System

Abstract

A system is provided.SOLUTION: A system, comprising: means for obtaining location information of an area where a user is currently walking; means for sending the location information to a server; means for generating recommendation information based on the location information; and means for providing the recommendation information to the user as voice guidance.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] Conventional map services have limited ways for users to obtain detailed information about the area around their current location, making it difficult for users to easily obtain local recommendations, real-time weather information, and discount information. Searches for restaurants and other places are also not based on specific criteria, making them inconvenient. For this reason, there is a demand for real-time information provision tailored to the type of information and services users need around their current location. [Means for solving the problem]

[0005] To solve this problem, the present invention provides the following means. First, a means is provided for the user to acquire current location information. This location information is transmitted from the terminal to a server. Next, the server generates recommendation information for the surrounding area based on the received location information. This recommendation information is provided to the user as voice guidance. Also, a means is provided for the user to input a search query using free words, and the server generates restaurant information based on this search query. Furthermore, by providing this restaurant information to the user and providing a means for making a reservation at a specific restaurant, user convenience is improved. In particular, the system is characterized in that the recommendation information includes information related to the area around the user's current location, and the voice guidance is provided in real time based on the user's current location.

[0006] "User" refers to an individual who uses the system to access location information, recommendations, and search functions.

[0007] "Location information" is data that indicates a user's current geographic location, typically expressed in the form of latitude and longitude.

[0008] A "server" refers to a computer system that receives location information and search queries sent by users, generates information based on that information, and returns it to the terminal.

[0009] A "terminal" is a mobile device or computer used by a user, which acquires location information, transmits data to a server, provides voice guidance, and so on.

[0010] "Recommended information" refers to local information such as restaurants, cafes, events, and weather information provided based on the user's current location.

[0011] "Audio guidance" refers to a means of converting text information into audio and providing it to the user in real time.

[0012] A "search query" is a search condition entered by a user using free words.

[0013] "Restaurant information" refers to detailed information about restaurants provided based on a user's search query.

[0014] "Reservation means" refers to a function that allows a user to select a specific restaurant and make a reservation. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] The present invention is a system for providing real-time information related to the area in which a user is currently walking. This system acquires the user's location information, transmits it to a server, and provides audio guidance on recommendations, deals, weather, and other information based on the location information. The user can also enter a search query using free words, and the server will provide appropriate restaurant information based on the query and even allow the user to make reservations at those restaurants. The system's program processing is described in detail below in natural language.

[0037] First, the user launches the application. The device uses a GPS sensor to obtain the user's current location in real time. This location information is sent from the device to the server. The server receives the location information and uses a generation AI to search for recommendation information in the surrounding area. The generated recommendation information might be something like, "There is currently a 20% off campaign at the cafe 50 meters ahead on the right." The server sends this information to the device, and the device delivers the received information to the user as voice guidance.

[0038] Next, consider the case where a user uses free words to search for restaurants that meet specific criteria. The user enters the search criteria into the search box within the app, and the device sends this input to the server. The server analyzes the received free words and uses generative AI to search for appropriate restaurant information. Search results may include, for example, "XX restaurant, △△ bistro." These results are sent to the device, which displays them to the user in a list format.

[0039] When the user selects the desired restaurant from the list and makes a reservation, the terminal sends the entered reservation information back to the server. The server then connects with the restaurant's reservation system and confirms the reservation. Once the reservation is confirmed, the information is sent to the terminal and the user is notified. The user is provided with information such as, "Your reservation at Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[0040] As a concrete example, consider a case where a user is walking around Shinjuku Station. The user launches an application, and the device acquires location information around Shinjuku Station. Based on this location information, the server generates recommendation information, such as "A cafe on the street in front of the station is offering a limited-time discount on parfaits," and sends it to the device. The device then notifies the user of this information as voice guidance. Furthermore, if the user performs a free-word search for "a restaurant where I can drink with my boss for under 4,000 yen and where smoking is permitted," the server searches for restaurants that match the criteria and sends the results to the device. The user can then select the desired restaurant from the displayed list and make a reservation.

[0041] In this way, the present invention provides a system that provides real-time information related to the area the user is currently walking through, generates restaurant information tailored to the user's individual needs based on the user's search query, and allows the user to easily make reservations at those restaurants.

[0042] The processing flow will be explained below.

[0043] Providing recommended information for the area you are currently walking through

[0044] Step 1:

[0045] The user launches the app on their device.

[0046] A user taps an app icon on a device such as a smartphone or tablet to launch the application.

[0047] Step 2:

[0048] The device acquires location information.

[0049] The device's GPS sensor operates to obtain the user's current location (latitude and longitude) in real time.

[0050] The acquired location information is updated at regular intervals (for example, every 5 seconds).

[0051] Step 3:

[0052] The device sends location information to the server.

[0053] The device sends the acquired location information to the server via an HTTP request, which includes latitude, longitude, timestamp, etc.

[0054] Step 4:

[0055] The server generates recommendations.

[0056] The server analyzes the location information received and searches a database for recommended information for the surrounding area.

[0057] Generative AI is used to optimize recommendation information and generate text for voice guidance.

[0058] For example, "The cafe 50 meters ahead on the right is currently running a 20% off campaign."

[0059] Step 5:

[0060] The server sends the recommendation information to the device.

[0061] The server returns the generated text information for the voice guidance to the terminal as an HTTP response.

[0062] Step 6:

[0063] The device provides voice guidance.

[0064] The text information for voice guidance received by the device is converted into voice using a TTS (Text-to-Speech) engine.

[0065] Through the earphones, the user is given voice guidance such as, "There is currently a 20% off campaign at the cafe on the right, 50 meters ahead."

[0066] Free word search and restaurant reservations

[0067] Step 1:

[0068] The user inputs a free word.

[0069] The user enters a free word (for example, "smoking allowed, boss, under 4000 yen") into the search box within the app.

[0070] Your device temporarily stores what you type into the search box.

[0071] Step 2:

[0072] The terminal sends the free word to the server.

[0073] The device sends the saved free words to the server via an HTTP request, and the request includes the search query.

[0074] Step 3:

[0075] The server generates restaurant information based on the search query.

[0076] The server analyzes the received search query and generates restaurant information that matches the criteria from the database.

[0077] Use generative AI to optimize search results to best meet your needs.

[0078] Step 4:

[0079] The server transmits restaurant information to the terminal.

[0080] The server returns the optimized restaurant information to the terminal as an HTTP response.

[0081] Search results include details such as store name, address, opening hours, and price range.

[0082] Step 5:

[0083] The terminal displays the search results to the user.

[0084] The terminal displays the search results received to the user in list form.

[0085] Each item includes buttons such as "View details" and "Make a reservation."

[0086] Step 6:

[0087] The user selects a restaurant and makes a reservation.

[0088] The user selects the desired restaurant from the list and taps the "Make a reservation" button.

[0089] The terminal displays an interface for entering reservation information (date and time, number of people, special notes).

[0090] Step 7:

[0091] The terminal transmits the reservation information to the server.

[0092] The terminal sends the entered reservation information to the server via an HTTP request.

[0093] Step 8:

[0094] The server confirms the reservation.

[0095] Based on the reservation information received by the server, the reservation is confirmed in cooperation with the restaurant's reservation system.

[0096] The confirmed reservation information is returned to the terminal as an HTTP response.

[0097] Step 9:

[0098] The terminal notifies the user of the reservation confirmation information.

[0099] The terminal notifies the user of the received reservation confirmation information.

[0100] For example, the notification will be in the format "Reservation for XX Restaurant has been completed. Date and time: October 10, 2023, 19:00, Number of people: 2."

[0101] Example 1

[0102] 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."

[0103] There is a demand for a system that provides useful information in real time based on the user's current location information and enables easy and fast acquisition and reservation of restaurant information based on the user's individual search query. However, existing systems often lack sufficient speed and accuracy in providing information, or have difficulty providing information tailored to the user's needs. In particular, there is a lack of systems that seamlessly generate recommendation information in real time and make restaurant reservations based on free word searches.

[0104] 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.

[0105] In this invention, the server includes means for acquiring location information of an area where a user is currently walking, means for transmitting the location information to the server, means for generating recommendation information using a generative AI model based on the location information, means for providing the recommendation information to the user as audio guidance, means for the user to input a search query using free words, means for generating restaurant information using a generative AI model based on the search query, means for providing the restaurant information to the user, and means for making reservations at a specific restaurant based on the restaurant information. This enables the provision of real-time information based on the user's current location and the rapid provision of restaurant information and reservations that meet the user's individual needs.

[0106] "User" refers to an individual who uses the system to obtain real-time information and restaurant information and make reservations.

[0107] "Location information of the area currently being walked" refers to latitude and longitude information used to identify the user's current location using a GPS sensor or the like.

[0108] "Server" refers to a computer system that receives location information and search queries sent by users, generates information based on that information using a generative AI model, and sends it to a terminal.

[0109] A "generative AI model" refers to an artificial intelligence model that generates information in natural language based on a given prompt.

[0110] A "prompt sentence" refers to an input sentence that instructs a generative AI model to generate information.

[0111] "Recommended information" is information provided based on the user's current location using a generative AI model, such as restaurant campaign information and information about nearby facilities.

[0112] "Voice guidance" refers to a function that conveys recommended information generated by the device to the user by voice.

[0113] A "free word search query" refers to an input sentence in which a user enters any word within an application to search for information.

[0114] "Restaurant Information" refers to information about restaurants generated based on free-word search queries using a generative AI model.

[0115] "Reservation" refers to the procedure for reserving seats for a specific date, time and number of people at a restaurant of a user's choice.

[0116] "Reservation information" refers to detailed information such as the date and time and number of people entered by the user when making a reservation.

[0117] "Notification" refers to a message sent by the server to the user's terminal to inform them of reservation confirmation information or recommended information.

[0118] The present invention is a system that provides real-time information related to the area a user is currently walking in. This system acquires the user's location information, transmits it to a server, and provides audio guidance based on that location information, including recommendations, deals, and weather information. The user can also enter a search query using free words, and the server will provide information on appropriate restaurants based on that query and even allow the user to make reservations at those restaurants.

[0119] First, the user launches the application. The device uses the GPS sensor to obtain the user's current location in real time. This location information is then sent from the device to the server. The secure HTTPS protocol is used for communication to ensure data safety.

[0120] Once the server receives the location information, it uses a generative AI model, such as OpenAI's GPT-4, to generate recommendations for the surrounding area.

[0121] Example prompt sentence:

[0122] "The user is currently at Shinjuku Station. Are there any recommended cafes or restaurants nearby?"

[0123] The generative AI model generates appropriate recommendations based on these prompts. Examples of generated information include specific information such as, "The cafe 50 meters ahead on the right is currently offering a 20% off campaign." The generated recommendations are sent from the server to the device, which then converts the information into voice data using speech synthesis software (e.g., Google Text-to-Speech) and provides it to the user.

[0124] Next, we will explain how a user can use free words to search for restaurants that meet specific criteria. The user enters the search criteria into the search box within the app, and the device sends this input to the server. The server analyzes the received free words and uses the generative AI model again to search for appropriate restaurant information.

[0125] Example prompt sentence:

[0126] "Please tell me a restaurant where I can smoke while drinking with my boss for under 4,000 yen."

[0127] Based on this prompt, the generative AI model generates search results and returns them to the server. Examples of search results include "X restaurant, △△ bistro." These results are sent from the server to the device, which displays them to the user in list form. The user then selects the desired restaurant from the displayed list and makes a reservation.

[0128] When the user selects the desired restaurant from the list and makes a reservation, the terminal sends the entered reservation information back to the server. The server then connects with the restaurant's reservation system to confirm the reservation. Once the reservation is confirmed, the information is sent to the terminal and the user is notified. An example of a notification might include information such as, "Your reservation at Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[0129] As a concrete example, imagine a user walking around Shinjuku Station. The user launches an application, and the device obtains location information around Shinjuku Station. Based on this location information, the server generates recommendation information, such as "A cafe on the street in front of the station is offering a limited-time discount on parfaits," and sends it to the device. The device then notifies the user of this information as voice guidance. If the user then performs a free-word search for "a restaurant where I can drink with my boss for under 4,000 yen and where smoking is allowed," the server searches for restaurants that match the criteria and sends the results to the device. The user can then select the restaurant of their choice from the displayed list and make a reservation.

[0130] In this way, the present invention provides a system that provides real-time information related to the area in which a user is currently walking, generates restaurant information tailored to individual needs based on the user's search query, and allows users to easily make reservations at those restaurants.

[0131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0132] Step 1: Launch the application and get location information

[0133] The user launches an application.

[0134] The device activates the GPS sensor to obtain the user's current location, and obtains latitude and longitude information from the GPS sensor and updates it in real time.

[0135] Input: User application launch operation

[0136] Processing: GPS sensor acquires latitude and longitude information

[0137] Output: Current location (latitude, longitude)

[0138] Step 2: Send location information

[0139] The terminal transmits the acquired location information to the server using a secure communication protocol (for example, HTTPS).

[0140] Input: Location information (latitude, longitude)

[0141] Processing: Encrypt location information and send it to the server

[0142] Output: Location information sent to the server

[0143] Step 3: Generate recommendations

[0144] The server uses a generative AI model to generate nearby recommendations based on the received location information. As part of the generation process, it generates location-based prompts.

[0145] Example prompt: "The user is currently at Shinjuku Station. Are there any recommended cafes or restaurants nearby?"

[0146] Input: Location information (latitude, longitude)

[0147] Processing: Generative AI model generates information based on prompts

[0148] Output: Recommendation information (e.g. "The cafe on the right, 50 meters away, is currently offering a 20% discount campaign.")

[0149] Step 4: Send recommendations and voice guidance

[0150] The server transmits the generated recommendation information to the terminal.

[0151] The terminal uses voice synthesis software to convert the received recommendation information into voice data, which is then provided to the user as voice guidance.

[0152] Input:Recommendations

[0153] Processing: Converted into voice data using speech synthesis software and played through speakers

[0154] Output: Voice guidance (e.g. "There is a 20% off campaign going on at the cafe on your right, 50 meters ahead.")

[0155] Step 5: Enter and submit a free word search

[0156] The user enters a free word search query into a search box within the application.

[0157] The terminal transmits the entered search query to the server.

[0158] Input: Search query (e.g., "Restaurants where you can drink with your boss and smoke for under 4,000 yen")

[0159] Process: Send the search query to the server

[0160] Output: The search query sent to the server

[0161] Step 6: Generate search results

[0162] The server analyzes the received search query and generates appropriate restaurant information using a generative AI model. It also generates search results based on the prompt text.

[0163] Example prompt: "Please tell me a restaurant where I can smoke and drink with my boss for under 4000 yen."

[0164] Input: Search query

[0165] Processing: Generative AI model generates information based on prompts

[0166] Output: Restaurant information (e.g., "XX Restaurant, △△ Bistro")

[0167] Step 7: View and select search results

[0168] The terminal displays the restaurant information sent from the server in a list format to the user, and the user selects the restaurant of their choice from the displayed list.

[0169] Input: Restaurant information

[0170] Action: Display information in list format

[0171] Output: List view and user selection

[0172] Step 8: Submit and confirm your reservation

[0173] The terminal transmits reservation information for the restaurant selected by the user to the server, including the date, time, number of people, etc.

[0174] The server connects with the restaurant's reservation system to confirm the reservation.

[0175] Input: Reservation information (date, time, number of people, etc.)

[0176] Process: Link with reservation system and confirm reservation

[0177] Output: Confirmed reservation information

[0178] Step 9: Notification of confirmed reservation information

[0179] The server transmits information that the reservation has been confirmed to the terminal, and the terminal notifies the user of the information.

[0180] Input: Confirmed reservation information

[0181] Processing: Send to device and notify user

[0182] Output: Notification (e.g. "Your reservation for Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2")

[0183] These steps will enable users to smoothly access real-time local information, search for restaurants, and make reservations.

[0184] (Application example 1)

[0185] 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."

[0186] In modern cities, there is an increasing need for users to quickly obtain real-time information about the places they are walking, especially about discount campaigns, recommended places, and emergency weather information. Users also need to be able to easily search for restaurants and stores that meet specific criteria and smoothly make reservations. However, existing systems are limited in the information they can provide and lack real-time capabilities and ease of operation.

[0187] 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.

[0188] In this invention, the server includes means for acquiring location information, means for transmitting the location information to the server, means for generating recommendation information based on the location information using a generative AI model, means for providing the generated recommendation information as voice guidance and as an augmented reality display, means for displaying store information based on a search query entered by a user, and means for confirming a reservation for the store online. This allows a user to receive real-time information related to their current location by voice and augmented reality, making it even easier to search for and make reservations for restaurants and stores.

[0189] "Location information" refers to geographic data such as the latitude and longitude of a user's current physical location.

[0190] "Server" means a computer system accessible over a network that receives and processes data, such as location information or search queries, and provides the results.

[0191] A "generative AI model" refers to an algorithm or program that uses artificial intelligence techniques to generate useful information based on a user's location or search query.

[0192] "Recommended information" refers to information about stores and services suggested based on the user's current location and interests.

[0193] "Audio guidance" refers to a technology that provides information to users by reading out text information aloud.

[0194] "Augmented reality display" refers to a technology that displays digital information superimposed on the actual field of vision.

[0195] A "search query" refers to free words or conditions that a user enters to search for specific information.

[0196] "Store information" refers to detailed information such as the name, location, business hours, and service details of restaurants, retail stores, etc.

[0197] "Reservation" refers to the advance application procedure for a user to use a store or service on a specific date and time.

[0198] A system for implementing this invention provides real-time information related to the area a user is currently walking in. The system is composed of a terminal such as a smartphone or smart glasses, and a server.

[0199] First, when a user launches the application, the device uses a GPS sensor to obtain the user's current location in real time. This location information is then sent to a server via the Internet. The server then uses a generative AI model to generate recommendations for the area based on the received location information. For example, the generated information might be something like, "There's a 20% off campaign going on at the cafe 50 meters ahead on the right." The generated recommendations are then provided to the user via the smartphone screen, voice guidance, or augmented reality display on the smart glasses.

[0200] Next, consider the case where a user uses the device's free-word search function to search for restaurant information based on specific criteria. For example, if the user enters "restaurants where I can drink with my boss and where smoking is allowed for under 4,000 yen," the device sends this search query to the server. The server uses a generative AI model to search for and generate relevant restaurant information and sends the search results to the device. The device displays the results to the user in a list format, such as "X Restaurant, XX Bistro." The user selects the desired restaurant from the list and completes the reservation online. Once the reservation is confirmed, the server sends the information to the device, and the user is notified in the form of a message such as, "Your reservation for X Restaurant has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[0201] The hardware used to implement the system includes smartphones and smart glasses with built-in GPS sensors. The software uses generative AI models (e.g., GPT-3) and speech synthesis libraries (e.g., pyttsx3). The generative AI models are particularly important in generating information in real time based on the user's current location and search query.

[0202] As a concrete example, consider the case where a user is walking around Shinjuku Station. The application obtains location information around Shinjuku Station, and the server generates recommendation information such as "A cafe on the street in front of the station is offering a limited-time discount on parfaits." This information is displayed in augmented reality through the smart glasses and also conveyed via voice guidance. The user can also easily search for "izakayas where you can drink for under 3,000 yen" and make a reservation from the suggested restaurants.

[0203] An example of a program prompt is:

[0204] "Tell me about great deals within 500 meters of my current location"

[0205] "Please find a restaurant where I can smoke while drinking with my boss for under 4,000 yen."

[0206] These prompts allow the generative AI model to provide users with relevant information, enabling real-time information retrieval and a convenient booking experience.

[0207] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0208] Step 1:

[0209] The user launches the application. The device uses the built-in GPS sensor to obtain the user's current location in real time. The obtained location information is sent to the server in the form of latitude and longitude.

[0210] Input: Real-time location information (latitude and longitude) from the GPS sensor

[0211] Data processing / calculation: Acquisition and transmission of location information

[0212] Output: Send location information to the server

[0213] Step 2:

[0214] The server receives the location information and uses a generative AI model to generate recommendations for the area based on the location information. For example, it generates information such as "There is currently a 20% off campaign at the cafe on the right, 50 meters away."

[0215] Input: Location information (latitude and longitude) sent from the device

[0216] Data processing / calculation: Generating recommendations using generative AI models

[0217] Output: Recommendations

[0218] Step 3:

[0219] The server sends the generated recommendation information to the device, which then provides the received recommendation information to the user in the form of voice guidance and augmented reality display. On smartphones, this is done by displaying the screen and providing voice notifications, while on smart glasses, this is done by providing augmented reality display.

[0220] Input: Recommendations sent from the server

[0221] Data processing / calculation: Format conversion of recommended information (voice, augmented reality)

[0222] Output: Voice guidance and augmented reality display

[0223] Step 4:

[0224] A user inputs a search query using free words. For example, if the user inputs "a restaurant where I can drink with my boss and where smoking is allowed for less than 4,000 yen," the search query is sent from the device to the server.

[0225] Input: User's search query (free word)

[0226] Data processing / calculation: Sending search queries

[0227] Output: Sending a search query to the server

[0228] Step 5:

[0229] The server analyzes the received search query and uses a generative AI model to generate appropriate restaurant information, such as "XX Restaurant, △△ Bistro."

[0230] Input: Search query sent from the device

[0231] Data processing / calculation: Generate restaurant information using generative AI models

[0232] Output: Restaurant information

[0233] Step 6:

[0234] The server sends the generated restaurant information to the terminal, which displays the search results in a list to the user, who then selects the restaurant of their choice from the list.

[0235] Input: Restaurant information sent from the server

[0236] Data processing / calculation: Displaying restaurant information in list format

[0237] Output: List of restaurants

[0238] Step 7:

[0239] The user selects the restaurant of their choice and makes a reservation. The terminal sends the reservation information to the server. The server then connects with the restaurant's reservation system to confirm the reservation.

[0240] Input: User's restaurant selection and reservation information

[0241] Data processing / calculation: Sending reservation information and linking with reservation systems

[0242] Output: Confirmed reservation information

[0243] Step 8:

[0244] The server sends the information that the reservation has been confirmed to the terminal. The terminal then notifies the user of the reservation confirmation information. For example, the terminal may notify the user that "Your reservation at Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[0245] Input: Confirmed reservation information sent from the server

[0246] Data processing / calculation: Notification of reservation confirmation information

[0247] Output: Confirmation of reservation sent to user

[0248] 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.

[0249] The present invention is a system that provides real-time information related to the area where a user is currently walking, and includes an emotion engine that recognizes the user's emotions and adjusts recommended information. The system acquires the user's location information, generates recommended information based on that information, and provides it as voice guidance. The user can also enter a free-word search query, generate restaurant information based on that, and make reservations. The emotion engine analyzes the user's voice input and facial expressions, and adjusts the information provided based on the results of that analysis. The system's program processing is specifically explained below in natural language.

[0250] When a user launches the application, the device uses the GPS sensor to obtain the current location (latitude and longitude) in real time. This location information is sent to the server. The server uses a generation AI to search for recommended information in the surrounding area based on the received location information and sends the results to the device. The device then provides the received information to the user as voice guidance.

[0251] By incorporating an emotion engine, the system can analyze the user's emotional state and adjust recommendations based on that information. For example, if the user says "I'm tired," the emotion engine will recommend cafes and quiet places where the user can relax. Also, if the user has a smiling expression, the emotion engine will suggest fun events and restaurants with a cheerful atmosphere.

[0252] As a concrete example, consider the case where a user is walking around Shinjuku Station. The user launches an application, and the device acquires location information around Shinjuku Station. Based on this location information, the server generates recommendation information such as, "There's a new cafe about a three-minute walk away. They're currently offering half-price drinks as part of their opening campaign." and sends this information to the device. The device then relays this information to the user as voice guidance.

[0253] Furthermore, if the user voice-inputs "I'm tired and want to rest somewhere," the emotion engine will determine the user's state as "fatigue," and the server will provide information about places to relax, such as "You can relax in a nearby park."

[0254] When a user wants to search for a restaurant based on specific criteria, they can use the free word search function. For example, they can enter a search query such as "a table for drinking with my boss under 4000 yen, smoking allowed." The device sends this input to the server, which then generates a list of restaurants that match the criteria. Search results include candidates such as "XX restaurant, △△ bistro." When the user selects the desired restaurant and makes a reservation, the device sends the reservation information to the server, and the server confirms the reservation and returns the information to the device.

[0255] In this way, the present invention provides real-time information based on the user's current location and also provides information that takes the user's emotions into consideration. Restaurant search and reservation functions are also integrated, making this a system that greatly improves user convenience.

[0256] The processing flow will be explained below.

[0257] Providing recommended information for the area you are currently walking in (embedded emotion engine)

[0258] Step 1:

[0259] The user launches the app on their device.

[0260] A user taps an app icon on a device such as a smartphone or tablet to launch the application.

[0261] Step 2:

[0262] The device acquires location information.

[0263] The device's GPS sensor operates to obtain the user's current location (latitude and longitude) in real time.

[0264] The acquired location information is updated at regular intervals (for example, every 5 seconds).

[0265] Step 3:

[0266] The device sends location information to the server.

[0267] The device sends the acquired location information to the server via an HTTP request, which includes latitude, longitude, timestamp, etc.

[0268] Step 4:

[0269] The server generates recommendations.

[0270] The server analyzes the location information received and searches a database for recommended information for the surrounding area.

[0271] Generative AI is used to optimize recommendation information and generate text for voice guidance.

[0272] For example, "The cafe 50 meters ahead on the right is currently running a 20% off campaign."

[0273] Step 5:

[0274] The server sends the recommendation information to the device.

[0275] The server returns the generated text information for the voice guidance to the terminal as an HTTP response.

[0276] Step 6:

[0277] The device uses an emotion engine to analyze the user's emotions.

[0278] The terminal acquires the user's voice input or facial expression data.

[0279] An emotion engine analyzes this data to determine the user's current emotional state (e.g., "tired," "happy," etc.).

[0280] Step 7:

[0281] The device requests adjustments to the recommendations from the server.

[0282] The device sends the analysis results to the server and requests that recommendations be re-adjusted based on the user's emotional state.

[0283] Step 8:

[0284] The server adjusts recommendations based on the emotional state.

[0285] Based on the emotion analysis results, the server searches the database for new recommended information that matches the user's emotions.

[0286] For example, if the user is "tired," information about cafes and parks where they can relax is provided.

[0287] The server sends the re-adjusted recommendations to the device.

[0288] Step 9:

[0289] The device provides tailored recommendations as voice guidance.

[0290] The adjusted recommendation information text received by the device is converted into audio using a TTS (Text-to-Speech) engine.

[0291] Through the earphones, the user is given audio guidance such as, "There is a cafe where you can relax 50 meters ahead. You seem tired."

[0292] Free word search and restaurant reservations (including emotion engine)

[0293] Step 1:

[0294] The user inputs a free word.

[0295] The user enters a free word (for example, "smoking allowed, boss, under 4000 yen") into the search box within the app.

[0296] Your device temporarily stores what you type into the search box.

[0297] Step 2:

[0298] The terminal sends the free word to the server.

[0299] The device sends the saved free words to the server via an HTTP request, and the request includes the search query.

[0300] Step 3:

[0301] The server generates restaurant information based on the search query.

[0302] The server analyzes the received search query and generates restaurant information that matches the criteria from the database.

[0303] Use generative AI to optimize search results to best meet your needs.

[0304] Step 4:

[0305] The server transmits restaurant information to the terminal.

[0306] The server returns the optimized restaurant information to the terminal as an HTTP response.

[0307] Search results include details such as store name, address, opening hours, and price range.

[0308] Step 5:

[0309] The device uses an emotion engine to analyze the user's emotions.

[0310] The terminal acquires the user's voice input or facial expression data.

[0311] An emotion engine analyzes this data to determine the user's current emotional state.

[0312] Step 6:

[0313] The device makes a request to the server to tailor the search results.

[0314] The device sends the analysis results to the server and requests that the search results be re-adjusted based on the user's emotional state.

[0315] Step 7:

[0316] The server adjusts search results based on emotional state.

[0317] Based on the emotion analysis results, the server regenerates search results from the database that are appropriate to the user's emotions.

[0318] For example, if the user is in the mood for "celebration," a restaurant with special seating and courses will be offered.

[0319] Step 8:

[0320] The device displays the re-calibrated search results to the user.

[0321] The terminal displays the search results after the readjustment received to the user in list form.

[0322] Each item includes buttons such as "View details" and "Make a reservation."

[0323] Step 9:

[0324] The user selects a restaurant and makes a reservation.

[0325] The user selects the desired restaurant from the list and taps the "Make a reservation" button.

[0326] The terminal displays an interface for entering reservation information (date and time, number of people, special notes).

[0327] Step 10:

[0328] The terminal transmits the reservation information to the server.

[0329] The terminal sends the entered reservation information to the server via an HTTP request.

[0330] Step 11:

[0331] The server confirms the reservation.

[0332] Based on the reservation information received by the server, the reservation is confirmed in cooperation with the restaurant's reservation system.

[0333] The confirmed reservation information is returned to the terminal as an HTTP response.

[0334] Step 12:

[0335] The terminal notifies the user of the reservation confirmation information.

[0336] The terminal notifies the user of the received reservation confirmation information.

[0337] For example, the notification will be in the format "Reservation for XX Restaurant has been completed. Date and time: October 10, 2023, 19:00, Number of people: 2."

[0338] Example 2

[0339] 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."

[0340] Conventional information provision systems not only lack the ability to provide appropriate recommendations based on the user's location information in real time, but also the ability to adjust the information according to the user's emotional state. Furthermore, they lack the ability to allow users to search for restaurant information by specifying detailed conditions and make immediate reservations. This makes it difficult to improve user satisfaction and results in low convenience.

[0341] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0342] In this invention, the server includes a means for acquiring location information of the area where the user is currently walking, a means for transmitting the location information to the server, and a means for generating recommendation information based on the location information. This enables real-time information provision based on the user's current location. It also includes an emotion engine that analyzes the user's emotional state and a means for adjusting recommendation information based on the emotional state. This enables information provision according to the user's emotions. Furthermore, by including a means for generating recommendation information and restaurant information using a generative AI model and a means for generating information based on a prompt sentence entered by the user, highly accurate information provision that satisfies the user is realized. Furthermore, by including a means for the user to input a search query using free words, a means for generating restaurant information based on the search query, and a means for making a reservation at a specific restaurant based on the search query, a highly convenient restaurant search and reservation function is also provided.

[0343] "User" refers to a person who uses the system.

[0344] "Location Information" refers to geographic data including a user's current latitude and longitude.

[0345] "Server" refers to a computer system that receives and processes data sent from a user's terminal.

[0346] An "emotion engine" refers to a combination of software or hardware that analyzes a user's voice and facial expressions to determine the user's emotional state.

[0347] "Recommended information" refers to information generated based on the user's location information and emotional state, and includes places and events that may be of interest to the user.

[0348] "Audio guidance" refers to guidance information provided to the user by voice.

[0349] A "free word search" refers to a search that is conducted by the user entering any word or phrase.

[0350] A "search query" refers to text data that represents search conditions or requests that a user inputs into a system.

[0351] "Restaurant information" refers to various data about restaurants (e.g., restaurant name, price range, seating availability, etc.) generated by the system based on a user's search query.

[0352] "Generative AI models" refer to algorithms and systems that use artificial intelligence to generate information based on user requests.

[0353] A "prompt sentence" refers to the input text that serves as the basis for generating information for a generative AI model.

[0354] The present invention is a system that provides real-time information related to the area where a user is currently walking, including an emotion engine that recognizes the user's emotions and adjusts recommended information. The system acquires the user's location information, generates recommended information based on that information, and provides it as voice guidance. The user can also input a free-word search query, generate restaurant information based on that, and make reservations. The emotion engine analyzes the user's voice input and facial expressions and adjusts the information provided based on the results of the analysis.

[0355] When a user launches an application, the device uses a GPS sensor to obtain the current location (latitude and longitude) in real time. This location information is sent to a server. The device is equipped with a GPS sensor and a communication module required for sending and receiving data. Specific hardware examples include smartphones, tablets, and laptops.

[0356] The server uses the generated AI to search for recommendations in the surrounding area based on the received location information. The generated AI can be, for example, OpenAI's GPT-4. The server sends the following prompt to the generated AI:

[0357] "Tell me some recommended spots near my current location"

[0358] Based on the information provided by the generating AI, the server further organizes the information and sends it to the terminal.

[0359] The device then provides the received information to the user as voice guidance, using voice synthesis software such as the Google Cloud Text-to-Speech API.

[0360] By incorporating an emotion engine, the system analyzes the user's emotional state and adjusts recommendations based on that information. The device uses a microphone to collect the user's voice input and a camera to recognize the user's facial expressions. The emotion engine can use the Google Cloud Speech-to-Text API or Azure's Emotion API. For example, if the user says "I'm tired," the emotion engine will recommend cafes and quiet places where the user can relax. If the user has a smiling expression, the emotion engine will suggest fun events and restaurants with a cheerful atmosphere.

[0361] As a concrete example, consider the case where a user is walking around Shinjuku Station. The user launches an application, and the device acquires location information around Shinjuku Station. Based on this location information, the server generates recommendation information such as, "There's a new cafe about a three-minute walk away. They're currently offering half-price drinks as part of their opening campaign." and sends this information to the device. The device then relays this information to the user as voice guidance.

[0362] Furthermore, if the user voice-inputs "I'm tired and want to rest somewhere," the emotion engine will determine the user's state as "fatigue," and the server will provide information about places to relax, such as "You can relax in a nearby park."

[0363] When a user wants to search for a restaurant based on specific criteria, they can use the free word search function. For example, they can enter a search query such as "a table for drinking with my boss under 4000 yen, smoking allowed." The device sends this input to the server, which then generates a list of restaurants that match the criteria. Search results include candidates such as "XX restaurant, △△ bistro." When the user selects the desired restaurant and makes a reservation, the device sends the reservation information to the server, and the server confirms the reservation and returns the information to the device.

[0364] In this way, the present invention provides real-time information based on the user's current location and also provides information that takes the user's emotions into consideration. Restaurant search and reservation functions are also integrated, making this a system that greatly improves user convenience.

[0365] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0366] Step 1:

[0367] The user launches the application

[0368] A user taps an application on their smartphone to launch it. The device loads the application's interface and various functions and becomes ready. The user's operation is the input, and the application screen is displayed as the output.

[0369] Step 2:

[0370] The device obtains its current location

[0371] The device activates its built-in GPS sensor and obtains its current latitude and longitude information. Specifically, the device's location service is activated and receives signals from GPS satellites to determine its location. The input is the signal from the GPS satellites, and the output is the obtained latitude and longitude information. This data is stored internally in JSON format or other appropriate format.

[0372] Step 3:

[0373] Sending location information

[0374] The device packs the acquired location information into packets and sends them to the server using the HTTPS protocol. The input is the latitude and longitude information acquired by the device, and the output is data that is sent to the server. The specific operation utilizes the device's communication module.

[0375] Step 4:

[0376] Server-generated recommendations

[0377] The server sends a specific prompt to the generative AI model (e.g., a generation algorithm) based on the received location information. This prompt might be something like, "Tell me some recommended spots near the user's current location." The server receives the location information as input, and uses that information to process the data to generate an appropriate prompt. The output is recommendations based on this prompt. A cloud-based model (e.g., GPT-4) is used as the generative AI, which returns the results to the server.

[0378] Step 5:

[0379] Analysis by emotion engine

[0380] The device uses a microphone to collect the user's voice input and a camera to recognize facial expressions. Inputs include the user's voice data and video data from the camera. This data is sent to a local emotion analysis engine. Specifically, Google Cloud Speech-to-Text API and Azure Emotion API are used. Data processing involves converting the voice data into text and determining the user's emotional state, and the results are output.

[0381] Step 6:

[0382] Server-adjusted recommendations

[0383] The server adjusts the recommendation information based on the emotional information received from the emotion engine. The input is data on the user's emotional state, and the output is new recommendation information generated according to the emotion. For example, if the user's state is determined to be "fatigue," the server adjusts the recommendation information to provide information on relaxing cafes and quiet spots.

[0384] Step 7:

[0385] Providing recommendations

[0386] The device receives the final recommendation information sent from the server and provides it to the user as voice guidance. Specifically, it generates synthetic voice using Google Cloud Text-to-Speech API, etc. The input is the recommendation information data from the server, and the output is the generated voice guidance, which is provided to the user.

[0387] Step 8:

[0388] Perform a free word search

[0389] The user enters a free word containing a specific requirement into the search bar within the application. For example, a search query such as "a table for drinks with my boss for under 4000 yen, smoking allowed" is entered. The input is the user's free-form text data, which the device packs into packets to send to the server. The output is the data to be sent to the server.

[0390] Step 9:

[0391] Server generates restaurant information

[0392] Based on a free-word search query, the server uses a generative AI model to generate information about restaurants that match the criteria. For example, using the "Search for Restaurants" prompt. The input is the search query data, and the output is a list of restaurants based on the search criteria. This information is processed on the server and may also retrieve information from databases or external APIs.

[0393] Step 10:

[0394] Providing restaurant information and reservations

[0395] The user selects the restaurant of their choice and makes a reservation. The terminal packs the reservation information into a packet and sends it to the server. The input is the user's selection data and reservation information, and the output is the data to be sent to the server. The server processes the received reservation information and makes an actual reservation request to the restaurant. Information indicating that the reservation has been confirmed is then returned to the terminal, and the terminal notifies the user that the reservation has been confirmed.

[0396] (Application example 2)

[0397] 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."

[0398] Conventional navigation systems and information systems provide recommended information based on the user's current location, but because they do not take the user's emotional state into account, they may not fully meet the needs of individual users. Furthermore, even systems that provide restaurant information or have reservation functions have difficulty providing appropriate information based on the user's mood and situation. Therefore, the present invention aims to provide information that reflects the user's emotional state and customized navigation guidance for autonomous vehicles.

[0399] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring location information of the area where the user is currently located, means for transmitting the location information to the server, and means for generating recommended information based on the location information. This makes it possible to provide information in real time based on the user's current location.

[0400] Furthermore, a means for analyzing the emotional state of the user and a means for adjusting the recommended information based on the emotional state are added, thereby enabling the provision of information customized according to the user's mood and state.

[0401] The system also includes a means for inputting a search query using free words, a means for generating restaurant information based on the search query, a means for providing the restaurant information to the user, a means for reserving a specific restaurant based on the search query, and a means for adjusting the restaurant information based on the emotional state, thereby enabling the user to search for restaurants using detailed conditions and obtain optimal results according to their emotions.

[0402] "Location information of the area where the user is currently located" is data that indicates the geographical location where the user is located at a particular point in time.

[0403] A "server" is a computer system that processes and stores information over a network and provides data and services to client devices.

[0404] "Recommended information" is useful data or guidance that is generated based on the user's current location and other conditions and provided to the user.

[0405] "Audio guidance" is a method of providing information to a user using audio.

[0406] "Emotional state" refers to the user's current mood and psychological state, and analyzing this makes it possible to provide information suited to the user's needs and requests.

[0407] A "conditioning tool" is a method or process that changes or optimizes information or data based on specific conditions or criteria.

[0408] A "means for entering a search query using free words" is an interface that allows users to search for information using any word or phrase.

[0409] "Restaurant information" is information about a specific restaurant, including location, menu, price, and ratings.

[0410] A "reservation means" is a method or tool that a user uses to reserve a particular service or facility in advance.

[0411] A "generative AI model" is an algorithm that uses generative adversarial networks and other artificial intelligence techniques to automatically generate new data or information based on input data.

[0412] A "prompt sentence" is a string or sentence that is input to a generative AI model to prompt it to generate appropriate data.

[0413] The present invention is a system that acquires location information of the user's current location, analyzes the user's emotional state based on that information, and provides appropriate recommended information as audio guidance. The following hardware and software are used to implement the present invention.

[0414] Hardware

[0415] GPS sensor: Used to obtain the user's current location in real time.

[0416] Microphone and camera: Used to analyze the user's voice input and facial expressions to determine their emotional state.

[0417] Terminal (smartphone or in-car display): Used to run the system and provide voice guidance to the user.

[0418] Server: Used to generate recommendations using a generative AI model based on the user's location and emotional state, and send them to the device.

[0419] software

[0420] Location information acquisition software (GPS library): Works with the GPS sensor to acquire the user's current location.

[0421] Emotion analysis software (EmotionEngine): Analyzes the user's voice input and facial expression data to determine their emotional state.

[0422] Text-to-Speech software: Provides users with recommended information as audio guidance.

[0423] Generative AI model: Generates recommendations based on the user's current location and emotional state.

[0424] Processing flow explanation

[0425] 1. Location information acquisition: The device uses the GPS sensor to acquire the user's current location (latitude and longitude) in real time. This location information is sent to the server.

[0426] 2. Emotional state analysis: The device's microphone and camera are used to collect the user's voice input and facial expressions, which are then analyzed by the Emotion Engine.

[0427] 3. Information generation: The server receives the user's location information and emotional state and generates recommendations using a generative AI model. For example, it analyzes prompts such as "Recommend places around (latitude, longitude) for a person feeling (emotion)."

[0428] 4. Providing information: The server sends the generated recommendation information to the terminal, which uses TextToSpeech software to provide it to the user as voice guidance.

[0429] Specific examples

[0430] When a user is in an autonomous vehicle, the system operates as follows: Suppose the user's vehicle arrives at its current location (e.g., Shinjuku Ward, Tokyo). The GPS acquires this location information and sends it to the server. At the same time, the user vocally inputs, "I'm tired." The Emotion Engine analyzes this voice and determines the user's emotional state as "fatigue." The server sends the prompt "Recommend places around 35.6895,139.6917 for a person feeling tired" to the generative AI model, generating information recommending places to relax. The device receives this information and provides voice guidance to the user, saying, "The nearby cafe is quiet and relaxing."

[0431] In this way, the present invention provides real-time information based on the user's current location and emotional state, enabling customized navigation guidance, particularly in autonomous vehicles.

[0432] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0433] Step 1:

[0434] The device uses the GPS sensor to obtain the user's current location (latitude and longitude) in real time. This location information becomes input data, and the device sends it to the server.

[0435] Step 2:

[0436] Based on the location information received, the server retrieves information about the surrounding area from a database and sends a prompt to the generative AI model based on that information. This prompt includes a sentence in the format "Recommend places around (latitude, longitude)." The AI ​​model generates recommendations based on this prompt. The generated recommendations become the output data.

[0437] Step 3:

[0438] The device collects the user's voice input and facial expressions using a microphone and camera, and sends the data to the Emotion Engine. This input data is analyzed by the Emotion Engine, which determines the user's emotional state. The analysis results are output as emotions such as "fatigue" or "enjoyment."

[0439] Step 4:

[0440] The server receives the emotional state output from the Emotion Engine and adjusts the recommendation information based on that information. For example, if the user's emotional state is "fatigue," it will prioritize recommendations of cafes and parks where people can relax. This adjusted information is then output again.

[0441] Step 5:

[0442] The server sends the adjusted recommendations to the device, which then uses TextToSpeech software to provide the recommendations to the user as voice guidance, which is the final output.

[0443] Step 6:

[0444] When a user wants to perform a free-word search, they input a search query into their device. This query becomes input data and is sent to the server. The server retrieves restaurant information from a database based on this query and generates appropriate restaurant information using a generative AI model.

[0445] Step 7:

[0446] The server sends the generated restaurant information to the terminal. The terminal displays the information to the user, who selects the desired restaurant and makes a reservation. This reservation information is sent to the server, which processes the reservation. Reservation confirmation information is sent to the terminal and notified to the user.

[0447] This allows users to obtain real-time information about their current location and experience navigation guidance customized to their emotional state.

[0448] 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.

[0449] 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.

[0450] 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.

[0451] [Second embodiment]

[0452] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0453] 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.

[0454] 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).

[0455] 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.

[0456] 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.

[0457] 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).

[0458] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0459] 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.

[0460] 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.

[0461] 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.

[0462] 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.

[0463] 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."

[0464] The present invention is a system for providing real-time information related to the area in which a user is currently walking. This system acquires the user's location information, transmits it to a server, and provides audio guidance on recommendations, deals, weather, and other information based on the location information. The user can also enter a search query using free words, and the server will provide appropriate restaurant information based on the query and even allow the user to make reservations at those restaurants. The system's program processing is described in detail below in natural language.

[0465] First, the user launches the application. The device uses a GPS sensor to obtain the user's current location in real time. This location information is sent from the device to the server. The server receives the location information and uses a generation AI to search for recommendation information in the surrounding area. The generated recommendation information might be something like, "There is currently a 20% off campaign at the cafe 50 meters ahead on the right." The server sends this information to the device, and the device delivers the received information to the user as voice guidance.

[0466] Next, consider the case where a user uses free words to search for restaurants that meet specific criteria. The user enters the search criteria into the search box within the app, and the device sends this input to the server. The server analyzes the received free words and uses generative AI to search for appropriate restaurant information. Search results may include, for example, "XX restaurant, △△ bistro." These results are sent to the device, which displays them to the user in a list format.

[0467] When the user selects the desired restaurant from the list and makes a reservation, the terminal sends the entered reservation information back to the server. The server then connects with the restaurant's reservation system and confirms the reservation. Once the reservation is confirmed, the information is sent to the terminal and the user is notified. The user is provided with information such as, "Your reservation at Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[0468] As a concrete example, consider a case where a user is walking around Shinjuku Station. The user launches an application, and the device acquires location information around Shinjuku Station. Based on this location information, the server generates recommendation information, such as "A cafe on the street in front of the station is offering a limited-time discount on parfaits," and sends it to the device. The device then notifies the user of this information as voice guidance. Furthermore, if the user performs a free-word search for "a restaurant where I can drink with my boss for under 4,000 yen and where smoking is permitted," the server searches for restaurants that match the criteria and sends the results to the device. The user can then select the desired restaurant from the displayed list and make a reservation.

[0469] In this way, the present invention provides a system that provides real-time information related to the area the user is currently walking through, generates restaurant information tailored to the user's individual needs based on the user's search query, and allows the user to easily make reservations at those restaurants.

[0470] The processing flow will be explained below.

[0471] Providing recommended information for the area you are currently walking through

[0472] Step 1:

[0473] The user launches the app on their device.

[0474] A user taps an app icon on a device such as a smartphone or tablet to launch the application.

[0475] Step 2:

[0476] The device acquires location information.

[0477] The device's GPS sensor operates to obtain the user's current location (latitude and longitude) in real time.

[0478] The acquired location information is updated at regular intervals (for example, every 5 seconds).

[0479] Step 3:

[0480] The device sends location information to the server.

[0481] The device sends the acquired location information to the server via an HTTP request, which includes latitude, longitude, timestamp, etc.

[0482] Step 4:

[0483] The server generates recommendations.

[0484] The server analyzes the location information received and searches a database for recommended information for the surrounding area.

[0485] Generative AI is used to optimize recommendation information and generate text for voice guidance.

[0486] For example, "The cafe 50 meters ahead on the right is currently running a 20% off campaign."

[0487] Step 5:

[0488] The server sends the recommendation information to the device.

[0489] The server returns the generated text information for the voice guidance to the terminal as an HTTP response.

[0490] Step 6:

[0491] The device provides voice guidance.

[0492] The text information for voice guidance received by the device is converted into voice using a TTS (Text-to-Speech) engine.

[0493] Through the earphones, the user is given voice guidance such as, "There is currently a 20% off campaign at the cafe on the right, 50 meters ahead."

[0494] Free word search and restaurant reservations

[0495] Step 1:

[0496] The user inputs a free word.

[0497] The user enters a free word (for example, "smoking allowed, boss, under 4000 yen") into the search box within the app.

[0498] Your device temporarily stores what you type into the search box.

[0499] Step 2:

[0500] The terminal sends the free word to the server.

[0501] The device sends the saved free words to the server via an HTTP request, and the request includes the search query.

[0502] Step 3:

[0503] The server generates restaurant information based on the search query.

[0504] The server analyzes the received search query and generates restaurant information that matches the criteria from the database.

[0505] Use generative AI to optimize search results to best meet your needs.

[0506] Step 4:

[0507] The server transmits restaurant information to the terminal.

[0508] The server returns the optimized restaurant information to the terminal as an HTTP response.

[0509] Search results include details such as store name, address, opening hours, and price range.

[0510] Step 5:

[0511] The terminal displays the search results to the user.

[0512] The terminal displays the search results received to the user in list form.

[0513] Each item includes buttons such as "View details" and "Make a reservation."

[0514] Step 6:

[0515] The user selects a restaurant and makes a reservation.

[0516] The user selects the desired restaurant from the list and taps the "Make a reservation" button.

[0517] The terminal displays an interface for entering reservation information (date and time, number of people, special notes).

[0518] Step 7:

[0519] The terminal transmits the reservation information to the server.

[0520] The terminal sends the entered reservation information to the server via an HTTP request.

[0521] Step 8:

[0522] The server confirms the reservation.

[0523] Based on the reservation information received by the server, the reservation is confirmed in cooperation with the restaurant's reservation system.

[0524] The confirmed reservation information is returned to the terminal as an HTTP response.

[0525] Step 9:

[0526] The terminal notifies the user of the reservation confirmation information.

[0527] The terminal notifies the user of the received reservation confirmation information.

[0528] For example, the notification will be in the format "Reservation for XX Restaurant has been completed. Date and time: October 10, 2023, 19:00, Number of people: 2."

[0529] Example 1

[0530] 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."

[0531] There is a demand for a system that provides useful information in real time based on the user's current location information and enables easy and fast acquisition and reservation of restaurant information based on the user's individual search query. However, existing systems often lack sufficient speed and accuracy in providing information, or have difficulty providing information tailored to the user's needs. In particular, there is a lack of systems that seamlessly generate recommendation information in real time and make restaurant reservations based on free word searches.

[0532] 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.

[0533] In this invention, the server includes means for acquiring location information of an area where a user is currently walking, means for transmitting the location information to the server, means for generating recommendation information using a generative AI model based on the location information, means for providing the recommendation information to the user as audio guidance, means for the user to input a search query using free words, means for generating restaurant information using a generative AI model based on the search query, means for providing the restaurant information to the user, and means for making reservations at a specific restaurant based on the restaurant information. This enables the provision of real-time information based on the user's current location and the rapid provision of restaurant information and reservations that meet the user's individual needs.

[0534] "User" refers to an individual who uses the system to obtain real-time information and restaurant information and make reservations.

[0535] "Location information of the area currently being walked" refers to latitude and longitude information used to identify the user's current location using a GPS sensor or the like.

[0536] "Server" refers to a computer system that receives location information and search queries sent by users, generates information based on that information using a generative AI model, and sends it to a terminal.

[0537] A "generative AI model" refers to an artificial intelligence model that generates information in natural language based on a given prompt.

[0538] A "prompt sentence" refers to an input sentence that instructs a generative AI model to generate information.

[0539] "Recommended information" is information provided based on the user's current location using a generative AI model, such as restaurant campaign information and information about nearby facilities.

[0540] "Voice guidance" refers to a function that conveys recommended information generated by the device to the user by voice.

[0541] A "free word search query" refers to an input sentence in which a user enters any word within an application to search for information.

[0542] "Restaurant Information" refers to information about restaurants generated based on free-word search queries using a generative AI model.

[0543] "Reservation" refers to the procedure for reserving seats for a specific date, time and number of people at a restaurant of a user's choice.

[0544] "Reservation information" refers to detailed information such as the date and time and number of people entered by the user when making a reservation.

[0545] "Notification" refers to a message sent by the server to the user's terminal to inform them of reservation confirmation information or recommended information.

[0546] The present invention is a system that provides real-time information related to the area a user is currently walking in. This system acquires the user's location information, transmits it to a server, and provides audio guidance based on that location information, including recommendations, deals, and weather information. The user can also enter a search query using free words, and the server will provide information on appropriate restaurants based on that query and even allow the user to make reservations at those restaurants.

[0547] First, the user launches the application. The device uses the GPS sensor to obtain the user's current location in real time. This location information is then sent from the device to the server. The secure HTTPS protocol is used for communication to ensure data safety.

[0548] Once the server receives the location information, it uses a generative AI model, such as OpenAI's GPT-4, to generate recommendations for the surrounding area.

[0549] Example prompt sentence:

[0550] "The user is currently at Shinjuku Station. Are there any recommended cafes or restaurants nearby?"

[0551] The generative AI model generates appropriate recommendations based on these prompts. Examples of generated information include specific information such as, "The cafe 50 meters ahead on the right is currently offering a 20% off campaign." The generated recommendations are sent from the server to the device, which then converts the information into voice data using speech synthesis software (e.g., Google Text-to-Speech) and provides it to the user.

[0552] Next, we will explain how a user can use free words to search for restaurants that meet specific criteria. The user enters the search criteria into the search box within the app, and the device sends this input to the server. The server analyzes the received free words and uses the generative AI model again to search for appropriate restaurant information.

[0553] Example prompt sentence:

[0554] "Please tell me a restaurant where I can smoke while drinking with my boss for under 4,000 yen."

[0555] Based on this prompt, the generative AI model generates search results and returns them to the server. Examples of search results include "X restaurant, △△ bistro." These results are sent from the server to the device, which displays them to the user in list form. The user then selects the desired restaurant from the displayed list and makes a reservation.

[0556] When the user selects the desired restaurant from the list and makes a reservation, the terminal sends the entered reservation information back to the server. The server then connects with the restaurant's reservation system to confirm the reservation. Once the reservation is confirmed, the information is sent to the terminal and the user is notified. An example of a notification might include information such as, "Your reservation at Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[0557] As a concrete example, imagine a user walking around Shinjuku Station. The user launches an application, and the device obtains location information around Shinjuku Station. Based on this location information, the server generates recommendation information, such as "A cafe on the street in front of the station is offering a limited-time discount on parfaits," and sends it to the device. The device then notifies the user of this information as voice guidance. If the user then performs a free-word search for "a restaurant where I can drink with my boss for under 4,000 yen and where smoking is allowed," the server searches for restaurants that match the criteria and sends the results to the device. The user can then select the restaurant of their choice from the displayed list and make a reservation.

[0558] In this way, the present invention provides a system that provides real-time information related to the area in which a user is currently walking, generates restaurant information tailored to individual needs based on the user's search query, and allows users to easily make reservations at those restaurants.

[0559] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0560] Step 1: Launch the application and get location information

[0561] The user launches an application.

[0562] The device activates the GPS sensor to obtain the user's current location, and obtains latitude and longitude information from the GPS sensor and updates it in real time.

[0563] Input: User application launch operation

[0564] Processing: GPS sensor acquires latitude and longitude information

[0565] Output: Current location (latitude, longitude)

[0566] Step 2: Send location information

[0567] The terminal transmits the acquired location information to the server using a secure communication protocol (for example, HTTPS).

[0568] Input: Location information (latitude, longitude)

[0569] Processing: Encrypt location information and send it to the server

[0570] Output: Location information sent to the server

[0571] Step 3: Generate recommendations

[0572] The server uses a generative AI model to generate nearby recommendations based on the received location information. As part of the generation process, it generates location-based prompts.

[0573] Example prompt: "The user is currently at Shinjuku Station. Are there any recommended cafes or restaurants nearby?"

[0574] Input: Location information (latitude, longitude)

[0575] Processing: Generative AI model generates information based on prompts

[0576] Output: Recommendation information (e.g. "The cafe on the right, 50 meters away, is currently offering a 20% discount campaign.")

[0577] Step 4: Send recommendations and voice guidance

[0578] The server transmits the generated recommendation information to the terminal.

[0579] The terminal uses voice synthesis software to convert the received recommendation information into voice data, which is then provided to the user as voice guidance.

[0580] Input:Recommendations

[0581] Processing: Converted into voice data using speech synthesis software and played through speakers

[0582] Output: Voice guidance (e.g. "There is a 20% off campaign going on at the cafe on your right, 50 meters ahead.")

[0583] Step 5: Enter and submit a free word search

[0584] The user enters a free word search query into a search box within the application.

[0585] The terminal transmits the entered search query to the server.

[0586] Input: Search query (e.g., "Restaurants where you can drink with your boss and smoke for under 4,000 yen")

[0587] Process: Send the search query to the server

[0588] Output: The search query sent to the server

[0589] Step 6: Generate search results

[0590] The server analyzes the received search query and generates appropriate restaurant information using a generative AI model. It also generates search results based on the prompt text.

[0591] Example prompt: "Please tell me a restaurant where I can smoke and drink with my boss for under 4000 yen."

[0592] Input: Search query

[0593] Processing: Generative AI model generates information based on prompts

[0594] Output: Restaurant information (e.g., "XX Restaurant, △△ Bistro")

[0595] Step 7: View and select search results

[0596] The terminal displays the restaurant information sent from the server in a list format to the user, and the user selects the restaurant of their choice from the displayed list.

[0597] Input: Restaurant information

[0598] Action: Display information in list format

[0599] Output: List view and user selection

[0600] Step 8: Submit and confirm your reservation

[0601] The terminal transmits reservation information for the restaurant selected by the user to the server, including the date, time, number of people, etc.

[0602] The server connects with the restaurant's reservation system to confirm the reservation.

[0603] Input: Reservation information (date, time, number of people, etc.)

[0604] Process: Link with reservation system and confirm reservation

[0605] Output: Confirmed reservation information

[0606] Step 9: Notification of confirmed reservation information

[0607] The server transmits information that the reservation has been confirmed to the terminal, and the terminal notifies the user of the information.

[0608] Input: Confirmed reservation information

[0609] Processing: Send to device and notify user

[0610] Output: Notification (e.g. "Your reservation for Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2")

[0611] These steps will enable users to smoothly access real-time local information, search for restaurants, and make reservations.

[0612] (Application example 1)

[0613] 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."

[0614] In modern cities, there is an increasing need for users to quickly obtain real-time information about the places they are walking, especially about discount campaigns, recommended places, and emergency weather information. Users also need to be able to easily search for restaurants and stores that meet specific criteria and smoothly make reservations. However, existing systems are limited in the information they can provide and lack real-time capabilities and ease of operation.

[0615] 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.

[0616] In this invention, the server includes means for acquiring location information, means for transmitting the location information to the server, means for generating recommendation information based on the location information using a generative AI model, means for providing the generated recommendation information as voice guidance and as an augmented reality display, means for displaying store information based on a search query entered by a user, and means for confirming a reservation for the store online. This allows a user to receive real-time information related to their current location by voice and augmented reality, making it even easier to search for and make reservations for restaurants and stores.

[0617] "Location information" refers to geographic data such as the latitude and longitude of a user's current physical location.

[0618] "Server" means a computer system accessible over a network that receives and processes data, such as location information or search queries, and provides the results.

[0619] A "generative AI model" refers to an algorithm or program that uses artificial intelligence techniques to generate useful information based on a user's location or search query.

[0620] "Recommended information" refers to information about stores and services suggested based on the user's current location and interests.

[0621] "Audio guidance" refers to a technology that provides information to users by reading out text information aloud.

[0622] "Augmented reality display" refers to a technology that displays digital information superimposed on the actual field of vision.

[0623] A "search query" refers to free words or conditions that a user enters to search for specific information.

[0624] "Store information" refers to detailed information such as the name, location, business hours, and service details of restaurants, retail stores, etc.

[0625] "Reservation" refers to the advance application procedure for a user to use a store or service on a specific date and time.

[0626] A system for implementing this invention provides real-time information related to the area a user is currently walking in. The system is composed of a terminal such as a smartphone or smart glasses, and a server.

[0627] First, when a user launches the application, the device uses a GPS sensor to obtain the user's current location in real time. This location information is then sent to a server via the Internet. The server then uses a generative AI model to generate recommendations for the area based on the received location information. For example, the generated information might be something like, "There's a 20% off campaign going on at the cafe 50 meters ahead on the right." The generated recommendations are then provided to the user via the smartphone screen, voice guidance, or augmented reality display on the smart glasses.

[0628] Next, consider the case where a user uses the device's free-word search function to search for restaurant information based on specific criteria. For example, if the user enters "restaurants where I can drink with my boss and where smoking is allowed for under 4,000 yen," the device sends this search query to the server. The server uses a generative AI model to search for and generate relevant restaurant information and sends the search results to the device. The device displays the results to the user in a list format, such as "X Restaurant, XX Bistro." The user selects the desired restaurant from the list and completes the reservation online. Once the reservation is confirmed, the server sends the information to the device, and the user is notified in the form of a message such as, "Your reservation for X Restaurant has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[0629] The hardware used to implement the system includes smartphones and smart glasses with built-in GPS sensors. The software uses generative AI models (e.g., GPT-3) and speech synthesis libraries (e.g., pyttsx3). The generative AI models are particularly important in generating information in real time based on the user's current location and search query.

[0630] As a concrete example, consider the case where a user is walking around Shinjuku Station. The application obtains location information around Shinjuku Station, and the server generates recommendation information such as "A cafe on the street in front of the station is offering a limited-time discount on parfaits." This information is displayed in augmented reality through the smart glasses and also conveyed via voice guidance. The user can also easily search for "izakayas where you can drink for under 3,000 yen" and make a reservation from the suggested restaurants.

[0631] An example of a program prompt is:

[0632] "Tell me about great deals within 500 meters of my current location"

[0633] "Please find a restaurant where I can smoke while drinking with my boss for under 4,000 yen."

[0634] These prompts allow the generative AI model to provide users with relevant information, enabling real-time information retrieval and a convenient booking experience.

[0635] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0636] Step 1:

[0637] The user launches the application. The device uses the built-in GPS sensor to obtain the user's current location in real time. The obtained location information is sent to the server in the form of latitude and longitude.

[0638] Input: Real-time location information (latitude and longitude) from the GPS sensor

[0639] Data processing / calculation: Acquisition and transmission of location information

[0640] Output: Send location information to the server

[0641] Step 2:

[0642] The server receives the location information and uses a generative AI model to generate recommendations for the area based on the location information. For example, it generates information such as "There is currently a 20% off campaign at the cafe on the right, 50 meters away."

[0643] Input: Location information (latitude and longitude) sent from the device

[0644] Data processing / calculation: Generating recommendations using generative AI models

[0645] Output: Recommendations

[0646] Step 3:

[0647] The server sends the generated recommendation information to the device, which then provides the received recommendation information to the user in the form of voice guidance and augmented reality display. On smartphones, this is done by displaying the screen and providing voice notifications, while on smart glasses, this is done by providing augmented reality display.

[0648] Input: Recommendations sent from the server

[0649] Data processing / calculation: Format conversion of recommended information (voice, augmented reality)

[0650] Output: Voice guidance and augmented reality display

[0651] Step 4:

[0652] A user inputs a search query using free words. For example, if the user inputs "a restaurant where I can drink with my boss and where smoking is allowed for less than 4,000 yen," the search query is sent from the device to the server.

[0653] Input: User's search query (free word)

[0654] Data processing / calculation: Sending search queries

[0655] Output: Sending a search query to the server

[0656] Step 5:

[0657] The server analyzes the received search query and uses a generative AI model to generate appropriate restaurant information, such as "XX Restaurant, △△ Bistro."

[0658] Input: Search query sent from the device

[0659] Data processing / calculation: Generate restaurant information using generative AI models

[0660] Output: Restaurant information

[0661] Step 6:

[0662] The server sends the generated restaurant information to the terminal, which displays the search results in a list to the user, who then selects the restaurant of their choice from the list.

[0663] Input: Restaurant information sent from the server

[0664] Data processing / calculation: Displaying restaurant information in list format

[0665] Output: List of restaurants

[0666] Step 7:

[0667] The user selects the restaurant of their choice and makes a reservation. The terminal sends the reservation information to the server. The server then connects with the restaurant's reservation system to confirm the reservation.

[0668] Input: User's restaurant selection and reservation information

[0669] Data processing / calculation: Sending reservation information and linking with reservation systems

[0670] Output: Confirmed reservation information

[0671] Step 8:

[0672] The server sends the information that the reservation has been confirmed to the terminal. The terminal then notifies the user of the reservation confirmation information. For example, the terminal may notify the user that "Your reservation at Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[0673] Input: Confirmed reservation information sent from the server

[0674] Data processing / calculation: Notification of reservation confirmation information

[0675] Output: Confirmation of reservation sent to user

[0676] 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.

[0677] The present invention is a system that provides real-time information related to the area where a user is currently walking, and includes an emotion engine that recognizes the user's emotions and adjusts recommended information. The system acquires the user's location information, generates recommended information based on that information, and provides it as voice guidance. The user can also enter a free-word search query, generate restaurant information based on that, and make reservations. The emotion engine analyzes the user's voice input and facial expressions, and adjusts the information provided based on the results of that analysis. The system's program processing is specifically explained below in natural language.

[0678] When a user launches the application, the device uses the GPS sensor to obtain the current location (latitude and longitude) in real time. This location information is sent to the server. The server uses a generation AI to search for recommended information in the surrounding area based on the received location information and sends the results to the device. The device then provides the received information to the user as voice guidance.

[0679] By incorporating an emotion engine, the system can analyze the user's emotional state and adjust recommendations based on that information. For example, if the user says "I'm tired," the emotion engine will recommend cafes and quiet places where the user can relax. Also, if the user has a smiling expression, the emotion engine will suggest fun events and restaurants with a cheerful atmosphere.

[0680] As a concrete example, consider the case where a user is walking around Shinjuku Station. The user launches an application, and the device acquires location information around Shinjuku Station. Based on this location information, the server generates recommendation information such as, "There's a new cafe about a three-minute walk away. They're currently offering half-price drinks as part of their opening campaign." and sends this information to the device. The device then relays this information to the user as voice guidance.

[0681] Furthermore, if the user voice-inputs "I'm tired and want to rest somewhere," the emotion engine will determine the user's state as "fatigue," and the server will provide information about places to relax, such as "You can relax in a nearby park."

[0682] When a user wants to search for a restaurant based on specific criteria, they can use the free word search function. For example, they can enter a search query such as "a table for drinking with my boss under 4000 yen, smoking allowed." The device sends this input to the server, which then generates a list of restaurants that match the criteria. Search results include candidates such as "XX restaurant, △△ bistro." When the user selects the desired restaurant and makes a reservation, the device sends the reservation information to the server, and the server confirms the reservation and returns the information to the device.

[0683] In this way, the present invention provides real-time information based on the user's current location and also provides information that takes the user's emotions into consideration. Restaurant search and reservation functions are also integrated, making this a system that greatly improves user convenience.

[0684] The processing flow will be explained below.

[0685] Providing recommended information for the area you are currently walking in (embedded emotion engine)

[0686] Step 1:

[0687] The user launches the app on their device.

[0688] A user taps an app icon on a device such as a smartphone or tablet to launch the application.

[0689] Step 2:

[0690] The device acquires location information.

[0691] The device's GPS sensor operates to obtain the user's current location (latitude and longitude) in real time.

[0692] The acquired location information is updated at regular intervals (for example, every 5 seconds).

[0693] Step 3:

[0694] The device sends location information to the server.

[0695] The device sends the acquired location information to the server via an HTTP request, which includes latitude, longitude, timestamp, etc.

[0696] Step 4:

[0697] The server generates recommendations.

[0698] The server analyzes the location information received and searches a database for recommended information for the surrounding area.

[0699] Generative AI is used to optimize recommendation information and generate text for voice guidance.

[0700] For example, "The cafe 50 meters ahead on the right is currently running a 20% off campaign."

[0701] Step 5:

[0702] The server sends the recommendation information to the device.

[0703] The server returns the generated text information for the voice guidance to the terminal as an HTTP response.

[0704] Step 6:

[0705] The device uses an emotion engine to analyze the user's emotions.

[0706] The terminal acquires the user's voice input or facial expression data.

[0707] An emotion engine analyzes this data to determine the user's current emotional state (e.g., "tired," "happy," etc.).

[0708] Step 7:

[0709] The device requests adjustments to the recommendations from the server.

[0710] The device sends the analysis results to the server and requests that recommendations be re-adjusted based on the user's emotional state.

[0711] Step 8:

[0712] The server adjusts recommendations based on the emotional state.

[0713] Based on the emotion analysis results, the server searches the database for new recommended information that matches the user's emotions.

[0714] For example, if the user is "tired," information about cafes and parks where they can relax is provided.

[0715] The server sends the re-adjusted recommendations to the device.

[0716] Step 9:

[0717] The device provides tailored recommendations as voice guidance.

[0718] The adjusted recommendation information text received by the device is converted into audio using a TTS (Text-to-Speech) engine.

[0719] Through the earphones, the user is given audio guidance such as, "There is a cafe where you can relax 50 meters ahead. You seem tired."

[0720] Free word search and restaurant reservations (including emotion engine)

[0721] Step 1:

[0722] The user inputs a free word.

[0723] The user enters a free word (for example, "smoking allowed, boss, under 4000 yen") into the search box within the app.

[0724] Your device temporarily stores what you type into the search box.

[0725] Step 2:

[0726] The terminal sends the free word to the server.

[0727] The device sends the saved free words to the server via an HTTP request, and the request includes the search query.

[0728] Step 3:

[0729] The server generates restaurant information based on the search query.

[0730] The server analyzes the received search query and generates restaurant information that matches the criteria from the database.

[0731] Use generative AI to optimize search results to best meet your needs.

[0732] Step 4:

[0733] The server transmits restaurant information to the terminal.

[0734] The server returns the optimized restaurant information to the terminal as an HTTP response.

[0735] Search results include details such as store name, address, opening hours, and price range.

[0736] Step 5:

[0737] The device uses an emotion engine to analyze the user's emotions.

[0738] The terminal acquires the user's voice input or facial expression data.

[0739] An emotion engine analyzes this data to determine the user's current emotional state.

[0740] Step 6:

[0741] The device makes a request to the server to tailor the search results.

[0742] The device sends the analysis results to the server and requests that the search results be re-adjusted based on the user's emotional state.

[0743] Step 7:

[0744] The server adjusts search results based on emotional state.

[0745] Based on the emotion analysis results, the server regenerates search results from the database that are appropriate to the user's emotions.

[0746] For example, if the user is in the mood for "celebration," a restaurant with special seating and courses will be offered.

[0747] Step 8:

[0748] The device displays the re-calibrated search results to the user.

[0749] The terminal displays the search results after the readjustment received to the user in list form.

[0750] Each item includes buttons such as "View details" and "Make a reservation."

[0751] Step 9:

[0752] The user selects a restaurant and makes a reservation.

[0753] The user selects the desired restaurant from the list and taps the "Make a reservation" button.

[0754] The terminal displays an interface for entering reservation information (date and time, number of people, special notes).

[0755] Step 10:

[0756] The terminal transmits the reservation information to the server.

[0757] The terminal sends the entered reservation information to the server via an HTTP request.

[0758] Step 11:

[0759] The server confirms the reservation.

[0760] Based on the reservation information received by the server, the reservation is confirmed in cooperation with the restaurant's reservation system.

[0761] The confirmed reservation information is returned to the terminal as an HTTP response.

[0762] Step 12:

[0763] The terminal notifies the user of the reservation confirmation information.

[0764] The terminal notifies the user of the received reservation confirmation information.

[0765] For example, the notification will be in the format "Reservation for XX Restaurant has been completed. Date and time: October 10, 2023, 19:00, Number of people: 2."

[0766] Example 2

[0767] 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."

[0768] Conventional information provision systems not only lack the ability to provide appropriate recommendations based on the user's location information in real time, but also the ability to adjust the information according to the user's emotional state. Furthermore, they lack the ability to allow users to search for restaurant information by specifying detailed conditions and make immediate reservations. This makes it difficult to improve user satisfaction and results in low convenience.

[0769] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0770] In this invention, the server includes a means for acquiring location information of the area where the user is currently walking, a means for transmitting the location information to the server, and a means for generating recommendation information based on the location information. This enables real-time information provision based on the user's current location. It also includes an emotion engine that analyzes the user's emotional state and a means for adjusting recommendation information based on the emotional state. This enables information provision according to the user's emotions. Furthermore, by including a means for generating recommendation information and restaurant information using a generative AI model and a means for generating information based on a prompt sentence entered by the user, highly accurate information provision that satisfies the user is realized. Furthermore, by including a means for the user to input a search query using free words, a means for generating restaurant information based on the search query, and a means for making a reservation at a specific restaurant based on the search query, a highly convenient restaurant search and reservation function is also provided.

[0771] "User" refers to a person who uses the system.

[0772] "Location Information" refers to geographic data including a user's current latitude and longitude.

[0773] "Server" refers to a computer system that receives and processes data sent from a user's terminal.

[0774] An "emotion engine" refers to a combination of software or hardware that analyzes a user's voice and facial expressions to determine the user's emotional state.

[0775] "Recommended information" refers to information generated based on the user's location information and emotional state, and includes places and events that may be of interest to the user.

[0776] "Audio guidance" refers to guidance information provided to the user by voice.

[0777] A "free word search" refers to a search that is conducted by the user entering any word or phrase.

[0778] A "search query" refers to text data that represents search conditions or requests that a user inputs into a system.

[0779] "Restaurant information" refers to various data about restaurants (e.g., restaurant name, price range, seating availability, etc.) generated by the system based on a user's search query.

[0780] "Generative AI models" refer to algorithms and systems that use artificial intelligence to generate information based on user requests.

[0781] A "prompt sentence" refers to the input text that serves as the basis for generating information for a generative AI model.

[0782] The present invention is a system that provides real-time information related to the area where a user is currently walking, including an emotion engine that recognizes the user's emotions and adjusts recommended information. The system acquires the user's location information, generates recommended information based on that information, and provides it as voice guidance. The user can also input a free-word search query, generate restaurant information based on that, and make reservations. The emotion engine analyzes the user's voice input and facial expressions and adjusts the information provided based on the results of the analysis.

[0783] When a user launches an application, the device uses a GPS sensor to obtain the current location (latitude and longitude) in real time. This location information is sent to a server. The device is equipped with a GPS sensor and a communication module required for sending and receiving data. Specific hardware examples include smartphones, tablets, and laptops.

[0784] The server uses the generated AI to search for recommendations in the surrounding area based on the received location information. The generated AI can be, for example, OpenAI's GPT-4. The server sends the following prompt to the generated AI:

[0785] "Tell me some recommended spots near my current location"

[0786] Based on the information provided by the generating AI, the server further organizes the information and sends it to the terminal.

[0787] The device then provides the received information to the user as voice guidance, using voice synthesis software such as the Google Cloud Text-to-Speech API.

[0788] By incorporating an emotion engine, the system analyzes the user's emotional state and adjusts recommendations based on that information. The device uses a microphone to collect the user's voice input and a camera to recognize the user's facial expressions. The emotion engine can use the Google Cloud Speech-to-Text API or Azure's Emotion API. For example, if the user says "I'm tired," the emotion engine will recommend cafes and quiet places where the user can relax. If the user has a smiling expression, the emotion engine will suggest fun events and restaurants with a cheerful atmosphere.

[0789] As a concrete example, consider the case where a user is walking around Shinjuku Station. The user launches an application, and the device acquires location information around Shinjuku Station. Based on this location information, the server generates recommendation information such as, "There's a new cafe about a three-minute walk away. They're currently offering half-price drinks as part of their opening campaign." and sends this information to the device. The device then relays this information to the user as voice guidance.

[0790] Furthermore, if the user voice-inputs "I'm tired and want to rest somewhere," the emotion engine will determine the user's state as "fatigue," and the server will provide information about places to relax, such as "You can relax in a nearby park."

[0791] When a user wants to search for a restaurant based on specific criteria, they can use the free word search function. For example, they can enter a search query such as "a table for drinking with my boss under 4000 yen, smoking allowed." The device sends this input to the server, which then generates a list of restaurants that match the criteria. Search results include candidates such as "XX restaurant, △△ bistro." When the user selects the desired restaurant and makes a reservation, the device sends the reservation information to the server, and the server confirms the reservation and returns the information to the device.

[0792] In this way, the present invention provides real-time information based on the user's current location and also provides information that takes the user's emotions into consideration. Restaurant search and reservation functions are also integrated, making this a system that greatly improves user convenience.

[0793] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0794] Step 1:

[0795] The user launches the application

[0796] A user taps an application on their smartphone to launch it. The device loads the application's interface and various functions and becomes ready. The user's operation is the input, and the application screen is displayed as the output.

[0797] Step 2:

[0798] The device obtains its current location

[0799] The device activates its built-in GPS sensor and obtains its current latitude and longitude information. Specifically, the device's location service is activated and receives signals from GPS satellites to determine its location. The input is the signal from the GPS satellites, and the output is the obtained latitude and longitude information. This data is stored internally in JSON format or other appropriate format.

[0800] Step 3:

[0801] Sending location information

[0802] The device packs the acquired location information into packets and sends them to the server using the HTTPS protocol. The input is the latitude and longitude information acquired by the device, and the output is data that is sent to the server. The specific operation utilizes the device's communication module.

[0803] Step 4:

[0804] Server-generated recommendations

[0805] The server sends a specific prompt to the generative AI model (e.g., a generation algorithm) based on the received location information. This prompt might be something like, "Tell me some recommended spots near the user's current location." The server receives the location information as input, and uses that information to process the data to generate an appropriate prompt. The output is recommendations based on this prompt. A cloud-based model (e.g., GPT-4) is used as the generative AI, which returns the results to the server.

[0806] Step 5:

[0807] Analysis by emotion engine

[0808] The device uses a microphone to collect the user's voice input and a camera to recognize facial expressions. Inputs include the user's voice data and video data from the camera. This data is sent to a local emotion analysis engine. Specifically, Google Cloud Speech-to-Text API and Azure Emotion API are used. Data processing involves converting the voice data into text and determining the user's emotional state, and the results are output.

[0809] Step 6:

[0810] Server-adjusted recommendations

[0811] The server adjusts the recommendation information based on the emotional information received from the emotion engine. The input is data on the user's emotional state, and the output is new recommendation information generated according to the emotion. For example, if the user's state is determined to be "fatigue," the server adjusts the recommendation information to provide information on relaxing cafes and quiet spots.

[0812] Step 7:

[0813] Providing recommendations

[0814] The device receives the final recommendation information sent from the server and provides it to the user as voice guidance. Specifically, it generates synthetic voice using Google Cloud Text-to-Speech API, etc. The input is the recommendation information data from the server, and the output is the generated voice guidance, which is provided to the user.

[0815] Step 8:

[0816] Perform a free word search

[0817] The user enters a free word containing a specific requirement into the search bar within the application. For example, a search query such as "a table for drinks with my boss for under 4000 yen, smoking allowed" is entered. The input is the user's free-form text data, which the device packs into packets to send to the server. The output is the data to be sent to the server.

[0818] Step 9:

[0819] Server generates restaurant information

[0820] Based on a free-word search query, the server uses a generative AI model to generate information about restaurants that match the criteria. For example, using the "Search for Restaurants" prompt. The input is the search query data, and the output is a list of restaurants based on the search criteria. This information is processed on the server and may also retrieve information from databases or external APIs.

[0821] Step 10:

[0822] Providing restaurant information and reservations

[0823] The user selects the restaurant of their choice and makes a reservation. The terminal packs the reservation information into a packet and sends it to the server. The input is the user's selection data and reservation information, and the output is the data to be sent to the server. The server processes the received reservation information and makes an actual reservation request to the restaurant. Information indicating that the reservation has been confirmed is then returned to the terminal, and the terminal notifies the user that the reservation has been confirmed.

[0824] (Application example 2)

[0825] 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."

[0826] Conventional navigation systems and information systems provide recommended information based on the user's current location, but because they do not take the user's emotional state into account, they may not fully meet the needs of individual users. Furthermore, even systems that provide restaurant information or have reservation functions have difficulty providing appropriate information based on the user's mood and situation. Therefore, the present invention aims to provide information that reflects the user's emotional state and customized navigation guidance for autonomous vehicles.

[0827] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring location information of the area where the user is currently located, means for transmitting the location information to the server, and means for generating recommended information based on the location information. This makes it possible to provide information in real time based on the user's current location.

[0828] Furthermore, a means for analyzing the emotional state of the user and a means for adjusting the recommended information based on the emotional state are added, thereby enabling the provision of information customized according to the user's mood and state.

[0829] The system also includes a means for inputting a search query using free words, a means for generating restaurant information based on the search query, a means for providing the restaurant information to the user, a means for reserving a specific restaurant based on the search query, and a means for adjusting the restaurant information based on the emotional state, thereby enabling the user to search for restaurants using detailed conditions and obtain optimal results according to their emotions.

[0830] "Location information of the area where the user is currently located" is data that indicates the geographical location where the user is located at a particular point in time.

[0831] A "server" is a computer system that processes and stores information over a network and provides data and services to client devices.

[0832] "Recommended information" is useful data or guidance that is generated based on the user's current location and other conditions and provided to the user.

[0833] "Audio guidance" is a method of providing information to a user using audio.

[0834] "Emotional state" refers to the user's current mood and psychological state, and analyzing this makes it possible to provide information suited to the user's needs and requests.

[0835] A "conditioning tool" is a method or process that changes or optimizes information or data based on specific conditions or criteria.

[0836] A "means for entering a search query using free words" is an interface that allows users to search for information using any word or phrase.

[0837] "Restaurant information" is information about a specific restaurant, including location, menu, price, and ratings.

[0838] A "reservation means" is a method or tool that a user uses to reserve a particular service or facility in advance.

[0839] A "generative AI model" is an algorithm that uses generative adversarial networks and other artificial intelligence techniques to automatically generate new data or information based on input data.

[0840] A "prompt sentence" is a string or sentence that is input to a generative AI model to prompt it to generate appropriate data.

[0841] The present invention is a system that acquires location information of the user's current location, analyzes the user's emotional state based on that information, and provides appropriate recommended information as audio guidance. The following hardware and software are used to implement the present invention.

[0842] Hardware

[0843] GPS sensor: Used to obtain the user's current location in real time.

[0844] Microphone and camera: Used to analyze the user's voice input and facial expressions to determine their emotional state.

[0845] Terminal (smartphone or in-car display): Used to run the system and provide voice guidance to the user.

[0846] Server: Used to generate recommendations using a generative AI model based on the user's location and emotional state, and send them to the device.

[0847] software

[0848] Location information acquisition software (GPS library): Works with the GPS sensor to acquire the user's current location.

[0849] Emotion analysis software (EmotionEngine): Analyzes the user's voice input and facial expression data to determine their emotional state.

[0850] Text-to-Speech software: Provides users with recommended information as audio guidance.

[0851] Generative AI model: Generates recommendations based on the user's current location and emotional state.

[0852] Processing flow explanation

[0853] 1. Location information acquisition: The device uses the GPS sensor to acquire the user's current location (latitude and longitude) in real time. This location information is sent to the server.

[0854] 2. Emotional state analysis: The device's microphone and camera are used to collect the user's voice input and facial expressions, which are then analyzed by the Emotion Engine.

[0855] 3. Information generation: The server receives the user's location information and emotional state and generates recommendations using a generative AI model. For example, it analyzes prompts such as "Recommend places around (latitude, longitude) for a person feeling (emotion)."

[0856] 4. Providing information: The server sends the generated recommendation information to the terminal, which uses TextToSpeech software to provide it to the user as voice guidance.

[0857] Specific examples

[0858] When a user is in an autonomous vehicle, the system operates as follows: Suppose the user's vehicle arrives at its current location (e.g., Shinjuku Ward, Tokyo). The GPS acquires this location information and sends it to the server. At the same time, the user vocally inputs, "I'm tired." The Emotion Engine analyzes this voice and determines the user's emotional state as "fatigue." The server sends the prompt "Recommend places around 35.6895,139.6917 for a person feeling tired" to the generative AI model, generating information recommending places to relax. The device receives this information and provides voice guidance to the user, saying, "The nearby cafe is quiet and relaxing."

[0859] In this way, the present invention provides real-time information based on the user's current location and emotional state, enabling customized navigation guidance, particularly in autonomous vehicles.

[0860] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0861] Step 1:

[0862] The device uses the GPS sensor to obtain the user's current location (latitude and longitude) in real time. This location information becomes input data, and the device sends it to the server.

[0863] Step 2:

[0864] Based on the location information received, the server retrieves information about the surrounding area from a database and sends a prompt to the generative AI model based on that information. This prompt includes a sentence in the format "Recommend places around (latitude, longitude)." The AI ​​model generates recommendations based on this prompt. The generated recommendations become the output data.

[0865] Step 3:

[0866] The device collects the user's voice input and facial expressions using a microphone and camera, and sends the data to the Emotion Engine. This input data is analyzed by the Emotion Engine, which determines the user's emotional state. The analysis results are output as emotions such as "fatigue" or "enjoyment."

[0867] Step 4:

[0868] The server receives the emotional state output from the Emotion Engine and adjusts the recommendation information based on that information. For example, if the user's emotional state is "fatigue," it will prioritize recommendations of cafes and parks where people can relax. This adjusted information is then output again.

[0869] Step 5:

[0870] The server sends the adjusted recommendations to the device, which then uses TextToSpeech software to provide the recommendations to the user as voice guidance, which is the final output.

[0871] Step 6:

[0872] When a user wants to perform a free-word search, they input a search query into their device. This query becomes input data and is sent to the server. The server retrieves restaurant information from a database based on this query and generates appropriate restaurant information using a generative AI model.

[0873] Step 7:

[0874] The server sends the generated restaurant information to the terminal. The terminal displays the information to the user, who selects the desired restaurant and makes a reservation. This reservation information is sent to the server, which processes the reservation. Reservation confirmation information is sent to the terminal and notified to the user.

[0875] This allows users to obtain real-time information about their current location and experience navigation guidance customized to their emotional state.

[0876] 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.

[0877] 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.

[0878] 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.

[0879] [Third embodiment]

[0880] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0881] 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.

[0882] 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).

[0883] 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.

[0884] 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.

[0885] 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).

[0886] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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."

[0892] The present invention is a system for providing real-time information related to the area in which a user is currently walking. This system acquires the user's location information, transmits it to a server, and provides audio guidance on recommendations, deals, weather, and other information based on the location information. The user can also enter a search query using free words, and the server will provide appropriate restaurant information based on the query and even allow the user to make reservations at those restaurants. The system's program processing is described in detail below in natural language.

[0893] First, the user launches the application. The device uses a GPS sensor to obtain the user's current location in real time. This location information is sent from the device to the server. The server receives the location information and uses a generation AI to search for recommendation information in the surrounding area. The generated recommendation information might be something like, "There is currently a 20% off campaign at the cafe 50 meters ahead on the right." The server sends this information to the device, and the device delivers the received information to the user as voice guidance.

[0894] Next, consider the case where a user uses free words to search for restaurants that meet specific criteria. The user enters the search criteria into the search box within the app, and the device sends this input to the server. The server analyzes the received free words and uses generative AI to search for appropriate restaurant information. Search results may include, for example, "XX restaurant, △△ bistro." These results are sent to the device, which displays them to the user in a list format.

[0895] When the user selects the desired restaurant from the list and makes a reservation, the terminal sends the entered reservation information back to the server. The server then connects with the restaurant's reservation system and confirms the reservation. Once the reservation is confirmed, the information is sent to the terminal and the user is notified. The user is provided with information such as, "Your reservation at Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[0896] As a concrete example, consider a case where a user is walking around Shinjuku Station. The user launches an application, and the device acquires location information around Shinjuku Station. Based on this location information, the server generates recommendation information, such as "A cafe on the street in front of the station is offering a limited-time discount on parfaits," and sends it to the device. The device then notifies the user of this information as voice guidance. Furthermore, if the user performs a free-word search for "a restaurant where I can drink with my boss for under 4,000 yen and where smoking is permitted," the server searches for restaurants that match the criteria and sends the results to the device. The user can then select the desired restaurant from the displayed list and make a reservation.

[0897] In this way, the present invention provides a system that provides real-time information related to the area the user is currently walking through, generates restaurant information tailored to the user's individual needs based on the user's search query, and allows the user to easily make reservations at those restaurants.

[0898] The processing flow will be explained below.

[0899] Providing recommended information for the area you are currently walking through

[0900] Step 1:

[0901] The user launches the app on their device.

[0902] A user taps an app icon on a device such as a smartphone or tablet to launch the application.

[0903] Step 2:

[0904] The device acquires location information.

[0905] The device's GPS sensor operates to obtain the user's current location (latitude and longitude) in real time.

[0906] The acquired location information is updated at regular intervals (for example, every 5 seconds).

[0907] Step 3:

[0908] The device sends location information to the server.

[0909] The device sends the acquired location information to the server via an HTTP request, which includes latitude, longitude, timestamp, etc.

[0910] Step 4:

[0911] The server generates recommendations.

[0912] The server analyzes the location information received and searches a database for recommended information for the surrounding area.

[0913] Generative AI is used to optimize recommendation information and generate text for voice guidance.

[0914] For example, "The cafe 50 meters ahead on the right is currently running a 20% off campaign."

[0915] Step 5:

[0916] The server sends the recommendation information to the device.

[0917] The server returns the generated text information for the voice guidance to the terminal as an HTTP response.

[0918] Step 6:

[0919] The device provides voice guidance.

[0920] The text information for voice guidance received by the device is converted into voice using a TTS (Text-to-Speech) engine.

[0921] Through the earphones, the user is given voice guidance such as, "There is currently a 20% off campaign at the cafe on the right, 50 meters ahead."

[0922] Free word search and restaurant reservations

[0923] Step 1:

[0924] The user inputs a free word.

[0925] The user enters a free word (for example, "smoking allowed, boss, under 4000 yen") into the search box within the app.

[0926] Your device temporarily stores what you type into the search box.

[0927] Step 2:

[0928] The terminal sends the free word to the server.

[0929] The device sends the saved free words to the server via an HTTP request, and the request includes the search query.

[0930] Step 3:

[0931] The server generates restaurant information based on the search query.

[0932] The server analyzes the received search query and generates restaurant information that matches the criteria from the database.

[0933] Use generative AI to optimize search results to best meet your needs.

[0934] Step 4:

[0935] The server transmits restaurant information to the terminal.

[0936] The server returns the optimized restaurant information to the terminal as an HTTP response.

[0937] Search results include details such as store name, address, opening hours, and price range.

[0938] Step 5:

[0939] The terminal displays the search results to the user.

[0940] The terminal displays the search results received to the user in list form.

[0941] Each item includes buttons such as "View details" and "Make a reservation."

[0942] Step 6:

[0943] The user selects a restaurant and makes a reservation.

[0944] The user selects the desired restaurant from the list and taps the "Make a reservation" button.

[0945] The terminal displays an interface for entering reservation information (date and time, number of people, special notes).

[0946] Step 7:

[0947] The terminal transmits the reservation information to the server.

[0948] The terminal sends the entered reservation information to the server via an HTTP request.

[0949] Step 8:

[0950] The server confirms the reservation.

[0951] Based on the reservation information received by the server, the reservation is confirmed in cooperation with the restaurant's reservation system.

[0952] The confirmed reservation information is returned to the terminal as an HTTP response.

[0953] Step 9:

[0954] The terminal notifies the user of the reservation confirmation information.

[0955] The terminal notifies the user of the received reservation confirmation information.

[0956] For example, the notification will be in the format "Reservation for XX Restaurant has been completed. Date and time: October 10, 2023, 19:00, Number of people: 2."

[0957] Example 1

[0958] 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."

[0959] There is a demand for a system that provides useful information in real time based on the user's current location information and enables easy and fast acquisition and reservation of restaurant information based on the user's individual search query. However, existing systems often lack sufficient speed and accuracy in providing information, or have difficulty providing information tailored to the user's needs. In particular, there is a lack of systems that seamlessly generate recommendation information in real time and make restaurant reservations based on free word searches.

[0960] 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.

[0961] In this invention, the server includes means for acquiring location information of an area where a user is currently walking, means for transmitting the location information to the server, means for generating recommendation information using a generative AI model based on the location information, means for providing the recommendation information to the user as audio guidance, means for the user to input a search query using free words, means for generating restaurant information using a generative AI model based on the search query, means for providing the restaurant information to the user, and means for making reservations at a specific restaurant based on the restaurant information. This enables the provision of real-time information based on the user's current location and the rapid provision of restaurant information and reservations that meet the user's individual needs.

[0962] "User" refers to an individual who uses the system to obtain real-time information and restaurant information and make reservations.

[0963] "Location information of the area currently being walked" refers to latitude and longitude information used to identify the user's current location using a GPS sensor or the like.

[0964] "Server" refers to a computer system that receives location information and search queries sent by users, generates information based on that information using a generative AI model, and sends it to a terminal.

[0965] A "generative AI model" refers to an artificial intelligence model that generates information in natural language based on a given prompt.

[0966] A "prompt sentence" refers to an input sentence that instructs a generative AI model to generate information.

[0967] "Recommended information" is information provided based on the user's current location using a generative AI model, such as restaurant campaign information and information about nearby facilities.

[0968] "Voice guidance" refers to a function that conveys recommended information generated by the device to the user by voice.

[0969] A "free word search query" refers to an input sentence in which a user enters any word within an application to search for information.

[0970] "Restaurant Information" refers to information about restaurants generated based on free-word search queries using a generative AI model.

[0971] "Reservation" refers to the procedure for reserving seats for a specific date, time and number of people at a restaurant of a user's choice.

[0972] "Reservation information" refers to detailed information such as the date and time and number of people entered by the user when making a reservation.

[0973] "Notification" refers to a message sent by the server to the user's terminal to inform them of reservation confirmation information or recommended information.

[0974] The present invention is a system that provides real-time information related to the area a user is currently walking in. This system acquires the user's location information, transmits it to a server, and provides audio guidance based on that location information, including recommendations, deals, and weather information. The user can also enter a search query using free words, and the server will provide information on appropriate restaurants based on that query and even allow the user to make reservations at those restaurants.

[0975] First, the user launches the application. The device uses the GPS sensor to obtain the user's current location in real time. This location information is then sent from the device to the server. The secure HTTPS protocol is used for communication to ensure data safety.

[0976] Once the server receives the location information, it uses a generative AI model, such as OpenAI's GPT-4, to generate recommendations for the surrounding area.

[0977] Example prompt sentence:

[0978] "The user is currently at Shinjuku Station. Are there any recommended cafes or restaurants nearby?"

[0979] The generative AI model generates appropriate recommendations based on these prompts. Examples of generated information include specific information such as, "The cafe 50 meters ahead on the right is currently offering a 20% off campaign." The generated recommendations are sent from the server to the device, which then converts the information into voice data using speech synthesis software (e.g., Google Text-to-Speech) and provides it to the user.

[0980] Next, we will explain how a user can use free words to search for restaurants that meet specific criteria. The user enters the search criteria into the search box within the app, and the device sends this input to the server. The server analyzes the received free words and uses the generative AI model again to search for appropriate restaurant information.

[0981] Example prompt sentence:

[0982] "Please tell me a restaurant where I can smoke while drinking with my boss for under 4,000 yen."

[0983] Based on this prompt, the generative AI model generates search results and returns them to the server. Examples of search results include "X restaurant, △△ bistro." These results are sent from the server to the device, which displays them to the user in list form. The user then selects the desired restaurant from the displayed list and makes a reservation.

[0984] When the user selects the desired restaurant from the list and makes a reservation, the terminal sends the entered reservation information back to the server. The server then connects with the restaurant's reservation system to confirm the reservation. Once the reservation is confirmed, the information is sent to the terminal and the user is notified. An example of a notification might include information such as, "Your reservation at Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[0985] As a concrete example, imagine a user walking around Shinjuku Station. The user launches an application, and the device obtains location information around Shinjuku Station. Based on this location information, the server generates recommendation information, such as "A cafe on the street in front of the station is offering a limited-time discount on parfaits," and sends it to the device. The device then notifies the user of this information as voice guidance. If the user then performs a free-word search for "a restaurant where I can drink with my boss for under 4,000 yen and where smoking is allowed," the server searches for restaurants that match the criteria and sends the results to the device. The user can then select the restaurant of their choice from the displayed list and make a reservation.

[0986] In this way, the present invention provides a system that provides real-time information related to the area in which a user is currently walking, generates restaurant information tailored to individual needs based on the user's search query, and allows users to easily make reservations at those restaurants.

[0987] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0988] Step 1: Launch the application and get location information

[0989] The user launches an application.

[0990] The device activates the GPS sensor to obtain the user's current location, and obtains latitude and longitude information from the GPS sensor and updates it in real time.

[0991] Input: User application launch operation

[0992] Processing: GPS sensor acquires latitude and longitude information

[0993] Output: Current location (latitude, longitude)

[0994] Step 2: Send location information

[0995] The terminal transmits the acquired location information to the server using a secure communication protocol (for example, HTTPS).

[0996] Input: Location information (latitude, longitude)

[0997] Processing: Encrypt location information and send it to the server

[0998] Output: Location information sent to the server

[0999] Step 3: Generate recommendations

[1000] The server uses a generative AI model to generate nearby recommendations based on the received location information. As part of the generation process, it generates location-based prompts.

[1001] Example prompt: "The user is currently at Shinjuku Station. Are there any recommended cafes or restaurants nearby?"

[1002] Input: Location information (latitude, longitude)

[1003] Processing: Generative AI model generates information based on prompts

[1004] Output: Recommendation information (e.g. "The cafe on the right, 50 meters away, is currently offering a 20% discount campaign.")

[1005] Step 4: Send recommendations and voice guidance

[1006] The server transmits the generated recommendation information to the terminal.

[1007] The terminal uses voice synthesis software to convert the received recommendation information into voice data, which is then provided to the user as voice guidance.

[1008] Input:Recommendations

[1009] Processing: Converted into voice data using speech synthesis software and played through speakers

[1010] Output: Voice guidance (e.g. "There is a 20% off campaign going on at the cafe on your right, 50 meters ahead.")

[1011] Step 5: Enter and submit a free word search

[1012] The user enters a free word search query into a search box within the application.

[1013] The terminal transmits the entered search query to the server.

[1014] Input: Search query (e.g., "Restaurants where you can drink with your boss and smoke for under 4,000 yen")

[1015] Process: Send the search query to the server

[1016] Output: The search query sent to the server

[1017] Step 6: Generate search results

[1018] The server analyzes the received search query and generates appropriate restaurant information using a generative AI model. It also generates search results based on the prompt text.

[1019] Example prompt: "Please tell me a restaurant where I can smoke and drink with my boss for under 4000 yen."

[1020] Input: Search query

[1021] Processing: Generative AI model generates information based on prompts

[1022] Output: Restaurant information (e.g., "XX Restaurant, △△ Bistro")

[1023] Step 7: View and select search results

[1024] The terminal displays the restaurant information sent from the server in a list format to the user, and the user selects the restaurant of their choice from the displayed list.

[1025] Input: Restaurant information

[1026] Action: Display information in list format

[1027] Output: List view and user selection

[1028] Step 8: Submit and confirm your reservation

[1029] The terminal transmits reservation information for the restaurant selected by the user to the server, including the date, time, number of people, etc.

[1030] The server connects with the restaurant's reservation system to confirm the reservation.

[1031] Input: Reservation information (date, time, number of people, etc.)

[1032] Process: Link with reservation system and confirm reservation

[1033] Output: Confirmed reservation information

[1034] Step 9: Notification of confirmed reservation information

[1035] The server transmits information that the reservation has been confirmed to the terminal, and the terminal notifies the user of the information.

[1036] Input: Confirmed reservation information

[1037] Processing: Send to device and notify user

[1038] Output: Notification (e.g. "Your reservation for Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2")

[1039] These steps will enable users to smoothly access real-time local information, search for restaurants, and make reservations.

[1040] (Application example 1)

[1041] 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."

[1042] In modern cities, there is an increasing need for users to quickly obtain real-time information about the places they are walking, especially about discount campaigns, recommended places, and emergency weather information. Users also need to be able to easily search for restaurants and stores that meet specific criteria and smoothly make reservations. However, existing systems are limited in the information they can provide and lack real-time capabilities and ease of operation.

[1043] 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.

[1044] In this invention, the server includes means for acquiring location information, means for transmitting the location information to the server, means for generating recommendation information based on the location information using a generative AI model, means for providing the generated recommendation information as voice guidance and as an augmented reality display, means for displaying store information based on a search query entered by a user, and means for confirming a reservation for the store online. This allows a user to receive real-time information related to their current location by voice and augmented reality, making it even easier to search for and make reservations for restaurants and stores.

[1045] "Location information" refers to geographic data such as the latitude and longitude of a user's current physical location.

[1046] "Server" means a computer system accessible over a network that receives and processes data, such as location information or search queries, and provides the results.

[1047] A "generative AI model" refers to an algorithm or program that uses artificial intelligence techniques to generate useful information based on a user's location or search query.

[1048] "Recommended information" refers to information about stores and services suggested based on the user's current location and interests.

[1049] "Audio guidance" refers to a technology that provides information to users by reading out text information aloud.

[1050] "Augmented reality display" refers to a technology that displays digital information superimposed on the actual field of vision.

[1051] A "search query" refers to free words or conditions that a user enters to search for specific information.

[1052] "Store information" refers to detailed information such as the name, location, business hours, and service details of restaurants, retail stores, etc.

[1053] "Reservation" refers to the advance application procedure for a user to use a store or service on a specific date and time.

[1054] A system for implementing this invention provides real-time information related to the area a user is currently walking in. The system is composed of a terminal such as a smartphone or smart glasses, and a server.

[1055] First, when a user launches the application, the device uses a GPS sensor to obtain the user's current location in real time. This location information is then sent to a server via the Internet. The server then uses a generative AI model to generate recommendations for the area based on the received location information. For example, the generated information might be something like, "There's a 20% off campaign going on at the cafe 50 meters ahead on the right." The generated recommendations are then provided to the user via the smartphone screen, voice guidance, or augmented reality display on the smart glasses.

[1056] Next, consider the case where a user uses the device's free-word search function to search for restaurant information based on specific criteria. For example, if the user enters "restaurants where I can drink with my boss and where smoking is allowed for under 4,000 yen," the device sends this search query to the server. The server uses a generative AI model to search for and generate relevant restaurant information and sends the search results to the device. The device displays the results to the user in a list format, such as "X Restaurant, XX Bistro." The user selects the desired restaurant from the list and completes the reservation online. Once the reservation is confirmed, the server sends the information to the device, and the user is notified in the form of a message such as, "Your reservation for X Restaurant has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[1057] The hardware used to implement the system includes smartphones and smart glasses with built-in GPS sensors. The software uses generative AI models (e.g., GPT-3) and speech synthesis libraries (e.g., pyttsx3). The generative AI models are particularly important in generating information in real time based on the user's current location and search query.

[1058] As a concrete example, consider the case where a user is walking around Shinjuku Station. The application obtains location information around Shinjuku Station, and the server generates recommendation information such as "A cafe on the street in front of the station is offering a limited-time discount on parfaits." This information is displayed in augmented reality through the smart glasses and also conveyed via voice guidance. The user can also easily search for "izakayas where you can drink for under 3,000 yen" and make a reservation from the suggested restaurants.

[1059] An example of a program prompt is:

[1060] "Tell me about great deals within 500 meters of my current location"

[1061] "Please find a restaurant where I can smoke while drinking with my boss for under 4,000 yen."

[1062] These prompts allow the generative AI model to provide users with relevant information, enabling real-time information retrieval and a convenient booking experience.

[1063] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1064] Step 1:

[1065] The user launches the application. The device uses the built-in GPS sensor to obtain the user's current location in real time. The obtained location information is sent to the server in the form of latitude and longitude.

[1066] Input: Real-time location information (latitude and longitude) from the GPS sensor

[1067] Data processing / calculation: Acquisition and transmission of location information

[1068] Output: Send location information to the server

[1069] Step 2:

[1070] The server receives the location information and uses a generative AI model to generate recommendations for the area based on the location information. For example, it generates information such as "There is currently a 20% off campaign at the cafe on the right, 50 meters away."

[1071] Input: Location information (latitude and longitude) sent from the device

[1072] Data processing / calculation: Generating recommendations using generative AI models

[1073] Output: Recommendations

[1074] Step 3:

[1075] The server sends the generated recommendation information to the device, which then provides the received recommendation information to the user in the form of voice guidance and augmented reality display. On smartphones, this is done by displaying the screen and providing voice notifications, while on smart glasses, this is done by providing augmented reality display.

[1076] Input: Recommendations sent from the server

[1077] Data processing / calculation: Format conversion of recommended information (voice, augmented reality)

[1078] Output: Voice guidance and augmented reality display

[1079] Step 4:

[1080] A user inputs a search query using free words. For example, if the user inputs "a restaurant where I can drink with my boss and where smoking is allowed for less than 4,000 yen," the search query is sent from the device to the server.

[1081] Input: User's search query (free word)

[1082] Data processing / calculation: Sending search queries

[1083] Output: Sending a search query to the server

[1084] Step 5:

[1085] The server analyzes the received search query and uses a generative AI model to generate appropriate restaurant information, such as "XX Restaurant, △△ Bistro."

[1086] Input: Search query sent from the device

[1087] Data processing / calculation: Generate restaurant information using generative AI models

[1088] Output: Restaurant information

[1089] Step 6:

[1090] The server sends the generated restaurant information to the terminal, which displays the search results in a list to the user, who then selects the restaurant of their choice from the list.

[1091] Input: Restaurant information sent from the server

[1092] Data processing / calculation: Displaying restaurant information in list format

[1093] Output: List of restaurants

[1094] Step 7:

[1095] The user selects the restaurant of their choice and makes a reservation. The terminal sends the reservation information to the server. The server then connects with the restaurant's reservation system to confirm the reservation.

[1096] Input: User's restaurant selection and reservation information

[1097] Data processing / calculation: Sending reservation information and linking with reservation systems

[1098] Output: Confirmed reservation information

[1099] Step 8:

[1100] The server sends the information that the reservation has been confirmed to the terminal. The terminal then notifies the user of the reservation confirmation information. For example, the terminal may notify the user that "Your reservation at Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[1101] Input: Confirmed reservation information sent from the server

[1102] Data processing / calculation: Notification of reservation confirmation information

[1103] Output: Confirmation of reservation sent to user

[1104] 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.

[1105] The present invention is a system that provides real-time information related to the area where a user is currently walking, and includes an emotion engine that recognizes the user's emotions and adjusts recommended information. The system acquires the user's location information, generates recommended information based on that information, and provides it as voice guidance. The user can also enter a free-word search query, generate restaurant information based on that, and make reservations. The emotion engine analyzes the user's voice input and facial expressions, and adjusts the information provided based on the results of that analysis. The system's program processing is specifically explained below in natural language.

[1106] When a user launches the application, the device uses the GPS sensor to obtain the current location (latitude and longitude) in real time. This location information is sent to the server. The server uses a generation AI to search for recommended information in the surrounding area based on the received location information and sends the results to the device. The device then provides the received information to the user as voice guidance.

[1107] By incorporating an emotion engine, the system can analyze the user's emotional state and adjust recommendations based on that information. For example, if the user says "I'm tired," the emotion engine will recommend cafes and quiet places where the user can relax. Also, if the user has a smiling expression, the emotion engine will suggest fun events and restaurants with a cheerful atmosphere.

[1108] As a concrete example, consider the case where a user is walking around Shinjuku Station. The user launches an application, and the device acquires location information around Shinjuku Station. Based on this location information, the server generates recommendation information such as, "There's a new cafe about a three-minute walk away. They're currently offering half-price drinks as part of their opening campaign." and sends this information to the device. The device then relays this information to the user as voice guidance.

[1109] Furthermore, if the user voice-inputs "I'm tired and want to rest somewhere," the emotion engine will determine the user's state as "fatigue," and the server will provide information about places to relax, such as "You can relax in a nearby park."

[1110] When a user wants to search for a restaurant based on specific criteria, they can use the free word search function. For example, they can enter a search query such as "a table for drinking with my boss under 4000 yen, smoking allowed." The device sends this input to the server, which then generates a list of restaurants that match the criteria. Search results include candidates such as "XX restaurant, △△ bistro." When the user selects the desired restaurant and makes a reservation, the device sends the reservation information to the server, and the server confirms the reservation and returns the information to the device.

[1111] In this way, the present invention provides real-time information based on the user's current location and also provides information that takes the user's emotions into consideration. Restaurant search and reservation functions are also integrated, making this a system that greatly improves user convenience.

[1112] The processing flow will be explained below.

[1113] Providing recommended information for the area you are currently walking in (embedded emotion engine)

[1114] Step 1:

[1115] The user launches the app on their device.

[1116] A user taps an app icon on a device such as a smartphone or tablet to launch the application.

[1117] Step 2:

[1118] The device acquires location information.

[1119] The device's GPS sensor operates to obtain the user's current location (latitude and longitude) in real time.

[1120] The acquired location information is updated at regular intervals (for example, every 5 seconds).

[1121] Step 3:

[1122] The device sends location information to the server.

[1123] The device sends the acquired location information to the server via an HTTP request, which includes latitude, longitude, timestamp, etc.

[1124] Step 4:

[1125] The server generates recommendations.

[1126] The server analyzes the location information received and searches a database for recommended information for the surrounding area.

[1127] Generative AI is used to optimize recommendation information and generate text for voice guidance.

[1128] For example, "The cafe 50 meters ahead on the right is currently running a 20% off campaign."

[1129] Step 5:

[1130] The server sends the recommendation information to the device.

[1131] The server returns the generated text information for the voice guidance to the terminal as an HTTP response.

[1132] Step 6:

[1133] The device uses an emotion engine to analyze the user's emotions.

[1134] The terminal acquires the user's voice input or facial expression data.

[1135] An emotion engine analyzes this data to determine the user's current emotional state (e.g., "tired," "happy," etc.).

[1136] Step 7:

[1137] The device requests adjustments to the recommendations from the server.

[1138] The device sends the analysis results to the server and requests that recommendations be re-adjusted based on the user's emotional state.

[1139] Step 8:

[1140] The server adjusts recommendations based on the emotional state.

[1141] Based on the emotion analysis results, the server searches the database for new recommended information that matches the user's emotions.

[1142] For example, if the user is "tired," information about cafes and parks where they can relax is provided.

[1143] The server sends the re-adjusted recommendations to the device.

[1144] Step 9:

[1145] The device provides tailored recommendations as voice guidance.

[1146] The adjusted recommendation information text received by the device is converted into audio using a TTS (Text-to-Speech) engine.

[1147] Through the earphones, the user is given audio guidance such as, "There is a cafe where you can relax 50 meters ahead. You seem tired."

[1148] Free word search and restaurant reservations (including emotion engine)

[1149] Step 1:

[1150] The user inputs a free word.

[1151] The user enters a free word (for example, "smoking allowed, boss, under 4000 yen") into the search box within the app.

[1152] Your device temporarily stores what you type into the search box.

[1153] Step 2:

[1154] The terminal sends the free word to the server.

[1155] The device sends the saved free words to the server via an HTTP request, and the request includes the search query.

[1156] Step 3:

[1157] The server generates restaurant information based on the search query.

[1158] The server analyzes the received search query and generates restaurant information that matches the criteria from the database.

[1159] Use generative AI to optimize search results to best meet your needs.

[1160] Step 4:

[1161] The server transmits restaurant information to the terminal.

[1162] The server returns the optimized restaurant information to the terminal as an HTTP response.

[1163] Search results include details such as store name, address, opening hours, and price range.

[1164] Step 5:

[1165] The device uses an emotion engine to analyze the user's emotions.

[1166] The terminal acquires the user's voice input or facial expression data.

[1167] An emotion engine analyzes this data to determine the user's current emotional state.

[1168] Step 6:

[1169] The device makes a request to the server to tailor the search results.

[1170] The device sends the analysis results to the server and requests that the search results be re-adjusted based on the user's emotional state.

[1171] Step 7:

[1172] The server adjusts search results based on emotional state.

[1173] Based on the emotion analysis results, the server regenerates search results from the database that are appropriate to the user's emotions.

[1174] For example, if the user is in the mood for "celebration," a restaurant with special seating and courses will be offered.

[1175] Step 8:

[1176] The device displays the re-calibrated search results to the user.

[1177] The terminal displays the search results after the readjustment received to the user in list form.

[1178] Each item includes buttons such as "View details" and "Make a reservation."

[1179] Step 9:

[1180] The user selects a restaurant and makes a reservation.

[1181] The user selects the desired restaurant from the list and taps the "Make a reservation" button.

[1182] The terminal displays an interface for entering reservation information (date and time, number of people, special notes).

[1183] Step 10:

[1184] The terminal transmits the reservation information to the server.

[1185] The terminal sends the entered reservation information to the server via an HTTP request.

[1186] Step 11:

[1187] The server confirms the reservation.

[1188] Based on the reservation information received by the server, the reservation is confirmed in cooperation with the restaurant's reservation system.

[1189] The confirmed reservation information is returned to the terminal as an HTTP response.

[1190] Step 12:

[1191] The terminal notifies the user of the reservation confirmation information.

[1192] The terminal notifies the user of the received reservation confirmation information.

[1193] For example, the notification will be in the format "Reservation for XX Restaurant has been completed. Date and time: October 10, 2023, 19:00, Number of people: 2."

[1194] Example 2

[1195] 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."

[1196] Conventional information provision systems not only lack the ability to provide appropriate recommendations based on the user's location information in real time, but also the ability to adjust the information according to the user's emotional state. Furthermore, they lack the ability to allow users to search for restaurant information by specifying detailed conditions and make immediate reservations. This makes it difficult to improve user satisfaction and results in low convenience.

[1197] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1198] In this invention, the server includes a means for acquiring location information of the area where the user is currently walking, a means for transmitting the location information to the server, and a means for generating recommendation information based on the location information. This enables real-time information provision based on the user's current location. It also includes an emotion engine that analyzes the user's emotional state and a means for adjusting recommendation information based on the emotional state. This enables information provision according to the user's emotions. Furthermore, by including a means for generating recommendation information and restaurant information using a generative AI model and a means for generating information based on a prompt sentence entered by the user, highly accurate information provision that satisfies the user is realized. Furthermore, by including a means for the user to input a search query using free words, a means for generating restaurant information based on the search query, and a means for making a reservation at a specific restaurant based on the search query, a highly convenient restaurant search and reservation function is also provided.

[1199] "User" refers to a person who uses the system.

[1200] "Location Information" refers to geographic data including a user's current latitude and longitude.

[1201] "Server" refers to a computer system that receives and processes data sent from a user's terminal.

[1202] An "emotion engine" refers to a combination of software or hardware that analyzes a user's voice and facial expressions to determine the user's emotional state.

[1203] "Recommended information" refers to information generated based on the user's location information and emotional state, and includes places and events that may be of interest to the user.

[1204] "Audio guidance" refers to guidance information provided to the user by voice.

[1205] A "free word search" refers to a search that is conducted by the user entering any word or phrase.

[1206] A "search query" refers to text data that represents search conditions or requests that a user inputs into a system.

[1207] "Restaurant information" refers to various data about restaurants (e.g., restaurant name, price range, seating availability, etc.) generated by the system based on a user's search query.

[1208] "Generative AI models" refer to algorithms and systems that use artificial intelligence to generate information based on user requests.

[1209] A "prompt sentence" refers to the input text that serves as the basis for generating information for a generative AI model.

[1210] The present invention is a system that provides real-time information related to the area where a user is currently walking, including an emotion engine that recognizes the user's emotions and adjusts recommended information. The system acquires the user's location information, generates recommended information based on that information, and provides it as voice guidance. The user can also input a free-word search query, generate restaurant information based on that, and make reservations. The emotion engine analyzes the user's voice input and facial expressions and adjusts the information provided based on the results of the analysis.

[1211] When a user launches an application, the device uses a GPS sensor to obtain the current location (latitude and longitude) in real time. This location information is sent to a server. The device is equipped with a GPS sensor and a communication module required for sending and receiving data. Specific hardware examples include smartphones, tablets, and laptops.

[1212] The server uses the generated AI to search for recommendations in the surrounding area based on the received location information. The generated AI can be, for example, OpenAI's GPT-4. The server sends the following prompt to the generated AI:

[1213] "Tell me some recommended spots near my current location"

[1214] Based on the information provided by the generating AI, the server further organizes the information and sends it to the terminal.

[1215] The device then provides the received information to the user as voice guidance, using voice synthesis software such as the Google Cloud Text-to-Speech API.

[1216] By incorporating an emotion engine, the system analyzes the user's emotional state and adjusts recommendations based on that information. The device uses a microphone to collect the user's voice input and a camera to recognize the user's facial expressions. The emotion engine can use the Google Cloud Speech-to-Text API or Azure's Emotion API. For example, if the user says "I'm tired," the emotion engine will recommend cafes and quiet places where the user can relax. If the user has a smiling expression, the emotion engine will suggest fun events and restaurants with a cheerful atmosphere.

[1217] As a concrete example, consider the case where a user is walking around Shinjuku Station. The user launches an application, and the device acquires location information around Shinjuku Station. Based on this location information, the server generates recommendation information such as, "There's a new cafe about a three-minute walk away. They're currently offering half-price drinks as part of their opening campaign." and sends this information to the device. The device then relays this information to the user as voice guidance.

[1218] Furthermore, if the user voice-inputs "I'm tired and want to rest somewhere," the emotion engine will determine the user's state as "fatigue," and the server will provide information about places to relax, such as "You can relax in a nearby park."

[1219] When a user wants to search for a restaurant based on specific criteria, they can use the free word search function. For example, they can enter a search query such as "a table for drinking with my boss under 4000 yen, smoking allowed." The device sends this input to the server, which then generates a list of restaurants that match the criteria. Search results include candidates such as "XX restaurant, △△ bistro." When the user selects the desired restaurant and makes a reservation, the device sends the reservation information to the server, and the server confirms the reservation and returns the information to the device.

[1220] In this way, the present invention provides real-time information based on the user's current location and also provides information that takes the user's emotions into consideration. Restaurant search and reservation functions are also integrated, making this a system that greatly improves user convenience.

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

[1222] Step 1:

[1223] The user launches the application

[1224] A user taps an application on their smartphone to launch it. The device loads the application's interface and various functions and becomes ready. The user's operation is the input, and the application screen is displayed as the output.

[1225] Step 2:

[1226] The device obtains its current location

[1227] The device activates its built-in GPS sensor and obtains its current latitude and longitude information. Specifically, the device's location service is activated and receives signals from GPS satellites to determine its location. The input is the signal from the GPS satellites, and the output is the obtained latitude and longitude information. This data is stored internally in JSON format or other appropriate format.

[1228] Step 3:

[1229] Sending location information

[1230] The device packs the acquired location information into packets and sends them to the server using the HTTPS protocol. The input is the latitude and longitude information acquired by the device, and the output is data that is sent to the server. The specific operation utilizes the device's communication module.

[1231] Step 4:

[1232] Server-generated recommendations

[1233] The server sends a specific prompt to the generative AI model (e.g., a generation algorithm) based on the received location information. This prompt might be something like, "Tell me some recommended spots near the user's current location." The server receives the location information as input, and uses that information to process the data to generate an appropriate prompt. The output is recommendations based on this prompt. A cloud-based model (e.g., GPT-4) is used as the generative AI, which returns the results to the server.

[1234] Step 5:

[1235] Analysis by emotion engine

[1236] The device uses a microphone to collect the user's voice input and a camera to recognize facial expressions. Inputs include the user's voice data and video data from the camera. This data is sent to a local emotion analysis engine. Specifically, Google Cloud Speech-to-Text API and Azure Emotion API are used. Data processing involves converting the voice data into text and determining the user's emotional state, and the results are output.

[1237] Step 6:

[1238] Server-adjusted recommendations

[1239] The server adjusts the recommendation information based on the emotional information received from the emotion engine. The input is data on the user's emotional state, and the output is new recommendation information generated according to the emotion. For example, if the user's state is determined to be "fatigue," the server adjusts the recommendation information to provide information on relaxing cafes and quiet spots.

[1240] Step 7:

[1241] Providing recommendations

[1242] The device receives the final recommendation information sent from the server and provides it to the user as voice guidance. Specifically, it generates synthetic voice using Google Cloud Text-to-Speech API, etc. The input is the recommendation information data from the server, and the output is the generated voice guidance, which is provided to the user.

[1243] Step 8:

[1244] Perform a free word search

[1245] The user enters a free word containing a specific requirement into the search bar within the application. For example, a search query such as "a table for drinks with my boss for under 4000 yen, smoking allowed" is entered. The input is the user's free-form text data, which the device packs into packets to send to the server. The output is the data to be sent to the server.

[1246] Step 9:

[1247] Server generates restaurant information

[1248] Based on a free-word search query, the server uses a generative AI model to generate information about restaurants that match the criteria. For example, using the "Search for Restaurants" prompt. The input is the search query data, and the output is a list of restaurants based on the search criteria. This information is processed on the server and may also retrieve information from databases or external APIs.

[1249] Step 10:

[1250] Providing restaurant information and reservations

[1251] The user selects the restaurant of their choice and makes a reservation. The terminal packs the reservation information into a packet and sends it to the server. The input is the user's selection data and reservation information, and the output is the data to be sent to the server. The server processes the received reservation information and makes an actual reservation request to the restaurant. Information indicating that the reservation has been confirmed is then returned to the terminal, and the terminal notifies the user that the reservation has been confirmed.

[1252] (Application example 2)

[1253] 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."

[1254] Conventional navigation systems and information systems provide recommended information based on the user's current location, but because they do not take the user's emotional state into account, they may not fully meet the needs of individual users. Furthermore, even systems that provide restaurant information or have reservation functions have difficulty providing appropriate information based on the user's mood and situation. Therefore, the present invention aims to provide information that reflects the user's emotional state and customized navigation guidance for autonomous vehicles.

[1255] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring location information of the area where the user is currently located, means for transmitting the location information to the server, and means for generating recommended information based on the location information. This makes it possible to provide information in real time based on the user's current location.

[1256] Furthermore, a means for analyzing the emotional state of the user and a means for adjusting the recommended information based on the emotional state are added, thereby enabling the provision of information customized according to the user's mood and state.

[1257] The system also includes a means for inputting a search query using free words, a means for generating restaurant information based on the search query, a means for providing the restaurant information to the user, a means for reserving a specific restaurant based on the search query, and a means for adjusting the restaurant information based on the emotional state, thereby enabling the user to search for restaurants using detailed conditions and obtain optimal results according to their emotions.

[1258] "Location information of the area where the user is currently located" is data that indicates the geographical location where the user is located at a particular point in time.

[1259] A "server" is a computer system that processes and stores information over a network and provides data and services to client devices.

[1260] "Recommended information" is useful data or guidance that is generated based on the user's current location and other conditions and provided to the user.

[1261] "Audio guidance" is a method of providing information to a user using audio.

[1262] "Emotional state" refers to the user's current mood and psychological state, and analyzing this makes it possible to provide information suited to the user's needs and requests.

[1263] A "conditioning tool" is a method or process that changes or optimizes information or data based on specific conditions or criteria.

[1264] A "means for entering a search query using free words" is an interface that allows users to search for information using any word or phrase.

[1265] "Restaurant information" is information about a specific restaurant, including location, menu, price, and ratings.

[1266] A "reservation means" is a method or tool that a user uses to reserve a particular service or facility in advance.

[1267] A "generative AI model" is an algorithm that uses generative adversarial networks and other artificial intelligence techniques to automatically generate new data or information based on input data.

[1268] A "prompt sentence" is a string or sentence that is input to a generative AI model to prompt it to generate appropriate data.

[1269] The present invention is a system that acquires location information of the user's current location, analyzes the user's emotional state based on that information, and provides appropriate recommended information as audio guidance. The following hardware and software are used to implement the present invention.

[1270] Hardware

[1271] GPS sensor: Used to obtain the user's current location in real time.

[1272] Microphone and camera: Used to analyze the user's voice input and facial expressions to determine their emotional state.

[1273] Terminal (smartphone or in-car display): Used to run the system and provide voice guidance to the user.

[1274] Server: Used to generate recommendations using a generative AI model based on the user's location and emotional state, and send them to the device.

[1275] software

[1276] Location information acquisition software (GPS library): Works with the GPS sensor to acquire the user's current location.

[1277] Emotion analysis software (EmotionEngine): Analyzes the user's voice input and facial expression data to determine their emotional state.

[1278] Text-to-Speech software: Provides users with recommended information as audio guidance.

[1279] Generative AI model: Generates recommendations based on the user's current location and emotional state.

[1280] Processing flow explanation

[1281] 1. Location information acquisition: The device uses the GPS sensor to acquire the user's current location (latitude and longitude) in real time. This location information is sent to the server.

[1282] 2. Emotional state analysis: The device's microphone and camera are used to collect the user's voice input and facial expressions, which are then analyzed by the Emotion Engine.

[1283] 3. Information generation: The server receives the user's location information and emotional state and generates recommendations using a generative AI model. For example, it analyzes prompts such as "Recommend places around (latitude, longitude) for a person feeling (emotion)."

[1284] 4. Providing information: The server sends the generated recommendation information to the terminal, which uses TextToSpeech software to provide it to the user as voice guidance.

[1285] Specific examples

[1286] When a user is in an autonomous vehicle, the system operates as follows: Suppose the user's vehicle arrives at its current location (e.g., Shinjuku Ward, Tokyo). The GPS acquires this location information and sends it to the server. At the same time, the user vocally inputs, "I'm tired." The Emotion Engine analyzes this voice and determines the user's emotional state as "fatigue." The server sends the prompt "Recommend places around 35.6895,139.6917 for a person feeling tired" to the generative AI model, generating information recommending places to relax. The device receives this information and provides voice guidance to the user, saying, "The nearby cafe is quiet and relaxing."

[1287] In this way, the present invention provides real-time information based on the user's current location and emotional state, enabling customized navigation guidance, particularly in autonomous vehicles.

[1288] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1289] Step 1:

[1290] The device uses the GPS sensor to obtain the user's current location (latitude and longitude) in real time. This location information becomes input data, and the device sends it to the server.

[1291] Step 2:

[1292] Based on the location information received, the server retrieves information about the surrounding area from a database and sends a prompt to the generative AI model based on that information. This prompt includes a sentence in the format "Recommend places around (latitude, longitude)." The AI ​​model generates recommendations based on this prompt. The generated recommendations become the output data.

[1293] Step 3:

[1294] The device collects the user's voice input and facial expressions using a microphone and camera, and sends the data to the Emotion Engine. This input data is analyzed by the Emotion Engine, which determines the user's emotional state. The analysis results are output as emotions such as "fatigue" or "enjoyment."

[1295] Step 4:

[1296] The server receives the emotional state output from the Emotion Engine and adjusts the recommendation information based on that information. For example, if the user's emotional state is "fatigue," it will prioritize recommendations of cafes and parks where people can relax. This adjusted information is then output again.

[1297] Step 5:

[1298] The server sends the adjusted recommendations to the device, which then uses TextToSpeech software to provide the recommendations to the user as voice guidance, which is the final output.

[1299] Step 6:

[1300] When a user wants to perform a free-word search, they input a search query into their device. This query becomes input data and is sent to the server. The server retrieves restaurant information from a database based on this query and generates appropriate restaurant information using a generative AI model.

[1301] Step 7:

[1302] The server sends the generated restaurant information to the terminal. The terminal displays the information to the user, who selects the desired restaurant and makes a reservation. This reservation information is sent to the server, which processes the reservation. Reservation confirmation information is sent to the terminal and notified to the user.

[1303] This allows users to obtain real-time information about their current location and experience navigation guidance customized to their emotional state.

[1304] 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.

[1305] 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.

[1306] 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.

[1307] [Fourth embodiment]

[1308] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1309] 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.

[1310] 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).

[1311] 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.

[1312] 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.

[1313] 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).

[1314] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1315] 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.

[1316] 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.

[1317] 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.

[1318] 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.

[1319] 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.

[1320] 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."

[1321] The present invention is a system for providing real-time information related to the area in which a user is currently walking. This system acquires the user's location information, transmits it to a server, and provides audio guidance on recommendations, deals, weather, and other information based on the location information. The user can also enter a search query using free words, and the server will provide appropriate restaurant information based on the query and even allow the user to make reservations at those restaurants. The system's program processing is described in detail below in natural language.

[1322] First, the user launches the application. The device uses a GPS sensor to obtain the user's current location in real time. This location information is sent from the device to the server. The server receives the location information and uses a generation AI to search for recommendation information in the surrounding area. The generated recommendation information might be something like, "There is currently a 20% off campaign at the cafe 50 meters ahead on the right." The server sends this information to the device, and the device delivers the received information to the user as voice guidance.

[1323] Next, consider the case where a user uses free words to search for restaurants that meet specific criteria. The user enters the search criteria into the search box within the app, and the device sends this input to the server. The server analyzes the received free words and uses generative AI to search for appropriate restaurant information. Search results may include, for example, "XX restaurant, △△ bistro." These results are sent to the device, which displays them to the user in a list format.

[1324] When the user selects the desired restaurant from the list and makes a reservation, the terminal sends the entered reservation information back to the server. The server then connects with the restaurant's reservation system and confirms the reservation. Once the reservation is confirmed, the information is sent to the terminal and the user is notified. The user is provided with information such as, "Your reservation at Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[1325] As a concrete example, consider a case where a user is walking around Shinjuku Station. The user launches an application, and the device acquires location information around Shinjuku Station. Based on this location information, the server generates recommendation information, such as "A cafe on the street in front of the station is offering a limited-time discount on parfaits," and sends it to the device. The device then notifies the user of this information as voice guidance. Furthermore, if the user performs a free-word search for "a restaurant where I can drink with my boss for under 4,000 yen and where smoking is permitted," the server searches for restaurants that match the criteria and sends the results to the device. The user can then select the desired restaurant from the displayed list and make a reservation.

[1326] In this way, the present invention provides a system that provides real-time information related to the area the user is currently walking through, generates restaurant information tailored to the user's individual needs based on the user's search query, and allows the user to easily make reservations at those restaurants.

[1327] The processing flow will be explained below.

[1328] Providing recommended information for the area you are currently walking through

[1329] Step 1:

[1330] The user launches the app on their device.

[1331] A user taps an app icon on a device such as a smartphone or tablet to launch the application.

[1332] Step 2:

[1333] The device acquires location information.

[1334] The device's GPS sensor operates to obtain the user's current location (latitude and longitude) in real time.

[1335] The acquired location information is updated at regular intervals (for example, every 5 seconds).

[1336] Step 3:

[1337] The device sends location information to the server.

[1338] The device sends the acquired location information to the server via an HTTP request, which includes latitude, longitude, timestamp, etc.

[1339] Step 4:

[1340] The server generates recommendations.

[1341] The server analyzes the location information received and searches a database for recommended information for the surrounding area.

[1342] Generative AI is used to optimize recommendation information and generate text for voice guidance.

[1343] For example, "The cafe 50 meters ahead on the right is currently running a 20% off campaign."

[1344] Step 5:

[1345] The server sends the recommendation information to the device.

[1346] The server returns the generated text information for the voice guidance to the terminal as an HTTP response.

[1347] Step 6:

[1348] The device provides voice guidance.

[1349] The text information for voice guidance received by the device is converted into voice using a TTS (Text-to-Speech) engine.

[1350] Through the earphones, the user is given voice guidance such as, "There is currently a 20% off campaign at the cafe on the right, 50 meters ahead."

[1351] Free word search and restaurant reservations

[1352] Step 1:

[1353] The user inputs a free word.

[1354] The user enters a free word (for example, "smoking allowed, boss, under 4000 yen") into the search box within the app.

[1355] Your device temporarily stores what you type into the search box.

[1356] Step 2:

[1357] The terminal sends the free word to the server.

[1358] The device sends the saved free words to the server via an HTTP request, and the request includes the search query.

[1359] Step 3:

[1360] The server generates restaurant information based on the search query.

[1361] The server analyzes the received search query and generates restaurant information that matches the criteria from the database.

[1362] Use generative AI to optimize search results to best meet your needs.

[1363] Step 4:

[1364] The server transmits restaurant information to the terminal.

[1365] The server returns the optimized restaurant information to the terminal as an HTTP response.

[1366] Search results include details such as store name, address, opening hours, and price range.

[1367] Step 5:

[1368] The terminal displays the search results to the user.

[1369] The terminal displays the search results received to the user in list form.

[1370] Each item includes buttons such as "View details" and "Make a reservation."

[1371] Step 6:

[1372] The user selects a restaurant and makes a reservation.

[1373] The user selects the desired restaurant from the list and taps the "Make a reservation" button.

[1374] The terminal displays an interface for entering reservation information (date and time, number of people, special notes).

[1375] Step 7:

[1376] The terminal transmits the reservation information to the server.

[1377] The terminal sends the entered reservation information to the server via an HTTP request.

[1378] Step 8:

[1379] The server confirms the reservation.

[1380] Based on the reservation information received by the server, the reservation is confirmed in cooperation with the restaurant's reservation system.

[1381] The confirmed reservation information is returned to the terminal as an HTTP response.

[1382] Step 9:

[1383] The terminal notifies the user of the reservation confirmation information.

[1384] The terminal notifies the user of the received reservation confirmation information.

[1385] For example, the notification will be in the format "Reservation for XX Restaurant has been completed. Date and time: October 10, 2023, 19:00, Number of people: 2."

[1386] Example 1

[1387] 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."

[1388] There is a demand for a system that provides useful information in real time based on the user's current location information and enables easy and fast acquisition and reservation of restaurant information based on the user's individual search query. However, existing systems often lack sufficient speed and accuracy in providing information, or have difficulty providing information tailored to the user's needs. In particular, there is a lack of systems that seamlessly generate recommendation information in real time and make restaurant reservations based on free word searches.

[1389] 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.

[1390] In this invention, the server includes means for acquiring location information of an area where a user is currently walking, means for transmitting the location information to the server, means for generating recommendation information using a generative AI model based on the location information, means for providing the recommendation information to the user as audio guidance, means for the user to input a search query using free words, means for generating restaurant information using a generative AI model based on the search query, means for providing the restaurant information to the user, and means for making reservations at a specific restaurant based on the restaurant information. This enables the provision of real-time information based on the user's current location and the rapid provision of restaurant information and reservations that meet the user's individual needs.

[1391] "User" refers to an individual who uses the system to obtain real-time information and restaurant information and make reservations.

[1392] "Location information of the area currently being walked" refers to latitude and longitude information used to identify the user's current location using a GPS sensor or the like.

[1393] "Server" refers to a computer system that receives location information and search queries sent by users, generates information based on that information using a generative AI model, and sends it to a terminal.

[1394] A "generative AI model" refers to an artificial intelligence model that generates information in natural language based on a given prompt.

[1395] A "prompt sentence" refers to an input sentence that instructs a generative AI model to generate information.

[1396] "Recommended information" is information provided based on the user's current location using a generative AI model, such as restaurant campaign information and information about nearby facilities.

[1397] "Voice guidance" refers to a function that conveys recommended information generated by the device to the user by voice.

[1398] A "free word search query" refers to an input sentence in which a user enters any word within an application to search for information.

[1399] "Restaurant Information" refers to information about restaurants generated based on free-word search queries using a generative AI model.

[1400] "Reservation" refers to the procedure for reserving seats for a specific date, time and number of people at a restaurant of a user's choice.

[1401] "Reservation information" refers to detailed information such as the date and time and number of people entered by the user when making a reservation.

[1402] "Notification" refers to a message sent by the server to the user's terminal to inform them of reservation confirmation information or recommended information.

[1403] The present invention is a system that provides real-time information related to the area a user is currently walking in. This system acquires the user's location information, transmits it to a server, and provides audio guidance based on that location information, including recommendations, deals, and weather information. The user can also enter a search query using free words, and the server will provide information on appropriate restaurants based on that query and even allow the user to make reservations at those restaurants.

[1404] First, the user launches the application. The device uses the GPS sensor to obtain the user's current location in real time. This location information is then sent from the device to the server. The secure HTTPS protocol is used for communication to ensure data safety.

[1405] Once the server receives the location information, it uses a generative AI model, such as OpenAI's GPT-4, to generate recommendations for the surrounding area.

[1406] Example prompt sentence:

[1407] "The user is currently at Shinjuku Station. Are there any recommended cafes or restaurants nearby?"

[1408] The generative AI model generates appropriate recommendations based on these prompts. Examples of generated information include specific information such as, "The cafe 50 meters ahead on the right is currently offering a 20% off campaign." The generated recommendations are sent from the server to the device, which then converts the information into voice data using speech synthesis software (e.g., Google Text-to-Speech) and provides it to the user.

[1409] Next, we will explain how a user can use free words to search for restaurants that meet specific criteria. The user enters the search criteria into the search box within the app, and the device sends this input to the server. The server analyzes the received free words and uses the generative AI model again to search for appropriate restaurant information.

[1410] Example prompt sentence:

[1411] "Please tell me a restaurant where I can smoke while drinking with my boss for under 4,000 yen."

[1412] Based on this prompt, the generative AI model generates search results and returns them to the server. Examples of search results include "X restaurant, △△ bistro." These results are sent from the server to the device, which displays them to the user in list form. The user then selects the desired restaurant from the displayed list and makes a reservation.

[1413] When the user selects the desired restaurant from the list and makes a reservation, the terminal sends the entered reservation information back to the server. The server then connects with the restaurant's reservation system to confirm the reservation. Once the reservation is confirmed, the information is sent to the terminal and the user is notified. An example of a notification might include information such as, "Your reservation at Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[1414] As a concrete example, imagine a user walking around Shinjuku Station. The user launches an application, and the device obtains location information around Shinjuku Station. Based on this location information, the server generates recommendation information, such as "A cafe on the street in front of the station is offering a limited-time discount on parfaits," and sends it to the device. The device then notifies the user of this information as voice guidance. If the user then performs a free-word search for "a restaurant where I can drink with my boss for under 4,000 yen and where smoking is allowed," the server searches for restaurants that match the criteria and sends the results to the device. The user can then select the restaurant of their choice from the displayed list and make a reservation.

[1415] In this way, the present invention provides a system that provides real-time information related to the area in which a user is currently walking, generates restaurant information tailored to individual needs based on the user's search query, and allows users to easily make reservations at those restaurants.

[1416] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1417] Step 1: Launch the application and get location information

[1418] The user launches an application.

[1419] The device activates the GPS sensor to obtain the user's current location, and obtains latitude and longitude information from the GPS sensor and updates it in real time.

[1420] Input: User application launch operation

[1421] Processing: GPS sensor acquires latitude and longitude information

[1422] Output: Current location (latitude, longitude)

[1423] Step 2: Send location information

[1424] The terminal transmits the acquired location information to the server using a secure communication protocol (for example, HTTPS).

[1425] Input: Location information (latitude, longitude)

[1426] Processing: Encrypt location information and send it to the server

[1427] Output: Location information sent to the server

[1428] Step 3: Generate recommendations

[1429] The server uses a generative AI model to generate nearby recommendations based on the received location information. As part of the generation process, it generates location-based prompts.

[1430] Example prompt: "The user is currently at Shinjuku Station. Are there any recommended cafes or restaurants nearby?"

[1431] Input: Location information (latitude, longitude)

[1432] Processing: Generative AI model generates information based on prompts

[1433] Output: Recommendation information (e.g. "The cafe on the right, 50 meters away, is currently offering a 20% discount campaign.")

[1434] Step 4: Send recommendations and voice guidance

[1435] The server transmits the generated recommendation information to the terminal.

[1436] The terminal uses voice synthesis software to convert the received recommendation information into voice data, which is then provided to the user as voice guidance.

[1437] Input:Recommendations

[1438] Processing: Converted into voice data using speech synthesis software and played through speakers

[1439] Output: Voice guidance (e.g. "There is a 20% off campaign going on at the cafe on your right, 50 meters ahead.")

[1440] Step 5: Enter and submit a free word search

[1441] The user enters a free word search query into a search box within the application.

[1442] The terminal transmits the entered search query to the server.

[1443] Input: Search query (e.g., "Restaurants where you can drink with your boss and smoke for under 4,000 yen")

[1444] Process: Send the search query to the server

[1445] Output: The search query sent to the server

[1446] Step 6: Generate search results

[1447] The server analyzes the received search query and generates appropriate restaurant information using a generative AI model. It also generates search results based on the prompt text.

[1448] Example prompt: "Please tell me a restaurant where I can smoke and drink with my boss for under 4000 yen."

[1449] Input: Search query

[1450] Processing: Generative AI model generates information based on prompts

[1451] Output: Restaurant information (e.g., "XX Restaurant, △△ Bistro")

[1452] Step 7: View and select search results

[1453] The terminal displays the restaurant information sent from the server in a list format to the user, and the user selects the restaurant of their choice from the displayed list.

[1454] Input: Restaurant information

[1455] Action: Display information in list format

[1456] Output: List view and user selection

[1457] Step 8: Submit and confirm your reservation

[1458] The terminal transmits reservation information for the restaurant selected by the user to the server, including the date, time, number of people, etc.

[1459] The server connects with the restaurant's reservation system to confirm the reservation.

[1460] Input: Reservation information (date, time, number of people, etc.)

[1461] Process: Link with reservation system and confirm reservation

[1462] Output: Confirmed reservation information

[1463] Step 9: Notification of confirmed reservation information

[1464] The server transmits information that the reservation has been confirmed to the terminal, and the terminal notifies the user of the information.

[1465] Input: Confirmed reservation information

[1466] Processing: Send to device and notify user

[1467] Output: Notification (e.g. "Your reservation for Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2")

[1468] These steps will enable users to smoothly access real-time local information, search for restaurants, and make reservations.

[1469] (Application example 1)

[1470] 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."

[1471] In modern cities, there is an increasing need for users to quickly obtain real-time information about the places they are walking, especially about discount campaigns, recommended places, and emergency weather information. Users also need to be able to easily search for restaurants and stores that meet specific criteria and smoothly make reservations. However, existing systems are limited in the information they can provide and lack real-time capabilities and ease of operation.

[1472] 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.

[1473] In this invention, the server includes means for acquiring location information, means for transmitting the location information to the server, means for generating recommendation information based on the location information using a generative AI model, means for providing the generated recommendation information as voice guidance and as an augmented reality display, means for displaying store information based on a search query entered by a user, and means for confirming a reservation for the store online. This allows a user to receive real-time information related to their current location by voice and augmented reality, making it even easier to search for and make reservations for restaurants and stores.

[1474] "Location information" refers to geographic data such as the latitude and longitude of a user's current physical location.

[1475] "Server" means a computer system accessible over a network that receives and processes data, such as location information or search queries, and provides the results.

[1476] A "generative AI model" refers to an algorithm or program that uses artificial intelligence techniques to generate useful information based on a user's location or search query.

[1477] "Recommended information" refers to information about stores and services suggested based on the user's current location and interests.

[1478] "Audio guidance" refers to a technology that provides information to users by reading out text information aloud.

[1479] "Augmented reality display" refers to a technology that displays digital information superimposed on the actual field of vision.

[1480] A "search query" refers to free words or conditions that a user enters to search for specific information.

[1481] "Store information" refers to detailed information such as the name, location, business hours, and service details of restaurants, retail stores, etc.

[1482] "Reservation" refers to the advance application procedure for a user to use a store or service on a specific date and time.

[1483] A system for implementing this invention provides real-time information related to the area a user is currently walking in. The system is composed of a terminal such as a smartphone or smart glasses, and a server.

[1484] First, when a user launches the application, the device uses a GPS sensor to obtain the user's current location in real time. This location information is then sent to a server via the Internet. The server then uses a generative AI model to generate recommendations for the area based on the received location information. For example, the generated information might be something like, "There's a 20% off campaign going on at the cafe 50 meters ahead on the right." The generated recommendations are then provided to the user via the smartphone screen, voice guidance, or augmented reality display on the smart glasses.

[1485] Next, consider the case where a user uses the device's free-word search function to search for restaurant information based on specific criteria. For example, if the user enters "restaurants where I can drink with my boss and where smoking is allowed for under 4,000 yen," the device sends this search query to the server. The server uses a generative AI model to search for and generate relevant restaurant information and sends the search results to the device. The device displays the results to the user in a list format, such as "X Restaurant, XX Bistro." The user selects the desired restaurant from the list and completes the reservation online. Once the reservation is confirmed, the server sends the information to the device, and the user is notified in the form of a message such as, "Your reservation for X Restaurant has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[1486] The hardware used to implement the system includes smartphones and smart glasses with built-in GPS sensors. The software uses generative AI models (e.g., GPT-3) and speech synthesis libraries (e.g., pyttsx3). The generative AI models are particularly important in generating information in real time based on the user's current location and search query.

[1487] As a concrete example, consider the case where a user is walking around Shinjuku Station. The application obtains location information around Shinjuku Station, and the server generates recommendation information such as "A cafe on the street in front of the station is offering a limited-time discount on parfaits." This information is displayed in augmented reality through the smart glasses and also conveyed via voice guidance. The user can also easily search for "izakayas where you can drink for under 3,000 yen" and make a reservation from the suggested restaurants.

[1488] An example of a program prompt is:

[1489] "Tell me about great deals within 500 meters of my current location"

[1490] "Please find a restaurant where I can smoke while drinking with my boss for under 4,000 yen."

[1491] These prompts allow the generative AI model to provide users with relevant information, enabling real-time information retrieval and a convenient booking experience.

[1492] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1493] Step 1:

[1494] The user launches the application. The device uses the built-in GPS sensor to obtain the user's current location in real time. The obtained location information is sent to the server in the form of latitude and longitude.

[1495] Input: Real-time location information (latitude and longitude) from the GPS sensor

[1496] Data processing / calculation: Acquisition and transmission of location information

[1497] Output: Send location information to the server

[1498] Step 2:

[1499] The server receives the location information and uses a generative AI model to generate recommendations for the area based on the location information. For example, it generates information such as "There is currently a 20% off campaign at the cafe on the right, 50 meters away."

[1500] Input: Location information (latitude and longitude) sent from the device

[1501] Data processing / calculation: Generating recommendations using generative AI models

[1502] Output: Recommendations

[1503] Step 3:

[1504] The server sends the generated recommendation information to the device, which then provides the received recommendation information to the user in the form of voice guidance and augmented reality display. On smartphones, this is done by displaying the screen and providing voice notifications, while on smart glasses, this is done by providing augmented reality display.

[1505] Input: Recommendations sent from the server

[1506] Data processing / calculation: Format conversion of recommended information (voice, augmented reality)

[1507] Output: Voice guidance and augmented reality display

[1508] Step 4:

[1509] A user inputs a search query using free words. For example, if the user inputs "a restaurant where I can drink with my boss and where smoking is allowed for less than 4,000 yen," the search query is sent from the device to the server.

[1510] Input: User's search query (free word)

[1511] Data processing / calculation: Sending search queries

[1512] Output: Sending a search query to the server

[1513] Step 5:

[1514] The server analyzes the received search query and uses a generative AI model to generate appropriate restaurant information, such as "XX Restaurant, △△ Bistro."

[1515] Input: Search query sent from the device

[1516] Data processing / calculation: Generate restaurant information using generative AI models

[1517] Output: Restaurant information

[1518] Step 6:

[1519] The server sends the generated restaurant information to the terminal, which displays the search results in a list to the user, who then selects the restaurant of their choice from the list.

[1520] Input: Restaurant information sent from the server

[1521] Data processing / calculation: Displaying restaurant information in list format

[1522] Output: List of restaurants

[1523] Step 7:

[1524] The user selects the restaurant of their choice and makes a reservation. The terminal sends the reservation information to the server. The server then connects with the restaurant's reservation system to confirm the reservation.

[1525] Input: User's restaurant selection and reservation information

[1526] Data processing / calculation: Sending reservation information and linking with reservation systems

[1527] Output: Confirmed reservation information

[1528] Step 8:

[1529] The server sends the information that the reservation has been confirmed to the terminal. The terminal then notifies the user of the reservation confirmation information. For example, the terminal may notify the user that "Your reservation at Restaurant X has been completed. Date and time: October 10, 2023, 7:00 PM, Number of people: 2."

[1530] Input: Confirmed reservation information sent from the server

[1531] Data processing / calculation: Notification of reservation confirmation information

[1532] Output: Confirmation of reservation sent to user

[1533] 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.

[1534] The present invention is a system that provides real-time information related to the area where a user is currently walking, and includes an emotion engine that recognizes the user's emotions and adjusts recommended information. The system acquires the user's location information, generates recommended information based on that information, and provides it as voice guidance. The user can also enter a free-word search query, generate restaurant information based on that, and make reservations. The emotion engine analyzes the user's voice input and facial expressions, and adjusts the information provided based on the results of that analysis. The system's program processing is specifically explained below in natural language.

[1535] When a user launches the application, the device uses the GPS sensor to obtain the current location (latitude and longitude) in real time. This location information is sent to the server. The server uses a generation AI to search for recommended information in the surrounding area based on the received location information and sends the results to the device. The device then provides the received information to the user as voice guidance.

[1536] By incorporating an emotion engine, the system can analyze the user's emotional state and adjust recommendations based on that information. For example, if the user says "I'm tired," the emotion engine will recommend cafes and quiet places where the user can relax. Also, if the user has a smiling expression, the emotion engine will suggest fun events and restaurants with a cheerful atmosphere.

[1537] As a concrete example, consider the case where a user is walking around Shinjuku Station. The user launches an application, and the device acquires location information around Shinjuku Station. Based on this location information, the server generates recommendation information such as, "There's a new cafe about a three-minute walk away. They're currently offering half-price drinks as part of their opening campaign." and sends this information to the device. The device then relays this information to the user as voice guidance.

[1538] Furthermore, if the user voice-inputs "I'm tired and want to rest somewhere," the emotion engine will determine the user's state as "fatigue," and the server will provide information about places to relax, such as "You can relax in a nearby park."

[1539] When a user wants to search for a restaurant based on specific criteria, they can use the free word search function. For example, they can enter a search query such as "a table for drinking with my boss under 4000 yen, smoking allowed." The device sends this input to the server, which then generates a list of restaurants that match the criteria. Search results include candidates such as "XX restaurant, △△ bistro." When the user selects the desired restaurant and makes a reservation, the device sends the reservation information to the server, and the server confirms the reservation and returns the information to the device.

[1540] In this way, the present invention provides real-time information based on the user's current location and also provides information that takes the user's emotions into consideration. Restaurant search and reservation functions are also integrated, making this a system that greatly improves user convenience.

[1541] The processing flow will be explained below.

[1542] Providing recommended information for the area you are currently walking in (embedded emotion engine)

[1543] Step 1:

[1544] The user launches the app on their device.

[1545] A user taps an app icon on a device such as a smartphone or tablet to launch the application.

[1546] Step 2:

[1547] The device acquires location information.

[1548] The device's GPS sensor operates to obtain the user's current location (latitude and longitude) in real time.

[1549] The acquired location information is updated at regular intervals (for example, every 5 seconds).

[1550] Step 3:

[1551] The device sends location information to the server.

[1552] The device sends the acquired location information to the server via an HTTP request, which includes latitude, longitude, timestamp, etc.

[1553] Step 4:

[1554] The server generates recommendations.

[1555] The server analyzes the location information received and searches a database for recommended information for the surrounding area.

[1556] Generative AI is used to optimize recommendation information and generate text for voice guidance.

[1557] For example, "The cafe 50 meters ahead on the right is currently running a 20% off campaign."

[1558] Step 5:

[1559] The server sends the recommendation information to the device.

[1560] The server returns the generated text information for the voice guidance to the terminal as an HTTP response.

[1561] Step 6:

[1562] The device uses an emotion engine to analyze the user's emotions.

[1563] The terminal acquires the user's voice input or facial expression data.

[1564] An emotion engine analyzes this data to determine the user's current emotional state (e.g., "tired," "happy," etc.).

[1565] Step 7:

[1566] The device requests adjustments to the recommendations from the server.

[1567] The device sends the analysis results to the server and requests that recommendations be re-adjusted based on the user's emotional state.

[1568] Step 8:

[1569] The server adjusts recommendations based on the emotional state.

[1570] Based on the emotion analysis results, the server searches the database for new recommended information that matches the user's emotions.

[1571] For example, if the user is "tired," information about cafes and parks where they can relax is provided.

[1572] The server sends the re-adjusted recommendations to the device.

[1573] Step 9:

[1574] The device provides tailored recommendations as voice guidance.

[1575] The adjusted recommendation information text received by the device is converted into audio using a TTS (Text-to-Speech) engine.

[1576] Through the earphones, the user is given audio guidance such as, "There is a cafe where you can relax 50 meters ahead. You seem tired."

[1577] Free word search and restaurant reservations (including emotion engine)

[1578] Step 1:

[1579] The user inputs a free word.

[1580] The user enters a free word (for example, "smoking allowed, boss, under 4000 yen") into the search box within the app.

[1581] Your device temporarily stores what you type into the search box.

[1582] Step 2:

[1583] The terminal sends the free word to the server.

[1584] The device sends the saved free words to the server via an HTTP request, and the request includes the search query.

[1585] Step 3:

[1586] The server generates restaurant information based on the search query.

[1587] The server analyzes the received search query and generates restaurant information that matches the criteria from the database.

[1588] Use generative AI to optimize search results to best meet your needs.

[1589] Step 4:

[1590] The server transmits restaurant information to the terminal.

[1591] The server returns the optimized restaurant information to the terminal as an HTTP response.

[1592] Search results include details such as store name, address, opening hours, and price range.

[1593] Step 5:

[1594] The device uses an emotion engine to analyze the user's emotions.

[1595] The terminal acquires the user's voice input or facial expression data.

[1596] An emotion engine analyzes this data to determine the user's current emotional state.

[1597] Step 6:

[1598] The device makes a request to the server to tailor the search results.

[1599] The device sends the analysis results to the server and requests that the search results be re-adjusted based on the user's emotional state.

[1600] Step 7:

[1601] The server adjusts search results based on emotional state.

[1602] Based on the emotion analysis results, the server regenerates search results from the database that are appropriate to the user's emotions.

[1603] For example, if the user is in the mood for "celebration," a restaurant with special seating and courses will be offered.

[1604] Step 8:

[1605] The device displays the re-calibrated search results to the user.

[1606] The terminal displays the search results after the readjustment received to the user in list form.

[1607] Each item includes buttons such as "View details" and "Make a reservation."

[1608] Step 9:

[1609] The user selects a restaurant and makes a reservation.

[1610] The user selects the desired restaurant from the list and taps the "Make a reservation" button.

[1611] The terminal displays an interface for entering reservation information (date and time, number of people, special notes).

[1612] Step 10:

[1613] The terminal transmits the reservation information to the server.

[1614] The terminal sends the entered reservation information to the server via an HTTP request.

[1615] Step 11:

[1616] The server confirms the reservation.

[1617] Based on the reservation information received by the server, the reservation is confirmed in cooperation with the restaurant's reservation system.

[1618] The confirmed reservation information is returned to the terminal as an HTTP response.

[1619] Step 12:

[1620] The terminal notifies the user of the reservation confirmation information.

[1621] The terminal notifies the user of the received reservation confirmation information.

[1622] For example, the notification will be in the format "Reservation for XX Restaurant has been completed. Date and time: October 10, 2023, 19:00, Number of people: 2."

[1623] Example 2

[1624] 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."

[1625] Conventional information provision systems not only lack the ability to provide appropriate recommendations based on the user's location information in real time, but also the ability to adjust the information according to the user's emotional state. Furthermore, they lack the ability to allow users to search for restaurant information by specifying detailed conditions and make immediate reservations. This makes it difficult to improve user satisfaction and results in low convenience.

[1626] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1627] In this invention, the server includes a means for acquiring location information of the area where the user is currently walking, a means for transmitting the location information to the server, and a means for generating recommendation information based on the location information. This enables real-time information provision based on the user's current location. It also includes an emotion engine that analyzes the user's emotional state and a means for adjusting recommendation information based on the emotional state. This enables information provision according to the user's emotions. Furthermore, by including a means for generating recommendation information and restaurant information using a generative AI model and a means for generating information based on a prompt sentence entered by the user, highly accurate information provision that satisfies the user is realized. Furthermore, by including a means for the user to input a search query using free words, a means for generating restaurant information based on the search query, and a means for making a reservation at a specific restaurant based on the search query, a highly convenient restaurant search and reservation function is also provided.

[1628] "User" refers to a person who uses the system.

[1629] "Location Information" refers to geographic data including a user's current latitude and longitude.

[1630] "Server" refers to a computer system that receives and processes data sent from a user's terminal.

[1631] An "emotion engine" refers to a combination of software or hardware that analyzes a user's voice and facial expressions to determine the user's emotional state.

[1632] "Recommended information" refers to information generated based on the user's location information and emotional state, and includes places and events that may be of interest to the user.

[1633] "Audio guidance" refers to guidance information provided to the user by voice.

[1634] A "free word search" refers to a search that is conducted by the user entering any word or phrase.

[1635] A "search query" refers to text data that represents search conditions or requests that a user inputs into a system.

[1636] "Restaurant information" refers to various data about restaurants (e.g., restaurant name, price range, seating availability, etc.) generated by the system based on a user's search query.

[1637] "Generative AI models" refer to algorithms and systems that use artificial intelligence to generate information based on user requests.

[1638] A "prompt sentence" refers to the input text that serves as the basis for generating information for a generative AI model.

[1639] The present invention is a system that provides real-time information related to the area where a user is currently walking, including an emotion engine that recognizes the user's emotions and adjusts recommended information. The system acquires the user's location information, generates recommended information based on that information, and provides it as voice guidance. The user can also input a free-word search query, generate restaurant information based on that, and make reservations. The emotion engine analyzes the user's voice input and facial expressions and adjusts the information provided based on the results of the analysis.

[1640] When a user launches an application, the device uses a GPS sensor to obtain the current location (latitude and longitude) in real time. This location information is sent to a server. The device is equipped with a GPS sensor and a communication module required for sending and receiving data. Specific hardware examples include smartphones, tablets, and laptops.

[1641] The server uses the generated AI to search for recommendations in the surrounding area based on the received location information. The generated AI can be, for example, OpenAI's GPT-4. The server sends the following prompt to the generated AI:

[1642] "Tell me some recommended spots near my current location"

[1643] Based on the information provided by the generating AI, the server further organizes the information and sends it to the terminal.

[1644] The device then provides the received information to the user as voice guidance, using voice synthesis software such as the Google Cloud Text-to-Speech API.

[1645] By incorporating an emotion engine, the system analyzes the user's emotional state and adjusts recommendations based on that information. The device uses a microphone to collect the user's voice input and a camera to recognize the user's facial expressions. The emotion engine can use the Google Cloud Speech-to-Text API or Azure's Emotion API. For example, if the user says "I'm tired," the emotion engine will recommend cafes and quiet places where the user can relax. If the user has a smiling expression, the emotion engine will suggest fun events and restaurants with a cheerful atmosphere.

[1646] As a concrete example, consider the case where a user is walking around Shinjuku Station. The user launches an application, and the device acquires location information around Shinjuku Station. Based on this location information, the server generates recommendation information such as, "There's a new cafe about a three-minute walk away. They're currently offering half-price drinks as part of their opening campaign." and sends this information to the device. The device then relays this information to the user as voice guidance.

[1647] Furthermore, if the user voice-inputs "I'm tired and want to rest somewhere," the emotion engine will determine the user's state as "fatigue," and the server will provide information about places to relax, such as "You can relax in a nearby park."

[1648] When a user wants to search for a restaurant based on specific criteria, they can use the free word search function. For example, they can enter a search query such as "a table for drinking with my boss under 4000 yen, smoking allowed." The device sends this input to the server, which then generates a list of restaurants that match the criteria. Search results include candidates such as "XX restaurant, △△ bistro." When the user selects the desired restaurant and makes a reservation, the device sends the reservation information to the server, and the server confirms the reservation and returns the information to the device.

[1649] In this way, the present invention provides real-time information based on the user's current location and also provides information that takes the user's emotions into consideration. Restaurant search and reservation functions are also integrated, making this a system that greatly improves user convenience.

[1650] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1651] Step 1:

[1652] The user launches the application

[1653] A user taps an application on their smartphone to launch it. The device loads the application's interface and various functions and becomes ready. The user's operation is the input, and the application screen is displayed as the output.

[1654] Step 2:

[1655] The device obtains its current location

[1656] The device activates its built-in GPS sensor and obtains its current latitude and longitude information. Specifically, the device's location service is activated and receives signals from GPS satellites to determine its location. The input is the signal from the GPS satellites, and the output is the obtained latitude and longitude information. This data is stored internally in JSON format or other appropriate format.

[1657] Step 3:

[1658] Sending location information

[1659] The device packs the acquired location information into packets and sends them to the server using the HTTPS protocol. The input is the latitude and longitude information acquired by the device, and the output is data that is sent to the server. The specific operation utilizes the device's communication module.

[1660] Step 4:

[1661] Server-generated recommendations

[1662] The server sends a specific prompt to the generative AI model (e.g., a generation algorithm) based on the received location information. This prompt might be something like, "Tell me some recommended spots near the user's current location." The server receives the location information as input, and uses that information to process the data to generate an appropriate prompt. The output is recommendations based on this prompt. A cloud-based model (e.g., GPT-4) is used as the generative AI, which returns the results to the server.

[1663] Step 5:

[1664] Analysis by emotion engine

[1665] The device uses a microphone to collect the user's voice input and a camera to recognize facial expressions. Inputs include the user's voice data and video data from the camera. This data is sent to a local emotion analysis engine. Specifically, Google Cloud Speech-to-Text API and Azure Emotion API are used. Data processing involves converting the voice data into text and determining the user's emotional state, and the results are output.

[1666] Step 6:

[1667] Server-adjusted recommendations

[1668] The server adjusts the recommendation information based on the emotional information received from the emotion engine. The input is data on the user's emotional state, and the output is new recommendation information generated according to the emotion. For example, if the user's state is determined to be "fatigue," the server adjusts the recommendation information to provide information on relaxing cafes and quiet spots.

[1669] Step 7:

[1670] Providing recommendations

[1671] The device receives the final recommendation information sent from the server and provides it to the user as voice guidance. Specifically, it generates synthetic voice using Google Cloud Text-to-Speech API, etc. The input is the recommendation information data from the server, and the output is the generated voice guidance, which is provided to the user.

[1672] Step 8:

[1673] Perform a free word search

[1674] The user enters a free word containing a specific requirement into the search bar within the application. For example, a search query such as "a table for drinks with my boss for under 4000 yen, smoking allowed" is entered. The input is the user's free-form text data, which the device packs into packets to send to the server. The output is the data to be sent to the server.

[1675] Step 9:

[1676] Server generates restaurant information

[1677] Based on a free-word search query, the server uses a generative AI model to generate information about restaurants that match the criteria. For example, using the "Search for Restaurants" prompt. The input is the search query data, and the output is a list of restaurants based on the search criteria. This information is processed on the server and may also retrieve information from databases or external APIs.

[1678] Step 10:

[1679] Providing restaurant information and reservations

[1680] The user selects the restaurant of their choice and makes a reservation. The terminal packs the reservation information into a packet and sends it to the server. The input is the user's selection data and reservation information, and the output is the data to be sent to the server. The server processes the received reservation information and makes an actual reservation request to the restaurant. Information indicating that the reservation has been confirmed is then returned to the terminal, and the terminal notifies the user that the reservation has been confirmed.

[1681] (Application example 2)

[1682] 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."

[1683] Conventional navigation systems and information systems provide recommended information based on the user's current location, but because they do not take the user's emotional state into account, they may not fully meet the needs of individual users. Furthermore, even systems that provide restaurant information or have reservation functions have difficulty providing appropriate information based on the user's mood and situation. Therefore, the present invention aims to provide information that reflects the user's emotional state and customized navigation guidance for autonomous vehicles.

[1684] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring location information of the area where the user is currently located, means for transmitting the location information to the server, and means for generating recommended information based on the location information. This makes it possible to provide information in real time based on the user's current location.

[1685] Furthermore, a means for analyzing the emotional state of the user and a means for adjusting the recommended information based on the emotional state are added, thereby enabling the provision of information customized according to the user's mood and state.

[1686] The system also includes a means for inputting a search query using free words, a means for generating restaurant information based on the search query, a means for providing the restaurant information to the user, a means for reserving a specific restaurant based on the search query, and a means for adjusting the restaurant information based on the emotional state, thereby enabling the user to search for restaurants using detailed conditions and obtain optimal results according to their emotions.

[1687] "Location information of the area where the user is currently located" is data that indicates the geographical location where the user is located at a particular point in time.

[1688] A "server" is a computer system that processes and stores information over a network and provides data and services to client devices.

[1689] "Recommended information" is useful data or guidance that is generated based on the user's current location and other conditions and provided to the user.

[1690] "Audio guidance" is a method of providing information to a user using audio.

[1691] "Emotional state" refers to the user's current mood and psychological state, and analyzing this makes it possible to provide information suited to the user's needs and requests.

[1692] A "conditioning tool" is a method or process that changes or optimizes information or data based on specific conditions or criteria.

[1693] A "means for entering a search query using free words" is an interface that allows users to search for information using any word or phrase.

[1694] "Restaurant information" is information about a specific restaurant, including location, menu, price, and ratings.

[1695] A "reservation means" is a method or tool that a user uses to reserve a particular service or facility in advance.

[1696] A "generative AI model" is an algorithm that uses generative adversarial networks and other artificial intelligence techniques to automatically generate new data or information based on input data.

[1697] A "prompt sentence" is a string or sentence that is input to a generative AI model to prompt it to generate appropriate data.

[1698] The present invention is a system that acquires location information of the user's current location, analyzes the user's emotional state based on that information, and provides appropriate recommended information as audio guidance. The following hardware and software are used to implement the present invention.

[1699] Hardware

[1700] GPS sensor: Used to obtain the user's current location in real time.

[1701] Microphone and camera: Used to analyze the user's voice input and facial expressions to determine their emotional state.

[1702] Terminal (smartphone or in-car display): Used to run the system and provide voice guidance to the user.

[1703] Server: Used to generate recommendations using a generative AI model based on the user's location and emotional state, and send them to the device.

[1704] software

[1705] Location information acquisition software (GPS library): Works with the GPS sensor to acquire the user's current location.

[1706] Emotion analysis software (EmotionEngine): Analyzes the user's voice input and facial expression data to determine their emotional state.

[1707] Text-to-Speech software: Provides users with recommended information as audio guidance.

[1708] Generative AI model: Generates recommendations based on the user's current location and emotional state.

[1709] Processing flow explanation

[1710] 1. Location information acquisition: The device uses the GPS sensor to acquire the user's current location (latitude and longitude) in real time. This location information is sent to the server.

[1711] 2. Emotional state analysis: The device's microphone and camera are used to collect the user's voice input and facial expressions, which are then analyzed by the Emotion Engine.

[1712] 3. Information generation: The server receives the user's location information and emotional state and generates recommendations using a generative AI model. For example, it analyzes prompts such as "Recommend places around (latitude, longitude) for a person feeling (emotion)."

[1713] 4. Providing information: The server sends the generated recommendation information to the terminal, which uses TextToSpeech software to provide it to the user as voice guidance.

[1714] Specific examples

[1715] When a user is in an autonomous vehicle, the system operates as follows: Suppose the user's vehicle arrives at its current location (e.g., Shinjuku Ward, Tokyo). The GPS acquires this location information and sends it to the server. At the same time, the user vocally inputs, "I'm tired." The Emotion Engine analyzes this voice and determines the user's emotional state as "fatigue." The server sends the prompt "Recommend places around 35.6895,139.6917 for a person feeling tired" to the generative AI model, generating information recommending places to relax. The device receives this information and provides voice guidance to the user, saying, "The nearby cafe is quiet and relaxing."

[1716] In this way, the present invention provides real-time information based on the user's current location and emotional state, enabling customized navigation guidance, particularly in autonomous vehicles.

[1717] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1718] Step 1:

[1719] The device uses the GPS sensor to obtain the user's current location (latitude and longitude) in real time. This location information becomes input data, and the device sends it to the server.

[1720] Step 2:

[1721] Based on the location information received, the server retrieves information about the surrounding area from a database and sends a prompt to the generative AI model based on that information. This prompt includes a sentence in the format "Recommend places around (latitude, longitude)." The AI ​​model generates recommendations based on this prompt. The generated recommendations become the output data.

[1722] Step 3:

[1723] The device collects the user's voice input and facial expressions using a microphone and camera, and sends the data to the Emotion Engine. This input data is analyzed by the Emotion Engine, which determines the user's emotional state. The analysis results are output as emotions such as "fatigue" or "enjoyment."

[1724] Step 4:

[1725] The server receives the emotional state output from the Emotion Engine and adjusts the recommendation information based on that information. For example, if the user's emotional state is "fatigue," it will prioritize recommendations of cafes and parks where people can relax. This adjusted information is then output again.

[1726] Step 5:

[1727] The server sends the adjusted recommendations to the device, which then uses TextToSpeech software to provide the recommendations to the user as voice guidance, which is the final output.

[1728] Step 6:

[1729] When a user wants to perform a free-word search, they input a search query into their device. This query becomes input data and is sent to the server. The server retrieves restaurant information from a database based on this query and generates appropriate restaurant information using a generative AI model.

[1730] Step 7:

[1731] The server sends the generated restaurant information to the terminal. The terminal displays the information to the user, who selects the desired restaurant and makes a reservation. This reservation information is sent to the server, which processes the reservation. Reservation confirmation information is sent to the terminal and notified to the user.

[1732] This allows users to obtain real-time information about their current location and experience navigation guidance customized to their emotional state.

[1733] 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.

[1734] 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.

[1735] 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.

[1736] 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.

[1737] 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.

[1738] 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.

[1739] 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).

[1740] 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, motorcycles, and other devices, 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.

[1741] 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."

[1742] 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.

[1743] 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).

[1744] 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.

[1745] 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.

[1746] 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.

[1747] 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.

[1748] 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.

[1749] 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.

[1750] 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 rea...

Claims

1. A means for acquiring location information of an area where a user is currently walking; means for transmitting the location information to a server; means for generating recommendation information based on the location information; means for providing the recommended information to a user as voice guidance; A system including:

2. A means for a user to input a search query using free words; A means for generating restaurant information based on the search query; means for providing the restaurant information to a user; means for making a reservation at a particular restaurant based on the search query; The system of claim 1 further comprising:

3. the recommended information includes information related to the vicinity of the user's current location; 10. The system of claim 1, wherein the audio guidance is provided in real time based on the user's current location.

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