System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting a user's group information, favorite attractions, desired rest time, and scheduled time to leave; means for collecting real-time data of a theme park; means for analyzing the user's input information and the real-time data and calculating an optimal attraction use order; and means for providing a schedule to the user based on the calculated use order.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] While visiting theme parks and amusement parks, waiting times for attractions and crowding can make it difficult to enjoy the park efficiently. This problem is particularly pronounced for groups of multiple people or families, making it difficult to adjust each person's preferences and rest times. On the other hand, planning a schedule without taking real-time wait times and weather information into account results in wasted time and prevents visitors from enjoying the park experience to the fullest. There is a need to solve these problems. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for inputting user group information, favorite attractions, desired rest periods, and planned departure times, and a means for collecting real-time data from the theme park. The system includes a means for analyzing the user's input information and the real-time data to calculate the optimal attraction usage order, and a means for providing the user with a schedule based on the calculated usage order. The real-time data also includes attraction wait times, weather information, and walking speed. The system further includes a means for updating the schedule in real time and notifying the user, thereby providing a more comfortable and efficient theme park experience.

[0006] A "user" is an individual or group member who visits a theme park or amusement park and uses the system.

[0007] "Group information" is information about the composition of a group entered by the user, and is data including the number of people, age range, specific wishes and restrictions, and the like.

[0008] "Favorite Attractions" is a list of specific attractions that the user would like to visit.

[0009] The "desired break time" is a specific time period during which the user desires to take a break and its duration.

[0010] The "planned time of departure" is the time when the user plans to leave the theme park or amusement park.

[0011] "Real-time data" refers to the latest information obtained from theme parks and amusement parks, including attraction wait times, weather data, walking speed, and the like.

[0012] "Waiting time" refers to the amount of time a user must wait before being able to use each attraction.

[0013] A "schedule" is a timetable provided to enable users to efficiently enjoy a theme park, and includes plans such as the order in which attractions are to be used and break times.

[0014] "Input means" refers to a device or interface that a user uses to provide the necessary information to the system.

[0015] The "analysis means" is a system that analyzes data based on user input information and real-time data, and calculates the optimal order in which to use the attractions.

[0016] "Provision means" refers to a function or method for notifying the user of the calculated optimal schedule.

[0017] The "update means" is a system that keeps schedule information up to date in real time and makes changes or notifies users as necessary. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] The present invention is a system for optimizing a user's theme park experience by combining input information from the user with theme park data collected in real time to provide an efficient schedule. This system is realized through the cooperation of terminals and a server.

[0040] Overview of program processing

[0041] Collecting user input

[0042] The user enters the following information through the terminal:

[0043] Group information (number of people, age group, etc.)

[0044] A list of favorite attractions

[0045] Break time requests

[0046] Scheduled departure time

[0047] Real-time data collection

[0048] The server will interface with the theme park's management system and collect the following data in real time:

[0049] Waiting times for each attraction

[0050] Weather information

[0051] Travel time based on walking speed

[0052] Analyzing data and generating schedules

[0053] The server generates a schedule based on user input and real-time data in the following steps:

[0054] Analyze the user's desired information and set priorities.

[0055] Calculate the optimal order for visiting attractions based on real-time data (e.g., Dijkstra algorithm).

[0056] Adjust the overall schedule taking into account break times and planned departure times.

[0057] Schedule provision

[0058] The server sends the generated schedule to the terminal, which then displays it to the user. The schedule is provided in the form of a timetable, clearly indicating the attractions to visit during each time period and break times.

[0059] Real-time updates and notifications

[0060] The device periodically communicates with the server to request real-time information updates.

[0061] The server recalculates the schedule based on the new real-time data and sends any necessary changes to the terminal.

[0062] The device notifies users of updates and clearly shows any changes to the schedule, allowing users to receive real-time information on changes in wait times, attraction cancellations, and more.

[0063] Specific examples

[0064] For families

[0065] As an example, a case where a family uses the system will be described.

[0066] 1. Collecting user input information

[0067] The user inputs information into the terminal that the user is a family of four (two adults and two children).

[0068] His favorite attractions are roller coasters, merry-go-rounds, and Ferris wheels.

[0069] We would like to have a one-hour break from 12:00, and plan to leave the school at 18:00.

[0070] 2. Real-time data collection

[0071] The server collects real-time data from the theme park's management system, such as waiting times for roller coasters: 30 minutes, merry-go-rounds: 15 minutes, and ferris wheels: 20 minutes.

[0072] 3. Data Analysis and Schedule Generation

[0073] The server analyzes the user's desired information and optimizes the order in which each attraction is visited.

[0074] Taking into account break times and planned departure times, we generate a schedule like this:

[0075] 10:00 Roller Coaster

[0076] 11:00 Merry-go-round

[0077] 12:00 Break

[0078] 13:00 Ferris wheel

[0079] 4. Providing a schedule

[0080] The terminal displays the generated schedule to the user with family, providing it in the form of a timetable.

[0081] 5. Real-time updates and notifications

[0082] For example, if the wait time for a roller coaster increases to 50 minutes, the device will contact the server and request an updated schedule.

[0083] The server recalculates the schedule based on the new data and sends it to the terminal.

[0084] The device will notify the user of the new schedule and clearly indicate the changes.

[0085] The above is an embodiment of the present invention, and this system allows users to enjoy an efficient and comfortable theme park experience.

[0086] The processing flow will be explained below.

[0087] Step 1:

[0088] The terminal displays an input form to the user. The user enters group information (number of people, age group, etc.), a list of favorite attractions, desired break time, and planned departure time. When the user finishes entering information, he or she presses the submit button.

[0089] Step 2:

[0090] The device sends the information entered by the user to the server. The data sent is in structured JSON format.

[0091] Step 3:

[0092] The server collects real-time data from the theme park's management system and APIs, including wait times for each attraction, weather information, and travel times based on walking speed.

[0093] Step 4:

[0094] The server analyzes the input information from the user and the collected real-time data, and sets the priority of each attraction by linking the user's preferences with the real-time data.

[0095] Step 5:

[0096] The server calculates the optimal order in which to visit attractions, and optimizes the user's schedule using route optimization algorithms such as the Greedy algorithm and Dijkstra algorithm.

[0097] Step 6:

[0098] The server generates an optimal schedule based on the calculation results, which incorporates the specified break times and planned departure times.

[0099] Step 7:

[0100] The server generates a schedule and sends it to the terminal. The schedule is in a clear and easy-to-understand timetable format.

[0101] Step 8:

[0102] The terminal displays the schedule to the user, who then moves around the theme park according to the schedule and enjoys the attractions.

[0103] Step 9:

[0104] The device periodically requests the latest real-time data from the server to ensure the schedule is up-to-date with fluctuations in waiting times and weather.

[0105] Step 10:

[0106] The server recalculates the schedule based on new real-time data and sends the updated schedule to the device as needed.

[0107] Step 11:

[0108] The device notifies the user of schedule updates, for example, via push notifications or alerts, so that the user can respond quickly.

[0109] Example 1

[0110] 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."

[0111] In traditional theme park experiences, users had to check attraction wait times, weather, and travel times themselves, and then create a schedule based on that information. However, it was difficult to manually check and appropriately reflect this data, which fluctuates in real time, making efficient scheduling difficult. In particular, for large groups such as families, it is not easy to efficiently move around while satisfying everyone's wishes. This resulted in a decline in the quality of the user experience.

[0112] 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.

[0113] In this invention, the server includes means for inputting user group information, favorite video content, desired break times, and scheduled end times, means for collecting real-time data about the theme park, means for analyzing the user's input information and the real-time data and calculating an optimal video content viewing order, means for providing the user with a schedule based on the calculated viewing order, and means for updating and notifying the user of the schedule in real time via the user's terminal, thereby enabling the user to automatically receive an optimized schedule in real time and efficiently tour the theme park.

[0114] "User" refers to an individual or group who uses the theme park.

[0115] "Group information" refers to data including information such as the number of users, age range, and relationships.

[0116] "Favorite video content" refers to the types and lists of attractions and shows that the user wishes to view.

[0117] "Rest time" refers to a period of time set by the user for rest during their visit to the theme park.

[0118] "Scheduled end time" refers to the time the user plans to leave the theme park.

[0119] "Real-time theme park data" refers to the latest information at the moment, such as waiting times for each attraction within the theme park, operation status, weather information, and user travel times.

[0120] "Server" refers to a computer system that processes user input information and real-time data, and generates and manages optimal schedules.

[0121] "Terminal" refers to a device that allows a user to input information and view a generated schedule.

[0122] "Schedule" refers to an optimized theme park tour plan based on user preferences and real-time data.

[0123] "Viewing order" refers to the optimal order in which attractions and shows are viewed, calculated based on user preferences and real-time data.

[0124] "Notification" refers to the act of sending the latest schedule changes and alerts from the server to the user via the device.

[0125] The present invention is a system for optimizing a user's theme park experience by combining input information from the user with theme park data collected in real time to provide an efficient schedule. This system is realized through the cooperation of terminals and a server.

[0126] Specifically, users use their devices to input group information (number of people, age group, etc.), a list of their favorite attractions, desired rest times, and planned time to leave the park. This information is sent from the devices to the server. The server collects real-time data from the theme park's management system and weather information API. This real-time data includes waiting times for each attraction, operation status, weather information, and travel times based on the user's walking speed.

[0127] The server analyzes the input information sent by the user and the collected real-time data, and optimizes the order in which the attractions can be visited based on the user's preferences. For example, it calculates the optimal order using an algorithm such as Dijkstra's algorithm. The generated schedule is sent from the server to the terminal, which displays it to the user in the form of a timetable.

[0128] The terminal also periodically communicates with the server to request updates to real-time information. The server recalculates the schedule based on the latest real-time data and, if necessary, sends the revised schedule to the terminal. The terminal then notifies the user of the updated information and clearly indicates any changes to the schedule. This allows the user to immediately receive information on real-time changes in waiting times, attraction cancellations, and other such information.

[0129] Specific examples

[0130] Families can use the system by following these steps:

[0131] 1. Collecting user input information

[0132] The user inputs information into the terminal that the user is a family of four (two adults and two children).

[0133] His favorite attractions are roller coasters, merry-go-rounds, and Ferris wheels.

[0134] We would like to have a one-hour break from 12:00, and plan to leave the school at 18:00.

[0135] 2. Real-time data collection

[0136] The server collects real-time data from the theme park's management system, such as waiting times for roller coasters: 30 minutes, merry-go-rounds: 15 minutes, and ferris wheels: 20 minutes.

[0137] Also, sunny weather data is acquired as weather information.

[0138] 3. Data Analysis and Schedule Generation

[0139] The server analyzes the user's preferences and optimizes the order in which each attraction is visited. Taking into account break times and the planned time of departure, the server generates the following schedule:

[0140] 10:00 Roller Coaster

[0141] 11:00 Merry-go-round

[0142] 12:00 Break

[0143] 13:00 Ferris wheel

[0144] 4. Providing a schedule

[0145] The server transmits the generated schedule to the terminal, which displays it to the user in the form of a timetable.

[0146] 5. Real-time updates and notifications

[0147] For example, if the wait time for a roller coaster increases to 50 minutes, the device contacts the server and requests an updated schedule. The server recalculates the schedule based on the new data and sends it to the device. The device then notifies the user of the new schedule and clearly indicates the changes.

[0148] Prompt Sentence Examples

[0149] Below is an example of a prompt sentence to input to the generative AI model.

[0150] A family of four users (two adults and two children) goes to a theme park. Their favorite attractions are the roller coaster, merry-go-round, and Ferris wheel. They would like to take a one-hour break from noon, and plan to leave the park at 6:00 PM. Real-time data shows the waiting time for the roller coaster is 30 minutes, the merry-go-round is 15 minutes, the Ferris wheel is 20 minutes, and the weather is sunny. Based on this information, please generate the optimal schedule.

[0151] This system allows users to enjoy an efficient and comfortable theme park experience.

[0152] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0153] Step 1:

[0154] Collecting user input

[0155] Users enter information about their visit to the theme park into the device, including group information (number of people, age group), a list of favorite attractions, break times, and planned time to leave. The data is stored on the device and sent to a server for later analysis.

[0156] Input: Group information, attraction list, break times, planned departure time

[0157] Output: A dataset containing the user's input information

[0158] Step 2:

[0159] Real-time data collection

[0160] The server works with the theme park's management system to collect real-time data, such as waiting times for each attraction, operation status, weather information, and user travel time. This data is then analyzed. The server periodically calls the theme park's real-time data API to obtain the latest information.

[0161] Input: Real-time Data API endpoint

[0162] Output: Real-time data (waiting time, weather information, operation status, travel time)

[0163] Step 3:

[0164] Analyzing data and generating schedules

[0165] The server performs analysis based on the user's input information and real-time data. It first analyzes the user's desired information and sets the priority of each attraction. It then calculates the optimal order in which the attractions should be used based on the real-time data. For example, it uses Dijkstra's algorithm to calculate the shortest time for the entire route. The server uses an optimization algorithm to generate a schedule that meets the user's wishes.

[0166] Input: User input information, real-time data

[0167] Output: Optimized schedule

[0168] Step 4:

[0169] Schedule provision

[0170] The server sends the generated schedule to the terminal, which analyzes it and displays it to the user in the form of a timetable. A graphical interface is provided so that the user can check the schedule. A system is also included that notifies the user when the schedule is changed.

[0171] Input: Optimized schedule

[0172] Output: Schedule display in timetable format

[0173] Step 5:

[0174] Real-time updates and notifications

[0175] The terminal periodically communicates with the server to request updates with new real-time data. The server recalculates the schedule based on the latest data and sends the new schedule to the terminal. The terminal then notifies the user of the new schedule information and displays details of any changes. This allows the user to receive real-time information on changes in waiting times and attraction cancellations.

[0176] Input: Real-time data, schedule recalculation request

[0177] Output: Updated schedule, notification to users

[0178] The above is the specific process flow and the operations at each step. This system enables users to have an efficient and comfortable experience in the theme park.

[0179] (Application example 1)

[0180] 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."

[0181] The present invention relates to a schedule generation system for optimizing user experiences at commercial facilities such as theme parks. Conventional theme park systems have faced problems, such as difficulty in efficiently viewing attractions in the order desired by users, and waiting times and congestion can hinder efficient enjoyment. Similarly, physical stores such as shopping centers face the same problem of inconvenience caused by fluctuations in inventory information and congestion when users are trying to efficiently purchase products. In response to these problems, the present invention aims to solve common issues at theme parks and physical stores by combining user input information with real-time data.

[0182] 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.

[0183] In this invention, the server includes means for inputting user group information, favorite attractions, desired rest periods, and planned time of departure, means for collecting real-time data about the theme park, means for analyzing the user's input information and the real-time data to calculate an optimal order for visiting attractions, means for providing the user with a schedule based on the calculated order of visits, means for collecting inventory information and congestion information based on the data to calculate an optimal order for purchasing products, means for providing the user with a shopping schedule based on the optimal order for purchasing products, and means for updating the shopping schedule in real time and notifying the user. This enables efficient use of attractions in the theme park and efficient purchases at physical stores.

[0184] "User group information" refers to attribute information such as the number of people in the group to which the user belongs and their age group.

[0185] "Favorite attractions" refers to a list of attractions that the user particularly wishes to experience.

[0186] The "desired break time" is a time period designated in advance by the user during which the user wishes to take a break.

[0187] "Scheduled departure time" refers to the time when the user plans to leave the theme park.

[0188] "Real-time theme park data" refers to various data collected in real time within a theme park, such as waiting times for attractions and weather information.

[0189] "Inventory information" refers to information about the current inventory status of each product in the store.

[0190] "Crowd information" refers to information about the current congestion situation in each area of ​​a theme park or physical store.

[0191] The "optimal order of attractions" refers to the order in which a user can efficiently experience attractions, calculated based on the user's input information and real-time data.

[0192] The "optimal product purchasing order" is the order in which a user can efficiently purchase products, calculated based on inventory information and congestion information.

[0193] A "shopping schedule" is a schedule that includes the optimal order of purchasing products within a commercial facility, calculated based on user input information and real-time data.

[0194] "Means for real-time updates" refers to a mechanism in which the server recalculates the schedule based on new data and provides it to the user immediately.

[0195] The present invention relates to a system for optimizing user experiences at theme parks and brick-and-mortar stores. The system is implemented using the following hardware and software.

[0196] Hardware and software used

[0197] 1. User device: Smartphone (e.g. iPhone, Android Phone)

[0198] 2. Server: Cloud server (e.g. AWS, Google Cloud)

[0199] 3. Frontend: React Native, Flutter

[0200] 4. Backend: Python, Django / Flask

[0201] 5. Database: PostgreSQL

[0202] 6. Notification System: Firebase Cloud Messaging

[0203] System Overview

[0204] 1. Collecting user input information

[0205] Users use a smartphone app to input information such as group details, favorite attractions, desired rest times, and planned time to leave the park, which is then sent to a server and stored in a database.

[0206] 2. Real-time data collection

[0207] The server collects real-time data from IoT sensors in theme park management systems and physical stores, including wait times for each attraction, weather information, product availability, and congestion information for each area.

[0208] 3. Data Analysis and Schedule Generation

[0209] The server analyzes the user's input information and real-time data to calculate the optimal order of attractions and product purchases for the user. Specific algorithms used are shortest path algorithms such as Dijkstra's algorithm.

[0210] 4. Providing a schedule

[0211] The server generates a schedule, which is sent to a smartphone app and displayed to the user in the form of a timetable, which clearly indicates the order and times for each attraction and product purchase.

[0212] 5. Real-time updates and notifications

[0213] The smartphone app periodically communicates with the server to request updates on real-time information. The server recalculates the schedule based on the new real-time data and notifies the user of the updated schedule. This allows users to enjoy an optimal experience based on the most up-to-date information.

[0214] Specific examples

[0215] As an example, a case where a user efficiently shops at a physical store will be described.

[0216] 1. Collecting user input information

[0217] Using the app, users input a list of items they want to buy (e.g., milk, bread, eggs), group information (two adults, two children), and desired shopping time (e.g., two hours).

[0218] 2. Real-time data collection

[0219] The server collects real-time inventory information for each product and congestion information for each area of ​​the store from the store's management system and IoT sensors.

[0220] 3. Data Analysis and Schedule Generation

[0221] The server analyzes the user's input information and calculates the optimal product purchase order based on inventory and congestion information. For example, it uses Dijkstra's algorithm to generate a route that allows the user to efficiently obtain products.

[0222] 4. Providing a schedule

[0223] The server generates a schedule, which is sent to a smartphone app and displayed to the user in a timetable format. The schedule clearly indicates the time and order in which each item can be purchased.

[0224] 5. Real-time updates and notifications

[0225] For example, if bread stocks run low or a particular area of ​​the store becomes busy, the smartphone app communicates with the server and requests an updated schedule. The server recalculates the schedule based on the new data and sends it to the app. The app then notifies the user of the changed schedule, ensuring they receive instant updates.

[0226] Prompt Sentence Examples

[0227] Generate your shopping schedule using the following information:

[0228] User ID: 123

[0229] Group Information: 2 adults, 2 children

[0230] Shopping list: milk, bread, eggs

[0231] Likes: Electronics, toys

[0232] Desired shopping time: 2 hours

[0233] These steps allow users to enjoy an efficient and stress-free experience at theme parks and brick-and-mortar stores.

[0234] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0235] Step 1:

[0236] Collecting user input

[0237] Using a smartphone app, users input information about their group, their favorite attractions, desired rest time, planned time of departure, and a list of items they wish to purchase. The device temporarily stores this data and sends it to the server.

[0238] Input: User's group information, favorite attractions, desired rest time, planned departure time, list of items desired for purchase

[0239] Output: User data sent to the server

[0240] Step 2:

[0241] Real-time data collection for theme parks and brick-and-mortar stores

[0242] The server collects real-time data from the theme park's management system and IoT sensors in physical stores. This data includes waiting times for each attraction, weather information, product inventory status, and store congestion information. The server stores this data in a database.

[0243] Input: Real-time data from theme parks and physical stores (attraction waiting times, weather information, inventory status, crowd information)

[0244] Output: Real-time data stored in a database

[0245] Step 3:

[0246] Analyzing data and generating schedules

[0247] The server analyzes the user's input information and real-time data. Using shortest path algorithms such as Dijkstra's algorithm, it calculates the optimal order for the user to visit attractions and purchase products. Based on the analysis results, it generates a schedule and formats it into a timetable.

[0248] Input: User data, real-time data

[0249] Output: Schedule in timetable format

[0250] Step 4:

[0251] Schedule provision

[0252] The server sends the generated schedule to the smartphone app, which then displays it to the user. The timetable includes the order in which each attraction should be visited and the order and specific times for purchasing merchandise.

[0253] Input: Schedule data

[0254] Output: Timetable displayed on smartphone app

[0255] Step 5:

[0256] Real-time updates and notifications

[0257] The device periodically communicates with the server to request updates on real-time information. The server recalculates the schedule based on the new data and sends the updated schedule to the device. The device then uses its notification function to inform the user of the latest schedule.

[0258] Input: Updated real-time data, request data

[0259] Output: Updated schedule and notification information

[0260] These steps will ensure an efficient and comfortable experience at theme parks and brick-and-mortar stores.

[0261] 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.

[0262] The present invention is a system that generates a schedule taking into account a user's emotional state to optimize the user's theme park experience. The system provides an optimal order for visiting attractions based on user input information and real-time data, and further analyzes the user's emotional state using an emotion engine to optimize behavior.

[0263] Overview of program processing

[0264] Collecting user input

[0265] The user enters the following information through the terminal:

[0266] Group information (number of people, age group, etc.)

[0267] A list of favorite attractions

[0268] Break time requests

[0269] Scheduled departure time

[0270] Real-time data collection

[0271] The server collects the following data in real time from the theme park's management system and API:

[0272] Waiting times for each attraction

[0273] Weather information

[0274] Travel time based on walking speed

[0275] Emotion recognition by emotion engine

[0276] The device's built-in emotion engine recognizes the user's emotional state in real time from their facial expressions and voice, and this information is sent to the server via an API.

[0277] Analyzing data and generating schedules

[0278] The server generates a schedule based on user input, real-time data, and emotion data from the emotion engine in the following steps:

[0279] Analyze the user's desired information and set priorities.

[0280] The optimal order of attraction use is calculated based on real-time data and emotional state (e.g., Dijkstra algorithm).

[0281] Adjust the overall schedule to take into account break times, planned dismissal times, and emotional states.

[0282] Schedule provision

[0283] The server sends the generated schedule to the terminal, which then displays it to the user. The schedule is provided in the form of a timetable, clearly indicating the attractions to visit during each time period and break times.

[0284] Real-time updates and notifications

[0285] The device periodically communicates with the server to request real-time information updates.

[0286] The server recalculates the schedule based on new real-time data and the emotional state of the emotion engine, and sends any necessary changes to the device.

[0287] The device notifies users of updates and highlights schedule changes, allowing users to instantly receive real-time information on wait times, attraction cancellations, emotion-based suggestions, and more.

[0288] Specific examples

[0289] For families

[0290] As an example, a case where a family uses the system will be described.

[0291] 1. Collecting user input information

[0292] A family of four users (two adults and two children) enters information into the terminal.

[0293] His favorite attractions are roller coasters, merry-go-rounds, and Ferris wheels.

[0294] We would like to have a one-hour break from 12:00, and plan to leave the school at 18:00.

[0295] 2. Real-time data collection

[0296] The server collects real-time data from the theme park's management system, such as waiting times for roller coasters: 30 minutes, merry-go-rounds: 15 minutes, and ferris wheels: 20 minutes.

[0297] 3. Emotion Recognition by Emotion Engine

[0298] The emotion engine recognizes the user's emotional state from their facial expressions and voice and sends it to the server via API. For example, if a child is recognized as tired, that information is conveyed to the server.

[0299] 4. Data Analysis and Schedule Generation

[0300] The server analyzes the user's desired information, real-time data, and emotional state to optimize the order in which each attraction is used.

[0301] Taking into account break times, expected departure times, and emotional states, we generate a schedule like this:

[0302] 10:00 Roller Coaster

[0303] 11:00 Merry-go-round

[0304] 12:00 Break (Consider children's fatigue and suggest a relaxing rest area)

[0305] 13:00 Ferris wheel

[0306] 5. Providing a schedule

[0307] The terminal displays the generated schedule to the user with family, providing it in the form of a timetable.

[0308] 6. Real-time updates and notifications

[0309] For example, if the wait time for a roller coaster increases to 50 minutes, the device will contact the server and request an updated schedule.

[0310] The server recalculates the schedule based on the new data and emotional state and sends it to the device.

[0311] The device will notify the user of the new schedule and clearly indicate the changes.

[0312] The above is an embodiment of the present invention, and this system allows users to enjoy an efficient and comfortable theme park experience. By adding an emotion recognition function using an emotion engine, flexible suggestions and schedule adjustments based on the user's emotional state become possible, making it possible to provide even more personalized services.

[0313] The processing flow will be explained below.

[0314] Step 1:

[0315] The terminal displays an input form to the user. The user enters group information (number of people, age group, etc.), a list of favorite attractions, desired break time, and planned departure time. When the user finishes entering information, he or she presses the submit button.

[0316] Step 2:

[0317] The device sends the information entered by the user to the server. The data sent is in structured JSON format.

[0318] Step 3:

[0319] The server collects real-time data from the theme park's management system and APIs, including wait times for each attraction, weather information, and travel times based on walking speed.

[0320] Step 4:

[0321] The emotion engine installed in the device recognizes the user's emotional state in real time from their facial expressions and voice. The emotion engine uses sensor devices such as cameras and microphones to acquire the user's emotional data.

[0322] Step 5:

[0323] The device transmits the emotion data acquired by the emotion engine to the server, and the transmitted data is also in a structured format.

[0324] Step 6:

[0325] The server analyzes the input information from the user, real-time data, and emotional data from the emotion engine. It combines the user's wishes with the real-time data and emotional state to set the priority of each attraction.

[0326] Step 7:

[0327] The server calculates the optimal order in which to visit attractions, and optimizes the user's schedule using route optimization algorithms such as the Greedy algorithm and Dijkstra algorithm.

[0328] Step 8:

[0329] The server generates an optimal schedule based on the calculation results. The generated schedule includes designated break times and planned departure times, and also takes into account the user's emotional state.

[0330] Step 9:

[0331] The server generates a schedule and sends it to the terminal. The schedule is in a clear and easy-to-understand timetable format.

[0332] Step 10:

[0333] The device displays a schedule to the user, who then moves around the theme park and enjoys the attractions based on the schedule. During this time, the device continues to monitor the user's emotional state in real time.

[0334] Step 11:

[0335] The device periodically requests the latest real-time and emotional data from the server to keep the schedule updated according to waiting times, weather fluctuations, and changes in emotional state.

[0336] Step 12:

[0337] The server recalculates the schedule based on new real-time data and emotion data, and sends the updated schedule to the device as needed.

[0338] Step 13:

[0339] The device notifies users of schedule updates, for example, via push notifications or alerts, allowing users to react quickly to changes, enabling users to enjoy an optimal theme park experience based on their emotional state.

[0340] Example 2

[0341] 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."

[0342] When visiting a theme park, it is necessary to automatically generate and provide an efficient and comfortable schedule that comprehensively considers a user's group information, favorite attractions, real-time wait times, weather, and the user's emotional state. Conventional systems have difficulty combining these various factors, often forcing users to struggle with cumbersome procedures and schedule adjustments. In particular, the lack of real-time updates and optimization based on emotional state makes it difficult to provide a satisfying user experience.

[0343] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0344] In this invention, the server includes means for inputting user group information, favorite attractions, desired rest periods, and planned time of departure, means for collecting real-time data from the theme park, means for analyzing the user's emotional state using an emotion recognition engine installed in the terminal, means for analyzing the user's input information, the real-time data, and the emotional state and calculating an optimal order for visiting attractions, and means for providing the user with a schedule based on the calculated order of visiting attractions. This makes it possible to provide an efficient and comfortable theme park experience that takes into account the diverse needs and situations of users.

[0345] "User group information" is information about the people accompanying the user when visiting a theme park, including the number of people and their age groups.

[0346] "Favorite Attractions" is a list of attractions within the theme park that the user would like to visit.

[0347] "Desired rest time" refers to the time period and length of time during which the user desires to rest in the theme park.

[0348] The "planned time of departure" is the time when the user plans to leave the theme park.

[0349] "Real-time theme park data" refers to data that is collected instantly, such as waiting times for attractions within the theme park, weather information, and travel times based on walking speed.

[0350] An "emotion recognition engine" is a software or hardware mechanism that is installed on a device and analyzes the user's facial expressions and voice to recognize their emotional state.

[0351] A "schedule" is a plan that summarizes attractions to visit, rest times, etc. in the form of a timetable so that the user can visit the theme park efficiently and comfortably.

[0352] "Providing a schedule" is the process in which the server sends the generated schedule to the terminal so that the user can check it.

[0353] This invention is a system that generates a schedule taking into account the user's emotional state in order to optimize the user's theme park experience. The entire system consists of a server, a terminal, and an emotion recognition engine.

[0354] Collecting user input

[0355] The user inputs group information (number of people, age group, etc.), a list of favorite attractions, desired rest time, and planned time to leave the park through the terminal. The terminal then transmits this input information to the server.

[0356] Real-time data collection

[0357] The server collects real-time data via the theme park's management system and API, including:

[0358] Waiting times for each attraction

[0359] Weather information

[0360] Travel time based on walking speed

[0361] Emotion recognition by emotion engine

[0362] The emotion recognition engine installed in the device recognizes the user's facial expressions and voice in real time. This recognition data is sent to the server via API. The emotion recognition engine includes facial expression analysis software and voice analysis software.

[0363] Analyzing data and generating schedules

[0364] The server analyzes user input, real-time data, and emotion data obtained from an emotion recognition engine all at once. Based on this analysis, it sets priorities and uses an algorithm (e.g., Dijkstra algorithm) to determine the optimal order in which attractions should be used. Furthermore, it adjusts the overall schedule, taking into account break times, planned departure times, and the user's emotional state.

[0365] Schedule provision

[0366] The schedule generated by the server is sent to the terminal and displayed to the user in the form of a timetable, allowing the user to easily check the attractions to be visited and break times via their smartphone or tablet.

[0367] Real-time updates and notifications

[0368] The device periodically communicates with the server to request new real-time information. The server recalculates the schedule based on the latest real-time data and emotion data. If necessary, the server sends a new schedule to the device, which then notifies the user of the updated information. This allows users to instantly receive information such as real-time changes in waiting times, attraction cancellations, and suggestions based on the user's emotions.

[0369] Specific examples

[0370] For families

[0371] A family of users (two adults and two children) visiting a theme park uses the system as follows:

[0372] 1. Collecting input information: Log in to the terminal and enter the number of people in your family, your favorite attraction (roller coaster, merry-go-round, Ferris wheel), break time (1 hour from 12 noon), and planned time to leave the park (6 p.m.).

[0373] 2. Real-time data collection: The server collects the waiting time for each attraction (e.g., 30 minutes for roller coaster, 15 minutes for merry-go-round, 20 minutes for Ferris wheel) in real time from the theme park's management system.

[0374] 3. Emotion recognition: The device camera captures the child's facial expression, and the emotion recognition engine recognizes "fatigue." This data is sent to the server.

[0375] 4. Schedule Generation: Based on this data, the server calculates the order in which each attraction should be visited and generates the following schedule:

[0376] 10:00 Roller Coaster

[0377] 11:00 Merry-go-round

[0378] 12:00 Break (Area for children to relax as they are tired)

[0379] 13:00 Ferris wheel

[0380] 5. Providing the schedule: The terminal displays the generated schedule to the user in the form of a timetable.

[0381] 6. Real-time updates and notifications: Devices periodically communicate with the server and schedules are updated based on new data. For example, if the waiting time for a roller coaster changes to 50 minutes, a new schedule will be generated.

[0382] Prompt Sentence Examples

[0383] Here are some examples of prompts to input to the generative AI model:

[0384] "Generate an example of a day's schedule for a family (2 adults, 2 children) at a theme park based on the following information: roller coaster (wait time 30 minutes), merry-go-round (wait time 15 minutes), ferris wheel (wait time 20 minutes). The emotion engine recognizes that the children are tired. The break time is 1 hour from 12 noon, and the planned departure time is 6:00 PM."

[0385] The above is an embodiment of the present invention, and this system allows users to enjoy an efficient and comfortable theme park experience. By using an emotion recognition engine, flexible suggestions and schedule adjustments based on the user's emotional state can be made, and more personalized services can be provided.

[0386] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0387] Step 1: Collecting User Input

[0388] 1. Start typing:

[0389] Users launch the application on their device and log in using their account information. They input information such as the number of people in their family or group, their age group, a list of their favorite attractions, desired rest times, and the planned time to leave the park.

[0390] Input: User's demographic information, desired attraction, break time, and departure time

[0391] Output: The input information is sent to the server

[0392] Step 2: Collect real-time data

[0393] 1. Data Request:

[0394] The server sends data requests to the theme park's management system and API, specifically requesting wait times for each attraction, weather information, and predicted travel times based on walking speed.

[0395] Input: Server data request

[0396] Output: Real-time data from theme park management systems

[0397] 2. Data Collection:

[0398] The server receives real-time data such as waiting times, weather information, and travel times from the management system or API and stores it in a database.

[0399] Input: Real-time data

[0400] Output: Real-time data stored in a database

[0401] Step 3: Emotion recognition by the emotion engine

[0402] 1. Emotional data collection:

[0403] The device's camera and microphone are used to capture the user's facial expressions and voice, and this data is fed into the emotion engine.

[0404] Input: Real-time user facial and voice data

[0405] Output: Raw data sent to the sentiment engine

[0406] 2. Sentiment analysis:

[0407] The emotion engine analyzes the captured data and recognizes the user's emotional state, for example, detecting a smile indicates "happiness" and a frown indicates "fatigue."

[0408] Input: Raw data (facial expressions and voice)

[0409] Output: Perceived emotional state

[0410] 3. Emotional data transmission:

[0411] The device sends the recognized emotion data to the server via API.

[0412] Input: Recognized emotion data

[0413] Output: Emotion data sent to the server

[0414] Step 4: Analyze data and generate a schedule

[0415] 1. Data Integration:

[0416] The server integrates user input information, real-time data, and emotional data, enabling comprehensive analysis.

[0417] Input: User input, real-time data, emotional data

[0418] Output: A consolidated dataset

[0419] 2. Priority settings:

[0420] The server sets priorities for attractions based on the user's desired information.

[0421] Input: Integrated dataset

[0422] Output: A prioritized list of attractions

[0423] 3. Schedule optimization:

[0424] The server uses algorithms such as Dijkstra's algorithm to calculate the optimal order in which to visit attractions, thereby minimizing waiting times and travel times.

[0425] Input: Attraction priority list, consolidated data

[0426] Output: Optimized attraction usage order

[0427] 4. Overall schedule adjustment:

[0428] The server adjusts the overall schedule taking into account break times, departure times, and the user's emotional state, for example, by shortening break times based on the user's emotional state.

[0429] Input: Optimized attraction order, user's desired time

[0430] Output: Adjusted overall schedule

[0431] Step 5: Provide a schedule

[0432] 1. Schedule generation:

[0433] The server creates an optimized and coordinated schedule, including attractions to visit, break times, travel times, etc.

[0434] Input: Adjusted overall schedule

[0435] Output: The generated schedule

[0436] 2. Data transmission:

[0437] The server transmits the generated schedule to the terminal.

[0438] Input: Generated schedule

[0439] Output: Schedule sent to the terminal

[0440] 3.Display:

[0441] The terminal displays the received schedule in a timetable format to the user, allowing the user to check the attractions to be visited and break times.

[0442] Input: Schedule sent to the terminal

[0443] Output: The schedule as seen by the user

[0444] Step 6: Real-time updates and notifications

[0445] 1. Regular communication:

[0446] The device periodically communicates with the server to request updates on the latest real-time data and emotion data.

[0447] Input: Update request

[0448] Output: Latest data

[0449] 2. Recalculate the schedule:

[0450] The server recalculates the existing schedule based on new real-time data and emotion data, and generates new schedules as needed.

[0451] Input: Latest real-time data, sentiment data

[0452] Output: Recalculated schedule

[0453] 3. Schedule Update:

[0454] The server transmits the newly generated schedule to the terminal.

[0455] Input: Recalculated schedule

[0456] Output: Update schedule sent to the device

[0457] 4. Notice:

[0458] The device notifies the user of schedule changes, allowing the user to take action based on the latest situation.

[0459] Input: Updated schedule

[0460] Output: Changes notified to the user

[0461] These are the processing steps of the system's program. It is possible to provide an optimal schedule by comprehensively analyzing user input, real-time data, and emotional data. This process allows users to enjoy an efficient and comfortable theme park experience.

[0462] (Application example 2)

[0463] 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."

[0464] Modern theme parks and shopping malls are required to provide optimal experiences for visitors. However, conventional systems have difficulty not only taking real-time information into account but also flexibly adjusting schedules based on the user's emotional state. This often leads to stress and a disappointing experience for users. It has also been difficult to accurately predict congestion and waiting times at theme parks and shopping malls and suggest optimal routes and stores. To solve these problems, a system is needed that can analyze users' real-time behavior and emotions in an integrated manner and provide optimal schedules.

[0465] 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 inputting a user's group information, favorite attractions, desired rest time, and planned departure time, means for collecting real-time data about the theme park, means for analyzing the user's input information and the real-time data and calculating an optimal order for visiting attractions, means for providing the user with a schedule based on the calculated order of visits, means for recognizing the user's emotional state in real time and optimizing the schedule based on the emotional state, and means for providing a shopping route based on real-time store information from online stores and the user's emotional state. This enables the user to have an optimal theme park experience and shopping experience tailored to their emotional state.

[0466] "User group information" is information about the entire group, such as the number of users and their age groups.

[0467] "Favorite attractions" is a list of attractions in which the user has particular interests or concerns.

[0468] "Desired break time" is information about the specific time or period when the user wishes to take a break.

[0469] The "planned time of departure" is the time when the user plans to leave the theme park.

[0470] "Real-time theme park data" refers to the latest information about theme parks, such as current wait times for attractions, weather information, and walking speeds.

[0471] "Emotional state" refers to the current emotion recognized from the user's facial expression and voice, and includes, for example, stress level and fatigue level.

[0472] A "shopping route" is an optimal route for a user to efficiently navigate around a shopping mall or store.

[0473] "Real-time updates" means constantly updating systems and data based on the latest information.

[0474] The present invention is a system for optimizing a user's theme park and shopping experience. The system analyzes a user's input information, real-time data, and emotional state to provide optimal attractions and shopping routes. The following description details a specific embodiment of the system.

[0475] 1. Collecting user input information

[0476] The device (e.g. smartphone or tablet) collects the following information from the user:

[0477] Group information (number of people, age group, etc.)

[0478] A list of your favorite attractions and products

[0479] Break time requests

[0480] Scheduled time of leaving the park or store

[0481] 2. Real-time data collection

[0482] The server collects the following real-time data from the theme park and shopping mall management systems and public APIs:

[0483] Waiting times for each attraction

[0484] Current Weather Information

[0485] Store congestion status and sales information

[0486] Travel time based on user walking speed

[0487] 3. Emotion Recognition by Emotion Engine

[0488] An emotion engine (specifically, the EmotionEngine library) installed on the device recognizes the user's emotional state in real time from their facial expressions and voice. This information is sent to the server via an API. For example, if the user is tired or stressed, that information is communicated to the server.

[0489] 4. Data Analysis and Optimization

[0490] The server generates the optimal order of attractions and shopping routes based on the user's input information, collected real-time data, and emotion data from the emotion engine. This includes the following steps:

[0491] Analyze user preferences and set priorities

[0492] Calculate the optimal order of attractions and stores based on real-time data and emotional state (e.g., Dijkstra algorithm)

[0493] Adjust the overall schedule taking into account break times and planned departure times

[0494] 5. Providing a schedule

[0495] The server generates a schedule and sends it to the device, which then displays it to the user in the form of a timetable, clearly indicating the attractions and shops to visit during each time period, as well as break times.

[0496] 6. Real-time updates and notifications

[0497] The device periodically communicates with the server to request updates of real-time information. The server recalculates the schedule based on the new real-time data and the emotional state of the emotion engine, and sends any necessary changes to the device, allowing the user to see the changes immediately.

[0498] Specific examples

[0499] For families

[0500] 1. Collection of information:

[0501] A family of four users enters information into the terminal. They select roller coaster, merry-go-round, and Ferris wheel as their preferred attractions. They request a one-hour break from 12:00 and plan to leave the park at 18:00.

[0502] 2. Real-time data:

[0503] The waiting time for the roller coaster is 30 minutes, the merry-go-round is 15 minutes, and the Ferris wheel is 20 minutes.

[0504] 3. Emotional state:

[0505] The emotion engine recognizes fatigue from the user's facial expression.

[0506] 4. Optimization:

[0507] The server generates a schedule and sets the roller coaster at 10:00, the merry-go-round at 11:00, the break at 12:00, and the Ferris wheel at 13:00.

[0508] 5.Display:

[0509] It displays the timetable on the device and sends necessary notifications.

[0510] Prompt Sentence Examples

[0511] Write Python code that takes into account unique user information, real-time data, and emotion recognition results to provide an optimal shopping experience schedule. The schedule includes the following items: time, store name, and wait time. Using the user's preferred categories and their real-time data, suggest appropriate break times based on the user's emotional state.

[0512] The above is a specific embodiment of the present invention. This system enables flexible schedule adjustment based on the user's emotional state, providing a more comfortable and efficient experience.

[0513] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0514] Step 1:

[0515] The terminal collects input information from the user, such as group information (number of people, age group), a list of favorite attractions, desired rest periods, and planned departure time. This information serves as the basis for the system to understand the user's preferences and plans and generate a personalized schedule.

[0516] Input: Number of users, age group, list of favorite attractions, desired break time, planned time to leave the park

[0517] Output: A dataset of user-entered information

[0518] Specific behavior:

[0519] The terminal displays an information input form through a user interface.

[0520] The user enters the required information into the form and presses the "Submit" button.

[0521] The terminal collects the input information and sends it to the server as a data set.

[0522] Step 2:

[0523] The server collects real-time data from theme parks and shopping malls, including attraction wait times, weather information, store occupancy and sales information, and user walking speeds. This data is collected using APIs.

[0524] Input: Theme park and shopping mall APIs

[0525] Output: Real-time data

[0526] Specific behavior:

[0527] The server periodically sends requests to the API to retrieve the latest real-time data.

[0528] The collected data is organized on the server and prepared for analysis.

[0529] Step 3:

[0530] The device's built-in emotion engine recognizes the user's emotional state in real time from their facial expressions and voice. This information is sent to the server via an API. For example, the user's fatigue level and stress level can be recognized.

[0531] Input: User's facial expressions and voice data

[0532] Output: Emotional state data

[0533] Specific behavior:

[0534] The device's camera and microphone are used to collect the user's facial expressions and voice.

[0535] An emotion engine (such as the EmotionEngine library) analyzes this data and identifies the emotional state.

[0536] The recognized emotional state data is transmitted to a server.

[0537] Step 4:

[0538] The server analyzes user input, real-time data, and emotional data to generate the optimal order of attractions and shopping routes, using algorithms such as Dijkstra's algorithm.

[0539] Input: User-entered information, real-time data, emotional state data

[0540] Output: Optimal schedule (order of attractions, shopping route)

[0541] Specific behavior:

[0542] The server integrates the various collected data and runs optimization algorithms.

[0543] The optimal order of use is calculated taking into account the waiting time at each attraction and store, the level of congestion, and the user's emotional state.

[0544] Adjust the overall schedule, taking into account break times and planned dismissal times.

[0545] Step 5:

[0546] The server transmits the generated schedule to the terminal, which displays it to the user in the form of a timetable.

[0547] Input: Optimal schedule

[0548] Output: Schedule display in timetable format

[0549] Specific behavior:

[0550] The server transmits the generated schedule data to the terminal.

[0551] The terminal visually displays the schedule in a timetable format, allowing users to act based on this display.

[0552] Step 6:

[0553] The device periodically communicates with the server to request real-time updates. The server recalculates the schedule based on the new data and emotional state, and sends any necessary changes to the device, where the user can immediately see the changes.

[0554] Input: Regular real-time data and emotional state data

[0555] Output: Updated schedule

[0556] Specific behavior:

[0557] The terminal requests real-time data updates from the server at regular intervals.

[0558] The server retrieves the new data and analyzes the emotional state again.

[0559] Recalculate the schedule as needed and send updates to the terminal.

[0560] The terminal notifies the user of the updated schedule and displays the changes.

[0561] The above are the specific processing steps in the program of the system of the present invention, which allows the user to always have the most optimal theme park and shopping experience based on the latest information and emotional state.

[0562] 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.

[0563] 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.

[0564] 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.

[0565] [Second embodiment]

[0566] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0567] 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.

[0568] 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).

[0569] 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.

[0570] 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.

[0571] 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).

[0572] 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.

[0573] 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.

[0574] 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.

[0575] 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.

[0576] 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.

[0577] 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."

[0578] The present invention is a system for optimizing a user's theme park experience by combining input information from the user with theme park data collected in real time to provide an efficient schedule. This system is realized through the cooperation of terminals and a server.

[0579] Overview of program processing

[0580] Collecting user input

[0581] The user enters the following information through the terminal:

[0582] Group information (number of people, age group, etc.)

[0583] A list of favorite attractions

[0584] Break time requests

[0585] Scheduled departure time

[0586] Real-time data collection

[0587] The server will interface with the theme park's management system and collect the following data in real time:

[0588] Waiting times for each attraction

[0589] Weather information

[0590] Travel time based on walking speed

[0591] Analyzing data and generating schedules

[0592] The server generates a schedule based on user input and real-time data in the following steps:

[0593] Analyze the user's desired information and set priorities.

[0594] Calculate the optimal order for visiting attractions based on real-time data (e.g., Dijkstra algorithm).

[0595] Adjust the overall schedule taking into account break times and planned departure times.

[0596] Schedule provision

[0597] The server sends the generated schedule to the terminal, which then displays it to the user. The schedule is provided in the form of a timetable, clearly indicating the attractions to visit during each time period and break times.

[0598] Real-time updates and notifications

[0599] The device periodically communicates with the server to request real-time information updates.

[0600] The server recalculates the schedule based on the new real-time data and sends any necessary changes to the terminal.

[0601] The device notifies users of updates and clearly shows any changes to the schedule, allowing users to receive real-time information on changes in wait times, attraction cancellations, and more.

[0602] Specific examples

[0603] For families

[0604] As an example, a case where a family uses the system will be described.

[0605] 1. Collecting user input information

[0606] The user inputs information into the terminal that the user is a family of four (two adults and two children).

[0607] His favorite attractions are roller coasters, merry-go-rounds, and Ferris wheels.

[0608] We would like to have a one-hour break from 12:00, and plan to leave the school at 18:00.

[0609] 2. Real-time data collection

[0610] The server collects real-time data from the theme park's management system, such as waiting times for roller coasters: 30 minutes, merry-go-rounds: 15 minutes, and ferris wheels: 20 minutes.

[0611] 3. Data Analysis and Schedule Generation

[0612] The server analyzes the user's desired information and optimizes the order in which each attraction is visited.

[0613] Taking into account break times and planned departure times, we generate a schedule like this:

[0614] 10:00 Roller Coaster

[0615] 11:00 Merry-go-round

[0616] 12:00 Break

[0617] 13:00 Ferris wheel

[0618] 4. Providing a schedule

[0619] The terminal displays the generated schedule to the user with family, providing it in the form of a timetable.

[0620] 5. Real-time updates and notifications

[0621] For example, if the wait time for a roller coaster increases to 50 minutes, the device will contact the server and request an updated schedule.

[0622] The server recalculates the schedule based on the new data and sends it to the terminal.

[0623] The device will notify the user of the new schedule and clearly indicate the changes.

[0624] The above is an embodiment of the present invention, and this system allows users to enjoy an efficient and comfortable theme park experience.

[0625] The processing flow will be explained below.

[0626] Step 1:

[0627] The terminal displays an input form to the user. The user enters group information (number of people, age group, etc.), a list of favorite attractions, desired break time, and planned departure time. When the user finishes entering information, he or she presses the submit button.

[0628] Step 2:

[0629] The device sends the information entered by the user to the server. The data sent is in structured JSON format.

[0630] Step 3:

[0631] The server collects real-time data from the theme park's management system and APIs, including wait times for each attraction, weather information, and travel times based on walking speed.

[0632] Step 4:

[0633] The server analyzes the input information from the user and the collected real-time data, and sets the priority of each attraction by linking the user's preferences with the real-time data.

[0634] Step 5:

[0635] The server calculates the optimal order in which to visit attractions, and optimizes the user's schedule using route optimization algorithms such as the Greedy algorithm and Dijkstra algorithm.

[0636] Step 6:

[0637] The server generates an optimal schedule based on the calculation results, which incorporates the specified break times and planned departure times.

[0638] Step 7:

[0639] The server generates a schedule and sends it to the terminal. The schedule is in a clear and easy-to-understand timetable format.

[0640] Step 8:

[0641] The terminal displays the schedule to the user, who then moves around the theme park according to the schedule and enjoys the attractions.

[0642] Step 9:

[0643] The device periodically requests the latest real-time data from the server to ensure the schedule is up-to-date with fluctuations in waiting times and weather.

[0644] Step 10:

[0645] The server recalculates the schedule based on new real-time data and sends the updated schedule to the device as needed.

[0646] Step 11:

[0647] The device notifies the user of schedule updates, for example, via push notifications or alerts, so that the user can respond quickly.

[0648] Example 1

[0649] 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."

[0650] In traditional theme park experiences, users had to check attraction wait times, weather, and travel times themselves, and then create a schedule based on that information. However, it was difficult to manually check and appropriately reflect this data, which fluctuates in real time, making efficient scheduling difficult. In particular, for large groups such as families, it is not easy to efficiently move around while satisfying everyone's wishes. This resulted in a decline in the quality of the user experience.

[0651] 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.

[0652] In this invention, the server includes means for inputting user group information, favorite video content, desired break times, and scheduled end times, means for collecting real-time data about the theme park, means for analyzing the user's input information and the real-time data and calculating an optimal video content viewing order, means for providing the user with a schedule based on the calculated viewing order, and means for updating and notifying the user of the schedule in real time via the user's terminal, thereby enabling the user to automatically receive an optimized schedule in real time and efficiently tour the theme park.

[0653] "User" refers to an individual or group who uses the theme park.

[0654] "Group information" refers to data including information such as the number of users, age range, and relationships.

[0655] "Favorite video content" refers to the types and lists of attractions and shows that the user wishes to view.

[0656] "Rest time" refers to a period of time set by the user for rest during their visit to the theme park.

[0657] "Scheduled end time" refers to the time the user plans to leave the theme park.

[0658] "Real-time theme park data" refers to the latest information at the moment, such as waiting times for each attraction within the theme park, operation status, weather information, and user travel times.

[0659] "Server" refers to a computer system that processes user input information and real-time data, and generates and manages optimal schedules.

[0660] "Terminal" refers to a device that allows a user to input information and view a generated schedule.

[0661] "Schedule" refers to an optimized theme park tour plan based on user preferences and real-time data.

[0662] "Viewing order" refers to the optimal order in which attractions and shows are viewed, calculated based on user preferences and real-time data.

[0663] "Notification" refers to the act of sending the latest schedule changes and alerts from the server to the user via the device.

[0664] The present invention is a system for optimizing a user's theme park experience by combining input information from the user with theme park data collected in real time to provide an efficient schedule. This system is realized through the cooperation of terminals and a server.

[0665] Specifically, users use their devices to input group information (number of people, age group, etc.), a list of their favorite attractions, desired rest times, and planned time to leave the park. This information is sent from the devices to the server. The server collects real-time data from the theme park's management system and weather information API. This real-time data includes waiting times for each attraction, operation status, weather information, and travel times based on the user's walking speed.

[0666] The server analyzes the input information sent by the user and the collected real-time data, and optimizes the order in which the attractions can be visited based on the user's preferences. For example, it calculates the optimal order using an algorithm such as Dijkstra's algorithm. The generated schedule is sent from the server to the terminal, which displays it to the user in the form of a timetable.

[0667] The terminal also periodically communicates with the server to request updates to real-time information. The server recalculates the schedule based on the latest real-time data and, if necessary, sends the revised schedule to the terminal. The terminal then notifies the user of the updated information and clearly indicates any changes to the schedule. This allows the user to immediately receive information on real-time changes in waiting times, attraction cancellations, and other such information.

[0668] Specific examples

[0669] Families can use the system by following these steps:

[0670] 1. Collecting user input information

[0671] The user inputs information into the terminal that the user is a family of four (two adults and two children).

[0672] His favorite attractions are roller coasters, merry-go-rounds, and Ferris wheels.

[0673] We would like to have a one-hour break from 12:00, and plan to leave the school at 18:00.

[0674] 2. Real-time data collection

[0675] The server collects real-time data from the theme park's management system, such as waiting times for roller coasters: 30 minutes, merry-go-rounds: 15 minutes, and ferris wheels: 20 minutes.

[0676] Also, sunny weather data is acquired as weather information.

[0677] 3. Data Analysis and Schedule Generation

[0678] The server analyzes the user's preferences and optimizes the order in which each attraction is visited. Taking into account break times and the planned time of departure, the server generates the following schedule:

[0679] 10:00 Roller Coaster

[0680] 11:00 Merry-go-round

[0681] 12:00 Break

[0682] 13:00 Ferris wheel

[0683] 4. Providing a schedule

[0684] The server transmits the generated schedule to the terminal, which displays it to the user in the form of a timetable.

[0685] 5. Real-time updates and notifications

[0686] For example, if the wait time for a roller coaster increases to 50 minutes, the device contacts the server and requests an updated schedule. The server recalculates the schedule based on the new data and sends it to the device. The device then notifies the user of the new schedule and clearly indicates the changes.

[0687] Prompt Sentence Examples

[0688] Below is an example of a prompt sentence to input to the generative AI model.

[0689] A family of four users (two adults and two children) goes to a theme park. Their favorite attractions are the roller coaster, merry-go-round, and Ferris wheel. They would like to take a one-hour break from noon, and plan to leave the park at 6:00 PM. Real-time data shows the waiting time for the roller coaster is 30 minutes, the merry-go-round is 15 minutes, the Ferris wheel is 20 minutes, and the weather is sunny. Based on this information, please generate the optimal schedule.

[0690] This system allows users to enjoy an efficient and comfortable theme park experience.

[0691] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0692] Step 1:

[0693] Collecting user input

[0694] Users enter information about their visit to the theme park into the device, including group information (number of people, age group), a list of favorite attractions, break times, and planned time to leave. The data is stored on the device and sent to a server for later analysis.

[0695] Input: Group information, attraction list, break times, planned departure time

[0696] Output: A dataset containing the user's input information

[0697] Step 2:

[0698] Real-time data collection

[0699] The server works with the theme park's management system to collect real-time data, such as waiting times for each attraction, operation status, weather information, and user travel time. This data is then analyzed. The server periodically calls the theme park's real-time data API to obtain the latest information.

[0700] Input: Real-time Data API endpoint

[0701] Output: Real-time data (waiting time, weather information, operation status, travel time)

[0702] Step 3:

[0703] Analyzing data and generating schedules

[0704] The server performs analysis based on the user's input information and real-time data. It first analyzes the user's desired information and sets the priority of each attraction. It then calculates the optimal order in which the attractions should be used based on the real-time data. For example, it uses Dijkstra's algorithm to calculate the shortest time for the entire route. The server uses an optimization algorithm to generate a schedule that meets the user's wishes.

[0705] Input: User input information, real-time data

[0706] Output: Optimized schedule

[0707] Step 4:

[0708] Schedule provision

[0709] The server sends the generated schedule to the terminal, which analyzes it and displays it to the user in the form of a timetable. A graphical interface is provided so that the user can check the schedule. A system is also included that notifies the user when the schedule is changed.

[0710] Input: Optimized schedule

[0711] Output: Schedule display in timetable format

[0712] Step 5:

[0713] Real-time updates and notifications

[0714] The terminal periodically communicates with the server to request updates with new real-time data. The server recalculates the schedule based on the latest data and sends the new schedule to the terminal. The terminal then notifies the user of the new schedule information and displays details of any changes. This allows the user to receive real-time information on changes in waiting times and attraction cancellations.

[0715] Input: Real-time data, schedule recalculation request

[0716] Output: Updated schedule, notification to users

[0717] The above is the specific process flow and the operations at each step. This system enables users to have an efficient and comfortable experience in the theme park.

[0718] (Application example 1)

[0719] 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."

[0720] The present invention relates to a schedule generation system for optimizing user experiences at commercial facilities such as theme parks. Conventional theme park systems have faced problems, such as difficulty in efficiently viewing attractions in the order desired by users, and waiting times and congestion can hinder efficient enjoyment. Similarly, physical stores such as shopping centers face the same problem of inconvenience caused by fluctuations in inventory information and congestion when users are trying to efficiently purchase products. In response to these problems, the present invention aims to solve common issues at theme parks and physical stores by combining user input information with real-time data.

[0721] 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.

[0722] In this invention, the server includes means for inputting user group information, favorite attractions, desired rest periods, and planned time of departure, means for collecting real-time data about the theme park, means for analyzing the user's input information and the real-time data to calculate an optimal order for visiting attractions, means for providing the user with a schedule based on the calculated order of visits, means for collecting inventory information and congestion information based on the data to calculate an optimal order for purchasing products, means for providing the user with a shopping schedule based on the optimal order for purchasing products, and means for updating the shopping schedule in real time and notifying the user. This enables efficient use of attractions in the theme park and efficient purchases at physical stores.

[0723] "User group information" refers to attribute information such as the number of people in the group to which the user belongs and their age group.

[0724] "Favorite attractions" refers to a list of attractions that the user particularly wishes to experience.

[0725] The "desired break time" is a time period designated in advance by the user during which the user wishes to take a break.

[0726] "Scheduled departure time" refers to the time when the user plans to leave the theme park.

[0727] "Real-time theme park data" refers to various data collected in real time within a theme park, such as waiting times for attractions and weather information.

[0728] "Inventory information" refers to information about the current inventory status of each product in the store.

[0729] "Crowd information" refers to information about the current congestion situation in each area of ​​a theme park or physical store.

[0730] The "optimal order of attractions" refers to the order in which a user can efficiently experience attractions, calculated based on the user's input information and real-time data.

[0731] The "optimal product purchasing order" is the order in which a user can efficiently purchase products, calculated based on inventory information and congestion information.

[0732] A "shopping schedule" is a schedule that includes the optimal order of purchasing products within a commercial facility, calculated based on user input information and real-time data.

[0733] "Means for real-time updates" refers to a mechanism in which the server recalculates the schedule based on new data and provides it to the user immediately.

[0734] The present invention relates to a system for optimizing user experiences at theme parks and brick-and-mortar stores. The system is implemented using the following hardware and software.

[0735] Hardware and software used

[0736] 1. User device: Smartphone (e.g. iPhone, Android Phone)

[0737] 2. Server: Cloud server (e.g. AWS, Google Cloud)

[0738] 3. Frontend: React Native, Flutter

[0739] 4. Backend: Python, Django / Flask

[0740] 5. Database: PostgreSQL

[0741] 6. Notification System: Firebase Cloud Messaging

[0742] System Overview

[0743] 1. Collecting user input information

[0744] Users use a smartphone app to input information such as group details, favorite attractions, desired rest times, and planned time to leave the park, which is then sent to a server and stored in a database.

[0745] 2. Real-time data collection

[0746] The server collects real-time data from IoT sensors in theme park management systems and physical stores, including wait times for each attraction, weather information, product availability, and congestion information for each area.

[0747] 3. Data Analysis and Schedule Generation

[0748] The server analyzes the user's input information and real-time data to calculate the optimal order of attractions and product purchases for the user. Specific algorithms used are shortest path algorithms such as Dijkstra's algorithm.

[0749] 4. Providing a schedule

[0750] The server generates a schedule, which is sent to a smartphone app and displayed to the user in the form of a timetable, which clearly indicates the order and times for each attraction and product purchase.

[0751] 5. Real-time updates and notifications

[0752] The smartphone app periodically communicates with the server to request updates on real-time information. The server recalculates the schedule based on the new real-time data and notifies the user of the updated schedule. This allows users to enjoy an optimal experience based on the most up-to-date information.

[0753] Specific examples

[0754] As an example, a case where a user efficiently shops at a physical store will be described.

[0755] 1. Collecting user input information

[0756] Using the app, users input a list of items they want to buy (e.g., milk, bread, eggs), group information (two adults, two children), and desired shopping time (e.g., two hours).

[0757] 2. Real-time data collection

[0758] The server collects real-time inventory information for each product and congestion information for each area of ​​the store from the store's management system and IoT sensors.

[0759] 3. Data Analysis and Schedule Generation

[0760] The server analyzes the user's input information and calculates the optimal product purchase order based on inventory and congestion information. For example, it uses Dijkstra's algorithm to generate a route that allows the user to efficiently obtain products.

[0761] 4. Providing a schedule

[0762] The server generates a schedule, which is sent to a smartphone app and displayed to the user in a timetable format. The schedule clearly indicates the time and order in which each item can be purchased.

[0763] 5. Real-time updates and notifications

[0764] For example, if bread stocks run low or a particular area of ​​the store becomes busy, the smartphone app communicates with the server and requests an updated schedule. The server recalculates the schedule based on the new data and sends it to the app. The app then notifies the user of the changed schedule, ensuring they receive instant updates.

[0765] Prompt Sentence Examples

[0766] Generate your shopping schedule using the following information:

[0767] User ID: 123

[0768] Group Information: 2 adults, 2 children

[0769] Shopping list: milk, bread, eggs

[0770] Likes: Electronics, toys

[0771] Desired shopping time: 2 hours

[0772] These steps allow users to enjoy an efficient and stress-free experience at theme parks and brick-and-mortar stores.

[0773] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0774] Step 1:

[0775] Collecting user input

[0776] Using a smartphone app, users input information about their group, their favorite attractions, desired rest time, planned time of departure, and a list of items they wish to purchase. The device temporarily stores this data and sends it to the server.

[0777] Input: User's group information, favorite attractions, desired rest time, planned departure time, list of items desired for purchase

[0778] Output: User data sent to the server

[0779] Step 2:

[0780] Real-time data collection for theme parks and brick-and-mortar stores

[0781] The server collects real-time data from the theme park's management system and IoT sensors in physical stores. This data includes waiting times for each attraction, weather information, product inventory status, and store congestion information. The server stores this data in a database.

[0782] Input: Real-time data from theme parks and physical stores (attraction waiting times, weather information, inventory status, crowd information)

[0783] Output: Real-time data stored in a database

[0784] Step 3:

[0785] Analyzing data and generating schedules

[0786] The server analyzes the user's input information and real-time data. Using shortest path algorithms such as Dijkstra's algorithm, it calculates the optimal order for the user to visit attractions and purchase products. Based on the analysis results, it generates a schedule and formats it into a timetable.

[0787] Input: User data, real-time data

[0788] Output: Schedule in timetable format

[0789] Step 4:

[0790] Schedule provision

[0791] The server sends the generated schedule to the smartphone app, which then displays it to the user. The timetable includes the order in which each attraction should be visited and the order and specific times for purchasing merchandise.

[0792] Input: Schedule data

[0793] Output: Timetable displayed on smartphone app

[0794] Step 5:

[0795] Real-time updates and notifications

[0796] The device periodically communicates with the server to request updates on real-time information. The server recalculates the schedule based on the new data and sends the updated schedule to the device. The device then uses its notification function to inform the user of the latest schedule.

[0797] Input: Updated real-time data, request data

[0798] Output: Updated schedule and notification information

[0799] These steps will ensure an efficient and comfortable experience at theme parks and brick-and-mortar stores.

[0800] 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.

[0801] The present invention is a system that generates a schedule taking into account a user's emotional state to optimize the user's theme park experience. The system provides an optimal order for visiting attractions based on user input information and real-time data, and further analyzes the user's emotional state using an emotion engine to optimize behavior.

[0802] Overview of program processing

[0803] Collecting user input

[0804] The user enters the following information through the terminal:

[0805] Group information (number of people, age group, etc.)

[0806] A list of favorite attractions

[0807] Break time requests

[0808] Scheduled departure time

[0809] Real-time data collection

[0810] The server collects the following data in real time from the theme park's management system and API:

[0811] Waiting times for each attraction

[0812] Weather information

[0813] Travel time based on walking speed

[0814] Emotion recognition by emotion engine

[0815] The device's built-in emotion engine recognizes the user's emotional state in real time from their facial expressions and voice, and this information is sent to the server via an API.

[0816] Analyzing data and generating schedules

[0817] The server generates a schedule based on user input, real-time data, and emotion data from the emotion engine in the following steps:

[0818] Analyze the user's desired information and set priorities.

[0819] The optimal order of attraction use is calculated based on real-time data and emotional state (e.g., Dijkstra algorithm).

[0820] Adjust the overall schedule to take into account break times, planned dismissal times, and emotional states.

[0821] Schedule provision

[0822] The server sends the generated schedule to the terminal, which then displays it to the user. The schedule is provided in the form of a timetable, clearly indicating the attractions to visit during each time period and break times.

[0823] Real-time updates and notifications

[0824] The device periodically communicates with the server to request real-time information updates.

[0825] The server recalculates the schedule based on new real-time data and the emotional state of the emotion engine, and sends any necessary changes to the device.

[0826] The device notifies users of updates and highlights schedule changes, allowing users to instantly receive real-time information on wait times, attraction cancellations, emotion-based suggestions, and more.

[0827] Specific examples

[0828] For families

[0829] As an example, a case where a family uses the system will be described.

[0830] 1. Collecting user input information

[0831] A family of four users (two adults and two children) enters information into the terminal.

[0832] His favorite attractions are roller coasters, merry-go-rounds, and Ferris wheels.

[0833] We would like to have a one-hour break from 12:00, and plan to leave the school at 18:00.

[0834] 2. Real-time data collection

[0835] The server collects real-time data from the theme park's management system, such as waiting times for roller coasters: 30 minutes, merry-go-rounds: 15 minutes, and ferris wheels: 20 minutes.

[0836] 3. Emotion Recognition by Emotion Engine

[0837] The emotion engine recognizes the user's emotional state from their facial expressions and voice and sends it to the server via API. For example, if a child is recognized as tired, that information is conveyed to the server.

[0838] 4. Data Analysis and Schedule Generation

[0839] The server analyzes the user's desired information, real-time data, and emotional state to optimize the order in which each attraction is used.

[0840] Taking into account break times, expected departure times, and emotional states, we generate a schedule like this:

[0841] 10:00 Roller Coaster

[0842] 11:00 Merry-go-round

[0843] 12:00 Break (Consider children's fatigue and suggest a relaxing rest area)

[0844] 13:00 Ferris wheel

[0845] 5. Providing a schedule

[0846] The terminal displays the generated schedule to the user with family, providing it in the form of a timetable.

[0847] 6. Real-time updates and notifications

[0848] For example, if the wait time for a roller coaster increases to 50 minutes, the device will contact the server and request an updated schedule.

[0849] The server recalculates the schedule based on the new data and emotional state and sends it to the device.

[0850] The device will notify the user of the new schedule and clearly indicate the changes.

[0851] The above is an embodiment of the present invention, and this system allows users to enjoy an efficient and comfortable theme park experience. By adding an emotion recognition function using an emotion engine, flexible suggestions and schedule adjustments based on the user's emotional state become possible, making it possible to provide even more personalized services.

[0852] The processing flow will be explained below.

[0853] Step 1:

[0854] The terminal displays an input form to the user. The user enters group information (number of people, age group, etc.), a list of favorite attractions, desired break time, and planned departure time. When the user finishes entering information, he or she presses the submit button.

[0855] Step 2:

[0856] The device sends the information entered by the user to the server. The data sent is in structured JSON format.

[0857] Step 3:

[0858] The server collects real-time data from the theme park's management system and APIs, including wait times for each attraction, weather information, and travel times based on walking speed.

[0859] Step 4:

[0860] The emotion engine installed in the device recognizes the user's emotional state in real time from their facial expressions and voice. The emotion engine uses sensor devices such as cameras and microphones to acquire the user's emotional data.

[0861] Step 5:

[0862] The device transmits the emotion data acquired by the emotion engine to the server, and the transmitted data is also in a structured format.

[0863] Step 6:

[0864] The server analyzes the input information from the user, real-time data, and emotional data from the emotion engine. It combines the user's wishes with the real-time data and emotional state to set the priority of each attraction.

[0865] Step 7:

[0866] The server calculates the optimal order in which to visit attractions, and optimizes the user's schedule using route optimization algorithms such as the Greedy algorithm and Dijkstra algorithm.

[0867] Step 8:

[0868] The server generates an optimal schedule based on the calculation results. The generated schedule includes designated break times and planned departure times, and also takes into account the user's emotional state.

[0869] Step 9:

[0870] The server generates a schedule and sends it to the terminal. The schedule is in a clear and easy-to-understand timetable format.

[0871] Step 10:

[0872] The device displays a schedule to the user, who then moves around the theme park and enjoys the attractions based on the schedule. During this time, the device continues to monitor the user's emotional state in real time.

[0873] Step 11:

[0874] The device periodically requests the latest real-time and emotional data from the server to keep the schedule updated according to waiting times, weather fluctuations, and changes in emotional state.

[0875] Step 12:

[0876] The server recalculates the schedule based on new real-time data and emotion data, and sends the updated schedule to the device as needed.

[0877] Step 13:

[0878] The device notifies users of schedule updates, for example, via push notifications or alerts, allowing users to react quickly to changes, enabling users to enjoy an optimal theme park experience based on their emotional state.

[0879] Example 2

[0880] 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."

[0881] When visiting a theme park, it is necessary to automatically generate and provide an efficient and comfortable schedule that comprehensively considers a user's group information, favorite attractions, real-time wait times, weather, and the user's emotional state. Conventional systems have difficulty combining these various factors, often forcing users to struggle with cumbersome procedures and schedule adjustments. In particular, the lack of real-time updates and optimization based on emotional state makes it difficult to provide a satisfying user experience.

[0882] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0883] In this invention, the server includes means for inputting user group information, favorite attractions, desired rest periods, and planned time of departure, means for collecting real-time data from the theme park, means for analyzing the user's emotional state using an emotion recognition engine installed in the terminal, means for analyzing the user's input information, the real-time data, and the emotional state and calculating an optimal order for visiting attractions, and means for providing the user with a schedule based on the calculated order of visiting attractions. This makes it possible to provide an efficient and comfortable theme park experience that takes into account the diverse needs and situations of users.

[0884] "User group information" is information about the people accompanying the user when visiting a theme park, including the number of people and their age groups.

[0885] "Favorite Attractions" is a list of attractions within the theme park that the user would like to visit.

[0886] "Desired rest time" refers to the time period and length of time during which the user desires to rest in the theme park.

[0887] The "planned time of departure" is the time when the user plans to leave the theme park.

[0888] "Real-time theme park data" refers to data that is collected instantly, such as waiting times for attractions within the theme park, weather information, and travel times based on walking speed.

[0889] An "emotion recognition engine" is a software or hardware mechanism that is installed on a device and analyzes the user's facial expressions and voice to recognize their emotional state.

[0890] A "schedule" is a plan that summarizes attractions to visit, rest times, etc. in the form of a timetable so that the user can visit the theme park efficiently and comfortably.

[0891] "Providing a schedule" is the process in which the server sends the generated schedule to the terminal so that the user can check it.

[0892] This invention is a system that generates a schedule taking into account the user's emotional state in order to optimize the user's theme park experience. The entire system consists of a server, a terminal, and an emotion recognition engine.

[0893] Collecting user input

[0894] The user inputs group information (number of people, age group, etc.), a list of favorite attractions, desired rest time, and planned time to leave the park through the terminal. The terminal then transmits this input information to the server.

[0895] Real-time data collection

[0896] The server collects real-time data via the theme park's management system and API, including:

[0897] Waiting times for each attraction

[0898] Weather information

[0899] Travel time based on walking speed

[0900] Emotion recognition by emotion engine

[0901] The emotion recognition engine installed in the device recognizes the user's facial expressions and voice in real time. This recognition data is sent to the server via API. The emotion recognition engine includes facial expression analysis software and voice analysis software.

[0902] Analyzing data and generating schedules

[0903] The server analyzes user input, real-time data, and emotion data obtained from an emotion recognition engine all at once. Based on this analysis, it sets priorities and uses an algorithm (e.g., Dijkstra algorithm) to determine the optimal order in which attractions should be used. Furthermore, it adjusts the overall schedule, taking into account break times, planned departure times, and the user's emotional state.

[0904] Schedule provision

[0905] The schedule generated by the server is sent to the terminal and displayed to the user in the form of a timetable, allowing the user to easily check the attractions to be visited and break times via their smartphone or tablet.

[0906] Real-time updates and notifications

[0907] The device periodically communicates with the server to request new real-time information. The server recalculates the schedule based on the latest real-time data and emotion data. If necessary, the server sends a new schedule to the device, which then notifies the user of the updated information. This allows users to instantly receive information such as real-time changes in waiting times, attraction cancellations, and suggestions based on the user's emotions.

[0908] Specific examples

[0909] For families

[0910] A family of users (two adults and two children) visiting a theme park uses the system as follows:

[0911] 1. Collecting input information: Log in to the terminal and enter the number of people in your family, your favorite attraction (roller coaster, merry-go-round, Ferris wheel), break time (1 hour from 12 noon), and planned time to leave the park (6 p.m.).

[0912] 2. Real-time data collection: The server collects the waiting time for each attraction (e.g., 30 minutes for roller coaster, 15 minutes for merry-go-round, 20 minutes for Ferris wheel) in real time from the theme park's management system.

[0913] 3. Emotion recognition: The device camera captures the child's facial expression, and the emotion recognition engine recognizes "fatigue." This data is sent to the server.

[0914] 4. Schedule Generation: Based on this data, the server calculates the order in which each attraction should be visited and generates the following schedule:

[0915] 10:00 Roller Coaster

[0916] 11:00 Merry-go-round

[0917] 12:00 Break (Area for children to relax as they are tired)

[0918] 13:00 Ferris wheel

[0919] 5. Providing the schedule: The terminal displays the generated schedule to the user in the form of a timetable.

[0920] 6. Real-time updates and notifications: Devices periodically communicate with the server and schedules are updated based on new data. For example, if the waiting time for a roller coaster changes to 50 minutes, a new schedule will be generated.

[0921] Prompt Sentence Examples

[0922] Here are some examples of prompts to input to the generative AI model:

[0923] "Generate an example of a day's schedule for a family (2 adults, 2 children) at a theme park based on the following information: roller coaster (wait time 30 minutes), merry-go-round (wait time 15 minutes), ferris wheel (wait time 20 minutes). The emotion engine recognizes that the children are tired. The break time is 1 hour from 12 noon, and the planned departure time is 6:00 PM."

[0924] The above is an embodiment of the present invention, and this system allows users to enjoy an efficient and comfortable theme park experience. By using an emotion recognition engine, flexible suggestions and schedule adjustments based on the user's emotional state can be made, and more personalized services can be provided.

[0925] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0926] Step 1: Collecting User Input

[0927] 1. Start typing:

[0928] Users launch the application on their device and log in using their account information. They input information such as the number of people in their family or group, their age group, a list of their favorite attractions, desired rest times, and the planned time to leave the park.

[0929] Input: User's demographic information, desired attraction, break time, and departure time

[0930] Output: The input information is sent to the server

[0931] Step 2: Collect real-time data

[0932] 1. Data Request:

[0933] The server sends data requests to the theme park's management system and API, specifically requesting wait times for each attraction, weather information, and predicted travel times based on walking speed.

[0934] Input: Server data request

[0935] Output: Real-time data from theme park management systems

[0936] 2. Data Collection:

[0937] The server receives real-time data such as waiting times, weather information, and travel times from the management system or API and stores it in a database.

[0938] Input: Real-time data

[0939] Output: Real-time data stored in a database

[0940] Step 3: Emotion recognition by the emotion engine

[0941] 1. Emotional data collection:

[0942] The device's camera and microphone are used to capture the user's facial expressions and voice, and this data is fed into the emotion engine.

[0943] Input: Real-time user facial and voice data

[0944] Output: Raw data sent to the sentiment engine

[0945] 2. Sentiment analysis:

[0946] The emotion engine analyzes the captured data and recognizes the user's emotional state, for example, detecting a smile indicates "happiness" and a frown indicates "fatigue."

[0947] Input: Raw data (facial expressions and voice)

[0948] Output: Perceived emotional state

[0949] 3. Emotional data transmission:

[0950] The device sends the recognized emotion data to the server via API.

[0951] Input: Recognized emotion data

[0952] Output: Emotion data sent to the server

[0953] Step 4: Analyze data and generate a schedule

[0954] 1. Data Integration:

[0955] The server integrates user input information, real-time data, and emotional data, enabling comprehensive analysis.

[0956] Input: User input, real-time data, emotional data

[0957] Output: A consolidated dataset

[0958] 2. Priority settings:

[0959] The server sets priorities for attractions based on the user's desired information.

[0960] Input: Integrated dataset

[0961] Output: A prioritized list of attractions

[0962] 3. Schedule optimization:

[0963] The server uses algorithms such as Dijkstra's algorithm to calculate the optimal order in which to visit attractions, thereby minimizing waiting times and travel times.

[0964] Input: Attraction priority list, consolidated data

[0965] Output: Optimized attraction usage order

[0966] 4. Overall schedule adjustment:

[0967] The server adjusts the overall schedule taking into account break times, departure times, and the user's emotional state, for example, by shortening break times based on the user's emotional state.

[0968] Input: Optimized attraction order, user's desired time

[0969] Output: Adjusted overall schedule

[0970] Step 5: Provide a schedule

[0971] 1. Schedule generation:

[0972] The server creates an optimized and coordinated schedule, including attractions to visit, break times, travel times, etc.

[0973] Input: Adjusted overall schedule

[0974] Output: The generated schedule

[0975] 2. Data transmission:

[0976] The server transmits the generated schedule to the terminal.

[0977] Input: Generated schedule

[0978] Output: Schedule sent to the terminal

[0979] 3.Display:

[0980] The terminal displays the received schedule in a timetable format to the user, allowing the user to check the attractions to be visited and break times.

[0981] Input: Schedule sent to the terminal

[0982] Output: The schedule as seen by the user

[0983] Step 6: Real-time updates and notifications

[0984] 1. Regular communication:

[0985] The device periodically communicates with the server to request updates on the latest real-time data and emotion data.

[0986] Input: Update request

[0987] Output: Latest data

[0988] 2. Recalculate the schedule:

[0989] The server recalculates the existing schedule based on new real-time data and emotion data, and generates new schedules as needed.

[0990] Input: Latest real-time data, sentiment data

[0991] Output: Recalculated schedule

[0992] 3. Schedule Update:

[0993] The server transmits the newly generated schedule to the terminal.

[0994] Input: Recalculated schedule

[0995] Output: Update schedule sent to the device

[0996] 4. Notice:

[0997] The device notifies the user of schedule changes, allowing the user to take action based on the latest situation.

[0998] Input: Updated schedule

[0999] Output: Changes notified to the user

[1000] These are the processing steps of the system's program. It is possible to provide an optimal schedule by comprehensively analyzing user input, real-time data, and emotional data. This process allows users to enjoy an efficient and comfortable theme park experience.

[1001] (Application example 2)

[1002] 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."

[1003] Modern theme parks and shopping malls are required to provide optimal experiences for visitors. However, conventional systems have difficulty not only taking real-time information into account but also flexibly adjusting schedules based on the user's emotional state. This often leads to stress and a disappointing experience for users. It has also been difficult to accurately predict congestion and waiting times at theme parks and shopping malls and suggest optimal routes and stores. To solve these problems, a system is needed that can analyze users' real-time behavior and emotions in an integrated manner and provide optimal schedules.

[1004] 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 inputting a user's group information, favorite attractions, desired rest time, and planned departure time, means for collecting real-time data about the theme park, means for analyzing the user's input information and the real-time data and calculating an optimal order for visiting attractions, means for providing the user with a schedule based on the calculated order of visits, means for recognizing the user's emotional state in real time and optimizing the schedule based on the emotional state, and means for providing a shopping route based on real-time store information from online stores and the user's emotional state. This enables the user to have an optimal theme park experience and shopping experience tailored to their emotional state.

[1005] "User group information" is information about the entire group, such as the number of users and their age groups.

[1006] "Favorite attractions" is a list of attractions in which the user has particular interests or concerns.

[1007] "Desired break time" is information about the specific time or period when the user wishes to take a break.

[1008] The "planned time of departure" is the time when the user plans to leave the theme park.

[1009] "Real-time theme park data" refers to the latest information about theme parks, such as current wait times for attractions, weather information, and walking speeds.

[1010] "Emotional state" refers to the current emotion recognized from the user's facial expression and voice, and includes, for example, stress level and fatigue level.

[1011] A "shopping route" is an optimal route for a user to efficiently navigate around a shopping mall or store.

[1012] "Real-time updates" means constantly updating systems and data based on the latest information.

[1013] The present invention is a system for optimizing a user's theme park and shopping experience. The system analyzes a user's input information, real-time data, and emotional state to provide optimal attractions and shopping routes. The following description details a specific embodiment of the system.

[1014] 1. Collecting user input information

[1015] The device (e.g. smartphone or tablet) collects the following information from the user:

[1016] Group information (number of people, age group, etc.)

[1017] A list of your favorite attractions and products

[1018] Break time requests

[1019] Scheduled time of leaving the park or store

[1020] 2. Real-time data collection

[1021] The server collects the following real-time data from the theme park and shopping mall management systems and public APIs:

[1022] Waiting times for each attraction

[1023] Current Weather Information

[1024] Store congestion status and sales information

[1025] Travel time based on user walking speed

[1026] 3. Emotion Recognition by Emotion Engine

[1027] An emotion engine (specifically, the EmotionEngine library) installed on the device recognizes the user's emotional state in real time from their facial expressions and voice. This information is sent to the server via an API. For example, if the user is tired or stressed, that information is communicated to the server.

[1028] 4. Data Analysis and Optimization

[1029] The server generates the optimal order of attractions and shopping routes based on the user's input information, collected real-time data, and emotion data from the emotion engine. This includes the following steps:

[1030] Analyze user preferences and set priorities

[1031] Calculate the optimal order of attractions and stores based on real-time data and emotional state (e.g., Dijkstra algorithm)

[1032] Adjust the overall schedule taking into account break times and planned departure times

[1033] 5. Providing a schedule

[1034] The server generates a schedule and sends it to the device, which then displays it to the user in the form of a timetable, clearly indicating the attractions and shops to visit during each time period, as well as break times.

[1035] 6. Real-time updates and notifications

[1036] The device periodically communicates with the server to request updates of real-time information. The server recalculates the schedule based on the new real-time data and the emotional state of the emotion engine, and sends any necessary changes to the device, allowing the user to see the changes immediately.

[1037] Specific examples

[1038] For families

[1039] 1. Collection of information:

[1040] A family of four users enters information into the terminal. They select roller coaster, merry-go-round, and Ferris wheel as their preferred attractions. They request a one-hour break from 12:00 and plan to leave the park at 18:00.

[1041] 2. Real-time data:

[1042] The waiting time for the roller coaster is 30 minutes, the merry-go-round is 15 minutes, and the Ferris wheel is 20 minutes.

[1043] 3. Emotional state:

[1044] The emotion engine recognizes fatigue from the user's facial expression.

[1045] 4. Optimization:

[1046] The server generates a schedule and sets the roller coaster at 10:00, the merry-go-round at 11:00, the break at 12:00, and the Ferris wheel at 13:00.

[1047] 5.Display:

[1048] It displays the timetable on the device and sends necessary notifications.

[1049] Prompt Sentence Examples

[1050] Write Python code that takes into account unique user information, real-time data, and emotion recognition results to provide an optimal shopping experience schedule. The schedule includes the following items: time, store name, and wait time. Using the user's preferred categories and their real-time data, suggest appropriate break times based on the user's emotional state.

[1051] The above is a specific embodiment of the present invention. This system enables flexible schedule adjustment based on the user's emotional state, providing a more comfortable and efficient experience.

[1052] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1053] Step 1:

[1054] The terminal collects input information from the user, such as group information (number of people, age group), a list of favorite attractions, desired rest periods, and planned departure time. This information serves as the basis for the system to understand the user's preferences and plans and generate a personalized schedule.

[1055] Input: Number of users, age group, list of favorite attractions, desired break time, planned time to leave the park

[1056] Output: A dataset of user-entered information

[1057] Specific behavior:

[1058] The terminal displays an information input form through a user interface.

[1059] The user enters the required information into the form and presses the "Submit" button.

[1060] The terminal collects the input information and sends it to the server as a data set.

[1061] Step 2:

[1062] The server collects real-time data from theme parks and shopping malls, including attraction wait times, weather information, store occupancy and sales information, and user walking speeds. This data is collected using APIs.

[1063] Input: Theme park and shopping mall APIs

[1064] Output: Real-time data

[1065] Specific behavior:

[1066] The server periodically sends requests to the API to retrieve the latest real-time data.

[1067] The collected data is organized on the server and prepared for analysis.

[1068] Step 3:

[1069] The device's built-in emotion engine recognizes the user's emotional state in real time from their facial expressions and voice. This information is sent to the server via an API. For example, the user's fatigue level and stress level can be recognized.

[1070] Input: User's facial expressions and voice data

[1071] Output: Emotional state data

[1072] Specific behavior:

[1073] The device's camera and microphone are used to collect the user's facial expressions and voice.

[1074] An emotion engine (such as the EmotionEngine library) analyzes this data and identifies the emotional state.

[1075] The recognized emotional state data is transmitted to a server.

[1076] Step 4:

[1077] The server analyzes user input, real-time data, and emotional data to generate the optimal order of attractions and shopping routes, using algorithms such as Dijkstra's algorithm.

[1078] Input: User-entered information, real-time data, emotional state data

[1079] Output: Optimal schedule (order of attractions, shopping route)

[1080] Specific behavior:

[1081] The server integrates the various collected data and runs optimization algorithms.

[1082] The optimal order of use is calculated taking into account the waiting time at each attraction and store, the level of congestion, and the user's emotional state.

[1083] Adjust the overall schedule, taking into account break times and planned dismissal times.

[1084] Step 5:

[1085] The server transmits the generated schedule to the terminal, which displays it to the user in the form of a timetable.

[1086] Input: Optimal schedule

[1087] Output: Schedule display in timetable format

[1088] Specific behavior:

[1089] The server transmits the generated schedule data to the terminal.

[1090] The terminal visually displays the schedule in a timetable format, allowing users to act based on this display.

[1091] Step 6:

[1092] The device periodically communicates with the server to request real-time updates. The server recalculates the schedule based on the new data and emotional state, and sends any necessary changes to the device, where the user can immediately see the changes.

[1093] Input: Regular real-time data and emotional state data

[1094] Output: Updated schedule

[1095] Specific behavior:

[1096] The terminal requests real-time data updates from the server at regular intervals.

[1097] The server retrieves the new data and analyzes the emotional state again.

[1098] Recalculate the schedule as needed and send updates to the terminal.

[1099] The terminal notifies the user of the updated schedule and displays the changes.

[1100] The above are the specific processing steps in the program of the system of the present invention, which allows the user to always have the most optimal theme park and shopping experience based on the latest information and emotional state.

[1101] 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.

[1102] 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.

[1103] 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.

[1104] [Third embodiment]

[1105] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1106] 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.

[1107] 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).

[1108] 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.

[1109] 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.

[1110] 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).

[1111] 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.

[1112] 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.

[1113] 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.

[1114] 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.

[1115] 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.

[1116] 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."

[1117] The present invention is a system for optimizing a user's theme park experience by combining input information from the user with theme park data collected in real time to provide an efficient schedule. This system is realized through the cooperation of terminals and a server.

[1118] Overview of program processing

[1119] Collecting user input

[1120] The user enters the following information through the terminal:

[1121] Group information (number of people, age group, etc.)

[1122] A list of favorite attractions

[1123] Break time requests

[1124] Scheduled departure time

[1125] Real-time data collection

[1126] The server will interface with the theme park's management system and collect the following data in real time:

[1127] Waiting times for each attraction

[1128] Weather information

[1129] Travel time based on walking speed

[1130] Analyzing data and generating schedules

[1131] The server generates a schedule based on user input and real-time data in the following steps:

[1132] Analyze the user's desired information and set priorities.

[1133] Calculate the optimal order for visiting attractions based on real-time data (e.g., Dijkstra algorithm).

[1134] Adjust the overall schedule taking into account break times and planned departure times.

[1135] Schedule provision

[1136] The server sends the generated schedule to the terminal, which then displays it to the user. The schedule is provided in the form of a timetable, clearly indicating the attractions to visit during each time period and break times.

[1137] Real-time updates and notifications

[1138] The device periodically communicates with the server to request real-time information updates.

[1139] The server recalculates the schedule based on the new real-time data and sends any necessary changes to the terminal.

[1140] The device notifies users of updates and clearly shows any changes to the schedule, allowing users to receive real-time information on changes in wait times, attraction cancellations, and more.

[1141] Specific examples

[1142] For families

[1143] As an example, a case where a family uses the system will be described.

[1144] 1. Collecting user input information

[1145] The user inputs information into the terminal that the user is a family of four (two adults and two children).

[1146] His favorite attractions are roller coasters, merry-go-rounds, and Ferris wheels.

[1147] We would like to have a one-hour break from 12:00, and plan to leave the school at 18:00.

[1148] 2. Real-time data collection

[1149] The server collects real-time data from the theme park's management system, such as waiting times for roller coasters: 30 minutes, merry-go-rounds: 15 minutes, and ferris wheels: 20 minutes.

[1150] 3. Data Analysis and Schedule Generation

[1151] The server analyzes the user's desired information and optimizes the order in which each attraction is visited.

[1152] Taking into account break times and planned departure times, we generate a schedule like this:

[1153] 10:00 Roller Coaster

[1154] 11:00 Merry-go-round

[1155] 12:00 Break

[1156] 13:00 Ferris wheel

[1157] 4. Providing a schedule

[1158] The terminal displays the generated schedule to the user with family, providing it in the form of a timetable.

[1159] 5. Real-time updates and notifications

[1160] For example, if the wait time for a roller coaster increases to 50 minutes, the device will contact the server and request an updated schedule.

[1161] The server recalculates the schedule based on the new data and sends it to the terminal.

[1162] The device will notify the user of the new schedule and clearly indicate the changes.

[1163] The above is an embodiment of the present invention, and this system allows users to enjoy an efficient and comfortable theme park experience.

[1164] The processing flow will be explained below.

[1165] Step 1:

[1166] The terminal displays an input form to the user. The user enters group information (number of people, age group, etc.), a list of favorite attractions, desired break time, and planned departure time. When the user finishes entering information, he or she presses the submit button.

[1167] Step 2:

[1168] The device sends the information entered by the user to the server. The data sent is in structured JSON format.

[1169] Step 3:

[1170] The server collects real-time data from the theme park's management system and APIs, including wait times for each attraction, weather information, and travel times based on walking speed.

[1171] Step 4:

[1172] The server analyzes the input information from the user and the collected real-time data, and sets the priority of each attraction by linking the user's preferences with the real-time data.

[1173] Step 5:

[1174] The server calculates the optimal order in which to visit attractions, and optimizes the user's schedule using route optimization algorithms such as the Greedy algorithm and Dijkstra algorithm.

[1175] Step 6:

[1176] The server generates an optimal schedule based on the calculation results, which incorporates the specified break times and planned departure times.

[1177] Step 7:

[1178] The server generates a schedule and sends it to the terminal. The schedule is in a clear and easy-to-understand timetable format.

[1179] Step 8:

[1180] The terminal displays the schedule to the user, who then moves around the theme park according to the schedule and enjoys the attractions.

[1181] Step 9:

[1182] The device periodically requests the latest real-time data from the server to ensure the schedule is up-to-date with fluctuations in waiting times and weather.

[1183] Step 10:

[1184] The server recalculates the schedule based on new real-time data and sends the updated schedule to the device as needed.

[1185] Step 11:

[1186] The device notifies the user of schedule updates, for example, via push notifications or alerts, so that the user can respond quickly.

[1187] Example 1

[1188] 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."

[1189] In traditional theme park experiences, users had to check attraction wait times, weather, and travel times themselves, and then create a schedule based on that information. However, it was difficult to manually check and appropriately reflect this data, which fluctuates in real time, making efficient scheduling difficult. In particular, for large groups such as families, it is not easy to efficiently move around while satisfying everyone's wishes. This resulted in a decline in the quality of the user experience.

[1190] 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.

[1191] In this invention, the server includes means for inputting user group information, favorite video content, desired break times, and scheduled end times, means for collecting real-time data about the theme park, means for analyzing the user's input information and the real-time data and calculating an optimal video content viewing order, means for providing the user with a schedule based on the calculated viewing order, and means for updating and notifying the user of the schedule in real time via the user's terminal, thereby enabling the user to automatically receive an optimized schedule in real time and efficiently tour the theme park.

[1192] "User" refers to an individual or group who uses the theme park.

[1193] "Group information" refers to data including information such as the number of users, age range, and relationships.

[1194] "Favorite video content" refers to the types and lists of attractions and shows that the user wishes to view.

[1195] "Rest time" refers to a period of time set by the user for rest during their visit to the theme park.

[1196] "Scheduled end time" refers to the time the user plans to leave the theme park.

[1197] "Real-time theme park data" refers to the latest information at the moment, such as waiting times for each attraction within the theme park, operation status, weather information, and user travel times.

[1198] "Server" refers to a computer system that processes user input information and real-time data, and generates and manages optimal schedules.

[1199] "Terminal" refers to a device that allows a user to input information and view a generated schedule.

[1200] "Schedule" refers to an optimized theme park tour plan based on user preferences and real-time data.

[1201] "Viewing order" refers to the optimal order in which attractions and shows are viewed, calculated based on user preferences and real-time data.

[1202] "Notification" refers to the act of sending the latest schedule changes and alerts from the server to the user via the device.

[1203] The present invention is a system for optimizing a user's theme park experience by combining input information from the user with theme park data collected in real time to provide an efficient schedule. This system is realized through the cooperation of terminals and a server.

[1204] Specifically, users use their devices to input group information (number of people, age group, etc.), a list of their favorite attractions, desired rest times, and planned time to leave the park. This information is sent from the devices to the server. The server collects real-time data from the theme park's management system and weather information API. This real-time data includes waiting times for each attraction, operation status, weather information, and travel times based on the user's walking speed.

[1205] The server analyzes the input information sent by the user and the collected real-time data, and optimizes the order in which the attractions can be visited based on the user's preferences. For example, it calculates the optimal order using an algorithm such as Dijkstra's algorithm. The generated schedule is sent from the server to the terminal, which displays it to the user in the form of a timetable.

[1206] The terminal also periodically communicates with the server to request updates to real-time information. The server recalculates the schedule based on the latest real-time data and, if necessary, sends the revised schedule to the terminal. The terminal then notifies the user of the updated information and clearly indicates any changes to the schedule. This allows the user to immediately receive information on real-time changes in waiting times, attraction cancellations, and other such information.

[1207] Specific examples

[1208] Families can use the system by following these steps:

[1209] 1. Collecting user input information

[1210] The user inputs information into the terminal that the user is a family of four (two adults and two children).

[1211] His favorite attractions are roller coasters, merry-go-rounds, and Ferris wheels.

[1212] We would like to have a one-hour break from 12:00, and plan to leave the school at 18:00.

[1213] 2. Real-time data collection

[1214] The server collects real-time data from the theme park's management system, such as waiting times for roller coasters: 30 minutes, merry-go-rounds: 15 minutes, and ferris wheels: 20 minutes.

[1215] Also, sunny weather data is acquired as weather information.

[1216] 3. Data Analysis and Schedule Generation

[1217] The server analyzes the user's preferences and optimizes the order in which each attraction is visited. Taking into account break times and the planned time of departure, the server generates the following schedule:

[1218] 10:00 Roller Coaster

[1219] 11:00 Merry-go-round

[1220] 12:00 Break

[1221] 13:00 Ferris wheel

[1222] 4. Providing a schedule

[1223] The server transmits the generated schedule to the terminal, which displays it to the user in the form of a timetable.

[1224] 5. Real-time updates and notifications

[1225] For example, if the wait time for a roller coaster increases to 50 minutes, the device contacts the server and requests an updated schedule. The server recalculates the schedule based on the new data and sends it to the device. The device then notifies the user of the new schedule and clearly indicates the changes.

[1226] Prompt Sentence Examples

[1227] Below is an example of a prompt sentence to input to the generative AI model.

[1228] A family of four users (two adults and two children) goes to a theme park. Their favorite attractions are the roller coaster, merry-go-round, and Ferris wheel. They would like to take a one-hour break from noon, and plan to leave the park at 6:00 PM. Real-time data shows the waiting time for the roller coaster is 30 minutes, the merry-go-round is 15 minutes, the Ferris wheel is 20 minutes, and the weather is sunny. Based on this information, please generate the optimal schedule.

[1229] This system allows users to enjoy an efficient and comfortable theme park experience.

[1230] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1231] Step 1:

[1232] Collecting user input

[1233] Users enter information about their visit to the theme park into the device, including group information (number of people, age group), a list of favorite attractions, break times, and planned time to leave. The data is stored on the device and sent to a server for later analysis.

[1234] Input: Group information, attraction list, break times, planned departure time

[1235] Output: A dataset containing the user's input information

[1236] Step 2:

[1237] Real-time data collection

[1238] The server works with the theme park's management system to collect real-time data, such as waiting times for each attraction, operation status, weather information, and user travel time. This data is then analyzed. The server periodically calls the theme park's real-time data API to obtain the latest information.

[1239] Input: Real-time Data API endpoint

[1240] Output: Real-time data (waiting time, weather information, operation status, travel time)

[1241] Step 3:

[1242] Analyzing data and generating schedules

[1243] The server performs analysis based on the user's input information and real-time data. It first analyzes the user's desired information and sets the priority of each attraction. It then calculates the optimal order in which the attractions should be used based on the real-time data. For example, it uses Dijkstra's algorithm to calculate the shortest time for the entire route. The server uses an optimization algorithm to generate a schedule that meets the user's wishes.

[1244] Input: User input information, real-time data

[1245] Output: Optimized schedule

[1246] Step 4:

[1247] Schedule provision

[1248] The server sends the generated schedule to the terminal, which analyzes it and displays it to the user in the form of a timetable. A graphical interface is provided so that the user can check the schedule. A system is also included that notifies the user when the schedule is changed.

[1249] Input: Optimized schedule

[1250] Output: Schedule display in timetable format

[1251] Step 5:

[1252] Real-time updates and notifications

[1253] The terminal periodically communicates with the server to request updates with new real-time data. The server recalculates the schedule based on the latest data and sends the new schedule to the terminal. The terminal then notifies the user of the new schedule information and displays details of any changes. This allows the user to receive real-time information on changes in waiting times and attraction cancellations.

[1254] Input: Real-time data, schedule recalculation request

[1255] Output: Updated schedule, notification to users

[1256] The above is the specific process flow and the operations at each step. This system enables users to have an efficient and comfortable experience in the theme park.

[1257] (Application example 1)

[1258] 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."

[1259] The present invention relates to a schedule generation system for optimizing user experiences at commercial facilities such as theme parks. Conventional theme park systems have faced problems, such as difficulty in efficiently viewing attractions in the order desired by users, and waiting times and congestion can hinder efficient enjoyment. Similarly, physical stores such as shopping centers face the same problem of inconvenience caused by fluctuations in inventory information and congestion when users are trying to efficiently purchase products. In response to these problems, the present invention aims to solve common issues at theme parks and physical stores by combining user input information with real-time data.

[1260] 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.

[1261] In this invention, the server includes means for inputting user group information, favorite attractions, desired rest periods, and planned time of departure, means for collecting real-time data about the theme park, means for analyzing the user's input information and the real-time data to calculate an optimal order for visiting attractions, means for providing the user with a schedule based on the calculated order of visits, means for collecting inventory information and congestion information based on the data to calculate an optimal order for purchasing products, means for providing the user with a shopping schedule based on the optimal order for purchasing products, and means for updating the shopping schedule in real time and notifying the user. This enables efficient use of attractions in the theme park and efficient purchases at physical stores.

[1262] "User group information" refers to attribute information such as the number of people in the group to which the user belongs and their age group.

[1263] "Favorite attractions" refers to a list of attractions that the user particularly wishes to experience.

[1264] The "desired break time" is a time period designated in advance by the user during which the user wishes to take a break.

[1265] "Scheduled departure time" refers to the time when the user plans to leave the theme park.

[1266] "Real-time theme park data" refers to various data collected in real time within a theme park, such as waiting times for attractions and weather information.

[1267] "Inventory information" refers to information about the current inventory status of each product in the store.

[1268] "Crowd information" refers to information about the current congestion situation in each area of ​​a theme park or physical store.

[1269] The "optimal order of attractions" refers to the order in which a user can efficiently experience attractions, calculated based on the user's input information and real-time data.

[1270] The "optimal product purchasing order" is the order in which a user can efficiently purchase products, calculated based on inventory information and congestion information.

[1271] A "shopping schedule" is a schedule that includes the optimal order of purchasing products within a commercial facility, calculated based on user input information and real-time data.

[1272] "Means for real-time updates" refers to a mechanism in which the server recalculates the schedule based on new data and provides it to the user immediately.

[1273] The present invention relates to a system for optimizing user experiences at theme parks and brick-and-mortar stores. The system is implemented using the following hardware and software.

[1274] Hardware and software used

[1275] 1. User device: Smartphone (e.g. iPhone, Android Phone)

[1276] 2. Server: Cloud server (e.g. AWS, Google Cloud)

[1277] 3. Frontend: React Native, Flutter

[1278] 4. Backend: Python, Django / Flask

[1279] 5. Database: PostgreSQL

[1280] 6. Notification System: Firebase Cloud Messaging

[1281] System Overview

[1282] 1. Collecting user input information

[1283] Users use a smartphone app to input information such as group details, favorite attractions, desired rest times, and planned time to leave the park, which is then sent to a server and stored in a database.

[1284] 2. Real-time data collection

[1285] The server collects real-time data from IoT sensors in theme park management systems and physical stores, including wait times for each attraction, weather information, product availability, and congestion information for each area.

[1286] 3. Data Analysis and Schedule Generation

[1287] The server analyzes the user's input information and real-time data to calculate the optimal order of attractions and product purchases for the user. Specific algorithms used are shortest path algorithms such as Dijkstra's algorithm.

[1288] 4. Providing a schedule

[1289] The server generates a schedule, which is sent to a smartphone app and displayed to the user in the form of a timetable, which clearly indicates the order and times for each attraction and product purchase.

[1290] 5. Real-time updates and notifications

[1291] The smartphone app periodically communicates with the server to request updates on real-time information. The server recalculates the schedule based on the new real-time data and notifies the user of the updated schedule. This allows users to enjoy an optimal experience based on the most up-to-date information.

[1292] Specific examples

[1293] As an example, a case where a user efficiently shops at a physical store will be described.

[1294] 1. Collecting user input information

[1295] Using the app, users input a list of items they want to buy (e.g., milk, bread, eggs), group information (two adults, two children), and desired shopping time (e.g., two hours).

[1296] 2. Real-time data collection

[1297] The server collects real-time inventory information for each product and congestion information for each area of ​​the store from the store's management system and IoT sensors.

[1298] 3. Data Analysis and Schedule Generation

[1299] The server analyzes the user's input information and calculates the optimal product purchase order based on inventory and congestion information. For example, it uses Dijkstra's algorithm to generate a route that allows the user to efficiently obtain products.

[1300] 4. Providing a schedule

[1301] The server generates a schedule, which is sent to a smartphone app and displayed to the user in a timetable format. The schedule clearly indicates the time and order in which each item can be purchased.

[1302] 5. Real-time updates and notifications

[1303] For example, if bread stocks run low or a particular area of ​​the store becomes busy, the smartphone app communicates with the server and requests an updated schedule. The server recalculates the schedule based on the new data and sends it to the app. The app then notifies the user of the changed schedule, ensuring they receive instant updates.

[1304] Prompt Sentence Examples

[1305] Generate your shopping schedule using the following information:

[1306] User ID: 123

[1307] Group Information: 2 adults, 2 children

[1308] Shopping list: milk, bread, eggs

[1309] Likes: Electronics, toys

[1310] Desired shopping time: 2 hours

[1311] These steps allow users to enjoy an efficient and stress-free experience at theme parks and brick-and-mortar stores.

[1312] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1313] Step 1:

[1314] Collecting user input

[1315] Using a smartphone app, users input information about their group, their favorite attractions, desired rest time, planned time of departure, and a list of items they wish to purchase. The device temporarily stores this data and sends it to the server.

[1316] Input: User's group information, favorite attractions, desired rest time, planned departure time, list of items desired for purchase

[1317] Output: User data sent to the server

[1318] Step 2:

[1319] Real-time data collection for theme parks and brick-and-mortar stores

[1320] The server collects real-time data from the theme park's management system and IoT sensors in physical stores. This data includes waiting times for each attraction, weather information, product inventory status, and store congestion information. The server stores this data in a database.

[1321] Input: Real-time data from theme parks and physical stores (attraction waiting times, weather information, inventory status, crowd information)

[1322] Output: Real-time data stored in a database

[1323] Step 3:

[1324] Analyzing data and generating schedules

[1325] The server analyzes the user's input information and real-time data. Using shortest path algorithms such as Dijkstra's algorithm, it calculates the optimal order for the user to visit attractions and purchase products. Based on the analysis results, it generates a schedule and formats it into a timetable.

[1326] Input: User data, real-time data

[1327] Output: Schedule in timetable format

[1328] Step 4:

[1329] Schedule provision

[1330] The server sends the generated schedule to the smartphone app, which then displays it to the user. The timetable includes the order in which each attraction should be visited and the order and specific times for purchasing merchandise.

[1331] Input: Schedule data

[1332] Output: Timetable displayed on smartphone app

[1333] Step 5:

[1334] Real-time updates and notifications

[1335] The device periodically communicates with the server to request updates on real-time information. The server recalculates the schedule based on the new data and sends the updated schedule to the device. The device then uses its notification function to inform the user of the latest schedule.

[1336] Input: Updated real-time data, request data

[1337] Output: Updated schedule and notification information

[1338] These steps will ensure an efficient and comfortable experience at theme parks and brick-and-mortar stores.

[1339] 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.

[1340] The present invention is a system that generates a schedule taking into account a user's emotional state to optimize the user's theme park experience. The system provides an optimal order for visiting attractions based on user input information and real-time data, and further analyzes the user's emotional state using an emotion engine to optimize behavior.

[1341] Overview of program processing

[1342] Collecting user input

[1343] The user enters the following information through the terminal:

[1344] Group information (number of people, age group, etc.)

[1345] A list of favorite attractions

[1346] Break time requests

[1347] Scheduled departure time

[1348] Real-time data collection

[1349] The server collects the following data in real time from the theme park's management system and API:

[1350] Waiting times for each attraction

[1351] Weather information

[1352] Travel time based on walking speed

[1353] Emotion recognition by emotion engine

[1354] The device's built-in emotion engine recognizes the user's emotional state in real time from their facial expressions and voice, and this information is sent to the server via an API.

[1355] Analyzing data and generating schedules

[1356] The server generates a schedule based on user input, real-time data, and emotion data from the emotion engine in the following steps:

[1357] Analyze the user's desired information and set priorities.

[1358] The optimal order of attraction use is calculated based on real-time data and emotional state (e.g., Dijkstra algorithm).

[1359] Adjust the overall schedule to take into account break times, planned dismissal times, and emotional states.

[1360] Schedule provision

[1361] The server sends the generated schedule to the terminal, which then displays it to the user. The schedule is provided in the form of a timetable, clearly indicating the attractions to visit during each time period and break times.

[1362] Real-time updates and notifications

[1363] The device periodically communicates with the server to request real-time information updates.

[1364] The server recalculates the schedule based on new real-time data and the emotional state of the emotion engine, and sends any necessary changes to the device.

[1365] The device notifies users of updates and highlights schedule changes, allowing users to instantly receive real-time information on wait times, attraction cancellations, emotion-based suggestions, and more.

[1366] Specific examples

[1367] For families

[1368] As an example, a case where a family uses the system will be described.

[1369] 1. Collecting user input information

[1370] A family of four users (two adults and two children) enters information into the terminal.

[1371] His favorite attractions are roller coasters, merry-go-rounds, and Ferris wheels.

[1372] We would like to have a one-hour break from 12:00, and plan to leave the school at 18:00.

[1373] 2. Real-time data collection

[1374] The server collects real-time data from the theme park's management system, such as waiting times for roller coasters: 30 minutes, merry-go-rounds: 15 minutes, and ferris wheels: 20 minutes.

[1375] 3. Emotion Recognition by Emotion Engine

[1376] The emotion engine recognizes the user's emotional state from their facial expressions and voice and sends it to the server via API. For example, if a child is recognized as tired, that information is conveyed to the server.

[1377] 4. Data Analysis and Schedule Generation

[1378] The server analyzes the user's desired information, real-time data, and emotional state to optimize the order in which each attraction is used.

[1379] Taking into account break times, expected departure times, and emotional states, we generate a schedule like this:

[1380] 10:00 Roller Coaster

[1381] 11:00 Merry-go-round

[1382] 12:00 Break (Consider children's fatigue and suggest a relaxing rest area)

[1383] 13:00 Ferris wheel

[1384] 5. Providing a schedule

[1385] The terminal displays the generated schedule to the user with family, providing it in the form of a timetable.

[1386] 6. Real-time updates and notifications

[1387] For example, if the wait time for a roller coaster increases to 50 minutes, the device will contact the server and request an updated schedule.

[1388] The server recalculates the schedule based on the new data and emotional state and sends it to the device.

[1389] The device will notify the user of the new schedule and clearly indicate the changes.

[1390] The above is an embodiment of the present invention, and this system allows users to enjoy an efficient and comfortable theme park experience. By adding an emotion recognition function using an emotion engine, flexible suggestions and schedule adjustments based on the user's emotional state become possible, making it possible to provide even more personalized services.

[1391] The processing flow will be explained below.

[1392] Step 1:

[1393] The terminal displays an input form to the user. The user enters group information (number of people, age group, etc.), a list of favorite attractions, desired break time, and planned departure time. When the user finishes entering information, he or she presses the submit button.

[1394] Step 2:

[1395] The device sends the information entered by the user to the server. The data sent is in structured JSON format.

[1396] Step 3:

[1397] The server collects real-time data from the theme park's management system and APIs, including wait times for each attraction, weather information, and travel times based on walking speed.

[1398] Step 4:

[1399] The emotion engine installed in the device recognizes the user's emotional state in real time from their facial expressions and voice. The emotion engine uses sensor devices such as cameras and microphones to acquire the user's emotional data.

[1400] Step 5:

[1401] The device transmits the emotion data acquired by the emotion engine to the server, and the transmitted data is also in a structured format.

[1402] Step 6:

[1403] The server analyzes the input information from the user, real-time data, and emotional data from the emotion engine. It combines the user's wishes with the real-time data and emotional state to set the priority of each attraction.

[1404] Step 7:

[1405] The server calculates the optimal order in which to visit attractions, and optimizes the user's schedule using route optimization algorithms such as the Greedy algorithm and Dijkstra algorithm.

[1406] Step 8:

[1407] The server generates an optimal schedule based on the calculation results. The generated schedule includes designated break times and planned departure times, and also takes into account the user's emotional state.

[1408] Step 9:

[1409] The server generates a schedule and sends it to the terminal. The schedule is in a clear and easy-to-understand timetable format.

[1410] Step 10:

[1411] The device displays a schedule to the user, who then moves around the theme park and enjoys the attractions based on the schedule. During this time, the device continues to monitor the user's emotional state in real time.

[1412] Step 11:

[1413] The device periodically requests the latest real-time and emotional data from the server to keep the schedule updated according to waiting times, weather fluctuations, and changes in emotional state.

[1414] Step 12:

[1415] The server recalculates the schedule based on new real-time data and emotion data, and sends the updated schedule to the device as needed.

[1416] Step 13:

[1417] The device notifies users of schedule updates, for example, via push notifications or alerts, allowing users to react quickly to changes, enabling users to enjoy an optimal theme park experience based on their emotional state.

[1418] Example 2

[1419] 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."

[1420] When visiting a theme park, it is necessary to automatically generate and provide an efficient and comfortable schedule that comprehensively considers a user's group information, favorite attractions, real-time wait times, weather, and the user's emotional state. Conventional systems have difficulty combining these various factors, often forcing users to struggle with cumbersome procedures and schedule adjustments. In particular, the lack of real-time updates and optimization based on emotional state makes it difficult to provide a satisfying user experience.

[1421] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1422] In this invention, the server includes means for inputting user group information, favorite attractions, desired rest periods, and planned time of departure, means for collecting real-time data from the theme park, means for analyzing the user's emotional state using an emotion recognition engine installed in the terminal, means for analyzing the user's input information, the real-time data, and the emotional state and calculating an optimal order for visiting attractions, and means for providing the user with a schedule based on the calculated order of visiting attractions. This makes it possible to provide an efficient and comfortable theme park experience that takes into account the diverse needs and situations of users.

[1423] "User group information" is information about the people accompanying the user when visiting a theme park, including the number of people and their age groups.

[1424] "Favorite Attractions" is a list of attractions within the theme park that the user would like to visit.

[1425] "Desired rest time" refers to the time period and length of time during which the user desires to rest in the theme park.

[1426] The "planned time of departure" is the time when the user plans to leave the theme park.

[1427] "Real-time theme park data" refers to data that is collected instantly, such as waiting times for attractions within the theme park, weather information, and travel times based on walking speed.

[1428] An "emotion recognition engine" is a software or hardware mechanism that is installed on a device and analyzes the user's facial expressions and voice to recognize their emotional state.

[1429] A "schedule" is a plan that summarizes attractions to visit, rest times, etc. in the form of a timetable so that the user can visit the theme park efficiently and comfortably.

[1430] "Providing a schedule" is the process in which the server sends the generated schedule to the terminal so that the user can check it.

[1431] This invention is a system that generates a schedule taking into account the user's emotional state in order to optimize the user's theme park experience. The entire system consists of a server, a terminal, and an emotion recognition engine.

[1432] Collecting user input

[1433] The user inputs group information (number of people, age group, etc.), a list of favorite attractions, desired rest time, and planned time to leave the park through the terminal. The terminal then transmits this input information to the server.

[1434] Real-time data collection

[1435] The server collects real-time data via the theme park's management system and API, including:

[1436] Waiting times for each attraction

[1437] Weather information

[1438] Travel time based on walking speed

[1439] Emotion recognition by emotion engine

[1440] The emotion recognition engine installed in the device recognizes the user's facial expressions and voice in real time. This recognition data is sent to the server via API. The emotion recognition engine includes facial expression analysis software and voice analysis software.

[1441] Analyzing data and generating schedules

[1442] The server analyzes user input, real-time data, and emotion data obtained from an emotion recognition engine all at once. Based on this analysis, it sets priorities and uses an algorithm (e.g., Dijkstra algorithm) to determine the optimal order in which attractions should be used. Furthermore, it adjusts the overall schedule, taking into account break times, planned departure times, and the user's emotional state.

[1443] Schedule provision

[1444] The schedule generated by the server is sent to the terminal and displayed to the user in the form of a timetable, allowing the user to easily check the attractions to be visited and break times via their smartphone or tablet.

[1445] Real-time updates and notifications

[1446] The device periodically communicates with the server to request new real-time information. The server recalculates the schedule based on the latest real-time data and emotion data. If necessary, the server sends a new schedule to the device, which then notifies the user of the updated information. This allows users to instantly receive information such as real-time changes in waiting times, attraction cancellations, and suggestions based on the user's emotions.

[1447] Specific examples

[1448] For families

[1449] A family of users (two adults and two children) visiting a theme park uses the system as follows:

[1450] 1. Collecting input information: Log in to the terminal and enter the number of people in your family, your favorite attraction (roller coaster, merry-go-round, Ferris wheel), break time (1 hour from 12 noon), and planned time to leave the park (6 p.m.).

[1451] 2. Real-time data collection: The server collects the waiting time for each attraction (e.g., 30 minutes for roller coaster, 15 minutes for merry-go-round, 20 minutes for Ferris wheel) in real time from the theme park's management system.

[1452] 3. Emotion recognition: The device camera captures the child's facial expression, and the emotion recognition engine recognizes "fatigue." This data is sent to the server.

[1453] 4. Schedule Generation: Based on this data, the server calculates the order in which each attraction should be visited and generates the following schedule:

[1454] 10:00 Roller Coaster

[1455] 11:00 Merry-go-round

[1456] 12:00 Break (Area for children to relax as they are tired)

[1457] 13:00 Ferris wheel

[1458] 5. Providing the schedule: The terminal displays the generated schedule to the user in the form of a timetable.

[1459] 6. Real-time updates and notifications: Devices periodically communicate with the server and schedules are updated based on new data. For example, if the waiting time for a roller coaster changes to 50 minutes, a new schedule will be generated.

[1460] Prompt Sentence Examples

[1461] Here are some examples of prompts to input to the generative AI model:

[1462] "Generate an example of a day's schedule for a family (2 adults, 2 children) at a theme park based on the following information: roller coaster (wait time 30 minutes), merry-go-round (wait time 15 minutes), ferris wheel (wait time 20 minutes). The emotion engine recognizes that the children are tired. The break time is 1 hour from 12 noon, and the planned departure time is 6:00 PM."

[1463] The above is an embodiment of the present invention, and this system allows users to enjoy an efficient and comfortable theme park experience. By using an emotion recognition engine, flexible suggestions and schedule adjustments based on the user's emotional state can be made, and more personalized services can be provided.

[1464] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1465] Step 1: Collecting User Input

[1466] 1. Start typing:

[1467] Users launch the application on their device and log in using their account information. They input information such as the number of people in their family or group, their age group, a list of their favorite attractions, desired rest times, and the planned time to leave the park.

[1468] Input: User's demographic information, desired attraction, break time, and departure time

[1469] Output: The input information is sent to the server

[1470] Step 2: Collect real-time data

[1471] 1. Data Request:

[1472] The server sends data requests to the theme park's management system and API, specifically requesting wait times for each attraction, weather information, and predicted travel times based on walking speed.

[1473] Input: Server data request

[1474] Output: Real-time data from theme park management systems

[1475] 2. Data Collection:

[1476] The server receives real-time data such as waiting times, weather information, and travel times from the management system or API and stores it in a database.

[1477] Input: Real-time data

[1478] Output: Real-time data stored in a database

[1479] Step 3: Emotion recognition by the emotion engine

[1480] 1. Emotional data collection:

[1481] The device's camera and microphone are used to capture the user's facial expressions and voice, and this data is fed into the emotion engine.

[1482] Input: Real-time user facial and voice data

[1483] Output: Raw data sent to the sentiment engine

[1484] 2. Sentiment analysis:

[1485] The emotion engine analyzes the captured data and recognizes the user's emotional state, for example, detecting a smile indicates "happiness" and a frown indicates "fatigue."

[1486] Input: Raw data (facial expressions and voice)

[1487] Output: Perceived emotional state

[1488] 3. Emotional data transmission:

[1489] The device sends the recognized emotion data to the server via API.

[1490] Input: Recognized emotion data

[1491] Output: Emotion data sent to the server

[1492] Step 4: Analyze data and generate a schedule

[1493] 1. Data Integration:

[1494] The server integrates user input information, real-time data, and emotional data, enabling comprehensive analysis.

[1495] Input: User input, real-time data, emotional data

[1496] Output: A consolidated dataset

[1497] 2. Priority settings:

[1498] The server sets priorities for attractions based on the user's desired information.

[1499] Input: Integrated dataset

[1500] Output: A prioritized list of attractions

[1501] 3. Schedule optimization:

[1502] The server uses algorithms such as Dijkstra's algorithm to calculate the optimal order in which to visit attractions, thereby minimizing waiting times and travel times.

[1503] Input: Attraction priority list, consolidated data

[1504] Output: Optimized attraction usage order

[1505] 4. Overall schedule adjustment:

[1506] The server adjusts the overall schedule taking into account break times, departure times, and the user's emotional state, for example, by shortening break times based on the user's emotional state.

[1507] Input: Optimized attraction order, user's desired time

[1508] Output: Adjusted overall schedule

[1509] Step 5: Provide a schedule

[1510] 1. Schedule generation:

[1511] The server creates an optimized and coordinated schedule, including attractions to visit, break times, travel times, etc.

[1512] Input: Adjusted overall schedule

[1513] Output: The generated schedule

[1514] 2. Data transmission:

[1515] The server transmits the generated schedule to the terminal.

[1516] Input: Generated schedule

[1517] Output: Schedule sent to the terminal

[1518] 3.Display:

[1519] The terminal displays the received schedule in a timetable format to the user, allowing the user to check the attractions to be visited and break times.

[1520] Input: Schedule sent to the terminal

[1521] Output: The schedule as seen by the user

[1522] Step 6: Real-time updates and notifications

[1523] 1. Regular communication:

[1524] The device periodically communicates with the server to request updates on the latest real-time data and emotion data.

[1525] Input: Update request

[1526] Output: Latest data

[1527] 2. Recalculate the schedule:

[1528] The server recalculates the existing schedule based on new real-time data and emotion data, and generates new schedules as needed.

[1529] Input: Latest real-time data, sentiment data

[1530] Output: Recalculated schedule

[1531] 3. Schedule Update:

[1532] The server transmits the newly generated schedule to the terminal.

[1533] Input: Recalculated schedule

[1534] Output: Update schedule sent to the device

[1535] 4. Notice:

[1536] The device notifies the user of schedule changes, allowing the user to take action based on the latest situation.

[1537] Input: Updated schedule

[1538] Output: Changes notified to the user

[1539] These are the processing steps of the system's program. It is possible to provide an optimal schedule by comprehensively analyzing user input, real-time data, and emotional data. This process allows users to enjoy an efficient and comfortable theme park experience.

[1540] (Application example 2)

[1541] 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."

[1542] Modern theme parks and shopping malls are required to provide optimal experiences for visitors. However, conventional systems have difficulty not only taking real-time information into account but also flexibly adjusting schedules based on the user's emotional state. This often leads to stress and a disappointing experience for users. It has also been difficult to accurately predict congestion and waiting times at theme parks and shopping malls and suggest optimal routes and stores. To solve these problems, a system is needed that can analyze users' real-time behavior and emotions in an integrated manner and provide optimal schedules.

[1543] 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 inputting a user's group information, favorite attractions, desired rest time, and planned departure time, means for collecting real-time data about the theme park, means for analyzing the user's input information and the real-time data and calculating an optimal order for visiting attractions, means for providing the user with a schedule based on the calculated order of visits, means for recognizing the user's emotional state in real time and optimizing the schedule based on the emotional state, and means for providing a shopping route based on real-time store information from online stores and the user's emotional state. This enables the user to have an optimal theme park experience and shopping experience tailored to their emotional state.

[1544] "User group information" is information about the entire group, such as the number of users and their age groups.

[1545] "Favorite attractions" is a list of attractions in which the user has particular interests or concerns.

[1546] "Desired break time" is information about the specific time or period when the user wishes to take a break.

[1547] The "planned time of departure" is the time when the user plans to leave the theme park.

[1548] "Real-time theme park data" refers to the latest information about theme parks, such as current wait times for attractions, weather information, and walking speeds.

[1549] "Emotional state" refers to the current emotion recognized from the user's facial expression and voice, and includes, for example, stress level and fatigue level.

[1550] A "shopping route" is an optimal route for a user to efficiently navigate around a shopping mall or store.

[1551] "Real-time updates" means constantly updating systems and data based on the latest information.

[1552] The present invention is a system for optimizing a user's theme park and shopping experience. The system analyzes a user's input information, real-time data, and emotional state to provide optimal attractions and shopping routes. The following description details a specific embodiment of the system.

[1553] 1. Collecting user input information

[1554] The device (e.g. smartphone or tablet) collects the following information from the user:

[1555] Group information (number of people, age group, etc.)

[1556] A list of your favorite attractions and products

[1557] Break time requests

[1558] Scheduled time of leaving the park or store

[1559] 2. Real-time data collection

[1560] The server collects the following real-time data from the theme park and shopping mall management systems and public APIs:

[1561] Waiting times for each attraction

[1562] Current Weather Information

[1563] Store congestion status and sales information

[1564] Travel time based on user walking speed

[1565] 3. Emotion Recognition by Emotion Engine

[1566] An emotion engine (specifically, the EmotionEngine library) installed on the device recognizes the user's emotional state in real time from their facial expressions and voice. This information is sent to the server via an API. For example, if the user is tired or stressed, that information is communicated to the server.

[1567] 4. Data Analysis and Optimization

[1568] The server generates the optimal order of attractions and shopping routes based on the user's input information, collected real-time data, and emotion data from the emotion engine. This includes the following steps:

[1569] Analyze user preferences and set priorities

[1570] Calculate the optimal order of attractions and stores based on real-time data and emotional state (e.g., Dijkstra algorithm)

[1571] Adjust the overall schedule taking into account break times and planned departure times

[1572] 5. Providing a schedule

[1573] The server generates a schedule and sends it to the device, which then displays it to the user in the form of a timetable, clearly indicating the attractions and shops to visit during each time period, as well as break times.

[1574] 6. Real-time updates and notifications

[1575] The device periodically communicates with the server to request updates of real-time information. The server recalculates the schedule based on the new real-time data and the emotional state of the emotion engine, and sends any necessary changes to the device, allowing the user to see the changes immediately.

[1576] Specific examples

[1577] For families

[1578] 1. Collection of information:

[1579] A family of four users enters information into the terminal. They select roller coaster, merry-go-round, and Ferris wheel as their preferred attractions. They request a one-hour break from 12:00 and plan to leave the park at 18:00.

[1580] 2. Real-time data:

[1581] The waiting time for the roller coaster is 30 minutes, the merry-go-round is 15 minutes, and the Ferris wheel is 20 minutes.

[1582] 3. Emotional state:

[1583] The emotion engine recognizes fatigue from the user's facial expression.

[1584] 4. Optimization:

[1585] The server generates a schedule and sets the roller coaster at 10:00, the merry-go-round at 11:00, the break at 12:00, and the Ferris wheel at 13:00.

[1586] 5.Display:

[1587] It displays the timetable on the device and sends necessary notifications.

[1588] Prompt Sentence Examples

[1589] Write Python code that takes into account unique user information, real-time data, and emotion recognition results to provide an optimal shopping experience schedule. The schedule includes the following items: time, store name, and wait time. Using the user's preferred categories and their real-time data, suggest appropriate break times based on the user's emotional state.

[1590] The above is a specific embodiment of the present invention. This system enables flexible schedule adjustment based on the user's emotional state, providing a more comfortable and efficient experience.

[1591] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1592] Step 1:

[1593] The terminal collects input information from the user, such as group information (number of people, age group), a list of favorite attractions, desired rest periods, and planned departure time. This information serves as the basis for the system to understand the user's preferences and plans and generate a personalized schedule.

[1594] Input: Number of users, age group, list of favorite attractions, desired break time, planned time to leave the park

[1595] Output: A dataset of user-entered information

[1596] Specific behavior:

[1597] The terminal displays an information input form through a user interface.

[1598] The user enters the required information into the form and presses the "Submit" button.

[1599] The terminal collects the input information and sends it to the server as a data set.

[1600] Step 2:

[1601] The server collects real-time data from theme parks and shopping malls, including attraction wait times, weather information, store occupancy and sales information, and user walking speeds. This data is collected using APIs.

[1602] Input: Theme park and shopping mall APIs

[1603] Output: Real-time data

[1604] Specific behavior:

[1605] The server periodically sends requests to the API to retrieve the latest real-time data.

[1606] The collected data is organized on the server and prepared for analysis.

[1607] Step 3:

[1608] The device's built-in emotion engine recognizes the user's emotional state in real time from their facial expressions and voice. This information is sent to the server via an API. For example, the user's fatigue level and stress level can be recognized.

[1609] Input: User's facial expressions and voice data

[1610] Output: Emotional state data

[1611] Specific behavior:

[1612] The device's camera and microphone are used to collect the user's facial expressions and voice.

[1613] An emotion engine (such as the EmotionEngine library) analyzes this data and identifies the emotional state.

[1614] The recognized emotional state data is transmitted to a server.

[1615] Step 4:

[1616] The server analyzes user input, real-time data, and emotional data to generate the optimal order of attractions and shopping routes, using algorithms such as Dijkstra's algorithm.

[1617] Input: User-entered information, real-time data, emotional state data

[1618] Output: Optimal schedule (order of attractions, shopping route)

[1619] Specific behavior:

[1620] The server integrates the various collected data and runs optimization algorithms.

[1621] The optimal order of use is calculated taking into account the waiting time at each attraction and store, the level of congestion, and the user's emotional state.

[1622] Adjust the overall schedule, taking into account break times and planned dismissal times.

[1623] Step 5:

[1624] The server transmits the generated schedule to the terminal, which displays it to the user in the form of a timetable.

[1625] Input: Optimal schedule

[1626] Output: Schedule display in timetable format

[1627] Specific behavior:

[1628] The server transmits the generated schedule data to the terminal.

[1629] The terminal visually displays the schedule in a timetable format, allowing users to act based on this display.

[1630] Step 6:

[1631] The device periodically communicates with the server to request real-time updates. The server recalculates the schedule based on the new data and emotional state, and sends any necessary changes to the device, where the user can immediately see the changes.

[1632] Input: Regular real-time data and emotional state data

[1633] Output: Updated schedule

[1634] Specific behavior:

[1635] The terminal requests real-time data updates from the server at regular intervals.

[1636] The server retrieves the new data and analyzes the emotional state again.

[1637] Recalculate the schedule as needed and send updates to the terminal.

[1638] The terminal notifies the user of the updated schedule and displays the changes.

[1639] The above are the specific processing steps in the program of the system of the present invention, which allows the user to always have the most optimal theme park and shopping experience based on the latest information and emotional state.

[1640] 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.

[1641] 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.

[1642] 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.

[1643] [Fourth embodiment]

[1644] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1645] 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.

[1646] 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).

[1647] 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.

[1648] 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.

[1649] 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).

[1650] 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.

[1651] 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.

[1652] 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.

[1653] 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.

[1654] 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.

[1655] 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.

[1656] 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."

[1657] The present invention is a system for optimizing a user's theme park experience by combining input information from the user with theme park data collected in real time to provide an efficient schedule. This system is realized through the cooperation of terminals and a server.

[1658] Overview of program processing

[1659] Collecting user input

[1660] The user enters the following information through the terminal:

[1661] Group information (number of people, age group, etc.)

[1662] A list of favorite attractions

[1663] Break time requests

[1664] Scheduled departure time

[1665] Real-time data collection

[1666] The server will interface with the theme park's management system and collect the following data in real time:

[1667] Waiting times for each attraction

[1668] Weather information

[1669] Travel time based on walking speed

[1670] Analyzing data and generating schedules

[1671] The server generates a schedule based on user input and real-time data in the following steps:

[1672] Analyze the user's desired information and set priorities.

[1673] Calculate the optimal order for visiting attractions based on real-time data (e.g., Dijkstra algorithm).

[1674] Adjust the overall schedule taking into account break times and planned departure times.

[1675] Schedule provision

[1676] The server sends the generated schedule to the terminal, which then displays it to the user. The schedule is provided in the form of a timetable, clearly indicating the attractions to visit during each time period and break times.

[1677] Real-time updates and notifications

[1678] The device periodically communicates with the server to request real-time information updates.

[1679] The server recalculates the schedule based on the new real-time data and sends any necessary changes to the terminal.

[1680] The device notifies users of updates and clearly shows any changes to the schedule, allowing users to receive real-time information on changes in wait times, attraction cancellations, and more.

[1681] Specific examples

[1682] For families

[1683] As an example, a case where a family uses the system will be described.

[1684] 1. Collecting user input information

[1685] The user inputs information into the terminal that the user is a family of four (two adults and two children).

[1686] His favorite attractions are roller coasters, merry-go-rounds, and Ferris wheels.

[1687] We would like to have a one-hour break from 12:00, and plan to leave the school at 18:00.

[1688] 2. Real-time data collection

[1689] The server collects real-time data from the theme park's management system, such as waiting times for roller coasters: 30 minutes, merry-go-rounds: 15 minutes, and ferris wheels: 20 minutes.

[1690] 3. Data Analysis and Schedule Generation

[1691] The server analyzes the user's desired information and optimizes the order in which each attraction is visited.

[1692] Taking into account break times and planned departure times, we generate a schedule like this:

[1693] 10:00 Roller Coaster

[1694] 11:00 Merry-go-round

[1695] 12:00 Break

[1696] 13:00 Ferris wheel

[1697] 4. Providing a schedule

[1698] The terminal displays the generated schedule to the user with family, providing it in the form of a timetable.

[1699] 5. Real-time updates and notifications

[1700] For example, if the wait time for a roller coaster increases to 50 minutes, the device will contact the server and request an updated schedule.

[1701] The server recalculates the schedule based on the new data and sends it to the terminal.

[1702] The device will notify the user of the new schedule and clearly indicate the changes.

[1703] The above is an embodiment of the present invention, and this system allows users to enjoy an efficient and comfortable theme park experience.

[1704] The processing flow will be explained below.

[1705] Step 1:

[1706] The terminal displays an input form to the user. The user enters group information (number of people, age group, etc.), a list of favorite attractions, desired break time, and planned departure time. When the user finishes entering information, he or she presses the submit button.

[1707] Step 2:

[1708] The device sends the information entered by the user to the server. The data sent is in structured JSON format.

[1709] Step 3:

[1710] The server collects real-time data from the theme park's management system and APIs, including wait times for each attraction, weather information, and travel times based on walking speed.

[1711] Step 4:

[1712] The server analyzes the input information from the user and the collected real-time data, and sets the priority of each attraction by linking the user's preferences with the real-time data.

[1713] Step 5:

[1714] The server calculates the optimal order in which to visit attractions, and optimizes the user's schedule using route optimization algorithms such as the Greedy algorithm and Dijkstra algorithm.

[1715] Step 6:

[1716] The server generates an optimal schedule based on the calculation results, which incorporates the specified break times and planned departure times.

[1717] Step 7:

[1718] The server generates a schedule and sends it to the terminal. The schedule is in a clear and easy-to-understand timetable format.

[1719] Step 8:

[1720] The terminal displays the schedule to the user, who then moves around the theme park according to the schedule and enjoys the attractions.

[1721] Step 9:

[1722] The device periodically requests the latest real-time data from the server to ensure the schedule is up-to-date with fluctuations in waiting times and weather.

[1723] Step 10:

[1724] The server recalculates the schedule based on new real-time data and sends the updated schedule to the device as needed.

[1725] Step 11:

[1726] The device notifies the user of schedule updates, for example, via push notifications or alerts, so that the user can respond quickly.

[1727] Example 1

[1728] 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."

[1729] In traditional theme park experiences, users had to check attraction wait times, weather, and travel times themselves, and then create a schedule based on that information. However, it was difficult to manually check and appropriately reflect this data, which fluctuates in real time, making efficient scheduling difficult. In particular, for large groups such as families, it is not easy to efficiently move around while satisfying everyone's wishes. This resulted in a decline in the quality of the user experience.

[1730] 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.

[1731] In this invention, the server includes means for inputting user group information, favorite video content, desired break times, and scheduled end times, means for collecting real-time data about the theme park, means for analyzing the user's input information and the real-time data and calculating an optimal video content viewing order, means for providing the user with a schedule based on the calculated viewing order, and means for updating and notifying the user of the schedule in real time via the user's terminal, thereby enabling the user to automatically receive an optimized schedule in real time and efficiently tour the theme park.

[1732] "User" refers to an individual or group who uses the theme park.

[1733] "Group information" refers to data including information such as the number of users, age range, and relationships.

[1734] "Favorite video content" refers to the types and lists of attractions and shows that the user wishes to view.

[1735] "Rest time" refers to a period of time set by the user for rest during their visit to the theme park.

[1736] "Scheduled end time" refers to the time the user plans to leave the theme park.

[1737] "Real-time theme park data" refers to the latest information at the moment, such as waiting times for each attraction within the theme park, operation status, weather information, and user travel times.

[1738] "Server" refers to a computer system that processes user input information and real-time data, and generates and manages optimal schedules.

[1739] "Terminal" refers to a device that allows a user to input information and view a generated schedule.

[1740] "Schedule" refers to an optimized theme park tour plan based on user preferences and real-time data.

[1741] "Viewing order" refers to the optimal order in which attractions and shows are viewed, calculated based on user preferences and real-time data.

[1742] "Notification" refers to the act of sending the latest schedule changes and alerts from the server to the user via the device.

[1743] The present invention is a system for optimizing a user's theme park experience by combining input information from the user with theme park data collected in real time to provide an efficient schedule. This system is realized through the cooperation of terminals and a server.

[1744] Specifically, users use their devices to input group information (number of people, age group, etc.), a list of their favorite attractions, desired rest times, and planned time to leave the park. This information is sent from the devices to the server. The server collects real-time data from the theme park's management system and weather information API. This real-time data includes waiting times for each attraction, operation status, weather information, and travel times based on the user's walking speed.

[1745] The server analyzes the input information sent by the user and the collected real-time data, and optimizes the order in which the attractions can be visited based on the user's preferences. For example, it calculates the optimal order using an algorithm such as Dijkstra's algorithm. The generated schedule is sent from the server to the terminal, which displays it to the user in the form of a timetable.

[1746] The terminal also periodically communicates with the server to request updates to real-time information. The server recalculates the schedule based on the latest real-time data and, if necessary, sends the revised schedule to the terminal. The terminal then notifies the user of the updated information and clearly indicates any changes to the schedule. This allows the user to immediately receive information on real-time changes in waiting times, attraction cancellations, and other such information.

[1747] Specific examples

[1748] Families can use the system by following these steps:

[1749] 1. Collecting user input information

[1750] The user inputs information into the terminal that the user is a family of four (two adults and two children).

[1751] His favorite attractions are roller coasters, merry-go-rounds, and Ferris wheels.

[1752] We would like to have a one-hour break from 12:00, and plan to leave the school at 18:00.

[1753] 2. Real-time data collection

[1754] The server collects real-time data from the theme park's management system, such as waiting times for roller coasters: 30 minutes, merry-go-rounds: 15 minutes, and ferris wheels: 20 minutes.

[1755] Also, sunny weather data is acquired as weather information.

[1756] 3. Data Analysis and Schedule Generation

[1757] The server analyzes the user's preferences and optimizes the order in which each attraction is visited. Taking into account break times and the planned time of departure, the server generates the following schedule:

[1758] 10:00 Roller Coaster

[1759] 11:00 Merry-go-round

[1760] 12:00 Break

[1761] 13:00 Ferris wheel

[1762] 4. Providing a schedule

[1763] The server transmits the generated schedule to the terminal, which displays it to the user in the form of a timetable.

[1764] 5. Real-time updates and notifications

[1765] For example, if the wait time for a roller coaster increases to 50 minutes, the device contacts the server and requests an updated schedule. The server recalculates the schedule based on the new data and sends it to the device. The device then notifies the user of the new schedule and clearly indicates the changes.

[1766] Prompt Sentence Examples

[1767] Below is an example of a prompt sentence to input to the generative AI model.

[1768] A family of four users (two adults and two children) goes to a theme park. Their favorite attractions are the roller coaster, merry-go-round, and Ferris wheel. They would like to take a one-hour break from noon, and plan to leave the park at 6:00 PM. Real-time data shows the waiting time for the roller coaster is 30 minutes, the merry-go-round is 15 minutes, the Ferris wheel is 20 minutes, and the weather is sunny. Based on this information, please generate the optimal schedule.

[1769] This system allows users to enjoy an efficient and comfortable theme park experience.

[1770] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1771] Step 1:

[1772] Collecting user input

[1773] Users enter information about their visit to the theme park into the device, including group information (number of people, age group), a list of favorite attractions, break times, and planned time to leave. The data is stored on the device and sent to a server for later analysis.

[1774] Input: Group information, attraction list, break times, planned departure time

[1775] Output: A dataset containing the user's input information

[1776] Step 2:

[1777] Real-time data collection

[1778] The server works with the theme park's management system to collect real-time data, such as waiting times for each attraction, operation status, weather information, and user travel time. This data is then analyzed. The server periodically calls the theme park's real-time data API to obtain the latest information.

[1779] Input: Real-time Data API endpoint

[1780] Output: Real-time data (waiting time, weather information, operation status, travel time)

[1781] Step 3:

[1782] Analyzing data and generating schedules

[1783] The server performs analysis based on the user's input information and real-time data. It first analyzes the user's desired information and sets the priority of each attraction. It then calculates the optimal order in which the attractions should be used based on the real-time data. For example, it uses Dijkstra's algorithm to calculate the shortest time for the entire route. The server uses an optimization algorithm to generate a schedule that meets the user's wishes.

[1784] Input: User input information, real-time data

[1785] Output: Optimized schedule

[1786] Step 4:

[1787] Schedule provision

[1788] The server sends the generated schedule to the terminal, which analyzes it and displays it to the user in the form of a timetable. A graphical interface is provided so that the user can check the schedule. A system is also included that notifies the user when the schedule is changed.

[1789] Input: Optimized schedule

[1790] Output: Schedule display in timetable format

[1791] Step 5:

[1792] Real-time updates and notifications

[1793] The terminal periodically communicates with the server to request updates with new real-time data. The server recalculates the schedule based on the latest data and sends the new schedule to the terminal. The terminal then notifies the user of the new schedule information and displays details of any changes. This allows the user to receive real-time information on changes in waiting times and attraction cancellations.

[1794] Input: Real-time data, schedule recalculation request

[1795] Output: Updated schedule, notification to users

[1796] The above is the specific process flow and the operations at each step. This system enables users to have an efficient and comfortable experience in the theme park.

[1797] (Application example 1)

[1798] 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."

[1799] The present invention relates to a schedule generation system for optimizing user experiences at commercial facilities such as theme parks. Conventional theme park systems have faced problems, such as difficulty in efficiently viewing attractions in the order desired by users, and waiting times and congestion can hinder efficient enjoyment. Similarly, physical stores such as shopping centers face the same problem of inconvenience caused by fluctuations in inventory information and congestion when users are trying to efficiently purchase products. In response to these problems, the present invention aims to solve common issues at theme parks and physical stores by combining user input information with real-time data.

[1800] 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.

[1801] In this invention, the server includes means for inputting user group information, favorite attractions, desired rest periods, and planned time of departure, means for collecting real-time data about the theme park, means for analyzing the user's input information and the real-time data to calculate an optimal order for visiting attractions, means for providing the user with a schedule based on the calculated order of visits, means for collecting inventory information and congestion information based on the data to calculate an optimal order for purchasing products, means for providing the user with a shopping schedule based on the optimal order for purchasing products, and means for updating the shopping schedule in real time and notifying the user. This enables efficient use of attractions in the theme park and efficient purchases at physical stores.

[1802] "User group information" refers to attribute information such as the number of people in the group to which the user belongs and their age group.

[1803] "Favorite attractions" refers to a list of attractions that the user particularly wishes to experience.

[1804] The "desired break time" is a time period designated in advance by the user during which the user wishes to take a break.

[1805] "Scheduled departure time" refers to the time when the user plans to leave the theme park.

[1806] "Real-time theme park data" refers to various data collected in real time within a theme park, such as waiting times for attractions and weather information.

[1807] "Inventory information" refers to information about the current inventory status of each product in the store.

[1808] "Crowd information" refers to information about the current congestion situation in each area of ​​a theme park or physical store.

[1809] The "optimal order of attractions" refers to the order in which a user can efficiently experience attractions, calculated based on the user's input information and real-time data.

[1810] The "optimal product purchasing order" is the order in which a user can efficiently purchase products, calculated based on inventory information and congestion information.

[1811] A "shopping schedule" is a schedule that includes the optimal order of purchasing products within a commercial facility, calculated based on user input information and real-time data.

[1812] "Means for real-time updates" refers to a mechanism in which the server recalculates the schedule based on new data and provides it to the user immediately.

[1813] The present invention relates to a system for optimizing user experiences at theme parks and brick-and-mortar stores. The system is implemented using the following hardware and software.

[1814] Hardware and software used

[1815] 1. User device: Smartphone (e.g. iPhone, Android Phone)

[1816] 2. Server: Cloud server (e.g. AWS, Google Cloud)

[1817] 3. Frontend: React Native, Flutter

[1818] 4. Backend: Python, Django / Flask

[1819] 5. Database: PostgreSQL

[1820] 6. Notification System: Firebase Cloud Messaging

[1821] System Overview

[1822] 1. Collecting user input information

[1823] Users use a smartphone app to input information such as group details, favorite attractions, desired rest times, and planned time to leave the park, which is then sent to a server and stored in a database.

[1824] 2. Real-time data collection

[1825] The server collects real-time data from IoT sensors in theme park management systems and physical stores, including wait times for each attraction, weather information, product availability, and congestion information for each area.

[1826] 3. Data Analysis and Schedule Generation

[1827] The server analyzes the user's input information and real-time data to calculate the optimal order of attractions and product purchases for the user. Specific algorithms used are shortest path algorithms such as Dijkstra's algorithm.

[1828] 4. Providing a schedule

[1829] The server generates a schedule, which is sent to a smartphone app and displayed to the user in the form of a timetable, which clearly indicates the order and times for each attraction and product purchase.

[1830] 5. Real-time updates and notifications

[1831] The smartphone app periodically communicates with the server to request updates on real-time information. The server recalculates the schedule based on the new real-time data and notifies the user of the updated schedule. This allows users to enjoy an optimal experience based on the most up-to-date information.

[1832] Specific examples

[1833] As an example, a case where a user efficiently shops at a physical store will be described.

[1834] 1. Collecting user input information

[1835] Using the app, users input a list of items they want to buy (e.g., milk, bread, eggs), group information (two adults, two children), and desired shopping time (e.g., two hours).

[1836] 2. Real-time data collection

[1837] The server collects real-time inventory information for each product and congestion information for each area of ​​the store from the store's management system and IoT sensors.

[1838] 3. Data Analysis and Schedule Generation

[1839] The server analyzes the user's input information and calculates the optimal product purchase order based on inventory and congestion information. For example, it uses Dijkstra's algorithm to generate a route that allows the user to efficiently obtain products.

[1840] 4. Providing a schedule

[1841] The server generates a schedule, which is sent to a smartphone app and displayed to the user in a timetable format. The schedule clearly indicates the time and order in which each item can be purchased.

[1842] 5. Real-time updates and notifications

[1843] For example, if bread stocks run low or a particular area of ​​the store becomes busy, the smartphone app communicates with the server and requests an updated schedule. The server recalculates the schedule based on the new data and sends it to the app. The app then notifies the user of the changed schedule, ensuring they receive instant updates.

[1844] Prompt Sentence Examples

[1845] Generate your shopping schedule using the following information:

[1846] User ID: 123

[1847] Group Information: 2 adults, 2 children

[1848] Shopping list: milk, bread, eggs

[1849] Likes: Electronics, toys

[1850] Desired shopping time: 2 hours

[1851] These steps allow users to enjoy an efficient and stress-free experience at theme parks and brick-and-mortar stores.

[1852] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1853] Step 1:

[1854] Collecting user input

[1855] Using a smartphone app, users input information about their group, their favorite attractions, desired rest time, planned time of departure, and a list of items they wish to purchase. The device temporarily stores this data and sends it to the server.

[1856] Input: User's group information, favorite attractions, desired rest time, planned departure time, list of items desired for purchase

[1857] Output: User data sent to the server

[1858] Step 2:

[1859] Real-time data collection for theme parks and brick-and-mortar stores

[1860] The server collects real-time data from the theme park's management system and IoT sensors in physical stores. This data includes waiting times for each attraction, weather information, product inventory status, and store congestion information. The server stores this data in a database.

[1861] Input: Real-time data from theme parks and physical stores (attraction waiting times, weather information, inventory status, crowd information)

[1862] Output: Real-time data stored in a database

[1863] Step 3:

[1864] Analyzing data and generating schedules

[1865] The server analyzes the user's input information and real-time data. Using shortest path algorithms such as Dijkstra's algorithm, it calculates the optimal order for the user to visit attractions and purchase products. Based on the analysis results, it generates a schedule and formats it into a timetable.

[1866] Input: User data, real-time data

[1867] Output: Schedule in timetable format

[1868] Step 4:

[1869] Schedule provision

[1870] The server sends the generated schedule to the smartphone app, which then displays it to the user. The timetable includes the order in which each attraction should be visited and the order and specific times for purchasing merchandise.

[1871] Input: Schedule data

[1872] Output: Timetable displayed on smartphone app

[1873] Step 5:

[1874] Real-time updates and notifications

[1875] The device periodically communicates with the server to request updates on real-time information. The server recalculates the schedule based on the new data and sends the updated schedule to the device. The device then uses its notification function to inform the user of the latest schedule.

[1876] Input: Updated real-time data, request data

[1877] Output: Updated schedule and notification information

[1878] These steps will ensure an efficient and comfortable experience at theme parks and brick-and-mortar stores.

[1879] 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.

[1880] The present invention is a system that generates a schedule taking into account a user's emotional state to optimize the user's theme park experience. The system provides an optimal order for visiting attractions based on user input information and real-time data, and further analyzes the user's emotional state using an emotion engine to optimize behavior.

[1881] Overview of program processing

[1882] Collecting user input

[1883] The user enters the following information through the terminal:

[1884] Group information (number of people, age group, etc.)

[1885] A list of favorite attractions

[1886] Break time requests

[1887] Scheduled departure time

[1888] Real-time data collection

[1889] The server collects the following data in real time from the theme park's management system and API:

[1890] Waiting times for each attraction

[1891] Weather information

[1892] Travel time based on walking speed

[1893] Emotion recognition by emotion engine

[1894] The device's built-in emotion engine recognizes the user's emotional state in real time from their facial expressions and voice, and this information is sent to the server via an API.

[1895] Analyzing data and generating schedules

[1896] The server generates a schedule based on user input, real-time data, and emotion data from the emotion engine in the following steps:

[1897] Analyze the user's desired information and set priorities.

[1898] The optimal order of attraction use is calculated based on real-time data and emotional state (e.g., Dijkstra algorithm).

[1899] Adjust the overall schedule to take into account break times, planned dismissal times, and emotional states.

[1900] Schedule provision

[1901] The server sends the generated schedule to the terminal, which then displays it to the user. The schedule is provided in the form of a timetable, clearly indicating the attractions to visit during each time period and break times.

[1902] Real-time updates and notifications

[1903] The device periodically communicates with the server to request real-time information updates.

[1904] The server recalculates the schedule based on new real-time data and the emotional state of the emotion engine, and sends any necessary changes to the device.

[1905] The device notifies users of updates and highlights schedule changes, allowing users to instantly receive real-time information on wait times, attraction cancellations, emotion-based suggestions, and more.

[1906] Specific examples

[1907] For families

[1908] As an example, a case where a family uses the system will be described.

[1909] 1. Collecting user input information

[1910] A family of four users (two adults and two children) enters information into the terminal.

[1911] His favorite attractions are roller coasters, merry-go-rounds, and Ferris wheels.

[1912] We would like to have a one-hour break from 12:00, and plan to leave the school at 18:00.

[1913] 2. Real-time data collection

[1914] The server collects real-time data from the theme park's management system, such as waiting times for roller coasters: 30 minutes, merry-go-rounds: 15 minutes, and ferris wheels: 20 minutes.

[1915] 3. Emotion Recognition by Emotion Engine

[1916] The emotion engine recognizes the user's emotional state from their facial expressions and voice and sends it to the server via API. For example, if a child is recognized as tired, that information is conveyed to the server.

[1917] 4. Data Analysis and Schedule Generation

[1918] The server analyzes the user's desired information, real-time data, and emotional state to optimize the order in which each attraction is used.

[1919] Taking into account break times, expected departure times, and emotional states, we generate a schedule like this:

[1920] 10:00 Roller Coaster

[1921] 11:00 Merry-go-round

[1922] 12:00 Break (Consider children's fatigue and suggest a relaxing rest area)

[1923] 13:00 Ferris wheel

[1924] 5. Providing a schedule

[1925] The terminal displays the generated schedule to the user with family, providing it in the form of a timetable.

[1926] 6. Real-time updates and notifications

[1927] For example, if the wait time for a roller coaster increases to 50 minutes, the device will contact the server and request an updated schedule.

[1928] The server recalculates the schedule based on the new data and emotional state and sends it to the device.

[1929] The device will notify the user of the new schedule and clearly indicate the changes.

[1930] The above is an embodiment of the present invention, and this system allows users to enjoy an efficient and comfortable theme park experience. By adding an emotion recognition function using an emotion engine, flexible suggestions and schedule adjustments based on the user's emotional state become possible, making it possible to provide even more personalized services.

[1931] The processing flow will be explained below.

[1932] Step 1:

[1933] The terminal displays an input form to the user. The user enters group information (number of people, age group, etc.), a list of favorite attractions, desired break time, and planned departure time. When the user finishes entering information, he or she presses the submit button.

[1934] Step 2:

[1935] The device sends the information entered by the user to the server. The data sent is in structured JSON format.

[1936] Step 3:

[1937] The server collects real-time data from the theme park's management system and APIs, including wait times for each attraction, weather information, and travel times based on walking speed.

[1938] Step 4:

[1939] The emotion engine installed in the device recognizes the user's emotional state in real time from their facial expressions and voice. The emotion engine uses sensor devices such as cameras and microphones to acquire the user's emotional data.

[1940] Step 5:

[1941] The device transmits the emotion data acquired by the emotion engine to the server, and the transmitted data is also in a structured format.

[1942] Step 6:

[1943] The server analyzes the input information from the user, real-time data, and emotional data from the emotion engine. It combines the user's wishes with the real-time data and emotional state to set the priority of each attraction.

[1944] Step 7:

[1945] The server calculates the optimal order in which to visit attractions, and optimizes the user's schedule using route optimization algorithms such as the Greedy algorithm and Dijkstra algorithm.

[1946] Step 8:

[1947] The server generates an optimal schedule based on the calculation results. The generated schedule includes designated break times and planned departure times, and also takes into account the user's emotional state.

[1948] Step 9:

[1949] The server generates a schedule and sends it to the terminal. The schedule is in a clear and easy-to-understand timetable format.

[1950] Step 10:

[1951] The device displays a schedule to the user, who then moves around the theme park and enjoys the attractions based on the schedule. During this time, the device continues to monitor the user's emotional state in real time.

[1952] Step 11:

[1953] The device periodically requests the latest real-time and emotional data from the server to keep the schedule updated according to waiting times, weather fluctuations, and changes in emotional state.

[1954] Step 12:

[1955] The server recalculates the schedule based on new real-time data and emotion data, and sends the updated schedule to the device as needed.

[1956] Step 13:

[1957] The device notifies users of schedule updates, for example, via push notifications or alerts, allowing users to react quickly to changes, enabling users to enjoy an optimal theme park experience based on their emotional state.

[1958] Example 2

[1959] 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."

[1960] When visiting a theme park, it is necessary to automatically generate and provide an efficient and comfortable schedule that comprehensively considers a user's group information, favorite attractions, real-time wait times, weather, and the user's emotional state. Conventional systems have difficulty combining these various factors, often forcing users to struggle with cumbersome procedures and schedule adjustments. In particular, the lack of real-time updates and optimization based on emotional state makes it difficult to provide a satisfying user experience.

[1961] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1962] In this invention, the server includes means for inputting user group information, favorite attractions, desired rest periods, and planned time of departure, means for collecting real-time data from the theme park, means for analyzing the user's emotional state using an emotion recognition engine installed in the terminal, means for analyzing the user's input information, the real-time data, and the emotional state and calculating an optimal order for visiting attractions, and means for providing the user with a schedule based on the calculated order of visiting attractions. This makes it possible to provide an efficient and comfortable theme park experience that takes into account the diverse needs and situations of users.

[1963] "User group information" is information about the people accompanying the user when visiting a theme park, including the number of people and their age groups.

[1964] "Favorite Attractions" is a list of attractions within the theme park that the user would like to visit.

[1965] "Desired rest time" refers to the time period and length of time during which the user desires to rest in the theme park.

[1966] The "planned time of departure" is the time when the user plans to leave the theme park.

[1967] "Real-time theme park data" refers to data that is collected instantly, such as waiting times for attractions within the theme park, weather information, and travel times based on walking speed.

[1968] An "emotion recognition engine" is a software or hardware mechanism that is installed on a device and analyzes the user's facial expressions and voice to recognize their emotional state.

[1969] A "schedule" is a plan that summarizes attractions to visit, rest times, etc. in the form of a timetable so that the user can visit the theme park efficiently and comfortably.

[1970] "Providing a schedule" is the process in which the server sends the generated schedule to the terminal so that the user can check it.

[1971] This invention is a system that generates a schedule taking into account the user's emotional state in order to optimize the user's theme park experience. The entire system consists of a server, a terminal, and an emotion recognition engine.

[1972] Collecting user input

[1973] The user inputs group information (number of people, age group, etc.), a list of favorite attractions, desired rest time, and planned time to leave the park through the terminal. The terminal then transmits this input information to the server.

[1974] Real-time data collection

[1975] The server collects real-time data via the theme park's management system and API, including:

[1976] Waiting times for each attraction

[1977] Weather information

[1978] Travel time based on walking speed

[1979] Emotion recognition by emotion engine

[1980] The emotion recognition engine installed in the device recognizes the user's facial expressions and voice in real time. This recognition data is sent to the server via API. The emotion recognition engine includes facial expression analysis software and voice analysis software.

[1981] Analyzing data and generating schedules

[1982] The server analyzes user input, real-time data, and emotion data obtained from an emotion recognition engine all at once. Based on this analysis, it sets priorities and uses an algorithm (e.g., Dijkstra algorithm) to determine the optimal order in which attractions should be used. Furthermore, it adjusts the overall schedule, taking into account break times, planned departure times, and the user's emotional state.

[1983] Schedule provision

[1984] The schedule generated by the server is sent to the terminal and displayed to the user in the form of a timetable, allowing the user to easily check the attractions to be visited and break times via their smartphone or tablet.

[1985] Real-time updates and notifications

[1986] The device periodically communicates with the server to request new real-time information. The server recalculates the schedule based on the latest real-time data and emotion data. If necessary, the server sends a new schedule to the device, which then notifies the user of the updated information. This allows users to instantly receive information such as real-time changes in waiting times, attraction cancellations, and suggestions based on the user's emotions.

[1987] Specific examples

[1988] For families

[1989] A family of users (two adults and two children) visiting a theme park uses the system as follows:

[1990] 1. Collecting input information: Log in to the terminal and enter the number of people in your family, your favorite attraction (roller coaster, merry-go-round, Ferris wheel), break time (1 hour from 12 noon), and planned time to leave the park (6 p.m.).

[1991] 2. Real-time data collection: The server collects the waiting time for each attraction (e.g., 30 minutes for roller coaster, 15 minutes for merry-go-round, 20 minutes for Ferris wheel) in real time from the theme park's management system.

[1992] 3. Emotion recognition: The device camera captures the child's facial expression, and the emotion recognition engine recognizes "fatigue." This data is sent to the server.

[1993] 4. Schedule Generation: Based on this data, the server calculates the order in which each attraction should be visited and generates the following schedule:

[1994] 10:00 Roller Coaster

[1995] 11:00 Merry-go-round

[1996] 12:00 Break (Area for children to relax as they are tired)

[1997] 13:00 Ferris wheel

[1998] 5. Providing the schedule: The terminal displays the generated schedule to the user in the form of a timetable.

[1999] 6. Real-time updates and notifications: Devices periodically communicate with the server and schedules are updated based on new data. For example, if the waiting time for a roller coaster changes to 50 minutes, a new schedule will be generated.

[2000] Prompt Sentence Examples

[2001] Here are some examples of prompts to input to the generative AI model:

[2002] "Generate an example of a day's schedule for a family (2 adults, 2 children) at a theme park based on the following information: roller coaster (wait time 30 minutes), merry-go-round (wait time 15 minutes), ferris wheel (wait time 20 minutes). The emotion engine recognizes that the children are tired. The break time is 1 hour from 12 noon, and the planned departure time is 6:00 PM."

[2003] The above is an embodiment of the present invention, and this system allows users to enjoy an efficient and comfortable theme park experience. By using an emotion recognition engine, flexible suggestions and schedule adjustments based on the user's emotional state can be made, and more personalized services can be provided.

[2004] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2005] Step 1: Collecting User Input

[2006] 1. Start typing:

[2007] Users launch the application on their device and log in using their account information. They input information such as the number of people in their family or group, their age group, a list of their favorite attractions, desired rest times, and the planned time to leave the park.

[2008] Input: User's demographic information, desired attraction, break time, and departure time

[2009] Output: The input information is sent to the server

[2010] Step 2: Collect real-time data

[2011] 1. Data Request:

[2012] The server sends data requests to the theme park's management system and API, specifically requesting wait times for each attraction, weather information, and predicted travel times based on walking speed.

[2013] Input: Server data request

[2014] Output: Real-time data from theme park management systems

[2015] 2. Data Collection:

[2016] The server receives real-time data such as waiting times, weather information, and travel times from the management system or API and stores it in a database.

[2017] Input: Real-time data

[2018] Output: Real-time data stored in a database

[2019] Step 3: Emotion recognition by the emotion engine

[2020] 1. Emotional data collection:

[2021] The device's camera and microphone are used to capture the user's facial expressions and voice, and this data is fed into the emotion engine.

[2022] Input: Real-time user facial and voice data

[2023] Output: Raw data sent to the sentiment engine

[2024] 2. Sentiment analysis:

[2025] The emotion engine analyzes the captured data and recognizes the user's emotional state, for example, detecting a smile indicates "happiness" and a frown indicates "fatigue."

[2026] Input: Raw data (facial expressions and voice)

[2027] Output: Perceived emotional state

[2028] 3. Emotional data transmission:

[2029] The device sends the recognized emotion data to the server via API.

[2030] Input: Recognized emotion data

[2031] Output: Emotion data sent to the server

[2032] Step 4: Analyze data and generate a schedule

[2033] 1. Data Integration:

[2034] The server integrates user input information, real-time data, and emotional data, enabling comprehensive analysis.

[2035] Input: User input, real-time data, emotional data

[2036] Output: A consolidated dataset

[2037] 2. Priority settings:

[2038] The server sets priorities for attractions based on the user's desired information.

[2039] Input: Integrated dataset

[2040] Output: A prioritized list of attractions

[2041] 3. Schedule optimization:

[2042] The server uses algorithms such as Dijkstra's algorithm to calculate the optimal order in which to visit attractions, thereby minimizing waiting times and travel times.

[2043] Input: Attraction priority list, consolidated data

[2044] Output: Optimized attraction usage order

[2045] 4. Overall schedule adjustment:

[2046] The server adjusts the overall schedule taking into account break times, departure times, and the user's emotional state, for example, by shortening break times based on the user's emotional state.

[2047] Input: Optimized attraction order, user's desired time

[2048] Output: Adjusted overall schedule

[2049] Step 5: Provide a schedule

[2050] 1. Schedule generation:

[2051] The server creates an optimized and coordinated schedule, including attractions to visit, break times, travel times, etc.

[2052] Input: Adjusted overall schedule

[2053] Output: The generated schedule

[2054] 2. Data transmission:

[2055] The server transmits the generated schedule to the terminal.

[2056] Input: Generated schedule

[2057] Output: Schedule sent to the terminal

[2058] 3.Display:

[2059] The terminal displays the received schedule in a timetable format to the user, allowing the user to check the attractions to be visited and break times.

[2060] Input: Schedule sent to the terminal

[2061] Output: The schedule as seen by the user

[2062] Step 6: Real-time updates and notifications

[2063] 1. Regular communication:

[2064] The device periodically communicates with the server to request updates on the latest real-time data and emotion data.

[2065] Input: Update request

[2066] Output: Latest data

[2067] 2. Recalculate the schedule:

[2068] The server recalculates the existing schedule based on new real-time data and emotion data, and generates new schedules as needed.

[2069] Input: Latest real-time data, sentiment data

[2070] Output: Recalculated schedule

[2071] 3. Schedule Update:

[2072] The server transmits the newly generated schedule to the terminal.

[2073] Input: Recalculated schedule

[2074] Output: Update schedule sent to the device

[2075] 4. Notice:

[2076] The device notifies the user of schedule changes, allowing the user to take action based on the latest situation.

[2077] Input: Updated schedule

[2078] Output: Changes notified to the user

[2079] These are the processing steps of the system's program. It is possible to provide an optimal schedule by comprehensively analyzing user input, real-time data, and emotional data. This process allows users to enjoy an efficient and comfortable theme park experience.

[2080] (Application example 2)

[2081] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2082] Modern theme parks and shopping malls are required to provide optimal experiences for visitors. However, conventional systems have difficulty not only taking real-time information into account but also flexibly adjusting schedules based on the user's emotional state. This often leads to stress and a disappointing experience for users. It has also been difficult to accurately predict congestion and waiting times at theme parks and shopping malls and suggest optimal routes and stores. To solve these problems, a system is needed that can analyze users' real-time behavior and emotions in an integrated manner and provide optimal schedules.

[2083] 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 inputting a user's group information, favorite attractions, desired rest time, and planned departure time, means for collecting real-time data about the theme park, means for analyzing the user's input information and the real-time data and calculating an optimal order for visiting attractions, means for providing the user with a schedule based on the calculated order of visits, means for recognizing the user's emotional state in real time and optimizing the schedule based on the emotional state, and means for providing a shopping route based on real-time store information from online stores and the user's emotional state. This enables the user to have an optimal theme park experience and shopping experience tailored to their emotional state.

[2084] "User group information" is information about the entire group, such as the number of users and their age groups.

[2085] "Favorite attractions" is a list of attractions in which the user has particular interests or concerns.

[2086] "Desired break time" is information about the specific time or period when the user wishes to take a break.

[2087] The "planned time of departure" is the time when the user plans to leave the theme park.

[2088] "Real-time theme park data" refers to the latest information about theme parks, such as current wait times for attractions, weather information, and walking speeds.

[2089] "Emotional state" refers to the current emotion recognized from the user's facial expression and voice, and includes, for example, stress level and fatigue level.

[2090] A "shopping route" is an optimal route for a user to efficiently navigate around a shopping mall or store.

[2091] "Real-time updates" means constantly updating systems and data based on the latest information.

[2092] The present invention is a system for optimizing a user's theme park and shopping experience. The system analyzes a user's input information, real-time data, and emotional state to provide optimal attractions and shopping routes. The following description details a specific embodiment of the system.

[2093] 1. Collecting user input information

[2094] The device (e.g. smartphone or tablet) collects the following information from the user:

[2095] Group information (number of people, age group, etc.)

[2096] A list of your favorite attractions and products

[2097] Break time requests

[2098] Scheduled time of leaving the park or store

[2099] 2. Real-time data collection

[2100] The server collects the following real-time data from the theme park and shopping mall management systems and public APIs:

[2101] Waiting times for each attraction

[2102] Current Weather Information

[2103] Store congestion status and sales information

[2104] Travel time based on user walking speed

[2105] 3. Emotion Recognition by Emotion Engine

[2106] An emotion engine (specifically, the EmotionEngine library) installed on the device recognizes the user's emotional state in real time from their facial expressions and voice. This information is sent to the server via an API. For example, if the user is tired or stressed, that information is communicated to the server.

[2107] 4. Data Analysis and Optimization

[2108] The server generates the optimal order of attractions and shopping routes based on the user's input information, collected real-time data, and emotion data from the emotion engine. This includes the following steps:

[2109] Analyze user preferences and set priorities

[2110] Calculate the optimal order of attractions and stores based on real-time data and emotional state (e.g., Dijkstra algorithm)

[2111] Adjust the overall schedule taking into account break times and planned departure times

[2112] 5. Providing a schedule

[2113] The server generates a schedule and sends it to the device, which then displays it to the user in the form of a timetable, clearly indicating the attractions and shops to visit during each time period, as well as break times.

[2114] 6. Real-time updates and notifications

[2115] The device periodically communicates with the server to request updates of real-time information. The server recalculates the schedule based on the new real-time data and the emotional state of the emotion engine, and sends any necessary changes to the device, allowing the user to see the changes immediately.

[2116] Specific examples

[2117] For families

[2118] 1. Collection of information:

[2119] A family of four users enters information into the terminal. They select roller coaster, merry-go-round, and Ferris wheel as their preferred attractions. They request a one-hour break from 12:00 and plan to leave the park at 18:00.

[2120] 2. Real-time data:

[2121] The waiting time for the roller coaster is 30 minutes, the merry-go-round is 15 minutes, and the Ferris wheel is 20 minutes.

[2122] 3. Emotional state:

[2123] The emotion engine recognizes fatigue from the user's facial expression.

[2124] 4. Optimization:

[2125] The server generates a schedule and sets the roller coaster at 10:00, the merry-go-round at 11:00, the break at 12:00, and the Ferris wheel at 13:00.

[2126] 5.Display:

[2127] It displays the timetable on the device and sends necessary notifications.

[2128] Prompt Sentence Examples

[2129] Write Python code that takes into account unique user information, real-time data, and emotion recognition results to provide an optimal shopping experience schedule. The schedule includes the following items: time, store name, and wait time. Using the user's preferred categories and their real-time data, suggest appropriate break times based on the user's emotional state.

[2130] The above is a specific embodiment of the present invention. This system enables flexible schedule adjustment based on the user's emotional state, providing a more comfortable and efficient experience.

[2131] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2132] Step 1:

[2133] The terminal collects input information from the user, such as group information (number of people, age group), a list of favorite attractions, desired rest periods, and planned departure time. This information serves as the basis for the system to understand the user's preferences and plans and generate a personalized schedule.

[2134] Input: Number of users, age group, list of favorite attractions, desired break time, planned time to leave the park

[2135] Output: A dataset of user-entered information

[2136] Specific behavior:

[2137] The terminal displays an information input form through a user interface.

[2138] The user enters the required information into the form and presses the "Submit" button.

[2139] The terminal collects the input information and sends it to the server as a data set.

[2140] Step 2:

[2141] The server collects real-time data from theme parks and shopping malls, including attraction wait times, weather information, store occupancy and sales information, and user walking speeds. This data is collected using APIs.

[2142] Input: Theme park and shopping mall APIs

[2143] Output: Real-time data

[2144] Specific behavior:

[2145] The server periodically sends requests to the API to retrieve the latest real-time data.

[2146] The collected data is organized on the server and prepared for analysis.

[2147] Step 3:

[2148] The device's built-in emotion engine recognizes the user's emotional state in real time from their facial expressions and voice. This information is sent to the server via an API. For example, the user's fatigue level and stress level can be recognized.

[2149] Input: User's facial expressions and voice data

[2150] Output: Emotional state data

[2151] Specific behavior:

[2152] The device's camera and microphone are used to collect the user's facial expressions and voice.

[2153] An emotion engine (such as the EmotionEngine library) analyzes this data and identifies the emotional state.

[2154] The recognized emotional state data is transmitted to a server.

[2155] Step 4:

[2156] The server analyzes user input, real-time data, and emotional data to generate the optimal order of attractions and shopping routes, using algorithms such as Dijkstra's algorithm.

[2157] Input: User-entered information, real-time data, emotional state data

[2158] Output: Optimal schedule (order of attractions, shopping route)

[2159] Specific behavior:

[2160] The server integrates the various collected data and runs optimization algorithms.

[2161] The optimal order of use is calculated taking into account the waiting time at each attraction and store, the level of congestion, and the user's emotional state.

[2162] Adjust the overall schedule, taking into account break times and planned dismissal times.

[2163] Step 5:

[2164] The server transmits the generated schedule to the terminal, which displays it to the user in the form of a timetable.

[2165] Input: Optimal schedule

[2166] Output: Schedule display in timetable format

[2167] Specific behavior:

[2168] The server transmits the generated schedule data to the terminal.

[2169] The terminal visually displays the schedule in a timetable format, allowing users to act based on this display.

[2170] Step 6:

[2171] The device periodically communicates with the server to request real-time updates. The server recalculates the schedule based on the new data and emotional state, and sends any necessary changes to the device, where the user can immediately see the changes.

[2172] Input: Regular real-time data and emotional state data

[2173] Output: Updated schedule

[2174] Specific behavior:

[2175] The terminal requests real-time data updates from the server at regular intervals.

[2176] The server retrieves the new data and analyzes the emotional state again.

[2177] Recalculate the schedule as needed and send updates to the terminal.

[2178] The terminal notifies the user of the updated schedule and displays the changes.

[2179] The above are the specific processing steps in the program of the system of the present invention, which allows the user to always have the most optimal theme park and shopping experience based on the latest information and emotional state.

[2180] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2181] 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.

[2182] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2183] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2184] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2185] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2186] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2187] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2188] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2189] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2190] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2191] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2192] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2193] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2194] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2195] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2196] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2197] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2198] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2199] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2200] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2201] The following is further disclosed regarding the above embodiment.

[2202] (Claim 1)

[2203] a means for inputting the user's group information, preferred attractions, desired rest time, and planned time of departure;

[2204] a means of collecting real-time data from the theme park;

[2205] means for analyzing the user's input information and the real-time data and calculating an optimal order for using attractions;

[2206] The system further includes means for providing a schedule to a user based on the calculated order of use.

[2207] (Claim 2)

[2208] 10. The system of claim 1, wherein the real-time data includes attraction wait times, weather information, and walking speed.

[2209] (Claim 3)

[2210] 10. The system of claim 1, further comprising means for updating the schedule in real time and notifying a user.

[2211] "Example 1"

[2212] (Claim 1)

[2213] A means for inputting user group information, preferred video content, desired break time, and scheduled end time;

[2214] a means of collecting real-time data from the theme park;

[2215] means for analyzing the user's input information and the real-time data and calculating an optimal viewing order of video content;

[2216] means for providing a schedule to a user based on the calculated viewing order;

[2217] means for updating and notifying the schedule in real time via a user's terminal;

[2218] A system including:

[2219] (Claim 2)

[2220] The system of claim 1 , wherein the real-time data includes viewpoint latency, external information, and travel time.

[2221] (Claim 3)

[2222] 10. The system of claim 1, further comprising means for periodically updating said schedule and providing and notifying a user of a recalculated schedule.

[2223] "Application Example 1"

[2224] (Claim 1)

[2225] a means for inputting the user's group information, preferred attractions, desired rest time, and planned time of departure;

[2226] a means of collecting real-time data from the theme park;

[2227] means for analyzing the user's input information and the real-time data and calculating an optimal order for using attractions;

[2228] means for providing a schedule to a user based on the calculated usage order;

[2229] A means for collecting inventory information and congestion information based on the data and calculating an optimal product purchasing order;

[2230] means for providing a shopping schedule to a user based on the optimal product purchasing order;

[2231] means for updating the shopping schedule in real time and notifying the user;

[2232] A system including:

[2233] (Claim 2)

[2234] 10. The system of claim 1, wherein the real-time data includes attraction wait times, weather information, and walking speed.

[2235] (Claim 3)

[2236] 10. The system of claim 1, further comprising means for updating the schedule in real time and notifying a user.

[2237] "Example 2: Combining Emotion Engines"

[2238] (Claim 1)

[2239] a means for inputting the user's group information, preferred attractions, desired rest time, and planned time of departure;

[2240] a means of collecting real-time data from the theme park;

[2241] means for analyzing the emotional state of a user using an emotion recognition engine installed in the terminal;

[2242] means for analyzing the user's input information, the real-time data, and the emotional state, and calculating an optimal order of attractions to be visited;

[2243] The system further includes means for providing a schedule to a user based on the calculated order of use.

[2244] (Claim 2)

[2245] 10. The system of claim 1, wherein the real-time data includes attraction wait times, weather information, and walking speed.

[2246] (Claim 3)

[2247] 10. The system of claim 1, further comprising means for updating the schedule in real time and notifying a user.

[2248] "Application example 2 when combining emotion engines"

[2249] New Claims

[2250] (Claim 1)

[2251] a means for inputting the user's group information, preferred attractions, desired rest time, and planned time of departure;

[2252] a means of collecting real-time data from the theme park;

[2253] means for analyzing the user's input information and the real-time data and calculating an optimal order for using attractions;

[2254] means for providing a schedule to a user based on the calculated usage order;

[2255] means for recognizing a user's emotional state in real time and optimizing a schedule based on said emotional state;

[2256] A means for providing a shopping route based on real-time store information and the user's emotional state in an online store;

[2257] A system including:

[2258] (Claim 2)

[2259] 10. The system of claim 1, wherein the real-time data includes attraction wait times, weather information, and walking speed.

[2260] (Claim 3)

[2261] 10. The system of claim 1, further comprising means for updating the schedule in real time and notifying a user. [Explanation of symbols]

[2262] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for inputting the user's group information, preferred attractions, desired rest time, and planned time of departure; a means of collecting real-time data from the theme park; means for analyzing the user's input information and the real-time data and calculating an optimal order for using attractions; The system further includes means for providing a schedule to a user based on the calculated order of use.

2. The system of claim 1 , wherein the real-time data includes attraction wait times, weather information, and walking speeds.

3. 10. The system of claim 1, further comprising means for updating said schedule in real time and notifying a user.

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