system

Abstract

We provide the system. [Solution] A means of collecting animal biological data from a health monitoring device, A means for integrating and analyzing the aforementioned biological data and animal husbandry information, A generation means for generating a story that describes the animal's situation based on the analysis results, A means of providing the generated stories to an online platform, 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, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In animal protection organizations, it is difficult to manage the health status of protected animals and effectively communicate that information to supporters and potential adopters. In particular, detailed health management using biological data requires specialized knowledge and resources, and many facilities are not adequately equipped to handle it. In addition, supporters lack means to directly understand how their support is helpful, and as a result, it is difficult to obtain sustainable support. The purpose of this invention is to solve these problems and streamline the process of animal health management and information dissemination.

Means for Solving the Problems

[0005] This invention provides means for collecting animal biometric data from a health monitoring device, and further means for integrating and analyzing the biometric data and animal care information. The proposed system includes means for generating a narrative representing the animal's condition based on the analysis results, and means for providing the generated narrative to an online platform. This enables efficient management of animal health data, transparent information provision to supporters, and promotion of sustainable support and acquisition of new foster families. Furthermore, the system includes means for selecting and integrating visual information, providing more detailed feedback to supporters and improving the effectiveness of support activities.

[0006] A "health monitoring device" is a device attached to a pet to collect biological data such as the animal's heart rate, body temperature, and activity level.

[0007] "Biometric data" refers to data that serves as an objective indicator of an animal's health status, such as heart rate, body temperature, and activity level.

[0008] "Breeding information" refers to data about the animal's daily behavior, habits, and living environment.

[0009] "Analysis" refers to the process of data processing using computer algorithms to evaluate the health status of animals based on collected biological data and breeding information.

[0010] "A means of generating narratives" refers to software or algorithms that automatically generate emotionally rich narratives describing the situations of animals, based on collected and analyzed data.

[0011] An "online platform" is an internet-based media or service for supporting and publishing generated stories and related information.

[0012] "Visual information" refers to visual data such as animal photographs and videos, which complement the narrative and enhance its visual appeal.

[0013] A "supporter" is an individual or organization that provides funds or supplies to support animal protection activities. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This 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 a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

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

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

[0017] In the following embodiments, a 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, a 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, a 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] This embodiment of the invention describes a specific example of a system that streamlines the health management and information provision of protected animals. The system consists of a health monitoring device, a data analysis server, a user terminal, and an online platform.

[0036] Overall system configuration

[0037] Health monitoring devices attached to animals acquire biometric data such as heart rate, body temperature, and activity level in real time. This data is transmitted to a server via wireless communication.

[0038] Data collection and analysis

[0039] The server records biological data received from monitoring devices into a database. It also records observation information about the animals entered by animal care staff using terminals. The server integrates this data and performs analysis using AI algorithms. The health status assessment obtained through this analysis is used to generate stories about the animals.

[0040] Story generation and publication

[0041] The server generates emotionally resonant stories that reflect the animal's health and behavior based on the analysis results. These stories are crucial content for conveying the animal's appeal to supporters and potential adopters. The generated stories, along with relevant visual information, are posted to an online platform.

[0042] Providing information to supporters

[0043] Users can access a dashboard through a dedicated application or website. This dashboard displays the latest health data, stories, and results of the support given to the animals. This allows users to see specifically how their support is making a difference.

[0044] Specific example

[0045] For example, in the case of a cat that a user is supporting, a monitoring device detects an increase in heart rate while the cat is sleeping, and the server receives data indicating an increase in active time. The server then analyzes this data and generates a story such as, "Today the cat played with its favorite toy for longer than usual!", selects a photo of the cat playing as visual information, and posts it on social media. Through this process, supporters can understand that their support is contributing to improving the cat's life.

[0046] In this way, the system integrates everything from animal health management to information dissemination, creating a mechanism that promotes support activities.

[0047] The following describes the processing flow.

[0048] Step 1:

[0049] The server automatically collects animal biometric data from the health monitoring device. This process is carried out by wirelessly transmitting the data obtained by the device in real time to the server. The biometric data includes information on heart rate, body temperature, and activity level.

[0050] Step 2:

[0051] The terminal provides an interface that allows zookeepers to input information about the animals' daily behavior and any abnormalities they observe. The information entered via the terminal is sent to a server and integrated with other data.

[0052] Step 3:

[0053] The server integrates the collected biometric data and breeding information and begins analysis using an AI algorithm. This analysis evaluates whether the data is within the normal range and quantifies the health status. If abnormal results are found, an alert is generated.

[0054] Step 4:

[0055] The server uses an AI generation program to create a story that reflects the animal's current condition based on the analysis results. The generated story is designed to include the animal's health status and any notable events that occurred on that day.

[0056] Step 5:

[0057] The server selects visual information related to the generated story and combines it to create an information package. This package is then prepared for posting to a social networking platform.

[0058] Step 6:

[0059] The server specifies the posting time and target social media platform, and posts the story and visual information package to the selected platform via an API. This ensures that the information is widely disseminated and reaches supporters and potential foster parents.

[0060] Step 7:

[0061] Users can access the dashboard using their own devices to view the latest health status of the animals they are supporting, posted stories, and the impact of their support activities. The dashboard reflects information from the server in real time.

[0062] (Example 1)

[0063] 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."

[0064] There is a need for a system that contributes to animal welfare by effectively monitoring the health status of animals and providing relevant information to supporters. This system needs to collect and analyze accurate data in real time and disseminate the information in an easy-to-understand and engaging format. However, conventional methods have problems with efficient information integration and sharing, preventing supporters from fully understanding the effectiveness of their support.

[0065] 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.

[0066] In this invention, the server includes means for receiving biological information of an animal from a health monitoring device, means for integrating and processing the biological information and animal management information, and means for generating a narrative that represents the animal's condition based on the processing results. This makes it possible to comprehensively monitor the animal's health status and provide caregivers with easily understandable, visually represented information.

[0067] A "health monitoring device" is a device used to acquire biological information about animals in real time.

[0068] "Biometric information" refers to data that indicates an animal's health status, such as heart rate, body temperature, and activity level.

[0069] "Management information" refers to data that includes observation records and behavioral history related to the care of animals.

[0070] A "communication network" refers to the entire infrastructure used for sending and receiving digital data.

[0071] "Processing" refers to the process of integrating and analyzing received biometric and management information.

[0072] A "generation method" is a mechanism for creating specific content or a story based on input data.

[0073] "Image information" refers to image data used to complement and visually represent a generated narrative.

[0074] A "supporter" is an individual or organization that provides support for the health management and welfare improvement of animals.

[0075] One embodiment of this invention involves a process for providing important information to caregivers and effectively managing the health status of animals through an animal health management system. This system primarily utilizes health monitoring devices, servers, user terminals, and a communication network.

[0076] The server receives biological information from the animals via health monitoring devices. Specifically, this includes information such as heart rate, body temperature, and activity level. The received biological information is recorded in a database on the server and further integrated with management information entered by animal care staff from user terminals.

[0077] The server uses an AI algorithm to analyze this integrated data. This AI algorithm, known as a generative AI model, has the ability to generate creative stories based on the analysis results. By inputting prompts into this model, the server generates stories that reflect the health status and behavior of animals.

[0078] The generated stories are integrated with image information and transmitted by the server to an online platform via a communication network. This allows users to view the latest health information and stories of the animals they are supporting through a dedicated application or website.

[0079] For example, if a monitoring device detects a change in the cat's heart rate, the server analyzes this data, generates a story such as, "Today, the cat played with its favorite toy for longer than usual!", and provides information to supporters by posting it on online platforms such as social media.

[0080] An example of a prompt message is: "Generate a story that reflects changes in the cat's heart rate and active time, based on the cat's health monitoring data. Use photos of the cat playing as visual information."

[0081] This format allows for detailed and engaging communication about the animals' health status, enabling supporters to conduct their aid activities more effectively.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] The server receives biological information from the animal's health monitoring device. Specifically, it collects data such as heart rate, body temperature, and activity level. This data is transmitted to the server wirelessly. The input is biological information from the health monitoring device, and the output is structured data recorded in the server's database.

[0085] Step 2:

[0086] The terminal is used by animal care staff to input observation information about the animals. This observation information includes diet, behavior, and any notable changes in health. The input is management information from the animal care staff, and the output is that this information is integrated and stored in the server's database.

[0087] Step 3:

[0088] The server integrates biometric and management information, retrieves it from a database, and performs analysis using AI algorithms. This analysis evaluates the animal's health status, detects abnormalities, and helps understand behavioral patterns. The input is integrated biometric and management information, and the output is the health status and behavioral evaluation as a result of the analysis.

[0089] Step 4:

[0090] The server utilizes a generative AI model to generate a story based on the analysis results. It inputs prompt sentences into the generative AI model to generate an emotionally rich story. The input consists of the analysis results and prompt sentences, and the output is the generated story.

[0091] Step 5:

[0092] The server selects image information related to the generated story, integrates it, and provides it to an online platform on a communication network. The input is the story and image information, and the output is the online post as visually enhanced content.

[0093] Step 6:

[0094] Users access a dedicated application or website to view the health status and generated stories of the animals they are supporting. This allows users to stay informed about the latest information and the impact of their support. The input is the content published on the platform, and the output is the user's informational experience as their perception and understanding.

[0095] (Application Example 1)

[0096] 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."

[0097] In modern times, understanding and participating in support activities for rescued animals is important, but there is a challenge in that it is difficult for supporters to easily grasp the health status of animals and the specific impact of support activities. In addition, there is a problem that support activities are not sufficiently promoted because there are insufficient means to effectively share the situation of animals with other supporters and prospective adopters and deepen interactions.

[0098] 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.

[0099] In this invention, the server includes means for collecting animal physiological data, means for integrating and analyzing the physiological data and animal management information, and means for generating a narrative of the animal's condition based on the analysis results. This allows caregivers to understand the animal's health status and activities in narrative form, and also enables them to share the generated information with other users and deepen their interactions.

[0100] A "biological monitoring device" is a device that acquires real-time physiological data such as the heart rate, body temperature, and activity level of animals.

[0101] "Physiological data" refers to data that indicates the health status and activity level of an animal, such as heart rate, body temperature, and exercise level.

[0102] "Management information" refers to information about the animals' care and lifestyle, including observational information provided by the caretaker.

[0103] "Analysis means" refers to processing means for integrating collected physiological data and management information and evaluating the health status of animals using AI algorithms.

[0104] A "narrative generation method" is a processing method for generating a narrative that expresses the health status and behavior of an animal in an emotionally rich manner, based on the analysis results.

[0105] A "dashboard" is a screen that provides users with a viewable format of the generated story and related visual information.

[0106] A "communication network" is a network used to send and receive information via the internet.

[0107] The system for realizing this invention consists of a bio-monitoring device that collects biological data from animals, a server that analyzes the data and generates and provides stories, and terminals for users to view and share stories.

[0108] First, a bio-monitoring device collects physiological data such as the animal's heart rate, body temperature, and activity level in real time. This device is equipped with a communication device and transmits the collected data wirelessly to a server.

[0109] Next, the server stores the received physiological data in a database. The server then analyzes the collected data using an AI algorithm (e.g., TENSORFLOW®) to assess the animal's health. Based on this assessment, it generates an emotionally resonant story using a generative AI model. The server visualizes this generated story in a dashboard format, making it accessible to users remotely.

[0110] Users with a device can access a dashboard via the internet. This dashboard displays the latest health data and generated stories of the animals. Users can share stories with other supporters and potential foster families and exchange information. They can also easily post stories to their own social networks using the social networking features.

[0111] For example, if a user's dog's heart rate data shows an increase in activity level, the server will use this data to generate a story such as, "Today the dog ran around the park full of energy!" A possible prompt for the generating AI model might be, "Based on recent heart rate and activity data, please create a story that reflects a lively day."

[0112] In this way, this system will enable the smooth progress of animal health management and support activities.

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] The bio-monitoring device collects physiological data such as the animal's heart rate, body temperature, and activity level in real time. It receives various physiological data from the animal as input and transmits it wirelessly to a server. The output is the transmission of data to the server.

[0116] Step 2:

[0117] The server stores physiological data received wirelessly in a database. It accumulates data by receiving physiological data from a biological monitoring device as input and storing it in the database. The output is the physiological data stored in the database.

[0118] Step 3:

[0119] The server retrieves physiological data stored in the database and analyzes it using an AI algorithm. This analysis uses the extracted physiological data as input to evaluate the animal's health status. The output is the health status evaluation result obtained from the analysis.

[0120] Step 4:

[0121] The server generates a story using a generative AI model based on the analysis. The prompt for the AI ​​model is something like, "Generate a story reflecting a day in the life of an animal, based on the health assessment results." The output is the generated story.

[0122] Step 5:

[0123] The server visualizes the generated stories in a dashboard format and provides them to the user via the terminal. This process takes the generated stories as input and outputs structured display data for display on the user's terminal.

[0124] Step 6:

[0125] Users access the dashboard using their devices and view the generated stories. Input is dashboard data provided by the server, and output is the user's visually perceived screen display. Users also perform actions necessary to share the stories on social networks.

[0126] Step 7:

[0127] Users share their stories with other supporters using social networking features via their devices and exchange information with them. The input is the data of the story they want to share, and the output is a social networking post that generates interaction with other users.

[0128] This processing flow allows users to effectively acquire and share stories based on animal physiological data.

[0129] 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.

[0130] In this embodiment of the invention, a system is provided that takes into account not only the health management and information provision of rescued animals, but also the emotions of the user. The system consists of a health monitoring device, a data analysis server, a user terminal, an emotion engine, and an online platform.

[0131] Overall system configuration

[0132] Animals are fitted with health monitoring devices that capture real-time biometric data such as heart rate, body temperature, and activity level. This data is transmitted to a server and stored in a database along with care information entered by animal care staff via terminals. The server uses AI algorithms to integrate and analyze this data to evaluate the animals' health status.

[0133] Embedding an emotion engine

[0134] The emotion engine is used to recognize user emotions and adjust the content of the stories and materials generated. By analyzing user feedback and reactions in real time as users view the content, the emotion engine enables the delivery of information tailored to individual users.

[0135] Story generation and customization

[0136] The server generates a story about the animal's situation based on analysis results and feedback from the emotion engine. The generated story is customized to suit the user's emotions and posted to an online platform along with relevant visual information. This allows supporters and potential adopters to access information about the animals in a more emotionally resonant way.

[0137] Providing information to supporters and utilizing their feedback

[0138] Users use their devices to check the latest health data and content for the animals they support via a dashboard. During this process, the emotion engine records the user's reactions and uses this information to suggest future content. For example, if a user shows a positive reaction to a particular type of story, this information will be reflected in the next story generation.

[0139] Specific example

[0140] A Facebook post about a dog named Coco, which a user supports, is based on data collected by a monitoring device, specifically "Increased walking time today." The emotion engine detects from past data that the user tends to prefer stories about "Increased Activity" and feeds this information back to the server. Based on the analysis, the server generates a story such as "Coco had a great time running around her favorite park!" and posts it along with a photo of Coco during her walk. This post is customized based on the emotion engine's analysis and is expected to strongly attract the user's interest.

[0141] In this way, the introduction of an emotion engine allows the system to personalize animal health management and information dissemination, promoting more effective support activities.

[0142] The following describes the processing flow.

[0143] Step 1:

[0144] The server collects animal biometric data in real time from health monitoring devices. The devices measure the animal's heart rate, body temperature, and activity level, and transmit this data to the server wirelessly, recording it in a database.

[0145] Step 2:

[0146] The terminal provides an interface for zookeepers to input information about the animals' behavior and health as observed. The zookeepers input this observation information into the terminal and send it to the server.

[0147] Step 3:

[0148] The server integrates and analyzes the collected biometric data and breeding information. Using AI algorithms, it assesses the animals' health status and generates a numerical score. If an abnormal pattern is detected, it triggers an alert.

[0149] Step 4:

[0150] The emotion engine analyzes the user's past feedback and emotional responses to evaluate their preferences and interests. Based on this evaluation, the server adjusts the process to generate a story that is best suited to the user.

[0151] Step 5:

[0152] Based on the analysis results and feedback from the emotion engine, the server generates a story to convey the animal's situation. The story includes the animal's health condition and notable events of the day, and is expressed with rich emotion.

[0153] Step 6:

[0154] The server selects visual materials (photos and videos) related to the story and creates a package that integrates them to match the story's content. The package is optimized to resonate with the user's emotions.

[0155] Step 7:

[0156] The server uses SNS APIs to post the generated story and visual material package to online platforms. Posting is scheduled at a designated time to ensure it reaches supporters and potential foster parents.

[0157] Step 8:

[0158] Users access the dashboard via their devices to view the latest health data and posts about the animals they are supporting. The sentiment engine collects user reactions to the content and uses them to generate future content.

[0159] This series of steps effectively combines animal health information with emotionally resonant stories, leading to increased support and engagement.

[0160] (Example 2)

[0161] 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".

[0162] Conventional animal health monitoring systems typically only analyze biometric data and provide information based on that data, failing to adequately appeal to the emotions of supporters and potential foster parents. Furthermore, providing interactive content that responds to users' emotions is difficult, making it challenging to increase supporter engagement.

[0163] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0164] In this invention, the server includes means for collecting animal biological parameters from a health monitoring device, means for integrating and analyzing the biological parameters and animal rearing information, means for evaluating the animal's health using an artificial intelligence algorithm, and means for generating a story that represents the animal's condition based on the analysis results, utilizing a generative artificial intelligence model. This makes it possible to analyze the user's emotional response in real time and adjust the content of the generated story.

[0165] A "health monitoring device" is a device used to acquire biological parameters such as heart rate, body temperature, and activity level of animals in real time.

[0166] "Biometric parameters" refer to measurable data such as heart rate, body temperature, and activity level that are necessary to understand an animal's health status.

[0167] "Animal care information" refers to information about the animal's living conditions, including records of its diet, environment, and behavior.

[0168] An "artificial intelligence algorithm" is a computational method for evaluating the health status of animals by integrating and analyzing collected biological parameters and breeding information.

[0169] A "generative artificial intelligence model" is a computational model used to generate narratives that describe the state of an animal based on analysis results.

[0170] The "emotion analysis function" is a feature that evaluates the user's emotional response in real time and adjusts the content provided according to the user's emotions.

[0171] An "online network" is a digital platform for transmitting and sharing generated stories and related information.

[0172] This invention is a system that enables highly personalized animal health monitoring and information provision. The system operates primarily through the involvement of a server, terminals, and users.

[0173] The server collects biological parameters such as heart rate, body temperature, and activity level in real time from health monitoring devices attached to the animals. This data is stored along with breeding information and comprehensively analyzed using artificial intelligence algorithms. The animal's health status is evaluated based on the analysis results, and a narrative representing the animal's condition is generated using a generative AI model.

[0174] The device is equipped with an emotion analysis function that evaluates the user's emotional response in real time. The device records the user's reaction when viewing content and sends this data to a server. The server uses the received emotion data to adjust the story content according to the user's emotions.

[0175] Users can receive and view the generated stories and associated image information through an online network. This allows information about the animals' health to be presented in an emotionally engaging way, increasing supporter engagement.

[0176] As a concrete example, the following is an example of a prompt based on animal biometric data. By entering "Create an inspiring story based on the animal's health data," the system generates a story based on the user's interests and emotions. In this way, the system provides high emotional value to the user while assisting with animal health management.

[0177] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0178] Step 1:

[0179] The server collects biological parameters such as heart rate, body temperature, and activity level in real time from health monitoring devices attached to animals. The input is the biological parameters from the health monitoring devices, and the output is the parameters stored in the database. By storing this data in the database, the server accumulates fundamental information about the animals' health status.

[0180] Step 2:

[0181] The server integrates and analyzes the collected biological parameters and breeding information. The inputs are the biological parameters obtained in the previous step and manually entered breeding information, and the output is the health assessment result. The server uses an artificial intelligence algorithm to analyze the data and assess the health status of the animals.

[0182] Step 3:

[0183] The device evaluates the user's emotional response in real time using sentiment analysis. The input is user reaction data while viewing content, and the output is the user's sentiment evaluation result. The device utilizes sentiment analysis to collect user feedback and transmits that data to the server.

[0184] Step 4:

[0185] The server uses a generative artificial intelligence model to generate a story that represents the animal's condition, based on the analysis results and emotion evaluation results. The input is the animal's health evaluation results and the user's emotion evaluation results, and the output is the generated story. The server provides the generative AI model with the prompt "Create an emotionally moving story based on the animal's health data" and creates the story.

[0186] Step 5:

[0187] The server customizes the generated story to suit the user's emotions and provides it to the online network along with relevant image information. The input is the story before customization and associated biometric data-based image information, while the output is the customized story published on the online network. The server provides the story in a user-accessible format and conveys animal information.

[0188] Step 6:

[0189] Users view stories generated via an online network using their devices and provide feedback. The input is the story on the online network, and the output is feedback data. Users provide feedback to the system through their impressions and emotional reactions to the story, which helps in generating future stories.

[0190] (Application Example 2)

[0191] 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."

[0192] In animal protection activities, it is crucial to effectively communicate the health status and daily lives of animals to supporters and potential adopters. However, traditional methods provide general information that does not adequately address the interests and feelings of individual supporters. This makes it difficult to increase motivation to support and promote continued engagement. There is a need for methods that allow supporters to feel a stronger connection with the animals.

[0193] 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.

[0194] In this invention, the server includes means for collecting animal biometric data, means for recognizing and adjusting the user's emotions using an emotion engine, and means for generating and providing customized stories. This makes it possible to provide personalized stories that respond to the emotions of individual supporters, thereby increasing their engagement in support activities.

[0195] A "health monitoring device" is a device used to acquire biological data such as heart rate, body temperature, and activity level of animals in real time.

[0196] "Biometric data" refers to data that indicates an animal's physiological state, such as its heart rate, body temperature, and activity level.

[0197] "Animal care information" refers to information about the animal's living environment, including its diet, exercise, sleep, and health history.

[0198] "Analysis means" refers to methods for integrating and analyzing biological data and breeding information to evaluate the health status of animals.

[0199] A "narrative generation method" is a means of generating a narrative about an animal's situation based on the analysis results.

[0200] An "online platform" is an internet-based environment for providing generated stories and related information in digital format.

[0201] An "emotion engine" is an engine that recognizes the user's emotions and adjusts information such as stories based on those emotions.

[0202] A "user terminal" is an electronic device used by a user to view information or provide feedback.

[0203] "Customization" refers to adjusting and personalizing the content and format of information according to the user's feelings and preferences.

[0204] The system implementing this invention aims to monitor the health status of animals in real time and provide data to the user, who is the caregiver, as a personalized narrative. The configuration and operation of this system are described below.

[0205] The server receives biometric data from health monitoring devices attached to the animals. This data includes heart rate, body temperature, and activity level. Furthermore, this biometric data is integrated with breeding information and stored in a database. On the server, AI algorithms are used to analyze this data and assess the animal's health status. Based on the results of this analysis, the server generates a narrative about the animal's situation.

[0206] The user's device incorporates an emotion engine that recognizes the user's emotions in real time. It collects the user's reactions and feedback as they view stories and adjusts subsequent story generation based on this data. This process customizes the generated stories to match the user's emotions, allowing the user to feel a deeper connection with the animal they are supporting.

[0207] As a concrete example, consider a scenario where a supporter user receives information about the animal they are supporting. The server generates a story based on data showing "how the animal spent the day." The emotion engine recognizes that the user prefers stories that evoke a sense of "happiness" and provides a corresponding story. For example, a story such as "Today the animal was having fun playing with a new toy" might be delivered through the application on the user's device, along with related photos and videos.

[0208] An example of a prompt to input into the generation AI model is: "User's preferred story type: Active activity, Animal data: {Heart rate: 90, Activity level: High}, User's emotion score: Positive, Theme of the story to generate: Fun playtime." This is expected to deliver the generated story in a way that appeals to the supporter's emotions, thereby encouraging continued support activities.

[0209] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0210] Step 1:

[0211] The server receives real-time biometric data from health monitoring devices attached to animals. Input data such as heart rate, body temperature, and activity level are obtained and temporarily stored. The server then formats this data and prepares it for storage in the database.

[0212] Step 2:

[0213] The server integrates biometric data and breeding information, performing integrated analysis with existing information stored in the database. The input is biometric data and breeding information, and the output is analysis results for evaluating the animals' health status. The server uses AI algorithms to perform tasks such as detecting anomalies and analyzing health trends.

[0214] Step 3:

[0215] The server generates a narrative that describes the animal's situation based on the analysis results. The input is the analysis results, and the output is the generated narrative. The server uses a generative AI model to construct narrative content that concretely describes the animal's activities and health status.

[0216] Step 4:

[0217] The device recognizes the user's emotions in real time. It uses data based on the user's facial expressions, behavior, and past feedback as input. An emotion engine analyzes this data and outputs the user's current emotional state.

[0218] Step 5:

[0219] The server customizes the generated story based on the user's emotional state. The input is the user's emotional state and the generated story, and the output is the story adjusted to suit the user. The server reflects the emotion analysis results to optimize the tone and expression of the content for each user.

[0220] Step 6:

[0221] The device provides users with customized stories. The input is the customized story, and the output is story content delivered along with visual information. The device enables story playback and feedback collection through its user interface.

[0222] 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.

[0223] 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.

[0224] 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.

[0225] [Second Embodiment]

[0226] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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).

[0232] 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.

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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".

[0238] This embodiment of the invention describes a specific example of a system that streamlines the health management and information provision of protected animals. The system consists of a health monitoring device, a data analysis server, a user terminal, and an online platform.

[0239] Overall system configuration

[0240] Health monitoring devices attached to animals acquire biometric data such as heart rate, body temperature, and activity level in real time. This data is transmitted to a server via wireless communication.

[0241] Data collection and analysis

[0242] The server records biological data received from monitoring devices into a database. It also records observation information about the animals entered by animal care staff using terminals. The server integrates this data and performs analysis using AI algorithms. The health status assessment obtained through this analysis is used to generate stories about the animals.

[0243] Story generation and publication

[0244] The server generates emotionally resonant stories that reflect the animal's health and behavior based on the analysis results. These stories are crucial content for conveying the animal's appeal to supporters and potential adopters. The generated stories, along with relevant visual information, are posted to an online platform.

[0245] Providing information to supporters

[0246] Users can access a dashboard through a dedicated application or website. This dashboard displays the latest health data, stories, and results of the support given to the animals. This allows users to see specifically how their support is making a difference.

[0247] Specific example

[0248] For example, in the case of a cat that a user is supporting, a monitoring device detects an increase in heart rate while the cat is sleeping, and the server receives data indicating an increase in active time. The server then analyzes this data and generates a story such as, "Today the cat played with its favorite toy for longer than usual!", selects a photo of the cat playing as visual information, and posts it on social media. Through this process, supporters can understand that their support is contributing to improving the cat's life.

[0249] In this way, the system integrates everything from animal health management to information dissemination, creating a mechanism that promotes support activities.

[0250] The following describes the processing flow.

[0251] Step 1:

[0252] The server automatically collects animal biometric data from the health monitoring device. This process is carried out by wirelessly transmitting the data obtained by the device in real time to the server. The biometric data includes information on heart rate, body temperature, and activity level.

[0253] Step 2:

[0254] The terminal provides an interface that allows zookeepers to input information about the animals' daily behavior and any abnormalities they observe. The information entered via the terminal is sent to a server and integrated with other data.

[0255] Step 3:

[0256] The server integrates the collected biometric data and breeding information and begins analysis using an AI algorithm. This analysis evaluates whether the data is within the normal range and quantifies the health status. If abnormal results are found, an alert is generated.

[0257] Step 4:

[0258] The server uses an AI generation program to create a story that reflects the animal's current condition based on the analysis results. The generated story is designed to include the animal's health status and any notable events that occurred on that day.

[0259] Step 5:

[0260] The server selects visual information related to the generated story and combines it to create an information package. This package is then prepared for posting to a social networking platform.

[0261] Step 6:

[0262] The server specifies the posting time and target social media platform, and posts the story and visual information package to the selected platform via an API. This ensures that the information is widely disseminated and reaches supporters and potential foster parents.

[0263] Step 7:

[0264] Users can access the dashboard using their own devices to view the latest health status of the animals they are supporting, posted stories, and the impact of their support activities. The dashboard reflects information from the server in real time.

[0265] (Example 1)

[0266] 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."

[0267] There is a need for a system that contributes to animal welfare by effectively monitoring the health status of animals and providing relevant information to supporters. This system needs to collect and analyze accurate data in real time and disseminate the information in an easy-to-understand and engaging format. However, conventional methods have problems with efficient information integration and sharing, preventing supporters from fully understanding the effectiveness of their support.

[0268] 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.

[0269] In this invention, the server includes means for receiving biological information of an animal from a health monitoring device, means for integrating and processing the biological information and animal management information, and means for generating a narrative that represents the animal's condition based on the processing results. This makes it possible to comprehensively monitor the animal's health status and provide caregivers with easily understandable, visually represented information.

[0270] A "health monitoring device" is a device used to acquire biological information about animals in real time.

[0271] "Biometric information" refers to data that indicates an animal's health status, such as heart rate, body temperature, and activity level.

[0272] "Management information" refers to data that includes observation records and behavioral history related to the care of animals.

[0273] A "communication network" refers to the entire infrastructure used for sending and receiving digital data.

[0274] "Processing" refers to the process of integrating and analyzing received biometric and management information.

[0275] A "generation method" is a mechanism for creating specific content or a story based on input data.

[0276] "Image information" refers to image data used to complement and visually represent a generated narrative.

[0277] A "supporter" is an individual or organization that provides support for the health management and welfare improvement of animals.

[0278] One embodiment of this invention involves a process for providing important information to caregivers and effectively managing the health status of animals through an animal health management system. This system primarily utilizes health monitoring devices, servers, user terminals, and a communication network.

[0279] The server receives biological information from the animals via health monitoring devices. Specifically, this includes information such as heart rate, body temperature, and activity level. The received biological information is recorded in a database on the server and further integrated with management information entered by animal care staff from user terminals.

[0280] For these integrated data, the server performs analysis using AI algorithms. This AI algorithm, known as a generative AI model, has the ability to generate creative stories based on the analysis results. The server inputs a prompt sentence into this model to generate a story that reflects the health status and behavior of the animal.

[0281] The generated story is integrated with the image information and sent by the server to an online platform through a communication network. As a result, users can view the latest health information and stories of the animals they are supporting via a dedicated application or website.

[0282] As a specific example, when the monitoring device detects a change in the heart rate of a cat, the server analyzes this data, generates a story such as "Today, it played with its favorite toy longer than usual!", and provides information to the supporters by posting it on an online platform such as SNS.

[0283] An example of a prompt sentence is "Please generate a story that reflects the changes in heart rate and active time based on the cat's health monitoring data. Use a photo of the cat playing as visual information."

[0284] In this form, it becomes possible to convey the health status of the animal in detail and appealingly, and supporters can carry out support activities more effectively.

[0285] The flow of the specific process in Example 1 will be described using FIG. 11.

[0286] Step 1:

[0287] The server receives the biological information of the animal from the health monitoring device. Specifically, it collects data such as heart rate, body temperature, and amount of exercise. This data is sent to the server via wireless communication. The input is the biological information from the health monitoring device, and the output is the structured data recorded in the database within the server.

[0288] Step 2:

[0289] The terminal is used by animal care staff to input observation information about the animals. This observation information includes diet, behavior, and any notable changes in health. The input is management information from the animal care staff, and the output is that this information is integrated and stored in the server's database.

[0290] Step 3:

[0291] The server integrates biometric and management information, retrieves it from a database, and performs analysis using AI algorithms. This analysis evaluates the animal's health status, detects abnormalities, and helps understand behavioral patterns. The input is integrated biometric and management information, and the output is the health status and behavioral evaluation as a result of the analysis.

[0292] Step 4:

[0293] The server utilizes a generative AI model to generate a story based on the analysis results. It inputs prompt sentences into the generative AI model to generate an emotionally rich story. The input consists of the analysis results and prompt sentences, and the output is the generated story.

[0294] Step 5:

[0295] The server selects image information related to the generated story, integrates it, and provides it to an online platform on the communication network. The input is the story and image information, and the output is the online post as visually enhanced content.

[0296] Step 6:

[0297] Users access a dedicated application or website to view the health status and generated stories of the animals they are supporting. This allows users to stay informed about the latest information and the impact of their support. The input is the content published on the platform, and the output is the user's informational experience as their perception and understanding.

[0298] (Application Example 1)

[0299] 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."

[0300] In modern times, understanding and participating in support activities for rescued animals is important, but there is a challenge in that it is difficult for supporters to easily grasp the health status of animals and the specific impact of support activities. In addition, there is a problem that support activities are not sufficiently promoted because there are insufficient means to effectively share the situation of animals with other supporters and prospective adopters and deepen interactions.

[0301] 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.

[0302] In this invention, the server includes means for collecting animal physiological data, means for integrating and analyzing the physiological data and animal management information, and means for generating a narrative of the animal's condition based on the analysis results. This allows caregivers to understand the animal's health status and activities in narrative form, and also enables them to share the generated information with other users and deepen their interactions.

[0303] A "biological monitoring device" is a device that acquires real-time physiological data such as the heart rate, body temperature, and activity level of animals.

[0304] "Physiological data" refers to data that indicates the health status and activity level of an animal, such as heart rate, body temperature, and exercise level.

[0305] "Management information" refers to information related to the breeding and living habits of animals, including observational information provided by breeders.

[0306] "Analysis means" is a processing means for integrating the collected physiological data and management information and evaluating the health status of animals using an AI algorithm.

[0307] "Story generation means" is a processing means for generating a story that richly expresses the health status and behavior of animals based on the analysis results.

[0308] "Dashboard" is a screen that provides the generated stories and related visual information in a form that can be browsed by users.

[0309] "Communication network" is a network for transmitting and receiving information via the Internet.

[0310] The system for realizing this invention is composed of a biological monitoring device that collects the biological data of animals, a server that analyzes the data and generates and provides stories, and a terminal for users to browse and share stories.

[0311] First, the biological monitoring device collects physiological data such as the heart rate, body temperature, and amount of exercise of animals in real time. This device has a communication device and wirelessly transmits the collected data to the server.

[0312] Next, the server stores the received physiological data in a database. The server further analyzes the data using an AI algorithm (e.g., TensorFlow) based on the collected data and evaluates the health status of the animals. Based on this evaluation, a richly emotional story is generated using a generation AI model. The server visualizes the generated story in a dashboard format so that users can access it remotely.

[0313] Users with a device can access a dashboard via the internet. This dashboard displays the latest health data and generated stories of the animals. Users can share stories with other supporters and potential foster families and exchange information. They can also easily post stories to their own social networks using the social networking features.

[0314] For example, if a user's dog's heart rate data shows an increase in activity level, the server will use this data to generate a story such as, "Today the dog ran around the park full of energy!" A possible prompt for the generating AI model might be, "Based on recent heart rate and activity data, please create a story that reflects a lively day."

[0315] In this way, this system will enable the smooth progress of animal health management and support activities.

[0316] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0317] Step 1:

[0318] The bio-monitoring device collects physiological data such as heart rate, body temperature, and activity level of animals in real time. It receives various physiological data from animals as input and transmits it wirelessly to a server. The output is the transmission of data to the server.

[0319] Step 2:

[0320] The server stores physiological data received wirelessly in a database. It accumulates data by receiving physiological data from a biological monitoring device as input and storing it in the database. The output is the physiological data stored in the database.

[0321] Step 3:

[0322] The server retrieves physiological data stored in the database and analyzes it using an AI algorithm. This analysis uses the extracted physiological data as input to evaluate the animal's health status. The output is the health status evaluation result obtained from the analysis.

[0323] Step 4:

[0324] The server generates a story using a generative AI model based on the analysis. The prompt for the AI ​​model is something like, "Generate a story reflecting a day in the life of an animal, based on the health assessment results." The output is the generated story.

[0325] Step 5:

[0326] The server visualizes the generated stories in a dashboard format and provides them to the user via the terminal. This process takes the generated stories as input and outputs structured display data for display on the user's terminal.

[0327] Step 6:

[0328] Users access the dashboard using their devices and view the generated stories. Input is dashboard data provided by the server, and output is the user's visually perceived screen display. Users also perform actions necessary to share the stories on social networks.

[0329] Step 7:

[0330] Users share stories with other supporters using social networking features via their devices and exchange information with them. The input is the data of the story they want to share, and the output is a social networking post that generates interaction with other users.

[0331] This processing flow allows users to effectively acquire and share stories based on animal physiological data.

[0332] 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.

[0333] In this embodiment of the invention, a system is provided that takes into account not only the health management and information provision of rescued animals, but also the emotions of the user. The system consists of a health monitoring device, a data analysis server, a user terminal, an emotion engine, and an online platform.

[0334] Overall system configuration

[0335] Animals are fitted with health monitoring devices that capture real-time biometric data such as heart rate, body temperature, and activity level. This data is transmitted to a server and stored in a database along with care information entered by animal care staff via terminals. The server uses AI algorithms to integrate and analyze this data to evaluate the animals' health status.

[0336] Embedding an emotion engine

[0337] The emotion engine is used to recognize user emotions and adjust the content of generated stories and materials. By analyzing user feedback and reactions in real time, the emotion engine enables the delivery of information tailored to individual users.

[0338] Story generation and customization

[0339] The server generates a story about the animal's situation based on analysis results and feedback from the emotion engine. The generated story is customized to suit the user's emotions and posted to an online platform along with relevant visual information. This allows supporters and potential adopters to access information about the animals in a more emotionally resonant way.

[0340] Providing information to supporters and utilizing their feedback

[0341] Users use their devices to check the latest health data and content for the animals they support via a dashboard. During this process, the emotion engine records the user's reactions and uses this information to suggest future content. For example, if a user shows a positive reaction to a particular type of story, this information will be reflected in the next story generation.

[0342] Specific example

[0343] A Facebook post about a dog named Coco, which a user supports, is based on data collected by a monitoring device, specifically "Increased walking time today." The emotion engine detects from past data that the user tends to prefer stories about "Increased Activity" and feeds this information back to the server. Based on the analysis, the server generates a story such as "Coco had a great time running around her favorite park!" and posts it along with a photo of Coco during her walk. This post is customized based on the emotion engine's analysis and is expected to strongly attract the user's interest.

[0344] In this way, the introduction of an emotion engine allows the system to personalize animal health management and information dissemination, promoting more effective support activities.

[0345] The following describes the processing flow.

[0346] Step 1:

[0347] The server collects animal biometric data in real time from health monitoring devices. The devices measure the animal's heart rate, body temperature, and activity level, and transmit this data to the server wirelessly, recording it in a database.

[0348] Step 2:

[0349] The terminal provides an interface for zookeepers to input information about the animals' behavior and health as observed. The zookeepers input this observation information into the terminal and send it to the server.

[0350] Step 3:

[0351] The server integrates and analyzes the collected biometric data and breeding information. Using AI algorithms, it assesses the animals' health status and generates a numerical score. If an abnormal pattern is detected, it triggers an alert.

[0352] Step 4:

[0353] The emotion engine analyzes the user's past feedback and emotional responses to evaluate their preferences and interests. Based on this evaluation, the server adjusts the process to generate a story that is best suited to the user.

[0354] Step 5:

[0355] Based on the analysis results and feedback from the emotion engine, the server generates a story to convey the animal's situation. The story includes the animal's health condition and notable events of the day, and is expressed with rich emotion.

[0356] Step 6:

[0357] The server selects visual materials (photos and videos) related to the story and creates a package that integrates them to match the story's content. The package is optimized to resonate with the user's emotions.

[0358] Step 7:

[0359] The server uses SNS APIs to post the generated story and visual material package to online platforms. Posting is scheduled at a designated time to ensure it reaches supporters and potential foster parents.

[0360] Step 8:

[0361] Users access the dashboard via their devices to view the latest health data and posts about the animals they are supporting. The sentiment engine collects user reactions to the content and uses them to generate future content.

[0362] This series of steps effectively combines animal health information with emotionally resonant stories, leading to increased support and engagement.

[0363] (Example 2)

[0364] 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".

[0365] Conventional animal health monitoring systems typically only analyze biometric data and provide information based on that data, failing to adequately appeal to the emotions of supporters and potential foster parents. Furthermore, providing interactive content that responds to users' emotions is difficult, making it challenging to increase supporter engagement.

[0366] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0367] In this invention, the server includes means for collecting animal biological parameters from a health monitoring device, means for integrating and analyzing the biological parameters and animal rearing information, means for evaluating the animal's health using an artificial intelligence algorithm, and means for generating a story that represents the animal's condition based on the analysis results, utilizing a generative artificial intelligence model. This makes it possible to analyze the user's emotional response in real time and adjust the content of the generated story.

[0368] A "health monitoring device" is a device used to acquire biological parameters such as heart rate, body temperature, and activity level of animals in real time.

[0369] "Biometric parameters" refer to measurable data such as heart rate, body temperature, and activity level that are necessary to understand an animal's health status.

[0370] "Animal care information" refers to information about the animal's living conditions, including records of its diet, environment, and behavior.

[0371] An "artificial intelligence algorithm" is a computational method for evaluating the health status of animals by integrating and analyzing collected biological parameters and breeding information.

[0372] A "generative artificial intelligence model" is a computational model used to generate narratives that describe the state of an animal based on analysis results.

[0373] The "emotion analysis function" is a feature that evaluates the user's emotional response in real time and adjusts the content provided according to the user's emotions.

[0374] An "online network" is a digital platform for transmitting and sharing generated stories and related information.

[0375] This invention is a system that enables highly personalized animal health monitoring and information provision. The system operates primarily through the involvement of a server, terminals, and users.

[0376] The server collects biological parameters such as heart rate, body temperature, and activity level in real time from health monitoring devices attached to the animals. This data is stored along with breeding information and comprehensively analyzed using artificial intelligence algorithms. The animal's health status is evaluated based on the analysis results, and a narrative representing the animal's condition is generated using a generative AI model.

[0377] The device is equipped with an emotion analysis function that evaluates the user's emotional response in real time. The device records the user's reaction when viewing content and sends this data to a server. The server uses the received emotion data to adjust the story content according to the user's emotions.

[0378] Users can receive and view the generated stories and associated image information through an online network. This allows information about the animals' health to be presented in an emotionally engaging way, increasing supporter engagement.

[0379] As a concrete example, the following is an example of a prompt based on animal biometric data. By entering "Create an inspiring story based on the animal's health data," the system generates a story based on the user's interests and emotions. In this way, the system provides high emotional value to the user while assisting with animal health management.

[0380] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0381] Step 1:

[0382] The server collects biological parameters such as heart rate, body temperature, and activity level in real time from health monitoring devices attached to animals. The input is the biological parameters from the health monitoring devices, and the output is the parameters stored in the database. By storing this data in the database, the server accumulates fundamental information about the animals' health status.

[0383] Step 2:

[0384] The server integrates and analyzes the collected biological parameters and breeding information. The inputs are the biological parameters obtained in the previous step and manually entered breeding information, and the output is the health assessment result. The server uses an artificial intelligence algorithm to analyze the data and assess the health status of the animals.

[0385] Step 3:

[0386] The device evaluates the user's emotional response in real time using sentiment analysis. The input is user reaction data while viewing content, and the output is the user's sentiment evaluation result. The device utilizes sentiment analysis to collect user feedback and transmits that data to the server.

[0387] Step 4:

[0388] The server uses a generative artificial intelligence model to generate a story that represents the animal's condition, based on the analysis results and emotion evaluation results. The input is the animal's health evaluation results and the user's emotion evaluation results, and the output is the generated story. The server provides the generative AI model with the prompt "Create an emotionally moving story based on the animal's health data" and creates the story.

[0389] Step 5:

[0390] The server customizes the generated story to suit the user's emotions and provides it to the online network along with relevant image information. The input is the story before customization and associated biometric data-based image information, while the output is the customized story published on the online network. The server provides the story in a user-accessible format and conveys animal information.

[0391] Step 6:

[0392] Users view stories generated via an online network using their devices and provide feedback. The input is the story on the online network, and the output is feedback data. Users provide feedback to the system through their impressions and emotional reactions to the story, which helps in generating future stories.

[0393] (Application Example 2)

[0394] 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 will be referred to as the "terminal."

[0395] In animal protection activities, it is crucial to effectively communicate the health status and daily lives of animals to supporters and potential adopters. However, traditional methods provide general information that does not adequately address the interests and feelings of individual supporters. This makes it difficult to increase motivation to support and promote continued engagement. There is a need for methods that allow supporters to feel a stronger connection with the animals.

[0396] 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.

[0397] In this invention, the server includes means for collecting animal biometric data, means for recognizing and adjusting the user's emotions using an emotion engine, and means for generating and providing customized stories. This makes it possible to provide personalized stories that respond to the emotions of individual supporters, thereby increasing their engagement in support activities.

[0398] A "health monitoring device" is a device used to acquire biological data such as heart rate, body temperature, and activity level of animals in real time.

[0399] "Biometric data" refers to data that indicates an animal's physiological state, such as its heart rate, body temperature, and activity level.

[0400] "Animal care information" refers to information about the animal's living environment, including its diet, exercise, sleep, and health history.

[0401] "Analysis means" refers to methods for integrating and analyzing biological data and breeding information to evaluate the health status of animals.

[0402] A "narrative generation method" is a means of generating a narrative about an animal's situation based on the analysis results.

[0403] An "online platform" is an internet-based environment for providing generated stories and related information in digital format.

[0404] An "emotion engine" is an engine that recognizes the user's emotions and adjusts information such as stories based on those emotions.

[0405] A "user terminal" is an electronic device used by a user to view information or provide feedback.

[0406] "Customization" refers to adjusting and personalizing the content and format of information according to the user's feelings and preferences.

[0407] The system implementing this invention aims to monitor the health status of animals in real time and provide data to the user, who is the caregiver, as a personalized narrative. The configuration and operation of this system are described below.

[0408] The server receives biometric data from health monitoring devices attached to the animals. This data includes heart rate, body temperature, and activity level. Furthermore, this biometric data is integrated with breeding information and stored in a database. On the server, AI algorithms are used to analyze this data and assess the animal's health status. Based on the results of this analysis, the server generates a narrative about the animal's situation.

[0409] The user's device incorporates an emotion engine that recognizes the user's emotions in real time. It collects the user's reactions and feedback as they view stories and adjusts subsequent story generation based on this data. This process customizes the generated stories to match the user's emotions, allowing the user to feel a deeper connection with the animal they are supporting.

[0410] As a concrete example, consider a scenario where a supporter user receives information about the animal they are supporting. The server generates a story based on data showing "how the animal spent the day." The emotion engine recognizes that the user prefers stories that evoke a sense of "happiness" and provides a corresponding story. For example, a story such as "Today the animal was having fun playing with a new toy" might be delivered through the application on the user's device, along with related photos and videos.

[0411] An example of a prompt to input into the generation AI model is: "User's preferred story type: Active activity, Animal data: {Heart rate: 90, Activity level: High}, User's emotion score: Positive, Theme of the story to generate: Fun playtime." This is expected to deliver the generated story in a way that appeals to the supporter's emotions, thereby encouraging continued support activities.

[0412] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0413] Step 1:

[0414] The server receives real-time biometric data from health monitoring devices attached to animals. Input data such as heart rate, body temperature, and activity level are obtained and temporarily stored. The server then formats this data and prepares it for storage in the database.

[0415] Step 2:

[0416] The server integrates biometric data and breeding information, performing integrated analysis with existing information stored in the database. The input is biometric data and breeding information, and the output is analysis results for evaluating the animals' health status. The server uses AI algorithms to perform tasks such as detecting anomalies and analyzing health trends.

[0417] Step 3:

[0418] The server generates a narrative that describes the animal's situation based on the analysis results. The input is the analysis results, and the output is the generated narrative. The server uses a generative AI model to construct narrative content that concretely describes the animal's activities and health status.

[0419] Step 4:

[0420] The device recognizes the user's emotions in real time. It uses data based on the user's facial expressions, behavior, and past feedback as input. An emotion engine analyzes this data and outputs the user's current emotional state.

[0421] Step 5:

[0422] The server customizes the generated story based on the user's emotional state. The input is the user's emotional state and the generated story, and the output is the story adjusted to suit the user. The server reflects the emotion analysis results to optimize the tone and expression of the content for each user.

[0423] Step 6:

[0424] The device provides users with customized stories. The input is the customized story, and the output is story content delivered along with visual information. The device enables story playback and feedback collection through its user interface.

[0425] 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.

[0426] 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.

[0427] 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.

[0428] [Third Embodiment]

[0429] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0430] 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.

[0431] 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).

[0432] 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.

[0433] 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.

[0434] 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).

[0435] 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.

[0436] 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.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] 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".

[0441] This embodiment of the invention describes a specific example of a system that streamlines the health management and information provision of protected animals. The system consists of a health monitoring device, a data analysis server, a user terminal, and an online platform.

[0442] Overall system configuration

[0443] Health monitoring devices attached to animals acquire biometric data such as heart rate, body temperature, and activity level in real time. This data is transmitted to a server via wireless communication.

[0444] Data collection and analysis

[0445] The server records biological data received from monitoring devices into a database. It also records observation information about the animals entered by animal care staff using terminals. The server integrates this data and performs analysis using AI algorithms. The health status assessment obtained through this analysis is used to generate stories about the animals.

[0446] Story generation and publication

[0447] The server generates emotionally resonant stories that reflect the animal's health and behavior based on the analysis results. These stories are crucial content for conveying the animal's appeal to supporters and potential adopters. The generated stories, along with relevant visual information, are posted to an online platform.

[0448] Providing information to supporters

[0449] Users can access a dashboard through a dedicated application or website. This dashboard displays the latest health data, stories, and results of the support given to the animals. This allows users to see specifically how their support is making a difference.

[0450] Specific example

[0451] For example, in the case of a cat that a user is supporting, a monitoring device detects an increase in heart rate while the cat is sleeping, and the server receives data indicating an increase in active time. The server then analyzes this data and generates a story such as, "Today the cat played with its favorite toy for longer than usual!", selects a photo of the cat playing as visual information, and posts it on social media. Through this process, supporters can understand that their support is contributing to improving the cat's life.

[0452] In this way, the system integrates everything from animal health management to information dissemination, creating a mechanism that promotes support activities.

[0453] The following describes the processing flow.

[0454] Step 1:

[0455] The server automatically collects animal biometric data from the health monitoring device. This process is carried out by wirelessly transmitting the data obtained by the device in real time to the server. The biometric data includes information on heart rate, body temperature, and activity level.

[0456] Step 2:

[0457] The terminal provides an interface that allows zookeepers to input information about the animals' daily behavior and any abnormalities they observe. The information entered via the terminal is sent to a server and integrated with other data.

[0458] Step 3:

[0459] The server integrates the collected biometric data and breeding information and begins analysis using an AI algorithm. This analysis evaluates whether the data is within the normal range and quantifies the health status. If abnormal results are found, an alert is generated.

[0460] Step 4:

[0461] The server uses an AI generation program to create a story that reflects the animal's current condition based on the analysis results. The generated story is designed to include the animal's health status and any notable events that occurred on that day.

[0462] Step 5:

[0463] The server selects visual information related to the generated story and combines it to create an information package. This package is then prepared for posting to a social networking platform.

[0464] Step 6:

[0465] The server specifies the posting time and target social media platform, and posts the story and visual information package to the selected platform via an API. This ensures that the information is widely disseminated and reaches supporters and potential foster parents.

[0466] Step 7:

[0467] Users can access the dashboard using their own devices to view the latest health status of the animals they are supporting, posted stories, and the impact of their support activities. The dashboard reflects information from the server in real time.

[0468] (Example 1)

[0469] 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."

[0470] There is a need for a system that contributes to animal welfare by effectively monitoring the health status of animals and providing relevant information to supporters. This system needs to collect and analyze accurate data in real time and disseminate the information in an easy-to-understand and engaging format. However, conventional methods have problems with efficient information integration and sharing, preventing supporters from fully understanding the effectiveness of their support.

[0471] 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.

[0472] In this invention, the server includes means for receiving biological information of an animal from a health monitoring device, means for integrating and processing the biological information and animal management information, and means for generating a narrative that represents the animal's condition based on the processing results. This makes it possible to comprehensively monitor the animal's health status and provide caregivers with easily understandable, visually represented information.

[0473] A "health monitoring device" is a device used to acquire biological information about animals in real time.

[0474] "Biometric information" refers to data that indicates an animal's health status, such as heart rate, body temperature, and activity level.

[0475] "Management information" refers to data that includes observation records and behavioral history related to the care of animals.

[0476] A "communication network" refers to the entire infrastructure used for sending and receiving digital data.

[0477] "Processing" refers to the process of integrating and analyzing received biometric and management information.

[0478] A "generation method" is a mechanism for creating specific content or a story based on input data.

[0479] "Image information" refers to image data used to complement and visually represent a generated narrative.

[0480] A "supporter" is an individual or organization that provides support for the health management and welfare improvement of animals.

[0481] One embodiment of this invention involves a process for providing important information to caregivers and effectively managing the health status of animals through an animal health management system. This system primarily utilizes health monitoring devices, servers, user terminals, and a communication network.

[0482] The server receives biological information from the animals via health monitoring devices. Specifically, this includes information such as heart rate, body temperature, and activity level. The received biological information is recorded in a database on the server and further integrated with management information entered by animal care staff from user terminals.

[0483] The server uses an AI algorithm to analyze this integrated data. This AI algorithm, known as a generative AI model, has the ability to generate creative stories based on the analysis results. By inputting prompts into this model, the server generates stories that reflect the health status and behavior of animals.

[0484] The generated stories are integrated with image information and transmitted by the server to an online platform via a communication network. This allows users to view the latest health information and stories of the animals they are supporting through a dedicated application or website.

[0485] For example, if a monitoring device detects a change in the cat's heart rate, the server analyzes this data, generates a story such as, "Today, the cat played with its favorite toy for longer than usual!", and provides information to supporters by posting it on online platforms such as social media.

[0486] An example of a prompt message is: "Generate a story that reflects changes in the cat's heart rate and active time, based on the cat's health monitoring data. Use photos of the cat playing as visual information."

[0487] This format allows for detailed and engaging communication about the animals' health status, enabling supporters to conduct their aid activities more effectively.

[0488] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0489] Step 1:

[0490] The server receives biological information from the animal's health monitoring device. Specifically, it collects data such as heart rate, body temperature, and activity level. This data is transmitted to the server wirelessly. The input is biological information from the health monitoring device, and the output is structured data recorded in the server's database.

[0491] Step 2:

[0492] The terminal is used by animal care staff to input observation information about the animals. This observation information includes diet, behavior, and any notable changes in health. The input is management information from the animal care staff, and the output is that this information is integrated and stored in the server's database.

[0493] Step 3:

[0494] The server integrates biometric and management information, retrieves it from a database, and performs analysis using AI algorithms. This analysis evaluates the animal's health status, detects abnormalities, and helps understand behavioral patterns. The input is integrated biometric and management information, and the output is the health status and behavioral evaluation as a result of the analysis.

[0495] Step 4:

[0496] The server utilizes a generative AI model to generate a story based on the analysis results. It inputs prompt sentences into the generative AI model to generate an emotionally rich story. The input consists of the analysis results and prompt sentences, and the output is the generated story.

[0497] Step 5:

[0498] The server selects image information related to the generated story, integrates it, and provides it to an online platform on the communication network. The input is the story and image information, and the output is the online post as visually enhanced content.

[0499] Step 6:

[0500] Users access a dedicated application or website to view the health status and generated stories of the animals they are supporting. This allows users to stay informed about the latest information and the impact of their support. The input is the content published on the platform, and the output is the user's informational experience as their perception and understanding.

[0501] (Application Example 1)

[0502] 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."

[0503] In modern times, understanding and participating in support activities for rescued animals is important, but there is a challenge in that it is difficult for supporters to easily grasp the health status of animals and the specific impact of support activities. In addition, there is a problem that support activities are not sufficiently promoted because there are insufficient means to effectively share the situation of animals with other supporters and prospective adopters and deepen interactions.

[0504] 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.

[0505] In this invention, the server includes means for collecting animal physiological data, means for integrating and analyzing the physiological data and animal management information, and means for generating a narrative of the animal's condition based on the analysis results. This allows caregivers to understand the animal's health status and activities in narrative form, and also enables them to share the generated information with other users and deepen their interactions.

[0506] A "biological monitoring device" is a device that acquires real-time physiological data such as the heart rate, body temperature, and activity level of animals.

[0507] "Physiological data" refers to data that indicates the health status and activity level of an animal, such as heart rate, body temperature, and exercise level.

[0508] "Management information" refers to information regarding the care and lifestyle of animals, including observational information provided by the caretaker.

[0509] "Analysis means" refers to processing means for integrating collected physiological data and management information and evaluating the health status of animals using AI algorithms.

[0510] A "narrative generation method" is a processing method for generating a narrative that expresses the health status and behavior of an animal in an emotionally rich manner, based on the analysis results.

[0511] A "dashboard" is a screen that provides users with a viewable format of the generated story and related visual information.

[0512] A "communication network" is a network used to send and receive information via the internet.

[0513] The system for realizing this invention consists of a bio-monitoring device that collects biological data from animals, a server that analyzes the data and generates and provides stories, and terminals for users to view and share stories.

[0514] First, a bio-monitoring device collects physiological data such as the animal's heart rate, body temperature, and activity level in real time. This device is equipped with a communication device and transmits the collected data wirelessly to a server.

[0515] Next, the server stores the received physiological data in a database. The server then analyzes the collected data using an AI algorithm (e.g., TensorFlow) to assess the animal's health. Based on this assessment, it generates an emotionally resonant story using a generative AI model. The server visualizes this generated story in a dashboard format, making it accessible to users remotely.

[0516] Users with a device can access a dashboard via the internet. This dashboard displays the latest health data and generated stories of the animals. Users can share stories with other supporters and potential foster families and exchange information. They can also easily post stories to their own social networks using the social networking features.

[0517] For example, if a user's dog's heart rate data shows an increase in activity level, the server will use this data to generate a story such as, "Today the dog ran around the park full of energy!" A possible prompt for the generating AI model might be, "Based on recent heart rate and activity data, please create a story that reflects a lively day."

[0518] In this way, this system will enable the smooth progress of animal health management and support activities.

[0519] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0520] Step 1:

[0521] The bio-monitoring device collects physiological data such as heart rate, body temperature, and activity level of animals in real time. It receives various physiological data from animals as input and transmits it wirelessly to a server. The output is the transmission of data to the server.

[0522] Step 2:

[0523] The server stores physiological data received wirelessly in a database. It accumulates data by receiving physiological data from a biological monitoring device as input and storing it in the database. The output is the physiological data stored in the database.

[0524] Step 3:

[0525] The server retrieves physiological data stored in the database and analyzes it using an AI algorithm. This analysis uses the extracted physiological data as input to evaluate the animal's health status. The output is the health status evaluation result obtained from the analysis.

[0526] Step 4:

[0527] The server generates a story using a generative AI model based on the analysis. The prompt for the AI ​​model is something like, "Generate a story reflecting a day in the life of an animal, based on the health assessment results." The output is the generated story.

[0528] Step 5:

[0529] The server visualizes the generated stories in a dashboard format and provides them to the user via the terminal. This process takes the generated stories as input and outputs structured display data for display on the user's terminal.

[0530] Step 6:

[0531] Users access the dashboard using their devices and view the generated stories. Input is dashboard data provided by the server, and output is the user's visually perceived screen display. Users also perform actions necessary to share the stories on social networks.

[0532] Step 7:

[0533] Users share stories with other supporters using social networking features via their devices and exchange information with them. The input is the data of the story they want to share, and the output is a social networking post that generates interaction with other users.

[0534] This processing flow allows users to effectively acquire and share stories based on animal physiological data.

[0535] 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.

[0536] In this embodiment of the invention, a system is provided that takes into account not only the health management and information provision of rescued animals, but also the emotions of the user. The system consists of a health monitoring device, a data analysis server, a user terminal, an emotion engine, and an online platform.

[0537] Overall system configuration

[0538] Animals are fitted with health monitoring devices that capture real-time biometric data such as heart rate, body temperature, and activity level. This data is transmitted to a server and stored in a database along with care information entered by animal care staff via terminals. The server uses AI algorithms to integrate and analyze this data to evaluate the animals' health status.

[0539] Embedding an emotion engine

[0540] The emotion engine is used to recognize user emotions and adjust the content of generated stories and materials. By analyzing user feedback and reactions in real time, the emotion engine enables the delivery of information tailored to individual users.

[0541] Story generation and customization

[0542] The server generates a story about the animal's situation based on analysis results and feedback from the emotion engine. The generated story is customized to suit the user's emotions and posted to an online platform along with relevant visual information. This allows supporters and potential adopters to access information about the animals in a more emotionally resonant way.

[0543] Providing information to supporters and utilizing their feedback

[0544] Users use their devices to check the latest health data and content for the animals they support via a dashboard. During this process, the emotion engine records the user's reactions and uses this information to suggest future content. For example, if a user shows a positive reaction to a particular type of story, this information will be reflected in the next story generation.

[0545] Specific example

[0546] A Facebook post about a dog named Coco, which a user supports, is based on data collected by a monitoring device, specifically "Increased walking time today." The emotion engine detects from past data that the user tends to prefer stories about "Increased Activity" and feeds this information back to the server. Based on the analysis, the server generates a story such as "Coco had a great time running around her favorite park!" and posts it along with a photo of Coco during her walk. This post is customized based on the emotion engine's analysis and is expected to strongly attract the user's interest.

[0547] In this way, the introduction of an emotion engine allows the system to personalize animal health management and information dissemination, promoting more effective support activities.

[0548] The following describes the processing flow.

[0549] Step 1:

[0550] The server collects animal biometric data in real time from health monitoring devices. The devices measure the animal's heart rate, body temperature, and activity level, and transmit this data to the server wirelessly, recording it in a database.

[0551] Step 2:

[0552] The terminal provides an interface for zookeepers to input information about the animals' behavior and health as observed. The zookeepers input this observation information into the terminal and send it to the server.

[0553] Step 3:

[0554] The server integrates and analyzes the collected biometric data and breeding information. Using AI algorithms, it assesses the animals' health status and generates a numerical score. If an abnormal pattern is detected, it triggers an alert.

[0555] Step 4:

[0556] The emotion engine analyzes the user's past feedback and emotional responses to evaluate their preferences and interests. Based on this evaluation, the server adjusts the process to generate a story that is best suited to the user.

[0557] Step 5:

[0558] The server generates a story to convey the animal's situation based on the analysis results and feedback from the emotion engine. The story is emotionally rich and includes the animal's health condition and notable events of the day.

[0559] Step 6:

[0560] The server selects visual materials (photos and videos) related to the story and creates a package that integrates them to match the story's content. The package is optimized to resonate with the user's emotions.

[0561] Step 7:

[0562] The server uses SNS APIs to post the generated story and visual material package to online platforms. Posting is scheduled at a designated time to ensure it reaches supporters and potential foster parents.

[0563] Step 8:

[0564] Users access the dashboard via their devices to view the latest health data and posts about the animals they are supporting. The sentiment engine collects user reactions to the content and uses them to generate future content.

[0565] This series of steps effectively combines animal health information with emotionally resonant stories, leading to increased support and engagement.

[0566] (Example 2)

[0567] 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."

[0568] Conventional animal health monitoring systems typically only analyze biometric data and provide information based on that data, failing to adequately appeal to the emotions of supporters and potential foster parents. Furthermore, providing interactive content that responds to users' emotions is difficult, making it challenging to increase supporter engagement.

[0569] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0570] In this invention, the server includes means for collecting animal biological parameters from a health monitoring device, means for integrating and analyzing the biological parameters and animal rearing information, means for evaluating the animal's health using an artificial intelligence algorithm, and means for generating a story that represents the animal's condition based on the analysis results, utilizing a generative artificial intelligence model. This makes it possible to analyze the user's emotional response in real time and adjust the content of the generated story.

[0571] A "health monitoring device" is a device used to acquire biological parameters such as heart rate, body temperature, and activity level of animals in real time.

[0572] "Biometric parameters" refer to measurable data such as heart rate, body temperature, and activity level that are necessary to understand an animal's health status.

[0573] "Animal care information" refers to information about the animal's living conditions, including records of its diet, environment, and behavior.

[0574] An "artificial intelligence algorithm" is a computational method for evaluating the health status of animals by integrating and analyzing collected biological parameters and breeding information.

[0575] A "generative artificial intelligence model" is a computational model used to generate narratives that describe the state of an animal based on analysis results.

[0576] The "emotion analysis function" is a feature that evaluates the user's emotional response in real time and adjusts the content provided according to the user's emotions.

[0577] An "online network" is a digital platform for transmitting and sharing generated stories and related information.

[0578] This invention is a system that enables highly personalized animal health monitoring and information provision. The system operates primarily through the involvement of a server, terminals, and users.

[0579] The server collects biological parameters such as heart rate, body temperature, and activity level in real time from health monitoring devices attached to the animals. This data is stored along with breeding information and comprehensively analyzed using artificial intelligence algorithms. The animal's health status is evaluated based on the analysis results, and a narrative representing the animal's condition is generated using a generative AI model.

[0580] The device is equipped with an emotion analysis function that evaluates the user's emotional response in real time. The device records the user's reaction when viewing content and sends this data to a server. The server uses the received emotion data to adjust the story content according to the user's emotions.

[0581] Users can receive and view the generated stories and associated image information through an online network. This allows information about the animals' health to be presented in an emotionally appealing way, increasing supporter engagement.

[0582] As a concrete example, the following is an example of a prompt based on animal biometric data. By entering "Create an inspiring story based on the animal's health data," the system generates a story based on the user's interests and emotions. In this way, the system provides high emotional value to the user while assisting with animal health management.

[0583] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0584] Step 1:

[0585] The server collects biological parameters such as heart rate, body temperature, and activity level in real time from health monitoring devices attached to animals. The input is the biological parameters from the health monitoring devices, and the output is the parameters stored in the database. By storing this data in the database, the server accumulates fundamental information about the animals' health status.

[0586] Step 2:

[0587] The server integrates and analyzes the collected biological parameters and breeding information. The inputs are the biological parameters obtained in the previous step and manually entered breeding information, and the output is the health assessment result. The server uses an artificial intelligence algorithm to analyze the data and assess the health status of the animals.

[0588] Step 3:

[0589] The device evaluates the user's emotional response in real time using sentiment analysis functionality. The input is user reaction data while viewing content, and the output is the user's sentiment evaluation result. The device utilizes sentiment analysis to collect user feedback and transmits this data to the server.

[0590] Step 4:

[0591] The server uses a generative artificial intelligence model to generate a story that represents the animal's condition, based on the analysis results and emotion evaluation results. The input is the animal's health evaluation results and the user's emotion evaluation results, and the output is the generated story. The server provides the generative AI model with the prompt "Create an emotionally moving story based on the animal's health data" and creates the story.

[0592] Step 5:

[0593] The server customizes the generated story to suit the user's emotions and provides it to the online network along with relevant image information. The input is the story before customization and associated biometric data-based image information, while the output is the customized story published on the online network. The server provides the story in a user-accessible format and conveys animal information.

[0594] Step 6:

[0595] Users view stories generated via an online network using their devices and provide feedback. The input is the story on the online network, and the output is feedback data. Users provide feedback to the system through their impressions and emotional reactions to the story, which helps in generating future stories.

[0596] (Application Example 2)

[0597] 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."

[0598] In animal protection activities, it is crucial to effectively communicate the health status and daily lives of animals to supporters and potential adopters. However, traditional methods provide general information that does not adequately address the interests and feelings of individual supporters. This makes it difficult to increase motivation to support and promote continued engagement. There is a need for methods that allow supporters to feel a stronger connection with the animals.

[0599] 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.

[0600] In this invention, the server includes means for collecting animal biometric data, means for recognizing and adjusting the user's emotions using an emotion engine, and means for generating and providing customized stories. This makes it possible to provide personalized stories that respond to the emotions of individual supporters, thereby increasing their engagement in support activities.

[0601] A "health monitoring device" is a device used to acquire biological data such as heart rate, body temperature, and activity level of animals in real time.

[0602] "Biometric data" refers to data that indicates an animal's physiological state, such as its heart rate, body temperature, and activity level.

[0603] "Animal care information" refers to information about the animal's living environment, including its diet, exercise, sleep, and health history.

[0604] "Analysis means" refers to methods for integrating and analyzing biological data and breeding information to evaluate the health status of animals.

[0605] A "narrative generation method" is a means of generating a narrative about an animal's situation based on the analysis results.

[0606] An "online platform" is an internet-based environment for providing generated stories and related information in digital format.

[0607] An "emotion engine" is an engine that recognizes the user's emotions and adjusts information such as stories based on those emotions.

[0608] A "user terminal" is an electronic device used by a user to view information or provide feedback.

[0609] "Customization" refers to adjusting and personalizing the content and format of information according to the user's feelings and preferences.

[0610] The system implementing this invention aims to monitor the health status of animals in real time and provide data to the user, who is a caregiver, as a personalized narrative. The configuration and operation of this system are described below.

[0611] The server receives biometric data from health monitoring devices attached to the animals. This data includes heart rate, body temperature, and activity level. Furthermore, this biometric data is integrated with breeding information and stored in a database. On the server, AI algorithms are used to analyze this data and assess the animal's health status. Based on the results of this analysis, the server generates a narrative about the animal's situation.

[0612] The user's device incorporates an emotion engine that recognizes the user's emotions in real time. It collects the user's reactions and feedback as they view stories and adjusts subsequent story generation based on this data. This process customizes the generated stories to match the user's emotions, allowing the user to feel a deeper connection with the animal they are supporting.

[0613] As a concrete example, consider a scenario where a supporter user receives information about the animal they are supporting. The server generates a story based on data showing "how the animal spent the day." The emotion engine recognizes that the user prefers stories that evoke a sense of "happiness" and provides a corresponding story. For example, a story such as "Today the animal was having fun playing with a new toy" might be delivered through the application on the user's device, along with related photos and videos.

[0614] An example of a prompt to input into the generation AI model is: "User's preferred story type: Active activity, Animal data: {Heart rate: 90, Activity level: High}, User's emotion score: Positive, Theme of the story to generate: Fun playtime." This is expected to deliver the generated story in a way that appeals to the supporter's emotions, thereby encouraging continued support activities.

[0615] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0616] Step 1:

[0617] The server receives real-time biometric data from health monitoring devices attached to animals. Input data such as heart rate, body temperature, and activity level are obtained and temporarily stored. The server then formats this data and prepares it for storage in the database.

[0618] Step 2:

[0619] The server integrates biometric data and breeding information, performing integrated analysis with existing information stored in the database. The input is biometric data and breeding information, and the output is analysis results for evaluating the animals' health status. The server uses AI algorithms to perform tasks such as detecting anomalies and analyzing health trends.

[0620] Step 3:

[0621] The server generates a narrative that describes the animal's situation based on the analysis results. The input is the analysis results, and the output is the generated narrative. The server uses a generative AI model to construct narrative content that concretely describes the animal's activities and health status.

[0622] Step 4:

[0623] The device recognizes the user's emotions in real time. It uses data based on the user's facial expressions, behavior, and past feedback as input. An emotion engine analyzes this data and outputs the user's current emotional state.

[0624] Step 5:

[0625] The server customizes the generated story based on the user's emotional state. The input is the user's emotional state and the generated story, and the output is the story adjusted to suit the user. The server reflects the emotion analysis results to optimize the tone and expression of the content for each user.

[0626] Step 6:

[0627] The device provides users with customized stories. The input is the customized story, and the output is story content delivered along with visual information. The device enables story playback and feedback collection through its user interface.

[0628] 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.

[0629] 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.

[0630] 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.

[0631] [Fourth Embodiment]

[0632] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0633] 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.

[0634] 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).

[0635] 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.

[0636] 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.

[0637] 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).

[0638] 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.

[0639] 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.

[0640] 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.

[0641] 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.

[0642] 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.

[0643] 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.

[0644] 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".

[0645] This embodiment of the invention describes a specific example of a system that streamlines the health management and information provision of protected animals. The system consists of a health monitoring device, a data analysis server, a user terminal, and an online platform.

[0646] Overall system configuration

[0647] Health monitoring devices attached to animals acquire biometric data such as heart rate, body temperature, and activity level in real time. This data is transmitted to a server via wireless communication.

[0648] Data collection and analysis

[0649] The server records biological data received from monitoring devices into a database. It also records observation information about the animals entered by animal care staff using terminals. The server integrates this data and performs analysis using AI algorithms. The health status assessment obtained through this analysis is used to generate stories about the animals.

[0650] Story generation and publication

[0651] The server generates emotionally resonant stories that reflect the animal's health and behavior based on the analysis results. These stories are crucial content for conveying the animal's appeal to supporters and potential adopters. The generated stories, along with relevant visual information, are posted to an online platform.

[0652] Providing information to supporters

[0653] Users can access a dashboard through a dedicated application or website. This dashboard displays the latest health data, stories, and results of the support given to the animals. This allows users to see specifically how their support is making a difference.

[0654] Specific example

[0655] For example, in the case of a cat that a user is supporting, a monitoring device detects an increase in heart rate while the cat is sleeping, and the server receives data indicating an increase in active time. The server then analyzes this data and generates a story such as, "Today the cat played with its favorite toy for longer than usual!", selects a photo of the cat playing as visual information, and posts it on social media. Through this process, supporters can understand that their support is contributing to improving the cat's life.

[0656] In this way, the system integrates everything from animal health management to information dissemination, creating a mechanism that promotes support activities.

[0657] The following describes the processing flow.

[0658] Step 1:

[0659] The server automatically collects animal biometric data from the health monitoring device. This process is carried out by wirelessly transmitting the data obtained by the device in real time to the server. The biometric data includes information on heart rate, body temperature, and activity level.

[0660] Step 2:

[0661] The terminal provides an interface that allows zookeepers to input information about the animals' daily behavior and any abnormalities they observe. The information entered via the terminal is sent to a server and integrated with other data.

[0662] Step 3:

[0663] The server integrates the collected biometric data and breeding information and begins analysis using an AI algorithm. This analysis evaluates whether the data is within the normal range and quantifies the health status. If abnormal results are found, an alert is generated.

[0664] Step 4:

[0665] The server uses an AI generation program to create a story that reflects the animal's current condition based on the analysis results. The generated story is designed to include the animal's health status and any notable events that occurred on that day.

[0666] Step 5:

[0667] The server selects visual information related to the generated story and combines it to create an information package. This package is then prepared for posting to a social networking platform.

[0668] Step 6:

[0669] The server specifies the posting time and target social media platform, and posts the story and visual information package to the selected platform via an API. This ensures that the information is widely disseminated and reaches supporters and potential foster parents.

[0670] Step 7:

[0671] Users can access the dashboard using their own devices to view the latest health status of the animals they are supporting, posted stories, and the impact of their support activities. The dashboard reflects information from the server in real time.

[0672] (Example 1)

[0673] 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".

[0674] There is a need for a system that contributes to animal welfare by effectively monitoring the health status of animals and providing relevant information to supporters. This system needs to collect and analyze accurate data in real time and disseminate the information in an easy-to-understand and engaging format. However, conventional methods have problems with efficient information integration and sharing, preventing supporters from fully understanding the effectiveness of their support.

[0675] 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.

[0676] In this invention, the server includes means for receiving biological information of an animal from a health monitoring device, means for integrating and processing the biological information and animal management information, and means for generating a narrative that represents the animal's condition based on the processing results. This makes it possible to comprehensively monitor the animal's health status and provide caregivers with easily understandable, visually represented information.

[0677] A "health monitoring device" is a device used to acquire biological information about animals in real time.

[0678] "Biometric information" refers to data that indicates an animal's health status, such as heart rate, body temperature, and activity level.

[0679] "Management information" refers to data that includes observation records and behavioral history related to the care of animals.

[0680] A "communication network" refers to the entire infrastructure used for sending and receiving digital data.

[0681] "Processing" refers to the process of integrating and analyzing received biometric and management information.

[0682] A "generation method" is a mechanism for creating specific content or a story based on input data.

[0683] "Image information" refers to image data used to complement and visually represent a generated narrative.

[0684] A "supporter" is an individual or organization that provides support for the health management and welfare improvement of animals.

[0685] One embodiment of this invention involves a process for providing important information to caregivers and effectively managing the health status of animals through an animal health management system. This system primarily utilizes health monitoring devices, servers, user terminals, and a communication network.

[0686] The server receives biological information from the animals via health monitoring devices. Specifically, this includes information such as heart rate, body temperature, and activity level. The received biological information is recorded in a database on the server and further integrated with management information entered by animal care staff from user terminals.

[0687] The server uses an AI algorithm to analyze this integrated data. This AI algorithm, known as a generative AI model, has the ability to generate creative stories based on the analysis results. By inputting prompts into this model, the server generates stories that reflect the health status and behavior of animals.

[0688] The generated stories are integrated with image information and transmitted by the server to an online platform via a communication network. This allows users to view the latest health information and stories of the animals they are supporting through a dedicated application or website.

[0689] For example, if a monitoring device detects a change in the cat's heart rate, the server analyzes this data, generates a story such as, "Today, the cat played with its favorite toy for longer than usual!", and provides information to supporters by posting it on online platforms such as social media.

[0690] An example of a prompt message is: "Generate a story that reflects changes in the cat's heart rate and active time, based on the cat's health monitoring data. Use photos of the cat playing as visual information."

[0691] This format allows for detailed and engaging communication about the animals' health status, enabling supporters to conduct their aid activities more effectively.

[0692] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0693] Step 1:

[0694] The server receives biological information from the animal's health monitoring device. Specifically, it collects data such as heart rate, body temperature, and activity level. This data is transmitted to the server wirelessly. The input is biological information from the health monitoring device, and the output is structured data recorded in the server's database.

[0695] Step 2:

[0696] The terminal is used by animal care staff to input observation information about the animals. This observation information includes diet, behavior, and any notable changes in health. The input is management information from the animal care staff, and the output is that this information is integrated and stored in the server's database.

[0697] Step 3:

[0698] The server integrates biometric and management information, retrieves it from a database, and performs analysis using AI algorithms. This analysis evaluates the animal's health status, detects abnormalities, and helps understand behavioral patterns. The input is integrated biometric and management information, and the output is the health status and behavioral evaluation as a result of the analysis.

[0699] Step 4:

[0700] The server utilizes a generative AI model to generate a story based on the analysis results. It inputs prompt sentences into the generative AI model to generate an emotionally rich story. The input consists of the analysis results and prompt sentences, and the output is the generated story.

[0701] Step 5:

[0702] The server selects image information related to the generated story, integrates it, and provides it to an online platform on the communication network. The input is the story and image information, and the output is the online post as visually enhanced content.

[0703] Step 6:

[0704] Users access a dedicated application or website to view the health status and generated stories of the animals they are supporting. This allows users to stay informed about the latest information and the impact of their support. The input is the content published on the platform, and the output is the user's informational experience as their perception and understanding.

[0705] (Application Example 1)

[0706] 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".

[0707] In modern times, understanding and participating in support activities for rescued animals is important, but there is a challenge in that it is difficult for supporters to easily grasp the health status of animals and the specific impact of support activities. In addition, there is a problem that support activities are not sufficiently promoted because there are insufficient means to effectively share the situation of animals with other supporters and prospective adopters and deepen interactions.

[0708] 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.

[0709] In this invention, the server includes means for collecting animal physiological data, means for integrating and analyzing the physiological data and animal management information, and means for generating a narrative of the animal's condition based on the analysis results. This allows caregivers to understand the animal's health status and activities in narrative form, and also enables them to share the generated information with other users and deepen their interactions.

[0710] A "biological monitoring device" is a device that acquires real-time physiological data such as the heart rate, body temperature, and activity level of animals.

[0711] "Physiological data" refers to data that indicates the health status and activity level of an animal, such as heart rate, body temperature, and exercise level.

[0712] "Management information" refers to information regarding the care and lifestyle of animals, including observational information provided by the caretaker.

[0713] "Analysis means" refers to processing means for integrating collected physiological data and management information and evaluating the health status of animals using AI algorithms.

[0714] A "narrative generation method" is a processing method for generating a narrative that expresses the health status and behavior of an animal in an emotionally rich manner, based on the analysis results.

[0715] A "dashboard" is a screen that provides users with a viewable format of the generated story and related visual information.

[0716] A "communication network" is a network used to send and receive information via the internet.

[0717] The system for realizing this invention consists of a bio-monitoring device that collects biological data from animals, a server that analyzes the data and generates and provides stories, and terminals for users to view and share stories.

[0718] First, a bio-monitoring device collects physiological data such as the animal's heart rate, body temperature, and activity level in real time. This device is equipped with a communication device and transmits the collected data wirelessly to a server.

[0719] Next, the server stores the received physiological data in a database. The server then analyzes the collected data using an AI algorithm (e.g., TensorFlow) to assess the animal's health. Based on this assessment, it generates an emotionally resonant story using a generative AI model. The server visualizes this generated story in a dashboard format, making it accessible to users remotely.

[0720] Users with a device can access a dashboard via the internet. This dashboard displays the latest health data and generated stories of the animals. Users can share stories with other supporters and potential foster families and exchange information. They can also easily post stories to their own social networks using the social networking features.

[0721] For example, if a user's dog's heart rate data shows an increase in activity level, the server will use this data to generate a story such as, "Today the dog ran around the park full of energy!" A possible prompt for the generating AI model might be, "Based on recent heart rate and activity data, please create a story that reflects a lively day."

[0722] In this way, this system will enable the smooth progress of animal health management and support activities.

[0723] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0724] Step 1:

[0725] The bio-monitoring device collects physiological data such as heart rate, body temperature, and activity level of animals in real time. It receives various physiological data from animals as input and transmits it wirelessly to a server. The output is the transmission of data to the server.

[0726] Step 2:

[0727] The server stores physiological data received wirelessly in a database. It accumulates data by receiving physiological data from a biological monitoring device as input and storing it in the database. The output is the physiological data stored in the database.

[0728] Step 3:

[0729] The server retrieves physiological data stored in the database and analyzes it using an AI algorithm. This analysis uses the extracted physiological data as input to evaluate the animal's health status. The output is the health status evaluation result obtained from the analysis.

[0730] Step 4:

[0731] The server generates a story using a generative AI model based on the analysis. The prompt for the AI ​​model is something like, "Generate a story reflecting a day in the life of an animal, based on the health assessment results." The output is the generated story.

[0732] Step 5:

[0733] The server visualizes the generated stories in a dashboard format and provides them to the user via the terminal. This process takes the generated stories as input and outputs structured display data for display on the user's terminal.

[0734] Step 6:

[0735] Users access the dashboard using their devices and view the generated stories. Input is dashboard data provided by the server, and output is the user's visually perceived screen display. Users also perform actions necessary to share the stories on social networks.

[0736] Step 7:

[0737] Users share stories with other supporters using social networking features via their devices and exchange information with them. The input is the data of the story they want to share, and the output is a social networking post that generates interaction with other users.

[0738] This processing flow allows users to effectively acquire and share stories based on animal physiological data.

[0739] 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.

[0740] In this embodiment of the invention, a system is provided that takes into account not only the health management and information provision of rescued animals, but also the emotions of the user. The system consists of a health monitoring device, a data analysis server, a user terminal, an emotion engine, and an online platform.

[0741] Overall system configuration

[0742] Animals are fitted with health monitoring devices that capture real-time biometric data such as heart rate, body temperature, and activity level. This data is transmitted to a server and stored in a database along with care information entered by animal care staff via terminals. The server uses AI algorithms to integrate and analyze this data to evaluate the animals' health status.

[0743] Embedding an emotion engine

[0744] The emotion engine is used to recognize user emotions and adjust the content of generated stories and materials. By analyzing user feedback and reactions in real time, the emotion engine enables the delivery of information tailored to individual users.

[0745] Story generation and customization

[0746] The server generates a story about the animal's situation based on analysis results and feedback from the emotion engine. The generated story is customized to suit the user's emotions and posted to an online platform along with relevant visual information. This allows supporters and potential adopters to access information about the animals in a more emotionally resonant way.

[0747] Providing information to supporters and utilizing their feedback

[0748] Users use their devices to check the latest health data and content for the animals they support via a dashboard. During this process, the emotion engine records the user's reactions and uses this information to suggest future content. For example, if a user shows a positive reaction to a particular type of story, this information will be reflected in the next story generation.

[0749] Specific example

[0750] A Facebook post about a dog named Coco, which a user supports, is based on data collected by a monitoring device, specifically "Increased walking time today." The emotion engine detects from past data that the user tends to prefer stories about "Increased Activity" and feeds this information back to the server. Based on the analysis, the server generates a story such as "Coco had a great time running around her favorite park!" and posts it along with a photo of Coco during her walk. This post is customized based on the emotion engine's analysis and is expected to strongly attract the user's interest.

[0751] In this way, the introduction of an emotion engine allows the system to personalize animal health management and information dissemination, promoting more effective support activities.

[0752] The following describes the processing flow.

[0753] Step 1:

[0754] The server collects animal biometric data in real time from health monitoring devices. The devices measure the animal's heart rate, body temperature, and activity level, and transmit this data to the server wirelessly, recording it in a database.

[0755] Step 2:

[0756] The terminal provides an interface for zookeepers to input information about the animals' behavior and health as observed. The zookeepers input this observation information into the terminal and send it to the server.

[0757] Step 3:

[0758] The server integrates and analyzes the collected biometric data and breeding information. Using AI algorithms, it assesses the animals' health status and generates a numerical score. If an abnormal pattern is detected, it triggers an alert.

[0759] Step 4:

[0760] The emotion engine analyzes the user's past feedback and emotional responses to evaluate their preferences and interests. Based on this evaluation, the server adjusts the process to generate a story that is best suited to the user.

[0761] Step 5:

[0762] The server generates a story to convey the animal's situation based on the analysis results and feedback from the emotion engine. The story is emotionally rich and includes the animal's health condition and notable events of the day.

[0763] Step 6:

[0764] The server selects visual materials (photos and videos) related to the story and creates a package that integrates them to match the story's content. The package is optimized to resonate with the user's emotions.

[0765] Step 7:

[0766] The server uses SNS APIs to post the generated story and visual material package to online platforms. Posting is scheduled at a designated time to ensure it reaches supporters and potential foster parents.

[0767] Step 8:

[0768] Users access the dashboard via their devices to view the latest health data and posts about the animals they are supporting. The sentiment engine collects user reactions to the content and uses them to generate future content.

[0769] This series of steps effectively combines animal health information with emotionally resonant stories, leading to increased support and engagement.

[0770] (Example 2)

[0771] 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".

[0772] Conventional animal health monitoring systems typically only analyze biometric data and provide information based on that data, failing to adequately appeal to the emotions of supporters and potential foster parents. Furthermore, providing interactive content that responds to users' emotions is difficult, making it challenging to increase supporter engagement.

[0773] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0774] In this invention, the server includes means for collecting animal biological parameters from a health monitoring device, means for integrating and analyzing the biological parameters and animal rearing information, means for evaluating the animal's health using an artificial intelligence algorithm, and means for generating a story that represents the animal's condition based on the analysis results, utilizing a generative artificial intelligence model. This makes it possible to analyze the user's emotional response in real time and adjust the content of the generated story.

[0775] A "health monitoring device" is a device used to acquire biological parameters such as heart rate, body temperature, and activity level of animals in real time.

[0776] "Biometric parameters" refer to measurable data such as heart rate, body temperature, and activity level that are necessary to understand an animal's health status.

[0777] "Animal care information" refers to information about the animal's living conditions, including records of its diet, environment, and behavior.

[0778] An "artificial intelligence algorithm" is a computational method for evaluating the health status of animals by integrating and analyzing collected biological parameters and breeding information.

[0779] A "generative artificial intelligence model" is a computational model used to generate narratives that describe the state of an animal based on analysis results.

[0780] The "emotion analysis function" is a feature that evaluates the user's emotional response in real time and adjusts the content provided according to the user's emotions.

[0781] An "online network" is a digital platform for transmitting and sharing generated stories and related information.

[0782] This invention is a system that enables highly personalized animal health monitoring and information provision. The system operates primarily through the involvement of a server, terminals, and users.

[0783] The server collects biological parameters such as heart rate, body temperature, and activity level in real time from health monitoring devices attached to the animals. This data is stored along with breeding information and comprehensively analyzed using artificial intelligence algorithms. The animal's health status is evaluated based on the analysis results, and a narrative representing the animal's condition is generated using a generative AI model.

[0784] The device is equipped with an emotion analysis function that evaluates the user's emotional response in real time. The device records the user's reaction when viewing content and sends this data to a server. The server uses the received emotion data to adjust the story content according to the user's emotions.

[0785] Users can receive and view the generated stories and associated image information through an online network. This allows information about the animals' health to be presented in an emotionally appealing way, increasing supporter engagement.

[0786] As a concrete example, the following is an example of a prompt based on animal biometric data. By entering "Create an inspiring story based on the animal's health data," the system generates a story based on the user's interests and emotions. In this way, the system provides high emotional value to the user while assisting with animal health management.

[0787] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0788] Step 1:

[0789] The server collects biological parameters such as heart rate, body temperature, and activity level in real time from health monitoring devices attached to animals. The input is the biological parameters from the health monitoring devices, and the output is the parameters stored in the database. By storing this data in the database, the server accumulates fundamental information about the animals' health status.

[0790] Step 2:

[0791] The server integrates and analyzes the collected biological parameters and breeding information. The inputs are the biological parameters obtained in the previous step and manually entered breeding information, and the output is the health assessment result. The server uses an artificial intelligence algorithm to analyze the data and assess the health status of the animals.

[0792] Step 3:

[0793] The device evaluates the user's emotional response in real time using sentiment analysis functionality. The input is user reaction data while viewing content, and the output is the user's sentiment evaluation result. The device utilizes sentiment analysis to collect user feedback and transmits this data to the server.

[0794] Step 4:

[0795] The server uses a generative artificial intelligence model to generate a story that represents the animal's condition, based on the analysis results and emotion evaluation results. The input is the animal's health evaluation results and the user's emotion evaluation results, and the output is the generated story. The server provides the generative AI model with the prompt "Create an emotionally moving story based on the animal's health data" and creates the story.

[0796] Step 5:

[0797] The server customizes the generated story to suit the user's emotions and provides it to the online network along with relevant image information. The input is the story before customization and associated biometric data-based image information, while the output is the customized story published on the online network. The server provides the story in a user-accessible format and conveys animal information.

[0798] Step 6:

[0799] Users view stories generated via an online network using their devices and provide feedback. The input is the story on the online network, and the output is feedback data. Users provide feedback to the system through their impressions and emotional reactions to the story, which helps in generating future stories.

[0800] (Application Example 2)

[0801] 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".

[0802] In animal protection activities, it is crucial to effectively communicate the health status and daily lives of animals to supporters and potential adopters. However, traditional methods provide general information that does not adequately address the interests and feelings of individual supporters. This makes it difficult to increase motivation to support and promote continued engagement. There is a need for methods that allow supporters to feel a stronger connection with the animals.

[0803] 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.

[0804] In this invention, the server includes means for collecting animal biometric data, means for recognizing and adjusting the user's emotions using an emotion engine, and means for generating and providing customized stories. This makes it possible to provide personalized stories that respond to the emotions of individual supporters, thereby increasing their engagement in support activities.

[0805] A "health monitoring device" is a device used to acquire biological data such as heart rate, body temperature, and activity level of animals in real time.

[0806] "Biometric data" refers to data that indicates an animal's physiological state, such as its heart rate, body temperature, and activity level.

[0807] "Animal care information" refers to information about the animal's living environment, including its diet, exercise, sleep, and health history.

[0808] "Analysis means" refers to methods for integrating and analyzing biological data and breeding information to evaluate the health status of animals.

[0809] A "narrative generation method" is a means of generating a narrative about an animal's situation based on the analysis results.

[0810] An "online platform" is an internet-based environment for providing generated stories and related information in digital format.

[0811] An "emotion engine" is an engine that recognizes the user's emotions and adjusts information such as stories based on those emotions.

[0812] A "user terminal" is an electronic device used by a user to view information or provide feedback.

[0813] "Customization" refers to adjusting and personalizing the content and format of information according to the user's feelings and preferences.

[0814] The system implementing this invention aims to monitor the health status of animals in real time and provide data to the user, who is a caregiver, as a personalized narrative. The configuration and operation of this system are described below.

[0815] The server receives biometric data from health monitoring devices attached to the animals. This data includes heart rate, body temperature, and activity level. Furthermore, this biometric data is integrated with breeding information and stored in a database. On the server, AI algorithms are used to analyze this data and assess the animal's health status. Based on the results of this analysis, the server generates a narrative about the animal's situation.

[0816] The user's device incorporates an emotion engine that recognizes the user's emotions in real time. It collects the user's reactions and feedback as they view stories and adjusts subsequent story generation based on this data. This process customizes the generated stories to match the user's emotions, allowing the user to feel a deeper connection with the animal they are supporting.

[0817] As a concrete example, consider a scenario where a supporter user receives information about the animal they are supporting. The server generates a story based on data showing "how the animal spent the day." The emotion engine recognizes that the user prefers stories that evoke a sense of "happiness" and provides a corresponding story. For example, a story such as "Today the animal was having fun playing with a new toy" might be delivered through the application on the user's device, along with related photos and videos.

[0818] An example of a prompt to input into the generation AI model is: "User's preferred story type: Active activity, Animal data: {Heart rate: 90, Activity level: High}, User's emotion score: Positive, Theme of the story to generate: Fun playtime." This is expected to deliver the generated story in a way that appeals to the supporter's emotions, thereby encouraging continued support activities.

[0819] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0820] Step 1:

[0821] The server receives real-time biometric data from health monitoring devices attached to animals. Input data such as heart rate, body temperature, and activity level are obtained and temporarily stored. The server then formats this data and prepares it for storage in the database.

[0822] Step 2:

[0823] The server integrates biometric data and breeding information, performing integrated analysis with existing information stored in the database. The input is biometric data and breeding information, and the output is analysis results for evaluating the animals' health status. The server uses AI algorithms to perform tasks such as detecting anomalies and analyzing health trends.

[0824] Step 3:

[0825] The server generates a narrative that describes the animal's situation based on the analysis results. The input is the analysis results, and the output is the generated narrative. The server uses a generative AI model to construct narrative content that concretely describes the animal's activities and health status.

[0826] Step 4:

[0827] The device recognizes the user's emotions in real time. It uses data based on the user's facial expressions, behavior, and past feedback as input. An emotion engine analyzes this data and outputs the user's current emotional state.

[0828] Step 5:

[0829] The server customizes the generated story based on the user's emotional state. The input is the user's emotional state and the generated story, and the output is the story adjusted to suit the user. The server reflects the emotion analysis results to optimize the tone and expression of the content for each user.

[0830] Step 6:

[0831] The device provides users with customized stories. The input is the customized story, and the output is story content delivered along with visual information. The device enables story playback and feedback collection through its user interface.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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."

[0841] 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.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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.

[0852] 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 to be incorporated by reference.

[0853] The following is further disclosed regarding the embodiments described above.

[0854] (Claim 1)

[0855] A means of collecting animal biological data from a health monitoring device,

[0856] A means for integrating and analyzing the aforementioned biological data and animal husbandry information,

[0857] A generation means for generating a story that describes the animal's situation based on the analysis results,

[0858] A means of providing the generated stories to an online platform,

[0859] A system that includes this.

[0860] (Claim 2)

[0861] The system according to claim 1, further comprising means for selecting and integrating visual information related to the generated narrative.

[0862] (Claim 3)

[0863] The system according to claim 1, further comprising means for providing the aforementioned biological data and analysis results to a supporter, enabling the supporter to understand the animal's health status and the impact of the support activities.

[0864] "Example 1"

[0865] (Claim 1)

[0866] A means for receiving animal biological information from a health monitoring device,

[0867] Means for integrating and processing the aforementioned biological information and animal management information,

[0868] A generation means for generating a story that describes the animal's situation based on the processing results,

[0869] A means of providing the generated story to a communication network,

[0870] A system that includes this.

[0871] (Claim 2)

[0872] The system according to claim 1, which selects and integrates image information related to the generated story.

[0873] (Claim 3)

[0874] The system according to claim 1, which provides the aforementioned biological information and processing results to a supporter, enabling the supporter to understand the animal's health status and the impact of the support activities.

[0875] "Application Example 1"

[0876] (Claim 1)

[0877] A means of collecting animal physiological data from a biological monitoring device,

[0878] A means for integrating and analyzing the aforementioned physiological data and animal management information,

[0879] A means of generating a narrative of the animal's situation based on the analysis results,

[0880] A means of providing the generated story as a dashboard that users can view,

[0881] A means that enables users to share the aforementioned story via a communication network and interact with other users,

[0882] A system that includes this.

[0883] (Claim 2)

[0884] The system according to claim 1, further comprising means for selecting, integrating, and displaying visual information related to the physiological data and analysis results.

[0885] (Claim 3)

[0886] The system according to claim 1, further comprising means for users to share the generated story and related visual information with other users through a social networking service and to facilitate interaction.

[0887] "Example 2 of combining an emotion engine"

[0888] (Claim 1)

[0889] A means for collecting animal biological parameters from a health monitoring device,

[0890] The system has a function to integrate and analyze the aforementioned biological parameters and animal rearing information, and provides means for evaluating animal health using an artificial intelligence algorithm.

[0891] A means of generating a story that describes the state of an animal based on analysis results, utilizing a generative artificial intelligence model,

[0892] A means including an emotion analysis function that analyzes the user's emotional response in real time and adjusts the content of the generated story,

[0893] A means of providing customized stories to an online network,

[0894] A system that includes this.

[0895] (Claim 2)

[0896] The system according to claim 1, comprising means for selecting and integrating image information related to the generated story, and providing it to an online network as visually appealing content.

[0897] (Claim 3)

[0898] The system according to claim 1, comprising means for providing the aforementioned biological parameters and analysis results to the supporter so that the supporter can understand the animal's health status and the impact of support behavior, and further recording the supporter's emotional feedback and reflecting it in the next story generation.

[0899] "Application example 2 when combining with an emotional engine"

[0900] (Claim 1)

[0901] A means of collecting animal biological data from a health monitoring device,

[0902] A means for integrating and analyzing the aforementioned biological data and animal husbandry information,

[0903] A generation means for generating a story that describes the animal's situation based on the analysis results,

[0904] A means of providing the generated stories to an online platform,

[0905] A means including an emotion engine that recognizes user emotions and adjusts the generated narrative,

[0906] A means of customizing and delivering emotion-based stories using the user's device,

[0907] A system that includes this.

[0908] (Claim 2)

[0909] The system according to claim 1, further comprising means for selecting and integrating visual information related to the generated narrative.

[0910] (Claim 3)

[0911] The system according to claim 1, further comprising means for providing the aforementioned biological data and analysis results to a supporter, enabling the supporter to understand the animal's health status and the impact of the support activities. [Explanation of Symbols]

[0912] 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 collecting animal biological data from a health monitoring device, A means for integrating and analyzing the aforementioned biological data and animal husbandry information, A generation means for generating a story that describes the animal's situation based on the analysis results, A means of providing the generated stories to an online platform, A system that includes this.

2. The system according to claim 1, further comprising means for selecting and integrating visual information related to the generated narrative.

3. The system according to claim 1, further comprising means for providing the aforementioned biological data and analysis results to a supporter, enabling the supporter to understand the animal's health status and the impact of the support activities.

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