system

Abstract

We provide the system. [Solution] Information processing means for collecting guest information and providing personalized accommodation experiences based on that information, A profile generation means for analyzing collected information and generating guest profiles, A display generation means for customizing the video and interface of the accommodation facility using the aforementioned profile, Environmental control means for detecting the physiological data and emotional state of guests and adjusting lighting and sound accordingly, A system including language processing and response means for providing multilingual information services.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In conventional accommodation facilities, experiences corresponding to the individual needs and preferences of each guest are not provided, and many general services are provided, so it is difficult to improve the satisfaction of the stay. Therefore, the problem is how to realize an individually optimized experience demanded by guests.

Means for Solving the Problems

[0005] To address this challenge, the system includes information processing means for collecting guest information and providing personalized accommodation experiences based on that information. Furthermore, it includes profile generation means for analyzing the collected information and generating guest profiles. This allows for the customization of in-accommodation video and interfaces using display generation means to generate individually optimized displays, and includes environmental control means for adjusting lighting and sound according to the guest's physiological data and emotional state. In addition, the system can be further improved by including language processing and response means for providing multilingual information services.

[0006] "Information processing means" refers to a device or software that has the function of organizing and analyzing collected data.

[0007] "Profile generation means" refers to a device or method for creating a dataset based on collected guest information to provide a customized experience tailored to that guest.

[0008] "Display generation means" refers to a device or software that has the function of generating images and interfaces according to the preferences and needs of guests and outputting them to a display device.

[0009] "Environmental control means" refers to a device or software for dynamically adjusting environmental settings such as lighting and sound according to the physiological data and emotional state of the guests.

[0010] "Language processing and response means" refers to a device or software with multilingual capabilities for analyzing linguistic input from guests and generating appropriate responses.

[0011] A "menu creation method" refers to a device or software that has the function of creating personalized menus based on the guest's food preferences and information on local ingredients.

[0012] A "guide plan generation device" is a device or software that creates and presents an optimal sightseeing guide plan based on the composition information of the guests. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiment for Carrying Out the Invention

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0017] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the 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.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0027] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention is a technology for providing individually optimized experiences for hotel guests, and specifically consists of a process from information gathering and analysis to customization based on the results. A specific example of the system's operation is given below.

[0035] Information gathering

[0036] The server collects personal information, purpose of stay, hobbies, and food preferences from guests through online forms when they make reservations. It also records past stay history to build more accurate profiles.

[0037] Profile generation

[0038] The server uses the collected data to analyze guests' preferences and generate individually optimized profiles. These profiles are then used to customize the various services offered by the accommodation.

[0039] Display customization

[0040] The terminal plays a individually generated welcome video on the lobby display upon the user's arrival. This video combines seasonal changes and local scenery with content tailored to the user's interests.

[0041] Adjusting the guest room environment

[0042] Sensors built into the device monitor the user's heart rate and facial expressions in real time. Based on this data, the device provides optimized lighting and music for the user. For example, if the device determines that the user is relaxed, it will play calming music and use warm-colored lighting.

[0043] AI concierge response

[0044] Users can ask questions and request services in their own language. The server uses language processing algorithms to analyze these requests and instructs the terminal to provide an appropriate response. Multilingual support prevents misunderstandings due to language barriers.

[0045] Personalized meals and tours

[0046] The server suggests personalized menus based on the user's food preferences and information on local ingredients. Furthermore, it generates tour plans tailored to the family structure and interests, with a robot guide providing the tour. The tour content is adjusted to suit the user's schedule and interests.

[0047] As described above, the system of the present invention realizes an individually optimized stay experience through the cooperation of the server, terminal, and user. This system allows guests to have a special experience tailored to them, and is expected to improve their satisfaction.

[0048] The following describes the processing flow.

[0049] Step 1:

[0050] The server receives information provided by guests. Specifically, it collects personal information, purpose of stay, hobbies, and food preferences via online reservation forms and stores them in a database.

[0051] Step 2:

[0052] The server analyzes the accumulated data and creates guest profiles. These profiles include guidelines on how to customize the services provided during their stay.

[0053] Step 3:

[0054] The terminal controls displays installed in the lobby and guest rooms. Based on profile information sent from the server, it generates videos tailored to the guest's preferences and needs and plays them as a welcome movie.

[0055] Step 4:

[0056] The device's sensors detect the user's heart rate and facial expressions in real time. Based on this, the system evaluates the user's emotional state and adjusts the environment settings (lighting, music) accordingly.

[0057] Step 5:

[0058] Users can enter questions and requests into the device. They can enter them in their preferred language and interact with the information through a multilingual UI.

[0059] Step 6:

[0060] The server processes user requests received from the terminal. It uses natural language processing to analyze the input request and generate or retrieve appropriate information.

[0061] Step 7:

[0062] The terminal, having received instructions from the server, provides a response to the user. It accurately conveys the necessary information and services in the user's language using screen displays and audio output.

[0063] Step 8:

[0064] The server generates an optimal menu based on the user's food preferences and information on local ingredients. This menu is then presented to the user via their terminal.

[0065] Step 9:

[0066] The server creates tour plans for sightseeing and leisure based on the user's configuration information. The details of the plan are sent to the robot guide, and the user is guided on a tour tailored to their needs.

[0067] This series of processes enables the system to provide users with highly personalized services.

[0068] (Example 1)

[0069] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0070] In modern accommodations, it is common to provide a uniform service to all guests, making it difficult to offer personalized experiences tailored to the individual tastes, preferences, and needs of each guest. This can lead to decreased guest satisfaction and reduced willingness to return. Furthermore, efficiently implementing multilingual support and real-time environmental adjustments presents technical challenges.

[0071] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0072] In this invention, the server includes data processing means for collecting guest information and providing a personalized accommodation experience based on that information; information generation means for analyzing the information and generating guest profiles; and content generation means for providing customized content using the profiles and generated AI models. This enables the provision of personalized experiences, multilingual information services, and real-time environment adjustments.

[0073] "Data processing means" refers to technical means for analyzing information obtained from guests and providing personalized experiences based on that data.

[0074] "Information generation means" refers to technical means that are responsible for analyzing collected data to create profiles of guests.

[0075] "Display creation means" refers to a function for customizing the display and operation screens of accommodation facilities based on the guest's profile.

[0076] "Environmental adjustment means" refers to technologies that detect the physiological data and emotional state of guests and adjust lighting and sound based on the collected information.

[0077] "Language processing and response provision means" refers to technical means that understand and process guests' requests in multiple languages ​​and provide appropriate responses.

[0078] "Content generation means" refers to a technical means that uses a generation AI model to provide customized content based on the guest's profile.

[0079] "Means including sensors and control systems" refers to a system configuration for detecting guests' physiological information in real time in a guest room and adjusting the environment based on that data.

[0080] This invention is a system for providing guests with an individualized lodging experience, and implements a variety of technologies including data processing, information generation, display customization, environment adjustment, language processing, and content generation.

[0081] The server collects personal information, preferences, purpose of stay, and past stay history from guests through online forms when they make reservations. This uses a web server and a database management system. The server analyzes the collected data and generates a profile for each guest. The analysis incorporates a generative AI model to recognize patterns in the data and create personalized profiles.

[0082] The terminal functions as an interface within the accommodation, displaying a welcome video based on the guest's profile upon arrival. The software within the terminal uses prompt messages to instruct a generation AI model to create appropriate content for this video. An example of a specific prompt message would be: "Please customize the content of the welcome video based on the guest information. Username: Yamada, Language: Japanese, Hobbies: Trekking, Purpose of Stay: Sightseeing."

[0083] Sensors installed on the terminal acquire guests' physiological data in real time and transmit it to a server. The server analyzes this data and dynamically adjusts environmental settings such as lighting and music according to the guests' emotional state and stress levels. This real-time adjustment is a crucial function for ensuring guests have a comfortable stay.

[0084] Furthermore, when a user makes a question or request in their native language, the server uses a language processing algorithm to analyze it and generate an appropriate response. This enables smooth communication even for guests who speak different languages.

[0085] Overall, this system can provide guests with personalized and valuable experiences, improving the service level of accommodations.

[0086] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0087] Step 1:

[0088] The server collects reservation information through online form submissions from guests. This input data includes personal information, hobbies, and purpose of stay. Based on this information, the server creates records in a database and prepares them for analysis. The output is structured data that can be analyzed.

[0089] Step 2:

[0090] The server uses a generative AI model based on the collected data to generate guest profiles. The input is the structured data obtained in step 1, which the server's algorithm analyzes to predict and generate guest preference patterns. The output is individually customized profile information.

[0091] Step 3:

[0092] The terminal generates a welcome movie to display in the lobby based on profile information received from the server. The input is profile information, which is sent as a prompt to a generation AI model, which then generates appropriate content. The output is a movie containing a user-optimized welcome message.

[0093] Step 4:

[0094] The terminal's sensors monitor the guest's heart rate and facial expressions in real time within the room and transmit this data to a server. The input is biosensor data, which is analyzed to determine the guest's state (stress, relaxation, etc.). The output is lighting and music settings data that reflect the guest's state.

[0095] Step 5:

[0096] When a user enters a question in their native language via their device, the server performs language processing and generates the necessary response. The input is a question in the user's language, which is analyzed and understood by AI to generate an appropriate answer on the server. The output is service information and response messages in a language the user understands.

[0097] Step 6:

[0098] The server generates personalized meal menus based on the generated guest profiles and local ingredient information. The input is the profile and local information, and a food recommendation algorithm is used to suggest the most suitable menu. The output is a personalized menu suggestion, providing dishes tailored to the user's preferences.

[0099] (Application Example 1)

[0100] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0101] Accommodations and retail stores that offer personalized experiences are required to provide services tailored to individual preferences and needs in order to increase customer satisfaction. However, currently, it is difficult to properly collect individual customer information and immediately reflect it in the service, resulting in the challenge of only being able to provide standardized services to customers.

[0102] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0103] In this invention, the server includes information processing means for collecting guest or customer information and providing personalized experiences based on that information; profile generation means for analyzing the collected information and generating a profile; and information presentation means for presenting relevant product information in-store in real time based on the customer's purchase history and preferences. This makes it possible to provide personalized services and product information that meet the specific needs of the customer.

[0104] "Information processing means" refers to a system that collects information about guests or customers and manages and analyzes the data necessary to provide personalized experiences.

[0105] A "profile generation method" is a function that analyzes collected customer information and creates a profile that includes characteristics and preferences tailored to each individual customer.

[0106] "Display generation means" refers to a device or function that provides customized video and interface content at accommodation facilities and shops based on a generated profile.

[0107] "Environmental control means" refers to a system that optimally adjusts lighting, sound, and other environmental elements according to the customer's physiological data and emotional state.

[0108] "Language processing and response means" refers to technologies that analyze language and generate and present appropriate responses in order to provide information services that support multiple languages.

[0109] "Information presentation means" refers to technology that displays relevant product information in-store in real time, based on the customer's purchase history and preferences.

[0110] A "promotion generation method" is a function that identifies recommended products according to the customer's profile and generates promotions based on those products.

[0111] This invention constructs a system for providing personalized customer experiences in accommodations and retail stores. The main components of the system include information processing means, profile generation means, display generation means, environment control means, information presentation means, promotion generation means, language processing and response means.

[0112] The server collects information provided in advance by guests or customers, such as their store visit history and purchase history. This information is used to generate customer profiles. The profile generation system analyzes and stores profiles tailored to individual customers based on the collected data. For example, if a customer frequently purchases a particular brand or product, that preference will be reflected in their profile.

[0113] The terminal uses a display generation mechanism to present customized information based on the customer's profile when they visit a hotel or physical store. Within the store, product information and promotional videos are displayed in the customer's field of vision using a smartphone or smart glasses. This information is presented in real time, and relevant information about products the customer shows interest in is provided immediately.

[0114] Furthermore, through environmental control systems, customer physiological data and emotions are analyzed via sensors, and lighting and music are automatically adjusted accordingly. For example, if a customer prefers a calm atmosphere, the lighting is set to warm tones and relaxing music is played.

[0115] Customers, even if they use different languages, can receive guidance and answers to their questions within stores and accommodations through multilingual information services. The language processing and response means uses a generative AI model to perform language analysis and generate responses in the appropriate language.

[0116] For example, when a customer is looking for a specific product in a store, a prompt message such as "Based on this customer's past purchase history, generate and display information about products they should be interested in now" can be entered into the AI ​​model, and relevant information will be presented immediately.

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] The server collects personal information and purchase history provided in advance by guests or customers. The information entered includes name, address, past purchase history, and preferred categories. The server stores this data in a database in preparation for later profile generation. The output is formatted customer information data.

[0120] Step 2:

[0121] The server generates customer profiles using the collected data. The input is the customer information data obtained in Step 1. Using a generation AI model, it analyzes customer preferences and interests to output a personalized profile. This profile includes frequently purchased items and topics of interest.

[0122] Step 3:

[0123] The terminal displays product information based on a customer's profile in real time when they enter the store. The input is the customer profile obtained in step 2. The prompt message "Generate interesting product information based on this customer's profile and display it on the screen" is input to the AI ​​model, and the generated information is output. Specifically, a product promotional video is displayed on the smart glasses.

[0124] Step 4:

[0125] Users search for products or ask questions within the store. The terminal receives this as input and outputs appropriate answers using a multilingual FAQ system. The terminal provides responses via voice or text to enhance user convenience.

[0126] Step 5:

[0127] The terminal uses sensors to detect the customer's physiological data and facial expressions in real time. Inputs include the customer's heart rate and facial expression data. Based on this, environmental control systems adjust lighting and sound, providing an optimized environment as output. For example, the lighting might be changed to a warmer color to promote relaxation.

[0128] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0129] This invention is a system for providing personalized experiences based on guests' emotions. It achieves a high degree of personalization by accurately recognizing each guest's emotions and introducing the most appropriate service accordingly. This system centers around an emotion engine and encompasses a series of processes from information gathering and analysis to service delivery.

[0130] Information gathering

[0131] The server not only collects guests' personal information and past usage history, but also stores specific preferences and needs provided during booking in a database.

[0132] Profile generation

[0133] The server analyzes the collected data and generates a user profile. This profile is combined with the sentiment data captured by the sentiment engine and used to design customized services.

[0134] Acquisition of emotional data

[0135] Sensors installed on the device acquire physiological indicators such as the user's heart rate, facial expressions, and voice tone, and transmit them to a server. The server processes this data in real time, and an emotion engine identifies the user's emotional state.

[0136] Analysis and response to emotional states

[0137] The server analyzes the data acquired using an emotion engine and selects appropriate services using emotional response mechanisms. For example, if the device detects that the user is stressed, it will automatically play relaxing music and change the lighting to a calming tone.

[0138] Personalized content delivery

[0139] The device provides users with personalized entertainment and information in real time based on their emotions. It can also automatically update movie and music playlists in response to changes in the user's emotions.

[0140] Multilingual support service

[0141] Based on the results of emotion recognition, the system generates accurate responses in multiple languages ​​to user questions and requests. The server uses natural language processing technology to compensate for language differences and return appropriate information.

[0142] As a concrete example, if the system detects that a user is excited, it will recommend upbeat background music or energizing video content. Conversely, for users who intend to spend their time quietly, it will provide calming music and warm lighting. In this way, the present invention can cater to the emotions of guests and provide a high level of satisfaction through an individualized experience.

[0143] The following describes the processing flow.

[0144] Step 1:

[0145] Users make accommodation reservations and, at that time, enter personal information, purpose of stay, food preferences, desired experiences, etc., into an online form. This information is sent to the server.

[0146] Step 2:

[0147] The server analyzes the received information and generates a profile of the guest. This profile is used as the basis for providing customized services during their stay.

[0148] Step 3:

[0149] The terminal uses sensors installed in the guest room to monitor physiological indicators such as the user's heart rate, facial expressions, and voice tone. This data is sent to a server for processing by the emotion engine.

[0150] Step 4:

[0151] The server activates an emotion engine, analyzes the user's physiological data in real time, and identifies the user's emotional state. Emotional states are classified into categories such as stress, relaxation, and excitement.

[0152] Step 5:

[0153] Based on the analysis results from the emotion engine, the server issues commands to the terminal. For example, if the server determines that the user is relaxed, the terminal changes the room lighting to a warm color and plays relaxing music.

[0154] Step 6:

[0155] Based on the user's interests, the device suggests entertainment content that matches their mood. Based on instructions from the server, lists of movies and music are customized to the user's preferences.

[0156] Step 7:

[0157] When the server receives a question or request from a user, it uses natural language processing to analyze it and generates a multilingual response. The terminal then returns the information to the user in an appropriate format.

[0158] Step 8:

[0159] The server accumulates emotional data acquired daily and updates and optimizes profiles based on long-term data. This feedback loop ensures that even more precise service is provided during subsequent stays.

[0160] In this way, data and commands are exchanged between the server, terminal, and user, enabling the provision of a personalized and advanced accommodation experience to the user.

[0161] (Example 2)

[0162] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0163] Traditional accommodations have been unable to provide a uniform service to guests, making it difficult to customize services to meet individual needs and emotional states. Therefore, providing personalized experiences is essential to increasing guest satisfaction. However, in practice, it is difficult to accommodate the changing preferences and emotions of each guest, and there are technical challenges, particularly in overcoming language barriers while providing emotion-based service.

[0164] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0165] In this invention, the server includes information processing means for collecting guest information and providing a personalized accommodation experience based on that information and past usage history; profile generation means for analyzing the collected information and generating a detailed profile of the guest; and environment adjustment means for customizing the lighting and sound environment of the accommodation using the profile and acquired guest emotional state data. This enables a personalized experience that provides a high level of satisfaction in accordance with the guest's emotional state.

[0166] "Information processing means" refers to a device or system that has the function of collecting information and past usage history of guests and providing personalized accommodation experiences based on that information.

[0167] "Profile generation means" refers to a device or system for analyzing collected information to generate a detailed profile of a guest.

[0168] "Environmental adjustment means" refers to a device or system for customizing the lighting and sound environment of accommodation using acquired emotional state data of guests.

[0169] "Personalized content generation means" refers to a device or system for providing appropriate content in real time based on information obtained from sentiment analysis.

[0170] "Language processing and response means" refers to a device or system for providing multilingual information tailored to the emotional state of guests in response to their inquiries.

[0171] "Means of providing food" refers to a device or system for generating and providing personalized menus based on the food preferences of guests and the characteristics of the region.

[0172] A "guide plan generation means" is a device or system for dynamically adjusting tourist information based on the emotional state and compositional information of the guests.

[0173] This invention relates to a system that provides personalized experiences based on the emotional state of guests in accommodation facilities. Centered around an emotion engine, it covers a series of processes from information gathering and analysis to service delivery.

[0174] First, the server processes guest information. Specifically, it stores guests' personal information, past stay history, and preferences and needs provided during booking in a database. This data is analyzed and used to generate detailed guest profiles. Statistical analysis software and data mining techniques are being considered as methods for profile generation.

[0175] Next, the device acquires the user's physiological data. Specifically, it monitors facial expressions and voice tone in real time using a heart rate sensor and camera. This data is sent to a server and analyzed by an emotion engine. Once the emotional state is identified, the lighting and acoustic environment are automatically adjusted accordingly. This process requires appropriate processing equipment to execute the algorithms.

[0176] Furthermore, the device provides users with entertainment and information tailored to their needs in real time, based on sentiment analysis. Music playlists and movie recommendations are automatically updated according to the user's mood. This feature utilizes a generative AI model to optimize content delivery.

[0177] As part of the multilingual service, the server uses natural language processing technology to generate responses tailored to the guest's language. This enables a more empathetic service that transcends language barriers.

[0178] For example, if the server detects that the user is excited, the terminal will play upbeat background music and provide video content to enhance their energy. On the other hand, if the server recognizes that the user wants to relax, it will provide calming music and warm lighting. An example of a prompt message would be, "What services should be provided when a guest's emotions indicate stress? Please suggest specific music and lighting settings."

[0179] In this way, it is possible to provide a customized experience that matches the emotions of the guests.

[0180] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0181] Step 1:

[0182] The server collects basic guest information, past stay history, and specific preferences and needs entered during booking into a database. Based on this input data, it uses a database management system to organize and store the information. Specifically, the server registers information when a guest checks in and identifies similar past stay patterns.

[0183] Step 2:

[0184] The server generates guest profiles using the collected data. It processes the entered basic information and historical data through an analysis algorithm to extract behavioral patterns and preferences. As a result, a profile optimized for each individual guest is output. Specifically, the server uses machine learning models to predict behavior and infer preferences.

[0185] Step 3:

[0186] The terminal acquires guests' physiological data in real time. User input includes heart rate, facial expression analysis, and voice tone, and this data is collected from sensors. The terminal sends this physiological data to a server, where it is analyzed by an emotion engine. Specifically, the terminal uses its camera to record video and its microphone to record voice tone.

[0187] Step 4:

[0188] The server performs emotional analysis based on the received physiological data to identify the guest's emotional state. This analysis involves applying the input data to an emotion engine algorithm and outputting emotions such as stress, joy, or excitement. Specifically, the server processes the data in real time and assigns the appropriate emotion category.

[0189] Step 5:

[0190] The terminal provides guests with entertainment and information tailored to their emotional state based on its analysis. The user's emotional state is the input, and based on this, the terminal selects and outputs music playlists and video content. Specifically, the terminal plays music appropriate to the emotion and delivers content suitable for the display device.

[0191] Step 6:

[0192] The server provides multilingual support services, generating responses in the appropriate language based on user inquiries. Input includes the guest's emotional state and language preferences, while output is information provided in the corresponding language. Specifically, the server uses natural language processing to translate user questions and provides responses tailored to their emotional state.

[0193] (Application Example 2)

[0194] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0195] In the realm of transportation, it is difficult for passengers to enjoy a comfortable and personalized experience over extended periods. In particular, autonomous vehicles require adjustments to the in-car environment based on the passenger's emotions and physiological state, but there is a lack of appropriate means to achieve this.

[0196] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0197] In this invention, the server includes information processing means for collecting guest information and providing a personalized accommodation experience based on that information; profile generation means for analyzing the collected information and generating a guest profile; display generation means for customizing the accommodation's images and interface; and emotion response means for acquiring passenger physiological data in the means of transport and adjusting the in-vehicle environment based on emotion analysis. This makes it possible to provide a travel environment optimized for the passenger's emotions.

[0198] - "Means of transportation" is a general term for devices and systems used to physically transport people or goods from one point to another.

[0199] "Passenger" refers to a person who is inside a means of transportation.

[0200] "Physiological data" refers to measurable data related to an individual's physical condition, such as heart rate, breathing patterns, and body temperature.

[0201] "Emotional analysis" is a process that identifies and evaluates an individual's emotional state using physiological data, facial expressions, voice, and other information.

[0202] "In-vehicle environment" refers to all physical and psychological elements within a means of transportation that affect passengers, such as lighting, sound, and temperature.

[0203] "Emotional response means" refers to mechanisms and methods for adjusting the in-vehicle environment and services according to the passenger's emotions, based on the results of emotion analysis.

[0204] To implement this invention, a system involving a server, terminals, and a vehicle as a means of transportation is required. The server is responsible for collecting physiological data and personal information of passengers and generating emotional profiles by analyzing them. Specifically, an emotional analysis engine running on the server takes the passenger's heart rate and facial expression data as input and determines their emotional state in real time.

[0205] The terminals include wearable devices worn by passengers, such as smart glasses and heart rate sensors. These devices continuously monitor physiological data and upload it to a server. Specific hardware examples include cameras from Logitech and heart rate sensors from Polar.

[0206] Within the vehicle, the in-car environment is dynamically adjusted based on the emotional state provided by the server. The emotional response system sets the in-car environment, including lighting tones and sound selection, to best suit the passenger's emotions. To this end, the emotional engine works in conjunction with the vehicle's control system to perform automatic adjustments.

[0207] For example, if the system determines that a passenger is relaxed, it can adjust the interior lighting to a warm color and select calming music. An example of a prompt using the generative AI model is shown below: "If the user is relaxed, please recommend a music playlist they like." In this way, it is possible to provide a comfortable travel experience while being attentive to the passenger's emotions.

[0208] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0209] Step 1:

[0210] The server receives physiological data from passengers collected from terminals. The input data includes heart rate and image data for facial expression analysis. Using this input data, the emotion analysis engine on the server performs initial analysis to identify emotions.

[0211] Step 2:

[0212] The emotion analysis engine analyzes received heart rate and facial expression data based on algorithms to determine the passenger's emotional state. Data processing includes preprocessing of image data and smoothing of heart rate data to determine the emotional category (relaxed, tense, excited, etc.). The analyzed emotional state is then output.

[0213] Step 3:

[0214] The server transmits the analyzed emotional state to the vehicle. The vehicle then prepares to adjust the in-vehicle environment based on the emotional state. This output data is passed to the environmental control system and used in the next adjustment step.

[0215] Step 4:

[0216] The in-vehicle environmental control system adjusts lighting tones and music selection based on the passenger's emotional state, as received from a server. Specifically, if the passenger is relaxed, the lighting will change to warm tones and soothing music will be played. This automatic adjustment optimizes the environment to the passenger's emotional state.

[0217] Step 5:

[0218] The user experiences the adjusted in-car environment. User feedback and changes in physiological data are newly collected and sent to the server. This allows the system to continuously optimize the environment while striving to maintain passenger comfort.

[0219] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0220] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0221] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0222] [Second Embodiment]

[0223] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0224] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0225] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0226] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0227] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0228] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0229] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0230] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0231] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0232] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0233] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0234] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0235] This invention is a technology for providing individually optimized experiences for hotel guests, and specifically consists of a process from information gathering and analysis to customization based on the results. A specific example of the system's operation is given below.

[0236] Information gathering

[0237] The server collects personal information, purpose of stay, hobbies, and food preferences from guests through online forms when they make reservations. It also records past stay history to build more accurate profiles.

[0238] Profile generation

[0239] The server uses the collected data to analyze guests' preferences and generate individually optimized profiles. These profiles are then used to customize the various services offered by the accommodation.

[0240] Display customization

[0241] The terminal plays a individually generated welcome video on the lobby display upon the user's arrival. This video combines seasonal changes and local scenery with content tailored to the user's interests.

[0242] Adjusting the guest room environment

[0243] Sensors built into the device monitor the user's heart rate and facial expressions in real time. Based on this data, the device provides optimized lighting and music for the user. For example, if the device determines that the user is relaxed, it will play calming music and use warm-colored lighting.

[0244] AI concierge response

[0245] Users can ask questions and request services in their own language. The server uses language processing algorithms to analyze these requests and instructs the terminal to provide an appropriate response. Multilingual support prevents misunderstandings due to language barriers.

[0246] Personalized meals and tours

[0247] The server suggests personalized menus based on the user's food preferences and information on local ingredients. Furthermore, it generates tour plans tailored to the family structure and interests, with a robot guide providing the tour. The tour content is adjusted to suit the user's schedule and interests.

[0248] As described above, the system of the present invention realizes an individually optimized stay experience through the cooperation of the server, terminal, and user. This system allows guests to have a special experience tailored to them, and is expected to improve their satisfaction.

[0249] The following describes the processing flow.

[0250] Step 1:

[0251] The server receives information provided by guests. Specifically, it collects personal information, purpose of stay, hobbies, and food preferences via online reservation forms and stores them in a database.

[0252] Step 2:

[0253] The server analyzes the accumulated data and creates guest profiles. These profiles include guidelines on how to customize the services provided during their stay.

[0254] Step 3:

[0255] The terminal controls displays installed in the lobby and guest rooms. Based on profile information sent from the server, it generates videos tailored to the guest's preferences and needs and plays them as a welcome movie.

[0256] Step 4:

[0257] The device's sensors detect the user's heart rate and facial expressions in real time. Based on this, the system evaluates the user's emotional state and adjusts the environment settings (lighting, music) accordingly.

[0258] Step 5:

[0259] Users can enter questions and requests into the device. They can enter them in their preferred language and interact with the information through a multilingual UI.

[0260] Step 6:

[0261] The server processes user requests received from the terminal. It uses natural language processing to analyze the input request and generate or retrieve appropriate information.

[0262] Step 7:

[0263] The terminal, having received instructions from the server, provides a response to the user. It accurately conveys the necessary information and services in the user's language using screen displays and audio output.

[0264] Step 8:

[0265] The server generates an optimal menu based on the user's food preferences and information on local ingredients. This menu is then presented to the user via their terminal.

[0266] Step 9:

[0267] The server creates tour plans for sightseeing and leisure based on the user's configuration information. The details of the plan are sent to the robot guide, and the user is guided on a tour tailored to their needs.

[0268] This series of processes enables the system to provide users with highly personalized services.

[0269] (Example 1)

[0270] Next, we will describe Example 1. 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."

[0271] In modern accommodations, it is common to provide a uniform service to all guests, making it difficult to offer personalized experiences tailored to the individual tastes, preferences, and needs of each guest. This can lead to decreased guest satisfaction and reduced willingness to return. Furthermore, efficiently implementing multilingual support and real-time environmental adjustments presents technical challenges.

[0272] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0273] In this invention, the server includes data processing means for collecting guest information and providing a personalized accommodation experience based on that information; information generation means for analyzing the information and generating guest profiles; and content generation means for providing customized content using the profiles and generated AI models. This enables the provision of personalized experiences, multilingual information services, and real-time environment adjustments.

[0274] "Data processing means" refers to technical means for analyzing information obtained from guests and providing personalized experiences based on that data.

[0275] "Information generation means" refers to technical means that are responsible for analyzing collected data to create profiles of guests.

[0276] "Display creation means" refers to a function for customizing the display and operation screens of accommodation facilities based on the guest's profile.

[0277] "Environmental adjustment means" refers to technologies that detect the physiological data and emotional state of guests and adjust lighting and sound based on the collected information.

[0278] "Language processing and response provision means" refers to technical means that understand and process guests' requests in multiple languages ​​and provide appropriate responses.

[0279] The "content generation means" is a technical means for providing customized content based on the profile of the guest using a generative AI model.

[0280] The "means including sensors and a control system" is a system configuration for detecting the physiological information of the guest in real time in the guest room and adjusting the environment based on the data.

[0281] The present invention is a system for providing an individualized accommodation experience to guests, implementing various technologies including data processing, information generation, display customization, environment adjustment, language processing, and content generation.

[0282] The server collects personal information, preferences, purpose of stay, and past accommodation history of the guest through an online form when the guest makes a reservation. A web server and a database management system are used for this. The server analyzes the accumulated data and generates a profile for each guest. The analysis incorporates a generative AI model to recognize data patterns and create an individualized profile.

[0283] The terminal functions as an interface within the accommodation facility and displays a welcome movie based on the guest's profile on the display upon arrival. For this movie generation, the software in the terminal uses a prompt sentence and requests the generative AI model to create appropriate content. An example of a specific prompt sentence is "Please customize the content of the welcome movie based on the guest information. Username: Yamada, Language: Japanese, Hobby: Trekking, Purpose of stay: Sightseeing".

[0284] The sensors installed in the terminal acquire the physiological data of the guest in real time and transmit it to the server. The server analyzes this data and dynamically adjusts the environmental settings such as lighting and music according to the guest's emotional state and stress level. This real-time adjustment is an important function to enable the guest to have a comfortable environment.

[0285] Furthermore, when a user makes a question or request in their native language, the server analyzes this using a language processing algorithm and generates an appropriate response. This enables smooth communication even for guests who speak different languages.

[0286] Overall, this system can provide a valuable individualized experience for guests and improve the service level of the accommodation facility.

[0287] The flow of the specific process in Example 1 will be described using FIG. 11.

[0288] Step 1:

[0289] The server collects reservation information through the online form input of the guest. The input data includes personal information, hobbies, and purpose of stay. Based on this information, the server creates a record in the database and prepares for analysis. The output is structured data that can be analyzed.

[0290] Step 2:

[0291] The server uses the generated AI model with the collected data to generate a profile of the guest. The input is the structured data obtained in Step 1, and the algorithms in the server analyze this to predict and generate the guest's preference pattern. The output is individually customized profile information.

[0292] Step 3:

[0293] The terminal generates a welcome movie to be displayed in the lobby based on the profile information received from the server. The input is the profile information, which is sent as a prompt sentence to the generated AI model to perform the operation of generating appropriate content. The output is a movie containing a welcome message optimized for the user.

[0294] Step 4:

[0295] The terminal's sensors monitor the guest's heart rate and facial expressions in real time within the room and transmit this data to a server. The input is biosensor data, which is analyzed to determine the guest's state (stress, relaxation, etc.). The output is lighting and music settings data that reflect the guest's state.

[0296] Step 5:

[0297] When a user enters a question in their native language via their device, the server performs language processing and generates the necessary response. The input is a question in the user's language, which is analyzed and understood by AI to generate an appropriate answer on the server. The output is service information and response messages in a language the user understands.

[0298] Step 6:

[0299] The server generates personalized meal menus based on the generated guest profiles and local ingredient information. The input is the profile and local information, and a food recommendation algorithm is used to suggest the most suitable menu. The output is a personalized menu suggestion, providing dishes tailored to the user's preferences.

[0300] (Application Example 1)

[0301] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0302] Accommodations and retail stores that offer personalized experiences are required to provide services tailored to individual preferences and needs in order to increase customer satisfaction. However, currently, it is difficult to properly collect individual customer information and immediately reflect it in the service, resulting in the challenge of only being able to provide standardized services to customers.

[0303] Specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is implemented by the following means.

[0304] In this invention, the server includes information processing means for collecting information of a lodger or a customer and providing an individualized experience based on the information, profile generation means for analyzing the collected information and generating a profile, and information presentation means for presenting relevant product information in the store in real time based on the customer's purchase history and preferences. This enables the provision of personalized services and product information that meet the specific needs of customers.

[0305] The "information processing means" is a mechanism for collecting information of a lodger or a customer and managing and analyzing the data necessary to provide an individualized experience.

[0306] The "profile generation means" is a function for analyzing the collected customer information and creating a profile including characteristics and preferences suitable for individual customers.

[0307] The "display generation means" is a device or function for customizing and providing videos and interfaces in accommodation facilities or stores based on the generated profile.

[0308] The "environment control means" is a mechanism for optimally adjusting lighting, sound, and other environmental elements according to the physiological data and emotional state of the customer.

[0309] The "language processing and response means" is a technology for analyzing languages and generating and presenting appropriate responses in order to provide information services corresponding to multiple languages.

[0310] The "information presentation means" is a technology for displaying relevant product information in the store in real time based on the customer's purchase history and preferences.

[0311] A "promotion generation method" is a function that identifies recommended products according to the customer's profile and generates promotions based on those products.

[0312] This invention constructs a system for providing personalized customer experiences in accommodations and retail stores. The main components of the system include information processing means, profile generation means, display generation means, environment control means, information presentation means, promotion generation means, language processing and response means.

[0313] The server collects information provided in advance by guests or customers, such as their store visit history and purchase history. This information is used to generate customer profiles. The profile generation system analyzes and stores profiles tailored to individual customers based on the collected data. For example, if a customer frequently purchases a particular brand or product, that preference will be reflected in their profile.

[0314] The terminal uses a display generation mechanism to present customized information based on the customer's profile when they visit a hotel or physical store. Within the store, product information and promotional videos are displayed in the customer's field of vision using a smartphone or smart glasses. This information is presented in real time, and relevant information about products the customer shows interest in is provided immediately.

[0315] Furthermore, through environmental control systems, customer physiological data and emotions are analyzed via sensors, and lighting and music are automatically adjusted accordingly. For example, if a customer prefers a calm atmosphere, the lighting is set to warm tones and relaxing music is played.

[0316] Customers, even if they use different languages, can receive guidance and answers to their questions within stores and accommodations through multilingual information services. The language processing and response means uses a generative AI model to perform language analysis and generate responses in the appropriate language.

[0317] For example, when a customer is looking for a specific product in a store, a prompt message such as "Based on this customer's past purchase history, generate and display information about products they should be interested in now" can be entered into the AI ​​model, and relevant information will be presented immediately.

[0318] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0319] Step 1:

[0320] The server collects personal information and purchase history provided in advance by guests or customers. The information entered includes name, address, past purchase history, and preferred categories. The server stores this data in a database in preparation for later profile generation. The output is formatted customer information data.

[0321] Step 2:

[0322] The server generates customer profiles using the collected data. The input is the customer information data obtained in Step 1. Using a generation AI model, it analyzes customer preferences and interests to output a personalized profile. This profile includes frequently purchased items and topics of interest.

[0323] Step 3:

[0324] The terminal displays product information based on a customer's profile in real time when they enter the store. The input is the customer profile obtained in step 2. The prompt message "Generate interesting product information based on this customer's profile and display it on the screen" is input to the AI ​​model, and the generated information is output. Specifically, a product promotional video is displayed on the smart glasses.

[0325] Step 4:

[0326] Users search for products or ask questions within the store. The terminal receives this as input and outputs appropriate answers using a multilingual FAQ system. The terminal provides responses via voice or text, enhancing user convenience.

[0327] Step 5:

[0328] The terminal uses sensors to detect the customer's physiological data and facial expressions in real time. Inputs include the customer's heart rate and facial expression data. Based on this, environmental control systems adjust lighting and sound, providing an optimized environment as output. For example, the lighting might be changed to a warmer color to promote relaxation.

[0329] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0330] This invention is a system for providing personalized experiences based on guests' emotions. It achieves a high degree of personalization by accurately recognizing each guest's emotions and introducing the most appropriate service accordingly. This system centers around an emotion engine and encompasses a series of processes from information gathering and analysis to service delivery.

[0331] Information gathering

[0332] The server not only collects guests' personal information and past usage history, but also stores specific preferences and needs provided during booking in a database.

[0333] Profile generation

[0334] The server analyzes the collected data and generates a user profile. This profile is combined with the sentiment data captured by the sentiment engine and used to customize the service design.

[0335] Acquisition of emotional data

[0336] Sensors installed on the device acquire physiological indicators such as the user's heart rate, facial expressions, and voice tone, and transmit them to a server. The server processes this data in real time, and an emotion engine identifies the user's emotional state.

[0337] Analysis and response to emotional states

[0338] The server analyzes the data acquired using an emotion engine and selects appropriate services using emotional response mechanisms. For example, if the device detects that the user is stressed, it will automatically play relaxing music and change the lighting to a calming tone.

[0339] Personalized content delivery

[0340] The device provides users with personalized entertainment and information in real time based on their emotions. It can also automatically update movie and music playlists in response to changes in the user's emotions.

[0341] Multilingual support service

[0342] Based on the results of emotion recognition, the system generates accurate responses in multiple languages ​​to user questions and requests. The server uses natural language processing technology to compensate for language differences and return appropriate information.

[0343] As a concrete example, if the system detects that a user is excited, it will recommend upbeat background music or energizing video content. Conversely, for users who intend to spend their time quietly, it will provide calming music and warm lighting. In this way, the present invention can cater to the emotions of guests and provide a high level of satisfaction through an individualized experience.

[0344] The following describes the processing flow.

[0345] Step 1:

[0346] Users make accommodation reservations and, at that time, enter personal information, purpose of stay, food preferences, desired experiences, etc., into an online form. This information is sent to the server.

[0347] Step 2:

[0348] The server analyzes the received information and generates a profile of the guest. This profile is used as the basis for providing customized services during their stay.

[0349] Step 3:

[0350] The terminal uses sensors installed in the guest room to monitor physiological indicators such as the user's heart rate, facial expressions, and voice tone. This data is sent to a server for processing by the emotion engine.

[0351] Step 4:

[0352] The server activates an emotion engine, analyzes the user's physiological data in real time, and identifies the user's emotional state. Emotional states are classified into categories such as stress, relaxation, and excitement.

[0353] Step 5:

[0354] Based on the analysis results from the emotion engine, the server issues commands to the terminal. For example, if the server determines that the user is relaxed, the terminal changes the room lighting to a warm color and plays relaxing music.

[0355] Step 6:

[0356] Based on the user's interests, the device suggests entertainment content that matches their mood. Based on instructions from the server, lists of movies and music are customized to the user's preferences.

[0357] Step 7:

[0358] When the server receives a question or request from a user, it uses natural language processing to analyze it and generates a multilingual response. The terminal then returns the information to the user in an appropriate format.

[0359] Step 8:

[0360] The server accumulates emotional data acquired daily and updates and optimizes profiles based on long-term data. This feedback loop ensures that even more precise service is provided during subsequent stays.

[0361] In this way, data and commands are exchanged between the server, terminal, and user, enabling the provision of a personalized and advanced accommodation experience to the user.

[0362] (Example 2)

[0363] Next, we will describe Example 2. 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".

[0364] Traditional accommodations have been unable to provide a uniform service to guests, making it difficult to customize services to meet individual needs and emotional states. Therefore, providing personalized experiences is essential to increasing guest satisfaction. However, in practice, it is difficult to accommodate the changing preferences and emotions of each guest, and there are technical challenges, particularly in overcoming language barriers while providing emotion-based service.

[0365] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0366] In this invention, the server includes information processing means for collecting guest information and providing a personalized accommodation experience based on that information and past usage history; profile generation means for analyzing the collected information and generating a detailed profile of the guest; and environment adjustment means for customizing the lighting and sound environment of the accommodation using the profile and acquired guest emotional state data. This enables a personalized experience that provides a high level of satisfaction in accordance with the guest's emotional state.

[0367] "Information processing means" refers to a device or system that has the function of collecting information and past usage history of guests and providing an individualized accommodation experience based on that information.

[0368] "Profile generation means" refers to a device or system for analyzing collected information to generate a detailed profile of a guest.

[0369] "Environmental adjustment means" refers to a device or system for customizing the lighting and sound environment of accommodation using acquired emotional state data of guests.

[0370] "Personalized content generation means" refers to a device or system for providing appropriate content in real time based on information obtained from sentiment analysis.

[0371] "Language processing and response means" refers to a device or system for providing multilingual information tailored to the emotional state of guests in response to their inquiries.

[0372] "Means of providing food" refers to a device or system for generating and providing personalized menus based on the food preferences of guests and the characteristics of the region.

[0373] A "guide plan generation means" is a device or system for dynamically adjusting tourist information based on the emotional state and compositional information of the guests.

[0374] This invention relates to a system that provides personalized experiences based on the emotional state of guests in accommodation facilities. Centered around an emotion engine, it covers a series of processes from information gathering and analysis to service delivery.

[0375] First, the server processes guest information. Specifically, it stores guests' personal information, past stay history, and preferences and needs provided during booking in a database. This data is analyzed and used to generate detailed guest profiles. Statistical analysis software and data mining techniques are being considered as methods for profile generation.

[0376] Next, the device acquires the user's physiological data. Specifically, it monitors facial expressions and voice tone in real time using a heart rate sensor and camera. This data is sent to a server and analyzed by an emotion engine. Once the emotional state is identified, the lighting and acoustic environment are automatically adjusted accordingly. This process requires appropriate processing equipment to execute the algorithms.

[0377] Furthermore, the device provides users with entertainment and information tailored to their needs in real time, based on sentiment analysis. Music playlists and movie recommendations are automatically updated according to the user's mood. This feature utilizes a generative AI model to optimize content delivery.

[0378] As part of the multilingual service, the server uses natural language processing technology to generate responses tailored to the guest's language. This enables a more empathetic service that transcends language barriers.

[0379] For example, if the server detects that the user is excited, the terminal will play upbeat background music and provide video content to enhance their energy. On the other hand, if the server recognizes that the user wants to relax, it will provide calming music and warm lighting. An example of a prompt message would be, "What services should be provided when a guest's emotions indicate stress? Please suggest specific music and lighting settings."

[0380] In this way, it is possible to provide a customized experience that matches the emotions of the guests.

[0381] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0382] Step 1:

[0383] The server collects basic guest information, past stay history, and specific preferences and needs entered during booking into a database. Based on this input data, it uses a database management system to organize and store the information. Specifically, the server registers information when a guest checks in and identifies similar past stay patterns.

[0384] Step 2:

[0385] The server generates guest profiles using the collected data. It processes the entered basic information and historical data through an analysis algorithm to extract behavioral patterns and preferences. As a result, a profile optimized for each individual guest is output. Specifically, the server uses machine learning models to predict behavior and infer preferences.

[0386] Step 3:

[0387] The terminal acquires guests' physiological data in real time. User input includes heart rate, facial expression analysis, and voice tone, and this data is collected from sensors. The terminal sends this physiological data to a server, where it is analyzed by an emotion engine. Specifically, the terminal uses its camera to record video and its microphone to record voice tone.

[0388] Step 4:

[0389] The server performs emotional analysis based on the received physiological data to identify the guest's emotional state. This analysis involves applying the input data to an emotion engine algorithm and outputting emotions such as stress, joy, or excitement. Specifically, the server processes the data in real time and assigns the appropriate emotion category.

[0390] Step 5:

[0391] The terminal provides guests with entertainment and information tailored to their emotional state based on its analysis. The user's emotional state is the input, and based on this, the terminal selects and outputs music playlists and video content. Specifically, the terminal plays music appropriate to the emotion and delivers content suitable for the display device.

[0392] Step 6:

[0393] The server provides multilingual support services, generating responses in the appropriate language based on user inquiries. Input includes the guest's emotional state and language preferences, while output is information provided in the corresponding language. Specifically, the server uses natural language processing to translate user questions and provides responses tailored to their emotional state.

[0394] (Application Example 2)

[0395] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0396] In the realm of transportation, it is difficult for passengers to enjoy a comfortable and personalized experience over extended periods. In particular, autonomous vehicles require adjustments to the in-car environment based on the passenger's emotions and physiological state, but there is a lack of appropriate means to achieve this.

[0397] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0398] In this invention, the server includes information processing means for collecting guest information and providing a personalized accommodation experience based on that information; profile generation means for analyzing the collected information and generating a guest profile; display generation means for customizing the accommodation's images and interface; and emotion response means for acquiring passenger physiological data in the means of transport and adjusting the in-vehicle environment based on emotion analysis. This makes it possible to provide a travel environment optimized for the passenger's emotions.

[0399] - "Means of transportation" is a general term for devices and systems used to physically transport people or goods from one point to another.

[0400] "Passenger" refers to a person who is inside a means of transportation.

[0401] "Physiological data" refers to measurable data related to an individual's physical condition, such as heart rate, breathing patterns, and body temperature.

[0402] "Emotional analysis" is a process that identifies and evaluates an individual's emotional state using physiological data, facial expressions, voice, and other information.

[0403] "In-vehicle environment" refers to all physical and psychological elements within a means of transportation that affect passengers, such as lighting, sound, and temperature.

[0404] "Emotional response means" refers to mechanisms and methods for adjusting the in-vehicle environment and services according to the passenger's emotions, based on the results of emotion analysis.

[0405] To implement this invention, a system involving a server, terminals, and a vehicle as a means of transportation is required. The server is responsible for collecting physiological data and personal information of passengers and generating emotional profiles by analyzing them. Specifically, an emotional analysis engine running on the server takes the passenger's heart rate and facial expression data as input and determines their emotional state in real time.

[0406] The terminals include wearable devices worn by passengers, such as smart glasses and heart rate sensors. These devices continuously monitor physiological data and upload it to a server. Specific hardware examples include cameras from Logitech and heart rate sensors from Polar.

[0407] Within the vehicle, the in-car environment is dynamically adjusted based on the emotional state provided by the server. The emotional response system sets the in-car environment, including lighting tones and sound selection, to best suit the passenger's emotions. To this end, the emotional engine works in conjunction with the vehicle's control system to perform automatic adjustments.

[0408] For example, if the system determines that a passenger is relaxed, it can adjust the interior lighting to a warm color and select calming music. An example of a prompt using the generative AI model is shown below: "If the user is relaxed, please recommend a music playlist they like." In this way, it is possible to provide a comfortable travel experience while being attentive to the passenger's emotions.

[0409] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0410] Step 1:

[0411] The server receives physiological data from passengers collected from terminals. The input data includes heart rate and image data for facial expression analysis. Using this input data, the emotion analysis engine on the server performs initial analysis to identify emotions.

[0412] Step 2:

[0413] The emotion analysis engine analyzes received heart rate and facial expression data based on algorithms to determine the passenger's emotional state. Data processing includes preprocessing of image data and smoothing of heart rate data to determine the emotional category (relaxed, tense, excited, etc.). The analyzed emotional state is then output.

[0414] Step 3:

[0415] The server transmits the analyzed emotional state to the vehicle. The vehicle then prepares to adjust the in-vehicle environment based on the emotional state. This output data is passed to the environmental control system and used in the next adjustment step.

[0416] Step 4:

[0417] The in-vehicle environmental control system adjusts lighting tones and music selection based on the passenger's emotional state, as received from a server. Specifically, if the passenger is relaxed, the lighting will change to warm tones and soothing music will be played. This automatic adjustment optimizes the environment to the passenger's emotional state.

[0418] Step 5:

[0419] The user experiences the adjusted in-car environment. User feedback and changes in physiological data are newly collected and sent to the server. This allows the system to continuously optimize the environment while striving to maintain passenger comfort.

[0420] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0421] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0422] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0423] [Third Embodiment]

[0424] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0425] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0426] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0427] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0428] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0429] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0430] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0431] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0432] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0433] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0434] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0435] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0436] This invention is a technology for providing individually optimized experiences for hotel guests, and specifically consists of a process from information gathering and analysis to customization based on the results. A specific example of the system's operation is given below.

[0437] Information gathering

[0438] The server collects personal information, purpose of stay, hobbies, and food preferences from guests through online forms when they make reservations. It also records past stay history to build more accurate profiles.

[0439] Profile generation

[0440] The server uses the collected data to analyze guests' preferences and generate individually optimized profiles. These profiles are then used to customize the various services offered by the accommodation.

[0441] Display customization

[0442] The terminal plays a individually generated welcome video on the lobby display upon the user's arrival. This video combines seasonal changes and local scenery with content tailored to the user's interests.

[0443] Adjusting the guest room environment

[0444] Sensors built into the device monitor the user's heart rate and facial expressions in real time. Based on this data, the device provides optimized lighting and music for the user. For example, if the device determines that the user is relaxed, it will play calming music and use warm-colored lighting.

[0445] AI concierge response

[0446] Users can ask questions and request services in their own language. The server uses language processing algorithms to analyze these requests and instructs the terminal to provide an appropriate response. Multilingual support prevents misunderstandings due to language barriers.

[0447] Personalized meals and tours

[0448] The server suggests personalized menus based on the user's food preferences and information on local ingredients. Furthermore, it generates tour plans tailored to the family structure and interests, with a robot guide providing the tour. The tour content is adjusted to suit the user's schedule and interests.

[0449] As described above, the system of the present invention realizes an individually optimized stay experience through the cooperation of the server, terminal, and user. This system allows guests to have a special experience tailored to them, and is expected to improve their satisfaction.

[0450] The following describes the processing flow.

[0451] Step 1:

[0452] The server receives information provided by guests. Specifically, it collects personal information, purpose of stay, hobbies, and food preferences via online reservation forms and stores them in a database.

[0453] Step 2:

[0454] The server analyzes the accumulated data and creates guest profiles. These profiles include guidelines on how to customize the services provided during their stay.

[0455] Step 3:

[0456] The terminal controls displays installed in the lobby and guest rooms. Based on profile information sent from the server, it generates videos tailored to the guest's preferences and needs and plays them as a welcome movie.

[0457] Step 4:

[0458] The device's sensors detect the user's heart rate and facial expressions in real time. Based on this, the system evaluates the user's emotional state and adjusts the environment settings (lighting, music) accordingly.

[0459] Step 5:

[0460] Users can enter questions and requests into the device. They can enter them in their preferred language and interact with the information through a multilingual UI.

[0461] Step 6:

[0462] The server processes user requests received from the terminal. It uses natural language processing to analyze the input request and generate or retrieve appropriate information.

[0463] Step 7:

[0464] The terminal, having received instructions from the server, provides a response to the user. It accurately conveys the necessary information and services in the user's language using screen displays and audio output.

[0465] Step 8:

[0466] The server generates an optimal menu based on the user's food preferences and information on local ingredients. This menu is then presented to the user via their terminal.

[0467] Step 9:

[0468] The server creates tour plans for sightseeing and leisure based on the user's configuration information. The details of the plan are sent to the robot guide, and the user is guided on a tour tailored to their needs.

[0469] This series of processes enables the system to provide users with highly personalized services.

[0470] (Example 1)

[0471] Next, we will describe Example 1. 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."

[0472] In modern accommodations, it is common to provide a uniform service to all guests, making it difficult to offer personalized experiences tailored to the individual tastes, preferences, and needs of each guest. This can lead to decreased guest satisfaction and reduced willingness to return. Furthermore, efficiently implementing multilingual support and real-time environmental adjustments presents technical challenges.

[0473] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0474] In this invention, the server includes data processing means for collecting guest information and providing a personalized accommodation experience based on that information; information generation means for analyzing the information and generating guest profiles; and content generation means for providing customized content using the profiles and generated AI models. This enables the provision of personalized experiences, multilingual information services, and real-time environment adjustments.

[0475] "Data processing means" refers to technical means for analyzing information obtained from guests and providing personalized experiences based on that data.

[0476] "Information generation means" refers to technical means that are responsible for analyzing collected data to create profiles of guests.

[0477] "Display creation means" refers to a function for customizing the display and operation screens of accommodation facilities based on the guest's profile.

[0478] "Environmental adjustment means" refers to technologies that detect the physiological data and emotional state of guests and adjust lighting and sound based on the collected information.

[0479] "Language processing and response provision means" refers to technical means that understand and process guests' requests in multiple languages ​​and provide appropriate responses.

[0480] "Content generation means" refers to a technical means that uses a generation AI model to provide customized content based on the guest's profile.

[0481] "Means including sensors and control systems" refers to a system configuration for detecting guests' physiological information in real time in a guest room and adjusting the environment based on that data.

[0482] This invention is a system for providing guests with an individualized lodging experience, and implements a variety of technologies including data processing, information generation, display customization, environment adjustment, language processing, and content generation.

[0483] The server collects personal information, preferences, purpose of stay, and past stay history from guests through online forms when they make reservations. This uses a web server and a database management system. The server analyzes the collected data and generates a profile for each guest. The analysis incorporates a generative AI model to recognize patterns in the data and create personalized profiles.

[0484] The terminal functions as an interface within the accommodation, displaying a welcome video based on the guest's profile upon arrival. The software within the terminal uses prompt messages to instruct a generation AI model to create appropriate content for this video. An example of a specific prompt message would be: "Please customize the content of the welcome video based on the guest information. Username: Yamada, Language: Japanese, Hobbies: Trekking, Purpose of Stay: Sightseeing."

[0485] Sensors installed on the terminal acquire guests' physiological data in real time and transmit it to a server. The server analyzes this data and dynamically adjusts environmental settings such as lighting and music according to the guests' emotional state and stress levels. This real-time adjustment is a crucial function for ensuring guests have a comfortable stay.

[0486] Furthermore, when a user makes a question or request in their native language, the server uses a language processing algorithm to analyze it and generate an appropriate response. This enables smooth communication even for guests who speak different languages.

[0487] Overall, this system can provide guests with personalized and valuable experiences, improving the service level of accommodations.

[0488] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0489] Step 1:

[0490] The server collects reservation information through online form submissions from guests. This input data includes personal information, hobbies, and purpose of stay. Based on this information, the server creates records in a database and prepares them for analysis. The output is structured data that can be analyzed.

[0491] Step 2:

[0492] The server uses a generative AI model based on the collected data to generate guest profiles. The input is the structured data obtained in step 1, which the server's algorithm analyzes to predict and generate guest preference patterns. The output is individually customized profile information.

[0493] Step 3:

[0494] The terminal generates a welcome movie to display in the lobby based on profile information received from the server. The input is profile information, which is sent as a prompt to a generation AI model, which then generates appropriate content. The output is a movie containing a user-optimized welcome message.

[0495] Step 4:

[0496] The terminal's sensors monitor the guest's heart rate and facial expressions in real time within the room and transmit this data to a server. The input is biosensor data, which is analyzed to determine the guest's state (stress, relaxation, etc.). The output is lighting and music settings data that reflect the guest's state.

[0497] Step 5:

[0498] When a user enters a question in their native language via their device, the server performs language processing and generates the necessary response. The input is a question in the user's language, which is analyzed and understood by AI to generate an appropriate answer on the server. The output is service information and response messages in a language the user understands.

[0499] Step 6:

[0500] The server generates personalized meal menus based on the generated guest profiles and local ingredient information. The input is the profile and local information, and a food recommendation algorithm is used to suggest the most suitable menu. The output is a personalized menu suggestion, providing dishes tailored to the user's preferences.

[0501] (Application Example 1)

[0502] Next, we will explain Application Example 1. In the following explanation, 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."

[0503] Accommodations and retail stores that offer personalized experiences are required to provide services tailored to individual preferences and needs in order to increase customer satisfaction. However, currently, it is difficult to properly collect individual customer information and immediately reflect it in the service, resulting in the challenge of only being able to provide standardized services to customers.

[0504] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0505] In this invention, the server includes information processing means for collecting guest or customer information and providing personalized experiences based on that information; profile generation means for analyzing the collected information and generating a profile; and information presentation means for presenting relevant product information in-store in real time based on the customer's purchase history and preferences. This makes it possible to provide personalized services and product information that meet the specific needs of the customer.

[0506] "Information processing means" refers to a system that collects information about guests or customers and manages and analyzes the data necessary to provide personalized experiences.

[0507] A "profile generation method" is a function that analyzes collected customer information and creates a profile that includes characteristics and preferences tailored to each individual customer.

[0508] "Display generation means" refers to a device or function that provides customized video and interface content at accommodation facilities and shops based on a generated profile.

[0509] An "environmental control system" is a mechanism that optimally adjusts lighting, sound, and other environmental elements according to the customer's physiological data and emotional state.

[0510] "Language processing and response means" refers to technologies that analyze language and generate and present appropriate responses in order to provide information services that support multiple languages.

[0511] "Information presentation means" refers to technology that displays relevant product information in-store in real time, based on the customer's purchase history and preferences.

[0512] A "promotion generation method" is a function that identifies recommended products according to the customer's profile and generates promotions based on those products.

[0513] This invention constructs a system for providing personalized customer experiences in accommodations and retail stores. The main components of the system include information processing means, profile generation means, display generation means, environment control means, information presentation means, promotion generation means, language processing and response means.

[0514] The server collects information provided in advance by guests or customers, such as their store visit history and purchase history. This information is used to generate customer profiles. The profile generation system analyzes and stores profiles tailored to individual customers based on the collected data. For example, if a customer frequently purchases a particular brand or product, that preference will be reflected in their profile.

[0515] The terminal uses a display generation mechanism to present customized information based on the customer's profile when they visit a hotel or physical store. Within the store, product information and promotional videos are displayed in the customer's field of vision using a smartphone or smart glasses. This information is presented in real time, and relevant information about products the customer shows interest in is provided immediately.

[0516] Furthermore, through environmental control systems, customer physiological data and emotions are analyzed via sensors, and lighting and music are automatically adjusted accordingly. For example, if a customer prefers a calm atmosphere, the lighting is set to warm tones and relaxing music is played.

[0517] Customers, even if they use different languages, can receive guidance and answers to their questions within stores and accommodations through multilingual information services. The language processing and response means uses a generative AI model to perform language analysis and generate responses in the appropriate language.

[0518] For example, when a customer is looking for a specific product in a store, a prompt message such as "Based on this customer's past purchase history, generate and display information about products they should be interested in now" can be entered into the AI ​​model, and relevant information will be presented immediately.

[0519] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0520] Step 1:

[0521] The server collects personal information and purchase history provided in advance by guests or customers. The information entered includes name, address, past purchase history, and preferred categories. The server stores this data in a database in preparation for later profile generation. The output is formatted customer information data.

[0522] Step 2:

[0523] The server generates customer profiles using the collected data. The input is the customer information data obtained in Step 1. Using a generation AI model, it analyzes customer preferences and interests to output a personalized profile. This profile includes frequently purchased items and topics of interest.

[0524] Step 3:

[0525] The terminal displays product information based on a customer's profile in real time when they enter the store. The input is the customer profile obtained in step 2. The prompt message "Generate interesting product information based on this customer's profile and display it on the screen" is input to the AI ​​model, and the generated information is output. Specifically, a product promotional video is displayed on the smart glasses.

[0526] Step 4:

[0527] Users search for products or ask questions within the store. The terminal receives this as input and outputs appropriate answers using a multilingual FAQ system. The terminal provides responses via voice or text, enhancing user convenience.

[0528] Step 5:

[0529] The terminal uses sensors to detect the customer's physiological data and facial expressions in real time. Inputs include the customer's heart rate and facial expression data. Based on this, environmental control systems adjust lighting and sound, providing an optimized environment as output. For example, the lighting might be changed to a warmer color to promote relaxation.

[0530] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0531] This invention is a system for providing personalized experiences based on guests' emotions. It achieves a high degree of personalization by accurately recognizing each guest's emotions and introducing the most appropriate service accordingly. This system centers around an emotion engine and encompasses a series of processes from information gathering and analysis to service delivery.

[0532] Information gathering

[0533] The server not only collects guests' personal information and past usage history, but also stores specific preferences and needs provided during booking in a database.

[0534] Profile generation

[0535] The server analyzes the collected data and generates a user profile. This profile is combined with the sentiment data captured by the sentiment engine and used to customize the service design.

[0536] Acquisition of emotional data

[0537] Sensors installed on the device acquire physiological indicators such as the user's heart rate, facial expressions, and voice tone, and transmit them to a server. The server processes this data in real time, and an emotion engine identifies the user's emotional state.

[0538] Analysis and response to emotional states

[0539] The server analyzes the data acquired using an emotion engine and selects appropriate services using emotional response mechanisms. For example, if the device detects that the user is stressed, it will automatically play relaxing music and change the lighting to a calming tone.

[0540] Personalized content delivery

[0541] The device provides users with personalized entertainment and information in real time based on their emotions. It can also automatically update movie and music playlists in response to changes in the user's emotions.

[0542] Multilingual support service

[0543] Based on the results of emotion recognition, the system generates accurate responses in multiple languages ​​to user questions and requests. The server uses natural language processing technology to compensate for language differences and return appropriate information.

[0544] As a concrete example, if the system detects that a user is excited, it will recommend upbeat background music or energizing video content. Conversely, for users who intend to spend their time quietly, it will provide calming music and warm lighting. In this way, the present invention can cater to the emotions of guests and provide a high level of satisfaction through an individualized experience.

[0545] The following describes the processing flow.

[0546] Step 1:

[0547] Users make accommodation reservations and, at that time, enter personal information, purpose of stay, food preferences, desired experiences, etc., into an online form. This information is sent to the server.

[0548] Step 2:

[0549] The server analyzes the received information and generates a profile of the guest. This profile is used as the basis for providing customized services during their stay.

[0550] Step 3:

[0551] The terminal uses sensors installed in the guest room to monitor physiological indicators such as the user's heart rate, facial expressions, and voice tone. This data is sent to a server for processing by the emotion engine.

[0552] Step 4:

[0553] The server activates an emotion engine, analyzes the user's physiological data in real time, and identifies the user's emotional state. Emotional states are classified into categories such as stress, relaxation, and excitement.

[0554] Step 5:

[0555] Based on the analysis results from the emotion engine, the server issues commands to the terminal. For example, if the server determines that the user is relaxed, the terminal changes the room lighting to a warm color and plays relaxing music.

[0556] Step 6:

[0557] Based on the user's interests, the device suggests entertainment content that matches their mood. Based on instructions from the server, lists of movies and music are customized to the user's preferences.

[0558] Step 7:

[0559] When the server receives a question or request from a user, it uses natural language processing to analyze it and generates a multilingual response. The terminal then returns the information to the user in an appropriate format.

[0560] Step 8:

[0561] The server accumulates emotional data acquired daily and updates and optimizes profiles based on long-term data. This feedback loop ensures that even more precise service is provided during subsequent stays.

[0562] In this way, data and commands are exchanged between the server, terminal, and user, enabling the provision of a personalized and advanced accommodation experience to the user.

[0563] (Example 2)

[0564] Next, we will describe Example 2. 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."

[0565] Traditional accommodations have been unable to provide a uniform service to guests, making it difficult to customize services to meet individual needs and emotional states. Therefore, providing personalized experiences is essential to increasing guest satisfaction. However, in practice, it is difficult to accommodate the changing preferences and emotions of each guest, and there are technical challenges, particularly in overcoming language barriers while providing emotion-based service.

[0566] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0567] In this invention, the server includes information processing means for collecting guest information and providing a personalized accommodation experience based on that information and past usage history; profile generation means for analyzing the collected information and generating a detailed profile of the guest; and environment adjustment means for customizing the lighting and sound environment of the accommodation using the profile and acquired guest emotional state data. This enables a personalized experience that provides a high level of satisfaction in accordance with the guest's emotional state.

[0568] "Information processing means" refers to a device or system that has the function of collecting information and past usage history of guests and providing an individualized accommodation experience based on that information.

[0569] "Profile generation means" refers to a device or system for analyzing collected information to generate a detailed profile of a guest.

[0570] "Environmental adjustment means" refers to a device or system for customizing the lighting and sound environment of accommodation using acquired emotional state data of guests.

[0571] "Personalized content generation means" refers to a device or system for providing appropriate content in real time based on information obtained from sentiment analysis.

[0572] "Language processing and response means" refers to a device or system for providing multilingual information tailored to the emotional state of guests in response to their inquiries.

[0573] "Means of providing food" refers to a device or system for generating and providing personalized menus based on the food preferences of guests and the characteristics of the region.

[0574] A "guide plan generation means" is a device or system for dynamically adjusting tourist information based on the emotional state and compositional information of the guests.

[0575] This invention relates to a system that provides personalized experiences based on the emotional state of guests in accommodation facilities. Centered around an emotion engine, it covers a series of processes from information gathering and analysis to service delivery.

[0576] First, the server processes guest information. Specifically, it stores guests' personal information, past stay history, and preferences and needs provided during booking in a database. This data is analyzed and used to generate detailed guest profiles. Statistical analysis software and data mining techniques are being considered as methods for profile generation.

[0577] Next, the device acquires the user's physiological data. Specifically, it monitors facial expressions and voice tone in real time using a heart rate sensor and camera. This data is sent to a server and analyzed by an emotion engine. Once the emotional state is identified, the lighting and acoustic environment are automatically adjusted accordingly. This process requires appropriate processing equipment to execute the algorithms.

[0578] Furthermore, the device provides users with entertainment and information tailored to their needs in real time, based on sentiment analysis. Music playlists and movie recommendations are automatically updated according to the user's mood. This feature utilizes a generative AI model to optimize content delivery.

[0579] As part of the multilingual service, the server uses natural language processing technology to generate responses tailored to the guest's language. This enables a more empathetic service that transcends language barriers.

[0580] For example, if the server detects that the user is excited, the terminal will play upbeat background music and provide video content to enhance their energy. On the other hand, if the server recognizes that the user wants to relax, it will provide calming music and warm lighting. An example of a prompt message would be, "What services should be provided when a guest's emotions indicate stress? Please suggest specific music and lighting settings."

[0581] In this way, it is possible to provide a customized experience that matches the emotions of the guests.

[0582] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0583] Step 1:

[0584] The server collects basic guest information, past stay history, and specific preferences and needs entered during booking into a database. Based on this input data, it uses a database management system to organize and store the information. Specifically, the server registers information when a guest checks in and identifies similar past stay patterns.

[0585] Step 2:

[0586] The server generates guest profiles using the collected data. It processes the entered basic information and historical data through an analysis algorithm to extract behavioral patterns and preferences. As a result, a profile optimized for each individual guest is output. Specifically, the server uses machine learning models to predict behavior and infer preferences.

[0587] Step 3:

[0588] The terminal acquires guests' physiological data in real time. User input includes heart rate, facial expression analysis, and voice tone, and this data is collected from sensors. The terminal sends this physiological data to a server, where it is analyzed by an emotion engine. Specifically, the terminal uses its camera to record video and its microphone to record voice tone.

[0589] Step 4:

[0590] The server performs emotional analysis based on the received physiological data to identify the guest's emotional state. This analysis involves applying the input data to an emotion engine algorithm and outputting emotions such as stress, joy, or excitement. Specifically, the server processes the data in real time and assigns the appropriate emotion category.

[0591] Step 5:

[0592] The terminal provides guests with entertainment and information tailored to their emotional state based on its analysis. The user's emotional state is the input, and based on this, the terminal selects and outputs music playlists and video content. Specifically, the terminal plays music appropriate to the emotion and delivers content suitable for the display device.

[0593] Step 6:

[0594] The server provides multilingual support services, generating responses in the appropriate language based on user inquiries. Input includes the guest's emotional state and language preferences, while output is information provided in the corresponding language. Specifically, the server uses natural language processing to translate user questions and provides responses tailored to their emotional state.

[0595] (Application Example 2)

[0596] Next, we will explain application example 2. In the following explanation, 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."

[0597] In the realm of transportation, it is difficult for passengers to enjoy a comfortable and personalized experience over extended periods. In particular, autonomous vehicles require adjustments to the in-car environment based on the passenger's emotions and physiological state, but there is a lack of appropriate means to achieve this.

[0598] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0599] In this invention, the server includes information processing means for collecting guest information and providing a personalized accommodation experience based on that information; profile generation means for analyzing the collected information and generating a guest profile; display generation means for customizing the accommodation's images and interface; and emotion response means for acquiring passenger physiological data in the means of transport and adjusting the in-vehicle environment based on emotion analysis. This makes it possible to provide a travel environment optimized for the passenger's emotions.

[0600] - "Means of transportation" is a general term for devices and systems used to physically transport people or goods from one point to another.

[0601] "Passenger" refers to a person who is inside a means of transportation.

[0602] "Physiological data" refers to measurable data related to an individual's physical condition, such as heart rate, breathing patterns, and body temperature.

[0603] "Emotional analysis" is a process that identifies and evaluates an individual's emotional state using physiological data, facial expressions, voice, and other information.

[0604] "In-vehicle environment" refers to all physical and psychological elements within a means of transportation that affect passengers, such as lighting, sound, and temperature.

[0605] "Emotional response means" refers to mechanisms and methods for adjusting the in-vehicle environment and services according to the passenger's emotions, based on the results of emotion analysis.

[0606] To implement this invention, a system involving a server, terminals, and a vehicle as a means of transportation is required. The server is responsible for collecting physiological data and personal information of passengers and generating emotional profiles by analyzing them. Specifically, an emotional analysis engine running on the server takes the passenger's heart rate and facial expression data as input and determines their emotional state in real time.

[0607] The terminals include wearable devices worn by passengers, such as smart glasses and heart rate sensors. These devices continuously monitor physiological data and upload it to a server. Specific hardware examples include cameras from Logitech and heart rate sensors from Polar.

[0608] Within the vehicle, the in-car environment is dynamically adjusted based on the emotional state provided by the server. The emotional response system sets the in-car environment, including lighting tones and sound selection, to best suit the passenger's emotions. To this end, the emotional engine works in conjunction with the vehicle's control system to perform automatic adjustments.

[0609] For example, if the system determines that a passenger is relaxed, it can adjust the interior lighting to a warm color and select calming music. An example of a prompt using the generative AI model is shown below: "If the user is relaxed, please recommend a music playlist they like." In this way, it is possible to provide a comfortable travel experience while being attentive to the passenger's emotions.

[0610] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0611] Step 1:

[0612] The server receives physiological data from passengers collected from terminals. The input data includes heart rate and image data for facial expression analysis. Using this input data, the emotion analysis engine on the server performs initial analysis to identify emotions.

[0613] Step 2:

[0614] The emotion analysis engine analyzes received heart rate and facial expression data based on algorithms to determine the passenger's emotional state. Data processing includes preprocessing of image data and smoothing of heart rate data to determine the emotional category (relaxed, tense, excited, etc.). The analyzed emotional state is then output.

[0615] Step 3:

[0616] The server transmits the analyzed emotional state to the vehicle. The vehicle then prepares to adjust the in-vehicle environment based on the emotional state. This output data is passed to the environmental control system and used in the next adjustment step.

[0617] Step 4:

[0618] The in-vehicle environmental control system adjusts lighting tones and music selection based on the passenger's emotional state, as received from a server. Specifically, if the passenger is relaxed, the lighting will change to warm tones and soothing music will be played. This automatic adjustment optimizes the environment to the passenger's emotional state.

[0619] Step 5:

[0620] The user experiences the adjusted in-car environment. User feedback and changes in physiological data are newly collected and sent to the server. This allows the system to continuously optimize the environment while striving to maintain passenger comfort.

[0621] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0622] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0623] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0624] [Fourth Embodiment]

[0625] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0626] As shown in Figure 7, the 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.

[0627] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0628] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0629] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0630] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0631] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0632] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0633] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0634] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0635] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0636] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0637] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0638] This invention is a technology for providing individually optimized experiences for hotel guests, and specifically consists of a process from information gathering and analysis to customization based on the results. A specific example of the system's operation is given below.

[0639] Information gathering

[0640] The server collects personal information, purpose of stay, hobbies, and food preferences from guests through online forms when they make reservations. It also records past stay history to build more accurate profiles.

[0641] Profile generation

[0642] The server uses the collected data to analyze guests' preferences and generate individually optimized profiles. These profiles are then used to customize the various services offered by the accommodation.

[0643] Display customization

[0644] The terminal plays a individually generated welcome video on the lobby display upon the user's arrival. This video combines seasonal changes and local scenery with content tailored to the user's interests.

[0645] Adjusting the guest room environment

[0646] Sensors built into the device monitor the user's heart rate and facial expressions in real time. Based on this data, the device provides optimized lighting and music for the user. For example, if the device determines that the user is relaxed, it will play calming music and use warm-colored lighting.

[0647] AI concierge response

[0648] Users can ask questions and request services in their own language. The server uses language processing algorithms to analyze these requests and instructs the terminal to provide an appropriate response. Multilingual support prevents misunderstandings due to language barriers.

[0649] Personalized meals and tours

[0650] The server suggests personalized menus based on the user's food preferences and information on local ingredients. Furthermore, it generates tour plans tailored to the family structure and interests, with a robot guide providing the tour. The tour content is adjusted to suit the user's schedule and interests.

[0651] As described above, the system of the present invention realizes an individually optimized stay experience through the cooperation of the server, terminal, and user. This system allows guests to have a special experience tailored to them, and is expected to improve their satisfaction.

[0652] The following describes the processing flow.

[0653] Step 1:

[0654] The server receives information provided by guests. Specifically, it collects personal information, purpose of stay, hobbies, and food preferences via online reservation forms and stores them in a database.

[0655] Step 2:

[0656] The server analyzes the accumulated data and creates guest profiles. These profiles include guidelines on how to customize the services provided during their stay.

[0657] Step 3:

[0658] The terminal controls displays installed in the lobby and guest rooms. Based on profile information sent from the server, it generates videos tailored to the guest's preferences and needs and plays them as a welcome movie.

[0659] Step 4:

[0660] The device's sensors detect the user's heart rate and facial expressions in real time. Based on this, the system evaluates the user's emotional state and adjusts the environment settings (lighting, music) accordingly.

[0661] Step 5:

[0662] Users can enter questions and requests into the device. They can enter them in their preferred language and interact with the information through a multilingual UI.

[0663] Step 6:

[0664] The server processes user requests received from the terminal. It uses natural language processing to analyze the input request and generate or retrieve appropriate information.

[0665] Step 7:

[0666] The terminal, having received instructions from the server, provides a response to the user. It accurately conveys the necessary information and services in the user's language using screen displays and audio output.

[0667] Step 8:

[0668] The server generates an optimal menu based on the user's food preferences and information on local ingredients. This menu is then presented to the user via their terminal.

[0669] Step 9:

[0670] The server creates tour plans for sightseeing and leisure based on the user's configuration information. The details of the plan are sent to the robot guide, and the user is guided on a tour tailored to their needs.

[0671] This series of processes enables the system to provide users with highly personalized services.

[0672] (Example 1)

[0673] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0674] In modern accommodations, it is common to provide a uniform service to all guests, making it difficult to offer personalized experiences tailored to the individual tastes, preferences, and needs of each guest. This can lead to decreased guest satisfaction and reduced willingness to return. Furthermore, efficiently implementing multilingual support and real-time environmental adjustments presents technical challenges.

[0675] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0676] In this invention, the server includes data processing means for collecting guest information and providing a personalized accommodation experience based on that information; information generation means for analyzing the information and generating guest profiles; and content generation means for providing customized content using the profiles and generated AI models. This enables the provision of personalized experiences, multilingual information services, and real-time environment adjustments.

[0677] "Data processing means" refers to technical means for analyzing information obtained from guests and providing personalized experiences based on that data.

[0678] "Information generation means" refers to technical means that are responsible for analyzing collected data to create profiles of guests.

[0679] "Display creation means" refers to a function for customizing the display and operation screens of accommodation facilities based on the guest's profile.

[0680] "Environmental adjustment means" refers to technologies that detect the physiological data and emotional state of guests and adjust lighting and sound based on the collected information.

[0681] "Language processing and response provision means" refers to technical means that understand and process guests' requests in multiple languages ​​and provide appropriate responses.

[0682] "Content generation means" refers to a technical means that uses a generation AI model to provide customized content based on the guest's profile.

[0683] "Means including sensors and control systems" refers to a system configuration for detecting guests' physiological information in real time in a guest room and adjusting the environment based on that data.

[0684] This invention is a system for providing guests with an individualized lodging experience, and implements a variety of technologies including data processing, information generation, display customization, environment adjustment, language processing, and content generation.

[0685] The server collects personal information, preferences, purpose of stay, and past stay history from guests through online forms when they make reservations. This uses a web server and a database management system. The server analyzes the collected data and generates a profile for each guest. The analysis incorporates a generative AI model to recognize patterns in the data and create personalized profiles.

[0686] The terminal functions as an interface within the accommodation, displaying a welcome video based on the guest's profile upon arrival. The software within the terminal uses prompt messages to instruct a generation AI model to create appropriate content for this video. An example of a specific prompt message would be: "Please customize the content of the welcome video based on the guest information. Username: Yamada, Language: Japanese, Hobbies: Trekking, Purpose of Stay: Sightseeing."

[0687] Sensors installed on the terminal acquire guests' physiological data in real time and transmit it to a server. The server analyzes this data and dynamically adjusts environmental settings such as lighting and music according to the guests' emotional state and stress levels. This real-time adjustment is a crucial function for ensuring guests have a comfortable stay.

[0688] Furthermore, when a user makes a question or request in their native language, the server uses a language processing algorithm to analyze it and generate an appropriate response. This enables smooth communication even for guests who speak different languages.

[0689] Overall, this system can provide guests with personalized and valuable experiences, improving the service level of accommodations.

[0690] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0691] Step 1:

[0692] The server collects reservation information through online form submissions from guests. This input data includes personal information, hobbies, and purpose of stay. Based on this information, the server creates records in a database and prepares them for analysis. The output is structured data that can be analyzed.

[0693] Step 2:

[0694] The server uses a generative AI model based on the collected data to generate guest profiles. The input is the structured data obtained in step 1, which the server's algorithm analyzes to predict and generate guest preference patterns. The output is individually customized profile information.

[0695] Step 3:

[0696] The terminal generates a welcome movie to display in the lobby based on profile information received from the server. The input is profile information, which is sent as a prompt to a generation AI model, which then generates appropriate content. The output is a movie containing a user-optimized welcome message.

[0697] Step 4:

[0698] The terminal's sensors monitor the guest's heart rate and facial expressions in real time within the room and transmit this data to a server. The input is biosensor data, which is analyzed to determine the guest's state (stress, relaxation, etc.). The output is lighting and music settings data that reflect the guest's state.

[0699] Step 5:

[0700] When a user enters a question in their native language via their device, the server performs language processing and generates the necessary response. The input is a question in the user's language, which is analyzed and understood by AI to generate an appropriate answer on the server. The output is service information and response messages in a language the user understands.

[0701] Step 6:

[0702] The server generates personalized meal menus based on the generated guest profiles and local ingredient information. The input is the profile and local information, and a food recommendation algorithm is used to suggest the most suitable menu. The output is a personalized menu suggestion, providing dishes tailored to the user's preferences.

[0703] (Application Example 1)

[0704] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0705] Accommodations and retail stores that offer personalized experiences are required to provide services tailored to individual preferences and needs in order to increase customer satisfaction. However, currently, it is difficult to properly collect individual customer information and immediately reflect it in the service, resulting in the challenge of only being able to provide standardized services to customers.

[0706] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0707] In this invention, the server includes information processing means for collecting guest or customer information and providing personalized experiences based on that information; profile generation means for analyzing the collected information and generating a profile; and information presentation means for presenting relevant product information in-store in real time based on the customer's purchase history and preferences. This makes it possible to provide personalized services and product information that meet the specific needs of the customer.

[0708] "Information processing means" refers to a system that collects information about guests or customers and manages and analyzes the data necessary to provide personalized experiences.

[0709] A "profile generation method" is a function that analyzes collected customer information and creates a profile that includes characteristics and preferences tailored to each individual customer.

[0710] "Display generation means" refers to a device or function that provides customized video and interface content at accommodation facilities and shops based on a generated profile.

[0711] An "environmental control system" is a mechanism that optimally adjusts lighting, sound, and other environmental elements according to the customer's physiological data and emotional state.

[0712] "Language processing and response means" refers to technologies that analyze language and generate and present appropriate responses in order to provide information services that support multiple languages.

[0713] "Information presentation means" refers to technology that displays relevant product information in-store in real time, based on the customer's purchase history and preferences.

[0714] A "promotion generation method" is a function that identifies recommended products according to the customer's profile and generates promotions based on those products.

[0715] This invention constructs a system for providing personalized customer experiences in accommodations and retail stores. The main components of the system include information processing means, profile generation means, display generation means, environment control means, information presentation means, promotion generation means, language processing and response means.

[0716] The server collects information provided in advance by guests or customers, such as their store visit history and purchase history. This information is used to generate customer profiles. The profile generation system analyzes and stores profiles tailored to individual customers based on the collected data. For example, if a customer frequently purchases a particular brand or product, that preference will be reflected in their profile.

[0717] The terminal uses a display generation mechanism to present customized information based on the customer's profile when they visit a hotel or physical store. Within the store, product information and promotional videos are displayed in the customer's field of vision using a smartphone or smart glasses. This information is presented in real time, and relevant information about products the customer shows interest in is provided immediately.

[0718] Furthermore, through environmental control systems, customer physiological data and emotions are analyzed via sensors, and lighting and music are automatically adjusted accordingly. For example, if a customer prefers a calm atmosphere, the lighting is set to warm tones and relaxing music is played.

[0719] Customers, even if they use different languages, can receive guidance and answers to their questions within stores and accommodations through multilingual information services. The language processing and response means uses a generative AI model to perform language analysis and generate responses in the appropriate language.

[0720] For example, when a customer is looking for a specific product in a store, a prompt message such as "Based on this customer's past purchase history, generate and display information about products they should be interested in now" can be entered into the AI ​​model, and relevant information will be presented immediately.

[0721] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0722] Step 1:

[0723] The server collects personal information and purchase history provided in advance by guests or customers. The information entered includes name, address, past purchase history, and preferred categories. The server stores this data in a database in preparation for later profile generation. The output is formatted customer information data.

[0724] Step 2:

[0725] The server generates customer profiles using the collected data. The input is the customer information data obtained in Step 1. Using a generation AI model, it analyzes customer preferences and interests to output a personalized profile. This profile includes frequently purchased items and topics of interest.

[0726] Step 3:

[0727] The terminal displays product information based on a customer's profile in real time when they enter the store. The input is the customer profile obtained in step 2. The prompt message "Generate interesting product information based on this customer's profile and display it on the screen" is input to the AI ​​model, and the generated information is output. Specifically, a product promotional video is displayed on the smart glasses.

[0728] Step 4:

[0729] Users search for products or ask questions within the store. The terminal receives this as input and outputs appropriate answers using a multilingual FAQ system. The terminal provides responses via voice or text, enhancing user convenience.

[0730] Step 5:

[0731] The terminal uses sensors to detect the customer's physiological data and facial expressions in real time. Inputs include the customer's heart rate and facial expression data. Based on this, environmental control systems adjust lighting and sound, providing an optimized environment as output. For example, the lighting might be changed to a warmer color to promote relaxation.

[0732] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0733] This invention is a system for providing personalized experiences based on guests' emotions. It achieves a high degree of personalization by accurately recognizing each guest's emotions and introducing the most appropriate service accordingly. This system centers around an emotion engine and encompasses a series of processes from information gathering and analysis to service delivery.

[0734] Information gathering

[0735] The server not only collects guests' personal information and past usage history, but also stores specific preferences and needs provided during booking in a database.

[0736] Profile generation

[0737] The server analyzes the collected data and generates a user profile. This profile is combined with the sentiment data captured by the sentiment engine and used to customize the service design.

[0738] Acquisition of emotional data

[0739] Sensors installed on the device acquire physiological indicators such as the user's heart rate, facial expressions, and voice tone, and transmit them to a server. The server processes this data in real time, and an emotion engine identifies the user's emotional state.

[0740] Analysis and response to emotional states

[0741] The server analyzes the data acquired using an emotion engine and selects appropriate services using emotional response mechanisms. For example, if the device detects that the user is stressed, it will automatically play relaxing music and change the lighting to a calming tone.

[0742] Personalized content delivery

[0743] The device provides users with personalized entertainment and information in real time based on their emotions. It can also automatically update movie and music playlists in response to changes in the user's emotions.

[0744] Multilingual support service

[0745] Based on the results of emotion recognition, the system generates accurate responses in multiple languages ​​to user questions and requests. The server uses natural language processing technology to compensate for language differences and return appropriate information.

[0746] As a concrete example, if the system detects that a user is excited, it will recommend upbeat background music or energizing video content. Conversely, for users who intend to spend their time quietly, it will provide calming music and warm lighting. In this way, the present invention can cater to the emotions of guests and provide a high level of satisfaction through an individualized experience.

[0747] The following describes the processing flow.

[0748] Step 1:

[0749] Users make accommodation reservations and, at that time, enter personal information, purpose of stay, food preferences, desired experiences, etc., into an online form. This information is sent to the server.

[0750] Step 2:

[0751] The server analyzes the received information and generates a profile of the guest. This profile is used as the basis for providing customized services during their stay.

[0752] Step 3:

[0753] The terminal uses sensors installed in the guest room to monitor physiological indicators such as the user's heart rate, facial expressions, and voice tone. This data is sent to a server for processing by the emotion engine.

[0754] Step 4:

[0755] The server activates an emotion engine, analyzes the user's physiological data in real time, and identifies the user's emotional state. Emotional states are classified into categories such as stress, relaxation, and excitement.

[0756] Step 5:

[0757] Based on the analysis results from the emotion engine, the server issues commands to the terminal. For example, if the server determines that the user is relaxed, the terminal changes the room lighting to a warm color and plays relaxing music.

[0758] Step 6:

[0759] Based on the user's interests, the device suggests entertainment content that matches their mood. Based on instructions from the server, lists of movies and music are customized to the user's preferences.

[0760] Step 7:

[0761] When the server receives a question or request from a user, it uses natural language processing to analyze it and generates a multilingual response. The terminal then returns the information to the user in an appropriate format.

[0762] Step 8:

[0763] The server accumulates emotional data acquired daily and updates and optimizes profiles based on long-term data. This feedback loop ensures that even more precise service is provided during subsequent stays.

[0764] In this way, data and commands are exchanged between the server, terminal, and user, enabling the provision of a personalized and advanced accommodation experience to the user.

[0765] (Example 2)

[0766] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0767] Traditional accommodations have been unable to provide a uniform service to guests, making it difficult to customize services to meet individual needs and emotional states. Therefore, providing personalized experiences is essential to increasing guest satisfaction. However, in practice, it is difficult to accommodate the changing preferences and emotions of each guest, and there are technical challenges, particularly in overcoming language barriers while providing emotion-based service.

[0768] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0769] In this invention, the server includes information processing means for collecting guest information and providing a personalized accommodation experience based on that information and past usage history; profile generation means for analyzing the collected information and generating a detailed profile of the guest; and environment adjustment means for customizing the lighting and sound environment of the accommodation using the profile and acquired guest emotional state data. This enables a personalized experience that provides a high level of satisfaction in accordance with the guest's emotional state.

[0770] "Information processing means" refers to a device or system that has the function of collecting information and past usage history of guests and providing an individualized accommodation experience based on that information.

[0771] "Profile generation means" refers to a device or system for analyzing collected information to generate a detailed profile of a guest.

[0772] "Environmental adjustment means" refers to a device or system for customizing the lighting and sound environment of accommodation using acquired emotional state data of guests.

[0773] "Personalized content generation means" refers to a device or system for providing appropriate content in real time based on information obtained from sentiment analysis.

[0774] "Language processing and response means" refers to a device or system for providing multilingual information tailored to the emotional state of guests in response to their inquiries.

[0775] "Means of providing food" refers to a device or system for generating and providing personalized menus based on the food preferences of guests and the characteristics of the region.

[0776] A "guide plan generation means" is a device or system for dynamically adjusting tourist information based on the emotional state and compositional information of the guests.

[0777] This invention relates to a system that provides personalized experiences based on the emotional state of guests in accommodation facilities. Centered around an emotion engine, it covers a series of processes from information gathering and analysis to service delivery.

[0778] First, the server processes guest information. Specifically, it stores guests' personal information, past stay history, and preferences and needs provided during booking in a database. This data is analyzed and used to generate detailed guest profiles. Statistical analysis software and data mining techniques are being considered as methods for profile generation.

[0779] Next, the device acquires the user's physiological data. Specifically, it monitors facial expressions and voice tone in real time using a heart rate sensor and camera. This data is sent to a server and analyzed by an emotion engine. Once the emotional state is identified, the lighting and acoustic environment are automatically adjusted accordingly. This process requires appropriate processing equipment to execute the algorithms.

[0780] Furthermore, the device provides users with entertainment and information tailored to their needs in real time, based on sentiment analysis. Music playlists and movie recommendations are automatically updated according to the user's mood. This feature utilizes a generative AI model to optimize content delivery.

[0781] As part of the multilingual service, the server uses natural language processing technology to generate responses tailored to the guest's language. This enables a more empathetic service that transcends language barriers.

[0782] For example, if the server detects that the user is excited, the terminal will play upbeat background music and provide video content to enhance their energy. On the other hand, if the server recognizes that the user wants to relax, it will provide calming music and warm lighting. An example of a prompt message would be, "What services should be provided when a guest's emotions indicate stress? Please suggest specific music and lighting settings."

[0783] In this way, it is possible to provide a customized experience that matches the emotions of the guests.

[0784] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0785] Step 1:

[0786] The server collects basic guest information, past stay history, and specific preferences and needs entered during booking into a database. Based on this input data, it uses a database management system to organize and store the information. Specifically, the server registers information when a guest checks in and identifies similar past stay patterns.

[0787] Step 2:

[0788] The server generates guest profiles using the collected data. It processes the entered basic information and historical data through an analysis algorithm to extract behavioral patterns and preferences. As a result, a profile optimized for each individual guest is output. Specifically, the server uses machine learning models to predict behavior and infer preferences.

[0789] Step 3:

[0790] The terminal acquires guests' physiological data in real time. User input includes heart rate, facial expression analysis, and voice tone, and this data is collected from sensors. The terminal sends this physiological data to a server, where it is analyzed by an emotion engine. Specifically, the terminal uses its camera to record video and its microphone to record voice tone.

[0791] Step 4:

[0792] The server performs emotional analysis based on the received physiological data to identify the guest's emotional state. This analysis involves applying the input data to an emotion engine algorithm and outputting emotions such as stress, joy, or excitement. Specifically, the server processes the data in real time and assigns the appropriate emotion category.

[0793] Step 5:

[0794] The terminal provides guests with entertainment and information tailored to their emotional state based on its analysis. The user's emotional state is the input, and based on this, the terminal selects and outputs music playlists and video content. Specifically, the terminal plays music appropriate to the emotion and delivers content suitable for the display device.

[0795] Step 6:

[0796] The server provides multilingual support services, generating responses in the appropriate language based on user inquiries. Input includes the guest's emotional state and language preferences, while output is information provided in the corresponding language. Specifically, the server uses natural language processing to translate user questions and provides responses tailored to their emotional state.

[0797] (Application Example 2)

[0798] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0799] In the realm of transportation, it is difficult for passengers to enjoy a comfortable and personalized experience over extended periods. In particular, autonomous vehicles require adjustments to the in-car environment based on the passenger's emotions and physiological state, but there is a lack of appropriate means to achieve this.

[0800] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0801] In this invention, the server includes information processing means for collecting guest information and providing a personalized accommodation experience based on that information; profile generation means for analyzing the collected information and generating a guest profile; display generation means for customizing the accommodation's images and interface; and emotion response means for acquiring passenger physiological data in the means of transport and adjusting the in-vehicle environment based on emotion analysis. This makes it possible to provide a travel environment optimized for the passenger's emotions.

[0802] - "Means of transportation" is a general term for devices and systems used to physically transport people or goods from one point to another.

[0803] "Passenger" refers to a person who is inside a means of transportation.

[0804] "Physiological data" refers to measurable data related to an individual's physical condition, such as heart rate, breathing patterns, and body temperature.

[0805] "Emotional analysis" is a process that identifies and evaluates an individual's emotional state using physiological data, facial expressions, voice, and other information.

[0806] "In-vehicle environment" refers to all physical and psychological elements within a means of transportation that affect passengers, such as lighting, sound, and temperature.

[0807] "Emotional response means" refers to mechanisms and methods for adjusting the in-vehicle environment and services according to the passenger's emotions, based on the results of emotion analysis.

[0808] To implement this invention, a system involving a server, terminals, and a vehicle as a means of transportation is required. The server is responsible for collecting physiological data and personal information of passengers and generating emotional profiles by analyzing them. Specifically, an emotional analysis engine running on the server takes the passenger's heart rate and facial expression data as input and determines their emotional state in real time.

[0809] The terminals include wearable devices worn by passengers, such as smart glasses and heart rate sensors. These devices continuously monitor physiological data and upload it to a server. Specific hardware examples include cameras from Logitech and heart rate sensors from Polar.

[0810] Within the vehicle, the in-car environment is dynamically adjusted based on the emotional state provided by the server. The emotional response system sets the in-car environment, including lighting tones and sound selection, to best suit the passenger's emotions. To this end, the emotional engine works in conjunction with the vehicle's control system to perform automatic adjustments.

[0811] For example, if the system determines that a passenger is relaxed, it can adjust the interior lighting to a warm color and select calming music. An example of a prompt using the generative AI model is shown below: "If the user is relaxed, please recommend a music playlist they like." In this way, it is possible to provide a comfortable travel experience while being attentive to the passenger's emotions.

[0812] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0813] Step 1:

[0814] The server receives physiological data from passengers collected from terminals. The input data includes heart rate and image data for facial expression analysis. Using this input data, the emotion analysis engine on the server performs initial analysis to identify emotions.

[0815] Step 2:

[0816] The emotion analysis engine analyzes received heart rate and facial expression data based on algorithms to determine the passenger's emotional state. Data processing includes preprocessing of image data and smoothing of heart rate data to determine the emotional category (relaxed, tense, excited, etc.). The analyzed emotional state is then output.

[0817] Step 3:

[0818] The server transmits the analyzed emotional state to the vehicle. The vehicle then prepares to adjust the in-vehicle environment based on the emotional state. This output data is passed to the environmental control system and used in the next adjustment step.

[0819] Step 4:

[0820] The in-vehicle environmental control system adjusts lighting tones and music selection based on the passenger's emotional state, as received from a server. Specifically, if the passenger is relaxed, the lighting will change to warm tones and soothing music will be played. This automatic adjustment optimizes the environment to the passenger's emotional state.

[0821] Step 5:

[0822] The user experiences the adjusted in-car environment. User feedback and changes in physiological data are newly collected and sent to the server. This allows the system to continuously optimize the environment while striving to maintain passenger comfort.

[0823] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0824] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0825] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0826] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0827] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0828] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0829] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0830] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0831] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0832] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0833] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0834] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0835] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0836] 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.

[0837] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0838] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0839] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0840] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0841] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0842] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0843] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0844] The following is further disclosed regarding the embodiments described above.

[0845] (Claim 1)

[0846] Information processing means for collecting guest information and providing personalized accommodation experiences based on that information,

[0847] A profile generation means for analyzing collected information and generating guest profiles,

[0848] A display generation means for customizing the video and interface of the accommodation facility using the aforementioned profile,

[0849] Environmental control means for detecting the physiological data and emotional state of guests and adjusting lighting and sound accordingly,

[0850] A system including language processing and response means for providing multilingual information services.

[0851] (Claim 2)

[0852] The system according to claim 1, further comprising a menu creation means for generating a personalized menu based on the guest's food preferences and local ingredient information.

[0853] (Claim 3)

[0854] The system according to claim 1, further comprising means for generating a guide plan for adjusting tourist information based on the composition information of the guests.

[0855] "Example 1"

[0856] (Claim 1)

[0857] A data processing means for collecting guest information and providing personalized accommodation experiences based on that information,

[0858] Information generation means for analyzing collected information and generating guest profiles,

[0859] A means for creating displays to customize the display and operation screens of accommodations using the aforementioned profile,

[0860] Environmental adjustment means for detecting the physiological data and emotional state of guests and adjusting lighting and sound accordingly,

[0861] Language processing and response provision means for providing multilingual information services,

[0862] Content generation means for providing customized content using the aforementioned profile and generation AI model,

[0863] A means including sensors and control systems for adjusting the guest environment in real time,

[0864] A system that includes this.

[0865] (Claim 2)

[0866] The system according to claim 1, further comprising a means for creating meals to generate an individualized meal plan based on the guest's food preferences and local ingredient information.

[0867] (Claim 3)

[0868] The system according to claim 1, further comprising means for creating a plan to adjust tourist information based on the attribute information of the guests.

[0869] "Application Example 1"

[0870] (Claim 1)

[0871] Information processing means for collecting guest information and providing personalized accommodation experiences based on that information,

[0872] A profile generation means for analyzing collected information and generating guest profiles,

[0873] A display generation means for customizing the video and interface of the accommodation facility using the aforementioned profile,

[0874] Environmental control means for detecting the physiological data and emotional state of guests and adjusting lighting and sound accordingly,

[0875] Language processing and response means for providing multilingual information services,

[0876] An information display method for presenting relevant product information in real time based on the customer's purchase history and preferences in a store,

[0877] A means of generating promotions to provide recommended products tailored to customer profiles within a store,

[0878] A system that includes this.

[0879] (Claim 2)

[0880] The system according to claim 1, further comprising a menu creation means for generating a personalized menu based on the guest's food preferences and local ingredient information.

[0881] (Claim 3)

[0882] The system according to claim 1, further comprising means for generating a guide plan for adjusting tourist information based on the composition information of the guests.

[0883] "Example 2 of combining an emotion engine"

[0884] (Claim 1)

[0885] Information processing means for collecting guest information and providing personalized accommodation experiences based on that information and past usage history,

[0886] A profile generation means for analyzing collected information and generating detailed profiles of guests,

[0887] Environmental adjustment means for customizing the lighting and sound environment of the accommodation using the aforementioned profile and acquired guest emotional state data,

[0888] A means for generating personalized content in real time, based on information obtained from sentiment analysis,

[0889] A system including language processing and response means for providing multilingual information tailored to the emotional state of guests in response to their inquiries.

[0890] (Claim 2)

[0891] The system according to claim 1, further comprising means for providing food to generate a personalized menu based on the food preferences of guests and the characteristics of the region.

[0892] (Claim 3)

[0893] The system according to claim 1, further comprising means for generating a guide plan for dynamically adjusting tourist information based on the emotional state and configuration information of guests.

[0894] "Application example 2 when combining with an emotional engine"

[0895] (Claim 1)

[0896] Information processing means for collecting guest information and providing personalized accommodation experiences based on that information,

[0897] A profile generation means for analyzing collected information and generating guest profiles,

[0898] A display generation means for customizing the video and interface of the accommodation facility using the aforementioned profile,

[0899] Environmental control means for detecting the physiological data and emotional state of guests and adjusting lighting and sound accordingly,

[0900] A means of emotional response for acquiring physiological data of passengers in a means of transportation and adjusting the in-vehicle environment based on emotional analysis,

[0901] A system including language processing and response means for providing multilingual information services.

[0902] (Claim 2)

[0903] The system according to claim 1, further comprising a menu creation means for generating a personalized menu based on the guest's food preferences and local ingredient information.

[0904] (Claim 3)

[0905] The system according to claim 1, further comprising means for generating a guide plan for adjusting tourist information based on the composition information of the guests. [Explanation of Symbols]

[0906] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Information processing means for collecting guest information and providing personalized accommodation experiences based on that information, A profile generation means for analyzing collected information and generating guest profiles, A display generation means for customizing the video and interface of the accommodation facility using the aforementioned profile, Environmental control means for detecting the physiological data and emotional state of guests and adjusting lighting and sound accordingly, A system including language processing and response means for providing multilingual information services.

2. The system according to claim 1, further comprising a menu creation means for generating a personalized menu based on the guest's food preferences and local ingredient information.

3. The system according to claim 1, further comprising means for generating a guide plan for adjusting tourist information based on the composition information of the guests.

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