system

Abstract

We provide the system. [Solution] A means of collecting excrement and environmental data, equipped with various sensors, A means for transmitting collected data to a data processing device via wireless communication, A means of analyzing received data using artificial intelligence to evaluate health status, A means of providing users with health advice based on analysis results, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, people's health management is an important issue, but the current situation is that the health data obtained in daily life is not fully utilized. For example, although toilets are facilities used by everyone, the data of important health indicators obtained from them are not currently fully utilized. Therefore, there is a need for a new method to monitor and improve health status through daily use. Also, an unpleasant toilet environment can also cause stress, so environmental improvement should be solved simultaneously.

Means for Solving the Problems

[0005] This invention relates to a system that monitors health status by installing a device equipped with various sensors in a toilet and collecting data on excrement and the environment. The collected data is transmitted to a data processing device via wireless communication, where it is analyzed using artificial intelligence. Based on the resulting analysis, the user is provided with personalized health advice. Furthermore, if an unpleasant odor is detected by the odor sensor, the system automatically supplies fragrance to provide a comfortable environment. The system also includes a means to enable more specialized health management by providing the analyzed health data to medical institutions. This realizes a new health management system that utilizes the everyday space of a toilet.

[0006] "Various sensors" are devices used to measure the state of the environment and waste products, detecting odors, temperature, humidity, chemical composition, etc.

[0007] "Excrement and environmental data" refers to data on the properties of excrement and the environment within the toilet, obtained during toilet use, and is information used to assess health status.

[0008] "Wireless communication" refers to methods of sending and receiving data using technologies such as Wi-Fi and 5G, and is a technology that allows data transfer without using physical cables.

[0009] A "data processing device" is a computer system used to analyze and process collected data, and includes a platform for running artificial intelligence.

[0010] "Analyzing using artificial intelligence" refers to the process of analyzing collected data using technologies such as machine learning algorithms to assess health status and detect abnormalities.

[0011] "Health advice" refers to information and suggestions provided to users based on analysis results, aimed at encouraging improvements in lifestyle and appropriate behavior.

[0012] A "smell sensor" is a sensor device that detects odor components in the air and measures their concentration and quality.

[0013] "Supplying fragrance" refers to the process of automatically spraying scented substances to maintain a pleasant toilet environment.

[0014] "Health data" is a general term for information indicating the characteristics of excrement and the user's health status, and includes insights obtained through analysis.

[0015] "Providing data to medical institutions" means transmitting the analyzed health data to medical professionals and facilities for use in professional evaluation and diagnosis. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10]It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described according to the accompanying drawings.

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

[0019] In the following embodiments, a processor with a reference number (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, a RAM (Random Access Memory) with a reference number is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention describes a system for collecting and analyzing sensor data using a toilet, in order to improve health management in daily life. The system consists of various sensors installed in the toilet, a server for processing the data, and a smartphone application for the user.

[0038] The terminal (sensor device inside the toilet) monitors the color, shape, and chemical composition of excrement obtained during toilet use, as well as the ambient temperature, humidity, and odor, in real time. This sensor information is integrated within the terminal at regular intervals and transmitted wirelessly to a server in the cloud as an exclusively selected dataset.

[0039] The server operates in a cloud computing environment, efficiently storing and preprocessing received data. It then uses artificial intelligence algorithms to monitor the user's health status and generate analysis results. During the analysis process, machine learning models identify patterns that indicate health indicators and detect anomalies and health risks.

[0040] The analysis results are sent by the server to an application installed on the user's smartphone. This application provides reports using an intuitive interface, easily conveying specific health advice to the user. For example, if vitamin deficiencies or insufficient fluid intake are detected, the necessary nutrients and corrective measures are specifically presented to the user.

[0041] Furthermore, the system also has a function that automatically supplies fragrance when it detects unpleasant odors, keeping the toilet environment comfortable. In addition, the health data obtained is securely encrypted and, if necessary and with the user's consent, provided to medical institutions for professional health management and diagnosis.

[0042] As a concrete example, the system activates when a user visits the toilet in the morning. If it detects that the previous night's meal contained excessive salt, the server sends a notification to the user recommending salt restriction for maintaining heart health. In this way, continuous health management is achieved.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The terminal collects data in real time from various sensors installed in the toilet, including temperature, humidity, odor, and the color, shape, and chemical composition of excrement.

[0046] Step 2:

[0047] The device packets the collected data at regular intervals and prepares to send it to a server in the cloud via a Wi-Fi or 5G network.

[0048] Step 3:

[0049] The server receives data sent from the terminal and stores it in a secure database. The received data undergoes preprocessing (data cleansing and format conversion).

[0050] Step 4:

[0051] The server inputs the pre-processed data into an AI algorithm and begins analyzing the data. Here, a machine learning model is used to perform health indicator analysis and anomaly detection, and to assess the user's health status.

[0052] Step 5:

[0053] The server generates a user health status report based on the results obtained from the analysis. The report includes information on diet, hydration, and suggestions and advice on necessary actions.

[0054] Step 6:

[0055] The server pushes the generated health report to the user's smartphone application, allowing the user to immediately review its contents.

[0056] Step 7:

[0057] Users access health reports through a smartphone app and take necessary lifestyle improvements based on the advice provided.

[0058] Step 8:

[0059] When the device detects an unpleasant odor using its odor sensor, it automatically sprays fragrance to improve the toilet environment.

[0060] Step 9:

[0061] The server, with the user's consent, encrypts the analysis results and provides the data to medical institutions as needed. This provision is for professional diagnosis purposes.

[0062] (Example 1)

[0063] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0064] Traditional health management methods based on excrement and environmental data suffer from fragmented data collection and analysis, making real-time health assessment and personalized health advice difficult. Furthermore, there are challenges such as the lack of automated solutions for environmental odor control and the insufficient means of securely sharing analysis results with healthcare institutions.

[0065] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0066] In this invention, the server includes means for collecting environmental information, including the physical and chemical attributes of excrement; means for transmitting integrated data to a data processing device using wireless communication technology; and means for analyzing the data using a generative AI model to identify health indicators and detect abnormal values ​​and health risks. This enables detailed real-time assessment of health status, allowing for the provision of personalized health advice, improved environmental comfort, and support for medical management through secure data sharing.

[0067] "Excrement" refers to solid or liquid waste products expelled from the body of an organism, and it is important data that reflects the health status of the organism.

[0068] "Environmental information" refers to physical conditions inside the toilet, such as temperature, humidity, and odor, which are factors that affect the user's health and comfort.

[0069] A "sensor group" is a system of devices that arranges multiple different types of sensors together, each measuring a different parameter.

[0070] Wireless communication technology is a technology that uses radio waves to send and receive information between devices, and has the advantage of being able to transfer data without using cables.

[0071] A "data processing device" is a computer system that stores, preprocesses, and analyzes received sensor data, and is typically located on the cloud.

[0072] A "generative AI model" is an artificial intelligence system that learns patterns based on past data and performs inferences on new data.

[0073] "Health indicators" are evaluation criteria that show the user's health status, and specifically include nutritional status and disease risk.

[0074] An "abnormal value" refers to a health indicator that falls outside the normal range and may indicate a health risk.

[0075] "Health risk" refers to an indicator of a condition that may potentially lead to illness or health problems in the future.

[0076] A "user device" is an electronic device used to receive analysis results and provide information to the user, and includes smartphones and similar devices.

[0077] "Fragrance supply" is the process of releasing fragrance to improve the odor of the toilet environment.

[0078] A "medical institution" is an organization that provides specialized medical services, and includes hospitals and clinics.

[0079] "Encrypted communication" is a technology that uses algorithms to transform data in order to protect its contents from third parties during transmission.

[0080] This invention provides a toilet-based sensor data collection and analysis system for improving health management. The following describes how this system is configured and operates.

[0081] The terminal (sensor device inside the toilet) not only acquires data such as the color, shape, and chemical composition of excrement in real time, but also monitors information such as the temperature, humidity, and odor of the toilet environment. This data is collected by multiple sensors and integrated at specific time intervals.

[0082] Using wireless communication technology (e.g., Wi-Fi or Bluetooth), the terminal transmits the collected data to the server. The server is located in a cloud computing environment and includes a database system for storing the received data and preprocessing modules for efficiently processing the data.

[0083] Next, the server analyzes the data using a generative AI model. The machine learning algorithm learns patterns based on past health data and known health indicators, and performs an efficient process of identifying health indicators in new data and identifying outliers and health risks.

[0084] Once the analysis is complete, the server notifies the user's device (smartphone) of the results. The notification provides health advice and warnings through an intuitive interface. For example, if the user is prone to nutritional deficiencies, the application will provide health advice such as, "You are deficient in vitamin D. Try getting some sunlight or consuming foods containing vitamin D."

[0085] Furthermore, the device has a function that automatically dispenses fragrance when it detects unpleasant odors using sensors, keeping the toilet environment comfortable. In addition, the server uses encryption technology to securely protect data and can provide data to medical institutions with the user's consent.

[0086] An example of a prompt message could be a request like, "Tell me my health predictions based on my recent eating habits," which would allow the user to receive personalized feedback for ongoing health management.

[0087] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0088] Step 1:

[0089] The device uses sensors to monitor the color, shape, and chemical composition of waste, as well as the temperature, humidity, and odor of the toilet during use. The sensor system is complex, using optical sensors to capture color and shape, and gas sensors to detect odor. The input is raw data measured by various sensors, which is then digitized and converted into a usable format. The output is integrated environmental data.

[0090] Step 2:

[0091] The terminal aggregates integrated environmental data at regular time intervals (e.g., every 5 minutes) and sends it to the server in the form of data packets via wireless communication technology. The input is the integrated environmental data, and the output is the data packets sent to the server. This operation is achieved by triggering a wireless communication module.

[0092] Step 3:

[0093] The server stores the received data in a database in the cloud. A database management system supports this process, ensuring that the data is stored systematically. The input is data packets sent from the terminal, and the output is structured data stored in the database.

[0094] Step 4:

[0095] The server preprocesses the data stored in the database. It removes outliers and appropriately imputes missing values ​​to prepare the data for analysis. The input is structured data in the database, and the output is clean, preprocessed data.

[0096] Step 5:

[0097] The server supplies pre-processed data to a generating AI model for data analysis. Machine learning algorithms identify health indicators and pinpoint outliers and health risks. The input is pre-processed, clean data, and the output is the analyzed results, namely health status and risk assessments.

[0098] Step 6:

[0099] The server sends the analysis results to the user's smartphone application. The results are visualized and presented to the user through an intuitive interface. The input is the analyzed results, and the output is visual feedback on the user's smartphone screen. The application displays specific health advice, such as "You are deficient in Vitamin D."

[0100] Step 7:

[0101] The device automatically activates the fragrance dispenser and releases a scent when it detects an unpleasant odor using its sensor. The input is the odor sensor detection data, and the output is the improved toilet environment. This operation is performed automatically based on a pre-set threshold.

[0102] Step 8:

[0103] The server transmits encrypted data to healthcare institutions based on user consent. This process is performed using a secure communication protocol. The input is the analysis results and user consent, and the output is health data that reaches the healthcare institution. This procedure allows healthcare institutions to make expert diagnoses based on detailed health information.

[0104] (Application Example 1)

[0105] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0106] Conventional health management systems have struggled to monitor excrement and environmental data in detail in real time, making it difficult to immediately detect abnormalities and prompt appropriate responses. Furthermore, they lacked a visual means of confirming changes in users' health status or suspicious environmental changes, resulting in a lack of immediacy and convenience.

[0107] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0108] In this invention, the server includes a device equipped with various sensors to monitor excrement and environmental data, means for transmitting the collected data to a processing unit via wireless communication, and means for analyzing the received data using a machine learning algorithm to determine the user's health status. This allows the user to understand changes in their health status in real time, immediately detect abnormal situations, and take appropriate measures.

[0109] "Various sensors" is a general term for a variety of sensing devices installed to monitor excrement and environmental data.

[0110] "Wireless communication" is a method of transmitting data using radio waves without requiring a physical connection.

[0111] A "processing unit" is a device or system equipped with computing resources for analyzing and determining received data.

[0112] A "machine learning algorithm" is a type of computational method that learns patterns from data and outputs analysis results.

[0113] "Health guidance" refers to the act of providing users with specific advice on improving or maintaining their health based on the analysis results.

[0114] "Anomaly detection" is a means of identifying data or situations that deviate from normal conditions and issuing warnings.

[0115] The system implementing this invention consists of a terminal installed in the toilet, a server in the cloud, and a smart device owned by the user. The terminal is equipped with various sensors that detect excrement and environmental data (temperature, humidity, odor, etc.), and this data is monitored in real time. The data acquired by the sensors is transmitted to a processing unit on the cloud server via wireless communication methods such as Wi-Fi or Bluetooth.

[0116] The server analyzes the received data using machine learning algorithms based on Python and TENSORFLOW®. This allows for a comprehensive assessment of the user's health status, and an immediate alarm is issued if an abnormality is detected. The analysis results and alarm details are sent via secure communication to the user's smartphone or smart glasses.

[0117] In this case, the application is developed using React Native or Flutter®, providing users with a visually intuitive interface. Health guidance and abnormal alerts are presented through an intuitive dashboard, and corrective actions and contact information for specialists are also provided as needed.

[0118] For example, if a user uses a toilet while wearing smart glasses and an unusual odor is detected, the system analyzes the situation in the cloud and displays a notification through the glasses such as, "Please ventilate immediately." Furthermore, by using a generative AI model, it is possible to perform a deeper analysis by inputting prompts such as, "Please comprehensively assess the user's health condition after using the toilet."

[0119] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0120] Step 1:

[0121] The terminal uses various sensors installed in the toilet to detect the color, shape, and chemical composition of excrement, as well as the ambient temperature, humidity, and odor in real time. The input is physical environmental data, and the output is this data temporarily stored as digitized information within the terminal. Specifically, the sensors collect data at regular intervals, the terminal's processor standardizes the format, and then prepares the data for subsequent processing.

[0122] Step 2:

[0123] The device uses wireless communication to transmit collected data to a server in the cloud. The input is digitized sensor data stored within the device, and the output is data packets transmitted over the network. Specifically, the device periodically adds data to a queue or, when certain conditions are met, sends the data packets to the server using a reliable communication protocol.

[0124] Step 3:

[0125] The server analyzes received sensor data using a machine learning algorithm based on Python and TensorFlow to evaluate the user's health status. The input is sensor data sent from the terminal, and the output is the health status evaluation result and whether or not there are abnormalities. Specifically, the server preprocesses the data, then inputs it into a pre-trained machine learning model to estimate the health status, and performs an evaluation if an abnormal pattern is detected.

[0126] Step 4:

[0127] The server notifies the user's smart device of the analysis results. The input is health assessment data generated based on the analysis, and the output is a notification message. Specifically, the server generates the notification content and pushes the information to the user's specified device using services such as Azure Notification Hubs.

[0128] Step 5:

[0129] Users check notifications displayed on their smartphones or smart glasses and take necessary actions according to the health guidance and warnings provided. Inputs include notification information from the server, and outputs include user actions or feedback to the system. Specifically, users act according to the instructions presented by the device and record their reactions within the application as needed.

[0130] Step 6:

[0131] The user inputs prompts to a generated AI model to request further health assessments and advice. The input consists of user prompts, and the output is detailed analysis results or suggestions from the AI ​​model. Specifically, the user provides natural language input through the application, and the AI ​​model performs additional analysis based on this input and returns the results.

[0132] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0133] This invention is a system that combines multiple sensors installed in a toilet with an emotion engine to gain a more comprehensive understanding of the user's health condition and support appropriate health management. This system consists of a terminal, a server, and a user's smartphone application.

[0134] The device is equipped with various sensors that measure temperature, humidity, odor, and the chemical composition of waste, as well as a camera and microphone to capture the user's facial expressions and voice. This allows the device to collect environmental data and user emotional data while the user is using the toilet. This data is transmitted to a server in real time via wireless communication.

[0135] The server securely stores received environmental and emotional data in a database and performs analysis using AI technology. The analysis includes health status assessment based on excrement and environmental data, and recognition of the user's emotional state using an emotion engine. The emotion engine uses voice analysis and facial expression analysis technologies to evaluate the user's emotions, such as their psychological state and stress level.

[0136] The analysis results are generated by the server as a health status report, which includes advice based on emotional state and health indicators. This report is pushed to the user's smartphone app, allowing them to immediately review its contents. Furthermore, the user's emotional data is recorded chronologically, enabling analysis of long-term emotional patterns.

[0137] Users can use the provided health advice to review their daily lifestyle habits and decide to seek medical attention if necessary. If they are experiencing emotional instability, they will also be offered suggestions for relaxation and stress reduction techniques.

[0138] As a concrete example, when a user used the toilet, the device detected data suggesting an imbalance in gut flora and also sensed tension from the user's facial expression. Based on this information, the server sent a notification to the user suggesting easily digestible meals and introducing deep breathing techniques for relaxation. In this way, users can receive care not only for their physical health but also for their mental health.

[0139] The following describes the processing flow.

[0140] Step 1:

[0141] The device uses sensors installed in the toilet to collect temperature, humidity, odor, and the color and chemical composition of waste in real time. It also simultaneously captures the user's facial expressions and voice data using a camera and microphone.

[0142] Step 2:

[0143] The device packages the collected environmental data and user sentiment data and sends it to a server in the cloud using a Wi-Fi or 5G network.

[0144] Step 3:

[0145] The server receives data sent from the terminal and securely stores it in the database. During storage, it prepares and preprocesses the data and converts it into a format that can be used for AI analysis.

[0146] Step 4:

[0147] The server uses AI algorithms to analyze waste and environmental data to assess health status. Simultaneously, an emotion engine analyzes facial expressions and voice data to recognize the user's emotional state. This analysis determines the user's stress level and subjective well-being.

[0148] Step 5:

[0149] Based on the health assessment and emotion recognition results, the server generates a detailed report and health advice. This advice includes suggestions regarding diet and hydration, as well as guidance on maintaining mental well-being.

[0150] Step 6:

[0151] The server sends the generated results to the user's smartphone app via push notification, allowing the user to check their health report at any time.

[0152] Step 7:

[0153] Users check notifications through the app, and based on the results, decide and take necessary health improvement actions. If needed, they can utilize relaxation methods and psychological support that address their emotional state.

[0154] Step 8:

[0155] The server records and continuously analyzes users' long-term health data and emotional patterns, evolving the system to enable more personalized advice.

[0156] (Example 2)

[0157] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0158] In modern society, it is important to comprehensively understand and appropriately manage an individual's health status. However, conventional health management methods have been limited to collecting physical data, and have not adequately considered psychological and emotional aspects of health maintenance. This invention aims to improve physical and mental health by comprehensively evaluating health and emotional states based on data obtained using various sensors in toilets and providing appropriate advice.

[0159] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0160] In this invention, the server includes means for collecting biological waste and surrounding information, equipped with various detectors; means for transmitting the collected data to an information processing device via wireless communication; and means for analyzing the received data using an intelligent system and evaluating the user's health status. This makes it possible to comprehensively understand not only the user's physical health but also their psychological state and to provide appropriate health guidance.

[0161] "Various detectors" is a general term for devices used to measure temperature, humidity, odor, and the chemical composition of biological waste.

[0162] "Biological waste" refers to waste products excreted from the human body and are analyzed to assess health status.

[0163] "Surrounding information" refers to data that indicates the state of the environment, such as temperature, humidity, and odor.

[0164] An "information processing device" is a system for receiving and analyzing collected data.

[0165] "Wireless communication" is a means of communication that transmits and receives data without using cables.

[0166] An "intelligent system" is a technology that uses artificial intelligence to analyze and evaluate data.

[0167] "Health guidelines" refer to advice and recommended actions provided to users based on an assessment of their health status.

[0168] An "emotion analysis engine" is a technology that evaluates a user's emotional state based on voice and facial expression data.

[0169] A "terminal device" refers to an electronic device used directly by the user, and is used for notification and confirmation of information.

[0170] This invention is a system that uses various detectors installed in a toilet to comprehensively understand the user's physical and emotional state and support health management. This system consists of a terminal, a server, and the user's mobile information terminal.

[0171] The device is equipped with multiple detectors to measure temperature, humidity, odor, and the chemical composition of biological waste. It also collects data on the user's emotional state by recording their facial expressions and voice using a camera and microphone. This information is transmitted to a server in real time via wireless communication.

[0172] The server has a database for securely storing data received from the terminal. The server analyzes the data through an intelligent system utilizing artificial intelligence. The analysis includes health status assessment based on excrement and environmental data, and analysis of the user's psychological state using an emotion analysis engine. A health status report is generated based on the analysis results, which includes health guidelines for the user. This report is pushed to the mobile device, ensuring that the user is always provided with the latest information.

[0173] Users can adjust their daily lifestyle habits by utilizing health advice and recommended actions based on their emotional state, as notified via their device. For example, if data indicates that a user's gut balance is poor, the server provides health guidelines, including suggestions for easily digestible meals. Similarly, if the user's level of tension is detected from their facial expression data, suggestions for relaxation techniques are also provided. In this way, users can manage both their physical and mental health.

[0174] An example of a prompt to be input to the generating AI model would be: "Based on the user's gut balance data and emotional state, please suggest recommended lifestyle improvements."

[0175] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0176] Step 1:

[0177] The device measures temperature, humidity, odor, and the chemical composition of biowaste, and records the user's facial expressions and voice. The input data obtained from these sensors and devices is collected as environmental data and user emotion data. Specifically, the temperature sensor measures room temperature, and the humidity sensor measures humidity in the air. The odor sensor detects volatile compounds in the space, and the chemical sensor analyzes the chemical composition of excrement. In addition, the camera captures the user's facial expressions, and the microphone acquires voice data. The collected data is converted into packets and transmitted to the server in real time.

[0178] Step 2:

[0179] The server receives data transmitted from the terminal and stores it in a database. The input data is classified into environmental data and sentiment data and stored securely. The server then prepares to perform data analysis using artificial intelligence with this stored data. Encryption technology is used throughout this process to maintain data integrity and completeness.

[0180] Step 3:

[0181] The server activates its intelligent system and begins analyzing the received data. First, it assesses the user's health status using environmental data and biowaste data. Specifically, an AI algorithm detects abnormalities in chemical composition and environmental changes. Next, it uses an emotion analysis engine to analyze voice data and facial expression data to assess the user's psychological state and stress level. During this process, the AI ​​performs analysis based on conditions specified as prompts (e.g., "Based on the user's gut balance data and emotional state, please suggest recommended lifestyle improvements."). The analysis results are compiled into a report.

[0182] Step 4:

[0183] The server compiles the generated health status report into health guidelines and pushes them to the user's mobile device. The notification includes specific advice related to the user's health and emotional state. For example, if the user indicates high stress levels, relaxation methods such as deep breathing exercises will be suggested. The user will be shown specific methods for adjusting their daily lifestyle based on the health guidelines.

[0184] Step 5:

[0185] Users review health status reports notified on their devices and take action on the advice provided. If necessary, they review their daily schedules and habits and manage their lifestyle appropriately. As a result, users can improve their health and well-being.

[0186] (Application Example 2)

[0187] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0188] Traditional health management systems have focused on evaluating users' physical health, but lack analysis of emotional states and the response based on those states. Furthermore, commercial facilities fail to offer personalized services and products tailored to users' health conditions, resulting in insufficient personalization of services. This means users miss out on necessary health guidance and appropriate product information, missing opportunities for service improvement at commercial facilities.

[0189] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0190] In this invention, the server includes means for collecting excrement and surrounding environment data using various sensors, means for transmitting the collected data to a data processing device via wireless communication, means for analyzing the received data using artificial intelligence and evaluating the user's health status, means for providing health advice to the user based on the analysis results, and means for suggesting products or services within a commercial facility based on the analysis results. This makes it possible to provide personalized services and suggest products according to the user's health status.

[0191] "Various sensors" are devices that detect temperature, humidity, odor, chemical composition of excrement, as well as facial expressions and voices.

[0192] Wireless communication is a method of transmitting data without using physical connections such as cables.

[0193] A "data processing device" is a device, such as a computer or server, that analyzes received data and extracts necessary information.

[0194] "Artificial intelligence" is a technology that uses machines to mimic human intelligence and perform data analysis and predictions.

[0195] "Health advice" refers to guidelines for behaviors and lifestyle habits recommended to improve the user's health.

[0196] A "commercial facility" is a store or facility that provides goods and services to consumers.

[0197] "Service proposals" refer to information about appropriate products and services to be offered to users based on the analysis results.

[0198] In this invention, a terminal installed in a toilet collects data to comprehensively evaluate the user's health condition. The terminal is equipped with various sensors to measure temperature, humidity, odor, and the chemical composition of excrement, as well as a camera and microphone to capture the user's facial expressions and voice. This allows for the acquisition of environmental and emotional data obtained while the user is using the toilet.

[0199] Data obtained from sensors is transmitted to a server in real time via wireless communication. The server securely stores the received data in a database and analyzes the user's health and emotional state using AI technology. Data processing is performed using machine learning platforms such as Amazon SageMaker. The analysis results are generated as health advice to assess the user's health status and are notified to the user's smartphone in real time.

[0200] Furthermore, based on the analysis results, personalized product or service suggestions will be provided for use within the commercial facility. This will help users make informed purchasing decisions and utilize services within the facility.

[0201] For example, suppose a user uses the restroom and an imbalance in their gut flora is detected, along with increased stress levels observed in their facial expression. In this case, the server sends a push notification offering suggestions for easily digestible meals and a discount coupon for relaxation products at the store. This allows the user to receive both health and stress relief.

[0202] An example of a prompt to input into the generating AI model would be, "Based on the user's health data, please suggest products and services appropriate to their health condition." This prompt allows the AI ​​to derive the most suitable suggestions for each user.

[0203] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0204] Step 1:

[0205] The terminal acquires various sensor data from users using the toilet, including temperature, humidity, odor, and the chemical composition of excrement. This data is then packetized and prepared along with facial expression data and voice data captured by the camera and microphone. The input consists of sensor data and emotion data, while the output is an integrated data packet.

[0206] Step 2:

[0207] The terminal transmits the generated data packets to the server in real time via Bluetooth or Wi-Fi. The input is the integrated data packets, and the output is the result of data transmission via wireless communication.

[0208] Step 3:

[0209] The server stores the received data in a database and analyzes the acquired data on Amazon SageMaker. It uses an AI algorithm to evaluate health and emotional states and generates analysis results. The input is the transmitted data packets, and the output is the analyzed health and emotional state evaluation results.

[0210] Step 4:

[0211] The server uses an AI model generated based on the analysis results to produce healthcare advice tailored to the user's health condition, as well as recommendations for products and services within the commercial facility. The AI ​​model is invoked using prompts to generate personalized advice text. The input is the analysis results, and the output is user-specific advice and suggestions.

[0212] Step 5:

[0213] The server sends the generated advice and suggestions to the user's smartphone via push notification. The input is the generated advice text and suggestions, and the output is the notification result sent to the user's device.

[0214] Step 6:

[0215] Users check the advice and suggestions they receive via push notifications on their smartphones and use the suggested products or services as needed. The input is the information received via push notifications, and the output is the user's actions.

[0216] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0217] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0218] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0219] [Second Embodiment]

[0220] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0221] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0222] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0223] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0224] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0225] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0226] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0227] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0228] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0229] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0230] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0231] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0232] This invention describes a system for collecting and analyzing sensor data using a toilet, in order to improve health management in daily life. The system consists of various sensors installed in the toilet, a server for processing the data, and a smartphone application for the user.

[0233] The terminal (sensor device inside the toilet) monitors the color, shape, and chemical composition of excrement obtained during toilet use, as well as the ambient temperature, humidity, and odor, in real time. This sensor information is integrated within the terminal at regular intervals and transmitted wirelessly to a server in the cloud as an exclusively selected dataset.

[0234] The server operates in a cloud computing environment, efficiently storing and preprocessing received data. It then uses artificial intelligence algorithms to monitor the user's health status and generate analysis results. During the analysis process, machine learning models identify patterns that indicate health indicators and detect anomalies and health risks.

[0235] The analysis results are sent by the server to an application installed on the user's smartphone. This application provides reports using an intuitive interface, easily conveying specific health advice to the user. For example, if vitamin deficiencies or insufficient fluid intake are detected, the necessary nutrients and corrective measures are specifically presented to the user.

[0236] Furthermore, the system also has a function that automatically supplies fragrance when it detects unpleasant odors, keeping the toilet environment comfortable. In addition, the health data obtained is securely encrypted and, if necessary and with the user's consent, provided to medical institutions for professional health management and diagnosis.

[0237] As a concrete example, the system activates when a user visits the toilet in the morning. If it detects that the previous night's meal contained excessive salt, the server sends a notification to the user recommending salt restriction for maintaining heart health. In this way, continuous health management is achieved.

[0238] The following describes the processing flow.

[0239] Step 1:

[0240] The terminal collects data in real time from various sensors installed in the toilet, including temperature, humidity, odor, and the color, shape, and chemical composition of excrement.

[0241] Step 2:

[0242] The device packets the collected data at regular intervals and prepares to send it to a server in the cloud via a Wi-Fi or 5G network.

[0243] Step 3:

[0244] The server receives data sent from the terminal and stores it in a secure database. The received data undergoes preprocessing (data cleansing and format conversion).

[0245] Step 4:

[0246] The server inputs the pre-processed data into an AI algorithm and begins analyzing the data. Here, a machine learning model is used to perform health indicator analysis and anomaly detection, and to assess the user's health status.

[0247] Step 5:

[0248] The server generates a user health status report based on the results obtained from the analysis. The report includes information on diet, hydration, and suggestions and advice on necessary actions.

[0249] Step 6:

[0250] The server pushes the generated health report to the user's smartphone application, allowing the user to immediately review its contents.

[0251] Step 7:

[0252] Users access health reports through a smartphone app and take necessary lifestyle improvements based on the advice provided.

[0253] Step 8:

[0254] When the device detects an unpleasant odor using its odor sensor, it automatically sprays fragrance to improve the toilet environment.

[0255] Step 9:

[0256] The server, with the user's consent, encrypts the analysis results and provides the data to medical institutions as needed. This provision is for professional diagnosis purposes.

[0257] (Example 1)

[0258] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0259] Traditional health management methods based on excrement and environmental data suffer from fragmented data collection and analysis, making real-time health assessment and personalized health advice difficult. Furthermore, there are challenges such as the lack of automated solutions for environmental odor control and the insufficient means of securely sharing analysis results with healthcare institutions.

[0260] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0261] In this invention, the server includes means for collecting environmental information, including the physical and chemical attributes of excrement; means for transmitting integrated data to a data processing device using wireless communication technology; and means for analyzing the data using a generative AI model to identify health indicators and detect abnormal values ​​and health risks. This enables detailed real-time assessment of health status, allowing for the provision of personalized health advice, improved environmental comfort, and support for medical management through secure data sharing.

[0262] "Excrement" refers to solid or liquid waste products expelled from the body of an organism, and it is important data that reflects the health status of the organism.

[0263] "Environmental information" refers to physical conditions inside the toilet, such as temperature, humidity, and odor, which are factors that affect the user's health and comfort.

[0264] A "sensor group" is a system of devices that arranges multiple different types of sensors together, each measuring a different parameter.

[0265] Wireless communication technology is a technology that uses radio waves to send and receive information between devices, and has the advantage of being able to transfer data without using cables.

[0266] A "data processing device" is a computer system that stores, preprocesses, and analyzes received sensor data, and is typically located on the cloud.

[0267] A "generative AI model" is an artificial intelligence system that learns patterns based on past data and performs inferences on new data.

[0268] "Health indicators" are evaluation criteria that show the user's health status, and specifically include nutritional status and disease risk.

[0269] An "abnormal value" refers to a health indicator that falls outside the normal range and may indicate a health risk.

[0270] "Health risk" refers to an indicator of a condition that may potentially lead to illness or health problems in the future.

[0271] A "user device" is an electronic device that receives analysis results and provides information to the user, and includes smartphones and other similar devices.

[0272] "Fragrance supply" is the process of releasing fragrance to improve the odor of the toilet environment.

[0273] A "medical institution" is an organization that provides specialized medical services, and includes hospitals and clinics.

[0274] "Encrypted communication" is a technology that uses algorithms to transform data in order to protect its contents from third parties during transmission.

[0275] This invention provides a toilet-based sensor data collection and analysis system for improving health management. The following describes how this system is configured and operates.

[0276] The terminal (sensor device inside the toilet) not only acquires data such as the color, shape, and chemical composition of excrement in real time, but also monitors information such as the temperature, humidity, and odor of the toilet environment. This data is collected by multiple sensors and integrated at specific time intervals.

[0277] Using wireless communication technology (e.g., Wi-Fi or Bluetooth), the terminal transmits the collected data to the server. The server is located in a cloud computing environment and includes a database system for storing the received data and preprocessing modules for efficiently processing the data.

[0278] Next, the server analyzes the data using a generative AI model. The machine learning algorithm learns patterns based on past health data and known health indicators, and performs an efficient process of identifying health indicators in new data and identifying outliers and health risks.

[0279] Once the analysis is complete, the server notifies the user's device (smartphone) of the results. The notification provides health advice and warnings through an intuitive interface. For example, if the user is prone to nutritional deficiencies, the application will provide health advice such as, "You are deficient in vitamin D. Try getting some sunlight or consuming foods containing vitamin D."

[0280] Furthermore, the device has a function that automatically dispenses fragrance when it detects unpleasant odors using sensors, keeping the toilet environment comfortable. In addition, the server uses encryption technology to securely protect data and can provide data to medical institutions with the user's consent.

[0281] As an example of a prompt sentence, a request such as "Tell me the health prediction based on recent eating habits" can be considered, and the user can obtain individual feedback for continuous health management.

[0282] The flow of the specific process in Example 1 will be described using FIG. 11.

[0283] Step 1:

[0284] The terminal monitors the color, shape, chemical composition of excrement during toilet use, and further monitors the temperature, humidity, and odor in the toilet with sensors. The sensor system is complex, capturing color and shape with optical sensors and detecting odor with gas sensors. The input is the raw data measured by various sensors, which are digitized and converted into a usable format. The output is integrated environmental data.

[0285] Step 2:

[0286] The terminal summarizes the integrated environmental data at regular time intervals (for example, every 5 minutes) and transmits it to the server via wireless communication technology in the form of data packets. The input is the integrated environmental data, and the output is the data packet transmitted to the server. This operation is realized by triggering the wireless communication module.

[0287] Step 3:

[0288] The server stores the received data in a database in the cloud. The database management system supports this process, and the data is stored systematically. The input is the data packet transmitted from the terminal, and the output is the structured data stored in the database.

[0289] Step 4:

[0290] The server preprocesses the data stored in the database. It removes outliers and appropriately imputes missing values ​​to prepare the data for analysis. The input is structured data in the database, and the output is clean, preprocessed data.

[0291] Step 5:

[0292] The server supplies pre-processed data to a generating AI model for data analysis. Machine learning algorithms identify health indicators and pinpoint outliers and health risks. The input is pre-processed, clean data, and the output is the analyzed results, namely health status and risk assessments.

[0293] Step 6:

[0294] The server sends the analysis results to the user's smartphone application. The results are visualized and presented to the user through an intuitive interface. The input is the analyzed results, and the output is visual feedback on the user's smartphone screen. The application displays specific health advice, such as "You are deficient in Vitamin D."

[0295] Step 7:

[0296] The device automatically activates the fragrance dispenser and releases a scent when it detects an unpleasant odor using its sensor. The input is the odor sensor detection data, and the output is the improved toilet environment. This operation is performed automatically based on a pre-set threshold.

[0297] Step 8:

[0298] The server transmits encrypted data to healthcare institutions based on user consent. This process is performed using a secure communication protocol. The input is the analysis results and user consent, and the output is health data that reaches the healthcare institution. This procedure allows healthcare institutions to make expert diagnoses based on detailed health information.

[0299] (Application Example 1)

[0300] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0301] In the conventional health management system, it has been difficult to monitor excretory products and environmental data in detail in real time, immediately detect abnormalities, and prompt appropriate responses. In addition, there has been a lack of means to visually confirm changes in the user's health condition and suspicious environmental changes, lacking immediacy and convenience.

[0302] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0303] In this invention, the server includes a device equipped with various sensors for monitoring excretory products and environmental data, means for transmitting the collected data to the processing unit via wireless communication, and means for analyzing the received data using a machine learning algorithm to determine the health condition. Thereby, the user can grasp changes in the health condition in real time, immediately detect abnormal situations, and take appropriate measures.

[0304] "Various sensors" is a general term for various sensing devices installed for monitoring excretory products and environmental data.

[0305] "Wireless communication" is a method of transmitting data using radio waves without the need for a physical connection.

[0306] "Processing unit" is a device or system equipped with computer resources for analyzing and determining the received data.

[0307] "Machine learning algorithm" is a type of computational method that learns patterns from data and outputs analysis results.

[0308] "Health guidance" refers to the act of providing users with specific advice on improving or maintaining their health based on the analysis results.

[0309] "Anomaly detection" is a means of identifying data or situations that deviate from normal conditions and issuing warnings.

[0310] The system implementing this invention consists of a terminal installed in the toilet, a server in the cloud, and a smart device owned by the user. The terminal is equipped with various sensors that detect excrement and environmental data (temperature, humidity, odor, etc.), and this data is monitored in real time. The data acquired by the sensors is transmitted to a processing unit on the cloud server via wireless communication methods such as Wi-Fi or Bluetooth.

[0311] The server analyzes the received data using machine learning algorithms based on Python and TensorFlow. This allows for a comprehensive assessment of the user's health status, and an immediate alarm is issued if an anomaly is detected. The analysis results and alarm details are sent via secure communication to the user's smartphone or smart glasses.

[0312] In this case, the application is developed using React Native or Flutter, providing a visually intuitive interface for the user. Health guidance and abnormal alerts are presented through an intuitive dashboard, and corrective actions and contact information for specialists are also provided as needed.

[0313] For example, if a user uses a toilet while wearing smart glasses and an unusual odor is detected, the system analyzes the situation in the cloud and displays a notification through the glasses such as, "Please ventilate immediately." Furthermore, by using a generative AI model, it is possible to perform a deeper analysis by inputting prompts such as, "Please comprehensively assess the user's health condition after using the toilet."

[0314] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0315] Step 1:

[0316] The terminal uses various sensors installed in the toilet to detect the color, shape, and chemical composition of excrement, as well as the ambient temperature, humidity, and odor in real time. The input is physical environmental data, and the output is this data temporarily stored as digitized information within the terminal. Specifically, the sensors collect data at regular intervals, the terminal's processor standardizes the format, and then prepares the data for subsequent processing.

[0317] Step 2:

[0318] The device uses wireless communication to transmit collected data to a server in the cloud. The input is digitized sensor data stored within the device, and the output is data packets transmitted over the network. Specifically, the device periodically adds data to a queue or, when certain conditions are met, sends the data packets to the server using a reliable communication protocol.

[0319] Step 3:

[0320] The server analyzes received sensor data using a machine learning algorithm based on Python and TensorFlow to evaluate the user's health status. The input is sensor data sent from the terminal, and the output is the health status evaluation result and whether or not there are abnormalities. Specifically, the server preprocesses the data, then inputs it into a pre-trained machine learning model to estimate the health status, and performs an evaluation if an abnormal pattern is detected.

[0321] Step 4:

[0322] The server notifies the user's smart device of the analysis results. The input is health assessment data generated based on the analysis, and the output is a notification message. Specifically, the server generates the notification content and pushes the information to the user's specified device using services such as Azure Notification Hubs.

[0323] Step 5:

[0324] Users check notifications displayed on their smartphones or smart glasses and take necessary actions according to the health guidance and warnings provided. Inputs include notification information from the server, and outputs include user actions or feedback to the system. Specifically, users act according to the instructions presented by the device and record their reactions within the application as needed.

[0325] Step 6:

[0326] The user inputs prompts to a generated AI model to request further health assessments and advice. The input consists of user prompts, and the output is detailed analysis results or suggestions from the AI ​​model. Specifically, the user provides natural language input through the application, and the AI ​​model performs additional analysis based on this input and returns the results.

[0327] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0328] This invention is a system that combines multiple sensors installed in a toilet with an emotion engine to gain a more comprehensive understanding of the user's health condition and support appropriate health management. This system consists of a terminal, a server, and a user's smartphone application.

[0329] The device is equipped with various sensors that measure temperature, humidity, odor, and the chemical composition of waste, as well as a camera and microphone to capture the user's facial expressions and voice. This allows the device to collect environmental data and user emotional data while the user is using the toilet. This data is transmitted to a server in real time via wireless communication.

[0330] The server securely stores received environmental and emotional data in a database and performs analysis using AI technology. The analysis includes health status assessment based on excrement and environmental data, and recognition of the user's emotional state using an emotion engine. The emotion engine uses voice analysis and facial expression analysis technologies to evaluate the user's emotions, such as their psychological state and stress level.

[0331] The analysis results are generated by the server as a health status report, which includes advice based on emotional state and health indicators. This report is pushed to the user's smartphone app, allowing them to immediately review its contents. Furthermore, the user's emotional data is recorded chronologically, enabling analysis of long-term emotional patterns.

[0332] Users can use the provided health advice to review their daily lifestyle habits and decide to seek medical attention if necessary. If they are experiencing emotional instability, they will also be offered suggestions for relaxation and stress reduction techniques.

[0333] As a concrete example, when a user used the toilet, the device detected data suggesting an imbalance in gut flora and also sensed tension from the user's facial expression. Based on this information, the server sent a notification to the user suggesting easily digestible meals and introducing deep breathing techniques for relaxation. In this way, users can receive care not only for their physical health but also for their mental health.

[0334] The following describes the processing flow.

[0335] Step 1:

[0336] The device uses sensors installed in the toilet to collect temperature, humidity, odor, and the color and chemical composition of waste in real time. It also uses a camera and microphone to simultaneously capture the user's facial expressions and voice data.

[0337] Step 2:

[0338] The device packages the collected environmental data and user sentiment data and sends it to a server in the cloud using a Wi-Fi or 5G network.

[0339] Step 3:

[0340] The server receives data sent from the terminal and securely stores it in the database. During storage, it prepares and preprocesses the data and converts it into a format that can be used for AI analysis.

[0341] Step 4:

[0342] The server uses AI algorithms to analyze waste and environmental data to assess health status. Simultaneously, an emotion engine analyzes facial expressions and voice data to recognize the user's emotional state. This analysis determines the user's stress level and subjective well-being.

[0343] Step 5:

[0344] Based on the health assessment and emotion recognition results, the server generates a detailed report and health advice. This advice includes suggestions regarding diet and hydration, as well as guidance on maintaining mental well-being.

[0345] Step 6:

[0346] The server sends the generated results to the user's smartphone app via push notification, allowing the user to check their health report at any time.

[0347] Step 7:

[0348] Users check notifications through the app, and based on the results, decide and take necessary health improvement actions. If needed, they can utilize relaxation methods and psychological support that address their emotional state.

[0349] Step 8:

[0350] The server records and continuously analyzes users' long-term health data and emotional patterns, evolving the system to enable more personalized advice.

[0351] (Example 2)

[0352] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0353] In modern society, it is important to comprehensively understand and appropriately manage an individual's health status. However, conventional health management methods have been limited to collecting physical data, and have not adequately considered psychological and emotional aspects of health maintenance. This invention aims to improve physical and mental health by comprehensively evaluating health and emotional states based on data obtained using various sensors in toilets and providing appropriate advice.

[0354] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0355] In this invention, the server includes means for collecting biological waste and surrounding information, equipped with various detectors; means for transmitting the collected data to an information processing device via wireless communication; and means for analyzing the received data using an intelligent system and evaluating the user's health status. This makes it possible to comprehensively understand not only the user's physical health but also their psychological state and to provide appropriate health guidance.

[0356] "Various detectors" is a general term for devices used to measure temperature, humidity, odor, and the chemical composition of biological waste.

[0357] "Biological waste" refers to waste products excreted from the human body and are analyzed to assess health status.

[0358] "Surrounding information" refers to data that indicates the state of the environment, such as temperature, humidity, and odor.

[0359] An "information processing device" is a system for receiving and analyzing collected data.

[0360] "Wireless communication" is a means of communication that transmits and receives data without using cables.

[0361] An "intelligent system" is a technology that uses artificial intelligence to analyze and evaluate data.

[0362] "Health guidelines" refer to advice and recommended actions provided to users based on an assessment of their health status.

[0363] An "emotion analysis engine" is a technology that evaluates a user's emotional state based on voice and facial expression data.

[0364] A "terminal device" refers to an electronic device used directly by the user, and is used for notification and confirmation of information.

[0365] This invention is a system that uses various detectors installed in a toilet to comprehensively understand the user's physical and emotional state and support health management. This system consists of a terminal, a server, and the user's mobile information terminal.

[0366] The device is equipped with multiple detectors to measure temperature, humidity, odor, and the chemical composition of biological waste. It also collects data on the user's emotional state by recording their facial expressions and voice using a camera and microphone. This information is transmitted to a server in real time via wireless communication.

[0367] The server has a database for securely storing data received from the terminal. The server analyzes the data through an intelligent system utilizing artificial intelligence. The analysis includes health status assessment based on excrement and environmental data, and analysis of the user's psychological state using an emotion analysis engine. A health status report is generated based on the analysis results, which includes health guidelines for the user. This report is pushed to the mobile device, ensuring that the user is always provided with the latest information.

[0368] Users can adjust their daily lifestyle habits by utilizing health advice and recommended actions based on their emotional state, as notified via their device. For example, if data indicates that a user's gut balance is poor, the server provides health guidelines, including suggestions for easily digestible meals. Similarly, if the user's level of tension is detected from their facial expression data, suggestions for relaxation techniques are also provided. In this way, users can manage both their physical and mental health.

[0369] An example of a prompt to be input into the generating AI model would be: "Based on the user's gut balance data and emotional state, please suggest recommended lifestyle improvements."

[0370] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0371] Step 1:

[0372] The device measures temperature, humidity, odor, and the chemical composition of biowaste, and records the user's facial expressions and voice. The input data obtained from these sensors and devices is collected as environmental data and user emotion data. Specifically, the temperature sensor measures room temperature, and the humidity sensor measures humidity in the air. The odor sensor detects volatile compounds in the space, and the chemical sensor analyzes the chemical composition of excrement. In addition, the camera captures the user's facial expressions, and the microphone acquires voice data. The collected data is converted into packets and transmitted to the server in real time.

[0373] Step 2:

[0374] The server receives data transmitted from the terminal and stores it in a database. The input data is classified into environmental data and sentiment data and stored securely. The server then prepares to perform data analysis using artificial intelligence with this stored data. Encryption technology is used throughout this process to maintain data integrity and completeness.

[0375] Step 3:

[0376] The server activates its intelligent system and begins analyzing the received data. First, it assesses the user's health status using environmental data and biowaste data. Specifically, an AI algorithm detects abnormalities in chemical composition and environmental changes. Next, it uses an emotion analysis engine to analyze voice data and facial expression data to assess the user's psychological state and stress level. During this process, the AI ​​performs analysis based on conditions specified as prompts (e.g., "Based on the user's gut balance data and emotional state, please suggest recommended lifestyle improvements."). The analysis results are compiled into a report.

[0377] Step 4:

[0378] The server compiles the generated health status report into health guidelines and pushes them to the user's mobile device. The notification includes specific advice related to the user's health and emotional state. For example, if the user indicates high stress levels, relaxation methods such as deep breathing exercises will be suggested. The user will be shown specific methods for adjusting their daily lifestyle based on the health guidelines.

[0379] Step 5:

[0380] Users review health status reports notified on their devices and act on the advice provided. If necessary, they review their daily schedules and habits and manage their lifestyle appropriately. As a result, users can improve their health and well-being.

[0381] (Application Example 2)

[0382] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0383] Traditional health management systems have focused on evaluating users' physical health, but lack analysis of emotional states and the response based on those states. Furthermore, commercial facilities fail to offer personalized services and products tailored to users' health conditions, resulting in insufficient personalization of services. This means users miss out on necessary health guidance and appropriate product information, missing opportunities for service improvement at commercial facilities.

[0384] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0385] In this invention, the server includes means for collecting excrement and surrounding environment data using various sensors, means for transmitting the collected data to a data processing device via wireless communication, means for analyzing the received data using artificial intelligence and evaluating the user's health status, means for providing health advice to the user based on the analysis results, and means for suggesting products or services within a commercial facility based on the analysis results. This makes it possible to provide personalized services and suggest products according to the user's health status.

[0386] "Various sensors" are devices that detect temperature, humidity, odor, chemical composition of excrement, as well as facial expressions and voices.

[0387] Wireless communication is a method of transmitting data without using physical connections such as cables.

[0388] A "data processing device" is a device, such as a computer or server, that analyzes received data and extracts necessary information.

[0389] "Artificial intelligence" is a technology that uses machines to mimic human intelligence and perform data analysis and predictions.

[0390] "Health advice" refers to guidelines for behaviors and lifestyle habits recommended to improve the user's health.

[0391] A "commercial facility" is a store or facility that provides goods and services to consumers.

[0392] "Service proposals" refer to information about appropriate products and services to be offered to users based on the analysis results.

[0393] In this invention, a terminal installed in a toilet collects data to comprehensively evaluate the user's health condition. The terminal is equipped with various sensors to measure temperature, humidity, odor, and the chemical composition of excrement, as well as a camera and microphone to capture the user's facial expressions and voice. This allows for the acquisition of environmental and emotional data obtained while the user is using the toilet.

[0394] Data obtained from sensors is transmitted to a server in real time via wireless communication. The server securely stores the received data in a database and analyzes the user's health and emotional state using AI technology. Data processing is performed using machine learning platforms such as Amazon SageMaker. The analysis results are generated as health advice to assess the user's health status and are notified to the user's smartphone in real time.

[0395] Furthermore, based on the analysis results, personalized product or service suggestions will be provided for use within the commercial facility. This will help users make informed purchasing decisions and utilize services within the facility.

[0396] For example, suppose a user uses the restroom and an imbalance in their gut flora is detected, along with increased stress levels observed in their facial expression. In this case, the server sends a push notification offering suggestions for easily digestible meals and a discount coupon for relaxation products at the store. This allows the user to receive both health and stress relief.

[0397] An example of a prompt to input into the generating AI model would be, "Based on the user's health data, please suggest products and services appropriate to their health condition." This prompt allows the AI ​​to derive the most suitable suggestions for each user.

[0398] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0399] Step 1:

[0400] The terminal acquires various sensor data from users using the toilet, including temperature, humidity, odor, and the chemical composition of excrement. This data is then packetized and prepared along with facial expression data and voice data captured by the camera and microphone. The input consists of sensor data and emotion data, while the output is an integrated data packet.

[0401] Step 2:

[0402] The terminal transmits the generated data packets to the server in real time via Bluetooth or Wi-Fi. The input is the integrated data packets, and the output is the result of data transmission via wireless communication.

[0403] Step 3:

[0404] The server stores the received data in a database and analyzes the acquired data on Amazon SageMaker. It uses an AI algorithm to evaluate health and emotional states and generates analysis results. The input is the transmitted data packets, and the output is the analyzed health and emotional state evaluation results.

[0405] Step 4:

[0406] The server uses an AI model generated based on the analysis results to produce healthcare advice tailored to the user's health condition, as well as recommendations for products and services within the commercial facility. The AI ​​model is invoked using prompts to generate personalized advice text. The input is the analysis results, and the output is user-specific advice and suggestions.

[0407] Step 5:

[0408] The server sends the generated advice and suggestions to the user's smartphone via push notification. The input is the generated advice text and suggestions, and the output is the notification result sent to the user's device.

[0409] Step 6:

[0410] Users check the advice and suggestions they receive via push notifications on their smartphones and use the suggested products or services as needed. The input is the information received via push notifications, and the output is the user's actions.

[0411] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0412] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0413] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0414] [Third Embodiment]

[0415] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0416] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0417] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0418] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0419] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0420] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0421] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0422] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0423] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0424] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0425] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0426] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0427] This invention describes a system for collecting and analyzing sensor data using a toilet, in order to improve health management in daily life. The system consists of various sensors installed in the toilet, a server for processing the data, and a smartphone application for the user.

[0428] The terminal (sensor device inside the toilet) monitors the color, shape, and chemical composition of excrement obtained during toilet use, as well as the ambient temperature, humidity, and odor, in real time. This sensor information is integrated within the terminal at regular intervals and transmitted wirelessly to a server in the cloud as an exclusively selected dataset.

[0429] The server operates in a cloud computing environment, efficiently storing and preprocessing received data. It then uses artificial intelligence algorithms to monitor the user's health status and generate analysis results. During the analysis process, machine learning models identify patterns that indicate health indicators and detect anomalies and health risks.

[0430] The analysis results are sent by the server to an application installed on the user's smartphone. This application provides reports using an intuitive interface, easily conveying specific health advice to the user. For example, if vitamin deficiencies or insufficient fluid intake are detected, the necessary nutrients and corrective measures are specifically presented to the user.

[0431] Furthermore, the system also has a function that automatically supplies fragrance when it detects unpleasant odors, keeping the toilet environment comfortable. In addition, the health data obtained is securely encrypted and, if necessary and with the user's consent, provided to medical institutions for professional health management and diagnosis.

[0432] As a concrete example, the system activates when a user visits the toilet in the morning. If it detects that the previous night's meal contained excessive salt, the server sends a notification to the user recommending salt restriction for maintaining heart health. In this way, continuous health management is achieved.

[0433] The following describes the processing flow.

[0434] Step 1:

[0435] The terminal collects data in real time from various sensors installed in the toilet, including temperature, humidity, odor, and the color, shape, and chemical composition of excrement.

[0436] Step 2:

[0437] The device packets the collected data at regular intervals and prepares to send it to a server in the cloud via a Wi-Fi or 5G network.

[0438] Step 3:

[0439] The server receives data sent from the terminal and stores it in a secure database. The received data undergoes preprocessing (data cleansing and format conversion).

[0440] Step 4:

[0441] The server inputs the pre-processed data into an AI algorithm and begins analyzing the data. Here, a machine learning model is used to perform health indicator analysis and anomaly detection, and to assess the user's health status.

[0442] Step 5:

[0443] The server generates a user health status report based on the results obtained from the analysis. The report includes information on diet, hydration, and suggestions and advice on necessary actions.

[0444] Step 6:

[0445] The server pushes the generated health report to the user's smartphone application, allowing the user to immediately review its contents.

[0446] Step 7:

[0447] Users access health reports through a smartphone app and take necessary lifestyle improvements based on the advice provided.

[0448] Step 8:

[0449] When the device detects an unpleasant odor using its odor sensor, it automatically sprays fragrance to improve the toilet environment.

[0450] Step 9:

[0451] The server, with the user's consent, encrypts the analysis results and provides the data to medical institutions as needed. This provision is for professional diagnosis purposes.

[0452] (Example 1)

[0453] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0454] Traditional health management methods based on excrement and environmental data suffer from fragmented data collection and analysis, making real-time health assessment and personalized health advice difficult. Furthermore, there are challenges such as the lack of automated solutions for environmental odor control and the insufficient means of securely sharing analysis results with healthcare institutions.

[0455] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0456] In this invention, the server includes means for collecting environmental information, including the physical and chemical attributes of excrement; means for transmitting integrated data to a data processing device using wireless communication technology; and means for analyzing the data using a generative AI model to identify health indicators and detect abnormal values ​​and health risks. This enables detailed real-time assessment of health status, allowing for the provision of personalized health advice, improved environmental comfort, and support for medical management through secure data sharing.

[0457] "Excrement" refers to solid or liquid waste products expelled from the body of an organism, and it is important data that reflects the health status of the organism.

[0458] "Environmental information" refers to physical conditions inside the toilet, such as temperature, humidity, and odor, which are factors that affect the user's health and comfort.

[0459] A "sensor group" is a system of devices that arranges multiple different types of sensors together, each measuring a different parameter.

[0460] Wireless communication technology is a technology that uses radio waves to send and receive information between devices, and has the advantage of being able to transfer data without using cables.

[0461] A "data processing device" is a computer system that stores, preprocesses, and analyzes received sensor data, and is typically located on the cloud.

[0462] A "generative AI model" is an artificial intelligence system that learns patterns based on past data and performs inferences on new data.

[0463] "Health indicators" are evaluation criteria that show the user's health status, and specifically include nutritional status and disease risk.

[0464] An "abnormal value" refers to a health indicator that falls outside the normal range and may indicate a health risk.

[0465] "Health risk" refers to an indicator of a condition that may potentially lead to illness or health problems in the future.

[0466] A "user device" is an electronic device that receives analysis results and provides information to the user, and includes smartphones and other similar devices.

[0467] "Fragrance supply" is the process of releasing fragrance to improve the odor of the toilet environment.

[0468] A "medical institution" is an organization that provides specialized medical services, and includes hospitals and clinics.

[0469] "Encrypted communication" is a technology that uses algorithms to transform data in order to protect its contents from third parties during transmission.

[0470] This invention provides a toilet-based sensor data collection and analysis system for improving health management. The following describes how this system is configured and operates.

[0471] The terminal (sensor device inside the toilet) not only acquires data such as the color, shape, and chemical composition of excrement in real time, but also monitors information such as the temperature, humidity, and odor of the toilet environment. This data is collected by multiple sensors and integrated at specific time intervals.

[0472] Using wireless communication technology (e.g., Wi-Fi or Bluetooth), the terminal transmits the collected data to the server. The server is located in a cloud computing environment and includes a database system for storing the received data and preprocessing modules for efficiently processing the data.

[0473] Next, the server analyzes the data using a generative AI model. The machine learning algorithm learns patterns based on past health data and known health indicators, and performs an efficient process of identifying health indicators in new data and identifying outliers and health risks.

[0474] Once the analysis is complete, the server notifies the user's device (smartphone) of the results. The notification provides health advice and warnings through an intuitive interface. For example, if the user is prone to nutritional deficiencies, the application will provide health advice such as, "You are deficient in vitamin D. Try getting some sunlight or consuming foods containing vitamin D."

[0475] Furthermore, the device has a function that automatically dispenses fragrance when it detects unpleasant odors using sensors, keeping the toilet environment comfortable. In addition, the server uses encryption technology to securely protect data and can provide data to medical institutions with the user's consent.

[0476] An example of a prompt message could be a request like, "Tell me my health predictions based on my recent eating habits," which would allow the user to receive personalized feedback for ongoing health management.

[0477] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0478] Step 1:

[0479] The device uses sensors to monitor the color, shape, and chemical composition of waste, as well as the temperature, humidity, and odor of the toilet during use. The sensor system is complex, using optical sensors to capture color and shape, and gas sensors to detect odor. The input is raw data measured by various sensors, which is then digitized and converted into a usable format. The output is integrated environmental data.

[0480] Step 2:

[0481] The terminal aggregates integrated environmental data at regular time intervals (e.g., every 5 minutes) and sends it to the server in the form of data packets via wireless communication technology. The input is the integrated environmental data, and the output is the data packets sent to the server. This operation is achieved by triggering a wireless communication module.

[0482] Step 3:

[0483] The server stores the received data in a database in the cloud. A database management system supports this process, ensuring that the data is stored systematically. The input is data packets sent from the terminal, and the output is structured data stored in the database.

[0484] Step 4:

[0485] The server preprocesses the data stored in the database. It removes outliers and appropriately imputes missing values ​​to prepare the data for analysis. The input is structured data in the database, and the output is clean, preprocessed data.

[0486] Step 5:

[0487] The server supplies pre-processed data to a generating AI model for data analysis. Machine learning algorithms identify health indicators and pinpoint outliers and health risks. The input is pre-processed, clean data, and the output is the analyzed results, namely health status and risk assessments.

[0488] Step 6:

[0489] The server sends the analysis results to the user's smartphone application. The results are visualized and presented to the user through an intuitive interface. The input is the analyzed results, and the output is visual feedback on the user's smartphone screen. The application displays specific health advice, such as "You are deficient in Vitamin D."

[0490] Step 7:

[0491] The device automatically activates the fragrance dispenser and releases a scent when it detects an unpleasant odor using its sensor. The input is the odor sensor detection data, and the output is the improved toilet environment. This operation is performed automatically based on a pre-set threshold.

[0492] Step 8:

[0493] The server transmits encrypted data to healthcare institutions based on user consent. This process is performed using a secure communication protocol. The input is the analysis results and user consent, and the output is health data that reaches the healthcare institution. This procedure allows healthcare institutions to make expert diagnoses based on detailed health information.

[0494] (Application Example 1)

[0495] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0496] Conventional health management systems have struggled to monitor excrement and environmental data in detail in real time, making it difficult to immediately detect abnormalities and prompt appropriate responses. Furthermore, they lacked a visual means of confirming changes in users' health status or suspicious environmental changes, resulting in a lack of immediacy and convenience.

[0497] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0498] In this invention, the server includes a device equipped with various sensors to monitor excrement and environmental data, means for transmitting the collected data to a processing unit via wireless communication, and means for analyzing the received data using a machine learning algorithm to determine the user's health status. This allows the user to understand changes in their health status in real time, immediately detect abnormal situations, and take appropriate measures.

[0499] "Various sensors" is a general term for a variety of sensing devices installed to monitor excrement and environmental data.

[0500] "Wireless communication" is a method of transmitting data using radio waves without requiring a physical connection.

[0501] A "processing unit" is a device or system equipped with computing resources for analyzing and determining received data.

[0502] A "machine learning algorithm" is a type of computational method that learns patterns from data and outputs analysis results.

[0503] "Health guidance" refers to the act of providing users with specific advice on improving or maintaining their health based on the analysis results.

[0504] "Anomaly detection" is a means of identifying data or situations that deviate from normal conditions and issuing warnings.

[0505] The system implementing this invention consists of a terminal installed in the toilet, a server in the cloud, and a smart device owned by the user. The terminal is equipped with various sensors that detect excrement and environmental data (temperature, humidity, odor, etc.), and this data is monitored in real time. The data acquired by the sensors is transmitted to a processing unit on the cloud server via wireless communication methods such as Wi-Fi or Bluetooth.

[0506] The server analyzes the received data using machine learning algorithms based on Python and TensorFlow. This allows for a comprehensive assessment of the user's health status, and an immediate alarm is issued if an anomaly is detected. The analysis results and alarm details are sent via secure communication to the user's smartphone or smart glasses.

[0507] In this case, the application is developed using React Native or Flutter, providing a visually intuitive interface for the user. Health guidance and abnormal alerts are presented through an intuitive dashboard, and corrective actions and contact information for specialists are also provided as needed.

[0508] For example, if a user uses a toilet while wearing smart glasses and an unusual odor is detected, the system analyzes the situation in the cloud and displays a notification through the glasses such as, "Please ventilate immediately." Furthermore, by using a generative AI model, it is possible to perform a deeper analysis by inputting prompts such as, "Please comprehensively assess the user's health condition after using the toilet."

[0509] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0510] Step 1:

[0511] The terminal uses various sensors installed in the toilet to detect the color, shape, and chemical composition of excrement, as well as the ambient temperature, humidity, and odor in real time. The input is physical environmental data, and the output is this data temporarily stored as digitized information within the terminal. Specifically, the sensors collect data at regular intervals, the terminal's processor standardizes the format, and then prepares the data for subsequent processing.

[0512] Step 2:

[0513] The device uses wireless communication to transmit collected data to a server in the cloud. The input is digitized sensor data stored within the device, and the output is data packets transmitted over the network. Specifically, the device periodically adds data to a queue or, when certain conditions are met, sends the data packets to the server using a reliable communication protocol.

[0514] Step 3:

[0515] The server analyzes received sensor data using a machine learning algorithm based on Python and TensorFlow to evaluate the user's health status. The input is sensor data sent from the terminal, and the output is the health status evaluation result and whether or not there are abnormalities. Specifically, the server preprocesses the data, then inputs it into a pre-trained machine learning model to estimate the health status, and performs an evaluation if an abnormal pattern is detected.

[0516] Step 4:

[0517] The server notifies the user's smart device of the analysis results. The input is health assessment data generated based on the analysis, and the output is a notification message. Specifically, the server generates the notification content and pushes the information to the user's specified device using services such as Azure Notification Hubs.

[0518] Step 5:

[0519] Users check notifications displayed on their smartphones or smart glasses and take necessary actions according to the health guidance and warnings provided. Inputs include notification information from the server, and outputs include user actions or feedback to the system. Specifically, users act according to the instructions presented by the device and record their reactions within the application as needed.

[0520] Step 6:

[0521] The user inputs prompts to a generated AI model to request further health assessments and advice. The input consists of user prompts, and the output is detailed analysis results or suggestions from the AI ​​model. Specifically, the user provides natural language input through the application, and the AI ​​model performs additional analysis based on this input and returns the results.

[0522] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0523] This invention is a system that combines multiple sensors installed in a toilet with an emotion engine to gain a more comprehensive understanding of the user's health condition and support appropriate health management. This system consists of a terminal, a server, and a user's smartphone application.

[0524] The device is equipped with various sensors that measure temperature, humidity, odor, and the chemical composition of waste, as well as a camera and microphone to capture the user's facial expressions and voice. This allows the device to collect environmental data and user emotional data while the user is using the toilet. This data is transmitted to a server in real time via wireless communication.

[0525] The server securely stores received environmental and emotional data in a database and performs analysis using AI technology. The analysis includes health status assessment based on excrement and environmental data, and recognition of the user's emotional state using an emotion engine. The emotion engine uses voice analysis and facial expression analysis technologies to evaluate the user's emotions, such as their psychological state and stress level.

[0526] The analysis results are generated by the server as a health status report, which includes advice based on emotional state and health indicators. This report is pushed to the user's smartphone app, allowing them to immediately review its contents. Furthermore, the user's emotional data is recorded chronologically, enabling analysis of long-term emotional patterns.

[0527] Users can use the provided health advice to review their daily lifestyle habits and decide to seek medical attention if necessary. If they are experiencing emotional instability, they will also be offered suggestions for relaxation and stress reduction techniques.

[0528] As a concrete example, when a user used the toilet, the device detected data suggesting an imbalance in gut flora and also sensed tension from the user's facial expression. Based on this information, the server sent a notification to the user suggesting easily digestible meals and introducing deep breathing techniques for relaxation. In this way, users can receive care not only for their physical health but also for their mental health.

[0529] The following describes the processing flow.

[0530] Step 1:

[0531] The device uses sensors installed in the toilet to collect temperature, humidity, odor, and the color and chemical composition of waste in real time. It also uses a camera and microphone to simultaneously capture the user's facial expressions and voice data.

[0532] Step 2:

[0533] The device packages the collected environmental data and user sentiment data and sends it to a server in the cloud using a Wi-Fi or 5G network.

[0534] Step 3:

[0535] The server receives data sent from the terminal and securely stores it in the database. During storage, it prepares and preprocesses the data and converts it into a format that can be used for AI analysis.

[0536] Step 4:

[0537] The server uses AI algorithms to analyze waste and environmental data to assess health status. Simultaneously, an emotion engine analyzes facial expressions and voice data to recognize the user's emotional state. This analysis determines the user's stress level and subjective well-being.

[0538] Step 5:

[0539] Based on the health assessment and emotion recognition results, the server generates a detailed report and health advice. This advice includes suggestions regarding diet and hydration, as well as guidance on maintaining mental well-being.

[0540] Step 6:

[0541] The server sends the generated results to the user's smartphone app via push notification, allowing the user to check their health report at any time.

[0542] Step 7:

[0543] Users check notifications through the app, and based on the results, decide and take necessary health improvement actions. If needed, they can utilize relaxation methods and psychological support that address their emotional state.

[0544] Step 8:

[0545] The server records and continuously analyzes users' long-term health data and emotional patterns, evolving the system to enable more personalized advice.

[0546] (Example 2)

[0547] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0548] In modern society, it is important to comprehensively understand and appropriately manage an individual's health status. However, conventional health management methods have been limited to collecting physical data, and have not adequately considered psychological and emotional aspects of health maintenance. This invention aims to improve physical and mental health by comprehensively evaluating health and emotional states based on data obtained using various sensors in toilets and providing appropriate advice.

[0549] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0550] In this invention, the server includes means for collecting biological waste and surrounding information, equipped with various detectors; means for transmitting the collected data to an information processing device via wireless communication; and means for analyzing the received data using an intelligent system and evaluating the user's health status. This makes it possible to comprehensively understand not only the user's physical health but also their psychological state and to provide appropriate health guidance.

[0551] "Various detectors" is a general term for devices used to measure temperature, humidity, odor, and the chemical composition of biological waste.

[0552] "Biological waste" refers to waste products excreted from the human body and are analyzed to assess health status.

[0553] "Surrounding information" refers to data that indicates the state of the environment, such as temperature, humidity, and odor.

[0554] An "information processing device" is a system for receiving and analyzing collected data.

[0555] "Wireless communication" is a means of communication that transmits and receives data without using cables.

[0556] An "intelligent system" is a technology that uses artificial intelligence to analyze and evaluate data.

[0557] "Health guidelines" refer to advice and recommended actions provided to users based on an assessment of their health status.

[0558] An "emotion analysis engine" is a technology that evaluates a user's emotional state based on voice and facial expression data.

[0559] A "terminal device" refers to an electronic device used directly by the user, and is used for notification and confirmation of information.

[0560] This invention is a system that uses various detectors installed in a toilet to comprehensively understand the user's physical and emotional state and support health management. This system consists of a terminal, a server, and the user's mobile information terminal.

[0561] The device is equipped with multiple detectors to measure temperature, humidity, odor, and the chemical composition of biological waste. It also collects data on the user's emotional state by recording their facial expressions and voice using a camera and microphone. This information is transmitted to a server in real time via wireless communication.

[0562] The server has a database for securely storing data received from the terminal. The server analyzes the data through an intelligent system utilizing artificial intelligence. The analysis includes health status assessment based on excrement and environmental data, and analysis of the user's psychological state using an emotion analysis engine. A health status report is generated based on the analysis results, which includes health guidelines for the user. This report is pushed to the mobile device, ensuring that the user is always provided with the latest information.

[0563] Users can adjust their daily lifestyle habits by utilizing health advice and recommended actions based on their emotional state, as notified via their device. For example, if data indicates that a user's gut balance is poor, the server provides health guidelines, including suggestions for easily digestible meals. Similarly, if the user's level of tension is detected from their facial expression data, suggestions for relaxation techniques are also provided. In this way, users can manage both their physical and mental health.

[0564] An example of a prompt to be input into the generating AI model would be: "Based on the user's gut balance data and emotional state, please suggest recommended lifestyle improvements."

[0565] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0566] Step 1:

[0567] The device measures temperature, humidity, odor, and the chemical composition of biowaste, and records the user's facial expressions and voice. The input data obtained from these sensors and devices is collected as environmental data and user emotion data. Specifically, the temperature sensor measures room temperature, and the humidity sensor measures humidity in the air. The odor sensor detects volatile compounds in the space, and the chemical sensor analyzes the chemical composition of excrement. In addition, the camera captures the user's facial expressions, and the microphone acquires voice data. The collected data is converted into packets and transmitted to the server in real time.

[0568] Step 2:

[0569] The server receives data transmitted from the terminal and stores it in a database. The input data is classified into environmental data and sentiment data and stored securely. The server then prepares to perform data analysis using artificial intelligence with this stored data. Encryption technology is used throughout this process to maintain data integrity and completeness.

[0570] Step 3:

[0571] The server activates its intelligent system and begins analyzing the received data. First, it assesses the user's health status using environmental data and biowaste data. Specifically, an AI algorithm detects abnormalities in chemical composition and environmental changes. Next, it uses an emotion analysis engine to analyze voice data and facial expression data to assess the user's psychological state and stress level. During this process, the AI ​​performs analysis based on conditions specified as prompts (e.g., "Based on the user's gut balance data and emotional state, please suggest recommended lifestyle improvements."). The analysis results are compiled into a report.

[0572] Step 4:

[0573] The server compiles the generated health status report into health guidelines and pushes them to the user's mobile device. The notification includes specific advice related to the user's health and emotional state. For example, if the user indicates high stress levels, relaxation methods such as deep breathing exercises will be suggested. The user will be shown specific methods for adjusting their daily lifestyle based on the health guidelines.

[0574] Step 5:

[0575] Users review health status reports notified on their devices and act on the advice provided. If necessary, they review their daily schedules and habits and manage their lifestyle appropriately. As a result, users can improve their health and well-being.

[0576] (Application Example 2)

[0577] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0578] Traditional health management systems have focused on evaluating users' physical health, but lack analysis of emotional states and the response based on those states. Furthermore, commercial facilities fail to offer personalized services and products tailored to users' health conditions, resulting in insufficient personalization of services. This means users miss out on necessary health guidance and appropriate product information, missing opportunities for service improvement at commercial facilities.

[0579] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0580] In this invention, the server includes means for collecting excrement and surrounding environment data using various sensors, means for transmitting the collected data to a data processing device via wireless communication, means for analyzing the received data using artificial intelligence and evaluating the user's health status, means for providing health advice to the user based on the analysis results, and means for suggesting products or services within a commercial facility based on the analysis results. This makes it possible to provide personalized services and suggest products according to the user's health status.

[0581] "Various sensors" are devices that detect temperature, humidity, odor, chemical composition of excrement, as well as facial expressions and voices.

[0582] Wireless communication is a method of transmitting data without using physical connections such as cables.

[0583] A "data processing device" is a device, such as a computer or server, that analyzes received data and extracts necessary information.

[0584] "Artificial intelligence" is a technology that uses machines to mimic human intelligence and perform data analysis and predictions.

[0585] "Health advice" refers to guidelines for behaviors and lifestyle habits recommended to improve the user's health.

[0586] A "commercial facility" is a store or facility that provides goods and services to consumers.

[0587] "Service proposals" refer to information about appropriate products and services to be offered to users based on the analysis results.

[0588] In this invention, a terminal installed in a toilet collects data to comprehensively evaluate the user's health condition. The terminal is equipped with various sensors to measure temperature, humidity, odor, and the chemical composition of excrement, as well as a camera and microphone to capture the user's facial expressions and voice. This allows for the acquisition of environmental and emotional data obtained while the user is using the toilet.

[0589] Data obtained from sensors is transmitted to a server in real time via wireless communication. The server securely stores the received data in a database and analyzes the user's health and emotional state using AI technology. Data processing is performed using machine learning platforms such as Amazon SageMaker. The analysis results are generated as health advice to assess the user's health status and are notified to the user's smartphone in real time.

[0590] Furthermore, based on the analysis results, personalized product or service suggestions will be provided for use within the commercial facility. This will help users make informed purchasing decisions and utilize services within the facility.

[0591] For example, suppose a user uses the restroom and an imbalance in their gut flora is detected, along with increased stress levels observed in their facial expression. In this case, the server sends a push notification offering suggestions for easily digestible meals and a discount coupon for relaxation products at the store. This allows the user to receive both health and stress relief.

[0592] An example of a prompt to input into the generating AI model would be, "Based on the user's health data, please suggest products and services appropriate to their health condition." This prompt allows the AI ​​to derive the most suitable suggestions for each user.

[0593] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0594] Step 1:

[0595] The terminal acquires various sensor data from users using the toilet, including temperature, humidity, odor, and the chemical composition of excrement. This data is then packetized and prepared along with facial expression data and voice data captured by the camera and microphone. The input consists of sensor data and emotion data, while the output is an integrated data packet.

[0596] Step 2:

[0597] The terminal transmits the generated data packets to the server in real time via Bluetooth or Wi-Fi. The input is the integrated data packets, and the output is the result of data transmission via wireless communication.

[0598] Step 3:

[0599] The server stores the received data in a database and analyzes the acquired data on Amazon SageMaker. It uses an AI algorithm to evaluate health and emotional states and generates analysis results. The input is the transmitted data packets, and the output is the analyzed health and emotional state evaluation results.

[0600] Step 4:

[0601] The server uses an AI model generated based on the analysis results to produce healthcare advice tailored to the user's health condition, as well as recommendations for products and services within the commercial facility. The AI ​​model is invoked using prompts to generate personalized advice text. The input is the analysis results, and the output is user-specific advice and suggestions.

[0602] Step 5:

[0603] The server sends the generated advice and suggestions to the user's smartphone via push notification. The input is the generated advice text and suggestions, and the output is the notification result sent to the user's device.

[0604] Step 6:

[0605] Users check the advice and suggestions they receive via push notifications on their smartphones and use the suggested products or services as needed. The input is the information received via push notifications, and the output is the user's actions.

[0606] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0607] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0608] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0609] [Fourth Embodiment]

[0610] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0611] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0612] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0613] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0614] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0615] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0616] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0617] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0618] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0619] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0620] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0621] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0622] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0623] This invention describes a system for collecting and analyzing sensor data using a toilet, in order to improve health management in daily life. The system consists of various sensors installed in the toilet, a server for processing the data, and a smartphone application for the user.

[0624] The terminal (sensor device inside the toilet) monitors the color, shape, and chemical composition of excrement obtained during toilet use, as well as the ambient temperature, humidity, and odor, in real time. This sensor information is integrated within the terminal at regular intervals and transmitted wirelessly to a server in the cloud as an exclusively selected dataset.

[0625] The server operates in a cloud computing environment, efficiently storing and preprocessing received data. It then uses artificial intelligence algorithms to monitor the user's health status and generate analysis results. During the analysis process, machine learning models identify patterns that indicate health indicators and detect anomalies and health risks.

[0626] The analysis results are sent by the server to an application installed on the user's smartphone. This application provides reports using an intuitive interface, easily conveying specific health advice to the user. For example, if vitamin deficiencies or insufficient fluid intake are detected, the necessary nutrients and corrective measures are specifically presented to the user.

[0627] Furthermore, the system also has a function that automatically supplies fragrance when it detects unpleasant odors, keeping the toilet environment comfortable. In addition, the health data obtained is securely encrypted and, if necessary and with the user's consent, provided to medical institutions for professional health management and diagnosis.

[0628] As a concrete example, the system activates when a user visits the toilet in the morning. If it detects that the previous night's meal contained excessive salt, the server sends a notification to the user recommending salt restriction for maintaining heart health. In this way, continuous health management is achieved.

[0629] The following describes the processing flow.

[0630] Step 1:

[0631] The terminal collects data in real time from various sensors installed in the toilet, including temperature, humidity, odor, and the color, shape, and chemical composition of excrement.

[0632] Step 2:

[0633] The device packets the collected data at regular intervals and prepares to send it to a server in the cloud via a Wi-Fi or 5G network.

[0634] Step 3:

[0635] The server receives data sent from the terminal and stores it in a secure database. The received data undergoes preprocessing (data cleansing and format conversion).

[0636] Step 4:

[0637] The server inputs the pre-processed data into an AI algorithm and begins analyzing the data. Here, a machine learning model is used to perform health indicator analysis and anomaly detection, and to assess the user's health status.

[0638] Step 5:

[0639] The server generates a user health status report based on the results obtained from the analysis. The report includes information on diet, hydration, and suggestions and advice on necessary actions.

[0640] Step 6:

[0641] The server pushes the generated health report to the user's smartphone application, allowing the user to immediately review its contents.

[0642] Step 7:

[0643] Users access health reports through a smartphone app and take necessary lifestyle improvements based on the advice provided.

[0644] Step 8:

[0645] When the device detects an unpleasant odor using its odor sensor, it automatically sprays fragrance to improve the toilet environment.

[0646] Step 9:

[0647] The server, with the user's consent, encrypts the analysis results and provides the data to medical institutions as needed. This provision is for professional diagnosis purposes.

[0648] (Example 1)

[0649] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0650] Traditional health management methods based on excrement and environmental data suffer from fragmented data collection and analysis, making real-time health assessment and personalized health advice difficult. Furthermore, there are challenges such as the lack of automated solutions for environmental odor control and the insufficient means of securely sharing analysis results with healthcare institutions.

[0651] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0652] In this invention, the server includes means for collecting environmental information, including the physical and chemical attributes of excrement; means for transmitting integrated data to a data processing device using wireless communication technology; and means for analyzing the data using a generative AI model to identify health indicators and detect abnormal values ​​and health risks. This enables detailed real-time assessment of health status, allowing for the provision of personalized health advice, improved environmental comfort, and support for medical management through secure data sharing.

[0653] "Excrement" refers to solid or liquid waste products expelled from the body of an organism, and it is important data that reflects the health status of the organism.

[0654] "Environmental information" refers to physical conditions inside the toilet, such as temperature, humidity, and odor, which are factors that affect the user's health and comfort.

[0655] A "sensor group" is a system of devices that arranges multiple different types of sensors together, each measuring a different parameter.

[0656] Wireless communication technology is a technology that uses radio waves to send and receive information between devices, and has the advantage of being able to transfer data without using cables.

[0657] A "data processing device" is a computer system that stores, preprocesses, and analyzes received sensor data, and is typically located on the cloud.

[0658] A "generative AI model" is an artificial intelligence system that learns patterns based on past data and performs inferences on new data.

[0659] "Health indicators" are evaluation criteria that show the user's health status, and specifically include nutritional status and disease risk.

[0660] An "abnormal value" refers to a health indicator that falls outside the normal range and may indicate a health risk.

[0661] "Health risk" refers to an indicator of a condition that may potentially lead to illness or health problems in the future.

[0662] A "user device" is an electronic device that receives analysis results and provides information to the user, and includes smartphones and other similar devices.

[0663] "Fragrance supply" is the process of releasing fragrance to improve the odor of the toilet environment.

[0664] A "medical institution" is an organization that provides specialized medical services, and includes hospitals and clinics.

[0665] "Encrypted communication" is a technology that uses algorithms to transform data in order to protect its contents from third parties during transmission.

[0666] This invention provides a toilet-based sensor data collection and analysis system for improving health management. The following describes how this system is configured and operates.

[0667] The terminal (sensor device inside the toilet) not only acquires data such as the color, shape, and chemical composition of excrement in real time, but also monitors information such as the temperature, humidity, and odor of the toilet environment. This data is collected by multiple sensors and integrated at specific time intervals.

[0668] Using wireless communication technology (e.g., Wi-Fi or Bluetooth), the terminal transmits the collected data to the server. The server is located in a cloud computing environment and includes a database system for storing the received data and preprocessing modules for efficiently processing the data.

[0669] Next, the server analyzes the data using a generative AI model. The machine learning algorithm learns patterns based on past health data and known health indicators, and performs an efficient process of identifying health indicators in new data and identifying outliers and health risks.

[0670] Once the analysis is complete, the server notifies the user's device (smartphone) of the results. The notification provides health advice and warnings through an intuitive interface. For example, if the user is prone to nutritional deficiencies, the application will provide health advice such as, "You are deficient in vitamin D. Try getting some sunlight or consuming foods containing vitamin D."

[0671] Furthermore, the device has a function that automatically dispenses fragrance when it detects unpleasant odors using sensors, keeping the toilet environment comfortable. In addition, the server uses encryption technology to securely protect data and can provide data to medical institutions with the user's consent.

[0672] An example of a prompt message could be a request like, "Tell me my health predictions based on my recent eating habits," which would allow the user to receive personalized feedback for ongoing health management.

[0673] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0674] Step 1:

[0675] The device uses sensors to monitor the color, shape, and chemical composition of waste, as well as the temperature, humidity, and odor of the toilet during use. The sensor system is complex, using optical sensors to capture color and shape, and gas sensors to detect odor. The input is raw data measured by various sensors, which is then digitized and converted into a usable format. The output is integrated environmental data.

[0676] Step 2:

[0677] The terminal aggregates integrated environmental data at regular time intervals (e.g., every 5 minutes) and sends it to the server in the form of data packets via wireless communication technology. The input is the integrated environmental data, and the output is the data packets sent to the server. This operation is achieved by triggering a wireless communication module.

[0678] Step 3:

[0679] The server stores the received data in a database in the cloud. A database management system supports this process, ensuring that the data is stored systematically. The input is data packets sent from the terminal, and the output is structured data stored in the database.

[0680] Step 4:

[0681] The server preprocesses the data stored in the database. It removes outliers and appropriately imputes missing values ​​to prepare the data for analysis. The input is structured data in the database, and the output is clean, preprocessed data.

[0682] Step 5:

[0683] The server supplies pre-processed data to a generating AI model for data analysis. Machine learning algorithms identify health indicators and pinpoint outliers and health risks. The input is pre-processed, clean data, and the output is the analyzed results, namely health status and risk assessments.

[0684] Step 6:

[0685] The server sends the analysis results to the user's smartphone application. The results are visualized and presented to the user through an intuitive interface. The input is the analyzed results, and the output is visual feedback on the user's smartphone screen. The application displays specific health advice, such as "You are deficient in Vitamin D."

[0686] Step 7:

[0687] The device automatically activates the fragrance dispenser and releases a scent when it detects an unpleasant odor using its sensor. The input is the odor sensor detection data, and the output is the improved toilet environment. This operation is performed automatically based on a pre-set threshold.

[0688] Step 8:

[0689] The server transmits encrypted data to healthcare institutions based on user consent. This process is performed using a secure communication protocol. The input is the analysis results and user consent, and the output is health data that reaches the healthcare institution. This procedure allows healthcare institutions to make expert diagnoses based on detailed health information.

[0690] (Application Example 1)

[0691] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0692] Conventional health management systems have struggled to monitor excrement and environmental data in detail in real time, making it difficult to immediately detect abnormalities and prompt appropriate responses. Furthermore, they lacked a visual means of confirming changes in users' health status or suspicious environmental changes, resulting in a lack of immediacy and convenience.

[0693] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0694] In this invention, the server includes a device equipped with various sensors to monitor excrement and environmental data, means for transmitting the collected data to a processing unit via wireless communication, and means for analyzing the received data using a machine learning algorithm to determine the user's health status. This allows the user to understand changes in their health status in real time, immediately detect abnormal situations, and take appropriate measures.

[0695] "Various sensors" is a general term for a variety of sensing devices installed to monitor excrement and environmental data.

[0696] "Wireless communication" is a method of transmitting data using radio waves without requiring a physical connection.

[0697] A "processing unit" is a device or system equipped with computing resources for analyzing and determining received data.

[0698] A "machine learning algorithm" is a type of computational method that learns patterns from data and outputs analysis results.

[0699] "Health guidance" refers to the act of providing users with specific advice on improving or maintaining their health based on the analysis results.

[0700] "Anomaly detection" is a means of identifying data or situations that deviate from normal conditions and issuing warnings.

[0701] The system implementing this invention consists of a terminal installed in the toilet, a server in the cloud, and a smart device owned by the user. The terminal is equipped with various sensors that detect excrement and environmental data (temperature, humidity, odor, etc.), and this data is monitored in real time. The data acquired by the sensors is transmitted to a processing unit on the cloud server via wireless communication methods such as Wi-Fi or Bluetooth.

[0702] The server analyzes the received data using machine learning algorithms based on Python and TensorFlow. This allows for a comprehensive assessment of the user's health status, and an immediate alarm is issued if an anomaly is detected. The analysis results and alarm details are sent via secure communication to the user's smartphone or smart glasses.

[0703] In this case, the application is developed using React Native or Flutter, providing a visually intuitive interface for the user. Health guidance and abnormal alerts are presented through an intuitive dashboard, and corrective actions and contact information for specialists are also provided as needed.

[0704] For example, if a user uses a toilet while wearing smart glasses and an unusual odor is detected, the system analyzes the situation in the cloud and displays a notification through the glasses such as, "Please ventilate immediately." Furthermore, by using a generative AI model, it is possible to perform a deeper analysis by inputting prompts such as, "Please comprehensively assess the user's health condition after using the toilet."

[0705] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0706] Step 1:

[0707] The terminal uses various sensors installed in the toilet to detect the color, shape, and chemical composition of excrement, as well as the ambient temperature, humidity, and odor in real time. The input is physical environmental data, and the output is this data temporarily stored as digitized information within the terminal. Specifically, the sensors collect data at regular intervals, the terminal's processor standardizes the format, and then prepares the data for subsequent processing.

[0708] Step 2:

[0709] The device uses wireless communication to transmit collected data to a server in the cloud. The input is digitized sensor data stored within the device, and the output is data packets transmitted over the network. Specifically, the device periodically adds data to a queue or, when certain conditions are met, sends the data packets to the server using a reliable communication protocol.

[0710] Step 3:

[0711] The server analyzes received sensor data using a machine learning algorithm based on Python and TensorFlow to evaluate the user's health status. The input is sensor data sent from the terminal, and the output is the health status evaluation result and whether or not there are abnormalities. Specifically, the server preprocesses the data, then inputs it into a pre-trained machine learning model to estimate the health status, and performs an evaluation if an abnormal pattern is detected.

[0712] Step 4:

[0713] The server notifies the user's smart device of the analysis results. The input is health assessment data generated based on the analysis, and the output is a notification message. Specifically, the server generates the notification content and pushes the information to the user's specified device using services such as Azure Notification Hubs.

[0714] Step 5:

[0715] Users check notifications displayed on their smartphones or smart glasses and take necessary actions according to the health guidance and warnings provided. Inputs include notification information from the server, and outputs include user actions or feedback to the system. Specifically, users act according to the instructions presented by the device and record their reactions within the application as needed.

[0716] Step 6:

[0717] The user inputs prompts to a generated AI model to request further health assessments and advice. The input consists of user prompts, and the output is detailed analysis results or suggestions from the AI ​​model. Specifically, the user provides natural language input through the application, and the AI ​​model performs additional analysis based on this input and returns the results.

[0718] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0719] This invention is a system that combines multiple sensors installed in a toilet with an emotion engine to gain a more comprehensive understanding of the user's health condition and support appropriate health management. This system consists of a terminal, a server, and a user's smartphone application.

[0720] The device is equipped with various sensors that measure temperature, humidity, odor, and the chemical composition of waste, as well as a camera and microphone to capture the user's facial expressions and voice. This allows the device to collect environmental data and user emotional data while the user is using the toilet. This data is transmitted to a server in real time via wireless communication.

[0721] The server securely stores received environmental and emotional data in a database and performs analysis using AI technology. The analysis includes health status assessment based on excrement and environmental data, and recognition of the user's emotional state using an emotion engine. The emotion engine uses voice analysis and facial expression analysis technologies to evaluate the user's emotions, such as their psychological state and stress level.

[0722] The analysis results are generated by the server as a health status report, which includes advice based on emotional state and health indicators. This report is pushed to the user's smartphone app, allowing them to immediately review its contents. Furthermore, the user's emotional data is recorded chronologically, enabling analysis of long-term emotional patterns.

[0723] Users can use the provided health advice to review their daily lifestyle habits and decide to seek medical attention if necessary. If they are experiencing emotional instability, they will also be offered suggestions for relaxation and stress reduction techniques.

[0724] As a concrete example, when a user used the toilet, the device detected data suggesting an imbalance in gut flora and also sensed tension from the user's facial expression. Based on this information, the server sent a notification to the user suggesting easily digestible meals and introducing deep breathing techniques for relaxation. In this way, users can receive care not only for their physical health but also for their mental health.

[0725] The following describes the processing flow.

[0726] Step 1:

[0727] The device uses sensors installed in the toilet to collect temperature, humidity, odor, and the color and chemical composition of waste in real time. It also uses a camera and microphone to simultaneously capture the user's facial expressions and voice data.

[0728] Step 2:

[0729] The device packages the collected environmental data and user sentiment data and sends it to a server in the cloud using a Wi-Fi or 5G network.

[0730] Step 3:

[0731] The server receives data sent from the terminal and securely stores it in the database. During storage, it prepares and preprocesses the data and converts it into a format that can be used for AI analysis.

[0732] Step 4:

[0733] The server uses AI algorithms to analyze waste and environmental data to assess health status. Simultaneously, an emotion engine analyzes facial expressions and voice data to recognize the user's emotional state. This analysis determines the user's stress level and subjective well-being.

[0734] Step 5:

[0735] Based on the health assessment and emotion recognition results, the server generates a detailed report and health advice. This advice includes suggestions regarding diet and hydration, as well as guidance on maintaining mental well-being.

[0736] Step 6:

[0737] The server sends the generated results to the user's smartphone app via push notification, allowing the user to check their health report at any time.

[0738] Step 7:

[0739] Users check notifications through the app, and based on the results, decide and take necessary health improvement actions. If needed, they can utilize relaxation methods and psychological support that address their emotional state.

[0740] Step 8:

[0741] The server records and continuously analyzes users' long-term health data and emotional patterns, evolving the system to enable more personalized advice.

[0742] (Example 2)

[0743] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0744] In modern society, it is important to comprehensively understand and appropriately manage an individual's health status. However, conventional health management methods have been limited to collecting physical data, and have not adequately considered psychological and emotional aspects of health maintenance. This invention aims to improve physical and mental health by comprehensively evaluating health and emotional states based on data obtained using various sensors in toilets and providing appropriate advice.

[0745] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0746] In this invention, the server includes means for collecting biological waste and surrounding information, equipped with various detectors; means for transmitting the collected data to an information processing device via wireless communication; and means for analyzing the received data using an intelligent system and evaluating the user's health status. This makes it possible to comprehensively understand not only the user's physical health but also their psychological state and to provide appropriate health guidance.

[0747] "Various detectors" is a general term for devices used to measure temperature, humidity, odor, and the chemical composition of biological waste.

[0748] "Biological waste" refers to waste products excreted from the human body and are analyzed to assess health status.

[0749] "Surrounding information" refers to data that indicates the state of the environment, such as temperature, humidity, and odor.

[0750] An "information processing device" is a system for receiving and analyzing collected data.

[0751] "Wireless communication" is a means of communication that transmits and receives data without using cables.

[0752] An "intelligent system" is a technology that uses artificial intelligence to analyze and evaluate data.

[0753] "Health guidelines" refer to advice and recommended actions provided to users based on an assessment of their health status.

[0754] An "emotion analysis engine" is a technology that evaluates a user's emotional state based on voice and facial expression data.

[0755] A "terminal device" refers to an electronic device used directly by the user, and is used for notification and confirmation of information.

[0756] This invention is a system that uses various detectors installed in a toilet to comprehensively understand the user's physical and emotional state and support health management. This system consists of a terminal, a server, and the user's mobile information terminal.

[0757] The device is equipped with multiple detectors to measure temperature, humidity, odor, and the chemical composition of biological waste. It also collects data on the user's emotional state by recording their facial expressions and voice using a camera and microphone. This information is transmitted to a server in real time via wireless communication.

[0758] The server has a database for securely storing data received from the terminal. The server analyzes the data through an intelligent system utilizing artificial intelligence. The analysis includes health status assessment based on excrement and environmental data, and analysis of the user's psychological state using an emotion analysis engine. A health status report is generated based on the analysis results, which includes health guidelines for the user. This report is pushed to the mobile device, ensuring that the user is always provided with the latest information.

[0759] Users can adjust their daily lifestyle habits by utilizing health advice and recommended actions based on their emotional state, as notified via their device. For example, if data indicates that a user's gut balance is poor, the server provides health guidelines, including suggestions for easily digestible meals. Similarly, if the user's level of tension is detected from their facial expression data, suggestions for relaxation techniques are also provided. In this way, users can manage both their physical and mental health.

[0760] An example of a prompt to be input into the generating AI model would be: "Based on the user's gut balance data and emotional state, please suggest recommended lifestyle improvements."

[0761] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0762] Step 1:

[0763] The device measures temperature, humidity, odor, and the chemical composition of biowaste, and records the user's facial expressions and voice. The input data obtained from these sensors and devices is collected as environmental data and user emotion data. Specifically, the temperature sensor measures room temperature, and the humidity sensor measures humidity in the air. The odor sensor detects volatile compounds in the space, and the chemical sensor analyzes the chemical composition of excrement. In addition, the camera captures the user's facial expressions, and the microphone acquires voice data. The collected data is converted into packets and transmitted to the server in real time.

[0764] Step 2:

[0765] The server receives data transmitted from the terminal and stores it in a database. The input data is classified into environmental data and sentiment data and stored securely. The server then prepares to perform data analysis using artificial intelligence with this stored data. Encryption technology is used throughout this process to maintain data integrity and completeness.

[0766] Step 3:

[0767] The server activates its intelligent system and begins analyzing the received data. First, it assesses the user's health status using environmental data and biowaste data. Specifically, an AI algorithm detects abnormalities in chemical composition and environmental changes. Next, it uses an emotion analysis engine to analyze voice data and facial expression data to assess the user's psychological state and stress level. During this process, the AI ​​performs analysis based on conditions specified as prompts (e.g., "Based on the user's gut balance data and emotional state, please suggest recommended lifestyle improvements."). The analysis results are compiled into a report.

[0768] Step 4:

[0769] The server compiles the generated health status report into health guidelines and pushes them to the user's mobile device. The notification includes specific advice related to the user's health and emotional state. For example, if the user indicates high stress levels, relaxation methods such as deep breathing exercises will be suggested. The user will be shown specific methods for adjusting their daily lifestyle based on the health guidelines.

[0770] Step 5:

[0771] Users review health status reports notified on their devices and act on the advice provided. If necessary, they review their daily schedules and habits and manage their lifestyle appropriately. As a result, users can improve their health and well-being.

[0772] (Application Example 2)

[0773] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0774] Traditional health management systems have focused on evaluating users' physical health, but lack analysis of emotional states and the response based on those states. Furthermore, commercial facilities fail to offer personalized services and products tailored to users' health conditions, resulting in insufficient personalization of services. This means users miss out on necessary health guidance and appropriate product information, missing opportunities for service improvement at commercial facilities.

[0775] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0776] In this invention, the server includes means for collecting excrement and surrounding environment data using various sensors, means for transmitting the collected data to a data processing device via wireless communication, means for analyzing the received data using artificial intelligence and evaluating the user's health status, means for providing health advice to the user based on the analysis results, and means for suggesting products or services within a commercial facility based on the analysis results. This makes it possible to provide personalized services and suggest products according to the user's health status.

[0777] "Various sensors" are devices that detect temperature, humidity, odor, chemical composition of excrement, as well as facial expressions and voices.

[0778] Wireless communication is a method of transmitting data without using physical connections such as cables.

[0779] A "data processing device" is a device, such as a computer or server, that analyzes received data and extracts necessary information.

[0780] "Artificial intelligence" is a technology that uses machines to mimic human intelligence and perform data analysis and predictions.

[0781] "Health advice" refers to guidelines for behaviors and lifestyle habits recommended to improve the user's health.

[0782] A "commercial facility" is a store or facility that provides goods and services to consumers.

[0783] "Service proposals" refer to information about appropriate products and services to be offered to users based on the analysis results.

[0784] In this invention, a terminal installed in a toilet collects data to comprehensively evaluate the user's health condition. The terminal is equipped with various sensors to measure temperature, humidity, odor, and the chemical composition of excrement, as well as a camera and microphone to capture the user's facial expressions and voice. This allows for the acquisition of environmental and emotional data obtained while the user is using the toilet.

[0785] Data obtained from sensors is transmitted to a server in real time via wireless communication. The server securely stores the received data in a database and analyzes the user's health and emotional state using AI technology. Data processing is performed using machine learning platforms such as Amazon SageMaker. The analysis results are generated as health advice to assess the user's health status and are notified to the user's smartphone in real time.

[0786] Furthermore, based on the analysis results, personalized product or service suggestions will be provided for use within the commercial facility. This will help users make informed purchasing decisions and utilize services within the facility.

[0787] For example, suppose a user uses the restroom and an imbalance in their gut flora is detected, along with increased stress levels observed in their facial expression. In this case, the server sends a push notification offering suggestions for easily digestible meals and a discount coupon for relaxation products at the store. This allows the user to receive both health and stress relief.

[0788] An example of a prompt to input into the generating AI model would be, "Based on the user's health data, please suggest products and services appropriate to their health condition." This prompt allows the AI ​​to derive the most suitable suggestions for each user.

[0789] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0790] Step 1:

[0791] The terminal acquires various sensor data from users using the toilet, including temperature, humidity, odor, and the chemical composition of excrement. This data is then packetized and prepared along with facial expression data and voice data captured by the camera and microphone. The input consists of sensor data and emotion data, while the output is an integrated data packet.

[0792] Step 2:

[0793] The terminal transmits the generated data packets to the server in real time via Bluetooth or Wi-Fi. The input is the integrated data packets, and the output is the result of data transmission via wireless communication.

[0794] Step 3:

[0795] The server stores the received data in a database and analyzes the acquired data on Amazon SageMaker. It uses an AI algorithm to evaluate health and emotional states and generates analysis results. The input is the transmitted data packets, and the output is the analyzed health and emotional state evaluation results.

[0796] Step 4:

[0797] The server uses an AI model generated based on the analysis results to produce healthcare advice tailored to the user's health condition, as well as recommendations for products and services within the commercial facility. The AI ​​model is invoked using prompts to generate personalized advice text. The input is the analysis results, and the output is user-specific advice and suggestions.

[0798] Step 5:

[0799] The server sends the generated advice and suggestions to the user's smartphone via push notification. The input is the generated advice text and suggestions, and the output is the notification result sent to the user's device.

[0800] Step 6:

[0801] Users check the advice and suggestions they receive via push notifications on their smartphones and use the suggested products or services as needed. The input is the information received via push notifications, and the output is the user's actions.

[0802] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0803] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0804] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0805] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0806] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0807] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0808] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0809] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0810] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0811] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0812] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0813] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0814] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0815] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0816] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0817] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0818] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0819] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0820] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0821] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0822] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0823] The following is further disclosed regarding the embodiments described above.

[0824] (Claim 1)

[0825] A means of collecting excrement and environmental data, equipped with various sensors,

[0826] A means for transmitting collected data to a data processing device via wireless communication,

[0827] A means of analyzing received data using artificial intelligence to evaluate health status,

[0828] A means of providing users with health advice based on analysis results,

[0829] A system that includes this.

[0830] (Claim 2)

[0831] The system according to claim 1, comprising means for automatically supplying fragrance for environmental improvement using a scent sensor.

[0832] (Claim 3)

[0833] The system according to claim 1, comprising communication means for providing the analyzed data to a medical institution.

[0834] "Example 1"

[0835] (Claim 1)

[0836] A group of sensors for collecting environmental information including the physical and chemical attributes of excrement, and means for integrating the data at regular intervals,

[0837] A means of transmitting integrated data to a data processing device using wireless communication technology,

[0838] A means of accumulating and pre-processing received data in a cloud computing environment,

[0839] A method for analyzing data using a generative AI model, identifying health indicators, and detecting anomalies and health risks,

[0840] A means of notifying the user device of the analysis results and providing health advice through an intuitive interface,

[0841] A system that includes this.

[0842] (Claim 2)

[0843] The system according to claim 1, comprising a means for maintaining a comfortable environment by automatically supplying fragrance based on environmental information using an odor sensor.

[0844] (Claim 3)

[0845] The system according to claim 1, further comprising encrypted communication means for securely sharing analysis data with medical institutions with user consent.

[0846] "Application Example 1"

[0847] (Claim 1)

[0848] A device equipped with various sensors to monitor excrement and environmental data,

[0849] Means for transmitting collected data to a processing unit via wireless communication,

[0850] A means of determining health status by analyzing received data using a machine learning algorithm,

[0851] A means of providing health guidance to users based on the analysis results,

[0852] A means having a function to issue an alarm when abnormal environmental data is detected,

[0853] A system that includes this.

[0854] (Claim 2)

[0855] The system according to claim 1, comprising means for automatically supplying aromatic substances for environmental improvement using odor-sensing sensors.

[0856] (Claim 3)

[0857] The system according to claim 1, further comprising a communication device for transferring the analyzed data to a medical institution.

[0858] "Example 2 of combining an emotion engine"

[0859] (Claim 1)

[0860] A means of collecting biological waste and surrounding information, equipped with various detectors,

[0861] A means for transmitting collected data to an information processing device via wireless communication,

[0862] A means of analyzing received data using an intelligent system to evaluate health status,

[0863] A means of providing users with health guidelines based on analysis results,

[0864] A means for evaluating psychological state from voice and facial expression data using an emotion analysis engine,

[0865] A means for generating a health status report and notifying a terminal device,

[0866] A system that includes this.

[0867] (Claim 2)

[0868] The system according to claim 1, further comprising means for automatically supplying fragrance for improving the surrounding environment using an odor detector.

[0869] (Claim 3)

[0870] The system according to claim 1, comprising communication means for providing the analyzed information to a medical institution.

[0871] "Application example 2 when combining with an emotional engine"

[0872] (Claim 1)

[0873] A means of collecting data on excrement and the surrounding environment, equipped with various sensors,

[0874] A means for transmitting collected data to a data processing device via wireless communication,

[0875] A means of analyzing received data using artificial intelligence to evaluate health status,

[0876] A means of providing health advice to users based on the analysis results,

[0877] A means of proposing products or services within a commercial facility based on the analysis results,

[0878] A system that includes this.

[0879] (Claim 2)

[0880] The system according to claim 1, comprising means for automatically supplying fragrance for environmental improvement using a scent sensor.

[0881] (Claim 3)

[0882] The system according to claim 1, further comprising communication means for providing the analyzed data to an external healthcare service provider. [Explanation of Symbols]

[0883] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of collecting excrement and environmental data, equipped with various sensors, A means for transmitting collected data to a data processing device via wireless communication, A means of analyzing received data using artificial intelligence to evaluate health status, A means of providing users with health advice based on analysis results, A system that includes this.

2. The system according to claim 1, comprising means for automatically supplying fragrance for environmental improvement using a scent sensor.

3. The system according to claim 1, further comprising communication means for providing the analyzed data to a medical institution.

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