1. Receiving a travel planning request from a user

[1800] The system receives a travel planning request from the user, such as a basic request like "Please deliver sushi for two in Okinawa" via a device like a smartphone or smart glasses, and then sends information such as the trip destination, number of people, and desired services to the server.

[1801] 2. Request analysis using natural language processing

[1802] The server then uses natural language processing (NLP) technology to analyze the incoming request and determine the destination, number of people, and desired services, using an NLP engine such as Google Cloud Natural Language API.

[1803] 3. Accommodation and sightseeing suggestions

[1804] Based on the analyzed request information, the server generates appropriate suggestions from a database of affiliated accommodation and tourist destinations. For example, if a user inputs "I'm planning a five-day trip to Okinawa for my family of four," the system will search for hotels and tourist attractions in Okinawa Prefecture and make suggestions based on the user's preferences and budget.

[1805] 4. Generate inventory list and purchase links

[1806] The server generates a list of necessary items to bring based on the weather information and activities of the destination. For example, if you are traveling to Okinawa in the summer, it will list light clothing and beach sandals, and provide a purchasing link. This link is designed so that the user can easily purchase the items on an online shopping site.

[1807] 5. Optimizing travel routes

[1808] The server uses external services such as Google Maps API to optimize travel routes between tourist spots. It generates an optimal travel schedule by taking into account the travel time and transportation means to each tourist spot. For example, it suggests a schedule such as "30 minutes by rental car from Hotel A to Shuri Castle."

[1809] 6. Get real-time traffic and congestion information

[1810] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and re-proposes routes and schedules as necessary. For example, congestion information is used to suggest, "Shuri Castle is crowded, so let's change our visit to the afternoon."

[1811] 7. Arrange for meal delivery

[1812] The server arranges meal delivery to the travel destination based on the user's request. It searches a database of affiliated restaurants to suggest appropriate menus and restaurants to the user. It then arranges delivery based on the user's selection. Delivery progress information is tracked in real time and notified to the user.

[1813] 8. Providing emergency response

[1814] If a problem occurs during a trip, such as a breakdown in a rental car, the user sends an emergency request to the system. The server analyzes the request, coordinates with affiliated support centers and the necessary emergency response, and provides the user with instructions on how to resolve the issue.

[1815] Hardware and software used

[1816] Smartphones / Smart Glasses: Used as an interface for the user.

[1817] Server: Receives, analyzes, proposes, arranges and notifies requests.

[1818] Natural language processing engine: Analyzes user requests using the Google Cloud Natural Language API, etc.

[1819] Database: Stores information about affiliated accommodations, tourist spots, and restaurants (MySQL, etc.).

[1820] External API service: Uses Google Maps API to optimize travel routes and obtain traffic information.

[1821] Delivery management system: Use APIs such as Uber Eats to schedule and track food deliveries.

[1822] Specific examples and input prompts for generative AI models

[1823] Example: "Sushi delivery for two in Okinawa."

[1824] Prompt statement:

[1825] Message: "Sushi delivery for two in Okinawa"

[1826] Destination: Okinawa

[1827] Type of cuisine: Sushi

[1828] Number of people: 2 people

[1829] Analyze the request details.

[1830] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1831] Step 1:

[1832] A user submits a travel planning request.

[1833] The user uses a smartphone or smart glasses to input and send a request message such as "Please deliver sushi for two in Okinawa," which is then sent to the server.

[1834] Input: Request message (e.g. "Please deliver sushi for two in Okinawa")

[1835] Output: The server receives the request message.

[1836] Step 2:

[1837] The server receives the request and performs analysis using natural language processing (NLP).

[1838] The server uses an NLP engine such as Google Cloud Natural Language API to analyze the request message and extract information such as the destination (Okinawa), number of people (2), and desired service (sushi delivery).

[1839] Input: Request message

[1840] Output: Extracted information (destination, number of people, desired services)

[1841] Step 3:

[1842] The server generates suggestions for accommodation and sightseeing spots.

[1843] Based on the user's request, the server searches its database of affiliated accommodation and tourist destinations and generates suggestions suitable for the user. For example, it searches for hotels and tourist attractions in Okinawa Prefecture and makes suggestions based on the user's preferences and budget.

[1844] Input: Request details (destination, number of people, desired service)

[1845] Output: Accommodation and sightseeing suggestions

[1846] Step 4:

[1847] The server generates the inventory list and purchase links.

[1848] The server generates a packing list based on the weather information of the destination and the planned activities. For example, if traveling to Okinawa in the summer, the list may include sunscreen, light clothing, beach sandals, etc. Then, based on the packing list, it generates a purchase link to an online shopping site and provides it to the user.

[1849] Input: Weather information, activity information

[1850] Output: Inventory list and purchase links

[1851] Step 5:

[1852] The server optimizes the travel route.

[1853] The server uses external services such as Google Maps API to calculate travel routes between the proposed tourist spots and generate an optimal travel schedule, taking into account the travel time to each tourist spot and the means of transportation (e.g., public transportation, rental car, etc.).

[1854] Input: tourist destination information, transportation data

[1855] Output: Travel routes and schedules

[1856] Step 6:

[1857] The server retrieves real-time traffic and congestion information and re-suggests routes and schedules.

[1858] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and based on that information, it re-proposes optimal routes and schedules to users. For example, if Shuri Castle is crowded, it will re-propose a visit to the castle in the afternoon.

[1859] Input: Real-time traffic information, congestion information

[1860] Output: Reproposed route and schedule

[1861] Step 7:

[1862] The server proposes and arranges meal delivery at the travel destination.

[1863] Based on the user's request, the server searches a database of affiliated restaurants and suggests appropriate menus and restaurants to the user. It also arranges delivery from the restaurant selected by the user and tracks the delivery progress in real time.

[1864] Input: Request details, partner restaurant data

[1865] Output: Suggested restaurant and ordering information, tracking information

[1866] Step 8:

[1867] The server provides emergency response for travel issues.

[1868] If a user encounters a problem during their trip, they send an emergency request to the server, which analyzes the request, coordinates with affiliated support centers and necessary emergency response, and provides the user with a solution and contact information.

[1869] Input: Urgent Request

[1870] Output: Emergency response arrangements and solution proposals

[1871] 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.

[1872] The system of the present invention is designed to enable users to smoothly execute their travel plans and quickly respond to any problems that may arise during the trip. Furthermore, the present invention incorporates an emotion engine that recognizes the user's emotions and adjusts the content of the suggestions based on those emotions. Each component of the present invention and its function will be described in detail below.

[1873] 1. Receiving a travel planning request

[1874] A user sends a travel request to the LINE Official Account. For example, the user sends a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[1875] The server receives this message and uses natural language processing (NLP) techniques to extract information from the request, such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[1876] 2. Accommodation and sightseeing suggestions

[1877] The server searches a database of affiliated accommodations and tourist destinations, for example, to extract suitable options from hotels and tourist attractions in Okinawa Prefecture, taking into account criteria such as the user's preferences, budget, and popularity.

[1878] Next, the server will suggest information about the selected accommodations and sightseeing spots to the user. For example, suggestions such as "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium" will be sent via LINE message.

[1879] The server uses an emotion engine to recognize the user's feelings toward these suggestions. For example, if a user sends a message saying "Hotel A is too expensive," the emotion engine recognizes that the user has a negative feeling toward the suggestion.

[1880] 3. Optimizing travel routes

[1881] The server uses external services such as Google Maps API to calculate travel routes between the proposed tourist spots, generating an optimal travel schedule for the user, taking into account the travel time and transportation method (public transportation, rental car, etc.) to each tourist spot.

[1882] For example, schedule information such as "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street" is sent to the user via LINE message. If the user expresses dissatisfaction by saying "the travel time is too long," the emotion engine will pick up on the user's emotions, and the server will recalculate the travel route based on this.

[1883] 4. Inventory list and purchase suggestions

[1884] The server creates a packing list based on the weather and planned activities of the destination. For example, if traveling to Okinawa in the summer, the list might include sunscreen, light clothing, and flip-flops.

[1885] The server provides a purchasing link based on the list of belongings, for example, "Flip-flops, sunscreen, and beach towels are available for purchase at the online shop," and sends the link to the user via LINE message.

[1886] 5. Route re-proposal based on congestion

[1887] The server periodically obtains real-time traffic conditions and congestion information for tourist spots, and then re-proposes optimal routes and schedules to users based on the day's congestion forecast and traffic conditions.

[1888] For example, if Shuri Castle is crowded, the server sends the user a message such as "Shuri Castle is crowded, so we suggest you reschedule your visit to the afternoon."

[1889] 6. Emergency Response

[1890] If a user encounters a problem during their trip, they can send a support request through the LINE official account. For example, if their rental car breaks down, they can send a message saying, "My rental car has broken down."

[1891] The server analyzes this message and arranges for an emergency response from an affiliated support center or service, then sends the user a LINE message with instructions on how to resolve the problem and the contact details of the nearest repair service.

[1892] 7. Use of Emotion Engines

[1893] The server uses an emotion engine to recognize emotions from the user's message. For example, if the user feels that they "don't like" the proposed accommodation, the emotion engine captures that negative emotion.

[1894] The server adjusts its suggestions based on the captured emotions. If the user expresses positive emotions, it stores the emotion information to use it in future suggestions. This ensures that the next time the user submits a request, suggestions will take into account their previous emotional history.

[1895] By combining this emotion engine, the system can make suggestions that are in line with the user's emotions and provide a comprehensive service, from travel planning to support during the trip.

[1896] The processing flow will be explained below.

[1897] Step 1:

[1898] A user sends a travel request through the LINE official account. For example, they send a message saying, "I'd like to take a five-day trip to Okinawa for my family of four."

[1899] Step 2:

[1900] The server analyzes the received message and uses natural language processing (NLP) technology to extract information from the request, such as the destination (Okinawa), trip duration (5 days), and participants (a family of four).

[1901] Step 3:

[1902] The server searches a database of affiliated accommodations and tourist destinations, extracting appropriate options based on the user's preferences, budget, popularity, and other criteria.

[1903] Step 4:

[1904] The server selects and suggests information about accommodation and sightseeing spots to the user. Example of suggestion: Send information such as "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, Okinawa Churaumi Aquarium" via LINE message.

[1905] Step 5:

[1906] The user reviews the suggestions and provides feedback, for example, a message saying "Hotel A is too expensive."

[1907] Step 6:

[1908] The emotion engine analyzes the user feedback and recognizes emotions. In this case, the emotion engine catches negative emotions (felt too high).

[1909] Step 7:

[1910] The server then adjusts the recommendation based on the emotion engine's analysis, for example by finding another hotel within the customer's budget and suggesting, "How about Hotel B?"

[1911] Step 8:

[1912] The server calculates the travel routes between the proposed tourist spots using the Google Maps API, etc., and obtains the optimal travel route and travel time between each tourist spot.

[1913] Step 9:

[1914] The server creates an optimal schedule for the user based on the route information it obtains. Schedule example: "Day 1: 30 minutes by rental car from Hotel B to Shuri Castle, dinner at Kokusai Street" is sent via LINE message.

[1915] Step 10:

[1916] Users can review the schedule and provide feedback, such as "travel time is too long."

[1917] Step 11:

[1918] The emotion engine again analyzes the user feedback and recognizes emotions, in this case catching the negative emotion (travel time is too long).

[1919] Step 12:

[1920] The server again adjusts the suggestion, for example, calculating a new route to shorten the travel time, such as "leave in the afternoon instead."

[1921] Step 13:

[1922] The server creates a packing list based on weather information and planned activities. For example, the list might include "sunscreen, light clothing, and flip-flops."

[1923] Step 14:

[1924] The server provides a link to purchase items based on the list. For example, it sends a LINE message containing information such as "Flip-flops, sunscreen, and beach towels can be purchased from the online shop."

[1925] Step 15:

[1926] The server periodically retrieves real-time traffic information and congestion information for tourist spots, e.g., makes an API request every 15 minutes.

[1927] Step 16:

[1928] The server will re-suggest routes and schedules for the user based on the latest information as needed. For example, a LINE message will be sent saying, "Shuri Castle is crowded, so we suggest visiting in the afternoon."

[1929] Step 17:

[1930] If a user encounters a problem during their trip, they can send a support request through LINE, for example, by sending a message saying, "My rental car has broken down."

[1931] Step 18:

[1932] The server analyzes the support request and dispatches affiliated support centers or emergency response services depending on the type of problem.

[1933] Step 19:

[1934] The server will send a LINE message to the user with instructions on how to resolve the issue and the contact information for the nearest repair service. For example, it might say, "The nearest repair service is here."

[1935] By combining this emotion engine, the system can make suggestions that are in line with the user's emotions and provide a comprehensive service, from travel planning to support during the trip.

[1936] Example 2

[1937] 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."

[1938] Conventional travel planning support systems make suggestions based on the user's preferences, but they have the problem of being unable to respond flexibly to the user's emotions and real-time circumstances. Furthermore, they lack functionality that consistently supports the entire travel plan, such as packing lists, route optimization, and emergency response.

[1939] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving a travel plan request from a user, means for analyzing the requested information and extracting the destination, travel period, and participating members, means for generating suggestions of accommodation and sightseeing spots based on the extracted information, means for analyzing the user's feelings about the proposed accommodation and sightseeing spots, means for adjusting the suggestions based on the user's feelings, means for optimizing travel routes between the proposed sightseeing spots, means for generating a packing list based on weather information and activities at the travel destination and providing a purchasing link, means for obtaining real-time traffic conditions and congestion information at sightseeing spots and re-proposing routes and schedules, and means for providing emergency response for problems encountered during the trip. This allows users to receive comprehensive services from travel planning to support during the trip.

[1940] "User" refers to an individual or organization that uses the System to plan and execute travel plans.

[1941] "Travel plan request" refers to the act of a user sending information about a travel plan, such as destination, travel period, and participating members, to the server.

[1942] "Means" refers to a method, apparatus, or component in a system for achieving a particular purpose.

[1943] "Requested Information" means the data provided by a User to a Server in a Travel Planning Request.

[1944] "Analyzing information" refers to the process of analyzing received data and understanding or classifying its content.

[1945] "Destination" refers to the final destination or place of stay of a trip.

[1946] "Travel Period" refers to the time span from the start to the end of a trip.

[1947] "Participating Member" means an individual person participating in a trip.

[1948] "Accommodation" refers to the place where you stay during your trip.

[1949] "Tourist destinations" refer to tourist attractions and places of interest that are planned to be visited during a trip.

[1950] "Emotion analysis" refers to the process of reading a user's emotional state from their messages and feedback.

[1951] "Adjusting suggestions based on emotions" refers to the act of changing or optimizing the system's suggestions by taking into account the user's emotional information.

[1952] "Route optimization" refers to the process of adjusting travel routes during a planned trip to make them more efficient and effective.

[1953] "Weather Information" refers to data regarding weather conditions at a travel destination.

[1954] "Activities" refers to events or activities planned to take place during a trip.

[1955] A "packing list" is a list of items that should be brought on a trip.

[1956] "Purchase Link" means an online link to purchase an item included in the inventory list.

[1957] "Real-time traffic conditions" refers to information about current traffic conditions and status.

[1958] "Crowding information for tourist spots" refers to information on the current level of congestion at tourist spots and famous places.

[1959] "Route and schedule re-proposal" refers to the act of reevaluating travel plans based on real-time information and providing optimal travel routes and time allocations.

[1960] "Emergency response" refers to dealing with and providing support in the event of an unexpected problem occurring during travel.

[1961] The system of the present invention provides users with a consistent service from planning a trip to support during the trip. Each component of the present invention and its function will be described in detail below.

[1962] 1. Receiving and analyzing travel planning requests

[1963] A user sends a travel request to a LINE official account. For example, a message such as "I'm looking for a five-day trip to Okinawa for a family of four" is sent. The server receives this message and uses natural language processing (NLP) technology to extract key information from the request (destination, trip duration, and participating members). A common natural language processing API (such as Google Cloud Natural Language API) is used as the NLP engine.

[1964] 2. Accommodation and sightseeing suggestions

[1965] The server searches a database of affiliated accommodations and tourist destinations. For example, it executes SQL queries using a database management system (e.g., MySQL) to select accommodations and tourist destinations that fit the user's preferences and budget. The server then suggests information about the selected accommodations and tourist destinations to the user. Examples of suggestions could include "Hotel A near Kokusai Street, Beach Resort Hotel B, Shuri Castle, and Okinawa Churaumi Aquarium."

[1966] 3. Analyzing user sentiment and adjusting suggestions

[1967] When a user sends a LINE message with their opinion or thoughts about a suggestion, the server uses an emotion engine to analyze the user's emotions. The emotion engine uses a machine learning model (e.g., BERT), for example. Based on the results of this emotion analysis, the server adjusts the suggestion. For example, if a user sends negative feedback such as "Hotel A is too expensive," the server will reconsider the accommodation options and make a new suggestion.

[1968] 4. Optimizing travel routes

[1969] The server uses the Google Maps API to calculate travel routes between the suggested tourist spots. It generates the optimal travel schedule for the user, taking into account public transportation, rental cars, and other means of transportation. For example, it sends the user a LINE message with schedule information such as "Day 1: 30 minutes by rental car from Hotel A to Shuri Castle, dinner at Kokusai Street."

[1970] 5. Create a packing list and get purchase suggestions

[1971] The server creates a packing list based on the weather information for the destination and the planned activities. It uses a weather API (e.g., OpenWeatherMap API) to obtain weather information. It also provides links to purchase specific products based on the packing list. For example, it sends a LINE message to the user with links to purchase beach sandals and sunscreen.

[1972] 6. Re-suggestions based on real-time information

[1973] The server periodically obtains real-time traffic conditions and congestion information at tourist spots, and based on this information, re-proposes optimal routes and schedules. It obtains information using traffic APIs (e.g., Google Maps Traffic) and congestion information services (e.g., Tourist Information API) and makes appropriate suggestions to the user. For example, it sends a message such as, "Shuri Castle is crowded, so we suggest you change your visit to the afternoon."

[1974] 7. Emergency Response

[1975] If a user encounters a problem during their trip, they can send a support request through their official LINE account. For example, if they send a message like "My rental car has broken down," the server will analyze the message and arrange for an emergency response from an affiliated support center. The server will then send a LINE message to the user with instructions on how to resolve the problem and the contact details of the nearest repair service.

[1976] Specific examples

[1977] Below is a concrete example of how the system works.

[1978] Start planning your trip

[1979] 1. A user sends a message to the LINE official account saying, "I'd like to t...

Claims

1. means for receiving a travel planning request from a user; means for generating accommodation and tourist destination suggestions based on the requested information; a means of optimizing travel routes between proposed tourist destinations; A means for generating a packing list based on weather information and activities at the travel destination and providing a purchasing link; A means to obtain real-time traffic conditions and congestion information at tourist spots and re-propose routes and schedules; A means of providing emergency response to travel issues; A system including:

2. 10. The system of claim 1, further comprising means for selecting the accommodation and sightseeing suggestions based on at least a user's preferences, budget, and popularity.

3. The system of claim 1 , further comprising means for generating the luggage list by combining weather information API and travel activity information.

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