System

Abstract

A system is provided.SOLUTION: An automatic conditioning note system for recording a living habit of a pet, comprising: means for recording a food intake of the pet; means for recording an exercise amount of the pet; means for recording a weight of the pet; means for recording a situation of excretion of the pet; means for analyzing a health condition of the pet based on the recorded information to detect an abnormality; and means for notifying a user when the abnormality is detected.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Pet owners often overlook changes in their pets' physical condition or behavior in their daily lives. Accurately understanding these changes can be difficult, especially in busy environments or when multiple people are caring for a pet. Because pets tend to hide their pain or discomfort, owners often delay noticing, potentially leading to neglecting their pet's health. There is a need for a system that can improve this situation, more accurately understand a pet's health condition, and quickly respond if an abnormality occurs. [Means for solving the problem]

[0005] The present invention solves the above problems by providing an automatic conditioning notebook system for recording a pet's lifestyle habits. This system includes a means for automatically recording the pet's food intake, exercise, weight, and excretion status, a means for analyzing the pet's health condition based on this data, and a means for detecting abnormalities. It also includes a means for notifying the user when an abnormality is detected.

[0006] The present invention also includes a means for recording video data of the way a pet walks or runs, and for detecting abnormalities by learning from the video data, thereby enabling early detection of abnormalities in the pet's muscles or joints and enabling the user to take appropriate measures.

[0007] In addition, by recording the number of times your pet goes to the toilet and the amount of water it consumes and including means to detect abnormalities based on that data, abnormalities in your pet's internal organ or kidney function can be detected early, allowing the user to respond quickly.

[0008] A "pet" is an animal that humans keep in their homes, and is generally a mammal such as a dog or cat.

[0009] "Lifestyle habits" refers to the daily behaviors and activities of pets, including eating, exercise, excretion, and sleep.

[0010] An "automatic conditioning note system" is a system that automatically records and analyzes a pet's lifestyle habits to manage its health.

[0011] "Food intake" refers to the amount of food a pet consumes, and primarily refers to the intake of calories and nutrients.

[0012] "Amount of exercise" refers to the amount of exercise a pet undergoes, including distance walked, time spent playing, calories burned, and the like.

[0013] "Weight" refers to the pet's current body weight.

[0014] "Excretion status" refers to the frequency and content of a pet's excretion, including the number and amount of urine and feces.

[0015] "Health" refers to the pet's overall physical health and is evaluated based on indicators such as weight, amount of food eaten, amount of exercise, and excretion status.

[0016] "Analysis" refers to the process of analyzing the recorded data and determining the pet's health condition or any abnormalities.

[0017] "Abnormal" refers to a deviation from a pet's normal lifestyle or health, including sudden fluctuations in weight or unusual movement patterns.

[0018] "User" refers to a person who uses this system to manage the lifestyle habits of a pet, and is primarily a pet owner.

[0019] "Notification" refers to messages and alerts that the system sends to the user to inform them of abnormalities.

[0020] "Video data of walking and running" refers to video data that records how a pet walks or runs.

[0021] "Learning" refers to the machine learning process that uses the data collected by the system to continually understand and improve your pet's behavioral patterns and health.

[0022] "Toilet visits" refers to how often your pet uses the toilet.

[0023] "Water intake" refers to the amount of water your pet drinks on a daily basis. [Brief explanation of the drawings]

[0024] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2]1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0025] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0026] First, the terms used in the following description will be explained.

[0027] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0028] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0029] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0030] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0031] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0032] [First embodiment]

[0033] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0034] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0035] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0036] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0037] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0038] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0039] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0040] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0041] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0042] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0043] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0044] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0045] The present invention relates to an automatic conditioning note system for recording the lifestyle habits of pets and analyzing their health conditions. Specific embodiments of the system are described below.

[0046] System configuration

[0047] The system includes multiple devices, a server, and a user interface to monitor, record, and analyze pet behavior and health. Each device automatically records the pet's food intake, exercise, weight, and excretion status.

[0048] Terminal

[0049] The terminal is composed of various devices such as:

[0050] 1. Smart scale

[0051] When your pet steps on the scale, its weight is measured and the data is recorded along with a timestamp.

[0052] 2. Automatic feeder

[0053] Every time your pet eats, the amount of food eaten is recorded and the data is saved with a timestamp.

[0054] 3. Pet Activity Monitor

[0055] Attached to a collar or harness, it measures the pet's activity, specifically recording data such as the number of steps taken, distance traveled, and calories burned.

[0056] 4. Smart Toilet

[0057] Record data on the number of times your pet goes to the toilet, the time it takes, and the amount and condition of its waste.

[0058] server

[0059] The server is the main processor that receives, stores, and analyzes data sent from the device.

[0060] 1. Data Receipt and Storage

[0061] The server receives the data sent by the device in real time and stores it in a database for each pet.

[0062] 2. Data Analysis

[0063] The server analyzes the stored data and evaluates the pet's health, particularly checking for weight fluctuations, changes in activity, and abnormalities in elimination frequency.

[0064] 3. Anomaly Detection

[0065] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[0066] User Interface

[0067] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[0068] 1. Displaying data

[0069] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[0070] 2. Alert Notifications

[0071] If an anomaly is detected, users can receive alerts via push notification or email.

[0072] Program processing

[0073] Terminal

[0074] The device collects and transmits data. Specifically, when a pet steps on the scale, it automatically measures its weight and sends the data to the server. Similarly, the automatic feeder records the pet's food intake, and the activity monitor measures its exercise. This information is then sent to the server.

[0075] server

[0076] The server centrally manages all data sent from the devices and stores it in a database. It then uses algorithms to analyze the data and check for any abnormalities in weight fluctuations, exercise volume, excretion status, etc. For example, if the server detects a sudden change in weight over a short period of time or an abnormal change in exercise patterns, it generates an alert and notifies the user.

[0077] User

[0078] Users can check their pet's condition using a smartphone app. The app sends data requests to the server and displays the latest information. The app's intuitive interface provides detailed statistical data and graphs on food intake, exercise, weight, and excretion status. If any abnormalities are detected, the app notifies the user with specific countermeasures.

[0079] Specific examples

[0080] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to a server. The server then compares the data with the previous measurement and analyzes it for any abnormal fluctuations. If there is a sudden weight loss, the user receives an alert notification on their smartphone app saying, "Sudden weight fluctuations have been detected. Please consult a veterinarian." The user can open the app, check the detailed data, and contact a veterinarian if necessary. In this way, users can monitor their pet's health in real time and respond quickly to any abnormalities.

[0081] As described above, the present invention enables detailed data collection and analysis to assist in the health management of pets, and enables prompt notification of abnormalities.

[0082] The processing flow will be explained below.

[0083] Step 1:

[0084] The device will measure your pet's weight.

[0085] When a pet steps onto the smart scale, the device uses sensors to measure its weight, timestamps the data, and stores it in its internal memory.

[0086] Step 2:

[0087] The device records the amount of food consumed.

[0088] When your pet eats from the automatic feeder, the device records the amount of food fed and a timestamp, and stores it in its internal memory.

[0089] Step 3:

[0090] The device measures the amount of exercise.

[0091] The pet activity monitor collects your pet's exercise data (steps, distance traveled, calories burned, etc.) in real time and stores it in its internal memory along with a timestamp.

[0092] Step 4:

[0093] The device records the excretion status.

[0094] When your pet uses the smart toilet, the device records the number of times it defecates and a timestamp, and if necessary, stores the amount and condition of the waste in its internal memory.

[0095] Step 5:

[0096] The terminal transmits the collected data to the server.

[0097] At regular intervals or when a specific event occurs (for example, immediately after a pet steps on the scale), the device sends the collected data to a server via Internet communication.

[0098] Step 6:

[0099] The server receives and stores the data.

[0100] The server receives data sent from the device in real time and stores it in a database for each pet. It also validates the data to check for any irregularities.

[0101] Step 7:

[0102] The server analyzes the data.

[0103] The server analyzes the stored data periodically or on an event-driven basis, checking for abnormalities in weight fluctuations, exercise volume, excretion status, etc. If a problem is detected, an alert is generated.

[0104] Step 8:

[0105] The server detects the abnormality and notifies the user.

[0106] If the server detects an anomaly based on the analysis results, it will send an alert to the user via email or push notification, which will also include detailed information about the anomaly.

[0107] Step 9:

[0108] The user checks the data in the app.

[0109] The user opens the smartphone app, retrieves the latest data from the server, and visually checks it. The app displays detailed data such as food intake, exercise, weight, and excretion status, as well as an overview of any abnormalities.

[0110] Step 10:

[0111] The user handles the abnormality.

[0112] The user receives an alert notification from the server, checks the details, and takes appropriate action, such as taking their pet to the vet.

[0113] Example 1

[0114] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0115] Managing pet health is an important issue for pet owners, and early detection of illness is especially important. However, detailed monitoring of a pet's health requires the collection and analysis of a wide range of data, including food intake, exercise, weight, and excretion patterns. Conventional methods require manually recording this data, which is laborious and time-consuming and can be inaccurate. Furthermore, even if an abnormality is discovered, it is difficult to respond immediately, increasing the risk to the pet's health.

[0116] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0117] In this invention, the server includes means for recording the amount of food eaten by the pet, means for recording the amount of exercise the pet does, means for recording the weight of the pet, means for recording the excretion status of the pet, means for transmitting the recorded data, means for storing the received data, means for analyzing the stored data and evaluating the health status of the pet, means for detecting abnormalities based on the analysis results, and means for notifying the user when an abnormality is detected. This makes it possible to closely monitor the health status of the pet in real time and quickly notify the user when an abnormality is discovered. Furthermore, the user can easily check this data through an intuitive interface and take prompt action.

[0118] A "means for recording pet food intake" is a device that automatically measures the amount of food consumed by a pet and stores the data.

[0119] The "means for recording the amount of exercise of a pet" is a device that measures the amount of exercise that a pet performs and records the data.

[0120] A "means for recording a pet's weight" is a device that measures a pet's weight and stores the data.

[0121] A "means for recording pet excretion status" is a device that records the frequency and content of a pet's excretion.

[0122] The "means for transmitting recorded data" is a device that transmits collected data to a central management device such as a server.

[0123] "Means for storing received data" is a device that stores the transmitted data in a local database.

[0124] The "means for analyzing the stored data and assessing the health condition of the pet" refers to algorithms or software for assessing the health condition of the pet using the stored data.

[0125] "Means for detecting anomalies based on analysis results" refers to a mechanism for identifying abnormal patterns or values ​​from analyzed data.

[0126] The "means for notifying the user when an abnormality is detected" refers to a device or system that notifies the user of the information when an abnormality is discovered.

[0127] The present invention relates to an automatic conditioning note system for recording the lifestyle habits of pets and analyzing their health conditions. Specific embodiments of the system are described below.

[0128] System configuration

[0129] The system includes multiple devices, a server, and a user interface to monitor, record, and analyze pet behavior and health status. The following terminals are used:

[0130] Terminal

[0131] 1. Smart scale

[0132] The smart scale measures the pet's weight when it steps on the scale, records the data with a timestamp, and transmits the data to a server via Wi-Fi or Bluetooth.

[0133] 2. Automatic feeder

[0134] The automatic feeder measures the amount of food your pet eats and records the data with a timestamp, which is then sent to a server via Wi-Fi or Bluetooth.

[0135] 3. Pet Activity Monitor

[0136] The activity monitor is attached to a collar or harness and records the pet's activity, such as steps taken, distance traveled, and calories burned, and the data is also sent to a server.

[0137] 4. Smart Toilet

[0138] The smart toilet records the number of times your pet goes to the toilet, the time it takes, and the amount and condition of the waste, and sends the data to a server via Wi-Fi or Bluetooth.

[0139] server

[0140] The server receives the data sent from the terminals and manages it in a unified manner.

[0141] 1. Data Receipt and Storage

[0142] The server receives the data sent from the device in real time and stores it in a database for each pet.

[0143] 2. Data Analysis

[0144] The server uses algorithms to analyze the stored data, particularly for weight fluctuations, changes in activity levels, and abnormal bowel movements. For example, if a sudden weight loss or abnormal movement patterns are detected, an alert will be generated.

[0145] 3. Anomaly Detection

[0146] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[0147] User Interface

[0148] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[0149] 1. Displaying data

[0150] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[0151] 2. Alert Notifications

[0152] If an anomaly is detected, users can receive alerts via push notification or email.

[0153] Specific examples

[0154] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to a server. The server then compares the data with the previous measurement and analyzes it for any abnormal fluctuations. If there is a sudden weight loss, the user will receive an alert notification on their smartphone app saying, "Sudden weight fluctuations have been detected. Please consult a veterinarian." The user can then open the app, check the detailed data, and contact a veterinarian if necessary.

[0155] Prompt Sentence Examples

[0156] You can generate a report on your pet's health by inputting the following prompts into the generative AI model:

[0157] Prompt statement:

[0158] Generate detailed reports on your pet's health using data from your automated pet conditioning notes system, including:

[0159] body weight

[0160] Amount of food

[0161] Exercise volume (steps, distance traveled, calories burned)

[0162] Excretion status (number of times, condition of excrement)

[0163] Please also mention any sudden weight fluctuations or changes in exercise patterns. We will assess your pet's health and recommend any necessary measures.

[0164] Using this prompt, the generative AI model can create a specific and detailed report on the pet's health.

[0165] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0166] Step 1: Data collection

[0167] The devices collect data on the pet's behavior and health. When a user places their pet on a smart scale, the scale measures the pet's weight and records the data with a timestamp. Similarly, an automatic feeder measures the amount of food a pet eats, and a pet activity monitor records the number of steps taken, distance traveled, and calories burned. A smart toilet records the number of times the pet defecates, the time, and the amount and condition of the waste. The input is the data measured by each device, and the output is this data recorded with a timestamp.

[0168] Step 2: Send data

[0169] The devices send the data they collect to a server. Smart scales, automatic feeders, pet activity monitors, and smart toilets all send data to a server via Wi-Fi or Bluetooth. The input is the recorded data with a timestamp, and the output is the data being sent to the server.

[0170] Step 3: Receiving and storing data

[0171] The server receives the data sent from the terminal and manages it in a unified manner. The received data is stored in a database and classified for each pet. The input is the data sent from the terminal, and the output is that this data is stored in the server's database.

[0172] Step 4: Data analysis

[0173] The server uses the stored data to analyze the pet's health. During the data analysis process, algorithms are used to check for weight fluctuations, changes in activity levels, and abnormalities in excretion. For example, sudden weight fluctuations and abnormal movement patterns are detected. The input is the stored data, and the output is various health indicators and abnormality detection results.

[0174] Step 5: Anomaly detection

[0175] The server detects anomalies from the analyzed data. If a sudden weight gain or loss or an abnormal exercise pattern is found, it is deemed to be an anomaly. The input is the analysis results, and the output is information tagged as an anomaly. Specifically, if a sudden weight loss is detected, for example, it is tagged as "sudden weight loss."

[0176] Step 6: User Notification

[0177] The server notifies the user if an abnormality is detected. When an abnormality is detected, a push notification is sent to the user's smartphone or email. The input is the abnormality detection result, and the output is a notification message to the user. For example, a notification may be sent saying, "A sudden weight fluctuation has been detected. Please consult a veterinarian."

[0178] Step 7: Data display

[0179] Users access the system using a smartphone or computer to view and check data. Data on weight, food intake, exercise, and excretion status can be visually checked as graphs and statistical information through an app or web interface. The input is the saved data and analysis results, and the output is a screen where the user can check the visualized data. For example, a graph showing the weight fluctuations of a pet over the past week is displayed.

[0180] (Application example 1)

[0181] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0182] It is important to reliably monitor the health of pets when traveling or driving long distances with pets, but conventional systems have had difficulty monitoring the health of pets in the vehicle in real time. Furthermore, there is no means of quickly notifying the user when an abnormality is detected, which tends to result in delayed response. There is a need for a new monitoring system that can solve these issues and ensure the safety and health of pets.

[0183] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0184] In this invention, the server includes a means for recording the amount of food eaten, a means for recording the amount of exercise, a means for recording the weight, a processing means in the vehicle for receiving, saving, and analyzing the data in real time, a means for analyzing the health condition of the pet based on the analyzed data and detecting abnormalities, and a notification means mounted in the vehicle for notifying the user when an abnormality is detected. This makes it possible to monitor the health condition of the pet in the vehicle in real time, and to quickly notify the user when an abnormality occurs.

[0185] "Pet lifestyle" refers to the daily activities of pets, such as eating, exercise, weight changes, and excretory behavior.

[0186] An "automatic conditioning note system" is a system that automatically records a pet's lifestyle habits, analyzes its health condition, and notifies the user if any abnormalities are detected.

[0187] "Means for recording food intake" refers to a device or sensor that automatically measures and records the amount of food consumed by a pet.

[0188] "Means for recording physical activity" refers to devices or sensors that automatically measure and record a pet's physical activity.

[0189] "Weight recording means" refers to a device that automatically measures and records a pet's weight.

[0190] "Means for recording excretion status" refers to a device that automatically measures and records the frequency and amount of pet excretion.

[0191] "Processing means for receiving, storing, and analyzing data in real time" refers to a processing system for receiving data sent from a terminal, storing it, and instantly analyzing it to determine the health condition of a pet.

[0192] "Means for detecting abnormalities" refers to algorithms and analytical methods for detecting abnormalities in health status based on recorded data.

[0193] "Means for notifying" refers to a means for notifying the user of a detected abnormality, and includes methods such as push notifications to a smartphone or displaying the information on the vehicle's display.

[0194] "Notification means installed in the vehicle" refers to a means for notifying the driver using an in-vehicle display or alert system when a pet shows signs of abnormal health.

[0195] The present invention relates to an automatic conditioning note system for recording pet lifestyle habits and analyzing their health status. This system monitors and notifies users to ensure the health of their pets in an autonomous vehicle. Specific embodiments of the system are described below.

[0196] System configuration

[0197] The system includes multiple sensors, a server, and a user interface to monitor, record, and analyze pet behavior and health. Each sensor automatically records the pet's food intake, exercise, weight, and excretion status.

[0198] sensor

[0199] The sensor consists of various devices such as:

[0200] 1. Smart scale

[0201] When your pet steps on the scale, its weight is measured and the data is recorded along with a timestamp.

[0202] 2. Automatic feeder

[0203] Every time your pet eats, the amount of food eaten is recorded and the data is saved with a timestamp.

[0204] 3. Pet Activity Monitor

[0205] Attached to a collar or harness, it measures the pet's activity, specifically recording data such as the number of steps taken, distance traveled, and calories burned.

[0206] 4. Smart Toilet

[0207] Record data on the number of times your pet goes to the toilet, the time it takes, and the amount and condition of its waste.

[0208] server

[0209] The server is the main processor that receives, stores, and analyzes the data sent from the sensors. Specific use cases are shown below.

[0210] 1. Data Receipt and Storage

[0211] The server receives the data sent by the sensors in real time and stores it in a database (e.g., MySQL) for each pet.

[0212] 2. Data Analysis

[0213] The server analyzes the stored data using a real-time data analysis system (e.g., Apache Kafka) to assess the pet's health, particularly by checking for changes in weight, activity levels, and abnormalities in defecation frequency.

[0214] 3. Anomaly Detection

[0215] The server detects abnormalities based on the analysis results, and if an abnormality is detected, it alerts the user via a notification system installed in the vehicle.

[0216] User Interface

[0217] Users can use their smartphone or the vehicle's on-board display to check the information provided by the system and take any necessary action.

[0218] 1. Displaying data

[0219] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[0220] 2. Alert Notifications

[0221] If an abnormality is detected, the user can receive an alert via push notification on the vehicle's display or smartphone.

[0222] Specific examples

[0223] For example, suppose a user is driving a long distance with their pet and the pet steps onto the smart scale inside the car. The scale measures the pet's weight and sends the data to a server in real time. The data is stored in a database and compared with past data to analyze whether there are any abnormal weight fluctuations. If there is a sudden weight loss, the server will use the analysis results to display an alert on the car's display saying, "A sudden weight fluctuation has been detected. Please consult a veterinarian."

[0224] Prompt Sentence Examples

[0225] "Design a real-time alert system that analyzes this pet's health data and notifies the user if there are any abnormalities."

[0226] "Create a program that monitors your pet's weight fluctuations, food intake, exercise, and elimination, and generates alerts if it detects any abnormalities."

[0227] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0228] Step 1:

[0229] The device uses sensors to collect data on your pet's behavior (e.g., food intake, exercise, weight, and excretion status). This data is recorded in different formats depending on the type of sensor, but it is all time-stamped. For example, the weight measured by a smart scale and the time of measurement are generated as data.

[0230] Step 2:

[0231] The terminal transmits the collected data to the vehicle's central processing unit (CPU). During this process, the data is periodically stored in a buffer and transmitted in batches at regular intervals. The input here is the terminal data, and the output is the data transmitted to the vehicle CPU.

[0232] Step 3:

[0233] The server stores the data received from the CPU in a database (e.g., MySQL). During this storage process, the data is categorized by pet and organized chronologically. The input is data from the CPU, and the output is the information stored in the database.

[0234] Step 4:

[0235] The server analyzes the stored data using a real-time data analysis system (e.g., Apache Kafka). This analysis detects sudden changes in weight and abnormal decreases or increases in exercise volume. The input is data obtained from the database, and the output is the analysis result, indicating whether or not there are any abnormalities.

[0236] Step 5:

[0237] If the server detects an abnormality based on the analysis results, it sends an alert to the user via the notification system. This alert is displayed on the vehicle's display or on a smartphone app. The input is the analysis results, and the output is an alert notification to the user interface.

[0238] Step 6:

[0239] The user checks the received alert notification and learns that there is something wrong with their pet's health. Specific actions include checking the notification displayed on the vehicle's display or receiving a push notification on their smartphone. The input here is the alert notification, and the output is the user's action (for example, contacting a veterinarian).

[0240] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0241] The present invention relates to an automatic conditioning note system for recording pet lifestyle habits and analyzing health conditions. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the system is able to appropriately adjust notification content according to the user's emotional state. A specific embodiment of the system is shown below.

[0242] System configuration

[0243] The system includes multiple terminals, a server, a user interface, and an emotion engine to monitor, record, and analyze pet behavior and health. Each terminal automatically records the pet's food intake, exercise, weight, and excretion status.

[0244] Terminal

[0245] The terminal consists of the following devices:

[0246] 1. Smart scale

[0247] When your pet steps on the scale, its weight is measured and the data is recorded along with a timestamp.

[0248] 2. Automatic feeder

[0249] Every time your pet eats, the amount of food eaten is recorded and the data is saved with a timestamp.

[0250] 3. Pet Activity Monitor

[0251] Attached to a collar or harness, it measures the pet's activity, specifically recording data such as the number of steps taken, distance traveled, and calories burned.

[0252] 4. Smart Toilet

[0253] Record data on the number of times your pet goes to the toilet, the time it takes, and the amount and condition of its waste.

[0254] server

[0255] The server is the main processor that receives, stores, and analyzes data sent from the device.

[0256] 1. Data Receipt and Storage

[0257] The server receives the data sent by the device in real time and stores it in a database for each pet. It also validates the data to check for any irregularities.

[0258] 2. Data Analysis

[0259] The server analyzes the stored data and evaluates the pet's health, particularly checking for changes in weight, activity levels, and abnormalities in excretion.

[0260] 3. Anomaly Detection

[0261] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[0262] 4. Emotion Engine

[0263] The server analyzes the user's emotions from their voice and facial expressions through an emotion engine, and adjusts the message sent when an abnormality is notified according to their emotional state. The emotion engine evaluates the user's emotional state in real time and provides appropriate countermeasures.

[0264] User Interface

[0265] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[0266] 1. Displaying data

[0267] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[0268] 2. Alert Notifications

[0269] If an anomaly is detected, the user will receive an alert via push notification or email, and the emotion engine will analyze the user's emotional state and provide appropriate message content.

[0270] Program processing

[0271] Terminal

[0272] The devices collect and transmit data. For example, when a pet steps on a scale, it automatically measures its weight and sends the data to a server. Similarly, an automatic feeder records food intake, and an activity monitor measures exercise. Each device collects data along with a timestamp and sends it to the server.

[0273] server

[0274] The server centrally manages all data sent from the devices and stores it in a database. It then uses algorithms to analyze the data and check for abnormalities in weight fluctuations, exercise volume, excretion status, etc. If an abnormality is detected, the server generates an alert and, after analyzing the user's emotional state with an emotion engine, determines the appropriate notification content.

[0275] User

[0276] Users can check their pet's condition using a smartphone app. The app sends data requests to the server and displays the latest information. The app's intuitive interface provides detailed statistical data and graphs on food intake, exercise, weight, and excretion status. If an abnormality is detected, an emotion engine generates a message that takes the user's emotions into consideration and advises on how to respond.

[0277] Specific examples

[0278] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to the server. The server then compares the data with the previous measurement and analyzes it for any abnormal fluctuations. If there is a sudden weight loss, the emotion engine analyzes the user's voice and facial expressions and generates a message based on the level of urgency. For example, if the user is already stressed or anxious, a notification will be sent stating, "A sudden weight fluctuation has been detected. Please remain calm and consult a veterinarian first." The user can open the app, check the detailed data, and contact a veterinarian if necessary, enabling quick and effective health management of their pet.

[0279] As a result, the present invention not only helps manage the health of pets, but also reduces the psychological burden on users and helps build a better relationship between pets and their owners.

[0280] The processing flow will be explained below.

[0281] Step 1:

[0282] The device will measure your pet's weight.

[0283] When a pet steps onto the smart scale, the device uses sensors to measure its weight, timestamps the data, and stores it in its internal memory.

[0284] Step 2:

[0285] The device records the amount of food consumed.

[0286] When your pet eats from the automatic feeder, the device records the amount of food fed and a timestamp, and stores it in its internal memory.

[0287] Step 3:

[0288] The device measures the amount of exercise.

[0289] The pet activity monitor collects your pet's exercise data (steps, distance traveled, calories burned, etc.) in real time and stores it in its internal memory along with a timestamp.

[0290] Step 4:

[0291] The device records the excretion status.

[0292] When your pet uses the smart toilet, the device records the number of times it defecates and a timestamp, and if necessary, stores the amount and condition of the waste in its internal memory.

[0293] Step 5:

[0294] The terminal transmits the collected data to the server.

[0295] At regular intervals or when a specific event occurs (for example, immediately after the pet steps on the scale), the device sends the collected data to a server via Internet communication.

[0296] Step 6:

[0297] The server receives and stores the data.

[0298] The server receives the data sent from the device in real time, validates the data, and then stores it in a database for each pet.

[0299] Step 7:

[0300] The server analyzes the data.

[0301] The server periodically analyzes the stored data to detect sudden changes in weight, abnormalities in exercise, abnormalities in excretion, etc. For example, if a sudden decrease in weight over a short period of time is confirmed, it will detect this as an abnormality.

[0302] Step 8:

[0303] The server detects the abnormality and activates the emotion engine.

[0304] Based on the detected anomaly, the server activates the emotion engine and analyzes the user's emotions from their voice and facial expressions. The emotion engine evaluates the user's emotional state in real time.

[0305] Step 9:

[0306] The server notifies the user based on the result of the emotion engine.

[0307] Based on the analysis results of the emotion engine, the server generates a message offering the user the best course of action. For example, if the user is already stressed, the server may send a notification saying, "A sudden weight fluctuation has been detected. Please stay calm and consult your veterinarian."

[0308] Step 10:

[0309] The user checks the data in the app and takes action.

[0310] The user opens the smartphone app, retrieves the latest data from the server, and visually checks it. The app displays information on the pet's food intake, exercise, weight, excretion status, and a series of abnormalities and emotional analysis results. Based on this information, the user can take appropriate measures, such as contacting a veterinarian for advice.

[0311] Example 2

[0312] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0313] Pet health management is extremely important in today's world, but accurately understanding a pet's health condition requires collecting and appropriately analyzing a large amount of data. Users must also respond quickly and appropriately to any abnormalities in their pets, which requires notifications that take the user's emotional state into consideration. However, conventional systems do not adequately collect and analyze pet lifestyle data, and do not provide notifications that take the user's emotional state into consideration. As a result, pet health management is not adequately managed, placing an excessive psychological burden on users.

[0314] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0315] In this invention, the server includes means for recording the amount of food eaten by the pet, means for recording the amount of exercise the pet does, means for recording the weight of the pet, means for recording the excretion status of the pet, means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities, means for analyzing the emotional state of the user, and means for adjusting the content of notifications according to the emotional state of the user when an abnormality is detected. This allows for the collection and analysis of detailed data on the pet's lifestyle habits and for appropriate notifications to be provided taking the user's emotional state into consideration. This allows for effective and prompt health management of the pet and reduces the psychological burden on the user.

[0316] The "means for recording pet food intake" is a device that automatically measures the amount of food consumed by a pet, and stores the data with a timestamp.

[0317] The "means for recording the amount of exercise of a pet" is a device that measures and records data related to the exercise of a pet, such as the number of steps taken, distance traveled, and calories burned.

[0318] The "means for recording a pet's weight" is a device that automatically measures a pet's weight when the pet steps onto the measuring device, and stores the data with a timestamp.

[0319] A "means for recording pet excretion status" is a device that records data regarding the number of times and time when a pet uses the toilet, as well as the amount and condition of excrement.

[0320] "Means for analyzing the health condition of a pet based on the recorded data and detecting abnormalities" refers to algorithms and software for detecting the health condition and abnormalities of a pet by analyzing the recorded data.

[0321] The "means for analyzing the user's emotional state" refers to algorithms and software for analyzing the user's voice and facial expression data and assessing the user's emotional state in real time.

[0322] The "means for adjusting the notification content according to the user's emotional state when an abnormality is detected" refers to algorithms and software for changing the notification content taking into account the user's current emotional state when an abnormality is detected in the pet.

[0323] The present invention relates to an automatic conditioning note system for recording pets' lifestyle habits and analyzing their health condition. It also features an emotion engine that recognizes the user's emotions, allowing it to appropriately adjust notification content according to the user's emotional state.

[0324] System configuration

[0325] The system includes multiple terminals, a server, a user interface, and an emotion engine for monitoring, recording, and analyzing pet behavior and health. Each terminal automatically records the pet's food intake, exercise, weight, and excretion status. Details are provided below.

[0326] Terminal

[0327] A terminal consists of the following devices:

[0328] 1. Smart scale

[0329] When your pet steps on the scale, it automatically measures their weight, stores the data with a timestamp, and sends it to a server via Wi-Fi or Bluetooth.

[0330] 2. Automatic feeder

[0331] Every time your pet eats, the amount of food is measured and stored with a timestamp, and this data is also sent to a server via Wi-Fi or Bluetooth.

[0332] 3. Pet Activity Monitor

[0333] Attached to a collar or harness, it measures your pet's activity in real time, and sends the data to a server at regular intervals.

[0334] 4. Smart Toilet

[0335] When your pet uses the litter box, data on the number of times, duration, amount and condition of the waste is recorded and sent to a server via Wi-Fi or Bluetooth.

[0336] server

[0337] The server receives and centralizes the data sent from the devices in real time. The data is processed in the following ways:

[0338] 1. Data Receipt and Storage

[0339] The data sent from the device is received in real time and stored in a database for each pet, while data validation is also performed to check for any fraudulent data.

[0340] 2. Data Analysis

[0341] The stored data is analyzed using an algorithm to check for fluctuations in weight, changes in activity, and abnormalities in excretion.

[0342] 3. Anomaly Detection

[0343] Anomalies are detected based on the analysis results and users are notified as necessary.

[0344] 4. Emotion Engine

[0345] Analyzes the user's voice and facial expression data to evaluate the user's emotional state in real time, and adjusts the message content when an abnormality is notified according to the user's emotional state.

[0346] User Interface

[0347] Users can use their smartphones or computers to check the information provided by the system and take the necessary action:

[0348] 1. Displaying data

[0349] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[0350] 2. Alert Notifications

[0351] If an anomaly is detected, you will receive an alert via push notification or email. The emotion engine will analyze the user's emotional state and provide appropriate message content.

[0352] Specific examples

[0353] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to the server. The server receives this data in real time and compares it with the previous measurement data. If there is a sudden weight loss, the emotion engine analyzes the user's voice and facial expressions and generates a message according to the level of urgency.

[0354] For example, if the user is already stressed or anxious, a message will be generated saying, "Sudden weight loss has been detected. Please stay calm and consult a veterinarian." The user can then open the smartphone app, check the detailed data, and contact a veterinarian if necessary.

[0355] Prompt Sentence Examples

[0356] Here are some examples of prompts to input to the generative AI model:

[0357] "If a pet loses weight suddenly, generate a notification message that takes into account the user's emotional state."

[0358] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0359] Program processing flow

[0360] Step 1: Data collection

[0361] Terminal

[0362] The device collects various data about your pet, including its weight, how much it eats, how much it exercises, and its excretion habits.

[0363] Input: Pet weight, food intake, exercise activity, toilet use

[0364] Output: weight data, food intake data, exercise data, excretion data

[0365] Specific operations: The smart scale measures weight and stores the data in its internal memory with a timestamp. The automatic feeder measures food intake and stores the data with a timestamp. The activity monitor measures exercise volume and stores the data with a timestamp. The smart toilet records bowel movements and stores the data with a timestamp.

[0366] Step 2: Send data

[0367] Terminal

[0368] The device sends the collected data to a server via Wi-Fi or Bluetooth.

[0369] Input: weight data, food intake data, exercise data, excretion data

[0370] Output: Various data sent to the server

[0371] Specific operation: Collected data is sent to the server via Wi-Fi or Bluetooth at regular intervals. For example, every time a pet steps on the scale, the data is sent to the server immediately.

[0372] Step 3: Receiving and storing data

[0373] server

[0374] The server receives the data sent from the terminal in real time and stores it in a database.

[0375] Input: weight data, food intake data, exercise data, excretion data

[0376] Output: Saved database entries

[0377] Specific behavior: The server validates the received data and stores it in the database, for example, checking for invalid or missing data and storing only accurate data.

[0378] Step 4: Data analysis

[0379] server

[0380] The server analyzes the stored data and assesses the pet's health.

[0381] Input: Saved weight data, food intake data, exercise data, excretion data

[0382] Output: Analysis results (health status assessment, abnormality detection)

[0383] Specific operation: The system uses an algorithm to analyze data and detect weight fluctuations, changes in activity, and abnormalities in excretion. For example, it checks weight fluctuations over the past week and evaluates whether there are any sudden increases or decreases.

[0384] Step 5: Detect anomalies and generate notifications

[0385] server

[0386] The server detects anomalies based on the analysis results and generates messages to notify the user as needed, taking into account the user's emotional state using an emotion engine.

[0387] Input: Analysis results (health status assessment, abnormality detection), user emotional state data

[0388] Output: Notification message to send to the user

[0389] Specific behavior: If an abnormality is detected, the server uses the emotion engine to analyze the user's voice and facial expressions and generate an appropriate message. For example, if the user is stressed, the server generates a message saying, "Sudden weight loss has been detected. Please stay calm and consult a veterinarian."

[0390] Step 6: Receive notifications and respond

[0391] User

[0392] Users receive notifications on their smartphones or computers to check their pet's status.

[0393] Input: Notification message, application data request

[0394] Output: Detailed data displayed in the application, user's response actions

[0395] Specific behavior: The user taps the notification to open the app and view detailed health data. If necessary, the user can take appropriate action, such as contacting a veterinarian. For example, the user can view a graph of their pet's weight over time in the app and identify the cause of any abnormalities.

[0396] The above is the specific processing flow of the program of this system.

[0397] (Application example 2)

[0398] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0399] Conventional pet health management systems have the problem that data recording and analysis are one-way, and notifications do not take into account the user's emotional state, which increases the psychological burden on the user. Furthermore, when an abnormality is detected, the response is left up to the user, making it difficult to determine the level of urgency. Furthermore, security services also require flexible responses that take into account the user's emotions.

[0400] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0401] In this invention, the server includes means for recording the amount of food eaten by the pet, means for recording the amount of exercise the pet does, means for recording the weight of the pet, means for recording the excretion status of the pet, means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities, means for notifying the user when an abnormality is detected, and means for analyzing the user's emotions and generating notification content according to the emotions. This makes it possible to both manage the health of the pet and reduce the psychological burden on the user, and also enables flexible responses in security services.

[0402] The "means for recording the amount of food eaten by a pet" is a device for recording the amount of food eaten by a pet each time the pet eats a meal and saving the data together with a timestamp.

[0403] A "means for recording a pet's exercise volume" is a device that is attached to a pet's collar or harness and records exercise data such as the number of steps taken, distance traveled, and calories burned.

[0404] The "means for recording pet weight" is a device that measures the weight of a pet when it gets on the platform and records the data along with a timestamp.

[0405] A "means for recording pet excretion status" is a device that records data regarding the number of times and time a pet uses the toilet, as well as the amount and condition of excrement.

[0406] The "means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities" refers to an algorithm that analyzes the collected data and detects abnormalities in the pet's health condition based on changes in weight, amount of exercise, excretion status, etc.

[0407] The "means for notifying the user when an abnormality is detected" is a system that sends a warning message to the user via push notification or email when an abnormality is detected.

[0408] "Means for analyzing the user's emotions and generating notification content according to the emotions" refers to a system that uses an emotion analysis engine to evaluate the user's voice and facial expressions and adjusts the notification message to match their emotional state.

[0409] This invention is an automatic conditioning note system for recording pet lifestyle habits and analyzing health conditions, and reduces the psychological burden on users by using an emotion engine to notify them according to their emotional state. Furthermore, by applying this system to security services, it can realize flexible responses according to the user's emotional state.

[0410] System configuration

[0411] Terminal

[0412] The terminal consists of the following devices:

[0413] 1. Smart scale

[0414] When your pet steps on the scale, it automatically measures its weight and sends the data to a server, along with a timestamp.

[0415] 2. Automatic feeder

[0416] Every time your pet eats, the amount of food eaten is recorded and sent to a server, also with a timestamp.

[0417] 3. Pet Activity Monitor

[0418] Attached to a collar or harness, it measures the pet's activity, recording steps taken, distance traveled, calories burned, and more.

[0419] 4. Smart Toilet

[0420] Data on how many times and for how long your pet uses the litter box, as well as the amount and condition of the waste, is recorded and sent to a server.

[0421] server

[0422] The server is the main processor that receives, stores, and analyzes data sent from the device.

[0423] 1. Data Receipt and Storage

[0424] The server receives data sent from the device in real time and stores it in a database for each pet. It also validates the data and detects and eliminates fraudulent data.

[0425] 2. Data Analysis

[0426] The server analyzes the stored data and evaluates the pet's health, checking for weight fluctuations, changes in activity, and abnormalities in excretion.

[0427] 3. Anomaly Detection

[0428] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[0429] 4. Emotion Engine

[0430] The server analyzes the user's emotions from their voice and facial expressions through an emotion engine, adjusts the message when an abnormality is notified based on their emotional state, evaluates their emotional state in real time, and provides appropriate countermeasures.

[0431] User Interface

[0432] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[0433] 1. Displaying data

[0434] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[0435] 2. Alert Notifications

[0436] If an anomaly is detected, the user will receive an alert via push notification or email, and the emotion engine will analyze the user's emotional state and provide appropriate message content.

[0437] Specific examples

[0438] For example, if a motion sensor in the living room detects suspicious activity while the user is out, the security camera captures the video, the EmotionRecognizer detects the user's stress level, and the NotificationSystem sends a message saying, "Suspicious activity has been detected in the living room. Please check immediately."

[0439] Examples of prompt statements

[0440] If the motion sensor in the living room detects suspicious activity while the family is out, analyze the emotional state of the user when they open the app and generate an appropriate notification message.

[0441] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0442] Step 1:

[0443] The terminal collects data from various devices (smart scales, automatic feeders, pet activity monitors, and smart toilets). Each device measures and records data on pet behavior and status (weight, food intake, exercise, and excretion status) with a timestamp. This data is sent to the server in real time.

[0444] Input: Pet's lifestyle data

[0445] Output: Sending recorded data to a server

[0446] Step 2:

[0447] The server receives data from the device in real time and stores it in a database for each pet. At this time, it validates the data and rejects any invalid data.

[0448] Input: Data sent from the terminal

[0449] Output: Validated data saved to the database

[0450] Step 3:

[0451] The server analyzes the stored data and assesses the pet's health, specifically by using algorithms to analyze changes in the pet's weight, activity level, and abnormalities in excretion.

[0452] Input: Data stored in a database

[0453] Output: Analysis results on pet health

[0454] Step 4:

[0455] The server detects abnormalities based on the analysis results, such as a sudden weight loss or an extreme decrease in exercise volume, and identifies the abnormality.

[0456] Input: Analysis results

[0457] Output: Anomaly detection alert

[0458] Step 5:

[0459] If an anomaly is detected, the server uses an emotion engine to analyze the user's emotions, collecting voice and facial expression data to evaluate the user's emotions in real time.

[0460] Input: User's voice and facial expression data

[0461] Output: User's emotional state

[0462] Step 6:

[0463] The server adjusts the notification message depending on the user's emotional state and sends the appropriate notification to the user, for example, if the user is stressed, it sends a gentle, soothing message.

[0464] Input: Anomaly detection alerts and user emotional state

[0465] Output: A notification message to the user

[0466] Step 7:

[0467] Users can then open the app based on the notification to view details of their pet's health, and the app will visually display the latest data and analysis results, prompting them to take any necessary action.

[0468] Input: Notification messages and application access

[0469] Output: Detailed health status data and analysis results

[0470] This makes it possible to realize a system that not only manages the health of pets, but also reduces the psychological burden on users and provides appropriate countermeasures.

[0471] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0472] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0473] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0474] [Second embodiment]

[0475] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0476] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0477] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0478] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0479] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0480] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0481] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0482] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0483] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0484] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0485] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0486] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0487] The present invention relates to an automatic conditioning note system for recording the lifestyle habits of pets and analyzing their health conditions. Specific embodiments of the system are described below.

[0488] System configuration

[0489] The system includes multiple devices, a server, and a user interface to monitor, record, and analyze pet behavior and health. Each device automatically records the pet's food intake, exercise, weight, and excretion status.

[0490] Terminal

[0491] The terminal is composed of various devices such as:

[0492] 1. Smart scale

[0493] When your pet steps on the scale, its weight is measured and the data is recorded along with a timestamp.

[0494] 2. Automatic feeder

[0495] Every time your pet eats, the amount of food eaten is recorded and the data is saved with a timestamp.

[0496] 3. Pet Activity Monitor

[0497] Attached to a collar or harness, it measures the pet's activity, specifically recording data such as the number of steps taken, distance traveled, and calories burned.

[0498] 4. Smart Toilet

[0499] Record data on the number of times your pet goes to the toilet, the time it takes, and the amount and condition of its waste.

[0500] server

[0501] The server is the main processor that receives, stores, and analyzes data sent from the device.

[0502] 1. Data Receipt and Storage

[0503] The server receives the data sent by the device in real time and stores it in a database for each pet.

[0504] 2. Data Analysis

[0505] The server analyzes the stored data and evaluates the pet's health, particularly checking for weight fluctuations, changes in activity, and abnormalities in elimination frequency.

[0506] 3. Anomaly Detection

[0507] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[0508] User Interface

[0509] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[0510] 1. Displaying data

[0511] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[0512] 2. Alert Notifications

[0513] If an anomaly is detected, users can receive alerts via push notification or email.

[0514] Program processing

[0515] Terminal

[0516] The device collects and transmits data. Specifically, when a pet steps on the scale, it automatically measures its weight and sends the data to the server. Similarly, the automatic feeder records the pet's food intake, and the activity monitor measures its exercise. This information is then sent to the server.

[0517] server

[0518] The server centrally manages all data sent from the devices and stores it in a database. It then uses algorithms to analyze the data and check for any abnormalities in weight fluctuations, exercise volume, excretion status, etc. For example, if the server detects a sudden change in weight over a short period of time or an abnormal change in exercise patterns, it generates an alert and notifies the user.

[0519] User

[0520] Users can check their pet's condition using a smartphone app. The app sends data requests to the server and displays the latest information. The app's intuitive interface provides detailed statistical data and graphs on food intake, exercise, weight, and excretion status. If any abnormalities are detected, the app notifies the user with specific countermeasures.

[0521] Specific examples

[0522] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to a server. The server then compares the data with the previous measurement and analyzes it for any abnormal fluctuations. If there is a sudden weight loss, the user receives an alert notification on their smartphone app saying, "Sudden weight fluctuations have been detected. Please consult a veterinarian." The user can open the app, check the detailed data, and contact a veterinarian if necessary. In this way, users can monitor their pet's health in real time and respond quickly to any abnormalities.

[0523] As described above, the present invention enables detailed data collection and analysis to assist in the health management of pets, and enables prompt notification of abnormalities.

[0524] The processing flow will be explained below.

[0525] Step 1:

[0526] The device will measure your pet's weight.

[0527] When a pet steps onto the smart scale, the device uses sensors to measure its weight, timestamps the data, and stores it in its internal memory.

[0528] Step 2:

[0529] The device records the amount of food consumed.

[0530] When your pet eats from the automatic feeder, the device records the amount of food fed and a timestamp, and stores it in its internal memory.

[0531] Step 3:

[0532] The device measures the amount of exercise.

[0533] The pet activity monitor collects your pet's exercise data (steps, distance traveled, calories burned, etc.) in real time and stores it in its internal memory along with a timestamp.

[0534] Step 4:

[0535] The device records the excretion status.

[0536] When your pet uses the smart toilet, the device records the number of times it defecates and a timestamp, and if necessary, stores the amount and condition of the waste in its internal memory.

[0537] Step 5:

[0538] The terminal transmits the collected data to the server.

[0539] At regular intervals or when a specific event occurs (for example, immediately after a pet steps on the scale), the device sends the collected data to a server via Internet communication.

[0540] Step 6:

[0541] The server receives and stores the data.

[0542] The server receives data sent from the device in real time and stores it in a database for each pet. It also validates the data to check for any irregularities.

[0543] Step 7:

[0544] The server analyzes the data.

[0545] The server analyzes the stored data periodically or on an event-driven basis, checking for abnormalities in weight fluctuations, exercise volume, excretion status, etc. If a problem is detected, an alert is generated.

[0546] Step 8:

[0547] The server detects the abnormality and notifies the user.

[0548] If the server detects an anomaly based on the analysis results, it will send an alert to the user via email or push notification, which will also include detailed information about the anomaly.

[0549] Step 9:

[0550] The user checks the data in the app.

[0551] The user opens the smartphone app, retrieves the latest data from the server, and visually checks it. The app displays detailed data such as food intake, exercise, weight, and excretion status, as well as an overview of any abnormalities.

[0552] Step 10:

[0553] The user handles the abnormality.

[0554] The user receives an alert notification from the server, checks the details, and takes appropriate action, such as taking their pet to the vet.

[0555] Example 1

[0556] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0557] Managing pet health is an important issue for pet owners, and early detection of illness is especially important. However, detailed monitoring of a pet's health requires the collection and analysis of a wide range of data, including food intake, exercise, weight, and excretion patterns. Conventional methods require manually recording this data, which is laborious and time-consuming and can be inaccurate. Furthermore, even if an abnormality is discovered, it is difficult to respond immediately, increasing the risk to the pet's health.

[0558] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0559] In this invention, the server includes means for recording the amount of food eaten by the pet, means for recording the amount of exercise the pet does, means for recording the weight of the pet, means for recording the excretion status of the pet, means for transmitting the recorded data, means for storing the received data, means for analyzing the stored data and evaluating the health status of the pet, means for detecting abnormalities based on the analysis results, and means for notifying the user when an abnormality is detected. This makes it possible to closely monitor the health status of the pet in real time and quickly notify the user when an abnormality is discovered. Furthermore, the user can easily check this data through an intuitive interface and take prompt action.

[0560] A "means for recording pet food intake" is a device that automatically measures the amount of food consumed by a pet and stores the data.

[0561] The "means for recording the amount of exercise of a pet" is a device that measures the amount of exercise that a pet performs and records the data.

[0562] A "means for recording a pet's weight" is a device that measures a pet's weight and stores the data.

[0563] A "means for recording pet excretion status" is a device that records the frequency and content of a pet's excretion.

[0564] The "means for transmitting recorded data" is a device that transmits collected data to a central management device such as a server.

[0565] "Means for storing received data" is a device that stores the transmitted data in a local database.

[0566] The "means for analyzing the stored data and assessing the health condition of the pet" refers to algorithms or software for assessing the health condition of the pet using the stored data.

[0567] "Means for detecting anomalies based on analysis results" refers to a mechanism for identifying abnormal patterns or values ​​from analyzed data.

[0568] The "means for notifying the user when an abnormality is detected" refers to a device or system that notifies the user of the information when an abnormality is discovered.

[0569] The present invention relates to an automatic conditioning note system for recording the lifestyle habits of pets and analyzing their health conditions. Specific embodiments of the system are described below.

[0570] System configuration

[0571] The system includes multiple devices, a server, and a user interface to monitor, record, and analyze pet behavior and health status. The following terminals are used:

[0572] Terminal

[0573] 1. Smart scale

[0574] The smart scale measures the pet's weight when it steps on the scale, records the data with a timestamp, and transmits the data to a server via Wi-Fi or Bluetooth.

[0575] 2. Automatic feeder

[0576] The automatic feeder measures the amount of food your pet eats and records the data with a timestamp, which is then sent to a server via Wi-Fi or Bluetooth.

[0577] 3. Pet Activity Monitor

[0578] The activity monitor is attached to a collar or harness and records the pet's activity, such as steps taken, distance traveled, and calories burned, and the data is also sent to a server.

[0579] 4. Smart Toilet

[0580] The smart toilet records the number of times your pet goes to the toilet, the time it takes, and the amount and condition of the waste, and sends the data to a server via Wi-Fi or Bluetooth.

[0581] server

[0582] The server receives the data sent from the terminals and manages it in a unified manner.

[0583] 1. Data Receipt and Storage

[0584] The server receives the data sent from the device in real time and stores it in a database for each pet.

[0585] 2. Data Analysis

[0586] The server uses algorithms to analyze the stored data, particularly for weight fluctuations, changes in activity levels, and abnormal bowel movements. For example, if a sudden weight loss or abnormal movement patterns are detected, an alert will be generated.

[0587] 3. Anomaly Detection

[0588] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[0589] User Interface

[0590] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[0591] 1. Displaying data

[0592] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[0593] 2. Alert Notifications

[0594] If an anomaly is detected, users can receive alerts via push notification or email.

[0595] Specific examples

[0596] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to a server. The server then compares the data with the previous measurement and analyzes it for any abnormal fluctuations. If there is a sudden weight loss, the user will receive an alert notification on their smartphone app saying, "Sudden weight fluctuations have been detected. Please consult a veterinarian." The user can then open the app, check the detailed data, and contact a veterinarian if necessary.

[0597] Prompt Sentence Examples

[0598] You can generate a report on your pet's health by inputting the following prompts into the generative AI model:

[0599] Prompt statement:

[0600] Generate detailed reports on your pet's health using data from your automated pet conditioning notes system, including:

[0601] body weight

[0602] Amount of food

[0603] Exercise volume (steps, distance traveled, calories burned)

[0604] Excretion status (number of times, condition of excrement)

[0605] Please also mention any sudden weight fluctuations or changes in exercise patterns. We will assess your pet's health and recommend any necessary measures.

[0606] Using this prompt, the generative AI model can create a specific and detailed report on the pet's health.

[0607] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0608] Step 1: Data collection

[0609] The devices collect data on the pet's behavior and health. When a user places their pet on a smart scale, the scale measures the pet's weight and records the data with a timestamp. Similarly, an automatic feeder measures the amount of food a pet eats, and a pet activity monitor records the number of steps taken, distance traveled, and calories burned. A smart toilet records the number of times the pet defecates, the time, and the amount and condition of the waste. The input is the data measured by each device, and the output is this data recorded with a timestamp.

[0610] Step 2: Send data

[0611] The devices send the data they collect to a server. Smart scales, automatic feeders, pet activity monitors, and smart toilets all send data to a server via Wi-Fi or Bluetooth. The input is the recorded data with a timestamp, and the output is the data being sent to the server.

[0612] Step 3: Receiving and storing data

[0613] The server receives the data sent from the terminal and manages it in a unified manner. The received data is stored in a database and classified for each pet. The input is the data sent from the terminal, and the output is that this data is stored in the server's database.

[0614] Step 4: Data analysis

[0615] The server uses the stored data to analyze the pet's health. During the data analysis process, algorithms are used to check for weight fluctuations, changes in activity levels, and abnormalities in excretion. For example, sudden weight fluctuations and abnormal movement patterns are detected. The input is the stored data, and the output is various health indicators and abnormality detection results.

[0616] Step 5: Anomaly detection

[0617] The server detects anomalies from the analyzed data. If a sudden weight gain or loss or an abnormal exercise pattern is found, it is deemed to be an anomaly. The input is the analysis results, and the output is information tagged as an anomaly. Specifically, if a sudden weight loss is detected, for example, it is tagged as "sudden weight loss."

[0618] Step 6: User Notification

[0619] The server notifies the user if an abnormality is detected. When an abnormality is detected, a push notification is sent to the user's smartphone or email. The input is the abnormality detection result, and the output is a notification message to the user. For example, a notification may be sent saying, "A sudden weight fluctuation has been detected. Please consult a veterinarian."

[0620] Step 7: Data display

[0621] Users access the system using a smartphone or computer to view and check data. Data on weight, food intake, exercise, and excretion status can be visually checked as graphs and statistical information through an app or web interface. The input is the saved data and analysis results, and the output is a screen where the user can check the visualized data. For example, a graph showing the weight fluctuations of a pet over the past week is displayed.

[0622] (Application example 1)

[0623] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0624] It is important to reliably monitor the health of pets when traveling or driving long distances with pets, but conventional systems have had difficulty monitoring the health of pets in the vehicle in real time. Furthermore, there is no means of quickly notifying the user when an abnormality is detected, which tends to result in delayed response. There is a need for a new monitoring system that can solve these issues and ensure the safety and health of pets.

[0625] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0626] In this invention, the server includes a means for recording the amount of food eaten, a means for recording the amount of exercise, a means for recording the weight, a processing means in the vehicle for receiving, saving, and analyzing the data in real time, a means for analyzing the health condition of the pet based on the analyzed data and detecting abnormalities, and a notification means mounted in the vehicle for notifying the user when an abnormality is detected. This makes it possible to monitor the health condition of the pet in the vehicle in real time, and to quickly notify the user when an abnormality occurs.

[0627] "Pet lifestyle" refers to the daily activities of pets, such as eating, exercise, weight changes, and excretory behavior.

[0628] An "automatic conditioning note system" is a system that automatically records a pet's lifestyle habits, analyzes its health condition, and notifies the user if any abnormalities are detected.

[0629] "Means for recording food intake" refers to a device or sensor that automatically measures and records the amount of food consumed by a pet.

[0630] "Means for recording physical activity" refers to devices or sensors that automatically measure and record a pet's physical activity.

[0631] "Weight recording means" refers to a device that automatically measures and records a pet's weight.

[0632] "Means for recording excretion status" refers to a device that automatically measures and records the frequency and amount of pet excretion.

[0633] "Processing means for receiving, storing, and analyzing data in real time" refers to a processing system for receiving data sent from a terminal, storing it, and instantly analyzing it to determine the health condition of a pet.

[0634] "Means for detecting abnormalities" refers to algorithms and analytical methods for detecting abnormalities in health status based on recorded data.

[0635] "Means for notifying" refers to a means for notifying the user of a detected abnormality, and includes methods such as push notifications to a smartphone or displaying the information on the vehicle's display.

[0636] "Notification means installed in the vehicle" refers to a means for notifying the driver using an in-vehicle display or alert system when a pet shows signs of abnormal health.

[0637] The present invention relates to an automatic conditioning note system for recording pet lifestyle habits and analyzing their health status. This system monitors and notifies users to ensure the health of their pets in an autonomous vehicle. Specific embodiments of the system are described below.

[0638] System configuration

[0639] The system includes multiple sensors, a server, and a user interface to monitor, record, and analyze pet behavior and health. Each sensor automatically records the pet's food intake, exercise, weight, and excretion status.

[0640] sensor

[0641] The sensor consists of various devices such as:

[0642] 1. Smart scale

[0643] When your pet steps on the scale, its weight is measured and the data is recorded along with a timestamp.

[0644] 2. Automatic feeder

[0645] Every time your pet eats, the amount of food eaten is recorded and the data is saved with a timestamp.

[0646] 3. Pet Activity Monitor

[0647] Attached to a collar or harness, it measures the pet's activity, specifically recording data such as the number of steps taken, distance traveled, and calories burned.

[0648] 4. Smart Toilet

[0649] Record data on the number of times your pet goes to the toilet, the time it takes, and the amount and condition of its waste.

[0650] server

[0651] The server is the main processor that receives, stores, and analyzes the data sent from the sensors. Specific use cases are shown below.

[0652] 1. Data Receipt and Storage

[0653] The server receives the data sent by the sensors in real time and stores it in a database (e.g., MySQL) for each pet.

[0654] 2. Data Analysis

[0655] The server analyzes the stored data using a real-time data analysis system (e.g., Apache Kafka) to assess the pet's health, particularly by checking for changes in weight, activity levels, and abnormalities in defecation frequency.

[0656] 3. Anomaly Detection

[0657] The server detects abnormalities based on the analysis results, and if an abnormality is detected, it alerts the user via a notification system installed in the vehicle.

[0658] User Interface

[0659] Users can use their smartphone or the vehicle's on-board display to check the information provided by the system and take any necessary action.

[0660] 1. Displaying data

[0661] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[0662] 2. Alert Notifications

[0663] If an abnormality is detected, the user can receive an alert via push notification on the vehicle's display or smartphone.

[0664] Specific examples

[0665] For example, suppose a user is driving a long distance with their pet and the pet steps onto the smart scale inside the car. The scale measures the pet's weight and sends the data to a server in real time. The data is stored in a database and compared with past data to analyze whether there are any abnormal weight fluctuations. If there is a sudden weight loss, the server will use the analysis results to display an alert on the car's display saying, "A sudden weight fluctuation has been detected. Please consult a veterinarian."

[0666] Prompt Sentence Examples

[0667] "Design a real-time alert system that analyzes this pet's health data and notifies the user if there are any abnormalities."

[0668] "Create a program that monitors your pet's weight fluctuations, food intake, exercise, and elimination, and generates alerts if it detects any abnormalities."

[0669] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0670] Step 1:

[0671] The device uses sensors to collect data on your pet's behavior (e.g., food intake, exercise, weight, and excretion status). This data is recorded in different formats depending on the type of sensor, but it is all time-stamped. For example, the weight measured by a smart scale and the time of measurement are generated as data.

[0672] Step 2:

[0673] The terminal transmits the collected data to the vehicle's central processing unit (CPU). During this process, the data is periodically stored in a buffer and transmitted in batches at regular intervals. The input here is the terminal data, and the output is the data transmitted to the vehicle CPU.

[0674] Step 3:

[0675] The server stores the data received from the CPU in a database (e.g., MySQL). During this storage process, the data is categorized by pet and organized chronologically. The input is data from the CPU, and the output is the information stored in the database.

[0676] Step 4:

[0677] The server analyzes the stored data using a real-time data analysis system (e.g., Apache Kafka). This analysis detects sudden changes in weight and abnormal decreases or increases in exercise volume. The input is data obtained from the database, and the output is the analysis result, indicating whether or not there are any abnormalities.

[0678] Step 5:

[0679] If the server detects an abnormality based on the analysis results, it sends an alert to the user via the notification system. This alert is displayed on the vehicle's display or on a smartphone app. The input is the analysis results, and the output is an alert notification to the user interface.

[0680] Step 6:

[0681] The user checks the received alert notification and learns that there is something wrong with their pet's health. Specific actions include checking the notification displayed on the vehicle's display or receiving a push notification on their smartphone. The input here is the alert notification, and the output is the user's action (for example, contacting a veterinarian).

[0682] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0683] The present invention relates to an automatic conditioning note system for recording pet lifestyle habits and analyzing health conditions. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the system is able to appropriately adjust notification content according to the user's emotional state. A specific embodiment of the system is shown below.

[0684] System configuration

[0685] The system includes multiple terminals, a server, a user interface, and an emotion engine to monitor, record, and analyze pet behavior and health. Each terminal automatically records the pet's food intake, exercise, weight, and excretion status.

[0686] Terminal

[0687] The terminal consists of the following devices:

[0688] 1. Smart scale

[0689] When your pet steps on the scale, its weight is measured and the data is recorded along with a timestamp.

[0690] 2. Automatic feeder

[0691] Every time your pet eats, the amount of food eaten is recorded and the data is saved with a timestamp.

[0692] 3. Pet Activity Monitor

[0693] Attached to a collar or harness, it measures the pet's activity, specifically recording data such as the number of steps taken, distance traveled, and calories burned.

[0694] 4. Smart Toilet

[0695] Record data on the number of times your pet goes to the toilet, the time it takes, and the amount and condition of its waste.

[0696] server

[0697] The server is the main processor that receives, stores, and analyzes data sent from the device.

[0698] 1. Data Receipt and Storage

[0699] The server receives the data sent by the device in real time and stores it in a database for each pet. It also validates the data to check for any irregularities.

[0700] 2. Data Analysis

[0701] The server analyzes the stored data and evaluates the pet's health, particularly checking for changes in weight, activity levels, and abnormalities in excretion.

[0702] 3. Anomaly Detection

[0703] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[0704] 4. Emotion Engine

[0705] The server analyzes the user's emotions from their voice and facial expressions through an emotion engine, and adjusts the message sent when an abnormality is notified according to their emotional state. The emotion engine evaluates the user's emotional state in real time and provides appropriate countermeasures.

[0706] User Interface

[0707] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[0708] 1. Displaying data

[0709] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[0710] 2. Alert Notifications

[0711] If an anomaly is detected, the user will receive an alert via push notification or email, and the emotion engine will analyze the user's emotional state and provide appropriate message content.

[0712] Program processing

[0713] Terminal

[0714] The devices collect and transmit data. For example, when a pet steps on a scale, it automatically measures its weight and sends the data to a server. Similarly, an automatic feeder records food intake, and an activity monitor measures exercise. Each device collects data along with a timestamp and sends it to the server.

[0715] server

[0716] The server centrally manages all data sent from the devices and stores it in a database. It then uses algorithms to analyze the data and check for abnormalities in weight fluctuations, exercise volume, excretion status, etc. If an abnormality is detected, the server generates an alert and, after analyzing the user's emotional state with an emotion engine, determines the appropriate notification content.

[0717] User

[0718] Users can check their pet's condition using a smartphone app. The app sends data requests to the server and displays the latest information. The app's intuitive interface provides detailed statistical data and graphs on food intake, exercise, weight, and excretion status. If an abnormality is detected, an emotion engine generates a message that takes the user's emotions into consideration and advises on how to respond.

[0719] Specific examples

[0720] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to the server. The server then compares the data with the previous measurement and analyzes it for any abnormal fluctuations. If there is a sudden weight loss, the emotion engine analyzes the user's voice and facial expressions and generates a message based on the level of urgency. For example, if the user is already stressed or anxious, a notification will be sent stating, "A sudden weight fluctuation has been detected. Please remain calm and consult a veterinarian first." The user can open the app, check the detailed data, and contact a veterinarian if necessary, enabling quick and effective health management of their pet.

[0721] As a result, the present invention not only helps manage the health of pets, but also reduces the psychological burden on users and helps build a better relationship between pets and their owners.

[0722] The processing flow will be explained below.

[0723] Step 1:

[0724] The device will measure your pet's weight.

[0725] When a pet steps onto the smart scale, the device uses sensors to measure its weight, timestamps the data, and stores it in its internal memory.

[0726] Step 2:

[0727] The device records the amount of food consumed.

[0728] When your pet eats from the automatic feeder, the device records the amount of food fed and a timestamp, and stores it in its internal memory.

[0729] Step 3:

[0730] The device measures the amount of exercise.

[0731] The pet activity monitor collects your pet's exercise data (steps, distance traveled, calories burned, etc.) in real time and stores it in its internal memory along with a timestamp.

[0732] Step 4:

[0733] The device records the excretion status.

[0734] When your pet uses the smart toilet, the device records the number of times it defecates and a timestamp, and if necessary, stores the amount and condition of the waste in its internal memory.

[0735] Step 5:

[0736] The terminal transmits the collected data to the server.

[0737] At regular intervals or when a specific event occurs (for example, immediately after the pet steps on the scale), the device sends the collected data to a server via Internet communication.

[0738] Step 6:

[0739] The server receives and stores the data.

[0740] The server receives the data sent from the device in real time, validates the data, and then stores it in a database for each pet.

[0741] Step 7:

[0742] The server analyzes the data.

[0743] The server periodically analyzes the stored data to detect sudden changes in weight, abnormalities in exercise, abnormalities in excretion, etc. For example, if a sudden decrease in weight over a short period of time is confirmed, it will detect this as an abnormality.

[0744] Step 8:

[0745] The server detects the abnormality and activates the emotion engine.

[0746] Based on the detected anomaly, the server activates the emotion engine and analyzes the user's emotions from their voice and facial expressions. The emotion engine evaluates the user's emotional state in real time.

[0747] Step 9:

[0748] The server notifies the user based on the result of the emotion engine.

[0749] Based on the analysis results of the emotion engine, the server generates a message offering the user the best course of action. For example, if the user is already stressed, the server may send a notification saying, "A sudden weight fluctuation has been detected. Please stay calm and consult your veterinarian."

[0750] Step 10:

[0751] The user checks the data in the app and takes action.

[0752] The user opens the smartphone app, retrieves the latest data from the server, and visually checks it. The app displays information on the pet's food intake, exercise, weight, excretion status, and a series of abnormalities and emotional analysis results. Based on this information, the user can take appropriate measures, such as contacting a veterinarian for advice.

[0753] Example 2

[0754] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0755] Pet health management is extremely important in today's world, but accurately understanding a pet's health condition requires collecting and appropriately analyzing a large amount of data. Users must also respond quickly and appropriately to any abnormalities in their pets, which requires notifications that take the user's emotional state into consideration. However, conventional systems do not adequately collect and analyze pet lifestyle data, and do not provide notifications that take the user's emotional state into consideration. As a result, pet health management is not adequately managed, placing an excessive psychological burden on users.

[0756] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0757] In this invention, the server includes means for recording the amount of food eaten by the pet, means for recording the amount of exercise the pet does, means for recording the weight of the pet, means for recording the excretion status of the pet, means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities, means for analyzing the emotional state of the user, and means for adjusting the content of notifications according to the emotional state of the user when an abnormality is detected. This allows for the collection and analysis of detailed data on the pet's lifestyle habits and for appropriate notifications to be provided taking the user's emotional state into consideration. This allows for effective and prompt health management of the pet and reduces the psychological burden on the user.

[0758] The "means for recording pet food intake" is a device that automatically measures the amount of food consumed by a pet, and stores the data with a timestamp.

[0759] The "means for recording the amount of exercise of a pet" is a device that measures and records data related to the exercise of a pet, such as the number of steps taken, distance traveled, and calories burned.

[0760] The "means for recording a pet's weight" is a device that automatically measures a pet's weight when the pet steps onto the measuring device, and stores the data with a timestamp.

[0761] A "means for recording pet excretion status" is a device that records data regarding the number of times and time when a pet uses the toilet, as well as the amount and condition of excrement.

[0762] "Means for analyzing the health condition of a pet based on the recorded data and detecting abnormalities" refers to algorithms and software for detecting the health condition and abnormalities of a pet by analyzing the recorded data.

[0763] The "means for analyzing the user's emotional state" refers to algorithms and software for analyzing the user's voice and facial expression data and assessing the user's emotional state in real time.

[0764] The "means for adjusting the notification content according to the user's emotional state when an abnormality is detected" refers to algorithms and software for changing the notification content taking into account the user's current emotional state when an abnormality is detected in the pet.

[0765] The present invention relates to an automatic conditioning note system for recording pets' lifestyle habits and analyzing their health condition. It also features an emotion engine that recognizes the user's emotions, allowing it to appropriately adjust notification content according to the user's emotional state.

[0766] System configuration

[0767] The system includes multiple terminals, a server, a user interface, and an emotion engine for monitoring, recording, and analyzing pet behavior and health. Each terminal automatically records the pet's food intake, exercise, weight, and excretion status. Details are provided below.

[0768] Terminal

[0769] A terminal consists of the following devices:

[0770] 1. Smart scale

[0771] When your pet steps on the scale, it automatically measures their weight, stores the data with a timestamp, and sends it to a server via Wi-Fi or Bluetooth.

[0772] 2. Automatic feeder

[0773] Every time your pet eats, the amount of food is measured and stored with a timestamp, and this data is also sent to a server via Wi-Fi or Bluetooth.

[0774] 3. Pet Activity Monitor

[0775] Attached to a collar or harness, it measures your pet's activity in real time, and sends the data to a server at regular intervals.

[0776] 4. Smart Toilet

[0777] When your pet uses the litter box, data on the number of times, duration, amount and condition of the waste is recorded and sent to a server via Wi-Fi or Bluetooth.

[0778] server

[0779] The server receives and centralizes the data sent from the devices in real time. The data is processed in the following ways:

[0780] 1. Data Receipt and Storage

[0781] The data sent from the device is received in real time and stored in a database for each pet, while data validation is also performed to check for any fraudulent data.

[0782] 2. Data Analysis

[0783] The stored data is analyzed using an algorithm to check for fluctuations in weight, changes in activity, and abnormalities in excretion.

[0784] 3. Anomaly Detection

[0785] Anomalies are detected based on the analysis results and users are notified as necessary.

[0786] 4. Emotion Engine

[0787] Analyzes the user's voice and facial expression data to evaluate the user's emotional state in real time, and adjusts the message content when an abnormality is notified according to the user's emotional state.

[0788] User Interface

[0789] Users can use their smartphones or computers to check the information provided by the system and take the necessary action:

[0790] 1. Displaying data

[0791] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[0792] 2. Alert Notifications

[0793] If an anomaly is detected, you will receive an alert via push notification or email. The emotion engine will analyze the user's emotional state and provide appropriate message content.

[0794] Specific examples

[0795] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to the server. The server receives this data in real time and compares it with the previous measurement data. If there is a sudden weight loss, the emotion engine analyzes the user's voice and facial expressions and generates a message according to the level of urgency.

[0796] For example, if the user is already stressed or anxious, a message will be generated saying, "Sudden weight loss has been detected. Please stay calm and consult a veterinarian." The user can then open the smartphone app, check the detailed data, and contact a veterinarian if necessary.

[0797] Prompt Sentence Examples

[0798] Here are some examples of prompts to input to the generative AI model:

[0799] "If a pet loses weight suddenly, generate a notification message that takes into account the user's emotional state."

[0800] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0801] Program processing flow

[0802] Step 1: Data collection

[0803] Terminal

[0804] The device collects various data about your pet, including its weight, how much it eats, how much it exercises, and its excretion habits.

[0805] Input: Pet weight, food intake, exercise activity, toilet use

[0806] Output: weight data, food intake data, exercise data, excretion data

[0807] Specific operations: The smart scale measures weight and stores the data in its internal memory with a timestamp. The automatic feeder measures food intake and stores the data with a timestamp. The activity monitor measures exercise volume and stores the data with a timestamp. The smart toilet records bowel movements and stores the data with a timestamp.

[0808] Step 2: Send data

[0809] Terminal

[0810] The device sends the collected data to a server via Wi-Fi or Bluetooth.

[0811] Input: weight data, food intake data, exercise data, excretion data

[0812] Output: Various data sent to the server

[0813] Specific operation: Collected data is sent to the server via Wi-Fi or Bluetooth at regular intervals. For example, every time a pet steps on the scale, the data is sent to the server immediately.

[0814] Step 3: Receiving and storing data

[0815] server

[0816] The server receives the data sent from the terminal in real time and stores it in a database.

[0817] Input: weight data, food intake data, exercise data, excretion data

[0818] Output: Saved database entries

[0819] Specific behavior: The server validates the received data and stores it in the database, for example, checking for invalid or missing data and storing only accurate data.

[0820] Step 4: Data analysis

[0821] server

[0822] The server analyzes the stored data and assesses the pet's health.

[0823] Input: Saved weight data, food intake data, exercise data, excretion data

[0824] Output: Analysis results (health status assessment, abnormality detection)

[0825] Specific operation: The system uses an algorithm to analyze data and detect weight fluctuations, changes in activity, and abnormalities in excretion. For example, it checks weight fluctuations over the past week and evaluates whether there are any sudden increases or decreases.

[0826] Step 5: Detect anomalies and generate notifications

[0827] server

[0828] The server detects anomalies based on the analysis results and generates messages to notify the user as needed, taking into account the user's emotional state using an emotion engine.

[0829] Input: Analysis results (health status assessment, abnormality detection), user emotional state data

[0830] Output: Notification message to send to the user

[0831] Specific behavior: If an abnormality is detected, the server uses the emotion engine to analyze the user's voice and facial expressions and generate an appropriate message. For example, if the user is stressed, the server generates a message saying, "Sudden weight loss has been detected. Please stay calm and consult a veterinarian."

[0832] Step 6: Receive notifications and respond

[0833] User

[0834] Users receive notifications on their smartphones or computers to check their pet's status.

[0835] Input: Notification message, application data request

[0836] Output: Detailed data displayed in the application, user's response actions

[0837] Specific behavior: The user taps the notification to open the app and view detailed health data. If necessary, the user can take appropriate action, such as contacting a veterinarian. For example, the user can view a graph of their pet's weight over time in the app and identify the cause of any abnormalities.

[0838] The above is the specific processing flow of the program of this system.

[0839] (Application example 2)

[0840] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0841] Conventional pet health management systems have the problem that data recording and analysis are one-way, and notifications do not take into account the user's emotional state, which increases the psychological burden on the user. Furthermore, when an abnormality is detected, the response is left up to the user, making it difficult to determine the level of urgency. Furthermore, security services also require flexible responses that take into account the user's emotions.

[0842] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0843] In this invention, the server includes means for recording the amount of food eaten by the pet, means for recording the amount of exercise the pet does, means for recording the weight of the pet, means for recording the excretion status of the pet, means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities, means for notifying the user when an abnormality is detected, and means for analyzing the user's emotions and generating notification content according to the emotions. This makes it possible to both manage the health of the pet and reduce the psychological burden on the user, and also enables flexible responses in security services.

[0844] The "means for recording the amount of food eaten by a pet" is a device for recording the amount of food eaten by a pet each time the pet eats a meal and saving the data together with a timestamp.

[0845] A "means for recording a pet's exercise volume" is a device that is attached to a pet's collar or harness and records exercise data such as the number of steps taken, distance traveled, and calories burned.

[0846] The "means for recording pet weight" is a device that measures the weight of a pet when it gets on the platform and records the data along with a timestamp.

[0847] A "means for recording pet excretion status" is a device that records data regarding the number of times and time a pet uses the toilet, as well as the amount and condition of excrement.

[0848] The "means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities" refers to an algorithm that analyzes the collected data and detects abnormalities in the pet's health condition based on changes in weight, amount of exercise, excretion status, etc.

[0849] The "means for notifying the user when an abnormality is detected" is a system that sends a warning message to the user via push notification or email when an abnormality is detected.

[0850] "Means for analyzing the user's emotions and generating notification content according to the emotions" refers to a system that uses an emotion analysis engine to evaluate the user's voice and facial expressions and adjusts the notification message to match their emotional state.

[0851] This invention is an automatic conditioning note system for recording pet lifestyle habits and analyzing health conditions, and reduces the psychological burden on users by using an emotion engine to notify them according to their emotional state. Furthermore, by applying this system to security services, it can realize flexible responses according to the user's emotional state.

[0852] System configuration

[0853] Terminal

[0854] The terminal consists of the following devices:

[0855] 1. Smart scale

[0856] When your pet steps on the scale, it automatically measures its weight and sends the data to a server, along with a timestamp.

[0857] 2. Automatic feeder

[0858] Every time your pet eats, the amount of food eaten is recorded and sent to a server, also with a timestamp.

[0859] 3. Pet Activity Monitor

[0860] Attached to a collar or harness, it measures the pet's activity, recording steps taken, distance traveled, calories burned, and more.

[0861] 4. Smart Toilet

[0862] Data on how many times and for how long your pet uses the litter box, as well as the amount and condition of the waste, is recorded and sent to a server.

[0863] server

[0864] The server is the main processor that receives, stores, and analyzes data sent from the device.

[0865] 1. Data Receipt and Storage

[0866] The server receives data sent from the device in real time and stores it in a database for each pet. It also validates the data and detects and eliminates fraudulent data.

[0867] 2. Data Analysis

[0868] The server analyzes the stored data and evaluates the pet's health, checking for weight fluctuations, changes in activity, and abnormalities in excretion.

[0869] 3. Anomaly Detection

[0870] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[0871] 4. Emotion Engine

[0872] The server analyzes the user's emotions from their voice and facial expressions through an emotion engine, adjusts the message when an abnormality is notified based on their emotional state, evaluates their emotional state in real time, and provides appropriate countermeasures.

[0873] User Interface

[0874] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[0875] 1. Displaying data

[0876] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[0877] 2. Alert Notifications

[0878] If an anomaly is detected, the user will receive an alert via push notification or email, and the emotion engine will analyze the user's emotional state and provide appropriate message content.

[0879] Specific examples

[0880] For example, if a motion sensor in the living room detects suspicious activity while the user is out, the security camera captures the video, the EmotionRecognizer detects the user's stress level, and the NotificationSystem sends a message saying, "Suspicious activity has been detected in the living room. Please check immediately."

[0881] Examples of prompt statements

[0882] If the motion sensor in the living room detects suspicious activity while the family is out, analyze the emotional state of the user when they open the app and generate an appropriate notification message.

[0883] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0884] Step 1:

[0885] The terminal collects data from various devices (smart scales, automatic feeders, pet activity monitors, and smart toilets). Each device measures and records data on pet behavior and status (weight, food intake, exercise, and excretion status) with a timestamp. This data is sent to the server in real time.

[0886] Input: Pet's lifestyle data

[0887] Output: Sending recorded data to a server

[0888] Step 2:

[0889] The server receives data from the device in real time and stores it in a database for each pet. At this time, it validates the data and rejects any invalid data.

[0890] Input: Data sent from the terminal

[0891] Output: Validated data saved to the database

[0892] Step 3:

[0893] The server analyzes the stored data and assesses the pet's health, specifically by using algorithms to analyze changes in the pet's weight, activity level, and abnormalities in excretion.

[0894] Input: Data stored in a database

[0895] Output: Analysis results on pet health

[0896] Step 4:

[0897] The server detects abnormalities based on the analysis results, such as a sudden weight loss or an extreme decrease in exercise volume, and identifies the abnormality.

[0898] Input: Analysis results

[0899] Output: Anomaly detection alert

[0900] Step 5:

[0901] If an anomaly is detected, the server uses an emotion engine to analyze the user's emotions, collecting voice and facial expression data to evaluate the user's emotions in real time.

[0902] Input: User's voice and facial expression data

[0903] Output: User's emotional state

[0904] Step 6:

[0905] The server adjusts the notification message depending on the user's emotional state and sends the appropriate notification to the user, for example, if the user is stressed, it sends a gentle, soothing message.

[0906] Input: Anomaly detection alerts and user emotional state

[0907] Output: A notification message to the user

[0908] Step 7:

[0909] Users can then open the app based on the notification to view details of their pet's health, and the app will visually display the latest data and analysis results, prompting them to take any necessary action.

[0910] Input: Notification messages and application access

[0911] Output: Detailed health status data and analysis results

[0912] This makes it possible to realize a system that not only manages the health of pets, but also reduces the psychological burden on users and provides appropriate countermeasures.

[0913] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0914] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0915] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0916] [Third embodiment]

[0917] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0918] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0919] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0920] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0921] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0922] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0923] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0924] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0925] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0926] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0927] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0928] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0929] The present invention relates to an automatic conditioning note system for recording the lifestyle habits of pets and analyzing their health conditions. Specific embodiments of the system are described below.

[0930] System configuration

[0931] The system includes multiple devices, a server, and a user interface to monitor, record, and analyze pet behavior and health. Each device automatically records the pet's food intake, exercise, weight, and excretion status.

[0932] Terminal

[0933] The terminal is composed of various devices such as:

[0934] 1. Smart scale

[0935] When your pet steps on the scale, its weight is measured and the data is recorded along with a timestamp.

[0936] 2. Automatic feeder

[0937] Every time your pet eats, the amount of food eaten is recorded and the data is saved with a timestamp.

[0938] 3. Pet Activity Monitor

[0939] Attached to a collar or harness, it measures the pet's activity, specifically recording data such as the number of steps taken, distance traveled, and calories burned.

[0940] 4. Smart Toilet

[0941] Record data on the number of times your pet goes to the toilet, the time it takes, and the amount and condition of its waste.

[0942] server

[0943] The server is the main processor that receives, stores, and analyzes data sent from the device.

[0944] 1. Data Receipt and Storage

[0945] The server receives the data sent by the device in real time and stores it in a database for each pet.

[0946] 2. Data Analysis

[0947] The server analyzes the stored data and evaluates the pet's health, particularly checking for weight fluctuations, changes in activity, and abnormalities in elimination frequency.

[0948] 3. Anomaly Detection

[0949] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[0950] User Interface

[0951] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[0952] 1. Displaying data

[0953] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[0954] 2. Alert Notifications

[0955] If an anomaly is detected, users can receive alerts via push notification or email.

[0956] Program processing

[0957] Terminal

[0958] The device collects and transmits data. Specifically, when a pet steps on the scale, it automatically measures its weight and sends the data to the server. Similarly, the automatic feeder records the pet's food intake, and the activity monitor measures its exercise. This information is then sent to the server.

[0959] server

[0960] The server centrally manages all data sent from the devices and stores it in a database. It then uses algorithms to analyze the data and check for any abnormalities in weight fluctuations, exercise volume, excretion status, etc. For example, if the server detects a sudden change in weight over a short period of time or an abnormal change in exercise patterns, it generates an alert and notifies the user.

[0961] User

[0962] Users can check their pet's condition using a smartphone app. The app sends data requests to the server and displays the latest information. The app's intuitive interface provides detailed statistical data and graphs on food intake, exercise, weight, and excretion status. If any abnormalities are detected, the app notifies the user with specific countermeasures.

[0963] Specific examples

[0964] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to a server. The server then compares the data with the previous measurement and analyzes it for any abnormal fluctuations. If there is a sudden weight loss, the user receives an alert notification on their smartphone app saying, "Sudden weight fluctuations have been detected. Please consult a veterinarian." The user can open the app, check the detailed data, and contact a veterinarian if necessary. In this way, users can monitor their pet's health in real time and respond quickly to any abnormalities.

[0965] As described above, the present invention enables detailed data collection and analysis to assist in the health management of pets, and enables prompt notification of abnormalities.

[0966] The processing flow will be explained below.

[0967] Step 1:

[0968] The device will measure your pet's weight.

[0969] When a pet steps onto the smart scale, the device uses sensors to measure its weight, timestamps the data, and stores it in its internal memory.

[0970] Step 2:

[0971] The device records the amount of food consumed.

[0972] When your pet eats from the automatic feeder, the device records the amount of food fed and a timestamp, and stores it in its internal memory.

[0973] Step 3:

[0974] The device measures the amount of exercise.

[0975] The pet activity monitor collects your pet's exercise data (steps, distance traveled, calories burned, etc.) in real time and stores it in its internal memory along with a timestamp.

[0976] Step 4:

[0977] The device records the excretion status.

[0978] When your pet uses the smart toilet, the device records the number of times it defecates and a timestamp, and if necessary, stores the amount and condition of the waste in its internal memory.

[0979] Step 5:

[0980] The terminal transmits the collected data to the server.

[0981] At regular intervals or when a specific event occurs (for example, immediately after a pet steps on the scale), the device sends the collected data to a server via Internet communication.

[0982] Step 6:

[0983] The server receives and stores the data.

[0984] The server receives data sent from the device in real time and stores it in a database for each pet. It also validates the data to check for any irregularities.

[0985] Step 7:

[0986] The server analyzes the data.

[0987] The server analyzes the stored data periodically or on an event-driven basis, checking for abnormalities in weight fluctuations, exercise volume, excretion status, etc. If a problem is detected, an alert is generated.

[0988] Step 8:

[0989] The server detects the abnormality and notifies the user.

[0990] If the server detects an anomaly based on the analysis results, it will send an alert to the user via email or push notification, which will also include detailed information about the anomaly.

[0991] Step 9:

[0992] The user checks the data in the app.

[0993] The user opens the smartphone app, retrieves the latest data from the server, and visually checks it. The app displays detailed data such as food intake, exercise, weight, and excretion status, as well as an overview of any abnormalities.

[0994] Step 10:

[0995] The user handles the abnormality.

[0996] The user receives an alert notification from the server, checks the details, and takes appropriate action, such as taking their pet to the vet.

[0997] Example 1

[0998] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0999] Managing pet health is an important issue for pet owners, and early detection of illness is especially important. However, detailed monitoring of a pet's health requires the collection and analysis of a wide range of data, including food intake, exercise, weight, and excretion patterns. Conventional methods require manually recording this data, which is laborious and time-consuming and can be inaccurate. Furthermore, even if an abnormality is discovered, it is difficult to respond immediately, increasing the risk to the pet's health.

[1000] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1001] In this invention, the server includes means for recording the amount of food eaten by the pet, means for recording the amount of exercise the pet does, means for recording the weight of the pet, means for recording the excretion status of the pet, means for transmitting the recorded data, means for storing the received data, means for analyzing the stored data and evaluating the health status of the pet, means for detecting abnormalities based on the analysis results, and means for notifying the user when an abnormality is detected. This makes it possible to closely monitor the health status of the pet in real time and quickly notify the user when an abnormality is discovered. Furthermore, the user can easily check this data through an intuitive interface and take prompt action.

[1002] A "means for recording pet food intake" is a device that automatically measures the amount of food consumed by a pet and stores the data.

[1003] The "means for recording the amount of exercise of a pet" is a device that measures the amount of exercise that a pet performs and records the data.

[1004] A "means for recording a pet's weight" is a device that measures a pet's weight and stores the data.

[1005] A "means for recording pet excretion status" is a device that records the frequency and content of a pet's excretion.

[1006] The "means for transmitting recorded data" is a device that transmits collected data to a central management device such as a server.

[1007] "Means for storing received data" is a device that stores the transmitted data in a local database.

[1008] The "means for analyzing the stored data and assessing the health condition of the pet" refers to algorithms or software for assessing the health condition of the pet using the stored data.

[1009] "Means for detecting anomalies based on analysis results" refers to a mechanism for identifying abnormal patterns or values ​​from analyzed data.

[1010] The "means for notifying the user when an abnormality is detected" refers to a device or system that notifies the user of the information when an abnormality is discovered.

[1011] The present invention relates to an automatic conditioning note system for recording the lifestyle habits of pets and analyzing their health conditions. Specific embodiments of the system are described below.

[1012] System configuration

[1013] The system includes multiple devices, a server, and a user interface to monitor, record, and analyze pet behavior and health status. The following terminals are used:

[1014] Terminal

[1015] 1. Smart scale

[1016] The smart scale measures the pet's weight when it steps on the scale, records the data with a timestamp, and transmits the data to a server via Wi-Fi or Bluetooth.

[1017] 2. Automatic feeder

[1018] The automatic feeder measures the amount of food your pet eats and records the data with a timestamp, which is then sent to a server via Wi-Fi or Bluetooth.

[1019] 3. Pet Activity Monitor

[1020] The activity monitor is attached to a collar or harness and records the pet's activity, such as steps taken, distance traveled, and calories burned, and the data is also sent to a server.

[1021] 4. Smart Toilet

[1022] The smart toilet records the number of times your pet goes to the toilet, the time it takes, and the amount and condition of the waste, and sends the data to a server via Wi-Fi or Bluetooth.

[1023] server

[1024] The server receives the data sent from the terminals and manages it in a unified manner.

[1025] 1. Data Receipt and Storage

[1026] The server receives the data sent from the device in real time and stores it in a database for each pet.

[1027] 2. Data Analysis

[1028] The server uses algorithms to analyze the stored data, particularly for weight fluctuations, changes in activity levels, and abnormal bowel movements. For example, if a sudden weight loss or abnormal movement patterns are detected, an alert will be generated.

[1029] 3. Anomaly Detection

[1030] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[1031] User Interface

[1032] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[1033] 1. Displaying data

[1034] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[1035] 2. Alert Notifications

[1036] If an anomaly is detected, users can receive alerts via push notification or email.

[1037] Specific examples

[1038] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to a server. The server then compares the data with the previous measurement and analyzes it for any abnormal fluctuations. If there is a sudden weight loss, the user will receive an alert notification on their smartphone app saying, "Sudden weight fluctuations have been detected. Please consult a veterinarian." The user can then open the app, check the detailed data, and contact a veterinarian if necessary.

[1039] Prompt Sentence Examples

[1040] You can generate a report on your pet's health by inputting the following prompts into the generative AI model:

[1041] Prompt statement:

[1042] Generate detailed reports on your pet's health using data from your automated pet conditioning notes system, including:

[1043] body weight

[1044] Amount of food

[1045] Exercise volume (steps, distance traveled, calories burned)

[1046] Excretion status (number of times, condition of excrement)

[1047] Please also mention any sudden weight fluctuations or changes in exercise patterns. We will assess your pet's health and recommend any necessary measures.

[1048] Using this prompt, the generative AI model can create a specific and detailed report on the pet's health.

[1049] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1050] Step 1: Data collection

[1051] The devices collect data on the pet's behavior and health. When a user places their pet on a smart scale, the scale measures the pet's weight and records the data with a timestamp. Similarly, an automatic feeder measures the amount of food a pet eats, and a pet activity monitor records the number of steps taken, distance traveled, and calories burned. A smart toilet records the number of times the pet defecates, the time, and the amount and condition of the waste. The input is the data measured by each device, and the output is this data recorded with a timestamp.

[1052] Step 2: Send data

[1053] The devices send the data they collect to a server. Smart scales, automatic feeders, pet activity monitors, and smart toilets all send data to a server via Wi-Fi or Bluetooth. The input is the recorded data with a timestamp, and the output is the data being sent to the server.

[1054] Step 3: Receiving and storing data

[1055] The server receives the data sent from the terminal and manages it in a unified manner. The received data is stored in a database and classified for each pet. The input is the data sent from the terminal, and the output is that this data is stored in the server's database.

[1056] Step 4: Data analysis

[1057] The server uses the stored data to analyze the pet's health. During the data analysis process, algorithms are used to check for weight fluctuations, changes in activity levels, and abnormalities in excretion. For example, sudden weight fluctuations and abnormal movement patterns are detected. The input is the stored data, and the output is various health indicators and abnormality detection results.

[1058] Step 5: Anomaly detection

[1059] The server detects anomalies from the analyzed data. If a sudden weight gain or loss or an abnormal exercise pattern is found, it is deemed to be an anomaly. The input is the analysis results, and the output is information tagged as an anomaly. Specifically, if a sudden weight loss is detected, for example, it is tagged as "sudden weight loss."

[1060] Step 6: User Notification

[1061] The server notifies the user if an abnormality is detected. When an abnormality is detected, a push notification is sent to the user's smartphone or email. The input is the abnormality detection result, and the output is a notification message to the user. For example, a notification may be sent saying, "A sudden weight fluctuation has been detected. Please consult a veterinarian."

[1062] Step 7: Data display

[1063] Users access the system using a smartphone or computer to view and check data. Data on weight, food intake, exercise, and excretion status can be visually checked as graphs and statistical information through an app or web interface. The input is the saved data and analysis results, and the output is a screen where the user can check the visualized data. For example, a graph showing the weight fluctuations of a pet over the past week is displayed.

[1064] (Application example 1)

[1065] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1066] It is important to reliably monitor the health of pets when traveling or driving long distances with pets, but conventional systems have had difficulty monitoring the health of pets in the vehicle in real time. Furthermore, there is no means of quickly notifying the user when an abnormality is detected, which tends to result in delayed response. There is a need for a new monitoring system that can solve these issues and ensure the safety and health of pets.

[1067] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1068] In this invention, the server includes a means for recording the amount of food eaten, a means for recording the amount of exercise, a means for recording the weight, a processing means in the vehicle for receiving, saving, and analyzing the data in real time, a means for analyzing the health condition of the pet based on the analyzed data and detecting abnormalities, and a notification means mounted in the vehicle for notifying the user when an abnormality is detected. This makes it possible to monitor the health condition of the pet in the vehicle in real time, and to quickly notify the user when an abnormality occurs.

[1069] "Pet lifestyle" refers to the daily activities of pets, such as eating, exercise, weight changes, and excretory behavior.

[1070] An "automatic conditioning note system" is a system that automatically records a pet's lifestyle habits, analyzes its health condition, and notifies the user if any abnormalities are detected.

[1071] "Means for recording food intake" refers to a device or sensor that automatically measures and records the amount of food consumed by a pet.

[1072] "Means for recording physical activity" refers to devices or sensors that automatically measure and record a pet's physical activity.

[1073] "Weight recording means" refers to a device that automatically measures and records a pet's weight.

[1074] "Means for recording excretion status" refers to a device that automatically measures and records the frequency and amount of pet excretion.

[1075] "Processing means for receiving, storing, and analyzing data in real time" refers to a processing system for receiving data sent from a terminal, storing it, and instantly analyzing it to determine the health condition of a pet.

[1076] "Means for detecting abnormalities" refers to algorithms and analytical methods for detecting abnormalities in health status based on recorded data.

[1077] "Means for notifying" refers to a means for notifying the user of a detected abnormality, and includes methods such as push notifications to a smartphone or displaying the information on the vehicle's display.

[1078] "Notification means installed in the vehicle" refers to a means for notifying the driver using an in-vehicle display or alert system when a pet shows signs of abnormal health.

[1079] The present invention relates to an automatic conditioning note system for recording pet lifestyle habits and analyzing their health status. This system monitors and notifies users to ensure the health of their pets in an autonomous vehicle. Specific embodiments of the system are described below.

[1080] System configuration

[1081] The system includes multiple sensors, a server, and a user interface to monitor, record, and analyze pet behavior and health. Each sensor automatically records the pet's food intake, exercise, weight, and excretion status.

[1082] sensor

[1083] The sensor consists of various devices such as:

[1084] 1. Smart scale

[1085] When your pet steps on the scale, its weight is measured and the data is recorded along with a timestamp.

[1086] 2. Automatic feeder

[1087] Every time your pet eats, the amount of food eaten is recorded and the data is saved with a timestamp.

[1088] 3. Pet Activity Monitor

[1089] Attached to a collar or harness, it measures the pet's activity, specifically recording data such as the number of steps taken, distance traveled, and calories burned.

[1090] 4. Smart Toilet

[1091] Record data on the number of times your pet goes to the toilet, the time it takes, and the amount and condition of its waste.

[1092] server

[1093] The server is the main processor that receives, stores, and analyzes the data sent from the sensors. Specific use cases are shown below.

[1094] 1. Data Receipt and Storage

[1095] The server receives the data sent by the sensors in real time and stores it in a database (e.g., MySQL) for each pet.

[1096] 2. Data Analysis

[1097] The server analyzes the stored data using a real-time data analysis system (e.g., Apache Kafka) to assess the pet's health, particularly by checking for changes in weight, activity levels, and abnormalities in defecation frequency.

[1098] 3. Anomaly Detection

[1099] The server detects abnormalities based on the analysis results, and if an abnormality is detected, it alerts the user via a notification system installed in the vehicle.

[1100] User Interface

[1101] Users can use their smartphone or the vehicle's on-board display to check the information provided by the system and take any necessary action.

[1102] 1. Displaying data

[1103] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[1104] 2. Alert Notifications

[1105] If an abnormality is detected, the user can receive an alert via push notification on the vehicle's display or smartphone.

[1106] Specific examples

[1107] For example, suppose a user is driving a long distance with their pet and the pet steps onto the smart scale inside the car. The scale measures the pet's weight and sends the data to a server in real time. The data is stored in a database and compared with past data to analyze whether there are any abnormal weight fluctuations. If there is a sudden weight loss, the server will use the analysis results to display an alert on the car's display saying, "A sudden weight fluctuation has been detected. Please consult a veterinarian."

[1108] Prompt Sentence Examples

[1109] "Design a real-time alert system that analyzes this pet's health data and notifies the user if there are any abnormalities."

[1110] "Create a program that monitors your pet's weight fluctuations, food intake, exercise, and elimination, and generates alerts if it detects any abnormalities."

[1111] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1112] Step 1:

[1113] The device uses sensors to collect data on your pet's behavior (e.g., food intake, exercise, weight, and excretion status). This data is recorded in different formats depending on the type of sensor, but it is all time-stamped. For example, the weight measured by a smart scale and the time of measurement are generated as data.

[1114] Step 2:

[1115] The terminal transmits the collected data to the vehicle's central processing unit (CPU). During this process, the data is periodically stored in a buffer and transmitted in batches at regular intervals. The input here is the terminal data, and the output is the data transmitted to the vehicle CPU.

[1116] Step 3:

[1117] The server stores the data received from the CPU in a database (e.g., MySQL). During this storage process, the data is categorized by pet and organized chronologically. The input is data from the CPU, and the output is the information stored in the database.

[1118] Step 4:

[1119] The server analyzes the stored data using a real-time data analysis system (e.g., Apache Kafka). This analysis detects sudden changes in weight and abnormal decreases or increases in exercise volume. The input is data obtained from the database, and the output is the analysis result, indicating whether or not there are any abnormalities.

[1120] Step 5:

[1121] If the server detects an abnormality based on the analysis results, it sends an alert to the user via the notification system. This alert is displayed on the vehicle's display or on a smartphone app. The input is the analysis results, and the output is an alert notification to the user interface.

[1122] Step 6:

[1123] The user checks the received alert notification and learns that there is something wrong with their pet's health. Specific actions include checking the notification displayed on the vehicle's display or receiving a push notification on their smartphone. The input here is the alert notification, and the output is the user's action (for example, contacting a veterinarian).

[1124] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1125] The present invention relates to an automatic conditioning note system for recording pet lifestyle habits and analyzing health conditions. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the system is able to appropriately adjust notification content according to the user's emotional state. A specific embodiment of the system is shown below.

[1126] System configuration

[1127] The system includes multiple terminals, a server, a user interface, and an emotion engine to monitor, record, and analyze pet behavior and health. Each terminal automatically records the pet's food intake, exercise, weight, and excretion status.

[1128] Terminal

[1129] The terminal consists of the following devices:

[1130] 1. Smart scale

[1131] When your pet steps on the scale, its weight is measured and the data is recorded along with a timestamp.

[1132] 2. Automatic feeder

[1133] Every time your pet eats, the amount of food eaten is recorded and the data is saved with a timestamp.

[1134] 3. Pet Activity Monitor

[1135] Attached to a collar or harness, it measures the pet's activity, specifically recording data such as the number of steps taken, distance traveled, and calories burned.

[1136] 4. Smart Toilet

[1137] Record data on the number of times your pet goes to the toilet, the time it takes, and the amount and condition of its waste.

[1138] server

[1139] The server is the main processor that receives, stores, and analyzes data sent from the device.

[1140] 1. Data Receipt and Storage

[1141] The server receives the data sent by the device in real time and stores it in a database for each pet. It also validates the data to check for any irregularities.

[1142] 2. Data Analysis

[1143] The server analyzes the stored data and evaluates the pet's health, particularly checking for changes in weight, activity levels, and abnormalities in excretion.

[1144] 3. Anomaly Detection

[1145] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[1146] 4. Emotion Engine

[1147] The server analyzes the user's emotions from their voice and facial expressions through an emotion engine, and adjusts the message sent when an abnormality is notified according to their emotional state. The emotion engine evaluates the user's emotional state in real time and provides appropriate countermeasures.

[1148] User Interface

[1149] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[1150] 1. Displaying data

[1151] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[1152] 2. Alert Notifications

[1153] If an anomaly is detected, the user will receive an alert via push notification or email, and the emotion engine will analyze the user's emotional state and provide appropriate message content.

[1154] Program processing

[1155] Terminal

[1156] The devices collect and transmit data. For example, when a pet steps on a scale, it automatically measures its weight and sends the data to a server. Similarly, an automatic feeder records food intake, and an activity monitor measures exercise. Each device collects data along with a timestamp and sends it to the server.

[1157] server

[1158] The server centrally manages all data sent from the devices and stores it in a database. It then uses algorithms to analyze the data and check for abnormalities in weight fluctuations, exercise volume, excretion status, etc. If an abnormality is detected, the server generates an alert and, after analyzing the user's emotional state with an emotion engine, determines the appropriate notification content.

[1159] User

[1160] Users can check their pet's condition using a smartphone app. The app sends data requests to the server and displays the latest information. The app's intuitive interface provides detailed statistical data and graphs on food intake, exercise, weight, and excretion status. If an abnormality is detected, an emotion engine generates a message that takes the user's emotions into consideration and advises on how to respond.

[1161] Specific examples

[1162] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to the server. The server then compares the data with the previous measurement and analyzes it for any abnormal fluctuations. If there is a sudden weight loss, the emotion engine analyzes the user's voice and facial expressions and generates a message based on the level of urgency. For example, if the user is already stressed or anxious, a notification will be sent stating, "A sudden weight fluctuation has been detected. Please remain calm and consult a veterinarian first." The user can open the app, check the detailed data, and contact a veterinarian if necessary, enabling quick and effective health management of their pet.

[1163] As a result, the present invention not only helps manage the health of pets, but also reduces the psychological burden on users and helps build a better relationship between pets and their owners.

[1164] The processing flow will be explained below.

[1165] Step 1:

[1166] The device will measure your pet's weight.

[1167] When a pet steps onto the smart scale, the device uses sensors to measure its weight, timestamps the data, and stores it in its internal memory.

[1168] Step 2:

[1169] The device records the amount of food consumed.

[1170] When your pet eats from the automatic feeder, the device records the amount of food fed and a timestamp, and stores it in its internal memory.

[1171] Step 3:

[1172] The device measures the amount of exercise.

[1173] The pet activity monitor collects your pet's exercise data (steps, distance traveled, calories burned, etc.) in real time and stores it in its internal memory along with a timestamp.

[1174] Step 4:

[1175] The device records the excretion status.

[1176] When your pet uses the smart toilet, the device records the number of times it defecates and a timestamp, and if necessary, stores the amount and condition of the waste in its internal memory.

[1177] Step 5:

[1178] The terminal transmits the collected data to the server.

[1179] At regular intervals or when a specific event occurs (for example, immediately after the pet steps on the scale), the device sends the collected data to a server via Internet communication.

[1180] Step 6:

[1181] The server receives and stores the data.

[1182] The server receives the data sent from the device in real time, validates the data, and then stores it in a database for each pet.

[1183] Step 7:

[1184] The server analyzes the data.

[1185] The server periodically analyzes the stored data to detect sudden changes in weight, abnormalities in exercise, abnormalities in excretion, etc. For example, if a sudden decrease in weight over a short period of time is confirmed, it will detect this as an abnormality.

[1186] Step 8:

[1187] The server detects the abnormality and activates the emotion engine.

[1188] Based on the detected anomaly, the server activates the emotion engine and analyzes the user's emotions from their voice and facial expressions. The emotion engine evaluates the user's emotional state in real time.

[1189] Step 9:

[1190] The server notifies the user based on the result of the emotion engine.

[1191] Based on the analysis results of the emotion engine, the server generates a message offering the user the best course of action. For example, if the user is already stressed, the server may send a notification saying, "A sudden weight fluctuation has been detected. Please stay calm and consult your veterinarian."

[1192] Step 10:

[1193] The user checks the data in the app and takes action.

[1194] The user opens the smartphone app, retrieves the latest data from the server, and visually checks it. The app displays information on the pet's food intake, exercise, weight, excretion status, and a series of abnormalities and emotional analysis results. Based on this information, the user can take appropriate measures, such as contacting a veterinarian for advice.

[1195] Example 2

[1196] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1197] Pet health management is extremely important in today's world, but accurately understanding a pet's health condition requires collecting and appropriately analyzing a large amount of data. Users must also respond quickly and appropriately to any abnormalities in their pets, which requires notifications that take the user's emotional state into consideration. However, conventional systems do not adequately collect and analyze pet lifestyle data, and do not provide notifications that take the user's emotional state into consideration. As a result, pet health management is not adequately managed, placing an excessive psychological burden on users.

[1198] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1199] In this invention, the server includes means for recording the amount of food eaten by the pet, means for recording the amount of exercise the pet does, means for recording the weight of the pet, means for recording the excretion status of the pet, means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities, means for analyzing the emotional state of the user, and means for adjusting the content of notifications according to the emotional state of the user when an abnormality is detected. This allows for the collection and analysis of detailed data on the pet's lifestyle habits and for appropriate notifications to be provided taking the user's emotional state into consideration. This allows for effective and prompt health management of the pet and reduces the psychological burden on the user.

[1200] The "means for recording pet food intake" is a device that automatically measures the amount of food consumed by a pet, and stores the data with a timestamp.

[1201] The "means for recording the amount of exercise of a pet" is a device that measures and records data related to the exercise of a pet, such as the number of steps taken, distance traveled, and calories burned.

[1202] The "means for recording a pet's weight" is a device that automatically measures a pet's weight when the pet steps onto the measuring device, and stores the data with a timestamp.

[1203] A "means for recording pet excretion status" is a device that records data regarding the number of times and time when a pet uses the toilet, as well as the amount and condition of excrement.

[1204] "Means for analyzing the health condition of a pet based on the recorded data and detecting abnormalities" refers to algorithms and software for detecting the health condition and abnormalities of a pet by analyzing the recorded data.

[1205] The "means for analyzing the user's emotional state" refers to algorithms and software for analyzing the user's voice and facial expression data and assessing the user's emotional state in real time.

[1206] The "means for adjusting the notification content according to the user's emotional state when an abnormality is detected" refers to algorithms and software for changing the notification content taking into account the user's current emotional state when an abnormality is detected in the pet.

[1207] The present invention relates to an automatic conditioning note system for recording pets' lifestyle habits and analyzing their health condition. It also features an emotion engine that recognizes the user's emotions, allowing it to appropriately adjust notification content according to the user's emotional state.

[1208] System configuration

[1209] The system includes multiple terminals, a server, a user interface, and an emotion engine for monitoring, recording, and analyzing pet behavior and health. Each terminal automatically records the pet's food intake, exercise, weight, and excretion status. Details are provided below.

[1210] Terminal

[1211] A terminal consists of the following devices:

[1212] 1. Smart scale

[1213] When your pet steps on the scale, it automatically measures their weight, stores the data with a timestamp, and sends it to a server via Wi-Fi or Bluetooth.

[1214] 2. Automatic feeder

[1215] Every time your pet eats, the amount of food is measured and stored with a timestamp, and this data is also sent to a server via Wi-Fi or Bluetooth.

[1216] 3. Pet Activity Monitor

[1217] Attached to a collar or harness, it measures your pet's activity in real time, and sends the data to a server at regular intervals.

[1218] 4. Smart Toilet

[1219] When your pet uses the litter box, data on the number of times, duration, amount and condition of the waste is recorded and sent to a server via Wi-Fi or Bluetooth.

[1220] server

[1221] The server receives and centralizes the data sent from the devices in real time. The data is processed in the following ways:

[1222] 1. Data Receipt and Storage

[1223] The data sent from the device is received in real time and stored in a database for each pet, while data validation is also performed to check for any fraudulent data.

[1224] 2. Data Analysis

[1225] The stored data is analyzed using an algorithm to check for fluctuations in weight, changes in activity, and abnormalities in excretion.

[1226] 3. Anomaly Detection

[1227] Anomalies are detected based on the analysis results and users are notified as necessary.

[1228] 4. Emotion Engine

[1229] Analyzes the user's voice and facial expression data to evaluate the user's emotional state in real time, and adjusts the message content when an abnormality is notified according to the user's emotional state.

[1230] User Interface

[1231] Users can use their smartphones or computers to check the information provided by the system and take the necessary action:

[1232] 1. Displaying data

[1233] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[1234] 2. Alert Notifications

[1235] If an anomaly is detected, you will receive an alert via push notification or email. The emotion engine will analyze the user's emotional state and provide appropriate message content.

[1236] Specific examples

[1237] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to the server. The server receives this data in real time and compares it with the previous measurement data. If there is a sudden weight loss, the emotion engine analyzes the user's voice and facial expressions and generates a message according to the level of urgency.

[1238] For example, if the user is already stressed or anxious, a message will be generated saying, "Sudden weight loss has been detected. Please stay calm and consult a veterinarian." The user can then open the smartphone app, check the detailed data, and contact a veterinarian if necessary.

[1239] Prompt Sentence Examples

[1240] Here are some examples of prompts to input to the generative AI model:

[1241] "If a pet loses weight suddenly, generate a notification message that takes into account the user's emotional state."

[1242] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1243] Program processing flow

[1244] Step 1: Data collection

[1245] Terminal

[1246] The device collects various data about your pet, including its weight, how much it eats, how much it exercises, and its excretion habits.

[1247] Input: Pet weight, food intake, exercise activity, toilet use

[1248] Output: weight data, food intake data, exercise data, excretion data

[1249] Specific operations: The smart scale measures weight and stores the data in its internal memory with a timestamp. The automatic feeder measures food intake and stores the data with a timestamp. The activity monitor measures exercise volume and stores the data with a timestamp. The smart toilet records bowel movements and stores the data with a timestamp.

[1250] Step 2: Send data

[1251] Terminal

[1252] The device sends the collected data to a server via Wi-Fi or Bluetooth.

[1253] Input: weight data, food intake data, exercise data, excretion data

[1254] Output: Various data sent to the server

[1255] Specific operation: Collected data is sent to the server via Wi-Fi or Bluetooth at regular intervals. For example, every time a pet steps on the scale, the data is sent to the server immediately.

[1256] Step 3: Receiving and storing data

[1257] server

[1258] The server receives the data sent from the terminal in real time and stores it in a database.

[1259] Input: weight data, food intake data, exercise data, excretion data

[1260] Output: Saved database entries

[1261] Specific behavior: The server validates the received data and stores it in the database, for example, checking for invalid or missing data and storing only accurate data.

[1262] Step 4: Data analysis

[1263] server

[1264] The server analyzes the stored data and assesses the pet's health.

[1265] Input: Saved weight data, food intake data, exercise data, excretion data

[1266] Output: Analysis results (health status assessment, abnormality detection)

[1267] Specific operation: The system uses an algorithm to analyze data and detect weight fluctuations, changes in activity, and abnormalities in excretion. For example, it checks weight fluctuations over the past week and evaluates whether there are any sudden increases or decreases.

[1268] Step 5: Detect anomalies and generate notifications

[1269] server

[1270] The server detects anomalies based on the analysis results and generates messages to notify the user as needed, taking into account the user's emotional state using an emotion engine.

[1271] Input: Analysis results (health status assessment, abnormality detection), user emotional state data

[1272] Output: Notification message to send to the user

[1273] Specific behavior: If an abnormality is detected, the server uses the emotion engine to analyze the user's voice and facial expressions and generate an appropriate message. For example, if the user is stressed, the server generates a message saying, "Sudden weight loss has been detected. Please stay calm and consult a veterinarian."

[1274] Step 6: Receive notifications and respond

[1275] User

[1276] Users receive notifications on their smartphones or computers to check their pet's status.

[1277] Input: Notification message, application data request

[1278] Output: Detailed data displayed in the application, user's response actions

[1279] Specific behavior: The user taps the notification to open the app and view detailed health data. If necessary, the user can take appropriate action, such as contacting a veterinarian. For example, the user can view a graph of their pet's weight over time in the app and identify the cause of any abnormalities.

[1280] The above is the specific processing flow of the program of this system.

[1281] (Application example 2)

[1282] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1283] Conventional pet health management systems have the problem that data recording and analysis are one-way, and notifications do not take into account the user's emotional state, which increases the psychological burden on the user. Furthermore, when an abnormality is detected, the response is left up to the user, making it difficult to determine the level of urgency. Furthermore, security services also require flexible responses that take into account the user's emotions.

[1284] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1285] In this invention, the server includes means for recording the amount of food eaten by the pet, means for recording the amount of exercise the pet does, means for recording the weight of the pet, means for recording the excretion status of the pet, means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities, means for notifying the user when an abnormality is detected, and means for analyzing the user's emotions and generating notification content according to the emotions. This makes it possible to both manage the health of the pet and reduce the psychological burden on the user, and also enables flexible responses in security services.

[1286] The "means for recording the amount of food eaten by a pet" is a device for recording the amount of food eaten by a pet each time the pet eats a meal and saving the data together with a timestamp.

[1287] A "means for recording a pet's exercise volume" is a device that is attached to a pet's collar or harness and records exercise data such as the number of steps taken, distance traveled, and calories burned.

[1288] The "means for recording pet weight" is a device that measures the weight of a pet when it gets on the platform and records the data along with a timestamp.

[1289] A "means for recording pet excretion status" is a device that records data regarding the number of times and time a pet uses the toilet, as well as the amount and condition of excrement.

[1290] The "means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities" refers to an algorithm that analyzes the collected data and detects abnormalities in the pet's health condition based on changes in weight, amount of exercise, excretion status, etc.

[1291] The "means for notifying the user when an abnormality is detected" is a system that sends a warning message to the user via push notification or email when an abnormality is detected.

[1292] "Means for analyzing the user's emotions and generating notification content according to the emotions" refers to a system that uses an emotion analysis engine to evaluate the user's voice and facial expressions and adjusts the notification message to match their emotional state.

[1293] This invention is an automatic conditioning note system for recording pet lifestyle habits and analyzing health conditions, and reduces the psychological burden on users by using an emotion engine to notify them according to their emotional state. Furthermore, by applying this system to security services, it can realize flexible responses according to the user's emotional state.

[1294] System configuration

[1295] Terminal

[1296] The terminal consists of the following devices:

[1297] 1. Smart scale

[1298] When your pet steps on the scale, it automatically measures its weight and sends the data to a server, along with a timestamp.

[1299] 2. Automatic feeder

[1300] Every time your pet eats, the amount of food eaten is recorded and sent to a server, also with a timestamp.

[1301] 3. Pet Activity Monitor

[1302] Attached to a collar or harness, it measures the pet's activity, recording steps taken, distance traveled, calories burned, and more.

[1303] 4. Smart Toilet

[1304] Data on how many times and for how long your pet uses the litter box, as well as the amount and condition of the waste, is recorded and sent to a server.

[1305] server

[1306] The server is the main processor that receives, stores, and analyzes data sent from the device.

[1307] 1. Data Receipt and Storage

[1308] The server receives data sent from the device in real time and stores it in a database for each pet. It also validates the data and detects and eliminates fraudulent data.

[1309] 2. Data Analysis

[1310] The server analyzes the stored data and evaluates the pet's health, checking for weight fluctuations, changes in activity, and abnormalities in excretion.

[1311] 3. Anomaly Detection

[1312] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[1313] 4. Emotion Engine

[1314] The server analyzes the user's emotions from their voice and facial expressions through an emotion engine, adjusts the message when an abnormality is notified based on their emotional state, evaluates their emotional state in real time, and provides appropriate countermeasures.

[1315] User Interface

[1316] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[1317] 1. Displaying data

[1318] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[1319] 2. Alert Notifications

[1320] If an anomaly is detected, the user will receive an alert via push notification or email, and the emotion engine will analyze the user's emotional state and provide appropriate message content.

[1321] Specific examples

[1322] For example, if a motion sensor in the living room detects suspicious activity while the user is out, the security camera captures the video, the EmotionRecognizer detects the user's stress level, and the NotificationSystem sends a message saying, "Suspicious activity has been detected in the living room. Please check immediately."

[1323] Examples of prompt statements

[1324] If the motion sensor in the living room detects suspicious activity while the family is out, analyze the emotional state of the user when they open the app and generate an appropriate notification message.

[1325] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1326] Step 1:

[1327] The terminal collects data from various devices (smart scales, automatic feeders, pet activity monitors, and smart toilets). Each device measures and records data on pet behavior and status (weight, food intake, exercise, and excretion status) with a timestamp. This data is sent to the server in real time.

[1328] Input: Pet's lifestyle data

[1329] Output: Sending recorded data to a server

[1330] Step 2:

[1331] The server receives data from the device in real time and stores it in a database for each pet. At this time, it validates the data and rejects any invalid data.

[1332] Input: Data sent from the terminal

[1333] Output: Validated data saved to the database

[1334] Step 3:

[1335] The server analyzes the stored data and assesses the pet's health, specifically by using algorithms to analyze changes in the pet's weight, activity level, and abnormalities in excretion.

[1336] Input: Data stored in a database

[1337] Output: Analysis results on pet health

[1338] Step 4:

[1339] The server detects abnormalities based on the analysis results, such as a sudden weight loss or an extreme decrease in exercise volume, and identifies the abnormality.

[1340] Input: Analysis results

[1341] Output: Anomaly detection alert

[1342] Step 5:

[1343] If an anomaly is detected, the server uses an emotion engine to analyze the user's emotions, collecting voice and facial expression data to evaluate the user's emotions in real time.

[1344] Input: User's voice and facial expression data

[1345] Output: User's emotional state

[1346] Step 6:

[1347] The server adjusts the notification message depending on the user's emotional state and sends the appropriate notification to the user, for example, if the user is stressed, it sends a gentle, soothing message.

[1348] Input: Anomaly detection alerts and user emotional state

[1349] Output: A notification message to the user

[1350] Step 7:

[1351] Users can then open the app based on the notification to view details of their pet's health, and the app will visually display the latest data and analysis results, prompting them to take any necessary action.

[1352] Input: Notification messages and application access

[1353] Output: Detailed health status data and analysis results

[1354] This makes it possible to realize a system that not only manages the health of pets, but also reduces the psychological burden on users and provides appropriate countermeasures.

[1355] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1356] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1357] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1358] [Fourth embodiment]

[1359] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1360] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1361] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1362] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1363] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1364] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1365] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1366] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1367] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1368] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1369] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1370] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1371] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1372] The present invention relates to an automatic conditioning note system for recording the lifestyle habits of pets and analyzing their health conditions. Specific embodiments of the system are described below.

[1373] System configuration

[1374] The system includes multiple devices, a server, and a user interface to monitor, record, and analyze pet behavior and health. Each device automatically records the pet's food intake, exercise, weight, and excretion status.

[1375] Terminal

[1376] The terminal is composed of various devices such as:

[1377] 1. Smart scale

[1378] When your pet steps on the scale, its weight is measured and the data is recorded along with a timestamp.

[1379] 2. Automatic feeder

[1380] Every time your pet eats, the amount of food eaten is recorded and the data is saved with a timestamp.

[1381] 3. Pet Activity Monitor

[1382] Attached to a collar or harness, it measures the pet's activity, specifically recording data such as the number of steps taken, distance traveled, and calories burned.

[1383] 4. Smart Toilet

[1384] Record data on the number of times your pet goes to the toilet, the time it takes, and the amount and condition of its waste.

[1385] server

[1386] The server is the main processor that receives, stores, and analyzes data sent from the device.

[1387] 1. Data Receipt and Storage

[1388] The server receives the data sent by the device in real time and stores it in a database for each pet.

[1389] 2. Data Analysis

[1390] The server analyzes the stored data and evaluates the pet's health, particularly checking for weight fluctuations, changes in activity, and abnormalities in elimination frequency.

[1391] 3. Anomaly Detection

[1392] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[1393] User Interface

[1394] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[1395] 1. Displaying data

[1396] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[1397] 2. Alert Notifications

[1398] If an anomaly is detected, users can receive alerts via push notification or email.

[1399] Program processing

[1400] Terminal

[1401] The device collects and transmits data. Specifically, when a pet steps on the scale, it automatically measures its weight and sends the data to the server. Similarly, the automatic feeder records the pet's food intake, and the activity monitor measures its exercise. This information is then sent to the server.

[1402] server

[1403] The server centrally manages all data sent from the devices and stores it in a database. It then uses algorithms to analyze the data and check for any abnormalities in weight fluctuations, exercise volume, excretion status, etc. For example, if the server detects a sudden change in weight over a short period of time or an abnormal change in exercise patterns, it generates an alert and notifies the user.

[1404] User

[1405] Users can check their pet's condition using a smartphone app. The app sends data requests to the server and displays the latest information. The app's intuitive interface provides detailed statistical data and graphs on food intake, exercise, weight, and excretion status. If any abnormalities are detected, the app notifies the user with specific countermeasures.

[1406] Specific examples

[1407] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to a server. The server then compares the data with the previous measurement and analyzes it for any abnormal fluctuations. If there is a sudden weight loss, the user receives an alert notification on their smartphone app saying, "Sudden weight fluctuations have been detected. Please consult a veterinarian." The user can open the app, check the detailed data, and contact a veterinarian if necessary. In this way, users can monitor their pet's health in real time and respond quickly to any abnormalities.

[1408] As described above, the present invention enables detailed data collection and analysis to assist in the health management of pets, and enables prompt notification of abnormalities.

[1409] The processing flow will be explained below.

[1410] Step 1:

[1411] The device will measure your pet's weight.

[1412] When a pet steps onto the smart scale, the device uses sensors to measure its weight, timestamps the data, and stores it in its internal memory.

[1413] Step 2:

[1414] The device records the amount of food consumed.

[1415] When your pet eats from the automatic feeder, the device records the amount of food fed and a timestamp, and stores it in its internal memory.

[1416] Step 3:

[1417] The device measures the amount of exercise.

[1418] The pet activity monitor collects your pet's exercise data (steps, distance traveled, calories burned, etc.) in real time and stores it in its internal memory along with a timestamp.

[1419] Step 4:

[1420] The device records the excretion status.

[1421] When your pet uses the smart toilet, the device records the number of times it defecates and a timestamp, and if necessary, stores the amount and condition of the waste in its internal memory.

[1422] Step 5:

[1423] The terminal transmits the collected data to the server.

[1424] At regular intervals or when a specific event occurs (for example, immediately after a pet steps on the scale), the device sends the collected data to a server via Internet communication.

[1425] Step 6:

[1426] The server receives and stores the data.

[1427] The server receives data sent from the device in real time and stores it in a database for each pet. It also validates the data to check for any irregularities.

[1428] Step 7:

[1429] The server analyzes the data.

[1430] The server analyzes the stored data periodically or on an event-driven basis, checking for abnormalities in weight fluctuations, exercise volume, excretion status, etc. If a problem is detected, an alert is generated.

[1431] Step 8:

[1432] The server detects the abnormality and notifies the user.

[1433] If the server detects an anomaly based on the analysis results, it will send an alert to the user via email or push notification, which will also include detailed information about the anomaly.

[1434] Step 9:

[1435] The user checks the data in the app.

[1436] The user opens the smartphone app, retrieves the latest data from the server, and visually checks it. The app displays detailed data such as food intake, exercise, weight, and excretion status, as well as an overview of any abnormalities.

[1437] Step 10:

[1438] The user handles the abnormality.

[1439] The user receives an alert notification from the server, checks the details, and takes appropriate action, such as taking their pet to the vet.

[1440] Example 1

[1441] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1442] Managing pet health is an important issue for pet owners, and early detection of illness is especially important. However, detailed monitoring of a pet's health requires the collection and analysis of a wide range of data, including food intake, exercise, weight, and excretion patterns. Conventional methods require manually recording this data, which is laborious and time-consuming and can be inaccurate. Furthermore, even if an abnormality is discovered, it is difficult to respond immediately, increasing the risk to the pet's health.

[1443] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1444] In this invention, the server includes means for recording the amount of food eaten by the pet, means for recording the amount of exercise the pet does, means for recording the weight of the pet, means for recording the excretion status of the pet, means for transmitting the recorded data, means for storing the received data, means for analyzing the stored data and evaluating the health status of the pet, means for detecting abnormalities based on the analysis results, and means for notifying the user when an abnormality is detected. This makes it possible to closely monitor the health status of the pet in real time and quickly notify the user when an abnormality is discovered. Furthermore, the user can easily check this data through an intuitive interface and take prompt action.

[1445] A "means for recording pet food intake" is a device that automatically measures the amount of food consumed by a pet and stores the data.

[1446] The "means for recording the amount of exercise of a pet" is a device that measures the amount of exercise that a pet performs and records the data.

[1447] A "means for recording a pet's weight" is a device that measures a pet's weight and stores the data.

[1448] A "means for recording pet excretion status" is a device that records the frequency and content of a pet's excretion.

[1449] The "means for transmitting recorded data" is a device that transmits collected data to a central management device such as a server.

[1450] "Means for storing received data" is a device that stores the transmitted data in a local database.

[1451] The "means for analyzing the stored data and assessing the health condition of the pet" refers to algorithms or software for assessing the health condition of the pet using the stored data.

[1452] "Means for detecting anomalies based on analysis results" refers to a mechanism for identifying abnormal patterns or values ​​from analyzed data.

[1453] The "means for notifying the user when an abnormality is detected" refers to a device or system that notifies the user of the information when an abnormality is discovered.

[1454] The present invention relates to an automatic conditioning note system for recording the lifestyle habits of pets and analyzing their health conditions. Specific embodiments of the system are described below.

[1455] System configuration

[1456] The system includes multiple devices, a server, and a user interface to monitor, record, and analyze pet behavior and health status. The following terminals are used:

[1457] Terminal

[1458] 1. Smart scale

[1459] The smart scale measures the pet's weight when it steps on the scale, records the data with a timestamp, and transmits the data to a server via Wi-Fi or Bluetooth.

[1460] 2. Automatic feeder

[1461] The automatic feeder measures the amount of food your pet eats and records the data with a timestamp, which is then sent to a server via Wi-Fi or Bluetooth.

[1462] 3. Pet Activity Monitor

[1463] The activity monitor is attached to a collar or harness and records the pet's activity, such as steps taken, distance traveled, and calories burned, and the data is also sent to a server.

[1464] 4. Smart Toilet

[1465] The smart toilet records the number of times your pet goes to the toilet, the time it takes, and the amount and condition of the waste, and sends the data to a server via Wi-Fi or Bluetooth.

[1466] server

[1467] The server receives the data sent from the terminals and manages it in a unified manner.

[1468] 1. Data Receipt and Storage

[1469] The server receives the data sent from the device in real time and stores it in a database for each pet.

[1470] 2. Data Analysis

[1471] The server uses algorithms to analyze the stored data, particularly for weight fluctuations, changes in activity levels, and abnormal bowel movements. For example, if a sudden weight loss or abnormal movement patterns are detected, an alert will be generated.

[1472] 3. Anomaly Detection

[1473] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[1474] User Interface

[1475] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[1476] 1. Displaying data

[1477] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[1478] 2. Alert Notifications

[1479] If an anomaly is detected, users can receive alerts via push notification or email.

[1480] Specific examples

[1481] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to a server. The server then compares the data with the previous measurement and analyzes it for any abnormal fluctuations. If there is a sudden weight loss, the user will receive an alert notification on their smartphone app saying, "Sudden weight fluctuations have been detected. Please consult a veterinarian." The user can then open the app, check the detailed data, and contact a veterinarian if necessary.

[1482] Prompt Sentence Examples

[1483] You can generate a report on your pet's health by inputting the following prompts into the generative AI model:

[1484] Prompt statement:

[1485] Generate detailed reports on your pet's health using data from your automated pet conditioning notes system, including:

[1486] body weight

[1487] Amount of food

[1488] Exercise volume (steps, distance traveled, calories burned)

[1489] Excretion status (number of times, condition of excrement)

[1490] Please also mention any sudden weight fluctuations or changes in exercise patterns. We will assess your pet's health and recommend any necessary measures.

[1491] Using this prompt, the generative AI model can create a specific and detailed report on the pet's health.

[1492] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1493] Step 1: Data collection

[1494] The devices collect data on the pet's behavior and health. When a user places their pet on a smart scale, the scale measures the pet's weight and records the data with a timestamp. Similarly, an automatic feeder measures the amount of food a pet eats, and a pet activity monitor records the number of steps taken, distance traveled, and calories burned. A smart toilet records the number of times the pet defecates, the time, and the amount and condition of the waste. The input is the data measured by each device, and the output is this data recorded with a timestamp.

[1495] Step 2: Send data

[1496] The devices send the data they collect to a server. Smart scales, automatic feeders, pet activity monitors, and smart toilets all send data to a server via Wi-Fi or Bluetooth. The input is the recorded data with a timestamp, and the output is the data being sent to the server.

[1497] Step 3: Receiving and storing data

[1498] The server receives the data sent from the terminal and manages it in a unified manner. The received data is stored in a database and classified for each pet. The input is the data sent from the terminal, and the output is that this data is stored in the server's database.

[1499] Step 4: Data analysis

[1500] The server uses the stored data to analyze the pet's health. During the data analysis process, algorithms are used to check for weight fluctuations, changes in activity levels, and abnormalities in excretion. For example, sudden weight fluctuations and abnormal movement patterns are detected. The input is the stored data, and the output is various health indicators and abnormality detection results.

[1501] Step 5: Anomaly detection

[1502] The server detects anomalies from the analyzed data. If a sudden weight gain or loss or an abnormal exercise pattern is found, it is deemed to be an anomaly. The input is the analysis results, and the output is information tagged as an anomaly. Specifically, if a sudden weight loss is detected, for example, it is tagged as "sudden weight loss."

[1503] Step 6: User Notification

[1504] The server notifies the user if an abnormality is detected. When an abnormality is detected, a push notification is sent to the user's smartphone or email. The input is the abnormality detection result, and the output is a notification message to the user. For example, a notification may be sent saying, "A sudden weight fluctuation has been detected. Please consult a veterinarian."

[1505] Step 7: Data display

[1506] Users access the system using a smartphone or computer to view and check data. Data on weight, food intake, exercise, and excretion status can be visually checked as graphs and statistical information through an app or web interface. The input is the saved data and analysis results, and the output is a screen where the user can check the visualized data. For example, a graph showing the weight fluctuations of a pet over the past week is displayed.

[1507] (Application example 1)

[1508] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1509] It is important to reliably monitor the health of pets when traveling or driving long distances with pets, but conventional systems have had difficulty monitoring the health of pets in the vehicle in real time. Furthermore, there is no means of quickly notifying the user when an abnormality is detected, which tends to result in delayed response. There is a need for a new monitoring system that can solve these issues and ensure the safety and health of pets.

[1510] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1511] In this invention, the server includes a means for recording the amount of food eaten, a means for recording the amount of exercise, a means for recording the weight, a processing means in the vehicle for receiving, saving, and analyzing the data in real time, a means for analyzing the health condition of the pet based on the analyzed data and detecting abnormalities, and a notification means mounted in the vehicle for notifying the user when an abnormality is detected. This makes it possible to monitor the health condition of the pet in the vehicle in real time, and to quickly notify the user when an abnormality occurs.

[1512] "Pet lifestyle" refers to the daily activities of pets, such as eating, exercise, weight changes, and excretory behavior.

[1513] An "automatic conditioning note system" is a system that automatically records a pet's lifestyle habits, analyzes its health condition, and notifies the user if any abnormalities are detected.

[1514] "Means for recording food intake" refers to a device or sensor that automatically measures and records the amount of food consumed by a pet.

[1515] "Means for recording physical activity" refers to devices or sensors that automatically measure and record a pet's physical activity.

[1516] "Weight recording means" refers to a device that automatically measures and records a pet's weight.

[1517] "Means for recording excretion status" refers to a device that automatically measures and records the frequency and amount of pet excretion.

[1518] "Processing means for receiving, storing, and analyzing data in real time" refers to a processing system for receiving data sent from a terminal, storing it, and instantly analyzing it to determine the health condition of a pet.

[1519] "Means for detecting abnormalities" refers to algorithms and analytical methods for detecting abnormalities in health status based on recorded data.

[1520] "Means for notifying" refers to a means for notifying the user of a detected abnormality, and includes methods such as push notifications to a smartphone or displaying the information on the vehicle's display.

[1521] "Notification means installed in the vehicle" refers to a means for notifying the driver using an in-vehicle display or alert system when a pet shows signs of abnormal health.

[1522] The present invention relates to an automatic conditioning note system for recording pet lifestyle habits and analyzing their health status. This system monitors and notifies users to ensure the health of their pets in an autonomous vehicle. Specific embodiments of the system are described below.

[1523] System configuration

[1524] The system includes multiple sensors, a server, and a user interface to monitor, record, and analyze pet behavior and health. Each sensor automatically records the pet's food intake, exercise, weight, and excretion status.

[1525] sensor

[1526] The sensor consists of various devices such as:

[1527] 1. Smart scale

[1528] When your pet steps on the scale, its weight is measured and the data is recorded along with a timestamp.

[1529] 2. Automatic feeder

[1530] Every time your pet eats, the amount of food eaten is recorded and the data is saved with a timestamp.

[1531] 3. Pet Activity Monitor

[1532] Attached to a collar or harness, it measures the pet's activity, specifically recording data such as the number of steps taken, distance traveled, and calories burned.

[1533] 4. Smart Toilet

[1534] Record data on the number of times your pet goes to the toilet, the time it takes, and the amount and condition of its waste.

[1535] server

[1536] The server is the main processor that receives, stores, and analyzes the data sent from the sensors. Specific use cases are shown below.

[1537] 1. Data Receipt and Storage

[1538] The server receives the data sent by the sensors in real time and stores it in a database (e.g., MySQL) for each pet.

[1539] 2. Data Analysis

[1540] The server analyzes the stored data using a real-time data analysis system (e.g., Apache Kafka) to assess the pet's health, particularly by checking for changes in weight, activity levels, and abnormalities in defecation frequency.

[1541] 3. Anomaly Detection

[1542] The server detects abnormalities based on the analysis results, and if an abnormality is detected, it alerts the user via a notification system installed in the vehicle.

[1543] User Interface

[1544] Users can use their smartphone or the vehicle's on-board display to check the information provided by the system and take any necessary action.

[1545] 1. Displaying data

[1546] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[1547] 2. Alert Notifications

[1548] If an abnormality is detected, the user can receive an alert via push notification on the vehicle's display or smartphone.

[1549] Specific examples

[1550] For example, suppose a user is driving a long distance with their pet and the pet steps onto the smart scale inside the car. The scale measures the pet's weight and sends the data to a server in real time. The data is stored in a database and compared with past data to analyze whether there are any abnormal weight fluctuations. If there is a sudden weight loss, the server will use the analysis results to display an alert on the car's display saying, "A sudden weight fluctuation has been detected. Please consult a veterinarian."

[1551] Prompt Sentence Examples

[1552] "Design a real-time alert system that analyzes this pet's health data and notifies the user if there are any abnormalities."

[1553] "Create a program that monitors your pet's weight fluctuations, food intake, exercise, and elimination, and generates alerts if it detects any abnormalities."

[1554] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1555] Step 1:

[1556] The device uses sensors to collect data on your pet's behavior (e.g., food intake, exercise, weight, and excretion status). This data is recorded in different formats depending on the type of sensor, but it is all time-stamped. For example, the weight measured by a smart scale and the time of measurement are generated as data.

[1557] Step 2:

[1558] The terminal transmits the collected data to the vehicle's central processing unit (CPU). During this process, the data is periodically stored in a buffer and transmitted in batches at regular intervals. The input here is the terminal data, and the output is the data transmitted to the vehicle CPU.

[1559] Step 3:

[1560] The server stores the data received from the CPU in a database (e.g., MySQL). During this storage process, the data is categorized by pet and organized chronologically. The input is data from the CPU, and the output is the information stored in the database.

[1561] Step 4:

[1562] The server analyzes the stored data using a real-time data analysis system (e.g., Apache Kafka). This analysis detects sudden changes in weight and abnormal decreases or increases in exercise volume. The input is data obtained from the database, and the output is the analysis result, indicating whether or not there are any abnormalities.

[1563] Step 5:

[1564] If the server detects an abnormality based on the analysis results, it sends an alert to the user via the notification system. This alert is displayed on the vehicle's display or on a smartphone app. The input is the analysis results, and the output is an alert notification to the user interface.

[1565] Step 6:

[1566] The user checks the received alert notification and learns that there is something wrong with their pet's health. Specific actions include checking the notification displayed on the vehicle's display or receiving a push notification on their smartphone. The input here is the alert notification, and the output is the user's action (for example, contacting a veterinarian).

[1567] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1568] The present invention relates to an automatic conditioning note system for recording pet lifestyle habits and analyzing health conditions. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the system is able to appropriately adjust notification content according to the user's emotional state. A specific embodiment of the system is shown below.

[1569] System configuration

[1570] The system includes multiple terminals, a server, a user interface, and an emotion engine to monitor, record, and analyze pet behavior and health. Each terminal automatically records the pet's food intake, exercise, weight, and excretion status.

[1571] Terminal

[1572] The terminal consists of the following devices:

[1573] 1. Smart scale

[1574] When your pet steps on the scale, its weight is measured and the data is recorded along with a timestamp.

[1575] 2. Automatic feeder

[1576] Every time your pet eats, the amount of food eaten is recorded and the data is saved with a timestamp.

[1577] 3. Pet Activity Monitor

[1578] Attached to a collar or harness, it measures the pet's activity, specifically recording data such as the number of steps taken, distance traveled, and calories burned.

[1579] 4. Smart Toilet

[1580] Record data on the number of times your pet goes to the toilet, the time it takes, and the amount and condition of its waste.

[1581] server

[1582] The server is the main processor that receives, stores, and analyzes data sent from the device.

[1583] 1. Data Receipt and Storage

[1584] The server receives the data sent by the device in real time and stores it in a database for each pet. It also validates the data to check for any irregularities.

[1585] 2. Data Analysis

[1586] The server analyzes the stored data and evaluates the pet's health, particularly checking for changes in weight, activity levels, and abnormalities in excretion.

[1587] 3. Anomaly Detection

[1588] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[1589] 4. Emotion Engine

[1590] The server analyzes the user's emotions from their voice and facial expressions through an emotion engine, and adjusts the message sent when an abnormality is notified according to their emotional state. The emotion engine evaluates the user's emotional state in real time and provides appropriate countermeasures.

[1591] User Interface

[1592] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[1593] 1. Displaying data

[1594] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[1595] 2. Alert Notifications

[1596] If an anomaly is detected, the user will receive an alert via push notification or email, and the emotion engine will analyze the user's emotional state and provide appropriate message content.

[1597] Program processing

[1598] Terminal

[1599] The devices collect and transmit data. For example, when a pet steps on a scale, it automatically measures its weight and sends the data to a server. Similarly, an automatic feeder records food intake, and an activity monitor measures exercise. Each device collects data along with a timestamp and sends it to the server.

[1600] server

[1601] The server centrally manages all data sent from the devices and stores it in a database. It then uses algorithms to analyze the data and check for abnormalities in weight fluctuations, exercise volume, excretion status, etc. If an abnormality is detected, the server generates an alert and, after analyzing the user's emotional state with an emotion engine, determines the appropriate notification content.

[1602] User

[1603] Users can check their pet's condition using a smartphone app. The app sends data requests to the server and displays the latest information. The app's intuitive interface provides detailed statistical data and graphs on food intake, exercise, weight, and excretion status. If an abnormality is detected, an emotion engine generates a message that takes the user's emotions into consideration and advises on how to respond.

[1604] Specific examples

[1605] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to the server. The server then compares the data with the previous measurement and analyzes it for any abnormal fluctuations. If there is a sudden weight loss, the emotion engine analyzes the user's voice and facial expressions and generates a message based on the level of urgency. For example, if the user is already stressed or anxious, a notification will be sent stating, "A sudden weight fluctuation has been detected. Please remain calm and consult a veterinarian first." The user can open the app, check the detailed data, and contact a veterinarian if necessary, enabling quick and effective health management of their pet.

[1606] As a result, the present invention not only helps manage the health of pets, but also reduces the psychological burden on users and helps build a better relationship between pets and their owners.

[1607] The processing flow will be explained below.

[1608] Step 1:

[1609] The device will measure your pet's weight.

[1610] When a pet steps onto the smart scale, the device uses sensors to measure its weight, timestamps the data, and stores it in its internal memory.

[1611] Step 2:

[1612] The device records the amount of food consumed.

[1613] When your pet eats from the automatic feeder, the device records the amount of food fed and a timestamp, and stores it in its internal memory.

[1614] Step 3:

[1615] The device measures the amount of exercise.

[1616] The pet activity monitor collects your pet's exercise data (steps, distance traveled, calories burned, etc.) in real time and stores it in its internal memory along with a timestamp.

[1617] Step 4:

[1618] The device records the excretion status.

[1619] When your pet uses the smart toilet, the device records the number of times it defecates and a timestamp, and if necessary, stores the amount and condition of the waste in its internal memory.

[1620] Step 5:

[1621] The terminal transmits the collected data to the server.

[1622] At regular intervals or when a specific event occurs (for example, immediately after the pet steps on the scale), the device sends the collected data to a server via Internet communication.

[1623] Step 6:

[1624] The server receives and stores the data.

[1625] The server receives the data sent from the device in real time, validates the data, and then stores it in a database for each pet.

[1626] Step 7:

[1627] The server analyzes the data.

[1628] The server periodically analyzes the stored data to detect sudden changes in weight, abnormalities in exercise, abnormalities in excretion, etc. For example, if a sudden decrease in weight over a short period of time is confirmed, it will detect this as an abnormality.

[1629] Step 8:

[1630] The server detects the abnormality and activates the emotion engine.

[1631] Based on the detected anomaly, the server activates the emotion engine and analyzes the user's emotions from their voice and facial expressions. The emotion engine evaluates the user's emotional state in real time.

[1632] Step 9:

[1633] The server notifies the user based on the result of the emotion engine.

[1634] Based on the analysis results of the emotion engine, the server generates a message offering the user the best course of action. For example, if the user is already stressed, the server may send a notification saying, "A sudden weight fluctuation has been detected. Please stay calm and consult your veterinarian."

[1635] Step 10:

[1636] The user checks the data in the app and takes action.

[1637] The user opens the smartphone app, retrieves the latest data from the server, and visually checks it. The app displays information on the pet's food intake, exercise, weight, excretion status, and a series of abnormalities and emotional analysis results. Based on this information, the user can take appropriate measures, such as contacting a veterinarian for advice.

[1638] Example 2

[1639] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1640] Pet health management is extremely important in today's world, but accurately understanding a pet's health condition requires collecting and appropriately analyzing a large amount of data. Users must also respond quickly and appropriately to any abnormalities in their pets, which requires notifications that take the user's emotional state into consideration. However, conventional systems do not adequately collect and analyze pet lifestyle data, and do not provide notifications that take the user's emotional state into consideration. As a result, pet health management is not adequately managed, placing an excessive psychological burden on users.

[1641] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1642] In this invention, the server includes means for recording the amount of food eaten by the pet, means for recording the amount of exercise the pet does, means for recording the weight of the pet, means for recording the excretion status of the pet, means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities, means for analyzing the emotional state of the user, and means for adjusting the content of notifications according to the emotional state of the user when an abnormality is detected. This allows for the collection and analysis of detailed data on the pet's lifestyle habits and for appropriate notifications to be provided taking the user's emotional state into consideration. This allows for effective and prompt health management of the pet and reduces the psychological burden on the user.

[1643] The "means for recording pet food intake" is a device that automatically measures the amount of food consumed by a pet, and stores the data with a timestamp.

[1644] The "means for recording the amount of exercise of a pet" is a device that measures and records data related to the exercise of a pet, such as the number of steps taken, distance traveled, and calories burned.

[1645] The "means for recording a pet's weight" is a device that automatically measures a pet's weight when the pet steps onto the measuring device, and stores the data with a timestamp.

[1646] A "means for recording pet excretion status" is a device that records data regarding the number of times and time when a pet uses the toilet, as well as the amount and condition of excrement.

[1647] "Means for analyzing the health condition of a pet based on the recorded data and detecting abnormalities" refers to algorithms and software for detecting the health condition and abnormalities of a pet by analyzing the recorded data.

[1648] The "means for analyzing the user's emotional state" refers to algorithms and software for analyzing the user's voice and facial expression data and assessing the user's emotional state in real time.

[1649] The "means for adjusting the notification content according to the user's emotional state when an abnormality is detected" refers to algorithms and software for changing the notification content taking into account the user's current emotional state when an abnormality is detected in the pet.

[1650] The present invention relates to an automatic conditioning note system for recording pets' lifestyle habits and analyzing their health condition. It also features an emotion engine that recognizes the user's emotions, allowing it to appropriately adjust notification content according to the user's emotional state.

[1651] System configuration

[1652] The system includes multiple terminals, a server, a user interface, and an emotion engine for monitoring, recording, and analyzing pet behavior and health. Each terminal automatically records the pet's food intake, exercise, weight, and excretion status. Details are provided below.

[1653] Terminal

[1654] A terminal consists of the following devices:

[1655] 1. Smart scale

[1656] When your pet steps on the scale, it automatically measures their weight, stores the data with a timestamp, and sends it to a server via Wi-Fi or Bluetooth.

[1657] 2. Automatic feeder

[1658] Every time your pet eats, the amount of food is measured and stored with a timestamp, and this data is also sent to a server via Wi-Fi or Bluetooth.

[1659] 3. Pet Activity Monitor

[1660] Attached to a collar or harness, it measures your pet's activity in real time, and sends the data to a server at regular intervals.

[1661] 4. Smart Toilet

[1662] When your pet uses the litter box, data on the number of times, duration, amount and condition of the waste is recorded and sent to a server via Wi-Fi or Bluetooth.

[1663] server

[1664] The server receives and centralizes the data sent from the devices in real time. The data is processed in the following ways:

[1665] 1. Data Receipt and Storage

[1666] The data sent from the device is received in real time and stored in a database for each pet, while data validation is also performed to check for any fraudulent data.

[1667] 2. Data Analysis

[1668] The stored data is analyzed using an algorithm to check for fluctuations in weight, changes in activity, and abnormalities in excretion.

[1669] 3. Anomaly Detection

[1670] Anomalies are detected based on the analysis results and users are notified as necessary.

[1671] 4. Emotion Engine

[1672] Analyzes the user's voice and facial expression data to evaluate the user's emotional state in real time, and adjusts the message content when an abnormality is notified according to the user's emotional state.

[1673] User Interface

[1674] Users can use their smartphones or computers to check the information provided by the system and take the necessary action:

[1675] 1. Displaying data

[1676] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[1677] 2. Alert Notifications

[1678] If an anomaly is detected, you will receive an alert via push notification or email. The emotion engine will analyze the user's emotional state and provide appropriate message content.

[1679] Specific examples

[1680] For example, when a user places their pet on a smart scale in the morning, the scale measures the pet's weight and sends the data to the server. The server receives this data in real time and compares it with the previous measurement data. If there is a sudden weight loss, the emotion engine analyzes the user's voice and facial expressions and generates a message according to the level of urgency.

[1681] For example, if the user is already stressed or anxious, a message will be generated saying, "Sudden weight loss has been detected. Please stay calm and consult a veterinarian." The user can then open the smartphone app, check the detailed data, and contact a veterinarian if necessary.

[1682] Prompt Sentence Examples

[1683] Here are some examples of prompts to input to the generative AI model:

[1684] "If a pet loses weight suddenly, generate a notification message that takes into account the user's emotional state."

[1685] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1686] Program processing flow

[1687] Step 1: Data collection

[1688] Terminal

[1689] The device collects various data about your pet, including its weight, how much it eats, how much it exercises, and its excretion habits.

[1690] Input: Pet weight, food intake, exercise activity, toilet use

[1691] Output: weight data, food intake data, exercise data, excretion data

[1692] Specific operations: The smart scale measures weight and stores the data in its internal memory with a timestamp. The automatic feeder measures food intake and stores the data with a timestamp. The activity monitor measures exercise volume and stores the data with a timestamp. The smart toilet records bowel movements and stores the data with a timestamp.

[1693] Step 2: Send data

[1694] Terminal

[1695] The device sends the collected data to a server via Wi-Fi or Bluetooth.

[1696] Input: weight data, food intake data, exercise data, excretion data

[1697] Output: Various data sent to the server

[1698] Specific operation: Collected data is sent to the server via Wi-Fi or Bluetooth at regular intervals. For example, every time a pet steps on the scale, the data is sent to the server immediately.

[1699] Step 3: Receiving and storing data

[1700] server

[1701] The server receives the data sent from the terminal in real time and stores it in a database.

[1702] Input: weight data, food intake data, exercise data, excretion data

[1703] Output: Saved database entries

[1704] Specific behavior: The server validates the received data and stores it in the database, for example, checking for invalid or missing data and storing only accurate data.

[1705] Step 4: Data analysis

[1706] server

[1707] The server analyzes the stored data and assesses the pet's health.

[1708] Input: Saved weight data, food intake data, exercise data, excretion data

[1709] Output: Analysis results (health status assessment, abnormality detection)

[1710] Specific operation: The system uses an algorithm to analyze data and detect weight fluctuations, changes in activity, and abnormalities in excretion. For example, it checks weight fluctuations over the past week and evaluates whether there are any sudden increases or decreases.

[1711] Step 5: Detect anomalies and generate notifications

[1712] server

[1713] The server detects anomalies based on the analysis results and generates messages to notify the user as needed, taking into account the user's emotional state using an emotion engine.

[1714] Input: Analysis results (health status assessment, abnormality detection), user emotional state data

[1715] Output: Notification message to send to the user

[1716] Specific behavior: If an abnormality is detected, the server uses the emotion engine to analyze the user's voice and facial expressions and generate an appropriate message. For example, if the user is stressed, the server generates a message saying, "Sudden weight loss has been detected. Please stay calm and consult a veterinarian."

[1717] Step 6: Receive notifications and respond

[1718] User

[1719] Users receive notifications on their smartphones or computers to check their pet's status.

[1720] Input: Notification message, application data request

[1721] Output: Detailed data displayed in the application, user's response actions

[1722] Specific behavior: The user taps the notification to open the app and view detailed health data. If necessary, the user can take appropriate action, such as contacting a veterinarian. For example, the user can view a graph of their pet's weight over time in the app and identify the cause of any abnormalities.

[1723] The above is the specific processing flow of the program of this system.

[1724] (Application example 2)

[1725] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1726] Conventional pet health management systems have the problem that data recording and analysis are one-way, and notifications do not take into account the user's emotional state, which increases the psychological burden on the user. Furthermore, when an abnormality is detected, the response is left up to the user, making it difficult to determine the level of urgency. Furthermore, security services also require flexible responses that take into account the user's emotions.

[1727] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1728] In this invention, the server includes means for recording the amount of food eaten by the pet, means for recording the amount of exercise the pet does, means for recording the weight of the pet, means for recording the excretion status of the pet, means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities, means for notifying the user when an abnormality is detected, and means for analyzing the user's emotions and generating notification content according to the emotions. This makes it possible to both manage the health of the pet and reduce the psychological burden on the user, and also enables flexible responses in security services.

[1729] The "means for recording the amount of food eaten by a pet" is a device for recording the amount of food eaten by a pet each time the pet eats a meal and saving the data together with a timestamp.

[1730] A "means for recording a pet's exercise volume" is a device that is attached to a pet's collar or harness and records exercise data such as the number of steps taken, distance traveled, and calories burned.

[1731] The "means for recording pet weight" is a device that measures the weight of a pet when it gets on the platform and records the data along with a timestamp.

[1732] A "means for recording pet excretion status" is a device that records data regarding the number of times and time a pet uses the toilet, as well as the amount and condition of excrement.

[1733] The "means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities" refers to an algorithm that analyzes the collected data and detects abnormalities in the pet's health condition based on changes in weight, amount of exercise, excretion status, etc.

[1734] The "means for notifying the user when an abnormality is detected" is a system that sends a warning message to the user via push notification or email when an abnormality is detected.

[1735] "Means for analyzing the user's emotions and generating notification content according to the emotions" refers to a system that uses an emotion analysis engine to evaluate the user's voice and facial expressions and adjusts the notification message to match their emotional state.

[1736] This invention is an automatic conditioning note system for recording pet lifestyle habits and analyzing health conditions, and reduces the psychological burden on users by using an emotion engine to notify them according to their emotional state. Furthermore, by applying this system to security services, it can realize flexible responses according to the user's emotional state.

[1737] System configuration

[1738] Terminal

[1739] The terminal consists of the following devices:

[1740] 1. Smart scale

[1741] When your pet steps on the scale, it automatically measures its weight and sends the data to a server, along with a timestamp.

[1742] 2. Automatic feeder

[1743] Every time your pet eats, the amount of food eaten is recorded and sent to a server, also with a timestamp.

[1744] 3. Pet Activity Monitor

[1745] Attached to a collar or harness, it measures the pet's activity, recording steps taken, distance traveled, calories burned, and more.

[1746] 4. Smart Toilet

[1747] Data on how many times and for how long your pet uses the litter box, as well as the amount and condition of the waste, is recorded and sent to a server.

[1748] server

[1749] The server is the main processor that receives, stores, and analyzes data sent from the device.

[1750] 1. Data Receipt and Storage

[1751] The server receives data sent from the device in real time and stores it in a database for each pet. It also validates the data and detects and eliminates fraudulent data.

[1752] 2. Data Analysis

[1753] The server analyzes the stored data and evaluates the pet's health, checking for weight fluctuations, changes in activity, and abnormalities in excretion.

[1754] 3. Anomaly Detection

[1755] The server detects abnormalities based on the analysis results and notifies the user as necessary.

[1756] 4. Emotion Engine

[1757] The server analyzes the user's emotions from their voice and facial expressions through an emotion engine, adjusts the message when an abnormality is notified based on their emotional state, evaluates their emotional state in real time, and provides appropriate countermeasures.

[1758] User Interface

[1759] Users can use their smartphones or computers to check the information provided by the system and take any necessary action.

[1760] 1. Displaying data

[1761] Users can visually check data such as their pet's weight, amount of food eaten, amount of exercise, and excretion status through the application.

[1762] 2. Alert Notifications

[1763] If an anomaly is detected, the user will receive an alert via push notification or email, and the emotion engine will analyze the user's emotional state and provide appropriate message content.

[1764] Specific examples

[1765] For example, if a motion sensor in the living room detects suspicious activity while the user is out, the security camera captures the video, the EmotionRecognizer detects the user's stress level, and the NotificationSystem sends a message saying, "Suspicious activity has been detected in the living room. Please check immediately."

[1766] Examples of prompt statements

[1767] If the motion sensor in the living room detects suspicious activity while the family is out, analyze the emotional state of the user when they open the app and generate an appropriate notification message.

[1768] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1769] Step 1:

[1770] The terminal collects data from various devices (smart scales, automatic feeders, pet activity monitors, and smart toilets). Each device measures and records data on pet behavior and status (weight, food intake, exercise, and excretion status) with a timestamp. This data is sent to the server in real time.

[1771] Input: Pet's lifestyle data

[1772] Output: Sending recorded data to a server

[1773] Step 2:

[1774] The server receives data from the device in real time and stores it in a database for each pet. At this time, it validates the data and rejects any invalid data.

[1775] Input: Data sent from the terminal

[1776] Output: Validated data saved to the database

[1777] Step 3:

[1778] The server analyzes the stored data and assesses the pet's health, specifically by using algorithms to analyze changes in the pet's weight, activity level, and abnormalities in excretion.

[1779] Input: Data stored in a database

[1780] Output: Analysis results on pet health

[1781] Step 4:

[1782] The server detects abnormalities based on the analysis results, such as a sudden weight loss or an extreme decrease in exercise volume, and identifies the abnormality.

[1783] Input: Analysis results

[1784] Output: Anomaly detection alert

[1785] Step 5:

[1786] If an anomaly is detected, the server uses an emotion engine to analyze the user's emotions, collecting voice and facial expression data to evaluate the user's emotions in real time.

[1787] Input: User's voice and facial expression data

[1788] Output: User's emotional state

[1789] Step 6:

[1790] The server adjusts the notification message depending on the user's emotional state and sends the appropriate notification to the user, for example, if the user is stressed, it sends a gentle, soothing message.

[1791] Input: Anomaly detection alerts and user emotional state

[1792] Output: A notification message to the user

[1793] Step 7:

[1794] Users can then open the app based on the notification to view details of their pet's health, and the app will visually display the latest data and analysis results, prompting them to take any necessary action.

[1795] Input: Notification messages and application access

[1796] Output: Detailed health status data and analysis results

[1797] This makes it possible to realize a system that not only manages the health of pets, but also reduces the psychological burden on users and provides appropriate countermeasures.

[1798] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1799] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1800] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1801] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1802] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1803] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1804] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1805] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1806] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1807] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1808] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1809] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1810] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1811] 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.

[1812] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1813] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1814] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1815] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1816] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1817] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1818] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1819] The following is further disclosed regarding the above embodiment.

[1820] (Claim 1)

[1821] An automatic conditioning note system for recording the lifestyle habits of a pet, comprising:

[1822] A way to record your pet's food intake,

[1823] A means for recording your pet's exercise;

[1824] a means of recording the pet's weight;

[1825] A means to record your pet's excretion status,

[1826] A means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities;

[1827] means for notifying a user when the abnormality is detected;

[1828] A system including:

[1829] (Claim 2)

[1830] 2. The system according to claim 1, wherein the recorded data includes video data of the way the pet walks or runs, and the analyzing means learns the video data and detects abnormalities.

[1831] (Claim 3)

[1832] 2. The system according to claim 1, wherein the recorded data includes the number of times the pet goes to the toilet and the amount of water it consumes, and the analyzing means detects abnormalities based on the data.

[1833] "Example 1"

[1834] (Claim 1)

[1835] A way to record your pet's food intake,

[1836] A means for recording your pet's exercise;

[1837] a means of recording the pet's weight;

[1838] A means to record your pet's excretion status,

[1839] means for transmitting the recorded data;

[1840] means for storing the received data;

[1841] A means for analyzing the stored data and assessing the health status of the pet;

[1842] a means for detecting anomalies based on the analysis results;

[1843] means for notifying a user when the abnormality is detected;

[1844] A system including:

[1845] (Claim 2)

[1846] The system according to claim 1, which has a function of analyzing sudden fluctuations in a pet's weight, abnormalities in movement patterns, and large fluctuations in food intake, and issuing an alert notification when abnormalities are detected.

[1847] (Claim 3)

[1848] 10. The system of claim 1, further comprising a user interface that provides detailed statistics and graphs of the recorded data, allowing the user to visually monitor the health of their pet.

[1849] "Application Example 1"

[1850] (Claim 1)

[1851] An automatic conditioning note system for recording the lifestyle habits of a pet, comprising:

[1852] A way to record your pet's food intake,

[1853] A means for recording your pet's exercise;

[1854] a means of recording the pet's weight;

[1855] A means to record your pet's excretion status,

[1856] processing means within the vehicle for receiving, storing and analyzing said data in real time;

[1857] A means for analyzing the health condition of the pet based on the analyzed data and detecting abnormalities;

[1858] a notification means mounted on the vehicle for notifying a user when the abnormality is detected;

[1859] A system including:

[1860] (Claim 2)

[1861] 2. The system according to claim 1, wherein the recorded data includes video data of the way the pet walks or runs, and the analyzing means learns the video data and detects abnormalities.

[1862] (Claim 3)

[1863] 2. The system according to claim 1, wherein the recorded data includes the number of times the pet goes to the toilet and the amount of water it consumes, and the analyzing means detects abnormalities based on the data.

[1864] "Example 2: Combining Emotion Engines"

[1865] (Claim 1)

[1866] An automatic conditioning note system for recording the lifestyle habits of a pet, comprising:

[1867] A way to record your pet's food intake,

[1868] A means for recording your pet's exercise;

[1869] a means of recording the pet's weight;

[1870] A means to record your pet's excretion status,

[1871] A means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities;

[1872] means for analyzing the emotional state of the user;

[1873] means for adjusting the content of a notification in accordance with the emotional state of the user when the abnormality is detected;

[1874] A system including:

[1875] (Claim 2)

[1876] 2. The system according to claim 1, wherein the recorded data includes video data of the way the pet walks or runs, and the analyzing means learns the video data and detects abnormalities.

[1877] (Claim 3)

[1878] 2. The system according to claim 1, wherein the recorded data includes the number of times the pet goes to the toilet and the amount of water it consumes, and the analyzing means detects abnormalities based on the data.

[1879] "Application example 2 when combining emotion engines"

[1880] (Claim 1)

[1881] An automatic conditioning note system for recording the lifestyle habits of a pet, comprising:

[1882] A way to record your pet's food intake,

[1883] A means for recording your pet's exercise;

[1884] a means of recording the pet's weight;

[1885] A means to record your pet's excretion status,

[1886] A means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities;

[1887] means for notifying a user when the abnormality is detected;

[1888] A means for analyzing a user's emotions and generating notification content according to the emotions;

[1889] A system including:

[1890] (Claim 2)

[1891] 2. The system according to claim 1, wherein the recorded data includes video data of the way the pet walks or runs, and the analyzing means learns the video data and detects abnormalities.

[1892] (Claim 3)

[1893] 2. The system according to claim 1, wherein the recorded data includes the number of times the pet goes to the toilet and the amount of water it consumes, and the analyzing means detects abnormalities based on the data. [Explanation of symbols]

[1894] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. An automatic conditioning note system for recording the lifestyle habits of a pet, comprising: A way to record your pet's food intake, A means for recording your pet's exercise; a means of recording the pet's weight; A means to record your pet's excretion status, A means for analyzing the health condition of the pet based on the recorded data and detecting abnormalities; means for notifying a user when the abnormality is detected; A system including:

2. 2. The system according to claim 1, wherein the recorded data includes video data of the pet's walking and running, and the analyzing means learns the video data and detects abnormalities.

3. 2. The system according to claim 1, wherein the recorded data includes the number of times the pet goes to the toilet and the amount of water it consumes, and the analyzing means detects abnormalities based on the data.

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