system

Abstract

We provide the system. [Solution] A means of receiving information about pets and storing it in a database, A means for analyzing the aforementioned information to identify the pet's behavioral patterns and preferences, A means for generating an individualized entertainment plan based on the aforementioned behavioral patterns and preferences, A means of presenting the aforementioned plan to the user, A means for receiving user feedback and retraining the model to improve the generated plan, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot performed by at least one processor, the method including: receiving a user utterance; adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot; encoding the prompt; and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] For pet owners, it is not easy to understand the individual preferences and behavior patterns of their pets and provide appropriate entertainment. In particular, for busy owners, it is difficult to ensure effective playtime to deepen their daily relationship with their pets and enhance the happiness of their pets. The present invention aims to solve these problems by proposing a customized entertainment plan according to the personality of the pet.

Means for Solving the Problems

[0005] This invention includes means for receiving information about a pet, analyzing that information to identify the pet's behavioral patterns and preferences, and generating and presenting a personalized entertainment plan based on that information. Furthermore, it includes means for receiving feedback from the user and retraining the model to improve the generated plan. In this way, by continuously providing plans that are suited to the pet's preferences and behavior, it becomes possible to enrich the relationship between the pet owner and their pet.

[0006] "Information about pets" refers to all information related to pets, including their breed, age, sex, past behavioral history, preferences, and health status.

[0007] A "database" refers to an information management system that stores and allows access to and searching of collected information about pets.

[0008] "Behavioral patterns" refer to the tendencies, such as the timing, frequency, and content of specific behaviors and activities that a pet exhibits.

[0009] "Preferences" refer to the types of play, toys, treats, and activities that pets particularly enjoy.

[0010] An "entertainment plan" refers to a plan that includes playtime, toys, and activities designed to suit the pet's personality and needs.

[0011] A "user" refers to a pet owner who uses the system to receive an entertainment plan for their pet.

[0012] "Feedback" refers to evaluations and comments provided by users regarding their pet's reactions and behavior.

[0013] "Retraining" refers to the process by which a system updates its AI model based on user feedback to improve accuracy and performance. [Brief explanation of the drawing]

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

MODE FOR CARRYING OUT THE INVENTION

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

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

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

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

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

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

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

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

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

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

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

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

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

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

[0035] The present invention provides an AI-driven service that collects information about pets and generates personalized entertainment plans based on that information. The main components of this system are the user's terminal, a server, and an AI model that performs analysis and plan generation.

[0036] User's device: Pet owners input information about their pets into the system via smartphones or computers. This includes the pet's breed, age, sex, past behavioral history, and presumed preferences. The device can also observe and input the pet's daily behavior.

[0037] Server: The server receives data sent from terminals and stores it in a database. Since the received information is difficult to analyze directly, the server standardizes the data and processes missing data and outliers. The processed data is then prepared for analysis by an AI model.

[0038] AI Model: The server-based AI model analyzes pet behavior patterns and identifies pet preferences. This model learns from past and incoming data to generate an optimal entertainment plan for each individual pet. The plan includes the most effective activity times for the pet, recommended toys, and activities.

[0039] Specific example: For instance, a user's dog (a 2-year-old Labrador Retriever) tends to enjoy playing with balls and water. The user inputs this information via their device and reports the dog's health and mood daily. The server receives the information, and an AI model analyzes it to create the most effective entertainment plan. The plan might suggest playing fetch in the park in the evenings on weekdays and include water play in a dog pool on weekends. The user follows this plan and provides feedback on the dog's reactions and new behaviors, which helps to further optimize the plan.

[0040] In this way, this system aims to provide new and enjoyable experiences for both pets and their owners, and to improve the quality of life for pets.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users use their devices to enter basic information about their pets. This information includes the pet's breed, age, sex, past behavioral history, and preferences. Users can also record daily observations of their pets.

[0044] Step 2:

[0045] The terminal organizes the information entered by the user and sends it to the server. This information can be updated in real time and automatically sent to the server.

[0046] Step 3:

[0047] The server receives information sent from the terminal and stores it in the database. If the data is not standardized, the server unifies the data structure and detects and corrects missing data and outliers.

[0048] Step 4:

[0049] The AI ​​model on the server receives the formatted data and analyzes the pet's behavior patterns and preferences. Machine learning algorithms are used for the analysis to identify specific patterns and preferences.

[0050] Step 5:

[0051] Based on the analysis results, the AI ​​model generates a customized entertainment plan for each individual pet. The plan clearly outlines recommended activities, equipment to be used, and activity times.

[0052] Step 6:

[0053] The server sends the generated entertainment plan to the device. The device notifies the user of the plan and displays it for them to view within the app.

[0054] Step 7:

[0055] The user engages in playtime with their pet based on the provided plan. If the pet's reaction or new behaviors are observed, the user inputs this information as feedback into their device.

[0056] Step 8:

[0057] The device sends user feedback to the server. The server feeds this feedback into the AI ​​model, which is then used to retrain the model and improve the accuracy of the plan.

[0058] Step 9:

[0059] The server regenerates an optimized plan based on the feedback and sends it to the device. This iterative process ensures that the pet continuously receives the best possible entertainment experience.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] Modern pet owners are seeking personalized entertainment plans to improve their pets' quality of life, but there is a lack of concrete ways to provide them. Traditional methods fail to adequately analyze information needed to understand each pet's individual preferences and behavioral models and propose appropriate activities, thus failing to fully enhance pets' well-being and quality of activity.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes means for receiving data about pets and storing it in an information collection, means for standardizing the data and correcting missing data and outliers, and means for analyzing the information and identifying the pet's behavioral model and preferences. This makes it possible to generate and present personalized entertainment plans to the user.

[0065] "Pets" is a general term for animals that are kept in homes or special facilities and have an affinity for humans.

[0066] "Data" refers to a collection of information gathered for a specific purpose, such as the type of pet, age, sex, behavioral history, and preferences.

[0067] An "information collection" refers to an electronic database or server-based repository used to systematically store collected data.

[0068] "Standardization" is a process for converting collected data into a format that is easy to analyze, and it includes preprocessing to maintain data integrity.

[0069] "Missing data" refers to data that lacks information that should be present, and it needs to be supplemented to maintain the accuracy of the analysis.

[0070] An "outlier" refers to a value within a data set that deviates significantly from the normal range and requires special consideration in data processing.

[0071] A "behavioral model" is a model used to predict and explain the behavioral patterns that a pet may exhibit, based on its past behavioral data.

[0072] "Preferences" refer to specific activities, possessions, or environmental characteristics that a pet particularly enjoys.

[0073] An "entertainment plan" is a specific activity program designed individually based on the pet's behavioral model and preferences, with the aim of improving the pet's quality of life.

[0074] A "learning algorithm" refers to a method that automatically learns patterns and trends from data to make future predictions and decisions.

[0075] "Retraining" is the process of retraining an existing learning algorithm using new data to achieve better performance.

[0076] This invention describes a specific embodiment for implementing a pet entertainment plan generation system. This system is implemented using a user terminal, a server, and a generative AI model that performs analysis and plan generation.

[0077] User's terminal

[0078] Users enter detailed information about their pets into the system using their smartphones or computers. Typical information includes the pet's breed, age, sex, behavioral history, and preferences. The device can also observe the pet's daily behavior and input it as new data. This allows users to understand their pet's condition and reactions in real time and provide appropriate information.

[0079] server

[0080] The server has the function of receiving data sent from the user's terminal and storing it in a database. The server standardizes the received data and corrects missing data and outliers. This prepares the data in a format suitable for analysis by generative AI models, providing a foundation for obtaining accurate analysis results.

[0081] Generative AI Models

[0082] The generative AI model implemented on the server analyzes the pet's behavior and preferences. This AI model learns from past and incoming data to generate personalized entertainment plans. The generated plans include the optimal activity times and recommended toys for the pet. For example, if a Labrador Retriever enjoys playing with a ball, the model might suggest a specific plan such as "30 minutes of ball throwing in the park in the evening."

[0083] Specific example

[0084] This section explains how to use this system with a user's two-year-old Labrador Retriever. Since the dog enjoys playing in water and fetching balls, the user inputs this information via a terminal. The server receives this data, fills in missing data, corrects outliers, and passes it to the generating AI model. The model analyzes the data and generates an entertainment plan, suggesting activities such as fetching balls in the park in the evenings on weekdays and including water play in a dog pool on weekends. The user then carries out daily activities based on this plan, and the plan is further optimized by inputting feedback on the pet's reactions and any new behaviors back into the terminal.

[0085] An example of a prompt message could be: "Create an entertainment plan for a 2-year-old Labrador Retriever. This dog enjoys playing with balls and water. What should you consider?" In this way, the system helps to take pet interaction to a new level.

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

[0087] Step 1:

[0088] Users enter information about their pets using a terminal. This data includes detailed information such as the pet's breed, age, sex, behavioral history, and preferences. Users also enter additional information about their pet's health and mood based on daily observations. This information is then transmitted from the terminal to the server.

[0089] Step 2:

[0090] The server receives data sent by the user and stores it in the database. If the input data is incomplete or abnormal, the server inspects it and performs a standardization process. Specifically, it fills in missing data and corrects outliers appropriately. This process prepares the data into an analyzable format and outputs it as a dataset that can be used in the next processing step.

[0091] Step 3:

[0092] A server-based AI model performs analysis using a well-organized dataset. The model processes the data to identify pet behaviors and preferences. This process integrates historical and new data, performing data calculations to reveal patterns and trends. The output is a personalized recreation plan, which includes optimal activity times and recommended toys.

[0093] Step 4:

[0094] The server sends the generated activity plan to the user's device. The user reviews this plan and uses it in actual activities with their pet. The user observes the pet's reactions and new behaviors obtained through the activities and inputs this feedback information into their device. This feedback is sent back to the server and used for the system's next learning cycle.

[0095] Step 5:

[0096] Based on feedback received from users, the server retrains the generating AI model. In this step, the AI ​​model iteratively learns using the latest data, including the feedback information. This results in more accurate entertainment plans that can quickly adapt to changes in the pet's preferences and behavior.

[0097] (Application Example 1)

[0098] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0099] When it comes to pet ownership, the challenge lies in how to effectively provide entertainment plans optimized for each individual pet, and how to facilitate users' purchasing behavior at commercial facilities based on the suggested entertainment. Conventional systems struggle to provide individualized plans based on pets' behavior and preferences, and there is no automated mechanism to link these plans to specific purchases at commercial facilities, resulting in a lack of improvement in the quality of pet care and entertainment.

[0100] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0101] In this invention, the server includes means for receiving information about pets and storing it in a data warehouse; means for analyzing the information to identify the pet's behavioral tendencies and preferences; means for generating an individualized activity plan based on the behavioral tendencies and preferences; and means for facilitating the user's purchase at commercial facilities based on the proposed products and services. This enables a smooth purchasing experience at commercial facilities while providing optimal entertainment for pets.

[0102] "Information about pets" refers to data necessary to identify the characteristics of a pet, such as its breed, age, sex, behavioral history, and preferences.

[0103] A "data warehouse" is a database system for accumulating and standardizing information about pets.

[0104] "Behavioral tendencies" refer to patterns and habits in a pet's movements and activities.

[0105] "Preferences" refer to the types of games, interests, and activities that pets enjoy.

[0106] An "individualized activity plan" is an entertainment plan optimized for each pet's characteristics, based on the information and analysis results received about the pet.

[0107] "Users" refers to pet owners or businesses that provide services or products related to pets.

[0108] A "commercial establishment" refers to a retail store or service provider that sells pet products or services.

[0109] "Recursion" refers to feedback information sent from the user to the system, including changes in the pet's reactions and behavior.

[0110] A "generative AI model" is an artificial intelligence model that analyzes pet information and automatically generates the optimal entertainment plan.

[0111] To implement this invention, a system is required that includes a user's terminal, a server, and a generated AI model. The user's terminal uses a smartphone or computer to input and transmit information about the pet. The terminal collects data on the pet's breed, age, sex, behavioral history, and preferences, and transmits this data to the server.

[0112] The server processes the data received from the terminal. This processing includes data standardization, imputation of missing values, and correction of outliers. This prepares the data for analysis. Next, a generative AI model within the server performs the analysis. Based on the accumulated data, this AI model identifies the pet's behavioral tendencies and preferences and generates an individualized activity plan.

[0113] The generated activity plan includes the optimal activity time for pets, recommended toys, and specific activities. Based on this plan, users can easily purchase suggested products and services from physical stores or online platforms. This enhances pet entertainment and improves the user's purchasing experience.

[0114] Furthermore, the AI ​​model continuously learns and optimizes by providing feedback to the server via the user's device regarding changes in the pet's reactions and behavior. This recursive process further refines the activity plan.

[0115] As a concrete example, a user uses a smartphone app to input information about their toy poodle. The AI ​​model analyzes that the dog likes intelligent toys, and the app suggests a new puzzle toy. It also shows that the toy is available for purchase at a nearby commercial facility, supporting the user's purchase. The prompt "Suggest what kind of toys this toy poodle would be interested in in the morning" is used as input to the AI ​​model.

[0116] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0117] Step 1:

[0118] The terminal collects pet information entered by the user (breed, age, sex, behavioral history, preferences) and sends it to the server as JSON data. This input data forms the basis for data processing on the server.

[0119] Step 2:

[0120] The server parses the JSON data received from the terminal and standardizes the data. Specifically, it imputes missing data values ​​with the mean and detects and corrects outliers appropriately. The goal is to store the data in the database in the correct format, and this is the output.

[0121] Step 3:

[0122] The server passes standardized data as input to a generating AI model. This model uses machine learning algorithms to analyze the data and identify the pet's behavioral tendencies and preferences. As output, it creates profile data based on the identified behavioral patterns and preferences.

[0123] Step 4:

[0124] Based on profile data created by a generative AI model, the server generates a personalized activity plan. This plan includes optimal activity times, recommended toys, and specific activities to suggest. The plan is sent to the device in JSON format.

[0125] Step 5:

[0126] The terminal presents the user with an activity plan received from the server. The user reviews the plan and uses it as information to facilitate product purchases at physical stores or online.

[0127] Step 6:

[0128] Users send feedback about their pets' reactions and behaviors to a server via their devices. This feedback data is then passed to the AI ​​model as input for retraining.

[0129] Step 7:

[0130] The server retrains the generating AI model based on user feedback data. This allows the system to continuously learn the pet's preferences and behavioral tendencies, improving its activity plan. The output results in improved profile data and activity plans.

[0131] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0132] This invention provides a system that generates personalized entertainment plans based on information about pets and dynamically adjusts the plans to take into account the user's emotions. The system's main components are the user's terminal, a server, and an emotion engine that performs emotion recognition.

[0133] User's device: Users use smartphones or computers to input information about their pets, such as breed, age, behavioral history, preferences, and daily behavioral observations, into the system. The device also captures the user's voice and text, which are processed as sentiment data.

[0134] Server: The server receives pet information and user emotion information sent from the terminal and stores it in a database. The received information is standardized into a format that is easy for the AI ​​model to interpret, and any missing data or outliers are processed.

[0135] AI Model and Emotion Engine: The AI ​​model on the server analyzes the pet's behavior patterns and preferences to generate an optimized entertainment plan. Meanwhile, the emotion engine analyzes the user's emotional state from voice and text data to recognize the user's current emotions. The AI ​​model then adjusts the plan considering this emotional data to generate a plan that matches the user's psychological state.

[0136] Specific example: The user's cat (2 years old, Siamese) enjoys playing with a ball and a laser pointer. The user inputs daily observations into the device and adds voice memos on days when the cat felt stressed. The server receives the configured information, and the AI ​​model analyzes it to create a new entertainment plan. Furthermore, it generates a plan that prioritizes activities with a moderate level of exercise to help the user relax. The user interacts with their pet according to the presented plan and inputs feedback into the device. This information is used to retrain the model, and a more accurate plan is provided the next time.

[0137] Thus, this system not only deepens the relationship between pets and their owners, but also takes into account the user's emotional state, enabling it to provide a more personalized entertainment experience.

[0138] The following describes the processing flow.

[0139] Step 1:

[0140] The user uses the device to input basic information about their pet and observations of their daily activities. The device also acquires the user's voice and text data and collects data on the user's emotional state.

[0141] Step 2:

[0142] The terminal organizes the collected pet information and emotional data and sends it to the server. This information is formatted to ensure reliable data reception.

[0143] Step 3:

[0144] The server receives information sent from the terminal and stores it in the database. Next, it detects and corrects any missing data or outliers so that the data can be analyzed by the AI ​​model.

[0145] Step 4:

[0146] The AI ​​model analyzes the pet's behavior patterns and preferences within the server. Based on past behavioral history and information provided by the user, it generates an entertainment plan optimized for each individual pet.

[0147] Step 5:

[0148] The emotion engine on the server analyzes the user's voice and text data to recognize the user's current emotional state. This information is then used in plan generation.

[0149] Step 6:

[0150] The AI ​​model incorporates the recognized user's emotional state and adjusts the entertainment plan accordingly. For example, if the user is feeling stressed, it prioritizes plans that include calming activities.

[0151] Step 7:

[0152] The server sends the customized entertainment plan to the device. The device notifies the user of the plan and allows them to view the details within the app.

[0153] Step 8:

[0154] The user engages in playtime with their pet according to the plan. In addition to the pet's reactions, changes in the user's own emotional state are also taken into consideration and recorded as feedback on the device.

[0155] Step 9:

[0156] The device sends feedback information to the server, and the AI ​​model and emotion engine retrain based on this information. This improves the accuracy of the next plan generated.

[0157] This entire process ensures that users can continuously receive the best possible entertainment experience for their pets, taking their emotions into consideration.

[0158] (Example 2)

[0159] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0160] In pet-owner interaction, there is a need to provide personalized entertainment experiences based on the pet's characteristics and the owner's emotional state. However, conventional systems have the challenge of not being able to effectively integrate and dynamically adjust these elements.

[0161] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving information about the pet and the user and storing it in a storage device, means for analyzing the information to identify the pet's behavior patterns and preferences, and means for analyzing the user's emotional state and generating an individualized entertainment plan that takes the user's emotional state into account based on the behavior patterns and preferences. This enables a dynamic and individualized entertainment experience based on the pet's characteristics and the user's emotions.

[0162] 1. A "pet" is an animal or living creature kept in a household, living with people, and being an object of play or emotional interaction.

[0163] 2. "User" refers to an individual or organization that uses this system to input data about their pet and receives an entertainment plan.

[0164] 3. "Storage device" refers to a hardware or software configuration that holds data and makes it accessible as needed.

[0165] 4. "Analysis" refers to the process of examining data in detail and extracting meaningful information and patterns.

[0166] 5. "Behavioral patterns" refer to consistent patterns of behavior and activity that a pet exhibits, which can be used to identify the pet's preferences and habits.

[0167] 6. "Preferences" refer to the activities and objects that pets particularly enjoy, and this information is used to generate entertainment plans.

[0168] 7. "Emotional state" refers to the user's psychological state and is analyzed from voice and text data.

[0169] 8. "Recreational plans" refer to activities and suggestions that can be enjoyed by both the pet and the user, based on the pet's characteristics and the user's emotional state.

[0170] 9. "Feedback" refers to information provided by users to the system, based on the pet's reactions and the results of its activities.

[0171] 10. "Retraining" refers to the process of updating the AI ​​model based on newly collected data and feedback to improve the accuracy of the next entertainment plan.

[0172] This invention provides a system that generates personalized entertainment plans based on the pet's characteristics and the user's emotional state in order to improve user-pet interaction. The system mainly uses a user terminal, a server, and an emotion engine that performs emotion analysis.

[0173] Users input information about their pets using devices such as smartphones or computers. This information includes the pet's breed, age, behavioral history, and preferences. In addition, users input emotional data, such as voice or text data, into their devices. For example, they might record a voice message saying, "I was happy to play with my pet a lot today." This data is then transmitted to a server via the internet.

[0174] The server stores the received data in storage. Analysis programs implemented in Python, R, etc., are used to process the data and identify the pet's behavioral patterns and preferences. Missing values ​​are imputed using the mean or median. Based on the analysis results, an optimal entertainment plan for the pet is developed.

[0175] The emotion engine analyzes the user's voice and text data to identify their emotional state. A natural language processing API is used as the emotion analysis tool. Based on these analysis results, the entertainment plan is dynamically adjusted according to the user's emotional state.

[0176] As a concrete example, consider a user who owns a two-year-old Siamese cat and knows that their cat enjoys playing with a laser pointer. The user inputs, "I'm a little tired today, but I'd like to play with my cat a little." The server then receives this information and develops a play plan that matches the pet's energy level and the user's fatigue level. By suggesting a short play session using a laser pointer, the system provides an experience that satisfies both the user and the pet.

[0177] This system continuously receives feedback from users and retrains its model to improve the accuracy of its entertainment planning. An example of a prompt might be, "My pet Siamese cat is 2 years old and loves playing with balls. Today she's stressed. What kind of game would you suggest?"

[0178] Through these means, the present invention makes it possible to provide pets and their owners with a more personalized and fulfilling entertainment experience.

[0179] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0180] Step 1:

[0181] The user uses a device to input information about their pet and their own emotional state. The input data includes the pet's breed, age, behavioral history, preferences, and audio or text indicating the user's emotional state. The data is formatted in JSON or another format and sent to the server.

[0182] Step 2:

[0183] The server stores the received data in its storage device. It saves it to a database and standardizes the input data into a parseable format. For example, it assigns labels to each category and quantifies sentiment data. This standardization process allows AI models to easily analyze the data.

[0184] Step 3:

[0185] The server's AI model uses standardized pet data to analyze pet behavior patterns and preferences. For example, it identifies the most active times of day for pets based on past data and outputs behavioral patterns based on those times. Based on these analysis results, it predicts what kind of entertainment pets prefer.

[0186] Step 4:

[0187] The server's emotion engine analyzes the user's emotional data to identify their current emotional state. It performs voice tone analysis and extracts keywords from text to determine whether the user is positive and relaxed, or negative and stressed. This is output as an emotion statement and applied to adjust the entertainment plan.

[0188] Step 5:

[0189] The AI ​​model on the server generates a personalized entertainment plan, taking into account the pet's behavior patterns and the user's emotional state. Through data calculations, it selects activities suitable for the pet and makes adjustments based on the user's emotional state. The generated plan is output in JSON format and sent to the device.

[0190] Step 6:

[0191] The user receives an entertainment plan generated on their device and implements it with their pet. They observe the results of the plan's implementation and the pet's reaction, and provide feedback based on that. This information is used to generate the next plan.

[0192] Step 7:

[0193] The server receives feedback data from users and uses it again to train the AI ​​model. This data is incorporated into the model's training, enabling more accurate plan generation. The system is continuously improved through this feedback.

[0194] (Application Example 2)

[0195] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0196] There is a need to enrich the interaction with pets and provide more personalized entertainment experiences that match the emotional state of the owner. Furthermore, there is a lack of dynamic content adjustments that respond to the owner's psychological state. To address this issue, a system is needed that enhances the enjoyment for both pets and their owners.

[0197] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0198] In this invention, the server includes means for receiving information about pets and storing it in a data area, means for identifying the pet's behavioral patterns and preferences, means for generating personalized entertainment plans, means for analyzing user emotional data and dynamically adjusting the entertainment plan, and means for selecting content according to the type of pet and providing interactive content. This enables a rich entertainment experience for both pets and their owners.

[0199] "Information about pets" includes data such as the pet's species, age, behavioral history, preferences, and daily behavioral observations.

[0200] "Data operating area" refers to a storage system for storing and analyzing information.

[0201] "Behavioral patterns" refer to the tendencies and habits of behaviors that pets exhibit on a daily basis.

[0202] "Preferences" refers to data indicating the types of games and foods that pets particularly enjoy.

[0203] An "entertainment plan" is a specific plan of play and activities generated based on the pet's behavioral patterns and preferences.

[0204] "User emotional data" refers to information that indicates the psychological state of a user, analyzed from the voice and text input they provide.

[0205] "Interactive content" refers to digital content that includes two-way entertainment elements that allow pets and their owners to participate directly.

[0206] "Dynamic adjustment" means modifying and optimizing the entertainment plan in real time based on user sentiment data.

[0207] "Feedback" refers to information that pet owners input into the system regarding their pet's reactions and their evaluation of the plan.

[0208] This invention realizes a system that provides personalized entertainment for pets and their owners. It begins with the user entering detailed information about their pet using their smartphone or tablet device. The device collects data such as the pet's breed, age, behavioral history, and preferences, and transmits it to a server. At the same time, the system acquires the user's emotional data through voice input and text analysis on the device.

[0209] The server stores the received information in its data storage area, and an AI model analyzes the pet's behavior patterns and preferences. Based on this data, the AI ​​model generates an optimal entertainment plan. An emotion engine is used to analyze the user's emotional data. This engine determines the user's psychological state from voice and text.

[0210] In this system, the AI ​​model plays a crucial role in providing plans that take the user's emotions into account. The plan is displayed on the user's device, suggesting optimal playtime and interactive content for the pet. The user plays with their pet according to the plan and inputs feedback into the device. This feedback is sent to the server and used to retrain the model, which in turn improves the generation of future plans.

[0211] A concrete example of this system is a user who owns a two-year-old Siamese cat. The user enters information about their pet, and on days when the cat is stressed, relaxation music is recommended accordingly. An example of a prompt message in this case would be, "Please suggest an entertainment plan for a two-year-old Siamese cat. The owner is stressed today." Based on this prompt, the AI ​​model dynamically selects appropriate content, providing the user with entertainment tailored to their needs.

[0212] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0213] Step 1:

[0214] The terminal receives information from the user, such as the pet's breed, age, behavioral history, and preferences. This input information is then converted into a standard data format for transmission. The output is the formatted pet information.

[0215] Step 2:

[0216] The device acquires the user's voice and text data and analyzes their emotional state. This analysis uses voice analysis software and text analysis algorithms. The input is the user's voice and text, and the output is the user's emotional data.

[0217] Step 3:

[0218] The server receives pet information and user emotion data sent from the terminal and stores them in the data storage area. After receiving the data, it performs data interpolation and removes outliers. The output is the formatted information in the database.

[0219] Step 4:

[0220] The AI ​​model on the server analyzes the pet's behavioral patterns and preferences based on data from the operating area and generates a personalized entertainment plan. Here, the learning algorithm of the generative AI model is applied. The input is standardized pet information, and the output is the entertainment plan.

[0221] Step 5:

[0222] The emotion engine uses the user's emotional data to dynamically adjust the generated entertainment plan. This provides a plan that is tailored to the user's psychological state. The input is the user's emotional data, and the output is the adjusted entertainment plan.

[0223] Step 6:

[0224] The terminal displays the entertainment plan received from the server to the user and provides interactive content. User interaction here serves as feedback. The input is the plan from the server, and the output is the displayed and executed plan.

[0225] Step 7:

[0226] Users input their reactions and opinions after spending time with their pets as feedback into the device. This feedback is sent from the device to the server and used to retrain the model. The output is the feedback information sent to the server, which contributes to improving the accuracy of the next entertainment plan.

[0227] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0228] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0229] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0230] [Second Embodiment]

[0231] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0232] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0233] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0234] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0235] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0236] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0237] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0238] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0239] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0240] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0241] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0242] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0243] The present invention provides an AI-driven service that collects information about pets and generates personalized entertainment plans based on that information. The main components of this system are the user's terminal, a server, and an AI model that performs analysis and plan generation.

[0244] User's device: Pet owners input information about their pets into the system via smartphones or computers. This includes the pet's breed, age, sex, past behavioral history, and presumed preferences. The device can also observe and input the pet's daily behavior.

[0245] Server: The server receives data sent from terminals and stores it in a database. Since the received information is difficult to analyze directly, the server standardizes the data and processes missing data and outliers. The processed data is then prepared for analysis by an AI model.

[0246] AI Model: The server-based AI model analyzes pet behavior patterns and identifies pet preferences. This model learns from past and incoming data to generate an optimal entertainment plan for each individual pet. The plan includes the most effective activity times for the pet, recommended toys, and activities.

[0247] Specific example: For instance, a user's dog (a 2-year-old Labrador Retriever) tends to enjoy playing with balls and water. The user inputs this information via their device and reports the dog's health and mood daily. The server receives the information, and an AI model analyzes it to create the most effective entertainment plan. The plan might suggest playing fetch in the park in the evenings on weekdays and include water play in a dog pool on weekends. The user follows this plan and provides feedback on the dog's reactions and new behaviors, which helps to further optimize the plan.

[0248] In this way, this system aims to provide new and enjoyable experiences for both pets and their owners, and to improve the quality of life for pets.

[0249] The following describes the processing flow.

[0250] Step 1:

[0251] Users use their devices to enter basic information about their pets. This information includes the pet's breed, age, sex, past behavioral history, and preferences. Users can also record daily observations of their pets.

[0252] Step 2:

[0253] The terminal organizes the information entered by the user and sends it to the server. This information can be updated in real time and automatically sent to the server.

[0254] Step 3:

[0255] The server receives information sent from the terminal and stores it in the database. If the data is not standardized, the server unifies the data structure and detects and corrects missing data and outliers.

[0256] Step 4:

[0257] The AI ​​model on the server receives the formatted data and analyzes the pet's behavior patterns and preferences. Machine learning algorithms are used for the analysis to identify specific patterns and preferences.

[0258] Step 5:

[0259] Based on the analysis results, the AI ​​model generates a customized entertainment plan for each individual pet. The plan clearly outlines recommended activities, equipment to be used, and activity times.

[0260] Step 6:

[0261] The server sends the generated entertainment plan to the device. The device notifies the user of the plan and displays it for them to view within the app.

[0262] Step 7:

[0263] The user engages in playtime with their pet based on the provided plan. If the pet's reaction or new behaviors are observed, the user inputs this information as feedback into their device.

[0264] Step 8:

[0265] The device sends user feedback to the server. The server feeds this feedback into the AI ​​model, which is then used to retrain the model and improve the accuracy of the plan.

[0266] Step 9:

[0267] The server regenerates an optimized plan based on the feedback and sends it to the device. This iterative process ensures that the pet continuously receives the best possible entertainment experience.

[0268] (Example 1)

[0269] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0270] Modern pet owners are seeking personalized entertainment plans to improve their pets' quality of life, but there is a lack of concrete ways to provide them. Traditional methods fail to adequately analyze information needed to understand each pet's individual preferences and behavioral models and propose appropriate activities, thus failing to fully enhance pets' well-being and quality of activity.

[0271] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0272] In this invention, the server includes means for receiving data about pets and storing it in an information collection, means for standardizing the data and correcting missing data and outliers, and means for analyzing the information and identifying the pet's behavioral model and preferences. This makes it possible to generate and present personalized entertainment plans to the user.

[0273] "Pets" is a general term for animals that are kept in homes or special facilities and have an affinity for humans.

[0274] "Data" refers to a collection of information gathered for a specific purpose, such as the type of pet, age, sex, behavioral history, and preferences.

[0275] An "information collection" refers to an electronic database or server-based repository used to systematically store collected data.

[0276] "Standardization" is a process for converting collected data into a format that is easy to analyze, and it includes preprocessing to maintain data integrity.

[0277] "Missing data" refers to data that lacks information that should be present, and it needs to be supplemented to maintain the accuracy of the analysis.

[0278] An "outlier" refers to a value within a data set that deviates significantly from the normal range and requires special consideration in data processing.

[0279] A "behavioral model" is a model used to predict and explain the behavioral patterns that a pet may exhibit, based on its past behavioral data.

[0280] "Preferences" refer to specific activities, possessions, or environmental characteristics that a pet particularly enjoys.

[0281] An "entertainment plan" is a specific activity program designed individually based on the pet's behavioral model and preferences, with the aim of improving the pet's quality of life.

[0282] A "learning algorithm" refers to a method that automatically learns patterns and trends from data to make future predictions and decisions.

[0283] "Retraining" is the process of retraining an existing learning algorithm using new data to achieve better performance.

[0284] In the present invention, a form for specifically implementing a pet entertainment plan generation system will be described. This system is realized using a user terminal, a server, and a generation AI model that performs analysis and plan generation.

[0285] User terminal

[0286] The user uses a smartphone or a computer to input detailed information about the pet into the system. Typical information includes the type, age, gender, behavior history, preferences, etc. of the pet. The terminal can also observe the daily behavior of the pet and input it as new data. This enables the user to grasp the state and reactions of the pet in real time and provide appropriate information.

[0287] Server

[0288] The server has a function of receiving data sent from the user terminal and storing it in a database. The server standardizes the received data and corrects missing data and outliers. This prepares the data in a format suitable for analysis by the generation AI model and provides a basis for obtaining accurate analysis results.

[0289] Generation AI model

[0290] The generation AI model implemented in the server analyzes the pet's behavior model and preferences. This AI model learns past data and incoming data and plays a role in generating individualized entertainment plans. The generated plans include the optimal activity time zone for the pet and recommended play equipment. For example, if a Labrador Retriever likes playing with a ball, the model proposes a specific plan such as "throwing the ball in the park for 30 minutes in the evening".

[0291] Specific example

[0292] This section explains how to use this system with a user's two-year-old Labrador Retriever. Since the dog enjoys playing in water and fetching balls, the user inputs this information via a terminal. The server receives this data, fills in missing data, corrects outliers, and passes it to the generating AI model. The model analyzes the data and generates an entertainment plan, suggesting activities such as fetching balls in the park in the evenings on weekdays and including water play in a dog pool on weekends. The user then carries out daily activities based on this plan, and the plan is further optimized by inputting feedback on the pet's reactions and any new behaviors back into the terminal.

[0293] An example of a prompt message could be: "Create an entertainment plan for a 2-year-old Labrador Retriever. This dog enjoys playing with balls and water. What should you consider?" In this way, the system helps to take pet interaction to a new level.

[0294] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0295] Step 1:

[0296] Users enter information about their pets using a terminal. This data includes detailed information such as the pet's breed, age, sex, behavioral history, and preferences. Users also enter additional information about their pet's health and mood based on daily observations. This information is then transmitted from the terminal to the server.

[0297] Step 2:

[0298] The server receives data sent by the user and stores it in the database. If the input data is incomplete or abnormal, the server inspects it and performs a standardization process. Specifically, it fills in missing data and corrects outliers appropriately. This process prepares the data into an analyzable format and outputs it as a dataset that can be used in the next processing step.

[0299] Step 3:

[0300] A server-based AI model performs analysis using a well-organized dataset. The model processes the data to identify pet behaviors and preferences. This process integrates historical and new data, performing data calculations to reveal patterns and trends. The output is a personalized recreation plan, which includes optimal activity times and recommended toys.

[0301] Step 4:

[0302] The server sends the generated activity plan to the user's device. The user reviews this plan and uses it in actual activities with their pet. The user observes the pet's reactions and new behaviors obtained through the activities and inputs this feedback information into their device. This feedback is sent back to the server and used for the system's next learning cycle.

[0303] Step 5:

[0304] Based on feedback received from users, the server retrains the generating AI model. In this step, the AI ​​model iteratively learns using the latest data, including the feedback information. This results in more accurate entertainment plans that can quickly adapt to changes in the pet's preferences and behavior.

[0305] (Application Example 1)

[0306] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0307] When raising pets, the issues are how to effectively provide an entertainment plan optimized for each individual pet and how to enable users to smoothly carry out purchase actions at commercial facilities based on the proposed entertainment. In conventional systems, it is difficult to provide an individualized plan based on the behavior and preferences of pets, and there is no automatic means to link it to specific purchases at commercial facilities, resulting in the problem that the quality of pet care and entertainment does not improve.

[0308] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0309] In this invention, the server includes means for receiving information related to a pet and storing it in a data warehouse, means for analyzing the information to identify the behavior trends and preferences of the pet, means for generating an individualized activity plan based on the behavior trends and preferences, and means for facilitating the purchase of a user at a commercial facility based on the proposed products and services. Thereby, while providing optimal entertainment for the pet, a smooth purchase experience at the commercial facility becomes possible.

[0310] "Information related to a pet" refers to data necessary to identify the characteristics of a pet, such as the type, age, gender, behavior history, and preferences of the pet.

[0311] "Data warehouse" refers to a database system for accumulating and standardizing information related to a pet.

[0312] "Behavior trend" refers to what indicates the patterns and habits in the actions and activities of a pet.

[0313] "Preference" refers to the object and activity content that a pet likes to play with and is interested in.

[0314] "Individualized activity plan" refers to an entertainment plan optimized for the characteristics of each pet based on the received pet information and analysis results.

[0315] "Users" refers to pet owners or businesses that provide services or products related to pets.

[0316] A "commercial establishment" refers to a retail store or service provider that sells pet products or services.

[0317] "Recursion" refers to feedback information sent from the user to the system, including changes in the pet's reactions and behavior.

[0318] A "generative AI model" is an artificial intelligence model that analyzes pet information and automatically generates the optimal entertainment plan.

[0319] To implement this invention, a system is required that includes a user's terminal, a server, and a generated AI model. The user's terminal uses a smartphone or computer to input and transmit information about the pet. The terminal collects data on the pet's breed, age, sex, behavioral history, and preferences, and transmits this data to the server.

[0320] The server processes the data received from the terminal. This processing includes data standardization, imputation of missing values, and correction of outliers. This prepares the data for analysis. Next, a generative AI model within the server performs the analysis. Based on the accumulated data, this AI model identifies the pet's behavioral tendencies and preferences and generates an individualized activity plan.

[0321] The generated activity plan includes the optimal activity time for pets, recommended toys, and specific activities. Based on this plan, users can easily purchase suggested products and services from physical stores or online platforms. This enhances pet entertainment and improves the user's purchasing experience.

[0322] Furthermore, the AI ​​model continuously learns and optimizes by providing feedback to the server via the user's device regarding changes in the pet's reactions and behavior. This recursive process further refines the activity plan.

[0323] As a concrete example, a user uses a smartphone app to input information about their toy poodle. The AI ​​model analyzes that the dog likes intelligent toys, and the app suggests a new puzzle toy. It also shows that the toy is available for purchase at a nearby commercial facility, supporting the user's purchase. The prompt "Suggest what kind of toys this toy poodle would be interested in in the morning" is used as input to the AI ​​model.

[0324] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0325] Step 1:

[0326] The terminal collects pet information entered by the user (breed, age, sex, behavioral history, preferences) and sends it to the server as JSON data. This input data forms the basis for data processing on the server.

[0327] Step 2:

[0328] The server parses the JSON data received from the terminal and standardizes the data. Specifically, it imputes missing data values ​​with the mean and detects and corrects outliers appropriately. The goal is to store the data in the database in the correct format, and this is the output.

[0329] Step 3:

[0330] The server passes standardized data as input to a generating AI model. This model uses machine learning algorithms to analyze the data and identify the pet's behavioral tendencies and preferences. As output, it creates profile data based on the identified behavioral patterns and preferences.

[0331] Step 4:

[0332] Based on profile data created by a generative AI model, the server generates a personalized activity plan. This plan includes optimal activity times, recommended toys, and specific activities to suggest. The plan is sent to the device in JSON format.

[0333] Step 5:

[0334] The terminal presents the user with an activity plan received from the server. The user reviews the plan and uses it as information to facilitate product purchases at physical stores or online.

[0335] Step 6:

[0336] Users send feedback about their pets' reactions and behaviors to a server via their devices. This feedback data is then passed to the AI ​​model as input for retraining.

[0337] Step 7:

[0338] The server retrains the generating AI model based on user feedback data. This allows the system to continuously learn the pet's preferences and behavioral tendencies, improving its activity plan. The output results in improved profile data and activity plans.

[0339] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0340] This invention provides a system that generates personalized entertainment plans based on information about pets and dynamically adjusts the plans to take into account the user's emotions. The system's main components are the user's terminal, a server, and an emotion engine that performs emotion recognition.

[0341] User's device: Users use smartphones or computers to input information about their pets, such as breed, age, behavioral history, preferences, and daily behavioral observations, into the system. The device also captures the user's voice and text, which are processed as sentiment data.

[0342] Server: The server receives pet information and user emotion information sent from the terminal and stores it in a database. The received information is standardized into a format that is easy for the AI ​​model to interpret, and any missing data or outliers are processed.

[0343] AI Model and Emotion Engine: The AI ​​model on the server analyzes the pet's behavior patterns and preferences to generate an optimized entertainment plan. Meanwhile, the emotion engine analyzes the user's emotional state from voice and text data to recognize the user's current emotions. The AI ​​model then adjusts the plan considering this emotional data to generate a plan that matches the user's psychological state.

[0344] Specific example: The user's cat (2 years old, Siamese) enjoys playing with a ball and a laser pointer. The user inputs daily observations into the device and adds voice memos on days when the cat felt stressed. The server receives the configured information, and the AI ​​model analyzes it to create a new entertainment plan. Furthermore, it generates a plan that prioritizes activities with a moderate level of exercise to help the user relax. The user interacts with their pet according to the presented plan and inputs feedback into the device. This information is used to retrain the model, and a more accurate plan is provided the next time.

[0345] Thus, this system not only deepens the relationship between pets and their owners, but also takes into account the user's emotional state, enabling it to provide a more personalized entertainment experience.

[0346] The following describes the processing flow.

[0347] Step 1:

[0348] The user uses the device to input basic information about their pet and observations of their daily activities. The device also acquires the user's voice and text data and collects data on the user's emotional state.

[0349] Step 2:

[0350] The terminal organizes the collected pet information and emotional data and sends it to the server. This information is formatted to ensure reliable data reception.

[0351] Step 3:

[0352] The server receives information sent from the terminal and stores it in the database. Next, it detects and corrects any missing data or outliers so that the data can be analyzed by the AI ​​model.

[0353] Step 4:

[0354] The AI ​​model analyzes the pet's behavior patterns and preferences within the server. Based on past behavioral history and information provided by the user, it generates an entertainment plan optimized for each individual pet.

[0355] Step 5:

[0356] The emotion engine on the server analyzes the user's voice and text data to recognize the user's current emotional state. This information is then used in plan generation.

[0357] Step 6:

[0358] The AI ​​model incorporates the recognized user's emotional state and adjusts the entertainment plan accordingly. For example, if the user is feeling stressed, it prioritizes plans that include calming activities.

[0359] Step 7:

[0360] The server sends the customized entertainment plan to the device. The device notifies the user of the plan and allows them to view the details within the app.

[0361] Step 8:

[0362] The user engages in playtime with their pet according to the plan. In addition to the pet's reactions, changes in the user's own emotional state are also taken into consideration and recorded as feedback on the device.

[0363] Step 9:

[0364] The device sends feedback information to the server, and the AI ​​model and emotion engine retrain based on this information. This improves the accuracy of the next plan generated.

[0365] This entire process ensures that users can continuously receive the best possible entertainment experience for their pets, taking their emotions into consideration.

[0366] (Example 2)

[0367] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0368] In pet-owner interaction, there is a need to provide personalized entertainment experiences based on the pet's characteristics and the owner's emotional state. However, conventional systems have the challenge of not being able to effectively integrate and dynamically adjust these elements.

[0369] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving information about the pet and the user and storing it in a storage device, means for analyzing the information to identify the pet's behavior patterns and preferences, and means for analyzing the user's emotional state and generating an individualized entertainment plan that takes the user's emotional state into account based on the behavior patterns and preferences. This enables a dynamic and individualized entertainment experience based on the pet's characteristics and the user's emotions.

[0370] 1. A "pet" is an animal or living creature kept in a household, living with people, and being an object of play or emotional interaction.

[0371] 2. "User" refers to an individual or organization that uses this system to input data about their pet and receives an entertainment plan.

[0372] 3. "Storage device" refers to a hardware or software configuration that holds data and makes it accessible as needed.

[0373] 4. "Analysis" refers to the process of examining data in detail and extracting meaningful information and patterns.

[0374] 5. "Behavioral patterns" refer to consistent patterns of behavior and activity that a pet exhibits, which can be used to identify the pet's preferences and habits.

[0375] 6. "Preferences" refer to the activities and objects that pets particularly enjoy, and this information is used to generate entertainment plans.

[0376] 7. "Emotional state" refers to the user's psychological state and is analyzed from voice and text data.

[0377] 8. "Recreational plans" refer to activities and suggestions that can be enjoyed by both the pet and the user, based on the pet's characteristics and the user's emotional state.

[0378] 9. "Feedback" refers to information provided by users to the system, based on the pet's reactions and the results of its activities.

[0379] 10. "Retraining" refers to the process of updating the AI ​​model based on newly collected data and feedback to improve the accuracy of the next entertainment plan.

[0380] This invention provides a system that generates personalized entertainment plans based on the pet's characteristics and the user's emotional state in order to improve user-pet interaction. The system mainly uses a user terminal, a server, and an emotion engine that performs emotion analysis.

[0381] Users input information about their pets using devices such as smartphones or computers. This information includes the pet's breed, age, behavioral history, and preferences. In addition, users input emotional data, such as voice or text data, into their devices. For example, they might record a voice message saying, "I was happy to play with my pet a lot today." This data is then transmitted to a server via the internet.

[0382] The server stores the received data in storage. Analysis programs implemented in Python, R, etc., are used to process the data and identify the pet's behavioral patterns and preferences. Missing values ​​are imputed using the mean or median. Based on the analysis results, an optimal entertainment plan for the pet is developed.

[0383] The emotion engine analyzes the user's voice and text data to identify their emotional state. A natural language processing API is used as the emotion analysis tool. Based on these analysis results, the entertainment plan is dynamically adjusted according to the user's emotional state.

[0384] As a concrete example, consider a user who owns a two-year-old Siamese cat and knows that their cat enjoys playing with a laser pointer. The user inputs, "I'm a little tired today, but I'd like to play with my cat a little." The server then receives this information and develops a play plan that matches the pet's energy level and the user's fatigue level. By suggesting a short play session using a laser pointer, the system provides an experience that satisfies both the user and the pet.

[0385] This system continuously receives feedback from users and retrains its model to improve the accuracy of its entertainment planning. An example of a prompt might be, "My pet Siamese cat is 2 years old and loves playing with balls. Today she's stressed. What kind of game would you suggest?"

[0386] Through these means, the present invention makes it possible to provide pets and their owners with a more personalized and fulfilling entertainment experience.

[0387] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0388] Step 1:

[0389] The user uses a device to input information about their pet and their own emotional state. The input data includes the pet's breed, age, behavioral history, preferences, and audio or text indicating the user's emotional state. The data is formatted in JSON or another format and sent to the server.

[0390] Step 2:

[0391] The server stores the received data in its storage device. It saves it to a database and standardizes the input data into a parseable format. For example, it assigns labels to each category and quantifies sentiment data. This standardization process allows AI models to easily analyze the data.

[0392] Step 3:

[0393] The server's AI model uses standardized pet data to analyze pet behavior patterns and preferences. For example, it identifies the most active times of day for pets based on past data and outputs behavioral patterns based on those times. Based on these analysis results, it predicts what kind of entertainment pets prefer.

[0394] Step 4:

[0395] The server's emotion engine analyzes the user's emotional data to identify their current emotional state. It performs voice tone analysis and extracts keywords from text to determine whether the user is positive and relaxed, or negative and stressed. This is output as an emotion statement and applied to adjust the entertainment plan.

[0396] Step 5:

[0397] The AI ​​model on the server generates a personalized entertainment plan, taking into account the pet's behavior patterns and the user's emotional state. Through data calculations, it selects activities suitable for the pet and makes adjustments based on the user's emotional state. The generated plan is output in JSON format and sent to the device.

[0398] Step 6:

[0399] The user receives an entertainment plan generated on their device and implements it with their pet. They observe the results of the plan's implementation and the pet's reaction, and provide feedback based on that. This information is used to generate the next plan.

[0400] Step 7:

[0401] The server receives feedback data from users and uses it again to train the AI ​​model. This data is incorporated into the model's training, enabling more accurate plan generation. The system is continuously improved through this feedback.

[0402] (Application Example 2)

[0403] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0404] There is a need to enrich the interaction with pets and provide more personalized entertainment experiences that match the emotional state of the owner. Furthermore, there is a lack of dynamic content adjustments that respond to the owner's psychological state. To address this issue, a system is needed that enhances the enjoyment for both pets and their owners.

[0405] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0406] In this invention, the server includes means for receiving information about pets and storing it in a data area, means for identifying the pet's behavioral patterns and preferences, means for generating personalized entertainment plans, means for analyzing user emotional data and dynamically adjusting the entertainment plan, and means for selecting content according to the type of pet and providing interactive content. This enables a rich entertainment experience for both pets and their owners.

[0407] "Information about pets" includes data such as the pet's species, age, behavioral history, preferences, and daily behavioral observations.

[0408] "Data operating area" refers to a storage system for storing and analyzing information.

[0409] "Behavioral patterns" refer to the tendencies and habits of behaviors that pets exhibit on a daily basis.

[0410] "Preferences" refers to data indicating the types of games and foods that pets particularly enjoy.

[0411] An "entertainment plan" is a specific plan of play and activities generated based on the pet's behavioral patterns and preferences.

[0412] "User emotional data" refers to information that indicates the psychological state of a user, analyzed from the voice and text input they provide.

[0413] "Interactive content" refers to digital content that includes two-way entertainment elements that allow pets and their owners to participate directly.

[0414] "Dynamic adjustment" means modifying and optimizing the entertainment plan in real time based on user sentiment data.

[0415] "Feedback" refers to information that pet owners input into the system regarding their pet's reactions and their evaluation of the plan.

[0416] This invention realizes a system that provides personalized entertainment for pets and their owners. It begins with the user entering detailed information about their pet using their smartphone or tablet device. The device collects data such as the pet's breed, age, behavioral history, and preferences, and transmits it to a server. At the same time, the system acquires the user's emotional data through voice input and text analysis on the device.

[0417] The server stores the received information in its data storage area, and an AI model analyzes the pet's behavior patterns and preferences. Based on this data, the AI ​​model generates an optimal entertainment plan. An emotion engine is used to analyze the user's emotional data. This engine determines the user's psychological state from voice and text.

[0418] In this system, the AI ​​model plays a crucial role in providing plans that take the user's emotions into account. The plan is displayed on the user's device, suggesting optimal playtime and interactive content for the pet. The user plays with their pet according to the plan and inputs feedback into the device. This feedback is sent to the server and used to retrain the model, which in turn improves the generation of future plans.

[0419] A concrete example of this system is a user who owns a two-year-old Siamese cat. The user enters information about their pet, and on days when the cat is stressed, relaxation music is recommended accordingly. An example of a prompt message in this case would be, "Please suggest an entertainment plan for a two-year-old Siamese cat. The owner is stressed today." Based on this prompt, the AI ​​model dynamically selects appropriate content, providing the user with entertainment tailored to their needs.

[0420] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0421] Step 1:

[0422] The terminal receives information from the user, such as the pet's breed, age, behavioral history, and preferences. This input information is then converted into a standard data format for transmission. The output is the formatted pet information.

[0423] Step 2:

[0424] The device acquires the user's voice and text data and analyzes their emotional state. This analysis uses voice analysis software and text analysis algorithms. The input is the user's voice and text, and the output is the user's emotional data.

[0425] Step 3:

[0426] The server receives pet information and user emotion data sent from the terminal and stores them in the data storage area. After receiving the data, it performs data interpolation and removes outliers. The output is the formatted information in the database.

[0427] Step 4:

[0428] The AI ​​model on the server analyzes the pet's behavioral patterns and preferences based on data from the operating area and generates a personalized entertainment plan. Here, the learning algorithm of the generative AI model is applied. The input is standardized pet information, and the output is the entertainment plan.

[0429] Step 5:

[0430] The emotion engine uses the user's emotional data to dynamically adjust the generated entertainment plan. This provides a plan that is tailored to the user's psychological state. The input is the user's emotional data, and the output is the adjusted entertainment plan.

[0431] Step 6:

[0432] The terminal displays the entertainment plan received from the server to the user and provides interactive content. User interaction here serves as feedback. The input is the plan from the server, and the output is the displayed and executed plan.

[0433] Step 7:

[0434] Users input their reactions and opinions after spending time with their pets as feedback into the device. This feedback is sent from the device to the server and used to retrain the model. The output is the feedback information sent to the server, which contributes to improving the accuracy of the next entertainment plan.

[0435] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0436] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0437] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0438] [Third Embodiment]

[0439] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0440] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0441] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0442] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0443] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0444] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0445] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0446] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0447] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0448] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0449] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0450] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0451] The present invention provides an AI-driven service that collects information about pets and generates personalized entertainment plans based on that information. The main components of this system are the user's terminal, a server, and an AI model that performs analysis and plan generation.

[0452] User's device: Pet owners input information about their pets into the system via smartphones or computers. This includes the pet's breed, age, sex, past behavioral history, and presumed preferences. The device can also observe and input the pet's daily behavior.

[0453] Server: The server receives data sent from terminals and stores it in a database. Since the received information is difficult to analyze directly, the server standardizes the data and processes missing data and outliers. The processed data is then prepared for analysis by an AI model.

[0454] AI Model: The server-based AI model analyzes pet behavior patterns and identifies pet preferences. This model learns from past and incoming data to generate an optimal entertainment plan for each individual pet. The plan includes the most effective activity times for the pet, recommended toys, and activities.

[0455] Specific example: For instance, a user's dog (a 2-year-old Labrador Retriever) tends to enjoy playing with balls and water. The user inputs this information via their device and reports the dog's health and mood daily. The server receives the information, and an AI model analyzes it to create the most effective entertainment plan. The plan might suggest playing fetch in the park in the evenings on weekdays and include water play in a dog pool on weekends. The user follows this plan and provides feedback on the dog's reactions and new behaviors, which helps to further optimize the plan.

[0456] In this way, this system aims to provide new and enjoyable experiences for both pets and their owners, and to improve the quality of life for pets.

[0457] The following describes the processing flow.

[0458] Step 1:

[0459] Users use their devices to enter basic information about their pets. This information includes the pet's breed, age, sex, past behavioral history, and preferences. Users can also record daily observations of their pets.

[0460] Step 2:

[0461] The terminal organizes the information entered by the user and sends it to the server. This information can be updated in real time and automatically sent to the server.

[0462] Step 3:

[0463] The server receives information sent from the terminal and stores it in the database. If the data is not standardized, the server unifies the data structure and detects and corrects missing data and outliers.

[0464] Step 4:

[0465] The AI ​​model on the server receives the formatted data and analyzes the pet's behavior patterns and preferences. Machine learning algorithms are used for the analysis to identify specific patterns and preferences.

[0466] Step 5:

[0467] Based on the analysis results, the AI ​​model generates a customized entertainment plan for each individual pet. The plan clearly outlines recommended activities, equipment to be used, and activity times.

[0468] Step 6:

[0469] The server sends the generated entertainment plan to the device. The device notifies the user of the plan and displays it for them to view within the app.

[0470] Step 7:

[0471] The user engages in playtime with their pet based on the provided plan. If the pet's reaction or new behaviors are observed, the user inputs this information as feedback into their device.

[0472] Step 8:

[0473] The device sends user feedback to the server. The server feeds this feedback into the AI ​​model, which is then used to retrain the model and improve the accuracy of the plan.

[0474] Step 9:

[0475] The server regenerates an optimized plan based on the feedback and sends it to the device. This iterative process ensures that the pet continuously receives the best possible entertainment experience.

[0476] (Example 1)

[0477] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0478] Modern pet owners are seeking personalized entertainment plans to improve their pets' quality of life, but there is a lack of concrete ways to provide them. Traditional methods fail to adequately analyze information needed to understand each pet's individual preferences and behavioral models and propose appropriate activities, thus failing to fully enhance pets' well-being and quality of activity.

[0479] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0480] In this invention, the server includes means for receiving data about pets and storing it in an information collection, means for standardizing the data and correcting missing data and outliers, and means for analyzing the information and identifying the pet's behavioral model and preferences. This makes it possible to generate and present personalized entertainment plans to the user.

[0481] "Pets" is a general term for animals that are kept in homes or special facilities and have an affinity for humans.

[0482] "Data" refers to a collection of information gathered for a specific purpose, such as the type of pet, age, sex, behavioral history, and preferences.

[0483] An "information collection" refers to an electronic database or server-based repository used to systematically store collected data.

[0484] "Standardization" is a process for converting collected data into a format that is easy to analyze, and it includes preprocessing to maintain data integrity.

[0485] "Missing data" refers to data that lacks information that should be present, and it needs to be supplemented to maintain the accuracy of the analysis.

[0486] An "outlier" refers to a value within a data set that deviates significantly from the normal range and requires special consideration in data processing.

[0487] A "behavioral model" is a model used to predict and explain the behavioral patterns that a pet may exhibit, based on its past behavioral data.

[0488] "Preferences" refer to specific activities, possessions, or environmental characteristics that a pet particularly enjoys.

[0489] An "entertainment plan" is a specific activity program designed individually based on the pet's behavioral model and preferences, with the aim of improving the pet's quality of life.

[0490] A "learning algorithm" refers to a method that automatically learns patterns and trends from data to make future predictions and decisions.

[0491] "Retraining" is the process of retraining an existing learning algorithm using new data to achieve better performance.

[0492] This invention describes a specific embodiment for implementing a pet entertainment plan generation system. This system is implemented using a user terminal, a server, and a generative AI model that performs analysis and plan generation.

[0493] User's terminal

[0494] Users enter detailed information about their pets into the system using their smartphones or computers. Typical information includes the pet's breed, age, sex, behavioral history, and preferences. The device can also observe the pet's daily behavior and input it as new data. This allows users to understand their pet's condition and reactions in real time and provide appropriate information.

[0495] server

[0496] The server has the function of receiving data sent from the user's terminal and storing it in a database. The server standardizes the received data and corrects missing data and outliers. This prepares the data in a format suitable for analysis by generative AI models, providing a foundation for obtaining accurate analysis results.

[0497] Generative AI Models

[0498] The generative AI model implemented on the server analyzes the pet's behavior and preferences. This AI model learns from past and incoming data to generate personalized entertainment plans. The generated plans include the optimal activity times and recommended toys for the pet. For example, if a Labrador Retriever enjoys playing with a ball, the model might suggest a specific plan such as "30 minutes of ball throwing in the park in the evening."

[0499] Specific example

[0500] This section explains how to use this system with a user's two-year-old Labrador Retriever. Since the dog enjoys playing in water and fetching balls, the user inputs this information via a terminal. The server receives this data, fills in missing data, corrects outliers, and passes it to the generating AI model. The model analyzes the data and generates an entertainment plan, suggesting activities such as fetching balls in the park in the evenings on weekdays and including water play in a dog pool on weekends. The user then carries out daily activities based on this plan, and the plan is further optimized by inputting feedback on the pet's reactions and any new behaviors back into the terminal.

[0501] An example of a prompt message could be: "Create an entertainment plan for a 2-year-old Labrador Retriever. This dog enjoys playing with balls and water. What should you consider?" In this way, the system helps to take pet interaction to a new level.

[0502] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0503] Step 1:

[0504] Users enter information about their pets using a terminal. This data includes detailed information such as the pet's breed, age, sex, behavioral history, and preferences. Users also enter additional information about their pet's health and mood based on daily observations. This information is then transmitted from the terminal to the server.

[0505] Step 2:

[0506] The server receives data sent by the user and stores it in the database. If the input data is incomplete or abnormal, the server inspects it and performs a standardization process. Specifically, it fills in missing data and corrects outliers appropriately. This process prepares the data into an analyzable format and outputs it as a dataset that can be used in the next processing step.

[0507] Step 3:

[0508] A server-based AI model performs analysis using a well-organized dataset. The model processes the data to identify pet behaviors and preferences. This process integrates historical and new data, performing data calculations to reveal patterns and trends. The output is a personalized recreation plan, which includes optimal activity times and recommended toys.

[0509] Step 4:

[0510] The server sends the generated activity plan to the user's device. The user reviews this plan and uses it in actual activities with their pet. The user observes the pet's reactions and new behaviors obtained through the activities and inputs this feedback information into their device. This feedback is sent back to the server and used for the system's next learning cycle.

[0511] Step 5:

[0512] Based on feedback received from users, the server retrains the generating AI model. In this step, the AI ​​model iteratively learns using the latest data, including the feedback information. This results in more accurate entertainment plans that can quickly adapt to changes in the pet's preferences and behavior.

[0513] (Application Example 1)

[0514] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0515] When it comes to pet ownership, the challenge lies in how to effectively provide entertainment plans optimized for each individual pet, and how to facilitate users' purchasing behavior at commercial facilities based on the suggested entertainment. Conventional systems struggle to provide individualized plans based on pets' behavior and preferences, and there is no automated mechanism to link these plans to specific purchases at commercial facilities, resulting in a lack of improvement in the quality of pet care and entertainment.

[0516] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0517] In this invention, the server includes means for receiving information about pets and storing it in a data warehouse; means for analyzing the information to identify the pet's behavioral tendencies and preferences; means for generating an individualized activity plan based on the behavioral tendencies and preferences; and means for facilitating the user's purchase at commercial facilities based on the proposed products and services. This enables a smooth purchasing experience at commercial facilities while providing optimal entertainment for pets.

[0518] "Information about pets" refers to data necessary to identify the characteristics of a pet, such as its breed, age, sex, behavioral history, and preferences.

[0519] A "data warehouse" is a database system for accumulating and standardizing information about pets.

[0520] "Behavioral tendencies" refer to patterns and habits in a pet's movements and activities.

[0521] "Preferences" refer to the types of games, interests, and activities that pets enjoy.

[0522] An "individualized activity plan" is an entertainment plan optimized for each pet's characteristics, based on the information and analysis results received about the pet.

[0523] "Users" refers to pet owners or businesses that provide services or products related to pets.

[0524] A "commercial establishment" refers to a retail store or service provider that sells pet products or services.

[0525] "Recursion" refers to feedback information sent from the user to the system, including changes in the pet's reactions and behavior.

[0526] A "generative AI model" is an artificial intelligence model that analyzes pet information and automatically generates the optimal entertainment plan.

[0527] To implement this invention, a system is required that includes a user's terminal, a server, and a generated AI model. The user's terminal uses a smartphone or computer to input and transmit information about the pet. The terminal collects data on the pet's breed, age, sex, behavioral history, and preferences, and transmits this data to the server.

[0528] The server processes the data received from the terminal. This processing includes data standardization, imputation of missing values, and correction of outliers. This prepares the data for analysis. Next, a generative AI model within the server performs the analysis. Based on the accumulated data, this AI model identifies the pet's behavioral tendencies and preferences and generates an individualized activity plan.

[0529] The generated activity plan includes the optimal activity time for pets, recommended toys, and specific activities. Based on this plan, users can easily purchase suggested products and services from physical stores or online platforms. This enhances pet entertainment and improves the user's purchasing experience.

[0530] Furthermore, the AI ​​model continuously learns and optimizes by providing feedback to the server via the user's device regarding changes in the pet's reactions and behavior. This recursive process further refines the activity plan.

[0531] As a concrete example, a user uses a smartphone app to input information about their toy poodle. The AI ​​model analyzes that the dog likes intelligent toys, and the app suggests a new puzzle toy. It also shows that the toy is available for purchase at a nearby commercial facility, supporting the user's purchase. The prompt "Suggest what kind of toys this toy poodle would be interested in in the morning" is used as input to the AI ​​model.

[0532] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0533] Step 1:

[0534] The terminal collects pet information entered by the user (breed, age, sex, behavioral history, preferences) and sends it to the server as JSON data. This input data forms the basis for data processing on the server.

[0535] Step 2:

[0536] The server parses the JSON data received from the terminal and standardizes the data. Specifically, it imputes missing data values ​​with the mean and detects and corrects outliers appropriately. The goal is to store the data in the database in the correct format, and this is the output.

[0537] Step 3:

[0538] The server passes standardized data as input to a generating AI model. This model uses machine learning algorithms to analyze the data and identify the pet's behavioral tendencies and preferences. As output, it creates profile data based on the identified behavioral patterns and preferences.

[0539] Step 4:

[0540] Based on profile data created by a generative AI model, the server generates a personalized activity plan. This plan includes optimal activity times, recommended toys, and specific activities to suggest. The plan is sent to the device in JSON format.

[0541] Step 5:

[0542] The terminal presents the user with an activity plan received from the server. The user reviews the plan and uses it as information to facilitate product purchases at physical stores or online.

[0543] Step 6:

[0544] Users send feedback about their pets' reactions and behaviors to a server via their devices. This feedback data is then passed to the AI ​​model as input for retraining.

[0545] Step 7:

[0546] The server retrains the generating AI model based on user feedback data. This allows the system to continuously learn the pet's preferences and behavioral tendencies, improving its activity plan. The output results in improved profile data and activity plans.

[0547] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0548] This invention provides a system that generates personalized entertainment plans based on information about pets and dynamically adjusts the plans to take into account the user's emotions. The system's main components are the user's terminal, a server, and an emotion engine that performs emotion recognition.

[0549] User's device: Users use smartphones or computers to input information about their pets, such as breed, age, behavioral history, preferences, and daily behavioral observations, into the system. The device also captures the user's voice and text, which are processed as sentiment data.

[0550] Server: The server receives pet information and user emotion information sent from the terminal and stores it in a database. The received information is standardized into a format that is easy for the AI ​​model to interpret, and any missing data or outliers are processed.

[0551] AI Model and Emotion Engine: The AI ​​model on the server analyzes the pet's behavior patterns and preferences to generate an optimized entertainment plan. Meanwhile, the emotion engine analyzes the user's emotional state from voice and text data to recognize the user's current emotions. The AI ​​model then adjusts the plan considering this emotional data to generate a plan that matches the user's psychological state.

[0552] Specific example: The user's cat (2 years old, Siamese) enjoys playing with a ball and a laser pointer. The user inputs daily observations into the device and adds voice memos on days when the cat felt stressed. The server receives the configured information, and the AI ​​model analyzes it to create a new entertainment plan. Furthermore, it generates a plan that prioritizes activities with a moderate level of exercise to help the user relax. The user interacts with their pet according to the presented plan and inputs feedback into the device. This information is used to retrain the model, and a more accurate plan is provided the next time.

[0553] Thus, this system not only deepens the relationship between pets and their owners, but also takes into account the user's emotional state, enabling it to provide a more personalized entertainment experience.

[0554] The following describes the processing flow.

[0555] Step 1:

[0556] The user uses the device to input basic information about their pet and observations of their daily activities. The device also acquires the user's voice and text data and collects data on the user's emotional state.

[0557] Step 2:

[0558] The terminal organizes the collected pet information and emotional data and sends it to the server. This information is formatted to ensure reliable data reception.

[0559] Step 3:

[0560] The server receives information sent from the terminal and stores it in the database. Next, it detects and corrects any missing data or outliers so that the data can be analyzed by the AI ​​model.

[0561] Step 4:

[0562] The AI ​​model analyzes the pet's behavior patterns and preferences within the server. Based on past behavioral history and information provided by the user, it generates an entertainment plan optimized for each individual pet.

[0563] Step 5:

[0564] The emotion engine on the server analyzes the user's voice and text data to recognize the user's current emotional state. This information is then used in plan generation.

[0565] Step 6:

[0566] The AI ​​model incorporates the recognized user's emotional state and adjusts the entertainment plan accordingly. For example, if the user is feeling stressed, it prioritizes plans that include calming activities.

[0567] Step 7:

[0568] The server sends the customized entertainment plan to the device. The device notifies the user of the plan and allows them to view the details within the app.

[0569] Step 8:

[0570] The user engages in playtime with their pet according to the plan. In addition to the pet's reactions, changes in the user's own emotional state are also taken into consideration and recorded as feedback on the device.

[0571] Step 9:

[0572] The device sends feedback information to the server, and the AI ​​model and emotion engine retrain based on this information. This improves the accuracy of the next plan generated.

[0573] This entire process ensures that users can continuously receive the best possible entertainment experience for their pets, taking their emotions into consideration.

[0574] (Example 2)

[0575] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0576] In pet-owner interaction, there is a need to provide personalized entertainment experiences based on the pet's characteristics and the owner's emotional state. However, conventional systems have the challenge of not being able to effectively integrate and dynamically adjust these elements.

[0577] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving information about the pet and the user and storing it in a storage device, means for analyzing the information to identify the pet's behavior patterns and preferences, and means for analyzing the user's emotional state and generating an individualized entertainment plan that takes the user's emotional state into account based on the behavior patterns and preferences. This enables a dynamic and individualized entertainment experience based on the pet's characteristics and the user's emotions.

[0578] 1. A "pet" is an animal or living creature kept in a household, living with people, and being an object of play or emotional interaction.

[0579] 2. "User" refers to an individual or organization that uses this system to input data about their pet and receives an entertainment plan.

[0580] 3. "Storage device" refers to a hardware or software configuration that holds data and makes it accessible as needed.

[0581] 4. "Analysis" refers to the process of examining data in detail and extracting meaningful information and patterns.

[0582] 5. "Behavioral patterns" refer to consistent patterns of behavior and activity that a pet exhibits, which can be used to identify the pet's preferences and habits.

[0583] 6. "Preferences" refer to the activities and objects that pets particularly enjoy, and this information is used to generate entertainment plans.

[0584] 7. "Emotional state" refers to the user's psychological state and is analyzed from voice and text data.

[0585] 8. "Recreational plans" refer to activities and suggestions that can be enjoyed by both the pet and the user, based on the pet's characteristics and the user's emotional state.

[0586] 9. "Feedback" refers to information provided by users to the system, based on the pet's reactions and the results of its activities.

[0587] 10. "Retraining" refers to the process of updating the AI ​​model based on newly collected data and feedback to improve the accuracy of the next entertainment plan.

[0588] This invention provides a system that generates personalized entertainment plans based on the pet's characteristics and the user's emotional state in order to improve user-pet interaction. The system mainly uses a user terminal, a server, and an emotion engine that performs emotion analysis.

[0589] Users input information about their pets using devices such as smartphones or computers. This information includes the pet's breed, age, behavioral history, and preferences. In addition, users input emotional data, such as voice or text data, into their devices. For example, they might record a voice message saying, "I was happy to play with my pet a lot today." This data is then transmitted to a server via the internet.

[0590] The server stores the received data in storage. Analysis programs implemented in Python, R, etc., are used to process the data and identify the pet's behavioral patterns and preferences. Missing values ​​are imputed using the mean or median. Based on the analysis results, an optimal entertainment plan for the pet is developed.

[0591] The emotion engine analyzes the user's voice and text data to identify their emotional state. A natural language processing API is used as the emotion analysis tool. Based on these analysis results, the entertainment plan is dynamically adjusted according to the user's emotional state.

[0592] As a concrete example, consider a user who owns a two-year-old Siamese cat and knows that their cat enjoys playing with a laser pointer. The user inputs, "I'm a little tired today, but I'd like to play with my cat a little." The server then receives this information and develops a play plan that matches the pet's energy level and the user's fatigue level. By suggesting a short play session using a laser pointer, the system provides an experience that satisfies both the user and the pet.

[0593] This system continuously receives feedback from users and retrains its model to improve the accuracy of its entertainment planning. An example of a prompt might be, "My pet Siamese cat is 2 years old and loves playing with balls. Today she's stressed. What kind of game would you suggest?"

[0594] Through these means, the present invention makes it possible to provide pets and their owners with a more personalized and fulfilling entertainment experience.

[0595] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0596] Step 1:

[0597] The user uses a device to input information about their pet and their own emotional state. The input data includes the pet's breed, age, behavioral history, preferences, and audio or text indicating the user's emotional state. The data is formatted in JSON or another format and sent to the server.

[0598] Step 2:

[0599] The server stores the received data in its storage device. It saves it to a database and standardizes the input data into a parseable format. For example, it assigns labels to each category and quantifies sentiment data. This standardization process allows AI models to easily analyze the data.

[0600] Step 3:

[0601] The server's AI model uses standardized pet data to analyze pet behavior patterns and preferences. For example, it identifies the most active times of day for pets based on past data and outputs behavioral patterns based on those times. Based on these analysis results, it predicts what kind of entertainment pets prefer.

[0602] Step 4:

[0603] The server's emotion engine analyzes the user's emotional data to identify their current emotional state. It performs voice tone analysis and extracts keywords from text to determine whether the user is positive and relaxed, or negative and stressed. This is output as an emotion statement and applied to adjust the entertainment plan.

[0604] Step 5:

[0605] The AI ​​model on the server generates a personalized entertainment plan, taking into account the pet's behavior patterns and the user's emotional state. Through data calculations, it selects activities suitable for the pet and makes adjustments based on the user's emotional state. The generated plan is output in JSON format and sent to the device.

[0606] Step 6:

[0607] The user receives an entertainment plan generated on their device and implements it with their pet. They observe the results of the plan's implementation and the pet's reaction, and provide feedback based on that. This information is used to generate the next plan.

[0608] Step 7:

[0609] The server receives feedback data from users and uses it again to train the AI ​​model. This data is incorporated into the model's training, enabling more accurate plan generation. The system is continuously improved through this feedback.

[0610] (Application Example 2)

[0611] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0612] There is a need to enrich the interaction with pets and provide more personalized entertainment experiences that match the emotional state of the owner. Furthermore, there is a lack of dynamic content adjustments that respond to the owner's psychological state. To address this issue, a system is needed that enhances the enjoyment for both pets and their owners.

[0613] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0614] In this invention, the server includes means for receiving information about pets and storing it in a data area, means for identifying the pet's behavioral patterns and preferences, means for generating personalized entertainment plans, means for analyzing user emotional data and dynamically adjusting the entertainment plan, and means for selecting content according to the type of pet and providing interactive content. This enables a rich entertainment experience for both pets and their owners.

[0615] "Information about pets" includes data such as the pet's species, age, behavioral history, preferences, and daily behavioral observations.

[0616] "Data operating area" refers to a storage system for storing and analyzing information.

[0617] "Behavioral patterns" refer to the tendencies and habits of behaviors that pets exhibit on a daily basis.

[0618] "Preferences" refers to data indicating the types of games and foods that pets particularly enjoy.

[0619] An "entertainment plan" is a specific plan of play and activities generated based on the pet's behavioral patterns and preferences.

[0620] "User emotional data" refers to information that indicates the psychological state of a user, analyzed from the voice and text input they provide.

[0621] "Interactive content" refers to digital content that includes two-way entertainment elements that allow pets and their owners to participate directly.

[0622] "Dynamic adjustment" means modifying and optimizing the entertainment plan in real time based on user sentiment data.

[0623] "Feedback" refers to information that pet owners input into the system regarding their pet's reactions and their evaluation of the plan.

[0624] This invention realizes a system that provides personalized entertainment for pets and their owners. It begins with the user entering detailed information about their pet using their smartphone or tablet device. The device collects data such as the pet's breed, age, behavioral history, and preferences, and transmits it to a server. At the same time, the system acquires the user's emotional data through voice input and text analysis on the device.

[0625] The server stores the received information in its data storage area, and an AI model analyzes the pet's behavior patterns and preferences. Based on this data, the AI ​​model generates an optimal entertainment plan. An emotion engine is used to analyze the user's emotional data. This engine determines the user's psychological state from voice and text.

[0626] In this system, the AI ​​model plays a crucial role in providing plans that take the user's emotions into account. The plan is displayed on the user's device, suggesting optimal playtime and interactive content for the pet. The user plays with their pet according to the plan and inputs feedback into the device. This feedback is sent to the server and used to retrain the model, which in turn improves the generation of future plans.

[0627] A concrete example of this system is a user who owns a two-year-old Siamese cat. The user enters information about their pet, and on days when the cat is stressed, relaxation music is recommended accordingly. An example of a prompt message in this case would be, "Please suggest an entertainment plan for a two-year-old Siamese cat. The owner is stressed today." Based on this prompt, the AI ​​model dynamically selects appropriate content, providing the user with entertainment tailored to their needs.

[0628] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0629] Step 1:

[0630] The terminal receives information from the user, such as the pet's breed, age, behavioral history, and preferences. This input information is then converted into a standard data format for transmission. The output is the formatted pet information.

[0631] Step 2:

[0632] The device acquires the user's voice and text data and analyzes their emotional state. This analysis uses voice analysis software and text analysis algorithms. The input is the user's voice and text, and the output is the user's emotional data.

[0633] Step 3:

[0634] The server receives pet information and user emotion data sent from the terminal and stores them in the data storage area. After receiving the data, it performs data interpolation and removes outliers. The output is the formatted information in the database.

[0635] Step 4:

[0636] The AI ​​model on the server analyzes the pet's behavioral patterns and preferences based on data from the operating area and generates a personalized entertainment plan. Here, the learning algorithm of the generative AI model is applied. The input is standardized pet information, and the output is the entertainment plan.

[0637] Step 5:

[0638] The emotion engine uses the user's emotional data to dynamically adjust the generated entertainment plan. This provides a plan that is tailored to the user's psychological state. The input is the user's emotional data, and the output is the adjusted entertainment plan.

[0639] Step 6:

[0640] The terminal displays the entertainment plan received from the server to the user and provides interactive content. User interaction here serves as feedback. The input is the plan from the server, and the output is the displayed and executed plan.

[0641] Step 7:

[0642] Users input their reactions and opinions after spending time with their pets as feedback into the device. This feedback is sent from the device to the server and used to retrain the model. The output is the feedback information sent to the server, which contributes to improving the accuracy of the next entertainment plan.

[0643] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0644] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0645] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0646] [Fourth Embodiment]

[0647] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0648] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0649] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0650] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0651] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0652] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0653] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0654] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0655] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0656] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0657] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0658] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0659] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0660] The present invention provides an AI-driven service that collects information about pets and generates personalized entertainment plans based on that information. The main components of this system are the user's terminal, a server, and an AI model that performs analysis and plan generation.

[0661] User's device: Pet owners input information about their pets into the system via smartphones or computers. This includes the pet's breed, age, sex, past behavioral history, and presumed preferences. The device can also observe and input the pet's daily behavior.

[0662] Server: The server receives data sent from terminals and stores it in a database. Since the received information is difficult to analyze directly, the server standardizes the data and processes missing data and outliers. The processed data is then prepared for analysis by an AI model.

[0663] AI Model: The server-based AI model analyzes pet behavior patterns and identifies pet preferences. This model learns from past and incoming data to generate an optimal entertainment plan for each individual pet. The plan includes the most effective activity times for the pet, recommended toys, and activities.

[0664] Specific example: For instance, a user's dog (a 2-year-old Labrador Retriever) tends to enjoy playing with balls and water. The user inputs this information via their device and reports the dog's health and mood daily. The server receives the information, and an AI model analyzes it to create the most effective entertainment plan. The plan might suggest playing fetch in the park in the evenings on weekdays and include water play in a dog pool on weekends. The user follows this plan and provides feedback on the dog's reactions and new behaviors, which helps to further optimize the plan.

[0665] In this way, this system aims to provide new and enjoyable experiences for both pets and their owners, and to improve the quality of life for pets.

[0666] The following describes the processing flow.

[0667] Step 1:

[0668] Users use their devices to enter basic information about their pets. This information includes the pet's breed, age, sex, past behavioral history, and preferences. Users can also record daily observations of their pets.

[0669] Step 2:

[0670] The terminal organizes the information entered by the user and sends it to the server. This information can be updated in real time and automatically sent to the server.

[0671] Step 3:

[0672] The server receives information sent from the terminal and stores it in the database. If the data is not standardized, the server unifies the data structure and detects and corrects missing data and outliers.

[0673] Step 4:

[0674] The AI ​​model on the server receives the formatted data and analyzes the pet's behavior patterns and preferences. Machine learning algorithms are used for the analysis to identify specific patterns and preferences.

[0675] Step 5:

[0676] Based on the analysis results, the AI ​​model generates a customized entertainment plan for each individual pet. The plan clearly outlines recommended activities, equipment to be used, and activity times.

[0677] Step 6:

[0678] The server sends the generated entertainment plan to the device. The device notifies the user of the plan and displays it for them to view within the app.

[0679] Step 7:

[0680] The user engages in playtime with their pet based on the provided plan. If the pet's reaction or new behaviors are observed, the user inputs this information as feedback into their device.

[0681] Step 8:

[0682] The device sends user feedback to the server. The server feeds this feedback into the AI ​​model, which is then used to retrain the model and improve the accuracy of the plan.

[0683] Step 9:

[0684] The server regenerates an optimized plan based on the feedback and sends it to the device. This iterative process ensures that the pet continuously receives the best possible entertainment experience.

[0685] (Example 1)

[0686] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0687] Modern pet owners are seeking personalized entertainment plans to improve their pets' quality of life, but there is a lack of concrete ways to provide them. Traditional methods fail to adequately analyze information needed to understand each pet's individual preferences and behavioral models and propose appropriate activities, thus failing to fully enhance pets' well-being and quality of activity.

[0688] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0689] In this invention, the server includes means for receiving data about pets and storing it in an information collection, means for standardizing the data and correcting missing data and outliers, and means for analyzing the information and identifying the pet's behavioral model and preferences. This makes it possible to generate and present personalized entertainment plans to the user.

[0690] "Pets" is a general term for animals that are kept in homes or special facilities and have an affinity for humans.

[0691] "Data" refers to a collection of information gathered for a specific purpose, such as the type of pet, age, sex, behavioral history, and preferences.

[0692] An "information collection" refers to an electronic database or server-based repository used to systematically store collected data.

[0693] "Standardization" is a process for converting collected data into a format that is easy to analyze, and it includes preprocessing to maintain data integrity.

[0694] "Missing data" refers to data that lacks information that should be present, and it needs to be supplemented to maintain the accuracy of the analysis.

[0695] An "outlier" refers to a value within a data set that deviates significantly from the normal range and requires special consideration in data processing.

[0696] A "behavioral model" is a model used to predict and explain the behavioral patterns that a pet may exhibit, based on its past behavioral data.

[0697] "Preferences" refer to specific activities, possessions, or environmental characteristics that a pet particularly enjoys.

[0698] An "entertainment plan" is a specific activity program designed individually based on the pet's behavioral model and preferences, with the aim of improving the pet's quality of life.

[0699] A "learning algorithm" refers to a method that automatically learns patterns and trends from data to make future predictions and decisions.

[0700] "Retraining" is the process of retraining an existing learning algorithm using new data to achieve better performance.

[0701] This invention describes a specific embodiment for implementing a pet entertainment plan generation system. This system is implemented using a user terminal, a server, and a generative AI model that performs analysis and plan generation.

[0702] User's terminal

[0703] Users enter detailed information about their pets into the system using their smartphones or computers. Typical information includes the pet's breed, age, sex, behavioral history, and preferences. The device can also observe the pet's daily behavior and input it as new data. This allows users to understand their pet's condition and reactions in real time and provide appropriate information.

[0704] server

[0705] The server has the function of receiving data sent from the user's terminal and storing it in a database. The server standardizes the received data and corrects missing data and outliers. This prepares the data in a format suitable for analysis by generative AI models, providing a foundation for obtaining accurate analysis results.

[0706] Generative AI Models

[0707] The generative AI model implemented on the server analyzes the pet's behavior and preferences. This AI model learns from past and incoming data to generate personalized entertainment plans. The generated plans include the optimal activity times and recommended toys for the pet. For example, if a Labrador Retriever enjoys playing with a ball, the model might suggest a specific plan such as "30 minutes of ball throwing in the park in the evening."

[0708] Specific example

[0709] This section explains how to use this system with a user's two-year-old Labrador Retriever. Since the dog enjoys playing in water and fetching balls, the user inputs this information via a terminal. The server receives this data, fills in missing data, corrects outliers, and passes it to the generating AI model. The model analyzes the data and generates an entertainment plan, suggesting activities such as fetching balls in the park in the evenings on weekdays and including water play in a dog pool on weekends. The user then carries out daily activities based on this plan, and the plan is further optimized by inputting feedback on the pet's reactions and any new behaviors back into the terminal.

[0710] An example of a prompt message could be: "Create an entertainment plan for a 2-year-old Labrador Retriever. This dog enjoys playing with balls and water. What should you consider?" In this way, the system helps to take pet interaction to a new level.

[0711] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0712] Step 1:

[0713] Users enter information about their pets using a terminal. This data includes detailed information such as the pet's breed, age, sex, behavioral history, and preferences. Users also enter additional information about their pet's health and mood based on daily observations. This information is then transmitted from the terminal to the server.

[0714] Step 2:

[0715] The server receives data sent by the user and stores it in the database. If the input data is incomplete or abnormal, the server inspects it and performs a standardization process. Specifically, it fills in missing data and corrects outliers appropriately. This process prepares the data into an analyzable format and outputs it as a dataset that can be used in the next processing step.

[0716] Step 3:

[0717] A server-based AI model performs analysis using a well-organized dataset. The model processes the data to identify pet behaviors and preferences. This process integrates historical and new data, performing data calculations to reveal patterns and trends. The output is a personalized recreation plan, which includes optimal activity times and recommended toys.

[0718] Step 4:

[0719] The server sends the generated activity plan to the user's device. The user reviews this plan and uses it in actual activities with their pet. The user observes the pet's reactions and new behaviors obtained through the activities and inputs this feedback information into their device. This feedback is sent back to the server and used for the system's next learning cycle.

[0720] Step 5:

[0721] Based on feedback received from users, the server retrains the generating AI model. In this step, the AI ​​model iteratively learns using the latest data, including the feedback information. This results in more accurate entertainment plans that can quickly adapt to changes in the pet's preferences and behavior.

[0722] (Application Example 1)

[0723] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0724] When it comes to pet ownership, the challenge lies in how to effectively provide entertainment plans optimized for each individual pet, and how to facilitate users' purchasing behavior at commercial facilities based on the suggested entertainment. Conventional systems struggle to provide individualized plans based on pets' behavior and preferences, and there is no automated mechanism to link these plans to specific purchases at commercial facilities, resulting in a lack of improvement in the quality of pet care and entertainment.

[0725] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0726] In this invention, the server includes means for receiving information about pets and storing it in a data warehouse; means for analyzing the information to identify the pet's behavioral tendencies and preferences; means for generating an individualized activity plan based on the behavioral tendencies and preferences; and means for facilitating the user's purchase at commercial facilities based on the proposed products and services. This enables a smooth purchasing experience at commercial facilities while providing optimal entertainment for pets.

[0727] "Information about pets" refers to data necessary to identify the characteristics of a pet, such as its breed, age, sex, behavioral history, and preferences.

[0728] A "data warehouse" is a database system for accumulating and standardizing information about pets.

[0729] "Behavioral tendencies" refer to patterns and habits in a pet's movements and activities.

[0730] "Preferences" refer to the types of games, interests, and activities that pets enjoy.

[0731] An "individualized activity plan" is an entertainment plan optimized for each pet's characteristics, based on the information and analysis results received about the pet.

[0732] "Users" refers to pet owners or businesses that provide services or products related to pets.

[0733] A "commercial establishment" refers to a retail store or service provider that sells pet products or services.

[0734] "Recursion" refers to feedback information sent from the user to the system, including changes in the pet's reactions and behavior.

[0735] A "generative AI model" is an artificial intelligence model that analyzes pet information and automatically generates the optimal entertainment plan.

[0736] To implement this invention, a system is required that includes a user's terminal, a server, and a generated AI model. The user's terminal uses a smartphone or computer to input and transmit information about the pet. The terminal collects data on the pet's breed, age, sex, behavioral history, and preferences, and transmits this data to the server.

[0737] The server processes the data received from the terminal. This processing includes data standardization, imputation of missing values, and correction of outliers. This prepares the data for analysis. Next, a generative AI model within the server performs the analysis. Based on the accumulated data, this AI model identifies the pet's behavioral tendencies and preferences and generates an individualized activity plan.

[0738] The generated activity plan includes the optimal activity time for pets, recommended toys, and specific activities. Based on this plan, users can easily purchase suggested products and services from physical stores or online platforms. This enhances pet entertainment and improves the user's purchasing experience.

[0739] Furthermore, the AI ​​model continuously learns and optimizes by providing feedback to the server via the user's device regarding changes in the pet's reactions and behavior. This recursive process further refines the activity plan.

[0740] As a concrete example, a user uses a smartphone app to input information about their toy poodle. The AI ​​model analyzes that the dog likes intelligent toys, and the app suggests a new puzzle toy. It also shows that the toy is available for purchase at a nearby commercial facility, supporting the user's purchase. The prompt "Suggest what kind of toys this toy poodle would be interested in in the morning" is used as input to the AI ​​model.

[0741] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0742] Step 1:

[0743] The terminal collects pet information entered by the user (breed, age, sex, behavioral history, preferences) and sends it to the server as JSON data. This input data forms the basis for data processing on the server.

[0744] Step 2:

[0745] The server parses the JSON data received from the terminal and standardizes the data. Specifically, it imputes missing data values ​​with the mean and detects and corrects outliers appropriately. The goal is to store the data in the database in the correct format, and this is the output.

[0746] Step 3:

[0747] The server passes standardized data as input to a generating AI model. This model uses machine learning algorithms to analyze the data and identify the pet's behavioral tendencies and preferences. As output, it creates profile data based on the identified behavioral patterns and preferences.

[0748] Step 4:

[0749] Based on profile data created by a generative AI model, the server generates a personalized activity plan. This plan includes optimal activity times, recommended toys, and specific activities to suggest. The plan is sent to the device in JSON format.

[0750] Step 5:

[0751] The terminal presents the user with an activity plan received from the server. The user reviews the plan and uses it as information to facilitate product purchases at physical stores or online.

[0752] Step 6:

[0753] Users send feedback about their pets' reactions and behaviors to a server via their devices. This feedback data is then passed to the AI ​​model as input for retraining.

[0754] Step 7:

[0755] The server retrains the generating AI model based on user feedback data. This allows the system to continuously learn the pet's preferences and behavioral tendencies, improving its activity plan. The output results in improved profile data and activity plans.

[0756] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0757] This invention provides a system that generates personalized entertainment plans based on information about pets and dynamically adjusts the plans to take into account the user's emotions. The system's main components are the user's terminal, a server, and an emotion engine that performs emotion recognition.

[0758] User's device: Users use smartphones or computers to input information about their pets, such as breed, age, behavioral history, preferences, and daily behavioral observations, into the system. The device also captures the user's voice and text, which are processed as sentiment data.

[0759] Server: The server receives pet information and user emotion information sent from the terminal and stores it in a database. The received information is standardized into a format that is easy for the AI ​​model to interpret, and any missing data or outliers are processed.

[0760] AI Model and Emotion Engine: The AI ​​model on the server analyzes the pet's behavior patterns and preferences to generate an optimized entertainment plan. Meanwhile, the emotion engine analyzes the user's emotional state from voice and text data to recognize the user's current emotions. The AI ​​model then adjusts the plan considering this emotional data to generate a plan that matches the user's psychological state.

[0761] Specific example: The user's cat (2 years old, Siamese) enjoys playing with a ball and a laser pointer. The user inputs daily observations into the device and adds voice memos on days when the cat felt stressed. The server receives the configured information, and the AI ​​model analyzes it to create a new entertainment plan. Furthermore, it generates a plan that prioritizes activities with a moderate level of exercise to help the user relax. The user interacts with their pet according to the presented plan and inputs feedback into the device. This information is used to retrain the model, and a more accurate plan is provided the next time.

[0762] Thus, this system not only deepens the relationship between pets and their owners, but also takes into account the user's emotional state, enabling it to provide a more personalized entertainment experience.

[0763] The following describes the processing flow.

[0764] Step 1:

[0765] The user uses the device to input basic information about their pet and observations of their daily activities. The device also acquires the user's voice and text data and collects data on the user's emotional state.

[0766] Step 2:

[0767] The terminal organizes the collected pet information and emotional data and sends it to the server. This information is formatted to ensure reliable data reception.

[0768] Step 3:

[0769] The server receives information sent from the terminal and stores it in the database. Next, it detects and corrects any missing data or outliers so that the data can be analyzed by the AI ​​model.

[0770] Step 4:

[0771] The AI ​​model analyzes the pet's behavior patterns and preferences within the server. Based on past behavioral history and information provided by the user, it generates an entertainment plan optimized for each individual pet.

[0772] Step 5:

[0773] The emotion engine on the server analyzes the user's voice and text data to recognize the user's current emotional state. This information is then used in plan generation.

[0774] Step 6:

[0775] The AI ​​model incorporates the recognized user's emotional state and adjusts the entertainment plan accordingly. For example, if the user is feeling stressed, it prioritizes plans that include calming activities.

[0776] Step 7:

[0777] The server sends the customized entertainment plan to the device. The device notifies the user of the plan and allows them to view the details within the app.

[0778] Step 8:

[0779] The user engages in playtime with their pet according to the plan. In addition to the pet's reactions, changes in the user's own emotional state are also taken into consideration and recorded as feedback on the device.

[0780] Step 9:

[0781] The device sends feedback information to the server, and the AI ​​model and emotion engine retrain based on this information. This improves the accuracy of the next plan generated.

[0782] This entire process ensures that users can continuously receive the best possible entertainment experience for their pets, taking their emotions into consideration.

[0783] (Example 2)

[0784] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0785] In pet-owner interaction, there is a need to provide personalized entertainment experiences based on the pet's characteristics and the owner's emotional state. However, conventional systems have the challenge of not being able to effectively integrate and dynamically adjust these elements.

[0786] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving information about the pet and the user and storing it in a storage device, means for analyzing the information to identify the pet's behavior patterns and preferences, and means for analyzing the user's emotional state and generating an individualized entertainment plan that takes the user's emotional state into account based on the behavior patterns and preferences. This enables a dynamic and individualized entertainment experience based on the pet's characteristics and the user's emotions.

[0787] 1. A "pet" is an animal or living creature kept in a household, living with people, and being an object of play or emotional interaction.

[0788] 2. "User" refers to an individual or organization that uses this system to input data about their pet and receives an entertainment plan.

[0789] 3. "Storage device" refers to a hardware or software configuration that holds data and makes it accessible as needed.

[0790] 4. "Analysis" refers to the process of examining data in detail and extracting meaningful information and patterns.

[0791] 5. "Behavioral patterns" refer to consistent patterns of behavior and activity that a pet exhibits, which can be used to identify the pet's preferences and habits.

[0792] 6. "Preferences" refer to the activities and objects that pets particularly enjoy, and this information is used to generate entertainment plans.

[0793] 7. "Emotional state" refers to the user's psychological state and is analyzed from voice and text data.

[0794] 8. "Recreational plans" refer to activities and suggestions that can be enjoyed by both the pet and the user, based on the pet's characteristics and the user's emotional state.

[0795] 9. "Feedback" refers to information provided by users to the system, based on the pet's reactions and the results of its activities.

[0796] 10. "Retraining" refers to the process of updating the AI ​​model based on newly collected data and feedback to improve the accuracy of the next entertainment plan.

[0797] This invention provides a system that generates personalized entertainment plans based on the pet's characteristics and the user's emotional state in order to improve user-pet interaction. The system mainly uses a user terminal, a server, and an emotion engine that performs emotion analysis.

[0798] Users input information about their pets using devices such as smartphones or computers. This information includes the pet's breed, age, behavioral history, and preferences. In addition, users input emotional data, such as voice or text data, into their devices. For example, they might record a voice message saying, "I was happy to play with my pet a lot today." This data is then transmitted to a server via the internet.

[0799] The server stores the received data in storage. Analysis programs implemented in Python, R, etc., are used to process the data and identify the pet's behavioral patterns and preferences. Missing values ​​are imputed using the mean or median. Based on the analysis results, an optimal entertainment plan for the pet is developed.

[0800] The emotion engine analyzes the user's voice and text data to identify their emotional state. A natural language processing API is used as the emotion analysis tool. Based on these analysis results, the entertainment plan is dynamically adjusted according to the user's emotional state.

[0801] As a concrete example, consider a user who owns a two-year-old Siamese cat and knows that their cat enjoys playing with a laser pointer. The user inputs, "I'm a little tired today, but I'd like to play with my cat a little." The server then receives this information and develops a play plan that matches the pet's energy level and the user's fatigue level. By suggesting a short play session using a laser pointer, the system provides an experience that satisfies both the user and the pet.

[0802] This system continuously receives feedback from users and retrains its model to improve the accuracy of its entertainment planning. An example of a prompt might be, "My pet Siamese cat is 2 years old and loves playing with balls. Today she's stressed. What kind of game would you suggest?"

[0803] Through these means, the present invention makes it possible to provide pets and their owners with a more personalized and fulfilling entertainment experience.

[0804] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0805] Step 1:

[0806] The user uses a device to input information about their pet and their own emotional state. The input data includes the pet's breed, age, behavioral history, preferences, and audio or text indicating the user's emotional state. The data is formatted in JSON or another format and sent to the server.

[0807] Step 2:

[0808] The server stores the received data in its storage device. It saves it to a database and standardizes the input data into a parseable format. For example, it assigns labels to each category and quantifies sentiment data. This standardization process allows AI models to easily analyze the data.

[0809] Step 3:

[0810] The server's AI model uses standardized pet data to analyze pet behavior patterns and preferences. For example, it identifies the most active times of day for pets based on past data and outputs behavioral patterns based on those times. Based on these analysis results, it predicts what kind of entertainment pets prefer.

[0811] Step 4:

[0812] The server's emotion engine analyzes the user's emotional data to identify their current emotional state. It performs voice tone analysis and extracts keywords from text to determine whether the user is positive and relaxed, or negative and stressed. This is output as an emotion statement and applied to adjust the entertainment plan.

[0813] Step 5:

[0814] The AI ​​model on the server generates a personalized entertainment plan, taking into account the pet's behavior patterns and the user's emotional state. Through data calculations, it selects activities suitable for the pet and makes adjustments based on the user's emotional state. The generated plan is output in JSON format and sent to the device.

[0815] Step 6:

[0816] The user receives an entertainment plan generated on their device and implements it with their pet. They observe the results of the plan's implementation and the pet's reaction, and provide feedback based on that. This information is used to generate the next plan.

[0817] Step 7:

[0818] The server receives feedback data from users and uses it again to train the AI ​​model. This data is incorporated into the model's training, enabling more accurate plan generation. The system is continuously improved through this feedback.

[0819] (Application Example 2)

[0820] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0821] There is a need to enrich the interaction with pets and provide more personalized entertainment experiences that match the emotional state of the owner. Furthermore, there is a lack of dynamic content adjustments that respond to the owner's psychological state. To address this issue, a system is needed that enhances the enjoyment for both pets and their owners.

[0822] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0823] In this invention, the server includes means for receiving information about pets and storing it in a data area, means for identifying the pet's behavioral patterns and preferences, means for generating personalized entertainment plans, means for analyzing user emotional data and dynamically adjusting the entertainment plan, and means for selecting content according to the type of pet and providing interactive content. This enables a rich entertainment experience for both pets and their owners.

[0824] "Information about pets" includes data such as the pet's species, age, behavioral history, preferences, and daily behavioral observations.

[0825] "Data operating area" refers to a storage system for storing and analyzing information.

[0826] "Behavioral patterns" refer to the tendencies and habits of behaviors that pets exhibit on a daily basis.

[0827] "Preferences" refers to data indicating the types of games and foods that pets particularly enjoy.

[0828] An "entertainment plan" is a specific plan of play and activities generated based on the pet's behavioral patterns and preferences.

[0829] "User emotional data" refers to information that indicates the psychological state of a user, analyzed from the voice and text input they provide.

[0830] "Interactive content" refers to digital content that includes two-way entertainment elements that allow pets and their owners to participate directly.

[0831] "Dynamic adjustment" means modifying and optimizing the entertainment plan in real time based on user sentiment data.

[0832] "Feedback" refers to information that pet owners input into the system regarding their pet's reactions and their evaluation of the plan.

[0833] This invention realizes a system that provides personalized entertainment for pets and their owners. It begins with the user entering detailed information about their pet using their smartphone or tablet device. The device collects data such as the pet's breed, age, behavioral history, and preferences, and transmits it to a server. At the same time, the system acquires the user's emotional data through voice input and text analysis on the device.

[0834] The server stores the received information in its data storage area, and an AI model analyzes the pet's behavior patterns and preferences. Based on this data, the AI ​​model generates an optimal entertainment plan. An emotion engine is used to analyze the user's emotional data. This engine determines the user's psychological state from voice and text.

[0835] In this system, the AI ​​model plays a crucial role in providing plans that take the user's emotions into account. The plan is displayed on the user's device, suggesting optimal playtime and interactive content for the pet. The user plays with their pet according to the plan and inputs feedback into the device. This feedback is sent to the server and used to retrain the model, which in turn improves the generation of future plans.

[0836] A concrete example of this system is a user who owns a two-year-old Siamese cat. The user enters information about their pet, and on days when the cat is stressed, relaxation music is recommended accordingly. An example of a prompt message in this case would be, "Please suggest an entertainment plan for a two-year-old Siamese cat. The owner is stressed today." Based on this prompt, the AI ​​model dynamically selects appropriate content, providing the user with entertainment tailored to their needs.

[0837] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0838] Step 1:

[0839] The terminal receives information from the user, such as the pet's breed, age, behavioral history, and preferences. This input information is then converted into a standard data format for transmission. The output is the formatted pet information.

[0840] Step 2:

[0841] The device acquires the user's voice and text data and analyzes their emotional state. This analysis uses voice analysis software and text analysis algorithms. The input is the user's voice and text, and the output is the user's emotional data.

[0842] Step 3:

[0843] The server receives pet information and user emotion data sent from the terminal and stores them in the data storage area. After receiving the data, it performs data interpolation and removes outliers. The output is the formatted information in the database.

[0844] Step 4:

[0845] The AI ​​model on the server analyzes the pet's behavioral patterns and preferences based on data from the operating area and generates a personalized entertainment plan. Here, the learning algorithm of the generative AI model is applied. The input is standardized pet information, and the output is the entertainment plan.

[0846] Step 5:

[0847] The emotion engine uses the user's emotional data to dynamically adjust the generated entertainment plan. This provides a plan that is tailored to the user's psychological state. The input is the user's emotional data, and the output is the adjusted entertainment plan.

[0848] Step 6:

[0849] The terminal displays the entertainment plan received from the server to the user and provides interactive content. User interaction here serves as feedback. The input is the plan from the server, and the output is the displayed and executed plan.

[0850] Step 7:

[0851] Users input their reactions and opinions after spending time with their pets as feedback into the device. This feedback is sent from the device to the server and used to retrain the model. The output is the feedback information sent to the server, which contributes to improving the accuracy of the next entertainment plan.

[0852] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0853] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0854] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0855] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0856] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0857] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0858] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0859] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0860] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0861] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0862] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0863] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0864] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0865] 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.

[0866] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0867] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0868] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0869] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0870] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0871] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0872] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0873] The following is further disclosed regarding the embodiments described above.

[0874] (Claim 1)

[0875] A means of receiving information about pets and storing it in a database,

[0876] A means for analyzing the aforementioned information to identify the pet's behavioral patterns and preferences,

[0877] A means for generating an individualized entertainment plan based on the aforementioned behavioral patterns and preferences,

[0878] A means of presenting the aforementioned plan to the user,

[0879] A means for receiving user feedback and retraining the model to improve the generated plan,

[0880] A system that includes this.

[0881] (Claim 2)

[0882] The system according to claim 1, wherein the entertainment plan includes the pet's activity time and recommended toys.

[0883] (Claim 3)

[0884] The system according to claim 1, wherein the feedback relates to the pet's reactions and behavioral patterns.

[0885] "Example 1"

[0886] (Claim 1)

[0887] A means for receiving data related to pets and storing it in an information collection,

[0888] A means for standardizing the aforementioned data and correcting missing data and outliers,

[0889] A means for analyzing the aforementioned information to identify the pet's behavioral model and preferences,

[0890] Means for generating an individualized entertainment plan based on the aforementioned behavioral model and preferences,

[0891] A means for presenting the aforementioned plan to the user,

[0892] A means for receiving user feedback and retraining the learning algorithm to improve the generated plan,

[0893] A system that includes this.

[0894] (Claim 2)

[0895] The system according to claim 1, wherein the recreation plan includes time slots for pet activities and recommended toys.

[0896] (Claim 3)

[0897] The system according to claim 1, wherein the feedback relates to a pet's response and behavior model.

[0898] "Application Example 1"

[0899] (Claim 1)

[0900] A means of receiving information about pets and storing it in a data warehouse,

[0901] A means for analyzing the aforementioned information to identify the behavioral tendencies and preferences of pets,

[0902] A means for generating an individualized activity plan based on the aforementioned behavioral tendencies and preferences,

[0903] A means of presenting the aforementioned activity plan to the user,

[0904] A means for receiving recursion from a user and retraining the model to improve the generated plan,

[0905] Based on the proposed products and services, means to make it easier for users to purchase them at commercial facilities,

[0906] A system that includes this.

[0907] (Claim 2)

[0908] The system according to claim 1, wherein the activity plan includes the pet's activity time and recommended toys.

[0909] (Claim 3)

[0910] The system according to claim 1, wherein the recursion relates to the pet's reactions and behavioral tendencies.

[0911] "Example 2 of combining an emotion engine"

[0912] (Claim 1)

[0913] Means for receiving and storing information about pets and users in a storage device,

[0914] A means for analyzing the aforementioned information to identify the pet's behavioral patterns and preferences,

[0915] A means for analyzing the user's emotional state and generating an individualized entertainment plan that takes the user's emotional state into account, based on the aforementioned behavioral patterns and preferences,

[0916] Means for providing the aforementioned plan to users,

[0917] A means for receiving feedback from users and retraining the model to improve the generated plan,

[0918] A system that includes this.

[0919] (Claim 2)

[0920] The system according to claim 1, wherein the recreation plan includes the pet's activity time and recommended toys.

[0921] (Claim 3)

[0922] The system according to claim 1, wherein the opinion relating to the reaction and behavioral patterns of a pet.

[0923] "Application example 2 of combining emotional engines"

[0924] (Claim 1)

[0925] A means for receiving information about pets and storing it in a data operating area,

[0926] A means for analyzing the aforementioned information to identify the pet's behavioral patterns and preferences,

[0927] A means for generating an individualized entertainment plan based on the aforementioned behavioral patterns and preferences,

[0928] A means of presenting the aforementioned plan to the user,

[0929] A means of analyzing user emotional data and dynamically adjusting entertainment plans,

[0930] A means for receiving feedback from users and retraining the model to improve the generated plan,

[0931] A means of selecting content according to the type of pet and providing interactive content that matches the user's psychological state,

[0932] A system that includes this.

[0933] (Claim 2)

[0934] The system according to claim 1, wherein the entertainment plan includes the pet's activity time and recommended play equipment, and further includes content that has a relaxation effect according to the user's emotional state.

[0935] (Claim 3)

[0936] The system according to claim 1, wherein the feedback relates to the pet's reactions and behavioral patterns, and is further based on the user's emotional data obtained. [Explanation of Symbols]

[0937] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving information about pets and storing it in a database, A means for analyzing the aforementioned information to identify the pet's behavioral patterns and preferences, A means for generating an individualized entertainment plan based on the aforementioned behavioral patterns and preferences, A means of presenting the aforementioned plan to the user, A means for receiving user feedback and retraining the model to improve the generated plan, A system that includes this.

2. The system according to claim 1, wherein the entertainment plan includes the pet's activity time and recommended toys.

3. The system according to claim 1, wherein the feedback relates to the pet's reactions and behavioral patterns.

Images