System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting an image and extracting flower features; means for matching the extracted flower features with an existing flower database; means for inputting user preferences and event information; means for recommending an optimal bouquet combination based on the preferences and event information; means for generating floral language and messages based on the recommended bouquets; and means for displaying the recommended bouquets and messages to the user and accepting user selections.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] There is a problem that bouquets given for major life events tend to be uniform, making it difficult to create unique and memorable bouquets. Therefore, there is a need for a system that allows users to easily select a unique bouquet to impress the recipient for a special event. In addition, when selecting a bouquet, it is necessary to instantly suggest a combination of flowers that matches the user's preferences and the characteristics of the event, and to add the meaning of the flowers or an inspiring message to increase the value of the gift. [Means for solving the problem]

[0005] The system includes a means for inputting an image and extracting flower features, a means for comparing the extracted flower features with an existing flower database, a means for inputting a user's preferences and event information, a means for recommending an optimal bouquet combination based on the preferences and event information, a means for generating a flower language and a message based on the recommended bouquet, and a means for displaying the recommended bouquet and message to the user and accepting the user's selection. Furthermore, in recommending bouquets, a means for displaying multiple candidates and their respective image compatibility, and the generated flower language and message use natural language generation technology to generate moving poems and haiku, allowing the user to easily give the optimal bouquet and message for a special event.

[0006] "Input image" refers to the operation of uploading an image of a flower taken by the user to the system.

[0007] "Means for extracting flower features" refers to the process of analyzing and obtaining feature data such as shape, color, and texture from flower images.

[0008] The "existing flower database" is a database that stores information on a wide variety of flowers, including information on varieties, colors, availability, and flower meanings.

[0009] "Matching means" refers to the process of comparing extracted flower characteristics with information in an existing database to identify matching data.

[0010] "Means for inputting user preferences and event information" refers to the operation by which the user inputs individual information such as the type of event, favorite color, budget, etc. into the system.

[0011] "Means for recommending the optimal bouquet combination" refers to the process of using AI technology to suggest bouquet candidates that are most suitable for the user based on the user's input preferences and event information, as well as the results of database matching.

[0012] "Method of generating flower language and messages" refers to the process of creating an inspiring poem or haiku based on the selected bouquet, utilizing the language of flowers for each flower and natural language generation technology.

[0013] The "means for accepting user selection" refers to the interface and operation procedures for displaying recommended bouquets and messages to the user and allowing the user to make the optimal selection.

[0014] "Means for displaying image compatibility" refers to a process for displaying an evaluation index for each of the recommended bouquet candidates that visually indicates the compatibility with the user's preferences and the event.

[0015] "Natural language generation technology" refers to technology that allows computers to generate natural-sounding words and sentences, making it possible to generate moving poems and haiku. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The system of the present invention utilizes AI technology to customize and suggest bouquets to be given to users for specific events based on personal preferences and messages. Specific embodiments of the system are described in detail below.

[0038] 1. Image input and processing

[0039] Users take photos of flowers in a flower shop using a smartphone or tablet and upload them to the system. The images are sent to the server via a dedicated application or web interface. The server processes the received images, performing preprocessing such as noise reduction and resizing.

[0040] 2. Image feature extraction and database matching

[0041] The server extracts flower features from the pre-processed images, including shape, color, and texture. The extracted feature data is then compared with an existing flower database, which stores information such as variety, color, availability, and flower language, and the server identifies matching flowers.

[0042] 3. Enter your preferences and event information

[0043] The user inputs information such as the type of event, preferred colors, budget, etc. into the system. This information is entered into the terminal via the user interface and sent to the server.

[0044] 4. Recommendation of the best bouquet

[0045] The server uses AI technology to recommend the optimal bouquet combination based on the information entered by the user and the results of database comparison. Multiple bouquet candidates are generated and the image compatibility of each is displayed. The compatibility is a numerical value that indicates how well the bouquet fits the user's preferences and the event.

[0046] 5. Creating flower language and messages

[0047] Based on the selected bouquet, the server collects the meanings of flowers and uses natural language generation technology to generate moving poems and messages, further enhancing the value of the gift.

[0048] 6. Display of recommendation results and messages

[0049] The terminal displays the bouquet candidates and generated messages sent from the server to the user, and the user can choose the bouquet and message they like best from multiple options.

[0050] Specific examples

[0051] For example, if a user wants to choose a bouquet for Mother's Day, they first upload a photo of the flowers they took at a florist to the system. Next, they enter information about the Mother's Day event, their preferred colors, and their budget. The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. Finally, the device displays candidate bouquets and a message containing the meanings of the flowers to the user, who then selects the most suitable bouquet and confirms their order.

[0052] This allows users to easily choose a very unique and inspiring bouquet for a special event.

[0053] The processing flow will be explained below.

[0054] Step 1:

[0055] The user takes a photo of a flower in a flower shop using a smartphone or tablet, takes the photo through a dedicated application or web interface, and uploads it to the system.

[0056] Step 2:

[0057] The device receives the uploaded image, temporarily stores it, and performs pre-processing such as image noise reduction and resizing.

[0058] Step 3:

[0059] The device sends the preprocessed image to the server, which receives the image and performs image analysis to extract the flower's characteristics (shape, color, texture, etc.).

[0060] Step 4:

[0061] The server compares the extracted flower characteristics data with an existing flower database, which includes information such as variety, color, availability, and flower language, and generates a list of the best-matching flowers.

[0062] Step 5:

[0063] The user uses a dedicated form to enter information such as the type of event (e.g., birthday, Mother's Day, graduation, etc.), favorite colors, budget, etc. The entered information is sent to the server via the terminal.

[0064] Step 6:

[0065] The server uses AI technology to generate optimal bouquet combination candidates based on the user's input information and matching results. The server calculates the image compatibility of multiple bouquet candidates and sends the data to the device.

[0066] Step 7:

[0067] The device receives the data from the server and displays bouquet candidates and their image compatibility. The user can then choose the bouquet they like best from the multiple options displayed.

[0068] Step 8:

[0069] The server collects the meanings of the flowers based on the selected bouquet and uses natural language generation technology to generate an inspiring poem or message, which is then sent back to the device.

[0070] Step 9:

[0071] The terminal displays the generated message to the user, who then reviews the bouquet and message and makes a final selection.

[0072] Step 10:

[0073] The user selects the most suitable bouquet and message and confirms the order. The confirmed order is transmitted to the server via the terminal, and the information is finally sent to the florist.

[0074] This allows users to send a unique and inspiring bouquet that is perfect for a special event.

[0075] Example 1

[0076] 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."

[0077] Traditional flower bouquet selection methods have the drawback of making it difficult for users to choose a bouquet that best suits their preferences and the event. It's particularly difficult to understand information such as the type and color of flowers, as well as stock availability, making it time-consuming to find the perfect combination. It's even more difficult to choose a bouquet that includes a moving message, making it difficult to enhance the value of the gift.

[0078] 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.

[0079] In this invention, the server includes means for inputting an image and extracting flower characteristics, means for comparing the extracted flower characteristics with an existing flower database, means for inputting a user's preferences and event information, means for recommending an optimal bouquet combination based on the preferences and event information, means for performing image preprocessing such as noise reduction and size adjustment, means for generating a flower meaning and message based on the recommended bouquet, means for generating an inspiring message using natural language generation technology, means for displaying the recommended bouquet and message to the user and accepting the user's selection, and means for displaying multiple candidates and their respective image suitability. This allows the user to easily select the optimal bouquet based on their preferences or a specific event, and further enhances the value of the bouquet as a gift by adding an inspiring message.

[0080] "Means for inputting an image and extracting flower characteristics" refers to a technology that analyzes a flower image provided by a user and extracts characteristics such as the type, color, shape, and texture of the flower from the image.

[0081] "Means for matching extracted flower characteristics with existing flower databases" refers to technology that uses extracted flower characteristic data to compare and match with information in existing flower databases that have been registered in advance.

[0082] "Means for inputting user preferences and event information" refers to the technology that allows users to input their preferences and specific event information (such as birthdays, weddings, Mother's Day, etc.) through an input form and transmit this information to the system.

[0083] "Means for recommending optimal bouquet combinations based on preferences and event information" refers to technology that uses AI technology to suggest multiple optimal bouquet combinations based on input user preferences and event information and database information.

[0084] "Means for noise removal and size adjustment as image preprocessing" refers to technology that removes noise from images and resizes them to an appropriate size to make images uploaded by users easier to analyze.

[0085] "Means for generating flower meanings and messages based on recommended bouquets" refers to technology that collects related flower meanings based on the proposed bouquet combination and generates a matching message or poem.

[0086] "Means for generating inspirational messages using natural language generation technology" refers to technology that utilizes natural language generation technology, such as a generative AI model, to automatically create inspirational messages or poems related to a specific bouquet of flowers.

[0087] "Means for displaying recommended bouquets and messages to the user and accepting the user's selection" refers to a technology in which the system displays the bouquet combinations suggested by the system and the generated message on the user's device, allowing the user to make the optimal selection and have it accepted by the system.

[0088] "Means for displaying multiple candidates and their respective image suitability" refers to a technology that visually displays multiple bouquet combination candidates and the suitability that indicates how well each bouquet suits the user's preferences or the event.

[0089] The present invention is a system that uses AI technology to customize and suggest bouquets to send to users for specific events based on personal preferences and messages. This system can be implemented using various hardware and software described below.

[0090] First, a user takes a photo of a particular flower at a florist using a smartphone or tablet, and then uploads the image to the server via a dedicated application or web interface, which sends the user's input data and image data to the server.

[0091] The server preprocesses the received images by removing noise and adjusting the size. For example, an image processing library such as OpenCV can be used for this process. Next, features such as color, shape, and texture are extracted from the preprocessed images. Deep learning techniques such as Convolutional Neural Network (CNN) can be used for this process.

[0092] The extracted feature data is compared with the flower database stored in the system, which stores detailed information about each flower, such as its variety, color, stock status, and flower language. The server compares the data with the database information to identify similar flowers.

[0093] Next, the user provides the system with personal information such as the type of event (e.g., birthday, wedding, Mother's Day, etc.), favorite colors, and budget through an input form. This information is sent from the terminal to the server.

[0094] The server uses an AI algorithm to recommend the optimal bouquet combination based on the user's preferences, event information, and matching results. Using collaborative filtering and recommender system techniques, multiple bouquet candidates are automatically generated and the image compatibility of each is calculated. Compatibility can be displayed using numerical scores or visual graphs.

[0095] The server then collects relevant flower meanings based on the recommended bouquet information and uses natural language generation technology (e.g., a generative AI model such as GPT-3) to generate an inspiring message, which can include a poem or a congratulatory message.

[0096] Finally, the terminal displays the bouquet options sent from the server and the generated message to the user, who can then choose the one they like best and place the order immediately.

[0097] Specific examples

[0098] For example, if a user wants to choose a bouquet for Mother's Day, they first upload a photo of the flowers they took at a florist to the system. Next, they enter the event information, "Mother's Day," along with their preferred colors (e.g., pink or white) and budget (e.g., under 5,000 yen). The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. Finally, the device displays candidate bouquets and a message containing the flower meanings to the user, who then selects the most suitable bouquet and confirms their order.

[0099] Prompt Sentence Examples

[0100] "I'd like to choose an inspiring bouquet for Mother's Day. I'd like to focus on pink flowers and keep the budget under 5,000 yen."

[0101] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0102] Step 1: Image Input and Preprocessing

[0103] Users upload photos of flowers taken at a florist to the system via a dedicated application or a web interface, and the terminal then sends the image data to the server.

[0104] The server performs noise reduction and size adjustment on the received image. Specifically, it uses OpenCV to remove noise and resize it to an appropriate size. As a result, the input is the flower image taken by the user, and the output is the preprocessed image.

[0105] Step 2: Image feature extraction and database matching

[0106] The server extracts features such as color, shape, and texture from the preprocessed image using a Convolutional Neural Network (CNN). The extracted feature data is then compared with the system's flower database.

[0107] Specifically, we generate a feature vector for each image and compare it with the feature vectors in the database. From this comparison, the input is the preprocessed image, and the output is the information on similar flowers.

[0108] Step 3: Enter your user information

[0109] The user provides information such as the type of event (e.g., birthday, wedding, Mother's Day), preferred colors, and budget to the system through an input form.

[0110] The terminal transmits this user information to the server in real time. The input is event information and preference data from the user, and the output is the user information transmitted to the server.

[0111] Step 4: Recommend the perfect bouquet

[0112] The server uses AI algorithms to generate the optimal bouquet combination based on the user's preferences, event information, and matching results, using collaborative filtering and recommender system techniques.

[0113] Specifically, multiple bouquet candidates are generated from the collected feature data and user information, and the image compatibility of each is calculated. The input is user information and feature data, and the output is bouquet candidates and compatibility.

[0114] Step 5: Creating the flower language and message

[0115] The server collects relevant flower meanings based on the recommended bouquet information and generates an inspirational message using a generative AI model (e.g., GPT-3).

[0116] Specifically, the system selects the flower language based on the combination of flowers in the bouquet and generates a message using natural language generation technology. The input is the bouquet information, and the output is the generated message.

[0117] Step 6: View and select recommendations

[0118] The terminal displays the bouquet candidates sent from the server and the generated message to the user, who then selects the bouquet he or she likes best and confirms the order.

[0119] Specifically, it displays bouquets and messages on the terminal screen and provides a selectable interface. The input is bouquet candidates and messages, and the output is the user's selection.

[0120] (Application example 1)

[0121] 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."

[0122] Conventional bouquet selection systems have the problem that they do not allow sufficient customization or personalization when users select the perfect bouquet for a specific event or preference. Also, the process of delivering the created bouquet and message is time-consuming, which makes it inconvenient for users.

[0123] 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.

[0124] In this invention, the server includes means for inputting an image and extracting flower characteristics, means for comparing the extracted flower characteristics with an existing flower database, means for inputting a user's preferences and event information, means for recommending an optimal bouquet combination based on the preferences and event information, means for generating a flower meaning and a message based on the recommended bouquet, means for displaying the recommended bouquet and message to the user and accepting the user's selection, and means for coordinating with an external delivery system to deliver the selected bouquet. This allows the user to easily select a customized bouquet according to a specific event or preference, and then have the bouquet delivered quickly.

[0125] The "means for inputting images" is a mechanism for users to upload photos of flowers they have taken to the system.

[0126] The "means for extracting flower characteristics" is a technology for analyzing information such as flower shape, color, and texture from uploaded images.

[0127] "Means for matching with an existing flower database" refers to a technique for comparing extracted feature information with information on flowers registered in a database to identify matching flowers.

[0128] The "means for inputting user preferences and event information" refers to an interface that allows a user to input information about their preferences and specific events, such as color preferences and budget, into the system.

[0129] "Means for recommending the best bouquet combination" refers to a technology in which AI recommends the best combination of flowers based on the information entered by the user and the matching results.

[0130] The "means for generating flower meanings and messages" is a technology that automatically generates flower meanings and moving messages based on recommended bouquets.

[0131] The "means for displaying to the user and accepting the user's selection" is an interface that visually displays the recommended bouquet and the generated message to the user, allowing the user to make the optimal selection.

[0132] The "means for coordinating with an external delivery system" is a technology for communicating with and coordinating with an external delivery service in order to deliver the selected bouquet to the specified location.

[0133] The system of the present invention utilizes AI technology to customize and suggest bouquets to send to users for specific events based on personal preferences and messages. This system is realized by combining the following components:

[0134] 1. Image input and processing

[0135] Users take photos of flowers using a smartphone or tablet and upload them to the server via a dedicated application. The server receives the images and performs preprocessing such as noise reduction and resizing.

[0136] 2. Image feature extraction and database matching

[0137] The server extracts flower features (shape, color, texture, etc.) from the preprocessed images. The extracted features are matched with an existing flower database, which includes information such as flower variety, color, availability, and flower language.

[0138] 3. Enter your preferences and event information

[0139] The user inputs information such as the type of event (e.g., Mother's Day), favorite colors, budget, etc. This information is sent to the server via a dedicated application.

[0140] 4. Recommendation of the best bouquet

[0141] The server uses AI technology to recommend the most suitable bouquet based on the results of matching the user's input information with image features. Multiple candidates are generated and the image compatibility of each is displayed. This compatibility is a numerical representation of how well the flower characteristics match the user's preferences and event information.

[0142] 5. Creating flower language and messages

[0143] Based on the selected bouquet, the server uses natural language generation technology to gather the language of flowers and generate an inspiring message, which will further enhance the value of the gift.

[0144] 6. Display of recommendation results and messages

[0145] The terminal displays the bouquet candidates and generated messages sent from the server to the user, and the user can choose the bouquet and message they like best from multiple options.

[0146] 7. Integration with external systems for delivery

[0147] The server connects to an external delivery system to deliver the bouquet selected by the user, so that the selected bouquet is quickly delivered to the specified location.

[0148] Examples of hardware and software used:

[0149] Hardware: smartphones, tablets, servers

[0150] Software: Python, TensorFlow (AI model), Django (web framework), React Native (mobile application)

[0151] Examples:

[0152] For example, if a user wants to choose a bouquet to give for Mother's Day, they first upload a photo of the flowers they took at a florist to the server via a dedicated application. Next, they enter information about the event, "Mother's Day," their preferred colors, and their budget. The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate the optimal bouquet combination, calculates the image compatibility of each, and displays it. The user then reviews the bouquet candidates and messages containing the flower meanings, selects the most suitable bouquet, and confirms their order. The selected bouquet is then quickly delivered in conjunction with an external delivery system.

[0153] Example prompt sentence:

[0154] I'd like to choose a bouquet to give for Mother's Day. I like pink roses, and my budget is under 5,000 yen. What kind of bouquet would you recommend?

[0155] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0156] Step 1:

[0157] Users take photos of flowers using a smartphone or tablet and upload the images to the server via a dedicated application. The input is the image of the flower, and the output is the image data sent to the server. Specifically, the user presses the "upload image" button in the application, selects the image they have taken, and uploads it.

[0158] Step 2:

[0159] The server performs preprocessing on the received image data. This preprocessing includes noise removal and size adjustment. The input is the image data sent by the user, and the output is preprocessed, clear image data. Specifically, the server uses a Python library to remove noise and adjust the size of the image.

[0160] Step 3:

[0161] The server uses an AI model (e.g., a deep learning model using TensorFlow) to extract flower features from preprocessed images. The input is the preprocessed image data, and the output is feature data such as shape, color, and texture. Specifically, the server runs an image analysis algorithm to extract features.

[0162] Step 4:

[0163] The server matches the extracted features with an existing flower database. The input is the flower feature data, and the output is the matching flower information in the database. Specifically, it compares the feature data with entries in the database and uses SQL queries to find the best match.

[0164] Step 5:

[0165] The user inputs information such as event information (e.g., Mother's Day), favorite colors, and budget into the system via a terminal. The input is the event information and favorite data, and the output is request data that includes this information. Specifically, the user enters the required information into the application's input fields and presses the "Submit" button.

[0166] Step 6:

[0167] The server uses AI technology to recommend the most suitable bouquet based on the information entered by the user and the results of matching image features. The input is the user's event information and feature data, and the output is a list of suitable bouquet candidates. Specifically, it uses a machine learning algorithm to generate the optimal bouquet and calculates the suitability of each candidate.

[0168] Step 7:

[0169] The server generates a flower language and message based on the sponsored bouquet using natural language generation technology (e.g., a generative AI model). The input is information about the selected bouquet, and the output is an inspiring message. Specifically, the server generates the message using a natural language generation algorithm.

[0170] Step 8:

[0171] The terminal displays the bouquet candidate list sent from the server and the generated message to the user. The input is the bouquet candidate and the message, and the output is the screen displayed on the terminal. Specifically, the candidate list and the message are visually displayed through the user interface (UI).

[0172] Step 9:

[0173] The user selects the bouquet and message they like best from multiple options and confirms the order. The input is the user's selection data, and the output is the order confirmation data. Specifically, the user presses the "Select a bouquet" button in the application, selects the desired bouquet and message, and confirms the order.

[0174] Step 10:

[0175] The server works with an external delivery system to deliver the selected bouquet. The input is order confirmation data, and the output is delivery request data. Specifically, the server calls the API of the delivery service and issues instructions to deliver the selected bouquet.

[0176] 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.

[0177] The system of the present invention utilizes AI technology and an emotion engine to customize and suggest bouquets to be given to users for specific events based on their personal preferences and emotions. Specific embodiments of the system are described in detail below.

[0178] 1. Image input and processing

[0179] Users take photos of flowers in a flower shop using a smartphone or tablet and upload the images to the system via a dedicated application or web interface. The device receives the images and performs preprocessing such as noise reduction and size adjustment. The preprocessed images are then sent to the server.

[0180] 2. Image feature extraction and database matching

[0181] The server extracts flower features from the preprocessed images and matches this feature data with an existing flower database, which contains information such as flower variety, color, availability, and flower language. The server generates a list of matching flowers.

[0182] 3. Enter your preferences and event information

[0183] The user inputs information into the system, such as the type of event, preferred colors, budget, etc. This information is sent to the server via the terminal.

[0184] 4. Emotion Recognition by Emotion Engine

[0185] The device analyzes the user's facial expressions and voice to recognize the user's emotions. The camera is used for facial recognition and the microphone is used for voice analysis. The recognized emotion data is sent to the server.

[0186] 5. Bouquet Recommendation

[0187] The server uses AI technology to generate optimal bouquet combination candidates based on the user's emotions, preferences, event information, and database matching results. Multiple bouquet candidates are generated and their image compatibility is calculated. The data is then sent to the device.

[0188] 6. Creating flower language and messages

[0189] Based on the selected bouquet, the server collects the flower language and uses natural language generation technology to generate an inspiring poem or message, customizing the message content based on the user's recognized emotions.

[0190] 7. Displaying recommended results and messages

[0191] The terminal receives the data from the server and displays the bouquet candidates, their image compatibility, and the generated message to the user. The user can then choose the bouquet they like best from the displayed multiple options.

[0192] Specific examples

[0193] For example, if a user wants to choose a bouquet for Mother's Day, they first upload a photo of the flowers they took at a florist to the system. Next, they enter information about the Mother's Day event, their preferred colors, and their budget. The device analyzes the user's facial expressions and voice to collect emotional data. The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. The server also generates an inspiring poem or message based on the user's emotional data and sends it to the device. Finally, the device displays bouquet options and messages to the user, who then selects the most suitable bouquet and confirms their order.

[0194] This allows users to send a unique and moving bouquet that is perfect for a special event. In addition, by utilizing the emotion engine, it is possible to make suggestions that are more suited to the user's current emotions.

[0195] The processing flow will be explained below.

[0196] Step 1:

[0197] The user takes a photo of a flower in a flower shop using a smartphone or tablet, takes the photo through a dedicated application or web interface, and uploads it to the system.

[0198] Step 2:

[0199] The device receives the uploaded image, temporarily stores the image, and performs preprocessing such as noise reduction and size adjustment.

[0200] Step 3:

[0201] The device sends the preprocessed image to the server, which receives the image and performs image analysis.

[0202] Step 4:

[0203] The server extracts flower features from the image, analyzing and obtaining data such as the flower's shape, color, and texture.

[0204] Step 5:

[0205] The server compares the extracted flower characteristics with an existing flower database, which includes information such as variety, color, availability, and flower language. The result is a list of matching flowers.

[0206] Step 6:

[0207] The user uses a dedicated form to enter information such as the type of event (e.g., birthday, Mother's Day, graduation, etc.), favorite colors, budget, etc. The entered information is sent to the server via the terminal.

[0208] Step 7:

[0209] The device analyzes the user's facial expressions and voice to collect emotional data. The camera is used for facial expression analysis, and the microphone is used for voice analysis.

[0210] Step 8:

[0211] The device sends the collected emotional data to a server, which then analyzes and determines the user's emotional state.

[0212] Step 9:

[0213] The server generates optimal bouquet combination candidates based on the user's preferences, event information, emotional data, and database matching results. AI technology is used to calculate multiple bouquet candidates and their image compatibility.

[0214] Step 10:

[0215] The server generates a message based on the selected bouquet, including the meaning of flowers, a moving poem, and a message, and customizes the message based on the user's emotional data.

[0216] Step 11:

[0217] The terminal displays the bouquet candidates, image compatibility, and the generated message to the user, who can then choose the bouquet they like best from the displayed multiple options.

[0218] Step 12:

[0219] The user selects the most suitable bouquet and message and confirms the order. The confirmed order is transmitted to the server via the terminal, and the information is finally sent to the florist.

[0220] Through this process, users can easily select the perfect bouquet for a special event and send it with an inspiring message.By using the emotion engine, suggestions can be made that are more suited to the user's current emotions.

[0221] Example 2

[0222] 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."

[0223] Conventional bouquet selection systems could suggest bouquets based on a user's personal preferences and event information, but it was difficult to suggest the optimal bouquet and message that took the user's emotions into consideration. This meant that it was not possible to provide bouquets and messages that better matched the user's emotions for special events, resulting in a problem of reduced user satisfaction.

[0224] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for inputting an image and extracting flower characteristics, means for comparing the extracted flower characteristics with an existing flower database, means for inputting a user's preferences and event information, means for recommending an optimal bouquet combination based on the preferences and event information, means for acquiring user emotion data using emotion recognition technology, means for customizing the bouquet and message content using the emotion data, means for generating a flower meaning and message based on the recommended bouquet, and means for displaying the recommended bouquet and message to the user and accepting the user's selection. This makes it possible to propose an optimal bouquet and provide an inspiring message that takes the user's emotions into consideration.

[0225] "Means for inputting an image and extracting flower characteristics" refers to a technology that allows a user to upload a photo of a flower they have taken to the system and recognize characteristics such as the flower variety, color, and shape from the image.

[0226] "Means for matching extracted flower characteristics with existing flower databases" refers to technology for comparing extracted flower characteristic data with data in existing flower databases and identifying matching flower types and information.

[0227] The "means for inputting user preferences and event information" is an interface that allows the user to input personal information such as the type of event, favorite colors, budget, etc., into the system.

[0228] "Means for recommending optimal bouquet combinations based on preferences and event information" refers to a system that uses AI technology to suggest multiple bouquet combinations based on user input data.

[0229] "Means for acquiring user emotional data using emotion recognition technology" refers to technology that uses a camera or microphone to analyze the user's facial expressions and voice and recognize their emotional state.

[0230] The "means for customizing the bouquet and message content using emotional data" is a system for individually adjusting the bouquet combination and message content based on the acquired emotional data.

[0231] The "means for generating flower meanings and messages based on recommended bouquets" refers to a technology for collecting flower meanings related to the flowers based on the type of bouquet proposed, and then generating a message using natural language generation technology.

[0232] The "means for displaying recommended bouquets and messages to the user and accepting the user's selection" is an interface that displays suggested bouquet candidates and related messages to the user via the terminal, allowing the user to select the most suitable bouquet.

[0233] The system of the present invention utilizes AI technology and an emotion engine to customize bouquets to be given to users on special occasions based on their personal preferences and emotions, and makes optimal suggestions. Specific embodiments of the system are described below.

[0234] The main processing of the system is performed using the following hardware and software.

[0235] Hardware: smartphones, tablets, cameras, microphones

[0236] Software: Dedicated applications, web interfaces, image processing algorithms, AI technology, natural language generation technology

[0237] First, a user takes a photo of a flower using a smartphone or tablet. The image is then uploaded to the system via a dedicated application or web interface. The device receives the image and performs preprocessing such as noise reduction and size adjustment. The preprocessed image is then sent to the server.

[0238] The server then extracts flower features from the preprocessed image, such as the flower's variety, color, shape, etc. The feature data is then matched against an existing flower database to generate a list of matching flowers.

[0239] The user then inputs information such as the type of event (e.g., Mother's Day), favorite colors, budget, etc. This information is sent to the server via the terminal.

[0240] Furthermore, the device uses a camera to capture the user's facial expressions and a microphone to record their voice. These are analyzed to extract the user's emotional data, which is then sent to the server.

[0241] Next, the server uses AI technology to generate the optimal bouquet combination based on the user's emotional data, preferences, event information, and image feature extraction results. Multiple bouquet candidates are generated and the image compatibility of each is calculated. This data is then sent to the device.

[0242] The server then collects the meanings of the flowers in the selected bouquet and uses natural language generation technology to generate moving poems and messages, taking into account the emotional data.

[0243] Finally, the device receives the data sent from the server and displays the bouquet candidates, image compatibility, and the generated message to the user. The user can then choose the bouquet they like best from multiple options.

[0244] As a concrete example, if a user wants to choose a bouquet for Mother's Day, they would follow these steps: The user uploads a photo of flowers taken at a florist to the system and enters information about the Mother's Day event, as well as their preferred colors and budget. The device collects the user's emotional data using facial recognition and voice analysis, and the server analyzes the image and compares it with a database to identify available flowers. The server then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. The server also generates an inspiring poem or message based on the user's emotional data and sends this to the device. Finally, the device displays candidate bouquets and messages to the user, who then selects the most suitable bouquet and confirms their order.

[0245] This system allows users to send personalized and inspiring bouquets perfect for special occasions, and by utilizing an emotion engine, it can make suggestions that better suit the user's current emotions.

[0246] An example of a prompt sentence is, "Please suggest a bouquet of pink and white flowers for Mother's Day within a budget of 5,000 yen. My mother likes a message that shows gratitude." Based on this prompt sentence, the system generates the optimal bouquet and message and suggests them to the user.

[0247] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0248] Step 1: Image Input and Preprocessing

[0249] A user takes a photo of a flower with a smartphone or tablet and uploads the image to the system through a dedicated application or web interface. The input is the flower image uploaded by the user. The device receives this image and performs preprocessing such as noise removal and size adjustment. The output is the preprocessed image. This preprocessing results in image data that is easy to analyze.

[0250] What it does: The user presses the "Take a photo of a flower" button in the app, then taps the "Upload" button after taking the photo. The device then analyzes the photo, removes unwanted noise, and resizes the image appropriately.

[0251] Step 2: Image feature extraction and database matching

[0252] The server extracts flower features from the preprocessed image. The input is the preprocessed image. The server uses image processing algorithms to extract feature data such as flower color, shape, and texture. The output is the extracted feature data. This feature data is then matched against an existing flower database. It is compared with the flower information in the database and a list of matching flowers is generated. The output is a list of matching flowers.

[0253] How it works: The server uses image processing algorithms to extract features such as color histogram and shape from the input image, and then compares that information with database entries to find a match.

[0254] Step 3: Enter your user information

[0255] The user inputs information such as the type of event (e.g., Mother's Day), favorite colors, and budget into the system. The input is the event information and favorite data entered by the user. The terminal receives this information and sends it to the server. The output is the user information sent to the server. This information becomes the basic data for recommending a bouquet that meets the user's request.

[0256] Specific operation: The user enters information such as "Mother's Day," "pink and white," and "budget 5,000 yen" into the form within the app and taps the "Submit" button. The device acquires the information and sends it to the server.

[0257] Step 4: Emotion Recognition with the Emotion Engine

[0258] The device uses a camera to capture the user's facial expression and a microphone to record the audio. The input is the video and audio data of the user's facial expression. These are analyzed to extract the user's emotional data. The output is the extracted emotional data. This emotional data is sent to the server.

[0259] How it works: When a user turns on the facial recognition feature, the camera captures a few seconds of the user's facial expressions. The microphone also records the user's speech. This data is analyzed to identify emotions such as "happiness," "sadness," and "excitement."

[0260] Step 5: Recommend the bouquet

[0261] The server uses AI technology to generate the optimal bouquet combination based on the user's emotional data, preferences, event information, and image feature extraction results. The inputs are emotional data, user preference information, event information, and image feature extraction results. Multiple bouquet candidates are generated and the image compatibility of each is calculated. The output is a list of bouquet candidates and their image compatibility. This data is sent to the device.

[0262] How it works: The AI ​​model analyzes the user's input data, generates multiple candidates, such as "a bouquet of pink carnations and white roses" and "a bouquet of pink and white tulips," and calculates the suitability of each candidate (for example, a score such as "90%" or "85%).

[0263] Step 6: Creating the flower language and message

[0264] Based on the selected bouquet, the server collects the language of flowers contained in the bouquet. The input is a list of candidate bouquets and their information. An inspiring poem or message is generated using natural language generation technology. The generated message is customized taking into account the emotional data. The output is the generated message. This message is sent to the device.

[0265] Specific operation: The server looks up the meaning of flowers, such as "carnation (love)" or "rose (love)," and generates a message such as "We present a beautiful bouquet to your mother with our love and gratitude."

[0266] Step 7: Viewing Recommendations and Messages

[0267] The terminal receives data from the server and displays recommended bouquet candidates, image compatibility, and a generated message to the user. The input is the bouquet candidate list sent from the server and the generated message. The output is the bouquet candidates and message displayed to the user. The user can choose the bouquet they like best from multiple options.

[0268] Specific behavior: The device displays options to the user, such as "Bouquet of pink carnations and white roses (suitability: 90%)," and displays a generated message for each option. The user taps the "Select" button to choose the best bouquet.

[0269] (Application example 2)

[0270] 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."

[0271] Currently, there is a lack of means to recommend optimal items based on a user's preferences, emotions, and event information, and to generate customized messages for those items. Furthermore, there are no systems that can accurately convert a user's voice input into text or identify emotions from facial expressions. This makes it difficult to provide services that truly match a user's emotions and preferences.

[0272] 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.

[0273] In this invention, the server includes means for inputting an image and extracting features of an object, means for comparing the extracted features with an existing database, means for inputting a user's preferences and event information, means for recommending an optimal combination of items based on the input information, means for generating a customized message based on the recommended items, means for displaying the recommended items and message to the user and accepting the user's selection, means for collecting the user's voice input and converting the voice data into text, and means for capturing the user's facial expressions and identifying emotions from the expressions, thereby making it possible to provide more appropriate and personalized services based on the user's emotions and preferences.

[0274] "Means for inputting images" refers to the function of capturing images using an electronic device such as a camera or scanner and loading them into the system.

[0275] "Means for extracting the characteristics of an object" is a function that analyzes attributes such as the shape, color, and texture of an object from an input image and extracts them as data.

[0276] "Means for matching with existing databases" refers to a function that compares extracted feature data with existing data in the system to identify matching or similar items.

[0277] The "means for inputting user preferences and event information" is an interface for inputting information about the user's favorite elements and events (for example, favorite color, budget, type of event).

[0278] The "means for recommending the most suitable combination of items" is a function that suggests the most suitable combination of items based on the information input by the user and the collation results.

[0279] The "means for generating a customized message" is a function that uses natural language generation technology to create a message related to the recommended item.

[0280] The "means for displaying to the user and accepting selection" is an interface that displays the recommended items and generated messages to the user and allows the user to select the desired items.

[0281] The "means for collecting voice input and converting voice data into text" is a function for recording the user's voice, analyzing the voice data, and converting it into text information.

[0282] The "means for capturing facial expressions and identifying emotions from facial expressions" is a function that uses a camera to capture the user's facial expressions and analyzes the image data to identify the user's emotions.

[0283] The system according to the present invention is a system that recommends a customized menu based on personal preferences and emotions when a user uses a food delivery service. The system includes the following means.

[0284] Hardware and Software

[0285] 1. Camera-equipped smartphone

[0286] Camera: Used to capture the user's face and analyze facial expressions.

[0287] Microphone: Used to collect the user's voice input.

[0288] 2. Server

[0289] Computational resources: process image and audio data, run AI models, and match data against databases.

[0290] Framework: We use TensorFlow and Keras to run our emotion recognition and natural language generation models.

[0291] 3. Cloud Database

[0292] Stores and manages user profiles, menu data, emotion data, etc.

[0293] System action

[0294] 1. Image input and feature extraction

[0295] When a user takes a picture of their face using their smartphone camera, the system captures this image. Then, using TensorFlow and Keras, it identifies emotions from facial expressions. For example, if a user smiles into the smartphone camera, the system detects the emotion "happiness."

[0296] 2. Voice to text conversion

[0297] When a user speaks into the microphone about their desired menu or event information, the voice data is converted into text using the SpeechRecognition library. For example, if a user types "I'd like a healthy lunch, please," this is sent as text data to the server.

[0298] 3. Database matching and item recommendation

[0299] The server compares the menu data stored in the cloud database with the user's input information and emotional data, and then recommends the menu that best suits the user's situation and emotions. For example, it recommends a "healthy lunch" and salads and fruits that best suit the emotion of "joy."

[0300] 4. Customized Message Generation

[0301] Based on the recommended menu, natural language generation technology is used to generate an inspiring message, such as "Enjoy a healthy lunch and an energetic afternoon."

[0302] 5. Display and selection reception

[0303] Finally, the recommended menu and customized message sent from the server are displayed on the smartphone, and the user selects the most suitable menu and confirms the order.

[0304] Specific examples

[0305] If a user is wondering what to order at a lunch meeting, the following process takes place:

[0306] 1. The camera captures the user's facial expression, and the system recognizes the emotion as "nervous."

[0307] 2. The user dictates, "What are your food recommendations for a lunch meeting?"

[0308] 3. The speech is converted to text and sent to the server along with the user's preferences and event information.

[0309] 4. The server analyzes this and recommends an appropriate menu item, such as a light sandwich or salad.

[0310] 5. A customized message is generated, such as "Enjoy a relaxing lunch meeting with this sandwich."

[0311] Prompt Sentence Examples

[0312] "What's the best food for a lunch meeting?"

[0313] "Do you have any menu suggestions for Mother's Day dinner?"

[0314] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0315] Step 1:

[0316] A user takes a picture of their face using the smartphone camera. The input is the user's face image, and the output is the captured image data. The camera detects the user's face and sends the image data to the device.

[0317] Step 2:

[0318] The device sends the captured image data to the processing module for preprocessing for facial expression recognition. Preprocessing includes noise reduction and size adjustment. The input is the captured image data, and the output is the preprocessed image data.

[0319] Step 3:

[0320] The device sends the preprocessed image data to the server and requests emotion recognition. The server uses TensorFlow and Keras to identify emotions from facial expressions. The recognized emotion data is output.

[0321] Step 4:

[0322] The user speaks the desired menu or event information into the smartphone's microphone. The input is voice data, and the output is recorded voice data. The microphone captures the voice and sends the voice data to the terminal.

[0323] Step 5:

[0324] The device converts the recorded voice data into text data using the SpeechRecognition library. The input is voice data and the output is text data. If recognition is successful, the voice data is converted into text format.

[0325] Step 6:

[0326] The terminal sends the text data to the server and stores it as user preference and event information. The input is text data, and the output is preference information and event information stored in the server's database.

[0327] Step 7:

[0328] The server compares the menu data stored in the cloud database with the user's preference and emotion data. As a result of the comparison, optimal menu candidates are generated. The input is preference and emotion data, and the output is a recommended menu.

[0329] Step 8:

[0330] The server generates a customized message based on the generated recommended menu using natural language generation technology. The input is the recommended menu information, and the output is the customized message. The message is intended to make the menu received by the user more meaningful.

[0331] Step 9:

[0332] The server sends the recommended menu and customized message to the terminal. The input is the recommended menu and message data, and the output is the information displayed on the display screen of the terminal.

[0333] Step 10:

[0334] The terminal displays the recommended menu and customized message received from the server to the user. The user selects the menu they like best from the displayed multiple options. The input is the recommended menu and message data, and the output is the user's selection.

[0335] Step 11:

[0336] When the user selects the most suitable menu item, the terminal sends the selection information to the server, and the order is confirmed. The input is the user's selection data, and the output is order confirmation data from the server.

[0337] 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.

[0338] 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.

[0339] 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.

[0340] [Second embodiment]

[0341] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0342] 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.

[0343] 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).

[0344] 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.

[0345] 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.

[0346] 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).

[0347] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0348] 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.

[0349] 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.

[0350] 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.

[0351] 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.

[0352] 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."

[0353] The system of the present invention utilizes AI technology to customize and suggest bouquets to be given to users for specific events based on personal preferences and messages. Specific embodiments of the system are described in detail below.

[0354] 1. Image input and processing

[0355] Users take photos of flowers in a flower shop using a smartphone or tablet and upload them to the system. The images are sent to the server via a dedicated application or web interface. The server processes the received images, performing preprocessing such as noise reduction and resizing.

[0356] 2. Image feature extraction and database matching

[0357] The server extracts flower features from the pre-processed images, including shape, color, and texture. The extracted feature data is then compared with an existing flower database, which stores information such as variety, color, availability, and flower language, and the server identifies matching flowers.

[0358] 3. Enter your preferences and event information

[0359] The user inputs information such as the type of event, preferred colors, budget, etc. into the system. This information is entered into the terminal via the user interface and sent to the server.

[0360] 4. Recommendation of the best bouquet

[0361] The server uses AI technology to recommend the optimal bouquet combination based on the information entered by the user and the results of database comparison. Multiple bouquet candidates are generated and the image compatibility of each is displayed. The compatibility is a numerical value that indicates how well the bouquet fits the user's preferences and the event.

[0362] 5. Creating flower language and messages

[0363] Based on the selected bouquet, the server collects the meanings of flowers and uses natural language generation technology to generate moving poems and messages, further enhancing the value of the gift.

[0364] 6. Display of recommendation results and messages

[0365] The terminal displays the bouquet candidates and generated messages sent from the server to the user, and the user can choose the bouquet and message they like best from multiple options.

[0366] Specific examples

[0367] For example, if a user wants to choose a bouquet for Mother's Day, they first upload a photo of the flowers they took at a florist to the system. Next, they enter information about the Mother's Day event, their preferred colors, and their budget. The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. Finally, the device displays candidate bouquets and a message containing the meanings of the flowers to the user, who then selects the most suitable bouquet and confirms their order.

[0368] This allows users to easily choose a very unique and inspiring bouquet for a special event.

[0369] The processing flow will be explained below.

[0370] Step 1:

[0371] The user takes a photo of a flower in a flower shop using a smartphone or tablet, takes the photo through a dedicated application or web interface, and uploads it to the system.

[0372] Step 2:

[0373] The device receives the uploaded image, temporarily stores it, and performs pre-processing such as image noise reduction and resizing.

[0374] Step 3:

[0375] The device sends the preprocessed image to the server, which receives the image and performs image analysis to extract the flower's characteristics (shape, color, texture, etc.).

[0376] Step 4:

[0377] The server compares the extracted flower characteristics data with an existing flower database, which includes information such as variety, color, availability, and flower language, and generates a list of the best-matching flowers.

[0378] Step 5:

[0379] The user uses a dedicated form to enter information such as the type of event (e.g., birthday, Mother's Day, graduation, etc.), favorite colors, budget, etc. The entered information is sent to the server via the terminal.

[0380] Step 6:

[0381] The server uses AI technology to generate optimal bouquet combination candidates based on the user's input information and matching results. The server calculates the image compatibility of multiple bouquet candidates and sends the data to the device.

[0382] Step 7:

[0383] The device receives the data from the server and displays bouquet candidates and their image compatibility. The user can then choose the bouquet they like best from the multiple options displayed.

[0384] Step 8:

[0385] The server collects the meanings of the flowers based on the selected bouquet and uses natural language generation technology to generate an inspiring poem or message, which is then sent back to the device.

[0386] Step 9:

[0387] The terminal displays the generated message to the user, who then reviews the bouquet and message and makes a final selection.

[0388] Step 10:

[0389] The user selects the most suitable bouquet and message and confirms the order. The confirmed order is transmitted to the server via the terminal, and the information is finally sent to the florist.

[0390] This allows users to send a unique and inspiring bouquet that is perfect for a special event.

[0391] Example 1

[0392] 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."

[0393] Traditional flower bouquet selection methods have the drawback of making it difficult for users to choose a bouquet that best suits their preferences and the event. It's particularly difficult to understand information such as the type and color of flowers, as well as stock availability, making it time-consuming to find the perfect combination. It's even more difficult to choose a bouquet that includes a moving message, making it difficult to enhance the value of the gift.

[0394] 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.

[0395] In this invention, the server includes means for inputting an image and extracting flower characteristics, means for comparing the extracted flower characteristics with an existing flower database, means for inputting a user's preferences and event information, means for recommending an optimal bouquet combination based on the preferences and event information, means for performing image preprocessing such as noise reduction and size adjustment, means for generating a flower meaning and message based on the recommended bouquet, means for generating an inspiring message using natural language generation technology, means for displaying the recommended bouquet and message to the user and accepting the user's selection, and means for displaying multiple candidates and their respective image suitability. This allows the user to easily select the optimal bouquet based on their preferences or a specific event, and further enhances the value of the bouquet as a gift by adding an inspiring message.

[0396] "Means for inputting an image and extracting flower characteristics" refers to a technology that analyzes a flower image provided by a user and extracts characteristics such as the type, color, shape, and texture of the flower from the image.

[0397] "Means for matching extracted flower characteristics with existing flower databases" refers to technology that uses extracted flower characteristic data to compare and match with information in existing flower databases that have been registered in advance.

[0398] "Means for inputting user preferences and event information" refers to the technology that allows users to input their preferences and specific event information (such as birthdays, weddings, Mother's Day, etc.) through an input form and transmit this information to the system.

[0399] "Means for recommending optimal bouquet combinations based on preferences and event information" refers to technology that uses AI technology to suggest multiple optimal bouquet combinations based on input user preferences and event information and database information.

[0400] "Means for noise removal and size adjustment as image preprocessing" refers to technology that removes noise from images and resizes them to an appropriate size to make images uploaded by users easier to analyze.

[0401] "Means for generating flower meanings and messages based on recommended bouquets" refers to technology that collects related flower meanings based on the proposed bouquet combination and generates a matching message or poem.

[0402] "Means for generating inspirational messages using natural language generation technology" refers to technology that utilizes natural language generation technology, such as a generative AI model, to automatically create inspirational messages or poems related to a specific bouquet of flowers.

[0403] "Means for displaying recommended bouquets and messages to the user and accepting the user's selection" refers to a technology in which the system displays the bouquet combinations suggested by the system and the generated message on the user's device, allowing the user to make the optimal selection and have it accepted by the system.

[0404] "Means for displaying multiple candidates and their respective image suitability" refers to a technology that visually displays multiple bouquet combination candidates and the suitability that indicates how well each bouquet suits the user's preferences or the event.

[0405] The present invention is a system that uses AI technology to customize and suggest bouquets to send to users for specific events based on personal preferences and messages. This system can be implemented using various hardware and software described below.

[0406] First, a user takes a photo of a particular flower at a florist using a smartphone or tablet, and then uploads the image to the server via a dedicated application or web interface, which sends the user's input data and image data to the server.

[0407] The server preprocesses the received images by removing noise and adjusting the size. For example, an image processing library such as OpenCV can be used for this process. Next, features such as color, shape, and texture are extracted from the preprocessed images. Deep learning techniques such as Convolutional Neural Network (CNN) can be used for this process.

[0408] The extracted feature data is compared with the flower database stored in the system, which stores detailed information about each flower, such as its variety, color, stock status, and flower language. The server compares the data with the database information to identify similar flowers.

[0409] Next, the user provides the system with personal information such as the type of event (e.g., birthday, wedding, Mother's Day, etc.), favorite colors, and budget through an input form. This information is sent from the terminal to the server.

[0410] The server uses an AI algorithm to recommend the optimal bouquet combination based on the user's preferences, event information, and matching results. Using collaborative filtering and recommender system techniques, multiple bouquet candidates are automatically generated and the image compatibility of each is calculated. Compatibility can be displayed using numerical scores or visual graphs.

[0411] The server then collects relevant flower meanings based on the recommended bouquet information and uses natural language generation technology (e.g., a generative AI model such as GPT-3) to generate an inspiring message, which can include a poem or a congratulatory message.

[0412] Finally, the terminal displays the bouquet options sent from the server and the generated message to the user, who can then choose the one they like best and place the order immediately.

[0413] Specific examples

[0414] For example, if a user wants to choose a bouquet for Mother's Day, they first upload a photo of the flowers they took at a florist to the system. Next, they enter the event information, "Mother's Day," along with their preferred colors (e.g., pink or white) and budget (e.g., under 5,000 yen). The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. Finally, the device displays candidate bouquets and a message containing the flower meanings to the user, who then selects the most suitable bouquet and confirms their order.

[0415] Prompt Sentence Examples

[0416] "I'd like to choose an inspiring bouquet for Mother's Day. I'd like to focus on pink flowers and keep the budget under 5,000 yen."

[0417] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0418] Step 1: Image Input and Preprocessing

[0419] Users upload photos of flowers taken at a florist to the system via a dedicated application or a web interface, and the terminal then sends the image data to the server.

[0420] The server performs noise reduction and size adjustment on the received image. Specifically, it uses OpenCV to remove noise and resize it to an appropriate size. As a result, the input is the flower image taken by the user, and the output is the preprocessed image.

[0421] Step 2: Image feature extraction and database matching

[0422] The server extracts features such as color, shape, and texture from the preprocessed image using a Convolutional Neural Network (CNN). The extracted feature data is then compared with the system's flower database.

[0423] Specifically, we generate a feature vector for each image and compare it with the feature vectors in the database. From this comparison, the input is the preprocessed image, and the output is the information on similar flowers.

[0424] Step 3: Enter your user information

[0425] The user provides information such as the type of event (e.g., birthday, wedding, Mother's Day), preferred colors, and budget to the system through an input form.

[0426] The terminal transmits this user information to the server in real time. The input is event information and preference data from the user, and the output is the user information transmitted to the server.

[0427] Step 4: Recommend the perfect bouquet

[0428] The server uses AI algorithms to generate the optimal bouquet combination based on the user's preferences, event information, and matching results, using collaborative filtering and recommender system techniques.

[0429] Specifically, multiple bouquet candidates are generated from the collected feature data and user information, and the image compatibility of each is calculated. The input is user information and feature data, and the output is bouquet candidates and compatibility.

[0430] Step 5: Creating the flower language and message

[0431] The server collects relevant flower meanings based on the recommended bouquet information and generates an inspirational message using a generative AI model (e.g., GPT-3).

[0432] Specifically, the system selects the flower language based on the combination of flowers in the bouquet and generates a message using natural language generation technology. The input is the bouquet information, and the output is the generated message.

[0433] Step 6: View and select recommendations

[0434] The terminal displays the bouquet candidates sent from the server and the generated message to the user, who then selects the bouquet he or she likes best and confirms the order.

[0435] Specifically, it displays bouquets and messages on the terminal screen and provides a selectable interface. The input is bouquet candidates and messages, and the output is the user's selection.

[0436] (Application example 1)

[0437] 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."

[0438] Conventional bouquet selection systems have the problem that they do not allow sufficient customization or personalization when users select the perfect bouquet for a specific event or preference. Also, the process of delivering the created bouquet and message is time-consuming, which makes it inconvenient for users.

[0439] 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.

[0440] In this invention, the server includes means for inputting an image and extracting flower characteristics, means for comparing the extracted flower characteristics with an existing flower database, means for inputting a user's preferences and event information, means for recommending an optimal bouquet combination based on the preferences and event information, means for generating a flower meaning and a message based on the recommended bouquet, means for displaying the recommended bouquet and message to the user and accepting the user's selection, and means for coordinating with an external delivery system to deliver the selected bouquet. This allows the user to easily select a customized bouquet according to a specific event or preference, and then have the bouquet delivered quickly.

[0441] The "means for inputting images" is a mechanism for users to upload photos of flowers they have taken to the system.

[0442] The "means for extracting flower characteristics" is a technology for analyzing information such as flower shape, color, and texture from uploaded images.

[0443] "Means for matching with an existing flower database" refers to a technique for comparing extracted feature information with information on flowers registered in a database to identify matching flowers.

[0444] The "means for inputting user preferences and event information" refers to an interface that allows a user to input information about their preferences and specific events, such as color preferences and budget, into the system.

[0445] "Means for recommending the best bouquet combination" refers to a technology in which AI recommends the best combination of flowers based on the information entered by the user and the matching results.

[0446] The "means for generating flower meanings and messages" is a technology that automatically generates flower meanings and moving messages based on recommended bouquets.

[0447] The "means for displaying to the user and accepting the user's selection" is an interface that visually displays the recommended bouquet and the generated message to the user, allowing the user to make the optimal selection.

[0448] The "means for coordinating with an external delivery system" is a technology for communicating with and coordinating with an external delivery service in order to deliver the selected bouquet to the specified location.

[0449] The system of the present invention utilizes AI technology to customize and suggest bouquets to send to users for specific events based on personal preferences and messages. This system is realized by combining the following components:

[0450] 1. Image input and processing

[0451] Users take photos of flowers using a smartphone or tablet and upload them to the server via a dedicated application. The server receives the images and performs preprocessing such as noise reduction and resizing.

[0452] 2. Image feature extraction and database matching

[0453] The server extracts flower features (shape, color, texture, etc.) from the preprocessed images. The extracted features are matched with an existing flower database, which includes information such as flower variety, color, availability, and flower language.

[0454] 3. Enter your preferences and event information

[0455] The user inputs information such as the type of event (e.g., Mother's Day), favorite colors, budget, etc. This information is sent to the server via a dedicated application.

[0456] 4. Recommendation of the best bouquet

[0457] The server uses AI technology to recommend the most suitable bouquet based on the results of matching the user's input information with image features. Multiple candidates are generated and the image compatibility of each is displayed. This compatibility is a numerical representation of how well the flower characteristics match the user's preferences and event information.

[0458] 5. Creating flower language and messages

[0459] Based on the selected bouquet, the server uses natural language generation technology to gather the language of flowers and generate an inspiring message, which will further enhance the value of the gift.

[0460] 6. Display of recommendation results and messages

[0461] The terminal displays the bouquet candidates and generated messages sent from the server to the user, and the user can choose the bouquet and message they like best from multiple options.

[0462] 7. Integration with external systems for delivery

[0463] The server connects to an external delivery system to deliver the bouquet selected by the user, so that the selected bouquet is quickly delivered to the specified location.

[0464] Examples of hardware and software used:

[0465] Hardware: smartphones, tablets, servers

[0466] Software: Python, TensorFlow (AI model), Django (web framework), React Native (mobile application)

[0467] Examples:

[0468] For example, if a user wants to choose a bouquet to give for Mother's Day, they first upload a photo of the flowers they took at a florist to the server via a dedicated application. Next, they enter information about the event, "Mother's Day," their preferred colors, and their budget. The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate the optimal bouquet combination, calculates the image compatibility of each, and displays it. The user then reviews the bouquet candidates and messages containing the flower meanings, selects the most suitable bouquet, and confirms their order. The selected bouquet is then quickly delivered in conjunction with an external delivery system.

[0469] Example prompt sentence:

[0470] I'd like to choose a bouquet to give for Mother's Day. I like pink roses, and my budget is under 5,000 yen. What kind of bouquet would you recommend?

[0471] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0472] Step 1:

[0473] Users take photos of flowers using a smartphone or tablet and upload the images to the server via a dedicated application. The input is the image of the flower, and the output is the image data sent to the server. Specifically, the user presses the "upload image" button in the application, selects the image they have taken, and uploads it.

[0474] Step 2:

[0475] The server performs preprocessing on the received image data. This preprocessing includes noise removal and size adjustment. The input is the image data sent by the user, and the output is preprocessed, clear image data. Specifically, the server uses a Python library to remove noise and adjust the size of the image.

[0476] Step 3:

[0477] The server uses an AI model (e.g., a deep learning model using TensorFlow) to extract flower features from preprocessed images. The input is the preprocessed image data, and the output is feature data such as shape, color, and texture. Specifically, the server runs an image analysis algorithm to extract features.

[0478] Step 4:

[0479] The server matches the extracted features with an existing flower database. The input is the flower feature data, and the output is the matching flower information in the database. Specifically, it compares the feature data with entries in the database and uses SQL queries to find the best match.

[0480] Step 5:

[0481] The user inputs information such as event information (e.g., Mother's Day), favorite colors, and budget into the system via a terminal. The input is the event information and favorite data, and the output is request data that includes this information. Specifically, the user enters the required information into the application's input fields and presses the "Submit" button.

[0482] Step 6:

[0483] The server uses AI technology to recommend the most suitable bouquet based on the information entered by the user and the results of matching image features. The input is the user's event information and feature data, and the output is a list of suitable bouquet candidates. Specifically, it uses a machine learning algorithm to generate the optimal bouquet and calculates the suitability of each candidate.

[0484] Step 7:

[0485] The server generates a flower language and message based on the sponsored bouquet using natural language generation technology (e.g., a generative AI model). The input is information about the selected bouquet, and the output is an inspiring message. Specifically, the server generates the message using a natural language generation algorithm.

[0486] Step 8:

[0487] The terminal displays the bouquet candidate list sent from the server and the generated message to the user. The input is the bouquet candidate and the message, and the output is the screen displayed on the terminal. Specifically, the candidate list and the message are visually displayed through the user interface (UI).

[0488] Step 9:

[0489] The user selects the bouquet and message they like best from multiple options and confirms the order. The input is the user's selection data, and the output is the order confirmation data. Specifically, the user presses the "Select a bouquet" button in the application, selects the desired bouquet and message, and confirms the order.

[0490] Step 10:

[0491] The server works with an external delivery system to deliver the selected bouquet. The input is order confirmation data, and the output is delivery request data. Specifically, the server calls the API of the delivery service and issues instructions to deliver the selected bouquet.

[0492] 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.

[0493] The system of the present invention utilizes AI technology and an emotion engine to customize and suggest bouquets to be given to users for specific events based on their personal preferences and emotions. Specific embodiments of the system are described in detail below.

[0494] 1. Image input and processing

[0495] Users take photos of flowers in a flower shop using a smartphone or tablet and upload the images to the system via a dedicated application or web interface. The device receives the images and performs preprocessing such as noise reduction and size adjustment. The preprocessed images are then sent to the server.

[0496] 2. Image feature extraction and database matching

[0497] The server extracts flower features from the preprocessed images and matches this feature data with an existing flower database, which contains information such as flower variety, color, availability, and flower language. The server generates a list of matching flowers.

[0498] 3. Enter your preferences and event information

[0499] The user inputs information into the system, such as the type of event, preferred colors, budget, etc. This information is sent to the server via the terminal.

[0500] 4. Emotion Recognition by Emotion Engine

[0501] The device analyzes the user's facial expressions and voice to recognize the user's emotions. The camera is used for facial recognition and the microphone is used for voice analysis. The recognized emotion data is sent to the server.

[0502] 5. Bouquet Recommendation

[0503] The server uses AI technology to generate optimal bouquet combination candidates based on the user's emotions, preferences, event information, and database matching results. Multiple bouquet candidates are generated and their image compatibility is calculated. The data is then sent to the device.

[0504] 6. Creating flower language and messages

[0505] Based on the selected bouquet, the server collects the flower language and uses natural language generation technology to generate an inspiring poem or message, customizing the message content based on the user's recognized emotions.

[0506] 7. Displaying recommended results and messages

[0507] The terminal receives the data from the server and displays the bouquet candidates, their image compatibility, and the generated message to the user. The user can then choose the bouquet they like best from the displayed multiple options.

[0508] Specific examples

[0509] For example, if a user wants to choose a bouquet for Mother's Day, they first upload a photo of the flowers they took at a florist to the system. Next, they enter information about the Mother's Day event, their preferred colors, and their budget. The device analyzes the user's facial expressions and voice to collect emotional data. The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. The server also generates an inspiring poem or message based on the user's emotional data and sends it to the device. Finally, the device displays bouquet options and messages to the user, who then selects the most suitable bouquet and confirms their order.

[0510] This allows users to send a unique and moving bouquet that is perfect for a special event. In addition, by utilizing the emotion engine, it is possible to make suggestions that are more suited to the user's current emotions.

[0511] The processing flow will be explained below.

[0512] Step 1:

[0513] The user takes a photo of a flower in a flower shop using a smartphone or tablet, takes the photo through a dedicated application or web interface, and uploads it to the system.

[0514] Step 2:

[0515] The device receives the uploaded image, temporarily stores the image, and performs preprocessing such as noise reduction and size adjustment.

[0516] Step 3:

[0517] The device sends the preprocessed image to the server, which receives the image and performs image analysis.

[0518] Step 4:

[0519] The server extracts flower features from the image, analyzing and obtaining data such as the flower's shape, color, and texture.

[0520] Step 5:

[0521] The server compares the extracted flower characteristics with an existing flower database, which includes information such as variety, color, availability, and flower language. The result is a list of matching flowers.

[0522] Step 6:

[0523] The user uses a dedicated form to enter information such as the type of event (e.g., birthday, Mother's Day, graduation, etc.), favorite colors, budget, etc. The entered information is sent to the server via the terminal.

[0524] Step 7:

[0525] The device analyzes the user's facial expressions and voice to collect emotional data. The camera is used for facial expression analysis, and the microphone is used for voice analysis.

[0526] Step 8:

[0527] The device sends the collected emotional data to a server, which then analyzes and determines the user's emotional state.

[0528] Step 9:

[0529] The server generates optimal bouquet combination candidates based on the user's preferences, event information, emotional data, and database matching results. AI technology is used to calculate multiple bouquet candidates and their image compatibility.

[0530] Step 10:

[0531] The server generates a message based on the selected bouquet, including the meaning of flowers, a moving poem, and a message, and customizes the message based on the user's emotional data.

[0532] Step 11:

[0533] The terminal displays the bouquet candidates, image compatibility, and the generated message to the user, who can then choose the bouquet they like best from the displayed multiple options.

[0534] Step 12:

[0535] The user selects the most suitable bouquet and message and confirms the order. The confirmed order is transmitted to the server via the terminal, and the information is finally sent to the florist.

[0536] Through this process, users can easily select the perfect bouquet for a special event and send it with an inspiring message.By using the emotion engine, suggestions can be made that are more suited to the user's current emotions.

[0537] Example 2

[0538] 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."

[0539] Conventional bouquet selection systems could suggest bouquets based on a user's personal preferences and event information, but it was difficult to suggest the optimal bouquet and message that took the user's emotions into consideration. This meant that it was not possible to provide bouquets and messages that better matched the user's emotions for special events, resulting in a problem of reduced user satisfaction.

[0540] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for inputting an image and extracting flower characteristics, means for comparing the extracted flower characteristics with an existing flower database, means for inputting a user's preferences and event information, means for recommending an optimal bouquet combination based on the preferences and event information, means for acquiring user emotion data using emotion recognition technology, means for customizing the bouquet and message content using the emotion data, means for generating a flower meaning and message based on the recommended bouquet, and means for displaying the recommended bouquet and message to the user and accepting the user's selection. This makes it possible to propose an optimal bouquet and provide an inspiring message that takes the user's emotions into consideration.

[0541] "Means for inputting an image and extracting flower characteristics" refers to a technology that allows a user to upload a photo of a flower they have taken to the system and recognize characteristics such as the flower variety, color, and shape from the image.

[0542] "Means for matching extracted flower characteristics with existing flower databases" refers to technology for comparing extracted flower characteristic data with data in existing flower databases and identifying matching flower types and information.

[0543] The "means for inputting user preferences and event information" is an interface that allows the user to input personal information such as the type of event, favorite colors, budget, etc., into the system.

[0544] "Means for recommending optimal bouquet combinations based on preferences and event information" refers to a system that uses AI technology to suggest multiple bouquet combinations based on user input data.

[0545] "Means for acquiring user emotional data using emotion recognition technology" refers to technology that uses a camera or microphone to analyze the user's facial expressions and voice and recognize their emotional state.

[0546] The "means for customizing the bouquet and message content using emotional data" is a system for individually adjusting the bouquet combination and message content based on the acquired emotional data.

[0547] The "means for generating flower meanings and messages based on recommended bouquets" refers to a technology for collecting flower meanings related to the flowers based on the type of bouquet proposed, and then generating a message using natural language generation technology.

[0548] The "means for displaying recommended bouquets and messages to the user and accepting the user's selection" is an interface that displays suggested bouquet candidates and related messages to the user via the terminal, allowing the user to select the most suitable bouquet.

[0549] The system of the present invention utilizes AI technology and an emotion engine to customize bouquets to be given to users on special occasions based on their personal preferences and emotions, and makes optimal suggestions. Specific embodiments of the system are described below.

[0550] The main processing of the system is performed using the following hardware and software.

[0551] Hardware: smartphones, tablets, cameras, microphones

[0552] Software: Dedicated applications, web interfaces, image processing algorithms, AI technology, natural language generation technology

[0553] First, a user takes a photo of a flower using a smartphone or tablet. The image is then uploaded to the system via a dedicated application or web interface. The device receives the image and performs preprocessing such as noise reduction and size adjustment. The preprocessed image is then sent to the server.

[0554] The server then extracts flower features from the preprocessed image, such as the flower's variety, color, shape, etc. The feature data is then matched against an existing flower database to generate a list of matching flowers.

[0555] The user then inputs information such as the type of event (e.g., Mother's Day), favorite colors, budget, etc. This information is sent to the server via the terminal.

[0556] Furthermore, the device uses a camera to capture the user's facial expressions and a microphone to record their voice. These are analyzed to extract the user's emotional data, which is then sent to the server.

[0557] Next, the server uses AI technology to generate the optimal bouquet combination based on the user's emotional data, preferences, event information, and image feature extraction results. Multiple bouquet candidates are generated and the image compatibility of each is calculated. This data is then sent to the device.

[0558] The server then collects the meanings of the flowers in the selected bouquet and uses natural language generation technology to generate moving poems and messages, taking into account the emotional data.

[0559] Finally, the device receives the data sent from the server and displays the bouquet candidates, image compatibility, and the generated message to the user. The user can then choose the bouquet they like best from multiple options.

[0560] As a concrete example, if a user wants to choose a bouquet for Mother's Day, they would follow these steps: The user uploads a photo of flowers taken at a florist to the system and enters information about the Mother's Day event, as well as their preferred colors and budget. The device collects the user's emotional data using facial recognition and voice analysis, and the server analyzes the image and compares it with a database to identify available flowers. The server then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. The server also generates an inspiring poem or message based on the user's emotional data and sends this to the device. Finally, the device displays candidate bouquets and messages to the user, who then selects the most suitable bouquet and confirms their order.

[0561] This system allows users to send personalized and inspiring bouquets perfect for special occasions, and by utilizing an emotion engine, it can make suggestions that better suit the user's current emotions.

[0562] An example of a prompt sentence is, "Please suggest a bouquet of pink and white flowers for Mother's Day within a budget of 5,000 yen. My mother likes a message that shows gratitude." Based on this prompt sentence, the system generates the optimal bouquet and message and suggests them to the user.

[0563] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0564] Step 1: Image Input and Preprocessing

[0565] A user takes a photo of a flower with a smartphone or tablet and uploads the image to the system through a dedicated application or web interface. The input is the flower image uploaded by the user. The device receives this image and performs preprocessing such as noise removal and size adjustment. The output is the preprocessed image. This preprocessing results in image data that is easy to analyze.

[0566] What it does: The user presses the "Take a photo of a flower" button in the app, then taps the "Upload" button after taking the photo. The device then analyzes the photo, removes unwanted noise, and resizes the image appropriately.

[0567] Step 2: Image feature extraction and database matching

[0568] The server extracts flower features from the preprocessed image. The input is the preprocessed image. The server uses image processing algorithms to extract feature data such as flower color, shape, and texture. The output is the extracted feature data. This feature data is then matched against an existing flower database. It is compared with the flower information in the database and a list of matching flowers is generated. The output is a list of matching flowers.

[0569] How it works: The server uses image processing algorithms to extract features such as color histogram and shape from the input image, and then compares that information with database entries to find a match.

[0570] Step 3: Enter your user information

[0571] The user inputs information such as the type of event (e.g., Mother's Day), favorite colors, and budget into the system. The input is the event information and favorite data entered by the user. The terminal receives this information and sends it to the server. The output is the user information sent to the server. This information becomes the basic data for recommending a bouquet that meets the user's request.

[0572] Specific operation: The user enters information such as "Mother's Day," "pink and white," and "budget 5,000 yen" into the form within the app and taps the "Submit" button. The device acquires the information and sends it to the server.

[0573] Step 4: Emotion Recognition with the Emotion Engine

[0574] The device uses a camera to capture the user's facial expression and a microphone to record the audio. The input is the video and audio data of the user's facial expression. These are analyzed to extract the user's emotional data. The output is the extracted emotional data. This emotional data is sent to the server.

[0575] How it works: When a user turns on the facial recognition feature, the camera captures a few seconds of the user's facial expressions. The microphone also records the user's speech. This data is analyzed to identify emotions such as "happiness," "sadness," and "excitement."

[0576] Step 5: Recommend the bouquet

[0577] The server uses AI technology to generate the optimal bouquet combination based on the user's emotional data, preferences, event information, and image feature extraction results. The inputs are emotional data, user preference information, event information, and image feature extraction results. Multiple bouquet candidates are generated and the image compatibility of each is calculated. The output is a list of bouquet candidates and their image compatibility. This data is sent to the device.

[0578] How it works: The AI ​​model analyzes the user's input data, generates multiple candidates, such as "a bouquet of pink carnations and white roses" and "a bouquet of pink and white tulips," and calculates the suitability of each candidate (for example, a score such as "90%" or "85%).

[0579] Step 6: Creating the flower language and message

[0580] Based on the selected bouquet, the server collects the language of flowers contained in the bouquet. The input is a list of candidate bouquets and their information. An inspiring poem or message is generated using natural language generation technology. The generated message is customized taking into account the emotional data. The output is the generated message. This message is sent to the device.

[0581] Specific operation: The server looks up the meaning of flowers, such as "carnation (love)" or "rose (love)," and generates a message such as "We present a beautiful bouquet to your mother with our love and gratitude."

[0582] Step 7: Viewing Recommendations and Messages

[0583] The terminal receives data from the server and displays recommended bouquet candidates, image compatibility, and a generated message to the user. The input is the bouquet candidate list sent from the server and the generated message. The output is the bouquet candidates and message displayed to the user. The user can choose the bouquet they like best from multiple options.

[0584] Specific behavior: The device displays options to the user, such as "Bouquet of pink carnations and white roses (suitability: 90%)," and displays a generated message for each option. The user taps the "Select" button to choose the best bouquet.

[0585] (Application example 2)

[0586] 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."

[0587] Currently, there is a lack of means to recommend optimal items based on a user's preferences, emotions, and event information, and to generate customized messages for those items. Furthermore, there are no systems that can accurately convert a user's voice input into text or identify emotions from facial expressions. This makes it difficult to provide services that truly match a user's emotions and preferences.

[0588] 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.

[0589] In this invention, the server includes means for inputting an image and extracting features of an object, means for comparing the extracted features with an existing database, means for inputting a user's preferences and event information, means for recommending an optimal combination of items based on the input information, means for generating a customized message based on the recommended items, means for displaying the recommended items and message to the user and accepting the user's selection, means for collecting the user's voice input and converting the voice data into text, and means for capturing the user's facial expressions and identifying emotions from the expressions, thereby making it possible to provide more appropriate and personalized services based on the user's emotions and preferences.

[0590] "Means for inputting images" refers to the function of capturing images using an electronic device such as a camera or scanner and loading them into the system.

[0591] "Means for extracting the characteristics of an object" is a function that analyzes attributes such as the shape, color, and texture of an object from an input image and extracts them as data.

[0592] "Means for matching with existing databases" refers to a function that compares extracted feature data with existing data in the system to identify matching or similar items.

[0593] The "means for inputting user preferences and event information" is an interface for inputting information about the user's favorite elements and events (for example, favorite color, budget, type of event).

[0594] The "means for recommending the most suitable combination of items" is a function that suggests the most suitable combination of items based on the information input by the user and the collation results.

[0595] The "means for generating a customized message" is a function that uses natural language generation technology to create a message related to the recommended item.

[0596] The "means for displaying to the user and accepting selection" is an interface that displays the recommended items and generated messages to the user and allows the user to select the desired items.

[0597] The "means for collecting voice input and converting voice data into text" is a function for recording the user's voice, analyzing the voice data, and converting it into text information.

[0598] The "means for capturing facial expressions and identifying emotions from facial expressions" is a function that uses a camera to capture the user's facial expressions and analyzes the image data to identify the user's emotions.

[0599] The system according to the present invention is a system that recommends a customized menu based on personal preferences and emotions when a user uses a food delivery service. The system includes the following means.

[0600] Hardware and Software

[0601] 1. Camera-equipped smartphone

[0602] Camera: Used to capture the user's face and analyze facial expressions.

[0603] Microphone: Used to collect the user's voice input.

[0604] 2. Server

[0605] Computational resources: process image and audio data, run AI models, and match data against databases.

[0606] Framework: We use TensorFlow and Keras to run our emotion recognition and natural language generation models.

[0607] 3. Cloud Database

[0608] Stores and manages user profiles, menu data, emotion data, etc.

[0609] System action

[0610] 1. Image input and feature extraction

[0611] When a user takes a picture of their face using their smartphone camera, the system captures this image. Then, using TensorFlow and Keras, it identifies emotions from facial expressions. For example, if a user smiles into the smartphone camera, the system detects the emotion "happiness."

[0612] 2. Voice to text conversion

[0613] When a user speaks into the microphone about their desired menu or event information, the voice data is converted into text using the SpeechRecognition library. For example, if a user types "I'd like a healthy lunch, please," this is sent as text data to the server.

[0614] 3. Database matching and item recommendation

[0615] The server compares the menu data stored in the cloud database with the user's input information and emotional data, and then recommends the menu that best suits the user's situation and emotions. For example, it recommends a "healthy lunch" and salads and fruits that best suit the emotion of "joy."

[0616] 4. Customized Message Generation

[0617] Based on the recommended menu, natural language generation technology is used to generate an inspiring message, such as "Enjoy a healthy lunch and an energetic afternoon."

[0618] 5. Display and selection reception

[0619] Finally, the recommended menu and customized message sent from the server are displayed on the smartphone, and the user selects the most suitable menu and confirms the order.

[0620] Specific examples

[0621] If a user is wondering what to order at a lunch meeting, the following process takes place:

[0622] 1. The camera captures the user's facial expression, and the system recognizes the emotion as "nervous."

[0623] 2. The user dictates, "What are your food recommendations for a lunch meeting?"

[0624] 3. The speech is converted to text and sent to the server along with the user's preferences and event information.

[0625] 4. The server analyzes this and recommends an appropriate menu item, such as a light sandwich or salad.

[0626] 5. A customized message is generated, such as "Enjoy a relaxing lunch meeting with this sandwich."

[0627] Prompt Sentence Examples

[0628] "What's the best food for a lunch meeting?"

[0629] "Do you have any menu suggestions for Mother's Day dinner?"

[0630] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0631] Step 1:

[0632] A user takes a picture of their face using the smartphone camera. The input is the user's face image, and the output is the captured image data. The camera detects the user's face and sends the image data to the device.

[0633] Step 2:

[0634] The device sends the captured image data to the processing module for preprocessing for facial expression recognition. Preprocessing includes noise reduction and size adjustment. The input is the captured image data, and the output is the preprocessed image data.

[0635] Step 3:

[0636] The device sends the preprocessed image data to the server and requests emotion recognition. The server uses TensorFlow and Keras to identify emotions from facial expressions. The recognized emotion data is output.

[0637] Step 4:

[0638] The user speaks the desired menu or event information into the smartphone's microphone. The input is voice data, and the output is recorded voice data. The microphone captures the voice and sends the voice data to the terminal.

[0639] Step 5:

[0640] The device converts the recorded voice data into text data using the SpeechRecognition library. The input is voice data and the output is text data. If recognition is successful, the voice data is converted into text format.

[0641] Step 6:

[0642] The terminal sends the text data to the server and stores it as user preference and event information. The input is text data, and the output is preference information and event information stored in the server's database.

[0643] Step 7:

[0644] The server compares the menu data stored in the cloud database with the user's preference and emotion data. As a result of the comparison, optimal menu candidates are generated. The input is preference and emotion data, and the output is a recommended menu.

[0645] Step 8:

[0646] The server generates a customized message based on the generated recommended menu using natural language generation technology. The input is the recommended menu information, and the output is the customized message. The message is intended to make the menu received by the user more meaningful.

[0647] Step 9:

[0648] The server sends the recommended menu and customized message to the terminal. The input is the recommended menu and message data, and the output is the information displayed on the display screen of the terminal.

[0649] Step 10:

[0650] The terminal displays the recommended menu and customized message received from the server to the user. The user selects the menu they like best from the displayed multiple options. The input is the recommended menu and message data, and the output is the user's selection.

[0651] Step 11:

[0652] When the user selects the most suitable menu item, the terminal sends the selection information to the server, and the order is confirmed. The input is the user's selection data, and the output is order confirmation data from the server.

[0653] 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.

[0654] 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.

[0655] 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.

[0656] [Third embodiment]

[0657] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0658] 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.

[0659] 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).

[0660] 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.

[0661] 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.

[0662] 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).

[0663] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0664] 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.

[0665] 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.

[0666] 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.

[0667] 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.

[0668] 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."

[0669] The system of the present invention utilizes AI technology to customize and suggest bouquets to be given to users for specific events based on personal preferences and messages. Specific embodiments of the system are described in detail below.

[0670] 1. Image input and processing

[0671] Users take photos of flowers in a flower shop using a smartphone or tablet and upload them to the system. The images are sent to the server via a dedicated application or web interface. The server processes the received images, performing preprocessing such as noise reduction and resizing.

[0672] 2. Image feature extraction and database matching

[0673] The server extracts flower features from the pre-processed images, including shape, color, and texture. The extracted feature data is then compared with an existing flower database, which stores information such as variety, color, availability, and flower language, and the server identifies matching flowers.

[0674] 3. Enter your preferences and event information

[0675] The user inputs information such as the type of event, preferred colors, budget, etc. into the system. This information is entered into the terminal via the user interface and sent to the server.

[0676] 4. Recommendation of the best bouquet

[0677] The server uses AI technology to recommend the optimal bouquet combination based on the information entered by the user and the results of database comparison. Multiple bouquet candidates are generated and the image compatibility of each is displayed. The compatibility is a numerical value that indicates how well the bouquet fits the user's preferences and the event.

[0678] 5. Creating flower language and messages

[0679] Based on the selected bouquet, the server collects the meanings of flowers and uses natural language generation technology to generate moving poems and messages, further enhancing the value of the gift.

[0680] 6. Display of recommendation results and messages

[0681] The terminal displays the bouquet candidates and generated messages sent from the server to the user, and the user can choose the bouquet and message they like best from multiple options.

[0682] Specific examples

[0683] For example, if a user wants to choose a bouquet for Mother's Day, they first upload a photo of the flowers they took at a florist to the system. Next, they enter information about the Mother's Day event, their preferred colors, and their budget. The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. Finally, the device displays candidate bouquets and a message containing the meanings of the flowers to the user, who then selects the most suitable bouquet and confirms their order.

[0684] This allows users to easily choose a very unique and inspiring bouquet for a special event.

[0685] The processing flow will be explained below.

[0686] Step 1:

[0687] The user takes a photo of a flower in a flower shop using a smartphone or tablet, takes the photo through a dedicated application or web interface, and uploads it to the system.

[0688] Step 2:

[0689] The device receives the uploaded image, temporarily stores it, and performs pre-processing such as image noise reduction and resizing.

[0690] Step 3:

[0691] The device sends the preprocessed image to the server, which receives the image and performs image analysis to extract the flower's characteristics (shape, color, texture, etc.).

[0692] Step 4:

[0693] The server compares the extracted flower characteristics data with an existing flower database, which includes information such as variety, color, availability, and flower language, and generates a list of the best-matching flowers.

[0694] Step 5:

[0695] The user uses a dedicated form to enter information such as the type of event (e.g., birthday, Mother's Day, graduation, etc.), favorite colors, budget, etc. The entered information is sent to the server via the terminal.

[0696] Step 6:

[0697] The server uses AI technology to generate optimal bouquet combination candidates based on the user's input information and matching results. The server calculates the image compatibility of multiple bouquet candidates and sends the data to the device.

[0698] Step 7:

[0699] The device receives the data from the server and displays bouquet candidates and their image compatibility. The user can then choose the bouquet they like best from the multiple options displayed.

[0700] Step 8:

[0701] The server collects the meanings of the flowers based on the selected bouquet and uses natural language generation technology to generate an inspiring poem or message, which is then sent back to the device.

[0702] Step 9:

[0703] The terminal displays the generated message to the user, who then reviews the bouquet and message and makes a final selection.

[0704] Step 10:

[0705] The user selects the most suitable bouquet and message and confirms the order. The confirmed order is transmitted to the server via the terminal, and the information is finally sent to the florist.

[0706] This allows users to send a unique and inspiring bouquet that is perfect for a special event.

[0707] Example 1

[0708] 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."

[0709] Traditional flower bouquet selection methods have the drawback of making it difficult for users to choose a bouquet that best suits their preferences and the event. It's particularly difficult to understand information such as the type and color of flowers, as well as stock availability, making it time-consuming to find the perfect combination. It's even more difficult to choose a bouquet that includes a moving message, making it difficult to enhance the value of the gift.

[0710] 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.

[0711] In this invention, the server includes means for inputting an image and extracting flower characteristics, means for comparing the extracted flower characteristics with an existing flower database, means for inputting a user's preferences and event information, means for recommending an optimal bouquet combination based on the preferences and event information, means for performing image preprocessing such as noise reduction and size adjustment, means for generating a flower meaning and message based on the recommended bouquet, means for generating an inspiring message using natural language generation technology, means for displaying the recommended bouquet and message to the user and accepting the user's selection, and means for displaying multiple candidates and their respective image suitability. This allows the user to easily select the optimal bouquet based on their preferences or a specific event, and further enhances the value of the bouquet as a gift by adding an inspiring message.

[0712] "Means for inputting an image and extracting flower characteristics" refers to a technology that analyzes a flower image provided by a user and extracts characteristics such as the type, color, shape, and texture of the flower from the image.

[0713] "Means for matching extracted flower characteristics with existing flower databases" refers to technology that uses extracted flower characteristic data to compare and match with information in existing flower databases that have been registered in advance.

[0714] "Means for inputting user preferences and event information" refers to the technology that allows users to input their preferences and specific event information (such as birthdays, weddings, Mother's Day, etc.) through an input form and transmit this information to the system.

[0715] "Means for recommending optimal bouquet combinations based on preferences and event information" refers to technology that uses AI technology to suggest multiple optimal bouquet combinations based on input user preferences and event information and database information.

[0716] "Means for noise removal and size adjustment as image preprocessing" refers to technology that removes noise from images and resizes them to an appropriate size to make images uploaded by users easier to analyze.

[0717] "Means for generating flower meanings and messages based on recommended bouquets" refers to technology that collects related flower meanings based on the proposed bouquet combination and generates a matching message or poem.

[0718] "Means for generating inspirational messages using natural language generation technology" refers to technology that utilizes natural language generation technology, such as a generative AI model, to automatically create inspirational messages or poems related to a specific bouquet of flowers.

[0719] "Means for displaying recommended bouquets and messages to the user and accepting the user's selection" refers to a technology in which the system displays the bouquet combinations suggested by the system and the generated message on the user's device, allowing the user to make the optimal selection and have it accepted by the system.

[0720] "Means for displaying multiple candidates and their respective image suitability" refers to a technology that visually displays multiple bouquet combination candidates and the suitability that indicates how well each bouquet suits the user's preferences or the event.

[0721] The present invention is a system that uses AI technology to customize and suggest bouquets to send to users for specific events based on personal preferences and messages. This system can be implemented using various hardware and software described below.

[0722] First, a user takes a photo of a particular flower at a florist using a smartphone or tablet, and then uploads the image to the server via a dedicated application or web interface, which sends the user's input data and image data to the server.

[0723] The server preprocesses the received images by removing noise and adjusting the size. For example, an image processing library such as OpenCV can be used for this process. Next, features such as color, shape, and texture are extracted from the preprocessed images. Deep learning techniques such as Convolutional Neural Network (CNN) can be used for this process.

[0724] The extracted feature data is compared with the flower database stored in the system, which stores detailed information about each flower, such as its variety, color, stock status, and flower language. The server compares the data with the database information to identify similar flowers.

[0725] Next, the user provides the system with personal information such as the type of event (e.g., birthday, wedding, Mother's Day, etc.), favorite colors, and budget through an input form. This information is sent from the terminal to the server.

[0726] The server uses an AI algorithm to recommend the optimal bouquet combination based on the user's preferences, event information, and matching results. Using collaborative filtering and recommender system techniques, multiple bouquet candidates are automatically generated and the image compatibility of each is calculated. Compatibility can be displayed using numerical scores or visual graphs.

[0727] The server then collects relevant flower meanings based on the recommended bouquet information and uses natural language generation technology (e.g., a generative AI model such as GPT-3) to generate an inspiring message, which can include a poem or a congratulatory message.

[0728] Finally, the terminal displays the bouquet options sent from the server and the generated message to the user, who can then choose the one they like best and place the order immediately.

[0729] Specific examples

[0730] For example, if a user wants to choose a bouquet for Mother's Day, they first upload a photo of the flowers they took at a florist to the system. Next, they enter the event information, "Mother's Day," along with their preferred colors (e.g., pink or white) and budget (e.g., under 5,000 yen). The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. Finally, the device displays candidate bouquets and a message containing the flower meanings to the user, who then selects the most suitable bouquet and confirms their order.

[0731] Prompt Sentence Examples

[0732] "I'd like to choose an inspiring bouquet for Mother's Day. I'd like to focus on pink flowers and keep the budget under 5,000 yen."

[0733] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0734] Step 1: Image Input and Preprocessing

[0735] Users upload photos of flowers taken at a florist to the system via a dedicated application or a web interface, and the terminal then sends the image data to the server.

[0736] The server performs noise reduction and size adjustment on the received image. Specifically, it uses OpenCV to remove noise and resize it to an appropriate size. As a result, the input is the flower image taken by the user, and the output is the preprocessed image.

[0737] Step 2: Image feature extraction and database matching

[0738] The server extracts features such as color, shape, and texture from the preprocessed image using a Convolutional Neural Network (CNN). The extracted feature data is then compared with the system's flower database.

[0739] Specifically, we generate a feature vector for each image and compare it with the feature vectors in the database. From this comparison, the input is the preprocessed image, and the output is the information on similar flowers.

[0740] Step 3: Enter your user information

[0741] The user provides information such as the type of event (e.g., birthday, wedding, Mother's Day), preferred colors, and budget to the system through an input form.

[0742] The terminal transmits this user information to the server in real time. The input is event information and preference data from the user, and the output is the user information transmitted to the server.

[0743] Step 4: Recommend the perfect bouquet

[0744] The server uses AI algorithms to generate the optimal bouquet combination based on the user's preferences, event information, and matching results, using collaborative filtering and recommender system techniques.

[0745] Specifically, multiple bouquet candidates are generated from the collected feature data and user information, and the image compatibility of each is calculated. The input is user information and feature data, and the output is bouquet candidates and compatibility.

[0746] Step 5: Creating the flower language and message

[0747] The server collects relevant flower meanings based on the recommended bouquet information and generates an inspirational message using a generative AI model (e.g., GPT-3).

[0748] Specifically, the system selects the flower language based on the combination of flowers in the bouquet and generates a message using natural language generation technology. The input is the bouquet information, and the output is the generated message.

[0749] Step 6: View and select recommendations

[0750] The terminal displays the bouquet candidates sent from the server and the generated message to the user, who then selects the bouquet he or she likes best and confirms the order.

[0751] Specifically, it displays bouquets and messages on the terminal screen and provides a selectable interface. The input is bouquet candidates and messages, and the output is the user's selection.

[0752] (Application example 1)

[0753] 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."

[0754] Conventional bouquet selection systems have the problem that they do not allow sufficient customization or personalization when users select the perfect bouquet for a specific event or preference. Also, the process of delivering the created bouquet and message is time-consuming, which makes it inconvenient for users.

[0755] 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.

[0756] In this invention, the server includes means for inputting an image and extracting flower characteristics, means for comparing the extracted flower characteristics with an existing flower database, means for inputting a user's preferences and event information, means for recommending an optimal bouquet combination based on the preferences and event information, means for generating a flower meaning and a message based on the recommended bouquet, means for displaying the recommended bouquet and message to the user and accepting the user's selection, and means for coordinating with an external delivery system to deliver the selected bouquet. This allows the user to easily select a customized bouquet according to a specific event or preference, and then have the bouquet delivered quickly.

[0757] The "means for inputting images" is a mechanism for users to upload photos of flowers they have taken to the system.

[0758] The "means for extracting flower characteristics" is a technology for analyzing information such as flower shape, color, and texture from uploaded images.

[0759] "Means for matching with an existing flower database" refers to a technique for comparing extracted feature information with information on flowers registered in a database to identify matching flowers.

[0760] The "means for inputting user preferences and event information" refers to an interface that allows a user to input information about their preferences and specific events, such as color preferences and budget, into the system.

[0761] "Means for recommending the best bouquet combination" refers to a technology in which AI recommends the best combination of flowers based on the information entered by the user and the matching results.

[0762] The "means for generating flower meanings and messages" is a technology that automatically generates flower meanings and moving messages based on recommended bouquets.

[0763] The "means for displaying to the user and accepting the user's selection" is an interface that visually displays the recommended bouquet and the generated message to the user, allowing the user to make the optimal selection.

[0764] The "means for coordinating with an external delivery system" is a technology for communicating with and coordinating with an external delivery service in order to deliver the selected bouquet to the specified location.

[0765] The system of the present invention utilizes AI technology to customize and suggest bouquets to send to users for specific events based on personal preferences and messages. This system is realized by combining the following components:

[0766] 1. Image input and processing

[0767] Users take photos of flowers using a smartphone or tablet and upload them to the server via a dedicated application. The server receives the images and performs preprocessing such as noise reduction and resizing.

[0768] 2. Image feature extraction and database matching

[0769] The server extracts flower features (shape, color, texture, etc.) from the preprocessed images. The extracted features are matched with an existing flower database, which includes information such as flower variety, color, availability, and flower language.

[0770] 3. Enter your preferences and event information

[0771] The user inputs information such as the type of event (e.g., Mother's Day), favorite colors, budget, etc. This information is sent to the server via a dedicated application.

[0772] 4. Recommendation of the best bouquet

[0773] The server uses AI technology to recommend the most suitable bouquet based on the results of matching the user's input information with image features. Multiple candidates are generated and the image compatibility of each is displayed. This compatibility is a numerical representation of how well the flower characteristics match the user's preferences and event information.

[0774] 5. Creating flower language and messages

[0775] Based on the selected bouquet, the server uses natural language generation technology to gather the language of flowers and generate an inspiring message, which will further enhance the value of the gift.

[0776] 6. Display of recommendation results and messages

[0777] The terminal displays the bouquet candidates and generated messages sent from the server to the user, and the user can choose the bouquet and message they like best from multiple options.

[0778] 7. Integration with external systems for delivery

[0779] The server connects to an external delivery system to deliver the bouquet selected by the user, so that the selected bouquet is quickly delivered to the specified location.

[0780] Examples of hardware and software used:

[0781] Hardware: smartphones, tablets, servers

[0782] Software: Python, TensorFlow (AI model), Django (web framework), React Native (mobile application)

[0783] Examples:

[0784] For example, if a user wants to choose a bouquet to give for Mother's Day, they first upload a photo of the flowers they took at a florist to the server via a dedicated application. Next, they enter information about the event, "Mother's Day," their preferred colors, and their budget. The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate the optimal bouquet combination, calculates the image compatibility of each, and displays it. The user then reviews the bouquet candidates and messages containing the flower meanings, selects the most suitable bouquet, and confirms their order. The selected bouquet is then quickly delivered in conjunction with an external delivery system.

[0785] Example prompt sentence:

[0786] I'd like to choose a bouquet to give for Mother's Day. I like pink roses, and my budget is under 5,000 yen. What kind of bouquet would you recommend?

[0787] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0788] Step 1:

[0789] Users take photos of flowers using a smartphone or tablet and upload the images to the server via a dedicated application. The input is the image of the flower, and the output is the image data sent to the server. Specifically, the user presses the "upload image" button in the application, selects the image they have taken, and uploads it.

[0790] Step 2:

[0791] The server performs preprocessing on the received image data. This preprocessing includes noise removal and size adjustment. The input is the image data sent by the user, and the output is preprocessed, clear image data. Specifically, the server uses a Python library to remove noise and adjust the size of the image.

[0792] Step 3:

[0793] The server uses an AI model (e.g., a deep learning model using TensorFlow) to extract flower features from preprocessed images. The input is the preprocessed image data, and the output is feature data such as shape, color, and texture. Specifically, the server runs an image analysis algorithm to extract features.

[0794] Step 4:

[0795] The server matches the extracted features with an existing flower database. The input is the flower feature data, and the output is the matching flower information in the database. Specifically, it compares the feature data with entries in the database and uses SQL queries to find the best match.

[0796] Step 5:

[0797] The user inputs information such as event information (e.g., Mother's Day), favorite colors, and budget into the system via a terminal. The input is the event information and favorite data, and the output is request data that includes this information. Specifically, the user enters the required information into the application's input fields and presses the "Submit" button.

[0798] Step 6:

[0799] The server uses AI technology to recommend the most suitable bouquet based on the information entered by the user and the results of matching image features. The input is the user's event information and feature data, and the output is a list of suitable bouquet candidates. Specifically, it uses a machine learning algorithm to generate the optimal bouquet and calculates the suitability of each candidate.

[0800] Step 7:

[0801] The server generates a flower language and message based on the sponsored bouquet using natural language generation technology (e.g., a generative AI model). The input is information about the selected bouquet, and the output is an inspiring message. Specifically, the server generates the message using a natural language generation algorithm.

[0802] Step 8:

[0803] The terminal displays the bouquet candidate list sent from the server and the generated message to the user. The input is the bouquet candidate and the message, and the output is the screen displayed on the terminal. Specifically, the candidate list and the message are visually displayed through the user interface (UI).

[0804] Step 9:

[0805] The user selects the bouquet and message they like best from multiple options and confirms the order. The input is the user's selection data, and the output is the order confirmation data. Specifically, the user presses the "Select a bouquet" button in the application, selects the desired bouquet and message, and confirms the order.

[0806] Step 10:

[0807] The server works with an external delivery system to deliver the selected bouquet. The input is order confirmation data, and the output is delivery request data. Specifically, the server calls the API of the delivery service and issues instructions to deliver the selected bouquet.

[0808] 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.

[0809] The system of the present invention utilizes AI technology and an emotion engine to customize and suggest bouquets to be given to users for specific events based on their personal preferences and emotions. Specific embodiments of the system are described in detail below.

[0810] 1. Image input and processing

[0811] Users take photos of flowers in a flower shop using a smartphone or tablet and upload the images to the system via a dedicated application or web interface. The device receives the images and performs preprocessing such as noise reduction and size adjustment. The preprocessed images are then sent to the server.

[0812] 2. Image feature extraction and database matching

[0813] The server extracts flower features from the preprocessed images and matches this feature data with an existing flower database, which contains information such as flower variety, color, availability, and flower language. The server generates a list of matching flowers.

[0814] 3. Enter your preferences and event information

[0815] The user inputs information into the system, such as the type of event, preferred colors, budget, etc. This information is sent to the server via the terminal.

[0816] 4. Emotion Recognition by Emotion Engine

[0817] The device analyzes the user's facial expressions and voice to recognize the user's emotions. The camera is used for facial recognition and the microphone is used for voice analysis. The recognized emotion data is sent to the server.

[0818] 5. Bouquet Recommendation

[0819] The server uses AI technology to generate optimal bouquet combination candidates based on the user's emotions, preferences, event information, and database matching results. Multiple bouquet candidates are generated and their image compatibility is calculated. The data is then sent to the device.

[0820] 6. Creating flower language and messages

[0821] Based on the selected bouquet, the server collects the flower language and uses natural language generation technology to generate an inspiring poem or message, customizing the message content based on the user's recognized emotions.

[0822] 7. Displaying recommended results and messages

[0823] The terminal receives the data from the server and displays the bouquet candidates, their image compatibility, and the generated message to the user. The user can then choose the bouquet they like best from the displayed multiple options.

[0824] Specific examples

[0825] For example, if a user wants to choose a bouquet for Mother's Day, they first upload a photo of the flowers they took at a florist to the system. Next, they enter information about the Mother's Day event, their preferred colors, and their budget. The device analyzes the user's facial expressions and voice to collect emotional data. The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. The server also generates an inspiring poem or message based on the user's emotional data and sends it to the device. Finally, the device displays bouquet options and messages to the user, who then selects the most suitable bouquet and confirms their order.

[0826] This allows users to send a unique and moving bouquet that is perfect for a special event. In addition, by utilizing the emotion engine, it is possible to make suggestions that are more suited to the user's current emotions.

[0827] The processing flow will be explained below.

[0828] Step 1:

[0829] The user takes a photo of a flower in a flower shop using a smartphone or tablet, takes the photo through a dedicated application or web interface, and uploads it to the system.

[0830] Step 2:

[0831] The device receives the uploaded image, temporarily stores the image, and performs preprocessing such as noise reduction and size adjustment.

[0832] Step 3:

[0833] The device sends the preprocessed image to the server, which receives the image and performs image analysis.

[0834] Step 4:

[0835] The server extracts flower features from the image, analyzing and obtaining data such as the flower's shape, color, and texture.

[0836] Step 5:

[0837] The server compares the extracted flower characteristics with an existing flower database, which includes information such as variety, color, availability, and flower language. The result is a list of matching flowers.

[0838] Step 6:

[0839] The user uses a dedicated form to enter information such as the type of event (e.g., birthday, Mother's Day, graduation, etc.), favorite colors, budget, etc. The entered information is sent to the server via the terminal.

[0840] Step 7:

[0841] The device analyzes the user's facial expressions and voice to collect emotional data. The camera is used for facial expression analysis, and the microphone is used for voice analysis.

[0842] Step 8:

[0843] The device sends the collected emotional data to a server, which then analyzes and determines the user's emotional state.

[0844] Step 9:

[0845] The server generates optimal bouquet combination candidates based on the user's preferences, event information, emotional data, and database matching results. AI technology is used to calculate multiple bouquet candidates and their image compatibility.

[0846] Step 10:

[0847] The server generates a message based on the selected bouquet, including the meaning of flowers, a moving poem, and a message, and customizes the message based on the user's emotional data.

[0848] Step 11:

[0849] The terminal displays the bouquet candidates, image compatibility, and the generated message to the user, who can then choose the bouquet they like best from the displayed multiple options.

[0850] Step 12:

[0851] The user selects the most suitable bouquet and message and confirms the order. The confirmed order is transmitted to the server via the terminal, and the information is finally sent to the florist.

[0852] Through this process, users can easily select the perfect bouquet for a special event and send it with an inspiring message.By using the emotion engine, suggestions can be made that are more suited to the user's current emotions.

[0853] Example 2

[0854] 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."

[0855] Conventional bouquet selection systems could suggest bouquets based on a user's personal preferences and event information, but it was difficult to suggest the optimal bouquet and message that took the user's emotions into consideration. This meant that it was not possible to provide bouquets and messages that better matched the user's emotions for special events, resulting in a problem of reduced user satisfaction.

[0856] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for inputting an image and extracting flower characteristics, means for comparing the extracted flower characteristics with an existing flower database, means for inputting a user's preferences and event information, means for recommending an optimal bouquet combination based on the preferences and event information, means for acquiring user emotion data using emotion recognition technology, means for customizing the bouquet and message content using the emotion data, means for generating a flower meaning and message based on the recommended bouquet, and means for displaying the recommended bouquet and message to the user and accepting the user's selection. This makes it possible to propose an optimal bouquet and provide an inspiring message that takes the user's emotions into consideration.

[0857] "Means for inputting an image and extracting flower characteristics" refers to a technology that allows a user to upload a photo of a flower they have taken to the system and recognize characteristics such as the flower variety, color, and shape from the image.

[0858] "Means for matching extracted flower characteristics with existing flower databases" refers to technology for comparing extracted flower characteristic data with data in existing flower databases and identifying matching flower types and information.

[0859] The "means for inputting user preferences and event information" is an interface that allows the user to input personal information such as the type of event, favorite colors, budget, etc., into the system.

[0860] "Means for recommending optimal bouquet combinations based on preferences and event information" refers to a system that uses AI technology to suggest multiple bouquet combinations based on user input data.

[0861] "Means for acquiring user emotional data using emotion recognition technology" refers to technology that uses a camera or microphone to analyze the user's facial expressions and voice and recognize their emotional state.

[0862] The "means for customizing the bouquet and message content using emotional data" is a system for individually adjusting the bouquet combination and message content based on the acquired emotional data.

[0863] The "means for generating flower meanings and messages based on recommended bouquets" refers to a technology for collecting flower meanings related to the flowers based on the type of bouquet proposed, and then generating a message using natural language generation technology.

[0864] The "means for displaying recommended bouquets and messages to the user and accepting the user's selection" is an interface that displays suggested bouquet candidates and related messages to the user via the terminal, allowing the user to select the most suitable bouquet.

[0865] The system of the present invention utilizes AI technology and an emotion engine to customize bouquets to be given to users on special occasions based on their personal preferences and emotions, and makes optimal suggestions. Specific embodiments of the system are described below.

[0866] The main processing of the system is performed using the following hardware and software.

[0867] Hardware: smartphones, tablets, cameras, microphones

[0868] Software: Dedicated applications, web interfaces, image processing algorithms, AI technology, natural language generation technology

[0869] First, a user takes a photo of a flower using a smartphone or tablet. The image is then uploaded to the system via a dedicated application or web interface. The device receives the image and performs preprocessing such as noise reduction and size adjustment. The preprocessed image is then sent to the server.

[0870] The server then extracts flower features from the preprocessed image, such as the flower's variety, color, shape, etc. The feature data is then matched against an existing flower database to generate a list of matching flowers.

[0871] The user then inputs information such as the type of event (e.g., Mother's Day), favorite colors, budget, etc. This information is sent to the server via the terminal.

[0872] Furthermore, the device uses a camera to capture the user's facial expressions and a microphone to record their voice. These are analyzed to extract the user's emotional data, which is then sent to the server.

[0873] Next, the server uses AI technology to generate the optimal bouquet combination based on the user's emotional data, preferences, event information, and image feature extraction results. Multiple bouquet candidates are generated and the image compatibility of each is calculated. This data is then sent to the device.

[0874] The server then collects the meanings of the flowers in the selected bouquet and uses natural language generation technology to generate moving poems and messages, taking into account the emotional data.

[0875] Finally, the device receives the data sent from the server and displays the bouquet candidates, image compatibility, and the generated message to the user. The user can then choose the bouquet they like best from multiple options.

[0876] As a concrete example, if a user wants to choose a bouquet for Mother's Day, they would follow these steps: The user uploads a photo of flowers taken at a florist to the system and enters information about the Mother's Day event, as well as their preferred colors and budget. The device collects the user's emotional data using facial recognition and voice analysis, and the server analyzes the image and compares it with a database to identify available flowers. The server then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. The server also generates an inspiring poem or message based on the user's emotional data and sends this to the device. Finally, the device displays candidate bouquets and messages to the user, who then selects the most suitable bouquet and confirms their order.

[0877] This system allows users to send personalized and inspiring bouquets perfect for special occasions, and by utilizing an emotion engine, it can make suggestions that better suit the user's current emotions.

[0878] An example of a prompt sentence is, "Please suggest a bouquet of pink and white flowers for Mother's Day within a budget of 5,000 yen. My mother likes a message that shows gratitude." Based on this prompt sentence, the system generates the optimal bouquet and message and suggests them to the user.

[0879] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0880] Step 1: Image Input and Preprocessing

[0881] A user takes a photo of a flower with a smartphone or tablet and uploads the image to the system through a dedicated application or web interface. The input is the flower image uploaded by the user. The device receives this image and performs preprocessing such as noise removal and size adjustment. The output is the preprocessed image. This preprocessing results in image data that is easy to analyze.

[0882] What it does: The user presses the "Take a photo of a flower" button in the app, then taps the "Upload" button after taking the photo. The device then analyzes the photo, removes unwanted noise, and resizes the image appropriately.

[0883] Step 2: Image feature extraction and database matching

[0884] The server extracts flower features from the preprocessed image. The input is the preprocessed image. The server uses image processing algorithms to extract feature data such as flower color, shape, and texture. The output is the extracted feature data. This feature data is then matched against an existing flower database. It is compared with the flower information in the database and a list of matching flowers is generated. The output is a list of matching flowers.

[0885] How it works: The server uses image processing algorithms to extract features such as color histogram and shape from the input image, and then compares that information with database entries to find a match.

[0886] Step 3: Enter your user information

[0887] The user inputs information such as the type of event (e.g., Mother's Day), favorite colors, and budget into the system. The input is the event information and favorite data entered by the user. The terminal receives this information and sends it to the server. The output is the user information sent to the server. This information becomes the basic data for recommending a bouquet that meets the user's request.

[0888] Specific operation: The user enters information such as "Mother's Day," "pink and white," and "budget 5,000 yen" into the form within the app and taps the "Submit" button. The device acquires the information and sends it to the server.

[0889] Step 4: Emotion Recognition with the Emotion Engine

[0890] The device uses a camera to capture the user's facial expression and a microphone to record the audio. The input is the video and audio data of the user's facial expression. These are analyzed to extract the user's emotional data. The output is the extracted emotional data. This emotional data is sent to the server.

[0891] How it works: When a user turns on the facial recognition feature, the camera captures a few seconds of the user's facial expressions. The microphone also records the user's speech. This data is analyzed to identify emotions such as "happiness," "sadness," and "excitement."

[0892] Step 5: Recommend the bouquet

[0893] The server uses AI technology to generate the optimal bouquet combination based on the user's emotional data, preferences, event information, and image feature extraction results. The inputs are emotional data, user preference information, event information, and image feature extraction results. Multiple bouquet candidates are generated and the image compatibility of each is calculated. The output is a list of bouquet candidates and their image compatibility. This data is sent to the device.

[0894] How it works: The AI ​​model analyzes the user's input data, generates multiple candidates, such as "a bouquet of pink carnations and white roses" and "a bouquet of pink and white tulips," and calculates the suitability of each candidate (for example, a score such as "90%" or "85%).

[0895] Step 6: Creating the flower language and message

[0896] Based on the selected bouquet, the server collects the language of flowers contained in the bouquet. The input is a list of candidate bouquets and their information. An inspiring poem or message is generated using natural language generation technology. The generated message is customized taking into account the emotional data. The output is the generated message. This message is sent to the device.

[0897] Specific operation: The server looks up the meaning of flowers, such as "carnation (love)" or "rose (love)," and generates a message such as "We present a beautiful bouquet to your mother with our love and gratitude."

[0898] Step 7: Viewing Recommendations and Messages

[0899] The terminal receives data from the server and displays recommended bouquet candidates, image compatibility, and a generated message to the user. The input is the bouquet candidate list sent from the server and the generated message. The output is the bouquet candidates and message displayed to the user. The user can choose the bouquet they like best from multiple options.

[0900] Specific behavior: The device displays options to the user, such as "Bouquet of pink carnations and white roses (suitability: 90%)," and displays a generated message for each option. The user taps the "Select" button to choose the best bouquet.

[0901] (Application example 2)

[0902] 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."

[0903] Currently, there is a lack of means to recommend optimal items based on a user's preferences, emotions, and event information, and to generate customized messages for those items. Furthermore, there are no systems that can accurately convert a user's voice input into text or identify emotions from facial expressions. This makes it difficult to provide services that truly match a user's emotions and preferences.

[0904] 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.

[0905] In this invention, the server includes means for inputting an image and extracting features of an object, means for comparing the extracted features with an existing database, means for inputting a user's preferences and event information, means for recommending an optimal combination of items based on the input information, means for generating a customized message based on the recommended items, means for displaying the recommended items and message to the user and accepting the user's selection, means for collecting the user's voice input and converting the voice data into text, and means for capturing the user's facial expressions and identifying emotions from the expressions, thereby making it possible to provide more appropriate and personalized services based on the user's emotions and preferences.

[0906] "Means for inputting images" refers to the function of capturing images using an electronic device such as a camera or scanner and loading them into the system.

[0907] "Means for extracting the characteristics of an object" is a function that analyzes attributes such as the shape, color, and texture of an object from an input image and extracts them as data.

[0908] "Means for matching with existing databases" refers to a function that compares extracted feature data with existing data in the system to identify matching or similar items.

[0909] The "means for inputting user preferences and event information" is an interface for inputting information about the user's favorite elements and events (for example, favorite color, budget, type of event).

[0910] The "means for recommending the most suitable combination of items" is a function that suggests the most suitable combination of items based on the information input by the user and the collation results.

[0911] The "means for generating a customized message" is a function that uses natural language generation technology to create a message related to the recommended item.

[0912] The "means for displaying to the user and accepting selection" is an interface that displays the recommended items and generated messages to the user and allows the user to select the desired items.

[0913] The "means for collecting voice input and converting voice data into text" is a function for recording the user's voice, analyzing the voice data, and converting it into text information.

[0914] The "means for capturing facial expressions and identifying emotions from facial expressions" is a function that uses a camera to capture the user's facial expressions and analyzes the image data to identify the user's emotions.

[0915] The system according to the present invention is a system that recommends a customized menu based on personal preferences and emotions when a user uses a food delivery service. The system includes the following means.

[0916] Hardware and Software

[0917] 1. Camera-equipped smartphone

[0918] Camera: Used to capture the user's face and analyze facial expressions.

[0919] Microphone: Used to collect the user's voice input.

[0920] 2. Server

[0921] Computational resources: process image and audio data, run AI models, and match data against databases.

[0922] Framework: We use TensorFlow and Keras to run our emotion recognition and natural language generation models.

[0923] 3. Cloud Database

[0924] Stores and manages user profiles, menu data, emotion data, etc.

[0925] System action

[0926] 1. Image input and feature extraction

[0927] When a user takes a picture of their face using their smartphone camera, the system captures this image. Then, using TensorFlow and Keras, it identifies emotions from facial expressions. For example, if a user smiles into the smartphone camera, the system detects the emotion "happiness."

[0928] 2. Voice to text conversion

[0929] When a user speaks into the microphone about their desired menu or event information, the voice data is converted into text using the SpeechRecognition library. For example, if a user types "I'd like a healthy lunch, please," this is sent as text data to the server.

[0930] 3. Database matching and item recommendation

[0931] The server compares the menu data stored in the cloud database with the user's input information and emotional data, and then recommends the menu that best suits the user's situation and emotions. For example, it recommends a "healthy lunch" and salads and fruits that best suit the emotion of "joy."

[0932] 4. Customized Message Generation

[0933] Based on the recommended menu, natural language generation technology is used to generate an inspiring message, such as "Enjoy a healthy lunch and an energetic afternoon."

[0934] 5. Display and selection reception

[0935] Finally, the recommended menu and customized message sent from the server are displayed on the smartphone, and the user selects the most suitable menu and confirms the order.

[0936] Specific examples

[0937] If a user is wondering what to order at a lunch meeting, the following process takes place:

[0938] 1. The camera captures the user's facial expression, and the system recognizes the emotion as "nervous."

[0939] 2. The user dictates, "What are your food recommendations for a lunch meeting?"

[0940] 3. The speech is converted to text and sent to the server along with the user's preferences and event information.

[0941] 4. The server analyzes this and recommends an appropriate menu item, such as a light sandwich or salad.

[0942] 5. A customized message is generated, such as "Enjoy a relaxing lunch meeting with this sandwich."

[0943] Prompt Sentence Examples

[0944] "What's the best food for a lunch meeting?"

[0945] "Do you have any menu suggestions for Mother's Day dinner?"

[0946] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0947] Step 1:

[0948] A user takes a picture of their face using the smartphone camera. The input is the user's face image, and the output is the captured image data. The camera detects the user's face and sends the image data to the device.

[0949] Step 2:

[0950] The device sends the captured image data to the processing module for preprocessing for facial expression recognition. Preprocessing includes noise reduction and size adjustment. The input is the captured image data, and the output is the preprocessed image data.

[0951] Step 3:

[0952] The device sends the preprocessed image data to the server and requests emotion recognition. The server uses TensorFlow and Keras to identify emotions from facial expressions. The recognized emotion data is output.

[0953] Step 4:

[0954] The user speaks the desired menu or event information into the smartphone's microphone. The input is voice data, and the output is recorded voice data. The microphone captures the voice and sends the voice data to the terminal.

[0955] Step 5:

[0956] The device converts the recorded voice data into text data using the SpeechRecognition library. The input is voice data and the output is text data. If recognition is successful, the voice data is converted into text format.

[0957] Step 6:

[0958] The terminal sends the text data to the server and stores it as user preference and event information. The input is text data, and the output is preference information and event information stored in the server's database.

[0959] Step 7:

[0960] The server compares the menu data stored in the cloud database with the user's preference and emotion data. As a result of the comparison, optimal menu candidates are generated. The input is preference and emotion data, and the output is a recommended menu.

[0961] Step 8:

[0962] The server generates a customized message based on the generated recommended menu using natural language generation technology. The input is the recommended menu information, and the output is the customized message. The message is intended to make the menu received by the user more meaningful.

[0963] Step 9:

[0964] The server sends the recommended menu and customized message to the terminal. The input is the recommended menu and message data, and the output is the information displayed on the display screen of the terminal.

[0965] Step 10:

[0966] The terminal displays the recommended menu and customized message received from the server to the user. The user selects the menu they like best from the displayed multiple options. The input is the recommended menu and message data, and the output is the user's selection.

[0967] Step 11:

[0968] When the user selects the most suitable menu item, the terminal sends the selection information to the server, and the order is confirmed. The input is the user's selection data, and the output is order confirmation data from the server.

[0969] 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.

[0970] 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.

[0971] 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.

[0972] [Fourth embodiment]

[0973] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0974] 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.

[0975] 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).

[0976] 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.

[0977] 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.

[0978] 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).

[0979] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0980] 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.

[0981] 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.

[0982] 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.

[0983] 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.

[0984] 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.

[0985] 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."

[0986] The system of the present invention utilizes AI technology to customize and suggest bouquets to be given to users for specific events based on personal preferences and messages. Specific embodiments of the system are described in detail below.

[0987] 1. Image input and processing

[0988] Users take photos of flowers in a flower shop using a smartphone or tablet and upload them to the system. The images are sent to the server via a dedicated application or web interface. The server processes the received images, performing preprocessing such as noise reduction and resizing.

[0989] 2. Image feature extraction and database matching

[0990] The server extracts flower features from the pre-processed images, including shape, color, and texture. The extracted feature data is then compared with an existing flower database, which stores information such as variety, color, availability, and flower language, and the server identifies matching flowers.

[0991] 3. Enter your preferences and event information

[0992] The user inputs information such as the type of event, preferred colors, budget, etc. into the system. This information is entered into the terminal via the user interface and sent to the server.

[0993] 4. Recommendation of the best bouquet

[0994] The server uses AI technology to recommend the optimal bouquet combination based on the information entered by the user and the results of database comparison. Multiple bouquet candidates are generated and the image compatibility of each is displayed. The compatibility is a numerical value that indicates how well the bouquet fits the user's preferences and the event.

[0995] 5. Creating flower language and messages

[0996] Based on the selected bouquet, the server collects the meanings of flowers and uses natural language generation technology to generate moving poems and messages, further enhancing the value of the gift.

[0997] 6. Display of recommendation results and messages

[0998] The terminal displays the bouquet candidates and generated messages sent from the server to the user, and the user can choose the bouquet and message they like best from multiple options.

[0999] Specific examples

[1000] For example, if a user wants to choose a bouquet for Mother's Day, they first upload a photo of the flowers they took at a florist to the system. Next, they enter information about the Mother's Day event, their preferred colors, and their budget. The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. Finally, the device displays candidate bouquets and a message containing the meanings of the flowers to the user, who then selects the most suitable bouquet and confirms their order.

[1001] This allows users to easily choose a very unique and inspiring bouquet for a special event.

[1002] The processing flow will be explained below.

[1003] Step 1:

[1004] The user takes a photo of a flower in a flower shop using a smartphone or tablet, takes the photo through a dedicated application or web interface, and uploads it to the system.

[1005] Step 2:

[1006] The device receives the uploaded image, temporarily stores it, and performs pre-processing such as image noise reduction and resizing.

[1007] Step 3:

[1008] The device sends the preprocessed image to the server, which receives the image and performs image analysis to extract the flower's characteristics (shape, color, texture, etc.).

[1009] Step 4:

[1010] The server compares the extracted flower characteristics data with an existing flower database, which includes information such as variety, color, availability, and flower language, and generates a list of the best-matching flowers.

[1011] Step 5:

[1012] The user uses a dedicated form to enter information such as the type of event (e.g., birthday, Mother's Day, graduation, etc.), favorite colors, budget, etc. The entered information is sent to the server via the terminal.

[1013] Step 6:

[1014] The server uses AI technology to generate optimal bouquet combination candidates based on the user's input information and matching results. The server calculates the image compatibility of multiple bouquet candidates and sends the data to the device.

[1015] Step 7:

[1016] The device receives the data from the server and displays bouquet candidates and their image compatibility. The user can then choose the bouquet they like best from the multiple options displayed.

[1017] Step 8:

[1018] The server collects the meanings of the flowers based on the selected bouquet and uses natural language generation technology to generate an inspiring poem or message, which is then sent back to the device.

[1019] Step 9:

[1020] The terminal displays the generated message to the user, who then reviews the bouquet and message and makes a final selection.

[1021] Step 10:

[1022] The user selects the most suitable bouquet and message and confirms the order. The confirmed order is transmitted to the server via the terminal, and the information is finally sent to the florist.

[1023] This allows users to send a unique and inspiring bouquet that is perfect for a special event.

[1024] Example 1

[1025] 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."

[1026] Traditional flower bouquet selection methods have the drawback of making it difficult for users to choose a bouquet that best suits their preferences and the event. It's particularly difficult to understand information such as the type and color of flowers, as well as stock availability, making it time-consuming to find the perfect combination. It's even more difficult to choose a bouquet that includes a moving message, making it difficult to enhance the value of the gift.

[1027] 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.

[1028] In this invention, the server includes means for inputting an image and extracting flower characteristics, means for comparing the extracted flower characteristics with an existing flower database, means for inputting a user's preferences and event information, means for recommending an optimal bouquet combination based on the preferences and event information, means for performing image preprocessing such as noise reduction and size adjustment, means for generating a flower meaning and message based on the recommended bouquet, means for generating an inspiring message using natural language generation technology, means for displaying the recommended bouquet and message to the user and accepting the user's selection, and means for displaying multiple candidates and their respective image suitability. This allows the user to easily select the optimal bouquet based on their preferences or a specific event, and further enhances the value of the bouquet as a gift by adding an inspiring message.

[1029] "Means for inputting an image and extracting flower characteristics" refers to a technology that analyzes a flower image provided by a user and extracts characteristics such as the type, color, shape, and texture of the flower from the image.

[1030] "Means for matching extracted flower characteristics with existing flower databases" refers to technology that uses extracted flower characteristic data to compare and match with information in existing flower databases that have been registered in advance.

[1031] "Means for inputting user preferences and event information" refers to the technology that allows users to input their preferences and specific event information (such as birthdays, weddings, Mother's Day, etc.) through an input form and transmit this information to the system.

[1032] "Means for recommending optimal bouquet combinations based on preferences and event information" refers to technology that uses AI technology to suggest multiple optimal bouquet combinations based on input user preferences and event information and database information.

[1033] "Means for noise removal and size adjustment as image preprocessing" refers to technology that removes noise from images and resizes them to an appropriate size to make images uploaded by users easier to analyze.

[1034] "Means for generating flower meanings and messages based on recommended bouquets" refers to technology that collects related flower meanings based on the proposed bouquet combination and generates a matching message or poem.

[1035] "Means for generating inspirational messages using natural language generation technology" refers to technology that utilizes natural language generation technology, such as a generative AI model, to automatically create inspirational messages or poems related to a specific bouquet of flowers.

[1036] "Means for displaying recommended bouquets and messages to the user and accepting the user's selection" refers to a technology in which the system displays the bouquet combinations suggested by the system and the generated message on the user's device, allowing the user to make the optimal selection and have it accepted by the system.

[1037] "Means for displaying multiple candidates and their respective image suitability" refers to a technology that visually displays multiple bouquet combination candidates and the suitability that indicates how well each bouquet suits the user's preferences or the event.

[1038] The present invention is a system that uses AI technology to customize and suggest bouquets to send to users for specific events based on personal preferences and messages. This system can be implemented using various hardware and software described below.

[1039] First, a user takes a photo of a particular flower at a florist using a smartphone or tablet, and then uploads the image to the server via a dedicated application or web interface, which sends the user's input data and image data to the server.

[1040] The server preprocesses the received images by removing noise and adjusting the size. For example, an image processing library such as OpenCV can be used for this process. Next, features such as color, shape, and texture are extracted from the preprocessed images. Deep learning techniques such as Convolutional Neural Network (CNN) can be used for this process.

[1041] The extracted feature data is compared with the flower database stored in the system, which stores detailed information about each flower, such as its variety, color, stock status, and flower language. The server compares the data with the database information to identify similar flowers.

[1042] Next, the user provides the system with personal information such as the type of event (e.g., birthday, wedding, Mother's Day, etc.), favorite colors, and budget through an input form. This information is sent from the terminal to the server.

[1043] The server uses an AI algorithm to recommend the optimal bouquet combination based on the user's preferences, event information, and matching results. Using collaborative filtering and recommender system techniques, multiple bouquet candidates are automatically generated and the image compatibility of each is calculated. Compatibility can be displayed using numerical scores or visual graphs.

[1044] The server then collects relevant flower meanings based on the recommended bouquet information and uses natural language generation technology (e.g., a generative AI model such as GPT-3) to generate an inspiring message, which can include a poem or a congratulatory message.

[1045] Finally, the terminal displays the bouquet options sent from the server and the generated message to the user, who can then choose the one they like best and place the order immediately.

[1046] Specific examples

[1047] For example, if a user wants to choose a bouquet for Mother's Day, they first upload a photo of the flowers they took at a florist to the system. Next, they enter the event information, "Mother's Day," along with their preferred colors (e.g., pink or white) and budget (e.g., under 5,000 yen). The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. Finally, the device displays candidate bouquets and a message containing the flower meanings to the user, who then selects the most suitable bouquet and confirms their order.

[1048] Prompt Sentence Examples

[1049] "I'd like to choose an inspiring bouquet for Mother's Day. I'd like to focus on pink flowers and keep the budget under 5,000 yen."

[1050] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1051] Step 1: Image Input and Preprocessing

[1052] Users upload photos of flowers taken at a florist to the system via a dedicated application or a web interface, and the terminal then sends the image data to the server.

[1053] The server performs noise reduction and size adjustment on the received image. Specifically, it uses OpenCV to remove noise and resize it to an appropriate size. As a result, the input is the flower image taken by the user, and the output is the preprocessed image.

[1054] Step 2: Image feature extraction and database matching

[1055] The server extracts features such as color, shape, and texture from the preprocessed image using a Convolutional Neural Network (CNN). The extracted feature data is then compared with the system's flower database.

[1056] Specifically, we generate a feature vector for each image and compare it with the feature vectors in the database. From this comparison, the input is the preprocessed image, and the output is the information on similar flowers.

[1057] Step 3: Enter your user information

[1058] The user provides information such as the type of event (e.g., birthday, wedding, Mother's Day), preferred colors, and budget to the system through an input form.

[1059] The terminal transmits this user information to the server in real time. The input is event information and preference data from the user, and the output is the user information transmitted to the server.

[1060] Step 4: Recommend the perfect bouquet

[1061] The server uses AI algorithms to generate the optimal bouquet combination based on the user's preferences, event information, and matching results, using collaborative filtering and recommender system techniques.

[1062] Specifically, multiple bouquet candidates are generated from the collected feature data and user information, and the image compatibility of each is calculated. The input is user information and feature data, and the output is bouquet candidates and compatibility.

[1063] Step 5: Creating the flower language and message

[1064] The server collects relevant flower meanings based on the recommended bouquet information and generates an inspirational message using a generative AI model (e.g., GPT-3).

[1065] Specifically, the system selects the flower language based on the combination of flowers in the bouquet and generates a message using natural language generation technology. The input is the bouquet information, and the output is the generated message.

[1066] Step 6: View and select recommendations

[1067] The terminal displays the bouquet candidates sent from the server and the generated message to the user, who then selects the bouquet he or she likes best and confirms the order.

[1068] Specifically, it displays bouquets and messages on the terminal screen and provides a selectable interface. The input is bouquet candidates and messages, and the output is the user's selection.

[1069] (Application example 1)

[1070] 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."

[1071] Conventional bouquet selection systems have the problem that they do not allow sufficient customization or personalization when users select the perfect bouquet for a specific event or preference. Also, the process of delivering the created bouquet and message is time-consuming, which makes it inconvenient for users.

[1072] 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.

[1073] In this invention, the server includes means for inputting an image and extracting flower characteristics, means for comparing the extracted flower characteristics with an existing flower database, means for inputting a user's preferences and event information, means for recommending an optimal bouquet combination based on the preferences and event information, means for generating a flower meaning and a message based on the recommended bouquet, means for displaying the recommended bouquet and message to the user and accepting the user's selection, and means for coordinating with an external delivery system to deliver the selected bouquet. This allows the user to easily select a customized bouquet according to a specific event or preference, and then have the bouquet delivered quickly.

[1074] The "means for inputting images" is a mechanism for users to upload photos of flowers they have taken to the system.

[1075] The "means for extracting flower characteristics" is a technology for analyzing information such as flower shape, color, and texture from uploaded images.

[1076] "Means for matching with an existing flower database" refers to a technique for comparing extracted feature information with information on flowers registered in a database to identify matching flowers.

[1077] The "means for inputting user preferences and event information" refers to an interface that allows a user to input information about their preferences and specific events, such as color preferences and budget, into the system.

[1078] "Means for recommending the best bouquet combination" refers to a technology in which AI recommends the best combination of flowers based on the information entered by the user and the matching results.

[1079] The "means for generating flower meanings and messages" is a technology that automatically generates flower meanings and moving messages based on recommended bouquets.

[1080] The "means for displaying to the user and accepting the user's selection" is an interface that visually displays the recommended bouquet and the generated message to the user, allowing the user to make the optimal selection.

[1081] The "means for coordinating with an external delivery system" is a technology for communicating with and coordinating with an external delivery service in order to deliver the selected bouquet to the specified location.

[1082] The system of the present invention utilizes AI technology to customize and suggest bouquets to send to users for specific events based on personal preferences and messages. This system is realized by combining the following components:

[1083] 1. Image input and processing

[1084] Users take photos of flowers using a smartphone or tablet and upload them to the server via a dedicated application. The server receives the images and performs preprocessing such as noise reduction and resizing.

[1085] 2. Image feature extraction and database matching

[1086] The server extracts flower features (shape, color, texture, etc.) from the preprocessed images. The extracted features are matched with an existing flower database, which includes information such as flower variety, color, availability, and flower language.

[1087] 3. Enter your preferences and event information

[1088] The user inputs information such as the type of event (e.g., Mother's Day), favorite colors, budget, etc. This information is sent to the server via a dedicated application.

[1089] 4. Recommendation of the best bouquet

[1090] The server uses AI technology to recommend the most suitable bouquet based on the results of matching the user's input information with image features. Multiple candidates are generated and the image compatibility of each is displayed. This compatibility is a numerical representation of how well the flower characteristics match the user's preferences and event information.

[1091] 5. Creating flower language and messages

[1092] Based on the selected bouquet, the server uses natural language generation technology to gather the language of flowers and generate an inspiring message, which will further enhance the value of the gift.

[1093] 6. Display of recommendation results and messages

[1094] The terminal displays the bouquet candidates and generated messages sent from the server to the user, and the user can choose the bouquet and message they like best from multiple options.

[1095] 7. Integration with external systems for delivery

[1096] The server connects to an external delivery system to deliver the bouquet selected by the user, so that the selected bouquet is quickly delivered to the specified location.

[1097] Examples of hardware and software used:

[1098] Hardware: smartphones, tablets, servers

[1099] Software: Python, TensorFlow (AI model), Django (web framework), React Native (mobile application)

[1100] Examples:

[1101] For example, if a user wants to choose a bouquet to give for Mother's Day, they first upload a photo of the flowers they took at a florist to the server via a dedicated application. Next, they enter information about the event, "Mother's Day," their preferred colors, and their budget. The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate the optimal bouquet combination, calculates the image compatibility of each, and displays it. The user then reviews the bouquet candidates and messages containing the flower meanings, selects the most suitable bouquet, and confirms their order. The selected bouquet is then quickly delivered in conjunction with an external delivery system.

[1102] Example prompt sentence:

[1103] I'd like to choose a bouquet to give for Mother's Day. I like pink roses, and my budget is under 5,000 yen. What kind of bouquet would you recommend?

[1104] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1105] Step 1:

[1106] Users take photos of flowers using a smartphone or tablet and upload the images to the server via a dedicated application. The input is the image of the flower, and the output is the image data sent to the server. Specifically, the user presses the "upload image" button in the application, selects the image they have taken, and uploads it.

[1107] Step 2:

[1108] The server performs preprocessing on the received image data. This preprocessing includes noise removal and size adjustment. The input is the image data sent by the user, and the output is preprocessed, clear image data. Specifically, the server uses a Python library to remove noise and adjust the size of the image.

[1109] Step 3:

[1110] The server uses an AI model (e.g., a deep learning model using TensorFlow) to extract flower features from preprocessed images. The input is the preprocessed image data, and the output is feature data such as shape, color, and texture. Specifically, the server runs an image analysis algorithm to extract features.

[1111] Step 4:

[1112] The server matches the extracted features with an existing flower database. The input is the flower feature data, and the output is the matching flower information in the database. Specifically, it compares the feature data with entries in the database and uses SQL queries to find the best match.

[1113] Step 5:

[1114] The user inputs information such as event information (e.g., Mother's Day), favorite colors, and budget into the system via a terminal. The input is the event information and favorite data, and the output is request data that includes this information. Specifically, the user enters the required information into the application's input fields and presses the "Submit" button.

[1115] Step 6:

[1116] The server uses AI technology to recommend the most suitable bouquet based on the information entered by the user and the results of matching image features. The input is the user's event information and feature data, and the output is a list of suitable bouquet candidates. Specifically, it uses a machine learning algorithm to generate the optimal bouquet and calculates the suitability of each candidate.

[1117] Step 7:

[1118] The server generates a flower language and message based on the sponsored bouquet using natural language generation technology (e.g., a generative AI model). The input is information about the selected bouquet, and the output is an inspiring message. Specifically, the server generates the message using a natural language generation algorithm.

[1119] Step 8:

[1120] The terminal displays the bouquet candidate list sent from the server and the generated message to the user. The input is the bouquet candidate and the message, and the output is the screen displayed on the terminal. Specifically, the candidate list and the message are visually displayed through the user interface (UI).

[1121] Step 9:

[1122] The user selects the bouquet and message they like best from multiple options and confirms the order. The input is the user's selection data, and the output is the order confirmation data. Specifically, the user presses the "Select a bouquet" button in the application, selects the desired bouquet and message, and confirms the order.

[1123] Step 10:

[1124] The server works with an external delivery system to deliver the selected bouquet. The input is order confirmation data, and the output is delivery request data. Specifically, the server calls the API of the delivery service and issues instructions to deliver the selected bouquet.

[1125] 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.

[1126] The system of the present invention utilizes AI technology and an emotion engine to customize and suggest bouquets to be given to users for specific events based on their personal preferences and emotions. Specific embodiments of the system are described in detail below.

[1127] 1. Image input and processing

[1128] Users take photos of flowers in a flower shop using a smartphone or tablet and upload the images to the system via a dedicated application or web interface. The device receives the images and performs preprocessing such as noise reduction and size adjustment. The preprocessed images are then sent to the server.

[1129] 2. Image feature extraction and database matching

[1130] The server extracts flower features from the preprocessed images and matches this feature data with an existing flower database, which contains information such as flower variety, color, availability, and flower language. The server generates a list of matching flowers.

[1131] 3. Enter your preferences and event information

[1132] The user inputs information into the system, such as the type of event, preferred colors, budget, etc. This information is sent to the server via the terminal.

[1133] 4. Emotion Recognition by Emotion Engine

[1134] The device analyzes the user's facial expressions and voice to recognize the user's emotions. The camera is used for facial recognition and the microphone is used for voice analysis. The recognized emotion data is sent to the server.

[1135] 5. Bouquet Recommendation

[1136] The server uses AI technology to generate optimal bouquet combination candidates based on the user's emotions, preferences, event information, and database matching results. Multiple bouquet candidates are generated and their image compatibility is calculated. The data is then sent to the device.

[1137] 6. Creating flower language and messages

[1138] Based on the selected bouquet, the server collects the flower language and uses natural language generation technology to generate an inspiring poem or message, customizing the message content based on the user's recognized emotions.

[1139] 7. Displaying recommended results and messages

[1140] The terminal receives the data from the server and displays the bouquet candidates, their image compatibility, and the generated message to the user. The user can then choose the bouquet they like best from the displayed multiple options.

[1141] Specific examples

[1142] For example, if a user wants to choose a bouquet for Mother's Day, they first upload a photo of the flowers they took at a florist to the system. Next, they enter information about the Mother's Day event, their preferred colors, and their budget. The device analyzes the user's facial expressions and voice to collect emotional data. The server analyzes the image and compares it with a database to identify available flowers. It then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. The server also generates an inspiring poem or message based on the user's emotional data and sends it to the device. Finally, the device displays bouquet options and messages to the user, who then selects the most suitable bouquet and confirms their order.

[1143] This allows users to send a unique and moving bouquet that is perfect for a special event. In addition, by utilizing the emotion engine, it is possible to make suggestions that are more suited to the user's current emotions.

[1144] The processing flow will be explained below.

[1145] Step 1:

[1146] The user takes a photo of a flower in a flower shop using a smartphone or tablet, takes the photo through a dedicated application or web interface, and uploads it to the system.

[1147] Step 2:

[1148] The device receives the uploaded image, temporarily stores the image, and performs preprocessing such as noise reduction and size adjustment.

[1149] Step 3:

[1150] The device sends the preprocessed image to the server, which receives the image and performs image analysis.

[1151] Step 4:

[1152] The server extracts flower features from the image, analyzing and obtaining data such as the flower's shape, color, and texture.

[1153] Step 5:

[1154] The server compares the extracted flower characteristics with an existing flower database, which includes information such as variety, color, availability, and flower language. The result is a list of matching flowers.

[1155] Step 6:

[1156] The user uses a dedicated form to enter information such as the type of event (e.g., birthday, Mother's Day, graduation, etc.), favorite colors, budget, etc. The entered information is sent to the server via the terminal.

[1157] Step 7:

[1158] The device analyzes the user's facial expressions and voice to collect emotional data. The camera is used for facial expression analysis, and the microphone is used for voice analysis.

[1159] Step 8:

[1160] The device sends the collected emotional data to a server, which then analyzes and determines the user's emotional state.

[1161] Step 9:

[1162] The server generates optimal bouquet combination candidates based on the user's preferences, event information, emotional data, and database matching results. AI technology is used to calculate multiple bouquet candidates and their image compatibility.

[1163] Step 10:

[1164] The server generates a message based on the selected bouquet, including the meaning of flowers, a moving poem, and a message, and customizes the message based on the user's emotional data.

[1165] Step 11:

[1166] The terminal displays the bouquet candidates, image compatibility, and the generated message to the user, who can then choose the bouquet they like best from the displayed multiple options.

[1167] Step 12:

[1168] The user selects the most suitable bouquet and message and confirms the order. The confirmed order is transmitted to the server via the terminal, and the information is finally sent to the florist.

[1169] Through this process, users can easily select the perfect bouquet for a special event and send it with an inspiring message.By using the emotion engine, suggestions can be made that are more suited to the user's current emotions.

[1170] Example 2

[1171] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1172] Conventional bouquet selection systems could suggest bouquets based on a user's personal preferences and event information, but it was difficult to suggest the optimal bouquet and message that took the user's emotions into consideration. This meant that it was not possible to provide bouquets and messages that better matched the user's emotions for special events, resulting in a problem of reduced user satisfaction.

[1173] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for inputting an image and extracting flower characteristics, means for comparing the extracted flower characteristics with an existing flower database, means for inputting a user's preferences and event information, means for recommending an optimal bouquet combination based on the preferences and event information, means for acquiring user emotion data using emotion recognition technology, means for customizing the bouquet and message content using the emotion data, means for generating a flower meaning and message based on the recommended bouquet, and means for displaying the recommended bouquet and message to the user and accepting the user's selection. This makes it possible to propose an optimal bouquet and provide an inspiring message that takes the user's emotions into consideration.

[1174] "Means for inputting an image and extracting flower characteristics" refers to a technology that allows a user to upload a photo of a flower they have taken to the system and recognize characteristics such as the flower variety, color, and shape from the image.

[1175] "Means for matching extracted flower characteristics with existing flower databases" refers to technology for comparing extracted flower characteristic data with data in existing flower databases and identifying matching flower types and information.

[1176] The "means for inputting user preferences and event information" is an interface that allows the user to input personal information such as the type of event, favorite colors, budget, etc., into the system.

[1177] "Means for recommending optimal bouquet combinations based on preferences and event information" refers to a system that uses AI technology to suggest multiple bouquet combinations based on user input data.

[1178] "Means for acquiring user emotional data using emotion recognition technology" refers to technology that uses a camera or microphone to analyze the user's facial expressions and voice and recognize their emotional state.

[1179] The "means for customizing the bouquet and message content using emotional data" is a system for individually adjusting the bouquet combination and message content based on the acquired emotional data.

[1180] The "means for generating flower meanings and messages based on recommended bouquets" refers to a technology for collecting flower meanings related to the flowers based on the type of bouquet proposed, and then generating a message using natural language generation technology.

[1181] The "means for displaying recommended bouquets and messages to the user and accepting the user's selection" is an interface that displays suggested bouquet candidates and related messages to the user via the terminal, allowing the user to select the most suitable bouquet.

[1182] The system of the present invention utilizes AI technology and an emotion engine to customize bouquets to be given to users on special occasions based on their personal preferences and emotions, and makes optimal suggestions. Specific embodiments of the system are described below.

[1183] The main processing of the system is performed using the following hardware and software.

[1184] Hardware: smartphones, tablets, cameras, microphones

[1185] Software: Dedicated applications, web interfaces, image processing algorithms, AI technology, natural language generation technology

[1186] First, a user takes a photo of a flower using a smartphone or tablet. The image is then uploaded to the system via a dedicated application or web interface. The device receives the image and performs preprocessing such as noise reduction and size adjustment. The preprocessed image is then sent to the server.

[1187] The server then extracts flower features from the preprocessed image, such as the flower's variety, color, shape, etc. The feature data is then matched against an existing flower database to generate a list of matching flowers.

[1188] The user then inputs information such as the type of event (e.g., Mother's Day), favorite colors, budget, etc. This information is sent to the server via the terminal.

[1189] Furthermore, the device uses a camera to capture the user's facial expressions and a microphone to record their voice. These are analyzed to extract the user's emotional data, which is then sent to the server.

[1190] Next, the server uses AI technology to generate the optimal bouquet combination based on the user's emotional data, preferences, event information, and image feature extraction results. Multiple bouquet candidates are generated and the image compatibility of each is calculated. This data is then sent to the device.

[1191] The server then collects the meanings of the flowers in the selected bouquet and uses natural language generation technology to generate moving poems and messages, taking into account the emotional data.

[1192] Finally, the device receives the data sent from the server and displays the bouquet candidates, image compatibility, and the generated message to the user. The user can then choose the bouquet they like best from multiple options.

[1193] As a concrete example, if a user wants to choose a bouquet for Mother's Day, they would follow these steps: The user uploads a photo of flowers taken at a florist to the system and enters information about the Mother's Day event, as well as their preferred colors and budget. The device collects the user's emotional data using facial recognition and voice analysis, and the server analyzes the image and compares it with a database to identify available flowers. The server then uses AI technology to generate optimal bouquet combinations and calculates the image compatibility of each. The server also generates an inspiring poem or message based on the user's emotional data and sends this to the device. Finally, the device displays candidate bouquets and messages to the user, who then selects the most suitable bouquet and confirms their order.

[1194] This system allows users to send personalized and inspiring bouquets perfect for special occasions, and by utilizing an emotion engine, it can make suggestions that better suit the user's current emotions.

[1195] An example of a prompt sentence is, "Please suggest a bouquet of pink and white flowers for Mother's Day within a budget of 5,000 yen. My mother likes a message that shows gratitude." Based on this prompt sentence, the system generates the optimal bouquet and message and suggests them to the user.

[1196] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1197] Step 1: Image Input and Preprocessing

[1198] A user takes a photo of a flower with a smartphone or tablet and uploads the image to the system through a dedicated application or web interface. The input is the flower image uploaded by the user. The device receives this image and performs preprocessing such as noise removal and size adjustment. The output is the preprocessed image. This preprocessing results in image data that is easy to analyze.

[1199] What it does: The user presses the "Take a photo of a flower" button in the app, then taps the "Upload" button after taking the photo. The device then analyzes the photo, removes unwanted noise, and resizes the image appropriately.

[1200] Step 2: Image feature extraction and database matching

[1201] The server extracts flower features from the preprocessed image. The input is the preprocessed image. The server uses image processing algorithms to extract feature data such as flower color, shape, and texture. The output is the extracted feature data. This feature data is then matched against an existing flower database. It is compared with the flower information in the database and a list of matching flowers is generated. The output is a list of matching flowers.

[1202] How it works: The server uses image processing algorithms to extract features such as color histogram and shape from the input image, and then compares that information with database entries to find a match.

[1203] Step 3: Enter your user information

[1204] The user inputs information such as the type of event (e.g., Mother's Day), favorite colors, and budget into the system. The input is the event information and favorite data entered by the user. The terminal receives this information and sends it to the server. The output is the user information sent to the server. This information becomes the basic data for recommending a bouquet that meets the user's request.

[1205] Specific operation: The user enters information such as "Mother's Day," "pink and white," and "budget 5,000 yen" into the form within the app and taps the "Submit" button. The device acquires the information and sends it to the server.

[1206] Step 4: Emotion Recognition with the Emotion Engine

[1207] The device uses a camera to capture the user's facial expression and a microphone to record the audio. The input is the video and audio data of the user's facial expression. These are analyzed to extract the user's emotional data. The output is the extracted emotional data. This emotional data is sent to the server.

[1208] How it works: When a user turns on the facial recognition feature, the camera captures a few seconds of the user's facial expressions. The microphone also records the user's speech. This data is analyzed to identify emotions such as "happiness," "sadness," and "excitement."

[1209] Step 5: Recommend the bouquet

[1210] The server uses AI technology to generate the optimal bouquet combination based on the user's emotional data, preferences, event information, and image feature extraction results. The inputs are emotional data, user preference information, event information, and image feature extraction results. Multiple bouquet candidates are generated and the image compatibility of each is calculated. The output is a list of bouquet candidates and their image compatibility. This data is sent to the device.

[1211] How it works: The AI ​​model analyzes the user's input data, generates multiple candidates, such as "a bouquet of pink carnations and white roses" and "a bouquet of pink and white tulips," and calculates the suitability of each candidate (for example, a score such as "90%" or "85%).

[1212] Step 6: Creating the flower language and message

[1213] Based on the selected bouquet, the server collects the language of flowers contained in the bouquet. The input is a list of candidate bouquets and their information. An inspiring poem or message is generated using natural language generation technology. The generated message is customized taking into account the emotional data. The output is the generated message. This message is sent to the device.

[1214] Specific operation: The server looks up the meaning of flowers, such as "carnation (love)" or "rose (love)," and generates a message such as "We present a beautiful bouquet to your mother with our love and gratitude."

[1215] Step 7: Viewing Recommendations and Messages

[1216] The terminal receives data from the server and displays recommended bouquet candidates, image compatibility, and a generated message to the user. The input is the bouquet candidate list sent from the server and the generated message. The output is the bouquet candidates and message displayed to the user. The user can choose the bouquet they like best from multiple options.

[1217] Specific behavior: The device displays options to the user, such as "Bouquet of pink carnations and white roses (suitability: 90%)," and displays a generated message for each option. The user taps the "Select" button to choose the best bouquet.

[1218] (Application example 2)

[1219] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1220] Currently, there is a lack of means to recommend optimal items based on a user's preferences, emotions, and event information, and to generate customized messages for those items. Furthermore, there are no systems that can accurately convert a user's voice input into text or identify emotions from facial expressions. This makes it difficult to provide services that truly match a user's emotions and preferences.

[1221] 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.

[1222] In this invention, the server includes means for inputting an image and extracting features of an object, means for comparing the extracted features with an existing database, means for inputting a user's preferences and event information, means for recommending an optimal combination of items based on the input information, means for generating a customized message based on the recommended items, means for displaying the recommended items and message to the user and accepting the user's selection, means for collecting the user's voice input and converting the voice data into text, and means for capturing the user's facial expressions and identifying emotions from the expressions, thereby making it possible to provide more appropriate and personalized services based on the user's emotions and preferences.

[1223] "Means for inputting images" refers to the function of capturing images using an electronic device such as a camera or scanner and loading them into the system.

[1224] "Means for extracting the characteristics of an object" is a function that analyzes attributes such as the shape, color, and texture of an object from an input image and extracts them as data.

[1225] "Means for matching with existing databases" refers to a function that compares extracted feature data with existing data in the system to identify matching or similar items.

[1226] The "means for inputting user preferences and event information" is an interface for inputting information about the user's favorite elements and events (for example, favorite color, budget, type of event).

[1227] The "means for recommending the most suitable combination of items" is a function that suggests the most suitable combination of items based on the information input by the user and the collation results.

[1228] The "means for generating a customized message" is a function that uses natural language generation technology to create a message related to the recommended item.

[1229] The "means for displaying to the user and accepting selection" is an interface that displays the recommended items and generated messages to the user and allows the user to select the desired items.

[1230] The "means for collecting voice input and converting voice data into text" is a function for recording the user's voice, analyzing the voice data, and converting it into text information.

[1231] The "means for capturing facial expressions and identifying emotions from facial expressions" is a function that uses a camera to capture the user's facial expressions and analyzes the image data to identify the user's emotions.

[1232] The system according to the present invention is a system that recommends a customized menu based on personal preferences and emotions when a user uses a food delivery service. The system includes the following means.

[1233] Hardware and Software

[1234] 1. Camera-equipped smartphone

[1235] Camera: Used to capture the user's face and analyze facial expressions.

[1236] Microphone: Used to collect the user's voice input.

[1237] 2. Server

[1238] Computational resources: process image and audio data, run AI models, and match data against databases.

[1239] Framework: We use TensorFlow and Keras to run our emotion recognition and natural language generation models.

[1240] 3. Cloud Database

[1241] Stores and manages user profiles, menu data, emotion data, etc.

[1242] System action

[1243] 1. Image input and feature extraction

[1244] When a user takes a picture of their face using their smartphone camera, the system captures this image. Then, using TensorFlow and Keras, it identifies emotions from facial expressions. For example, if a user smiles into the smartphone camera, the system detects the emotion "happiness."

[1245] 2. Voice to text conversion

[1246] When a user speaks into the microphone about their desired menu or event information, the voice data is converted into text using the SpeechRecognition library. For example, if a user types "I'd like a healthy lunch, please," this is sent as text data to the server.

[1247] 3. Database matching and item recommendation

[1248] The server compares the menu data stored in the cloud database with the user's input information and emotional data, and then recommends the menu that best suits the user's situation and emotions. For example, it recommends a "healthy lunch" and salads and fruits that best suit the emotion of "joy."

[1249] 4. Customized Message Generation

[1250] Based on the recommended menu, natural language generation technology is used to generate an inspiring message, such as "Enjoy a healthy lunch and an energetic afternoon."

[1251] 5. Display and selection reception

[1252] Finally, the recommended menu and customized message sent from the server are displayed on the smartphone, and the user selects the most suitable menu and confirms the order.

[1253] Specific examples

[1254] If a user is wondering what to order at a lunch meeting, the following process takes place:

[1255] 1. The camera captures the user's facial expression, and the system recognizes the emotion as "nervous."

[1256] 2. The user dictates, "What are your food recommendations for a lunch meeting?"

[1257] 3. The speech is converted to text and sent to the server along with the user's preferences and event information.

[1258] 4. The server analyzes this and recommends an appropriate menu item, such as a light sandwich or salad.

[1259] 5. A customized message is generated, such as "Enjoy a relaxing lunch meeting with this sandwich."

[1260] Prompt Sentence Examples

[1261] "What's the best food for a lunch meeting?"

[1262] "Do you have any menu suggestions for Mother's Day dinner?"

[1263] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1264] Step 1:

[1265] A user takes a picture of their face using the smartphone camera. The input is the user's face image, and the output is the captured image data. The camera detects the user's face and sends the image data to the device.

[1266] Step 2:

[1267] The device sends the captured image data to the processing module for preprocessing for facial expression recognition. Preprocessing includes noise reduction and size adjustment. The input is the captured image data, and the output is the preprocessed image data.

[1268] Step 3:

[1269] The device sends the preprocessed image data to the server and requests emotion recognition. The server uses TensorFlow and Keras to identify emotions from facial expressions. The recognized emotion data is output.

[1270] Step 4:

[1271] The user speaks the desired menu or event information into the smartphone's microphone. The input is voice data, and the output is recorded voice data. The microphone captures the voice and sends the voice data to the terminal.

[1272] Step 5:

[1273] The device converts the recorded voice data into text data using the SpeechRecognition library. The input is voice data and the output is text data. If recognition is successful, the voice data is converted into text format.

[1274] Step 6:

[1275] The terminal sends the text data to the server and stores it as user preference and event information. The input is text data, and the output is preference information and event information stored in the server's database.

[1276] Step 7:

[1277] The server compares the menu data stored in the cloud database with the user's preference and emotion data. As a result of the comparison, optimal menu candidates are generated. The input is preference and emotion data, and the output is a recommended menu.

[1278] Step 8:

[1279] The server generates a customized message based on the generated recommended menu using natural language generation technology. The input is the recommended menu information, and the output is the customized message. The message is intended to make the menu received by the user more meaningful.

[1280] Step 9:

[1281] The server sends the recommended menu and customized message to the terminal. The input is the recommended menu and message data, and the output is the information displayed on the display screen of the terminal.

[1282] Step 10:

[1283] The terminal displays the recommended menu and customized message received from the server to the user. The user selects the menu they like best from the displayed multiple options. The input is the recommended menu and message data, and the output is the user's selection.

[1284] Step 11:

[1285] When the user selects the most suitable menu item, the terminal sends the selection information to the server, and the order is confirmed. The input is the user's selection data, and the output is order confirmation data from the server.

[1286] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1287] 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.

[1288] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1289] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1290] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1291] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1292] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1293] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1294] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1295] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1296] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1297] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1298] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1299] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1300] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1301] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1302] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1303] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1304] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1305] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1306] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1307] The following is further disclosed regarding the above embodiment.

[1308] (Claim 1)

[1309] A means for inputting an image and extracting characteristics of a flower;

[1310] means for matching the extracted flower features with an existing flower database;

[1311] a means for inputting user preferences and event information;

[1312] A method to recommend the best bouquet combination based on preferences and event information,

[1313] A means for generating a flower language or message based on the recommended bouquet;

[1314] means for displaying the recommended bouquets and messages to the user and accepting the user's selection;

[1315] A system including:

[1316] (Claim 2)

[1317] 2. The system of claim 1, further comprising means for displaying a plurality of candidates and their respective image suitability scores in recommending bouquets.

[1318] (Claim 3)

[1319] The system according to claim 1, wherein the generated flower language and messages are generated using natural language generation technology to create moving poems and haiku.

[1320] "Example 1"

[1321] (Claim 1)

[1322] A means for inputting an image and extracting characteristics of a flower;

[1323] means for matching the extracted flower features with an existing flower database;

[1324] a means for inputting user preferences and event information;

[1325] A method to recommend the best bouquet combination based on preferences and event information,

[1326] A means for generating a flower language or message based on the recommended bouquet;

[1327] means for displaying the recommended bouquets and messages to the user and accepting the user's selection;

[1328] A method for preprocessing images to remove noise and adjust size,

[1329] A means for generating bouquet combinations using AI technology;

[1330] A means for generating inspirational messages using natural language generation technology;

[1331] A system including:

[1332] (Claim 2)

[1333] 2. The system of claim 1, further comprising means for displaying a plurality of candidates and their respective image suitability scores in recommending bouquets.

[1334] (Claim 3)

[1335] The system according to claim 1, wherein the generated flower language and message are inspiring messages generated using natural language generation technology.

[1336] "Application Example 1"

[1337] (Claim 1)

[1338] A means for inputting an image and extracting characteristics of a flower;

[1339] means for matching the extracted flower features with an existing flower database;

[1340] a means for inputting user preferences and event information;

[1341] A method to recommend the best bouquet combination based on preferences and event information,

[1342] A means for generating a flower language or message based on the recommended bouquet;

[1343] means for displaying the recommended bouquets and messages to the user and accepting the user's selection;

[1344] means for interfacing with an external delivery system to deliver the selected bouquet;

[1345] A system including:

[1346] (Claim 2)

[1347] 2. The system of claim 1, further comprising means for displaying a plurality of candidates and their respective image suitability scores in recommending bouquets.

[1348] (Claim 3)

[1349] The system according to claim 1, wherein the generated flower language and messages are generated using natural language generation technology to create moving poems and haiku.

[1350] "Example 2: Combining Emotion Engines"

[1351] (Claim 1)

[1352] A means for inputting an image and extracting characteristics of a flower;

[1353] means for matching the extracted flower features with an existing flower database;

[1354] a means for inputting user preferences and event information;

[1355] A method to recommend the best bouquet combination based on preferences and event information,

[1356] A means for generating a flower language or message based on the recommended bouquet;

[1357] A means for acquiring user emotion data using emotion recognition technology;

[1358] A way to customize bouquets and messages using emotional data;

[1359] means for displaying the recommended bouquets and messages to the user and accepting the user's selection;

[1360] A system including:

[1361] (Claim 2)

[1362] 10. The system of claim 1, further comprising means for displaying a plurality of candidates and their respective image suitability scores.

[1363] (Claim 3)

[1364] The system according to claim 1, wherein the generated flower language and message are inspiring poems and messages generated using natural language generation technology.

[1365] "Application example 2 when combining emotion engines"

[1366] (Claim 1)

[1367] A means for inputting an image and extracting features of an object;

[1368] a means for matching the extracted features with an existing database;

[1369] a means for inputting user preferences and event information;

[1370] A means for recommending an optimal combination of items based on the input information;

[1371] means for generating a customized message based on the recommended item;

[1372] means for displaying recommended items and messages to a user and accepting a user selection;

[1373] means for collecting user voice input and converting the voice data into text;

[1374] means for capturing a user's facial expression and identifying emotions from the facial expression;

[1375] A system including:

[1376] (Claim 2)

[1377] 10. The system of claim 1, further comprising means for displaying a plurality of candidates and their respective suitability scores in the recommendation.

[1378] (Claim 3)

[1379] 2. The system of claim 1, wherein the generated customized message is an inspiring sentence generated using natural language generation technology. [Explanation of symbols]

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Claims

1. A means for inputting an image and extracting characteristics of a flower; means for matching the extracted flower features with an existing flower database; a means for inputting user preferences and event information; A method to recommend the best bouquet combination based on preferences and event information, A means for generating a flower language or message based on the recommended bouquet; means for displaying the recommended bouquets and messages to the user and accepting the user's selection; A system including:

2. 2. The system of claim 1, further comprising means for displaying a plurality of candidates and their respective image suitability in recommending bouquets.

3. 2. The system according to claim 1, wherein the generated flower language and message are generated as moving poems or haiku using natural language generation technology.

Images