system

Abstract

Provide a system. A method for measuring the weight of an animal's meal; a means for measuring the water intake of the animal; a means for weighing animal waste; a means for storing the measured data; A means for visualizing daily nutritional intake and water intake based on the stored data; means for detecting an abnormality based on the visualized data; A means for notifying the abnormality in cooperation with pet insurance. Including system.

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] In today's world, managing the health of pet animals is a crucial issue. Continuously and accurately tracking an animal's food intake, water intake, and feces is essential for monitoring their health and detecting illnesses early. However, manually recording this data is time-consuming and prone to errors. Effective use of this data is also limited, making it difficult for owners to take appropriate measures at the right time. Therefore, there is a strong need for a system that can automatically measure and record an animal's health, detect abnormalities based on this data, and prompt appropriate action. [Means for solving the problem]

[0005] To address the above-mentioned challenges, the present invention provides an animal health management system. The system includes a means for weighing an animal's food intake, a means for measuring the animal's water intake, a means for weighing the animal's waste, a means for storing the measured data, a means for visualizing the animal's daily nutrient and water intake based on the stored data, a means for detecting abnormalities based on the visualized data, and a means for notifying the animal of the abnormality through cooperation with pet insurance. The system also includes a means for proposing a response appropriate to the type of abnormality detected and a means for storing the measured data in a cloud database via the Internet. This allows owners to monitor their animals' health in real time, quickly identify responses when an abnormality is detected, and, by utilizing pet insurance, facilitates animal health management.

[0006] "Animals" refers to living organisms that are commonly kept as pets, especially domestic animals such as cats and dogs.

[0007] "Measuring means" refers to devices or sensors used to measure the weight of an animal's food intake, water intake, and waste.

[0008] "Means for storing data" refers to memory or database systems for recording and storing measured data.

[0009] "Visualization means" refers to software or interfaces that visually display stored data and make it easy for users to understand.

[0010] "Anomaly detection methods" refers to algorithms and analytical tools that analyze stored data and automatically identify outliers or patterns that fall outside the normal range.

[0011] "Means of linking with pet insurance and sending notifications" refers to communication technologies and systems that automatically send information about abnormalities to the pet insurance company when they are detected and notify the user.

[0012] "Means for suggesting countermeasures" refers to software or a database that, when an abnormality is detected, presents the user with countermeasures or treatments appropriate to the abnormality.

[0013] A "cloud database" refers to an external data storage system accessible via the internet that can safely store large amounts of data and provide quick access when needed. [Brief explanation of the drawings]

[0014] [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 illustrating 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

[0015] 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.

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

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

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

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0029] 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.

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

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] This invention relates to a system that supports the health management of pet animals. This system measures and stores data on the animals' diet and excretion, detects abnormalities, and notifies users in cooperation with pet insurance. To effectively implement this system, the following elements and procedures are included:

[0036] element

[0037] 1. Meal measuring means: A scale is installed on the terminal to measure the weight of the food that the user gives to the animal. This serves to measure the weight of the bowl before the animal eats the food.

[0038] 2. Water measurement means: A scale is installed on the terminal to measure the weight of the water that the user gives to the animal. This can measure the weight of the water before the animal drinks it.

[0039] 3. Waste measurement: Animal litter boxes are equipped with sensors and scales to measure the weight of feces and urine, allowing for accurate measurement of the amount of waste.

[0040] 4. Data storage: The measured data on food intake, water intake, and excrement is sent from the device to a server and stored in a database. The stored data can be accessed later.

[0041] 5. Data visualization: Based on the received data, the server displays the animals' daily nutrient and water intake in graphs and tables. This visualization can be viewed by the user via a web browser or a dedicated app.

[0042] 6. Anomaly detection: The server is equipped with data analysis algorithms that automatically detect abnormal values ​​and patterns that exceed the normal range in the stored data.

[0043] 7. Pet Insurance Integration: If an abnormality is detected, the information is automatically sent to the pet insurance company, allowing users to quickly check whether their pet is eligible for insurance coverage.

[0044] 8. Solution suggestion method: The server suggests specific solutions and treatments to the user depending on the type of abnormality. This information is sent to the user's terminal.

[0045] Program processing

[0046] Measuring food intake

[0047] When a user feeds an animal, the user uses the scale on the device to measure the weight of the cat food, etc. The device sends this data to the server, which then records the measurement data.

[0048] Moisture measurement

[0049] Similarly, when a user gives water to an animal, the device measures the weight of the water, and this data is also sent to the server and recorded.

[0050] Measurement of excrement

[0051] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces and sends this data via the device to a server, which then records the data.

[0052] Data visualization

[0053] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables, and users can check this data via a web browser or a dedicated app.

[0054] Anomaly detection and notification

[0055] If the server's data analysis algorithm detects abnormal values ​​or patterns in the measurement data, the information is notified to the user and the pet insurance company.

[0056] Proposal for a solution

[0057] If an abnormality is detected, the server will suggest and notify the user of specific countermeasures and treatments according to the type of abnormality.

[0058] Specific examples

[0059] Let's say a user gives their pet 75 grams of cat food in the morning. At this time, the device measures the weight on a scale and sends the data to the server. The server records this in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, sent, and recorded. Furthermore, when the pet defecates, the toilet sensor measures 50 grams of urine and 20 grams of feces, and each data is sent and recorded to the server. Based on this data, the server visualizes the amount of nutritional and water intake for that day, and if any abnormalities are detected, it notifies the user and the pet insurance company.

[0060] The above is a detailed description of the embodiment of the present invention. This system allows users to efficiently and accurately manage the health status of their animals, detect abnormalities early, and take appropriate measures.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] The user places cat food into a bowl before feeding the animal.

[0064] Step 2:

[0065] The weight of the cat food in the bowl is measured using a scale installed on the terminal.

[0066] Step 3:

[0067] The device sends the measured weight of the meal (for example, 75 grams) to the server as data.

[0068] Step 4:

[0069] The server records the received data in the database as "2023-10-24 08:00, meal, 75 grams."

[0070] Step 5:

[0071] The user fills the water bowl before giving the animal water.

[0072] Step 6:

[0073] The weight of the water container is measured using a scale installed on the terminal.

[0074] Step 7:

[0075] The device sends the measured weight of the water (for example, 150 grams) to the server as data.

[0076] Step 8:

[0077] The server records the received data in the database as "2023-10-24 08:05, water, 150 grams."

[0078] Step 9:

[0079] Animals use the toilet to excrete urine and feces.

[0080] Step 10:

[0081] A sensor built into the toilet measures the weight of urine and feces.

[0082] Step 11:

[0083] The device sends the measured weight of the urine and feces (e.g., 50 grams of urine and 20 grams of feces) as data to the server.

[0084] Step 12:

[0085] The server records the received data in the database as "2023-10-24 18:00, urine, 50 grams" and "2023-10-24 18:05, feces, 20 grams."

[0086] Step 13:

[0087] At the end of the day, the server visualizes the animal's total food intake, water intake, urine volume, and feces volume based on the stored data.

[0088] Step 14:

[0089] Users can check their daily total data through a web browser or a dedicated app.

[0090] Step 15:

[0091] The server uses a data analysis algorithm to analyze the stored data and detect abnormal values ​​and patterns.

[0092] Step 16:

[0093] If an abnormality is detected, the server notifies the user and the pet insurance company of the information.

[0094] Step 17:

[0095] The server proposes specific countermeasures and treatment methods depending on the type of abnormality and notifies the user of this information.

[0096] This allows users to monitor the health of their animals in real time and take appropriate action quickly if any abnormalities are detected.

[0097] Example 1

[0098] 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."

[0099] In today's pet industry, it is difficult to efficiently and accurately manage the health of animals. Accurate data on food intake, water intake, and excrement must be collected, and any abnormalities must be detected early to allow appropriate measures to be taken. Furthermore, if an abnormality is detected, prompt action must be proposed and, if necessary, cooperation with an insurance agency must be coordinated. However, conventional systems are unable to fully meet these requirements, creating multiple challenges in pet health management.

[0100] 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.

[0101] In this invention, the server includes: means for measuring the animal's nutrient intake, means for measuring the animal's water intake, means for measuring the amount of animal waste; means for storing the measured data; means for visualizing daily nutrient and water intake based on the stored data; means for detecting abnormalities based on the visualized data; means for notifying an insurance company of the abnormality; means for proposing a response method according to the type of abnormality when the abnormality is detected; means for storing the measured data in a cloud database; means for analyzing the data stored in the cloud database to identify abnormal values ​​or patterns; and means for generating and transmitting notifications based on the identified abnormal values ​​or patterns. This allows for detailed and real-time monitoring of the animal's health, enabling early detection and prompt response to abnormalities. Furthermore, by linking with an insurance company, insurance coverage can be quickly confirmed, realizing comprehensive health management of pets.

[0102] "Animals" refers to living creatures such as mammals, birds, and reptiles kept as pets.

[0103] "Means for measuring nutrient intake" refers to a device or system used to measure the amount of food given to an animal.

[0104] "Means for measuring water intake" refers to a device or system for measuring the amount of water provided to an animal.

[0105] "Means for measuring the amount of waste" refers to sensors or devices for measuring the amount of urine or feces excreted by an animal.

[0106] "Means for storing measured data" refers to a storage system for recording the measured data and keeping it in a state where it can be accessed later.

[0107] "Visualization means" refers to devices or systems for visually displaying measured data, such as interfaces that display data in graph or table format.

[0108] "Anomaly detection methods" refers to data analysis algorithms or devices that identify and alert on abnormal values ​​or patterns that fall outside of the normal range.

[0109] "Means for linking and notifying insurance organizations" refers to systems or devices that notify insurance companies of detected abnormal values ​​or patterns to expedite insurance coverage confirmation.

[0110] "Means for proposing a countermeasure according to the type of abnormality" refers to a device or system for proposing specific countermeasures or treatment methods to the user based on the detected abnormality.

[0111] "Cloud database" refers to data storage that is remotely accessible via the internet.

[0112] "Means for analyzing data to identify outliers and patterns" refers to systems or software that analyze stored data and automatically detect values ​​that deviate from normal ranges or specific patterns.

[0113] "Means for generating and sending notifications" refers to a system or device for generating notifications based on detected anomalies or patterns and sending them to a user device or insurance organization.

[0114] MODE FOR CARRYING OUT THE INVENTION

[0115] This invention relates to a system that supports the health management of pet animals. This system measures and stores data on the animals' food intake, water intake, and excrement, detects abnormalities, and coordinates with insurance agencies. The following elements are required for the system to be implemented effectively:

[0116] element

[0117] 1. Meal measurement means: The user uses a scale installed on the terminal to measure the amount of food to be given to the animal. This is used to measure the weight of the bowl or container before the animal eats the food.

[0118] 2. Water measuring means: The user uses a scale also installed on the terminal to measure the amount of water to be given to the animal. This scale can measure the weight of the container into which water is poured.

[0119] 3. Waste measurement device: The litter boxes used by animals are equipped with sensors that measure the weight of feces and urine, allowing for accurate measurement of the amount of waste.

[0120] 4. Data storage: The measured data on food intake, water intake, and excrement is sent from the device to a server, which stores it in a cloud database. The stored data can be accessed later.

[0121] 5. Data visualization: Based on the received data, the server displays the animals' daily nutrient and water intake in graphs and tables. This visualization can be viewed by the user via a web browser or a dedicated app.

[0122] 6. Anomaly detection method: The server uses data analysis algorithms to detect abnormal values ​​and patterns in the stored data.

[0123] 7. Insurance Linkage: If an anomaly is detected, the information is automatically sent to insurance companies, allowing users to quickly check for potential insurance coverage.

[0124] 8. Solution suggestion method: The server suggests specific solutions and treatment methods to the user depending on the type of abnormality. This information is sent to the user's terminal.

[0125] Specific actions

[0126] Measuring food intake

[0127] The user measures the amount of food, such as cat food, that they give to their animal. Before putting the cat food into a bowl, the user resets the scale installed on the terminal and sets the weight of the bowl to 0 grams. Next, the user puts the cat food into the bowl and measures its weight. The terminal sends the measurement results to the server, which records the data.

[0128] Moisture measurement

[0129] Similarly, a user measures the amount of water given to an animal. The user places the container on the device's scale and resets the weight to 0 grams. Then, the user pours water into the container and measures its weight. The device sends the measurement result to the server, which records the data.

[0130] Measurement of excrement

[0131] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. This measurement data is sent via the device to a server, which then records the data.

[0132] Data visualization

[0133] The server visualizes the animals' daily nutritional and water intake based on the stored data, and users can check this data via a web browser or a dedicated app.

[0134] Anomaly detection and notification

[0135] If the server's data analysis algorithm detects abnormal values ​​or patterns in the measurement data, the information is notified to the user and insurance organization.

[0136] Proposal for a solution

[0137] If an abnormality is detected, the server will suggest specific countermeasures and treatment methods according to the type of abnormality to the user and notify them of this information.

[0138] Specific examples

[0139] Let's say a user gives their pet 75 grams of cat food in the morning. At this time, the scale on the device measures the weight of the cat food and sends that data to the server. The server records this in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, and the data is sent and recorded. Furthermore, when the pet defecates, the sensor in the litter box measures 50 grams of urine and 20 grams of feces, and each data is sent to the server and recorded. Based on this data, the server visualizes the day's nutritional and water intake, and if any abnormalities are detected, it notifies the user and the insurance company.

[0140] Example input to a generative AI model

[0141] Prompt Sentence Examples

[0142] Using a specific example of a pet health management system, please explain in detail the procedures for measuring food intake, water intake, and excrement, and visualizing the data. Also, please include how to detect abnormalities based on this data and propose countermeasures.

[0143] The system is designed to enable users to efficiently and accurately manage the health status of their animals, detect abnormalities early, and take appropriate measures.

[0144] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0145] Program processing steps

[0146] Measuring food intake

[0147] Step 1:

[0148] The user prepares the cat food. The cat food has not yet been placed in the bowl. The input at this point is that the amount of cat food has not yet been measured.

[0149] Step 2:

[0150] The user places the container on the device's scale and resets the weight to 0 grams. Next, the user puts cat food into the container and measures its weight. The input is the weight of the container with the cat food in it, and the output is the measured weight of the cat food. The device acquires this data and sends it to the server.

[0151] Step 3:

[0152] The server records the received weight data of the meal in a database. The database is saved in the format of "2023-10-24 08:00, Meal, 75 grams", for example. The input of this step is the weight data of the cat food sent from the terminal, and the output is the record saved in the database.

[0153] Moisture measurement

[0154] Step 1:

[0155] The user prepares the water. The input is the amount of water not yet in the container.

[0156] Step 2:

[0157] The user places a container on the device's scale and resets the weight to 0 grams. Next, the user pours water into the container and measures its weight. The input is the weight of the water poured into the container, and the output is the measured weight of the water. The device captures this data and sends it to the server.

[0158] Step 3:

[0159] The server records the received water weight data in a database. The database is saved in the format, for example, "2023-10-24 08:05, water, 150 grams." The input of this step is the water weight data sent from the device, and the output is the record saved in the database.

[0160] Measurement of excrement

[0161] Step 1:

[0162] The user prepares the animal litter box and verifies that the sensor is working properly. The input is the sensor readiness state.

[0163] Step 2:

[0164] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. The input is the animal's excretion behavior, and the output is the measured weight of the urine and feces. The device collects this data and sends it to a server.

[0165] Step 3:

[0166] The server records the received excrement weight data in a database. For example, the database stores the data in the format "2023-10-24 09:00, urine, 50 grams" or "2023-10-24 09:00, feces, 20 grams." The input for this step is the excrement weight data sent from the device, and the output is the record stored in the database.

[0167] Data visualization

[0168] Step 1:

[0169] The server retrieves the stored data on food, water, and excrement. The input is the data stored in the database.

[0170] Step 2:

[0171] The server uses a data analysis algorithm to analyze the meaning of each piece of data and calculate daily nutritional and fluid intake. The input is the acquired measurement data, and the output is the analyzed nutritional and fluid intake.

[0172] Step 3:

[0173] The server generates graphs and tables based on the analysis results, and provides these visualizations in a user-accessible interface. The input is the analysis results, and the output is the visualized graphs and tables.

[0174] Step 4:

[0175] Users can check their animals' daily nutritional and water intake in graphs and tables via a web browser or dedicated app. The input is visualized data, and the output is the user's confirmation actions.

[0176] Anomaly detection and notification

[0177] Step 1:

[0178] The server periodically monitors the stored data to detect abnormal values ​​and patterns. The input is the stored data, and the output is the detected abnormal values ​​and patterns.

[0179] Step 2:

[0180] The data analysis algorithm detects data that is out of the normal range, such as a lower than normal amount of urine. The input is the monitored data, and the output is the anomaly detection result.

[0181] Step 3:

[0182] The server generates a notification to the user and the health care provider, such as "Your urine output is lower than normal, which may indicate dehydration." The input is the detected anomaly, and the output is the generated notification.

[0183] Step 4:

[0184] The server generates and sends the notification to the user's device and the insurance company. The input is the generated notification and the output is the sent notification.

[0185] Proposal for a solution

[0186] Step 1:

[0187] The server analyzes the type of anomaly detected. The input is the anomaly data, and the output is the recognition result of the type of anomaly.

[0188] Step 2:

[0189] The server proposes specific countermeasures and treatment methods according to the type of abnormality. For example, it generates a suggestion such as "Your animal may be dehydrated. Increase its water intake and consult a veterinarian if necessary." The input is the type of abnormality recognized, and the output is a suggested countermeasure.

[0190] Step 3:

[0191] The server notifies the user of the generated proposal. The input is the proposal, and the output is the sent proposal notification.

[0192] (Application example 1)

[0193] 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."

[0194] In recent years, there has been a demand for systems that allow pet owners to take appropriate measures quickly in pet health management. However, conventional systems often take a long time to accurately measure data on pets' diet, water intake, and excrement, and to detect and notify abnormalities. Furthermore, they lack a mechanism for effectively informing users of how to respond when an abnormality is detected. Furthermore, there has been a lack of coordination with pet supply stores, making it difficult to smoothly purchase necessary care products. The present invention aims to solve these problems and provide a system that allows pet owners to manage their pet's health more efficiently and accurately.

[0195] 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.

[0196] In this invention, the server includes a means for notifying the user of recommended products in cooperation with a physical pet supply store, a means for notifying the user of a response method based on the detected abnormality, and a means for displaying the data and notification via a smartphone terminal, thereby making it possible to monitor the health condition of a pet in real time and quickly suggest appropriate response methods and care products when an abnormality is detected.

[0197] A "means for weighing animal food" is a device or scale that allows an owner to accurately measure the weight of food that is given to a pet.

[0198] A "means for measuring an animal's water intake" is a device or scale for measuring the amount of water a pet drinks.

[0199] "Means for measuring the weight of animal excrement" refers to devices or sensors for measuring the weight of feces and urine excreted by pets.

[0200] The "means for storing measured data" refers to a device or server for recording and storing the measured data on food, water, and excretion.

[0201] "Means for visualizing daily nutritional and water intake" refers to a device or program that visually displays a pet's nutritional and water intake in graph or table format based on stored data.

[0202] An "anomaly detection means" is a device or algorithm that automatically analyzes and detects abnormal values ​​or patterns in stored data.

[0203] The "means for notifying abnormalities in cooperation with pet insurance" is a device or program for promptly notifying detected abnormalities in cooperation with the pet insurance system.

[0204] "Means for notifying users of recommended products in cooperation with physical pet supply stores" refers to a device or program that works in cooperation with physical stores to notify users of the most suitable pet supplies based on the health condition of their pet.

[0205] "Means for notifying the user of a response method based on an abnormality detection" refers to a device or program that, when an abnormality is detected, notifies the user of a specific method or treatment for responding to the abnormality.

[0206] "Means for displaying data and notifications via a smartphone device" refers to a device or application that uses a smartphone to communicate pet data and notifications to the user.

[0207] The present invention is a system for supporting pet health management. This system measures data on pet food and water intake and excrement, and stores and analyzes that data to visualize pet health conditions and enable rapid response if an abnormality is detected. This system also works in conjunction with pet insurance and pet supply stores to support users in providing appropriate care.

[0208] element

[0209] 1. Dietary Measurement Instruments:

[0210] The user uses a scale to accurately measure the weight of food to feed to their pet, and the device sends the measurement results to the server.

[0211] 2. Moisture measurement method:

[0212] A scale is also installed to measure the weight of the water users give to their pets, and the measurement results are also sent to the server.

[0213] 3. Waste Measurement Methods:

[0214] The pet toilet is equipped with sensors and a scale to measure the weight of the waste, and the measured data is sent to a server via the device.

[0215] 4. Data storage means:

[0216] The server receives and stores these measurement data, which are then stored in a cloud database for later access.

[0217] 5. Data visualization methods:

[0218] The server uses the stored data to display the pet's daily nutritional and water intake in graphs and tables, allowing users to visually check this data via their smartphone.

[0219] 6. Anomaly detection methods:

[0220] The server is equipped with data analysis algorithms that automatically detect outliers and patterns that fall outside the normal range, and if anomalies are found, a notification is sent to the user.

[0221] 7. Pet insurance collaboration methods:

[0222] If an abnormality is detected, the information is automatically sent to your pet insurance company, allowing you to quickly check whether your pet is covered.

[0223] 8. Proposal of a solution:

[0224] The server will suggest specific measures and treatments to the user depending on the type of abnormality, and this information will be sent to the user's smartphone.

[0225] 9. Pet supply store collaboration methods:

[0226] The server works in conjunction with physical stores to notify users of the best pet products based on their pet's health condition. This notification provides users with information to help them smoothly purchase the necessary pet care products.

[0227] Hardware and software used

[0228] Smartphone:

[0229] An interface device that displays data and notifies the user.

[0230] scale:

[0231] A device for measuring the weight of food and water.

[0232] sensor:

[0233] A device for measuring the weight of excrement.

[0234] server:

[0235] Computer devices that store and analyze data, including cloud databases.

[0236] Data analysis algorithms:

[0237] Software for detecting anomalies in data.

[0238] Specific examples

[0239] When a user gives their pet 75 grams of cat food in the morning, the weight is measured on a scale and the data is sent to the server. The server records this in the database as "2023-10-24 08:00, Meal, 75 grams." The next time the pet is given 150 grams of water, the weight is measured, sent, and recorded in the same way. When the pet defecates, the toilet sensor measures 50 grams of urine and 20 grams of feces, and each data is sent and recorded to the server. Based on this data, the server visualizes the day's nutritional and water intake, and if any abnormalities are detected, it notifies the user and the pet insurance company. At this time, the server sends a notification to the user's smartphone recommending pet products based on the pet's health condition.

[0240] Prompt Sentence Examples

[0241] I'd like to develop a pet health management app. I'd like to implement the following features:

[0242] 1. Measure the amount of food, water, and excretion consumed and record it in a database.

[0243] 2. Display the animal's health status in graphs and tables from the recorded data.

[0244] 3. Detect anomalies and notify the user.

[0245] 4. Work with pet insurance companies to automatically send information when abnormalities are detected.

[0246] Generate the code to build these features in Python.

[0247] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0248] Step 1:

[0249] When a user feeds an animal, they measure the weight of the food, such as cat food, on the scale on the device. The input is the measured weight of the food, which is sent to the device. The device then sends this data to the server and records it in a database. The output is the recorded weight data.

[0250] Step 2:

[0251] When a user gives water to an animal, the user measures the weight of the water on the scale of the device. The input is the measured weight of the water, which is sent to the device. The device then sends this data to the server and records it in the database. The output is the recorded weight of the water.

[0252] Step 3:

[0253] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. The input is the measured weight of the urine and feces, which is sent to a terminal. The terminal then sends this data to a server and records it in a database. The output is the recorded weight of the excrement.

[0254] Step 4:

[0255] The server visualizes the animals' daily nutrient and water intake in graphs and tables based on the diet, water, and excrement data stored in the database. The input is the data stored in the database, which the server analyzes and processes to convert into visual information. The output is visualized graphs and tables.

[0256] Step 5:

[0257] The server uses an anomaly detection algorithm to detect abnormal values ​​and patterns in the data stored in the database. The input is the analyzed data, which the server then checks for anomalies. The output is the presence or absence of detected anomalies and their specific contents.

[0258] Step 6:

[0259] If an anomaly is detected, the server notifies the user of the information. The input is the data of the detected anomaly, which the server sends to the user's smartphone. The output is a notification message to the user.

[0260] Step 7:

[0261] The server sends a notification to the pet insurance company based on the detected anomaly. The input is the detected anomaly data, which the server automatically sends to the insurance company's system. The output is the notification data to the insurance company.

[0262] Step 8:

[0263] The server proposes specific countermeasures and treatments to the user according to the type of abnormality. The input is the abnormality detection data, which the server analyzes and generates an appropriate countermeasure. The output is a suggested message that is displayed on the user's smartphone.

[0264] Step 9:

[0265] The server works in conjunction with physical stores to notify users of the best pet products based on their pet's health condition. The input is anomaly detection data, and the server works with pet supply stores to generate appropriate product information based on this data. The output is a notification of recommended products sent to the user's smartphone.

[0266] 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.

[0267] This invention relates to a system that supports the health management of pet animals and also takes into account the user's emotions. This system measures and stores data on the animal's diet and excretion, detects abnormalities, notifies users in conjunction with pet insurance, analyzes the user's emotional state, and suggests appropriate measures to take. To effectively implement this system, the following elements and procedures are included:

[0268] element

[0269] 1. Meal measuring means: A scale is installed on the terminal to measure the weight of the food that the user gives to the animal. This serves to measure the weight of the bowl before the animal eats the food.

[0270] 2. Water measurement means: A scale is installed on the terminal to measure the weight of the water that the user gives to the animal. This can measure the weight of the water before the animal drinks it.

[0271] 3. Waste measurement: Animal litter boxes are equipped with sensors and scales to measure the weight of feces and urine, allowing for accurate measurement of the amount of waste.

[0272] 4. Data storage: The measured data on food intake, water intake, and excrement is sent from the device to a server and stored in a database. The stored data can be accessed later.

[0273] 5. Data visualization: Based on the received data, the server displays the animals' daily nutrient and water intake in graphs and tables. This visualization can be viewed by the user via a web browser or a dedicated app.

[0274] 6. Anomaly detection: The server is equipped with data analysis algorithms that automatically detect abnormal values ​​and patterns that exceed the normal range in the stored data.

[0275] 7. Pet Insurance Integration: If an abnormality is detected, the information is automatically sent to the pet insurance company, allowing users to quickly check whether their pet is eligible for insurance coverage.

[0276] 8. Solution suggestion method: The server suggests specific solutions and treatments to the user depending on the type of abnormality. This information is sent to the user's terminal.

[0277] 9. Emotion engine means: Equipped with software for analyzing the user's emotional state, it estimates the user's emotions when using the application.

[0278] 10. Emotion data analysis method: Based on the emotional data analyzed by the emotion engine, the system adjusts the notification method and response method for abnormalities.

[0279] Program processing

[0280] Measuring food intake

[0281] When a user feeds an animal, the user uses the scale on the device to measure the weight of the cat food, etc. The device sends this data to the server, which then records the measurement data.

[0282] Moisture measurement

[0283] Similarly, when a user gives water to an animal, the device measures the weight of the water, and this data is also sent to the server and recorded.

[0284] Measurement of excrement

[0285] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces and sends this data via the device to a server, which then records the data.

[0286] Data visualization

[0287] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables, and users can check this data via a web browser or a dedicated app.

[0288] Anomaly detection and notification

[0289] If the server's data analysis algorithm detects abnormal values ​​or patterns in the measurement data, the information is notified to the user and the pet insurance company.

[0290] Proposal for a solution

[0291] If an abnormality is detected, the server will suggest and notify the user of specific countermeasures and treatments according to the type of abnormality.

[0292] Analyzing emotion data and adjusting notification methods

[0293] The emotion engine analyzes the user's emotional state and the data is reflected in the system. For example, if the user is feeling stressed, the server will adjust the notification method to be softer.

[0294] Specific examples

[0295] Suppose a user feeds their pet 75 grams of cat food in the morning. The device measures the weight on a scale and sends the data to the server. The server records the weight in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, sent, and recorded. Furthermore, when the pet defecates, the litter box sensor measures 50 grams of urine and 20 grams of feces, sending the respective data to the server. Based on this data, the server visualizes the day's nutritional and water intake and notifies the user and the pet insurance company if an abnormality is detected. The server then suggests specific measures to take depending on the abnormality. Furthermore, the emotion engine analyzes the user's emotional state and appropriately adjusts the notification method. For example, if the user is feeling stressed, notifications are adjusted to a gentler tone.

[0296] This system allows users to efficiently and accurately manage their animals' health, detect abnormalities early, and take appropriate measures.It also takes the user's emotional state into consideration, making management easier and less stressful.

[0297] The processing flow will be explained below.

[0298] Step 1:

[0299] The user places cat food into a bowl before feeding the animal.

[0300] Step 2:

[0301] The weight of the cat food in the bowl is measured using a scale installed on the terminal.

[0302] Step 3:

[0303] The device sends the measured weight of the meal (for example, 75 grams) to the server as data.

[0304] Step 4:

[0305] The server records the received data in the database as "2023-10-24 08:00, meal, 75 grams."

[0306] Step 5:

[0307] The user fills the water bowl before giving the animal water.

[0308] Step 6:

[0309] The weight of the water container is measured using a scale installed on the terminal.

[0310] Step 7:

[0311] The device sends the measured weight of the water (for example, 150 grams) to the server as data.

[0312] Step 8:

[0313] The server records the received data in the database as "2023-10-24 08:05, water, 150 grams."

[0314] Step 9:

[0315] Animals use the toilet to excrete urine and feces.

[0316] Step 10:

[0317] A sensor built into the toilet measures the weight of urine and feces.

[0318] Step 11:

[0319] The device sends the measured weight of the urine and feces (e.g., 50 grams of urine and 20 grams of feces) as data to the server.

[0320] Step 12:

[0321] The server records the received data in the database as "2023-10-24 18:00, urine, 50 grams" and "2023-10-24 18:05, feces, 20 grams."

[0322] Step 13:

[0323] At the end of the day, the server visualizes the animal's total food intake, water intake, urine volume, and feces volume based on the stored data.

[0324] Step 14:

[0325] Users can check their daily total data through a web browser or a dedicated app.

[0326] Step 15:

[0327] The server uses a data analysis algorithm to analyze the stored data and detect abnormal values ​​and patterns.

[0328] Step 16:

[0329] If an abnormality is detected, the server notifies the user and the pet insurance company of the information.

[0330] Step 17:

[0331] The server proposes specific countermeasures and treatment methods depending on the type of abnormality and notifies the user of this information.

[0332] Step 18:

[0333] When a user accesses the dedicated app, the emotion engine analyzes the user's facial expressions and input data to estimate their emotional state.

[0334] Step 19:

[0335] The device transmits the emotion data analyzed by the emotion engine to the server.

[0336] Step 20:

[0337] The server stores the analyzed emotional data and adjusts the notification method based on the user's emotional state. For example, if the user is stressed, the notification will be delivered in a gentler tone.

[0338] The above are the specific processing steps based on the claims. This system allows users to efficiently and accurately manage the health status of their animals, detect abnormalities early and take appropriate measures, and even provides pleasant notifications that take into account the emotional state of the animals.

[0339] Example 2

[0340] 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."

[0341] While conventional animal health management systems have the ability to measure and record the amount of food and water intake and excrement of animals, they lack sufficient means for comprehensively managing the health of animals. Furthermore, while early response and appropriate measures are required when abnormalities in an animal's health are detected, methods for doing so are limited. Furthermore, since no systems exist that take the user's emotional state into consideration, a management method that is less stressful for users is needed.

[0342] 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.

[0343] In this invention, the server includes means for measuring the weight of the animal's food, means for measuring the animal's water intake, means for measuring the weight of the animal's waste, means for storing the measured data, means for visualizing the daily nutrient and water intake based on the stored data, means for detecting abnormalities based on the visualized data, means for notifying the insurance company of the abnormality in cooperation with the insurance company, means for analyzing the user's emotional state, and means for adjusting the notification method based on the analyzed emotional state data. This enables efficient and accurate management of the animal's health, early detection of abnormalities, and appropriate countermeasures. Furthermore, by taking the user's emotional state into consideration, management can be made easier to use and less stressful.

[0344] "Means for weighing animal food" means any device or equipment used to accurately measure the weight of food provided to an animal.

[0345] "Means for measuring animal water intake" refers to a device or instrument that accurately measures the amount of water consumed by an animal.

[0346] "Means for weighing animal waste" refers to a device or instrument that accurately measures the weight of feces or urine excreted by an animal.

[0347] "Means for storing the measured data" refers to a storage device or cloud database for storing measured data on food, water, and excrement over a long period of time.

[0348] "Means for visualizing daily nutrient and water intake amounts based on the stored data" refers to software or tools for visually displaying an animal's daily nutrient and water intake amounts based on the stored data.

[0349] "Means for detecting anomalies based on the visualized data" refers to algorithms or software for analyzing the visualized data and detecting abnormal values ​​or patterns that exceed the normal range.

[0350] "Means for coordinating with and notifying the insurance company of the abnormality" refers to a communication system or program that automatically sends information about an abnormality to the insurance company when it is detected.

[0351] "Means for analyzing the user's emotional state" refers to software, algorithms, and sensors for analyzing the user's emotional state.

[0352] "Means for adjusting the notification method based on the analyzed emotional state data" refers to a system or algorithm for adjusting the wording or method of notifications based on the analyzed emotional state data of the user.

[0353] This invention relates to a system that supports animal health management and takes into account the emotional state of the user. This system measures and stores the amount of food and water intake and excrement of the animal, visualizes the data, detects abnormalities, and also includes collaboration with pet insurance companies and analysis and adjustment of the user's emotional state.

[0354] Overall structure

[0355] The system includes the following elements:

[0356] 1. Food measurement method: A scale is installed on the terminal to measure the weight of the food that the user gives to the animal. A digital scale (e.g., a general digital scale) and a Python library (e.g., pySerial) are used.

[0357] 2. Water measurement means: A scale is installed on the terminal to measure the amount of water the user gives to the animal. It uses the same equipment and software as a digital scale.

[0358] 3. Waste measurement: The animal's litter box has built-in sensors (e.g., load cell sensors) and scales to measure the weight of feces and urine. Python libraries (e.g., Rpi.GPIO) are used.

[0359] 4. Data storage method: The measured data on food intake, water intake, and excrement is sent from the device to a server and stored in a database using a database such as MySQL (registered trademark) or PostgreSQL.

[0360] 5. Data visualization: Based on the received data, the server displays the animals' daily nutrient and water intake in graphs and tables. JavaScript (registered trademark) libraries (e.g., Chart.js, D3.js) are used.

[0361] 6. Anomaly detection means: The server is equipped with data analysis algorithms (e.g., scikit-learn, TENSORFLOW (registered trademark)) that automatically detect abnormal values ​​and patterns that exceed the normal range from the stored data.

[0362] 7. Insurance collaboration notification method: When an anomaly is detected, API collaboration or email services (e.g., SendGrid) are used to automatically send information to the insurance company.

[0363] 8. Response suggestion method: Specific response methods and treatments are suggested to the user depending on the type of abnormality. Using rule-based approaches and machine learning models.

[0364] 9. Sentiment Analysis Engine Means: Software and algorithms that analyze the user's emotional state (e.g., using NLP techniques, sentiment analysis libraries (e.g., NLTK, TextBlob)).

[0365] 10. Notification Tailoring: Systems and algorithms for tailoring notification language and delivery based on analyzed emotional state data.

[0366] Specific examples

[0367] Suppose a user feeds their pet 75 grams of cat food in the morning. The device measures the weight on a scale and sends the data to the server. The server records the weight in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, sent, and recorded. Furthermore, when the pet defecates, the litter box sensor measures 50 grams of urine and 20 grams of feces, and sends and records the respective data to the server. Based on this data, the server visualizes the day's nutritional and water intake and notifies the user and insurance company if an abnormality is detected. The server then suggests specific measures to take depending on the abnormality. Furthermore, an emotion analysis engine analyzes the user's emotional state and appropriately adjusts the notification method. For example, if the user is feeling stressed, notifications are adjusted to a gentler tone.

[0368] Prompt Sentence Examples

[0369] "Please tell us the specific steps of a system that helps manage the health of pet animals and takes user emotions into consideration. Also, please specify the specific hardware and software you will use."

[0370] This system allows users to efficiently and accurately manage the health of their animals, detect abnormalities early, and take appropriate measures.It also takes the user's emotional state into consideration, making management easier to use and less stressful.

[0371] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0372] Step 1: Measuring your food intake

[0373] When a user feeds an animal, the user uses the scale on the device to measure the weight of the cat food. The input is the cat food that the user places on the scale, and the output is the measured weight (for example, 75 grams). The device sends this data to the server, which records the measurement data in a database. Specifically, when the user places the cat food on the scale, the device measures the weight and sends the measurement result to the server. The server saves this in the database as "2023-10-24 08:00, Meal, 75 grams."

[0374] Step 2: Measure moisture content

[0375] When a user gives water to an animal, the terminal measures the weight of the water. The input is the water the user places on the scale, and the output is the measured weight (for example, 150 grams). The terminal sends this data to the server, which records the measurement data in a database. Specifically, when the user places water on the scale, the terminal measures the weight and sends the measurement result to the server. The server saves the data in the database as "2023-10-24 08:05, water, 150 grams."

[0376] Step 3: Measuring feces

[0377] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. The input is the urine and feces excreted by the animal into the toilet, and the output is the measured weight (for example, 50 grams of urine and 20 grams of feces). The terminal sends this data to a server, which records the measured data in a database. Specifically, when an animal uses the toilet, the sensor measures the weight of the urine and feces and sends the measurement results to the server. The server saves the data in the database as "2023-10-24 12:00, urine, 50 grams" and "2023-10-24 12:05, feces, 20 grams."

[0378] Step 4: Save your data

[0379] The server receives all measurement data sent from the terminal and stores it in a database. The input is the measurement data sent from the terminal, and the output is the data recorded in the database. Specifically, the server receives the measurement data and accurately records and stores it in the database.

[0380] Step 5: Visualize the data

[0381] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables. The input is the measurement data stored in the database, and the output is visualized data (graphs and tables). Users can check this data through a web browser or a dedicated app. Specifically, the server extracts data from the database, visualizes it using a JavaScript library, and displays it in the user's browser or app.

[0382] Step 6: Detect anomalies

[0383] The server uses data analysis algorithms to automatically detect outliers and patterns from the stored data. The input is the measurement data stored in the database, and the output is the detected anomaly information. Specifically, the server analyzes the data using scikit-learn and TensorFlow to detect values ​​and patterns that are outside the normal range.

[0384] Step 7: Insurance Linkage Notification

[0385] If the server detects an anomaly, it automatically sends that information to the insurance company. The input is the detected anomaly information, and the output is the notification sent to the insurance company. Specifically, the server sends the anomaly information using the insurance company's API, or notifies the company using an email service.

[0386] Step 8: Propose a course of action

[0387] When an abnormality is detected, the server proposes specific countermeasures and treatments to the user depending on the type of abnormality. The input is the detected abnormality information, and the output is the proposed countermeasure. Specifically, the server generates a countermeasure using a pre-configured rule-based model or machine learning model and notifies the user.

[0388] Step 9: Analyze emotion data and adjust notification methods

[0389] The server uses an emotion engine to analyze the user's emotional state and adjust the notification method. The input is the user's emotional data, and the output is the adjusted notification method. Specifically, the server uses NLP technology and an emotion analysis library to estimate the user's emotional state, and adjusts the content and tone of the notification based on the results.

[0390] (Application example 2)

[0391] 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."

[0392] It is difficult to accurately manage the health status of animals in animal health management facilities such as pet shops. It is also necessary to notify staff and insurance agencies of this information in a timely manner, and to provide an appropriate notification method that reflects the emotional state of users (staff and owners). Conventional systems have difficulty meeting these diverse requirements, so a system is needed that efficiently and accurately manages the health status of animals and reduces the psychological burden on those involved.

[0393] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for measuring the weight of the animal's food, means for measuring the amount of water the animal consumes, means for measuring the weight of the animal's waste, means for storing the measured data, means for visualizing the daily nutrient intake and water intake based on the stored data, means for detecting abnormalities based on the visualized data, means for notifying the abnormality to a cooperating insurance company, and means for supporting animal health management at an animal health management facility, analyzing the emotional state of a facility staff member, and adjusting an appropriate notification method. This enables efficient and accurate management of the animal's health status, enables rapid response to abnormalities and smooth collaboration with insurance companies, and enables notifications that take the emotional state of the staff member into consideration.

[0394] "Means for measuring the weight of food given to animals" refers to a device that measures the weight of food given to animals using a sensor or scale attached to a feeder.

[0395] A "means for measuring the amount of water consumed by an animal" is a device that uses a sensor or scale installed at the water trough to measure the amount of water an animal drinks.

[0396] A "means for measuring the weight of animal excrement" is a device that uses sensors or scales installed in the animal's litter box to measure the weight of animal excrement such as feces and urine.

[0397] "Means for storing measured data" refers to a system that stores measured data such as food intake, water intake, and amount of excrement in a database or on the cloud.

[0398] The "means for visualizing daily nutritional and water intake" is a system that uses stored data to display an animal's daily food and water intake in graphs and tables, allowing it to be visually confirmed.

[0399] "Means for detecting anomalies" refers to algorithms or programs that analyze measurement data and automatically detect abnormal data or patterns that exceed the normal range.

[0400] The "means of notifying affiliated insurance companies" refers to a system that automatically sends information to insurance companies that hold insurance contracts for animals when an abnormality is detected.

[0401] "Animal health management support means" refers to a series of devices and systems that effectively manage the health of animals based on measurement data on their food, water intake, and excretion.

[0402] The "means for analyzing the emotional state of personnel" refers to software or algorithms for analyzing the emotional state of users who operate the system, such as facility staff or animal owners.

[0403] The "means for adjusting the appropriate notification method" is a system for notifying the user in the most appropriate way according to their emotional state based on the analyzed emotional data.

[0404] To implement this invention, it is necessary to build a system with multiple measurement means that can analyze the user's emotional state and provide appropriate notification methods, as well as manage the animal's health.

[0405] System configuration

[0406] The system mainly consists of the following hardware and software:

[0407] Food weighing device: A scale attached to the feeder to measure the weight of the animal's food.

[0408] Water measuring device: a scale to measure the amount of water an animal consumes. This is placed at the water trough.

[0409] Waste measurement means: sensors and scales built into the litter box used by animals.

[0410] Data storage means: A database for storing measured data. A cloud database is used.

[0411] Visualization method: Using a data analysis algorithm on the server, daily nutritional and water intake amounts are displayed in graphs and tables.

[0412] Anomaly detection method: An algorithm that analyzes measurement data and automatically detects anomalies outside the normal range.

[0413] Notification method: A system that notifies collaborating insurance companies when an abnormality is detected.

[0414] Emotion analysis tool: Software for analyzing the user's emotional state.

[0415] Notification method adjustment means: A system that adjusts the notification method based on the analyzed emotion data.

[0416] Example

[0417] As an example of the system, the following steps are followed.

[0418] Meal Measurement

[0419] When a user feeds an animal, they use a scale attached to the device to measure the weight of the cat food, etc. The measurement data is automatically sent to the server and recorded in a database.

[0420] Moisture measurement

[0421] Similarly, the amount of water is measured using a scale installed on the device, and this measurement data is also sent to the server and stored.

[0422] excrement measurement

[0423] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces and sends the data to a server for recording.

[0424] Data visualization

[0425] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables, and users can check this data via a web browser or a dedicated app.

[0426] Anomaly detection and notification

[0427] The server's data analysis algorithm automatically detects abnormal values ​​and patterns in the measurement data, and if an abnormality is detected, the information is automatically notified to the pet insurance company.

[0428] Proposal for a solution

[0429] If an abnormality is detected, the server notifies the user of specific countermeasures and treatments according to the type of abnormality.

[0430] Analyzing emotion data and adjusting notification methods

[0431] Emotion analysis software analyzes the user's emotional state and adjusts notifications based on that data - for example, if the user is stressed, notifications will be adjusted to a gentler tone.

[0432] Examples and prompts

[0433] As a concrete example, consider the case of managing the health of animals in a pet shop. When a pet shop staff member gives an animal 75 grams of cat food, they measure it on a scale on their device and send the data to a server. Based on the data, the server will suggest appropriate measures to take and adjust the notification content if an abnormality is detected.

[0434] An example of a prompt for a generative AI model is as follows:

[0435] text

[0436] A pet shop has implemented a system that measures the amount of food and water intake and waste produced by animals, and detects abnormalities based on health management data. If an abnormality is detected, staff are notified and the system coordinates with the pet insurance company. Staff who appear stressed are also notified in a gentle tone. As a concrete example, please demonstrate the process of measuring 75 grams of cat food, 150 grams of water, and 70 grams of waste, detecting abnormalities, and suggesting how to address them.

[0437] This prompt sentence helps the generative AI model to gain a deeper understanding of the system's operational flow and behavior.

[0438] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0439] Step 1:

[0440] The user uses the scale on the device to measure the weight of the food to be given to the animal. The input is the amount of food, such as cat food, and the output is the measured weight data. This measurement data is converted into digital data within the device so that the weight of the cat food is recorded accurately.

[0441] Step 2:

[0442] The device sends the measured weight data to the server. The input is the measured data, and the output is the data stored in the cloud database. The transmission protocol is HTTP request, and the data is securely stored on the server.

[0443] Step 3:

[0444] Similarly, the user weighs the amount of water to give to the animal on a scale. The input is the amount of water, and the output is the measured weight. This data is also converted into digital data by the terminal.

[0445] Step 4:

[0446] The device sends the measured water weight data to the server. The input is the data measured earlier, and the output is the data to be saved in the cloud database. The transmission is also done using an HTTP request.

[0447] Step 5:

[0448] When an animal uses the toilet, a sensor inside the toilet measures the weight of the waste (urine and feces). The input is the amount of waste, and the output is the measured weight. This data is converted into digital data by the sensor inside the toilet.

[0449] Step 6:

[0450] The device sends the measured excrement weight data to the server. The input is the measured data, and the output is the data stored in the cloud database. The measured data is sent to the server using a secure communication protocol.

[0451] Step 7:

[0452] The server visualizes the animals' daily nutritional and water intake based on the stored data. The input is data stored in a cloud database, and the output is visualized data displayed in graphs and tables. Data analysis algorithms handle this process and convert the data into an easy-to-understand format.

[0453] Step 8:

[0454] The server's data analysis algorithm automatically detects abnormal values ​​and patterns in the measurement data. The input is daily nutrition and fluid intake data, and the output is the anomaly detection results. Statistical methods and machine learning algorithms are used to identify abnormal patterns.

[0455] Step 9:

[0456] If an anomaly is detected, the server automatically notifies the insurance company of that information. The input is the anomaly detection result, and the output is a notification message to the insurance company. Notifications are sent via email, API calls, etc.

[0457] Step 10:

[0458] The server proposes specific measures to the user (staff or owner) depending on the type of abnormality. The input at this time is the type of abnormality and its detailed information, and the output is a message proposing measures and treatment. The measures are determined by referring to prescription examples stored in a database in advance.

[0459] Step 11:

[0460] Emotion analysis software installed on the device is used to analyze the user's emotional state. The input is the user's operation log and facial expression data, and the output is analyzed emotional state data. Emotion analysis uses machine learning algorithms and NLP (natural language processing) technology.

[0461] Step 12:

[0462] The server adjusts the notification method based on the analyzed emotional data. The input is the analyzed emotional state data, and the output is an adjusted notification message. For example, if the user is feeling stressed, a notification with a gentler tone is generated. This reduces the user's psychological burden.

[0463] 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.

[0464] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0465] 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.

[0466] [Second embodiment]

[0467] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0468] 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.

[0469] 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).

[0470] 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.

[0471] 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.

[0472] 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).

[0473] 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.

[0474] 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.

[0475] 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.

[0476] 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.

[0477] 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.

[0478] 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."

[0479] This invention relates to a system that supports the health management of pet animals. This system measures and stores data on the animals' diet and excretion, detects abnormalities, and notifies users in cooperation with pet insurance. To effectively implement this system, the following elements and procedures are included:

[0480] element

[0481] 1. Meal measuring means: A scale is installed on the terminal to measure the weight of the food that the user gives to the animal. This serves to measure the weight of the bowl before the animal eats the food.

[0482] 2. Water measurement means: A scale is installed on the terminal to measure the weight of the water that the user gives to the animal. This can measure the weight of the water before the animal drinks it.

[0483] 3. Waste measurement: Animal litter boxes are equipped with sensors and scales to measure the weight of feces and urine, allowing for accurate measurement of the amount of waste.

[0484] 4. Data storage: The measured data on food intake, water intake, and excrement is sent from the device to a server and stored in a database. The stored data can be accessed later.

[0485] 5. Data visualization: Based on the received data, the server displays the animals' daily nutrient and water intake in graphs and tables. This visualization can be viewed by the user via a web browser or a dedicated app.

[0486] 6. Anomaly detection: The server is equipped with data analysis algorithms that automatically detect abnormal values ​​and patterns that exceed the normal range in the stored data.

[0487] 7. Pet Insurance Integration: If an abnormality is detected, the information is automatically sent to the pet insurance company, allowing users to quickly check whether their pet is eligible for insurance coverage.

[0488] 8. Solution suggestion method: The server suggests specific solutions and treatments to the user depending on the type of abnormality. This information is sent to the user's terminal.

[0489] Program processing

[0490] Measuring food intake

[0491] When a user feeds an animal, the user uses the scale on the device to measure the weight of the cat food, etc. The device sends this data to the server, which then records the measurement data.

[0492] Moisture measurement

[0493] Similarly, when a user gives water to an animal, the device measures the weight of the water, and this data is also sent to the server and recorded.

[0494] Measurement of excrement

[0495] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces and sends this data via the device to a server, which then records the data.

[0496] Data visualization

[0497] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables, and users can check this data via a web browser or a dedicated app.

[0498] Anomaly detection and notification

[0499] If the server's data analysis algorithm detects abnormal values ​​or patterns in the measurement data, the information is notified to the user and the pet insurance company.

[0500] Proposal for a solution

[0501] If an abnormality is detected, the server will suggest and notify the user of specific countermeasures and treatments according to the type of abnormality.

[0502] Specific examples

[0503] Let's say a user gives their pet 75 grams of cat food in the morning. At this time, the device measures the weight on a scale and sends the data to the server. The server records this in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, sent, and recorded. Furthermore, when the pet defecates, the toilet sensor measures 50 grams of urine and 20 grams of feces, and each data is sent and recorded to the server. Based on this data, the server visualizes the amount of nutritional and water intake for that day, and if any abnormalities are detected, it notifies the user and the pet insurance company.

[0504] The above is a detailed description of the embodiment of the present invention. This system allows users to efficiently and accurately manage the health status of their animals, detect abnormalities early, and take appropriate measures.

[0505] The processing flow will be explained below.

[0506] Step 1:

[0507] The user places cat food into a bowl before feeding the animal.

[0508] Step 2:

[0509] The weight of the cat food in the bowl is measured using a scale installed on the terminal.

[0510] Step 3:

[0511] The device sends the measured weight of the meal (for example, 75 grams) to the server as data.

[0512] Step 4:

[0513] The server records the received data in the database as "2023-10-24 08:00, meal, 75 grams."

[0514] Step 5:

[0515] The user fills the water bowl before giving the animal water.

[0516] Step 6:

[0517] The weight of the water container is measured using a scale installed on the terminal.

[0518] Step 7:

[0519] The device sends the measured weight of the water (for example, 150 grams) to the server as data.

[0520] Step 8:

[0521] The server records the received data in the database as "2023-10-24 08:05, water, 150 grams."

[0522] Step 9:

[0523] Animals use the toilet to excrete urine and feces.

[0524] Step 10:

[0525] A sensor built into the toilet measures the weight of urine and feces.

[0526] Step 11:

[0527] The device sends the measured weight of the urine and feces (e.g., 50 grams of urine and 20 grams of feces) as data to the server.

[0528] Step 12:

[0529] The server records the received data in the database as "2023-10-24 18:00, urine, 50 grams" and "2023-10-24 18:05, feces, 20 grams."

[0530] Step 13:

[0531] At the end of the day, the server visualizes the animal's total food intake, water intake, urine volume, and feces volume based on the stored data.

[0532] Step 14:

[0533] Users can check their daily total data through a web browser or a dedicated app.

[0534] Step 15:

[0535] The server uses a data analysis algorithm to analyze the stored data and detect abnormal values ​​and patterns.

[0536] Step 16:

[0537] If an abnormality is detected, the server notifies the user and the pet insurance company of the information.

[0538] Step 17:

[0539] The server proposes specific countermeasures and treatment methods depending on the type of abnormality and notifies the user of this information.

[0540] This allows users to monitor the health of their animals in real time and take appropriate action quickly if any abnormalities are detected.

[0541] Example 1

[0542] 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."

[0543] In today's pet industry, it is difficult to efficiently and accurately manage the health of animals. Accurate data on food intake, water intake, and excrement must be collected, and any abnormalities must be detected early to allow appropriate measures to be taken. Furthermore, if an abnormality is detected, prompt action must be proposed and, if necessary, cooperation with an insurance agency must be coordinated. However, conventional systems are unable to fully meet these requirements, creating multiple challenges in pet health management.

[0544] 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.

[0545] In this invention, the server includes: means for measuring the animal's nutrient intake, means for measuring the animal's water intake, means for measuring the amount of animal waste; means for storing the measured data; means for visualizing daily nutrient and water intake based on the stored data; means for detecting abnormalities based on the visualized data; means for notifying an insurance company of the abnormality; means for proposing a response method according to the type of abnormality when the abnormality is detected; means for storing the measured data in a cloud database; means for analyzing the data stored in the cloud database to identify abnormal values ​​or patterns; and means for generating and transmitting notifications based on the identified abnormal values ​​or patterns. This allows for detailed and real-time monitoring of the animal's health, enabling early detection and prompt response to abnormalities. Furthermore, by linking with an insurance company, insurance coverage can be quickly confirmed, realizing comprehensive health management of pets.

[0546] "Animals" refers to living creatures such as mammals, birds, and reptiles kept as pets.

[0547] "Means for measuring nutrient intake" refers to a device or system used to measure the amount of food given to an animal.

[0548] "Means for measuring water intake" refers to a device or system for measuring the amount of water provided to an animal.

[0549] "Means for measuring the amount of waste" refers to sensors or devices for measuring the amount of urine or feces excreted by an animal.

[0550] "Means for storing measured data" refers to a storage system for recording the measured data and keeping it in a state where it can be accessed later.

[0551] "Visualization means" refers to devices or systems for visually displaying measured data, such as interfaces that display data in graph or table format.

[0552] "Anomaly detection methods" refers to data analysis algorithms or devices that identify and alert on abnormal values ​​or patterns that fall outside of the normal range.

[0553] "Means for linking and notifying insurance organizations" refers to systems or devices that notify insurance companies of detected abnormal values ​​or patterns to expedite insurance coverage confirmation.

[0554] "Means for proposing a countermeasure according to the type of abnormality" refers to a device or system for proposing specific countermeasures or treatment methods to the user based on the detected abnormality.

[0555] "Cloud database" refers to data storage that is remotely accessible via the internet.

[0556] "Means for analyzing data to identify outliers and patterns" refers to systems or software that analyze stored data and automatically detect values ​​that deviate from normal ranges or specific patterns.

[0557] "Means for generating and sending notifications" refers to a system or device for generating notifications based on detected anomalies or patterns and sending them to a user device or insurance organization.

[0558] MODE FOR CARRYING OUT THE INVENTION

[0559] This invention relates to a system that supports the health management of pet animals. This system measures and stores data on the animals' food intake, water intake, and excrement, detects abnormalities, and coordinates with insurance agencies. The following elements are required for the system to be implemented effectively:

[0560] element

[0561] 1. Meal measurement means: The user uses a scale installed on the terminal to measure the amount of food to be given to the animal. This is used to measure the weight of the bowl or container before the animal eats the food.

[0562] 2. Water measuring means: The user uses a scale also installed on the terminal to measure the amount of water to be given to the animal. This scale can measure the weight of the container into which water is poured.

[0563] 3. Waste measurement device: The litter boxes used by animals are equipped with sensors that measure the weight of feces and urine, allowing for accurate measurement of the amount of waste.

[0564] 4. Data storage: The measured data on food intake, water intake, and excrement is sent from the device to a server, which stores it in a cloud database. The stored data can be accessed later.

[0565] 5. Data visualization: Based on the received data, the server displays the animals' daily nutrient and water intake in graphs and tables. This visualization can be viewed by the user via a web browser or a dedicated app.

[0566] 6. Anomaly detection method: The server uses data analysis algorithms to detect abnormal values ​​and patterns in the stored data.

[0567] 7. Insurance Linkage: If an anomaly is detected, the information is automatically sent to insurance companies, allowing users to quickly check for potential insurance coverage.

[0568] 8. Solution suggestion method: The server suggests specific solutions and treatment methods to the user depending on the type of abnormality. This information is sent to the user's terminal.

[0569] Specific actions

[0570] Measuring food intake

[0571] The user measures the amount of food, such as cat food, that they give to their animal. Before putting the cat food into a bowl, the user resets the scale installed on the terminal and sets the weight of the bowl to 0 grams. Next, the user puts the cat food into the bowl and measures its weight. The terminal sends the measurement results to the server, which records the data.

[0572] Moisture measurement

[0573] Similarly, a user measures the amount of water given to an animal. The user places the container on the device's scale and resets the weight to 0 grams. Then, the user pours water into the container and measures its weight. The device sends the measurement result to the server, which records the data.

[0574] Measurement of excrement

[0575] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. This measurement data is sent via the device to a server, which then records the data.

[0576] Data visualization

[0577] The server visualizes the animals' daily nutritional and water intake based on the stored data, and users can check this data via a web browser or a dedicated app.

[0578] Anomaly detection and notification

[0579] If the server's data analysis algorithm detects abnormal values ​​or patterns in the measurement data, the information is notified to the user and insurance organization.

[0580] Proposal for a solution

[0581] If an abnormality is detected, the server will suggest specific countermeasures and treatment methods according to the type of abnormality to the user and notify them of this information.

[0582] Specific examples

[0583] Let's say a user gives their pet 75 grams of cat food in the morning. At this time, the scale on the device measures the weight of the cat food and sends that data to the server. The server records this in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, and the data is sent and recorded. Furthermore, when the pet defecates, the sensor in the litter box measures 50 grams of urine and 20 grams of feces, and each data is sent to the server and recorded. Based on this data, the server visualizes the day's nutritional and water intake, and if any abnormalities are detected, it notifies the user and the insurance company.

[0584] Example input to a generative AI model

[0585] Prompt Sentence Examples

[0586] Using a specific example of a pet health management system, please explain in detail the procedures for measuring food intake, water intake, and excrement, and visualizing the data. Also, please include how to detect abnormalities based on this data and propose countermeasures.

[0587] The system is designed to enable users to efficiently and accurately manage the health status of their animals, detect abnormalities early, and take appropriate measures.

[0588] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0589] Program processing steps

[0590] Measuring food intake

[0591] Step 1:

[0592] The user prepares the cat food. The cat food has not yet been placed in the bowl. The input at this point is that the amount of cat food has not yet been measured.

[0593] Step 2:

[0594] The user places the container on the device's scale and resets the weight to 0 grams. Next, the user puts cat food into the container and measures its weight. The input is the weight of the container with the cat food in it, and the output is the measured weight of the cat food. The device acquires this data and sends it to the server.

[0595] Step 3:

[0596] The server records the received weight data of the meal in a database. The database is saved in the format of "2023-10-24 08:00, Meal, 75 grams", for example. The input of this step is the weight data of the cat food sent from the terminal, and the output is the record saved in the database.

[0597] Moisture measurement

[0598] Step 1:

[0599] The user prepares the water. The input is the amount of water not yet in the container.

[0600] Step 2:

[0601] The user places a container on the device's scale and resets the weight to 0 grams. Next, the user pours water into the container and measures its weight. The input is the weight of the water poured into the container, and the output is the measured weight of the water. The device captures this data and sends it to the server.

[0602] Step 3:

[0603] The server records the received water weight data in a database. The database is saved in the format, for example, "2023-10-24 08:05, water, 150 grams." The input of this step is the water weight data sent from the device, and the output is the record saved in the database.

[0604] Measurement of excrement

[0605] Step 1:

[0606] The user prepares the animal litter box and verifies that the sensor is working properly. The input is the sensor readiness state.

[0607] Step 2:

[0608] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. The input is the animal's excretion behavior, and the output is the measured weight of the urine and feces. The device collects this data and sends it to a server.

[0609] Step 3:

[0610] The server records the received excrement weight data in a database. For example, the database stores the data in the format "2023-10-24 09:00, urine, 50 grams" or "2023-10-24 09:00, feces, 20 grams." The input for this step is the excrement weight data sent from the device, and the output is the record stored in the database.

[0611] Data visualization

[0612] Step 1:

[0613] The server retrieves the stored data on food, water, and excrement. The input is the data stored in the database.

[0614] Step 2:

[0615] The server uses a data analysis algorithm to analyze the meaning of each piece of data and calculate daily nutritional and fluid intake. The input is the acquired measurement data, and the output is the analyzed nutritional and fluid intake.

[0616] Step 3:

[0617] The server generates graphs and tables based on the analysis results, and provides these visualizations in a user-accessible interface. The input is the analysis results, and the output is the visualized graphs and tables.

[0618] Step 4:

[0619] Users can check their animals' daily nutritional and water intake in graphs and tables via a web browser or dedicated app. The input is visualized data, and the output is the user's confirmation actions.

[0620] Anomaly detection and notification

[0621] Step 1:

[0622] The server periodically monitors the stored data to detect abnormal values ​​and patterns. The input is the stored data, and the output is the detected abnormal values ​​and patterns.

[0623] Step 2:

[0624] The data analysis algorithm detects data that is out of the normal range, such as a lower than normal amount of urine. The input is the monitored data, and the output is the anomaly detection result.

[0625] Step 3:

[0626] The server generates a notification to the user and the health care provider, such as "Your urine output is lower than normal, which may indicate dehydration." The input is the detected anomaly, and the output is the generated notification.

[0627] Step 4:

[0628] The server generates and sends the notification to the user's device and the insurance company. The input is the generated notification and the output is the sent notification.

[0629] Proposal for a solution

[0630] Step 1:

[0631] The server analyzes the type of anomaly detected. The input is the anomaly data, and the output is the recognition result of the type of anomaly.

[0632] Step 2:

[0633] The server proposes specific countermeasures and treatment methods according to the type of abnormality. For example, it generates a suggestion such as "Your animal may be dehydrated. Increase its water intake and consult a veterinarian if necessary." The input is the type of abnormality recognized, and the output is a suggested countermeasure.

[0634] Step 3:

[0635] The server notifies the user of the generated proposal. The input is the proposal, and the output is the sent proposal notification.

[0636] (Application example 1)

[0637] 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."

[0638] In recent years, there has been a demand for systems that allow pet owners to take appropriate measures quickly in pet health management. However, conventional systems often take a long time to accurately measure data on pets' diet, water intake, and excrement, and to detect and notify abnormalities. Furthermore, they lack a mechanism for effectively informing users of how to respond when an abnormality is detected. Furthermore, there has been a lack of coordination with pet supply stores, making it difficult to smoothly purchase necessary care products. The present invention aims to solve these problems and provide a system that allows pet owners to manage their pet's health more efficiently and accurately.

[0639] 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.

[0640] In this invention, the server includes a means for notifying the user of recommended products in cooperation with a physical pet supply store, a means for notifying the user of a response method based on the detected abnormality, and a means for displaying the data and notification via a smartphone terminal, thereby making it possible to monitor the health condition of a pet in real time and quickly suggest appropriate response methods and care products when an abnormality is detected.

[0641] A "means for weighing animal food" is a device or scale that allows an owner to accurately measure the weight of food that is given to a pet.

[0642] A "means for measuring an animal's water intake" is a device or scale for measuring the amount of water a pet drinks.

[0643] "Means for measuring the weight of animal excrement" refers to devices or sensors for measuring the weight of feces and urine excreted by pets.

[0644] The "means for storing measured data" refers to a device or server for recording and storing the measured data on food, water, and excretion.

[0645] "Means for visualizing daily nutritional and water intake" refers to a device or program that visually displays a pet's nutritional and water intake in graph or table format based on stored data.

[0646] An "anomaly detection means" is a device or algorithm that automatically analyzes and detects abnormal values ​​or patterns in stored data.

[0647] The "means for notifying abnormalities in cooperation with pet insurance" is a device or program for promptly notifying detected abnormalities in cooperation with the pet insurance system.

[0648] "Means for notifying users of recommended products in cooperation with physical pet supply stores" refers to a device or program that works in cooperation with physical stores to notify users of the most suitable pet supplies based on the health condition of their pet.

[0649] "Means for notifying the user of a response method based on an abnormality detection" refers to a device or program that, when an abnormality is detected, notifies the user of a specific method or treatment for responding to the abnormality.

[0650] "Means for displaying data and notifications via a smartphone device" refers to a device or application that uses a smartphone to communicate pet data and notifications to the user.

[0651] The present invention is a system for supporting pet health management. This system measures data on pet food and water intake and excrement, and stores and analyzes that data to visualize pet health conditions and enable rapid response if an abnormality is detected. This system also works in conjunction with pet insurance and pet supply stores to support users in providing appropriate care.

[0652] element

[0653] 1. Dietary Measurement Instruments:

[0654] The user uses a scale to accurately measure the weight of food to feed to their pet, and the device sends the measurement results to the server.

[0655] 2. Moisture measurement method:

[0656] A scale is also installed to measure the weight of the water users give to their pets, and the measurement results are also sent to the server.

[0657] 3. Waste Measurement Methods:

[0658] The pet toilet is equipped with sensors and a scale to measure the weight of the waste, and the measured data is sent to a server via the device.

[0659] 4. Data storage means:

[0660] The server receives and stores these measurement data, which are then stored in a cloud database for later access.

[0661] 5. Data visualization methods:

[0662] The server uses the stored data to display the pet's daily nutritional and water intake in graphs and tables, allowing users to visually check this data via their smartphone.

[0663] 6. Anomaly detection methods:

[0664] The server is equipped with data analysis algorithms that automatically detect outliers and patterns that fall outside the normal range, and if anomalies are found, a notification is sent to the user.

[0665] 7. Pet insurance collaboration methods:

[0666] If an abnormality is detected, the information is automatically sent to your pet insurance company, allowing you to quickly check whether your pet is covered.

[0667] 8. Proposal of a solution:

[0668] The server will suggest specific measures and treatments to the user depending on the type of abnormality, and this information will be sent to the user's smartphone.

[0669] 9. Pet supply store collaboration methods:

[0670] The server works in conjunction with physical stores to notify users of the best pet products based on their pet's health condition. This notification provides users with information to help them smoothly purchase the necessary pet care products.

[0671] Hardware and software used

[0672] Smartphone:

[0673] An interface device that displays data and notifies the user.

[0674] scale:

[0675] A device for measuring the weight of food and water.

[0676] sensor:

[0677] A device for measuring the weight of excrement.

[0678] server:

[0679] Computer devices that store and analyze data, including cloud databases.

[0680] Data analysis algorithms:

[0681] Software for detecting anomalies in data.

[0682] Specific examples

[0683] When a user gives their pet 75 grams of cat food in the morning, the weight is measured on a scale and the data is sent to the server. The server records this in the database as "2023-10-24 08:00, Meal, 75 grams." The next time the pet is given 150 grams of water, the weight is measured, sent, and recorded in the same way. When the pet defecates, the toilet sensor measures 50 grams of urine and 20 grams of feces, and each data is sent and recorded to the server. Based on this data, the server visualizes the day's nutritional and water intake, and if any abnormalities are detected, it notifies the user and the pet insurance company. At this time, the server sends a notification to the user's smartphone recommending pet products based on the pet's health condition.

[0684] Prompt Sentence Examples

[0685] I'd like to develop a pet health management app. I'd like to implement the following features:

[0686] 1. Measure the amount of food, water, and excretion consumed and record it in a database.

[0687] 2. Display the animal's health status in graphs and tables from the recorded data.

[0688] 3. Detect anomalies and notify the user.

[0689] 4. Work with pet insurance companies to automatically send information when abnormalities are detected.

[0690] Generate the code to build these features in Python.

[0691] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0692] Step 1:

[0693] When a user feeds an animal, they measure the weight of the food, such as cat food, on the scale on the device. The input is the measured weight of the food, which is sent to the device. The device then sends this data to the server and records it in a database. The output is the recorded weight data.

[0694] Step 2:

[0695] When a user gives water to an animal, the user measures the weight of the water on the scale of the device. The input is the measured weight of the water, which is sent to the device. The device then sends this data to the server and records it in the database. The output is the recorded weight of the water.

[0696] Step 3:

[0697] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. The input is the measured weight of the urine and feces, which is sent to a terminal. The terminal then sends this data to a server and records it in a database. The output is the recorded weight of the excrement.

[0698] Step 4:

[0699] The server visualizes the animals' daily nutrient and water intake in graphs and tables based on the diet, water, and excrement data stored in the database. The input is the data stored in the database, which the server analyzes and processes to convert into visual information. The output is visualized graphs and tables.

[0700] Step 5:

[0701] The server uses an anomaly detection algorithm to detect abnormal values ​​and patterns in the data stored in the database. The input is the analyzed data, which the server then checks for anomalies. The output is the presence or absence of detected anomalies and their specific contents.

[0702] Step 6:

[0703] If an anomaly is detected, the server notifies the user of the information. The input is the data of the detected anomaly, which the server sends to the user's smartphone. The output is a notification message to the user.

[0704] Step 7:

[0705] The server sends a notification to the pet insurance company based on the detected anomaly. The input is the detected anomaly data, which the server automatically sends to the insurance company's system. The output is the notification data to the insurance company.

[0706] Step 8:

[0707] The server proposes specific countermeasures and treatments to the user according to the type of abnormality. The input is the abnormality detection data, which the server analyzes and generates an appropriate countermeasure. The output is a suggested message that is displayed on the user's smartphone.

[0708] Step 9:

[0709] The server works in conjunction with physical stores to notify users of the best pet products based on their pet's health condition. The input is anomaly detection data, and the server works with pet supply stores to generate appropriate product information based on this data. The output is a notification of recommended products sent to the user's smartphone.

[0710] 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.

[0711] This invention relates to a system that supports the health management of pet animals and also takes into account the user's emotions. This system measures and stores data on the animal's diet and excretion, detects abnormalities, notifies users in conjunction with pet insurance, analyzes the user's emotional state, and suggests appropriate measures to take. To effectively implement this system, the following elements and procedures are included:

[0712] element

[0713] 1. Meal measuring means: A scale is installed on the terminal to measure the weight of the food that the user gives to the animal. This serves to measure the weight of the bowl before the animal eats the food.

[0714] 2. Water measurement means: A scale is installed on the terminal to measure the weight of the water that the user gives to the animal. This can measure the weight of the water before the animal drinks it.

[0715] 3. Waste measurement: Animal litter boxes are equipped with sensors and scales to measure the weight of feces and urine, allowing for accurate measurement of the amount of waste.

[0716] 4. Data storage: The measured data on food intake, water intake, and excrement is sent from the device to a server and stored in a database. The stored data can be accessed later.

[0717] 5. Data visualization: Based on the received data, the server displays the animals' daily nutrient and water intake in graphs and tables. This visualization can be viewed by the user via a web browser or a dedicated app.

[0718] 6. Anomaly detection: The server is equipped with data analysis algorithms that automatically detect abnormal values ​​and patterns that exceed the normal range in the stored data.

[0719] 7. Pet Insurance Integration: If an abnormality is detected, the information is automatically sent to the pet insurance company, allowing users to quickly check whether their pet is eligible for insurance coverage.

[0720] 8. Solution suggestion method: The server suggests specific solutions and treatments to the user depending on the type of abnormality. This information is sent to the user's terminal.

[0721] 9. Emotion engine means: Equipped with software for analyzing the user's emotional state, it estimates the user's emotions when using the application.

[0722] 10. Emotion data analysis method: Based on the emotional data analyzed by the emotion engine, the system adjusts the notification method and response method for abnormalities.

[0723] Program processing

[0724] Measuring food intake

[0725] When a user feeds an animal, the user uses the scale on the device to measure the weight of the cat food, etc. The device sends this data to the server, which then records the measurement data.

[0726] Moisture measurement

[0727] Similarly, when a user gives water to an animal, the device measures the weight of the water, and this data is also sent to the server and recorded.

[0728] Measurement of excrement

[0729] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces and sends this data via the device to a server, which then records the data.

[0730] Data visualization

[0731] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables, and users can check this data via a web browser or a dedicated app.

[0732] Anomaly detection and notification

[0733] If the server's data analysis algorithm detects abnormal values ​​or patterns in the measurement data, the information is notified to the user and the pet insurance company.

[0734] Proposal for a solution

[0735] If an abnormality is detected, the server will suggest and notify the user of specific countermeasures and treatments according to the type of abnormality.

[0736] Analyzing emotion data and adjusting notification methods

[0737] The emotion engine analyzes the user's emotional state and the data is reflected in the system. For example, if the user is feeling stressed, the server will adjust the notification method to be softer.

[0738] Specific examples

[0739] Suppose a user feeds their pet 75 grams of cat food in the morning. The device measures the weight on a scale and sends the data to the server. The server records the weight in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, sent, and recorded. Furthermore, when the pet defecates, the litter box sensor measures 50 grams of urine and 20 grams of feces, sending the respective data to the server. Based on this data, the server visualizes the day's nutritional and water intake and notifies the user and the pet insurance company if an abnormality is detected. The server then suggests specific measures to take depending on the abnormality. Furthermore, the emotion engine analyzes the user's emotional state and appropriately adjusts the notification method. For example, if the user is feeling stressed, notifications are adjusted to a gentler tone.

[0740] This system allows users to efficiently and accurately manage their animals' health, detect abnormalities early, and take appropriate measures.It also takes the user's emotional state into consideration, making management easier and less stressful.

[0741] The processing flow will be explained below.

[0742] Step 1:

[0743] The user places cat food into a bowl before feeding the animal.

[0744] Step 2:

[0745] The weight of the cat food in the bowl is measured using a scale installed on the terminal.

[0746] Step 3:

[0747] The device sends the measured weight of the meal (for example, 75 grams) to the server as data.

[0748] Step 4:

[0749] The server records the received data in the database as "2023-10-24 08:00, meal, 75 grams."

[0750] Step 5:

[0751] The user fills the water bowl before giving the animal water.

[0752] Step 6:

[0753] The weight of the water container is measured using a scale installed on the terminal.

[0754] Step 7:

[0755] The device sends the measured weight of the water (for example, 150 grams) to the server as data.

[0756] Step 8:

[0757] The server records the received data in the database as "2023-10-24 08:05, water, 150 grams."

[0758] Step 9:

[0759] Animals use the toilet to excrete urine and feces.

[0760] Step 10:

[0761] A sensor built into the toilet measures the weight of urine and feces.

[0762] Step 11:

[0763] The device sends the measured weight of the urine and feces (e.g., 50 grams of urine and 20 grams of feces) as data to the server.

[0764] Step 12:

[0765] The server records the received data in the database as "2023-10-24 18:00, urine, 50 grams" and "2023-10-24 18:05, feces, 20 grams."

[0766] Step 13:

[0767] At the end of the day, the server visualizes the animal's total food intake, water intake, urine volume, and feces volume based on the stored data.

[0768] Step 14:

[0769] Users can check their daily total data through a web browser or a dedicated app.

[0770] Step 15:

[0771] The server uses a data analysis algorithm to analyze the stored data and detect abnormal values ​​and patterns.

[0772] Step 16:

[0773] If an abnormality is detected, the server notifies the user and the pet insurance company of the information.

[0774] Step 17:

[0775] The server proposes specific countermeasures and treatment methods depending on the type of abnormality and notifies the user of this information.

[0776] Step 18:

[0777] When a user accesses the dedicated app, the emotion engine analyzes the user's facial expressions and input data to estimate their emotional state.

[0778] Step 19:

[0779] The device transmits the emotion data analyzed by the emotion engine to the server.

[0780] Step 20:

[0781] The server stores the analyzed emotional data and adjusts the notification method based on the user's emotional state. For example, if the user is stressed, the notification will be delivered in a gentler tone.

[0782] The above are the specific processing steps based on the claims. This system allows users to efficiently and accurately manage the health status of their animals, detect abnormalities early and take appropriate measures, and even provides pleasant notifications that take into account the emotional state of the animals.

[0783] Example 2

[0784] 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."

[0785] While conventional animal health management systems have the ability to measure and record the amount of food and water intake and excrement of animals, they lack sufficient means for comprehensively managing the health of animals. Furthermore, while early response and appropriate measures are required when abnormalities in an animal's health are detected, methods for doing so are limited. Furthermore, since no systems exist that take the user's emotional state into consideration, a management method that is less stressful for users is needed.

[0786] 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.

[0787] In this invention, the server includes means for measuring the weight of the animal's food, means for measuring the animal's water intake, means for measuring the weight of the animal's waste, means for storing the measured data, means for visualizing the daily nutrient and water intake based on the stored data, means for detecting abnormalities based on the visualized data, means for notifying the insurance company of the abnormality in cooperation with the insurance company, means for analyzing the user's emotional state, and means for adjusting the notification method based on the analyzed emotional state data. This enables efficient and accurate management of the animal's health, early detection of abnormalities, and appropriate countermeasures. Furthermore, by taking the user's emotional state into consideration, management can be made easier to use and less stressful.

[0788] "Means for weighing animal food" means any device or equipment used to accurately measure the weight of food provided to an animal.

[0789] "Means for measuring animal water intake" refers to a device or instrument that accurately measures the amount of water consumed by an animal.

[0790] "Means for weighing animal waste" refers to a device or instrument that accurately measures the weight of feces or urine excreted by an animal.

[0791] "Means for storing the measured data" refers to a storage device or cloud database for storing measured data on food, water, and excrement over a long period of time.

[0792] "Means for visualizing daily nutrient and water intake amounts based on the stored data" refers to software or tools for visually displaying an animal's daily nutrient and water intake amounts based on the stored data.

[0793] "Means for detecting anomalies based on the visualized data" refers to algorithms or software for analyzing the visualized data and detecting abnormal values ​​or patterns that exceed the normal range.

[0794] "Means for coordinating with and notifying the insurance company of the abnormality" refers to a communication system or program that automatically sends information about an abnormality to the insurance company when it is detected.

[0795] "Means for analyzing the user's emotional state" refers to software, algorithms, and sensors for analyzing the user's emotional state.

[0796] "Means for adjusting the notification method based on the analyzed emotional state data" refers to a system or algorithm for adjusting the wording or method of notifications based on the analyzed emotional state data of the user.

[0797] This invention relates to a system that supports animal health management and takes into account the emotional state of the user. This system measures and stores the amount of food and water intake and excrement of the animal, visualizes the data, detects abnormalities, and also includes collaboration with pet insurance companies and analysis and adjustment of the user's emotional state.

[0798] Overall structure

[0799] The system includes the following elements:

[0800] 1. Food measurement method: A scale is installed on the terminal to measure the weight of the food that the user gives to the animal. A digital scale (e.g., a general digital scale) and a Python library (e.g., pySerial) are used.

[0801] 2. Water measurement means: A scale is installed on the terminal to measure the amount of water the user gives to the animal. It uses the same equipment and software as a digital scale.

[0802] 3. Waste measurement: The animal's litter box has built-in sensors (e.g., load cell sensors) and scales to measure the weight of feces and urine. Python libraries (e.g., Rpi.GPIO) are used.

[0803] 4. Data storage method: The measured data on food intake, water intake, and excrement is sent from the device to a server and stored in a database using a database such as MySQL or PostgreSQL.

[0804] 5. Data visualization: The server uses the received data to display the animals' daily nutrient and water intake in graphs and tables using JavaScript libraries (e.g., Chart.js, D3.js).

[0805] 6. Anomaly detection: The server is equipped with data analysis algorithms (e.g., scikit-learn, TensorFlow) that automatically detect outliers and patterns that exceed the normal range from the stored data.

[0806] 7. Insurance collaboration notification method: When an anomaly is detected, API collaboration or email services (e.g., SendGrid) are used to automatically send information to the insurance company.

[0807] 8. Response suggestion method: Specific response methods and treatments are suggested to the user depending on the type of abnormality. Using rule-based approaches and machine learning models.

[0808] 9. Sentiment Analysis Engine Means: Software and algorithms that analyze the user's emotional state (e.g., using NLP techniques, sentiment analysis libraries (e.g., NLTK, TextBlob)).

[0809] 10. Notification Tailoring: Systems and algorithms for tailoring notification language and delivery based on analyzed emotional state data.

[0810] Specific examples

[0811] Suppose a user feeds their pet 75 grams of cat food in the morning. The device measures the weight on a scale and sends the data to the server. The server records the weight in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, sent, and recorded. Furthermore, when the pet defecates, the litter box sensor measures 50 grams of urine and 20 grams of feces, and sends and records the respective data to the server. Based on this data, the server visualizes the day's nutritional and water intake and notifies the user and insurance company if an abnormality is detected. The server then suggests specific measures to take depending on the abnormality. Furthermore, an emotion analysis engine analyzes the user's emotional state and appropriately adjusts the notification method. For example, if the user is feeling stressed, notifications are adjusted to a gentler tone.

[0812] Prompt Sentence Examples

[0813] "Please tell us the specific steps of a system that helps manage the health of pet animals and takes user emotions into consideration. Also, please specify the specific hardware and software you will use."

[0814] This system allows users to efficiently and accurately manage the health of their animals, detect abnormalities early, and take appropriate measures.It also takes the user's emotional state into consideration, making management easier to use and less stressful.

[0815] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0816] Step 1: Measuring your food intake

[0817] When a user feeds an animal, the user uses the scale on the device to measure the weight of the cat food. The input is the cat food that the user places on the scale, and the output is the measured weight (for example, 75 grams). The device sends this data to the server, which records the measurement data in a database. Specifically, when the user places the cat food on the scale, the device measures the weight and sends the measurement result to the server. The server saves this in the database as "2023-10-24 08:00, Meal, 75 grams."

[0818] Step 2: Measure moisture content

[0819] When a user gives water to an animal, the terminal measures the weight of the water. The input is the water the user places on the scale, and the output is the measured weight (for example, 150 grams). The terminal sends this data to the server, which records the measurement data in a database. Specifically, when the user places water on the scale, the terminal measures the weight and sends the measurement result to the server. The server saves the data in the database as "2023-10-24 08:05, water, 150 grams."

[0820] Step 3: Measuring feces

[0821] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. The input is the urine and feces excreted by the animal into the toilet, and the output is the measured weight (for example, 50 grams of urine and 20 grams of feces). The terminal sends this data to a server, which records the measured data in a database. Specifically, when an animal uses the toilet, the sensor measures the weight of the urine and feces and sends the measurement results to the server. The server saves the data in the database as "2023-10-24 12:00, urine, 50 grams" and "2023-10-24 12:05, feces, 20 grams."

[0822] Step 4: Save your data

[0823] The server receives all measurement data sent from the terminal and stores it in a database. The input is the measurement data sent from the terminal, and the output is the data recorded in the database. Specifically, the server receives the measurement data and accurately records and stores it in the database.

[0824] Step 5: Visualize the data

[0825] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables. The input is the measurement data stored in the database, and the output is visualized data (graphs and tables). Users can check this data through a web browser or a dedicated app. Specifically, the server extracts data from the database, visualizes it using a JavaScript library, and displays it in the user's browser or app.

[0826] Step 6: Detect anomalies

[0827] The server uses data analysis algorithms to automatically detect outliers and patterns from the stored data. The input is the measurement data stored in the database, and the output is the detected anomaly information. Specifically, the server analyzes the data using scikit-learn and TensorFlow to detect values ​​and patterns that are outside the normal range.

[0828] Step 7: Insurance Linkage Notification

[0829] If the server detects an anomaly, it automatically sends that information to the insurance company. The input is the detected anomaly information, and the output is the notification sent to the insurance company. Specifically, the server sends the anomaly information using the insurance company's API, or notifies the company using an email service.

[0830] Step 8: Propose a course of action

[0831] When an abnormality is detected, the server proposes specific countermeasures and treatments to the user depending on the type of abnormality. The input is the detected abnormality information, and the output is the proposed countermeasure. Specifically, the server generates a countermeasure using a pre-configured rule-based model or machine learning model and notifies the user.

[0832] Step 9: Analyze emotion data and adjust notification methods

[0833] The server uses an emotion engine to analyze the user's emotional state and adjust the notification method. The input is the user's emotional data, and the output is the adjusted notification method. Specifically, the server uses NLP technology and an emotion analysis library to estimate the user's emotional state, and adjusts the content and tone of the notification based on the results.

[0834] (Application example 2)

[0835] 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."

[0836] It is difficult to accurately manage the health status of animals in animal health management facilities such as pet shops. It is also necessary to notify staff and insurance agencies of this information in a timely manner, and to provide an appropriate notification method that reflects the emotional state of users (staff and owners). Conventional systems have difficulty meeting these diverse requirements, so a system is needed that efficiently and accurately manages the health status of animals and reduces the psychological burden on those involved.

[0837] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for measuring the weight of the animal's food, means for measuring the amount of water the animal consumes, means for measuring the weight of the animal's waste, means for storing the measured data, means for visualizing the daily nutrient intake and water intake based on the stored data, means for detecting abnormalities based on the visualized data, means for notifying the abnormality to a cooperating insurance company, and means for supporting animal health management at an animal health management facility, analyzing the emotional state of a facility staff member, and adjusting an appropriate notification method. This enables efficient and accurate management of the animal's health status, enables rapid response to abnormalities and smooth collaboration with insurance companies, and enables notifications that take the emotional state of the staff member into consideration.

[0838] "Means for measuring the weight of food given to animals" refers to a device that measures the weight of food given to animals using a sensor or scale attached to a feeder.

[0839] A "means for measuring the amount of water consumed by an animal" is a device that uses a sensor or scale installed at the water trough to measure the amount of water an animal drinks.

[0840] A "means for measuring the weight of animal excrement" is a device that uses sensors or scales installed in the animal's litter box to measure the weight of animal excrement such as feces and urine.

[0841] "Means for storing measured data" refers to a system that stores measured data such as food intake, water intake, and amount of excrement in a database or on the cloud.

[0842] The "means for visualizing daily nutritional and water intake" is a system that uses stored data to display an animal's daily food and water intake in graphs and tables, allowing it to be visually confirmed.

[0843] "Means for detecting anomalies" refers to algorithms or programs that analyze measurement data and automatically detect abnormal data or patterns that exceed the normal range.

[0844] The "means of notifying affiliated insurance companies" refers to a system that automatically sends information to insurance companies that hold insurance contracts for animals when an abnormality is detected.

[0845] "Animal health management support means" refers to a series of devices and systems that effectively manage the health of animals based on measurement data on their food, water intake, and excretion.

[0846] The "means for analyzing the emotional state of personnel" refers to software or algorithms for analyzing the emotional state of users who operate the system, such as facility staff or animal owners.

[0847] The "means for adjusting the appropriate notification method" is a system for notifying the user in the most appropriate way according to their emotional state based on the analyzed emotional data.

[0848] To implement this invention, it is necessary to build a system with multiple measurement means that can analyze the user's emotional state and provide appropriate notification methods, as well as manage the animal's health.

[0849] System configuration

[0850] The system mainly consists of the following hardware and software:

[0851] Food weighing device: A scale attached to the feeder to measure the weight of the animal's food.

[0852] Water measuring device: a scale to measure the amount of water an animal consumes. This is placed at the water trough.

[0853] Waste measurement means: sensors and scales built into the litter box used by animals.

[0854] Data storage means: A database for storing measured data. A cloud database is used.

[0855] Visualization method: Using a data analysis algorithm on the server, daily nutritional and water intake amounts are displayed in graphs and tables.

[0856] Anomaly detection method: An algorithm that analyzes measurement data and automatically detects anomalies outside the normal range.

[0857] Notification method: A system that notifies collaborating insurance companies when an abnormality is detected.

[0858] Emotion analysis tool: Software for analyzing the user's emotional state.

[0859] Notification method adjustment means: A system that adjusts the notification method based on the analyzed emotion data.

[0860] Example

[0861] As an example of the system, the following steps are followed.

[0862] Meal Measurement

[0863] When a user feeds an animal, they use a scale attached to the device to measure the weight of the cat food, etc. The measurement data is automatically sent to the server and recorded in a database.

[0864] Moisture measurement

[0865] Similarly, the amount of water is measured using a scale installed on the device, and this measurement data is also sent to the server and stored.

[0866] excrement measurement

[0867] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces and sends the data to a server for recording.

[0868] Data visualization

[0869] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables, and users can check this data via a web browser or a dedicated app.

[0870] Anomaly detection and notification

[0871] The server's data analysis algorithm automatically detects abnormal values ​​and patterns in the measurement data, and if an abnormality is detected, the information is automatically notified to the pet insurance company.

[0872] Proposal for a solution

[0873] If an abnormality is detected, the server notifies the user of specific countermeasures and treatments according to the type of abnormality.

[0874] Analyzing emotion data and adjusting notification methods

[0875] Emotion analysis software analyzes the user's emotional state and adjusts notifications based on that data - for example, if the user is stressed, notifications will be adjusted to a gentler tone.

[0876] Examples and prompts

[0877] As a concrete example, consider the case of managing the health of animals in a pet shop. When a pet shop staff member gives an animal 75 grams of cat food, they measure it on a scale on their device and send the data to a server. Based on the data, the server will suggest appropriate measures to take and adjust the notification content if an abnormality is detected.

[0878] An example of a prompt for a generative AI model is as follows:

[0879] text

[0880] A pet shop has implemented a system that measures the amount of food and water intake and waste produced by animals, and detects abnormalities based on health management data. If an abnormality is detected, staff are notified and the system coordinates with the pet insurance company. Staff who appear stressed are also notified in a gentle tone. As a concrete example, please demonstrate the process of measuring 75 grams of cat food, 150 grams of water, and 70 grams of waste, detecting abnormalities, and suggesting how to address them.

[0881] This prompt sentence helps the generative AI model to gain a deeper understanding of the system's operational flow and behavior.

[0882] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0883] Step 1:

[0884] The user uses the scale on the device to measure the weight of the food to be given to the animal. The input is the amount of food, such as cat food, and the output is the measured weight data. This measurement data is converted into digital data within the device so that the weight of the cat food is recorded accurately.

[0885] Step 2:

[0886] The device sends the measured weight data to the server. The input is the measured data, and the output is the data stored in the cloud database. The transmission protocol is HTTP request, and the data is securely stored on the server.

[0887] Step 3:

[0888] Similarly, the user weighs the amount of water to give to the animal on a scale. The input is the amount of water, and the output is the measured weight. This data is also converted into digital data by the terminal.

[0889] Step 4:

[0890] The device sends the measured water weight data to the server. The input is the data measured earlier, and the output is the data to be saved in the cloud database. The transmission is also done using an HTTP request.

[0891] Step 5:

[0892] When an animal uses the toilet, a sensor inside the toilet measures the weight of the waste (urine and feces). The input is the amount of waste, and the output is the measured weight. This data is converted into digital data by the sensor inside the toilet.

[0893] Step 6:

[0894] The device sends the measured excrement weight data to the server. The input is the measured data, and the output is the data stored in the cloud database. The measured data is sent to the server using a secure communication protocol.

[0895] Step 7:

[0896] The server visualizes the animals' daily nutritional and water intake based on the stored data. The input is data stored in a cloud database, and the output is visualized data displayed in graphs and tables. Data analysis algorithms handle this process and convert the data into an easy-to-understand format.

[0897] Step 8:

[0898] The server's data analysis algorithm automatically detects abnormal values ​​and patterns in the measurement data. The input is daily nutrition and fluid intake data, and the output is the anomaly detection results. Statistical methods and machine learning algorithms are used to identify abnormal patterns.

[0899] Step 9:

[0900] If an anomaly is detected, the server automatically notifies the insurance company of that information. The input is the anomaly detection result, and the output is a notification message to the insurance company. Notifications are sent via email, API calls, etc.

[0901] Step 10:

[0902] The server proposes specific measures to the user (staff or owner) depending on the type of abnormality. The input at this time is the type of abnormality and its detailed information, and the output is a message proposing measures and treatment. The measures are determined by referring to prescription examples stored in a database in advance.

[0903] Step 11:

[0904] Emotion analysis software installed on the device is used to analyze the user's emotional state. The input is the user's operation log and facial expression data, and the output is analyzed emotional state data. Emotion analysis uses machine learning algorithms and NLP (natural language processing) technology.

[0905] Step 12:

[0906] The server adjusts the notification method based on the analyzed emotional data. The input is the analyzed emotional state data, and the output is an adjusted notification message. For example, if the user is feeling stressed, a notification with a gentler tone is generated. This reduces the user's psychological burden.

[0907] 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.

[0908] 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.

[0909] 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.

[0910] [Third embodiment]

[0911] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0912] 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.

[0913] 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).

[0914] 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.

[0915] 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.

[0916] 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).

[0917] 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.

[0918] 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.

[0919] 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.

[0920] 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.

[0921] 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.

[0922] 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."

[0923] This invention relates to a system that supports the health management of pet animals. This system measures and stores data on the animals' diet and excretion, detects abnormalities, and notifies users in cooperation with pet insurance. To effectively implement this system, the following elements and procedures are included:

[0924] element

[0925] 1. Meal measuring means: A scale is installed on the terminal to measure the weight of the food that the user gives to the animal. This serves to measure the weight of the bowl before the animal eats the food.

[0926] 2. Water measurement means: A scale is installed on the terminal to measure the weight of the water that the user gives to the animal. This can measure the weight of the water before the animal drinks it.

[0927] 3. Waste measurement: Animal litter boxes are equipped with sensors and scales to measure the weight of feces and urine, allowing for accurate measurement of the amount of waste.

[0928] 4. Data storage: The measured data on food intake, water intake, and excrement is sent from the device to a server and stored in a database. The stored data can be accessed later.

[0929] 5. Data visualization: Based on the received data, the server displays the animals' daily nutrient and water intake in graphs and tables. This visualization can be viewed by the user via a web browser or a dedicated app.

[0930] 6. Anomaly detection: The server is equipped with data analysis algorithms that automatically detect abnormal values ​​and patterns that exceed the normal range in the stored data.

[0931] 7. Pet Insurance Integration: If an abnormality is detected, the information is automatically sent to the pet insurance company, allowing users to quickly check whether their pet is eligible for insurance coverage.

[0932] 8. Solution suggestion method: The server suggests specific solutions and treatments to the user depending on the type of abnormality. This information is sent to the user's terminal.

[0933] Program processing

[0934] Measuring food intake

[0935] When a user feeds an animal, the user uses the scale on the device to measure the weight of the cat food, etc. The device sends this data to the server, which then records the measurement data.

[0936] Moisture measurement

[0937] Similarly, when a user gives water to an animal, the device measures the weight of the water, and this data is also sent to the server and recorded.

[0938] Measurement of excrement

[0939] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces and sends this data via the device to a server, which then records the data.

[0940] Data visualization

[0941] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables, and users can check this data via a web browser or a dedicated app.

[0942] Anomaly detection and notification

[0943] If the server's data analysis algorithm detects abnormal values ​​or patterns in the measurement data, the information is notified to the user and the pet insurance company.

[0944] Proposal for a solution

[0945] If an abnormality is detected, the server will suggest and notify the user of specific countermeasures and treatments according to the type of abnormality.

[0946] Specific examples

[0947] Let's say a user gives their pet 75 grams of cat food in the morning. At this time, the device measures the weight on a scale and sends the data to the server. The server records this in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, sent, and recorded. Furthermore, when the pet defecates, the toilet sensor measures 50 grams of urine and 20 grams of feces, and each data is sent and recorded to the server. Based on this data, the server visualizes the amount of nutritional and water intake for that day, and if any abnormalities are detected, it notifies the user and the pet insurance company.

[0948] The above is a detailed description of the embodiment of the present invention. This system allows users to efficiently and accurately manage the health status of their animals, detect abnormalities early, and take appropriate measures.

[0949] The processing flow will be explained below.

[0950] Step 1:

[0951] The user places cat food into a bowl before feeding the animal.

[0952] Step 2:

[0953] The weight of the cat food in the bowl is measured using a scale installed on the terminal.

[0954] Step 3:

[0955] The device sends the measured weight of the meal (for example, 75 grams) to the server as data.

[0956] Step 4:

[0957] The server records the received data in the database as "2023-10-24 08:00, meal, 75 grams."

[0958] Step 5:

[0959] The user fills the water bowl before giving the animal water.

[0960] Step 6:

[0961] The weight of the water container is measured using a scale installed on the terminal.

[0962] Step 7:

[0963] The device sends the measured weight of the water (for example, 150 grams) to the server as data.

[0964] Step 8:

[0965] The server records the received data in the database as "2023-10-24 08:05, water, 150 grams."

[0966] Step 9:

[0967] Animals use the toilet to excrete urine and feces.

[0968] Step 10:

[0969] A sensor built into the toilet measures the weight of urine and feces.

[0970] Step 11:

[0971] The device sends the measured weight of the urine and feces (e.g., 50 grams of urine and 20 grams of feces) as data to the server.

[0972] Step 12:

[0973] The server records the received data in the database as "2023-10-24 18:00, urine, 50 grams" and "2023-10-24 18:05, feces, 20 grams."

[0974] Step 13:

[0975] At the end of the day, the server visualizes the animal's total food intake, water intake, urine volume, and feces volume based on the stored data.

[0976] Step 14:

[0977] Users can check their daily total data through a web browser or a dedicated app.

[0978] Step 15:

[0979] The server uses a data analysis algorithm to analyze the stored data and detect abnormal values ​​and patterns.

[0980] Step 16:

[0981] If an abnormality is detected, the server notifies the user and the pet insurance company of the information.

[0982] Step 17:

[0983] The server proposes specific countermeasures and treatment methods depending on the type of abnormality and notifies the user of this information.

[0984] This allows users to monitor the health of their animals in real time and take appropriate action quickly if any abnormalities are detected.

[0985] Example 1

[0986] 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."

[0987] In today's pet industry, it is difficult to efficiently and accurately manage the health of animals. Accurate data on food intake, water intake, and excrement must be collected, and any abnormalities must be detected early to allow appropriate measures to be taken. Furthermore, if an abnormality is detected, prompt action must be proposed and, if necessary, cooperation with an insurance agency must be coordinated. However, conventional systems are unable to fully meet these requirements, creating multiple challenges in pet health management.

[0988] 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.

[0989] In this invention, the server includes: means for measuring the animal's nutrient intake, means for measuring the animal's water intake, means for measuring the amount of animal waste; means for storing the measured data; means for visualizing daily nutrient and water intake based on the stored data; means for detecting abnormalities based on the visualized data; means for notifying an insurance company of the abnormality; means for proposing a response method according to the type of abnormality when the abnormality is detected; means for storing the measured data in a cloud database; means for analyzing the data stored in the cloud database to identify abnormal values ​​or patterns; and means for generating and transmitting notifications based on the identified abnormal values ​​or patterns. This allows for detailed and real-time monitoring of the animal's health, enabling early detection and prompt response to abnormalities. Furthermore, by linking with an insurance company, insurance coverage can be quickly confirmed, realizing comprehensive health management of pets.

[0990] "Animals" refers to living creatures such as mammals, birds, and reptiles kept as pets.

[0991] "Means for measuring nutrient intake" refers to a device or system used to measure the amount of food given to an animal.

[0992] "Means for measuring water intake" refers to a device or system for measuring the amount of water provided to an animal.

[0993] "Means for measuring the amount of waste" refers to sensors or devices for measuring the amount of urine or feces excreted by an animal.

[0994] "Means for storing measured data" refers to a storage system for recording the measured data and keeping it in a state where it can be accessed later.

[0995] "Visualization means" refers to devices or systems for visually displaying measured data, such as interfaces that display data in graph or table format.

[0996] "Anomaly detection methods" refers to data analysis algorithms or devices that identify and alert on abnormal values ​​or patterns that fall outside of the normal range.

[0997] "Means for linking and notifying insurance organizations" refers to systems or devices that notify insurance companies of detected abnormal values ​​or patterns to expedite insurance coverage confirmation.

[0998] "Means for proposing a countermeasure according to the type of abnormality" refers to a device or system for proposing specific countermeasures or treatment methods to the user based on the detected abnormality.

[0999] "Cloud database" refers to data storage that is remotely accessible via the internet.

[1000] "Means for analyzing data to identify outliers and patterns" refers to systems or software that analyze stored data and automatically detect values ​​that deviate from normal ranges or specific patterns.

[1001] "Means for generating and sending notifications" refers to a system or device for generating notifications based on detected anomalies or patterns and sending them to a user device or insurance organization.

[1002] MODE FOR CARRYING OUT THE INVENTION

[1003] This invention relates to a system that supports the health management of pet animals. This system measures and stores data on the animals' food intake, water intake, and excrement, detects abnormalities, and coordinates with insurance agencies. The following elements are required for the system to be implemented effectively:

[1004] element

[1005] 1. Meal measurement means: The user uses a scale installed on the terminal to measure the amount of food to be given to the animal. This is used to measure the weight of the bowl or container before the animal eats the food.

[1006] 2. Water measuring means: The user uses a scale also installed on the terminal to measure the amount of water to be given to the animal. This scale can measure the weight of the container into which water is poured.

[1007] 3. Waste measurement device: The litter boxes used by animals are equipped with sensors that measure the weight of feces and urine, allowing for accurate measurement of the amount of waste.

[1008] 4. Data storage: The measured data on food intake, water intake, and excrement is sent from the device to a server, which stores it in a cloud database. The stored data can be accessed later.

[1009] 5. Data visualization: Based on the received data, the server displays the animals' daily nutrient and water intake in graphs and tables. This visualization can be viewed by the user via a web browser or a dedicated app.

[1010] 6. Anomaly detection method: The server uses data analysis algorithms to detect abnormal values ​​and patterns in the stored data.

[1011] 7. Insurance Linkage: If an anomaly is detected, the information is automatically sent to insurance companies, allowing users to quickly check for potential insurance coverage.

[1012] 8. Solution suggestion method: The server suggests specific solutions and treatment methods to the user depending on the type of abnormality. This information is sent to the user's terminal.

[1013] Specific actions

[1014] Measuring food intake

[1015] The user measures the amount of food, such as cat food, that they give to their animal. Before putting the cat food into a bowl, the user resets the scale installed on the terminal and sets the weight of the bowl to 0 grams. Next, the user puts the cat food into the bowl and measures its weight. The terminal sends the measurement results to the server, which records the data.

[1016] Moisture measurement

[1017] Similarly, a user measures the amount of water given to an animal. The user places the container on the device's scale and resets the weight to 0 grams. Then, the user pours water into the container and measures its weight. The device sends the measurement result to the server, which records the data.

[1018] Measurement of excrement

[1019] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. This measurement data is sent via the device to a server, which then records the data.

[1020] Data visualization

[1021] The server visualizes the animals' daily nutritional and water intake based on the stored data, and users can check this data via a web browser or a dedicated app.

[1022] Anomaly detection and notification

[1023] If the server's data analysis algorithm detects abnormal values ​​or patterns in the measurement data, the information is notified to the user and insurance organization.

[1024] Proposal for a solution

[1025] If an abnormality is detected, the server will suggest specific countermeasures and treatment methods according to the type of abnormality to the user and notify them of this information.

[1026] Specific examples

[1027] Let's say a user gives their pet 75 grams of cat food in the morning. At this time, the scale on the device measures the weight of the cat food and sends that data to the server. The server records this in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, and the data is sent and recorded. Furthermore, when the pet defecates, the sensor in the litter box measures 50 grams of urine and 20 grams of feces, and each data is sent to the server and recorded. Based on this data, the server visualizes the day's nutritional and water intake, and if any abnormalities are detected, it notifies the user and the insurance company.

[1028] Example input to a generative AI model

[1029] Prompt Sentence Examples

[1030] Using a specific example of a pet health management system, please explain in detail the procedures for measuring food intake, water intake, and excrement, and visualizing the data. Also, please include how to detect abnormalities based on this data and propose countermeasures.

[1031] The system is designed to enable users to efficiently and accurately manage the health status of their animals, detect abnormalities early, and take appropriate measures.

[1032] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1033] Program processing steps

[1034] Measuring food intake

[1035] Step 1:

[1036] The user prepares the cat food. The cat food has not yet been placed in the bowl. The input at this point is that the amount of cat food has not yet been measured.

[1037] Step 2:

[1038] The user places the container on the device's scale and resets the weight to 0 grams. Next, the user puts cat food into the container and measures its weight. The input is the weight of the container with the cat food in it, and the output is the measured weight of the cat food. The device acquires this data and sends it to the server.

[1039] Step 3:

[1040] The server records the received weight data of the meal in a database. The database is saved in the format of "2023-10-24 08:00, Meal, 75 grams", for example. The input of this step is the weight data of the cat food sent from the terminal, and the output is the record saved in the database.

[1041] Moisture measurement

[1042] Step 1:

[1043] The user prepares the water. The input is the amount of water not yet in the container.

[1044] Step 2:

[1045] The user places a container on the device's scale and resets the weight to 0 grams. Next, the user pours water into the container and measures its weight. The input is the weight of the water poured into the container, and the output is the measured weight of the water. The device captures this data and sends it to the server.

[1046] Step 3:

[1047] The server records the received water weight data in a database. The database is saved in the format, for example, "2023-10-24 08:05, water, 150 grams." The input of this step is the water weight data sent from the device, and the output is the record saved in the database.

[1048] Measurement of excrement

[1049] Step 1:

[1050] The user prepares the animal litter box and verifies that the sensor is working properly. The input is the sensor readiness state.

[1051] Step 2:

[1052] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. The input is the animal's excretion behavior, and the output is the measured weight of the urine and feces. The device collects this data and sends it to a server.

[1053] Step 3:

[1054] The server records the received excrement weight data in a database. For example, the database stores the data in the format "2023-10-24 09:00, urine, 50 grams" or "2023-10-24 09:00, feces, 20 grams." The input for this step is the excrement weight data sent from the device, and the output is the record stored in the database.

[1055] Data visualization

[1056] Step 1:

[1057] The server retrieves the stored data on food, water, and excrement. The input is the data stored in the database.

[1058] Step 2:

[1059] The server uses a data analysis algorithm to analyze the meaning of each piece of data and calculate daily nutritional and fluid intake. The input is the acquired measurement data, and the output is the analyzed nutritional and fluid intake.

[1060] Step 3:

[1061] The server generates graphs and tables based on the analysis results, and provides these visualizations in a user-accessible interface. The input is the analysis results, and the output is the visualized graphs and tables.

[1062] Step 4:

[1063] Users can check their animals' daily nutritional and water intake in graphs and tables via a web browser or dedicated app. The input is visualized data, and the output is the user's confirmation actions.

[1064] Anomaly detection and notification

[1065] Step 1:

[1066] The server periodically monitors the stored data to detect abnormal values ​​and patterns. The input is the stored data, and the output is the detected abnormal values ​​and patterns.

[1067] Step 2:

[1068] The data analysis algorithm detects data that is out of the normal range, such as a lower than normal amount of urine. The input is the monitored data, and the output is the anomaly detection result.

[1069] Step 3:

[1070] The server generates a notification to the user and the health care provider, such as "Your urine output is lower than normal, which may indicate dehydration." The input is the detected anomaly, and the output is the generated notification.

[1071] Step 4:

[1072] The server generates and sends the notification to the user's device and the insurance company. The input is the generated notification and the output is the sent notification.

[1073] Proposal for a solution

[1074] Step 1:

[1075] The server analyzes the type of anomaly detected. The input is the anomaly data, and the output is the recognition result of the type of anomaly.

[1076] Step 2:

[1077] The server proposes specific countermeasures and treatment methods according to the type of abnormality. For example, it generates a suggestion such as "Your animal may be dehydrated. Increase its water intake and consult a veterinarian if necessary." The input is the type of abnormality recognized, and the output is a suggested countermeasure.

[1078] Step 3:

[1079] The server notifies the user of the generated proposal. The input is the proposal, and the output is the sent proposal notification.

[1080] (Application example 1)

[1081] 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."

[1082] In recent years, there has been a demand for systems that allow pet owners to take appropriate measures quickly in pet health management. However, conventional systems often take a long time to accurately measure data on pets' diet, water intake, and excrement, and to detect and notify abnormalities. Furthermore, they lack a mechanism for effectively informing users of how to respond when an abnormality is detected. Furthermore, there has been a lack of coordination with pet supply stores, making it difficult to smoothly purchase necessary care products. The present invention aims to solve these problems and provide a system that allows pet owners to manage their pet's health more efficiently and accurately.

[1083] 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.

[1084] In this invention, the server includes a means for notifying the user of recommended products in cooperation with a physical pet supply store, a means for notifying the user of a response method based on the detected abnormality, and a means for displaying the data and notification via a smartphone terminal, thereby making it possible to monitor the health condition of a pet in real time and quickly suggest appropriate response methods and care products when an abnormality is detected.

[1085] A "means for weighing animal food" is a device or scale that allows an owner to accurately measure the weight of food that is given to a pet.

[1086] A "means for measuring an animal's water intake" is a device or scale for measuring the amount of water a pet drinks.

[1087] "Means for measuring the weight of animal excrement" refers to devices or sensors for measuring the weight of feces and urine excreted by pets.

[1088] The "means for storing measured data" refers to a device or server for recording and storing the measured data on food, water, and excretion.

[1089] "Means for visualizing daily nutritional and water intake" refers to a device or program that visually displays a pet's nutritional and water intake in graph or table format based on stored data.

[1090] An "anomaly detection means" is a device or algorithm that automatically analyzes and detects abnormal values ​​or patterns in stored data.

[1091] The "means for notifying abnormalities in cooperation with pet insurance" is a device or program for promptly notifying detected abnormalities in cooperation with the pet insurance system.

[1092] "Means for notifying users of recommended products in cooperation with physical pet supply stores" refers to a device or program that works in cooperation with physical stores to notify users of the most suitable pet supplies based on the health condition of their pet.

[1093] "Means for notifying the user of a response method based on an abnormality detection" refers to a device or program that, when an abnormality is detected, notifies the user of a specific method or treatment for responding to the abnormality.

[1094] "Means for displaying data and notifications via a smartphone device" refers to a device or application that uses a smartphone to communicate pet data and notifications to the user.

[1095] The present invention is a system for supporting pet health management. This system measures data on pet food and water intake and excrement, and stores and analyzes that data to visualize pet health conditions and enable rapid response if an abnormality is detected. This system also works in conjunction with pet insurance and pet supply stores to support users in providing appropriate care.

[1096] element

[1097] 1. Dietary Measurement Instruments:

[1098] The user uses a scale to accurately measure the weight of food to feed to their pet, and the device sends the measurement results to the server.

[1099] 2. Moisture measurement method:

[1100] A scale is also installed to measure the weight of the water users give to their pets, and the measurement results are also sent to the server.

[1101] 3. Waste Measurement Methods:

[1102] The pet toilet is equipped with sensors and a scale to measure the weight of the waste, and the measured data is sent to a server via the device.

[1103] 4. Data storage means:

[1104] The server receives and stores these measurement data, which are then stored in a cloud database for later access.

[1105] 5. Data visualization methods:

[1106] The server uses the stored data to display the pet's daily nutritional and water intake in graphs and tables, allowing users to visually check this data via their smartphone.

[1107] 6. Anomaly detection methods:

[1108] The server is equipped with data analysis algorithms that automatically detect outliers and patterns that fall outside the normal range, and if anomalies are found, a notification is sent to the user.

[1109] 7. Pet insurance collaboration methods:

[1110] If an abnormality is detected, the information is automatically sent to your pet insurance company, allowing you to quickly check whether your pet is covered.

[1111] 8. Proposal of a solution:

[1112] The server will suggest specific measures and treatments to the user depending on the type of abnormality, and this information will be sent to the user's smartphone.

[1113] 9. Pet supply store collaboration methods:

[1114] The server works in conjunction with physical stores to notify users of the best pet products based on their pet's health condition. This notification provides users with information to help them smoothly purchase the necessary pet care products.

[1115] Hardware and software used

[1116] Smartphone:

[1117] An interface device that displays data and notifies the user.

[1118] scale:

[1119] A device for measuring the weight of food and water.

[1120] sensor:

[1121] A device for measuring the weight of excrement.

[1122] server:

[1123] Computer devices that store and analyze data, including cloud databases.

[1124] Data analysis algorithms:

[1125] Software for detecting anomalies in data.

[1126] Specific examples

[1127] When a user gives their pet 75 grams of cat food in the morning, the weight is measured on a scale and the data is sent to the server. The server records this in the database as "2023-10-24 08:00, Meal, 75 grams." The next time the pet is given 150 grams of water, the weight is measured, sent, and recorded in the same way. When the pet defecates, the toilet sensor measures 50 grams of urine and 20 grams of feces, and each data is sent and recorded to the server. Based on this data, the server visualizes the day's nutritional and water intake, and if any abnormalities are detected, it notifies the user and the pet insurance company. At this time, the server sends a notification to the user's smartphone recommending pet products based on the pet's health condition.

[1128] Prompt Sentence Examples

[1129] I'd like to develop a pet health management app. I'd like to implement the following features:

[1130] 1. Measure the amount of food, water, and excretion consumed and record it in a database.

[1131] 2. Display the animal's health status in graphs and tables from the recorded data.

[1132] 3. Detect anomalies and notify the user.

[1133] 4. Work with pet insurance companies to automatically send information when abnormalities are detected.

[1134] Generate the code to build these features in Python.

[1135] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1136] Step 1:

[1137] When a user feeds an animal, they measure the weight of the food, such as cat food, on the scale on the device. The input is the measured weight of the food, which is sent to the device. The device then sends this data to the server and records it in a database. The output is the recorded weight data.

[1138] Step 2:

[1139] When a user gives water to an animal, the user measures the weight of the water on the scale of the device. The input is the measured weight of the water, which is sent to the device. The device then sends this data to the server and records it in the database. The output is the recorded weight of the water.

[1140] Step 3:

[1141] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. The input is the measured weight of the urine and feces, which is sent to a terminal. The terminal then sends this data to a server and records it in a database. The output is the recorded weight of the excrement.

[1142] Step 4:

[1143] The server visualizes the animals' daily nutrient and water intake in graphs and tables based on the diet, water, and excrement data stored in the database. The input is the data stored in the database, which the server analyzes and processes to convert into visual information. The output is visualized graphs and tables.

[1144] Step 5:

[1145] The server uses an anomaly detection algorithm to detect abnormal values ​​and patterns in the data stored in the database. The input is the analyzed data, which the server then checks for anomalies. The output is the presence or absence of detected anomalies and their specific contents.

[1146] Step 6:

[1147] If an anomaly is detected, the server notifies the user of the information. The input is the data of the detected anomaly, which the server sends to the user's smartphone. The output is a notification message to the user.

[1148] Step 7:

[1149] The server sends a notification to the pet insurance company based on the detected anomaly. The input is the detected anomaly data, which the server automatically sends to the insurance company's system. The output is the notification data to the insurance company.

[1150] Step 8:

[1151] The server proposes specific countermeasures and treatments to the user according to the type of abnormality. The input is the abnormality detection data, which the server analyzes and generates an appropriate countermeasure. The output is a suggested message that is displayed on the user's smartphone.

[1152] Step 9:

[1153] The server works in conjunction with physical stores to notify users of the best pet products based on their pet's health condition. The input is anomaly detection data, and the server works with pet supply stores to generate appropriate product information based on this data. The output is a notification of recommended products sent to the user's smartphone.

[1154] 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.

[1155] This invention relates to a system that supports the health management of pet animals and also takes into account the user's emotions. This system measures and stores data on the animal's diet and excretion, detects abnormalities, notifies users in conjunction with pet insurance, analyzes the user's emotional state, and suggests appropriate measures to take. To effectively implement this system, the following elements and procedures are included:

[1156] element

[1157] 1. Meal measuring means: A scale is installed on the terminal to measure the weight of the food that the user gives to the animal. This serves to measure the weight of the bowl before the animal eats the food.

[1158] 2. Water measurement means: A scale is installed on the terminal to measure the weight of the water that the user gives to the animal. This can measure the weight of the water before the animal drinks it.

[1159] 3. Waste measurement: Animal litter boxes are equipped with sensors and scales to measure the weight of feces and urine, allowing for accurate measurement of the amount of waste.

[1160] 4. Data storage: The measured data on food intake, water intake, and excrement is sent from the device to a server and stored in a database. The stored data can be accessed later.

[1161] 5. Data visualization: Based on the received data, the server displays the animals' daily nutrient and water intake in graphs and tables. This visualization can be viewed by the user via a web browser or a dedicated app.

[1162] 6. Anomaly detection: The server is equipped with data analysis algorithms that automatically detect abnormal values ​​and patterns that exceed the normal range in the stored data.

[1163] 7. Pet Insurance Integration: If an abnormality is detected, the information is automatically sent to the pet insurance company, allowing users to quickly check whether their pet is eligible for insurance coverage.

[1164] 8. Solution suggestion method: The server suggests specific solutions and treatments to the user depending on the type of abnormality. This information is sent to the user's terminal.

[1165] 9. Emotion engine means: Equipped with software for analyzing the user's emotional state, it estimates the user's emotions when using the application.

[1166] 10. Emotion data analysis method: Based on the emotional data analyzed by the emotion engine, the system adjusts the notification method and response method for abnormalities.

[1167] Program processing

[1168] Measuring food intake

[1169] When a user feeds an animal, the user uses the scale on the device to measure the weight of the cat food, etc. The device sends this data to the server, which then records the measurement data.

[1170] Moisture measurement

[1171] Similarly, when a user gives water to an animal, the device measures the weight of the water, and this data is also sent to the server and recorded.

[1172] Measurement of excrement

[1173] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces and sends this data via the device to a server, which then records the data.

[1174] Data visualization

[1175] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables, and users can check this data via a web browser or a dedicated app.

[1176] Anomaly detection and notification

[1177] If the server's data analysis algorithm detects abnormal values ​​or patterns in the measurement data, the information is notified to the user and the pet insurance company.

[1178] Proposal for a solution

[1179] If an abnormality is detected, the server will suggest and notify the user of specific countermeasures and treatments according to the type of abnormality.

[1180] Analyzing emotion data and adjusting notification methods

[1181] The emotion engine analyzes the user's emotional state and the data is reflected in the system. For example, if the user is feeling stressed, the server will adjust the notification method to be softer.

[1182] Specific examples

[1183] Suppose a user feeds their pet 75 grams of cat food in the morning. The device measures the weight on a scale and sends the data to the server. The server records the weight in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, sent, and recorded. Furthermore, when the pet defecates, the litter box sensor measures 50 grams of urine and 20 grams of feces, sending the respective data to the server. Based on this data, the server visualizes the day's nutritional and water intake and notifies the user and the pet insurance company if an abnormality is detected. The server then suggests specific measures to take depending on the abnormality. Furthermore, the emotion engine analyzes the user's emotional state and appropriately adjusts the notification method. For example, if the user is feeling stressed, notifications are adjusted to a gentler tone.

[1184] This system allows users to efficiently and accurately manage their animals' health, detect abnormalities early, and take appropriate measures.It also takes the user's emotional state into consideration, making management easier and less stressful.

[1185] The processing flow will be explained below.

[1186] Step 1:

[1187] The user places cat food into a bowl before feeding the animal.

[1188] Step 2:

[1189] The weight of the cat food in the bowl is measured using a scale installed on the terminal.

[1190] Step 3:

[1191] The device sends the measured weight of the meal (for example, 75 grams) to the server as data.

[1192] Step 4:

[1193] The server records the received data in the database as "2023-10-24 08:00, meal, 75 grams."

[1194] Step 5:

[1195] The user fills the water bowl before giving the animal water.

[1196] Step 6:

[1197] The weight of the water container is measured using a scale installed on the terminal.

[1198] Step 7:

[1199] The device sends the measured weight of the water (for example, 150 grams) to the server as data.

[1200] Step 8:

[1201] The server records the received data in the database as "2023-10-24 08:05, water, 150 grams."

[1202] Step 9:

[1203] Animals use the toilet to excrete urine and feces.

[1204] Step 10:

[1205] A sensor built into the toilet measures the weight of urine and feces.

[1206] Step 11:

[1207] The device sends the measured weight of the urine and feces (e.g., 50 grams of urine and 20 grams of feces) as data to the server.

[1208] Step 12:

[1209] The server records the received data in the database as "2023-10-24 18:00, urine, 50 grams" and "2023-10-24 18:05, feces, 20 grams."

[1210] Step 13:

[1211] At the end of the day, the server visualizes the animal's total food intake, water intake, urine volume, and feces volume based on the stored data.

[1212] Step 14:

[1213] Users can check their daily total data through a web browser or a dedicated app.

[1214] Step 15:

[1215] The server uses a data analysis algorithm to analyze the stored data and detect abnormal values ​​and patterns.

[1216] Step 16:

[1217] If an abnormality is detected, the server notifies the user and the pet insurance company of the information.

[1218] Step 17:

[1219] The server proposes specific countermeasures and treatment methods depending on the type of abnormality and notifies the user of this information.

[1220] Step 18:

[1221] When a user accesses the dedicated app, the emotion engine analyzes the user's facial expressions and input data to estimate their emotional state.

[1222] Step 19:

[1223] The device transmits the emotion data analyzed by the emotion engine to the server.

[1224] Step 20:

[1225] The server stores the analyzed emotional data and adjusts the notification method based on the user's emotional state. For example, if the user is stressed, the notification will be delivered in a gentler tone.

[1226] The above are the specific processing steps based on the claims. This system allows users to efficiently and accurately manage the health status of their animals, detect abnormalities early and take appropriate measures, and even provides pleasant notifications that take into account the emotional state of the animals.

[1227] Example 2

[1228] 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."

[1229] While conventional animal health management systems have the ability to measure and record the amount of food and water intake and excrement of animals, they lack sufficient means for comprehensively managing the health of animals. Furthermore, while early response and appropriate measures are required when abnormalities in an animal's health are detected, methods for doing so are limited. Furthermore, since no systems exist that take the user's emotional state into consideration, a management method that is less stressful for users is needed.

[1230] 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.

[1231] In this invention, the server includes means for measuring the weight of the animal's food, means for measuring the animal's water intake, means for measuring the weight of the animal's waste, means for storing the measured data, means for visualizing the daily nutrient and water intake based on the stored data, means for detecting abnormalities based on the visualized data, means for notifying the insurance company of the abnormality in cooperation with the insurance company, means for analyzing the user's emotional state, and means for adjusting the notification method based on the analyzed emotional state data. This enables efficient and accurate management of the animal's health, early detection of abnormalities, and appropriate countermeasures. Furthermore, by taking the user's emotional state into consideration, management can be made easier to use and less stressful.

[1232] "Means for weighing animal food" means any device or equipment used to accurately measure the weight of food provided to an animal.

[1233] "Means for measuring animal water intake" refers to a device or instrument that accurately measures the amount of water consumed by an animal.

[1234] "Means for weighing animal waste" refers to a device or instrument that accurately measures the weight of feces or urine excreted by an animal.

[1235] "Means for storing the measured data" refers to a storage device or cloud database for storing measured data on food, water, and excrement over a long period of time.

[1236] "Means for visualizing daily nutrient and water intake amounts based on the stored data" refers to software or tools for visually displaying an animal's daily nutrient and water intake amounts based on the stored data.

[1237] "Means for detecting anomalies based on the visualized data" refers to algorithms or software for analyzing the visualized data and detecting abnormal values ​​or patterns that exceed the normal range.

[1238] "Means for coordinating with and notifying the insurance company of the abnormality" refers to a communication system or program that automatically sends information about an abnormality to the insurance company when it is detected.

[1239] "Means for analyzing the user's emotional state" refers to software, algorithms, and sensors for analyzing the user's emotional state.

[1240] "Means for adjusting the notification method based on the analyzed emotional state data" refers to a system or algorithm for adjusting the wording or method of notifications based on the analyzed emotional state data of the user.

[1241] This invention relates to a system that supports animal health management and takes into account the emotional state of the user. This system measures and stores the amount of food and water intake and excrement of the animal, visualizes the data, detects abnormalities, and also includes collaboration with pet insurance companies and analysis and adjustment of the user's emotional state.

[1242] Overall structure

[1243] The system includes the following elements:

[1244] 1. Food measurement method: A scale is installed on the terminal to measure the weight of the food that the user gives to the animal. A digital scale (e.g., a general digital scale) and a Python library (e.g., pySerial) are used.

[1245] 2. Water measurement means: A scale is installed on the terminal to measure the amount of water the user gives to the animal. It uses the same equipment and software as a digital scale.

[1246] 3. Waste measurement: The animal's litter box has built-in sensors (e.g., load cell sensors) and scales to measure the weight of feces and urine. Python libraries (e.g., Rpi.GPIO) are used.

[1247] 4. Data storage method: The measured data on food intake, water intake, and excrement is sent from the device to a server and stored in a database using a database such as MySQL or PostgreSQL.

[1248] 5. Data visualization: The server uses the received data to display the animals' daily nutrient and water intake in graphs and tables using JavaScript libraries (e.g., Chart.js, D3.js).

[1249] 6. Anomaly detection: The server is equipped with data analysis algorithms (e.g., scikit-learn, TensorFlow) that automatically detect outliers and patterns that exceed the normal range from the stored data.

[1250] 7. Insurance collaboration notification method: When an anomaly is detected, API collaboration or email services (e.g., SendGrid) are used to automatically send information to the insurance company.

[1251] 8. Response suggestion method: Specific response methods and treatments are suggested to the user depending on the type of abnormality. Using rule-based approaches and machine learning models.

[1252] 9. Sentiment Analysis Engine Means: Software and algorithms that analyze the user's emotional state (e.g., using NLP techniques, sentiment analysis libraries (e.g., NLTK, TextBlob)).

[1253] 10. Notification Tailoring: Systems and algorithms for tailoring notification language and delivery based on analyzed emotional state data.

[1254] Specific examples

[1255] Suppose a user feeds their pet 75 grams of cat food in the morning. The device measures the weight on a scale and sends the data to the server. The server records the weight in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, sent, and recorded. Furthermore, when the pet defecates, the litter box sensor measures 50 grams of urine and 20 grams of feces, and sends and records the respective data to the server. Based on this data, the server visualizes the day's nutritional and water intake and notifies the user and insurance company if an abnormality is detected. The server then suggests specific measures to take depending on the abnormality. Furthermore, an emotion analysis engine analyzes the user's emotional state and appropriately adjusts the notification method. For example, if the user is feeling stressed, notifications are adjusted to a gentler tone.

[1256] Prompt Sentence Examples

[1257] "Please tell us the specific steps of a system that helps manage the health of pet animals and takes user emotions into consideration. Also, please specify the specific hardware and software you will use."

[1258] This system allows users to efficiently and accurately manage the health of their animals, detect abnormalities early, and take appropriate measures.It also takes the user's emotional state into consideration, making management easier to use and less stressful.

[1259] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1260] Step 1: Measuring your food intake

[1261] When a user feeds an animal, the user uses the scale on the device to measure the weight of the cat food. The input is the cat food that the user places on the scale, and the output is the measured weight (for example, 75 grams). The device sends this data to the server, which records the measurement data in a database. Specifically, when the user places the cat food on the scale, the device measures the weight and sends the measurement result to the server. The server saves this in the database as "2023-10-24 08:00, Meal, 75 grams."

[1262] Step 2: Measure moisture content

[1263] When a user gives water to an animal, the terminal measures the weight of the water. The input is the water the user places on the scale, and the output is the measured weight (for example, 150 grams). The terminal sends this data to the server, which records the measurement data in a database. Specifically, when the user places water on the scale, the terminal measures the weight and sends the measurement result to the server. The server saves the data in the database as "2023-10-24 08:05, water, 150 grams."

[1264] Step 3: Measuring feces

[1265] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. The input is the urine and feces excreted by the animal into the toilet, and the output is the measured weight (for example, 50 grams of urine and 20 grams of feces). The terminal sends this data to a server, which records the measured data in a database. Specifically, when an animal uses the toilet, the sensor measures the weight of the urine and feces and sends the measurement results to the server. The server saves the data in the database as "2023-10-24 12:00, urine, 50 grams" and "2023-10-24 12:05, feces, 20 grams."

[1266] Step 4: Save your data

[1267] The server receives all measurement data sent from the terminal and stores it in a database. The input is the measurement data sent from the terminal, and the output is the data recorded in the database. Specifically, the server receives the measurement data and accurately records and stores it in the database.

[1268] Step 5: Visualize the data

[1269] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables. The input is the measurement data stored in the database, and the output is visualized data (graphs and tables). Users can check this data through a web browser or a dedicated app. Specifically, the server extracts data from the database, visualizes it using a JavaScript library, and displays it in the user's browser or app.

[1270] Step 6: Detect anomalies

[1271] The server uses data analysis algorithms to automatically detect outliers and patterns from the stored data. The input is the measurement data stored in the database, and the output is the detected anomaly information. Specifically, the server analyzes the data using scikit-learn and TensorFlow to detect values ​​and patterns that are outside the normal range.

[1272] Step 7: Insurance Linkage Notification

[1273] If the server detects an anomaly, it automatically sends that information to the insurance company. The input is the detected anomaly information, and the output is the notification sent to the insurance company. Specifically, the server sends the anomaly information using the insurance company's API, or notifies the company using an email service.

[1274] Step 8: Propose a course of action

[1275] When an abnormality is detected, the server proposes specific countermeasures and treatments to the user depending on the type of abnormality. The input is the detected abnormality information, and the output is the proposed countermeasure. Specifically, the server generates a countermeasure using a pre-configured rule-based model or machine learning model and notifies the user.

[1276] Step 9: Analyze emotion data and adjust notification methods

[1277] The server uses an emotion engine to analyze the user's emotional state and adjust the notification method. The input is the user's emotional data, and the output is the adjusted notification method. Specifically, the server uses NLP technology and an emotion analysis library to estimate the user's emotional state, and adjusts the content and tone of the notification based on the results.

[1278] (Application example 2)

[1279] 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."

[1280] It is difficult to accurately manage the health status of animals in animal health management facilities such as pet shops. It is also necessary to notify staff and insurance agencies of this information in a timely manner, and to provide an appropriate notification method that reflects the emotional state of users (staff and owners). Conventional systems have difficulty meeting these diverse requirements, so a system is needed that efficiently and accurately manages the health status of animals and reduces the psychological burden on those involved.

[1281] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for measuring the weight of the animal's food, means for measuring the amount of water the animal consumes, means for measuring the weight of the animal's waste, means for storing the measured data, means for visualizing the daily nutrient intake and water intake based on the stored data, means for detecting abnormalities based on the visualized data, means for notifying the abnormality to a cooperating insurance company, and means for supporting animal health management at an animal health management facility, analyzing the emotional state of a facility staff member, and adjusting an appropriate notification method. This enables efficient and accurate management of the animal's health status, enables rapid response to abnormalities and smooth collaboration with insurance companies, and enables notifications that take the emotional state of the staff member into consideration.

[1282] "Means for measuring the weight of food given to animals" refers to a device that measures the weight of food given to animals using a sensor or scale attached to a feeder.

[1283] A "means for measuring the amount of water consumed by an animal" is a device that uses a sensor or scale installed at the water trough to measure the amount of water an animal drinks.

[1284] A "means for measuring the weight of animal excrement" is a device that uses sensors or scales installed in the animal's litter box to measure the weight of animal excrement such as feces and urine.

[1285] "Means for storing measured data" refers to a system that stores measured data such as food intake, water intake, and amount of excrement in a database or on the cloud.

[1286] The "means for visualizing daily nutritional and water intake" is a system that uses stored data to display an animal's daily food and water intake in graphs and tables, allowing it to be visually confirmed.

[1287] "Means for detecting anomalies" refers to algorithms or programs that analyze measurement data and automatically detect abnormal data or patterns that exceed the normal range.

[1288] The "means of notifying affiliated insurance companies" refers to a system that automatically sends information to insurance companies that hold insurance contracts for animals when an abnormality is detected.

[1289] "Animal health management support means" refers to a series of devices and systems that effectively manage the health of animals based on measurement data on their food, water intake, and excretion.

[1290] The "means for analyzing the emotional state of personnel" refers to software or algorithms for analyzing the emotional state of users who operate the system, such as facility staff or animal owners.

[1291] The "means for adjusting the appropriate notification method" is a system for notifying the user in the most appropriate way according to their emotional state based on the analyzed emotional data.

[1292] To implement this invention, it is necessary to build a system with multiple measurement means that can analyze the user's emotional state and provide appropriate notification methods, as well as manage the animal's health.

[1293] System configuration

[1294] The system mainly consists of the following hardware and software:

[1295] Food weighing device: A scale attached to the feeder to measure the weight of the animal's food.

[1296] Water measuring device: a scale to measure the amount of water an animal consumes. This is placed at the water trough.

[1297] Waste measurement means: sensors and scales built into the litter box used by animals.

[1298] Data storage means: A database for storing measured data. A cloud database is used.

[1299] Visualization method: Using a data analysis algorithm on the server, daily nutritional and water intake amounts are displayed in graphs and tables.

[1300] Anomaly detection method: An algorithm that analyzes measurement data and automatically detects anomalies outside the normal range.

[1301] Notification method: A system that notifies collaborating insurance companies when an abnormality is detected.

[1302] Emotion analysis tool: Software for analyzing the user's emotional state.

[1303] Notification method adjustment means: A system that adjusts the notification method based on the analyzed emotion data.

[1304] Example

[1305] As an example of the system, the following steps are followed.

[1306] Meal Measurement

[1307] When a user feeds an animal, they use a scale attached to the device to measure the weight of the cat food, etc. The measurement data is automatically sent to the server and recorded in a database.

[1308] Moisture measurement

[1309] Similarly, the amount of water is measured using a scale installed on the device, and this measurement data is also sent to the server and stored.

[1310] excrement measurement

[1311] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces and sends the data to a server for recording.

[1312] Data visualization

[1313] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables, and users can check this data via a web browser or a dedicated app.

[1314] Anomaly detection and notification

[1315] The server's data analysis algorithm automatically detects abnormal values ​​and patterns in the measurement data, and if an abnormality is detected, the information is automatically notified to the pet insurance company.

[1316] Proposal for a solution

[1317] If an abnormality is detected, the server notifies the user of specific countermeasures and treatments according to the type of abnormality.

[1318] Analyzing emotion data and adjusting notification methods

[1319] Emotion analysis software analyzes the user's emotional state and adjusts notifications based on that data - for example, if the user is stressed, notifications will be adjusted to a gentler tone.

[1320] Examples and prompts

[1321] As a concrete example, consider the case of managing the health of animals in a pet shop. When a pet shop staff member gives an animal 75 grams of cat food, they measure it on a scale on their device and send the data to a server. Based on the data, the server will suggest appropriate measures to take and adjust the notification content if an abnormality is detected.

[1322] An example of a prompt for a generative AI model is as follows:

[1323] text

[1324] A pet shop has implemented a system that measures the amount of food and water intake and waste produced by animals, and detects abnormalities based on health management data. If an abnormality is detected, staff are notified and the system coordinates with the pet insurance company. Staff who appear stressed are also notified in a gentle tone. As a concrete example, please demonstrate the process of measuring 75 grams of cat food, 150 grams of water, and 70 grams of waste, detecting abnormalities, and suggesting how to address them.

[1325] This prompt sentence helps the generative AI model to gain a deeper understanding of the system's operational flow and behavior.

[1326] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1327] Step 1:

[1328] The user uses the scale on the device to measure the weight of the food to be given to the animal. The input is the amount of food, such as cat food, and the output is the measured weight data. This measurement data is converted into digital data within the device so that the weight of the cat food is recorded accurately.

[1329] Step 2:

[1330] The device sends the measured weight data to the server. The input is the measured data, and the output is the data stored in the cloud database. The transmission protocol is HTTP request, and the data is securely stored on the server.

[1331] Step 3:

[1332] Similarly, the user weighs the amount of water to give to the animal on a scale. The input is the amount of water, and the output is the measured weight. This data is also converted into digital data by the terminal.

[1333] Step 4:

[1334] The device sends the measured water weight data to the server. The input is the data measured earlier, and the output is the data to be saved in the cloud database. The transmission is also done using an HTTP request.

[1335] Step 5:

[1336] When an animal uses the toilet, a sensor inside the toilet measures the weight of the waste (urine and feces). The input is the amount of waste, and the output is the measured weight. This data is converted into digital data by the sensor inside the toilet.

[1337] Step 6:

[1338] The device sends the measured excrement weight data to the server. The input is the measured data, and the output is the data stored in the cloud database. The measured data is sent to the server using a secure communication protocol.

[1339] Step 7:

[1340] The server visualizes the animals' daily nutritional and water intake based on the stored data. The input is data stored in a cloud database, and the output is visualized data displayed in graphs and tables. Data analysis algorithms handle this process and convert the data into an easy-to-understand format.

[1341] Step 8:

[1342] The server's data analysis algorithm automatically detects abnormal values ​​and patterns in the measurement data. The input is daily nutrition and fluid intake data, and the output is the anomaly detection results. Statistical methods and machine learning algorithms are used to identify abnormal patterns.

[1343] Step 9:

[1344] If an anomaly is detected, the server automatically notifies the insurance company of that information. The input is the anomaly detection result, and the output is a notification message to the insurance company. Notifications are sent via email, API calls, etc.

[1345] Step 10:

[1346] The server proposes specific measures to the user (staff or owner) depending on the type of abnormality. The input at this time is the type of abnormality and its detailed information, and the output is a message proposing measures and treatment. The measures are determined by referring to prescription examples stored in a database in advance.

[1347] Step 11:

[1348] Emotion analysis software installed on the device is used to analyze the user's emotional state. The input is the user's operation log and facial expression data, and the output is analyzed emotional state data. Emotion analysis uses machine learning algorithms and NLP (natural language processing) technology.

[1349] Step 12:

[1350] The server adjusts the notification method based on the analyzed emotional data. The input is the analyzed emotional state data, and the output is an adjusted notification message. For example, if the user is feeling stressed, a notification with a gentler tone is generated. This reduces the user's psychological burden.

[1351] 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.

[1352] 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.

[1353] 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.

[1354] [Fourth embodiment]

[1355] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1356] 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.

[1357] 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).

[1358] 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.

[1359] 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.

[1360] 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).

[1361] 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.

[1362] 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.

[1363] 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.

[1364] 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.

[1365] 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.

[1366] 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.

[1367] 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."

[1368] This invention relates to a system that supports the health management of pet animals. This system measures and stores data on the animals' diet and excretion, detects abnormalities, and notifies users in cooperation with pet insurance. To effectively implement this system, the following elements and procedures are included:

[1369] element

[1370] 1. Meal measuring means: A scale is installed on the terminal to measure the weight of the food that the user gives to the animal. This serves to measure the weight of the bowl before the animal eats the food.

[1371] 2. Water measurement means: A scale is installed on the terminal to measure the weight of the water that the user gives to the animal. This can measure the weight of the water before the animal drinks it.

[1372] 3. Waste measurement: Animal litter boxes are equipped with sensors and scales to measure the weight of feces and urine, allowing for accurate measurement of the amount of waste.

[1373] 4. Data storage: The measured data on food intake, water intake, and excrement is sent from the device to a server and stored in a database. The stored data can be accessed later.

[1374] 5. Data visualization: Based on the received data, the server displays the animals' daily nutrient and water intake in graphs and tables. This visualization can be viewed by the user via a web browser or a dedicated app.

[1375] 6. Anomaly detection: The server is equipped with data analysis algorithms that automatically detect abnormal values ​​and patterns that exceed the normal range in the stored data.

[1376] 7. Pet Insurance Integration: If an abnormality is detected, the information is automatically sent to the pet insurance company, allowing users to quickly check whether their pet is eligible for insurance coverage.

[1377] 8. Solution suggestion method: The server suggests specific solutions and treatments to the user depending on the type of abnormality. This information is sent to the user's terminal.

[1378] Program processing

[1379] Measuring food intake

[1380] When a user feeds an animal, the user uses the scale on the device to measure the weight of the cat food, etc. The device sends this data to the server, which then records the measurement data.

[1381] Moisture measurement

[1382] Similarly, when a user gives water to an animal, the device measures the weight of the water, and this data is also sent to the server and recorded.

[1383] Measurement of excrement

[1384] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces and sends this data via the device to a server, which then records the data.

[1385] Data visualization

[1386] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables, and users can check this data via a web browser or a dedicated app.

[1387] Anomaly detection and notification

[1388] If the server's data analysis algorithm detects abnormal values ​​or patterns in the measurement data, the information is notified to the user and the pet insurance company.

[1389] Proposal for a solution

[1390] If an abnormality is detected, the server will suggest and notify the user of specific countermeasures and treatments according to the type of abnormality.

[1391] Specific examples

[1392] Let's say a user gives their pet 75 grams of cat food in the morning. At this time, the device measures the weight on a scale and sends the data to the server. The server records this in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, sent, and recorded. Furthermore, when the pet defecates, the toilet sensor measures 50 grams of urine and 20 grams of feces, and each data is sent and recorded to the server. Based on this data, the server visualizes the amount of nutritional and water intake for that day, and if any abnormalities are detected, it notifies the user and the pet insurance company.

[1393] The above is a detailed description of the embodiment of the present invention. This system allows users to efficiently and accurately manage the health status of their animals, detect abnormalities early, and take appropriate measures.

[1394] The processing flow will be explained below.

[1395] Step 1:

[1396] The user places cat food into a bowl before feeding the animal.

[1397] Step 2:

[1398] The weight of the cat food in the bowl is measured using a scale installed on the terminal.

[1399] Step 3:

[1400] The device sends the measured weight of the meal (for example, 75 grams) to the server as data.

[1401] Step 4:

[1402] The server records the received data in the database as "2023-10-24 08:00, meal, 75 grams."

[1403] Step 5:

[1404] The user fills the water bowl before giving the animal water.

[1405] Step 6:

[1406] The weight of the water container is measured using a scale installed on the terminal.

[1407] Step 7:

[1408] The device sends the measured weight of the water (for example, 150 grams) to the server as data.

[1409] Step 8:

[1410] The server records the received data in the database as "2023-10-24 08:05, water, 150 grams."

[1411] Step 9:

[1412] Animals use the toilet to excrete urine and feces.

[1413] Step 10:

[1414] A sensor built into the toilet measures the weight of urine and feces.

[1415] Step 11:

[1416] The device sends the measured weight of the urine and feces (e.g., 50 grams of urine and 20 grams of feces) as data to the server.

[1417] Step 12:

[1418] The server records the received data in the database as "2023-10-24 18:00, urine, 50 grams" and "2023-10-24 18:05, feces, 20 grams."

[1419] Step 13:

[1420] At the end of the day, the server visualizes the animal's total food intake, water intake, urine volume, and feces volume based on the stored data.

[1421] Step 14:

[1422] Users can check their daily total data through a web browser or a dedicated app.

[1423] Step 15:

[1424] The server uses a data analysis algorithm to analyze the stored data and detect abnormal values ​​and patterns.

[1425] Step 16:

[1426] If an abnormality is detected, the server notifies the user and the pet insurance company of the information.

[1427] Step 17:

[1428] The server proposes specific countermeasures and treatment methods depending on the type of abnormality and notifies the user of this information.

[1429] This allows users to monitor the health of their animals in real time and take appropriate action quickly if any abnormalities are detected.

[1430] Example 1

[1431] 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."

[1432] In today's pet industry, it is difficult to efficiently and accurately manage the health of animals. Accurate data on food intake, water intake, and excrement must be collected, and any abnormalities must be detected early to allow appropriate measures to be taken. Furthermore, if an abnormality is detected, prompt action must be proposed and, if necessary, cooperation with an insurance agency must be coordinated. However, conventional systems are unable to fully meet these requirements, creating multiple challenges in pet health management.

[1433] 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.

[1434] In this invention, the server includes: means for measuring the animal's nutrient intake, means for measuring the animal's water intake, means for measuring the amount of animal waste; means for storing the measured data; means for visualizing daily nutrient and water intake based on the stored data; means for detecting abnormalities based on the visualized data; means for notifying an insurance company of the abnormality; means for proposing a response method according to the type of abnormality when the abnormality is detected; means for storing the measured data in a cloud database; means for analyzing the data stored in the cloud database to identify abnormal values ​​or patterns; and means for generating and transmitting notifications based on the identified abnormal values ​​or patterns. This allows for detailed and real-time monitoring of the animal's health, enabling early detection and prompt response to abnormalities. Furthermore, by linking with an insurance company, insurance coverage can be quickly confirmed, realizing comprehensive health management of pets.

[1435] "Animals" refers to living creatures such as mammals, birds, and reptiles kept as pets.

[1436] "Means for measuring nutrient intake" refers to a device or system used to measure the amount of food given to an animal.

[1437] "Means for measuring water intake" refers to a device or system for measuring the amount of water provided to an animal.

[1438] "Means for measuring the amount of waste" refers to sensors or devices for measuring the amount of urine or feces excreted by an animal.

[1439] "Means for storing measured data" refers to a storage system for recording the measured data and keeping it in a state where it can be accessed later.

[1440] "Visualization means" refers to devices or systems for visually displaying measured data, such as interfaces that display data in graph or table format.

[1441] "Anomaly detection methods" refers to data analysis algorithms or devices that identify and alert on abnormal values ​​or patterns that fall outside of the normal range.

[1442] "Means for linking and notifying insurance organizations" refers to systems or devices that notify insurance companies of detected abnormal values ​​or patterns to expedite insurance coverage confirmation.

[1443] "Means for proposing a countermeasure according to the type of abnormality" refers to a device or system for proposing specific countermeasures or treatment methods to the user based on the detected abnormality.

[1444] "Cloud database" refers to data storage that is remotely accessible via the internet.

[1445] "Means for analyzing data to identify outliers and patterns" refers to systems or software that analyze stored data and automatically detect values ​​that deviate from normal ranges or specific patterns.

[1446] "Means for generating and sending notifications" refers to a system or device for generating notifications based on detected anomalies or patterns and sending them to a user device or insurance organization.

[1447] MODE FOR CARRYING OUT THE INVENTION

[1448] This invention relates to a system that supports the health management of pet animals. This system measures and stores data on the animals' food intake, water intake, and excrement, detects abnormalities, and coordinates with insurance agencies. The following elements are required for the system to be implemented effectively:

[1449] element

[1450] 1. Meal measurement means: The user uses a scale installed on the terminal to measure the amount of food to be given to the animal. This is used to measure the weight of the bowl or container before the animal eats the food.

[1451] 2. Water measuring means: The user uses a scale also installed on the terminal to measure the amount of water to be given to the animal. This scale can measure the weight of the container into which water is poured.

[1452] 3. Waste measurement device: The litter boxes used by animals are equipped with sensors that measure the weight of feces and urine, allowing for accurate measurement of the amount of waste.

[1453] 4. Data storage: The measured data on food intake, water intake, and excrement is sent from the device to a server, which stores it in a cloud database. The stored data can be accessed later.

[1454] 5. Data visualization: Based on the received data, the server displays the animals' daily nutrient and water intake in graphs and tables. This visualization can be viewed by the user via a web browser or a dedicated app.

[1455] 6. Anomaly detection method: The server uses data analysis algorithms to detect abnormal values ​​and patterns in the stored data.

[1456] 7. Insurance Linkage: If an anomaly is detected, the information is automatically sent to insurance companies, allowing users to quickly check for potential insurance coverage.

[1457] 8. Solution suggestion method: The server suggests specific solutions and treatment methods to the user depending on the type of abnormality. This information is sent to the user's terminal.

[1458] Specific actions

[1459] Measuring food intake

[1460] The user measures the amount of food, such as cat food, that they give to their animal. Before putting the cat food into a bowl, the user resets the scale installed on the terminal and sets the weight of the bowl to 0 grams. Next, the user puts the cat food into the bowl and measures its weight. The terminal sends the measurement results to the server, which records the data.

[1461] Moisture measurement

[1462] Similarly, a user measures the amount of water given to an animal. The user places the container on the device's scale and resets the weight to 0 grams. Then, the user pours water into the container and measures its weight. The device sends the measurement result to the server, which records the data.

[1463] Measurement of excrement

[1464] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. This measurement data is sent via the device to a server, which then records the data.

[1465] Data visualization

[1466] The server visualizes the animals' daily nutritional and water intake based on the stored data, and users can check this data via a web browser or a dedicated app.

[1467] Anomaly detection and notification

[1468] If the server's data analysis algorithm detects abnormal values ​​or patterns in the measurement data, the information is notified to the user and insurance organization.

[1469] Proposal for a solution

[1470] If an abnormality is detected, the server will suggest specific countermeasures and treatment methods according to the type of abnormality to the user and notify them of this information.

[1471] Specific examples

[1472] Let's say a user gives their pet 75 grams of cat food in the morning. At this time, the scale on the device measures the weight of the cat food and sends that data to the server. The server records this in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, and the data is sent and recorded. Furthermore, when the pet defecates, the sensor in the litter box measures 50 grams of urine and 20 grams of feces, and each data is sent to the server and recorded. Based on this data, the server visualizes the day's nutritional and water intake, and if any abnormalities are detected, it notifies the user and the insurance company.

[1473] Example input to a generative AI model

[1474] Prompt Sentence Examples

[1475] Using a specific example of a pet health management system, please explain in detail the procedures for measuring food intake, water intake, and excrement, and visualizing the data. Also, please include how to detect abnormalities based on this data and propose countermeasures.

[1476] The system is designed to enable users to efficiently and accurately manage the health status of their animals, detect abnormalities early, and take appropriate measures.

[1477] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1478] Program processing steps

[1479] Measuring food intake

[1480] Step 1:

[1481] The user prepares the cat food. The cat food has not yet been placed in the bowl. The input at this point is that the amount of cat food has not yet been measured.

[1482] Step 2:

[1483] The user places the container on the device's scale and resets the weight to 0 grams. Next, the user puts cat food into the container and measures its weight. The input is the weight of the container with the cat food in it, and the output is the measured weight of the cat food. The device acquires this data and sends it to the server.

[1484] Step 3:

[1485] The server records the received weight data of the meal in a database. The database is saved in the format of "2023-10-24 08:00, Meal, 75 grams", for example. The input of this step is the weight data of the cat food sent from the terminal, and the output is the record saved in the database.

[1486] Moisture measurement

[1487] Step 1:

[1488] The user prepares the water. The input is the amount of water not yet in the container.

[1489] Step 2:

[1490] The user places a container on the device's scale and resets the weight to 0 grams. Next, the user pours water into the container and measures its weight. The input is the weight of the water poured into the container, and the output is the measured weight of the water. The device captures this data and sends it to the server.

[1491] Step 3:

[1492] The server records the received water weight data in a database. The database is saved in the format, for example, "2023-10-24 08:05, water, 150 grams." The input of this step is the water weight data sent from the device, and the output is the record saved in the database.

[1493] Measurement of excrement

[1494] Step 1:

[1495] The user prepares the animal litter box and verifies that the sensor is working properly. The input is the sensor readiness state.

[1496] Step 2:

[1497] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. The input is the animal's excretion behavior, and the output is the measured weight of the urine and feces. The device collects this data and sends it to a server.

[1498] Step 3:

[1499] The server records the received excrement weight data in a database. For example, the database stores the data in the format "2023-10-24 09:00, urine, 50 grams" or "2023-10-24 09:00, feces, 20 grams." The input for this step is the excrement weight data sent from the device, and the output is the record stored in the database.

[1500] Data visualization

[1501] Step 1:

[1502] The server retrieves the stored data on food, water, and excrement. The input is the data stored in the database.

[1503] Step 2:

[1504] The server uses a data analysis algorithm to analyze the meaning of each piece of data and calculate daily nutritional and fluid intake. The input is the acquired measurement data, and the output is the analyzed nutritional and fluid intake.

[1505] Step 3:

[1506] The server generates graphs and tables based on the analysis results, and provides these visualizations in a user-accessible interface. The input is the analysis results, and the output is the visualized graphs and tables.

[1507] Step 4:

[1508] Users can check their animals' daily nutritional and water intake in graphs and tables via a web browser or dedicated app. The input is visualized data, and the output is the user's confirmation actions.

[1509] Anomaly detection and notification

[1510] Step 1:

[1511] The server periodically monitors the stored data to detect abnormal values ​​and patterns. The input is the stored data, and the output is the detected abnormal values ​​and patterns.

[1512] Step 2:

[1513] The data analysis algorithm detects data that is out of the normal range, such as a lower than normal amount of urine. The input is the monitored data, and the output is the anomaly detection result.

[1514] Step 3:

[1515] The server generates a notification to the user and the health care provider, such as "Your urine output is lower than normal, which may indicate dehydration." The input is the detected anomaly, and the output is the generated notification.

[1516] Step 4:

[1517] The server generates and sends the notification to the user's device and the insurance company. The input is the generated notification and the output is the sent notification.

[1518] Proposal for a solution

[1519] Step 1:

[1520] The server analyzes the type of anomaly detected. The input is the anomaly data, and the output is the recognition result of the type of anomaly.

[1521] Step 2:

[1522] The server proposes specific countermeasures and treatment methods according to the type of abnormality. For example, it generates a suggestion such as "Your animal may be dehydrated. Increase its water intake and consult a veterinarian if necessary." The input is the type of abnormality recognized, and the output is a suggested countermeasure.

[1523] Step 3:

[1524] The server notifies the user of the generated proposal. The input is the proposal, and the output is the sent proposal notification.

[1525] (Application example 1)

[1526] 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."

[1527] In recent years, there has been a demand for systems that allow pet owners to take appropriate measures quickly in pet health management. However, conventional systems often take a long time to accurately measure data on pets' diet, water intake, and excrement, and to detect and notify abnormalities. Furthermore, they lack a mechanism for effectively informing users of how to respond when an abnormality is detected. Furthermore, there has been a lack of coordination with pet supply stores, making it difficult to smoothly purchase necessary care products. The present invention aims to solve these problems and provide a system that allows pet owners to manage their pet's health more efficiently and accurately.

[1528] 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.

[1529] In this invention, the server includes a means for notifying the user of recommended products in cooperation with a physical pet supply store, a means for notifying the user of a response method based on the detected abnormality, and a means for displaying the data and notification via a smartphone terminal, thereby making it possible to monitor the health condition of a pet in real time and quickly suggest appropriate response methods and care products when an abnormality is detected.

[1530] A "means for weighing animal food" is a device or scale that allows an owner to accurately measure the weight of food that is given to a pet.

[1531] A "means for measuring an animal's water intake" is a device or scale for measuring the amount of water a pet drinks.

[1532] "Means for measuring the weight of animal excrement" refers to devices or sensors for measuring the weight of feces and urine excreted by pets.

[1533] The "means for storing measured data" refers to a device or server for recording and storing the measured data on food, water, and excretion.

[1534] "Means for visualizing daily nutritional and water intake" refers to a device or program that visually displays a pet's nutritional and water intake in graph or table format based on stored data.

[1535] An "anomaly detection means" is a device or algorithm that automatically analyzes and detects abnormal values ​​or patterns in stored data.

[1536] The "means for notifying abnormalities in cooperation with pet insurance" is a device or program for promptly notifying detected abnormalities in cooperation with the pet insurance system.

[1537] "Means for notifying users of recommended products in cooperation with physical pet supply stores" refers to a device or program that works in cooperation with physical stores to notify users of the most suitable pet supplies based on the health condition of their pet.

[1538] "Means for notifying the user of a response method based on an abnormality detection" refers to a device or program that, when an abnormality is detected, notifies the user of a specific method or treatment for responding to the abnormality.

[1539] "Means for displaying data and notifications via a smartphone device" refers to a device or application that uses a smartphone to communicate pet data and notifications to the user.

[1540] The present invention is a system for supporting pet health management. This system measures data on pet food and water intake and excrement, and stores and analyzes that data to visualize pet health conditions and enable rapid response if an abnormality is detected. This system also works in conjunction with pet insurance and pet supply stores to support users in providing appropriate care.

[1541] element

[1542] 1. Dietary Measurement Instruments:

[1543] The user uses a scale to accurately measure the weight of food to feed to their pet, and the device sends the measurement results to the server.

[1544] 2. Moisture measurement method:

[1545] A scale is also installed to measure the weight of the water users give to their pets, and the measurement results are also sent to the server.

[1546] 3. Waste Measurement Methods:

[1547] The pet toilet is equipped with sensors and a scale to measure the weight of the waste, and the measured data is sent to a server via the device.

[1548] 4. Data storage means:

[1549] The server receives and stores these measurement data, which are then stored in a cloud database for later access.

[1550] 5. Data visualization methods:

[1551] The server uses the stored data to display the pet's daily nutritional and water intake in graphs and tables, allowing users to visually check this data via their smartphone.

[1552] 6. Anomaly detection methods:

[1553] The server is equipped with data analysis algorithms that automatically detect outliers and patterns that fall outside the normal range, and if anomalies are found, a notification is sent to the user.

[1554] 7. Pet insurance collaboration methods:

[1555] If an abnormality is detected, the information is automatically sent to your pet insurance company, allowing you to quickly check whether your pet is covered.

[1556] 8. Proposal of a solution:

[1557] The server will suggest specific measures and treatments to the user depending on the type of abnormality, and this information will be sent to the user's smartphone.

[1558] 9. Pet supply store collaboration methods:

[1559] The server works in conjunction with physical stores to notify users of the best pet products based on their pet's health condition. This notification provides users with information to help them smoothly purchase the necessary pet care products.

[1560] Hardware and software used

[1561] Smartphone:

[1562] An interface device that displays data and notifies the user.

[1563] scale:

[1564] A device for measuring the weight of food and water.

[1565] sensor:

[1566] A device for measuring the weight of excrement.

[1567] server:

[1568] Computer devices that store and analyze data, including cloud databases.

[1569] Data analysis algorithms:

[1570] Software for detecting anomalies in data.

[1571] Specific examples

[1572] When a user gives their pet 75 grams of cat food in the morning, the weight is measured on a scale and the data is sent to the server. The server records this in the database as "2023-10-24 08:00, Meal, 75 grams." The next time the pet is given 150 grams of water, the weight is measured, sent, and recorded in the same way. When the pet defecates, the toilet sensor measures 50 grams of urine and 20 grams of feces, and each data is sent and recorded to the server. Based on this data, the server visualizes the day's nutritional and water intake, and if any abnormalities are detected, it notifies the user and the pet insurance company. At this time, the server sends a notification to the user's smartphone recommending pet products based on the pet's health condition.

[1573] Prompt Sentence Examples

[1574] I'd like to develop a pet health management app. I'd like to implement the following features:

[1575] 1. Measure the amount of food, water, and excretion consumed and record it in a database.

[1576] 2. Display the animal's health status in graphs and tables from the recorded data.

[1577] 3. Detect anomalies and notify the user.

[1578] 4. Work with pet insurance companies to automatically send information when abnormalities are detected.

[1579] Generate the code to build these features in Python.

[1580] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1581] Step 1:

[1582] When a user feeds an animal, they measure the weight of the food, such as cat food, on the scale on the device. The input is the measured weight of the food, which is sent to the device. The device then sends this data to the server and records it in a database. The output is the recorded weight data.

[1583] Step 2:

[1584] When a user gives water to an animal, the user measures the weight of the water on the scale of the device. The input is the measured weight of the water, which is sent to the device. The device then sends this data to the server and records it in the database. The output is the recorded weight of the water.

[1585] Step 3:

[1586] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. The input is the measured weight of the urine and feces, which is sent to a terminal. The terminal then sends this data to a server and records it in a database. The output is the recorded weight of the excrement.

[1587] Step 4:

[1588] The server visualizes the animals' daily nutrient and water intake in graphs and tables based on the diet, water, and excrement data stored in the database. The input is the data stored in the database, which the server analyzes and processes to convert into visual information. The output is visualized graphs and tables.

[1589] Step 5:

[1590] The server uses an anomaly detection algorithm to detect abnormal values ​​and patterns in the data stored in the database. The input is the analyzed data, which the server then checks for anomalies. The output is the presence or absence of detected anomalies and their specific contents.

[1591] Step 6:

[1592] If an anomaly is detected, the server notifies the user of the information. The input is the data of the detected anomaly, which the server sends to the user's smartphone. The output is a notification message to the user.

[1593] Step 7:

[1594] The server sends a notification to the pet insurance company based on the detected anomaly. The input is the detected anomaly data, which the server automatically sends to the insurance company's system. The output is the notification data to the insurance company.

[1595] Step 8:

[1596] The server proposes specific countermeasures and treatments to the user according to the type of abnormality. The input is the abnormality detection data, which the server analyzes and generates an appropriate countermeasure. The output is a suggested message that is displayed on the user's smartphone.

[1597] Step 9:

[1598] The server works in conjunction with physical stores to notify users of the best pet products based on their pet's health condition. The input is anomaly detection data, and the server works with pet supply stores to generate appropriate product information based on this data. The output is a notification of recommended products sent to the user's smartphone.

[1599] 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.

[1600] This invention relates to a system that supports the health management of pet animals and also takes into account the user's emotions. This system measures and stores data on the animal's diet and excretion, detects abnormalities, notifies users in conjunction with pet insurance, analyzes the user's emotional state, and suggests appropriate measures to take. To effectively implement this system, the following elements and procedures are included:

[1601] element

[1602] 1. Meal measuring means: A scale is installed on the terminal to measure the weight of the food that the user gives to the animal. This serves to measure the weight of the bowl before the animal eats the food.

[1603] 2. Water measurement means: A scale is installed on the terminal to measure the weight of the water that the user gives to the animal. This can measure the weight of the water before the animal drinks it.

[1604] 3. Waste measurement: Animal litter boxes are equipped with sensors and scales to measure the weight of feces and urine, allowing for accurate measurement of the amount of waste.

[1605] 4. Data storage: The measured data on food intake, water intake, and excrement is sent from the device to a server and stored in a database. The stored data can be accessed later.

[1606] 5. Data visualization: Based on the received data, the server displays the animals' daily nutrient and water intake in graphs and tables. This visualization can be viewed by the user via a web browser or a dedicated app.

[1607] 6. Anomaly detection: The server is equipped with data analysis algorithms that automatically detect abnormal values ​​and patterns that exceed the normal range in the stored data.

[1608] 7. Pet Insurance Integration: If an abnormality is detected, the information is automatically sent to the pet insurance company, allowing users to quickly check whether their pet is eligible for insurance coverage.

[1609] 8. Solution suggestion method: The server suggests specific solutions and treatments to the user depending on the type of abnormality. This information is sent to the user's terminal.

[1610] 9. Emotion engine means: Equipped with software for analyzing the user's emotional state, it estimates the user's emotions when using the application.

[1611] 10. Emotion data analysis method: Based on the emotional data analyzed by the emotion engine, the system adjusts the notification method and response method for abnormalities.

[1612] Program processing

[1613] Measuring food intake

[1614] When a user feeds an animal, the user uses the scale on the device to measure the weight of the cat food, etc. The device sends this data to the server, which then records the measurement data.

[1615] Moisture measurement

[1616] Similarly, when a user gives water to an animal, the device measures the weight of the water, and this data is also sent to the server and recorded.

[1617] Measurement of excrement

[1618] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces and sends this data via the device to a server, which then records the data.

[1619] Data visualization

[1620] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables, and users can check this data via a web browser or a dedicated app.

[1621] Anomaly detection and notification

[1622] If the server's data analysis algorithm detects abnormal values ​​or patterns in the measurement data, the information is notified to the user and the pet insurance company.

[1623] Proposal for a solution

[1624] If an abnormality is detected, the server will suggest and notify the user of specific countermeasures and treatments according to the type of abnormality.

[1625] Analyzing emotion data and adjusting notification methods

[1626] The emotion engine analyzes the user's emotional state and the data is reflected in the system. For example, if the user is feeling stressed, the server will adjust the notification method to be softer.

[1627] Specific examples

[1628] Suppose a user feeds their pet 75 grams of cat food in the morning. The device measures the weight on a scale and sends the data to the server. The server records the weight in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, sent, and recorded. Furthermore, when the pet defecates, the litter box sensor measures 50 grams of urine and 20 grams of feces, sending the respective data to the server. Based on this data, the server visualizes the day's nutritional and water intake and notifies the user and the pet insurance company if an abnormality is detected. The server then suggests specific measures to take depending on the abnormality. Furthermore, the emotion engine analyzes the user's emotional state and appropriately adjusts the notification method. For example, if the user is feeling stressed, notifications are adjusted to a gentler tone.

[1629] This system allows users to efficiently and accurately manage their animals' health, detect abnormalities early, and take appropriate measures.It also takes the user's emotional state into consideration, making management easier and less stressful.

[1630] The processing flow will be explained below.

[1631] Step 1:

[1632] The user places cat food into a bowl before feeding the animal.

[1633] Step 2:

[1634] The weight of the cat food in the bowl is measured using a scale installed on the terminal.

[1635] Step 3:

[1636] The device sends the measured weight of the meal (for example, 75 grams) to the server as data.

[1637] Step 4:

[1638] The server records the received data in the database as "2023-10-24 08:00, meal, 75 grams."

[1639] Step 5:

[1640] The user fills the water bowl before giving the animal water.

[1641] Step 6:

[1642] The weight of the water container is measured using a scale installed on the terminal.

[1643] Step 7:

[1644] The device sends the measured weight of the water (for example, 150 grams) to the server as data.

[1645] Step 8:

[1646] The server records the received data in the database as "2023-10-24 08:05, water, 150 grams."

[1647] Step 9:

[1648] Animals use the toilet to excrete urine and feces.

[1649] Step 10:

[1650] A sensor built into the toilet measures the weight of urine and feces.

[1651] Step 11:

[1652] The device sends the measured weight of the urine and feces (e.g., 50 grams of urine and 20 grams of feces) as data to the server.

[1653] Step 12:

[1654] The server records the received data in the database as "2023-10-24 18:00, urine, 50 grams" and "2023-10-24 18:05, feces, 20 grams."

[1655] Step 13:

[1656] At the end of the day, the server visualizes the animal's total food intake, water intake, urine volume, and feces volume based on the stored data.

[1657] Step 14:

[1658] Users can check their daily total data through a web browser or a dedicated app.

[1659] Step 15:

[1660] The server uses a data analysis algorithm to analyze the stored data and detect abnormal values ​​and patterns.

[1661] Step 16:

[1662] If an abnormality is detected, the server notifies the user and the pet insurance company of the information.

[1663] Step 17:

[1664] The server proposes specific countermeasures and treatment methods depending on the type of abnormality and notifies the user of this information.

[1665] Step 18:

[1666] When a user accesses the dedicated app, the emotion engine analyzes the user's facial expressions and input data to estimate their emotional state.

[1667] Step 19:

[1668] The device transmits the emotion data analyzed by the emotion engine to the server.

[1669] Step 20:

[1670] The server stores the analyzed emotional data and adjusts the notification method based on the user's emotional state. For example, if the user is stressed, the notification will be delivered in a gentler tone.

[1671] The above are the specific processing steps based on the claims. This system allows users to efficiently and accurately manage the health status of their animals, detect abnormalities early and take appropriate measures, and even provides pleasant notifications that take into account the emotional state of the animals.

[1672] Example 2

[1673] 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."

[1674] While conventional animal health management systems have the ability to measure and record the amount of food and water intake and excrement of animals, they lack sufficient means for comprehensively managing the health of animals. Furthermore, while early response and appropriate measures are required when abnormalities in an animal's health are detected, methods for doing so are limited. Furthermore, since no systems exist that take the user's emotional state into consideration, a management method that is less stressful for users is needed.

[1675] 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.

[1676] In this invention, the server includes means for measuring the weight of the animal's food, means for measuring the animal's water intake, means for measuring the weight of the animal's waste, means for storing the measured data, means for visualizing the daily nutrient and water intake based on the stored data, means for detecting abnormalities based on the visualized data, means for notifying the insurance company of the abnormality in cooperation with the insurance company, means for analyzing the user's emotional state, and means for adjusting the notification method based on the analyzed emotional state data. This enables efficient and accurate management of the animal's health, early detection of abnormalities, and appropriate countermeasures. Furthermore, by taking the user's emotional state into consideration, management can be made easier to use and less stressful.

[1677] "Means for weighing animal food" means any device or equipment used to accurately measure the weight of food provided to an animal.

[1678] "Means for measuring animal water intake" refers to a device or instrument that accurately measures the amount of water consumed by an animal.

[1679] "Means for weighing animal waste" refers to a device or instrument that accurately measures the weight of feces or urine excreted by an animal.

[1680] "Means for storing the measured data" refers to a storage device or cloud database for storing measured data on food, water, and excrement over a long period of time.

[1681] "Means for visualizing daily nutrient and water intake amounts based on the stored data" refers to software or tools for visually displaying an animal's daily nutrient and water intake amounts based on the stored data.

[1682] "Means for detecting anomalies based on the visualized data" refers to algorithms or software for analyzing the visualized data and detecting abnormal values ​​or patterns that exceed the normal range.

[1683] "Means for coordinating with and notifying the insurance company of the abnormality" refers to a communication system or program that automatically sends information about an abnormality to the insurance company when it is detected.

[1684] "Means for analyzing the user's emotional state" refers to software, algorithms, and sensors for analyzing the user's emotional state.

[1685] "Means for adjusting the notification method based on the analyzed emotional state data" refers to a system or algorithm for adjusting the wording or method of notifications based on the analyzed emotional state data of the user.

[1686] This invention relates to a system that supports animal health management and takes into account the emotional state of the user. This system measures and stores the amount of food and water intake and excrement of the animal, visualizes the data, detects abnormalities, and also includes collaboration with pet insurance companies and analysis and adjustment of the user's emotional state.

[1687] Overall structure

[1688] The system includes the following elements:

[1689] 1. Food measurement method: A scale is installed on the terminal to measure the weight of the food that the user gives to the animal. A digital scale (e.g., a general digital scale) and a Python library (e.g., pySerial) are used.

[1690] 2. Water measurement means: A scale is installed on the terminal to measure the amount of water the user gives to the animal. It uses the same equipment and software as a digital scale.

[1691] 3. Waste measurement: The animal's litter box has built-in sensors (e.g., load cell sensors) and scales to measure the weight of feces and urine. Python libraries (e.g., Rpi.GPIO) are used.

[1692] 4. Data storage method: The measured data on food intake, water intake, and excrement is sent from the device to a server and stored in a database using a database such as MySQL or PostgreSQL.

[1693] 5. Data visualization: The server uses the received data to display the animals' daily nutrient and water intake in graphs and tables using JavaScript libraries (e.g., Chart.js, D3.js).

[1694] 6. Anomaly detection: The server is equipped with data analysis algorithms (e.g., scikit-learn, TensorFlow) that automatically detect outliers and patterns that exceed the normal range from the stored data.

[1695] 7. Insurance collaboration notification method: When an anomaly is detected, API collaboration or email services (e.g., SendGrid) are used to automatically send information to the insurance company.

[1696] 8. Response suggestion method: Specific response methods and treatments are suggested to the user depending on the type of abnormality. Using rule-based approaches and machine learning models.

[1697] 9. Sentiment Analysis Engine Means: Software and algorithms that analyze the user's emotional state (e.g., using NLP techniques, sentiment analysis libraries (e.g., NLTK, TextBlob)).

[1698] 10. Notification Tailoring: Systems and algorithms for tailoring notification language and delivery based on analyzed emotional state data.

[1699] Specific examples

[1700] Suppose a user feeds their pet 75 grams of cat food in the morning. The device measures the weight on a scale and sends the data to the server. The server records the weight in the database as "2023-10-24 08:00, Meal, 75 grams." Similarly, 150 grams of water is also measured, sent, and recorded. Furthermore, when the pet defecates, the litter box sensor measures 50 grams of urine and 20 grams of feces, and sends and records the respective data to the server. Based on this data, the server visualizes the day's nutritional and water intake and notifies the user and insurance company if an abnormality is detected. The server then suggests specific measures to take depending on the abnormality. Furthermore, an emotion analysis engine analyzes the user's emotional state and appropriately adjusts the notification method. For example, if the user is feeling stressed, notifications are adjusted to a gentler tone.

[1701] Prompt Sentence Examples

[1702] "Please tell us the specific steps of a system that helps manage the health of pet animals and takes user emotions into consideration. Also, please specify the specific hardware and software you will use."

[1703] This system allows users to efficiently and accurately manage the health of their animals, detect abnormalities early, and take appropriate measures.It also takes the user's emotional state into consideration, making management easier to use and less stressful.

[1704] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1705] Step 1: Measuring your food intake

[1706] When a user feeds an animal, the user uses the scale on the device to measure the weight of the cat food. The input is the cat food that the user places on the scale, and the output is the measured weight (for example, 75 grams). The device sends this data to the server, which records the measurement data in a database. Specifically, when the user places the cat food on the scale, the device measures the weight and sends the measurement result to the server. The server saves this in the database as "2023-10-24 08:00, Meal, 75 grams."

[1707] Step 2: Measure moisture content

[1708] When a user gives water to an animal, the terminal measures the weight of the water. The input is the water the user places on the scale, and the output is the measured weight (for example, 150 grams). The terminal sends this data to the server, which records the measurement data in a database. Specifically, when the user places water on the scale, the terminal measures the weight and sends the measurement result to the server. The server saves the data in the database as "2023-10-24 08:05, water, 150 grams."

[1709] Step 3: Measuring feces

[1710] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces. The input is the urine and feces excreted by the animal into the toilet, and the output is the measured weight (for example, 50 grams of urine and 20 grams of feces). The terminal sends this data to a server, which records the measured data in a database. Specifically, when an animal uses the toilet, the sensor measures the weight of the urine and feces and sends the measurement results to the server. The server saves the data in the database as "2023-10-24 12:00, urine, 50 grams" and "2023-10-24 12:05, feces, 20 grams."

[1711] Step 4: Save your data

[1712] The server receives all measurement data sent from the terminal and stores it in a database. The input is the measurement data sent from the terminal, and the output is the data recorded in the database. Specifically, the server receives the measurement data and accurately records and stores it in the database.

[1713] Step 5: Visualize the data

[1714] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables. The input is the measurement data stored in the database, and the output is visualized data (graphs and tables). Users can check this data through a web browser or a dedicated app. Specifically, the server extracts data from the database, visualizes it using a JavaScript library, and displays it in the user's browser or app.

[1715] Step 6: Detect anomalies

[1716] The server uses data analysis algorithms to automatically detect outliers and patterns from the stored data. The input is the measurement data stored in the database, and the output is the detected anomaly information. Specifically, the server analyzes the data using scikit-learn and TensorFlow to detect values ​​and patterns that are outside the normal range.

[1717] Step 7: Insurance Linkage Notification

[1718] If the server detects an anomaly, it automatically sends that information to the insurance company. The input is the detected anomaly information, and the output is the notification sent to the insurance company. Specifically, the server sends the anomaly information using the insurance company's API, or notifies the company using an email service.

[1719] Step 8: Propose a course of action

[1720] When an abnormality is detected, the server proposes specific countermeasures and treatments to the user depending on the type of abnormality. The input is the detected abnormality information, and the output is the proposed countermeasure. Specifically, the server generates a countermeasure using a pre-configured rule-based model or machine learning model and notifies the user.

[1721] Step 9: Analyze emotion data and adjust notification methods

[1722] The server uses an emotion engine to analyze the user's emotional state and adjust the notification method. The input is the user's emotional data, and the output is the adjusted notification method. Specifically, the server uses NLP technology and an emotion analysis library to estimate the user's emotional state, and adjusts the content and tone of the notification based on the results.

[1723] (Application example 2)

[1724] 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."

[1725] It is difficult to accurately manage the health status of animals in animal health management facilities such as pet shops. It is also necessary to notify staff and insurance agencies of this information in a timely manner, and to provide an appropriate notification method that reflects the emotional state of users (staff and owners). Conventional systems have difficulty meeting these diverse requirements, so a system is needed that efficiently and accurately manages the health status of animals and reduces the psychological burden on those involved.

[1726] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for measuring the weight of the animal's food, means for measuring the amount of water the animal consumes, means for measuring the weight of the animal's waste, means for storing the measured data, means for visualizing the daily nutrient intake and water intake based on the stored data, means for detecting abnormalities based on the visualized data, means for notifying the abnormality to a cooperating insurance company, and means for supporting animal health management at an animal health management facility, analyzing the emotional state of a facility staff member, and adjusting an appropriate notification method. This enables efficient and accurate management of the animal's health status, enables rapid response to abnormalities and smooth collaboration with insurance companies, and enables notifications that take the emotional state of the staff member into consideration.

[1727] "Means for measuring the weight of food given to animals" refers to a device that measures the weight of food given to animals using a sensor or scale attached to a feeder.

[1728] A "means for measuring the amount of water consumed by an animal" is a device that uses a sensor or scale installed at the water trough to measure the amount of water an animal drinks.

[1729] A "means for measuring the weight of animal excrement" is a device that uses sensors or scales installed in the animal's litter box to measure the weight of animal excrement such as feces and urine.

[1730] "Means for storing measured data" refers to a system that stores measured data such as food intake, water intake, and amount of excrement in a database or on the cloud.

[1731] The "means for visualizing daily nutritional and water intake" is a system that uses stored data to display an animal's daily food and water intake in graphs and tables, allowing it to be visually confirmed.

[1732] "Means for detecting anomalies" refers to algorithms or programs that analyze measurement data and automatically detect abnormal data or patterns that exceed the normal range.

[1733] The "means of notifying affiliated insurance companies" refers to a system that automatically sends information to insurance companies that hold insurance contracts for animals when an abnormality is detected.

[1734] "Animal health management support means" refers to a series of devices and systems that effectively manage the health of animals based on measurement data on their food, water intake, and excretion.

[1735] The "means for analyzing the emotional state of personnel" refers to software or algorithms for analyzing the emotional state of users who operate the system, such as facility staff or animal owners.

[1736] The "means for adjusting the appropriate notification method" is a system for notifying the user in the most appropriate way according to their emotional state based on the analyzed emotional data.

[1737] To implement this invention, it is necessary to build a system with multiple measurement means that can analyze the user's emotional state and provide appropriate notification methods, as well as manage the animal's health.

[1738] System configuration

[1739] The system mainly consists of the following hardware and software:

[1740] Food weighing device: A scale attached to the feeder to measure the weight of the animal's food.

[1741] Water measuring device: a scale to measure the amount of water an animal consumes. This is placed at the water trough.

[1742] Waste measurement means: sensors and scales built into the litter box used by animals.

[1743] Data storage means: A database for storing measured data. A cloud database is used.

[1744] Visualization method: Using a data analysis algorithm on the server, daily nutritional and water intake amounts are displayed in graphs and tables.

[1745] Anomaly detection method: An algorithm that analyzes measurement data and automatically detects anomalies outside the normal range.

[1746] Notification method: A system that notifies collaborating insurance companies when an abnormality is detected.

[1747] Emotion analysis tool: Software for analyzing the user's emotional state.

[1748] Notification method adjustment means: A system that adjusts the notification method based on the analyzed emotion data.

[1749] Example

[1750] As an example of the system, the following steps are followed.

[1751] Meal Measurement

[1752] When a user feeds an animal, they use a scale attached to the device to measure the weight of the cat food, etc. The measurement data is automatically sent to the server and recorded in a database.

[1753] Moisture measurement

[1754] Similarly, the amount of water is measured using a scale installed on the device, and this measurement data is also sent to the server and stored.

[1755] excrement measurement

[1756] When an animal uses the toilet, a sensor inside the toilet measures the weight of the urine and feces and sends the data to a server for recording.

[1757] Data visualization

[1758] The server uses the stored data to display the animals' daily nutrient and water intake in graphs and tables, and users can check this data via a web browser or a dedicated app.

[1759] Anomaly detection and notification

[1760] The server's data analysis algorithm automatically detects abnormal values ​​and patterns in the measurement data, and if an abnormality is detected, the information is automatically notified to the pet insurance company.

[1761] Proposal for a solution

[1762] If an abnormality is detected, the server notifies the user of specific countermeasures and treatments according to the type of abnormality.

[1763] Analyzing emotion data and adjusting notification methods

[1764] Emotion analysis software analyzes the user's emotional state and adjusts notifications based on that data - for example, if the user is stressed, notifications will be adjusted to a gentler tone.

[1765] Examples and prompts

[1766] As a concrete example, consider the case of managing the health of animals in a pet shop. When a pet shop staff member gives an animal 75 grams of cat food, they measure it on a scale on their device and send the data to a server. Based on the data, the server will suggest appropriate measures to take and adjust the notification content if an abnormality is detected.

[1767] An example of a prompt for a generative AI model is as follows:

[1768] text

[1769] A pet shop has implemented a system that measures the amount of food and water intake and waste produced by animals, and detects abnormalities based on health management data. If an abnormality is detected, staff are notified and the system coordinates with the pet insurance company. Staff who appear stressed are also notified in a gentle tone. As a concrete example, please demonstrate the process of measuring 75 grams of cat food, 150 grams of water, and 70 grams of waste, detecting abnormalities, and suggesting how to address them.

[1770] This prompt sentence helps the generative AI model to gain a deeper understanding of the system's operational flow and behavior.

[1771] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1772] Step 1:

[1773] The user uses the scale on the device to measure the weight of the food to be given to the animal. The input is the amount of food, such as cat food, and the output is the measured weight data. This measurement data is converted into digital data within the device so that the weight of the cat food is recorded accurately.

[1774] Step 2:

[1775] The device sends the measured weight data to the server. The input is the measured data, and the output is the data stored in the cloud database. The transmission protocol is HTTP request, and the data is securely stored on the server.

[1776] Step 3:

[1777] Similarly, the user weighs the amount of water to give to the animal on a scale. The input is the amount of water, and the output is the measured weight. This data is also converted into digital data by the terminal.

[1778] Step 4:

[1779] The device sends the measured water weight data to the server. The input is the data measured earlier, and the output is the data to be saved in the cloud database. The transmission is also done using an HTTP request.

[1780] Step 5:

[1781] When an animal uses the toilet, a sensor inside the toilet measures the weight of the waste (urine and feces). The input is the amount of waste, and the output is the measured weight. This data is converted into digital data by the sensor inside the toilet.

[1782] Step 6:

[1783] The device sends the measured excrement weight data to the server. The input is the measured data, and the output is the data stored in the cloud database. The measured data is sent to the server using a secure communication protocol.

[1784] Step 7:

[1785] The server visualizes the animals' daily nutritional and water intake based on the stored data. The input is data stored in a cloud database, and the output is visualized data displayed in graphs and tables. Data analysis algorithms handle this process and convert the data into an easy-to-understand format.

[1786] Step 8:

[1787] The server's data analysis algorithm automatically detects abnormal values ​​and patterns in the measurement data. The input is daily nutrition and fluid intake data, and the output is the anomaly detection results. Statistical methods and machine learning algorithms are used to identify abnormal patterns.

[1788] Step 9:

[1789] If an anomaly is detected, the server automatically notifies the insurance company of that information. The input is the anomaly detection result, and the output is a notification message to the insurance company. Notifications are sent via email, API calls, etc.

[1790] Step 10:

[1791] The server proposes specific measures to the user (staff or owner) depending on the type of abnormality. The input at this time is the type of abnormality and its detailed information, and the output is a message proposing measures and treatment. The measures are determined by referring to prescription examples stored in a database in advance.

[1792] Step 11:

[1793] Emotion analysis software installed on the device is used to analyze the user's emotional state. The input is the user's operation log and facial expression data, and the output is analyzed emotional state data. Emotion analysis uses machine learning algorithms and NLP (natural language processing) technology.

[1794] Step 12:

[1795] The server adjusts the notification method based on the analyzed emotional data. The input is the analyzed emotional state data, and the output is an adjusted notification message. For example, if the user is feeling stressed, a notification with a gentler tone is generated. This reduces the user's psychological burden.

[1796] 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.

[1797] 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.

[1798] 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.

[1799] 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.

[1800] 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.

[1801] These emotions are distributed in the 3 o'clock direction on emotion ma...

Claims

1. a means for weighing the animal's meal; a means for measuring the water intake of the animal; a means for weighing animal waste; a means for storing the measured data; A means for visualizing daily nutritional intake and water intake based on the stored data; means for detecting an abnormality based on the visualized data; A means for notifying the abnormality in cooperation with pet insurance. Including system.

2. The system according to claim 1 , further comprising: means for, when the abnormality is detected, proposing a method of dealing with the abnormality according to the type of the abnormality.

3. The system of claim 1 , further comprising: means for storing the measured data in a cloud database via the Internet.

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