System

Abstract

A system is provided.SOLUTION: A system comprising: means for acquiring position information of a user terminal; means for transmitting the acquired position information to a server; means for acquiring information of surrounding facilities based on the position information by the server; means for collecting vacant seat information of each facility in real time; means for inputting desired conditions of a user; means for proposing an optimum facility based on the desired conditions; and means for requesting a reservation of the proposed facility.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] When dining out, users often find themselves turned away because a restaurant is full when searching for a restaurant that meets their desired criteria, resulting in wasted effort and time. Furthermore, it is difficult for restaurants to provide real-time information about available seats, resulting in lost opportunities to attract customers and food waste. The present invention aims to solve these problems by providing a system that allows users to efficiently find and make reservations at their desired restaurants. [Means for solving the problem]

[0005] The present invention first provides a means for acquiring location information from a user device and includes a means for transmitting the acquired location information to a server. The server also includes a means for acquiring information on nearby facilities based on the received location information and collecting seat availability information for each facility in real time. The system then provides a means for the user to input desired conditions and includes a means for suggesting optimal facilities based on the desired conditions. Furthermore, the system includes a means for requesting a reservation at the suggested facility and a means for the server to process reservation requests to the facility, thereby realizing a system that allows users to efficiently find and make reservations at their desired restaurant. The system also includes a means for generating discount information for reducing food waste for facilities that are about to close and notifying the user of the discount information, and a means for accumulating users' past usage data and using AI to learn users' preferences, enabling more appropriate suggestions to be made.

[0006] "User terminal" refers to a mobile device used by a user, such as a mobile phone, smartphone, or tablet.

[0007] "Location Information" means information indicating the current geographic location of a user terminal, expressed in the form of latitude and longitude.

[0008] A "server" refers to a computer system for processing, storing, and communicating data, and exchanges data with user terminals via a network.

[0009] "Nearby facilities" refers to commercial facilities such as eateries, cafes, and restaurants located near the user's current location.

[0010] "Vacant seat information" is information that indicates the current availability of seats at a particular restaurant or facility.

[0011] "Desired conditions" are the criteria specified by the user when selecting a restaurant, and include specific requests such as non-smoking seats, famous dishes, budget, etc.

[0012] "Optimal facilities" refer to restaurants and facilities that are likely to provide the greatest satisfaction, taking into account the user's current location and desired conditions.

[0013] "Reservation Request" means a request sent by a User to a selected Facility to reserve a seat.

[0014] "Food waste reduction" refers to measures taken to prevent food ingredients and cooked meals from going to waste.

[0015] "Discount information" is information about price discounts offered by restaurants and facilities under certain conditions.

[0016] "AI" is an abbreviation for artificial intelligence, which refers to technology that learns from user data and supports decision-making based on specific rules and algorithms.

[0017] "Learning" refers to the process by which AI analyzes a user's past usage history and behavioral patterns and improves accuracy based on new information. [Brief explanation of the drawings]

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

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

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

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] ---

[0040] The present invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is configured using user terminals, a server, and databases and real-time seat availability information provided by restaurants.

[0041] Acquiring and sending location information

[0042] Device: When a user launches the app, the device uses its GPS to obtain its current location, which is then sent to the server in the form of latitude and longitude.

[0043] Example: A user starts a smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to a server.

[0044] Obtaining information on nearby facilities

[0045] Server: Based on the received location information, the server retrieves a list of restaurants in the vicinity from a database. This list includes basic information such as the restaurant name, location, and type.

[0046] Real-time collection of vacant seat information

[0047] Server: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[0048] Example: Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[0049] Setting desired conditions

[0050] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) into the app.

[0051] Terminal: The terminal organizes these conditions, converts them into JSON format, and sends them to the server.

[0052] Proposal of the best facility

[0053] Server: The server uses AI to select the most suitable restaurant based on the user's location and desired conditions. The AI ​​creates a list of restaurants that have available seats and meet the desired conditions in real time.

[0054] Terminal: The recommendation results received from the server are displayed on the user's terminal. The user can then choose from the multiple restaurants suggested.

[0055] Example: If a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," the server will search for restaurants that meet the conditions and suggest "Restaurant A" and "Cafe B."

[0056] Reservation Requests and Confirmations

[0057] User: Selects the desired restaurant from the suggested options and requests a reservation.

[0058] Terminal: The terminal sends the selected store information to the server and makes a reservation request.

[0059] Server: The server sends a reservation request to the selected restaurant, receives confirmation, and notifies the user of the result.

[0060] Example: A user selects "Restaurant A" and submits a reservation request. The server sends a request to Restaurant A and notifies the user that the reservation has been confirmed.

[0061] Food waste reduction and discount information

[0062] Server: Generates discount information for restaurants that are about to close to reduce food waste and notifies users.

[0063] Device: Discount information is displayed on the user's device, and immediate reservation is possible if desired.

[0064] Example: If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[0065] Learning user preferences

[0066] Server: The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Based on the learning results, the server makes more accurate suggestions for the next time the user uses the service.

[0067] Example: If a user has frequently dined in "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[0068] ---

[0069] In this way, the present invention allows users to efficiently find and reserve restaurants of their choice. It also enables restaurants to provide real-time information about available seats, providing a system that contributes to both attracting customers and reducing food waste.

[0070] The processing flow will be explained below.

[0071] ---

[0072] Step 1:

[0073] User: Launches the app and agrees to location data collection.

[0074] Step 2:

[0075] Device: If location access is allowed, the device's GPS function will be used to obtain the current location. Location information will be obtained in the form of latitude and longitude.

[0076] Step 3:

[0077] Device: Sends the acquired location information to the server. The sent information consists of latitude and longitude data.

[0078] Step 4:

[0079] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. The retrieved list contains basic information about each restaurant, such as its name, address, and type.

[0080] Step 5:

[0081] Server: Real-time seat availability information is collected from each restaurant using POS systems and motion sensors. The seat availability information is obtained via API.

[0082] Step 6:

[0083] Server: Organize the acquired vacant seat information and send it to the user's device in JSON format.

[0084] Step 7:

[0085] Terminal: The received seat availability information is displayed to the user. A list of stores with available seats is displayed.

[0086] Step 8:

[0087] User: Enter your desired conditions (e.g. non-smoking seat, private room, budget, etc.) on the app screen.

[0088] Step 9:

[0089] Terminal: Convert the entered desired conditions into JSON format and send it to the server.

[0090] Step 10:

[0091] Server: Based on the received desired conditions, AI is used to select the most suitable restaurant. The AI ​​refers to a list of nearby restaurants and real-time seat availability information to extract restaurants that meet the user's conditions.

[0092] Step 11:

[0093] Server: The AI ​​selection results are sent to the user's device in JSON format.

[0094] Step 12:

[0095] Terminal: The received suggestions are displayed to the user, who can then choose from the list of suggested restaurants.

[0096] Step 13:

[0097] User: Select the desired restaurant from the suggested restaurants (e.g., "Restaurant A").

[0098] Step 14:

[0099] Terminal: Send the selected store information to the server in JSON format.

[0100] Step 15:

[0101] Server: Sends a reservation request to the selected store via API. Waits for the reservation confirmation result.

[0102] Step 16:

[0103] Server: Receives the reservation confirmation result and sends it to the user's device in JSON format. For example, "Your reservation for Restaurant A has been confirmed."

[0104] Step 17:

[0105] Terminal: Notifies the user of the received reservation results.

[0106] Step 18:

[0107] Server: Receives information about upcoming closing times and generates discount information to reduce food waste.

[0108] Step 19:

[0109] Server: Sends discount information in JSON format to the user's device.

[0110] Step 20:

[0111] Device: Display discount information on the user's device and provide the option to take advantage of the discount and make an instant reservation.

[0112] Step 21:

[0113] User: Check the discount information and press the instant reservation button if desired.

[0114] Step 22:

[0115] Server: Processes discount reservation requests and sends the final results to the user terminal.

[0116] Step 23:

[0117] Server: User reservation data and usage history are stored in a database, and AI learns user preferences.

[0118] Step 24:

[0119] Server: From the next time you use the service, it will suggest more appropriate restaurants based on the learning results.

[0120] ---

[0121] In this way, we have specifically explained all the steps from obtaining the user's location information to confirming the reservation, providing discount information to reduce food waste, and learning the user's preferences.

[0122] Example 1

[0123] 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."

[0124] The problem that this invention aims to solve is to provide a system that allows users to efficiently find and make reservations at restaurants of their choice, and also allows restaurants to transmit information about available seats in real time, thereby contributing to both attracting customers and reducing food waste.

[0125] 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.

[0126] In this invention, the server includes means for acquiring location information from the user device, means for acquiring information on nearby facilities based on the acquired location information, means for collecting vacant seating information for each facility in real time, means for inputting the user's desired conditions, means for suggesting optimal facilities based on the desired conditions, means for requesting reservations at the suggested facilities, means for processing reservation requests to the facilities, means for generating discount information based on usage data and notifying the user, and means for accumulating past usage data and using a generative model to learn the user's preferences. This allows users to efficiently find and make reservations at their desired restaurants. Furthermore, restaurants can transmit vacant seating information in real time, achieving both customer attraction and food waste reduction.

[0127] A "user terminal" is a device operated by a user, and includes a smartphone, tablet, or personal computer.

[0128] "Location Information" means information indicating the current geographic location of a user terminal, expressed in the form of latitude and longitude.

[0129] A "server" refers to a computer system that receives requests from user terminals and provides the necessary information in cooperation with a database.

[0130] "Nearby facilities" refers to restaurants and other facilities within a certain range based on the user's current location.

[0131] "Vacancy information" is information showing the current seat availability at each facility, and is obtained in real time based on POS data and sensor information.

[0132] "Desired conditions" are conditions that a user specifies when choosing a restaurant or other facility, and include items such as non-smoking seats, private rooms, and budget.

[0133] "Optimal facility" refers to the ideal facility selected by AI based on the user's location information and desired conditions.

[0134] "Reservation Request" means a request by a User to communicate to a Facility selected by the User that the User wishes to make a reservation.

[0135] "Discount information" refers to information indicating discounts offered under specific conditions by the facility, and particularly includes information related to reducing food waste near closing time.

[0136] "Usage data" refers to historical information such as the facilities a user has used in the past and the conditions at that time.

[0137] A "generative model" is an artificial intelligence model that learns a user's preferences based on their past usage data and uses this information to make suggestions for future use.

[0138] The present invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is configured using user terminals, a server, and databases and real-time seat availability information provided by restaurants.

[0139] Acquiring and sending location information

[0140] Device: When a user launches the smartphone app, the device's GPS function is used to obtain the current location information. This location information is obtained in the form of latitude and longitude and sent to the server.

[0141] Example: A user starts a smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to a server.

[0142] Obtaining information on nearby facilities

[0143] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information about each restaurant, such as its name, location, and type (Japanese, Chinese, French, etc.).

[0144] Real-time collection of vacant seat information

[0145] Server: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[0146] Example: Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[0147] Setting desired conditions

[0148] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) into the app.

[0149] Terminal: The terminal organizes these desired conditions, converts them into JSON format, and sends them to the server.

[0150] Proposal of the best facility

[0151] Server: The server uses a generative AI model to select the most suitable restaurant based on the user's location and desired conditions. The generative AI model lists restaurants that have available seats and meet the desired conditions in real time.

[0152] Terminal: The recommendation results received from the server are displayed on the user's terminal. The user can then choose from the multiple restaurants suggested.

[0153] Example: If a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," the server will search for restaurants that meet the conditions and suggest "Restaurant A" and "Cafe B."

[0154] Reservation Requests and Confirmations

[0155] User: Selects the desired restaurant from the suggested options and requests a reservation.

[0156] Terminal: The terminal sends the selected store information to the server and makes a reservation request.

[0157] Server: The server sends a reservation request to the selected restaurant, receives confirmation, and notifies the user of the result.

[0158] Example: A user selects "Restaurant A" and submits a reservation request. The server sends a request to Restaurant A and notifies the user that the reservation has been confirmed.

[0159] Food waste reduction and discount information

[0160] Server: Generates discount information for restaurants that are about to close to reduce food waste and notifies users.

[0161] Device: Discount information is displayed on the user's device, and immediate reservation is possible if desired.

[0162] Example: If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[0163] Learning user preferences

[0164] Server: The server stores the user's past reservation data and usage history, and the generative AI model learns the user's preferences. Based on the learning results, the server makes more accurate suggestions for future use.

[0165] Example: If a user has frequently dined in "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[0166] Prompt Sentence Examples

[0167] Send the location information of users who have agreed to "Use current location." Send it to the server as latitude: 35.6585, longitude: 139.7454.

[0168] In this way, the present invention allows users to efficiently find and reserve restaurants of their choice. It also enables restaurants to provide real-time information about available seats, providing a system that contributes to both attracting customers and reducing food waste.

[0169] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0170] Step 1:

[0171] Obtaining location information

[0172] Input: The user launches the smartphone app and agrees to "Use my location."

[0173] What it does: Uses the device's GPS to obtain the current location.

[0174] Output: Location information in latitude and longitude format (e.g., latitude 35.6585, longitude 139.7454).

[0175] Step 2:

[0176] Sending location information

[0177] Input: The location information obtained in step 1.

[0178] Operation: The device sends the location information it has acquired to the server.

[0179] Output: The location information is sent to the server.

[0180] Step 3:

[0181] Obtaining information on nearby facilities

[0182] Input: Location sent to the server (latitude 35.6585, longitude 139.7454).

[0183] How it works: Based on your location, the server retrieves a list of nearby restaurants from a database, including the name, location, and type of each restaurant.

[0184] Output: A list of nearby restaurants (e.g. Restaurant A, Cafe B, etc.).

[0185] Step 4:

[0186] Gathering vacancy information

[0187] Input: List of nearby restaurants obtained in step 3.

[0188] Operation: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. The server obtains seat availability information via API.

[0189] Output: Real-time seat availability information (e.g. Restaurant A has 5 available seats).

[0190] Step 5:

[0191] Input of user's desired conditions

[0192] Input: The user enters their desired conditions (e.g., non-smoking seat, private room, budget under 5,000 yen) into the app.

[0193] Operation: The device converts the entered desired conditions into JSON format and sends it to the server.

[0194] Output: The preference data sent to the server.

[0195] Step 6:

[0196] Proposal of the best facility

[0197] Input: Your preferences submitted in step 5 and availability information collected in step 4.

[0198] How it works: The server uses the generative AI model to select the restaurant that best meets the desired criteria. The generative AI model then lists restaurants that have available seats and meet the desired criteria in real time.

[0199] Output: A list of the best restaurants (e.g. "Restaurant A", "Cafe B").

[0200] Step 7:

[0201] Displaying the proposed results

[0202] Input: The list of best restaurants selected in step 6.

[0203] Operation: The device displays the suggestions received from the server to the user in a list format.

[0204] Output: The user can view a list of suggested restaurants.

[0205] Step 8:

[0206] Submit a booking request

[0207] Input: The user selects the desired restaurant from the suggested restaurants.

[0208] Operation: The device sends the selected store information to the server and makes a reservation request.

[0209] Output: The booking request sent to the server.

[0210] Step 9:

[0211] Reservation processing and confirmation

[0212] Input: The booking request submitted in step 8.

[0213] Operation: The server sends a reservation request to the selected restaurant, receives confirmation, and notifies the user terminal of the confirmation result.

[0214] Output: Booking confirmation notification (e.g. "Your booking is confirmed").

[0215] Step 10:

[0216] Food waste reduction and discount information generation

[0217] Input: Closing time and restaurant availability.

[0218] How it works: The server generates discount information to reduce food waste and notifies the user.

[0219] Output: Discount information notification (e.g. "20% off food").

[0220] Step 11:

[0221] Learning user preferences

[0222] Input: User's past booking data and usage history.

[0223] How it works: A server stores this data and a generative AI model learns user preferences.

[0224] Output: Improved accuracy of suggestions from next time onwards (e.g., a user who has previously preferred Japanese food will be given priority in suggestions of Japanese restaurants).

[0225] In this way, each step specifically constitutes the operation of the entire system.

[0226] (Application example 1)

[0227] 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."

[0228] In today's busy lifestyles, users face challenges in efficiently finding nearby restaurants, selecting a menu that meets their desired criteria, and ordering delivery. Existing delivery services are unable to provide real-time information on available menu items and seating availability based on the user's current location, and there are limited means for users to track the progress of their delivery in real time. This results in reduced convenience for users, and restaurants also face challenges in efficiently attracting customers and reducing food waste.

[0229] 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.

[0230] In this invention, the server includes a means for displaying delivery options on the user terminal, a means for the server to acquire delivery progress information and notify the user terminal, and a means for collecting seat availability information of nearby facilities in real time, thereby enabling users to efficiently browse delivery menus of nearby restaurants and keep track of delivery progress in real time.

[0231] A "user terminal" is a portable electronic device for use by a user, such as a smartphone or tablet terminal.

[0232] "Location information" is data indicating the current location of a user terminal, and is geographical information expressed in the form of latitude and longitude.

[0233] A "server" is a computer system that processes and provides data over a network.

[0234] "Nearby facilities" are restaurants and other related facilities located near the current location of the user terminal.

[0235] "Vacant seat information" is data indicating the current availability of seats at surrounding facilities.

[0236] "Real-time" means that information is processed and updated almost instantaneously.

[0237] "Desired conditions" are conditions based on specific requests or preferences entered by the user, such as non-smoking seats or budget.

[0238] A "delivery menu" is a list of dishes and drinks that nearby facilities can provide to users.

[0239] "Delivery progress information" is status information that indicates the stage of delivery ordered by the user.

[0240] A "reservation request" is a request to make a reservation at a facility selected by the user.

[0241] "Food waste reduction" refers to efforts to reduce the waste of food and drink.

[0242] "Discount information" is data regarding discounts offered by establishments that are about to close.

[0243] "Past usage data" refers to historical information about reservations and orders previously made by a user.

[0244] "AI" stands for artificial intelligence, a system that uses techniques such as machine learning to learn user preferences.

[0245] This invention is a system that allows users to efficiently find their desired restaurant and place delivery orders and reservations. This system is configured using user terminals, a server, and real-time information on available seats and menu items available for delivery at restaurants.

[0246] Acquiring and sending location information

[0247] When a user launches a smartphone app, the device uses its GPS to obtain its current location information, which is then sent to a server in the form of latitude and longitude.

[0248] Obtaining information on nearby facilities

[0249] The server retrieves a list of restaurants in the vicinity from a database based on the received location information. This list includes basic information such as the restaurant name, location, and type.

[0250] Real-time collection of vacant seat information

[0251] The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[0252] Display of menu items available for delivery

[0253] The server collects information on delivery options from nearby restaurants and provides it to the user's device. Users can then browse the available menu items and place their order on the app.

[0254] Setting desired conditions

[0255] Users input their desired conditions (e.g., vegetarian options, budget, etc.) into the app. The device organizes these conditions, converts them into JSON format, and sends it to the server.

[0256] Proposal of the best facility

[0257] The server uses AI (artificial intelligence) to select the most suitable restaurant based on the user's location information and desired conditions. The AI ​​lists restaurants and delivery menus that have available seats and meet the desired conditions in real time. The recommendation results received from the server are displayed on the user's device, and the user can choose from multiple suggested restaurants and menus.

[0258] Reservation Requests and Confirmations

[0259] The user selects a desired restaurant from the suggested restaurants and requests a reservation. The terminal sends the selected restaurant information to the server and makes a reservation request. The server sends the reservation request to the selected restaurant and receives confirmation. The result is notified to the user terminal.

[0260] Delivery progress notifications

[0261] Once a delivery order is placed, the server obtains delivery progress information in real time and notifies the user's device, allowing the user to keep track of the progress of their order.

[0262] Food waste reduction and discount information

[0263] The server generates discount information for restaurants that are about to close and notifies the user of the discount information. The discount information is displayed on the user's device, and the user can make an immediate reservation if desired.

[0264] Learning user preferences

[0265] The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Based on the learning results, more accurate suggestions will be made the next time the user uses the restaurant. For example, if a user has frequently eaten at restaurants serving "Japanese cuisine" in the past, restaurants serving "Japanese cuisine" will be given priority in suggestions from the next time onwards.

[0266] As a specific example, when a user launches a smartphone app and agrees to "use current location," the app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to the server. The server then collects information about available seats and delivery options from nearby restaurants and provides it to the user. The user inputs desired conditions such as non-smoking seats and budget, and the most suitable restaurant is suggested. When a reservation request is sent, the server processes the request and notifies the user of the confirmation result. The app also has a function that notifies the user of the delivery progress in real time.

[0267] An example of a prompt sentence that can be used is, "Please tell me the detailed steps of an app that shows the process for ordering pasta and the delivery progress in real time when a FoodNavi user orders pasta."

[0268] This invention allows users to efficiently search restaurant delivery menus and enjoy delivery while checking the order status in real time. It also enables restaurants to provide real-time information and promote efforts to reduce food waste.

[0269] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0270] Step 1:

[0271] The user launches the smartphone app and agrees to the use of location information. The device uses its GPS function to obtain the user's current location information (latitude and longitude). Specifically, the app reads location coordinates from the smartphone's GPS sensor and stores that information in the device's memory. The input is the location information obtained from the GPS sensor, and the output is location information data to be sent to the server.

[0272] Step 2:

[0273] The user device sends the acquired location information (latitude and longitude) to the server. Specifically, it sends a request including the location information to the server using the HTTP POST method. The input is the location information stored in the device's memory, and the output is the HTTP request sent to the server.

[0274] Step 3:

[0275] The server retrieves information about nearby facilities from a database based on the received location information. This involves generating a search query based on the location information and querying the database. The input is the location information received by the server, and the output is a list of nearby facilities retrieved from the database.

[0276] Step 4:

[0277] The server collects vacant seat information in real time based on POS data and motion sensor information provided by each facility. Specifically, it obtains data from each facility's system via API, analyzes it, and checks whether there are any vacant seats. The input is POS data and motion sensor information, and the output is real-time vacant seat information.

[0278] Step 5:

[0279] The server collects information about menu items available for delivery from each nearby facility and provides it to the user's device. Specifically, it uses an API to obtain menu information, formats the data, and sends it to the user's device. The input is delivery menu information provided by each facility, and the output is the menu information displayed on the user's device.

[0280] Step 6:

[0281] The user enters their desired conditions (e.g., vegetarian options, budget, etc.) on the app. The device organizes these conditions, converts them into JSON format, and sends them to the server. Specifically, it takes the data entered from the user interface, converts it into a specific format, and sends it to the server. The input is the desired conditions entered by the user, and the output is the JSON data sent to the server.

[0282] Step 7:

[0283] The server uses AI to select the most suitable restaurant based on the user's location information and desired conditions. Specifically, the received location information and desired conditions are input into an AI model, which then generates a list of the most suitable restaurants. The input is the location information and desired conditions received by the server, and the output is a list of the most suitable restaurants.

[0284] Step 8:

[0285] The recommendation results received from the server are displayed on the user terminal. Specifically, the user terminal analyzes the information sent from the server and displays it on the user interface. The input is the recommendation results sent by the server, and the output is a list of facilities and menus displayed on the user terminal.

[0286] Step 9:

[0287] The user selects a desired restaurant from the suggested restaurants and requests a reservation. The user terminal sends the selected restaurant information to the server and requests a reservation. Specifically, the system obtains the user's selection and sends a request to the server using the HTTP POST method. The input is the restaurant information selected by the user, and the output is a reservation request sent to the server.

[0288] Step 10:

[0289] The server sends a reservation request to the selected restaurant and receives confirmation. The result is then notified to the user's terminal. Specifically, the server sends a request to the restaurant's system, and once confirmation is received, it sends the information to the user's terminal. The input is the reservation request from the user, and the output is a notification of reservation confirmation.

[0290] Step 11:

[0291] Once a delivery order is confirmed, the server obtains delivery progress information in real time and notifies the user terminal. Specifically, it receives progress information from the delivery system, formats it, and sends it to the user. The input is progress information from the delivery system, and the output is a notification message to the user terminal.

[0292] Step 12:

[0293] The server generates discount information for restaurants that are about to close to reduce food waste and notifies the user. Specifically, the server generates food waste reduction information for specific time periods and notifies the user of it. The input is the store's business information and food waste reduction conditions, and the output is a discount information notification sent to the user's terminal.

[0294] Step 13:

[0295] The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Specifically, past usage data is input into the AI ​​model, which analyzes the user's preferences and trends. The input is the user's past usage data, and the output is future recommendations based on the user's preferences.

[0296] 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.

[0297] ---

[0298] This invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is composed of a user terminal, a server, databases and real-time seat availability information provided by restaurants, and an emotion engine that recognizes the user's emotions.

[0299] Acquiring and sending location information

[0300] Device: When a user launches the app, the device uses its GPS to obtain its current location, which is then sent to the server in the form of latitude and longitude.

[0301] Example: A user starts a smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to a server.

[0302] Obtaining information on nearby facilities

[0303] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information such as the restaurant name, location, and type.

[0304] Real-time collection of vacant seat information

[0305] Server: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[0306] Example: Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[0307] Setting desired conditions

[0308] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) on the app.

[0309] Terminal: Organize the entered desired conditions, convert them into JSON format, and send them to the server.

[0310] Emotion recognition by emotion engine

[0311] On the device: The emotion engine analyzes the user's facial expressions and voice to determine their current emotional state, which is classified into categories such as "happiness," "sadness," and "anger."

[0312] Example: A user accesses the emotion engine through a camera or microphone. The emotion engine identifies "happiness" from the user's facial expressions and voice, and sends this as an analysis result to the server.

[0313] Proposal of the best facility

[0314] Server: The server uses AI to select the most suitable restaurant based on the user's location, desired conditions, and emotional state. The AI ​​refers to this data and creates a list of restaurants that match the user's conditions and emotions.

[0315] Terminal: The terminal displays the restaurant recommendations received from the server to the user, who can then choose from the multiple restaurants suggested.

[0316] Example: If a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," and the emotion engine recognizes "joy," the server will suggest "Restaurant A" and "Cafe B" that match the conditions and emotion.

[0317] Reservation Requests and Confirmations

[0318] User: Selects the desired restaurant from the suggested options and requests a reservation.

[0319] Terminal: Send the selected store information to the server in JSON format.

[0320] Server: Sends a reservation request to the selected store via API, receives confirmation, and notifies the user of the result.

[0321] Example: A user selects "Restaurant A" and submits a reservation request. The server sends a request to Restaurant A and notifies the user that the reservation has been confirmed.

[0322] Food waste reduction and discount information

[0323] Server: Generates discount information for restaurants that are about to close to reduce food waste and notifies users.

[0324] Device: Discount information is displayed on the user's device, and immediate reservation is possible if desired.

[0325] Example: If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[0326] Learning user preferences

[0327] Server: The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Based on the learning results, the server makes more accurate suggestions for the next time the user uses the service.

[0328] Example: If a user has frequently dined in "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[0329] ---

[0330] In this way, the present invention allows users to efficiently find and make reservations at restaurants of their choice. Furthermore, by taking into account the user's emotional state, it is possible to suggest restaurants that will provide a higher level of satisfaction. It also enables restaurants to provide information on available seats in real time, providing a system that contributes to both attracting customers and reducing food waste.

[0331] The processing flow will be explained below.

[0332] ---

[0333] Step 1:

[0334] User: Launches the app and agrees to location data collection.

[0335] Step 2:

[0336] Device: If location access is allowed, the device's GPS function will be used to obtain the current location, which will be in the form of latitude and longitude.

[0337] Step 3:

[0338] Device: Sends the acquired location information to the server. Specifically, sends the acquired latitude and longitude data in JSON format.

[0339] Step 4:

[0340] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information such as the restaurant's name, address, and type.

[0341] Step 5:

[0342] Server: Real-time seat availability information is collected via API based on POS systems and motion sensor information provided by each restaurant. The collected seat availability information is then organized.

[0343] Step 6:

[0344] Server: Convert the acquired vacancy information into JSON format and send it to the user's device.

[0345] Step 7:

[0346] Terminal: The received seat availability information is displayed to the user. A list of restaurants with available seats is displayed on the screen.

[0347] Step 8:

[0348] User: Enter desired conditions (e.g. non-smoking seat, private room, budget, etc.) on the app screen.

[0349] Step 9:

[0350] Terminal: Convert the entered desired conditions into JSON format and send it to the server.

[0351] Step 10:

[0352] On the device: The emotion engine analyzes the user's facial expressions and voice to determine their current emotional state. This emotion data is classified into categories such as "happiness," "sadness," and "anger."

[0353] Step 11:

[0354] Terminal: Converts the emotion data identified by the emotion engine into JSON format and sends it to the server.

[0355] Step 12:

[0356] Server: The AI ​​selects the most suitable restaurant based on the received desired conditions and emotional data. The AI ​​refers to this data and creates a list of restaurants that match the user's conditions and emotions.

[0357] Step 13:

[0358] Server: The AI ​​selection results are sent to the user's device in JSON format.

[0359] Step 14:

[0360] Terminal: The received recommendation results are displayed to the user, who can then choose from multiple suggested restaurants.

[0361] Step 15:

[0362] User: Select the desired restaurant (e.g., "Restaurant A") from the list of suggested restaurants.

[0363] Step 16:

[0364] Terminal: Send the selected store information to the server in JSON format.

[0365] Step 17:

[0366] Server: Send a reservation request to the selected store via API and wait for the reservation confirmation result.

[0367] Step 18:

[0368] Server: Receives the reservation confirmation result and sends it to the user's device in JSON format. Example: "Your reservation for Restaurant A has been confirmed."

[0369] Step 19:

[0370] Terminal: Notifies the user of the received reservation results.

[0371] Step 20:

[0372] Server: Receives information about upcoming closing times and generates discount information to reduce food waste.

[0373] Step 21:

[0374] Server: Sends discount information in JSON format to the user's device.

[0375] Step 22:

[0376] Terminal: Discount information is displayed to the user, and immediate booking is possible if desired.

[0377] Step 23:

[0378] User: Check the discount information and press the instant reservation button if desired.

[0379] Step 24:

[0380] Server: Processes discount reservation requests and sends the final results to the user terminal.

[0381] Step 25:

[0382] Server: User reservation data and usage history are stored in a database, and AI learns user preferences.

[0383] Step 26:

[0384] Server: From the next time you use the service, it will suggest more appropriate restaurants based on the learning results.

[0385] ---

[0386] In this way, we have explained in detail all the steps from obtaining the user's location information, recognizing emotions, suggesting the best restaurant, confirming the reservation, providing discount information to reduce food waste, and learning the user's preferences.

[0387] Example 2

[0388] 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."

[0389] In today's busy lifestyles, it is difficult for users to efficiently find and make reservations at restaurants. Furthermore, suggestions that do not take into account the user's current emotional state may result in low satisfaction. Furthermore, it is difficult for restaurants to provide real-time information on available tables, which leads to the problem of food waste.

[0390] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring location information of the user terminal, means for transmitting the acquired location information to the server, means for the server to acquire information on surrounding facilities based on the location information, means for collecting vacant seat information for each facility in real time, means for allowing the user to input desired conditions, means for suggesting optimal facilities based on the desired conditions, means including an emotion recognition engine for analyzing the user's emotional state, means for requesting reservations at the suggested facilities, and means for the server to process reservation requests for the facilities. This allows users to efficiently find their desired restaurant and make reservations that take their emotional state into consideration, resulting in higher satisfaction. It also enables restaurants to transmit vacant seat information in real time, contributing to reducing food waste.

[0391] "User terminal" refers to a device operated by a user, including smartphones, tablets, and personal computers.

[0392] "Location information" refers to coordinate information of a specific location, expressed in the form of latitude and longitude.

[0393] "Server" refers to a computer system that receives, processes, and manages data sent from multiple user terminals.

[0394] "Facilities" are places that users can visit, including eateries, cafes, restaurants, etc.

[0395] "Vacancy information" refers to data that shows the availability of seats within a facility in real time.

[0396] "Desired conditions" refer to the requirements and wishes that users have for the facility, and include elements such as non-smoking seats, private rooms, and budget.

[0397] An "emotion recognition engine" is software or hardware that analyzes a user's facial expressions and tone of voice to identify their emotional state.

[0398] "Reservation Request" means a request by a User to communicate to a Facility selected by the User that the User wishes to make a reservation.

[0399] "Food waste" refers to ingredients and cooked food that may be discarded without being consumed.

[0400] "Discount Information" means information about price discounts offered under certain conditions specified by the facility.

[0401] "AI" stands for artificial intelligence, a technology that gives computer systems the ability to analyze data and learn.

[0402] "Preference learning" is the process of analyzing a user's preferences and trends based on their past usage data and reflecting them in future suggestions.

[0403] MODE FOR CARRYING OUT THE INVENTION

[0404] This invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is composed of user terminals, a server, databases and real-time seat availability information provided by restaurants, and an emotion engine that recognizes the user's emotions.

[0405] Acquiring and sending location information

[0406] When a user launches the app and agrees to "Use current location," the device will use the built-in GPS to obtain current location information. This location information is obtained in the form of latitude and longitude, converted into JSON format, and then sent to the server using a secure communication protocol (HTTPS).

[0407] Examples:

[0408] The user starts the smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to the server.

[0409] Obtaining information on nearby facilities

[0410] The server retrieves a list of nearby restaurants from a database based on the received location information. This list includes basic information such as the restaurant name, address, category, and opening hours. The retrieved data is formatted in JSON and sent to the user's device.

[0411] Real-time collection of vacant seat information

[0412] The server collects POS system data and motion sensor information provided by each restaurant via API, obtains real-time seat availability information, converts the integrated data into JSON format, and prepares it for transmission to the user's device.

[0413] Examples:

[0414] Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[0415] Setting desired conditions

[0416] Users use the app's interface to input their preferences, such as non-smoking, private rooms, budget, etc. These preferences are organized, converted into JSON format, and sent to the server.

[0417] Examples:

[0418] When a user enters conditions such as "non-smoking seats," "private rooms," and "budget under 5,000 yen," this information is organized in JSON format and sent to the server.

[0419] Emotion recognition by emotion engine

[0420] The emotion engine analyzes the user's facial expressions and tone of voice through the user's camera and microphone. The emotion recognition algorithm identifies the user's current emotional state and converts the results into JSON format and sends it to the server.

[0421] Examples:

[0422] When a user accesses the emotion engine through a camera or microphone, the emotion engine recognizes "happiness" from the user's facial expressions and voice and sends the analysis results to the server.

[0423] Proposal of the best facility

[0424] The server uses AI to select the most suitable restaurant based on the user's location, desired conditions, and emotional state. The AI ​​model takes into account past data and user trends, creates a list of restaurants that match the conditions and emotions, and sends it in JSON format to the user's device.

[0425] Examples:

[0426] When a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," and the emotion engine recognizes "joy," the server will suggest "Restaurant A" and "Cafe B" that match the conditions and emotion.

[0427] Reservation Requests and Confirmations

[0428] The user selects the restaurant of their choice from the suggested options and requests a reservation. The selected restaurant information is converted to JSON format and sent to the server. The server then sends a reservation request to the selected restaurant via API, and sends the reservation confirmation in JSON format to the user's device.

[0429] Examples:

[0430] The user selects "Restaurant A" and submits a reservation request. The server makes a request to Restaurant A and notifies the user that the reservation has been confirmed.

[0431] Food waste reduction and discount information

[0432] The server generates discount information for restaurants that are about to close, in order to reduce food waste, and notifies the user. The discount information is converted into JSON format and displayed on the user's device.

[0433] Examples:

[0434] If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[0435] Learning user preferences

[0436] The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences, which are then used to make more accurate suggestions the next time the user uses the service.

[0437] Examples:

[0438] If a user has frequently visited "Japanese cuisine" restaurants in the past, "Japanese cuisine" restaurants will be prioritized in the list the next time suggestions are made.

[0439] Prompt Sentence Examples

[0440] I agree to "Use my current location" and suggest the best restaurant using a list of restaurants, seat availability information, and an emotion engine. My desired conditions are "non-smoking seat," "private room," "budget under 5,000 yen," and my emotional state is "delighted." I want to be able to make a reservation at the suggested restaurant.

[0441] This invention allows users to efficiently find the restaurant they want, and by taking their emotional state into consideration, it is possible to suggest restaurants that will increase their satisfaction. It also enables restaurants to send out information about available seats in real time, which will help reduce food waste.

[0442] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0443] Step 1: Obtaining and sending location information

[0444] Device:

[0445] When the app is launched, the device uses its built-in GPS to obtain its current location. This location information is obtained in the form of latitude and longitude and converted into JSON format. The converted location information is then sent to the server using a secure communication protocol (HTTPS).

[0446] Specific behavior:

[0447] Input: The user launches the app on their smartphone and agrees to "Use my location."

[0448] Data processing: Latitude and longitude data is obtained using the smartphone's GPS function and converted into JSON format.

[0449] Output: The converted location information is sent to the server.

[0450] Step 2: Obtain information about nearby facilities

[0451] server:

[0452] Based on the received location information, the server queries the database to obtain a list of nearby restaurants. This list includes basic information such as the restaurant name, address, category, and opening hours. The obtained data is formatted in JSON format and sent to the user's device.

[0453] Specific behavior:

[0454] Input: Location information in JSON format.

[0455] Data processing: Based on the received location information, an SQL query is executed on the database to obtain information on nearby facilities. The obtained information is then formatted into JSON format.

[0456] Output: Facility information in JSON format is sent to the user's device.

[0457] Step 3: Real-time collection of seat availability information

[0458] server:

[0459] The server collects POS system data and motion sensor information provided by each restaurant via API, obtains real-time seat availability information, converts the integrated data into JSON format, and prepares it for transmission to the user's device.

[0460] Specific behavior:

[0461] Input: POS system data and motion sensor information from each restaurant.

[0462] Data processing: Calls APIs to collect data from each store, centralizes it in the integration engine, and converts the data into JSON format.

[0463] Output: The vacancy information is converted to JSON format and sent to the user's device.

[0464] Step 4: Set your preferences

[0465] User:

[0466] Users use the app's interface to input their preferences, such as non-smoking, private rooms, and budget.

[0467] Device:

[0468] The entered desired conditions are organized, converted into JSON format, and sent to the server.

[0469] Specific behavior:

[0470] Input: The user enters their desired criteria into the app's interface.

[0471] Data processing: Convert the entered desired conditions into JSON format.

[0472] Output: The desired conditions are sent to the server.

[0473] Step 5: Emotion Recognition with the Emotion Engine

[0474] Device:

[0475] The emotion engine analyzes the user's facial expressions and tone of voice through the user's camera and microphone. The emotion recognition algorithm identifies the user's current emotional state and converts the results into JSON format and sends it to the server.

[0476] Specific behavior:

[0477] Input: The user accesses the emotion engine through a camera or microphone.

[0478] Data processing: The emotion recognition algorithm analyzes the acquired data to identify the emotional state, and converts the results into JSON format.

[0479] Output: The emotion recognition results are sent to the server.

[0480] Step 6: Propose the best facility

[0481] server:

[0482] The server uses AI to select the most suitable restaurant based on the user's location, desired conditions, and emotional state. The AI ​​model takes into account past data and user trends, creates a list of restaurants that match the conditions and emotions, and sends it in JSON format to the user's device.

[0483] Specific behavior:

[0484] Input: location, desired conditions, emotional data.

[0485] Data processing: The AI ​​model uses this data to select and list the best restaurants. The data is formatted into JSON format.

[0486] Output: The proposed results are sent to the user's device in JSON format.

[0487] Step 7: Reservation Request and Confirmation

[0488] User:

[0489] The user selects the desired restaurant from the suggested restaurants and requests a reservation.

[0490] Device:

[0491] Convert the selected store information into JSON format and send it to the server.

[0492] server:

[0493] A reservation request is sent to the selected store via API, and the reservation confirmation result is sent to the user's terminal in JSON format.

[0494] Specific behavior:

[0495] Input: The user selects the desired store.

[0496] Data processing: Convert the selected store information into JSON format.

[0497] Output: A reservation request is sent to the server, and the reservation confirmation result is sent to the user terminal.

[0498] Step 8: Reduce food waste and provide discount information

[0499] server:

[0500] To generate discount information for reducing food waste for restaurants that are about to close and notify the user of the information.

[0501] Device:

[0502] The discount information is converted to JSON format and displayed on the user's device. Based on this information, the user can make an immediate reservation if desired.

[0503] Specific behavior:

[0504] Input: Discount information from restaurants.

[0505] Data processing: Convert discount information into JSON format.

[0506] Output: The discount information is sent to the user's terminal and displayed.

[0507] Step 9: Learning User Preferences

[0508] server:

[0509] By accumulating the user's past reservation data and usage history, the AI ​​learns the user's preferences and uses the results to make more accurate suggestions the next time the user uses the service.

[0510] Specific behavior:

[0511] Input: Past reservation data and usage history.

[0512] Data processing: AI learns from this data and analyzes user preferences. The learning results are used to improve future recommendations.

[0513] Output: Suggestions based on the user's preferences will be reflected in future visits.

[0514] (Application example 2)

[0515] 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."

[0516] Conventional restaurant reservation systems easily provide information based on the user's current location and obtain real-time seat availability information, but they lack a mechanism for suggesting optimal restaurants that take the user's emotional state into account. Furthermore, they have not adequately implemented measures to reduce food waste through discount information for restaurants close to closing time, or to improve the accuracy of personalized recommendations based on the user's past usage data. To address these issues, the present invention aims to provide a restaurant recommendation system that takes the user's emotions into account, thereby enabling a more accurate reservation experience.

[0517] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0518] In this invention, the server includes means for acquiring location information of the user terminal, means for acquiring information on surrounding facilities based on the acquired location information, means for collecting information on available seats at each facility in real time, means for recognizing the emotional state of the user and suggesting facilities taking the emotional state into consideration, means for allowing the user to input desired conditions, means for suggesting optimal facilities based on the desired conditions, means for requesting a reservation at the suggested facility, and means for the server to process reservation requests for the facility. This makes it possible to suggest and reserve optimal restaurants taking the emotional state of the user into consideration.

[0519] A "user terminal" is a portable electronic device used to obtain location information and communicate with a server.

[0520] "Location Information" refers to the geographic coordinate information of a user's current location.

[0521] A "server" is a central processing unit that receives and processes data sent from a user terminal.

[0522] "Nearby facilities" refers to restaurants and other commercial facilities that are searched for based on the user's location information.

[0523] "Available seat information" is information that indicates the current number of available seats at a particular facility.

[0524] "Real-time" refers to information that is updated almost immediately.

[0525] "Desired conditions" refer to the requests and restrictions that users have when selecting a facility.

[0526] "Emotional state" refers to the user's current emotional state and is classified into categories such as "joy," "sadness," and "anger."

[0527] "Suggestion" refers to recommending the most suitable facility based on the user's desired conditions and emotional state.

[0528] "Reservation Request" means making a reservation for a proposed facility.

[0529] "Food waste reduction" refers to reducing the waste of surplus food ingredients in restaurants.

[0530] "Discount information" is information indicating the conditions under which the offered product will be cheaper than its regular price.

[0531] "Usage Data" refers to historical information about reservations and facility usage made by a user.

[0532] "AI" refers to artificial intelligence, a technology that analyzes and learns from user preferences and behavioral patterns based on data.

[0533] This invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is composed of a user terminal, a server, databases and real-time seat availability information provided by restaurants, and an emotion engine that recognizes the user's emotions.

[0534] Acquiring and sending location information

[0535] Device: When a user launches the app, the device uses its GPS function to obtain its current location. This location information is obtained in the form of latitude and longitude and sent to the server. Specifically, when a user launches the smartphone app and agrees to "Use current location," the location information is obtained as "Latitude: 35.6585, Longitude: 139.7454" and sent to the server.

[0536] Obtaining information on nearby facilities

[0537] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information such as the restaurant name, location, and type.

[0538] Real-time collection of vacant seat information

[0539] Server: The server collects seat availability information in real time based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is known. For example, if a restaurant uses a POS system and the data on the number of available seats reports that "there are currently five seats available," the server obtains this information and prepares to provide it to the user.

[0540] Setting desired conditions

[0541] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) on the app.

[0542] Terminal: Organize the entered desired conditions, convert them into JSON format, and send them to the server.

[0543] Emotion recognition by emotion engine

[0544] Device: The emotion engine analyzes the user's facial expressions and voice to identify their current emotional state. This emotional state is classified into categories such as "happiness," "sadness," and "anger." The user accesses the emotion engine via the camera or microphone, and the emotion engine identifies "happiness" from the user's facial expressions and voice and sends this as the analysis result to the server.

[0545] Proposal of the best facility

[0546] Server: The server uses AI to select the best restaurant based on the user's location, desired conditions, and emotional state. The AI ​​refers to this data and creates a list of restaurants that match the user's conditions and emotions.

[0547] Terminal: Displays the recommendation results received from the server to the user. The user can choose from multiple suggested restaurants. For example, if the user sets their desired conditions as "non-smoking seats," "private rooms," and "budget under 5,000 yen," and the emotion engine recognizes "joy," the server will suggest "Restaurant A" and "Cafe B" that match the conditions and emotion.

[0548] Reservation Requests and Confirmations

[0549] User: Selects the restaurant they want from the suggested options and requests a reservation.

[0550] Terminal: Send the selected store information to the server in JSON format.

[0551] Server: Sends a reservation request to the selected restaurant via API and receives confirmation. Notifies the user of the result. For example, if a user selects "Restaurant A" and sends a reservation request, the server makes a request to Restaurant A and notifies the user that the reservation has been confirmed.

[0552] Food waste reduction and discount information

[0553] Server: Generates discount information to reduce food waste for restaurants that are about to close and notifies users.

[0554] Device: Discount information will be displayed on the user's device, and they can make an instant reservation if they wish.

[0555] For example, if a restaurant offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an instant reservation.

[0556] Learning user preferences

[0557] Server: The AI ​​accumulates the user's past reservation data and usage history, and learns the user's preferences. Based on the learning results, it makes more accurate suggestions the next time the user uses the service. For example, if the user has often selected "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[0558] Example prompt sentence:

[0559] "The user wants to have a fun, delicious dinner. The current location is Tokyo Tower. Suggest a nearby restaurant with a private, non-smoking room, and a budget of under 5,000 yen."

[0560] In this way, this invention allows users to efficiently find and make reservations at restaurants of their choice. Furthermore, restaurant suggestions are made taking into account the user's emotional state, enabling a more satisfying reservation experience. It also enables restaurants to provide information on available seats in real time, providing a system that contributes to both attracting customers and reducing food waste.

[0561] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0562] Step 1:

[0563] Launch the app on the user's device and obtain the current location information.

[0564] Input: App launch, location information from GPS sensor

[0565] Output: The latitude and longitude data obtained (e.g., "Latitude: 35.6585, Longitude: 139.7454")

[0566] Specific operation: When a user launches the smartphone app and agrees to "Use current location," the device will use the GPS function to obtain the current location information, which will then be stored in the device's internal memory.

[0567] Step 2:

[0568] The acquired location information is sent to the server.

[0569] Input: Latitude and longitude data stored on the device

[0570] Output: Log of location information sent to the server

[0571] Specific operation: The device sends location information to the server using the server communication protocol. After sending, a log indicating the success is generated.

[0572] Step 3:

[0573] The server obtains information about nearby facilities based on location information.

[0574] Input: Location information received by the server

[0575] Output: List of nearby facilities (name, address, category, etc.)

[0576] Specific operation: Based on the location information received by the server, it sends a query to the database to obtain information about nearby facilities, and returns query results including facility name, address, type, etc.

[0577] Step 4:

[0578] The server collects vacant seat information for each facility in real time.

[0579] Input: List of nearby facilities

[0580] Output: Availability information for each assigned facility

[0581] Specific operation: The server sends a request to each restaurant's system (POS data, motion sensors, etc.) via API to obtain current seat availability information. The results are added to a list of nearby facilities.

[0582] Step 5:

[0583] The user enters the desired conditions.

[0584] Input: User's desired conditions (e.g., non-smoking seat, private room, budget, etc.)

[0585] Output: JSON format data of desired conditions

[0586] Specific operation: The user enters desired conditions on the app screen, and the information is converted to JSON format within the device.

[0587] Step 6:

[0588] The terminal transmits the desired conditions to the server.

[0589] Input: JSON format data of desired conditions

[0590] Output: Log of desired condition data sent to the server

[0591] Specific operation: The device sends the desired condition data in JSON format to the server and generates a log indicating that the transmission was successful.

[0592] Step 7:

[0593] The device recognizes the user's emotional state.

[0594] Input: User facial and voice data collected through the camera and microphone

[0595] Output: Emotional state category (e.g., "joy," "sadness," "anger," etc.)

[0596] Specific operation: The device's emotion recognition engine analyzes facial expressions and voice data, categorizes the user's emotional state, and sends the results to the server.

[0597] Step 8:

[0598] The server suggests the most suitable facility based on location information, desired conditions, and emotional state.

[0599] Input: User's location, desired conditions, emotional state

[0600] Output: List of optimal facilities

[0601] How it works: The server's AI uses the input data to select the most suitable facilities and generate a recommendation list, which includes each facility's rating and the degree of matching of the conditions.

[0602] Step 9:

[0603] Proposals from the server are displayed on the user's device.

[0604] Input: List of optimal facilities

[0605] Output: A list of suggested facilities displayed to the user

[0606] Specific operation: The server sends the generated list of optimal facilities to the terminal, which then visually displays it to the user, allowing the user to select a store from this list.

[0607] Step 10:

[0608] The user selects the desired facility and requests a reservation.

[0609] Input: Facility information selected by the user

[0610] Output: JSON format data of the reservation request

[0611] Specific operation: The user selects the desired facility from the list, and the facility information is converted into JSON format and sent to the server.

[0612] Step 11:

[0613] The server processes reservation requests to facilities.

[0614] Input: Reservation request data for the selected facility

[0615] Output: Confirmed reservation information

[0616] Specific operation: The server sends a reservation request to the facility via API, receives the processing result (reservation success or failure), and notifies the user's device.

[0617] Step 12:

[0618] The server generates discount information to reduce food waste and notifies the user.

[0619] Input: Information from the facility about closing time

[0620] Output: Discount information notification

[0621] Specific operation: Based on discount information provided by establishments that are about to close, the server generates information for reducing food waste and notifies the user. The user receives this information and can make an instant reservation.

[0622] Step 13:

[0623] The server stores users' past usage data and learns their preferences.

[0624] Input: User's past usage history data

[0625] Output: Learned user preference data

[0626] How it works: The server stores the user's past reservation data and usage history, and uses AI to analyze and learn the user's preferences. The results are reflected in the next proposal.

[0627] In this way, a system is constructed that allows users to efficiently find and make reservations at restaurants of their choice through each step.

[0628] 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.

[0629] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0630] 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.

[0631] [Second embodiment]

[0632] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0633] 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.

[0634] 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).

[0635] 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.

[0636] 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.

[0637] 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).

[0638] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0639] 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.

[0640] 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.

[0641] 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.

[0642] 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.

[0643] 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."

[0644] ---

[0645] The present invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is configured using user terminals, a server, and databases and real-time seat availability information provided by restaurants.

[0646] Acquiring and sending location information

[0647] Device: When a user launches the app, the device uses its GPS to obtain its current location, which is then sent to the server in the form of latitude and longitude.

[0648] Example: A user starts a smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to a server.

[0649] Obtaining information on nearby facilities

[0650] Server: Based on the received location information, the server retrieves a list of restaurants in the vicinity from a database. This list includes basic information such as the restaurant name, location, and type.

[0651] Real-time collection of vacant seat information

[0652] Server: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[0653] Example: Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[0654] Setting desired conditions

[0655] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) into the app.

[0656] Terminal: The terminal organizes these conditions, converts them into JSON format, and sends them to the server.

[0657] Proposal of the best facility

[0658] Server: The server uses AI to select the most suitable restaurant based on the user's location and desired conditions. The AI ​​creates a list of restaurants that have available seats and meet the desired conditions in real time.

[0659] Terminal: The recommendation results received from the server are displayed on the user's terminal. The user can then choose from the multiple restaurants suggested.

[0660] Example: If a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," the server will search for restaurants that meet the conditions and suggest "Restaurant A" and "Cafe B."

[0661] Reservation Requests and Confirmations

[0662] User: Selects the desired restaurant from the suggested options and requests a reservation.

[0663] Terminal: The terminal sends the selected store information to the server and makes a reservation request.

[0664] Server: The server sends a reservation request to the selected restaurant, receives confirmation, and notifies the user of the result.

[0665] Example: A user selects "Restaurant A" and submits a reservation request. The server sends a request to Restaurant A and notifies the user that the reservation has been confirmed.

[0666] Food waste reduction and discount information

[0667] Server: Generates discount information for restaurants that are about to close to reduce food waste and notifies users.

[0668] Device: Discount information is displayed on the user's device, and immediate reservation is possible if desired.

[0669] Example: If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[0670] Learning user preferences

[0671] Server: The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Based on the learning results, the server makes more accurate suggestions for the next time the user uses the service.

[0672] Example: If a user has frequently dined in "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[0673] ---

[0674] In this way, the present invention allows users to efficiently find and reserve restaurants of their choice. It also enables restaurants to provide real-time information about available seats, providing a system that contributes to both attracting customers and reducing food waste.

[0675] The processing flow will be explained below.

[0676] ---

[0677] Step 1:

[0678] User: Launches the app and agrees to location data collection.

[0679] Step 2:

[0680] Device: If location access is allowed, the device's GPS function will be used to obtain the current location. Location information will be obtained in the form of latitude and longitude.

[0681] Step 3:

[0682] Device: Sends the acquired location information to the server. The sent information consists of latitude and longitude data.

[0683] Step 4:

[0684] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. The retrieved list contains basic information about each restaurant, such as its name, address, and type.

[0685] Step 5:

[0686] Server: Real-time seat availability information is collected from each restaurant using POS systems and motion sensors. The seat availability information is obtained via API.

[0687] Step 6:

[0688] Server: Organize the acquired vacant seat information and send it to the user's device in JSON format.

[0689] Step 7:

[0690] Terminal: The received seat availability information is displayed to the user. A list of stores with available seats is displayed.

[0691] Step 8:

[0692] User: Enter your desired conditions (e.g. non-smoking seat, private room, budget, etc.) on the app screen.

[0693] Step 9:

[0694] Terminal: Convert the entered desired conditions into JSON format and send it to the server.

[0695] Step 10:

[0696] Server: Based on the received desired conditions, AI is used to select the most suitable restaurant. The AI ​​refers to a list of nearby restaurants and real-time seat availability information to extract restaurants that meet the user's conditions.

[0697] Step 11:

[0698] Server: The AI ​​selection results are sent to the user's device in JSON format.

[0699] Step 12:

[0700] Terminal: The received suggestions are displayed to the user, who can then choose from the list of suggested restaurants.

[0701] Step 13:

[0702] User: Select the desired restaurant from the suggested restaurants (e.g., "Restaurant A").

[0703] Step 14:

[0704] Terminal: Send the selected store information to the server in JSON format.

[0705] Step 15:

[0706] Server: Sends a reservation request to the selected store via API. Waits for the reservation confirmation result.

[0707] Step 16:

[0708] Server: Receives the reservation confirmation result and sends it to the user's device in JSON format. For example, "Your reservation for Restaurant A has been confirmed."

[0709] Step 17:

[0710] Terminal: Notifies the user of the received reservation results.

[0711] Step 18:

[0712] Server: Receives information about upcoming closing times and generates discount information to reduce food waste.

[0713] Step 19:

[0714] Server: Sends discount information in JSON format to the user's device.

[0715] Step 20:

[0716] Device: Display discount information on the user's device and provide the option to take advantage of the discount and make an instant reservation.

[0717] Step 21:

[0718] User: Check the discount information and press the instant reservation button if desired.

[0719] Step 22:

[0720] Server: Processes discount reservation requests and sends the final results to the user terminal.

[0721] Step 23:

[0722] Server: User reservation data and usage history are stored in a database, and AI learns user preferences.

[0723] Step 24:

[0724] Server: From the next time you use the service, it will suggest more appropriate restaurants based on the learning results.

[0725] ---

[0726] In this way, we have specifically explained all the steps from obtaining the user's location information to confirming the reservation, providing discount information to reduce food waste, and learning the user's preferences.

[0727] Example 1

[0728] 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."

[0729] The problem that this invention aims to solve is to provide a system that allows users to efficiently find and make reservations at restaurants of their choice, and also allows restaurants to transmit information about available seats in real time, thereby contributing to both attracting customers and reducing food waste.

[0730] 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.

[0731] In this invention, the server includes means for acquiring location information from the user device, means for acquiring information on nearby facilities based on the acquired location information, means for collecting vacant seating information for each facility in real time, means for inputting the user's desired conditions, means for suggesting optimal facilities based on the desired conditions, means for requesting reservations at the suggested facilities, means for processing reservation requests to the facilities, means for generating discount information based on usage data and notifying the user, and means for accumulating past usage data and using a generative model to learn the user's preferences. This allows users to efficiently find and make reservations at their desired restaurants. Furthermore, restaurants can transmit vacant seating information in real time, achieving both customer attraction and food waste reduction.

[0732] A "user terminal" is a device operated by a user, and includes a smartphone, tablet, or personal computer.

[0733] "Location Information" means information indicating the current geographic location of a user terminal, expressed in the form of latitude and longitude.

[0734] A "server" refers to a computer system that receives requests from user terminals and provides the necessary information in cooperation with a database.

[0735] "Nearby facilities" refers to restaurants and other facilities within a certain range based on the user's current location.

[0736] "Vacancy information" is information showing the current seat availability at each facility, and is obtained in real time based on POS data and sensor information.

[0737] "Desired conditions" are conditions that a user specifies when choosing a restaurant or other facility, and include items such as non-smoking seats, private rooms, and budget.

[0738] "Optimal facility" refers to the ideal facility selected by AI based on the user's location information and desired conditions.

[0739] "Reservation Request" means a request by a User to communicate to a Facility selected by the User that the User wishes to make a reservation.

[0740] "Discount information" refers to information indicating discounts offered under specific conditions by the facility, and particularly includes information related to reducing food waste near closing time.

[0741] "Usage data" refers to historical information such as the facilities a user has used in the past and the conditions at that time.

[0742] A "generative model" is an artificial intelligence model that learns a user's preferences based on their past usage data and uses this information to make suggestions for future use.

[0743] The present invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is configured using user terminals, a server, and databases and real-time seat availability information provided by restaurants.

[0744] Acquiring and sending location information

[0745] Device: When a user launches the smartphone app, the device's GPS function is used to obtain the current location information. This location information is obtained in the form of latitude and longitude and sent to the server.

[0746] Example: A user starts a smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to a server.

[0747] Obtaining information on nearby facilities

[0748] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information about each restaurant, such as its name, location, and type (Japanese, Chinese, French, etc.).

[0749] Real-time collection of vacant seat information

[0750] Server: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[0751] Example: Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[0752] Setting desired conditions

[0753] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) into the app.

[0754] Terminal: The terminal organizes these desired conditions, converts them into JSON format, and sends them to the server.

[0755] Proposal of the best facility

[0756] Server: The server uses a generative AI model to select the most suitable restaurant based on the user's location and desired conditions. The generative AI model lists restaurants that have available seats and meet the desired conditions in real time.

[0757] Terminal: The recommendation results received from the server are displayed on the user's terminal. The user can then choose from the multiple restaurants suggested.

[0758] Example: If a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," the server will search for restaurants that meet the conditions and suggest "Restaurant A" and "Cafe B."

[0759] Reservation Requests and Confirmations

[0760] User: Selects the desired restaurant from the suggested options and requests a reservation.

[0761] Terminal: The terminal sends the selected store information to the server and makes a reservation request.

[0762] Server: The server sends a reservation request to the selected restaurant, receives confirmation, and notifies the user of the result.

[0763] Example: A user selects "Restaurant A" and submits a reservation request. The server sends a request to Restaurant A and notifies the user that the reservation has been confirmed.

[0764] Food waste reduction and discount information

[0765] Server: Generates discount information for restaurants that are about to close to reduce food waste and notifies users.

[0766] Device: Discount information is displayed on the user's device, and immediate reservation is possible if desired.

[0767] Example: If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[0768] Learning user preferences

[0769] Server: The server stores the user's past reservation data and usage history, and the generative AI model learns the user's preferences. Based on the learning results, the server makes more accurate suggestions for future use.

[0770] Example: If a user has frequently dined in "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[0771] Prompt Sentence Examples

[0772] Send the location information of users who have agreed to "Use current location." Send it to the server as latitude: 35.6585, longitude: 139.7454.

[0773] In this way, the present invention allows users to efficiently find and reserve restaurants of their choice. It also enables restaurants to provide real-time information about available seats, providing a system that contributes to both attracting customers and reducing food waste.

[0774] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0775] Step 1:

[0776] Obtaining location information

[0777] Input: The user launches the smartphone app and agrees to "Use my location."

[0778] What it does: Uses the device's GPS to obtain the current location.

[0779] Output: Location information in latitude and longitude format (e.g., latitude 35.6585, longitude 139.7454).

[0780] Step 2:

[0781] Sending location information

[0782] Input: The location information obtained in step 1.

[0783] Operation: The device sends the location information it has acquired to the server.

[0784] Output: The location information is sent to the server.

[0785] Step 3:

[0786] Obtaining information on nearby facilities

[0787] Input: Location sent to the server (latitude 35.6585, longitude 139.7454).

[0788] How it works: Based on your location, the server retrieves a list of nearby restaurants from a database, including the name, location, and type of each restaurant.

[0789] Output: A list of nearby restaurants (e.g. Restaurant A, Cafe B, etc.).

[0790] Step 4:

[0791] Gathering vacancy information

[0792] Input: List of nearby restaurants obtained in step 3.

[0793] Operation: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. The server obtains seat availability information via API.

[0794] Output: Real-time seat availability information (e.g. Restaurant A has 5 available seats).

[0795] Step 5:

[0796] Input of user's desired conditions

[0797] Input: The user enters their desired conditions (e.g., non-smoking seat, private room, budget under 5,000 yen) into the app.

[0798] Operation: The device converts the entered desired conditions into JSON format and sends it to the server.

[0799] Output: The preference data sent to the server.

[0800] Step 6:

[0801] Proposal of the best facility

[0802] Input: Your preferences submitted in step 5 and availability information collected in step 4.

[0803] How it works: The server uses the generative AI model to select the restaurant that best meets the desired criteria. The generative AI model then lists restaurants that have available seats and meet the desired criteria in real time.

[0804] Output: A list of the best restaurants (e.g. "Restaurant A", "Cafe B").

[0805] Step 7:

[0806] Displaying the proposed results

[0807] Input: The list of best restaurants selected in step 6.

[0808] Operation: The device displays the suggestions received from the server to the user in a list format.

[0809] Output: The user can view a list of suggested restaurants.

[0810] Step 8:

[0811] Submit a booking request

[0812] Input: The user selects the desired restaurant from the suggested restaurants.

[0813] Operation: The device sends the selected store information to the server and makes a reservation request.

[0814] Output: The booking request sent to the server.

[0815] Step 9:

[0816] Reservation processing and confirmation

[0817] Input: The booking request submitted in step 8.

[0818] Operation: The server sends a reservation request to the selected restaurant, receives confirmation, and notifies the user terminal of the confirmation result.

[0819] Output: Booking confirmation notification (e.g. "Your booking is confirmed").

[0820] Step 10:

[0821] Food waste reduction and discount information generation

[0822] Input: Closing time and restaurant availability.

[0823] How it works: The server generates discount information to reduce food waste and notifies the user.

[0824] Output: Discount information notification (e.g. "20% off food").

[0825] Step 11:

[0826] Learning user preferences

[0827] Input: User's past booking data and usage history.

[0828] How it works: A server stores this data and a generative AI model learns user preferences.

[0829] Output: Improved accuracy of suggestions from next time onwards (e.g., a user who has previously preferred Japanese food will be given priority in suggestions of Japanese restaurants).

[0830] In this way, each step specifically constitutes the operation of the entire system.

[0831] (Application example 1)

[0832] 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."

[0833] In today's busy lifestyles, users face challenges in efficiently finding nearby restaurants, selecting a menu that meets their desired criteria, and ordering delivery. Existing delivery services are unable to provide real-time information on available menu items and seating availability based on the user's current location, and there are limited means for users to track the progress of their delivery in real time. This results in reduced convenience for users, and restaurants also face challenges in efficiently attracting customers and reducing food waste.

[0834] 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.

[0835] In this invention, the server includes a means for displaying delivery options on the user terminal, a means for the server to acquire delivery progress information and notify the user terminal, and a means for collecting seat availability information of nearby facilities in real time, thereby enabling users to efficiently browse delivery menus of nearby restaurants and keep track of delivery progress in real time.

[0836] A "user terminal" is a portable electronic device for use by a user, such as a smartphone or tablet terminal.

[0837] "Location information" is data indicating the current location of a user terminal, and is geographical information expressed in the form of latitude and longitude.

[0838] A "server" is a computer system that processes and provides data over a network.

[0839] "Nearby facilities" are restaurants and other related facilities located near the current location of the user terminal.

[0840] "Vacant seat information" is data indicating the current availability of seats at surrounding facilities.

[0841] "Real-time" means that information is processed and updated almost instantaneously.

[0842] "Desired conditions" are conditions based on specific requests or preferences entered by the user, such as non-smoking seats or budget.

[0843] A "delivery menu" is a list of dishes and drinks that nearby facilities can provide to users.

[0844] "Delivery progress information" is status information that indicates the stage of delivery ordered by the user.

[0845] A "reservation request" is a request to make a reservation at a facility selected by the user.

[0846] "Food waste reduction" refers to efforts to reduce the waste of food and drink.

[0847] "Discount information" is data regarding discounts offered by establishments that are about to close.

[0848] "Past usage data" refers to historical information about reservations and orders previously made by a user.

[0849] "AI" stands for artificial intelligence, a system that uses techniques such as machine learning to learn user preferences.

[0850] This invention is a system that allows users to efficiently find their desired restaurant and place delivery orders and reservations. This system is configured using user terminals, a server, and real-time information on available seats and menu items available for delivery at restaurants.

[0851] Acquiring and sending location information

[0852] When a user launches a smartphone app, the device uses its GPS to obtain its current location information, which is then sent to a server in the form of latitude and longitude.

[0853] Obtaining information on nearby facilities

[0854] The server retrieves a list of restaurants in the vicinity from a database based on the received location information. This list includes basic information such as the restaurant name, location, and type.

[0855] Real-time collection of vacant seat information

[0856] The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[0857] Display of menu items available for delivery

[0858] The server collects information on delivery options from nearby restaurants and provides it to the user's device. Users can then browse the available menu items and place their order on the app.

[0859] Setting desired conditions

[0860] Users input their desired conditions (e.g., vegetarian options, budget, etc.) into the app. The device organizes these conditions, converts them into JSON format, and sends it to the server.

[0861] Proposal of the best facility

[0862] The server uses AI (artificial intelligence) to select the most suitable restaurant based on the user's location information and desired conditions. The AI ​​lists restaurants and delivery menus that have available seats and meet the desired conditions in real time. The recommendation results received from the server are displayed on the user's device, and the user can choose from multiple suggested restaurants and menus.

[0863] Reservation Requests and Confirmations

[0864] The user selects a desired restaurant from the suggested restaurants and requests a reservation. The terminal sends the selected restaurant information to the server and makes a reservation request. The server sends the reservation request to the selected restaurant and receives confirmation. The result is notified to the user terminal.

[0865] Delivery progress notifications

[0866] Once a delivery order is placed, the server obtains delivery progress information in real time and notifies the user's device, allowing the user to keep track of the progress of their order.

[0867] Food waste reduction and discount information

[0868] The server generates discount information for restaurants that are about to close and notifies the user of the discount information. The discount information is displayed on the user's device, and the user can make an immediate reservation if desired.

[0869] Learning user preferences

[0870] The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Based on the learning results, more accurate suggestions will be made the next time the user uses the restaurant. For example, if a user has frequently eaten at restaurants serving "Japanese cuisine" in the past, restaurants serving "Japanese cuisine" will be given priority in suggestions from the next time onwards.

[0871] As a specific example, when a user launches a smartphone app and agrees to "use current location," the app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to the server. The server then collects information about available seats and delivery options from nearby restaurants and provides it to the user. The user inputs desired conditions such as non-smoking seats and budget, and the most suitable restaurant is suggested. When a reservation request is sent, the server processes the request and notifies the user of the confirmation result. The app also has a function that notifies the user of the delivery progress in real time.

[0872] An example of a prompt sentence that can be used is, "Please tell me the detailed steps of an app that shows the process for ordering pasta and the delivery progress in real time when a FoodNavi user orders pasta."

[0873] This invention allows users to efficiently search restaurant delivery menus and enjoy delivery while checking the order status in real time. It also enables restaurants to provide real-time information and promote efforts to reduce food waste.

[0874] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0875] Step 1:

[0876] The user launches the smartphone app and agrees to the use of location information. The device uses its GPS function to obtain the user's current location information (latitude and longitude). Specifically, the app reads location coordinates from the smartphone's GPS sensor and stores that information in the device's memory. The input is the location information obtained from the GPS sensor, and the output is location information data to be sent to the server.

[0877] Step 2:

[0878] The user device sends the acquired location information (latitude and longitude) to the server. Specifically, it sends a request including the location information to the server using the HTTP POST method. The input is the location information stored in the device's memory, and the output is the HTTP request sent to the server.

[0879] Step 3:

[0880] The server retrieves information about nearby facilities from a database based on the received location information. This involves generating a search query based on the location information and querying the database. The input is the location information received by the server, and the output is a list of nearby facilities retrieved from the database.

[0881] Step 4:

[0882] The server collects vacant seat information in real time based on POS data and motion sensor information provided by each facility. Specifically, it obtains data from each facility's system via API, analyzes it, and checks whether there are any vacant seats. The input is POS data and motion sensor information, and the output is real-time vacant seat information.

[0883] Step 5:

[0884] The server collects information about menu items available for delivery from each nearby facility and provides it to the user's device. Specifically, it uses an API to obtain menu information, formats the data, and sends it to the user's device. The input is delivery menu information provided by each facility, and the output is the menu information displayed on the user's device.

[0885] Step 6:

[0886] The user enters their desired conditions (e.g., vegetarian options, budget, etc.) on the app. The device organizes these conditions, converts them into JSON format, and sends them to the server. Specifically, it takes the data entered from the user interface, converts it into a specific format, and sends it to the server. The input is the desired conditions entered by the user, and the output is the JSON data sent to the server.

[0887] Step 7:

[0888] The server uses AI to select the most suitable restaurant based on the user's location information and desired conditions. Specifically, the received location information and desired conditions are input into an AI model, which then generates a list of the most suitable restaurants. The input is the location information and desired conditions received by the server, and the output is a list of the most suitable restaurants.

[0889] Step 8:

[0890] The recommendation results received from the server are displayed on the user terminal. Specifically, the user terminal analyzes the information sent from the server and displays it on the user interface. The input is the recommendation results sent by the server, and the output is a list of facilities and menus displayed on the user terminal.

[0891] Step 9:

[0892] The user selects a desired restaurant from the suggested restaurants and requests a reservation. The user terminal sends the selected restaurant information to the server and requests a reservation. Specifically, the system obtains the user's selection and sends a request to the server using the HTTP POST method. The input is the restaurant information selected by the user, and the output is a reservation request sent to the server.

[0893] Step 10:

[0894] The server sends a reservation request to the selected restaurant and receives confirmation. The result is then notified to the user's terminal. Specifically, the server sends a request to the restaurant's system, and once confirmation is received, it sends the information to the user's terminal. The input is the reservation request from the user, and the output is a notification of reservation confirmation.

[0895] Step 11:

[0896] Once a delivery order is confirmed, the server obtains delivery progress information in real time and notifies the user terminal. Specifically, it receives progress information from the delivery system, formats it, and sends it to the user. The input is progress information from the delivery system, and the output is a notification message to the user terminal.

[0897] Step 12:

[0898] The server generates discount information for restaurants that are about to close to reduce food waste and notifies the user. Specifically, the server generates food waste reduction information for specific time periods and notifies the user of it. The input is the store's business information and food waste reduction conditions, and the output is a discount information notification sent to the user's terminal.

[0899] Step 13:

[0900] The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Specifically, past usage data is input into the AI ​​model, which analyzes the user's preferences and trends. The input is the user's past usage data, and the output is future recommendations based on the user's preferences.

[0901] 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.

[0902] ---

[0903] This invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is composed of a user terminal, a server, databases and real-time seat availability information provided by restaurants, and an emotion engine that recognizes the user's emotions.

[0904] Acquiring and sending location information

[0905] Device: When a user launches the app, the device uses its GPS to obtain its current location, which is then sent to the server in the form of latitude and longitude.

[0906] Example: A user starts a smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to a server.

[0907] Obtaining information on nearby facilities

[0908] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information such as the restaurant name, location, and type.

[0909] Real-time collection of vacant seat information

[0910] Server: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[0911] Example: Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[0912] Setting desired conditions

[0913] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) on the app.

[0914] Terminal: Organize the entered desired conditions, convert them into JSON format, and send them to the server.

[0915] Emotion recognition by emotion engine

[0916] On the device: The emotion engine analyzes the user's facial expressions and voice to determine their current emotional state, which is classified into categories such as "happiness," "sadness," and "anger."

[0917] Example: A user accesses the emotion engine through a camera or microphone. The emotion engine identifies "happiness" from the user's facial expressions and voice, and sends this as an analysis result to the server.

[0918] Proposal of the best facility

[0919] Server: The server uses AI to select the most suitable restaurant based on the user's location, desired conditions, and emotional state. The AI ​​refers to this data and creates a list of restaurants that match the user's conditions and emotions.

[0920] Terminal: The terminal displays the restaurant recommendations received from the server to the user, who can then choose from the multiple restaurants suggested.

[0921] Example: If a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," and the emotion engine recognizes "joy," the server will suggest "Restaurant A" and "Cafe B" that match the conditions and emotion.

[0922] Reservation Requests and Confirmations

[0923] User: Selects the desired restaurant from the suggested options and requests a reservation.

[0924] Terminal: Send the selected store information to the server in JSON format.

[0925] Server: Sends a reservation request to the selected store via API, receives confirmation, and notifies the user of the result.

[0926] Example: A user selects "Restaurant A" and submits a reservation request. The server sends a request to Restaurant A and notifies the user that the reservation has been confirmed.

[0927] Food waste reduction and discount information

[0928] Server: Generates discount information for restaurants that are about to close to reduce food waste and notifies users.

[0929] Device: Discount information is displayed on the user's device, and immediate reservation is possible if desired.

[0930] Example: If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[0931] Learning user preferences

[0932] Server: The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Based on the learning results, the server makes more accurate suggestions for the next time the user uses the service.

[0933] Example: If a user has frequently dined in "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[0934] ---

[0935] In this way, the present invention allows users to efficiently find and make reservations at restaurants of their choice. Furthermore, by taking into account the user's emotional state, it is possible to suggest restaurants that will provide a higher level of satisfaction. It also enables restaurants to provide information on available seats in real time, providing a system that contributes to both attracting customers and reducing food waste.

[0936] The processing flow will be explained below.

[0937] ---

[0938] Step 1:

[0939] User: Launches the app and agrees to location data collection.

[0940] Step 2:

[0941] Device: If location access is allowed, the device's GPS function will be used to obtain the current location, which will be in the form of latitude and longitude.

[0942] Step 3:

[0943] Device: Sends the acquired location information to the server. Specifically, sends the acquired latitude and longitude data in JSON format.

[0944] Step 4:

[0945] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information such as the restaurant's name, address, and type.

[0946] Step 5:

[0947] Server: Real-time seat availability information is collected via API based on POS systems and motion sensor information provided by each restaurant. The collected seat availability information is then organized.

[0948] Step 6:

[0949] Server: Convert the acquired vacancy information into JSON format and send it to the user's device.

[0950] Step 7:

[0951] Terminal: The received seat availability information is displayed to the user. A list of restaurants with available seats is displayed on the screen.

[0952] Step 8:

[0953] User: Enter desired conditions (e.g. non-smoking seat, private room, budget, etc.) on the app screen.

[0954] Step 9:

[0955] Terminal: Convert the entered desired conditions into JSON format and send it to the server.

[0956] Step 10:

[0957] On the device: The emotion engine analyzes the user's facial expressions and voice to determine their current emotional state. This emotion data is classified into categories such as "happiness," "sadness," and "anger."

[0958] Step 11:

[0959] Terminal: Converts the emotion data identified by the emotion engine into JSON format and sends it to the server.

[0960] Step 12:

[0961] Server: The AI ​​selects the most suitable restaurant based on the received desired conditions and emotional data. The AI ​​refers to this data and creates a list of restaurants that match the user's conditions and emotions.

[0962] Step 13:

[0963] Server: The AI ​​selection results are sent to the user's device in JSON format.

[0964] Step 14:

[0965] Terminal: The received recommendation results are displayed to the user, who can then choose from multiple suggested restaurants.

[0966] Step 15:

[0967] User: Select the desired restaurant (e.g., "Restaurant A") from the list of suggested restaurants.

[0968] Step 16:

[0969] Terminal: Send the selected store information to the server in JSON format.

[0970] Step 17:

[0971] Server: Send a reservation request to the selected store via API and wait for the reservation confirmation result.

[0972] Step 18:

[0973] Server: Receives the reservation confirmation result and sends it to the user's device in JSON format. Example: "Your reservation for Restaurant A has been confirmed."

[0974] Step 19:

[0975] Terminal: Notifies the user of the received reservation results.

[0976] Step 20:

[0977] Server: Receives information about upcoming closing times and generates discount information to reduce food waste.

[0978] Step 21:

[0979] Server: Sends discount information in JSON format to the user's device.

[0980] Step 22:

[0981] Terminal: Discount information is displayed to the user, and immediate booking is possible if desired.

[0982] Step 23:

[0983] User: Check the discount information and press the instant reservation button if desired.

[0984] Step 24:

[0985] Server: Processes discount reservation requests and sends the final results to the user terminal.

[0986] Step 25:

[0987] Server: User reservation data and usage history are stored in a database, and AI learns user preferences.

[0988] Step 26:

[0989] Server: From the next time you use the service, it will suggest more appropriate restaurants based on the learning results.

[0990] ---

[0991] In this way, we have explained in detail all the steps from obtaining the user's location information, recognizing emotions, suggesting the best restaurant, confirming the reservation, providing discount information to reduce food waste, and learning the user's preferences.

[0992] Example 2

[0993] 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."

[0994] In today's busy lifestyles, it is difficult for users to efficiently find and make reservations at restaurants. Furthermore, suggestions that do not take into account the user's current emotional state may result in low satisfaction. Furthermore, it is difficult for restaurants to provide real-time information on available tables, which leads to the problem of food waste.

[0995] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring location information of the user terminal, means for transmitting the acquired location information to the server, means for the server to acquire information on surrounding facilities based on the location information, means for collecting vacant seat information for each facility in real time, means for allowing the user to input desired conditions, means for suggesting optimal facilities based on the desired conditions, means including an emotion recognition engine for analyzing the user's emotional state, means for requesting reservations at the suggested facilities, and means for the server to process reservation requests for the facilities. This allows users to efficiently find their desired restaurant and make reservations that take their emotional state into consideration, resulting in higher satisfaction. It also enables restaurants to transmit vacant seat information in real time, contributing to reducing food waste.

[0996] "User terminal" refers to a device operated by a user, including smartphones, tablets, and personal computers.

[0997] "Location information" refers to coordinate information of a specific location, expressed in the form of latitude and longitude.

[0998] "Server" refers to a computer system that receives, processes, and manages data sent from multiple user terminals.

[0999] "Facilities" are places that users can visit, including eateries, cafes, restaurants, etc.

[1000] "Vacancy information" refers to data that shows the availability of seats within a facility in real time.

[1001] "Desired conditions" refer to the requirements and wishes that users have for the facility, and include elements such as non-smoking seats, private rooms, and budget.

[1002] An "emotion recognition engine" is software or hardware that analyzes a user's facial expressions and tone of voice to identify their emotional state.

[1003] "Reservation Request" means a request by a User to communicate to a Facility selected by the User that the User wishes to make a reservation.

[1004] "Food waste" refers to ingredients and cooked food that may be discarded without being consumed.

[1005] "Discount Information" means information about price discounts offered under certain conditions specified by the facility.

[1006] "AI" stands for artificial intelligence, a technology that gives computer systems the ability to analyze data and learn.

[1007] "Preference learning" is the process of analyzing a user's preferences and trends based on their past usage data and reflecting them in future suggestions.

[1008] MODE FOR CARRYING OUT THE INVENTION

[1009] This invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is composed of a user terminal, a server, databases and real-time seat availability information provided by restaurants, and an emotion engine that recognizes the user's emotions.

[1010] Acquiring and sending location information

[1011] When a user launches the app and agrees to "Use current location," the device will use the built-in GPS to obtain the current location information. This location information is obtained in the form of latitude and longitude, converted into JSON format, and then sent to the server using a secure communication protocol (HTTPS).

[1012] Examples:

[1013] The user starts the smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to the server.

[1014] Obtaining information on nearby facilities

[1015] The server retrieves a list of nearby restaurants from a database based on the received location information. This list includes basic information such as the restaurant name, address, category, and opening hours. The retrieved data is formatted in JSON and sent to the user's device.

[1016] Real-time collection of vacant seat information

[1017] The server collects POS system data and motion sensor information provided by each restaurant via API, obtains real-time seat availability information, converts the integrated data into JSON format, and prepares it for transmission to the user's device.

[1018] Examples:

[1019] Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[1020] Setting desired conditions

[1021] Users use the app's interface to input their preferences, such as non-smoking, private rooms, budget, etc. These preferences are organized, converted into JSON format, and sent to the server.

[1022] Examples:

[1023] When a user enters conditions such as "non-smoking seats," "private rooms," and "budget under 5,000 yen," this information is organized in JSON format and sent to the server.

[1024] Emotion recognition by emotion engine

[1025] The emotion engine analyzes the user's facial expressions and tone of voice through the user's camera and microphone. The emotion recognition algorithm identifies the user's current emotional state and converts the results into JSON format and sends it to the server.

[1026] Examples:

[1027] When a user accesses the emotion engine through a camera or microphone, the emotion engine recognizes "happiness" from the user's facial expressions and voice and sends the analysis results to the server.

[1028] Proposal of the best facility

[1029] The server uses AI to select the most suitable restaurant based on the user's location, desired conditions, and emotional state. The AI ​​model takes into account past data and user trends, creates a list of restaurants that match the conditions and emotions, and sends it in JSON format to the user's device.

[1030] Examples:

[1031] When a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," and the emotion engine recognizes "joy," the server will suggest "Restaurant A" and "Cafe B" that match the conditions and emotion.

[1032] Reservation Requests and Confirmations

[1033] The user selects the restaurant of their choice from the suggested options and requests a reservation. The selected restaurant information is converted to JSON format and sent to the server. The server then sends a reservation request to the selected restaurant via API, and sends the reservation confirmation in JSON format to the user's device.

[1034] Examples:

[1035] The user selects "Restaurant A" and submits a reservation request. The server makes a request to Restaurant A and notifies the user that the reservation has been confirmed.

[1036] Food waste reduction and discount information

[1037] The server generates discount information for restaurants that are about to close, in order to reduce food waste, and notifies the user. The discount information is converted into JSON format and displayed on the user's device.

[1038] Examples:

[1039] If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[1040] Learning user preferences

[1041] The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences, which are then used to make more accurate suggestions the next time the user uses the service.

[1042] Examples:

[1043] If a user has frequently visited "Japanese cuisine" restaurants in the past, "Japanese cuisine" restaurants will be prioritized in the list the next time suggestions are made.

[1044] Prompt Sentence Examples

[1045] I agree to "Use my current location" and suggest the best restaurant using a list of restaurants, seat availability information, and an emotion engine. My desired conditions are "non-smoking seat," "private room," "budget under 5,000 yen," and my emotional state is "delighted." I want to be able to make a reservation at the suggested restaurant.

[1046] This invention allows users to efficiently find the restaurant they want, and by taking their emotional state into consideration, it is possible to suggest restaurants that will increase their satisfaction. It also enables restaurants to send out information about available seats in real time, which will help reduce food waste.

[1047] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1048] Step 1: Obtaining and sending location information

[1049] Device:

[1050] When the app is launched, the device uses its built-in GPS to obtain its current location. This location information is obtained in the form of latitude and longitude and converted into JSON format. The converted location information is then sent to the server using a secure communication protocol (HTTPS).

[1051] Specific behavior:

[1052] Input: The user launches the app on their smartphone and agrees to "Use my location."

[1053] Data processing: Latitude and longitude data is obtained using the smartphone's GPS function and converted into JSON format.

[1054] Output: The converted location information is sent to the server.

[1055] Step 2: Obtain information about nearby facilities

[1056] server:

[1057] Based on the received location information, the server queries the database to obtain a list of nearby restaurants. This list includes basic information such as the restaurant name, address, category, and opening hours. The obtained data is formatted in JSON format and sent to the user's device.

[1058] Specific behavior:

[1059] Input: Location information in JSON format.

[1060] Data processing: Based on the received location information, an SQL query is executed on the database to obtain information on nearby facilities. The obtained information is then formatted into JSON format.

[1061] Output: Facility information in JSON format is sent to the user's device.

[1062] Step 3: Real-time collection of seat availability information

[1063] server:

[1064] The server collects POS system data and motion sensor information provided by each restaurant via API, obtains real-time seat availability information, converts the integrated data into JSON format, and prepares it for transmission to the user's device.

[1065] Specific behavior:

[1066] Input: POS system data and motion sensor information from each restaurant.

[1067] Data processing: Calls APIs to collect data from each store, centralizes it in the integration engine, and converts the data into JSON format.

[1068] Output: The vacancy information is converted to JSON format and sent to the user's device.

[1069] Step 4: Set your preferences

[1070] User:

[1071] Users use the app's interface to input their preferences, such as non-smoking, private rooms, and budget.

[1072] Device:

[1073] The entered desired conditions are organized, converted into JSON format, and sent to the server.

[1074] Specific behavior:

[1075] Input: The user enters their desired criteria into the app's interface.

[1076] Data processing: Convert the entered desired conditions into JSON format.

[1077] Output: The desired conditions are sent to the server.

[1078] Step 5: Emotion Recognition with the Emotion Engine

[1079] Device:

[1080] The emotion engine analyzes the user's facial expressions and tone of voice through the user's camera and microphone. The emotion recognition algorithm identifies the user's current emotional state and converts the results into JSON format and sends it to the server.

[1081] Specific behavior:

[1082] Input: The user accesses the emotion engine through a camera or microphone.

[1083] Data processing: The emotion recognition algorithm analyzes the acquired data to identify the emotional state, and converts the results into JSON format.

[1084] Output: The emotion recognition results are sent to the server.

[1085] Step 6: Propose the best facility

[1086] server:

[1087] The server uses AI to select the most suitable restaurant based on the user's location, desired conditions, and emotional state. The AI ​​model takes into account past data and user trends, creates a list of restaurants that match the conditions and emotions, and sends it in JSON format to the user's device.

[1088] Specific behavior:

[1089] Input: location, desired conditions, emotional data.

[1090] Data processing: The AI ​​model uses this data to select and list the best restaurants. The data is formatted into JSON format.

[1091] Output: The proposed results are sent to the user's device in JSON format.

[1092] Step 7: Reservation Request and Confirmation

[1093] User:

[1094] The user selects the desired restaurant from the suggested restaurants and requests a reservation.

[1095] Device:

[1096] Convert the selected store information into JSON format and send it to the server.

[1097] server:

[1098] A reservation request is sent to the selected store via API, and the reservation confirmation result is sent to the user's terminal in JSON format.

[1099] Specific behavior:

[1100] Input: The user selects the desired store.

[1101] Data processing: Convert the selected store information into JSON format.

[1102] Output: A reservation request is sent to the server, and the reservation confirmation result is sent to the user terminal.

[1103] Step 8: Reduce food waste and provide discount information

[1104] server:

[1105] To generate discount information for reducing food waste for restaurants that are about to close and notify the user of the information.

[1106] Device:

[1107] The discount information is converted to JSON format and displayed on the user's device. Based on this information, the user can make an immediate reservation if desired.

[1108] Specific behavior:

[1109] Input: Discount information from restaurants.

[1110] Data processing: Convert discount information into JSON format.

[1111] Output: The discount information is sent to the user's terminal and displayed.

[1112] Step 9: Learning User Preferences

[1113] server:

[1114] By accumulating the user's past reservation data and usage history, the AI ​​learns the user's preferences and uses the results to make more accurate suggestions the next time the user uses the service.

[1115] Specific behavior:

[1116] Input: Past reservation data and usage history.

[1117] Data processing: AI learns from this data and analyzes user preferences. The learning results are used to improve future recommendations.

[1118] Output: Suggestions based on the user's preferences will be reflected in future visits.

[1119] (Application example 2)

[1120] 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."

[1121] Conventional restaurant reservation systems easily provide information based on the user's current location and obtain real-time seat availability information, but they lack a mechanism for suggesting optimal restaurants that take the user's emotional state into account. Furthermore, they have not adequately implemented measures to reduce food waste through discount information for restaurants close to closing time, or to improve the accuracy of personalized recommendations based on the user's past usage data. To address these issues, the present invention aims to provide a restaurant recommendation system that takes the user's emotions into account, thereby enabling a more accurate reservation experience.

[1122] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1123] In this invention, the server includes means for acquiring location information of the user terminal, means for acquiring information on surrounding facilities based on the acquired location information, means for collecting information on available seats at each facility in real time, means for recognizing the emotional state of the user and suggesting facilities taking the emotional state into consideration, means for allowing the user to input desired conditions, means for suggesting optimal facilities based on the desired conditions, means for requesting a reservation at the suggested facility, and means for the server to process reservation requests for the facility. This makes it possible to suggest and reserve optimal restaurants taking the emotional state of the user into consideration.

[1124] A "user terminal" is a portable electronic device used to obtain location information and communicate with a server.

[1125] "Location Information" refers to the geographic coordinate information of a user's current location.

[1126] A "server" is a central processing unit that receives and processes data sent from a user terminal.

[1127] "Nearby facilities" refers to restaurants and other commercial facilities that are searched for based on the user's location information.

[1128] "Available seat information" is information that indicates the current number of available seats at a particular facility.

[1129] "Real-time" refers to information that is updated almost immediately.

[1130] "Desired conditions" refer to the requests and restrictions that users have when selecting a facility.

[1131] "Emotional state" refers to the user's current emotional state and is classified into categories such as "joy," "sadness," and "anger."

[1132] "Suggestion" refers to recommending the most suitable facility based on the user's desired conditions and emotional state.

[1133] "Reservation Request" means making a reservation for a proposed facility.

[1134] "Food waste reduction" refers to reducing the waste of surplus food ingredients in restaurants.

[1135] "Discount information" is information indicating the conditions under which the offered product will be cheaper than its regular price.

[1136] "Usage Data" refers to historical information about reservations and facility usage made by a user.

[1137] "AI" refers to artificial intelligence, a technology that analyzes and learns from user preferences and behavioral patterns based on data.

[1138] This invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is composed of a user terminal, a server, databases and real-time seat availability information provided by restaurants, and an emotion engine that recognizes the user's emotions.

[1139] Acquiring and sending location information

[1140] Device: When a user launches the app, the device uses its GPS function to obtain its current location. This location information is obtained in the form of latitude and longitude and sent to the server. Specifically, when a user launches the smartphone app and agrees to "Use current location," the location information is obtained as "Latitude: 35.6585, Longitude: 139.7454" and sent to the server.

[1141] Obtaining information on nearby facilities

[1142] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information such as the restaurant name, location, and type.

[1143] Real-time collection of vacant seat information

[1144] Server: The server collects seat availability information in real time based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is known. For example, if a restaurant uses a POS system and the data on the number of available seats reports that "there are currently five seats available," the server obtains this information and prepares to provide it to the user.

[1145] Setting desired conditions

[1146] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) on the app.

[1147] Terminal: Organize the entered desired conditions, convert them into JSON format, and send them to the server.

[1148] Emotion recognition by emotion engine

[1149] Device: The emotion engine analyzes the user's facial expressions and voice to identify their current emotional state. This emotional state is classified into categories such as "happiness," "sadness," and "anger." The user accesses the emotion engine via the camera or microphone, and the emotion engine identifies "happiness" from the user's facial expressions and voice and sends this as the analysis result to the server.

[1150] Proposal of the best facility

[1151] Server: The server uses AI to select the best restaurant based on the user's location, desired conditions, and emotional state. The AI ​​refers to this data and creates a list of restaurants that match the user's conditions and emotions.

[1152] Terminal: Displays the recommendation results received from the server to the user. The user can choose from multiple suggested restaurants. For example, if the user sets their desired conditions as "non-smoking seats," "private rooms," and "budget under 5,000 yen," and the emotion engine recognizes "joy," the server will suggest "Restaurant A" and "Cafe B" that match the conditions and emotion.

[1153] Reservation Requests and Confirmations

[1154] User: Selects the restaurant they want from the suggested options and requests a reservation.

[1155] Terminal: Send the selected store information to the server in JSON format.

[1156] Server: Sends a reservation request to the selected restaurant via API and receives confirmation. Notifies the user of the result. For example, if a user selects "Restaurant A" and sends a reservation request, the server makes a request to Restaurant A and notifies the user that the reservation has been confirmed.

[1157] Food waste reduction and discount information

[1158] Server: Generates discount information to reduce food waste for restaurants that are about to close and notifies users.

[1159] Device: Discount information will be displayed on the user's device, and they can make an instant reservation if they wish.

[1160] For example, if a restaurant offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an instant reservation.

[1161] Learning user preferences

[1162] Server: The AI ​​accumulates the user's past reservation data and usage history, and learns the user's preferences. Based on the learning results, it makes more accurate suggestions the next time the user uses the service. For example, if the user has often selected "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[1163] Example prompt sentence:

[1164] "The user wants to have a fun, delicious dinner. The current location is Tokyo Tower. Suggest a nearby restaurant with a private, non-smoking room, and a budget of under 5,000 yen."

[1165] In this way, this invention allows users to efficiently find and make reservations at restaurants of their choice. Furthermore, restaurant suggestions are made taking into account the user's emotional state, enabling a more satisfying reservation experience. It also enables restaurants to provide information on available seats in real time, providing a system that contributes to both attracting customers and reducing food waste.

[1166] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1167] Step 1:

[1168] Launch the app on the user's device and obtain the current location information.

[1169] Input: App launch, location information from GPS sensor

[1170] Output: The latitude and longitude data obtained (e.g., "Latitude: 35.6585, Longitude: 139.7454")

[1171] Specific operation: When a user launches the smartphone app and agrees to "Use current location," the device will use the GPS function to obtain the current location information, which will then be stored in the device's internal memory.

[1172] Step 2:

[1173] The acquired location information is sent to the server.

[1174] Input: Latitude and longitude data stored on the device

[1175] Output: Log of location information sent to the server

[1176] Specific operation: The device sends location information to the server using the server communication protocol. After sending, a log indicating the success is generated.

[1177] Step 3:

[1178] The server obtains information about nearby facilities based on location information.

[1179] Input: Location information received by the server

[1180] Output: List of nearby facilities (name, address, category, etc.)

[1181] Specific operation: Based on the location information received by the server, it sends a query to the database to obtain information about nearby facilities, and returns query results including facility name, address, type, etc.

[1182] Step 4:

[1183] The server collects vacant seat information for each facility in real time.

[1184] Input: List of nearby facilities

[1185] Output: Availability information for each assigned facility

[1186] Specific operation: The server sends a request to each restaurant's system (POS data, motion sensors, etc.) via API to obtain current seat availability information. The results are added to a list of nearby facilities.

[1187] Step 5:

[1188] The user enters the desired conditions.

[1189] Input: User's desired conditions (e.g., non-smoking seat, private room, budget, etc.)

[1190] Output: JSON format data of desired conditions

[1191] Specific operation: The user enters desired conditions on the app screen, and the information is converted to JSON format within the device.

[1192] Step 6:

[1193] The terminal transmits the desired conditions to the server.

[1194] Input: JSON format data of desired conditions

[1195] Output: Log of desired condition data sent to the server

[1196] Specific operation: The device sends the desired condition data in JSON format to the server and generates a log indicating that the transmission was successful.

[1197] Step 7:

[1198] The device recognizes the user's emotional state.

[1199] Input: User facial and voice data collected through the camera and microphone

[1200] Output: Emotional state category (e.g., "joy," "sadness," "anger," etc.)

[1201] Specific operation: The device's emotion recognition engine analyzes facial expressions and voice data, categorizes the user's emotional state, and sends the results to the server.

[1202] Step 8:

[1203] The server suggests the most suitable facility based on location information, desired conditions, and emotional state.

[1204] Input: User's location, desired conditions, emotional state

[1205] Output: List of optimal facilities

[1206] How it works: The server's AI uses the input data to select the most suitable facilities and generate a recommendation list, which includes each facility's rating and the degree of matching of the conditions.

[1207] Step 9:

[1208] Proposals from the server are displayed on the user's device.

[1209] Input: List of optimal facilities

[1210] Output: A list of suggested facilities displayed to the user

[1211] Specific operation: The server sends the generated list of optimal facilities to the terminal, which then visually displays it to the user, allowing the user to select a store from this list.

[1212] Step 10:

[1213] The user selects the desired facility and requests a reservation.

[1214] Input: Facility information selected by the user

[1215] Output: JSON format data of the reservation request

[1216] Specific operation: The user selects the desired facility from the list, and the facility information is converted into JSON format and sent to the server.

[1217] Step 11:

[1218] The server processes reservation requests to facilities.

[1219] Input: Reservation request data for the selected facility

[1220] Output: Confirmed reservation information

[1221] Specific operation: The server sends a reservation request to the facility via API, receives the processing result (reservation success or failure), and notifies the user's device.

[1222] Step 12:

[1223] The server generates discount information to reduce food waste and notifies the user.

[1224] Input: Information from the facility about closing time

[1225] Output: Discount information notification

[1226] Specific operation: Based on discount information provided by establishments that are about to close, the server generates information for reducing food waste and notifies the user. The user receives this information and can make an instant reservation.

[1227] Step 13:

[1228] The server stores users' past usage data and learns their preferences.

[1229] Input: User's past usage history data

[1230] Output: Learned user preference data

[1231] How it works: The server stores the user's past reservation data and usage history, and uses AI to analyze and learn the user's preferences. The results are reflected in the next proposal.

[1232] In this way, a system is constructed that allows users to efficiently find and make reservations at restaurants of their choice through each step.

[1233] 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.

[1234] 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.

[1235] 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.

[1236] [Third embodiment]

[1237] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1238] 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.

[1239] 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).

[1240] 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.

[1241] 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.

[1242] 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).

[1243] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1244] 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.

[1245] 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.

[1246] 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.

[1247] 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.

[1248] 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."

[1249] ---

[1250] The present invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is configured using user terminals, a server, and databases and real-time seat availability information provided by restaurants.

[1251] Acquiring and sending location information

[1252] Device: When a user launches the app, the device uses its GPS to obtain its current location, which is then sent to the server in the form of latitude and longitude.

[1253] Example: A user starts a smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to a server.

[1254] Obtaining information on nearby facilities

[1255] Server: Based on the received location information, the server retrieves a list of restaurants in the vicinity from a database. This list includes basic information such as the restaurant name, location, and type.

[1256] Real-time collection of vacant seat information

[1257] Server: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[1258] Example: Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[1259] Setting desired conditions

[1260] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) into the app.

[1261] Terminal: The terminal organizes these conditions, converts them into JSON format, and sends them to the server.

[1262] Proposal of the best facility

[1263] Server: The server uses AI to select the most suitable restaurant based on the user's location and desired conditions. The AI ​​creates a list of restaurants that have available seats and meet the desired conditions in real time.

[1264] Terminal: The recommendation results received from the server are displayed on the user's terminal. The user can then choose from the multiple restaurants suggested.

[1265] Example: If a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," the server will search for restaurants that meet the conditions and suggest "Restaurant A" and "Cafe B."

[1266] Reservation Requests and Confirmations

[1267] User: Selects the desired restaurant from the suggested options and requests a reservation.

[1268] Terminal: The terminal sends the selected store information to the server and makes a reservation request.

[1269] Server: The server sends a reservation request to the selected restaurant, receives confirmation, and notifies the user of the result.

[1270] Example: A user selects "Restaurant A" and submits a reservation request. The server sends a request to Restaurant A and notifies the user that the reservation has been confirmed.

[1271] Food waste reduction and discount information

[1272] Server: Generates discount information for restaurants that are about to close to reduce food waste and notifies users.

[1273] Device: Discount information is displayed on the user's device, and immediate reservation is possible if desired.

[1274] Example: If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[1275] Learning user preferences

[1276] Server: The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Based on the learning results, the server makes more accurate suggestions for the next time the user uses the service.

[1277] Example: If a user has frequently dined in "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[1278] ---

[1279] In this way, the present invention allows users to efficiently find and reserve restaurants of their choice. It also enables restaurants to provide real-time information about available seats, providing a system that contributes to both attracting customers and reducing food waste.

[1280] The processing flow will be explained below.

[1281] ---

[1282] Step 1:

[1283] User: Launches the app and agrees to location data collection.

[1284] Step 2:

[1285] Device: If location access is allowed, the device's GPS function will be used to obtain the current location. Location information will be obtained in the form of latitude and longitude.

[1286] Step 3:

[1287] Device: Sends the acquired location information to the server. The sent information consists of latitude and longitude data.

[1288] Step 4:

[1289] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. The retrieved list contains basic information about each restaurant, such as its name, address, and type.

[1290] Step 5:

[1291] Server: Real-time seat availability information is collected from each restaurant using POS systems and motion sensors. The seat availability information is obtained via API.

[1292] Step 6:

[1293] Server: Organize the acquired vacant seat information and send it to the user's device in JSON format.

[1294] Step 7:

[1295] Terminal: The received seat availability information is displayed to the user. A list of stores with available seats is displayed.

[1296] Step 8:

[1297] User: Enter your desired conditions (e.g. non-smoking seat, private room, budget, etc.) on the app screen.

[1298] Step 9:

[1299] Terminal: Convert the entered desired conditions into JSON format and send it to the server.

[1300] Step 10:

[1301] Server: Based on the received desired conditions, AI is used to select the most suitable restaurant. The AI ​​refers to a list of nearby restaurants and real-time seat availability information to extract restaurants that meet the user's conditions.

[1302] Step 11:

[1303] Server: The AI ​​selection results are sent to the user's device in JSON format.

[1304] Step 12:

[1305] Terminal: The received suggestions are displayed to the user, who can then choose from the list of suggested restaurants.

[1306] Step 13:

[1307] User: Select the desired restaurant from the suggested restaurants (e.g., "Restaurant A").

[1308] Step 14:

[1309] Terminal: Send the selected store information to the server in JSON format.

[1310] Step 15:

[1311] Server: Sends a reservation request to the selected store via API. Waits for the reservation confirmation result.

[1312] Step 16:

[1313] Server: Receives the reservation confirmation result and sends it to the user's device in JSON format. For example, "Your reservation for Restaurant A has been confirmed."

[1314] Step 17:

[1315] Terminal: Notifies the user of the received reservation results.

[1316] Step 18:

[1317] Server: Receives information about upcoming closing times and generates discount information to reduce food waste.

[1318] Step 19:

[1319] Server: Sends discount information in JSON format to the user's device.

[1320] Step 20:

[1321] Device: Display discount information on the user's device and provide the option to take advantage of the discount and make an instant reservation.

[1322] Step 21:

[1323] User: Check the discount information and press the instant reservation button if desired.

[1324] Step 22:

[1325] Server: Processes discount reservation requests and sends the final results to the user terminal.

[1326] Step 23:

[1327] Server: User reservation data and usage history are stored in a database, and AI learns user preferences.

[1328] Step 24:

[1329] Server: From the next time you use the service, it will suggest more appropriate restaurants based on the learning results.

[1330] ---

[1331] In this way, we have specifically explained all the steps from obtaining the user's location information to confirming the reservation, providing discount information to reduce food waste, and learning the user's preferences.

[1332] Example 1

[1333] 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."

[1334] The problem that this invention aims to solve is to provide a system that allows users to efficiently find and make reservations at restaurants of their choice, and also allows restaurants to transmit information about available seats in real time, thereby contributing to both attracting customers and reducing food waste.

[1335] 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.

[1336] In this invention, the server includes means for acquiring location information from the user device, means for acquiring information on nearby facilities based on the acquired location information, means for collecting vacant seating information for each facility in real time, means for inputting the user's desired conditions, means for suggesting optimal facilities based on the desired conditions, means for requesting reservations at the suggested facilities, means for processing reservation requests to the facilities, means for generating discount information based on usage data and notifying the user, and means for accumulating past usage data and using a generative model to learn the user's preferences. This allows users to efficiently find and make reservations at their desired restaurants. Furthermore, restaurants can transmit vacant seating information in real time, achieving both customer attraction and food waste reduction.

[1337] A "user terminal" is a device operated by a user, and includes a smartphone, tablet, or personal computer.

[1338] "Location Information" means information indicating the current geographic location of a user terminal, expressed in the form of latitude and longitude.

[1339] A "server" refers to a computer system that receives requests from user terminals and provides the necessary information in cooperation with a database.

[1340] "Nearby facilities" refers to restaurants and other facilities within a certain range based on the user's current location.

[1341] "Vacancy information" is information showing the current seat availability at each facility, and is obtained in real time based on POS data and sensor information.

[1342] "Desired conditions" are conditions that a user specifies when choosing a restaurant or other facility, and include items such as non-smoking seats, private rooms, and budget.

[1343] "Optimal facility" refers to the ideal facility selected by AI based on the user's location information and desired conditions.

[1344] "Reservation Request" means a request by a User to communicate to a Facility selected by the User that the User wishes to make a reservation.

[1345] "Discount information" refers to information indicating discounts offered under specific conditions by the facility, and particularly includes information related to reducing food waste near closing time.

[1346] "Usage data" refers to historical information such as the facilities a user has used in the past and the conditions at that time.

[1347] A "generative model" is an artificial intelligence model that learns a user's preferences based on their past usage data and uses this information to make suggestions for future use.

[1348] The present invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is configured using user terminals, a server, and databases and real-time seat availability information provided by restaurants.

[1349] Acquiring and sending location information

[1350] Device: When a user launches the smartphone app, the device's GPS function is used to obtain the current location information. This location information is obtained in the form of latitude and longitude and sent to the server.

[1351] Example: A user starts a smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to a server.

[1352] Obtaining information on nearby facilities

[1353] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information about each restaurant, such as its name, location, and type (Japanese, Chinese, French, etc.).

[1354] Real-time collection of vacant seat information

[1355] Server: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[1356] Example: Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[1357] Setting desired conditions

[1358] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) into the app.

[1359] Terminal: The terminal organizes these desired conditions, converts them into JSON format, and sends them to the server.

[1360] Proposal of the best facility

[1361] Server: The server uses a generative AI model to select the most suitable restaurant based on the user's location and desired conditions. The generative AI model lists restaurants that have available seats and meet the desired conditions in real time.

[1362] Terminal: The recommendation results received from the server are displayed on the user's terminal. The user can then choose from the multiple restaurants suggested.

[1363] Example: If a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," the server will search for restaurants that meet the conditions and suggest "Restaurant A" and "Cafe B."

[1364] Reservation Requests and Confirmations

[1365] User: Selects the desired restaurant from the suggested options and requests a reservation.

[1366] Terminal: The terminal sends the selected store information to the server and makes a reservation request.

[1367] Server: The server sends a reservation request to the selected restaurant, receives confirmation, and notifies the user of the result.

[1368] Example: A user selects "Restaurant A" and submits a reservation request. The server sends a request to Restaurant A and notifies the user that the reservation has been confirmed.

[1369] Food waste reduction and discount information

[1370] Server: Generates discount information for restaurants that are about to close to reduce food waste and notifies users.

[1371] Device: Discount information is displayed on the user's device, and immediate reservation is possible if desired.

[1372] Example: If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[1373] Learning user preferences

[1374] Server: The server stores the user's past reservation data and usage history, and the generative AI model learns the user's preferences. Based on the learning results, the server makes more accurate suggestions for future use.

[1375] Example: If a user has frequently dined in "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[1376] Prompt Sentence Examples

[1377] Send the location information of users who have agreed to "Use current location." Send it to the server as latitude: 35.6585, longitude: 139.7454.

[1378] In this way, the present invention allows users to efficiently find and reserve restaurants of their choice. It also enables restaurants to provide real-time information about available seats, providing a system that contributes to both attracting customers and reducing food waste.

[1379] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1380] Step 1:

[1381] Obtaining location information

[1382] Input: The user launches the smartphone app and agrees to "Use my location."

[1383] What it does: Uses the device's GPS to obtain the current location.

[1384] Output: Location information in latitude and longitude format (e.g., latitude 35.6585, longitude 139.7454).

[1385] Step 2:

[1386] Sending location information

[1387] Input: The location information obtained in step 1.

[1388] Operation: The device sends the location information it has acquired to the server.

[1389] Output: The location information is sent to the server.

[1390] Step 3:

[1391] Obtaining information on nearby facilities

[1392] Input: Location sent to the server (latitude 35.6585, longitude 139.7454).

[1393] How it works: Based on your location, the server retrieves a list of nearby restaurants from a database, including the name, location, and type of each restaurant.

[1394] Output: A list of nearby restaurants (e.g. Restaurant A, Cafe B, etc.).

[1395] Step 4:

[1396] Gathering vacancy information

[1397] Input: List of nearby restaurants obtained in step 3.

[1398] Operation: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. The server obtains seat availability information via API.

[1399] Output: Real-time seat availability information (e.g. Restaurant A has 5 available seats).

[1400] Step 5:

[1401] Input of user's desired conditions

[1402] Input: The user enters their desired conditions (e.g., non-smoking seat, private room, budget under 5,000 yen) into the app.

[1403] Operation: The device converts the entered desired conditions into JSON format and sends it to the server.

[1404] Output: The preference data sent to the server.

[1405] Step 6:

[1406] Proposal of the best facility

[1407] Input: Your preferences submitted in step 5 and availability information collected in step 4.

[1408] How it works: The server uses the generative AI model to select the restaurant that best meets the desired criteria. The generative AI model then lists restaurants that have available seats and meet the desired criteria in real time.

[1409] Output: A list of the best restaurants (e.g. "Restaurant A", "Cafe B").

[1410] Step 7:

[1411] Displaying the proposed results

[1412] Input: The list of best restaurants selected in step 6.

[1413] Operation: The device displays the suggestions received from the server to the user in a list format.

[1414] Output: The user can view a list of suggested restaurants.

[1415] Step 8:

[1416] Submit a booking request

[1417] Input: The user selects the desired restaurant from the suggested restaurants.

[1418] Operation: The device sends the selected store information to the server and makes a reservation request.

[1419] Output: The booking request sent to the server.

[1420] Step 9:

[1421] Reservation processing and confirmation

[1422] Input: The booking request submitted in step 8.

[1423] Operation: The server sends a reservation request to the selected restaurant, receives confirmation, and notifies the user terminal of the confirmation result.

[1424] Output: Booking confirmation notification (e.g. "Your booking is confirmed").

[1425] Step 10:

[1426] Food waste reduction and discount information generation

[1427] Input: Closing time and restaurant availability.

[1428] How it works: The server generates discount information to reduce food waste and notifies the user.

[1429] Output: Discount information notification (e.g. "20% off food").

[1430] Step 11:

[1431] Learning user preferences

[1432] Input: User's past booking data and usage history.

[1433] How it works: A server stores this data and a generative AI model learns user preferences.

[1434] Output: Improved accuracy of suggestions from next time onwards (e.g., a user who has previously preferred Japanese food will be given priority in suggestions of Japanese restaurants).

[1435] In this way, each step specifically constitutes the operation of the entire system.

[1436] (Application example 1)

[1437] 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."

[1438] In today's busy lifestyles, users face challenges in efficiently finding nearby restaurants, selecting a menu that meets their desired criteria, and ordering delivery. Existing delivery services are unable to provide real-time information on available menu items and seating availability based on the user's current location, and there are limited means for users to track the progress of their delivery in real time. This results in reduced convenience for users, and restaurants also face challenges in efficiently attracting customers and reducing food waste.

[1439] 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.

[1440] In this invention, the server includes a means for displaying delivery options on the user terminal, a means for the server to acquire delivery progress information and notify the user terminal, and a means for collecting seat availability information of nearby facilities in real time, thereby enabling users to efficiently browse delivery menus of nearby restaurants and keep track of delivery progress in real time.

[1441] A "user terminal" is a portable electronic device for use by a user, such as a smartphone or tablet terminal.

[1442] "Location information" is data indicating the current location of a user terminal, and is geographical information expressed in the form of latitude and longitude.

[1443] A "server" is a computer system that processes and provides data over a network.

[1444] "Nearby facilities" are restaurants and other related facilities located near the current location of the user terminal.

[1445] "Vacant seat information" is data indicating the current availability of seats at surrounding facilities.

[1446] "Real-time" means that information is processed and updated almost instantaneously.

[1447] "Desired conditions" are conditions based on specific requests or preferences entered by the user, such as non-smoking seats or budget.

[1448] A "delivery menu" is a list of dishes and drinks that nearby facilities can provide to users.

[1449] "Delivery progress information" is status information that indicates the stage of delivery ordered by the user.

[1450] A "reservation request" is a request to make a reservation at a facility selected by the user.

[1451] "Food waste reduction" refers to efforts to reduce the waste of food and drink.

[1452] "Discount information" is data regarding discounts offered by establishments that are about to close.

[1453] "Past usage data" refers to historical information about reservations and orders previously made by a user.

[1454] "AI" stands for artificial intelligence, a system that uses techniques such as machine learning to learn user preferences.

[1455] This invention is a system that allows users to efficiently find their desired restaurant and place delivery orders and reservations. This system is configured using user terminals, a server, and real-time information on available seats and menu items available for delivery at restaurants.

[1456] Acquiring and sending location information

[1457] When a user launches a smartphone app, the device uses its GPS to obtain its current location information, which is then sent to a server in the form of latitude and longitude.

[1458] Obtaining information on nearby facilities

[1459] The server retrieves a list of restaurants in the vicinity from a database based on the received location information. This list includes basic information such as the restaurant name, location, and type.

[1460] Real-time collection of vacant seat information

[1461] The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[1462] Display of menu items available for delivery

[1463] The server collects information on delivery options from nearby restaurants and provides it to the user's device. Users can then browse the available menu items and place their order on the app.

[1464] Setting desired conditions

[1465] Users input their desired conditions (e.g., vegetarian options, budget, etc.) into the app. The device organizes these conditions, converts them into JSON format, and sends it to the server.

[1466] Proposal of the best facility

[1467] The server uses AI (artificial intelligence) to select the most suitable restaurant based on the user's location information and desired conditions. The AI ​​lists restaurants and delivery menus that have available seats and meet the desired conditions in real time. The recommendation results received from the server are displayed on the user's device, and the user can choose from multiple suggested restaurants and menus.

[1468] Reservation Requests and Confirmations

[1469] The user selects a desired restaurant from the suggested restaurants and requests a reservation. The terminal sends the selected restaurant information to the server and makes a reservation request. The server sends the reservation request to the selected restaurant and receives confirmation. The result is notified to the user terminal.

[1470] Delivery progress notifications

[1471] Once a delivery order is placed, the server obtains delivery progress information in real time and notifies the user's device, allowing the user to keep track of the progress of their order.

[1472] Food waste reduction and discount information

[1473] The server generates discount information for restaurants that are about to close and notifies the user of the discount information. The discount information is displayed on the user's device, and the user can make an immediate reservation if desired.

[1474] Learning user preferences

[1475] The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Based on the learning results, more accurate suggestions will be made the next time the user uses the restaurant. For example, if a user has frequently eaten at restaurants serving "Japanese cuisine" in the past, restaurants serving "Japanese cuisine" will be given priority in suggestions from the next time onwards.

[1476] As a specific example, when a user launches a smartphone app and agrees to "use current location," the app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to the server. The server then collects information about available seats and delivery options from nearby restaurants and provides it to the user. The user inputs desired conditions such as non-smoking seats and budget, and the most suitable restaurant is suggested. When a reservation request is sent, the server processes the request and notifies the user of the confirmation result. The app also has a function that notifies the user of the delivery progress in real time.

[1477] An example of a prompt sentence that can be used is, "Please tell me the detailed steps of an app that shows the process for ordering pasta and the delivery progress in real time when a FoodNavi user orders pasta."

[1478] This invention allows users to efficiently search restaurant delivery menus and enjoy delivery while checking the order status in real time. It also enables restaurants to provide real-time information and promote efforts to reduce food waste.

[1479] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1480] Step 1:

[1481] The user launches the smartphone app and agrees to the use of location information. The device uses its GPS function to obtain the user's current location information (latitude and longitude). Specifically, the app reads location coordinates from the smartphone's GPS sensor and stores that information in the device's memory. The input is the location information obtained from the GPS sensor, and the output is location information data to be sent to the server.

[1482] Step 2:

[1483] The user device sends the acquired location information (latitude and longitude) to the server. Specifically, it sends a request including the location information to the server using the HTTP POST method. The input is the location information stored in the device's memory, and the output is the HTTP request sent to the server.

[1484] Step 3:

[1485] The server retrieves information about nearby facilities from a database based on the received location information. This involves generating a search query based on the location information and querying the database. The input is the location information received by the server, and the output is a list of nearby facilities retrieved from the database.

[1486] Step 4:

[1487] The server collects vacant seat information in real time based on POS data and motion sensor information provided by each facility. Specifically, it obtains data from each facility's system via API, analyzes it, and checks whether there are any vacant seats. The input is POS data and motion sensor information, and the output is real-time vacant seat information.

[1488] Step 5:

[1489] The server collects information about menu items available for delivery from each nearby facility and provides it to the user's device. Specifically, it uses an API to obtain menu information, formats the data, and sends it to the user's device. The input is delivery menu information provided by each facility, and the output is the menu information displayed on the user's device.

[1490] Step 6:

[1491] The user enters their desired conditions (e.g., vegetarian options, budget, etc.) on the app. The device organizes these conditions, converts them into JSON format, and sends them to the server. Specifically, it takes the data entered from the user interface, converts it into a specific format, and sends it to the server. The input is the desired conditions entered by the user, and the output is the JSON data sent to the server.

[1492] Step 7:

[1493] The server uses AI to select the most suitable restaurant based on the user's location information and desired conditions. Specifically, the received location information and desired conditions are input into an AI model, which then generates a list of the most suitable restaurants. The input is the location information and desired conditions received by the server, and the output is a list of the most suitable restaurants.

[1494] Step 8:

[1495] The recommendation results received from the server are displayed on the user terminal. Specifically, the user terminal analyzes the information sent from the server and displays it on the user interface. The input is the recommendation results sent by the server, and the output is a list of facilities and menus displayed on the user terminal.

[1496] Step 9:

[1497] The user selects a desired restaurant from the suggested restaurants and requests a reservation. The user terminal sends the selected restaurant information to the server and requests a reservation. Specifically, the system obtains the user's selection and sends a request to the server using the HTTP POST method. The input is the restaurant information selected by the user, and the output is a reservation request sent to the server.

[1498] Step 10:

[1499] The server sends a reservation request to the selected restaurant and receives confirmation. The result is then notified to the user's terminal. Specifically, the server sends a request to the restaurant's system, and once confirmation is received, it sends the information to the user's terminal. The input is the reservation request from the user, and the output is a notification of reservation confirmation.

[1500] Step 11:

[1501] Once a delivery order is confirmed, the server obtains delivery progress information in real time and notifies the user terminal. Specifically, it receives progress information from the delivery system, formats it, and sends it to the user. The input is progress information from the delivery system, and the output is a notification message to the user terminal.

[1502] Step 12:

[1503] The server generates discount information for restaurants that are about to close to reduce food waste and notifies the user. Specifically, the server generates food waste reduction information for specific time periods and notifies the user of it. The input is the store's business information and food waste reduction conditions, and the output is a discount information notification sent to the user's terminal.

[1504] Step 13:

[1505] The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Specifically, past usage data is input into the AI ​​model, which analyzes the user's preferences and trends. The input is the user's past usage data, and the output is future recommendations based on the user's preferences.

[1506] 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.

[1507] ---

[1508] This invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is composed of a user terminal, a server, databases and real-time seat availability information provided by restaurants, and an emotion engine that recognizes the user's emotions.

[1509] Acquiring and sending location information

[1510] Device: When a user launches the app, the device uses its GPS to obtain its current location, which is then sent to the server in the form of latitude and longitude.

[1511] Example: A user starts a smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to a server.

[1512] Obtaining information on nearby facilities

[1513] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information such as the restaurant name, location, and type.

[1514] Real-time collection of vacant seat information

[1515] Server: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[1516] Example: Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[1517] Setting desired conditions

[1518] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) on the app.

[1519] Terminal: Organize the entered desired conditions, convert them into JSON format, and send them to the server.

[1520] Emotion recognition by emotion engine

[1521] On the device: The emotion engine analyzes the user's facial expressions and voice to determine their current emotional state, which is classified into categories such as "happiness," "sadness," and "anger."

[1522] Example: A user accesses the emotion engine through a camera or microphone. The emotion engine identifies "happiness" from the user's facial expressions and voice, and sends this as an analysis result to the server.

[1523] Proposal of the best facility

[1524] Server: The server uses AI to select the most suitable restaurant based on the user's location, desired conditions, and emotional state. The AI ​​refers to this data and creates a list of restaurants that match the user's conditions and emotions.

[1525] Terminal: The terminal displays the restaurant recommendations received from the server to the user, who can then choose from the multiple restaurants suggested.

[1526] Example: If a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," and the emotion engine recognizes "joy," the server will suggest "Restaurant A" and "Cafe B" that match the conditions and emotion.

[1527] Reservation Requests and Confirmations

[1528] User: Selects the desired restaurant from the suggested options and requests a reservation.

[1529] Terminal: Send the selected store information to the server in JSON format.

[1530] Server: Sends a reservation request to the selected store via API, receives confirmation, and notifies the user of the result.

[1531] Example: A user selects "Restaurant A" and submits a reservation request. The server sends a request to Restaurant A and notifies the user that the reservation has been confirmed.

[1532] Food waste reduction and discount information

[1533] Server: Generates discount information for restaurants that are about to close to reduce food waste and notifies users.

[1534] Device: Discount information is displayed on the user's device, and immediate reservation is possible if desired.

[1535] Example: If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[1536] Learning user preferences

[1537] Server: The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Based on the learning results, the server makes more accurate suggestions for the next time the user uses the service.

[1538] Example: If a user has frequently dined in "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[1539] ---

[1540] In this way, the present invention allows users to efficiently find and make reservations at restaurants of their choice. Furthermore, by taking into account the user's emotional state, it is possible to suggest restaurants that will provide a higher level of satisfaction. It also enables restaurants to provide information on available seats in real time, providing a system that contributes to both attracting customers and reducing food waste.

[1541] The processing flow will be explained below.

[1542] ---

[1543] Step 1:

[1544] User: Launches the app and agrees to location data collection.

[1545] Step 2:

[1546] Device: If location access is allowed, the device's GPS function will be used to obtain the current location, which will be in the form of latitude and longitude.

[1547] Step 3:

[1548] Device: Sends the acquired location information to the server. Specifically, sends the acquired latitude and longitude data in JSON format.

[1549] Step 4:

[1550] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information such as the restaurant's name, address, and type.

[1551] Step 5:

[1552] Server: Real-time seat availability information is collected via API based on POS systems and motion sensor information provided by each restaurant. The collected seat availability information is then organized.

[1553] Step 6:

[1554] Server: Convert the acquired vacancy information into JSON format and send it to the user's device.

[1555] Step 7:

[1556] Terminal: The received seat availability information is displayed to the user. A list of restaurants with available seats is displayed on the screen.

[1557] Step 8:

[1558] User: Enter desired conditions (e.g. non-smoking seat, private room, budget, etc.) on the app screen.

[1559] Step 9:

[1560] Terminal: Convert the entered desired conditions into JSON format and send it to the server.

[1561] Step 10:

[1562] On the device: The emotion engine analyzes the user's facial expressions and voice to determine their current emotional state. This emotion data is classified into categories such as "happiness," "sadness," and "anger."

[1563] Step 11:

[1564] Terminal: Converts the emotion data identified by the emotion engine into JSON format and sends it to the server.

[1565] Step 12:

[1566] Server: The AI ​​selects the most suitable restaurant based on the received desired conditions and emotional data. The AI ​​refers to this data and creates a list of restaurants that match the user's conditions and emotions.

[1567] Step 13:

[1568] Server: The AI ​​selection results are sent to the user's device in JSON format.

[1569] Step 14:

[1570] Terminal: The received recommendation results are displayed to the user, who can then choose from multiple suggested restaurants.

[1571] Step 15:

[1572] User: Select the desired restaurant (e.g., "Restaurant A") from the list of suggested restaurants.

[1573] Step 16:

[1574] Terminal: Send the selected store information to the server in JSON format.

[1575] Step 17:

[1576] Server: Send a reservation request to the selected store via API and wait for the reservation confirmation result.

[1577] Step 18:

[1578] Server: Receives the reservation confirmation result and sends it to the user's device in JSON format. Example: "Your reservation for Restaurant A has been confirmed."

[1579] Step 19:

[1580] Terminal: Notifies the user of the received reservation results.

[1581] Step 20:

[1582] Server: Receives information about upcoming closing times and generates discount information to reduce food waste.

[1583] Step 21:

[1584] Server: Sends discount information in JSON format to the user's device.

[1585] Step 22:

[1586] Terminal: Discount information is displayed to the user, and immediate booking is possible if desired.

[1587] Step 23:

[1588] User: Check the discount information and press the instant reservation button if desired.

[1589] Step 24:

[1590] Server: Processes discount reservation requests and sends the final results to the user terminal.

[1591] Step 25:

[1592] Server: User reservation data and usage history are stored in a database, and AI learns user preferences.

[1593] Step 26:

[1594] Server: From the next time you use the service, it will suggest more appropriate restaurants based on the learning results.

[1595] ---

[1596] In this way, we have explained in detail all the steps from obtaining the user's location information, recognizing emotions, suggesting the best restaurant, confirming the reservation, providing discount information to reduce food waste, and learning the user's preferences.

[1597] Example 2

[1598] 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."

[1599] In today's busy lifestyles, it is difficult for users to efficiently find and make reservations at restaurants. Furthermore, suggestions that do not take into account the user's current emotional state may result in low satisfaction. Furthermore, it is difficult for restaurants to provide real-time information on available tables, which leads to the problem of food waste.

[1600] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring location information of the user terminal, means for transmitting the acquired location information to the server, means for the server to acquire information on surrounding facilities based on the location information, means for collecting vacant seat information for each facility in real time, means for allowing the user to input desired conditions, means for suggesting optimal facilities based on the desired conditions, means including an emotion recognition engine for analyzing the user's emotional state, means for requesting reservations at the suggested facilities, and means for the server to process reservation requests for the facilities. This allows users to efficiently find their desired restaurant and make reservations that take their emotional state into consideration, resulting in higher satisfaction. It also enables restaurants to transmit vacant seat information in real time, contributing to reducing food waste.

[1601] "User terminal" refers to a device operated by a user, including smartphones, tablets, and personal computers.

[1602] "Location information" refers to coordinate information of a specific location, expressed in the form of latitude and longitude.

[1603] "Server" refers to a computer system that receives, processes, and manages data sent from multiple user terminals.

[1604] "Facilities" are places that users can visit, including eateries, cafes, restaurants, etc.

[1605] "Vacancy information" refers to data that shows the availability of seats within a facility in real time.

[1606] "Desired conditions" refer to the requirements and wishes that users have for the facility, and include elements such as non-smoking seats, private rooms, and budget.

[1607] An "emotion recognition engine" is software or hardware that analyzes a user's facial expressions and tone of voice to identify their emotional state.

[1608] "Reservation Request" means a request by a User to communicate to a Facility selected by the User that the User wishes to make a reservation.

[1609] "Food waste" refers to ingredients and cooked food that may be discarded without being consumed.

[1610] "Discount Information" means information about price discounts offered under certain conditions specified by the facility.

[1611] "AI" stands for artificial intelligence, a technology that gives computer systems the ability to analyze data and learn.

[1612] "Preference learning" is the process of analyzing a user's preferences and trends based on their past usage data and reflecting them in future suggestions.

[1613] MODE FOR CARRYING OUT THE INVENTION

[1614] This invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is composed of a user terminal, a server, databases and real-time seat availability information provided by restaurants, and an emotion engine that recognizes the user's emotions.

[1615] Acquiring and sending location information

[1616] When a user launches the app and agrees to "Use current location," the device will use the built-in GPS to obtain the current location information. This location information is obtained in the form of latitude and longitude, converted into JSON format, and then sent to the server using a secure communication protocol (HTTPS).

[1617] Examples:

[1618] The user starts the smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to the server.

[1619] Obtaining information on nearby facilities

[1620] The server retrieves a list of nearby restaurants from a database based on the received location information. This list includes basic information such as the restaurant name, address, category, and opening hours. The retrieved data is formatted in JSON and sent to the user's device.

[1621] Real-time collection of vacant seat information

[1622] The server collects POS system data and motion sensor information provided by each restaurant via API, obtains real-time seat availability information, converts the integrated data into JSON format, and prepares it for transmission to the user's device.

[1623] Examples:

[1624] Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[1625] Setting desired conditions

[1626] Users use the app's interface to input their preferences, such as non-smoking, private rooms, budget, etc. These preferences are organized, converted into JSON format, and sent to the server.

[1627] Examples:

[1628] When a user enters conditions such as "non-smoking seats," "private rooms," and "budget under 5,000 yen," this information is organized in JSON format and sent to the server.

[1629] Emotion recognition by emotion engine

[1630] The emotion engine analyzes the user's facial expressions and tone of voice through the user's camera and microphone. The emotion recognition algorithm identifies the user's current emotional state and converts the results into JSON format and sends it to the server.

[1631] Examples:

[1632] When a user accesses the emotion engine through a camera or microphone, the emotion engine recognizes "happiness" from the user's facial expressions and voice and sends the analysis results to the server.

[1633] Proposal of the best facility

[1634] The server uses AI to select the most suitable restaurant based on the user's location, desired conditions, and emotional state. The AI ​​model takes into account past data and user trends, creates a list of restaurants that match the conditions and emotions, and sends it in JSON format to the user's device.

[1635] Examples:

[1636] When a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," and the emotion engine recognizes "joy," the server will suggest "Restaurant A" and "Cafe B" that match the conditions and emotion.

[1637] Reservation Requests and Confirmations

[1638] The user selects the restaurant of their choice from the suggested options and requests a reservation. The selected restaurant information is converted to JSON format and sent to the server. The server then sends a reservation request to the selected restaurant via API, and sends the reservation confirmation in JSON format to the user's device.

[1639] Examples:

[1640] The user selects "Restaurant A" and submits a reservation request. The server makes a request to Restaurant A and notifies the user that the reservation has been confirmed.

[1641] Food waste reduction and discount information

[1642] The server generates discount information for restaurants that are about to close, in order to reduce food waste, and notifies the user. The discount information is converted into JSON format and displayed on the user's device.

[1643] Examples:

[1644] If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[1645] Learning user preferences

[1646] The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences, which are then used to make more accurate suggestions the next time the user uses the service.

[1647] Examples:

[1648] If a user has frequently visited "Japanese cuisine" restaurants in the past, "Japanese cuisine" restaurants will be prioritized in the list the next time suggestions are made.

[1649] Prompt Sentence Examples

[1650] I agree to "Use my current location" and suggest the best restaurant using a list of restaurants, seat availability information, and an emotion engine. My desired conditions are "non-smoking seat," "private room," "budget under 5,000 yen," and my emotional state is "delighted." I want to be able to make a reservation at the suggested restaurant.

[1651] This invention allows users to efficiently find the restaurant they want, and by taking their emotional state into consideration, it is possible to suggest restaurants that will increase their satisfaction. It also enables restaurants to send out information about available seats in real time, which will help reduce food waste.

[1652] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1653] Step 1: Obtaining and sending location information

[1654] Device:

[1655] When the app is launched, the device uses its built-in GPS to obtain its current location. This location information is obtained in the form of latitude and longitude and converted into JSON format. The converted location information is then sent to the server using a secure communication protocol (HTTPS).

[1656] Specific behavior:

[1657] Input: The user launches the app on their smartphone and agrees to "Use my location."

[1658] Data processing: Latitude and longitude data is obtained using the smartphone's GPS function and converted into JSON format.

[1659] Output: The converted location information is sent to the server.

[1660] Step 2: Obtain information about nearby facilities

[1661] server:

[1662] Based on the received location information, the server queries the database to obtain a list of nearby restaurants. This list includes basic information such as the restaurant name, address, category, and opening hours. The obtained data is formatted in JSON format and sent to the user's device.

[1663] Specific behavior:

[1664] Input: Location information in JSON format.

[1665] Data processing: Based on the received location information, an SQL query is executed on the database to obtain information on nearby facilities. The obtained information is then formatted into JSON format.

[1666] Output: Facility information in JSON format is sent to the user's device.

[1667] Step 3: Real-time collection of seat availability information

[1668] server:

[1669] The server collects POS system data and motion sensor information provided by each restaurant via API, obtains real-time seat availability information, converts the integrated data into JSON format, and prepares it for transmission to the user's device.

[1670] Specific behavior:

[1671] Input: POS system data and motion sensor information from each restaurant.

[1672] Data processing: Calls APIs to collect data from each store, centralizes it in the integration engine, and converts the data into JSON format.

[1673] Output: The vacancy information is converted to JSON format and sent to the user's device.

[1674] Step 4: Set your preferences

[1675] User:

[1676] Users use the app's interface to input their preferences, such as non-smoking, private rooms, and budget.

[1677] Device:

[1678] The entered desired conditions are organized, converted into JSON format, and sent to the server.

[1679] Specific behavior:

[1680] Input: The user enters their desired criteria into the app's interface.

[1681] Data processing: Convert the entered desired conditions into JSON format.

[1682] Output: The desired conditions are sent to the server.

[1683] Step 5: Emotion Recognition with the Emotion Engine

[1684] Device:

[1685] The emotion engine analyzes the user's facial expressions and tone of voice through the user's camera and microphone. The emotion recognition algorithm identifies the user's current emotional state and converts the results into JSON format and sends it to the server.

[1686] Specific behavior:

[1687] Input: The user accesses the emotion engine through a camera or microphone.

[1688] Data processing: The emotion recognition algorithm analyzes the acquired data to identify the emotional state, and converts the results into JSON format.

[1689] Output: The emotion recognition results are sent to the server.

[1690] Step 6: Propose the best facility

[1691] server:

[1692] The server uses AI to select the most suitable restaurant based on the user's location, desired conditions, and emotional state. The AI ​​model takes into account past data and user trends, creates a list of restaurants that match the conditions and emotions, and sends it in JSON format to the user's device.

[1693] Specific behavior:

[1694] Input: location, desired conditions, emotional data.

[1695] Data processing: The AI ​​model uses this data to select and list the best restaurants. The data is formatted into JSON format.

[1696] Output: The proposed results are sent to the user's device in JSON format.

[1697] Step 7: Reservation Request and Confirmation

[1698] User:

[1699] The user selects the desired restaurant from the suggested restaurants and requests a reservation.

[1700] Device:

[1701] Convert the selected store information into JSON format and send it to the server.

[1702] server:

[1703] A reservation request is sent to the selected store via API, and the reservation confirmation result is sent to the user's terminal in JSON format.

[1704] Specific behavior:

[1705] Input: The user selects the desired store.

[1706] Data processing: Convert the selected store information into JSON format.

[1707] Output: A reservation request is sent to the server, and the reservation confirmation result is sent to the user terminal.

[1708] Step 8: Reduce food waste and provide discount information

[1709] server:

[1710] To generate discount information for reducing food waste for restaurants that are about to close and notify the user of the information.

[1711] Device:

[1712] The discount information is converted to JSON format and displayed on the user's device. Based on this information, the user can make an immediate reservation if desired.

[1713] Specific behavior:

[1714] Input: Discount information from restaurants.

[1715] Data processing: Convert discount information into JSON format.

[1716] Output: The discount information is sent to the user's terminal and displayed.

[1717] Step 9: Learning User Preferences

[1718] server:

[1719] By accumulating the user's past reservation data and usage history, the AI ​​learns the user's preferences and uses the results to make more accurate suggestions the next time the user uses the service.

[1720] Specific behavior:

[1721] Input: Past reservation data and usage history.

[1722] Data processing: AI learns from this data and analyzes user preferences. The learning results are used to improve future recommendations.

[1723] Output: Suggestions based on the user's preferences will be reflected in future visits.

[1724] (Application example 2)

[1725] 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."

[1726] Conventional restaurant reservation systems easily provide information based on the user's current location and obtain real-time seat availability information, but they lack a mechanism for suggesting optimal restaurants that take the user's emotional state into account. Furthermore, they have not adequately implemented measures to reduce food waste through discount information for restaurants close to closing time, or to improve the accuracy of personalized recommendations based on the user's past usage data. To address these issues, the present invention aims to provide a restaurant recommendation system that takes the user's emotions into account, thereby enabling a more accurate reservation experience.

[1727] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1728] In this invention, the server includes means for acquiring location information of the user terminal, means for acquiring information on surrounding facilities based on the acquired location information, means for collecting information on available seats at each facility in real time, means for recognizing the emotional state of the user and suggesting facilities taking the emotional state into consideration, means for allowing the user to input desired conditions, means for suggesting optimal facilities based on the desired conditions, means for requesting a reservation at the suggested facility, and means for the server to process reservation requests for the facility. This makes it possible to suggest and reserve optimal restaurants taking the emotional state of the user into consideration.

[1729] A "user terminal" is a portable electronic device used to obtain location information and communicate with a server.

[1730] "Location Information" refers to the geographic coordinate information of a user's current location.

[1731] A "server" is a central processing unit that receives and processes data sent from a user terminal.

[1732] "Nearby facilities" refers to restaurants and other commercial facilities that are searched for based on the user's location information.

[1733] "Available seat information" is information that indicates the current number of available seats at a particular facility.

[1734] "Real-time" refers to information that is updated almost immediately.

[1735] "Desired conditions" refer to the requests and restrictions that users have when selecting a facility.

[1736] "Emotional state" refers to the user's current emotional state and is classified into categories such as "joy," "sadness," and "anger."

[1737] "Suggestion" refers to recommending the most suitable facility based on the user's desired conditions and emotional state.

[1738] "Reservation Request" means making a reservation for a proposed facility.

[1739] "Food waste reduction" refers to reducing the waste of surplus food ingredients in restaurants.

[1740] "Discount information" is information indicating the conditions under which the offered product will be cheaper than its regular price.

[1741] "Usage Data" refers to historical information about reservations and facility usage made by a user.

[1742] "AI" refers to artificial intelligence, a technology that analyzes and learns from user preferences and behavioral patterns based on data.

[1743] This invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is composed of a user terminal, a server, databases and real-time seat availability information provided by restaurants, and an emotion engine that recognizes the user's emotions.

[1744] Acquiring and sending location information

[1745] Device: When a user launches the app, the device uses its GPS function to obtain its current location. This location information is obtained in the form of latitude and longitude and sent to the server. Specifically, when a user launches the smartphone app and agrees to "Use current location," the location information is obtained as "Latitude: 35.6585, Longitude: 139.7454" and sent to the server.

[1746] Obtaining information on nearby facilities

[1747] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information such as the restaurant name, location, and type.

[1748] Real-time collection of vacant seat information

[1749] Server: The server collects seat availability information in real time based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is known. For example, if a restaurant uses a POS system and the data on the number of available seats reports that "there are currently five seats available," the server obtains this information and prepares to provide it to the user.

[1750] Setting desired conditions

[1751] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) on the app.

[1752] Terminal: Organize the entered desired conditions, convert them into JSON format, and send them to the server.

[1753] Emotion recognition by emotion engine

[1754] Device: The emotion engine analyzes the user's facial expressions and voice to identify their current emotional state. This emotional state is classified into categories such as "happiness," "sadness," and "anger." The user accesses the emotion engine via the camera or microphone, and the emotion engine identifies "happiness" from the user's facial expressions and voice and sends this as the analysis result to the server.

[1755] Proposal of the best facility

[1756] Server: The server uses AI to select the best restaurant based on the user's location, desired conditions, and emotional state. The AI ​​refers to this data and creates a list of restaurants that match the user's conditions and emotions.

[1757] Terminal: Displays the recommendation results received from the server to the user. The user can choose from multiple suggested restaurants. For example, if the user sets their desired conditions as "non-smoking seats," "private rooms," and "budget under 5,000 yen," and the emotion engine recognizes "joy," the server will suggest "Restaurant A" and "Cafe B" that match the conditions and emotion.

[1758] Reservation Requests and Confirmations

[1759] User: Selects the restaurant they want from the suggested options and requests a reservation.

[1760] Terminal: Send the selected store information to the server in JSON format.

[1761] Server: Sends a reservation request to the selected restaurant via API and receives confirmation. Notifies the user of the result. For example, if a user selects "Restaurant A" and sends a reservation request, the server makes a request to Restaurant A and notifies the user that the reservation has been confirmed.

[1762] Food waste reduction and discount information

[1763] Server: Generates discount information to reduce food waste for restaurants that are about to close and notifies users.

[1764] Device: Discount information will be displayed on the user's device, and they can make an instant reservation if they wish.

[1765] For example, if a restaurant offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an instant reservation.

[1766] Learning user preferences

[1767] Server: The AI ​​accumulates the user's past reservation data and usage history, and learns the user's preferences. Based on the learning results, it makes more accurate suggestions the next time the user uses the service. For example, if the user has often selected "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[1768] Example prompt sentence:

[1769] "The user wants to have a fun, delicious dinner. The current location is Tokyo Tower. Suggest a nearby restaurant with a private, non-smoking room, and a budget of under 5,000 yen."

[1770] In this way, this invention allows users to efficiently find and make reservations at restaurants of their choice. Furthermore, restaurant suggestions are made taking into account the user's emotional state, enabling a more satisfying reservation experience. It also enables restaurants to provide information on available seats in real time, providing a system that contributes to both attracting customers and reducing food waste.

[1771] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1772] Step 1:

[1773] Launch the app on the user's device and obtain the current location information.

[1774] Input: App launch, location information from GPS sensor

[1775] Output: The latitude and longitude data obtained (e.g., "Latitude: 35.6585, Longitude: 139.7454")

[1776] Specific operation: When a user launches the smartphone app and agrees to "Use current location," the device will use the GPS function to obtain the current location information, which will then be stored in the device's internal memory.

[1777] Step 2:

[1778] The acquired location information is sent to the server.

[1779] Input: Latitude and longitude data stored on the device

[1780] Output: Log of location information sent to the server

[1781] Specific operation: The device sends location information to the server using the server communication protocol. After sending, a log indicating the success is generated.

[1782] Step 3:

[1783] The server obtains information about nearby facilities based on location information.

[1784] Input: Location information received by the server

[1785] Output: List of nearby facilities (name, address, category, etc.)

[1786] Specific operation: Based on the location information received by the server, it sends a query to the database to obtain information about nearby facilities, and returns query results including facility name, address, type, etc.

[1787] Step 4:

[1788] The server collects vacant seat information for each facility in real time.

[1789] Input: List of nearby facilities

[1790] Output: Availability information for each assigned facility

[1791] Specific operation: The server sends a request to each restaurant's system (POS data, motion sensors, etc.) via API to obtain current seat availability information. The results are added to a list of nearby facilities.

[1792] Step 5:

[1793] The user enters the desired conditions.

[1794] Input: User's desired conditions (e.g., non-smoking seat, private room, budget, etc.)

[1795] Output: JSON format data of desired conditions

[1796] Specific operation: The user enters desired conditions on the app screen, and the information is converted to JSON format within the device.

[1797] Step 6:

[1798] The terminal transmits the desired conditions to the server.

[1799] Input: JSON format data of desired conditions

[1800] Output: Log of desired condition data sent to the server

[1801] Specific operation: The device sends the desired condition data in JSON format to the server and generates a log indicating that the transmission was successful.

[1802] Step 7:

[1803] The device recognizes the user's emotional state.

[1804] Input: User facial and voice data collected through the camera and microphone

[1805] Output: Emotional state category (e.g., "joy," "sadness," "anger," etc.)

[1806] Specific operation: The device's emotion recognition engine analyzes facial expressions and voice data, categorizes the user's emotional state, and sends the results to the server.

[1807] Step 8:

[1808] The server suggests the most suitable facility based on location information, desired conditions, and emotional state.

[1809] Input: User's location, desired conditions, emotional state

[1810] Output: List of optimal facilities

[1811] How it works: The server's AI uses the input data to select the most suitable facilities and generate a recommendation list, which includes each facility's rating and the degree of matching of the conditions.

[1812] Step 9:

[1813] Proposals from the server are displayed on the user's device.

[1814] Input: List of optimal facilities

[1815] Output: A list of suggested facilities displayed to the user

[1816] Specific operation: The server sends the generated list of optimal facilities to the terminal, which then visually displays it to the user, allowing the user to select a store from this list.

[1817] Step 10:

[1818] The user selects the desired facility and requests a reservation.

[1819] Input: Facility information selected by the user

[1820] Output: JSON format data of the reservation request

[1821] Specific operation: The user selects the desired facility from the list, and the facility information is converted into JSON format and sent to the server.

[1822] Step 11:

[1823] The server processes reservation requests to facilities.

[1824] Input: Reservation request data for the selected facility

[1825] Output: Confirmed reservation information

[1826] Specific operation: The server sends a reservation request to the facility via API, receives the processing result (reservation success or failure), and notifies the user's device.

[1827] Step 12:

[1828] The server generates discount information to reduce food waste and notifies the user.

[1829] Input: Information from the facility about closing time

[1830] Output: Discount information notification

[1831] Specific operation: Based on discount information provided by establishments that are about to close, the server generates information for reducing food waste and notifies the user. The user receives this information and can make an instant reservation.

[1832] Step 13:

[1833] The server stores users' past usage data and learns their preferences.

[1834] Input: User's past usage history data

[1835] Output: Learned user preference data

[1836] How it works: The server stores the user's past reservation data and usage history, and uses AI to analyze and learn the user's preferences. The results are reflected in the next proposal.

[1837] In this way, a system is constructed that allows users to efficiently find and make reservations at restaurants of their choice through each step.

[1838] 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.

[1839] 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.

[1840] 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.

[1841] [Fourth embodiment]

[1842] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1843] 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.

[1844] 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).

[1845] 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.

[1846] 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.

[1847] 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).

[1848] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1849] 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.

[1850] 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.

[1851] 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.

[1852] 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.

[1853] 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.

[1854] 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."

[1855] ---

[1856] The present invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is configured using user terminals, a server, and databases and real-time seat availability information provided by restaurants.

[1857] Acquiring and sending location information

[1858] Device: When a user launches the app, the device uses its GPS to obtain its current location, which is then sent to the server in the form of latitude and longitude.

[1859] Example: A user starts a smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to a server.

[1860] Obtaining information on nearby facilities

[1861] Server: Based on the received location information, the server retrieves a list of restaurants in the vicinity from a database. This list includes basic information such as the restaurant name, location, and type.

[1862] Real-time collection of vacant seat information

[1863] Server: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[1864] Example: Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[1865] Setting desired conditions

[1866] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) into the app.

[1867] Terminal: The terminal organizes these conditions, converts them into JSON format, and sends them to the server.

[1868] Proposal of the best facility

[1869] Server: The server uses AI to select the most suitable restaurant based on the user's location and desired conditions. The AI ​​creates a list of restaurants that have available seats and meet the desired conditions in real time.

[1870] Terminal: The recommendation results received from the server are displayed on the user's terminal. The user can then choose from the multiple restaurants suggested.

[1871] Example: If a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," the server will search for restaurants that meet the conditions and suggest "Restaurant A" and "Cafe B."

[1872] Reservation Requests and Confirmations

[1873] User: Selects the desired restaurant from the suggested options and requests a reservation.

[1874] Terminal: The terminal sends the selected store information to the server and makes a reservation request.

[1875] Server: The server sends a reservation request to the selected restaurant, receives confirmation, and notifies the user of the result.

[1876] Example: A user selects "Restaurant A" and submits a reservation request. The server sends a request to Restaurant A and notifies the user that the reservation has been confirmed.

[1877] Food waste reduction and discount information

[1878] Server: Generates discount information for restaurants that are about to close to reduce food waste and notifies users.

[1879] Device: Discount information is displayed on the user's device, and immediate reservation is possible if desired.

[1880] Example: If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[1881] Learning user preferences

[1882] Server: The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Based on the learning results, the server makes more accurate suggestions for the next time the user uses the service.

[1883] Example: If a user has frequently dined in "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[1884] ---

[1885] In this way, the present invention allows users to efficiently find and reserve restaurants of their choice. It also enables restaurants to provide real-time information about available seats, providing a system that contributes to both attracting customers and reducing food waste.

[1886] The processing flow will be explained below.

[1887] ---

[1888] Step 1:

[1889] User: Launches the app and agrees to location data collection.

[1890] Step 2:

[1891] Device: If location access is allowed, the device's GPS function will be used to obtain the current location. Location information will be obtained in the form of latitude and longitude.

[1892] Step 3:

[1893] Device: Sends the acquired location information to the server. The sent information consists of latitude and longitude data.

[1894] Step 4:

[1895] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. The retrieved list contains basic information about each restaurant, such as its name, address, and type.

[1896] Step 5:

[1897] Server: Real-time seat availability information is collected from each restaurant using POS systems and motion sensors. The seat availability information is obtained via API.

[1898] Step 6:

[1899] Server: Organize the acquired vacant seat information and send it to the user's device in JSON format.

[1900] Step 7:

[1901] Terminal: The received seat availability information is displayed to the user. A list of stores with available seats is displayed.

[1902] Step 8:

[1903] User: Enter your desired conditions (e.g. non-smoking seat, private room, budget, etc.) on the app screen.

[1904] Step 9:

[1905] Terminal: Convert the entered desired conditions into JSON format and send it to the server.

[1906] Step 10:

[1907] Server: Based on the received desired conditions, AI is used to select the most suitable restaurant. The AI ​​refers to a list of nearby restaurants and real-time seat availability information to extract restaurants that meet the user's conditions.

[1908] Step 11:

[1909] Server: The AI ​​selection results are sent to the user's device in JSON format.

[1910] Step 12:

[1911] Terminal: The received suggestions are displayed to the user, who can then choose from the list of suggested restaurants.

[1912] Step 13:

[1913] User: Select the desired restaurant from the suggested restaurants (e.g., "Restaurant A").

[1914] Step 14:

[1915] Terminal: Send the selected store information to the server in JSON format.

[1916] Step 15:

[1917] Server: Sends a reservation request to the selected store via API. Waits for the reservation confirmation result.

[1918] Step 16:

[1919] Server: Receives the reservation confirmation result and sends it to the user's device in JSON format. For example, "Your reservation for Restaurant A has been confirmed."

[1920] Step 17:

[1921] Terminal: Notifies the user of the received reservation results.

[1922] Step 18:

[1923] Server: Receives information about upcoming closing times and generates discount information to reduce food waste.

[1924] Step 19:

[1925] Server: Sends discount information in JSON format to the user's device.

[1926] Step 20:

[1927] Device: Display discount information on the user's device and provide the option to take advantage of the discount and make an instant reservation.

[1928] Step 21:

[1929] User: Check the discount information and press the instant reservation button if desired.

[1930] Step 22:

[1931] Server: Processes discount reservation requests and sends the final results to the user terminal.

[1932] Step 23:

[1933] Server: User reservation data and usage history are stored in a database, and AI learns user preferences.

[1934] Step 24:

[1935] Server: From the next time you use the service, it will suggest more appropriate restaurants based on the learning results.

[1936] ---

[1937] In this way, we have specifically explained all the steps from obtaining the user's location information to confirming the reservation, providing discount information to reduce food waste, and learning the user's preferences.

[1938] Example 1

[1939] 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."

[1940] The problem that this invention aims to solve is to provide a system that allows users to efficiently find and make reservations at restaurants of their choice, and also allows restaurants to transmit information about available seats in real time, thereby contributing to both attracting customers and reducing food waste.

[1941] 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.

[1942] In this invention, the server includes means for acquiring location information from the user device, means for acquiring information on nearby facilities based on the acquired location information, means for collecting vacant seating information for each facility in real time, means for inputting the user's desired conditions, means for suggesting optimal facilities based on the desired conditions, means for requesting reservations at the suggested facilities, means for processing reservation requests to the facilities, means for generating discount information based on usage data and notifying the user, and means for accumulating past usage data and using a generative model to learn the user's preferences. This allows users to efficiently find and make reservations at their desired restaurants. Furthermore, restaurants can transmit vacant seating information in real time, achieving both customer attraction and food waste reduction.

[1943] A "user terminal" is a device operated by a user, and includes a smartphone, tablet, or personal computer.

[1944] "Location Information" means information indicating the current geographic location of a user terminal, expressed in the form of latitude and longitude.

[1945] A "server" refers to a computer system that receives requests from user terminals and provides the necessary information in cooperation with a database.

[1946] "Nearby facilities" refers to restaurants and other facilities within a certain range based on the user's current location.

[1947] "Vacancy information" is information showing the current seat availability at each facility, and is obtained in real time based on POS data and sensor information.

[1948] "Desired conditions" are conditions that a user specifies when choosing a restaurant or other facility, and include items such as non-smoking seats, private rooms, and budget.

[1949] "Optimal facility" refers to the ideal facility selected by AI based on the user's location information and desired conditions.

[1950] "Reservation Request" means a request by a User to communicate to a Facility selected by the User that the User wishes to make a reservation.

[1951] "Discount information" refers to information indicating discounts offered under specific conditions by the facility, and particularly includes information related to reducing food waste near closing time.

[1952] "Usage data" refers to historical information such as the facilities a user has used in the past and the conditions at that time.

[1953] A "generative model" is an artificial intelligence model that learns a user's preferences based on their past usage data and uses this information to make suggestions for future use.

[1954] The present invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is configured using user terminals, a server, and databases and real-time seat availability information provided by restaurants.

[1955] Acquiring and sending location information

[1956] Device: When a user launches the smartphone app, the device's GPS function is used to obtain the current location information. This location information is obtained in the form of latitude and longitude and sent to the server.

[1957] Example: A user starts a smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to a server.

[1958] Obtaining information on nearby facilities

[1959] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information about each restaurant, such as its name, location, and type (Japanese, Chinese, French, etc.).

[1960] Real-time collection of vacant seat information

[1961] Server: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[1962] Example: Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[1963] Setting desired conditions

[1964] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) into the app.

[1965] Terminal: The terminal organizes these desired conditions, converts them into JSON format, and sends them to the server.

[1966] Proposal of the best facility

[1967] Server: The server uses a generative AI model to select the most suitable restaurant based on the user's location and desired conditions. The generative AI model lists restaurants that have available seats and meet the desired conditions in real time.

[1968] Terminal: The recommendation results received from the server are displayed on the user's terminal. The user can then choose from the multiple restaurants suggested.

[1969] Example: If a user sets their desired conditions as "non-smoking seat," "private room," and "budget under 5,000 yen," the server will search for restaurants that meet the conditions and suggest "Restaurant A" and "Cafe B."

[1970] Reservation Requests and Confirmations

[1971] User: Selects the desired restaurant from the suggested options and requests a reservation.

[1972] Terminal: The terminal sends the selected store information to the server and makes a reservation request.

[1973] Server: The server sends a reservation request to the selected restaurant, receives confirmation, and notifies the user of the result.

[1974] Example: A user selects "Restaurant A" and submits a reservation request. The server sends a request to Restaurant A and notifies the user that the reservation has been confirmed.

[1975] Food waste reduction and discount information

[1976] Server: Generates discount information for restaurants that are about to close to reduce food waste and notifies users.

[1977] Device: Discount information is displayed on the user's device, and immediate reservation is possible if desired.

[1978] Example: If Restaurant A offers a 20% discount on food two hours before closing, the server notifies the user of this information, allowing the user to make an immediate reservation.

[1979] Learning user preferences

[1980] Server: The server stores the user's past reservation data and usage history, and the generative AI model learns the user's preferences. Based on the learning results, the server makes more accurate suggestions for future use.

[1981] Example: If a user has frequently dined in "Japanese cuisine" in the past, "Japanese cuisine" restaurants will be prioritized in suggestions from the next time onwards.

[1982] Prompt Sentence Examples

[1983] Send the location information of users who have agreed to "Use current location." Send it to the server as latitude: 35.6585, longitude: 139.7454.

[1984] In this way, the present invention allows users to efficiently find and reserve restaurants of their choice. It also enables restaurants to provide real-time information about available seats, providing a system that contributes to both attracting customers and reducing food waste.

[1985] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1986] Step 1:

[1987] Obtaining location information

[1988] Input: The user launches the smartphone app and agrees to "Use my location."

[1989] What it does: Uses the device's GPS to obtain the current location.

[1990] Output: Location information in latitude and longitude format (e.g., latitude 35.6585, longitude 139.7454).

[1991] Step 2:

[1992] Sending location information

[1993] Input: The location information obtained in step 1.

[1994] Operation: The device sends the location information it has acquired to the server.

[1995] Output: The location information is sent to the server.

[1996] Step 3:

[1997] Obtaining information on nearby facilities

[1998] Input: Location sent to the server (latitude 35.6585, longitude 139.7454).

[1999] How it works: Based on your location, the server retrieves a list of nearby restaurants from a database, including the name, location, and type of each restaurant.

[2000] Output: A list of nearby restaurants (e.g. Restaurant A, Cafe B, etc.).

[2001] Step 4:

[2002] Gathering vacancy information

[2003] Input: List of nearby restaurants obtained in step 3.

[2004] Operation: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. The server obtains seat availability information via API.

[2005] Output: Real-time seat availability information (e.g. Restaurant A has 5 available seats).

[2006] Step 5:

[2007] Input of user's desired conditions

[2008] Input: The user enters their desired conditions (e.g., non-smoking seat, private room, budget under 5,000 yen) into the app.

[2009] Operation: The device converts the entered desired conditions into JSON format and sends it to the server.

[2010] Output: The preference data sent to the server.

[2011] Step 6:

[2012] Proposal of the best facility

[2013] Input: Your preferences submitted in step 5 and availability information collected in step 4.

[2014] How it works: The server uses the generative AI model to select the restaurant that best meets the desired criteria. The generative AI model then lists restaurants that have available seats and meet the desired criteria in real time.

[2015] Output: A list of the best restaurants (e.g. "Restaurant A", "Cafe B").

[2016] Step 7:

[2017] Displaying the proposed results

[2018] Input: The list of best restaurants selected in step 6.

[2019] Operation: The device displays the suggestions received from the server to the user in a list format.

[2020] Output: The user can view a list of suggested restaurants.

[2021] Step 8:

[2022] Submit a booking request

[2023] Input: The user selects the desired restaurant from the suggested restaurants.

[2024] Operation: The device sends the selected store information to the server and makes a reservation request.

[2025] Output: The booking request sent to the server.

[2026] Step 9:

[2027] Reservation processing and confirmation

[2028] Input: The booking request submitted in step 8.

[2029] Operation: The server sends a reservation request to the selected restaurant, receives confirmation, and notifies the user terminal of the confirmation result.

[2030] Output: Booking confirmation notification (e.g. "Your booking is confirmed").

[2031] Step 10:

[2032] Food waste reduction and discount information generation

[2033] Input: Closing time and restaurant availability.

[2034] How it works: The server generates discount information to reduce food waste and notifies the user.

[2035] Output: Discount information notification (e.g. "20% off food").

[2036] Step 11:

[2037] Learning user preferences

[2038] Input: User's past booking data and usage history.

[2039] How it works: A server stores this data and a generative AI model learns user preferences.

[2040] Output: Improved accuracy of suggestions from next time onwards (e.g., a user who has previously preferred Japanese food will be given priority in suggestions of Japanese restaurants).

[2041] In this way, each step specifically constitutes the operation of the entire system.

[2042] (Application example 1)

[2043] 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."

[2044] In today's busy lifestyles, users face challenges in efficiently finding nearby restaurants, selecting a menu that meets their desired criteria, and ordering delivery. Existing delivery services are unable to provide real-time information on available menu items and seating availability based on the user's current location, and there are limited means for users to track the progress of their delivery in real time. This results in reduced convenience for users, and restaurants also face challenges in efficiently attracting customers and reducing food waste.

[2045] 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.

[2046] In this invention, the server includes a means for displaying delivery options on the user terminal, a means for the server to acquire delivery progress information and notify the user terminal, and a means for collecting seat availability information of nearby facilities in real time, thereby enabling users to efficiently browse delivery menus of nearby restaurants and keep track of delivery progress in real time.

[2047] A "user terminal" is a portable electronic device for use by a user, such as a smartphone or tablet terminal.

[2048] "Location information" is data indicating the current location of a user terminal, and is geographical information expressed in the form of latitude and longitude.

[2049] A "server" is a computer system that processes and provides data over a network.

[2050] "Nearby facilities" are restaurants and other related facilities located near the current location of the user terminal.

[2051] "Vacant seat information" is data indicating the current availability of seats at surrounding facilities.

[2052] "Real-time" means that information is processed and updated almost instantaneously.

[2053] "Desired conditions" are conditions based on specific requests or preferences entered by the user, such as non-smoking seats or budget.

[2054] A "delivery menu" is a list of dishes and drinks that nearby facilities can provide to users.

[2055] "Delivery progress information" is status information that indicates the stage of delivery ordered by the user.

[2056] A "reservation request" is a request to make a reservation at a facility selected by the user.

[2057] "Food waste reduction" refers to efforts to reduce the waste of food and drink.

[2058] "Discount information" is data regarding discounts offered by establishments that are about to close.

[2059] "Past usage data" refers to historical information about reservations and orders previously made by a user.

[2060] "AI" stands for artificial intelligence, a system that uses techniques such as machine learning to learn user preferences.

[2061] This invention is a system that allows users to efficiently find their desired restaurant and place delivery orders and reservations. This system is configured using user terminals, a server, and real-time information on available seats and menu items available for delivery at restaurants.

[2062] Acquiring and sending location information

[2063] When a user launches a smartphone app, the device uses its GPS to obtain its current location information, which is then sent to a server in the form of latitude and longitude.

[2064] Obtaining information on nearby facilities

[2065] The server retrieves a list of restaurants in the vicinity from a database based on the received location information. This list includes basic information such as the restaurant name, location, and type.

[2066] Real-time collection of vacant seat information

[2067] The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[2068] Display of menu items available for delivery

[2069] The server collects information on delivery options from nearby restaurants and provides it to the user's device. Users can then browse the available menu items and place their order on the app.

[2070] Setting desired conditions

[2071] Users input their desired conditions (e.g., vegetarian options, budget, etc.) into the app. The device organizes these conditions, converts them into JSON format, and sends it to the server.

[2072] Proposal of the best facility

[2073] The server uses AI (artificial intelligence) to select the most suitable restaurant based on the user's location information and desired conditions. The AI ​​lists restaurants and delivery menus that have available seats and meet the desired conditions in real time. The recommendation results received from the server are displayed on the user's device, and the user can choose from multiple suggested restaurants and menus.

[2074] Reservation Requests and Confirmations

[2075] The user selects a desired restaurant from the suggested restaurants and requests a reservation. The terminal sends the selected restaurant information to the server and makes a reservation request. The server sends the reservation request to the selected restaurant and receives confirmation. The result is notified to the user terminal.

[2076] Delivery progress notifications

[2077] Once a delivery order is placed, the server obtains delivery progress information in real time and notifies the user's device, allowing the user to keep track of the progress of their order.

[2078] Food waste reduction and discount information

[2079] The server generates discount information for restaurants that are about to close and notifies the user of the discount information. The discount information is displayed on the user's device, and the user can make an immediate reservation if desired.

[2080] Learning user preferences

[2081] The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Based on the learning results, more accurate suggestions will be made the next time the user uses the restaurant. For example, if a user has frequently eaten at restaurants serving "Japanese cuisine" in the past, restaurants serving "Japanese cuisine" will be given priority in suggestions from the next time onwards.

[2082] As a specific example, when a user launches a smartphone app and agrees to "use current location," the app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to the server. The server then collects information about available seats and delivery options from nearby restaurants and provides it to the user. The user inputs desired conditions such as non-smoking seats and budget, and the most suitable restaurant is suggested. When a reservation request is sent, the server processes the request and notifies the user of the confirmation result. The app also has a function that notifies the user of the delivery progress in real time.

[2083] An example of a prompt sentence that can be used is, "Please tell me the detailed steps of an app that shows the process for ordering pasta and the delivery progress in real time when a FoodNavi user orders pasta."

[2084] This invention allows users to efficiently search restaurant delivery menus and enjoy delivery while checking the order status in real time. It also enables restaurants to provide real-time information and promote efforts to reduce food waste.

[2085] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2086] Step 1:

[2087] The user launches the smartphone app and agrees to the use of location information. The device uses its GPS function to obtain the user's current location information (latitude and longitude). Specifically, the app reads location coordinates from the smartphone's GPS sensor and stores that information in the device's memory. The input is the location information obtained from the GPS sensor, and the output is location information data to be sent to the server.

[2088] Step 2:

[2089] The user device sends the acquired location information (latitude and longitude) to the server. Specifically, it sends a request including the location information to the server using the HTTP POST method. The input is the location information stored in the device's memory, and the output is the HTTP request sent to the server.

[2090] Step 3:

[2091] The server retrieves information about nearby facilities from a database based on the received location information. This involves generating a search query based on the location information and querying the database. The input is the location information received by the server, and the output is a list of nearby facilities retrieved from the database.

[2092] Step 4:

[2093] The server collects vacant seat information in real time based on POS data and motion sensor information provided by each facility. Specifically, it obtains data from each facility's system via API, analyzes it, and checks whether there are any vacant seats. The input is POS data and motion sensor information, and the output is real-time vacant seat information.

[2094] Step 5:

[2095] The server collects information about menu items available for delivery from each nearby facility and provides it to the user's device. Specifically, it uses an API to obtain menu information, formats the data, and sends it to the user's device. The input is delivery menu information provided by each facility, and the output is the menu information displayed on the user's device.

[2096] Step 6:

[2097] The user enters their desired conditions (e.g., vegetarian options, budget, etc.) on the app. The device organizes these conditions, converts them into JSON format, and sends them to the server. Specifically, it takes the data entered from the user interface, converts it into a specific format, and sends it to the server. The input is the desired conditions entered by the user, and the output is the JSON data sent to the server.

[2098] Step 7:

[2099] The server uses AI to select the most suitable restaurant based on the user's location information and desired conditions. Specifically, the received location information and desired conditions are input into an AI model, which then generates a list of the most suitable restaurants. The input is the location information and desired conditions received by the server, and the output is a list of the most suitable restaurants.

[2100] Step 8:

[2101] The recommendation results received from the server are displayed on the user terminal. Specifically, the user terminal analyzes the information sent from the server and displays it on the user interface. The input is the recommendation results sent by the server, and the output is a list of facilities and menus displayed on the user terminal.

[2102] Step 9:

[2103] The user selects a desired restaurant from the suggested restaurants and requests a reservation. The user terminal sends the selected restaurant information to the server and requests a reservation. Specifically, the system obtains the user's selection and sends a request to the server using the HTTP POST method. The input is the restaurant information selected by the user, and the output is a reservation request sent to the server.

[2104] Step 10:

[2105] The server sends a reservation request to the selected restaurant and receives confirmation. The result is then notified to the user's terminal. Specifically, the server sends a request to the restaurant's system, and once confirmation is received, it sends the information to the user's terminal. The input is the reservation request from the user, and the output is a notification of reservation confirmation.

[2106] Step 11:

[2107] Once a delivery order is confirmed, the server obtains delivery progress information in real time and notifies the user terminal. Specifically, it receives progress information from the delivery system, formats it, and sends it to the user. The input is progress information from the delivery system, and the output is a notification message to the user terminal.

[2108] Step 12:

[2109] The server generates discount information for restaurants that are about to close to reduce food waste and notifies the user. Specifically, the server generates food waste reduction information for specific time periods and notifies the user of it. The input is the store's business information and food waste reduction conditions, and the output is a discount information notification sent to the user's terminal.

[2110] Step 13:

[2111] The server stores the user's past reservation data and usage history, and the AI ​​learns the user's preferences. Specifically, past usage data is input into the AI ​​model, which analyzes the user's preferences and trends. The input is the user's past usage data, and the output is future recommendations based on the user's preferences.

[2112] 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.

[2113] ---

[2114] This invention is a system that allows users to efficiently find and reserve restaurants of their choice. This system is composed of a user terminal, a server, databases and real-time seat availability information provided by restaurants, and an emotion engine that recognizes the user's emotions.

[2115] Acquiring and sending location information

[2116] Device: When a user launches the app, the device uses its GPS to obtain its current location, which is then sent to the server in the form of latitude and longitude.

[2117] Example: A user starts a smartphone app and agrees to "Use current location." The app obtains the user's current location as "latitude: 35.6585, longitude: 139.7454" and sends this information to a server.

[2118] Obtaining information on nearby facilities

[2119] Server: Based on the received location information, the server retrieves a list of nearby restaurants from a database. This list includes basic information such as the restaurant name, location, and type.

[2120] Real-time collection of vacant seat information

[2121] Server: The server collects real-time seat availability information based on POS data and motion sensor information provided by each restaurant. This information is obtained via API, and the current seat availability status of each restaurant is revealed.

[2122] Example: Restaurant A has a POS system, and the data on the number of available seats is reported as "Currently, there are 5 seats available." The server obtains this information and prepares to provide it to the user.

[2123] Setting desired conditions

[2124] User: The user enters their desired conditions (e.g., non-smoking seat, private room, budget, etc.) on the app.

[2125] Terminal: Organize the entered desired conditions, convert them into JSON format, and send them to the server.

[2126] Emotion recognition by emotion engine

[2127] On the device: The emotion engine analyzes the user's facial expressions and voice to determine their current emotional state, which is classified into categories such as "happiness," "sadness," and "anger."

[2128] Example: A user accesses the emotion engine through a camera or microphone. The emotion engine identifies "happiness" from the user's facial expressions and voice, and sends this as an analysis result to the server.

[2129] Proposal of the best facility

[2130] Server: The server uses AI to select the most suitable restaurant based on the user's location, desired conditions, and emotional state. The AI ​​refers to this data and creates a list of restaurants that match the user's conditions and emotions.

[2131] Terminal: The terminal displays the restaurant recommendations received from the server t...

Claims

1. A means for obtaining location information of a user terminal; means for transmitting the acquired location information to a server; A means for the server to acquire information about surrounding facilities based on the location information; A means of collecting real-time seat availability information for each facility, A means for allowing a user to input desired conditions; A means to suggest the best facility based on desired conditions, a means of requesting reservations for the proposed facility; a means for the server to process reservation requests for the facility; A system including:

2. Generate discount information for reducing food waste for establishments that are about to close, including a means to notify users of discount information; The system of claim 1 .

3. Accumulates user's past usage data, including using AI to learn user preferences; The system of claim 1 .

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