System

Abstract

A system is provided.SOLUTION: A system comprising: means for acquiring location information of users; means for collecting private information such as hobbies, interests, and ages of the users; means for requesting a generation AI model to generate guide information based on the location information and the private information; means for transmitting the guide information generated by the generation AI model to terminals; and means for presenting the guide information received by the terminals to the users.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In facilities such as art galleries, museums, and historical buildings, it is difficult to understand the value and background of the exhibits without sufficient knowledge. Furthermore, on-site guides and explanations are subject to time constraints and language barriers, making it difficult to provide sufficient information for all visitors. Therefore, there is a need for a method to provide customized guides tailored to the interests and backgrounds of individual visitors and help them understand the exhibits. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including a means for acquiring user location information, a means for collecting personal information such as the user's hobbies, interests, and age, a means for requesting a generation AI model to generate guide information based on the location information and personal information, a means for transmitting the guide information generated by the generation AI model to a terminal, and a means for presenting the guide information received by the terminal to the user.In addition, by including a means for providing guide information in text or audio format and a means for receiving user feedback and requests for additional information and generating further guide information based thereon, it is possible to provide information optimized for each individual user and improve the viewing experience.

[0006] "User" means an individual or group that uses the system to receive guide information within the facility.

[0007] "Location Information" means information about a user's current location determined by GPS or other means.

[0008] "Personal information" refers to information such as a user's hobbies, interests, age, and profile.

[0009] A "generative AI model" is an artificial intelligence system that generates guide information based on acquired information.

[0010] "Guide information" refers to knowledge and explanations provided to users, such as background information and anecdotes about exhibits and buildings within the facility.

[0011] A "terminal" is an electronic device used by a user to access the system, such as a smartphone, tablet, or dedicated device.

[0012] A "means" is a method or apparatus for realizing a particular function within a system.

[0013] "Feedback" is any opinion or request for additional information that a user provides to the system. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] The system of the present invention provides customized guide information to users at facilities such as art galleries, museums, historical buildings, etc. This system is mainly composed of the following components: a means for acquiring the user's location information, a means for collecting personal information such as the user's hobbies, interests, and age, a means for requesting the generation of guide information from a generative AI model, a means for transmitting the generated guide information to a terminal, and a means for presenting the guide information received by the terminal to the user.

[0036] When a visitor enters an art gallery or museum, they launch an application using a smartphone or dedicated device. The user first enters personal information within the application. For example, the user provides information that they are interested in art and particularly like impressionist paintings. This information is then sent to the server by the device.

[0037] The device then uses its GPS to determine the user's current location (for example, if the user is in an area of ​​the museum where impressionist paintings are displayed), and this location information is also sent to the server.

[0038] The server requests the generative AI model to generate guide information based on the received personal information and location information. For example, a query such as "A user who is interested in art and likes impressionist paintings is in the current exhibition area. Please generate a relevant explanation." The generative AI model generates relevant guide information based on this query. For example, information about the main characteristics of impressionism, Monet's techniques and background, and other related artists is generated.

[0039] The generated guide information is sent from the server to the device. The device displays the received guide information and plays it back as audio if necessary. For example, a detailed description of an impressionist painting may be displayed on the user's smartphone while an audio guide is played back at the same time.

[0040] Additionally, users can use the application to provide feedback or request additional information. For example, if they want to know more about other works by Monet, they can enter additional questions. This information is sent back to the server, and the generative AI model generates new guide information and sends it to the device, which then presents this information to the user again.

[0041] In this way, the system of the present invention provides guide information in real time that is tailored to the individual interests and background of each user, thereby improving the viewing experience within the facility.

[0042] The processing flow will be explained below.

[0043] Step 1:

[0044] The user launches a dedicated application on their smartphone or device. First, the user sets up their profile within the application and enters personal information such as hobbies, interests, and age. For example, the user may provide information such as "I'm interested in art" or "I like impressionism."

[0045] Step 2:

[0046] The device uses GPS to acquire the user's current location, which is then sent to a server. For example, the server may detect that the user is in an area displaying impressionist paintings.

[0047] Step 3:

[0048] The device sends the user's personal information (such as hobbies, interests, and age) and the acquired location information to the server. The server receives this information.

[0049] Step 4:

[0050] Based on the personal information and location information received by the server, a query is generated to the generative AI model requesting the generation of guide information. For example, a query such as "A user who is interested in art and likes impressionism is currently in the current exhibition area. Please generate a relevant explanation."

[0051] Step 5:

[0052] The generative AI model generates guide information based on queries from the server. Specifically, it generates information about the history and characteristics of Impressionism, as well as famous works and artists. For example, it includes an explanation that "Monet's works are characterized by their use of light and color."

[0053] Step 6:

[0054] The server receives the generated guide information and transmits it to the terminal, which receives the guide information.

[0055] Step 7:

[0056] The device displays the guide information it receives and plays it back as audio if necessary. For example, a detailed description of a Monet work could be displayed on the smartphone screen while an audio guide is played at the same time.

[0057] Step 8:

[0058] Users can view the exhibits based on the guided information. If they have further questions or would like more information, they can provide feedback or request additional information through the application. For example, they can enter a request such as, "I'd like to know more about Monet's other famous works."

[0059] Step 9:

[0060] The device sends the user's feedback and request information to the server, which then requests the AI ​​model to generate additional guide information.

[0061] Step 10:

[0062] The generative AI model generates new information, which the server sends to the device, which then presents the new guide information to the user.

[0063] Through the above series of steps, this system can provide customized guide information tailored to each user's individual interests and needs in real time.

[0064] Example 1

[0065] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0066] Conventional facility guide systems could only provide general information to users, making it difficult to provide customized guide information tailored to individual interests in real time. Furthermore, they lacked a mechanism for automatically acquiring location information as users move around the facility and providing detailed guidance based on that information. Furthermore, they lacked the ability to flexibly respond to user feedback and requests for additional information and provide further customized information.

[0067] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0068] In this invention, the server includes means for acquiring user location information, means for collecting personal information such as the user's hobbies, interests, and age, means for generating a prompt sentence for requesting the generation of guide information from the generative AI model based on the location information and personal information, means for sending the generated prompt sentence to the generative AI model, means for sending the guide information generated by the generative AI model to a terminal, means for presenting the guide information received by the terminal to the user, means for collecting user feedback and requests for additional information, and means for again requesting the generation of guide information from the generative AI model based on the feedback and requests for additional information. This makes it possible to provide users with guide information customized to their individual interests in real time, and to provide information tailored to their movement within a facility and respond to requests for additional information.

[0069] "Location information" refers to data used to identify a user's current location.

[0070] "Personal Information" refers to information about a user's hobbies, interests, age, and other personal attributes.

[0071] A "generative AI model" refers to an artificial intelligence system that generates new information based on input data.

[0072] A "prompt sentence" refers to an input sentence that gives specific instructions to a generative AI model.

[0073] "Guide information" refers to information about explanations and commentary created by a generative AI model to be provided to users.

[0074] "Terminal" refers to a device that can be operated by a user (e.g., smartphone, tablet, dedicated device).

[0075] "Feedback" refers to the opinions and impressions that users provide to the system.

[0076] "Requesting additional information" refers to the user's request for more information from the system.

[0077] The system of the present invention provides customized guide information to users at facilities such as art galleries, museums, historical buildings, etc. This system mainly includes means for acquiring location information and personal information of the user and requesting the generation of guide information from a generative AI model based on the information.

[0078] When a user enters a facility, they launch the application using a smartphone or dedicated terminal. The user first enters personal information within the application. For example, the user provides information that they are interested in art and particularly like impressionist paintings. This information is then sent to the server by the terminal.

[0079] The device then uses its GPS to determine the user's current location (for example, if the user is in an area of ​​the museum where impressionist paintings are displayed), and this location information is also sent to the server.

[0080] The server requests the generative AI model to generate guide information based on the received personal information and location information. An example of a prompt sentence to use in this case is, "A user who is interested in art and likes impressionist paintings is in the current exhibition area. Please generate a relevant explanation." The generative AI model generates the appropriate guide information based on this prompt sentence. For example, it generates information about the main characteristics of impressionism, famous artists, techniques, and background.

[0081] The generated guide information is sent from the server to the device. The device displays the received guide information and plays it back as audio if necessary. For example, a detailed description of an impressionist painting may be displayed on the user's smartphone while an audio guide is played back at the same time.

[0082] Additionally, users can use the application to provide feedback or request additional information. For example, if they want to know more about other works by Monet, they can enter additional questions. This information is sent back to the server, and the generative AI model generates new guide information and sends it to the device. The device then presents this information to the user again.

[0083] In this way, the system of the present invention provides real-time guide information tailored to individual interests and backgrounds, improving the viewing experience within the facility. Specific hardware used includes smartphones and tablets with GPS functionality. Furthermore, it is desirable to use the latest AI algorithms based on natural language processing technology as the generative AI model.

[0084] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0085] Step 1:

[0086] A user enters a facility and launches an application.

[0087] Input: An application is started by a user action.

[0088] Output: None.

[0089] How it works: The user launches the facility application on their smartphone or dedicated device.

[0090] Step 2:

[0091] The user enters personal information within the application.

[0092] Input: Users enter personal information such as their interests, preferences, and age.

[0093] Output: The entered personal information is stored in the device's memory.

[0094] Action: For example, a user types, "I like impressionist paintings."

[0095] Step 3:

[0096] The device uses its GPS function to obtain the user's current location and transmits it to the server.

[0097] Input: Location information obtained by the device's GPS function.

[0098] Output: The location information is sent to the server.

[0099] Operation: For example, if the user is in the impressionist painting exhibition area, their location information is identified.

[0100] Step 4:

[0101] The device sends personal information to the server.

[0102] Input: Personal information entered by the user.

[0103] Output: Personal information is sent to the server.

[0104] How it works: For example, information such as "I'm interested in impressionist paintings" is sent to the server.

[0105] Step 5:

[0106] The server generates a prompt sentence to request the generative AI model to generate guide information based on location information and personal information.

[0107] Input: Location and personal information.

[0108] Output: The generated prompt statement.

[0109] Action: The server generates a prompt saying, "There is a user in the current exhibition area who is interested in art and likes impressionist paintings, so please generate a relevant description."

[0110] Step 6:

[0111] The server sends the generated prompt to the generative AI model.

[0112] Input: The generated prompt statement.

[0113] Output: The generated prompt sentence is sent to the generative AI model.

[0114] How it works: The server sends the generated prompt sentence to the generative AI model.

[0115] Step 7:

[0116] The generative AI model generates guide information and sends it to the server.

[0117] Input: The generated prompt statement.

[0118] Output: The generated guide information.

[0119] How it works: A generative AI model generates guide information about key features of impressionism, Monet's techniques, and more.

[0120] Step 8:

[0121] The server transmits the generated guide information to the terminal.

[0122] Input: Generated guide information.

[0123] Output: Guide information is sent to the terminal.

[0124] Operation: The server sends the generated guide information to the terminal.

[0125] Step 9:

[0126] The terminal displays the received guide information to the user and plays it back as audio if necessary.

[0127] Input: Guide information sent from the server.

[0128] Output: Guidance information displayed to the user and audio playback.

[0129] Operation: Guide information will be displayed on the user's smartphone and audio playback will begin.

[0130] Step 10:

[0131] The user enters feedback or a request for more information.

[0132] Input: User feedback or requests for additional information.

[0133] Output: Feedback and requests are stored in the device's memory.

[0134] Action: For example, a user types, "I'd like to know about other works by Monet."

[0135] Step 11:

[0136] The device sends a request for feedback or additional information to the server.

[0137] Input: User feedback or requests for additional information.

[0138] Output: Feedback or requests are sent to the server.

[0139] Operation: The device sends the user's request to the server.

[0140] Step 12:

[0141] Based on the feedback and requests for additional information received by the server, the generative AI model is again requested to generate guide information.

[0142] Input: User feedback or requests for additional information.

[0143] Output: The new prompt sent to the generative AI model.

[0144] What happens: The server again sends a request to the generative AI model.

[0145] Step 13:

[0146] The generative AI model generates new guide information and sends it to the server.

[0147] Input: New prompt text.

[0148] Output: The newly generated guide information.

[0149] How it works: A generative AI model generates guide information based on new user requests.

[0150] Step 14:

[0151] The server transmits the newly generated guide information to the terminal.

[0152] Input: The newly generated guide information.

[0153] Output: New guide information is sent to the terminal.

[0154] Operation: The server sends new guide information to the terminal.

[0155] Step 15:

[0156] The terminal displays the new guide information to the user and plays it aloud if necessary.

[0157] Input: New guide information.

[0158] Output: New guide information displayed to the user, and audio playback.

[0159] Operation: New guide information will be displayed on the user's smartphone, and audio playback will begin.

[0160] (Application example 1)

[0161] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0162] In industrial facilities, it is important for workers to work efficiently by providing appropriate work instructions in real time that are tailored to their individual skills and experience. However, current systems have difficulty providing customized work instructions based on the worker's current location and personal information, making it difficult to improve work efficiency. There is also a need for systems to receive feedback from workers and generate further work instructions appropriately.

[0163] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0164] In this invention, the server includes a means for acquiring location information of workers within an industrial facility, a means for collecting personal information such as the worker's skill level, experience, and work history, a means for sending a request to generate work instructions to a generative AI model based on the location information and personal information, a means for sending the work instructions generated by the generative AI model to a display device, and a means for presenting the work instructions received by the display device to the worker. This makes it possible to provide customized work instructions to workers in real time, thereby improving work efficiency.

[0165] The "location information acquisition means" is a means for acquiring the current location of a worker within an industrial facility.

[0166] "Means for collecting personal information" refers to means for collecting personal information such as the worker's technical level, experience, and work history.

[0167] The "generation request sending means" is a means for sending a request to generate work instructions to the generation AI model based on location information and personal information.

[0168] The "work instruction generation means" is a means for transmitting the work instructions generated by the generation AI model to the display device.

[0169] The "work instruction presenting means" is a means for presenting the work instructions received by the display device to the worker.

[0170] The "feedback receiving means" is a means for receiving feedback from the worker and requests for additional work information.

[0171] The "additional work instruction generation means" is a means for generating further work instructions based on feedback or requests for additional information.

[0172] This invention relates to a system that provides individual work instructions to workers in industrial facilities in real time. The system acquires the location information and personal information of the workers, generates optimal work instructions using a generative AI model, and presents them to the workers via a display device.

[0173] First, a GPS module is used to acquire the location information of the worker. The GPS module is used to identify the current location of the worker within the industrial facility. Next, a personal information collection means is used to send personal information such as the worker's skill level, experience, and work history to the server.

[0174] The server requests the generative AI model to generate work instructions based on the received location information and personal information. The generative AI model used in this process is stored on the cloud. The server also has the function of sending the generated work instructions to a display device. The display device could be, for example, smart glasses or a tablet terminal.

[0175] Not only can workers view work instructions through the display device, but they can also provide feedback or request additional information. These requests are sent back to the server, and the generative AI model responds by generating further work instructions and sending them to the display device. This two-way information exchange allows workers to work efficiently.

[0176] As a concrete example, suppose a worker moves to a new assembly area. The GPS module detects the worker's location and sends this location information to the server. At the same time, the worker's skill level and past assembly work experience are sent to the server via the personal information collection means. Based on this data, the server sends the following prompt to the generative AI model:

[0177] "The user's name is Yamada Taro and he has advanced experience. He is currently in the precision assembly area. Please generate the most suitable work instructions for this user."

[0178] Based on these prompts, the generative AI model generates work instructions, including optimal work procedures and precautions for precision assembly, and sends them to the server. The server then sends the received work instructions to a display device so that the worker can check them in real time. The worker can proceed with the work while checking the detailed procedures and safety precautions on the display device.

[0179] Furthermore, if a worker needs additional information, they can input a request via the display device. This request is sent to the server, and the generative AI model generates new information and sends it back to the display device. Through this process, the worker can obtain the necessary information in a timely manner and work efficiently.

[0180] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0181] Step 1:

[0182] The GPS module is used to obtain the current location of the worker. The input is the location data from the GPS module, and the output is the current coordinate information. The server receives this coordinate information.

[0183] Step 2:

[0184] Using a personal information collection means, personal information such as the worker's skill level, experience, and work history is collected. The input is the worker's profile data, and the output is a set of this personal information. The server receives this personal information.

[0185] Step 3:

[0186] Based on the location information and personal information received by the server, it sends a request to the generative AI model to generate work instructions. The input is a set of location information and personal information, and the output is a prompt sentence to be sent to the generative AI model. An example of a specific prompt sentence is, "The user's name is Mr. A, and he has advanced experience. He is currently in the precision assembly area. Please generate the most suitable work instructions for this user."

[0187] Step 4:

[0188] The generative AI model generates work instructions based on the received prompt. The input is the prompt, and the output is customized work instructions. The generated work instructions are sent to the server.

[0189] Step 5:

[0190] The server sends the work instructions received from the generative AI model to the display device. The input is the generated work instructions, and the output is the data sent to the display device.

[0191] Step 6:

[0192] The display device presents the received work instructions to the worker. The input is the work instructions sent from the server, and the output is the work instruction information displayed on the display device. For example, the instructions are displayed in text format on the screen of smart glasses or a tablet device, and are also played back as audio.

[0193] Step 7:

[0194] The worker inputs additional information and feedback through the display device. The input is the requested information from the worker, and the output is the data to be sent to the server. For example, a request such as "I would like to know more details about the current procedure" is input into the display device.

[0195] Step 8:

[0196] The server receives requests for additional information from the worker and sends the requests to the generative AI model. The input is the request for additional information, and the output is a new prompt sentence that is sent to the generative AI model.

[0197] Step 9:

[0198] The generative AI model generates more detailed work instructions based on the new prompt. The input is the new prompt, and the output is the new work instructions. The generated work instructions are sent to the server again.

[0199] Step 10:

[0200] The server retransmits the new work instructions received from the generative AI model to the display device. The input is the new work instructions, and the output is the data sent to the display device.

[0201] Step 11:

[0202] The display device then presents the new work instructions received to the worker. The input is the new work instructions sent from the server, and the output is the additional work instruction information displayed on the display device. This allows the worker to obtain the necessary additional information in real time and work efficiently.

[0203] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0204] The system of the present invention provides customized guide information to users at facilities such as art galleries, museums, and historical buildings, and also combines an emotion engine. The system is composed of the following components: a means for acquiring the user's location information, a means for collecting personal information such as the user's hobbies, interests, and age, a means for requesting the generation of guide information from a generative AI model, a means for sending the guide information generated by the generative AI model to a terminal, a means for presenting the guide information received by the terminal to the user, and an emotion engine that recognizes the user's emotions.

[0205] When a user enters a facility, they launch the application using a smartphone or dedicated terminal. First, the user sets up a profile within the application and enters personal information such as hobbies, interests, and age. For example, the user may provide information such as "I'm interested in art, and I particularly like impressionist paintings." This information is then sent to the server by the terminal.

[0206] The device then uses its GPS to determine the user's current location, which is also sent to the server. For example, the device may determine that the user is in the Impressionist paintings exhibit area of ​​a museum.

[0207] The server generates a query to the generative AI model based on the received personal information and location information, requesting the model to generate guide information. For example, the server generates a query such as, "A user who is interested in art and likes impressionist paintings is currently in the exhibition area. Please generate a relevant explanation." The generative AI model generates relevant guide information based on this query. For example, it generates information about the history and characteristics of impressionism, as well as famous works and artists.

[0208] The generated guide information is sent from the server to the device. The device displays the received guide information and plays it back as audio if necessary. For example, a detailed description of Monet's work may be displayed on the user's smartphone while an audio guide is played back at the same time.

[0209] Furthermore, the system includes an emotion engine that recognizes the user's emotions. The emotion engine recognizes emotions by analyzing the user's facial expressions and tone of voice. For example, when a user is viewing a Monet painting, if the emotion engine recognizes that the user is moved by the painting, this emotion data is sent to the server.

[0210] The server requests the generative AI model to customize the guide information based on the received emotional data. For example, if the user is moved, the server can request the generative AI model to provide a deeper artistic background or anecdotes that will amplify the emotion. The generative AI model generates more detailed information, which the server sends to the device. The device then presents the new guide information to the user.

[0211] Users can also use the application to provide feedback or request additional information, for example, by entering a request such as "I want to know more about other famous works by Monet." This information is then sent back to the server, where the generative AI model generates new guide information and sends it back to the device, which then presents this information to the user.

[0212] In this way, the system of the present invention can provide customized guide information in real time according to the user's individual interests and background, and can also use an emotion engine to provide detailed services based on the user's emotions.

[0213] The processing flow will be explained below.

[0214] Step 1:

[0215] The user launches a dedicated application on their smartphone or device. First, the user sets up their profile within the application and enters personal information such as hobbies, interests, and age. For example, the user may provide information such as "I'm interested in art" or "I like impressionism."

[0216] Step 2:

[0217] The device uses GPS to acquire the user's current location, which is then sent to a server. For example, the server may detect that the user is in an area displaying impressionist paintings.

[0218] Step 3:

[0219] The device sends the user's personal information (such as hobbies, interests, and age) and the acquired location information to the server. The server receives this information.

[0220] Step 4:

[0221] Based on the personal information and location information received by the server, a query is generated to the generative AI model requesting the generation of guide information. For example, a query such as "A user who is interested in art and likes impressionism is currently in the current exhibition area. Please generate a relevant explanation."

[0222] Step 5:

[0223] The generative AI model generates guide information based on queries from the server. Specifically, it generates information about the history and characteristics of Impressionism, as well as famous works and artists. For example, it includes an explanation that "Monet's works are characterized by their use of light and color."

[0224] Step 6:

[0225] The server receives the generated guide information and transmits it to the terminal, which receives the guide information.

[0226] Step 7:

[0227] The device displays the guide information it receives and plays it back as audio if necessary. For example, a detailed description of a Monet work could be displayed on the smartphone screen while an audio guide is played at the same time.

[0228] Step 8:

[0229] The user views the exhibits based on the guided information. If the user has further questions or wants more information, they can provide feedback or request additional information through the application. For example, they can enter a request such as, "I'd like to know more about Monet's other famous works."

[0230] Step 9:

[0231] The device sends the user's feedback and request information to the server, which then requests the AI ​​model to generate additional guide information.

[0232] Step 10:

[0233] The generative AI model generates new information, which the server sends to the device, which then presents the new guide information to the user.

[0234] Step 11:

[0235] The device's emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotions. For example, the device uses a camera and microphone to collect the user's reactions while viewing artwork.

[0236] Step 12:

[0237] The emotion engine recognizes the user's emotions and sends that information to the server. For example, it recognizes that the user is moved by a painting by Monet.

[0238] Step 13:

[0239] The server receives the emotion data and requests the generative AI model to customize the guide information based on that data. For example, the server requests the generative AI model to provide an episode that will further amplify the emotion of the user, since the user is moved by the emotion.

[0240] Step 14:

[0241] The generative AI model generates customized guide information, which the server sends to the device. The device then presents the new customized guide information to the user. For example, it provides touching episodes or background information on related works.

[0242] As described above, this system provides customized guide information in real time based on the user's individual interests and background, and further enriches the viewing experience by using an emotion engine to provide services based on the user's emotions.

[0243] Example 2

[0244] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0245] Conventional guide systems provide information based on the user's location and interests, but this is not sufficient to provide a personalized experience. Furthermore, they are unable to provide guide information that takes into account the user's emotions, making it difficult to increase satisfaction. Therefore, there is a demand for a system that can provide customized guide information in real time that is tailored to the user's individual interests and emotions.

[0246] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring location information of a user, means for collecting personal information such as the user's hobbies, interests, and age, means for requesting the generation of guide information from a generation AI model based on the location information and the personal information, means for transmitting the guide information generated by the generation AI model to a terminal, means for presenting the guide information received by the terminal to the user, means for recognizing the user's emotions, and means for customizing the guide information based on the emotion data. This makes it possible to provide customized guide information in real time that is tailored to the user's individual interests and emotions.

[0247] "User" refers to any individual or entity that uses the System.

[0248] "Location Information" means physical location data determined using GPS or other methods.

[0249] "Personal information" refers to information related to a specific individual, such as a user's hobbies, interests, age, etc.

[0250] "Generative AI model" refers to an artificial intelligence model that generates guide information and other data.

[0251] "Guide information" refers to explanations and information provided by a generative AI model based on the user's interests and location.

[0252] "Terminal" refers to a device used by a user, such as a smartphone or tablet.

[0253] "Emotional data" refers to data on a user's emotional state obtained by analyzing their facial expressions and tone of voice.

[0254] An "emotion engine" refers to a system that analyzes users' emotions and recognizes them as data.

[0255] The system of this invention provides customized guide information to users in facilities such as art galleries, museums, and historical buildings, and also combines an emotion engine. The system is mainly composed of three main components: a server, a terminal, and a user.

[0256] Hardware and software used

[0257] Devices: Smartphones, dedicated tablet devices

[0258] Server: Cloud server such as AWS (registered trademark) or Google (registered trademark) Cloud Platform

[0259] GPS function: Built-in to smartphones and tablets

[0260] Generative AI models: OpenAI (registered trademark) GPT-4 (registered trademark), Google BERT, etc.

[0261] Emotion engine: Affectiva SDK, Microsoft® Azure® Face API, etc.

[0262] Processing flow and specific examples

[0263] 1. User profile settings

[0264] Users enter the facility and launch the application on their smartphone or dedicated device. Within the application, they enter profile information such as their name, age, hobbies and interests. For example, they might enter information like, "I'm interested in art, and I particularly like impressionist paintings." This information is stored on the device and later sent to the server.

[0265] 2. Obtaining location information

[0266] The device uses its built-in GPS to determine its current location, which is then sent in encrypted form to a server, identifying, for example, the user as being in the impressionist paintings section of a museum.

[0267] 3. Guide information generation request

[0268] The server generates a query to request the generation of guide information from the generative AI model based on the user's profile information and location information. An example of a prompt sentence is "A user who is interested in art and likes impressionist paintings is in the current exhibition area, so please generate a relevant description."

[0269] 4. Guide information generation and transmission

[0270] The generative AI model receives and analyzes the prompt text and generates relevant guide information. For example, it generates information about the history and characteristics of Impressionism, as well as famous works and artists. This generated guide information is sent to the device via the server.

[0271] 5. Present guide information

[0272] The device displays the received guide information on its screen and plays it audibly as needed. For example, a detailed description of a Monet work may be displayed on the user's smartphone, and an audio guide may be played.

[0273] 6. Emotional Recognition

[0274] Using the device's camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice. The analysis results are sent to the server as emotion data. For example, it can recognize when a user is moved by a painting by Monet.

[0275] 7. Customizing guide information

[0276] Based on the emotion data, the server requests the generative AI model to generate new, more detailed guide information. For example, if a user is moved by something, it generates a request to add more in-depth artistic background or anecdotes. The newly generated information is then sent back to the device via the server and provided to the user.

[0277] 8. Feedback and Requests for Additional Information

[0278] Within the application, users can request feedback or additional information, for example, "I want to know more about other famous works by Monet." This request is sent to the server, where the generative AI model generates new guide information and sends it to the device, providing further information to the user.

[0279] As described above, the system of the present invention is capable of providing customized guide information in real time that is tailored to the individual interests and emotions of users, thereby increasing user satisfaction.

[0280] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0281] Step 1:

[0282] The user launches the application and enters their profile information.

[0283] Input: A user launches an application and enters profile information such as name, age, hobbies and interests.

[0284] How it works: The device stores the information the user enters within the application in a local database.

[0285] Output: User profile information is saved on the device.

[0286] Step 2:

[0287] The device acquires location information and sends it to the server.

[0288] Input: The device uses the GPS function to obtain the current location information.

[0289] Operation: The device encrypts the acquired location information and sends it to the server.

[0290] Output: Encrypted location information is sent to the server.

[0291] Step 3:

[0292] The server generates a request for generating guide information.

[0293] Input: The server receives the user's profile information and location information.

[0294] How it works: The server generates a prompt sentence to send to the generative AI model based on the received data. An example of a prompt sentence is, "A user who is interested in art and likes impressionist paintings is currently in the exhibition area, so please generate a relevant description."

[0295] Output: A prompt sentence is generated that is sent to the generative AI model.

[0296] Step 4:

[0297] A generative AI model generates guide information.

[0298] Input: A prompt sentence is sent to the generative AI model.

[0299] How it works: The generative AI model analyzes the prompt and generates relevant guide information, such as information about the history and characteristics of Impressionism, as well as famous works and artists.

[0300] Output: The generated guide information is returned to the server.

[0301] Step 5:

[0302] The server transmits the generated guide information to the terminal.

[0303] Input: The server receives guidance information from the generative AI model.

[0304] Operation: The server encrypts the guide information it receives and sends it to the user's terminal.

[0305] Output: Encrypted guide information is sent to the terminal.

[0306] Step 6:

[0307] The device displays or plays audible guide information.

[0308] Input: The device receives encrypted guide information from the server.

[0309] How it works: The device decrypts the encrypted information and displays it on the screen or plays it as an audio guide. For example, a detailed description of a Monet painting may be displayed on the user's smartphone, and an audio guide may be played.

[0310] Output: The guide information is displayed on the user's device and played back aloud.

[0311] Step 7:

[0312] The emotion engine recognizes the user's emotions.

[0313] Input: Capture the user's facial expressions and tone of voice using the device's camera and microphone.

[0314] How it works: The emotion engine analyzes the facial expressions and tone of voice it acquires to generate emotion data. This emotion data is sent to the server. For example, it recognizes when a user is moved by a painting by Monet.

[0315] Output: Emotion data is sent to the server.

[0316] Step 8:

[0317] The server customizes the guide information based on the emotion data.

[0318] Input: The server generates a new prompt sentence based on the emotion data received.

[0319] How it works: A new prompt is sent to the generative AI model, requesting it to generate more detailed guide information. For example, if a user is moved by something, a request is generated to add more in-depth artistic background or anecdotes. The newly generated information is then sent back to the device via the server.

[0320] Output: The customized guide information is sent to the device.

[0321] Step 9:

[0322] The user requests feedback or additional information.

[0323] Input: A user types feedback or a request for more information within an application. For example, "I want to know more about Monet's other famous works."

[0324] Operation: Request information is sent to the server, and the generative AI model generates new guide information and sends it to the device via the server.

[0325] Output: The new guide information is displayed on the user's device.

[0326] (Application example 2)

[0327] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0328] Conventional shopping guide systems have had difficulty providing customized information based on a user's location information or individual hobbies and interests. They also have difficulty recognizing a user's emotions and providing appropriate information accordingly. As a result, they have been unable to provide a satisfying shopping experience for users. The present invention aims to solve these problems and provide a personalized shopping guide for users.

[0329] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user location information, means for collecting personal information such as the user's hobbies, interests, and age, means for requesting the generation of guide information from the generative AI model based on the location information and personal information, means for transmitting the guide information generated by the generative AI model to the terminal, means for presenting the guide information received by the terminal to the user, means for recognizing emotions by analyzing the user's facial expressions and tone of voice, and means for requesting the generation of guide information from the generative AI model based on the emotion data. This makes it possible to provide a highly personalized shopping guide based on the user's individual hobbies, interests, location information, and emotions.

[0330] "User location information" is data that indicates the user's current geographical location.

[0331] "Hobbies and interests" is information related to activities or areas in which a user has a particular interest.

[0332] "Age" is data indicating the length of time calculated based on the user's date of birth.

[0333] "Personal information" refers to detailed data related to a user, such as hobbies, interests, age, etc.

[0334] A "generative AI model" is an artificial intelligence model that generates customized information based on input data.

[0335] "Guide information" is data output by the generative AI model that provides useful guidance and explanations to users.

[0336] "Terminal" refers to a computing device carried by a user, such as a smartphone or smart glasses.

[0337] "Facial expressions and tone of voice" refers to the user's facial expressions and speech patterns, and are data that provide clues to emotions.

[0338] "Emotion data" is data based on facial expressions and tone of voice that is analyzed to recognize the user's emotions.

[0339] "Customized" means that something is specifically tailored or modified to suit a particular user.

[0340] This invention builds a system that provides customized shopping guide information to users in physical stores such as shopping malls. The system acquires the user's location information, collects personal information such as hobbies, interests, and age, generates customized guide information using a generative AI model, and transmits it to the terminal. Another feature of the system is that it analyzes the user's facial expressions and tone of voice to recognize emotions and provides more appropriate guide information based on that emotional data.

[0341] Hardware and software configuration

[0342] Hardware

[0343] 1. Device: A device carried by a user, such as a smartphone or smart glasses.

[0344] 2. Server: A remote server that generates guide information and processes data.

[0345] software

[0346] 1. Location information acquisition software: Software that uses GPS functionality to determine the user's current location.

[0347] 2. Personal Information Collection Software: Software that allows users to set up a profile within an application and enter personal information such as hobbies, interests, age, etc.

[0348] 3. Generative AI model: An artificial intelligence model that generates customized guide information based on the user's location information and personal information.

[0349] 4. Emotion recognition software: Software that recognizes emotions by analyzing the user's facial expressions and tone of voice.

[0350] Data Flow and Processing

[0351] 1. Location information acquisition:

[0352] The server obtains location information from the user's device, which is precisely determined using GPS functionality.

[0353] 2. Collection of Personal Information:

[0354] The server collects personal information such as hobbies, interests, and age that users enter within the application.

[0355] 3. Guide information generation:

[0356] The server requests the generative AI model to generate guide information based on the collected location information and personal information, and creates a prompt sentence and passes it to the generative AI model.

[0357] example:

[0358] "The user is interested in the latest fashion and is currently located near 35.658581,139.745433 in the shopping mall. Please generate relevant guide information."

[0359] 4. Sending and Presenting Guide Information:

[0360] The server sends the guide information generated by the generative AI model to the device, which then displays the received guide information to the user and plays it back in audio format.

[0361] 5. Emotion Recognition and Customization:

[0362] The device analyzes the user's facial expressions and tone of voice to generate emotional data, which is then sent to the server, which then requests the AI ​​model to customize the guide information again.

[0363] Specific examples

[0364] A user enters a shopping mall and launches the application on their smartphone. They set up a profile and enter that they are interested in "latest fashion." The user's current location within the mall is identified using the GPS function, and the generative AI model generates customized guide information based on that information and personal information. The generated guide information is information about the latest fashion stores near the user's current location and is sent to the device. At that time, a prompt such as the following is sent to the generative AI model:

[0365] "The user is interested in the latest fashion and is currently located near 35.658581,139.745433 in the shopping mall. Please generate relevant guide information."

[0366] The guide information is displayed on the device and played back in audio format. In addition, the device analyzes the user's facial expressions and tone of voice and sends emotional data to the server. If the device recognizes that the user has an interested expression, the generative AI model generates more detailed information. This allows the device to provide highly personalized guide information to the user.

[0367] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0368] Step 1:

[0369] The server obtains the user's location information from the device. It uses the device's GPS function to determine the user's exact current location and sends that location information to the server. In this case, the input is the device's GPS data, and the output is the location information data received by the server.

[0370] Step 2:

[0371] The server collects personal information about users from their devices. It collects information such as hobbies, interests, and age entered by users within the application and stores this personal information in a database. The input is the profile information entered by the user, and the output is personal information data stored on the server.

[0372] Step 3:

[0373] The server requests the generative AI model to generate guide information based on the acquired location information and personal information. To do this, it creates a prompt sentence and sends it to the generative AI model. The input of the prompt sentence is the location information and personal information, and the output is the prompt sentence sent to the generative AI model.

[0374] Step 4:

[0375] The generative AI model generates guide information based on the sent prompt sentence. The input is the prompt sentence, and the output is customized guide information. The generated guide information is temporarily stored in a database.

[0376] Step 5:

[0377] The server sends the guide information generated by the generative AI model to the terminal. The terminal receives this guide information and displays it to the user or plays it back aloud. The input is the generated guide information, and the output is the guide information sent to the terminal.

[0378] Step 6:

[0379] The device generates emotion data by analyzing the user's facial expressions and tone of voice. It captures the user's facial expressions and voice using a camera and microphone, and analyzes them using emotion recognition software. The input is facial expression data and voice data, and the output is emotion data.

[0380] Step 7:

[0381] The server again requests the generative AI model to customize the guide information based on the emotion data sent from the device. It then creates a new prompt sentence based on the emotion data and sends it to the generative AI model. The input is the emotion data, and the output is the new prompt sentence.

[0382] Step 8:

[0383] The generative AI model generates more appropriate guide information based on the updated prompt. The input is the new prompt, and the output is further customized guide information. The generated guide information is again sent to the server and provided to the device.

[0384] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0385] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0386] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0387] [Second embodiment]

[0388] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0389] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0390] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0391] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0392] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0393] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0394] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0395] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0396] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0397] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0398] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0399] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0400] The system of the present invention provides customized guide information to users at facilities such as art galleries, museums, historical buildings, etc. This system is mainly composed of the following components: a means for acquiring the user's location information, a means for collecting personal information such as the user's hobbies, interests, and age, a means for requesting the generation of guide information from a generative AI model, a means for transmitting the generated guide information to a terminal, and a means for presenting the guide information received by the terminal to the user.

[0401] When a visitor enters an art gallery or museum, they launch an application using a smartphone or dedicated device. The user first enters personal information within the application. For example, the user provides information that they are interested in art and particularly like impressionist paintings. This information is then sent to the server by the device.

[0402] The device then uses its GPS to determine the user's current location (for example, if the user is in an area of ​​the museum where impressionist paintings are displayed), and this location information is also sent to the server.

[0403] The server requests the generative AI model to generate guide information based on the received personal information and location information. For example, a query such as "A user who is interested in art and likes impressionist paintings is in the current exhibition area. Please generate a relevant explanation." The generative AI model generates relevant guide information based on this query. For example, information about the main characteristics of impressionism, Monet's techniques and background, and other related artists is generated.

[0404] The generated guide information is sent from the server to the device. The device displays the received guide information and plays it back as audio if necessary. For example, a detailed description of an impressionist painting may be displayed on the user's smartphone while an audio guide is played back at the same time.

[0405] Additionally, users can use the application to provide feedback or request additional information. For example, if they want to know more about other works by Monet, they can enter additional questions. This information is sent back to the server, and the generative AI model generates new guide information and sends it to the device, which then presents this information to the user again.

[0406] In this way, the system of the present invention provides guide information in real time that is tailored to the individual interests and background of each user, thereby improving the viewing experience within the facility.

[0407] The processing flow will be explained below.

[0408] Step 1:

[0409] The user launches a dedicated application on their smartphone or device. First, the user sets up their profile within the application and enters personal information such as hobbies, interests, and age. For example, the user may provide information such as "I'm interested in art" or "I like impressionism."

[0410] Step 2:

[0411] The device uses GPS to acquire the user's current location, which is then sent to a server. For example, the server may detect that the user is in an area displaying impressionist paintings.

[0412] Step 3:

[0413] The device sends the user's personal information (such as hobbies, interests, and age) and the acquired location information to the server. The server receives this information.

[0414] Step 4:

[0415] Based on the personal information and location information received by the server, a query is generated to the generative AI model requesting the generation of guide information. For example, a query such as "A user who is interested in art and likes impressionism is currently in the current exhibition area. Please generate a relevant explanation."

[0416] Step 5:

[0417] The generative AI model generates guide information based on queries from the server. Specifically, it generates information about the history and characteristics of Impressionism, as well as famous works and artists. For example, it includes an explanation that "Monet's works are characterized by their use of light and color."

[0418] Step 6:

[0419] The server receives the generated guide information and transmits it to the terminal, which receives the guide information.

[0420] Step 7:

[0421] The device displays the guide information it receives and plays it back as audio if necessary. For example, a detailed description of a Monet work could be displayed on the smartphone screen while an audio guide is played at the same time.

[0422] Step 8:

[0423] Users can view the exhibits based on the guided information. If they have further questions or would like more information, they can provide feedback or request additional information through the application. For example, they can enter a request such as, "I'd like to know more about Monet's other famous works."

[0424] Step 9:

[0425] The device sends the user's feedback and request information to the server, which then requests the AI ​​model to generate additional guide information.

[0426] Step 10:

[0427] The generative AI model generates new information, which the server sends to the device, which then presents the new guide information to the user.

[0428] Through the above series of steps, this system can provide customized guide information tailored to each user's individual interests and needs in real time.

[0429] Example 1

[0430] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0431] Conventional facility guide systems could only provide general information to users, making it difficult to provide customized guide information tailored to individual interests in real time. Furthermore, they lacked a mechanism for automatically acquiring location information as users move around the facility and providing detailed guidance based on that information. Furthermore, they lacked the ability to flexibly respond to user feedback and requests for additional information and provide further customized information.

[0432] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0433] In this invention, the server includes means for acquiring user location information, means for collecting personal information such as the user's hobbies, interests, and age, means for generating a prompt sentence for requesting the generation of guide information from the generative AI model based on the location information and personal information, means for sending the generated prompt sentence to the generative AI model, means for sending the guide information generated by the generative AI model to a terminal, means for presenting the guide information received by the terminal to the user, means for collecting user feedback and requests for additional information, and means for again requesting the generation of guide information from the generative AI model based on the feedback and requests for additional information. This makes it possible to provide users with guide information customized to their individual interests in real time, and to provide information tailored to their movement within a facility and respond to requests for additional information.

[0434] "Location information" refers to data used to identify a user's current location.

[0435] "Personal Information" refers to information about a user's hobbies, interests, age, and other personal attributes.

[0436] A "generative AI model" refers to an artificial intelligence system that generates new information based on input data.

[0437] A "prompt sentence" refers to an input sentence that gives specific instructions to a generative AI model.

[0438] "Guide information" refers to information about explanations and commentary created by a generative AI model to be provided to users.

[0439] "Terminal" refers to a device that can be operated by a user (e.g., smartphone, tablet, dedicated device).

[0440] "Feedback" refers to the opinions and impressions that users provide to the system.

[0441] "Requesting additional information" refers to the user's request for more information from the system.

[0442] The system of the present invention provides customized guide information to users at facilities such as art galleries, museums, historical buildings, etc. This system mainly includes means for acquiring location information and personal information of the user and requesting the generation of guide information from a generative AI model based on the information.

[0443] When a user enters a facility, they launch the application using a smartphone or dedicated terminal. The user first enters personal information within the application. For example, the user provides information that they are interested in art and particularly like impressionist paintings. This information is then sent to the server by the terminal.

[0444] The device then uses its GPS to determine the user's current location (for example, if the user is in an area of ​​the museum where impressionist paintings are displayed), and this location information is also sent to the server.

[0445] The server requests the generative AI model to generate guide information based on the received personal information and location information. An example of a prompt sentence to use in this case is, "A user who is interested in art and likes impressionist paintings is in the current exhibition area. Please generate a relevant explanation." The generative AI model generates the appropriate guide information based on this prompt sentence. For example, it generates information about the main characteristics of impressionism, famous artists, techniques, and background.

[0446] The generated guide information is sent from the server to the device. The device displays the received guide information and plays it back as audio if necessary. For example, a detailed description of an impressionist painting may be displayed on the user's smartphone while an audio guide is played back at the same time.

[0447] Additionally, users can use the application to provide feedback or request additional information. For example, if they want to know more about other works by Monet, they can enter additional questions. This information is sent back to the server, and the generative AI model generates new guide information and sends it to the device. The device then presents this information to the user again.

[0448] In this way, the system of the present invention provides real-time guide information tailored to individual interests and backgrounds, improving the viewing experience within the facility. Specific hardware used includes smartphones and tablets with GPS functionality. Furthermore, it is desirable to use the latest AI algorithms based on natural language processing technology as the generative AI model.

[0449] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0450] Step 1:

[0451] A user enters a facility and launches an application.

[0452] Input: An application is started by a user action.

[0453] Output: None.

[0454] How it works: The user launches the facility application on their smartphone or dedicated device.

[0455] Step 2:

[0456] The user enters personal information within the application.

[0457] Input: Users enter personal information such as their interests, preferences, and age.

[0458] Output: The entered personal information is stored in the device's memory.

[0459] Action: For example, a user types, "I like impressionist paintings."

[0460] Step 3:

[0461] The device uses its GPS function to obtain the user's current location and transmits it to the server.

[0462] Input: Location information obtained by the device's GPS function.

[0463] Output: The location information is sent to the server.

[0464] Operation: For example, if the user is in the impressionist painting exhibition area, their location information is identified.

[0465] Step 4:

[0466] The device sends personal information to the server.

[0467] Input: Personal information entered by the user.

[0468] Output: Personal information is sent to the server.

[0469] How it works: For example, information such as "I'm interested in impressionist paintings" is sent to the server.

[0470] Step 5:

[0471] The server generates a prompt sentence to request the generative AI model to generate guide information based on location information and personal information.

[0472] Input: Location and personal information.

[0473] Output: The generated prompt statement.

[0474] Action: The server generates a prompt saying, "There is a user in the current exhibition area who is interested in art and likes impressionist paintings, so please generate a relevant description."

[0475] Step 6:

[0476] The server sends the generated prompt to the generative AI model.

[0477] Input: The generated prompt statement.

[0478] Output: The generated prompt sentence is sent to the generative AI model.

[0479] How it works: The server sends the generated prompt sentence to the generative AI model.

[0480] Step 7:

[0481] The generative AI model generates guide information and sends it to the server.

[0482] Input: The generated prompt statement.

[0483] Output: The generated guide information.

[0484] How it works: A generative AI model generates guide information about key features of impressionism, Monet's techniques, and more.

[0485] Step 8:

[0486] The server transmits the generated guide information to the terminal.

[0487] Input: Generated guide information.

[0488] Output: Guide information is sent to the terminal.

[0489] Operation: The server sends the generated guide information to the terminal.

[0490] Step 9:

[0491] The terminal displays the received guide information to the user and plays it back as audio if necessary.

[0492] Input: Guide information sent from the server.

[0493] Output: Guidance information displayed to the user and audio playback.

[0494] Operation: Guide information will be displayed on the user's smartphone and audio playback will begin.

[0495] Step 10:

[0496] The user enters feedback or a request for more information.

[0497] Input: User feedback or requests for additional information.

[0498] Output: Feedback and requests are stored in the device's memory.

[0499] Action: For example, a user types, "I'd like to know about other works by Monet."

[0500] Step 11:

[0501] The device sends a request for feedback or additional information to the server.

[0502] Input: User feedback or requests for additional information.

[0503] Output: Feedback or requests are sent to the server.

[0504] Operation: The device sends the user's request to the server.

[0505] Step 12:

[0506] Based on the feedback and requests for additional information received by the server, the generative AI model is again requested to generate guide information.

[0507] Input: User feedback or requests for additional information.

[0508] Output: The new prompt sent to the generative AI model.

[0509] What happens: The server again sends a request to the generative AI model.

[0510] Step 13:

[0511] The generative AI model generates new guide information and sends it to the server.

[0512] Input: New prompt text.

[0513] Output: The newly generated guide information.

[0514] How it works: A generative AI model generates guide information based on new user requests.

[0515] Step 14:

[0516] The server transmits the newly generated guide information to the terminal.

[0517] Input: The newly generated guide information.

[0518] Output: New guide information is sent to the terminal.

[0519] Operation: The server sends new guide information to the terminal.

[0520] Step 15:

[0521] The terminal displays the new guide information to the user and plays it aloud if necessary.

[0522] Input: New guide information.

[0523] Output: New guide information displayed to the user, and audio playback.

[0524] Operation: New guide information will be displayed on the user's smartphone, and audio playback will begin.

[0525] (Application example 1)

[0526] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0527] In industrial facilities, it is important for workers to work efficiently by providing appropriate work instructions in real time that are tailored to their individual skills and experience. However, current systems have difficulty providing customized work instructions based on the worker's current location and personal information, making it difficult to improve work efficiency. There is also a need for systems to receive feedback from workers and generate further work instructions appropriately.

[0528] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0529] In this invention, the server includes a means for acquiring location information of workers within an industrial facility, a means for collecting personal information such as the worker's skill level, experience, and work history, a means for sending a request to generate work instructions to a generative AI model based on the location information and personal information, a means for sending the work instructions generated by the generative AI model to a display device, and a means for presenting the work instructions received by the display device to the worker. This makes it possible to provide customized work instructions to workers in real time, thereby improving work efficiency.

[0530] The "location information acquisition means" is a means for acquiring the current location of a worker within an industrial facility.

[0531] "Means for collecting personal information" refers to means for collecting personal information such as the worker's technical level, experience, and work history.

[0532] The "generation request sending means" is a means for sending a request to generate work instructions to the generation AI model based on location information and personal information.

[0533] The "work instruction generation means" is a means for transmitting the work instructions generated by the generation AI model to the display device.

[0534] The "work instruction presenting means" is a means for presenting the work instructions received by the display device to the worker.

[0535] The "feedback receiving means" is a means for receiving feedback from the worker and requests for additional work information.

[0536] The "additional work instruction generation means" is a means for generating further work instructions based on feedback or requests for additional information.

[0537] This invention relates to a system that provides individual work instructions to workers in industrial facilities in real time. The system acquires the location information and personal information of the workers, generates optimal work instructions using a generative AI model, and presents them to the workers via a display device.

[0538] First, a GPS module is used to acquire the location information of the worker. The GPS module is used to identify the current location of the worker within the industrial facility. Next, a personal information collection means is used to send personal information such as the worker's skill level, experience, and work history to the server.

[0539] The server requests the generative AI model to generate work instructions based on the received location information and personal information. The generative AI model used in this process is stored on the cloud. The server also has the function of sending the generated work instructions to a display device. The display device could be, for example, smart glasses or a tablet terminal.

[0540] Not only can workers view work instructions through the display device, but they can also provide feedback or request additional information. These requests are sent back to the server, and the generative AI model responds by generating further work instructions and sending them to the display device. This two-way information exchange allows workers to work efficiently.

[0541] As a concrete example, suppose a worker moves to a new assembly area. The GPS module detects the worker's location and sends this location information to the server. At the same time, the worker's skill level and past assembly work experience are sent to the server via the personal information collection means. Based on this data, the server sends the following prompt to the generative AI model:

[0542] "The user's name is Yamada Taro and he has advanced experience. He is currently in the precision assembly area. Please generate the most suitable work instructions for this user."

[0543] Based on these prompts, the generative AI model generates work instructions, including optimal work procedures and precautions for precision assembly, and sends them to the server. The server then sends the received work instructions to a display device so that the worker can check them in real time. The worker can proceed with the work while checking the detailed procedures and safety precautions on the display device.

[0544] Furthermore, if a worker needs additional information, they can input a request via the display device. This request is sent to the server, and the generative AI model generates new information and sends it back to the display device. Through this process, the worker can obtain the necessary information in a timely manner and work efficiently.

[0545] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0546] Step 1:

[0547] The GPS module is used to obtain the current location of the worker. The input is the location data from the GPS module, and the output is the current coordinate information. The server receives this coordinate information.

[0548] Step 2:

[0549] Using a personal information collection means, personal information such as the worker's skill level, experience, and work history is collected. The input is the worker's profile data, and the output is a set of this personal information. The server receives this personal information.

[0550] Step 3:

[0551] Based on the location information and personal information received by the server, it sends a request to the generative AI model to generate work instructions. The input is a set of location information and personal information, and the output is a prompt sentence to be sent to the generative AI model. An example of a specific prompt sentence is, "The user's name is Mr. A, and he has advanced experience. He is currently in the precision assembly area. Please generate the most suitable work instructions for this user."

[0552] Step 4:

[0553] The generative AI model generates work instructions based on the received prompt. The input is the prompt, and the output is customized work instructions. The generated work instructions are sent to the server.

[0554] Step 5:

[0555] The server sends the work instructions received from the generative AI model to the display device. The input is the generated work instructions, and the output is the data sent to the display device.

[0556] Step 6:

[0557] The display device presents the received work instructions to the worker. The input is the work instructions sent from the server, and the output is the work instruction information displayed on the display device. For example, the instructions are displayed in text format on the screen of smart glasses or a tablet device, and are also played back as audio.

[0558] Step 7:

[0559] The worker inputs additional information and feedback through the display device. The input is the requested information from the worker, and the output is the data to be sent to the server. For example, a request such as "I would like to know more details about the current procedure" is input into the display device.

[0560] Step 8:

[0561] The server receives requests for additional information from the worker and sends the requests to the generative AI model. The input is the request for additional information, and the output is a new prompt sentence that is sent to the generative AI model.

[0562] Step 9:

[0563] The generative AI model generates more detailed work instructions based on the new prompt. The input is the new prompt, and the output is the new work instructions. The generated work instructions are sent to the server again.

[0564] Step 10:

[0565] The server retransmits the new work instructions received from the generative AI model to the display device. The input is the new work instructions, and the output is the data sent to the display device.

[0566] Step 11:

[0567] The display device then presents the new work instructions received to the worker. The input is the new work instructions sent from the server, and the output is the additional work instruction information displayed on the display device. This allows the worker to obtain the necessary additional information in real time and work efficiently.

[0568] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0569] The system of the present invention provides customized guide information to users at facilities such as art galleries, museums, and historical buildings, and also combines an emotion engine. The system is composed of the following components: a means for acquiring the user's location information, a means for collecting personal information such as the user's hobbies, interests, and age, a means for requesting the generation of guide information from a generative AI model, a means for sending the guide information generated by the generative AI model to a terminal, a means for presenting the guide information received by the terminal to the user, and an emotion engine that recognizes the user's emotions.

[0570] When a user enters a facility, they launch the application using a smartphone or dedicated terminal. First, the user sets up a profile within the application and enters personal information such as hobbies, interests, and age. For example, the user may provide information such as "I'm interested in art, and I particularly like impressionist paintings." This information is then sent to the server by the terminal.

[0571] The device then uses its GPS to determine the user's current location, which is also sent to the server. For example, the device may determine that the user is in the Impressionist paintings exhibit area of ​​a museum.

[0572] The server generates a query to the generative AI model based on the received personal information and location information, requesting the model to generate guide information. For example, the server generates a query such as, "A user who is interested in art and likes impressionist paintings is currently in the exhibition area. Please generate a relevant explanation." The generative AI model generates relevant guide information based on this query. For example, it generates information about the history and characteristics of impressionism, as well as famous works and artists.

[0573] The generated guide information is sent from the server to the device. The device displays the received guide information and plays it back as audio if necessary. For example, a detailed description of Monet's work may be displayed on the user's smartphone while an audio guide is played back at the same time.

[0574] Furthermore, the system includes an emotion engine that recognizes the user's emotions. The emotion engine recognizes emotions by analyzing the user's facial expressions and tone of voice. For example, when a user is viewing a Monet painting, if the emotion engine recognizes that the user is moved by the painting, this emotion data is sent to the server.

[0575] The server requests the generative AI model to customize the guide information based on the received emotional data. For example, if the user is moved, the server can request the generative AI model to provide a deeper artistic background or anecdotes that will amplify the emotion. The generative AI model generates more detailed information, which the server sends to the device. The device then presents the new guide information to the user.

[0576] Users can also use the application to provide feedback or request additional information, for example, by entering a request such as "I want to know more about other famous works by Monet." This information is then sent back to the server, where the generative AI model generates new guide information and sends it back to the device, which then presents this information to the user.

[0577] In this way, the system of the present invention can provide customized guide information in real time according to the user's individual interests and background, and can also use an emotion engine to provide detailed services based on the user's emotions.

[0578] The processing flow will be explained below.

[0579] Step 1:

[0580] The user launches a dedicated application on their smartphone or device. First, the user sets up their profile within the application and enters personal information such as hobbies, interests, and age. For example, the user may provide information such as "I'm interested in art" or "I like impressionism."

[0581] Step 2:

[0582] The device uses GPS to acquire the user's current location, which is then sent to a server. For example, the server may detect that the user is in an area displaying impressionist paintings.

[0583] Step 3:

[0584] The device sends the user's personal information (such as hobbies, interests, and age) and the acquired location information to the server. The server receives this information.

[0585] Step 4:

[0586] Based on the personal information and location information received by the server, a query is generated to the generative AI model requesting the generation of guide information. For example, a query such as "A user who is interested in art and likes impressionism is currently in the current exhibition area. Please generate a relevant explanation."

[0587] Step 5:

[0588] The generative AI model generates guide information based on queries from the server. Specifically, it generates information about the history and characteristics of Impressionism, as well as famous works and artists. For example, it includes an explanation that "Monet's works are characterized by their use of light and color."

[0589] Step 6:

[0590] The server receives the generated guide information and transmits it to the terminal, which receives the guide information.

[0591] Step 7:

[0592] The device displays the guide information it receives and plays it back as audio if necessary. For example, a detailed description of a Monet work could be displayed on the smartphone screen while an audio guide is played at the same time.

[0593] Step 8:

[0594] The user views the exhibits based on the guided information. If the user has further questions or wants more information, they can provide feedback or request additional information through the application. For example, they can enter a request such as, "I'd like to know more about Monet's other famous works."

[0595] Step 9:

[0596] The device sends the user's feedback and request information to the server, which then requests the AI ​​model to generate additional guide information.

[0597] Step 10:

[0598] The generative AI model generates new information, which the server sends to the device, which then presents the new guide information to the user.

[0599] Step 11:

[0600] The device's emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotions. For example, the device uses a camera and microphone to collect the user's reactions while viewing artwork.

[0601] Step 12:

[0602] The emotion engine recognizes the user's emotions and sends that information to the server. For example, it recognizes that the user is moved by a painting by Monet.

[0603] Step 13:

[0604] The server receives the emotion data and requests the generative AI model to customize the guide information based on that data. For example, the server requests the generative AI model to provide an episode that will further amplify the emotion of the user, since the user is moved by the emotion.

[0605] Step 14:

[0606] The generative AI model generates customized guide information, which the server sends to the device. The device then presents the new customized guide information to the user. For example, it provides touching episodes or background information on related works.

[0607] As described above, this system provides customized guide information in real time based on the user's individual interests and background, and further enriches the viewing experience by using an emotion engine to provide services based on the user's emotions.

[0608] Example 2

[0609] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0610] Conventional guide systems provide information based on the user's location and interests, but this is not sufficient to provide a personalized experience. Furthermore, they are unable to provide guide information that takes into account the user's emotions, making it difficult to increase satisfaction. Therefore, there is a demand for a system that can provide customized guide information in real time that is tailored to the user's individual interests and emotions.

[0611] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring location information of a user, means for collecting personal information such as the user's hobbies, interests, and age, means for requesting the generation of guide information from a generation AI model based on the location information and the personal information, means for transmitting the guide information generated by the generation AI model to a terminal, means for presenting the guide information received by the terminal to the user, means for recognizing the user's emotions, and means for customizing the guide information based on the emotion data. This makes it possible to provide customized guide information in real time that is tailored to the user's individual interests and emotions.

[0612] "User" refers to any individual or entity that uses the System.

[0613] "Location Information" means physical location data determined using GPS or other methods.

[0614] "Personal information" refers to information related to a specific individual, such as a user's hobbies, interests, age, etc.

[0615] "Generative AI model" refers to an artificial intelligence model that generates guide information and other data.

[0616] "Guide information" refers to explanations and information provided by a generative AI model based on the user's interests and location.

[0617] "Terminal" refers to a device used by a user, such as a smartphone or tablet.

[0618] "Emotional data" refers to data on a user's emotional state obtained by analyzing their facial expressions and tone of voice.

[0619] An "emotion engine" refers to a system that analyzes users' emotions and recognizes them as data.

[0620] The system of this invention provides customized guide information to users in facilities such as art galleries, museums, and historical buildings, and also combines an emotion engine. The system is mainly composed of three main components: a server, a terminal, and a user.

[0621] Hardware and software used

[0622] Devices: Smartphones, dedicated tablet devices

[0623] Server: Cloud server such as AWS or Google Cloud Platform

[0624] GPS function: Built-in to smartphones and tablets

[0625] Generative AI models: OpenAI GPT-4, Google BERT, etc.

[0626] Emotion engine: Affectiva SDK, Microsoft Azure Face API, etc.

[0627] Processing flow and specific examples

[0628] 1. User profile settings

[0629] Users enter the facility and launch the application on their smartphone or dedicated device. Within the application, they enter profile information such as their name, age, hobbies and interests. For example, they might enter information like, "I'm interested in art, and I particularly like impressionist paintings." This information is stored on the device and later sent to the server.

[0630] 2. Obtaining location information

[0631] The device uses its built-in GPS to determine its current location, which is then sent in encrypted form to a server, identifying, for example, the user as being in the impressionist paintings section of a museum.

[0632] 3. Guide information generation request

[0633] The server generates a query to request the generation of guide information from the generative AI model based on the user's profile information and location information. An example of a prompt sentence is "A user who is interested in art and likes impressionist paintings is in the current exhibition area, so please generate a relevant description."

[0634] 4. Guide information generation and transmission

[0635] The generative AI model receives and analyzes the prompt text and generates relevant guide information. For example, it generates information about the history and characteristics of Impressionism, as well as famous works and artists. This generated guide information is sent to the device via the server.

[0636] 5. Present guide information

[0637] The device displays the received guide information on its screen and plays it audibly as needed. For example, a detailed description of a Monet work may be displayed on the user's smartphone, and an audio guide may be played.

[0638] 6. Emotional Recognition

[0639] Using the device's camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice. The analysis results are sent to the server as emotion data. For example, it can recognize when a user is moved by a painting by Monet.

[0640] 7. Customizing guide information

[0641] Based on the emotion data, the server requests the generative AI model to generate new, more detailed guide information. For example, if a user is moved by something, it generates a request to add more in-depth artistic background or anecdotes. The newly generated information is then sent back to the device via the server and provided to the user.

[0642] 8. Feedback and Requests for Additional Information

[0643] Within the application, users can request feedback or additional information, for example, "I want to know more about other famous works by Monet." This request is sent to the server, where the generative AI model generates new guide information and sends it to the device, providing further information to the user.

[0644] As described above, the system of the present invention is capable of providing customized guide information in real time that is tailored to the individual interests and emotions of users, thereby increasing user satisfaction.

[0645] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0646] Step 1:

[0647] The user launches the application and enters their profile information.

[0648] Input: A user launches an application and enters profile information such as name, age, hobbies and interests.

[0649] How it works: The device stores the information the user enters within the application in a local database.

[0650] Output: User profile information is saved on the device.

[0651] Step 2:

[0652] The device acquires location information and sends it to the server.

[0653] Input: The device uses the GPS function to obtain the current location information.

[0654] Operation: The device encrypts the acquired location information and sends it to the server.

[0655] Output: Encrypted location information is sent to the server.

[0656] Step 3:

[0657] The server generates a request for generating guide information.

[0658] Input: The server receives the user's profile information and location information.

[0659] How it works: The server generates a prompt sentence to send to the generative AI model based on the received data. An example of a prompt sentence is, "A user who is interested in art and likes impressionist paintings is currently in the exhibition area, so please generate a relevant description."

[0660] Output: A prompt sentence is generated that is sent to the generative AI model.

[0661] Step 4:

[0662] A generative AI model generates guide information.

[0663] Input: A prompt sentence is sent to the generative AI model.

[0664] How it works: The generative AI model analyzes the prompt and generates relevant guide information, such as information about the history and characteristics of Impressionism, as well as famous works and artists.

[0665] Output: The generated guide information is returned to the server.

[0666] Step 5:

[0667] The server transmits the generated guide information to the terminal.

[0668] Input: The server receives guidance information from the generative AI model.

[0669] Operation: The server encrypts the guide information it receives and sends it to the user's terminal.

[0670] Output: Encrypted guide information is sent to the terminal.

[0671] Step 6:

[0672] The device displays or plays audible guide information.

[0673] Input: The device receives encrypted guide information from the server.

[0674] How it works: The device decrypts the encrypted information and displays it on the screen or plays it as an audio guide. For example, a detailed description of a Monet painting may be displayed on the user's smartphone, and an audio guide may be played.

[0675] Output: The guide information is displayed on the user's device and played back aloud.

[0676] Step 7:

[0677] The emotion engine recognizes the user's emotions.

[0678] Input: Capture the user's facial expressions and tone of voice using the device's camera and microphone.

[0679] How it works: The emotion engine analyzes the facial expressions and tone of voice it acquires to generate emotion data. This emotion data is sent to the server. For example, it recognizes when a user is moved by a painting by Monet.

[0680] Output: Emotion data is sent to the server.

[0681] Step 8:

[0682] The server customizes the guide information based on the emotion data.

[0683] Input: The server generates a new prompt sentence based on the emotion data received.

[0684] How it works: A new prompt is sent to the generative AI model, requesting it to generate more detailed guide information. For example, if a user is moved by something, a request is generated to add more in-depth artistic background or anecdotes. The newly generated information is then sent back to the device via the server.

[0685] Output: The customized guide information is sent to the device.

[0686] Step 9:

[0687] The user requests feedback or additional information.

[0688] Input: A user types feedback or a request for more information within an application. For example, "I want to know more about Monet's other famous works."

[0689] Operation: Request information is sent to the server, and the generative AI model generates new guide information and sends it to the device via the server.

[0690] Output: The new guide information is displayed on the user's device.

[0691] (Application example 2)

[0692] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0693] Conventional shopping guide systems have had difficulty providing customized information based on a user's location information or individual hobbies and interests. They also have difficulty recognizing a user's emotions and providing appropriate information accordingly. As a result, they have been unable to provide a satisfying shopping experience for users. The present invention aims to solve these problems and provide a personalized shopping guide for users.

[0694] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user location information, means for collecting personal information such as the user's hobbies, interests, and age, means for requesting the generation of guide information from the generative AI model based on the location information and personal information, means for transmitting the guide information generated by the generative AI model to the terminal, means for presenting the guide information received by the terminal to the user, means for recognizing emotions by analyzing the user's facial expressions and tone of voice, and means for requesting the generation of guide information from the generative AI model based on the emotion data. This makes it possible to provide a highly personalized shopping guide based on the user's individual hobbies, interests, location information, and emotions.

[0695] "User location information" is data that indicates the user's current geographical location.

[0696] "Hobbies and interests" is information related to activities or areas in which a user has a particular interest.

[0697] "Age" is data indicating the length of time calculated based on the user's date of birth.

[0698] "Personal information" refers to detailed data related to a user, such as hobbies, interests, age, etc.

[0699] A "generative AI model" is an artificial intelligence model that generates customized information based on input data.

[0700] "Guide information" is data output by the generative AI model that provides useful guidance and explanations to users.

[0701] "Terminal" refers to a computing device carried by a user, such as a smartphone or smart glasses.

[0702] "Facial expressions and tone of voice" refers to the user's facial expressions and speech patterns, and are data that provide clues to emotions.

[0703] "Emotion data" is data based on facial expressions and tone of voice that is analyzed to recognize the user's emotions.

[0704] "Customized" means that something is specifically tailored or modified to suit a particular user.

[0705] This invention builds a system that provides customized shopping guide information to users in physical stores such as shopping malls. The system acquires the user's location information, collects personal information such as hobbies, interests, and age, generates customized guide information using a generative AI model, and transmits it to the terminal. Another feature of the system is that it analyzes the user's facial expressions and tone of voice to recognize emotions and provides more appropriate guide information based on that emotional data.

[0706] Hardware and software configuration

[0707] Hardware

[0708] 1. Device: A device carried by a user, such as a smartphone or smart glasses.

[0709] 2. Server: A remote server that generates guide information and processes data.

[0710] software

[0711] 1. Location information acquisition software: Software that uses GPS functionality to determine the user's current location.

[0712] 2. Personal Information Collection Software: Software that allows users to set up a profile within an application and enter personal information such as hobbies, interests, age, etc.

[0713] 3. Generative AI model: An artificial intelligence model that generates customized guide information based on the user's location information and personal information.

[0714] 4. Emotion recognition software: Software that recognizes emotions by analyzing the user's facial expressions and tone of voice.

[0715] Data Flow and Processing

[0716] 1. Location information acquisition:

[0717] The server obtains location information from the user's device, which is precisely determined using GPS functionality.

[0718] 2. Collection of Personal Information:

[0719] The server collects personal information such as hobbies, interests, and age that users enter within the application.

[0720] 3. Guide information generation:

[0721] The server requests the generative AI model to generate guide information based on the collected location information and personal information, and creates a prompt sentence and passes it to the generative AI model.

[0722] example:

[0723] "The user is interested in the latest fashion and is currently located near 35.658581,139.745433 in the shopping mall. Please generate relevant guide information."

[0724] 4. Sending and Presenting Guide Information:

[0725] The server sends the guide information generated by the generative AI model to the device, which then displays the received guide information to the user and plays it back in audio format.

[0726] 5. Emotion Recognition and Customization:

[0727] The device analyzes the user's facial expressions and tone of voice to generate emotional data, which is then sent to the server, which then requests the AI ​​model to customize the guide information again.

[0728] Specific examples

[0729] A user enters a shopping mall and launches the application on their smartphone. They set up a profile and enter that they are interested in "latest fashion." The user's current location within the mall is identified using the GPS function, and the generative AI model generates customized guide information based on that information and personal information. The generated guide information is information about the latest fashion stores near the user's current location and is sent to the device. At that time, a prompt such as the following is sent to the generative AI model:

[0730] "The user is interested in the latest fashion and is currently located near 35.658581,139.745433 in the shopping mall. Please generate relevant guide information."

[0731] The guide information is displayed on the device and played back in audio format. In addition, the device analyzes the user's facial expressions and tone of voice and sends emotional data to the server. If the device recognizes that the user has an interested expression, the generative AI model generates more detailed information. This allows the device to provide highly personalized guide information to the user.

[0732] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0733] Step 1:

[0734] The server obtains the user's location information from the device. It uses the device's GPS function to determine the user's exact current location and sends that location information to the server. In this case, the input is the device's GPS data, and the output is the location information data received by the server.

[0735] Step 2:

[0736] The server collects personal information about users from their devices. It collects information such as hobbies, interests, and age entered by users within the application and stores this personal information in a database. The input is the profile information entered by the user, and the output is personal information data stored on the server.

[0737] Step 3:

[0738] The server requests the generative AI model to generate guide information based on the acquired location information and personal information. To do this, it creates a prompt sentence and sends it to the generative AI model. The input of the prompt sentence is the location information and personal information, and the output is the prompt sentence sent to the generative AI model.

[0739] Step 4:

[0740] The generative AI model generates guide information based on the sent prompt sentence. The input is the prompt sentence, and the output is customized guide information. The generated guide information is temporarily stored in a database.

[0741] Step 5:

[0742] The server sends the guide information generated by the generative AI model to the terminal. The terminal receives this guide information and displays it to the user or plays it back aloud. The input is the generated guide information, and the output is the guide information sent to the terminal.

[0743] Step 6:

[0744] The device generates emotion data by analyzing the user's facial expressions and tone of voice. It captures the user's facial expressions and voice using a camera and microphone, and analyzes them using emotion recognition software. The input is facial expression data and voice data, and the output is emotion data.

[0745] Step 7:

[0746] The server again requests the generative AI model to customize the guide information based on the emotion data sent from the device. It then creates a new prompt sentence based on the emotion data and sends it to the generative AI model. The input is the emotion data, and the output is the new prompt sentence.

[0747] Step 8:

[0748] The generative AI model generates more appropriate guide information based on the updated prompt. The input is the new prompt, and the output is further customized guide information. The generated guide information is again sent to the server and provided to the device.

[0749] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0750] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0751] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0752] [Third embodiment]

[0753] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0754] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0755] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0756] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0757] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0758] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0759] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0760] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0761] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0762] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0763] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0764] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0765] The system of the present invention provides customized guide information to users at facilities such as art galleries, museums, historical buildings, etc. This system is mainly composed of the following components: a means for acquiring the user's location information, a means for collecting personal information such as the user's hobbies, interests, and age, a means for requesting the generation of guide information from a generative AI model, a means for transmitting the generated guide information to a terminal, and a means for presenting the guide information received by the terminal to the user.

[0766] When a visitor enters an art gallery or museum, they launch an application using a smartphone or dedicated device. The user first enters personal information within the application. For example, the user provides information that they are interested in art and particularly like impressionist paintings. This information is then sent to the server by the device.

[0767] The device then uses its GPS to determine the user's current location (for example, if the user is in an area of ​​the museum where impressionist paintings are displayed), and this location information is also sent to the server.

[0768] The server requests the generative AI model to generate guide information based on the received personal information and location information. For example, a query such as "A user who is interested in art and likes impressionist paintings is in the current exhibition area. Please generate a relevant explanation." The generative AI model generates relevant guide information based on this query. For example, information about the main characteristics of impressionism, Monet's techniques and background, and other related artists is generated.

[0769] The generated guide information is sent from the server to the device. The device displays the received guide information and plays it back as audio if necessary. For example, a detailed description of an impressionist painting may be displayed on the user's smartphone while an audio guide is played back at the same time.

[0770] Additionally, users can use the application to provide feedback or request additional information. For example, if they want to know more about other works by Monet, they can enter additional questions. This information is sent back to the server, and the generative AI model generates new guide information and sends it to the device, which then presents this information to the user again.

[0771] In this way, the system of the present invention provides guide information in real time that is tailored to the individual interests and background of each user, thereby improving the viewing experience within the facility.

[0772] The processing flow will be explained below.

[0773] Step 1:

[0774] The user launches a dedicated application on their smartphone or device. First, the user sets up their profile within the application and enters personal information such as hobbies, interests, and age. For example, the user may provide information such as "I'm interested in art" or "I like impressionism."

[0775] Step 2:

[0776] The device uses GPS to acquire the user's current location, which is then sent to a server. For example, the server may detect that the user is in an area displaying impressionist paintings.

[0777] Step 3:

[0778] The device sends the user's personal information (such as hobbies, interests, and age) and the acquired location information to the server. The server receives this information.

[0779] Step 4:

[0780] Based on the personal information and location information received by the server, a query is generated to the generative AI model requesting the generation of guide information. For example, a query such as "A user who is interested in art and likes impressionism is currently in the current exhibition area. Please generate a relevant explanation."

[0781] Step 5:

[0782] The generative AI model generates guide information based on queries from the server. Specifically, it generates information about the history and characteristics of Impressionism, as well as famous works and artists. For example, it includes an explanation that "Monet's works are characterized by their use of light and color."

[0783] Step 6:

[0784] The server receives the generated guide information and transmits it to the terminal, which receives the guide information.

[0785] Step 7:

[0786] The device displays the guide information it receives and plays it back as audio if necessary. For example, a detailed description of a Monet work could be displayed on the smartphone screen while an audio guide is played at the same time.

[0787] Step 8:

[0788] Users can view the exhibits based on the guided information. If they have further questions or would like more information, they can provide feedback or request additional information through the application. For example, they can enter a request such as, "I'd like to know more about Monet's other famous works."

[0789] Step 9:

[0790] The device sends the user's feedback and request information to the server, which then requests the AI ​​model to generate additional guide information.

[0791] Step 10:

[0792] The generative AI model generates new information, which the server sends to the device, which then presents the new guide information to the user.

[0793] Through the above series of steps, this system can provide customized guide information tailored to each user's individual interests and needs in real time.

[0794] Example 1

[0795] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0796] Conventional facility guide systems could only provide general information to users, making it difficult to provide customized guide information tailored to individual interests in real time. Furthermore, they lacked a mechanism for automatically acquiring location information as users move around the facility and providing detailed guidance based on that information. Furthermore, they lacked the ability to flexibly respond to user feedback and requests for additional information and provide further customized information.

[0797] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0798] In this invention, the server includes means for acquiring user location information, means for collecting personal information such as the user's hobbies, interests, and age, means for generating a prompt sentence for requesting the generation of guide information from the generative AI model based on the location information and personal information, means for sending the generated prompt sentence to the generative AI model, means for sending the guide information generated by the generative AI model to a terminal, means for presenting the guide information received by the terminal to the user, means for collecting user feedback and requests for additional information, and means for again requesting the generation of guide information from the generative AI model based on the feedback and requests for additional information. This makes it possible to provide users with guide information customized to their individual interests in real time, and to provide information tailored to their movement within a facility and respond to requests for additional information.

[0799] "Location information" refers to data used to identify a user's current location.

[0800] "Personal Information" refers to information about a user's hobbies, interests, age, and other personal attributes.

[0801] A "generative AI model" refers to an artificial intelligence system that generates new information based on input data.

[0802] A "prompt sentence" refers to an input sentence that gives specific instructions to a generative AI model.

[0803] "Guide information" refers to information about explanations and commentary created by a generative AI model to be provided to users.

[0804] "Terminal" refers to a device that can be operated by a user (e.g., smartphone, tablet, dedicated device).

[0805] "Feedback" refers to the opinions and impressions that users provide to the system.

[0806] "Requesting additional information" refers to the user's request for more information from the system.

[0807] The system of the present invention provides customized guide information to users at facilities such as art galleries, museums, historical buildings, etc. This system mainly includes means for acquiring location information and personal information of the user and requesting the generation of guide information from a generative AI model based on the information.

[0808] When a user enters a facility, they launch the application using a smartphone or dedicated terminal. The user first enters personal information within the application. For example, the user provides information that they are interested in art and particularly like impressionist paintings. This information is then sent to the server by the terminal.

[0809] The device then uses its GPS to determine the user's current location (for example, if the user is in an area of ​​the museum where impressionist paintings are displayed), and this location information is also sent to the server.

[0810] The server requests the generative AI model to generate guide information based on the received personal information and location information. An example of a prompt sentence to use in this case is, "A user who is interested in art and likes impressionist paintings is in the current exhibition area. Please generate a relevant explanation." The generative AI model generates the appropriate guide information based on this prompt sentence. For example, it generates information about the main characteristics of impressionism, famous artists, techniques, and background.

[0811] The generated guide information is sent from the server to the device. The device displays the received guide information and plays it back as audio if necessary. For example, a detailed description of an impressionist painting may be displayed on the user's smartphone while an audio guide is played back at the same time.

[0812] Additionally, users can use the application to provide feedback or request additional information. For example, if they want to know more about other works by Monet, they can enter additional questions. This information is sent back to the server, and the generative AI model generates new guide information and sends it to the device. The device then presents this information to the user again.

[0813] In this way, the system of the present invention provides real-time guide information tailored to individual interests and backgrounds, improving the viewing experience within the facility. Specific hardware used includes smartphones and tablets with GPS functionality. Furthermore, it is desirable to use the latest AI algorithms based on natural language processing technology as the generative AI model.

[0814] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0815] Step 1:

[0816] A user enters a facility and launches an application.

[0817] Input: An application is started by a user action.

[0818] Output: None.

[0819] How it works: The user launches the facility application on their smartphone or dedicated device.

[0820] Step 2:

[0821] The user enters personal information within the application.

[0822] Input: Users enter personal information such as their interests, preferences, and age.

[0823] Output: The entered personal information is stored in the device's memory.

[0824] Action: For example, a user types, "I like impressionist paintings."

[0825] Step 3:

[0826] The device uses its GPS function to obtain the user's current location and transmits it to the server.

[0827] Input: Location information obtained by the device's GPS function.

[0828] Output: The location information is sent to the server.

[0829] Operation: For example, if the user is in the impressionist painting exhibition area, their location information is identified.

[0830] Step 4:

[0831] The device sends personal information to the server.

[0832] Input: Personal information entered by the user.

[0833] Output: Personal information is sent to the server.

[0834] How it works: For example, information such as "I'm interested in impressionist paintings" is sent to the server.

[0835] Step 5:

[0836] The server generates a prompt sentence to request the generative AI model to generate guide information based on location information and personal information.

[0837] Input: Location and personal information.

[0838] Output: The generated prompt statement.

[0839] Action: The server generates a prompt saying, "There is a user in the current exhibition area who is interested in art and likes impressionist paintings, so please generate a relevant description."

[0840] Step 6:

[0841] The server sends the generated prompt to the generative AI model.

[0842] Input: The generated prompt statement.

[0843] Output: The generated prompt sentence is sent to the generative AI model.

[0844] How it works: The server sends the generated prompt sentence to the generative AI model.

[0845] Step 7:

[0846] The generative AI model generates guide information and sends it to the server.

[0847] Input: The generated prompt statement.

[0848] Output: The generated guide information.

[0849] How it works: A generative AI model generates guide information about key features of impressionism, Monet's techniques, and more.

[0850] Step 8:

[0851] The server transmits the generated guide information to the terminal.

[0852] Input: Generated guide information.

[0853] Output: Guide information is sent to the terminal.

[0854] Operation: The server sends the generated guide information to the terminal.

[0855] Step 9:

[0856] The terminal displays the received guide information to the user and plays it back as audio if necessary.

[0857] Input: Guide information sent from the server.

[0858] Output: Guidance information displayed to the user and audio playback.

[0859] Operation: Guide information will be displayed on the user's smartphone and audio playback will begin.

[0860] Step 10:

[0861] The user enters feedback or a request for more information.

[0862] Input: User feedback or requests for additional information.

[0863] Output: Feedback and requests are stored in the device's memory.

[0864] Action: For example, a user types, "I'd like to know about other works by Monet."

[0865] Step 11:

[0866] The device sends a request for feedback or additional information to the server.

[0867] Input: User feedback or requests for additional information.

[0868] Output: Feedback or requests are sent to the server.

[0869] Operation: The device sends the user's request to the server.

[0870] Step 12:

[0871] Based on the feedback and requests for additional information received by the server, the generative AI model is again requested to generate guide information.

[0872] Input: User feedback or requests for additional information.

[0873] Output: The new prompt sent to the generative AI model.

[0874] What happens: The server again sends a request to the generative AI model.

[0875] Step 13:

[0876] The generative AI model generates new guide information and sends it to the server.

[0877] Input: New prompt text.

[0878] Output: The newly generated guide information.

[0879] How it works: A generative AI model generates guide information based on new user requests.

[0880] Step 14:

[0881] The server transmits the newly generated guide information to the terminal.

[0882] Input: The newly generated guide information.

[0883] Output: New guide information is sent to the terminal.

[0884] Operation: The server sends new guide information to the terminal.

[0885] Step 15:

[0886] The terminal displays the new guide information to the user and plays it aloud if necessary.

[0887] Input: New guide information.

[0888] Output: New guide information displayed to the user, and audio playback.

[0889] Operation: New guide information will be displayed on the user's smartphone, and audio playback will begin.

[0890] (Application example 1)

[0891] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0892] In industrial facilities, it is important for workers to work efficiently by providing appropriate work instructions in real time that are tailored to their individual skills and experience. However, current systems have difficulty providing customized work instructions based on the worker's current location and personal information, making it difficult to improve work efficiency. There is also a need for systems to receive feedback from workers and generate further work instructions appropriately.

[0893] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0894] In this invention, the server includes a means for acquiring location information of workers within an industrial facility, a means for collecting personal information such as the worker's skill level, experience, and work history, a means for sending a request to generate work instructions to a generative AI model based on the location information and personal information, a means for sending the work instructions generated by the generative AI model to a display device, and a means for presenting the work instructions received by the display device to the worker. This makes it possible to provide customized work instructions to workers in real time, thereby improving work efficiency.

[0895] The "location information acquisition means" is a means for acquiring the current location of a worker within an industrial facility.

[0896] "Means for collecting personal information" refers to means for collecting personal information such as the worker's technical level, experience, and work history.

[0897] The "generation request sending means" is a means for sending a request to generate work instructions to the generation AI model based on location information and personal information.

[0898] The "work instruction generation means" is a means for transmitting the work instructions generated by the generation AI model to the display device.

[0899] The "work instruction presenting means" is a means for presenting the work instructions received by the display device to the worker.

[0900] The "feedback receiving means" is a means for receiving feedback from the worker and requests for additional work information.

[0901] The "additional work instruction generation means" is a means for generating further work instructions based on feedback or requests for additional information.

[0902] This invention relates to a system that provides individual work instructions to workers in industrial facilities in real time. The system acquires the location information and personal information of the workers, generates optimal work instructions using a generative AI model, and presents them to the workers via a display device.

[0903] First, a GPS module is used to acquire the location information of the worker. The GPS module is used to identify the current location of the worker within the industrial facility. Next, a personal information collection means is used to send personal information such as the worker's skill level, experience, and work history to the server.

[0904] The server requests the generative AI model to generate work instructions based on the received location information and personal information. The generative AI model used in this process is stored on the cloud. The server also has the function of sending the generated work instructions to a display device. The display device could be, for example, smart glasses or a tablet terminal.

[0905] Not only can workers view work instructions through the display device, but they can also provide feedback or request additional information. These requests are sent back to the server, and the generative AI model responds by generating further work instructions and sending them to the display device. This two-way information exchange allows workers to work efficiently.

[0906] As a concrete example, suppose a worker moves to a new assembly area. The GPS module detects the worker's location and sends this location information to the server. At the same time, the worker's skill level and past assembly work experience are sent to the server via the personal information collection means. Based on this data, the server sends the following prompt to the generative AI model:

[0907] "The user's name is Yamada Taro and he has advanced experience. He is currently in the precision assembly area. Please generate the most suitable work instructions for this user."

[0908] Based on these prompts, the generative AI model generates work instructions, including optimal work procedures and precautions for precision assembly, and sends them to the server. The server then sends the received work instructions to a display device so that the worker can check them in real time. The worker can proceed with the work while checking the detailed procedures and safety precautions on the display device.

[0909] Furthermore, if a worker needs additional information, they can input a request via the display device. This request is sent to the server, and the generative AI model generates new information and sends it back to the display device. Through this process, the worker can obtain the necessary information in a timely manner and work efficiently.

[0910] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0911] Step 1:

[0912] The GPS module is used to obtain the current location of the worker. The input is the location data from the GPS module, and the output is the current coordinate information. The server receives this coordinate information.

[0913] Step 2:

[0914] Using a personal information collection means, personal information such as the worker's skill level, experience, and work history is collected. The input is the worker's profile data, and the output is a set of this personal information. The server receives this personal information.

[0915] Step 3:

[0916] Based on the location information and personal information received by the server, it sends a request to the generative AI model to generate work instructions. The input is a set of location information and personal information, and the output is a prompt sentence to be sent to the generative AI model. An example of a specific prompt sentence is, "The user's name is Mr. A, and he has advanced experience. He is currently in the precision assembly area. Please generate the most suitable work instructions for this user."

[0917] Step 4:

[0918] The generative AI model generates work instructions based on the received prompt. The input is the prompt, and the output is customized work instructions. The generated work instructions are sent to the server.

[0919] Step 5:

[0920] The server sends the work instructions received from the generative AI model to the display device. The input is the generated work instructions, and the output is the data sent to the display device.

[0921] Step 6:

[0922] The display device presents the received work instructions to the worker. The input is the work instructions sent from the server, and the output is the work instruction information displayed on the display device. For example, the instructions are displayed in text format on the screen of smart glasses or a tablet device, and are also played back as audio.

[0923] Step 7:

[0924] The worker inputs additional information and feedback through the display device. The input is the requested information from the worker, and the output is the data to be sent to the server. For example, a request such as "I would like to know more details about the current procedure" is input into the display device.

[0925] Step 8:

[0926] The server receives requests for additional information from the worker and sends the requests to the generative AI model. The input is the request for additional information, and the output is a new prompt sentence that is sent to the generative AI model.

[0927] Step 9:

[0928] The generative AI model generates more detailed work instructions based on the new prompt. The input is the new prompt, and the output is the new work instructions. The generated work instructions are sent to the server again.

[0929] Step 10:

[0930] The server retransmits the new work instructions received from the generative AI model to the display device. The input is the new work instructions, and the output is the data sent to the display device.

[0931] Step 11:

[0932] The display device then presents the new work instructions received to the worker. The input is the new work instructions sent from the server, and the output is the additional work instruction information displayed on the display device. This allows the worker to obtain the necessary additional information in real time and work efficiently.

[0933] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0934] The system of the present invention provides customized guide information to users at facilities such as art galleries, museums, and historical buildings, and also combines an emotion engine. The system is composed of the following components: a means for acquiring the user's location information, a means for collecting personal information such as the user's hobbies, interests, and age, a means for requesting the generation of guide information from a generative AI model, a means for sending the guide information generated by the generative AI model to a terminal, a means for presenting the guide information received by the terminal to the user, and an emotion engine that recognizes the user's emotions.

[0935] When a user enters a facility, they launch the application using a smartphone or dedicated terminal. First, the user sets up a profile within the application and enters personal information such as hobbies, interests, and age. For example, the user may provide information such as "I'm interested in art, and I particularly like impressionist paintings." This information is then sent to the server by the terminal.

[0936] The device then uses its GPS to determine the user's current location, which is also sent to the server. For example, the device may determine that the user is in the Impressionist paintings exhibit area of ​​a museum.

[0937] The server generates a query to the generative AI model based on the received personal information and location information, requesting the model to generate guide information. For example, the server generates a query such as, "A user who is interested in art and likes impressionist paintings is currently in the exhibition area. Please generate a relevant explanation." The generative AI model generates relevant guide information based on this query. For example, it generates information about the history and characteristics of impressionism, as well as famous works and artists.

[0938] The generated guide information is sent from the server to the device. The device displays the received guide information and plays it back as audio if necessary. For example, a detailed description of Monet's work may be displayed on the user's smartphone while an audio guide is played back at the same time.

[0939] Furthermore, the system includes an emotion engine that recognizes the user's emotions. The emotion engine recognizes emotions by analyzing the user's facial expressions and tone of voice. For example, when a user is viewing a Monet painting, if the emotion engine recognizes that the user is moved by the painting, this emotion data is sent to the server.

[0940] The server requests the generative AI model to customize the guide information based on the received emotional data. For example, if the user is moved, the server can request the generative AI model to provide a deeper artistic background or anecdotes that will amplify the emotion. The generative AI model generates more detailed information, which the server sends to the device. The device then presents the new guide information to the user.

[0941] Users can also use the application to provide feedback or request additional information, for example, by entering a request such as "I want to know more about other famous works by Monet." This information is then sent back to the server, where the generative AI model generates new guide information and sends it back to the device, which then presents this information to the user.

[0942] In this way, the system of the present invention can provide customized guide information in real time according to the user's individual interests and background, and can also use an emotion engine to provide detailed services based on the user's emotions.

[0943] The processing flow will be explained below.

[0944] Step 1:

[0945] The user launches a dedicated application on their smartphone or device. First, the user sets up their profile within the application and enters personal information such as hobbies, interests, and age. For example, the user may provide information such as "I'm interested in art" or "I like impressionism."

[0946] Step 2:

[0947] The device uses GPS to acquire the user's current location, which is then sent to a server. For example, the server may detect that the user is in an area displaying impressionist paintings.

[0948] Step 3:

[0949] The device sends the user's personal information (such as hobbies, interests, and age) and the acquired location information to the server. The server receives this information.

[0950] Step 4:

[0951] Based on the personal information and location information received by the server, a query is generated to the generative AI model requesting the generation of guide information. For example, a query such as "A user who is interested in art and likes impressionism is currently in the current exhibition area. Please generate a relevant explanation."

[0952] Step 5:

[0953] The generative AI model generates guide information based on queries from the server. Specifically, it generates information about the history and characteristics of Impressionism, as well as famous works and artists. For example, it includes an explanation that "Monet's works are characterized by their use of light and color."

[0954] Step 6:

[0955] The server receives the generated guide information and transmits it to the terminal, which receives the guide information.

[0956] Step 7:

[0957] The device displays the guide information it receives and plays it back as audio if necessary. For example, a detailed description of a Monet work could be displayed on the smartphone screen while an audio guide is played at the same time.

[0958] Step 8:

[0959] The user views the exhibits based on the guided information. If the user has further questions or wants more information, they can provide feedback or request additional information through the application. For example, they can enter a request such as, "I'd like to know more about Monet's other famous works."

[0960] Step 9:

[0961] The device sends the user's feedback and request information to the server, which then requests the AI ​​model to generate additional guide information.

[0962] Step 10:

[0963] The generative AI model generates new information, which the server sends to the device, which then presents the new guide information to the user.

[0964] Step 11:

[0965] The device's emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotions. For example, the device uses a camera and microphone to collect the user's reactions while viewing artwork.

[0966] Step 12:

[0967] The emotion engine recognizes the user's emotions and sends that information to the server. For example, it recognizes that the user is moved by a painting by Monet.

[0968] Step 13:

[0969] The server receives the emotion data and requests the generative AI model to customize the guide information based on that data. For example, the server requests the generative AI model to provide an episode that will further amplify the emotion of the user, since the user is moved by the emotion.

[0970] Step 14:

[0971] The generative AI model generates customized guide information, which the server sends to the device. The device then presents the new customized guide information to the user. For example, it provides touching episodes or background information on related works.

[0972] As described above, this system provides customized guide information in real time based on the user's individual interests and background, and further enriches the viewing experience by using an emotion engine to provide services based on the user's emotions.

[0973] Example 2

[0974] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0975] Conventional guide systems provide information based on the user's location and interests, but this is not sufficient to provide a personalized experience. Furthermore, they are unable to provide guide information that takes into account the user's emotions, making it difficult to increase satisfaction. Therefore, there is a demand for a system that can provide customized guide information in real time that is tailored to the user's individual interests and emotions.

[0976] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring location information of a user, means for collecting personal information such as the user's hobbies, interests, and age, means for requesting the generation of guide information from a generation AI model based on the location information and the personal information, means for transmitting the guide information generated by the generation AI model to a terminal, means for presenting the guide information received by the terminal to the user, means for recognizing the user's emotions, and means for customizing the guide information based on the emotion data. This makes it possible to provide customized guide information in real time that is tailored to the user's individual interests and emotions.

[0977] "User" refers to any individual or entity that uses the System.

[0978] "Location Information" means physical location data determined using GPS or other methods.

[0979] "Personal information" refers to information related to a specific individual, such as a user's hobbies, interests, age, etc.

[0980] "Generative AI model" refers to an artificial intelligence model that generates guide information and other data.

[0981] "Guide information" refers to explanations and information provided by a generative AI model based on the user's interests and location.

[0982] "Terminal" refers to a device used by a user, such as a smartphone or tablet.

[0983] "Emotional data" refers to data on a user's emotional state obtained by analyzing their facial expressions and tone of voice.

[0984] An "emotion engine" refers to a system that analyzes users' emotions and recognizes them as data.

[0985] The system of this invention provides customized guide information to users in facilities such as art galleries, museums, and historical buildings, and also combines an emotion engine. The system is mainly composed of three main components: a server, a terminal, and a user.

[0986] Hardware and software used

[0987] Devices: Smartphones, dedicated tablet devices

[0988] Server: Cloud server such as AWS or Google Cloud Platform

[0989] GPS function: Built-in to smartphones and tablets

[0990] Generative AI models: OpenAI GPT-4, Google BERT, etc.

[0991] Emotion engine: Affectiva SDK, Microsoft Azure Face API, etc.

[0992] Processing flow and specific examples

[0993] 1. User profile settings

[0994] Users enter the facility and launch the application on their smartphone or dedicated device. Within the application, they enter profile information such as their name, age, hobbies and interests. For example, they might enter information like, "I'm interested in art, and I particularly like impressionist paintings." This information is stored on the device and later sent to the server.

[0995] 2. Obtaining location information

[0996] The device uses its built-in GPS to determine its current location, which is then sent in encrypted form to a server, identifying, for example, the user as being in the impressionist paintings section of a museum.

[0997] 3. Guide information generation request

[0998] The server generates a query to request the generation of guide information from the generative AI model based on the user's profile information and location information. An example of a prompt sentence is "A user who is interested in art and likes impressionist paintings is in the current exhibition area, so please generate a relevant description."

[0999] 4. Guide information generation and transmission

[1000] The generative AI model receives and analyzes the prompt text and generates relevant guide information. For example, it generates information about the history and characteristics of Impressionism, as well as famous works and artists. This generated guide information is sent to the device via the server.

[1001] 5. Present guide information

[1002] The device displays the received guide information on its screen and plays it audibly as needed. For example, a detailed description of a Monet work may be displayed on the user's smartphone, and an audio guide may be played.

[1003] 6. Emotional Recognition

[1004] Using the device's camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice. The analysis results are sent to the server as emotion data. For example, it can recognize when a user is moved by a painting by Monet.

[1005] 7. Customizing guide information

[1006] Based on the emotion data, the server requests the generative AI model to generate new, more detailed guide information. For example, if a user is moved by something, it generates a request to add more in-depth artistic background or anecdotes. The newly generated information is then sent back to the device via the server and provided to the user.

[1007] 8. Feedback and Requests for Additional Information

[1008] Within the application, users can request feedback or additional information, for example, "I want to know more about other famous works by Monet." This request is sent to the server, where the generative AI model generates new guide information and sends it to the device, providing further information to the user.

[1009] As described above, the system of the present invention is capable of providing customized guide information in real time that is tailored to the individual interests and emotions of users, thereby increasing user satisfaction.

[1010] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1011] Step 1:

[1012] The user launches the application and enters their profile information.

[1013] Input: A user launches an application and enters profile information such as name, age, hobbies and interests.

[1014] How it works: The device stores the information the user enters within the application in a local database.

[1015] Output: User profile information is saved on the device.

[1016] Step 2:

[1017] The device acquires location information and sends it to the server.

[1018] Input: The device uses the GPS function to obtain the current location information.

[1019] Operation: The device encrypts the acquired location information and sends it to the server.

[1020] Output: Encrypted location information is sent to the server.

[1021] Step 3:

[1022] The server generates a request for generating guide information.

[1023] Input: The server receives the user's profile information and location information.

[1024] How it works: The server generates a prompt sentence to send to the generative AI model based on the received data. An example of a prompt sentence is, "A user who is interested in art and likes impressionist paintings is currently in the exhibition area, so please generate a relevant description."

[1025] Output: A prompt sentence is generated that is sent to the generative AI model.

[1026] Step 4:

[1027] A generative AI model generates guide information.

[1028] Input: A prompt sentence is sent to the generative AI model.

[1029] How it works: The generative AI model analyzes the prompt and generates relevant guide information, such as information about the history and characteristics of Impressionism, as well as famous works and artists.

[1030] Output: The generated guide information is returned to the server.

[1031] Step 5:

[1032] The server transmits the generated guide information to the terminal.

[1033] Input: The server receives guidance information from the generative AI model.

[1034] Operation: The server encrypts the guide information it receives and sends it to the user's terminal.

[1035] Output: Encrypted guide information is sent to the terminal.

[1036] Step 6:

[1037] The device displays or plays audible guide information.

[1038] Input: The device receives encrypted guide information from the server.

[1039] How it works: The device decrypts the encrypted information and displays it on the screen or plays it as an audio guide. For example, a detailed description of a Monet painting may be displayed on the user's smartphone, and an audio guide may be played.

[1040] Output: The guide information is displayed on the user's device and played back aloud.

[1041] Step 7:

[1042] The emotion engine recognizes the user's emotions.

[1043] Input: Capture the user's facial expressions and tone of voice using the device's camera and microphone.

[1044] How it works: The emotion engine analyzes the facial expressions and tone of voice it acquires to generate emotion data. This emotion data is sent to the server. For example, it recognizes when a user is moved by a painting by Monet.

[1045] Output: Emotion data is sent to the server.

[1046] Step 8:

[1047] The server customizes the guide information based on the emotion data.

[1048] Input: The server generates a new prompt sentence based on the emotion data received.

[1049] How it works: A new prompt is sent to the generative AI model, requesting it to generate more detailed guide information. For example, if a user is moved by something, a request is generated to add more in-depth artistic background or anecdotes. The newly generated information is then sent back to the device via the server.

[1050] Output: The customized guide information is sent to the device.

[1051] Step 9:

[1052] The user requests feedback or additional information.

[1053] Input: A user types feedback or a request for more information within an application. For example, "I want to know more about Monet's other famous works."

[1054] Operation: Request information is sent to the server, and the generative AI model generates new guide information and sends it to the device via the server.

[1055] Output: The new guide information is displayed on the user's device.

[1056] (Application example 2)

[1057] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1058] Conventional shopping guide systems have had difficulty providing customized information based on a user's location information or individual hobbies and interests. They also have difficulty recognizing a user's emotions and providing appropriate information accordingly. As a result, they have been unable to provide a satisfying shopping experience for users. The present invention aims to solve these problems and provide a personalized shopping guide for users.

[1059] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user location information, means for collecting personal information such as the user's hobbies, interests, and age, means for requesting the generation of guide information from the generative AI model based on the location information and personal information, means for transmitting the guide information generated by the generative AI model to the terminal, means for presenting the guide information received by the terminal to the user, means for recognizing emotions by analyzing the user's facial expressions and tone of voice, and means for requesting the generation of guide information from the generative AI model based on the emotion data. This makes it possible to provide a highly personalized shopping guide based on the user's individual hobbies, interests, location information, and emotions.

[1060] "User location information" is data that indicates the user's current geographical location.

[1061] "Hobbies and interests" is information related to activities or areas in which a user has a particular interest.

[1062] "Age" is data indicating the length of time calculated based on the user's date of birth.

[1063] "Personal information" refers to detailed data related to a user, such as hobbies, interests, age, etc.

[1064] A "generative AI model" is an artificial intelligence model that generates customized information based on input data.

[1065] "Guide information" is data output by the generative AI model that provides useful guidance and explanations to users.

[1066] "Terminal" refers to a computing device carried by a user, such as a smartphone or smart glasses.

[1067] "Facial expressions and tone of voice" refers to the user's facial expressions and speech patterns, and are data that provide clues to emotions.

[1068] "Emotion data" is data based on facial expressions and tone of voice that is analyzed to recognize the user's emotions.

[1069] "Customized" means that something is specifically tailored or modified to suit a particular user.

[1070] This invention builds a system that provides customized shopping guide information to users in physical stores such as shopping malls. The system acquires the user's location information, collects personal information such as hobbies, interests, and age, generates customized guide information using a generative AI model, and transmits it to the terminal. Another feature of the system is that it analyzes the user's facial expressions and tone of voice to recognize emotions and provides more appropriate guide information based on that emotional data.

[1071] Hardware and software configuration

[1072] Hardware

[1073] 1. Device: A device carried by a user, such as a smartphone or smart glasses.

[1074] 2. Server: A remote server that generates guide information and processes data.

[1075] software

[1076] 1. Location information acquisition software: Software that uses GPS functionality to determine the user's current location.

[1077] 2. Personal Information Collection Software: Software that allows users to set up a profile within an application and enter personal information such as hobbies, interests, age, etc.

[1078] 3. Generative AI model: An artificial intelligence model that generates customized guide information based on the user's location information and personal information.

[1079] 4. Emotion recognition software: Software that recognizes emotions by analyzing the user's facial expressions and tone of voice.

[1080] Data Flow and Processing

[1081] 1. Location information acquisition:

[1082] The server obtains location information from the user's device, which is precisely determined using GPS functionality.

[1083] 2. Collection of Personal Information:

[1084] The server collects personal information such as hobbies, interests, and age that users enter within the application.

[1085] 3. Guide information generation:

[1086] The server requests the generative AI model to generate guide information based on the collected location information and personal information, and creates a prompt sentence and passes it to the generative AI model.

[1087] example:

[1088] "The user is interested in the latest fashion and is currently located near 35.658581,139.745433 in the shopping mall. Please generate relevant guide information."

[1089] 4. Sending and Presenting Guide Information:

[1090] The server sends the guide information generated by the generative AI model to the device, which then displays the received guide information to the user and plays it back in audio format.

[1091] 5. Emotion Recognition and Customization:

[1092] The device analyzes the user's facial expressions and tone of voice to generate emotional data, which is then sent to the server, which then requests the AI ​​model to customize the guide information again.

[1093] Specific examples

[1094] A user enters a shopping mall and launches the application on their smartphone. They set up a profile and enter that they are interested in "latest fashion." The user's current location within the mall is identified using the GPS function, and the generative AI model generates customized guide information based on that information and personal information. The generated guide information is information about the latest fashion stores near the user's current location and is sent to the device. At that time, a prompt such as the following is sent to the generative AI model:

[1095] "The user is interested in the latest fashion and is currently located near 35.658581,139.745433 in the shopping mall. Please generate relevant guide information."

[1096] The guide information is displayed on the device and played back in audio format. In addition, the device analyzes the user's facial expressions and tone of voice and sends emotional data to the server. If the device recognizes that the user has an interested expression, the generative AI model generates more detailed information. This allows the device to provide highly personalized guide information to the user.

[1097] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1098] Step 1:

[1099] The server obtains the user's location information from the device. It uses the device's GPS function to determine the user's exact current location and sends that location information to the server. In this case, the input is the device's GPS data, and the output is the location information data received by the server.

[1100] Step 2:

[1101] The server collects personal information about users from their devices. It collects information such as hobbies, interests, and age entered by users within the application and stores this personal information in a database. The input is the profile information entered by the user, and the output is personal information data stored on the server.

[1102] Step 3:

[1103] The server requests the generative AI model to generate guide information based on the acquired location information and personal information. To do this, it creates a prompt sentence and sends it to the generative AI model. The input of the prompt sentence is the location information and personal information, and the output is the prompt sentence sent to the generative AI model.

[1104] Step 4:

[1105] The generative AI model generates guide information based on the sent prompt sentence. The input is the prompt sentence, and the output is customized guide information. The generated guide information is temporarily stored in a database.

[1106] Step 5:

[1107] The server sends the guide information generated by the generative AI model to the terminal. The terminal receives this guide information and displays it to the user or plays it back aloud. The input is the generated guide information, and the output is the guide information sent to the terminal.

[1108] Step 6:

[1109] The device generates emotion data by analyzing the user's facial expressions and tone of voice. It captures the user's facial expressions and voice using a camera and microphone, and analyzes them using emotion recognition software. The input is facial expression data and voice data, and the output is emotion data.

[1110] Step 7:

[1111] The server again requests the generative AI model to customize the guide information based on the emotion data sent from the device. It then creates a new prompt sentence based on the emotion data and sends it to the generative AI model. The input is the emotion data, and the output is the new prompt sentence.

[1112] Step 8:

[1113] The generative AI model generates more appropriate guide information based on the updated prompt. The input is the new prompt, and the output is further customized guide information. The generated guide information is again sent to the server and provided to the device.

[1114] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1115] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1116] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1117] [Fourth embodiment]

[1118] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1119] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1120] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1121] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1122] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1123] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1124] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1125] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1126] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1127] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1128] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1129] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1130] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1131] The system of the present invention provides customized guide information to users at facilities such as art galleries, museums, historical buildings, etc. This system is mainly composed of the following components: a means for acquiring the user's location information, a means for collecting personal information such as the user's hobbies, interests, and age, a means for requesting the generation of guide information from a generative AI model, a means for transmitting the generated guide information to a terminal, and a means for presenting the guide information received by the terminal to the user.

[1132] When a visitor enters an art gallery or museum, they launch an application using a smartphone or dedicated device. The user first enters personal information within the application. For example, the user provides information that they are interested in art and particularly like impressionist paintings. This information is then sent to the server by the device.

[1133] The device then uses its GPS to determine the user's current location (for example, if the user is in an area of ​​the museum where impressionist paintings are displayed), and this location information is also sent to the server.

[1134] The server requests the generative AI model to generate guide information based on the received personal information and location information. For example, a query such as "A user who is interested in art and likes impressionist paintings is in the current exhibition area. Please generate a relevant explanation." The generative AI model generates relevant guide information based on this query. For example, information about the main characteristics of impressionism, Monet's techniques and background, and other related artists is generated.

[1135] The generated guide information is sent from the server to the device. The device displays the received guide information and plays it back as audio if necessary. For example, a detailed description of an impressionist painting may be displayed on the user's smartphone while an audio guide is played back at the same time.

[1136] Additionally, users can use the application to provide feedback or request additional information. For example, if they want to know more about other works by Monet, they can enter additional questions. This information is sent back to the server, and the generative AI model generates new guide information and sends it to the device, which then presents this information to the user again.

[1137] In this way, the system of the present invention provides guide information in real time that is tailored to the individual interests and background of each user, thereby improving the viewing experience within the facility.

[1138] The processing flow will be explained below.

[1139] Step 1:

[1140] The user launches a dedicated application on their smartphone or device. First, the user sets up their profile within the application and enters personal information such as hobbies, interests, and age. For example, the user may provide information such as "I'm interested in art" or "I like impressionism."

[1141] Step 2:

[1142] The device uses GPS to acquire the user's current location, which is then sent to a server. For example, the server may detect that the user is in an area displaying impressionist paintings.

[1143] Step 3:

[1144] The device sends the user's personal information (such as hobbies, interests, and age) and the acquired location information to the server. The server receives this information.

[1145] Step 4:

[1146] Based on the personal information and location information received by the server, a query is generated to the generative AI model requesting the generation of guide information. For example, a query such as "A user who is interested in art and likes impressionism is currently in the current exhibition area. Please generate a relevant explanation."

[1147] Step 5:

[1148] The generative AI model generates guide information based on queries from the server. Specifically, it generates information about the history and characteristics of Impressionism, as well as famous works and artists. For example, it includes an explanation that "Monet's works are characterized by their use of light and color."

[1149] Step 6:

[1150] The server receives the generated guide information and transmits it to the terminal, which receives the guide information.

[1151] Step 7:

[1152] The device displays the guide information it receives and plays it back as audio if necessary. For example, a detailed description of a Monet work could be displayed on the smartphone screen while an audio guide is played at the same time.

[1153] Step 8:

[1154] Users can view the exhibits based on the guided information. If they have further questions or would like more information, they can provide feedback or request additional information through the application. For example, they can enter a request such as, "I'd like to know more about Monet's other famous works."

[1155] Step 9:

[1156] The device sends the user's feedback and request information to the server, which then requests the AI ​​model to generate additional guide information.

[1157] Step 10:

[1158] The generative AI model generates new information, which the server sends to the device, which then presents the new guide information to the user.

[1159] Through the above series of steps, this system can provide customized guide information tailored to each user's individual interests and needs in real time.

[1160] Example 1

[1161] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1162] Conventional facility guide systems could only provide general information to users, making it difficult to provide customized guide information tailored to individual interests in real time. Furthermore, they lacked a mechanism for automatically acquiring location information as users move around the facility and providing detailed guidance based on that information. Furthermore, they lacked the ability to flexibly respond to user feedback and requests for additional information and provide further customized information.

[1163] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1164] In this invention, the server includes means for acquiring user location information, means for collecting personal information such as the user's hobbies, interests, and age, means for generating a prompt sentence for requesting the generation of guide information from the generative AI model based on the location information and personal information, means for sending the generated prompt sentence to the generative AI model, means for sending the guide information generated by the generative AI model to a terminal, means for presenting the guide information received by the terminal to the user, means for collecting user feedback and requests for additional information, and means for again requesting the generation of guide information from the generative AI model based on the feedback and requests for additional information. This makes it possible to provide users with guide information customized to their individual interests in real time, and to provide information tailored to their movement within a facility and respond to requests for additional information.

[1165] "Location information" refers to data used to identify a user's current location.

[1166] "Personal Information" refers to information about a user's hobbies, interests, age, and other personal attributes.

[1167] A "generative AI model" refers to an artificial intelligence system that generates new information based on input data.

[1168] A "prompt sentence" refers to an input sentence that gives specific instructions to a generative AI model.

[1169] "Guide information" refers to information about explanations and commentary created by a generative AI model to be provided to users.

[1170] "Terminal" refers to a device that can be operated by a user (e.g., smartphone, tablet, dedicated device).

[1171] "Feedback" refers to the opinions and impressions that users provide to the system.

[1172] "Requesting additional information" refers to the user's request for more information from the system.

[1173] The system of the present invention provides customized guide information to users at facilities such as art galleries, museums, historical buildings, etc. This system mainly includes means for acquiring location information and personal information of the user and requesting the generation of guide information from a generative AI model based on the information.

[1174] When a user enters a facility, they launch the application using a smartphone or dedicated terminal. The user first enters personal information within the application. For example, the user provides information that they are interested in art and particularly like impressionist paintings. This information is then sent to the server by the terminal.

[1175] The device then uses its GPS to determine the user's current location (for example, if the user is in an area of ​​the museum where impressionist paintings are displayed), and this location information is also sent to the server.

[1176] The server requests the generative AI model to generate guide information based on the received personal information and location information. An example of a prompt sentence to use in this case is, "A user who is interested in art and likes impressionist paintings is in the current exhibition area. Please generate a relevant explanation." The generative AI model generates the appropriate guide information based on this prompt sentence. For example, it generates information about the main characteristics of impressionism, famous artists, techniques, and background.

[1177] The generated guide information is sent from the server to the device. The device displays the received guide information and plays it back as audio if necessary. For example, a detailed description of an impressionist painting may be displayed on the user's smartphone while an audio guide is played back at the same time.

[1178] Additionally, users can use the application to provide feedback or request additional information. For example, if they want to know more about other works by Monet, they can enter additional questions. This information is sent back to the server, and the generative AI model generates new guide information and sends it to the device. The device then presents this information to the user again.

[1179] In this way, the system of the present invention provides real-time guide information tailored to individual interests and backgrounds, improving the viewing experience within the facility. Specific hardware used includes smartphones and tablets with GPS functionality. Furthermore, it is desirable to use the latest AI algorithms based on natural language processing technology as the generative AI model.

[1180] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1181] Step 1:

[1182] A user enters a facility and launches an application.

[1183] Input: An application is started by a user action.

[1184] Output: None.

[1185] How it works: The user launches the facility application on their smartphone or dedicated device.

[1186] Step 2:

[1187] The user enters personal information within the application.

[1188] Input: Users enter personal information such as their interests, preferences, and age.

[1189] Output: The entered personal information is stored in the device's memory.

[1190] Action: For example, a user types, "I like impressionist paintings."

[1191] Step 3:

[1192] The device uses its GPS function to obtain the user's current location and transmits it to the server.

[1193] Input: Location information obtained by the device's GPS function.

[1194] Output: The location information is sent to the server.

[1195] Operation: For example, if the user is in the impressionist painting exhibition area, their location information is identified.

[1196] Step 4:

[1197] The device sends personal information to the server.

[1198] Input: Personal information entered by the user.

[1199] Output: Personal information is sent to the server.

[1200] How it works: For example, information such as "I'm interested in impressionist paintings" is sent to the server.

[1201] Step 5:

[1202] The server generates a prompt sentence to request the generative AI model to generate guide information based on location information and personal information.

[1203] Input: Location and personal information.

[1204] Output: The generated prompt statement.

[1205] Action: The server generates a prompt saying, "There is a user in the current exhibition area who is interested in art and likes impressionist paintings, so please generate a relevant description."

[1206] Step 6:

[1207] The server sends the generated prompt to the generative AI model.

[1208] Input: The generated prompt statement.

[1209] Output: The generated prompt sentence is sent to the generative AI model.

[1210] How it works: The server sends the generated prompt sentence to the generative AI model.

[1211] Step 7:

[1212] The generative AI model generates guide information and sends it to the server.

[1213] Input: The generated prompt statement.

[1214] Output: The generated guide information.

[1215] How it works: A generative AI model generates guide information about key features of impressionism, Monet's techniques, and more.

[1216] Step 8:

[1217] The server transmits the generated guide information to the terminal.

[1218] Input: Generated guide information.

[1219] Output: Guide information is sent to the terminal.

[1220] Operation: The server sends the generated guide information to the terminal.

[1221] Step 9:

[1222] The terminal displays the received guide information to the user and plays it back as audio if necessary.

[1223] Input: Guide information sent from the server.

[1224] Output: Guidance information displayed to the user and audio playback.

[1225] Operation: Guide information will be displayed on the user's smartphone and audio playback will begin.

[1226] Step 10:

[1227] The user enters feedback or a request for more information.

[1228] Input: User feedback or requests for additional information.

[1229] Output: Feedback and requests are stored in the device's memory.

[1230] Action: For example, a user types, "I'd like to know about other works by Monet."

[1231] Step 11:

[1232] The device sends a request for feedback or additional information to the server.

[1233] Input: User feedback or requests for additional information.

[1234] Output: Feedback or requests are sent to the server.

[1235] Operation: The device sends the user's request to the server.

[1236] Step 12:

[1237] Based on the feedback and requests for additional information received by the server, the generative AI model is again requested to generate guide information.

[1238] Input: User feedback or requests for additional information.

[1239] Output: The new prompt sent to the generative AI model.

[1240] What happens: The server again sends a request to the generative AI model.

[1241] Step 13:

[1242] The generative AI model generates new guide information and sends it to the server.

[1243] Input: New prompt text.

[1244] Output: The newly generated guide information.

[1245] How it works: A generative AI model generates guide information based on new user requests.

[1246] Step 14:

[1247] The server transmits the newly generated guide information to the terminal.

[1248] Input: The newly generated guide information.

[1249] Output: New guide information is sent to the terminal.

[1250] Operation: The server sends new guide information to the terminal.

[1251] Step 15:

[1252] The terminal displays the new guide information to the user and plays it aloud if necessary.

[1253] Input: New guide information.

[1254] Output: New guide information displayed to the user, and audio playback.

[1255] Operation: New guide information will be displayed on the user's smartphone, and audio playback will begin.

[1256] (Application example 1)

[1257] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1258] In industrial facilities, it is important for workers to work efficiently by providing appropriate work instructions in real time that are tailored to their individual skills and experience. However, current systems have difficulty providing customized work instructions based on the worker's current location and personal information, making it difficult to improve work efficiency. There is also a need for systems to receive feedback from workers and generate further work instructions appropriately.

[1259] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1260] In this invention, the server includes a means for acquiring location information of workers within an industrial facility, a means for collecting personal information such as the worker's skill level, experience, and work history, a means for sending a request to generate work instructions to a generative AI model based on the location information and personal information, a means for sending the work instructions generated by the generative AI model to a display device, and a means for presenting the work instructions received by the display device to the worker. This makes it possible to provide customized work instructions to workers in real time, thereby improving work efficiency.

[1261] The "location information acquisition means" is a means for acquiring the current location of a worker within an industrial facility.

[1262] "Means for collecting personal information" refers to means for collecting personal information such as the worker's technical level, experience, and work history.

[1263] The "generation request sending means" is a means for sending a request to generate work instructions to the generation AI model based on location information and personal information.

[1264] The "work instruction generation means" is a means for transmitting the work instructions generated by the generation AI model to the display device.

[1265] The "work instruction presenting means" is a means for presenting the work instructions received by the display device to the worker.

[1266] The "feedback receiving means" is a means for receiving feedback from the worker and requests for additional work information.

[1267] The "additional work instruction generation means" is a means for generating further work instructions based on feedback or requests for additional information.

[1268] This invention relates to a system that provides individual work instructions to workers in industrial facilities in real time. The system acquires the location information and personal information of the workers, generates optimal work instructions using a generative AI model, and presents them to the workers via a display device.

[1269] First, a GPS module is used to acquire the location information of the worker. The GPS module is used to identify the current location of the worker within the industrial facility. Next, a personal information collection means is used to send personal information such as the worker's skill level, experience, and work history to the server.

[1270] The server requests the generative AI model to generate work instructions based on the received location information and personal information. The generative AI model used in this process is stored on the cloud. The server also has the function of sending the generated work instructions to a display device. The display device could be, for example, smart glasses or a tablet terminal.

[1271] Not only can workers view work instructions through the display device, but they can also provide feedback or request additional information. These requests are sent back to the server, and the generative AI model responds by generating further work instructions and sending them to the display device. This two-way information exchange allows workers to work efficiently.

[1272] As a concrete example, suppose a worker moves to a new assembly area. The GPS module detects the worker's location and sends this location information to the server. At the same time, the worker's skill level and past assembly work experience are sent to the server via the personal information collection means. Based on this data, the server sends the following prompt to the generative AI model:

[1273] "The user's name is Yamada Taro and he has advanced experience. He is currently in the precision assembly area. Please generate the most suitable work instructions for this user."

[1274] Based on these prompts, the generative AI model generates work instructions, including optimal work procedures and precautions for precision assembly, and sends them to the server. The server then sends the received work instructions to a display device so that the worker can check them in real time. The worker can proceed with the work while checking the detailed procedures and safety precautions on the display device.

[1275] Furthermore, if a worker needs additional information, they can input a request via the display device. This request is sent to the server, and the generative AI model generates new information and sends it back to the display device. Through this process, the worker can obtain the necessary information in a timely manner and work efficiently.

[1276] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1277] Step 1:

[1278] The GPS module is used to obtain the current location of the worker. The input is the location data from the GPS module, and the output is the current coordinate information. The server receives this coordinate information.

[1279] Step 2:

[1280] Using a personal information collection means, personal information such as the worker's skill level, experience, and work history is collected. The input is the worker's profile data, and the output is a set of this personal information. The server receives this personal information.

[1281] Step 3:

[1282] Based on the location information and personal information received by the server, it sends a request to the generative AI model to generate work instructions. The input is a set of location information and personal information, and the output is a prompt sentence to be sent to the generative AI model. An example of a specific prompt sentence is, "The user's name is Mr. A, and he has advanced experience. He is currently in the precision assembly area. Please generate the most suitable work instructions for this user."

[1283] Step 4:

[1284] The generative AI model generates work instructions based on the received prompt. The input is the prompt, and the output is customized work instructions. The generated work instructions are sent to the server.

[1285] Step 5:

[1286] The server sends the work instructions received from the generative AI model to the display device. The input is the generated work instructions, and the output is the data sent to the display device.

[1287] Step 6:

[1288] The display device presents the received work instructions to the worker. The input is the work instructions sent from the server, and the output is the work instruction information displayed on the display device. For example, the instructions are displayed in text format on the screen of smart glasses or a tablet device, and are also played back as audio.

[1289] Step 7:

[1290] The worker inputs additional information and feedback through the display device. The input is the requested information from the worker, and the output is the data to be sent to the server. For example, a request such as "I would like to know more details about the current procedure" is input into the display device.

[1291] Step 8:

[1292] The server receives requests for additional information from the worker and sends the requests to the generative AI model. The input is the request for additional information, and the output is a new prompt sentence that is sent to the generative AI model.

[1293] Step 9:

[1294] The generative AI model generates more detailed work instructions based on the new prompt. The input is the new prompt, and the output is the new work instructions. The generated work instructions are sent to the server again.

[1295] Step 10:

[1296] The server retransmits the new work instructions received from the generative AI model to the display device. The input is the new work instructions, and the output is the data sent to the display device.

[1297] Step 11:

[1298] The display device then presents the new work instructions received to the worker. The input is the new work instructions sent from the server, and the output is the additional work instruction information displayed on the display device. This allows the worker to obtain the necessary additional information in real time and work efficiently.

[1299] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1300] The system of the present invention provides customized guide information to users at facilities such as art galleries, museums, and historical buildings, and also combines an emotion engine. The system is composed of the following components: a means for acquiring the user's location information, a means for collecting personal information such as the user's hobbies, interests, and age, a means for requesting the generation of guide information from a generative AI model, a means for sending the guide information generated by the generative AI model to a terminal, a means for presenting the guide information received by the terminal to the user, and an emotion engine that recognizes the user's emotions.

[1301] When a user enters a facility, they launch the application using a smartphone or dedicated terminal. First, the user sets up a profile within the application and enters personal information such as hobbies, interests, and age. For example, the user may provide information such as "I'm interested in art, and I particularly like impressionist paintings." This information is then sent to the server by the terminal.

[1302] The device then uses its GPS to determine the user's current location, which is also sent to the server. For example, the device may determine that the user is in the Impressionist paintings exhibit area of ​​a museum.

[1303] The server generates a query to the generative AI model based on the received personal information and location information, requesting the model to generate guide information. For example, the server generates a query such as, "A user who is interested in art and likes impressionist paintings is currently in the exhibition area. Please generate a relevant explanation." The generative AI model generates relevant guide information based on this query. For example, it generates information about the history and characteristics of impressionism, as well as famous works and artists.

[1304] The generated guide information is sent from the server to the device. The device displays the received guide information and plays it back as audio if necessary. For example, a detailed description of Monet's work may be displayed on the user's smartphone while an audio guide is played back at the same time.

[1305] Furthermore, the system includes an emotion engine that recognizes the user's emotions. The emotion engine recognizes emotions by analyzing the user's facial expressions and tone of voice. For example, when a user is viewing a Monet painting, if the emotion engine recognizes that the user is moved by the painting, this emotion data is sent to the server.

[1306] The server requests the generative AI model to customize the guide information based on the received emotional data. For example, if the user is moved, the server can request the generative AI model to provide a deeper artistic background or anecdotes that will amplify the emotion. The generative AI model generates more detailed information, which the server sends to the device. The device then presents the new guide information to the user.

[1307] Users can also use the application to provide feedback or request additional information, for example, by entering a request such as "I want to know more about other famous works by Monet." This information is then sent back to the server, where the generative AI model generates new guide information and sends it back to the device, which then presents this information to the user.

[1308] In this way, the system of the present invention can provide customized guide information in real time according to the user's individual interests and background, and can also use an emotion engine to provide detailed services based on the user's emotions.

[1309] The processing flow will be explained below.

[1310] Step 1:

[1311] The user launches a dedicated application on their smartphone or device. First, the user sets up their profile within the application and enters personal information such as hobbies, interests, and age. For example, the user may provide information such as "I'm interested in art" or "I like impressionism."

[1312] Step 2:

[1313] The device uses GPS to acquire the user's current location, which is then sent to a server. For example, the server may detect that the user is in an area displaying impressionist paintings.

[1314] Step 3:

[1315] The device sends the user's personal information (such as hobbies, interests, and age) and the acquired location information to the server. The server receives this information.

[1316] Step 4:

[1317] Based on the personal information and location information received by the server, a query is generated to the generative AI model requesting the generation of guide information. For example, a query such as "A user who is interested in art and likes impressionism is currently in the current exhibition area. Please generate a relevant explanation."

[1318] Step 5:

[1319] The generative AI model generates guide information based on queries from the server. Specifically, it generates information about the history and characteristics of Impressionism, as well as famous works and artists. For example, it includes an explanation that "Monet's works are characterized by their use of light and color."

[1320] Step 6:

[1321] The server receives the generated guide information and transmits it to the terminal, which receives the guide information.

[1322] Step 7:

[1323] The device displays the guide information it receives and plays it back as audio if necessary. For example, a detailed description of a Monet work could be displayed on the smartphone screen while an audio guide is played at the same time.

[1324] Step 8:

[1325] The user views the exhibits based on the guided information. If the user has further questions or wants more information, they can provide feedback or request additional information through the application. For example, they can enter a request such as, "I'd like to know more about Monet's other famous works."

[1326] Step 9:

[1327] The device sends the user's feedback and request information to the server, which then requests the AI ​​model to generate additional guide information.

[1328] Step 10:

[1329] The generative AI model generates new information, which the server sends to the device, which then presents the new guide information to the user.

[1330] Step 11:

[1331] The device's emotion engine analyzes the user's facial expressions and tone of voice to recognize their emotions. For example, the device uses a camera and microphone to collect the user's reactions while viewing artwork.

[1332] Step 12:

[1333] The emotion engine recognizes the user's emotions and sends that information to the server. For example, it recognizes that the user is moved by a painting by Monet.

[1334] Step 13:

[1335] The server receives the emotion data and requests the generative AI model to customize the guide information based on that data. For example, the server requests the generative AI model to provide an episode that will further amplify the emotion of the user, since the user is moved by the emotion.

[1336] Step 14:

[1337] The generative AI model generates customized guide information, which the server sends to the device. The device then presents the new customized guide information to the user. For example, it provides touching episodes or background information on related works.

[1338] As described above, this system provides customized guide information in real time based on the user's individual interests and background, and further enriches the viewing experience by using an emotion engine to provide services based on the user's emotions.

[1339] Example 2

[1340] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1341] Conventional guide systems provide information based on the user's location and interests, but this is not sufficient to provide a personalized experience. Furthermore, they are unable to provide guide information that takes into account the user's emotions, making it difficult to increase satisfaction. Therefore, there is a demand for a system that can provide customized guide information in real time that is tailored to the user's individual interests and emotions.

[1342] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for acquiring location information of a user, means for collecting personal information such as the user's hobbies, interests, and age, means for requesting the generation of guide information from a generation AI model based on the location information and the personal information, means for transmitting the guide information generated by the generation AI model to a terminal, means for presenting the guide information received by the terminal to the user, means for recognizing the user's emotions, and means for customizing the guide information based on the emotion data. This makes it possible to provide customized guide information in real time that is tailored to the user's individual interests and emotions.

[1343] "User" refers to any individual or entity that uses the System.

[1344] "Location Information" means physical location data determined using GPS or other methods.

[1345] "Personal information" refers to information related to a specific individual, such as a user's hobbies, interests, age, etc.

[1346] "Generative AI model" refers to an artificial intelligence model that generates guide information and other data.

[1347] "Guide information" refers to explanations and information provided by a generative AI model based on the user's interests and location.

[1348] "Terminal" refers to a device used by a user, such as a smartphone or tablet.

[1349] "Emotional data" refers to data on a user's emotional state obtained by analyzing their facial expressions and tone of voice.

[1350] An "emotion engine" refers to a system that analyzes users' emotions and recognizes them as data.

[1351] The system of this invention provides customized guide information to users in facilities such as art galleries, museums, and historical buildings, and also combines an emotion engine. The system is mainly composed of three main components: a server, a terminal, and a user.

[1352] Hardware and software used

[1353] Devices: Smartphones, dedicated tablet devices

[1354] Server: Cloud server such as AWS or Google Cloud Platform

[1355] GPS function: Built-in to smartphones and tablets

[1356] Generative AI models: OpenAI GPT-4, Google BERT, etc.

[1357] Emotion engine: Affectiva SDK, Microsoft Azure Face API, etc.

[1358] Processing flow and specific examples

[1359] 1. User profile settings

[1360] Users enter the facility and launch the application on their smartphone or dedicated device. Within the application, they enter profile information such as their name, age, hobbies and interests. For example, they might enter information like, "I'm interested in art, and I particularly like impressionist paintings." This information is stored on the device and later sent to the server.

[1361] 2. Obtaining location information

[1362] The device uses its built-in GPS to determine its current location, which is then sent in encrypted form to a server, identifying, for example, the user as being in the impressionist paintings section of a museum.

[1363] 3. Guide information generation request

[1364] The server generates a query to request the generation of guide information from the generative AI model based on the user's profile information and location information. An example of a prompt sentence is "A user who is interested in art and likes impressionist paintings is in the current exhibition area, so please generate a relevant description."

[1365] 4. Guide information generation and transmission

[1366] The generative AI model receives and analyzes the prompt text and generates relevant guide information. For example, it generates information about the history and characteristics of Impressionism, as well as famous works and artists. This generated guide information is sent to the device via the server.

[1367] 5. Present guide information

[1368] The device displays the received guide information on its screen and plays it audibly as needed. For example, a detailed description of a Monet work may be displayed on the user's smartphone, and an audio guide may be played.

[1369] 6. Emotional Recognition

[1370] Using the device's camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice. The analysis results are sent to the server as emotion data. For example, it can recognize when a user is moved by a painting by Monet.

[1371] 7. Customizing guide information

[1372] Based on the emotion data, the server requests the generative AI model to generate new, more detailed guide information. For example, if a user is moved by something, it generates a request to add more in-depth artistic background or anecdotes. The newly generated information is then sent back to the device via the server and provided to the user.

[1373] 8. Feedback and Requests for Additional Information

[1374] Within the application, users can request feedback or additional information, for example, "I want to know more about other famous works by Monet." This request is sent to the server, where the generative AI model generates new guide information and sends it to the device, providing further information to the user.

[1375] As described above, the system of the present invention is capable of providing customized guide information in real time that is tailored to the individual interests and emotions of users, thereby increasing user satisfaction.

[1376] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1377] Step 1:

[1378] The user launches the application and enters their profile information.

[1379] Input: A user launches an application and enters profile information such as name, age, hobbies and interests.

[1380] How it works: The device stores the information the user enters within the application in a local database.

[1381] Output: User profile information is saved on the device.

[1382] Step 2:

[1383] The device acquires location information and sends it to the server.

[1384] Input: The device uses the GPS function to obtain the current location information.

[1385] Operation: The device encrypts the acquired location information and sends it to the server.

[1386] Output: Encrypted location information is sent to the server.

[1387] Step 3:

[1388] The server generates a request for generating guide information.

[1389] Input: The server receives the user's profile information and location information.

[1390] How it works: The server generates a prompt sentence to send to the generative AI model based on the received data. An example of a prompt sentence is, "A user who is interested in art and likes impressionist paintings is currently in the exhibition area, so please generate a relevant description."

[1391] Output: A prompt sentence is generated that is sent to the generative AI model.

[1392] Step 4:

[1393] A generative AI model generates guide information.

[1394] Input: A prompt sentence is sent to the generative AI model.

[1395] How it works: The generative AI model analyzes the prompt and generates relevant guide information, such as information about the history and characteristics of Impressionism, as well as famous works and artists.

[1396] Output: The generated guide information is returned to the server.

[1397] Step 5:

[1398] The server transmits the generated guide information to the terminal.

[1399] Input: The server receives guidance information from the generative AI model.

[1400] Operation: The server encrypts the guide information it receives and sends it to the user's terminal.

[1401] Output: Encrypted guide information is sent to the terminal.

[1402] Step 6:

[1403] The device displays or plays audible guide information.

[1404] Input: The device receives encrypted guide information from the server.

[1405] How it works: The device decrypts the encrypted information and displays it on the screen or plays it as an audio guide. For example, a detailed description of a Monet painting may be displayed on the user's smartphone, and an audio guide may be played.

[1406] Output: The guide information is displayed on the user's device and played back aloud.

[1407] Step 7:

[1408] The emotion engine recognizes the user's emotions.

[1409] Input: Capture the user's facial expressions and tone of voice using the device's camera and microphone.

[1410] How it works: The emotion engine analyzes the facial expressions and tone of voice it acquires to generate emotion data. This emotion data is sent to the server. For example, it recognizes when a user is moved by a painting by Monet.

[1411] Output: Emotion data is sent to the server.

[1412] Step 8:

[1413] The server customizes the guide information based on the emotion data.

[1414] Input: The server generates a new prompt sentence based on the emotion data received.

[1415] How it works: A new prompt is sent to the generative AI model, requesting it to generate more detailed guide information. For example, if a user is moved by something, a request is generated to add more in-depth artistic background or anecdotes. The newly generated information is then sent back to the device via the server.

[1416] Output: The customized guide information is sent to the device.

[1417] Step 9:

[1418] The user requests feedback or additional information.

[1419] Input: A user types feedback or a request for more information within an application. For example, "I want to know more about Monet's other famous works."

[1420] Operation: Request information is sent to the server, and the generative AI model generates new guide information and sends it to the device via the server.

[1421] Output: The new guide information is displayed on the user's device.

[1422] (Application example 2)

[1423] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1424] Conventional shopping guide systems have had difficulty providing customized information based on a user's location information or individual hobbies and interests. They also have difficulty recognizing a user's emotions and providing appropriate information accordingly. As a result, they have been unable to provide a satisfying shopping experience for users. The present invention aims to solve these problems and provide a personalized shopping guide for users.

[1425] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user location information, means for collecting personal information such as the user's hobbies, interests, and age, means for requesting the generation of guide information from the generative AI model based on the location information and personal information, means for transmitting the guide information generated by the generative AI model to the terminal, means for presenting the guide information received by the terminal to the user, means for recognizing emotions by analyzing the user's facial expressions and tone of voice, and means for requesting the generation of guide information from the generative AI model based on the emotion data. This makes it possible to provide a highly personalized shopping guide based on the user's individual hobbies, interests, location information, and emotions.

[1426] "User location information" is data that indicates the user's current geographical location.

[1427] "Hobbies and interests" is information related to activities or areas in which a user has a particular interest.

[1428] "Age" is data indicating the length of time calculated based on the user's date of birth.

[1429] "Personal information" refers to detailed data related to a user, such as hobbies, interests, age, etc.

[1430] A "generative AI model" is an artificial intelligence model that generates customized information based on input data.

[1431] "Guide information" is data output by the generative AI model that provides useful guidance and explanations to users.

[1432] "Terminal" refers to a computing device carried by a user, such as a smartphone or smart glasses.

[1433] "Facial expressions and tone of voice" refers to the user's facial expressions and speech patterns, and are data that provide clues to emotions.

[1434] "Emotion data" is data based on facial expressions and tone of voice that is analyzed to recognize the user's emotions.

[1435] "Customized" means that something is specifically tailored or modified to suit a particular user.

[1436] This invention builds a system that provides customized shopping guide information to users in physical stores such as shopping malls. The system acquires the user's location information, collects personal information such as hobbies, interests, and age, generates customized guide information using a generative AI model, and transmits it to the terminal. Another feature of the system is that it analyzes the user's facial expressions and tone of voice to recognize emotions and provides more appropriate guide information based on that emotional data.

[1437] Hardware and software configuration

[1438] Hardware

[1439] 1. Device: A device carried by a user, such as a smartphone or smart glasses.

[1440] 2. Server: A remote server that generates guide information and processes data.

[1441] software

[1442] 1. Location information acquisition software: Software that uses GPS functionality to determine the user's current location.

[1443] 2. Personal Information Collection Software: Software that allows users to set up a profile within an application and enter personal information such as hobbies, interests, age, etc.

[1444] 3. Generative AI model: An artificial intelligence model that generates customized guide information based on the user's location information and personal information.

[1445] 4. Emotion recognition software: Software that recognizes emotions by analyzing the user's facial expressions and tone of voice.

[1446] Data Flow and Processing

[1447] 1. Location information acquisition:

[1448] The server obtains location information from the user's device, which is precisely determined using GPS functionality.

[1449] 2. Collection of Personal Information:

[1450] The server collects personal information such as hobbies, interests, and age that users enter within the application.

[1451] 3. Guide information generation:

[1452] The server requests the generative AI model to generate guide information based on the collected location information and personal information, and creates a prompt sentence and passes it to the generative AI model.

[1453] example:

[1454] "The user is interested in the latest fashion and is currently located near 35.658581,139.745433 in the shopping mall. Please generate relevant guide information."

[1455] 4. Sending and Presenting Guide Information:

[1456] The server sends the guide information generated by the generative AI model to the device, which then displays the received guide information to the user and plays it back in audio format.

[1457] 5. Emotion Recognition and Customization:

[1458] The device analyzes the user's facial expressions and tone of voice to generate emotional data, which is then sent to the server, which then requests the AI ​​model to customize the guide information again.

[1459] Specific examples

[1460] A user enters a shopping mall and launches the application on their smartphone. They set up a profile and enter that they are interested in "latest fashion." The user's current location within the mall is identified using the GPS function, and the generative AI model generates customized guide information based on that information and personal information. The generated guide information is information about the latest fashion stores near the user's current location and is sent to the device. At that time, a prompt such as the following is sent to the generative AI model:

[1461] "The user is interested in the latest fashion and is currently located near 35.658581,139.745433 in the shopping mall. Please generate relevant guide information."

[1462] The guide information is displayed on the device and played back in audio format. In addition, the device analyzes the user's facial expressions and tone of voice and sends emotional data to the server. If the device recognizes that the user has an interested expression, the generative AI model generates more detailed information. This allows the device to provide highly personalized guide information to the user.

[1463] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1464] Step 1:

[1465] The server obtains the user's location information from the device. It uses the device's GPS function to determine the user's exact current location and sends that location information to the server. In this case, the input is the device's GPS data, and the output is the location information data received by the server.

[1466] Step 2:

[1467] The server collects personal information about users from their devices. It collects information such as hobbies, interests, and age entered by users within the application and stores this personal information in a database. The input is the profile information entered by the user, and the output is personal information data stored on the server.

[1468] Step 3:

[1469] The server requests the generative AI model to generate guide information based on the acquired location information and personal information. To do this, it creates a prompt sentence and sends it to the generative AI model. The input of the prompt sentence is the location information and personal information, and the output is the prompt sentence sent to the generative AI model.

[1470] Step 4:

[1471] The generative AI model generates guide information based on the sent prompt sentence. The input is the prompt sentence, and the output is customized guide information. The generated guide information is temporarily stored in a database.

[1472] Step 5:

[1473] The server sends the guide information generated by the generative AI model to the terminal. The terminal receives this guide information and displays it to the user or plays it back aloud. The input is the generated guide information, and the output is the guide information sent to the terminal.

[1474] Step 6:

[1475] The device generates emotion data by analyzing the user's facial expressions and tone of voice. It captures the user's facial expressions and voice using a camera and microphone, and analyzes them using emotion recognition software. The input is facial expression data and voice data, and the output is emotion data.

[1476] Step 7:

[1477] The server again requests the generative AI model to customize the guide information based on the emotion data sent from the device. It then creates a new prompt sentence based on the emotion data and sends it to the generative AI model. The input is the emotion data, and the output is the new prompt sentence.

[1478] Step 8:

[1479] The generative AI model generates more appropriate guide information based on the updated prompt. The input is the new prompt, and the output is further customized guide information. The generated guide information is again sent to the server and provided to the device.

[1480] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1481] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1482] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1483] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1484] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1485] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1486] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1487] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1488] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1489] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1490] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1491] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1492] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1493] 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.

[1494] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1495] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1496] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1497] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1498] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1499] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1500] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1501] The following is further disclosed regarding the above embodiment.

[1502] (Claim 1)

[1503] A means for acquiring user location information;

[1504] How we collect personal information such as users' hobbies, interests, and age,

[1505] A means for requesting a generation AI model to generate guide information based on the location information and personal information;

[1506] A means for transmitting guide information generated by the generation AI model to a terminal;

[1507] means for presenting the guide information received by the terminal to a user;

[1508] A system including:

[1509] (Claim 2)

[1510] means for displaying the guide information in text format;

[1511] means for reproducing the guide information in audio format;

[1512] 10. The system of claim 1, comprising:

[1513] (Claim 3)

[1514] means for receiving feedback and requests for additional information from said user;

[1515] means for generating further guide information based on said feedback and requests for additional information;

[1516] 10. The system of claim 1, comprising:

[1517] "Example 1"

[1518] (Claim 1)

[1519] A means for acquiring user location information;

[1520] How we collect personal information such as users' hobbies, interests, and age,

[1521] A means for generating a prompt sentence for requesting the generation of guide information from the generation AI model based on the location information and personal information;

[1522] a means for transmitting the generated prompt sentence to a generative AI model;

[1523] A means for transmitting guide information generated by the generation AI model to a terminal;

[1524] means for presenting the guide information received by the terminal to a user;

[1525] a means of collecting user feedback and requests for additional information;

[1526] A means for requesting the generation AI model to generate guide information again based on the feedback and request for additional information;

[1527] A system including:

[1528] (Claim 2)

[1529] means for displaying the guide information in text format;

[1530] means for reproducing the guide information in audio format;

[1531] 10. The system of claim 1, comprising:

[1532] (Claim 3)

[1533] 10. The system of claim 1, further comprising means for generating further guide information based on said user's feedback and requests for additional information.

[1534] "Application Example 1"

[1535] (Claim 1)

[1536] A means for acquiring user location information;

[1537] How we collect personal information such as users' hobbies, interests, and age,

[1538] A means for requesting a generation AI model to generate guide information based on the location information and personal information;

[1539] A means for transmitting guide information generated by the generation AI model to a terminal;

[1540] means for presenting the guide information received by the terminal to a user;

[1541] a means for obtaining location information of a worker within an industrial facility;

[1542] A means of collecting personal information such as the worker's technical level, experience, and work history;

[1543] A means for sending a request to generate work instructions to a generative AI model based on the location information and personal information;

[1544] means for transmitting the work instructions generated by the generative AI model to a display device;

[1545] The system further includes means for presenting the work instructions received by the display device to a worker.

[1546] (Claim 2)

[1547] means for displaying the guide information in text format;

[1548] means for reproducing the guide information in audio format;

[1549] means for displaying the work instructions in text format;

[1550] 10. The system of claim 1, further comprising means for reproducing the work instructions in audio form.

[1551] (Claim 3)

[1552] means for receiving feedback and requests for additional information from said user;

[1553] means for generating further guide information based on said feedback and requests for additional information;

[1554] means for receiving feedback and requests for additional work information from the worker;

[1555] 10. The system of claim 1, further comprising means for generating further work instructions based on said feedback and requests for additional information.

[1556] "Example 2: Combining Emotion Engines"

[1557] (Claim 1)

[1558] A means for acquiring user location information;

[1559] How we collect personal information such as users' hobbies, interests, and age,

[1560] A means for requesting a generation AI model to generate guide information based on the location information and personal information;

[1561] A means for transmitting guide information generated by the generation AI model to a terminal;

[1562] means for presenting the guide information received by the terminal to a user;

[1563] a means for recognizing a user's emotion;

[1564] means for customizing guide information based on the emotion data;

[1565] A system including:

[1566] (Claim 2)

[1567] means for displaying the guide information in text format;

[1568] means for reproducing the guide information in audio format;

[1569] 10. The system of claim 1, comprising:

[1570] (Claim 3)

[1571] means for receiving feedback and requests for additional information from said user;

[1572] means for generating further guide information based on said feedback and requests for additional information;

[1573] 10. The system of claim 1, comprising:

[1574] "Application example 2 when combining emotion engines"

[1575] (Claim 1)

[1576] A means for acquiring user location information;

[1577] How we collect personal information such as users' hobbies, interests, and age,

[1578] A means for requesting a generation AI model to generate guide information based on the location information and personal information;

[1579] A means for transmitting guide information generated by the generation AI model to a terminal;

[1580] means for presenting the guide information received by the terminal to a user;

[1581] A means of recognizing emotions by analyzing the user's facial expressions and tone of voice;

[1582] A means for requesting customization of guide information from a generative AI model based on the emotion data;

[1583] A system including:

[1584] (Claim 2)

[1585] means for displaying the guide information in text format;

[1586] means for reproducing the guide information in audio format;

[1587] 10. The system of claim 1, comprising:

[1588] (Claim 3)

[1589] means for receiving feedback and requests for additional information from said user;

[1590] means for generating further guide information based on said feedback and requests for additional information;

[1591] 10. The system of claim 1, comprising: [Explanation of symbols]

[1592] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for acquiring user location information; How we collect personal information such as users' hobbies, interests, and age, A means for requesting a generation AI model to generate guide information based on the location information and personal information; A means for transmitting guide information generated by the generation AI model to a terminal; means for presenting the guide information received by the terminal to a user; A system including:

2. means for displaying the guide information in text format; means for reproducing the guide information in audio format; The system of claim 1 , comprising:

3. means for receiving feedback and requests for additional information from said user; means for generating further guide information based on said feedback and requests for additional information; The system of claim 1 , comprising:

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