Dehydration estimation device, toilet system, and method for controlling toilet system

Abstract

To provide appropriate estimation of dehydration.SOLUTION: A dehydration estimation device according to an embodiment includes: data storage means for storing urination data acquired based on urination of a user of the toilet of a toilet device; and dehydration estimation means for estimating the dehydration state of the user based on the urination data stored by the data storage means. The urination data includes urination information regarding urine volume or urine flow rate acquired based on a state change in a bowl unit provided in the toilet device.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The disclosed embodiments relate to a dehydration estimation device, a toilet system, and a method for controlling a toilet system. [Background technology]

[0002] In recent years, technologies have been developed to manage and provide users with information about their health. For example, a health management system has been provided that can provide more personalized prediction results for each user (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-174168 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the above-described conventional technology has room for improvement. For example, in the above-described conventional technology, in order to understand the health condition of a user (person to be managed) who is the subject of health management, it is necessary to access a medical information database containing the user's medical information. If the medical information of the person (user) who is to be managed cannot be obtained, it is difficult to understand the health condition of the person (user). As such, the above-described conventional technology has room for improvement in terms of the information used to understand a person's health condition. Therefore, it is desirable to appropriately estimate a person's health condition, such as dehydration, using information obtained from the person's daily life, for example.

[0005] The disclosed embodiments aim to provide a dehydration estimation device, a toilet system, and a control method for a toilet system that can appropriately estimate dehydration. [Means for solving the problem]

[0006] A dehydration estimation device according to one aspect of the embodiment comprises a data storage means for storing urination data obtained based on the urination of a toilet user in a toilet device, and a dehydration estimation means for estimating the dehydration state of the toilet user based on the urination data stored by the data storage means, wherein the urination data includes urination information regarding the amount of urine or urine flow rate obtained based on changes in the state within a bowl portion of the toilet device.

[0007] According to one aspect of the embodiment, a dehydration estimation device can easily estimate dehydration based on urine volume or urine flow rate estimated from changes in the state of the bowl. For example, the dehydration estimation device can acquire urination information based on changes in the state of the water seal in the toilet device, and estimate a person's dehydration state (dehydration state) through daily toilet use based on the urination data. Therefore, the dehydration estimation device can appropriately estimate dehydration. For example, changes in the state of the bowl are acquired by detection using a sensor. Examples of sensors include cameras, which are optical and image sensors, thermosensors that detect temperature, ultrasonic sensors that detect distance, and radio wave sensors. For example, by using a sensor suitable for detecting information used to estimate dehydration, various information indicating changes in the state of the bowl can be acquired through sensor detection, such as information on the movement of the water seal, information on sound, and information on changes in the state of the water seal in the trap section. Furthermore, the information on the swaying of the seal water includes, for example, at least one of the following information: the height of the swaying, the duration of the swaying of the seal water, the vertical width of the waves generated on the seal water surface, the distance between waves generated on the seal water surface, the amount of bubbles generated on the seal water surface, the size of the swaying area of ​​the seal water, the shape of the waves generated on the seal water surface, or optical data or temperature data obtained from such information. Furthermore, the information on urine includes, for example, at least one of the following information: the amount of urine voided per unit time, the total amount of urine voided, and the duration of urination. Furthermore, the information obtained from the information on urine includes, for example, at least one of the following information obtained from the information on urine: the interval (frequency) of toilet use, the cumulative amount of urine voided per day, health information, and the amount of water in the body.

[0008] In the dehydration estimation device according to one aspect of the embodiment, the urination data includes other urination information having at least one of information on urination time, number of urinations, or urination frequency.

[0009] This allows the dehydration estimation device to estimate dehydration with higher accuracy, and therefore the dehydration estimation device can appropriately estimate dehydration.

[0010] In one aspect of the embodiment, the dehydration estimation device is characterized in that the change in state within the bowl portion includes a change in state of the internal space of the bowl portion above the sealing water formed on the bottom side of the bowl portion, or a change in state of the sealing water.

[0011] This allows the change in state inside the bowl to be detected appropriately, and the dehydration estimation device can therefore estimate the dehydration state appropriately.

[0012] In one aspect of the embodiment, the dehydration estimation device is characterized in that the urination information includes information obtained based on a change in the state of the sealing water on the bowl portion side.

[0013] This allows the dehydration estimating device to easily estimate dehydration from changes in the water seal state on the bowl side, thereby enabling the dehydration estimating device to appropriately estimate dehydration.

[0014] In one aspect of the embodiment, the toilet device has a trap section that forms a water seal on the bottom side of the bowl section, and the urination information includes information obtained based on changes in the state of the water seal on the trap section side.

[0015] This allows the dehydration estimation device to easily estimate dehydration from changes in the trap-side water seal state, thereby enabling the dehydration estimation device to appropriately estimate dehydration.

[0016] In one aspect of the embodiment, the dehydration estimation device is characterized in that the urination information is obtained by detecting changes in the state of the seal water on the trap section side using a radio wave sensor, the detection range of the radio wave sensor is set to an area including the apex of the trap section, and the radio wave sensor detects changes in the state of the seal water based on overflow from the apex of the trap section.

[0017] This allows the radio wave sensor to detect changes in the state of the seal water with high accuracy, and the dehydration estimating device can therefore appropriately estimate dehydration.

[0018] In one aspect of the embodiment, the dehydration estimation device is characterized in that the urination information includes information obtained by detecting changes in the state of the sealed water formed on the bottom side of the bowl portion using a radio wave sensor or an optical sensor.

[0019] This allows the change in the state of the seal water to be detected with high accuracy, and the dehydration estimating device can therefore appropriately estimate dehydration.

[0020] In one aspect of the embodiment, the dehydration estimation device is characterized in that the urination information includes information obtained by detection by a sound sensor.

[0021] This allows the dehydration estimation device to estimate dehydration using state changes in the bowl portion, including sound information, and therefore the dehydration estimation device can appropriately estimate dehydration.

[0022] In one aspect of the embodiment, the dehydration estimation device is characterized in that the state change within the bowl portion includes at least one state change among humidity change, temperature change, and gas composition change associated with urination.

[0023] This allows the dehydration estimating device to increase the accuracy of estimating dehydration based on changes in humidity, etc., that accompany urination. Therefore, the dehydration estimating device can appropriately estimate dehydration.

[0024] In one aspect of the embodiment, the dehydration estimation device is characterized in that the urination information includes information obtained based on changes in the state of the sealing water due to urination, excluding changes in the state of the sealing water due to defecation.

[0025] This allows the dehydration estimation device to increase the accuracy of dehydration estimation by excluding defecation information, and therefore the dehydration estimation device can appropriately estimate dehydration.

[0026] In one aspect of the embodiment, the dehydration estimating device is characterized in that the dehydration estimating means estimates the dehydration state when an integrated value of the amount of urine over a predetermined time period is less than a predetermined value.

[0027] This allows the dehydration estimation device to further increase the accuracy of dehydration estimation by using the value obtained by integrating the urine volume over a predetermined period of time, thereby enabling the dehydration estimation device to appropriately estimate dehydration.

[0028] In one aspect of the embodiment, the dehydration estimating device is characterized in that the dehydration estimating means estimates the dehydration state when the urination interval is longer than a predetermined interval.

[0029] This allows the dehydration estimation device to further increase the accuracy of dehydration estimation by using the urination interval information, and therefore the dehydration estimation device can appropriately estimate dehydration.

[0030] In one aspect of the embodiment, the dehydration estimating device is characterized in that the dehydration estimating means estimates that the subject is dehydrated when the amount of urine in a predetermined period of time is less than a predetermined amount.

[0031] This allows the dehydration estimating device to further increase the accuracy of estimating dehydration by using the urine volume over a predetermined period, thereby enabling the dehydration estimating device to appropriately estimate dehydration.

[0032] In one aspect of the embodiment, the dehydration estimating device is characterized in that the dehydration estimating means estimates the dehydration state when the urination interval is longer than a predetermined interval and the urine volume is less than a predetermined volume.

[0033] This allows the dehydration estimation device to further increase the accuracy of dehydration estimation by using both the urination interval information and the urine volume over a predetermined period, thereby enabling the dehydration estimation device to appropriately estimate dehydration.

[0034] In one aspect of the embodiment, the dehydration estimation device is characterized in that the dehydration estimation means estimates the dehydration state based on the urination data and at least one of the toilet user's urination characteristics by age and season.

[0035] This allows the dehydration estimation device to further increase the accuracy of dehydration estimation by using at least one of the age and season-specific urination characteristics of the toilet user. Therefore, the dehydration estimation device can appropriately estimate dehydration.

[0036] In one aspect of the embodiment, the dehydration estimation device further includes a dehydration state assessment means that classifies the dehydration state of the toilet user into multiple levels based on the urination data, and the urination data includes information on urine color.The dehydration state assessment means is characterized in that when the amount of urine included in the urination data is less than a predetermined amount, the dehydration state assessment means classifies the dehydration state into multiple levels based on the urine color included in the urination data of the toilet user.

[0037] This allows the dehydration estimation device to generate information for assessing the dehydration state of the toilet user by classifying the dehydration state of the toilet user into multiple levels, thereby enabling the dehydration estimation device to appropriately assess dehydration.

[0038] In one aspect of the embodiment, the dehydration estimation device is characterized in that the dehydration estimation means refrains from estimating the state of dehydration when the number of urinations is equal to or less than a predetermined number of times based on the urination data.

[0039] This allows the dehydration estimating device to refrain from estimating the dehydration state when the number of urinations is equal to or less than the predetermined number, thereby preventing erroneous estimation of dehydration. Therefore, the dehydration estimating device can appropriately estimate dehydration.

[0040] A dehydration estimation device according to one aspect of the embodiment further includes a notification means for notifying a predetermined destination of highlight information indicating the health status of a toilet user based on urination data for a predetermined period including the most recent urination data, and is characterized in that if the number of urinations based on the urination data is less than a predetermined number, the notification means does not notify the predetermined destination of the highlight information.

[0041] This allows the dehydration estimation device to notify a predetermined recipient of highlight information indicating the health status of the toilet user while suppressing unnecessary notifications, thereby enabling the dehydration estimation device to appropriately provide information regarding health status such as dehydration.

[0042] In one aspect of the embodiment, the dehydration estimation device is characterized in that the notification means notifies the specified destination of recommendation information for improving the health condition of the toilet user based on the urination data for a specified period including the latest urination data, and if the number of urinations based on the urination data is less than a specified number, the notification means does not notify the specified destination of the recommendation information.

[0043] This allows the dehydration estimation device to notify a predetermined destination of recommended information for improving the health condition of the toilet user while suppressing unnecessary notifications, thereby enabling the dehydration estimation device to appropriately provide information regarding health conditions such as dehydration.

[0044] In one aspect of the embodiment, the dehydration estimation device is characterized in that the notification means notifies the specified destination of the next recommended information generated based on specified input information in response to the recommended information received by the toilet user.

[0045] This allows the dehydration estimation device to provide notifications tailored to each toilet user by notifying a predetermined destination of recommendation information generated based on feedback from the toilet user. Therefore, the dehydration estimation device can provide appropriate information regarding health conditions such as dehydration.

[0046] The dehydration estimation device according to one aspect of the embodiment further includes a frequent urination estimation means for estimating the toilet user's frequent urination based on the urination data, and the frequent urination estimation means is characterized in that it estimates frequent urination when the urination interval is shorter than a predetermined period.

[0047] This allows the dehydration estimation device to estimate not only dehydration but also frequent urination. Therefore, the toilet system control method can appropriately estimate health conditions such as dehydration and frequent urination.

[0048] A toilet system according to one aspect of the embodiment comprises a toilet device, a data storage means for storing urination data obtained based on urination by a toilet user in the toilet device, and a dehydration estimation means for estimating the dehydration state of the toilet user based on the urination data stored by the data storage means, wherein the urination data includes urination information regarding urine volume or urine flow rate obtained based on changes in the state within a bowl portion of the toilet device.

[0049] According to one aspect of the embodiment, the toilet system can easily estimate dehydration based on the urine volume or urine flow rate estimated from changes in the state of the bowl. Therefore, the toilet system can appropriately estimate dehydration.

[0050] A control method for a toilet system according to one aspect of an embodiment is a control method for a toilet system comprising a toilet device, a data storage means for storing urination data acquired based on urination by a toilet user in the toilet device, and a dehydration estimation means for estimating the dehydration state of the toilet user based on the urination data stored by the data storage means, and includes a first step of acquiring urination data based on urination by the toilet user in the toilet device, a second step of storing the urination data acquired by the first step in the data storage means, and a third step of estimating the dehydration state of the toilet user based on the urination data stored by the data storage means, wherein the third step estimates the dehydration state based on the urination data including urination information regarding urine volume or urine flow rate acquired based on changes in the state within a bowl portion of the toilet device.

[0051] According to the control method for a toilet system according to one aspect of the embodiment, dehydration can be easily estimated based on the urine volume or urine flow rate estimated from changes in the state of the bowl. Therefore, the control method for a toilet system can appropriately estimate dehydration. [Effects of the Invention]

[0052] According to one aspect of the embodiment, dehydration can be appropriately estimated. [Brief explanation of the drawings]

[0053] [Figure 1] FIG. 1 is a diagram showing an example of the configuration and processing overview of a toilet system according to a first embodiment. [Figure 2] FIG. 2 is a flowchart showing an example of a procedure of a process executed by the toilet system. [Figure 3] FIG. 3 is a diagram showing an example of information used for processing by the toilet system. [Figure 4] FIG. 4 is a perspective view showing an example of the configuration of a toilet system according to the second embodiment. [Figure 5] FIG. 5 is a perspective view showing an example of the configuration of a toilet seat device according to the second embodiment. [Figure 6] FIG. 6 is a perspective view showing an example of the configuration of a toilet seat device according to the second embodiment. [Figure 7] FIG. 7 is a side cross-sectional view showing an example of the configuration of a toilet seat device according to the second embodiment. [Figure 8] FIG. 8 is a block diagram showing an example of the configuration of a toilet seat device according to the second embodiment. [Figure 9] FIG. 9 is a block diagram showing an example of the configuration of the control device according to the second embodiment. [Figure 10] FIG. 10 is a flowchart showing an example of a procedure of a process executed by the toilet system. [Figure 11] FIG. 11 is a flowchart showing an example of a procedure of a process executed by the toilet system. [Figure 12] FIG. 12 is a diagram showing an example of the relationship between excrement and shaking. [Figure 13] FIG. 13 is a diagram showing an example of the relationship between an object other than excrement and shaking. [Figure 14] FIG. 14 is a diagram showing an example of the relationship between a user and the direction of urination. [Figure 15] FIG. 15 is a diagram showing an outline of the configuration and processing of the toilet system. [Figure 16] FIG. 16 is a diagram showing an example of the relationship between information about sway and urine flow rate. [Figure 17] FIG. 17 is a side cross-sectional view showing an example of the configuration of a toilet apparatus according to a third embodiment. [Figure 18] FIG. 18 is a diagram showing an example of image data captured by a camera and data obtained from the image data. [Figure 19] FIG. 19 is a diagram showing an example of a control flow of the toilet system. [Figure 20] FIG. 20 is a diagram showing a modified example of the control flow of the toilet system. [Figure 21] FIG. 21 is a diagram showing the relationship between the water seal pattern stored in the control unit and the urine flow rate. [Figure 22]FIG. 22 is a diagram showing the relationship between the water seal pattern stored in the control unit and the urine flow rate. [Figure 23] FIG. 23 is a diagram showing the relationship between the water seal pattern stored in the control unit and the urine flow rate. [Figure 24] FIG. 24 is a diagram showing an example of wave behavior. [Figure 25] FIG. 25 is a diagram showing an example of a detection mode of wave behavior. [Figure 26] FIG. 26 is a diagram showing an example of conversion into urine volume. [Figure 27] FIG. 27 is a diagram showing an example of the boundary position between the wave and the bowl portion. [Figure 28] FIG. 28 is a diagram showing an example of the timing for obtaining the initial state. [Figure 29] FIG. 29 is a diagram showing an example of the distance between the sensor and the water surface. [Figure 30] FIG. 30 is a diagram showing an example of shaking determination and urine volume. [Figure 31] FIG. 31 is a diagram showing an example of calculation of total urine volume. [Figure 32] FIG. 32 is a diagram showing an example of the relationship between sway and urine volume. [Figure 33] FIG. 33 is a diagram showing an example of the relationship between sway and urine volume. [Figure 34] FIG. 34 is a diagram showing an example of the relationship between the area and the total urine volume. [Figure 35] FIG. 35 is a diagram showing an example of calculation of the total amount of excrement. [Figure 36] FIG. 36 is a diagram showing an example in which a two-dimensional image is used. [Figure 37] FIG. 37 is a diagram showing an example of calculation of the total urine volume. [Figure 38] FIG. 38 is a diagram showing an example of the relationship between the area and the total urine volume. [Figure 39] FIG. 39 is a diagram showing an example of the detection range. [Figure 40] FIG. 40 is a diagram showing an example of shaking after urination. [Figure 41]FIG. 41 is a diagram showing an example of the relationship between the detection range and urination. [Figure 42] FIG. 42 is a diagram showing an example of shaking during urination. [Figure 43] FIG. 43 is a diagram showing an example of a detection mode. [Figure 44] FIG. 44 is a diagram showing an example of the relationship between detection and urine volume. [Figure 45] FIG. 45 is a perspective view showing an example of the configuration of a toilet seat apparatus according to the fourth embodiment. [Figure 46] FIG. 46 is a side cross-sectional view showing an example of the configuration of a toilet seat apparatus according to a fourth embodiment. [Figure 47] FIG. 47 is a block diagram showing an example of the configuration of a toilet seat device according to the fourth embodiment. [Figure 48] FIG. 48 is a diagram showing an example of calculation of excretion time. [Figure 49] FIG. 49 is a flowchart showing an example of a procedure of a process executed by the toilet system. [Figure 50] FIG. 50 is a flowchart showing an example of a procedure of a process executed by the toilet system. [Figure 51] FIG. 51 is a flowchart showing an example of a procedure of a process executed by the toilet system. [Figure 52] FIG. 52 is a diagram showing an example of a configuration using a plurality of sound detection sensors. [Figure 53] FIG. 53 is a diagram illustrating an example of sound information processing. [Figure 54] FIG. 54 is a diagram illustrating an example of sound information processing. [Figure 55] FIG. 55 is a flowchart showing an example of a processing procedure using a plurality of sound detection sensors. [Figure 56] FIG. 56 is a diagram showing an outline of the configuration and processing of the toilet system. [Figure 57] FIG. 57 is a perspective view showing an example of the configuration of a toilet seat apparatus according to the fifth embodiment. [Figure 58] FIG. 58 is a schematic diagram showing an example of the configuration of a toilet device according to the fifth embodiment. [Figure 59] FIG. 59 is a block diagram showing an example of the configuration of a toilet seat device and a radio wave sensor according to the fifth embodiment. [Figure 60] FIG. 60 is a diagram showing an outline of the process of estimating information related to excrement. [Figure 61] FIG. 61 is a diagram showing an example of the relationship between the flow rate and the height of overflow water. [Figure 62] FIG. 62 is a diagram showing an example of a state change accompanying a change in flow rate. [Figure 63] FIG. 63 is a diagram showing an example of detection information of the microwave sensor. [Figure 64] FIG. 64 is a diagram showing an example of the relationship between wavelengths. [Figure 65] FIG. 65 is a diagram showing an example of the characteristics of a radio wave sensor. [Figure 66] FIG. 66 is a diagram showing an example of a method for detecting a change in water level. [Figure 67] FIG. 67 is a diagram showing an example of a process for calculating a flow rate from a change in water level. [Figure 68] FIG. 68 is a diagram showing an example of a method for calculating a flow rate. [Figure 69] FIG. 69 is a diagram showing an example of a method for calculating a flow rate. [Figure 70] FIG. 70 is a diagram showing an example of the relationship between the area and the total urine volume. [Figure 71] FIG. 71 is a diagram showing an example of processing when defecation occurs during urination. [Figure 72] FIG. 72 is a diagram showing an example of processing when defecation occurs during urination. [Figure 73] FIG. 73 is a diagram showing an example of calculation using two outputs. [Figure 74] FIG. 74 is a diagram illustrating an example of the configuration of a radio wave sensor. [Figure 75] FIG. 75 is a diagram showing an example of processing using the relationship between two outputs. DETAILED DESCRIPTION OF THE INVENTION

[0054] Hereinafter, with reference to the accompanying drawings, an embodiment of the toilet system disclosed in the present application will be described in detail. Note that the present invention is not limited to the embodiment described below. Below, the processing performed by the toilet system 1 and the configuration for performing that processing will be described, but first various configurations of the toilet system and other components that are the premise will be described.

[0055] <1. First embodiment> <1-1. Toilet system configuration and processing overview> First, the configuration and processing overview of the toilet system according to the first embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the configuration and processing overview of the toilet system according to the first embodiment.

[0056] As shown in Fig. 1, the toilet system 1 includes a sensor device 12, a dehydration estimation device 13, and a toilet device 20. The dehydration estimation device 13 is communicatively connected to the sensor device 12 and acquires various information used for processing from the sensor device 12. For example, the dehydration estimation device 13 is communicatively connected to the sensor device 12 via a predetermined network (e.g., the Internet) in a wired or wireless manner. Furthermore, when acquiring information from the toilet device 20, the dehydration estimation device 13 may be communicatively connected to the toilet device 20 via a predetermined network in a wired or wireless manner.

[0057] Note that the toilet system 1 shown in Fig. 1 is merely an example, and the toilet system 1 is not limited to the configuration shown in Fig. 1 and any configuration can be adopted. For example, the toilet system 1 does not have to include the sensor device 12. Furthermore, the toilet system 1 may include multiple sensor devices 12, multiple dehydration estimation devices 13, and multiple toilet devices 20.

[0058] Sensor device 12 is a device that detects various types of information used in processing. Sensor device 12 detects changes in the state inside bowl portion 8 of toilet device 20. Changes in the state inside bowl portion 8 include changes in the state of the internal space of bowl portion 8 above the seal water formed on the bottom side of bowl portion 8, or changes in the state of the seal water.

[0059] For example, the sensor device 12 detects a change in the state inside the bowl portion 8, including a change in the state of the swaying of the seal water or the space above the seal water. For example, the sensor device 12 detects at least one of the space inside the bowl portion 8 of the toilet apparatus 20, the swaying of the seal water, and a change in the state related to the seal water. The sensor device 12 provides the detected information to the dehydration estimation device 13. For example, the sensor device 12 transmits the detected information to the dehydration estimation device 13.

[0060] In Fig. 1, sensor device 12 may detect changes in the condition of the space within bowl portion 8 of toilet device 20, the water seal WT formed in an area including the bottom side of bowl portion 8, the area within drain pipe 81 on the opposite side of the bottom side of bowl portion 8, etc. For example, sensor device 12 may detect changes in the condition of a detection range including at least one of areas AR1, AR2, and AR3 in Fig. 1. In this way, information used to estimate health conditions such as dehydration is collected from various subjects.

[0061] For example, the sensor device 12 may be a sound sensor (sound detection sensor) that detects sound, an image sensor (line sensor, camera, etc.) that captures images such as still images or videos, a temperature sensor that detects temperature, a humidity sensor that detects humidity, a radio wave sensor that detects radio waves, etc. For example, the sensor device 12 may be a vibration detection sensor 34, a sound detection sensor 34A, an optical sensor 34B, a camera 36, ​​a radio wave sensor 200, etc., which will be described later.

[0062] For example, if the sensor device 12 is a radio wave sensor such as the radio wave sensor 200, the detection range of the sensor device 12, which is a radio wave sensor, is set to an area including the apex of the trap section. In this case, the sensor device 12, which is a radio wave sensor, detects a change in the state of the seal water based on water overflowing from the apex of the trap section, as will be described in detail later. Note that the above is merely an example, and the sensor device 12 is not limited to the above, and any sensor can be used as long as it can detect information used by the dehydration estimation device 13 for the estimation process.

[0063] For example, sensor device 12 may be a moving object detection means such as a motion sensor that detects the urination posture or body movement of the toilet user. In this case, sensor device 12 as a moving object detection means may be placed in toilet room R (see FIG. 4 ). Sensor device 12 as a moving object detection means may also be mounted on a terminal device (terminal) such as a smartphone carried by the toilet user, and the terminal device may transmit detection information to dehydration estimation device 13.

[0064] Furthermore, the terminal device carried by the toilet user may have a position sensor that detects its position, such as a GPS (Global Positioning System) sensor. For example, the terminal device carried by the toilet user may transmit information indicating its detected position to dehydration estimation device 13. As a result, dehydration estimation device 13 receives the position of the terminal device carried by the toilet user, i.e., information indicating the toilet user's position, as external data. Note that the terminal device carried by the toilet user may obtain information indicating its position using any method, not limited to a position sensor such as a GPS sensor. For example, the terminal device carried by the toilet user may obtain information indicating its estimated position based on a wireless communication function such as Wi-Fi (registered trademark) (Wireless Fidelity) or Bluetooth (registered trademark).

[0065] Dehydration estimation device 13 is a computer (information processing device) that provides services related to a person's health condition, such as dehydration. Dehydration estimation device 13 performs estimation processing to estimate dehydration of a toilet user (also simply referred to as "user") based on urination data acquired based on the urination of the toilet user. Dehydration estimation device 13 estimates dehydration of a toilet user based on urination data acquired based on the toilet user's urination into toilet device 20. For example, the urination data includes urination information related to the amount of urine or urine flow rate acquired based on changes in the state inside bowl portion 8 of toilet device 20.

[0066] Here, urine volume and urine flow rate are both the same in terms of the amount of urine excreted by a user. However, urine volume is an indicator of the amount of urine excreted by a user, and urine flow rate is an indicator of the strength (force) of urine excreted by a user. For example, if the amount of urine excreted by a user is the same, the urine flow rate will be different if the strength (force) of urine excreted by the user is different. For example, even if the amount of urine excreted by a user is the same, the shorter the time it takes to complete the excretion of that amount of urine, the larger the urine flow rate will be, and the longer the time it takes to complete the excretion of that amount of urine, the smaller the urine flow rate will be. For example, the dehydration estimation device 13 calculates the urine flow rate (= urine volume / urination time) by dividing the urine volume of the user's urination by the time required for that urination (urination time). Note that when focusing only on the amount of urine excreted by a user and using urine volume and urine flow rate without any particular distinction, urine flow rate may be interpreted as urine volume, and urine volume may be interpreted as urine flow rate.

[0067] For example, dehydration estimation device 13 may be a control device 100 (described later) or the like. Note that the above is merely an example, and dehydration estimation device 13 may be any device that can detect the estimation process. For example, dehydration estimation device 13 may be a server device such as a cloud server.

[0068] The toilet device 20 is a device used by toilet users for excretion. In Fig. 1, the toilet device 20 includes a toilet bowl 7 having a bowl portion 8 and a toilet seat 5 on which a user sits when using the toilet bowl 7 to excrete. Note that the configuration shown in Fig. 1 is merely an example, and any sensor can be used in the toilet device 20 as long as it includes the toilet bowl 7 having the bowl portion 8.

[0069] 1 illustrates the sensor device 12 at a position separated from the toilet device 20 to illustrate the device configuration, but the sensor device 12 is disposed at a position where the toilet device 20 can detect desired information in order to detect that information. The sensor device 12 may be disposed within the toilet device 20. In this case, the toilet device 20 may include the sensor device 12. The dehydration estimating device 13 may also be disposed within the toilet device 20. In this case, the toilet device 20 may include the dehydration estimating device 13.

[0070] Here, we will briefly explain the process outline shown in Fig. 1. In Fig. 1, sensor device 12 detects a change in state inside bowl portion 8 of toilet device 20 (step S1). For example, sensor device 12 detects a change in state inside bowl portion 8 within a detection range that includes at least one of areas AR1, AR2, and AR3 in Fig. 1.

[0071] The dehydration estimation device 13 acquires information detected by the sensor device 12 from the sensor device 12 (step S2). For example, the dehydration estimation device 13 acquires urination data from the sensor device 12. In this case, the dehydration estimation device 13 stores the urination data acquired from the sensor device 12 in the data storage means 14. For example, the dehydration estimation device 13 may generate urination data based on the information acquired from the sensor device 12. For example, the dehydration estimation device 13 generates urination data based on the urination information acquired from the sensor device 12. In this case, the dehydration estimation device 13 stores the urination data generated based on the information acquired from the sensor device 12 in the data storage means 14.

[0072] Then, dehydration estimation device 13 estimates the dehydration of the toilet user based on the urination data stored in data storage means 14 (step S3). For example, dehydration estimation device 13 estimates the dehydration of a toilet user who has used toilet device 20 based on the urination data stored in data storage means 14. For example, dehydration estimation device 13 may estimate that a toilet user is in a dehydrated state (also simply referred to as "dehydration") if the integrated value of the toilet user's urine volume over a predetermined period of time is less than a predetermined value, based on the urination data stored in data storage means 14. The predetermined period of time can be set arbitrarily. For example, the predetermined period of time may be set based on the division of time periods in a day (24 hours).

[0073] For example, the predetermined time may be set based on the time period of morning (e.g., between 3:00 and 9:00), daytime (e.g., between 9:00 and 15:00), evening (e.g., between 15:00 and 21:00), or nighttime (e.g., between 21:00 and 3:00). Note that the division into time periods of one day (24 hours) described above is merely an example, and the division into time periods of one day (24 hours) is not limited to the above, and may be any division, such as nighttime (e.g., between 22:00 and 6:00) and non-nighttime (e.g., between 6:00 and 22:00). For example, dehydration estimation device 13 estimates that a toilet user is dehydrated when the integrated value of the amount of urine voided during the time the toilet user was in a space (e.g., a house) where toilet device 20 is installed is less than a predetermined value.

[0074] For example, dehydration estimation device 13 may estimate dehydration based on information about the toilet user while they are asleep or during times other than when they are asleep (active time). In this case, dehydration estimation device 13 may, for example, acquire lifestyle pattern information including at least one of information indicating when the toilet user is asleep (sleeping period) or information indicating when the toilet user is awake (active time) in any manner. For example, dehydration estimation device 13 may acquire the lifestyle pattern information of the toilet user from the toilet user's terminal device. In this case, the toilet user's terminal device may transmit to dehydration estimation device 13 lifestyle pattern information generated based on information input by the toilet user or collected by detection by a built-in sensor. Note that the above-described processing is merely an example, and dehydration estimation device 13 may estimate whether the toilet user is dehydrated by any processing using urination data.

[0075] The above-described process allows the toilet system 1 to appropriately estimate dehydration. This allows the toilet system 1 to estimate health conditions based on urination status, for example, in toilets for homes or elderly care facilities. In this way, the toilet system 1 measures the urine volume or urine flow rate based on changes in the state of the bowl caused by urination, and can estimate dehydration based on the measurement results of the urine volume or urine flow rate.

[0076] Furthermore, dehydration estimation device 13 may perform various information processing operations in addition to the above-described estimation of dehydration. For example, dehydration estimation device 13 may perform processing related to the evaluation of dehydration, such as classifying dehydration. Based on the estimation result of dehydration, dehydration estimation device 13 generates a classification of the toilet user's dehydration as information related to the evaluation of dehydration for the toilet user. For example, dehydration estimation device 13 may provide information related to dehydration, such as a notification regarding dehydration. Dehydration estimation device 13 notifies a predetermined destination of the estimation result of dehydration.

[0077] Furthermore, dehydration estimating device 13 may estimate the toilet user's frequent urination based on the urination data stored in data storage means 14. For example, dehydration estimating device 13 estimates the toilet user's nocturia during the night (e.g., between 10 PM and 6 AM) as an example of frequent urination.

[0078] For example, dehydration estimation device 13 estimates whether a toilet user who uses toilet device 20 has frequent urination based on the urination data stored in data storage means 14. For example, dehydration estimation device 13 may estimate that a toilet user has frequent urination if the amount of urine per night or the average amount of urine at night meets a criterion for frequent urination based on the urination data stored in data storage means 14. Note that the above-described processing is merely an example, and dehydration estimation device 13 may estimate whether a toilet user has frequent urination by any processing using the urination data.

[0079] <1-2. Functional configuration of the dehydration estimation device> The functional configuration of the dehydration estimation device will be described below. As shown in Fig. 1, dehydration estimation device 13 has data storage means 14, dehydration estimation means 15, evaluation means 16, notification means 17, and frequent urination estimation means 18. Note that dehydration estimation device 13 may also have an input unit (e.g., keyboard, mouse, etc.) that accepts various operations from an administrator of dehydration estimation device 13, and a display unit (e.g., liquid crystal display, etc.) that displays various information. Dehydration estimation device 13 may also have communication means for communicating with other devices.

[0080] The communication means is realized by, for example, a communication circuit or the like. The communication means is connected to a predetermined network by wire or wirelessly, and transmits and receives information to and from an external information processing device. For example, the communication means is connected to a predetermined network by wire or wirelessly, and transmits and receives information to and from other devices such as the sensor device 12. For example, the communication means may be a communication unit 101, which will be described later.

[0081] The data storage means 14 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. For example, the data storage means 14 is a computer-readable recording medium that non-temporarily records data used by various information processing programs and the like.

[0082] The data storage means 14 according to the embodiment stores various information necessary for processing. The data storage means 14 stores various information acquired from other devices such as various sensors. For example, the data storage means 14 stores urination data acquired based on urination by a toilet user in the toilet device 20.

[0083] For example, the urination data includes urination information related to the amount of urine or the amount of urine flow obtained based on a change in the state of the bowl portion 8 of the toilet device 20. For example, the urination data includes other urination information having at least one of information on the time of urination, the number of times of urination, or the frequency of urination. Also, for example, the urination data includes information on the color of urine (urine color).

[0084] For example, the urination information includes information obtained based on a change in the state of the water seal on the bowl portion 8 side. For example, the urination information includes information obtained based on a change in the state of the water seal on the trap portion side. For example, the urination information is information obtained by detecting a change in the state of the water seal on the trap portion side using a radio wave sensor.

[0085] For example, the urination information includes information obtained by detection by a sound sensor. The state change inside the bowl portion 8 includes at least one state change among changes in humidity, temperature, and gas composition that accompany urination. For example, the urination information includes information obtained based on changes in the state of the water seal caused by urination, excluding changes in the state of the water seal caused by defecation. For example, the urination information includes information obtained by detecting changes in the state of the water seal formed on the bottom side of the bowl portion 8 using a radio wave sensor or an optical sensor.

[0086] For example, the data storage means 14 stores information regarding the toilet user's actions, status, etc. in the toilet. For example, the data storage means 14 stores data obtained from the analysis of information collected by the sensor device 12, etc. The data storage means 14 stores information regarding the toilet user's urination. The data storage means 14 stores historical information regarding the toilet user's urination. For example, the data storage means 14 stores the number of urinations, the amount of urination, the duration of urination, and the date and time of urination (time of urination). The data storage means 14 also stores information regarding the toilet user's defecation. The data storage means 14 stores historical information regarding the toilet user's defecation. For example, the data storage means 14 stores the number of defecations, the amount of urination, the duration of defecation, and the date and time of defecation (time of defecation).

[0087] For example, data storage means 14 stores data based on detection by sensor device 12. For example, data storage means 14 stores data acquired by dehydration estimation means 15. Data storage means 14 stores information used by dehydration estimation means 15 for estimation processing. Data storage means 14 stores information used by evaluation means 16 for processing. Data storage means 14 stores information used by notification means 17 for information provision processing. Data storage means 14 stores information used by urination frequency estimation means 18 for estimation processing.

[0088] For example, the data storage means 14 stores information about urination during the daytime (for example, between 6:00 and 22:00). For example, the data storage means 14 stores daytime urination data. For example, the data storage means 14 stores the amount of urine or the amount of urine flow per daytime. For example, the data storage means 14 stores the average amount of urine or the average amount of urine flow per daytime.

[0089] For example, the data storage means 14 stores information about nighttime urination. For example, the data storage means 14 stores nighttime urination data. For example, the data storage means 14 stores the amount of urine or the urine flow rate per night. For example, the data storage means 14 stores the average amount of urine or the average urine flow rate per night.

[0090] Note that the data storage means 14 is not limited to the above and may store various types of information depending on the purpose. For example, the data storage means 14 stores information indicating the location where the toilet device 20 is installed. For example, the data storage means 14 stores information indicating the location of the facility where the toilet device 20 is installed (such as the toilet user's home). For example, the data storage means 14 stores various types of information related to toilet users as external data. For example, the data storage means 14 stores attribute information indicating the attributes of the toilet users, such as their age and gender. For example, the data storage means 14 stores behavior information indicating the behavior of the toilet users. For example, the data storage means 14 stores location information indicating the location of the toilet users. For example, when there are multiple toilet users (users), the data storage means 14 stores information identifying the toilet users (such as a user ID) in association with the information on the toilet users.

[0091] Furthermore, for example, the data storage means 14 may be the storage unit 120 described later. For example, the data storage means 14 may store information stored in the storage unit 120 described later.

[0092] Each unit (also referred to as an "information processing unit") that performs information processing, such as dehydration estimation means 15, evaluation means 16, notification means 17, and frequent urination estimation means 18, is realized by, for example, a central processing unit (CPU) or a graphics processing unit (GPU) executing a program (e.g., various information processing programs related to the present disclosure) stored within dehydration estimation device 13 using RAM or the like as a working area. Furthermore, information processing units, such as dehydration estimation means 15, evaluation means 16, notification means 17, and frequent urination estimation means 18, are realized by, for example, an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

[0093] Dehydration estimation means 15 executes estimation processing to estimate various information related to the health of the toilet user. Dehydration estimation means 15 executes estimation processing to estimate dehydration of the toilet user. Dehydration estimation means 15 executes estimation processing related to dehydration described above.

[0094] The dehydration estimation means 15 estimates the dehydration state of the toilet user based on the urination data stored in the data storage means 14. The dehydration estimation means 15 estimates the dehydration state when the integrated value of the amount of urine over a predetermined period of time is less than a predetermined value. The dehydration estimation means 15 estimates the dehydration state when the urination interval is longer than a predetermined interval. The dehydration estimation means 15 estimates the dehydration state when the amount of urine over a predetermined period of time is less than a predetermined amount.

[0095] The dehydration estimation means 15 estimates a dehydration state when the urination interval is longer than a predetermined interval and the urine volume is less than a predetermined volume. The dehydration estimation means 15 estimates a dehydration state based on the urination data and at least one of the toilet user's age-specific and season-specific urination characteristics. The dehydration estimation means 15 suspends estimation of a dehydration state when the number of urinations based on the urination data is equal to or less than a predetermined number of times.

[0096] The evaluation means 16 executes an evaluation process to evaluate various information related to the health of the toilet user. The evaluation means 16 executes an evaluation process to evaluate the dehydration of the toilet user. The evaluation means 16 executes the evaluation process related to dehydration described above. For example, the evaluation means 16 is a dehydration state evaluation means that classifies the dehydration state of the toilet user into multiple levels based on urination data. When the amount of urine included in the urination data is less than a predetermined amount, the evaluation means 16 classifies the dehydration state into multiple levels based on the urine color included in the urination data of the toilet user.

[0097] Notification means 17 executes a notification process to notify various information related to the toilet user's health. Notification means 17 executes a process to send information related to the toilet user's dehydration to another information processing device such as the toilet user's terminal device. Notification means 17 executes the notification process related to dehydration described above.

[0098] The notification means 17 notifies a predetermined destination of highlight information (topic information) indicating the health status of the toilet user based on urination data for a predetermined period, including the most recent urination data. For example, if it is estimated that the toilet user is dehydrated, the notification means 17 transmits highlight information indicating that the toilet user is estimated to be dehydrated to the toilet user's terminal device.

[0099] Note that the above information is merely an example, and any information indicating the health condition of the toilet user can be used as the highlight information. Furthermore, if the number of urinations based on the urination data is below a predetermined number, the notification means 17 will not notify the specified destination of the highlight information. For example, if the number of urinations by the toilet user is below a predetermined number, the notification means 17 will not send the highlight information to the toilet user's terminal device.

[0100] Notification means 17 notifies a predetermined destination of recommendation information (recommended information) for improving the health condition of the toilet user based on urination data for a predetermined period, including the most recent urination data. For example, if notification means 17 determines that the toilet user is dehydrated, it transmits recommendation information for the toilet user to improve dehydration, such as information indicating a lifestyle pattern for improving dehydration, to the toilet user's terminal device.

[0101] Note that the above information is merely an example, and any information that improves the health condition of the toilet user can be used as the recommendation information. Furthermore, if the number of urinations based on the urination data is below a predetermined number, the notification means 17 will not notify the recommendation information to a predetermined destination. For example, if the number of urinations by the toilet user is below a predetermined number, the notification means 17 will not send the recommendation information to the toilet user's terminal device.

[0102] Notification means 17 notifies a predetermined destination of next recommended information that is generated based on predetermined input information in response to the recommended information received by the toilet user. For example, notification means 17 may receive information indicating the toilet user's behavior (reaction) in response to the recommended information as feedback, and notify the toilet user of recommended information that is suitable for the toilet user based on the received feedback. For example, if the toilet user takes action (reacts) in response to recommended information for improving dehydration, notification means 17 may notify the toilet user of more detailed information for improving dehydration as the next recommended information.

[0103] For example, when notification means 17 acquires input information (behavioral information) from the toilet user indicating that the toilet user has performed an operation to select recommended information, it may generate more detailed information about the recommended information and transmit the generated information to the toilet user's terminal device as the next recommended information.For example, when notification means 17 acquires input information (behavioral information) from the toilet user indicating that the toilet user has performed a search using a keyword related to the recommended information, it may generate more detailed information about the recommended information and transmit the generated information to the toilet user's terminal device as the next recommended information.

[0104] The above process is merely an example, and the notification means 17 may determine the next recommended information for the toilet user based on the toilet user's behavior (reaction) to the recommended information and provide it to the toilet user.

[0105] The frequent urination estimation means 18 executes estimation processing to estimate various information related to the health of the toilet user. The frequent urination estimation means 18 executes estimation processing to estimate the frequent urination of the toilet user. The frequent urination estimation means 18 executes estimation processing related to the frequent urination described above.

[0106] The frequent urination estimation means 18 estimates the frequent urination of the toilet user based on the urination data. The frequent urination estimation means 18 estimates frequent urination when the urination interval is shorter than a predetermined period.

[0107] The urination frequency estimation means 18 estimates the urination frequency of the toilet user based on the urination data in the data storage means 14. The urination frequency estimation means 18 estimates the urination frequency of the toilet user based on the urination data stored by the data storage means 14. The urination frequency estimation means 18 estimates the urination frequency based on the urine volume or urine flow rate per night, or the average urine volume or average urine flow rate during the night, using the urination information and nighttime urination information specified by other urination information.

[0108] The frequent urination estimation means 18 estimates frequent urination based on daytime and nighttime urination data specified by the urination information and other urination information. The frequent urination estimation means 18 estimates frequent urination based on the daytime urine volume or urine flow rate per urination and the nighttime urine volume or urine flow rate per urination.

[0109] The urination frequency estimation means 18 estimates urination frequency based on the daytime average urine volume or average urine flow rate and the nighttime average urine volume or average urine flow rate. The urination frequency estimation means 18 estimates urination frequency using the urination information and nighttime urination information identified from other urination information when there are multiple urinations at night and the relationship between the urine volume or urine flow rate per urination and the interval between urination times satisfies a predetermined condition.

[0110] The urination frequency estimation means 18 may generate urination data by analyzing information collected by detection by the sensor device 12. In this case, the urination frequency estimation means 18 estimates urination frequency using the urination data generated from the information collected by detection by the sensor device 12. For example, the urination frequency estimation means 18 estimates urination frequency using urination information related to urine volume or urine flow rate and other urination information including at least one of information related to urination time, urination frequency, or urination frequency.

[0111] For example, if a comparison result between the amount of urine a toilet user makes per daytime visit and the amount of urine a toilet user makes per nighttime visit satisfies a predetermined condition, frequent urination estimation means 18 estimates that the toilet user has frequent urination. For example, frequent urination estimation means 18 estimates that the toilet user has frequent urination if the difference between the amount of urine a toilet user makes per daytime visit and the amount of urine a toilet user makes per nighttime visit is equal to or greater than a predetermined value.

[0112] For example, if the comparison result between the toilet user's average daytime urine volume and the toilet user's average nighttime urine volume satisfies a predetermined condition, the frequent urination estimation means 18 estimates that the toilet user has frequent urination. For example, if the difference between the toilet user's average daytime urine volume and the toilet user's average nighttime urine volume is equal to or greater than a predetermined value, the frequent urination estimation means 18 estimates that the toilet user has frequent urination.

[0113] For example, the frequent urination estimation means 18 identifies (generates) nighttime urination information using urination information related to urine volume or urine flow rate and other urination information including at least one of information on urination time, urination frequency, or urination frequency. For example, the frequent urination estimation means 18 references the toilet user's nighttime urination information and estimates that the toilet user has frequent urination if the toilet user has urinated multiple times during the night and the relationship between the toilet user's urine volume per urination and the interval between urination times satisfies a predetermined condition. For example, the frequent urination estimation means 18 estimates that the toilet user has frequent urination if the toilet user has urinated multiple times during the night and the value calculated from the toilet user's urine volume per urination and the interval between urination times satisfies a predetermined condition.

[0114] Furthermore, the urination frequency estimation means 18 may estimate various types of urination frequency for a toilet user, not limited to nocturia. For example, the urination frequency estimation means 18 may estimate the urination frequency of a toilet user during the day (periods other than nighttime). For example, the urination frequency estimation means 18 may estimate the urination frequency of a toilet user during the hours when the toilet user is sleeping (frequent urination during bedtime). For example, if the toilet user's bedtime in their lifestyle pattern is not nighttime, the urination frequency estimation means 18 may estimate the urination frequency during bedtime for that user. Note that bedtime here refers to, for example, the period from when the toilet user goes to sleep until they wake up (the time period when they are sleeping). When estimating the urination frequency of a toilet user during the hours when the toilet user is sleeping, the urination frequency estimation means 18 may estimate the urination frequency of a toilet user by processing for estimating nocturia.

[0115] For example, the frequent urination estimation means 18 may estimate the toilet user's frequent urination during the time period when the toilet user is asleep, by replacing "nighttime" in the processing for nocturia with "bedtime" and performing the same processing as in the estimation of nocturia. Furthermore, when information other than "bedtime" is also used, the frequent urination estimation means 18 may estimate the toilet user's frequent urination during the time period when the toilet user is asleep, by replacing "nighttime" in the processing for nocturia with "bedtime" and "daytime" with "other than bedtime" and performing the same processing as in the estimation of nocturia. Note that the frequent urination estimation means 18 may be integrated with the dehydration estimation means 15. The dehydration estimation means 15 may have the function of the frequent urination estimation means 18 and may execute the processing of the frequent urination estimation means 18. In this case, the dehydration estimation device 13 does not need to have the frequent urination estimation means 18.

[0116] For example, the information processing units such as the dehydration estimation means 15, the evaluation means 16, the notification means 17, and the frequent urination estimation means 18 may be the control unit 130 described later. For example, the information processing units such as the dehydration estimation means 15, the evaluation means 16, the notification means 17, and the frequent urination estimation means 18 may execute the processes executed by the control unit 130 described later.

[0117] <1-3. Processing flow> An example of a processing flow executed by the toilet system will now be described with reference to Figures 2 and 3. Figure 2 is a flowchart showing an example of the processing procedure executed by the toilet system. Figure 3 is a diagram showing an example of information used by the toilet system for processing. For example, the urination data used by the toilet system 1 includes, as a urination record, information such as the user's name, date and time, urine volume, and urine color. The urination data may also include information such as urine flow rate and excretion posture.

[0118] In the following, an example will be described in which the user U1 is the subject of the estimation process (the toilet user). Also, although the toilet system 1 will be described as the processing subject, the following process may be performed by any of the devices, such as the sensor device 12, the dehydration estimation device 13, or the toilet device 20, depending on the device configuration included in the toilet system 1.

[0119] 2, the toilet system 1 determines whether or not the user U1, who is the subject of the estimation process, is at home (step S11). For example, the toilet system 1 determines whether or not the user U1 is at his or her home. Note that the space where the toilet device 20 is located is not limited to a home, and may be any space such as a facility for the elderly.

[0120] For example, the toilet system 1 determines whether the user U1 is at home using external data based on GPS or the like. For example, if the position of the user U1 detected by GPS or the like is within a predetermined range from the position of the user U1's house, the toilet system 1 determines that the user U1 is at home.

[0121] Note that the above is merely an example, and the toilet system 1 may determine whether the user U1 is at home using various information as appropriate. For example, the toilet system 1 may determine whether the user U1 is at home based on information input by the user U1. Furthermore, when performing processing using data on urination by the user U1 outside the home, the toilet system 1 may skip the determination in step S11 and perform processing from step S12 onwards. In other words, the toilet system 1 may perform processing using any information that can be processed, for example, performing processing using at least one of urination at the user U1's home and urination outside the user U1's home.

[0122] If the user U1, who is the subject of the estimation process, is not at home (step S11: No), the toilet system 1 repeats the process of step S11.

[0123] When the user U1, who is the subject of the estimation process, is at home (step S11: Yes), the toilet system 1 determines whether or not the user U1 has urinated (step S12). For example, when the user U1, who is the subject of the estimation process, is at home, the toilet system 1 determines whether or not the user U1 has urinated.

[0124] If there is no urination (step S12: No), the toilet system 1 makes a determination based on the urination interval (step S13). For example, if user U1 urinates, the toilet system 1 makes a determination based on comparing user U1's urination interval with a standard. For example, the toilet system 1 may use a standard depending on the subject of the estimation process. For example, the toilet system 1 may set a standard for user U1 based on user U1's past urination interval. For example, if user U1's usual urination interval is long, the toilet system 1 may use a standard for subjects with longer urination intervals, or if user U1's usual urination interval is short, the toilet system 1 may use a standard for subjects with shorter urination intervals.

[0125] For example, the toilet system 1 may use information such as the data DT2 in FIG. 3 to set a standard for a subject of the estimation process based on urination characteristics according to generation, season, etc. The vertical axis of the data DT2 corresponds to the urination volume, and the horizontal axis corresponds to the urination interval. The data DT2 in FIG. 3 shows an example of a distribution over the past three years. For example, if user U1 is in his / her 50s, the toilet system 1 may set a standard based on information about the urination characteristics of each season of the 50s. For example, if the season is summer, the toilet system 1 may determine whether user U1's urination interval is long or short by comparing the urination characteristics of summers in their 50s over the past three years with user U1's urination this summer (the most recent summer result). For example, if the season is winter, the toilet system 1 may determine whether user U1's urination interval is long or short over a long period, such as the past three years, by comparing the urination characteristics of winters in their 50s over the past three years with user U1's urination this winter (the most recent winter result).

[0126] Furthermore, if information indicating the trend of user U1's own seasonal urination characteristics over the past few years (e.g., three years) (such as the trend of the user over several years in FIG. 3 ) is available, the toilet system 1 may set the criteria based on the information on user U1's own seasonal urination characteristics over the past few years (e.g., three years). For example, if the season is summer, the toilet system 1 may determine whether user U1's urination interval is long or short by comparing the trend of user U1's own summer urination characteristics over the past three years with user U1's urination this summer (the result of the most recent summer). For example, if the season is winter, the toilet system 1 may determine whether user U1's urination interval over a long period, such as the past three years, is long or short by comparing the trend of user U1's own winter urination characteristics over the past three years with user U1's urination this winter (the result of the most recent winter).

[0127] If the urination interval is short (step S13: short), the toilet system 1 estimates it as OK (no problem) (step S14) and returns to step S11 to perform the process. For example, if the urination interval of user U1 is less than a threshold based on the user U1's past urination intervals (e.g., an average value), the toilet system 1 returns to step S11 to repeat the process for user U1. Note that when returning to step S11 to repeat the process, the toilet system 1 may also execute a frequent urination estimation algorithm in parallel. For example, if the urination interval of user U1 is short, the toilet system 1 executes a process to estimate frequent urination for user U1 in parallel, and returns to step S11 to perform the process. Note that the toilet system 1 does not have to execute the frequent urination estimation algorithm.

[0128] If the urination interval is long (step S13: Long), the toilet system 1 estimates that the user U1 is dehydrated and issues an alert (step S21). For example, if the urination interval is long, the toilet system 1 estimates that the user U1 may be dehydrated and evaluates the user U1's dehydration. As a result, the toilet system 1 evaluates (classifies) the user U1 as dehydrated, category #3, and issues an alert according to the evaluation (classification). For example, the toilet system 1 uses information such as that shown in data DT3 in FIG. 3 to evaluate (classify) the user U1's dehydration state as "high level of caution" and transmits alert information indicating that the dehydration level is level 5 on a five-point scale to the user U1's terminal device.

[0129] If urination has occurred (step S12: Yes), the toilet system 1 performs a most recent comparison of the urination interval (step S15). For example, if urination has occurred, the toilet system 1 performs a comparison using the most recent urination interval, such as the most recent week. For example, the toilet system 1 performs a comparison using the most recent urination interval of the user U1 and a recent comparison standard, such as a threshold based on the average value of the most recent urination interval. For example, the toilet system 1 may use external data based on GPS or the like to estimate whether the user U1 is indoors or outdoors, and set the most recent comparison standard (threshold) based on the estimated user U1 environment. For example, the toilet system 1 may set the most recent comparison standard (threshold) based on the season, room temperature, etc.

[0130] For example, the toilet system 1 may use information such as the data DT1 in FIG. 3 to set a standard for the subject of the estimation process based on the urination characteristics of each generation. The vertical axis of the data DT1 corresponds to the urination volume, and the horizontal axis corresponds to the urination interval. For example, if user U1 is in his / her 50s, the toilet system 1 may set a standard based on information about the urination characteristics of people in their 50s. In this case, the toilet system 1 may compare the urination characteristics of people in their 50s with user U1's urination interval (the current result) to determine whether user U1's urination interval in a short period, such as the most recent period, is long or short.

[0131] Furthermore, if information indicating the recent tendency of the user U1's own urination characteristics (such as the recent tendency in FIG. 3) is available, the toilet system 1 may set the criteria based on the information on the user U1's own urination characteristics. In this case, the toilet system 1 may compare the recent tendency of the user U1's own urination characteristics with the user U1's urination interval (the current result) to determine whether the user U1's urination interval in a short period, such as the most recent period, is long or short.

[0132] If the most recent urination interval is not long (step S15: No), the toilet system 1 performs the process of step S18. On the other hand, if the most recent urination interval is long (step S15: Yes), the toilet system 1 determines whether the urination interval is consecutive (step S16). For example, if the toilet system 1 determines that the most recent urination interval is long for two or more consecutive urinations, it determines that the urination interval is consecutive. Note that the number of times (reference value) used to determine whether the urination interval is consecutive is not limited to two, and may be three or more.

[0133] If the occurrences are consecutive (step S16: Yes), the toilet system 1 sets the level of caution to +a (step S17) and performs the process of step S 18. For example, if the occurrences are consecutive, the toilet system 1 sets a flag to set the level for evaluation (classification) to +a.

[0134] If the timings are not consecutive (step S16: No), the toilet system 1 performs the process of step S18. The toilet system 1 makes a determination based on the amount of urine voided (step S18). For example, the toilet system 1 makes a determination based on a comparison between the amount of urine voided by the user U1 and a standard. The standard may be set according to the urination interval. For example, the toilet system 1 may use information such as data DT1, DT2, etc. shown in FIG. 3 to set a standard according to the subject of the estimation process based on urination characteristics based on factors such as generation and season.

[0135] If the amount of urine is small (step S18: small), the toilet system 1 makes a determination based on the urine color (step S19). For example, if the amount of urine excreted by the user U1 is less than a standard (a predetermined amount, etc.), the toilet system 1 makes a determination based on the urine color.

[0136] If the urine color is light (step S19: light), the toilet system 1 estimates that the user U1 is dehydrated and performs the process of step S21. For example, if the color of the user U1's urine is less than a predetermined threshold, the toilet system 1 evaluates (classifies) the user U1 as dehydrated, category #1, and issues an alert according to the evaluation (classification). For example, the toilet system 1 uses information such as that shown in data DT3 in FIG. 3 to evaluate (classify) the user U1's dehydration state as "low" and transmits alert information indicating that the dehydration level is level 1 or level 2 on a five-level scale to the user U1's terminal device.

[0137] For example, if the toilet system 1 does not perform the processing of step S17 and has not set the warning level to +a, it classifies the dehydration state of user U1 to level 1 of the "low" warning level and transmits alert information indicating level 1 to the terminal device of user U1. For example, if the toilet system 1 has set the warning level to +a by the processing of step S17, it classifies the dehydration state of user U1 to level 2 of the "low" warning level and transmits alert information indicating level 2 to the terminal device of user U1.

[0138] If the urine color is dark (step S19: dark), the toilet system 1 estimates that the user U1 is dehydrated and performs the process of step S21. For example, if the color of the user U1's urine is darker than a predetermined threshold, the toilet system 1 evaluates (classifies) the user U1 as dehydrated (category #2) and issues an alert according to the evaluation (classification). For example, the toilet system 1 uses information such as that shown in data DT3 in FIG. 3 to evaluate (classify) the user U1's dehydration state as "medium" and transmits alert information to the user U1's terminal device indicating that the dehydration level is level 3 or level 4 on a five-level scale.

[0139] For example, if the toilet system 1 does not perform the processing of step S17 and has not set the warning level to +a, it classifies the dehydration state of user U1 to level 3 of the "medium" warning level and transmits alert information indicating level 3 to the terminal device of user U1. For example, if the toilet system 1 has set the warning level to +a by the processing of step S17, it classifies the dehydration state of user U1 to level 4 of the "medium" warning level and transmits alert information indicating level 4 to the terminal device of user U1.

[0140] If the amount of urine is large (step S18: large), the toilet system 1 estimates it as OK (no problem) (step S20) and ends the process. For example, if the amount of urine voided by user U1 is equal to or greater than a standard (predetermined amount, etc.), the toilet system 1 estimates that user U1 is unlikely to be dehydrated and ends the process without issuing an alert. The toilet system 1 may execute a frequent urination estimation algorithm in parallel with the process of step S20. For example, if the amount of urine voided by user U1 is large, the toilet system 1 may start executing a process to estimate frequent urination for user U1 in parallel. The toilet system 1 does not have to execute the frequent urination estimation algorithm.

[0141] The above-described flowchart is merely an example, and the toilet system 1 may perform processing according to any flow as long as it is possible to estimate dehydration of the toilet user.

[0142] In the following, specific processing examples according to the sensors used will be described as second to fifth embodiments, assuming the above-described configuration and processing. For example, the second and third embodiments show examples in which a vibration detection sensor is used, the fourth embodiment shows an example in which a sound sensor is used, and the fifth embodiment shows an example in which a radio wave sensor is used. Note that in each of the following embodiments, explanations of points similar to those described in the first embodiment will be omitted as appropriate.

[0143] 2. Second embodiment <2-1. Toilet system configuration> First, the configuration of the toilet system according to the second embodiment will be described with reference to Fig. 4. Fig. 4 is a perspective view showing an example of the configuration of the toilet system according to the second embodiment.

[0144] As shown in Fig. 4, the toilet system 1 includes a toilet seat device 2 and an operating device 10. As shown in Fig. 4, a toilet bowl 7 is installed on a floor surface F in a toilet room R. In the following, the direction facing the interior of the toilet room R from the floor surface F will be described as "up."

[0145] The toilet bowl 7 is, for example, a ceramic toilet bowl. The toilet bowl 7 is formed with a bowl portion 8. The bowl portion 8 is concave downwards and is the portion that receives the user's excrement. The toilet bowl 7 is not limited to a floor-standing type as shown in the figure, and may be of any type as long as the toilet system 1 is applicable, such as a wall-mounted type. The toilet bowl 7 is provided with a rim portion 9 around the entire edge of the opening facing the bowl portion 8. In the toilet room R, for example, a flush water tank that stores flush water may be installed near the toilet bowl 7, or a so-called tankless type may be used in which no flush water tank is installed.

[0146] For example, when a user operates a flushing operation unit (not shown) for flushing provided in the toilet room R, toilet flushing is performed by supplying flush water to the bowl 8 of the toilet 7. The flushing operation unit may be an operation lever or a touch operation on a toilet flushing object displayed on the operation device 10. Note that the flushing operation unit is not limited to an operation lever or the like that causes toilet flushing to be performed manually by the user, but may also be one that causes toilet flushing to be performed by a human body detection sensor that detects the user, such as a seat sensor.

[0147] The toilet seat device 2 is attached to the top of the toilet bowl 7 and comprises a main body 3, a toilet lid 4, a toilet seat 5, and a flushing nozzle 6. The toilet seat device 2 is placed on top of the toilet bowl 7, which is formed with a bowl 8 that receives excrement. The toilet seat device 2 is placed on top of the toilet bowl 7 so that the flushing nozzle 6 advances into the bowl 8 before spraying flushing water. The toilet seat device 2 may be attached detachably to the toilet bowl 7, or may be attached so as to be integrated with the toilet bowl 7.

[0148] As shown in FIG. 4, the toilet seat 5 is formed in an annular shape with an opening 50 in the center, and is positioned along the rim portion 9 so as to overlap the opening of the toilet bowl 7. A user sits on the toilet seat 5. The toilet seat 5 functions as a seating portion that supports the buttocks of the seated user. Also, as shown in FIG. 4, one end of each of the toilet lid 4 and toilet seat 5 is pivotally supported by the main body portion 3, and they are attached so as to be rotatable (openable and closable) around the pivotal portion of the main body portion 3. The toilet lid 4 is attached to the toilet seat device 2 as needed, and the toilet seat device 2 does not necessarily have to have a toilet lid 4.

[0149] The cleaning nozzle 6 is a nozzle for discharging water for cleaning. The cleaning nozzle 6 is capable of spraying cleaning water. The cleaning nozzle 6 is capable of spraying cleaning water toward the user. The cleaning nozzle 6 is a nozzle for cleaning private parts. The cleaning nozzle 6 is configured to be able to advance and retreat relative to the main body cover 30, which is the housing of the main body 3, by driving a driving source such as an electric motor (such as the nozzle motor 61 in FIG. 8). The cleaning nozzle 6 is also connected to a water source such as a water pipe (not shown). When the cleaning nozzle 6 is in an advanced position (also referred to as the "advanced position") relative to the main body cover 30, which is the housing of the main body 3, as shown in FIG. 4, it sprays water from the water source onto the user's body to clean the private parts.

[0150] 4 shows the state in which the cleaning nozzle 6 is in the advanced position. The cleaning nozzle 6 may also be used to clean the inside of the toilet bowl 7 (bowl portion 8, etc.). The cleaning nozzle 6 may be used to be switchable between a private parts cleaning mode in which the private parts of the user are cleaned, and a toilet bowl cleaning mode in which water is sprayed inside the toilet bowl 7. For example, the cleaning nozzle 6 may be used to be switchable between the private parts cleaning mode and the toilet bowl cleaning mode in accordance with the control by the toilet seat device 2.

[0151] The operating device 10 is provided in the toilet room R. The operating device 10 is provided in a position where it can be operated by a user. The operating device 10 is provided in a position where it can be operated by a user when seated on the toilet seat 5. In FIG. 4, the operating device 10 is provided on a wall surface W on the right side as seen from a user seated on the toilet seat 5. Note that the operating device 10 may be provided in various ways, not just on a wall surface, as long as it is usable by a user seated on the toilet seat 5. For example, the operating device 10 may be provided integrally with the toilet seat apparatus 2.

[0152] The operating device 10 is connected to the toilet seat device 2 via a predetermined network so as to be able to communicate with the toilet seat device 2 via a wired or wireless connection. For example, the toilet seat device 2 and the operating device 10 may be connected in any manner as long as they are able to send and receive information, and may be connected to each other so as to be able to communicate with each other via a wired connection or a wireless connection.

[0153] The operation device 10 accepts various operations from a user via a display surface (for example, a display screen 11) using, for example, a touch panel function. The operation device 10 may also be provided with switches and buttons, and may accept various operations via the switches and buttons. The display screen 11 is a display screen of a tablet terminal or the like realized by, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display, and is a display device for displaying various information. That is, the operation device 10 accepts input from the user via the display screen 11 and also outputs information to the user. At this time, the operation device 10 identifies which pre-registered user the user is. Thereafter, the control unit 130 links the user information with information related to excrement or information obtained from the information related to excrement, which will be described later, and transmits the information to the user's terminal. At this time, information on the date and time when the information related to excrement was obtained may also be transmitted to the user's terminal. The display screen 11 is a display device for displaying various information.

[0154] The operation device 10 accepts a user's operation to stop a control being executed by the toilet seat device 2. The operation device 10 accepts a user's operation to start private parts washing by the toilet seat device 2. The operation device 10 accepts a user's instruction to the cleaning nozzle 6. The operation device 10 accepts a user's operation to cause the toilet seat device 2 to output a predetermined sound. The operation device 10 accepts a user's operation to perform a sterilization process to sterilize the cleaning nozzle 6 (see FIG. 4) of the toilet seat device 2 with disinfectant water. The operation device 10 accepts a user's operation to adjust the force of water spray during private parts washing by the toilet seat device 2. The operation device 10 accepts a user's operation to adjust the volume of the sound output by the toilet seat device 2. The operation device 10 accepts a user's operation to select a language when information regarding toilet usage is displayed on the operation device 10 or output as audio.

[0155] For example, the operation device 10 may display the above-described object that accepts the user's operation on the display screen 11, and execute various processes in response to the user's touch on the displayed object. For example, the operation device 10 may have a switch, button, etc. that accepts the above-described user's operation, and execute various processes in response to the user's touch on the switch, button, etc. Note that the above is just an example, and the operation device 10 may also accept a user's operation that executes various processes.

[0156] The toilet system 1 estimates the dehydration of the user (toilet user) using various configurations and processes described below. The toilet system 1 may provide information to a terminal device such as the user's smartphone based on the estimated information. The toilet system 1 may also provide information to an operating device 10 (or a display screen 11) in the toilet room R based on the calculated information.

[0157] <2-2. Configuration of the toilet seat device> Next, the configuration of the toilet seat device 2 will be described with reference to Fig. 5 and Fig. 6. Fig. 5 and Fig. 6 are perspective views showing an example of the configuration of a toilet seat device according to a second embodiment. Specifically, Fig. 5 is a view showing a state in which the lid part 110 of the toilet seat device 2 is closed (also referred to as a "closed state"). Also, Fig. 6 is a view showing a state in which the lid part 110 of the toilet seat device 2 is removed.

[0158] 5, when the lid 110 is in the closed state, the vibration detection sensor 34 is hidden behind the lid 110. When the lid 110 is in the closed state, the lid 110 is located in front of the vibration detection sensor 34. In this way, the lid 110 is located in front of the vibration detection sensor 34 when in the closed state.

[0159] 5 shows the cleaning nozzle 6 (see FIG. 4) in a position (also referred to as the "storage position") where it is stored within the main body cover 30. As shown in FIG. 5, when the cleaning nozzle 6 is in the storage position, the nozzle cover 60 is closed, and the cleaning nozzle 6 is hidden behind the nozzle cover 60. When cleaning is performed using the cleaning nozzle 6, the nozzle cover 60 is opened, and the cleaning nozzle 6 protrudes from the opening for the cleaning nozzle 6 in the main body cover 30, and the cleaning nozzle 6 transitions to an advanced state.

[0160] As shown in FIG. 6, when the lid 110 is removed, the vibration detection sensor 34 is exposed from the opening 31 of the main body cover 30. For example, when the lid 110 is open (also referred to as the "open state"), as shown in FIG. 6, the lid 110 is not positioned in front of the vibration detection sensor 34. As a result, when the lid 110 is in the open state, the vibration detection sensor 34 is exposed. When the lid 110 is in the open state, the vibration detection sensor 34 can detect the vibration of the seal water in the toilet bowl 7. Note that the toilet seat device 2 does not have to have the lid 110. In this case, the toilet seat device 2 does not have the lid 110 and the actuator 111, and the vibration detection sensor 34 may be always exposed.

[0161] Here, an example of vibration detection by the vibration detection sensor 34 will be described with reference to Fig. 7. Fig. 7 is a side cross-sectional view showing an example of the configuration of a toilet seat device according to the second embodiment. In the example of Fig. 7, the hatched areas in the bowl portion 8 of the toilet 7 are filled with seal water (water), and the seal water surface WS in Fig. 7 indicates the upper surface of the seal water.

[0162] In the example of Figure 7, the lid portion 110 is in an open position, exposing the vibration detection sensor 34. The vibration detection sensor 34 detects the vibration of the water seal surface WS of the water seal in the toilet bowl 7. The detection range DA1 in Figure 7 indicates the range detected by the vibration detection sensor 34. With this configuration, the toilet system 1 is able to detect the vibration of the water seal by the vibration detection sensor 34. Note that the detection range DA1 shown in Figure 7 is merely an example, and the vibration detection sensor 34 can be positioned in any manner as long as it is able to detect the vibration of at least a portion of the water seal surface WS.

[0163] 5 to 7 show an example of a configuration in which the toilet seat device 2 has the vibration detection sensor 34 disposed adjacent to the washing nozzle 6, but the vibration detection sensor 34 is not limited to being disposed adjacent to the washing nozzle 6 and may be disposed in various positions as long as the desired detection is possible. For example, the vibration detection sensor 34 is disposed in a position that suits the detection mode of the sensor used, depending on the type of sensor. FIG. 7 shows an example of a position in which the vibration detection sensor 34 is a non-contact type sensor, but if the vibration detection sensor 34 is a contact type sensor, for example, the vibration detection sensor 34 may be disposed in a position that comes into contact with the seal water in the bowl portion 8 of the toilet seat 5. Examples of sensors used for the vibration detection sensor 34 will be described later.

[0164] <2-3. Functional configuration of the toilet seat device> Next, the functional configuration of the toilet seat device 2 will be described with reference to Fig. 8. Fig. 8 is a block diagram showing an example of the configuration of a toilet seat device according to a second embodiment. As shown in Fig. 8, the toilet seat device 2 includes a human body detection sensor 32, a seating detection sensor 33, a shaking detection sensor 34, a control device 100, a nozzle motor 61, a flushing nozzle 6, a solenoid valve 71, a lid 110, and an actuator 111. Note that Fig. 8 omits illustration of some of the configuration of the toilet seat device 2 described in Fig. 4 (such as the main body 3, toilet seat 5, and toilet bowl 7).

[0165] 8 is merely an example, and the toilet seat device 2 can have any configuration. The human body detection sensor 32, seating detection sensor 33, vibration detection sensor 34, control device 100, etc. are arranged in any desired locations. For example, the vibration detection sensor 34 is provided in the main body 3 of the toilet seat device 2. The toilet seat device 2 transmits and receives information to and receives information from an information processing device such as the operating device 10 via a predetermined network (such as the Internet) in a wired or wireless manner using a communication device (such as the communication unit 101 of the control device 100 in FIG. 9).

[0166] The human body detection sensor 32 has a function of detecting a human body. For example, the human body detection sensor 32 is realized by a pyroelectric sensor using an infrared signal. For example, the human body detection sensor 32 may be realized by a μ (microwave) wave sensor. Note that the above is just an example, and the human body detection sensor 32 is not limited to the above and may detect a human body by various means. For example, the human body detection sensor 32 detects a person (such as a user) who enters the toilet room R (see FIG. 4). The human body detection sensor 32 outputs a detection signal to the control device 100.

[0167] The seating detection sensor 33 has a function of detecting a person sitting on the toilet seat device 2. The seating detection sensor 33 detects that a user is sitting on the toilet seat 5. The seating detection sensor 33 can detect that a user is sitting on the toilet seat 5. The seating detection sensor 33 also functions as a seat-leaving detection sensor that detects that a user has left the toilet seat 5. The seating detection sensor 33 detects the seated state of the user on the toilet seat 5.

[0168] For example, the seating detection sensor 33 detects that a user has sat on the toilet seat 5 using a load sensor. For example, the seating detection sensor 33 is an infrared light emitting / receiving distance measuring sensor, and may detect a human body present near the toilet seat 5 just before the person (user) sits on the toilet seat 5, or the user sitting on the toilet seat 5. Note that the above is just one example, and the seating detection sensor 33 may detect that a person has sat on the toilet seat device 2 by various means other than the above. The seating detection sensor 33 outputs a seating detection signal to the control device 100.

[0169] The vibration detection sensor 34 is a sensor that detects vibration. The vibration detection sensor 34 detects the vibration of the seal water in the toilet bowl 7. The vibration detection sensor 34 can have any configuration as long as it can detect the desired vibration. The vibration detection sensor 34 may be a non-contact sensor. For example, FIG. 7 shows a case where the vibration detection sensor 34 is a non-contact sensor. In this case, the vibration detection sensor 34 may be a camera, a line sensor, an ultrasonic sensor, an infrared sensor, etc. The vibration detection sensor 34 may also be a contact sensor. In this case, the vibration detection sensor 34 may be a float sensor, a pressure sensor, etc. Note that the above is merely an example, and any sensor may be used as the vibration detection sensor 34 as long as it can detect the desired vibration.

[0170] Furthermore, when the toilet system 1 detects the presence or absence of feces, the vibration detection sensor 34 may function as a feces detection means for detecting the presence or absence of feces. For example, if an imaging means such as a camera or a line sensor is used as the vibration detection sensor 34, the vibration detection sensor 34 may function as the feces detection means. The toilet system 1 may also have a feces detection means separate from the vibration detection sensor 34. In this case, the toilet system 1 may have an imaging means for imaging the inside of the bowl portion 8 as the feces detection means for detecting the presence or absence of feces. For example, the feces detection means may be a line sensor arranged facing the inside of the bowl portion 8, and may detect fallen objects such as excrement falling within the bowl portion 8. Alternatively, the feces detection means may be a camera arranged facing the water seal in the bowl portion 8, and may detect fallen objects such as excrement that have landed on the water seal.

[0171] The control device 100 controls various components and processes. The control device 100 is a computer (information processing device) that executes various information processing such as calculating the time the user is urinating (urination time) and the amount of urine (urine volume) excreted by the user. The control device 100 calculates the urination time based on the vibration of the water seal surface of the bowl portion 8 of the toilet stool 7 that receives the excrement. For example, the control device 100 calculates the urination time based on the time the water seal surface of the bowl portion 8 of the toilet stool 7 that receives the excrement vibrates by a predetermined value or more. The control device 100 calculates the total urine volume based on the calculated urination time and the urine volume per unit time (also called "unit urine volume") stored in the memory unit.

[0172] The control device 100 also controls various components of the toilet system 1. The control device 100 controls the nozzle motor 61, the solenoid valve 71, and the actuator 111. The control device 100 controls the nozzle motor 61, the solenoid valve 71, and the actuator 111 based on signals transmitted from the operating device 10.

[0173] The control device 100 controls the nozzle motor 61 based on a control instruction signal related to local cleaning transmitted from the operation device 10. The control device 100 controls the nozzle motor 61 to advance and retract the cleaning nozzle 6. The control device 100 controls the opening and closing of the solenoid valve 71.

[0174] The control device 100 controls the actuator 111 to open and close the lid portion 110. The control device 100 transmits control information to the actuator 111 to put the lid portion 110 in an open state. The control device 100 transmits control information to the actuator 111 to put the lid portion 110 in a closed state. The control device 100 controls the lid portion 110 to be in a closed state while the vibration detection sensor 34 is not detecting vibration, such as before the user uses the toilet bowl 7.

[0175] The control device 100 transmits control information to the nozzle motor 61, the solenoid valve 71, and the actuator 111 via wires. The control device 100 may also transmit control information to the nozzle motor 61, the solenoid valve 71, and the actuator 111 wirelessly. For example, if the control device 100 is configured as a device separate from the toilet seat device 2, it may transmit control information for the nozzle motor 61, the solenoid valve 71, and the actuator 111 wirelessly to the toilet seat device 2. In this case, the nozzle motor 61, the solenoid valve 71, and the actuator 111 may be controlled based on the control information received by the control device of the toilet seat device 2.

[0176] The control device 100 controls the opening and closing operation of the lid portion 110. The control device 100 opens the lid portion 110 when a user starts using the toilet bowl 7 as detected by the human body detection sensor 32 or the seating detection sensor 33, and closes the lid portion 110 when the user finishes using the toilet bowl 7 as detected by the human body detection sensor 32 or the seating detection sensor 33. The control device 100 also opens the lid portion 110 when the seating detection sensor 33 detects that the user has sat on the toilet seat 5, and closes the lid portion 110 when the seating detection sensor 33 detects that the user has left the toilet seat 5. For example, the control device 100 opens the lid portion 110 when the human body detection sensor 32 detects that the user has entered the toilet room R, and closes the lid portion 110 when the human body detection sensor 32 detects that the user has left the toilet room R.

[0177] Note that the opening and closing of the lid portion 110 described above is merely an example, and the control device 100 may control the opening and closing of the lid portion 110 based on various information. The control device 100 may open the lid portion 110 when the human body detection sensor 32 detects that a user is approaching the toilet bowl 7. For example, the control device 100 may open the lid portion 110 when it detects that the user is located within a predetermined range (e.g., 50 cm) from the toilet bowl 7. Furthermore, the control device 100 closes the lid portion 110 when the human body detection sensor 32 detects that the user has moved away from the toilet bowl 7. For example, the control device 100 closes the lid portion 110 when it detects that the user is located outside the predetermined range (e.g., 50 cm) from the toilet bowl 7.

[0178] The control device 100 closes the lid portion 110 in response to a user's instruction to operate the cleaning nozzle 6 via the operating device 10. The control device 100 closes the lid portion 110 in response to the operation of the cleaning nozzle 6. The control device 100 controls the lid portion 110 based on the user's operation of the operating device 10, which controls the cleaning nozzle 6. The control device 100 detects the operation of the cleaning nozzle 6 (the nozzle advancing into the bowl portion 8) and controls the lid portion 110.

[0179] The control device 100 controls the lid part 110 to open upward when placed on the toilet bowl 7. The control device 100 controls the lid part 110 to close when the cleaning nozzle 6 is in operation. The control device 100 controls the lid part 110 to close when the cleaning nozzle 6 arranged on the toilet bowl 7 is in operation.

[0180] The control device 100 may also control the vibration detection sensor 34. In this case, the vibration detection sensor 34 starts or stops detection in accordance with the control of the control device 100. The control device 100 transmits control information to the vibration detection sensor 34 to control the start or end of detection by the vibration detection sensor 34. For example, when the human body detection sensor 32 or the seating detection sensor 33 detects that a user has started using the toilet 7, the control device 100 transmits control information to the vibration detection sensor 34 to cause the vibration detection sensor 34 to start detection. For example, when the human body detection sensor 32 or the seating detection sensor 33 detects that a user has finished using the toilet 7, the control device 100 transmits control information to the vibration detection sensor 34 to cause the vibration detection sensor 34 to end detection.

[0181] The control device 100 also controls the toilet lid 4 and toilet seat 5 as shown in FIG. 4. The control device 100 controls the toilet lid 4 and toilet seat 5 based on signals transmitted from the operating device 10. The control device 100 controls the toilet lid 4 based on control instruction signals transmitted from the operating device 10 regarding the opening and closing of the toilet lid. The control device 100 controls the toilet seat 5 based on control instruction signals transmitted from the operating device 10 regarding the opening and closing of the seat. The control device 100 transmits control information to the toilet lid 4 and toilet seat 5 via a wired connection. The control device 100 may also transmit control information to the toilet lid 4 and toilet seat 5 wirelessly.

[0182] The control device 100 determines whether or not the human body detection sensor 32 has detected the entry of a user into the toilet room R. The control device 100 determines whether or not the human body detection sensor 32 has detected the entry of a user into the toilet room R. The control device 100 determines whether or not the seating detection sensor 33 has detected the sitting of a user. The control device 100 determines whether or not the seating detection sensor 33 has detected the sitting of a user on the toilet seat 5.

[0183] The solenoid valve 71 functions as a valve that electromagnetically controls the flow of a fluid. The solenoid valve 71 switches between supplying and stopping tap water from a water supply pipe, for example. The solenoid valve 71 controls opening and closing in response to instructions from the control device 100.

[0184] The nozzle motor 61 is a drive source (motor) that drives the cleaning nozzle 6 to advance and retract. The nozzle motor 61 controls the cleaning nozzle 6 to advance and retract relative to the main body cover 30 of the main body 3. The nozzle motor 61 controls the cleaning nozzle 6 to advance and retract in accordance with instructions from the control device 100.

[0185] The lid 110 can be positioned in front of the vibration detection sensor 34 and functions as a lid. The lid 110 is preferably formed of an opaque material to reduce the possibility that the vibration detection sensor 34 is visible and to ensure the user's privacy. For example, the lid 110 may be formed in an opaque state by coloring. The lid 110 may have an opaque material (paint) applied to its surface. Note that the lid 110 is not limited to an opaque structure and may be transparent. The lid 110 can be transitioned between an open state and a closed state by an actuator 111, and is positioned in front of the vibration detection sensor 34 or exposes the vibration detection sensor 34.

[0186] The actuator 111 is a drive source (motor) that puts the lid 110 into an open state or a closed state. The actuator 111 executes control to put the lid 110 into an open state or a closed state in response to instructions from the control device 100. The actuator 111 puts the lid 110 into a closed state when the cleaning nozzle 6 is operating. The actuator 111 puts the lid 110 into a closed state when the cleaning nozzle 6 arranged on the toilet bowl 7 is operating.

[0187] In the configuration shown in FIG. 8, the toilet seat device 2 includes the control device 100 and other components. However, the control device 100, the human body detection sensor 32, the seating detection sensor 33, and the vibration detection sensor 34 may be configured as separate devices from the toilet seat device 2. For example, the control device 100 may be configured as a separate device from the toilet seat device 2. For example, the control device 100 may be a server device located at a distance from the toilet seat device 2. In this case, the control device 100 communicates with each device, such as the toilet seat device 2, the human body detection sensor 32, the seating detection sensor 33, and the vibration detection sensor 34, and receives information necessary for calculating the urination time and urine volume from each device. In this case, the toilet seat device 2 may also have a configuration (such as a control circuit) for controlling various components of the toilet seat device 2, such as the nozzle motor 61, the solenoid valve 71, and the actuator 111. Note that the above is merely an example, and the toilet system 1 can employ any device configuration as long as the desired processing is possible.

[0188] <2-4. Functional configuration of the control device> The functional configuration of the control device will be described below with reference to Fig. 9. Fig. 9 is a block diagram showing an example of the configuration of the control device according to the second embodiment.

[0189] 9, the control device 100 includes a communication unit 101, a storage unit 120, and a control unit 130. The control device 100 may also include an input unit (e.g., a keyboard, a mouse, etc.) that accepts various operations from an administrator of the control device 100, and a display unit (e.g., a liquid crystal display, etc.) that displays various information.

[0190] The communication unit 101 is realized by, for example, a communication circuit or the like. The communication unit 101 is connected to a predetermined network by wire or wirelessly, and transmits and receives information to and from an external information processing device. For example, the communication unit 101 is connected to a predetermined network by wire or wirelessly, and transmits and receives information to and from other devices such as the operating device 10. Note that the communication unit 101 may be configured as a device (communication device) separate from the control device 100, and may be included in the toilet seat device 2.

[0191] The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. For example, the storage unit 120 is a computer-readable recording medium that non-temporarily records data used by various information processing programs and the like.

[0192] The storage unit 120 according to the second embodiment stores various pieces of information required for processing. The storage unit 120 stores various pieces of information acquired from other devices such as various sensors. For example, the storage unit 120 stores information related to a learning model (also simply referred to as a "model") used in processing. For example, the storage unit 120 stores a model used in the urination time calculation process. For example, the storage unit 120 stores various pieces of information (for example, information related to thresholds) used in various information processes. Furthermore, for example, the storage unit 120 according to the second embodiment stores information stored by the data storage means 14 described above.

[0193] The control unit 130 according to the second embodiment is realized by, for example, a CPU, a GPU, or the like executing a program (for example, various information processing programs according to the present disclosure) stored inside the control device 100 using a RAM or the like as a work area. The control unit 130 is also realized by, for example, an integrated circuit such as an ASIC or an FPGA.

[0194] As shown in Fig. 9, the control unit 130 has an acquisition unit 131, a measurement unit 132, a determination unit 133, an estimation unit 134, and an output unit 135, and realizes or executes the functions and actions of the information processing described below. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in Fig. 9, and may be other configurations as long as they perform the information processing described below. For example, the control unit 130 according to the second embodiment executes the processes executed by the information processing units such as the dehydration estimation means 15, evaluation means 16, notification means 17, and frequent urination estimation means 18 described above.

[0195] The acquisition unit 131 acquires various types of information. The acquisition unit 131 acquires various types of information from the storage unit 120. The acquisition unit 131 receives information from other devices. The acquisition unit 131 receives information (detection information, etc.) detected by various sensors from the various sensors. The acquisition unit 131 receives information (detection information, etc.) detected by each of the human body detection sensor 32, the seating detection sensor 33, and the vibration detection sensor 34 from each sensor. For example, the acquisition unit 131 receives information regarding vibration detected by the vibration detection sensor 34 from the vibration detection sensor 34.

[0196] For example, the acquisition unit 131 receives various types of information related to toilet users as external data. For example, the acquisition unit 131 receives attribute information indicating attributes such as the age and gender of the toilet user. For example, the acquisition unit 131 receives gender information indicating the gender of the toilet user from the toilet user's terminal device as attribute information. For example, the acquisition unit 131 receives behavior information indicating the behavior of the toilet user. For example, the acquisition unit 131 receives location information indicating the location of the toilet user. The acquisition unit 131 acquires information to be used for processing from the storage unit 120.

[0197] The measurement unit 132 performs various measurements. The measurement unit 132 performs various measurements using information stored in the storage unit 120. The measurement unit 132 measures the detection time by the sensor. The measurement unit 132 uses information detected by the vibration detection sensor 34 to measure the time (detection time) during which detection is being performed by the vibration detection sensor 34.

[0198] The measuring unit 132 measures the shaking of the water sealing surface of the bowl portion 8 of the toilet 7 using information detected by the shaking detection sensor 34. When a person approaches the toilet 7, the measuring unit 132 measures a reference shaking of the water sealing surface of the bowl portion 8 of the toilet 7. The measuring unit 132 measures the shaking of the water sealing surface of the bowl portion 8 of the toilet 7 based on the difference from the reference shaking.

[0199] The determination unit 133 performs a determination process. The determination unit 133 performs a determination process using various pieces of information stored in the storage unit 120. The determination unit 133 performs a determination process using various pieces of information acquired by the acquisition unit 131.

[0200] The determination unit 133 determines the cause of the water seal swaying of the toilet bowl 7 based on the detection results by the sway detection sensor 34. The determination unit 133 classifies the water seal swaying of the toilet bowl 7 based on the detection results by the sway detection sensor 34. The determination unit 133 determines which object is causing the water seal swaying of the toilet bowl 7 based on the detection results by the sway detection sensor 34.

[0201] The determination unit 133 determines whether an object has fallen (landed) into the seal water of the toilet bowl 7 based on the detection result of the vibration detection sensor 34. The determination unit 133 determines whether an object has landed in the seal water of the toilet bowl 7 based on the detection result of the vibration detection sensor 34. The determination unit 133 determines whether the object is excrement of the user based on the detection result of the vibration detection sensor 34.

[0202] For example, the determination unit 133 classifies the tremors into a plurality of types, including a first type of tremor caused by stool, a second type of tremor caused by urine, and a third type of tremor caused by both stool and urine. For example, the determination unit 133 classifies the tremor detected by the tremor detection sensor 34 into tremor caused by stool, tremor caused by urine, or tremor caused by both stool and urine.

[0203] The determination unit 133 may determine the presence of shaking using any method. For example, the determination unit 133 may determine the presence of shaking by detecting whether a signal level exceeds a threshold or by using AI (artificial intelligence). The determination unit 133 may also determine the presence of shaking by frequency analysis, image processing, machine learning, deep learning, or the like.

[0204] For example, the determination unit 133 determines the shaking using AI technology. For example, the determination unit 133 may determine the shaking using a model (also referred to as a "shake determination model") generated by machine learning. In this case, the shake determination model is trained in advance using training data indicating classification judgments. This training data includes multiple combinations of shake information of the seal water and labels (correct answer information) indicating the type of shake corresponding to the shake information. The type here indicates the object that caused the shake, such as feces, urine, or both feces and urine. For example, the training data includes multiple combinations of shake information such as the shake information SW1 to SW3 in FIG. 12 and labels (correct answer information) indicating objects that landed (fell) into the seal water when the shake corresponding to the shake information occurred in the seal water (e.g., feces, urine, or both feces and urine).

[0205] The vibration determination model is a model that receives vibration information as input and outputs information indicating the type of vibration corresponding to the input vibration information. For example, the vibration determination model is trained so that, when vibration information is input, it outputs information on a label (type of vibration) corresponding to the input vibration information. The vibration determination model is trained using various techniques related to so-called supervised learning as appropriate. In this case, the vibration determination model is stored in the storage unit 120, and the determination unit 133 may determine the vibration using the vibration determination model stored in the storage unit 120. For example, the control device 100 may perform a learning process and generate the vibration determination model. Note that the above is merely an example, and the determination unit 133 may determine the vibration using various information as appropriate.

[0206] Furthermore, the determination unit 133 may determine whether or not a defecation (faecal discharge) has occurred based on information detected by a stool detection means. The determination unit 133 may determine whether or not the user has defecate using information detected by a stool detection means such as the shaking detection sensor 34. The determination unit 133 determines whether or not a defecation has occurred based on an image captured by the stool detection means. Note that the above determination of whether or not a defecation has occurred is merely an example, and the determination unit 133 may determine whether or not a defecation has occurred by appropriately using various information when determining whether or not a defecation has occurred.

[0207] The estimation unit 134 according to the second embodiment functions as a dehydration estimation means. For example, the estimation unit 134 estimates the dehydration of the toilet user by the same processing as the dehydration estimation means 15 according to the first embodiment.

[0208] The estimation unit 134 estimates the dehydration state of the toilet user based on the urination data stored in the memory unit 120. The estimation unit 134 estimates the dehydration state when the integrated value of the urine volume over a predetermined period of time is less than a predetermined value. The estimation unit 134 estimates the dehydration state when the urination interval is longer than a predetermined interval. The estimation unit 134 estimates the dehydration state when the urine volume over a predetermined period of time is less than a predetermined volume. The estimation unit 134 estimates the dehydration state when the urination interval is longer than the predetermined interval and the urine volume is less than a predetermined volume.

[0209] The estimation unit 134 estimates the dehydration state based on the urination data and at least one of the toilet user's age-specific and season-specific urination characteristics. The estimation unit 134 suspends estimation of the dehydration state when the number of urinations based on the urination data is equal to or less than a predetermined number of times.

[0210] The estimation unit 134 according to the second embodiment functions as an evaluation unit. For example, the estimation unit 134 performs a process related to evaluation of dehydration of the toilet user by the same process as the evaluation unit 16 according to the first embodiment.

[0211] The estimation unit 134 functions as a dehydration assessment means that classifies the dehydration state of the toilet user into a plurality of levels based on the urination data. When the amount of urine included in the urination data is less than a predetermined amount, the estimation unit 134 classifies the dehydration state into a plurality of levels based on the urine color included in the urination data of the toilet user.

[0212] The estimation unit 134 according to the second embodiment functions as a frequent urination estimation means. For example, the estimation unit 134 estimates the frequent urination of the toilet user by the same processing as the frequent urination estimation means 18 according to the first embodiment.

[0213] The estimation unit 134 estimates the toilet user's frequent urination based on the urination data. The estimation unit 134 estimates frequent urination when the urination interval is shorter than a predetermined period.

[0214] The estimation unit 134 estimates the toilet user's frequency of urination based on the urination data stored in the memory unit 120. The estimation unit 134 estimates nocturia based on the urine volume or urine flow rate per night, or the average urine volume or average urine flow rate during the night, using the nighttime urination information identified from the urination information and other urination information.

[0215] The estimation unit 134 estimates nocturia based on the daytime and nighttime urination data identified by the urination information and other urination information. The estimation unit 134 estimates nocturia based on the daytime urine volume or urine flow rate per urination and the nighttime urine volume or urine flow rate per urination.

[0216] The estimation unit 134 estimates nocturia based on the average daytime urine volume or average urine flow rate and the average nighttime urine volume or average urine flow rate. The estimation unit 134 estimates nocturia using the nighttime urination information identified from the urination information and other urination information when there are multiple urinations at night and the relationship between the urine volume or urine flow rate per urination and the interval between urination times satisfies a predetermined condition.

[0217] The estimation unit 134 performs a calculation process. The estimation unit 134 performs a calculation process using various information stored in the storage unit 120. The estimation unit 134 performs a calculation process using various information acquired by the acquisition unit 131. The estimation unit 134 calculates the urination time based on the determination result by the determination unit 133.

[0218] The estimation unit 134 calculates the urination time based on the time during which the water sealing surface of the bowl portion 8 of the toilet 7 that receives the excrement sways by a predetermined value or more. The estimation unit 134 calculates the total urine volume based on the calculated urination time and the urine volume per unit time stored in the memory unit 120.

[0219] The estimation unit 134 classifies the calculated total urine volume into one of a plurality of levels. The estimation unit 134 categorizes the total urine volume into one of the levels of "large," "medium," and "small." For example, if the total urine volume is less than a first threshold, the estimation unit 134 classifies the total urine volume into the level "small." For example, if the total urine volume is equal to or greater than the first threshold and less than a second threshold that is greater than the first threshold, the estimation unit 134 classifies the total urine volume into the level "medium." For example, if the total urine volume is equal to or greater than the second threshold, the estimation unit 134 classifies the total urine volume into the level "large."

[0220] The estimation unit 134 calculates the time of shaking corresponding to the second type of shaking or the third type of shaking as the urination time. When shaking of the water seal surface of the bowl portion 8 of the toilet 7 is greater than a predetermined threshold, the estimation unit 134 calculates the urination time by excluding the time of the large shaking. When defecation is detected by a stool detection means that can detect the presence or absence of defecation, the estimation unit 134 calculates the urination time by excluding the time of shaking assumed to be due to defecation.

[0221] For example, the estimation unit 134 associates information related to excrement, such as urine volume and urination time, acquired by the above-described processing with time information (date and time, time period, period, etc.) related to the time when the information was acquired, and registers the information in the storage unit 120. For example, the estimation unit 134 executes processing using the acquired information related to excrement and the time information corresponding to the information. Through such processing, the estimation unit 134 estimates information used to estimate frequent urination.

[0222] The output unit 135 according to the second embodiment functions as a notification unit. For example, the output unit 135 performs a process for providing information about dehydration of the toilet user in the same manner as the notification unit 17 according to the first embodiment.

[0223] The output unit 135 notifies a predetermined destination of highlight information indicating the health status of the toilet user based on urination data for a predetermined period including the latest urination data. If the number of urinations based on the urination data is equal to or less than a predetermined number, the output unit 135 does not notify the predetermined destination of the highlight information.

[0224] The output unit 135 notifies a predetermined destination of recommendation information for improving the health condition of the toilet user based on urination data for a predetermined period, including the most recent urination data. If the number of urinations based on the urination data is less than a predetermined number, the output unit 135 does not notify the predetermined destination of the recommendation information. The output unit 135 notifies the predetermined destination of the next recommendation information generated based on predetermined input information in response to the recommendation information received by the toilet user.

[0225] The output unit 135 executes output processing to output various types of information. The output unit 135 functions as a transmission unit that transmits various types of information. The output unit 135 executes output processing by transmitting information to an external information processing device. The output unit 135 transmits information to an external information processing device. For example, the output unit 135 transmits various types of information to an administrator device such as a personal computer or smartphone used by an administrator. The output unit 135 may also execute output processing by transmitting information to the operation device 10 (or the display screen 11).

[0226] The output unit 135 transmits information indicating the urination time calculated by the estimation unit 134. The output unit 135 transmits information indicating the urine volume calculated by the estimation unit 134. The output unit 135 outputs information indicating any one of "large," "medium," or "small" indicating the total urine volume (level) categorized by the estimation unit 134. The output unit 135 transmits information indicating the level of the total urine volume.

[0227] The output unit 135 outputs information related to the health condition of the user estimated by the estimation unit 134. The output unit 135 outputs information related to frequent urination estimated by the estimation unit 134. The output unit 135 transmits information related to the health condition of the user, such as frequent urination, estimated by the estimation unit 134.

[0228] The output unit 135 notifies the user (toilet user) of information regarding the health condition of the user. The output unit 135 transmits the information regarding the health condition of the user to a terminal device such as a smartphone used by the user.

[0229] <2-5. Processing flow> From here, the processing flow executed by the toilet system will be explained. The toilet system 1 executes the following first and second processes. The toilet system 1 may execute either the first or second process. In the following, the toilet system 1 will be described as the processing subject, but the first and second processes may be executed by any device, such as the control device 100 or various sensors such as the vibration detection sensor 34, depending on the device configuration included in the toilet system 1.

[0230] <2-5-1. First process> First, a processing example shown in Fig. 10 will be described. Fig. 10 is a flowchart showing an example of a processing procedure executed by the toilet system. Specifically, Fig. 10 is a flowchart showing an example of a first processing procedure for calculation related to urination time and urine volume.

[0231] 10, the toilet system 1 determines whether or not a measurement start trigger has been received (step S101). For example, the toilet system 1 determines that a measurement start trigger has been received when it detects that a user has started using the toilet 7. If the toilet system 1 determines that a measurement start trigger has not been received (step S101: No), it repeats the processing of step S101.

[0232] When the toilet system 1 determines that a measurement start trigger has occurred (step S101: Yes), it sets "t=0" (step S102). For example, when the toilet system 1 detects that the user has started using the toilet 7 and determines that a measurement start trigger has occurred, it initializes the value of the urination score t, which counts the urination time, to 0.

[0233] Then, the toilet system 1 acquires the initial state (step S103). For example, the toilet system 1 acquires the sway of the water seal detected by the sway detection sensor 34 at that time (before the user starts urination) as the initial state.

[0234] The toilet system 1 performs measurements (step S104). For example, the toilet system 1 measures the sway of the seal water using the sway detection sensor 34. Then, the toilet system 1 calculates the difference from the initial state (step S105). For example, the toilet system 1 calculates the difference between the sway of the seal water measured in step S104 and the initial state acquired in step S103.

[0235] The toilet system 1 determines whether or not the water seal is swaying (step S106). For example, if the difference calculated in step S105 is equal to or greater than a predetermined value, the toilet system 1 determines that the water seal is swaying due to an object falling into the water seal (landing on water). If the toilet system 1 determines that the water seal is not swaying (step S106: No), it returns to step S104 and repeats the process.

[0236] If the toilet system 1 determines that there is water seal swaying (step S106: Yes), it determines whether the water seal swaying is due to stool (step S107). For example, if the model (sway determination model) to which the difference calculated in step S105 has been input outputs information indicating stool, the toilet system 1 determines that the water seal swaying is due to stool only. In other words, if the model outputs information indicating stool, the toilet system 1 determines that the user has excreted only stool. If the toilet system 1 determines that the water seal swaying is due to stool only (step S107: Yes), it makes a determination to end step S112.

[0237] If the toilet system 1 determines that the water seal swaying is not due to stool (step S107: No), it determines whether the water seal swaying is due to urine (step S108). For example, if the model to which the difference calculated in step S105 was input outputs information indicating urine, the toilet system 1 determines that the water seal swaying is due to urine only. In other words, if the model outputs information indicating urine, the toilet system 1 determines that the user has excreted urine only. If the toilet system 1 determines that the water seal swaying is due to urine only (step S108: Yes), it sets "t = t + 1" (step S109). For example, if the toilet system 1 determines that the water seal swaying is due to urine, it increases the value of the urination score t by 1. Then, the toilet system 1 performs an end determination of step S112.

[0238] If the toilet system 1 determines that the water seal swaying is not due to urine alone (step S108: No), it determines whether the water seal swaying is due to feces and urine (step S110). For example, if the model to which the difference calculated in step S105 was input outputs information indicating feces and urine, the toilet system 1 determines that the water seal swaying is due to both feces and urine. In other words, if the model outputs information indicating feces and urine, the toilet system 1 determines that the user has excreted both feces and urine. If the toilet system 1 determines that the water seal swaying is due to feces and urine (step S110: Yes), it sets "t = t + 1" (step S111). For example, if the toilet system 1 determines that the water seal swaying is due to feces and urine, it increases the value of the urination score t by 1. Then, the toilet system 1 performs an end determination in step S112.

[0239] The toilet system 1 determines whether or not a measurement end trigger has been generated (step S112). For example, the toilet system 1 determines that a measurement end trigger has been generated when it detects that the user has finished using the toilet 7. If the toilet system 1 determines that a measurement end trigger has not been generated (step S112: No), it returns to step S104 and repeats the process.

[0240] When the toilet system 1 determines that a measurement end trigger has been received (step S112: Yes), it calculates the total urination time (step S113). For example, the toilet system 1 calculates the total urination time based on the value of the urination score t, which is the counted urination time. For example, if the unit of the urination score t corresponds to seconds, the toilet system 1 calculates the number of seconds of the value of the urination score t as the total urination time. In this case, if the urination score t is "5", the toilet system 1 calculates the total urination time to be 5 seconds. The toilet system 1 calculates the total urination time using a function (urination time calculation function) that inputs the urination score t and outputs the total urination time. In this case, if the urination score t is "5", the toilet system 1 may input "5" into the urination time calculation function and determine the value output by the urination time calculation function as the total urination time.

[0241] Then, the toilet system 1 estimates the urine volume (step S114). For example, the toilet system 1 calculates the urine volume using the total urination time calculated in step S113. The toilet system 1 calculates the urine volume by multiplying the calculated urination time by the urine volume per unit time (unit urine volume) stored in the memory unit 120. For example, the unit urine volume may be set to any value within a range of 20 to 30 (ml / sec). The unit urine volume may be set for each gender. For example, the unit urine volume for women may be set to any value within a range of 10 to 50 (ml / sec). Furthermore, the unit urine volume for men may be set to any value within a range of 10 to 30 (ml / sec). Note that the above is merely an example, and the unit urine volume is not limited to the above, and any value may be set.

[0242] <2-5-2. Second process> Next, a processing example shown in Fig. 11 will be described. Fig. 11 is a flowchart showing an example of a processing procedure executed by the toilet system. Specifically, Fig. 11 is a flowchart showing an example of a second processing procedure for calculating urination time and urine volume. Note that explanations of points similar to Fig. 10 will be omitted as appropriate.

[0243] 11, the toilet system 1 determines whether or not a measurement start trigger has been received (step S201). For example, the toilet system 1 determines that a measurement start trigger has been received when it detects that a user has started using the toilet 7. If the toilet system 1 determines that a measurement start trigger has not been received (step S201: No), it repeats the processing of step S201.

[0244] When the toilet system 1 determines that a measurement start trigger has occurred (step S201: Yes), it sets "t=0" (step S202). For example, when the toilet system 1 detects that the user has started using the toilet 7 and determines that a measurement start trigger has occurred, it initializes the value of the urination score t, which counts the urination time, to 0.

[0245] Then, the toilet system 1 acquires the initial state (step S203). For example, the toilet system 1 acquires the sway of the water seal detected by the sway detection sensor 34 at that time (before the user starts urination) as the initial state.

[0246] The toilet system 1 performs measurements (step S204). For example, the toilet system 1 measures the sway of the seal water using the sway detection sensor 34. Then, the toilet system 1 calculates the difference from the initial state (step S205). For example, the toilet system 1 calculates the difference between the sway of the seal water measured in step S204 and the initial state acquired in step S203.

[0247] The toilet system 1 determines whether or not the water seal is swaying (step S206). For example, if the difference calculated in step S205 is equal to or greater than a predetermined value, the toilet system 1 determines that the water seal is swaying due to an object falling into the water seal (landing on water). If the toilet system 1 determines that the water seal is not swaying (step S206: No), it returns to step S204 and repeats the process.

[0248] When the toilet system 1 determines that there is water seal sway (step S206: Yes), it acquires sway information (step S207). For example, the toilet system 1 acquires differential information when it determines that there is water seal sway as sway information.

[0249] Then, the toilet system 1 determines whether or not a measurement end trigger has been generated (step S208). For example, the toilet system 1 determines that a measurement end trigger has been generated when it detects that the user has finished using the toilet 7. If the toilet system 1 determines that a measurement end trigger has not been generated (step S208: No), it returns to step S204 and repeats the process.

[0250] When the toilet system 1 determines that a measurement end trigger has occurred (step S208: Yes), it executes vibration information processing (step S209). For example, when the toilet system 1 detects that the user has finished using the toilet bowl 7 and determines that a measurement end trigger has occurred, it executes vibration information processing. For example, the toilet system 1 processes vibration information so as not to include large vibrations in urination. In this case, the toilet system 1 excludes vibration information with a difference equal to or greater than a predetermined value from the vibration information used to calculate the urination time.

[0251] The above-described motion information processing is merely an example, and the toilet system 1 may use various information to acquire motion information used to calculate the urination time. If there is a stool, the toilet system 1 processes the motion information so that the motion of the stool is not included in the urination. In this case, the toilet system 1 excludes motion information corresponding to the time when the presence of the stool is detected by a detection means other than the stool detection means from the motion information used to calculate the urination time.

[0252] Then, the toilet system 1 calculates the total urination time (step S210). For example, the toilet system 1 calculates the total urination time based on the vibration information after the processing of step S209. For example, the toilet system 1 calculates the total urination time as the sum of the times corresponding to the vibration information after the processing of step S209. In this case, if the total period during which the vibration information after the processing of step S209 was detected is 5 seconds, the toilet system 1 calculates the total urination time to be 5 seconds.

[0253] Then, the toilet system 1 estimates the urine volume (step S211). For example, the toilet system 1 calculates the urine volume using the total urination time calculated in step S210. The toilet system 1 calculates the urine volume by multiplying the calculated urination time by the urine volume per unit time (unit urine volume) stored in the memory unit 120.

[0254] <2-6. Relationship between objects and shaking> The relationship between the object and the vibration will now be described. Specifically, the relationship between the object falling into the seal water of the toilet bowl 7 of the toilet system 1 and the vibration will be described.

[0255] <2-6-1. Relationship between excrement and shaking> First, an example of the relationship between excrement and swaying (waveform of the water surface) will be described with reference to Fig. 12. Fig. 12 is a diagram showing an example of the relationship between excrement and swaying. Fig. 12 shows information about three types of swaying, corresponding to feces only, urine only, and both feces and urine (feces + urine).

[0256] The fluctuation information SW1 to SW3 shown in Fig. 12 indicates fluctuation information corresponding to each of three types. For example, the fluctuation information SW1 to SW3 shown in Fig. 12 indicates fluctuation information corresponding to a difference from the initial state.

[0257] For example, the vibration information SW1 corresponds to the difference from the initial state for the first type (feces only) vibration, and indicates vibration information for the seal water vibration caused only by feces, with vibrations other than feces removed. As shown in Figure 12, the first type (feces only) has a slow falling speed and a low frequency. Furthermore, the first type (feces only) has a large amount of falling material, a large amplitude with attenuation, and a short duration.

[0258] For example, the trembling information SW2 corresponds to the difference from the initial state for the trembling of the second type (urine only), and indicates the trembling information of the trembling of the sealed water caused by urine only, removing trembling caused by things other than urine. As shown in Figure 12, the second type (urine only) has a fast falling speed and a high frequency. Furthermore, the second type (urine only) has a small amount of falling material, a small amplitude, and a long duration.

[0259] For example, the fluctuation information SW3 corresponds to the difference from the initial state for the third type (feces and urine) of trembling, and indicates the fluctuation information of the water trembling caused by both feces and urine, removing the fluctuations caused by factors other than feces and urine. As shown in Figure 12, the third type (feces and urine) has a composite frequency (for example, a composite frequency of the fluctuation information SW1 and the fluctuation information SW2), and there is amplitude fluctuation other than simple attenuation.

[0260] <2-6-2. Relationship between objects other than excrement and shaking> Next, an example of the relationship between an object other than excrement and waving (waveform on the water surface) will be described with reference to Fig. 13. Fig. 13 is a diagram showing an example of the relationship between an object other than excrement and waving. Specifically, Fig. 13 is a diagram showing an example of the relationship between an object other than excrement, such as toilet paper (also simply called "paper"), and waving.

[0261] The vibration information SW4 shown in Figure 13 indicates vibration information for the fourth type of vibration, which is vibration caused by paper. For example, the vibration information SW4 shown in Figure 13 indicates vibration information corresponding to the difference from the initial state. For example, the vibration information SW4 corresponds to the difference from the initial state for the fourth type of vibration (paper only), and indicates vibration information for the vibration of the seal water caused by paper only, removing vibrations caused by things other than paper. As shown in Figure 13, the fourth type (paper only) has a slow falling speed and a low frequency. Furthermore, the fourth type (paper only) has a small amount of falling material, small amplitude with attenuation, and a short duration.

[0262] <2-7. Relationship between user and urination direction> Here, several patterns of the relationship between the user and the direction of urination are illustrated using Figure 14. Figure 14 is a diagram showing an example of the relationship between the user and the direction of urination. Specifically, Figure 14 is a conceptual diagram showing that the position where urine lands varies depending on the posture during urination. Figure 14 shows three urination patterns: a first pattern PT1, a second pattern PT2, and a third pattern PT3, and the arrows in each pattern indicate the main direction of urination.

[0263] For example, the first pattern PT1 in FIG. 14 corresponds to a pattern in which a woman urinates while sitting, and the urination direction primarily includes a direction that hits the water seal or a direction toward the inner circumferential surface of the bowl. The second pattern PT2 in FIG. 14 corresponds to a pattern in which a man urinates while sitting, and the urination direction primarily includes a direction toward the inner circumferential surface of the bowl. The third pattern PT3 in FIG. 14 corresponds to a pattern in which a man urinates while standing, and the urination direction primarily includes a direction toward the inside of the bowl, but varies widely. Even if the urination direction varies depending on the user's gender, posture, etc., the toilet system 1 can accurately calculate the urination time because it detects the movement of the water seal.

[0264] <2-8. Overall overview> From here, an overview of the configuration and processing of the toilet system 1 described above will be described with reference to Fig. 15. Fig. 15 is a diagram showing an overview of the configuration and processing of the toilet system. Note that explanations of points similar to those described above will be omitted as appropriate. For example, various types of sensors can be used for the vibration detection sensor 34. Furthermore, any method can be used for vibration determination (urination determination) performed by the toilet system 1.

[0265] As shown in Figure 15, vibrations caused by ventilation fans, door opening and closing, etc. can be a noise factor, but toilet system 1 can appropriately remove the noise factor by calculating the difference from the initial state. In toilet system 1, the start trigger for operation control may be the start of sitting, operation of the measurement start button, etc. Furthermore, in toilet system 1, the end trigger for operation control may be operation of the flush button, the passage of a predetermined time without vibration, detection of paper falling, operation of the measurement end button, etc.

[0266] Furthermore, the toilet system 1 may take any action when there is paper. For example, the toilet system 1 may exclude paper from the measurement when there is paper. Furthermore, when there is paper, the toilet system 1 may acquire (calculate) the difference from when the paper fell. Furthermore, when there is paper, the toilet system 1 may perform a process such as removing or sinking the paper. In this case, the toilet system 1 may control the flushing nozzle 6 to spray water on the paper, for example, to remove or sink the paper.

[0267] Furthermore, when the toilet system 1 detects urine swaying, it does not perform any operation that would cause noise from the water seal swaying. When the toilet system 1 detects urine swaying, it does not have to flush the toilet bowl 7 or perform a private cleaning. The toilet system 1 does not have to perform measurements when a private cleaning is in operation, and may end measurements when a private cleaning operation is performed. Furthermore, as described above, the toilet system 1 categorizes the total urine volume into "large," "medium," and "small" and outputs it.

[0268] FIG. 16 is a diagram showing an example of the relationship between information about swaying and urine flow rate (urinary flow rate), i.e., the amount of urine excreted per unit time. For example, when the magnitude of the vertical displacement, which is the height of the swaying (waves), is greater than a predetermined value, the control unit 130 estimates the urine flow rate to be "large," and when the magnitude of the vertical displacement, which is the height of the swaying (waves), is less than the predetermined value, the control unit 130 estimates the urine flow rate to be "small." For example, when the interval between waves, which are swaying, is greater than a predetermined value, the control unit 130 estimates the urine flow rate to be "small," and when the interval between waves, which are swaying, is less than the predetermined value, the control unit 130 estimates the urine flow rate to be "large." For example, when the amount of bubbles in the seal water is greater than a predetermined value, the control unit 130 estimates the urine flow rate to be "large," and when the amount of bubbles in the seal water is less than the predetermined value, the control unit 130 estimates the urine flow rate to be "small." Furthermore, for example, the control unit 130 estimates, as information regarding the sway of the seal water, the urine flow rate to be "small" if the shape of the sway is highly uniform, and estimates the urine flow rate to be "large" if the shape of the sway is low. Furthermore, for example, the control unit 130 estimates, as information regarding the sway of the seal water, the urine flow rate to be "small" if the area where the sway occurs is equal to or smaller than a predetermined value, and estimates the urine flow rate to be "large" if the area where the sway occurs is larger than the predetermined value. The control unit 130 controls the external terminal to display the urine flow rate, which is information regarding the obtained urine, or the total urine volume obtained by multiplying the urine flow rate by a predetermined value estimated as a typical urination time.

[0269] 3. Third Embodiment FIG. 17 is a side cross-sectional view showing an example of the configuration of a toilet apparatus according to the third embodiment. In this embodiment, a camera 36 is used as the vibration detection sensor. The camera 36 begins capturing images at predetermined intervals, triggered by detection by the seating detection sensor 33. The imaging area of ​​the camera 36 includes the seal water accumulated in the bowl portion 8 of the toilet 7, and image data of the seal water is acquired at predetermined intervals. More preferably, the imaging area of ​​the camera 36 is set so that the detection range includes the area forward of the center in the front-to-back direction of the seal water, which is preferable for detecting various vibrations of the seal water. In this embodiment, the direction from the buttocks to the toes when the user is sitting on the toilet seat is defined as the forward direction.

[0270] FIG. 18(A) is an image of the water seal during urination taken by camera 36. FIG. 18(B) is an image of the water seal taken by camera 36 immediately after the user sits down (before urination). FIG. 17(C) shows data in which the difference (amount of change) between the image in FIG. 18(A) and that in FIG. 18(B) is indicated by a white area. The white area in FIG. 18(C) is an area where the amount of change is equal to or greater than a predetermined value, specifically, an area where the amount of change in brightness is equal to or greater than 10, for example. As shown in FIG. 19, this difference analysis is performed each time an image is acquired at a predetermined timing. Based on the white areas in FIG. 18(C), the control unit 130 estimates the presence or absence of feces, the presence or absence of urine, and information about the urine. For example, if the area of ​​the continuous white areas is equal to or greater than a first predetermined value, the control unit 130 determines that the water seal is shaking (changing) due to feces, and determines that feces has fallen. For example, if the area of ​​the continuous white areas is smaller than the first predetermined value, the control unit 130 determines that urine, not feces, has been excreted. In this case, the control unit 130 determines that the urine flow rate is high if the total area of ​​the white areas in a predetermined area including the front of the toilet is equal to or greater than a second predetermined value, and determines that the urine flow rate is low if the total area of ​​the white areas in a predetermined area including the front of the toilet is smaller than the second predetermined value. The control unit 130 then controls the external terminal to display the largest urine flow rate obtained by performing this calculation each time an image is acquired at a predetermined timing as the representative urine flow rate. At this time, the control unit 130 determines the urination time by integrating the time during which the total area of ​​the white region is equal to or greater than a third predetermined value.The control unit 130 then estimates the total urine volume by integrating the determined urine flow rate and urination time.The control unit 130 controls the external terminal to display the obtained information about urine, such as the urine flow rate, urination time, and total urine volume.

[0271] As shown in Figure 20, instead of comparing an image of the water seal during urination taken by camera 36 with an image of the water seal taken by camera 36 immediately after the user sits down (before urination), it is also possible to compare image data of the water seal obtained by a sensor with image data obtained immediately before that image data was obtained, and extract the white area as shown in Figure 18(C). This makes it possible to grasp changes in real time that take into account time information about the water seal's movement, and to make a more accurate judgment. Note that it is not necessary to compare the immediately preceding image, but it is also possible to compare the image from, for example, the image two images before.

[0272] 21 to 23 are diagrams showing the relationship between the water seal fluctuation pattern stored in the control unit 130 and the urine flow rate. For example, as shown in FIGS. 21 to 23, the control unit 130 may store in advance the relationship between the water seal sway pattern and the urine flow rate for each water seal state (presence or absence of feces, presence or absence of paper, if present, size and shape of the feces or paper, position within the water seal, whether the feces or paper hit the water seal or was already present, etc.) and the urination state (position of impact, etc.), select the water seal and water seal sway pattern that most closely resembles the image data of the water seal captured at a predetermined timing, and determine information about urine (presence or absence of urination, amount of urination, etc.) from the stored data. The control unit 130 may extract feature values ​​related to the water seal sway pattern, such as the shape of the water seal sway and the presence or absence of bubbles, and determine information about urine based on the feature values. Note that the pre-stored relationship between the water seal pattern and urine flow rate and the feature values ​​related to the water seal sway may be derived using machine learning such as AI. If the water seal sway pattern is used to derive information about urine, information about urine may be derived directly from the image data acquired by the camera without extracting feature values ​​about the sway.

[0273] In the toilet system 1, the sensor that detects urine and the sensor that detects feces have been described as being the same sensor, but for example, the sensor that detects feces may be provided separately from the sensor that detects urine. The sensor that detects feces may be an optical sensor such as a line sensor, or a sensor that indirectly detects feces by using a gas sensor to detect gas during defecation. In this case, if feces is detected, measurement or determination of urine may not be performed. Specifically, for example, the control unit 130 is controlled so that information about the movement of the seal water obtained during the period in which feces is detected is not used in determining urine. This can further improve the accuracy of urine determination. Alternatively, the control unit 130 may correct information about the swaying of the water seal obtained during the period in which feces was detected and use the corrected information to determine whether the urine is present. This can further improve the accuracy of determining whether the urine is present.

[0274] In the toilet system 1, detection by the seat detection sensor 33 is used as a trigger for the camera 36 to start taking pictures, but for example, an illuminance sensor may be provided in the toilet seat device 2, and if the illuminance inside the bowl portion 8 falls below a predetermined value, or if the illuminance inside the bowl portion 8 remains below the predetermined value for a predetermined period of time, it may be determined that someone has sat down, and this may be used as a trigger for the camera 36 to start taking pictures.

[0275] In the toilet system 1, detection by the seating detection sensor 33 triggers the camera 36 to start capturing images. However, for example, even without detection by the seating detection sensor 33, a signal detecting that a user is in front of the toilet 7, such as a signal detecting the presence or absence of a user from a human body detection sensor, a signal detecting whether a door is open or closed from a door sensor provided on the door of the toilet room in which the toilet 7 is installed, or a signal detecting that the toilet lid of the toilet 7 is open, may also be used to trigger the camera 36 to start capturing images. This makes it possible to capture images of standing urination. In this case, the camera 36 may capture images in a standing urination capture mode separate from the capture of images of the camera 36 triggered by detection by the seating detection sensor 33. In the standing urination detection mode, the control unit 130, unlike the normal capture mode, determines that the image is urine and not feces even when there is a large amount of information regarding the swaying of urine (such as a large amount of vertical displacement of the swaying or a narrow interval between swaying waves). That is, for example, even if information on the swaying of the water seal that would be determined as feces is obtained in the normal imaging mode, the control unit 130 determines that the object is urine.

[0276] In the toilet system 1, the end of photography is triggered by the end of detection of a person sitting by the seat detection sensor 33, but photography may also be ended when the cleaning operation of the cleaning nozzle installed in the toilet seat device 2 or the cleaning operation of the bowl portion 8 is performed.

[0277] The control unit 130 of the toilet system 1 estimates and displays whether or not a user has urinated, as well as the urine flow rate, urination duration, and total urine volume. However, for example, it may also notify the user of the frequency of urination. Furthermore, the control unit 130 may control a display unit, such as a user's terminal or a manager's PC terminal, to issue an alarm notification based on at least one of information on the urine flow rate, urination duration, and total urine volume, and information on the frequency of urination. For example, if the control unit 130 receives information on at least one of low urine flow rate, short urination duration, and low total urine volume, as well as information on low urination frequency and short urination intervals, it may control a display unit, such as a user's terminal or a manager's PC terminal, to issue an alarm notification. In this case, the user or manager may externally input excretion information about the user (excretor), such as "incontinence information" and "information on urination in another toilet," into the display unit, and the control unit 130 may adjust the alarm notification conditions based on this excretion information.

[0278] As described above, the toilet system 1 uses any sensor to estimate information about excrement, such as information about urine. Hereinafter, several specific examples of the above-mentioned processes and concepts will be described. Note that processes that are described with the toilet system 1 as the processing entity and processes that do not explicitly state the processing entity may be performed by any device included in the toilet system 1, such as the control device 100 or various sensors, as long as the device is capable of performing the process, depending on the device configuration included in the toilet system 1.

[0279] As shown in Fig. 24, the toilet system 1 detects waves occurring on the water surface of the seal water, and estimates (acquires) information about urine, such as urine volume, based on the detection results. Fig. 24 is a diagram showing an example of wave behavior. For example, Fig. 24 shows an example of a change in the distance between the sensor and the water surface (liquid surface) of the seal water at viewpoint A (horizontal view) shown in Fig. 25. Fig. 25 is a diagram showing an example of how wave behavior is detected.

[0280] The sensor referred to here may be any of the above-mentioned vibration detection sensors 34, cameras 36, etc., and its placement may be any position as long as it allows for the desired detection. For example, Figure 25 illustrates an example in which the vibration detection sensor 34 is provided as in Figure 7, but the sensor is not limited to the vibration detection sensor 34 and may be any sensor such as a camera 36, ​​and may be placed in a position that allows for the desired detection. The vertical axis of Figure 24 corresponds to the distance between the sensor and the seal water surface, and the horizontal axis corresponds to time. Figure 24 shows, for example, the change in the distance between the sensor and the seal water surface, with the position of the seal water surface in a predetermined state (for example, a state without vibration) set as the reference "0."

[0281] Based on the detection by the sensor, the toilet system 1 may calculate (acquire) a representative value (representative value of the sensor-liquid level distance) indicating the distance between the sensor and the water surface of the sealed water (also called the "liquid level"). In the example shown in FIG. 24, the representative value may be, for example, the minimum value, average value, median value (frequently occurring value), or maximum value within a predetermined time period. The toilet system 1 detects the distance from the sensor to the wave (in the direction of gravity) and estimates information related to urine, such as urine volume, from the displacement.

[0282] For example, the toilet system 1 estimates (calculates) the urine volume from the representative value of the sensor-liquid level distance using a conversion formula based on the relationship shown in Figure 26. Figure 26 is a diagram showing an example of conversion to urine volume. For example, Figure 26 is a graph corresponding to the conversion formula between acquired information and urine volume. Note that the relationship shown in Figure 26 is merely an example, and the toilet system 1 may estimate information related to urine, such as urine volume, using any information.

[0283] The toilet system 1 may detect the boundary position between the wave and the bowl portion 8 (also called "ceramics") and estimate (acquire) information about urine, such as urine volume, from the displacement. For example, the toilet system 1 may estimate information about urine, such as urine volume, based on information about the boundary position between the wave and the bowl portion 8 (ceramics), as shown in FIG. 27. FIG. 27 is a diagram showing an example of the boundary position between the wave and the bowl portion. For example, the schematic diagram of the toilet bowl at the top in FIG. 27 shows the boundary position between the wave generated on the water seal surface and the ceramic. The thick line in the schematic diagram in FIG. 27 indicates the boundary position of the wave generated on the water seal surface. In this way, the schematic diagram in FIG. 27 shows the positional relationship between the toilet bowl and the water seal (the shaking part).

[0284] For example, the graph at the bottom of Fig. 27 shows information corresponding to the acquired information and the conversion formula for urine volume. For example, the toilet system 1 estimates (calculates) the urine volume from the boundary position between the wave and the ceramic using a conversion formula based on the relationship shown in the graph at the bottom of Fig. 27.

[0285] Furthermore, the toilet system 1 may acquire the initial state in any manner. For example, the toilet system 1 may acquire the initial state at the timing shown in FIG. 28. FIG. 28 is a diagram showing an example of the timing for acquiring the initial state. The waveforms in FIG. 28 correspond to the following processes from above: human body detection, selection of the seating or measurement start button, pre-flush / pre-mist (e.g., spraying mist (water) onto the surface of the bowl portion 8), toilet flushing, sensor measurement (urine measurement), and sensor measurement (reference state acquisition). For example, the horizontal direction of the waveforms in FIG. 28 corresponds to the passage of time, and the points (periods) where the waveforms rise correspond to the periods during which the processes corresponding to those waveforms are executed. As shown in FIG. 28, the initial state, which serves as the reference state, is acquired during a period before sensor measurement (urine measurement) begins.

[0286] For example, the toilet system 1 may determine the initial state during the period from the detection of a human body to the start of measurement. For example, the initial state may be the minimum, average, median, or maximum value of the water seal movement during the period.

[0287] In this way, the initial state is acquired during a period (also referred to as the "target period") that includes at least a portion of the period in which the waveform rises in Figure 28 (also referred to as the "candidate acquisition period"). The hatched period in Figure 28 (also referred to as the "influence period") corresponds to a period in which pre-flushing, pre-misting, etc. may be performed, causing turbulence on the water surface. Therefore, the toilet system 1 may acquire the initial state by using the period of the candidate acquisition period excluding the influence period as the target period. In other words, the toilet system 1 may acquire the initial state excluding the influence period.

[0288] As described above, the tremor determination model is trained to receive tremor information as input and output any information such as a tremor type corresponding to the input tremor information. For example, when tremor information is input, the tremor determination model is trained to output a label corresponding to the input tremor information and information on the amount of excrement corresponding to the input tremor information. For example, when tremor information is input, the tremor determination model is trained to output a label corresponding to the input tremor information and information on the amount of urine corresponding to the input tremor information.

[0289] For example, when vibration information is input, the vibration determination model is trained to output information indicating the level of urine volume corresponding to the input vibration information. For example, when vibration information is input, the vibration determination model is trained to output information indicating the level of urine volume corresponding to the input vibration information, in four levels: small, medium, and large. Note that the information on urine volume output by the vibration determination model is not limited to four levels, but may be three or less levels or five or more levels, or may be a specific numerical value indicating the urine volume.

[0290] For example, the toilet system 1 acquires information such as that shown in FIG. 29. FIG. 29 is a diagram showing an example of the distance between the sensor and the water surface. The vertical axis of FIG. 29 corresponds to the distance between the sensor and the water surface of the sealed water, and the horizontal axis corresponds to time. For example, the toilet system 1 may detect the distance using an image captured by a sensor such as a camera. In this case, the toilet system 1 may determine (estimate), for example, a location (position) with high brightness as a location (position) with a short distance. As mentioned above, the sensor is not limited to an image sensor that captures an image, and may be any sensor that can acquire information indicating the distance between the sensor and the water surface, such as an ultrasonic sensor.

[0291] For example, the toilet system 1 acquires the information shown in FIG. 30 from the information shown in FIG. 29. FIG. 30 is a diagram showing an example of sway determination and urine volume. For example, the toilet system 1 acquires the information shown in FIG. 30 using a sway determination model that outputs information on a label and urine volume. FIG. 30 shows that it was determined that there was no excrement from 0 to 2 seconds and from 13 to 15 seconds, and that an excretory act such as urination occurred between 2 and 13 seconds. That is, in FIG. 30, the toilet system 1 estimates the urination time to be 11 seconds. Note that the toilet system 1 may acquire the information shown in FIG. 30 using any information, not just the sway determination model, as long as it can acquire the information shown in FIG. 30.

[0292] For example, the toilet system 1 acquires the information shown in FIG. 31 from the information shown in FIG. 30. FIG. 31 is a diagram showing an example of calculating the total urine volume. The vertical axis of FIG. 31 corresponds to the urine volume per unit time (urine flow rate), and the horizontal axis corresponds to time. For example, the toilet system 1 plots points indicating the urine volume per unit time for the information shown in FIG. 30, excluding the period (7 to 9 seconds) in which feces are included in the determination. Note that the process shown in FIG. 31 is merely an example, and the toilet system 1 may also plot points based on the determination results for the period 7 to 9 seconds.

[0293] The toilet system 1 then calculates the area of ​​the region enclosed by the line connecting the points and the horizontal axis, and calculates the total urine volume from the area. In Figure 31, the toilet system 1 calculates the area of ​​the hatched region and converts the area into urine volume to calculate the total urine volume. In this way, the toilet system 1 may calculate the total urine volume by integrating the state determined from the shaking.

[0294] The toilet system 1 may have a relationship between swaying and urine flow rate in advance. For example, the toilet system 1 may store information such as that shown in FIG. 32 in, for example, the storage unit 120. FIG. 32 is a diagram showing an example of the relationship between swaying and urine volume. For example, FIG. 32 shows information indicating the correspondence between each level of urine volume and a numerical value indicating a specific volume. In this case, the toilet system 1 may calculate the total urine volume to be, for example, 220 mL, based on the information shown in FIG. 32, by converting the level at each time into a numerical value indicating a specific volume and integrating it.

[0295] Furthermore, for example, the toilet system 1 may store information such as that shown in FIG. 33 in, for example, the storage unit 120. FIG. 33 is a diagram showing an example of the relationship between shaking and urine volume. For example, FIG. 33 is information showing the correspondence between each level of urine volume and a numerical value corresponding to the area. In this case, the toilet system 1 calculates the area by converting the level at each time into a numerical value corresponding to the area and integrating it based on the information shown in FIG. 33. For example, the toilet system 1 calculates the area to be 22.

[0296] The toilet system 1 then calculates the total urine volume from the calculated area. For example, the toilet system 1 calculates the total urine volume using the area and a conversion formula based on the relationship shown in Figure 34. Figure 34 is a diagram showing an example of the relationship between area and total urine volume. For example, Figure 34 shows an example of a calibration curve for calculating the total urine volume from the area. For example, the toilet system 1 calculates the total urine volume to be 220 mL from the calculated area of ​​"22."

[0297] The toilet system 1 may provide (display) information using any of the acquired information. For example, the toilet system 1 may display information in stages such as large, medium, and small instead of displaying numerical values.

[0298] The toilet system 1 may also calculate the total amount of excrement using information on the water level difference as shown in Figure 35. Figure 35 is a diagram showing an example of how the total amount of excrement is calculated. Note that explanations of points similar to those described above will be omitted where appropriate. For example, the total amount of excrement here refers to the amount of excrement including urine and feces (stool).

[0299] For example, the toilet system 1 detects a still state before and after sloshing caused by urine. In Fig. 35, the toilet system 1 detects 0 to 2 seconds and 13 to 15 seconds as a still state before and after sloshing caused by urine.

[0300] The toilet system 1 then detects the total amount of excrement from the difference in water levels before and after. In Figure 35, the toilet system 1 determines the difference in water levels between 2 seconds and 13 seconds as the difference in water levels before and after, and detects the total amount of excrement from this difference in water levels before and after. In this case, the toilet system 1 may calculate the total amount of excrement using a conversion formula based on the relationship between the water level difference and a value indicating an amount such as the total amount of excrement. For example, the toilet system 1 converts the water level difference to calculate a value indicating an amount, and calculates the calculated value indicating an amount as the total amount of excrement.

[0301] Furthermore, when calculating the total urine volume, the toilet system 1 may calculate the total urine volume by subtracting information about the time when stool shaking occurred. In FIG. 35, the toilet system 1 may calculate the total urine volume by subtracting information corresponding to 7 to 9 seconds when stool shaking occurred. For example, the toilet system 1 may subtract the same amount for each time when stool shaking occurred, determine the amount of stool from the shaking and subtract it, or determine that stool has been present and not calculate the total urine volume. In this way, the toilet system 1 may calculate the total urine volume by subtracting information about the time when stool shaking occurred.

[0302] Note that the above is merely an example, and for example, the toilet system 1 may use information from a two-dimensional image. The toilet system 1 determines the presence and amount of excrement using information about the swaying of the water seal in a two-dimensional image of the toilet bowl 7 viewed from above. The toilet system 1 determines the presence and amount of excrement using information about the swaying of the water seal in a two-dimensional image of the bowl portion 8 captured from above. For example, the toilet system 1 determines the presence and amount of excrement based on the pattern (ripples) on the water seal surface in a two-dimensional image of the bowl portion 8 captured from above.

[0303] For example, when a two-dimensional image is input as the vibration information, the toilet system 1 acquires information such as that shown in Fig. 36 using a vibration determination model that outputs a label and urine volume information corresponding to the input vibration information. Fig. 36 is a diagram showing an example of using a two-dimensional image.

[0304] 36, when trembling information is input, the trembling determination model is trained to output information indicating the level of urine volume corresponding to the input trembling information, in three levels: small, large, etc. Note that the urine volume information output by the trembling determination model is not limited to three levels, but may be two levels or four or more levels as described above, or may be a specific numerical value indicating the urine volume.

[0305] Figure 36 shows that, out of the 0 to 9 seconds, it was determined that no excrement was present during the 0 to 1 second and 8 to 9 seconds, and that excretory behavior such as urination was determined to have occurred during the remaining time. That is, in Figure 36, the toilet system 1 estimates the urination time to be 7 seconds. Note that the toilet system 1 may acquire information such as that shown in Figure 36 using any information, not just using a sway determination model, as long as it is possible to acquire information such as that shown in Figure 36.

[0306] For example, the toilet system 1 acquires the information shown in Figure 37 from the information shown in Figure 36. Figure 37 is a diagram showing an example of calculation of total urine volume. The vertical axis of Figure 37 corresponds to the urine volume per unit time (urine flow rate), and the horizontal axis corresponds to time. For example, the toilet system 1 plots points indicating the urine volume per unit time for a period such as that shown in Figure 36.

[0307] The toilet system 1 then calculates the area of ​​the region enclosed by the line connecting those points and the horizontal axis. For example, the toilet system 1 calculates the area to be 8. The toilet system 1 then calculates the total urine volume from the calculated area.

[0308] The toilet system 1 may have a relationship between area and urine flow rate in advance. For example, the toilet system 1 may store information such as that shown in FIG. 38 in, for example, the storage unit 120. FIG. 38 is a diagram illustrating an example of the relationship between area and total urine volume. FIG. 38 illustrates information showing the correspondence between area and a level indicating the total urine volume. For example, FIG. 38 illustrates an example of converting area to total urine volume. Note that FIG. 38 illustrates an example in which the total urine volume level is indicated in four levels: 0, small, medium, and large. However, the information on the total urine volume is not limited to four levels, and may be three or fewer levels, five or more levels, or a specific numerical value indicating the total urine volume. In FIG. 38, for example, an area of ​​"3" corresponds to both an area of ​​"less than 5" and an area of ​​"less than 20." In this case, the toilet system 1 determines that the area corresponds to the smaller area of ​​"less than 5," and calculates the total urine volume corresponding to the area of ​​"3" as "small." In FIG. 38, the area "less than 5" may be the area "1 or more and less than 5", and the area "less than 20" may be the area "5 or more and less than 20".

[0309] For example, the toilet system 1 calculates the total urine volume based on the area and the relationship shown in Fig. 38. In Fig. 38, the toilet system 1 refers to the information indicating the correspondence relationship and calculates the total urine volume of "medium" corresponding to the area "less than 20" (i.e., 5 or more and less than 20) to which the calculated area of ​​"8" corresponds as the total urine volume corresponding to the calculated area of ​​"8".

[0310] As described above, the detection range DA1 is not limited to the range shown in Fig. 7 and may be any range. For example, the detection range DA1 may include the surface (ceramic surface) of the bowl portion 8. For example, the detection range DA1 may include the surface of the bowl portion 8 that is outside the water seal surface WS when the water seal surface WS is not shaking (in a stationary state). The toilet system 1 then includes the surface (ceramic surface) of the bowl portion 8 in the detection range DA1, acquires information indicating an area where shaking occurs that corresponds to an area where the water seal is present, and calculates information related to urine, such as urine volume, using the acquired information.

[0311] For example, the detection range DA1 may be a range as shown in Figure 39. Figure 39 is a diagram showing an example of the detection range. For example, the schematic diagram of the toilet bowl at the top of Figure 39 is a side cross-sectional view showing the general configuration of the toilet seat apparatus in order to show the detection range. Thus, in Figure 39, in order to illustrate an example of the detection range DA1, the other configuration is shown in a simplified manner.

[0312] As shown in FIG. 39, the detection range DA1 may include the surface of the bowl portion 8. For example, the detection range DA1 may be a range that can detect changes in the boundary between the water seal surface WS and the bowl portion 8 (ceramic) due to shaking of the water seal surface WS. Note that FIG. 39 shows a case where the detection range DA1 includes both ends (front and back) of the boundary between the water seal surface WS and the bowl portion 8 (ceramic), but the detection range DA1 can be set to any range as long as the information necessary for processing can be acquired. For example, if processing is possible with information on at least one end of the boundary between the water seal surface WS and the bowl portion 8 (ceramic), the detection range DA1 may be any range that includes at least one end of the boundary between the water seal surface WS and the bowl portion 8 (ceramic).

[0313] 39 shows the relationship between the detection range DA1 and the water seal surface WS. t1 corresponds to one end (front end) of the detection range DA1, and position X t2 corresponds to the other end (rear end) of the detection range DA1.

[0314] In the lower graph of Figure 39, position X WS1corresponds to one end (front end) of the water seal surface WS. That is, position X WS1 corresponds to the boundary at one end (front end) of the water sealing surface WS and the bowl portion 8 (ceramic).

[0315] Also, in the graph at the bottom of Figure 39, position X WS2 corresponds to the other end (rear end) of the water seal surface WS. That is, position X WS2 corresponds to the boundary on the other end side (rear end side) between the water sealing surface WS and the bowl portion 8 (ceramic).

[0316] The straight line portion in the graph at the bottom of FIG. 39 corresponds to the bowl portion 8 (pottery). That is, in the graph at the bottom of FIG. 39, the position X t1 and position X WS1 The area between the two points corresponds to one side (front side) of the bowl portion 8 (ceramic). In the graph at the bottom of Figure 39, the position X t2 and position X WS2 The space between corresponds to the other side (rear side) of the bowl portion 8 (ceramic).

[0317] The dotted line in the lower graph of Figure 39 corresponds to the water seal surface WS. WS1 and position X WS2 The area between corresponds to the water seal surface WS. Note that Fig. 39 shows a state when urination is not in progress, for example, a state after urination, and shows a state in which the fluctuation of the water seal surface WS is small.

[0318] When the detection range DA1 includes the bowl portion 8 (ceramic), the information acquired after urination is as shown in Fig. 40. Fig. 40 is a diagram showing an example of shaking after urination. Note that explanations of points similar to those explained in Fig. 39 etc. will be omitted as appropriate.

[0319] The upper graph in FIG. 40 (also referred to as the "first graph") shows an example of information acquired in a reference (default) state corresponding to a reference state (initial state, etc.). WS1 corresponds to the boundary between the water sealing surface WS and the bowl portion 8 (ceramic) at one end (front end) in the standard (default) state. WS2corresponds to the rear end (rear end side) boundary between the water sealing surface WS and the bowl portion 8 (ceramic) in the standard (default) state.

[0320] The graph in the center of FIG. 40 (also referred to as the "second graph") shows an example of information acquired when the amount of urination is small. The difference ΔWs in the graph in the center of FIG. 40 (second graph) is the difference between the boundary (position indicated by the dashed line) on one end side (front end side) of the water sealing surface WS and the bowl portion 8 (ceramic) in the second graph and the position X WS1 The difference between the boundary (position indicated by the dashed line) between the water sealing surface WS and the bowl portion 8 (ceramic) on the rear end side (rear end side) in the second graph and the position X in the first graph WS2 This corresponds to the difference between the two. In the center graph (second graph) in Figure 40, the amount of urination is small and the fluctuation of the water seal surface WS is small, so the value of the difference ΔWs is small. Note that the example shown in Figure 40 is a conceptual diagram to show that the boundary changes due to the fluctuation of the water seal surface, and the value of the difference ΔWs on both sides (left and right) in each graph may be different.

[0321] The lower graph in Fig. 40 (also referred to as "third graph") shows an example of information acquired when the amount of urination is large. The difference ΔWs in the lower graph (third graph) in Fig. 40 is the difference between the boundary (position indicated by the dashed line) on one end side (front end side) of the water sealing surface WS and the bowl portion 8 (ceramic) in the third graph and the position X WS1 The difference between the boundary (position indicated by the dashed line) between the water sealing surface WS and the bowl portion 8 (ceramic) on the rear end side (rear end side) in the third graph and the position X in the first graph WS2 In the lower graph (third graph) in FIG. 40, the amount of urination is large and the fluctuation of the water seal surface WS is large, so the value of the difference ΔWs is large.

[0322] The detection range DA1 shown in FIG. 41 is the detection range DA1 shown in FIG. 39, and the lower graph in FIG. 41 shows the state during urination, in which the water sealing surface WS sways significantly. When the detection range DA1 includes the bowl portion 8 (ceramic), the information acquired during urination is as shown in FIG. 42. FIG. 42 is a diagram showing an example of swaying during urination. Note that explanations of points similar to those explained in FIG. 39, FIG. 40, etc. will be omitted as appropriate.

[0323] The upper graph (first graph) in FIG. 42 shows an example of information acquired in a reference (default) state corresponding to a reference state (initial state, etc.). The center graph (also called the second graph) in FIG. 42 shows an example of information acquired when the amount of urination is small. The difference ΔWs in the center graph (second graph) in FIG. 42 is the difference between the boundary (position indicated by the dashed line) on one end side (front end side) of the water sealing surface WS and the bowl portion 8 (ceramic) in the second graph and the position X in the first graph. WS1 The difference between the boundary (position indicated by the dashed line) between the water sealing surface WS and the bowl portion 8 (ceramic) on the rear end side (rear end side) in the second graph and the position X in the first graph WS2 In the center graph (second graph) in Fig. 42, the amount of urination is small and the fluctuation of the water seal surface WS is small, so the value of the difference ΔWs is small.

[0324] The lower graph (third graph) in Fig. 42 shows an example of information acquired when the amount of urination is large. The difference ΔWs in the lower graph (third graph) in Fig. 42 is the difference between the boundary (position indicated by the dashed line) on one end side (front end side) of the water sealing surface WS and the bowl portion 8 (ceramic) in the third graph and the position X WS1 The difference between the boundary (position indicated by the dashed line) between the water sealing surface WS and the bowl portion 8 (ceramic) on the rear end side (rear end side) in the third graph and the position X in the first graph WS2 In the lower graph (third graph) in FIG. 42, the amount of urination is large and the fluctuation of the water seal surface WS is large, so the value of the difference ΔWs is large. In this way, the information obtained during urination has large waves and strong momentum.

[0325] Furthermore, for example, the detection range DA1 may be a range as shown in Fig. 43. Fig. 43 is a diagram showing an example of a detection mode. Note that explanations of points similar to those explained in Figs. 39 to 42 etc. will be omitted as appropriate.

[0326] In FIG. 43, the detection range DA1 is the range from a position (viewpoint) when viewing the toilet bowl 7 from above in a plan view, and includes the water seal surface WS and the surface of the bowl portion 8. As mentioned above, in this case too, if processing is possible with information on at least one end of the boundary between the water seal surface WS and the bowl portion 8 (ceramic), the detection range DA1 may be any range that includes at least one end of the boundary between the water seal surface WS and the bowl portion 8 (ceramic). In this case, the toilet system 1 estimates information related to excrement, such as an estimate of urine volume, using a two-dimensional image captured of the detection range DA1 shown in FIG. 43. For example, the toilet system 1 estimates information related to excrement, such as an estimate of urine volume, based on changes in the area occupied by the water seal surface WS in the two-dimensional image.

[0327] In the case of the detection range DA1 as shown in Fig. 43, the information acquired after urination is, for example, information as shown in Fig. 44. Fig. 44 is a diagram showing an example of the relationship between detection and urine volume.

[0328] The upper image in Figure 44 (also referred to as "first image") shows an example of information acquired in a reference (default) state corresponding to a reference state (initial state, etc.). The hatched oval portion in the image in Figure 44 corresponds to the water sealing surface WS, and the other portions (peripheral portions) correspond to the surface of the bowl portion 8, etc.

[0329] The dotted line on the left side of Fig. 44 corresponds to one end (front end) of the water sealing surface WS in the standard (default) state. In other words, the dotted line on the left side of Fig. 44 corresponds to the boundary on one end side (front end side) between the water sealing surface WS and the bowl portion 8 (ceramic) in the standard (default) state.

[0330] The dotted line on the right side of Fig. 44 corresponds to the other end (rear end) of the water sealing surface WS in the standard (default) state. That is, the dotted line on the right side of Fig. 44 corresponds to the rear end (rear end side) boundary between the water sealing surface WS and the bowl portion 8 (ceramic) in the standard (default) state.

[0331] The central image in Fig. 44 (also referred to as the "second image") shows an example of information acquired when the amount of urination is small. In the central image (second image) in Fig. 44, the amount of urination is small and the fluctuation of the water seal surface WS is small, so the increase in the water seal surface WS from the standard (default) state (the increase in the left and right direction in Fig. 44) is small.

[0332] The lower image in Fig. 44 (also referred to as "third image") shows an example of information acquired when the amount of urination is large. In the lower image (third image) in Fig. 44, the amount of urination is large and the fluctuation of the water seal surface WS is large, so the increase in the water seal surface WS from the standard (default) state (the increase in the left and right direction in Fig. 44) is large.

[0333] The toilet system 1 executes the above-mentioned process. For example, the toilet system 1 acquires information about urine by detecting the boundary line between the water seal surface WS, which is the water surface of the sealed water, and the surface of the bowl section 8 based on the change in the sensor output. The toilet system 1 determines the range where the change in state exceeds a predetermined value as the water seal surface WS, and acquires information about urine based on the change in the range.

[0334] The toilet system 1 acquires information about urine from information about the water seal pulsation and information about changes in the water seal level. For example, the toilet system 1 acquires water seal pulsation information based on the amount of displacement of the boundary position between the edge of the water seal upper surface (such as the water seal surface WS) in the bowl portion 8 and the upper surface of the bowl portion 8. The toilet system 1 detects water seal pulsation information based on the amount of displacement of the vertical distance between the sensor and waves generated in the water seal. The toilet system 1 acquires water seal pulsation information excluding fluctuations in the water seal due to a pre-cleaning process on the surface of the bowl portion 8. The toilet system 1 acquires water seal pulsation information based on the state of the water seal before the user uses the toilet. For example, the state of the water seal may be a predetermined water level, the boundary position between the edge of the water seal upper surface (such as the water seal surface WS) in the bowl portion 8 and the surface of the bowl portion 8, etc.

[0335] The control unit 130 of the toilet system 1 controls the amount of flush water supplied to the bowl portion 8 based on information about the swaying of the seal water. The control unit 130 estimates information about excrement, including information about urine excreted by the user, based on information about the swaying of the seal water obtained by the sensor, and performs control to present the excrement information or information obtained from the excrement information to the user. The sensor has a predetermined detection range within the bowl portion 8 that includes at least the seal water. The control unit 130 estimates the excrement information based on the output of the sensor corresponding to the bowl portion 8.

[0336] 4. Fourth Embodiment Next, a configuration example using a sound detection sensor (also referred to as a "sound sensor") will be described below as a fourth embodiment. Note that the external configuration of the toilet system 1 according to the fourth embodiment using the sound sensor is the same as that of the toilet system 1 according to the second embodiment when the lid 110 is closed, and therefore illustrations and detailed description thereof will be omitted.

[0337] <4-1. Configuration of the toilet seat device> Next, the configuration of a toilet seat device 2 according to a fourth embodiment will be described with reference to Fig. 45. Fig. 45 is a perspective view showing an example of the configuration of a toilet seat device according to the fourth embodiment. Specifically, Fig. 45 is a view showing a state in which the lid 110 of the toilet seat device 2 has been removed. Note that, in the toilet seat device 2 according to the fourth embodiment, descriptions of the same points as those of the toilet seat device 2 according to the second embodiment will be omitted as appropriate.

[0338] When the lid 110 is in the closed state, the sound detection sensor 34A is hidden behind the lid 110 (see FIG. 3). When the lid 110 is in the closed state, the lid 110 is located in front of the sound detection sensor 34A. In this way, the lid 110 is located in front of the sound detection sensor 34A in the closed state.

[0339] As shown in FIG. 45, when the lid 110 is removed, the sound detection sensor 34A is exposed from the opening 31 of the main body cover 30. For example, when the lid 110 is open (open state), as shown in FIG. 45, the lid 110 is not positioned in front of the sound detection sensor 34A. As a result, when the lid 110 is open, the sound detection sensor 34A is exposed. When the lid 110 is open, the sound detection sensor 34A can detect sounds inside the toilet bowl 7. Note that the toilet seat device 2 does not necessarily have the lid 110. In this case, the toilet seat device 2 does not have the lid 110 and the actuator 111, and the sound detection sensor 34A may be always exposed.

[0340] As shown in Figure 45, sound detection sensor 34A is disposed with its detection unit for detecting sound facing opening 31 of main body cover 30. For example, sound detection sensor 34A is disposed above or within bowl portion 8. Furthermore, a sound insulating wall 341 is provided within main body cover 30 in a position surrounding sound detection sensor 34A. This allows toilet system 1 to prevent sound detection sensor 34A from detecting sounds generated within main body cover 30, enabling sound detection sensor 34A to accurately detect sounds within the toilet bowl 7.

[0341] An example of sound detection by the sound detection sensor 34A will now be described with reference to FIG. 46. FIG. 46 is a side cross-sectional view showing an example of the configuration of a toilet seat device according to the fourth embodiment. For example, FIG. 46 shows the position of the lid 110 when the sound detection sensor 34A is in sound detection mode. As shown in FIG. 46, when the sound detection sensor 34A is in sound detection mode, the lid 110 is positioned above the detection direction of the sound detection sensor 34A. As a result, when the sound detection sensor 34A is in sound detection mode, the lid 110 functions as a sound-insulating wall that suppresses sound collection from above the sound detection sensor 34A. In this way, when the sound detection sensor 34A is in sound detection mode, the toilet system 1 operates so as to provide a sound-insulating wall that suppresses sound collection from above the sound detection sensor 34A.

[0342] In the example of Figure 46, the lid 110 is in the open position, exposing the sound detection sensor 34A. The sound detection sensor 34A detects sounds inside the toilet bowl 7. That is, the sound detection sensor 34A detects sounds on the surface of the bowl 8 of the toilet bowl 7. The detection range DA1 in Figure 46 indicates the range detected by the sound detection sensor 34A. With this configuration, the toilet system 1 is able to detect sounds inside the toilet bowl 7 using the sound detection sensor 34A. Note that the detection range DA1 shown in Figure 46 is just one example, and the sound detection sensor 34A can be positioned in any manner as long as it can detect at least some of the sounds inside the toilet bowl 7.

[0343] 45 and 46 show an example of a configuration in which the toilet seat device 2 has the sound detection sensor 34A disposed adjacent to the washing nozzle 6, but the sound detection sensor 34A is not limited to being disposed adjacent to the washing nozzle 6 and may be disposed in various positions as long as the desired detection is possible. For example, depending on the type of sensor used, the sound detection sensor 34A is disposed in a position that suits the detection mode of that sensor.

[0344] <4-2. Functional configuration of the toilet seat device> Next, the functional configuration of the toilet seat device 2 will be described with reference to Fig. 47. Fig. 47 is a block diagram showing an example of the configuration of a toilet seat device according to the fourth embodiment. As shown in Fig. 47, the toilet seat device 2 includes a human body detection sensor 32, a seating detection sensor 33, a sound detection sensor 34A, a control device 100, a nozzle motor 61, a flushing nozzle 6, a solenoid valve 71, a lid 110, and an actuator 111. Note that Fig. 47 omits illustration of some of the configuration of the toilet seat device 2 described in Fig. 4 (such as the main body 3, toilet seat 5, and toilet bowl 7).

[0345] 47 is merely an example, and the toilet seat device 2 can have any configuration. The human body detection sensor 32, seating detection sensor 33, sound detection sensor 34A, control device 100, etc. are arranged in any desired locations. For example, the sound detection sensor 34A is provided in the main body 3 of the toilet seat device 2. The toilet seat device 2 transmits and receives information to and from an information processing device such as the operating device 10 via a predetermined network (such as the Internet) by a communication device (such as the communication unit 101 of the control device 100) in a wired or wireless manner.

[0346] The sound detection sensor 34A is a sensor that detects sound. The sound detection sensor 34A detects sound inside the toilet bowl 7. For example, the sound detection sensor 34A detects sound around the water seal of the toilet bowl 7. The sound detection sensor 34A enters sound detection mode in response to the detection of a human body. For example, the sound detection sensor 34A enters sound detection mode in response to the detection of a human body by the human body detection sensor 32. For example, the sound detection sensor 34A enters sound detection mode while a person is detected by the human body detection sensor 32, and enters a mode in which sound detection is not performed (stop mode) while a person is not detected by the human body detection sensor 32. Any configuration can be adopted for the sound detection sensor 34A as long as it can detect the desired sound.

[0347] The sound detection sensor 34A is a microphone. For example, the sound detection sensor 34A is preferably a unidirectional (cardioid) microphone. Note that the above is merely an example, and any sensor may be used as the sound detection sensor 34A as long as it can detect the desired sound. The toilet system 1 may also have a sensor that detects sound within the main body 3, a sound output device (speaker) that outputs sound, etc., which will be described later.

[0348] Furthermore, when the toilet system 1 detects the presence or absence of feces, the toilet system 1 may have a feces detection means for detecting the presence or absence of feces. For example, the toilet system 1 may have an imaging means for imaging the inside of the bowl portion 8 as the feces detection means for detecting the presence or absence of feces. For example, the feces detection means may be a line sensor arranged facing the inside of the bowl portion 8, and may detect fallen objects such as excrement falling inside the bowl portion 8. Alternatively, the feces detection means may be a camera arranged facing the water seal inside the bowl portion 8, and may detect fallen objects such as excrement that have landed on the water seal. Note that the sound detection sensor 34A may function as the feces detection means.

[0349] The control device 100 controls various components and processes. The control device 100 is a computer (information processing device) that executes various information processes such as calculating the urination time and urine volume. The control device 100 calculates the urination time based on the sound inside the toilet bowl 7 that receives the excrement. For example, the control device 100 calculates the urination time based on the time during which the sound corresponding to urine is detected. The control device 100 calculates the total urine volume based on the calculated urination time and the urine volume per unit time (unit urine volume) stored in the memory unit. Note that in the control device 100 according to the fourth embodiment, explanations of the same points as those in the control device 100 according to the second embodiment will be omitted as appropriate.

[0350] The control device 100 controls the lid 110 to be closed while the sound detection sensor 34A is not detecting anything, such as before a user uses the toilet 7. The control device 100 may also control the sound detection sensor 34A. In this case, the sound detection sensor 34A starts or stops detection in response to control from the control device 100. The control device 100 transmits control information to the sound detection sensor 34A to control the start and end of detection by the sound detection sensor 34A. For example, when the human body detection sensor 32 or the seating detection sensor 33 detects that a user has started using the toilet 7, the control device 100 transmits control information to the sound detection sensor 34A to cause the sound detection sensor 34A to start detection. For example, when the human body detection sensor 32 or the seating detection sensor 33 detects that a user has stopped using the toilet 7, the control device 100 transmits control information to the sound detection sensor 34A to cause the sound detection sensor 34A to end detection.

[0351] The lid 110 can be positioned in front of the sound detection sensor 34A and functions as a lid. The lid 110 is preferably formed of an opaque material to reduce the possibility of the sound detection sensor 34A being visible and to ensure the user's privacy. For example, the lid 110 may be formed in an opaque state by coloring. The lid 110 may have an opaque material (paint) applied to its surface. Note that the lid 110 is not limited to an opaque structure and may be transparent. The lid 110 can be transitioned between an open state and a closed state by an actuator 111, and is positioned in front of the sound detection sensor 34A or exposes the sound detection sensor 34A.

[0352] In the configuration shown in FIG. 47, the toilet seat device 2 includes the control device 100 and other components. However, the control device 100, the human body detection sensor 32, the seating detection sensor 33, the sound detection sensor 34A, and other components may be configured as separate devices from the toilet seat device 2. For example, the control device 100 may be configured as a separate device from the toilet seat device 2. For example, the control device 100 may be a server device and located at a location separate from the toilet seat device 2. In this case, the control device 100 communicates with each device, such as the toilet seat device 2, the human body detection sensor 32, the seating detection sensor 33, and the sound detection sensor 34A, and receives information necessary for calculating the urination time and urine volume from each device. In this case, the toilet seat device 2 may also have a configuration (such as a control circuit) for controlling various components of the toilet seat device 2, such as the nozzle motor 61, the solenoid valve 71, and the actuator 111. Note that the above is merely an example, and the toilet system 1 can adopt any device configuration as long as it is capable of performing the desired processing.

[0353] <4-3. Functional configuration of the control device> The functional configuration of the control device according to the fourth embodiment will be described below. Note that a functional block diagram of the control device 100 according to the fourth embodiment is the same as that of the control device 100 according to the second embodiment, so it is not shown in the figure, and differences from the control device 100 according to the second embodiment will be mainly described.

[0354] The control device 100 according to the fourth embodiment includes a communication unit 101, a storage unit 120, and a control unit .

[0355] The storage unit 120 according to the fourth embodiment stores various pieces of information required for processing. The storage unit 120 stores various pieces of information acquired from other devices such as various sensors. For example, the storage unit 120 stores information related to a learning model (model) used for processing. For example, the storage unit 120 stores a model used for calculating the urination time. For example, the storage unit 120 stores various pieces of information (for example, information related to thresholds) used in various types of information processing.

[0356] The storage unit 120 stores information used to determine the time when the user starts urination (also referred to as the "urination start time") and the time when the user finishes urination (also referred to as the "urination end time"). It stores various numerical values ​​(thresholds) such as a first predetermined value, a second predetermined value, a third predetermined value, and a fourth predetermined value. The storage unit 120 stores various numerical values ​​(thresholds) such as the first predetermined value, the second predetermined value, the third predetermined value, and the fourth predetermined value used to determine the urination start time and the urination end time. Note that the various numerical values ​​such as the first predetermined value, the second predetermined value, the third predetermined value, and the fourth predetermined value can be set to any value. Furthermore, for example, the storage unit 120 according to the fourth embodiment stores the information stored in the data storage means 14 described above.

[0357] The control unit 130 according to the fourth embodiment has an acquisition unit 131, a measurement unit 132, a determination unit 133, an estimation unit 134, and an output unit 135, and realizes or executes the functions and actions of information processing described below. For example, the control unit 130 according to the fourth embodiment executes the processes executed by the information processing units such as the dehydration estimation means 15, the evaluation means 16, the notification means 17, and the frequent urination estimation means 18 described above.

[0358] The acquisition unit 131 according to the fourth embodiment acquires various types of information in the same manner as the acquisition unit 131 according to the second embodiment. The acquisition unit 131 receives information (detection information, etc.) detected by each of the human body detection sensor 32, the seating detection sensor 33, and the sound detection sensor 34A from each sensor. For example, the acquisition unit 131 receives information related to a sound detected by the sound detection sensor 34A from the sound detection sensor 34A. The acquisition unit 131 acquires information to be used for processing from the storage unit 120.

[0359] The measurement unit 132 according to the fourth embodiment performs various measurements in the same manner as the measurement unit 132 according to the second embodiment. The measurement unit 132 uses information detected by the sound detection sensor 34A to measure the time (detection time) during which detection is performed by the sound detection sensor 34A.

[0360] The measurement unit 132 uses the information detected by the sound detection sensor 34A to measure the sound inside the toilet bowl 7. The measurement unit 132 uses the information detected by the sound detection sensor 34A to measure the time that the sound is being generated inside the toilet bowl 7. The measurement unit 132 uses the information detected by the sound detection sensor 34A to measure the time that the sound corresponding to urine is being generated.

[0361] The determination unit 133 according to the fourth embodiment performs the determination process in the same manner as the determination unit 133 according to the second embodiment.

[0362] The determination unit 133 may determine the cause of the sound based on the detection result by the sound detection sensor 34A. The determination unit 133 classifies the cause of the sound based on the detection result by the sound detection sensor 34A. The determination unit 133 determines which object caused the sound based on the detection result by the sound detection sensor 34A. The determination unit 133 determines the user's excrement based on the detection result by the sound detection sensor 34A.

[0363] For example, the determination unit 133 classifies a plurality of types of sounds including a first type of sound that is a sound caused by feces, a second type of sound that is a sound caused by urine, and a third type of sound that is a sound caused by feces and urine. For example, the determination unit 133 classifies the sound detected by the sound detection sensor 34A as a sound caused by feces, a sound caused by urine, or a sound caused by feces and urine.

[0364] The determination unit 133 may perform sound determination using any method. For example, the determination unit 133 may perform sound determination based on whether a signal level exceeds a threshold or by using AI (artificial intelligence). The determination unit 133 may perform sound determination using frequency analysis, image processing, machine learning, deep learning, or the like.

[0365] For example, the determination unit 133 determines the sound using AI technology. For example, the determination unit 133 may determine the sound using a model (also referred to as a "sound determination model") generated by machine learning. In this case, the sound determination model is trained in advance using training data that indicates classification decisions. This training data includes multiple combinations of sound information and labels (correct answer information) that indicate the type of sound corresponding to the sound information. The type here indicates the object that caused the sound to be generated, such as feces, urine, or both feces and urine.

[0366] The sound determination model is a model that receives sound information as input and outputs information indicating the type of sound corresponding to the input sound information. For example, the sound determination model is trained so that when sound information is input, it outputs information on a label (type of sound) corresponding to the input sound information. The sound determination model is trained using various techniques related to so-called supervised learning as appropriate. In this case, the sound determination model is stored in the storage unit 120, and the determination unit 133 may determine sound using the sound determination model stored in the storage unit 120. For example, the control device 100 may perform a learning process and generate the sound determination model. Note that the above is merely an example, and the determination unit 133 may determine sound using various information as appropriate.

[0367] Furthermore, the determination unit 133 may determine whether or not a defecation (faecal discharge) has occurred based on information detected by a stool detection means. The determination unit 133 may determine whether or not the user has defecate using information detected by a stool detection means such as the sound detection sensor 34A. The determination unit 133 determines whether or not a defecation has occurred based on an image captured by the stool detection means. Note that the above determination of whether or not a defecation has occurred is merely an example, and the determination unit 133 may determine whether or not a defecation has occurred by appropriately using various information when determining whether or not a defecation has occurred.

[0368] The estimation unit 134 according to the fourth embodiment functions as a dehydration estimation means. For example, the estimation unit 134 estimates the dehydration of the toilet user by the same processing as the dehydration estimation means 15 according to the first embodiment.

[0369] The estimation unit 134 estimates the dehydration state of the toilet user based on the urination data stored in the memory unit 120. The estimation unit 134 estimates the dehydration state when the integrated value of the urine volume over a predetermined period of time is less than a predetermined value. The estimation unit 134 estimates the dehydration state when the urination interval is longer than a predetermined interval. The estimation unit 134 estimates the dehydration state when the urine volume over a predetermined period of time is less than a predetermined volume. The estimation unit 134 estimates the dehydration state when the urination interval is longer than the predetermined interval and the urine volume is less than a predetermined volume.

[0370] The estimation unit 134 estimates the dehydration state based on the urination data and at least one of the toilet user's age-specific and season-specific urination characteristics. The estimation unit 134 suspends estimation of the dehydration state when the number of urinations based on the urination data is equal to or less than a predetermined number of times.

[0371] The estimation unit 134 according to the fourth embodiment functions as an evaluation unit. For example, the estimation unit 134 executes a process related to evaluation of dehydration of the toilet user by the same process as the evaluation unit 16 according to the first embodiment.

[0372] The estimation unit 134 functions as a dehydration assessment means that classifies the dehydration state of the toilet user into a plurality of levels based on the urination data. When the amount of urine included in the urination data is less than a predetermined amount, the estimation unit 134 classifies the dehydration state into a plurality of levels based on the urine color included in the urination data of the toilet user.

[0373] The estimation unit 134 according to the fourth embodiment functions as a frequent urination estimation means. For example, the estimation unit 134 estimates the frequent urination of the toilet user by the same processing as the frequent urination estimation means 18 according to the first embodiment.

[0374] The estimation unit 134 estimates the toilet user's frequent urination based on the urination data. The estimation unit 134 estimates frequent urination when the urination interval is shorter than a predetermined period.

[0375] The estimation unit 134 estimates the toilet user's frequency of urination based on the urination data stored in the memory unit 120. The estimation unit 134 estimates nocturia based on the urine volume or urine flow rate per night, or the average urine volume or average urine flow rate during the night, using the nighttime urination information identified from the urination information and other urination information.

[0376] The estimation unit 134 estimates nocturia based on the daytime and nighttime urination data identified by the urination information and other urination information. The estimation unit 134 estimates nocturia based on the daytime urine volume or urine flow rate per urination and the nighttime urine volume or urine flow rate per urination.

[0377] The estimation unit 134 estimates nocturia based on the average daytime urine volume or average urine flow rate and the average nighttime urine volume or average urine flow rate. The estimation unit 134 estimates nocturia using the nighttime urination information identified from the urination information and other urination information when there are multiple urinations at night and the relationship between the urine volume or urine flow rate per urination and the interval between urination times satisfies a predetermined condition.

[0378] The estimation unit 134 according to the fourth embodiment performs various processes such as calculation processes, similar to the estimation unit 134 according to the second embodiment.

[0379] The estimation unit 134 calculates the urination time based on the time when a sound corresponding to urine is detected from within the bowl of the toilet detected by the sound detection sensor 34A. The estimation unit 134 calculates the total urine volume based on the calculated urination time and the urine volume per unit time stored in the memory unit 120.

[0380] The estimation unit 134 performs control not to adopt sound information about the cleaning when cleaning is detected based on the cleaning sound stored in the memory unit 120. The estimation unit 134 performs control not to adopt sound information about the sound dummy device when the sound dummy device has operated based on the sound generated by the sound dummy device stored in the memory unit 120. The estimation unit 134 performs control not to adopt sound information about the local cleaning device when the local cleaning device has operated based on the sound generated during operation of the local cleaning device (cleaning nozzle 6, etc.) stored in the memory unit 120.

[0381] The estimation unit 134 calculates the time of the sound corresponding to the second type sound or the third type sound as the urination time. When a sound detected by the sound detection sensor 34A is louder than a predetermined threshold, the estimation unit 134 calculates the urination time by excluding the time of the loud sound. When defecation is detected by a stool detection means that can detect the presence or absence of defecation, the estimation unit 134 calculates the urination time by excluding the time of the sound assumed to be defecation.

[0382] For example, the estimation unit 134 associates information related to excrement, such as urine volume and urination time, acquired by the above-described processing with time information (date and time, time period, period, etc.) related to the time when the information was acquired, and registers the information in the storage unit 120. For example, the estimation unit 134 executes processing using the acquired information related to excrement and the time information corresponding to the information. Through such processing, the estimation unit 134 estimates information used to estimate frequent urination.

[0383] The output unit 135 according to the fourth embodiment functions as a notification unit. For example, the output unit 135 performs a process for providing information about dehydration of the toilet user in the same manner as the notification unit 17 according to the first embodiment.

[0384] The output unit 135 notifies a predetermined destination of highlight information indicating the health status of the toilet user based on urination data for a predetermined period including the latest urination data. If the number of urinations based on the urination data is equal to or less than a predetermined number, the output unit 135 does not notify the predetermined destination of the highlight information.

[0385] The output unit 135 notifies a predetermined destination of recommendation information for improving the health condition of the toilet user based on urination data for a predetermined period, including the most recent urination data. If the number of urinations based on the urination data is less than a predetermined number, the output unit 135 does not notify the predetermined destination of the recommendation information. The output unit 135 notifies the predetermined destination of the next recommendation information generated based on predetermined input information in response to the recommendation information received by the toilet user.

[0386] The output unit 135 according to the fourth embodiment executes output processing to output various types of information, similar to the output unit 135 according to the second embodiment.

[0387] <4-4. Example of calculating excretion time> Here, an example of calculating the excretion time will be described with reference to Figure 48. Figure 48 is a diagram showing an example of calculating the excretion time. For example, Figure 48 is a diagram showing an example of sound generated in a toilet bowl that is the detection target. Chart GR1 in Figure 48 shows an example of the waveform of sound detected in a toilet bowl 7 where urination has occurred. In Figure 48, the vertical axis represents amplitude (voltage), i.e., the volume of the sound, and the horizontal axis represents time.

[0388] In Fig. 48, as shown in chart GR1, for sound detected by sound detection sensor 34A, an amplitude exceeding a predetermined threshold (Δs) is detected at time t1. In Fig. 48, as shown in chart GR1, an amplitude exceeding Δs is detected within a predetermined time between times t1 and t2. Then, in Fig. 48, as shown in chart GR1, for sound detected by sound detection sensor 34A, a period continues for a predetermined time during which an amplitude exceeding Δs is not detected at time t2. As a result, the control device 100 calculates the time between time t1 and time t2 as the excretion time (urination time) based on the sound for which an amplitude exceeding Δs is detected.

[0389] <4-5. Processing flow> From here, the processing flow executed by the toilet system will be explained. The toilet system 1 executes the following third process, fourth process, and fifth process. The toilet system 1 may execute any of the third to fifth processes. In the following, the toilet system 1 will be described as the processing subject, but the third to fifth processes may be executed by any device, such as the control device 100 or various sensors such as the sound detection sensor 34A, depending on the device configuration included in the toilet system 1.

[0390] <4-5-1. Third Process> First, a processing example shown in Fig. 49 will be described. Fig. 49 is a flowchart showing an example of a processing procedure executed by the toilet system. Specifically, Fig. 49 is a flowchart showing an example of a third processing procedure for calculation related to urination time and urine volume.

[0391] In Figure 49, the toilet system 1 determines whether or not a measurement start trigger has been received (step S301). For example, the toilet system 1 determines that a measurement start trigger has been received when it detects that a user has started using the toilet 7. If the toilet system 1 determines that a measurement start trigger has not been received (step S301: No), it repeats the processing of step S301.

[0392] When the toilet system 1 determines that a measurement start trigger has occurred (step S301: Yes), it sets "t=0" (step S302). For example, when the toilet system 1 detects that the user has started using the toilet 7 and determines that a measurement start trigger has occurred, it initializes the value of the urination score t, which counts the urination time, to 0.

[0393] Then, the toilet system 1 acquires the initial state (step S303). For example, the toilet system 1 acquires the sound inside the toilet bowl 7 detected by the sound detection sensor 34A at that time (before the user starts urination) as the initial state.

[0394] The toilet system 1 starts measurement (step S304). For example, the toilet system 1 starts measuring the sound inside the toilet bowl 7 using the sound detection sensor 34A. Then, the toilet system 1 calculates the difference from the initial state (step S305). For example, the toilet system 1 calculates the difference between the sound measured in step S304 and the initial state acquired in step S303.

[0395] The toilet system 1 determines whether or not there is a sound (step S306). For example, if the toilet system 1 detects a sound corresponding to urine, it determines that there is a sound. If the toilet system 1 determines that there is no sound (step S306: No), it performs the process of step S311.

[0396] If the toilet system 1 determines that there is a sound (step S306: Yes), it sets "ts=t1" (step S307). For example, if the toilet system 1 determines that there is a sound corresponding to urine, it sets the time t1 when the sound corresponding to urine began to be detected as the urination start time ts.

[0397] The toilet system 1 determines whether or not there is no sound (step S308). For example, the toilet system 1 determines that there is no sound when it no longer detects a sound corresponding to urine. If the toilet system 1 determines that there is no sound (step S308: No), it repeats the process of step S308.

[0398] If the toilet system 1 determines that there is sound (step S308: Yes), it sets "te = t2" (step S309). For example, if the toilet system 1 determines that there is no sound, it sets the time t2 when sound corresponding to urine is no longer detected as the urination end time te.

[0399] Then, the toilet system 1 sets "t=t+(te-ts)" (step S310). For example, the toilet system 1 adds the value obtained by subtracting the urination start time ts from the urination end time te to the urination score t.

[0400] Then, the toilet system 1 determines whether or not a measurement end trigger has been generated (step S311). For example, the toilet system 1 determines that a measurement end trigger has been generated when it detects that the user has finished using the toilet 7. If the toilet system 1 determines that a measurement end trigger has not been generated (step S311: No), it returns to step S305 and repeats the process.

[0401] When the toilet system 1 determines that a measurement end trigger has been received (step S311: Yes), it ends the measurement (step S312). Then, the toilet system 1 calculates the total urination time (step S313). For example, the toilet system 1 calculates the total urination time based on the value of the urination score t, which is the counted urination time. For example, if the unit of the urination score t corresponds to seconds, the toilet system 1 calculates the number of seconds of the value of the urination score t as the total urination time. In this case, if the urination score t is "5", the toilet system 1 calculates the total urination time to be 5 seconds. The toilet system 1 calculates the total urination time using a function (urination time calculation function) that inputs the urination score t and outputs the total urination time. In this case, if the urination score t is "5", the toilet system 1 may input "5" into the urination time calculation function and determine the value output by the urination time calculation function as the total urination time.

[0402] Then, the toilet system 1 estimates the urine volume (step S314). For example, the toilet system 1 calculates the urine volume using the total urination time calculated in step S313. The toilet system 1 calculates the urine volume by multiplying the calculated urination time by the urine volume per unit time (unit urine volume) stored in the memory unit 120. For example, the unit urine volume may be set to any value within a range of 20 to 30 (ml / sec). The unit urine volume may be set for each gender. For example, the unit urine volume for women may be set to any value within a range of 10 to 50 (ml / sec). Furthermore, the unit urine volume for men may be set to any value within a range of 10 to 30 (ml / sec). Note that the above is merely an example, and the unit urine volume is not limited to the above, and any value may be set.

[0403] <4-5-2. Fourth Process> Next, a processing example shown in Fig. 50 will be described. Fig. 50 is a flowchart showing an example of the procedure of the processing executed by the toilet system. Specifically, Fig. 50 is a flowchart showing an example of the procedure of a fourth processing for calculation related to urination time and urine volume. Note that explanations of points similar to Fig. 49 will be omitted as appropriate.

[0404] In Figure 50, the toilet system 1 determines whether or not a measurement start trigger has been received (step S401). For example, the toilet system 1 determines that a measurement start trigger has been received when it detects that a user has started using the toilet 7. If the toilet system 1 determines that a measurement start trigger has not been received (step S401: No), it repeats the processing of step S401.

[0405] When the toilet system 1 determines that a measurement start trigger has occurred (step S401: Yes), it sets "t=0" (step S402). For example, when the toilet system 1 detects that the user has started using the toilet 7 and determines that a measurement start trigger has occurred, it initializes the value of the urination score t, which counts the urination time, to 0.

[0406] Then, the toilet system 1 acquires the initial state (step S403). For example, the toilet system 1 acquires the sound inside the toilet bowl 7 detected by the sound detection sensor 34A at that time (before the user starts urination) as the initial state.

[0407] The toilet system 1 starts measurement (step S404). For example, the toilet system 1 starts measuring the sound inside the toilet bowl 7 using the sound detection sensor 34A. Then, the toilet system 1 calculates the difference from the initial state (step S405). For example, the toilet system 1 calculates the difference between the sound measured in step S404 and the initial state acquired in step S403.

[0408] The toilet system 1 determines whether or not there is a sound (step S406). For example, if the toilet system 1 detects a sound corresponding to urine, it determines that there is a sound. If the toilet system 1 determines that there is no sound (step S406: No), it performs the process of step S408.

[0409] If the toilet system 1 determines that there is a sound (step S406: Yes), it sets "t=t+1" (step S407). For example, if the toilet system 1 determines that there is a sound corresponding to urine, it increases the value of the urination score t by 1.

[0410] Then, the toilet system 1 determines whether or not a measurement end trigger has been generated (step S408). For example, the toilet system 1 determines that a measurement end trigger has been generated when it detects that the user has finished using the toilet 7. If the toilet system 1 determines that a measurement end trigger has not been generated (step S408: No), it returns to step S405 and repeats the process.

[0411] If the toilet system 1 determines that a measurement end trigger has been received (step S408: Yes), it ends the measurement (step S409). Then, the toilet system 1 calculates the total urination time (step S410). For example, the toilet system 1 calculates the total urination time based on the value of the urination score t, which is obtained by counting the urination time. For example, if the unit of the urination score t corresponds to seconds, the toilet system 1 calculates the number of seconds in the value of the urination score t as the total urination time. In this case, if the urination score t is "5", the toilet system 1 calculates that the total urination time is 5 seconds.

[0412] Then, the toilet system 1 estimates the urine volume (step S411). For example, the toilet system 1 calculates the urine volume using the total urination time calculated in step S410. The toilet system 1 calculates the urine volume by multiplying the calculated urination time by the urine volume per unit time (unit urine volume) stored in the memory unit 120.

[0413] <4-5-3. Fifth Processing> Next, a processing example shown in Fig. 51 will be described. Fig. 51 is a flowchart showing an example of the procedure of the processing executed by the toilet system. Specifically, Fig. 51 is a flowchart showing an example of the procedure of a fifth processing for calculation related to urination time and urine volume. Note that explanations of points similar to Fig. 49 and Fig. 50 will be omitted as appropriate.

[0414] In Figure 51, the toilet system 1 determines whether or not a measurement start trigger has been received (step S501). For example, the toilet system 1 determines that a measurement start trigger has been received when it detects that a user has started using the toilet 7. If the toilet system 1 determines that a measurement start trigger has not been received (step S501: No), it repeats the processing of step S501.

[0415] When the toilet system 1 determines that a measurement start trigger has occurred (step S501: Yes), it sets "t=0" (step S502). For example, when the toilet system 1 detects that the user has started using the toilet 7 and determines that a measurement start trigger has occurred, it initializes the value of the urination score t, which counts the urination time, to 0.

[0416] Then, the toilet system 1 acquires the initial state (step S503). For example, the toilet system 1 acquires the sound inside the toilet bowl 7 detected by the sound detection sensor 34A at that time (before the user starts urination) as the initial state.

[0417] The toilet system 1 starts measurement (step S504). For example, the toilet system 1 starts measuring the sound inside the toilet bowl 7 using the sound detection sensor 34A. Then, the toilet system 1 calculates the difference from the initial state (step S505). For example, the toilet system 1 calculates the difference between the sound measured in step S504 and the initial state acquired in step S503.

[0418] The toilet system 1 determines whether or not there is sound (step S506). For example, the toilet system 1 determines that there is sound if the difference calculated in step S505 is not 0. If the toilet system 1 determines that there is no sound (step S506: No), it performs the process of step S508.

[0419] If the toilet system 1 determines that there is sound (step S506: Yes), it acquires sound information (step S507). For example, if the difference calculated in step S505 is not 0, the toilet system 1 acquires the difference information as sound information.

[0420] Then, the toilet system 1 determines whether or not a measurement end trigger has been generated (step S508). For example, the toilet system 1 determines that a measurement end trigger has been generated when it detects that the user has finished using the toilet 7. If the toilet system 1 determines that a measurement end trigger has not been generated (step S508: No), it returns to step S505 and repeats the process.

[0421] If the toilet system 1 determines that a measurement end trigger has been received (step S508: Yes), it ends the measurement (step S509). Then, the toilet system 1 executes sound information processing (step S510). For example, if the toilet system 1 detects that the user has finished using the toilet 7 and determines that a measurement end trigger has been received, it executes sound information processing. For example, the toilet system 1 processes the sound information so that flushing sounds are not included in urination. In this case, the toilet system 1 excludes sound information corresponding to flushing sounds from the sound information used to calculate the urination time.

[0422] Note that the above-described sound information processing is merely an example, and the toilet system 1 may use various information to acquire sound information used to calculate urination time. For example, the toilet system 1 processes sound information so as not to include sounds emitted by the sound dummy device in urination. In this case, the toilet system 1 excludes sound information corresponding to the sound dummy device from the sound information used to calculate urination time. For example, the toilet system 1 processes sound information so as not to include sounds of private parts washing operation in urination. In this case, the toilet system 1 excludes sound information corresponding to sounds of private parts washing operation from the sound information used to calculate urination time.

[0423] Then, the toilet system 1 calculates the total urination time (step S511). For example, the toilet system 1 calculates the total urination time based on the value of the urination score t, which is obtained by counting the urination time. For example, if the unit of the urination score t corresponds to seconds, the toilet system 1 calculates the number of seconds of the value of the urination score t as the total urination time. In this case, if the urination score t is "5", the toilet system 1 calculates that the total urination time is 5 seconds.

[0424] Then, the toilet system 1 estimates the urine volume (step S512). For example, the toilet system 1 calculates the urine volume using the total urination time calculated in step S511. The toilet system 1 calculates the urine volume by multiplying the calculated urination time by the urine volume per unit time (unit urine volume) stored in the memory unit 120.

[0425] <4-6. Example of using multiple sound detection sensors> In the above example, the toilet system 1 uses one sound detection sensor 34A, but the toilet system 1 may use multiple sound detection sensors to calculate the urination time. In this regard, the following will be described as an example in which two sound detection sensors are used. Note that the same points as those described above will not be described again.

[0426] <4-6-1. Example of configuration using multiple sound detection sensors> First, an example of the sound produced by urine falling will be described with reference to Fig. 52. Fig. 52 is a diagram showing an example of a configuration using multiple sound detection sensors. Note that Fig. 52 shows only the components necessary for the explanation, and components such as the nozzle cover 60 are not shown.

[0427] In the example of FIG. 52, the toilet system 1 has two sensors, a first sound detection sensor 34A0 and a second sound detection sensor 34A2, and a sound output device 350. The first sound detection sensor 34A0 is a first microphone that detects sounds around the water seal of the toilet bowl 7. For example, the above-mentioned sound detection sensor 34A may be used as the first sound detection sensor 34A0. The second sound detection sensor 34A2 is a second microphone that acquires sounds other than those around the water seal of the toilet bowl 7. For example, the second sound detection sensor 34A2 is desirably an omnidirectional microphone.

[0428] The sound output device 350 is a speaker that outputs sound that cancels out sounds other than those around the water seal of the toilet bowl 7, which are acquired by the second sound detection sensor 34A2. As shown in FIG. 52, the sound output device 350 is exposed through the opening 31a of the main body cover 30. Note that the opening 31a may also be provided with an openable and closable lid, similar to the lid portion 110. In this case, the toilet seat apparatus 2 may have an openable and closable lid and an actuator that opens and closes the lid. Note that the lid and actuator corresponding to the opening 31a have the same configuration as the lid portion 110 and actuator 111 described above, and therefore detailed description thereof will be omitted.

[0429] 52 shows an example in which the toilet system 1 has a sound output device 350 for outputting a sound (cancelling sound) that cancels out the sound detected by the second sound detection sensor 34A2, but the toilet system 1 may also remove the sound detected by the second sound detection sensor 34A2 from the sound information through information processing. In this case, the toilet system 1 does not have the sound output device 350, and the control device 100 removes the sound detected by the second sound detection sensor 34A2 from the sound information through information processing.

[0430] <4-6-2. Examples of sound information processing> Next, an example of sound information processing when multiple sound detection sensors are used will be described with reference to Fig. 53 and Fig. 54. Fig. 53 and Fig. 54 are diagrams showing an example of sound information processing. Note that explanations of points similar to Fig. 48 will be omitted where appropriate.

[0431] First, the generation of information related to canceling sounds will be explained using Figure 53. Chart GR2 in Figure 53 shows an example of the waveform of sound detected by the first sound detection sensor 34A0. For example, chart GR2 shows the waveform of sound around the water seal in the toilet bowl 7. Chart GR3 in Figure 53 shows an example of the waveform of sound detected by the second sound detection sensor 34A2. For example, chart GR3 shows the waveform of sound other than that around the water seal in the toilet bowl 7.

[0432] The toilet system 1 generates information about a canceling sound to cancel out the sound detected by the second sound detection sensor 34A2, as shown in chart GR3. Chart GR4 in FIG. 53 shows an example of the waveform of the canceling sound generated and detected by the toilet system 1. For example, the control device 100 generates a sound that is in the opposite phase to the sound detected by the second sound detection sensor 34A2 as the canceling sound. Note that the above is merely an example, and the control device 100 may generate the canceling sound using any method.

[0433] First, the process for canceling out the sound detected by the second sound detection sensor 34A2 will be described with reference to Fig. 54. The toilet system 1 outputs a canceling sound as shown in chart GR4. For example, the sound output device 350 outputs a canceling sound as shown in chart GR4.

[0434] This allows the toilet system 1 to acquire sound from which the influence of the sound detected by the second sound detection sensor 34A2 has been removed. In FIG. 54, the toilet system 1 acquires sound from which the influence of the sound detected by the second sound detection sensor 34A2 has been removed, as shown in chart GR5. The toilet system 1 calculates the excretion time using sound information such as that shown in chart GR5. In FIG. 54, as shown in chart GR5, for sound detected by the first sound detection sensor 34A0, an amplitude exceeding a predetermined threshold (Δs) is detected at time t1. In FIG. 54, as shown in chart GR5, an amplitude exceeding Δs is detected within a predetermined time between times t1 and t2. Then, in FIG. 54, as shown in chart GR5, for sound detected by the first sound detection sensor 34A0, a period continues for a predetermined time period at time t2 during which an amplitude exceeding Δs is not detected. As a result, the control device 100 calculates the time between time t1 and time t2 as the excretion time (urination time) based on the sound for which an amplitude exceeding Δs is detected.

[0435] As described above, the toilet system 1 may remove the sound detected by the second sound detection sensor 34A2 from the sound information through information processing. In this case, the toilet system 1 may generate the sound shown in chart GR5 by combining the sound detected by the first sound detection sensor 34A0 as shown in chart GR2 with the canceling sound as shown in chart GR4.

[0436] <4-6-3. Sixth Process> Next, a processing example shown in Fig. 55 will be described. Fig. 55 is a flowchart showing an example of a processing procedure using a plurality of sound detection sensors. Specifically, Fig. 55 is a flowchart showing an example of a sixth processing procedure for calculation related to urination time and urine volume. Note that explanations of points similar to Figs. 49 to 51 will be omitted as appropriate.

[0437] In Figure 55, the toilet system 1 determines whether or not a measurement start trigger has been received (step S601). For example, the toilet system 1 determines that a measurement start trigger has been received when it detects that a user has started using the toilet 7. If the toilet system 1 determines that a measurement start trigger has not been received (step S601: No), it repeats the processing of step S601.

[0438] When the toilet system 1 determines that a measurement start trigger has occurred (step S601: Yes), it sets "t=0" (step S602). For example, when the toilet system 1 detects that the user has started using the toilet 7 and determines that a measurement start trigger has occurred, it initializes the value of the urination score t, which counts the urination time, to 0.

[0439] The toilet system 1 starts measurement (step S603). For example, the toilet system 1 starts measuring the sound inside the toilet bowl 7 using the sound detection sensor 34A. Then, the toilet system 1 generates a signal (microphone #2') that cancels out the output of microphone #2 (step S604). For example, the toilet system 1 generates a canceling sound that cancels out the output of microphone #2 through sound information processing. Then, the toilet system 1 combines microphone #1 and microphone #2' (step S605). For example, the toilet system 1 may combine microphone #1 and microphone #2' by outputting microphone #2', or may combine microphone #1 and microphone #2' through sound information processing.

[0440] The toilet system 1 determines whether or not there is a sound (step S606). For example, if the toilet system 1 detects a sound corresponding to urine, it determines that there is a sound. If the toilet system 1 determines that there is no sound (step S606: No), it performs the process of step S611.

[0441] If the toilet system 1 determines that there is a sound (step S606: Yes), it sets "ts=t1" (step S607). For example, if the toilet system 1 determines that there is a sound corresponding to urine, it sets the time t1 when the sound corresponding to urine began to be detected as the urination start time ts.

[0442] The toilet system 1 determines whether or not there is no sound (step S608). For example, the toilet system 1 determines that there is no sound when it no longer detects a sound corresponding to urine. If the toilet system 1 determines that there is no sound (step S608: No), it repeats the process of step S608.

[0443] If the toilet system 1 determines that there is sound (step S608: Yes), it sets "te = t2" (step S609). For example, if the toilet system 1 determines that there is no sound, it sets the time t2 when sound corresponding to urine is no longer detected as the urination end time te.

[0444] Then, the toilet system 1 sets "t=t+(te-ts)" (step S610). For example, the toilet system 1 adds the value obtained by subtracting the urination start time ts from the urination end time te to the urination score t.

[0445] Then, the toilet system 1 determines whether or not a measurement end trigger has been generated (step S611). For example, the toilet system 1 determines that a measurement end trigger has been generated when it detects that the user has finished using the toilet 7. If the toilet system 1 determines that a measurement end trigger has not been generated (step S611: No), it returns to step S604 and repeats the process.

[0446] If the toilet system 1 determines that a measurement end trigger has been received (step S611: Yes), it ends the measurement (step S612). Then, the toilet system 1 calculates the total urination time (step S613). For example, the toilet system 1 calculates the total urination time based on the value of the urination score t, which is obtained by counting the urination time. For example, if the unit of the urination score t corresponds to seconds, the toilet system 1 calculates the number of seconds in the value of the urination score t as the total urination time. In this case, if the urination score t is "5", the toilet system 1 calculates that the total urination time is 5 seconds.

[0447] Then, the toilet system 1 estimates the urine volume (step S614). For example, the toilet system 1 calculates the urine volume using the total urination time calculated in step S613. The toilet system 1 calculates the urine volume by multiplying the calculated urination time by the urine volume per unit time (unit urine volume) stored in the memory unit 120.

[0448] <4-7. Overall overview> From here, an overview of the configuration and processing of the toilet system 1 described above will be described with reference to Fig. 56. Fig. 56 is a diagram showing an overview of the configuration and processing of the toilet system. Note that explanations of points similar to those described above will be omitted as appropriate. For example, various types of sensors can be used for the sound detection sensor 34A.

[0449] As shown in Figure 56, the toilet system 1 may be configured to control its operation so that flushing and genital washing operations are not accepted during measurement (while urine sounds are being detected). In the toilet system 1, the start trigger for the operation control may be the start of sitting, operation of the measurement start button, etc. Furthermore, in the toilet system 1, the end trigger for the operation control may be operation of the flush button, the passage of a predetermined time without sound, detection of paper falling, or operation of the measurement end button, etc. Furthermore, as described above, the toilet system 1 outputs the total urine volume categorized into "large," "medium," and "small."

[0450] <5. Fifth Embodiment> Next, a configuration example that uses information related to a change in the state of the drain pipe will be described below as a fifth embodiment. Note that the toilet system 1 according to the fifth embodiment is shown as an example in which an optical sensor is included, and the external configuration of the toilet system 1 according to the fifth embodiment in this case is similar to that of the toilet system 1 according to the second embodiment when the lid 110 is closed, so illustrations and detailed description will be omitted. Note that the toilet system 1 according to the fifth embodiment may not include an optical sensor, and in this case, the toilet system 1 according to the fifth embodiment may not include the lid 110.

[0451] <5-1-1. Configuration of the toilet seat device> In FIG. 1, the toilet apparatus 20 has a toilet seat apparatus 2 that is installed above the toilet bowl 7. The configuration of the toilet seat apparatus 2 will be described below with reference to FIG. 57. FIG. 57 is a perspective view showing an example of the configuration of a toilet seat apparatus according to a fifth embodiment. Specifically, FIG. 57 is a view showing the toilet seat apparatus 2 with the lid 110 removed. Note that, in the toilet seat apparatus 2 according to the fifth embodiment, descriptions of the same aspects as those of the toilet seat apparatus 2 according to the second embodiment will be omitted where appropriate.

[0452] When the lid 110 is in the closed state, the optical sensor 34B is hidden behind the lid 110. When the lid 110 is in the closed state, the lid 110 is located in front of the optical sensor 34B. In this way, the lid 110 is located in front of the optical sensor 34B in the closed state.

[0453] As shown in FIG. 57, when the lid 110 is removed, the optical sensor 34B is exposed from the opening 31 of the main body cover 30. For example, when the lid 110 is open (open state), as shown in FIG. 57, the lid 110 is not positioned in front of the optical sensor 34B. As a result, when the lid 110 is open, the optical sensor 34B is exposed. When the lid 110 is open, the optical sensor 34B can detect changes in the state of the water seal in the toilet bowl 7. Note that the toilet seat device 2 does not need to have the lid 110. In this case, the toilet seat device 2 does not need to have the lid 110 and the actuator 111, and the optical sensor 34B may be always exposed.

[0454] <5-1-2. Configuration of drain pipes in toilet devices and placement of radio wave sensors> Next, an example of the configuration of a drain pipe and the placement of a radio wave sensor in a toilet apparatus will be described using Figure 58. Figure 58 is a schematic diagram showing an example of the configuration of a toilet apparatus according to the fifth embodiment. Specifically, Figure 58 is a schematic side cross-sectional view of the toilet bowl 7, showing only the essential parts of the configuration of the toilet apparatus 20, such as the toilet bowl 7, in order to show the configuration of the drain pipe 81 and the placement of the radio wave sensor 200. Note that the cross-sectional shape of the toilet bowl 7 in Figure 58 is merely one example, and the cavity inside the toilet bowl 7 may have any shape as long as the radio wave sensor 200 can be placed in a desired position; for example, only the location where the radio wave sensor 200 is placed may be hollow.

[0455] A drain pipe 81 communicates with an opening provided at the bottom of the bowl portion 8 of the toilet 7. The drain pipe 81 is a drain pipe from the bowl portion 8, and the internal space of the drain pipe 81 functions as a drainage channel. In FIG. 58, the drain pipe 81 has a U-shaped (V-shaped) shape that extends diagonally downward from the end connected to the bottom of the bowl portion 8 and then diagonally upward, before continuing downward. This forms a trap portion 82 in the drain pipe 81. The trap portion 82 forms a water seal WT including the bottom side of the bowl portion 8. Note that the configuration of the drain pipe 81 shown in FIG. 58 is merely one example, and any configuration can be used for the drain pipe 81 as long as it can form a trap that can perform the processing described below.

[0456] Figure 58 shows that the hatched areas in the bowl portion 8 of the toilet 7 and the drain pipe 81 are filled with a water seal WT (water). Also, in Figure 58, the water seal surface WS1 in Figure 58 indicates the upper surface formed on the bottom side of the bowl portion 8 by the water seal WT, and the water seal surface WS2 in Figure 58 indicates the upper surface formed on the trap portion 82 side by the water seal WT.

[0457] In Figure 58, an apex 821 is formed at the end of trap portion 82 opposite the end of drain pipe 81 that is connected to the bottom of bowl portion 8. Detection range DA11 of radio wave sensor 200 is set to an area that includes apex 821 of trap portion 82. For example, radio wave sensor 200 is positioned so that detection range DA11 includes apex 821 of trap portion 82. Note that the range shown in Figure 58 is merely one example of detection range DA11 of radio wave sensor 200, and detection range DA11 of radio wave sensor 200 is not limited to the range shown in Figure 58 and may be any range as long as it includes apex 821 of trap portion 82.

[0458] For example, the radio wave sensor 200 is a microwave sensor. In the following, a case where the radio wave sensor 200 is a microwave sensor will be described as an example, but the radio wave sensor 200 is not limited to a microwave sensor. For example, any sensor such as a millimeter wave sensor can be used as the radio wave sensor 200 as long as it is capable of performing the desired detection.

[0459] Radio wave sensor 200 can be positioned in any manner as long as detection range DA11 includes apex 821 of trap portion 82. For example, radio wave sensor 200 is positioned vertically above trap portion 82. For example, radio wave sensor 200 is positioned vertically above the water seal (e.g., water seal surface WS2) on the trap portion 82 side. For example, radio wave sensor 200 is provided along the outer wall of drain pipe 81 that has trap portion 82. In FIG. 58, radio wave sensor 200 is provided outside drain pipe 81 and above trap portion 82. In this case, a drainage channel from bowl portion 8 passes between radio wave sensor 200 and apex 821 of trap portion 82. As a result, a drainage channel from bowl portion 8 provided in toilet 7 passes between antenna portion 210 (see FIG. 59) of radio wave sensor 200 and apex 821 of trap portion 82.

[0460] The above-described arrangement is merely an example, and the radio wave sensor 200 may be arranged in various other ways. For example, the radio wave sensor 200 may be provided in the toilet seat device 2. When the radio wave sensor 200 is provided in the toilet seat device 2, the radio wave sensor 200 may be arranged on the bottom (lower side) of the toilet seat device 2. In this case, the antenna unit 210 of the radio wave sensor 200 is arranged on the bottom of the toilet seat device 2 on the toilet bowl 7 side. For example, the radio wave sensor 200 may be arranged in the main body unit 3, which is a functional unit. The radio wave sensor 200 may be arranged, for example, inside the main body cover 30. Below, an example will be described in which the radio wave sensor 200 is arranged on the upper side of the trap unit 82, as shown in FIG. 58.

[0461] With the above-described arrangement, the radio wave sensor 200 detects changes in the state of the water seal on the trap portion 82 side. The radio wave sensor 200 detects changes in the state of the water seal, including water overflowing from the apex 821 of the trap portion 82. For example, the radio wave sensor 200 detects changes in the state of the water seal on the trap portion 82 side due to excrement falling into the water seal on the bowl portion 8 side. For example, the radio wave sensor 200 detects changes in the state of the water seal based on water overflowing from the apex 821 of the trap portion 82, as will be described later.

[0462] Note that radio wave sensor 200 may be separate from toilet device 20 and detachable from toilet device 20. In this case, for example, radio wave sensor 200 may be a toilet device radio wave device installed in toilet device 20. Radio wave sensor 200 detects a change in state that occurs in the water seal on the trap unit 82 side that forms the water seal on the bottom side of bowl unit 8 when excrement falls into the water seal in bowl unit 8 of toilet device 20.

[0463] <5-2. Configuration of the toilet seat device and radio wave sensor> Next, the configuration of the toilet seat device 2 and the radio wave sensor 200 will be described with reference to Fig. 59. Fig. 59 is a block diagram showing an example of the configuration of the toilet seat device and the radio wave sensor according to the fifth embodiment.

[0464] <5-2-1. Functional configuration of the toilet seat device> First, we will explain the functional configuration of the toilet seat device 2. As shown in Fig. 59, the toilet seat device 2 includes a human body detection sensor 32, a seating detection sensor 33, an optical sensor 34B, a control device 100, a nozzle motor 61, a flushing nozzle 6, a solenoid valve 71, a lid 110, and an actuator 111. Note that Fig. 59 omits illustration of some of the configuration of the toilet seat device 2 described in Fig. 4 (such as the main body 3, toilet seat 5, and toilet bowl 7).

[0465] 59 is merely an example, and the toilet seat device 2 can have any configuration. The human body detection sensor 32, seating detection sensor 33, optical sensor 34B, control device 100, etc. are arranged in any desired locations. For example, the optical sensor 34B is provided in the main body 3 of the toilet seat device 2. The toilet seat device 2 transmits and receives information to and from an information processing device such as the operating device 10 via a predetermined network (such as the Internet) by a communication device (such as the communication unit 101 of the control device 100) in a wired or wireless manner.

[0466] The optical sensor 34B is a sensor that detects changes in the state of the toilet device 20. The optical sensor 34B detects changes in the state of the seal water in the toilet bowl 7. For example, the optical sensor 34B detects changes in the state of the bowl portion 8 side. The optical sensor 34B detects changes in the state of the seal water from the bowl portion 8 side at multiple times. For example, the optical sensor 34B includes the seal water on the bowl portion 8 side (e.g., the seal water surface WS1, etc.) in its detection range. Note that the above-described detection mode is merely an example, and the optical sensor 34B may perform any detection as long as the desired detection is possible.

[0467] For example, optical sensor 34B may detect feces before they hit the sealed water from the bowl portion 8 side. Optical sensor 34B detects feces falling inside bowl portion 8 (falling feces). In this case, optical sensor 34B includes the inside of bowl portion 8 in its detection range.

[0468] The optical sensor 34B can have any configuration as long as it can detect a desired state change. For example, depending on the type of sensor used, the optical sensor 34B is disposed at a position appropriate for the detection mode of the sensor. The optical sensor 34B may be a non-contact sensor. For example, FIG. 58 shows a case where the optical sensor 34B is a non-contact sensor. In this case, the optical sensor 34B may be a camera, a line sensor, an ultrasonic sensor, an infrared sensor, or the like. The optical sensor 34B may also be a contact sensor. In this case, the optical sensor 34B may be a float sensor, a pressure sensor, or the like. Note that the above is merely an example, and any sensor may be used as the optical sensor 34B as long as it can detect a desired state change.

[0469] Furthermore, when optical sensor 34B detects the presence or absence of feces, optical sensor 34B may be an imaging means such as a camera or a line sensor. In this case, for example, optical sensor 34B may be a line sensor arranged facing the inside of bowl portion 8, and may detect fallen objects such as excrement falling inside bowl portion 8. Furthermore, optical sensor 34B may be a camera arranged facing the water seal inside bowl portion 8, and may detect fallen objects such as excrement that have landed on the water seal.

[0470] The control device 100 controls various components and processes. The control device 100 is a computer (information processing device) that executes various information processes such as estimating (calculating) information related to excrement, such as urine flow rate (urine volume) or feces volume. The control device 100 functions as an estimation means that estimates information related to excrement, such as urine or feces, based on the detection results of the radio wave sensor 200. Note that in the control device 100 according to the fifth embodiment, explanations of the same points as those of the control device 100 according to the second embodiment will be omitted as appropriate.

[0471] The control device 100 estimates the urine flow rate or feces volume based on the change in the state of the water seal. For example, the control device 100 estimates the urine flow rate based on information about standing waves output from the radio wave sensor 200. For example, the control device 100 estimates information about the urine or feces volume based on the detection results of the radio wave sensor 200 and the optical sensor 34B.

[0472] For example, the control device 100 estimates information about urine or feces when there is a correlation between the detection results of the radio wave sensor 200 and the optical sensor 34B. For example, the control device 100 acquires information about urine or feces based on the detection results of the radio wave sensor 200 and the optical sensor 34B. For example, the control device 100 acquires information about feces based on the detection results of the optical sensor 34B, and acquires information about urine or feces based on the detection results of the radio wave sensor 200.

[0473] The control device 100 controls the lid portion 110 to be in the closed state while detection by the optical sensor 34B is not being performed, such as before the user uses the toilet bowl 7.

[0474] The control device 100 may also control the optical sensor 34B. In this case, the optical sensor 34B starts or stops detection in response to control by the control device 100. The control device 100 transmits control information to the optical sensor 34B to control the start or end of detection by the optical sensor 34B. For example, when the human body detection sensor 32 or the seating detection sensor 33 detects that a user has started using the toilet 7, the control device 100 transmits control information to the optical sensor 34B to cause the optical sensor 34B to start detection. For example, when the human body detection sensor 32 or the seating detection sensor 33 detects that a user has stopped using the toilet 7, the control device 100 transmits control information to the optical sensor 34B to cause the optical sensor 34B to end detection.

[0475] The control device 100 may also control the radio wave sensor 200. In this case, the radio wave sensor 200 starts or stops detection in accordance with the control of the control device 100. The control device 100 transmits control information to the radio wave sensor 200 for controlling the start or end of detection by the radio wave sensor 200. For example, when the human body detection sensor 32 or the seating detection sensor 33 detects that a user has started using the toilet 7, the control device 100 transmits control information to the radio wave sensor 200 to cause the radio wave sensor 200 to start detection. For example, when the human body detection sensor 32 or the seating detection sensor 33 detects that a user has stopped using the toilet 7, the control device 100 transmits control information to the radio wave sensor 200 to cause the radio wave sensor 200 to end detection.

[0476] The lid portion 110 can be positioned in front of the optical sensor 34B and functions as a lid. The lid portion 110 is preferably formed of an opaque material to reduce the possibility of the optical sensor 34B being visible and to ensure the user's privacy. For example, the lid portion 110 may be formed in an opaque state by coloring. The lid portion 110 may have an opaque material (paint) applied to its surface. Note that the lid portion 110 is not limited to an opaque structure and may be transparent. The lid portion 110 can transition between an open state and a closed state by an actuator 111, and is positioned in front of the optical sensor 34B or exposes the optical sensor 34B.

[0477] In the configuration shown in FIG. 59, the toilet seat device 2 includes the control device 100 and other components. However, the control device 100, the human body detection sensor 32, the seating detection sensor 33, the optical sensor 34B, and other components may be configured as separate devices from the toilet seat device 2. For example, the control device 100 may be configured as a separate device from the toilet seat device 2. For example, the control device 100 may be a server device located at a distance from the toilet seat device 2. In this case, the control device 100 communicates with each device, such as the toilet seat device 2, the human body detection sensor 32, the seating detection sensor 33, and the optical sensor 34B, and receives information necessary for estimating information related to excrement, such as urine flow rate (urine volume) or feces volume, from each device. In this case, the toilet seat device 2 may also have components (such as a control circuit) for controlling various components of the toilet seat device 2, such as the nozzle motor 61, the solenoid valve 71, and the actuator 111. Note that the above is merely an example, and the toilet system 1 can employ any device configuration as long as it is capable of performing the desired processing.

[0478] <5-2-2. Functional configuration of radio wave sensor> Next, a description will be given of the functional configuration of the radio wave sensor 200. As shown in FIG.

[0479] The antenna unit 210 has a function for transmitting and receiving radio waves, and includes a transmitting antenna 211 that transmits predetermined radio waves, and a receiving antenna 212 that receives the radio waves.

[0480] Any arrangement may be adopted for the arrangement of the antenna unit 210. For example, the antenna unit 210 is arranged near the trap unit 82. For example, the antenna unit 210 is provided on the outer wall of the drain pipe 81 that has the trap unit 82. The antenna unit 210 is provided along the outer wall of the drain pipe 81 that has the trap unit 82. Furthermore, for example, the antenna unit 210 is arranged vertically above the trap unit 82. Furthermore, for example, the antenna unit 210 is arranged vertically above the seal water on the trap unit 82 side.

[0481] Furthermore, when the radio wave sensor 200 is provided in the toilet seat apparatus 2, for example, the antenna unit 210 is disposed on the bottom (lower side) of the toilet seat apparatus 2. Note that the above-described arrangement of the antenna unit 210 is merely an example, and any arrangement of the antenna unit 210 can be adopted as long as the desired detection is possible. For example, the antenna unit 210 may be disposed outside the drain pipe 81, such as on the outer wall of the drain pipe 81, or may be disposed inside the drain pipe 81, as long as the desired detection is possible.

[0482] Circuit unit 220 has the function of executing processes related to transmitting and receiving radio waves. Circuit unit 220 includes a transmitter circuit 221 that functions as an electronic circuit that generates repeated electrical vibrations, and a detector circuit 222 that detects waves received by receiving antenna 212. Note that the configuration shown in FIG. 59 is merely an example, and radio wave sensor 200 can have any configuration. For example, it may have multiple detector circuits 222 as shown in FIG. 74, etc., but this will be described later. For example, the circuit configuration of radio wave sensor 200 that uses one output may be a configuration that has only one detector circuit 222 (e.g., detector circuit #1) obtained by omitting the part corresponding to detector circuit #2 from the circuit schematic diagram shown in FIG. 74.

[0483] The radio wave sensor 200 also has a function of transmitting information collected by detection to the control device 100. For example, the radio wave sensor 200 may be connected to the control device 100 by a wire and be able to communicate information with the control device 100. The radio wave sensor 200 may also be connected to the control device 100 and be able to communicate information with the control device 100. The radio wave sensor 200 may have a communication device for communicating with the control device 100.

[0484] <5-3. Functional configuration of the control device> The functional configuration of the control device according to the fifth embodiment will be described below. Note that a functional block diagram of the control device 100 according to the fifth embodiment is the same as that of the control device 100 according to the second embodiment, so it is not shown in the figure, and differences from the control device 100 according to the second embodiment will be mainly described.

[0485] The control device 100 according to the fifth embodiment includes a communication unit 101, a storage unit 120, and a control unit 130. The control device 100 according to the fifth embodiment may be connected to the radio wave sensor 200 via the communication unit 101 in a wired or wireless manner, and may transmit and receive information to and from the radio wave sensor 200.

[0486] The storage unit 120 according to the fifth embodiment stores various pieces of information required for processing. The storage unit 120 stores various pieces of information acquired from other devices such as various sensors. For example, the storage unit 120 stores information related to a learning model (model) used for processing. For example, the storage unit 120 stores a model used for estimating information related to excrement, such as urine flow rate (urine volume) or feces volume. For example, the storage unit 120 stores various pieces of information (e.g., information related to thresholds) used in various types of information processing. Furthermore, for example, the storage unit 120 according to the fifth embodiment stores information stored by the data storage means 14 described above.

[0487] The control unit 130 according to the fifth embodiment has an acquisition unit 131, a measurement unit 132, a determination unit 133, an estimation unit 134, and an output unit 135, and realizes or executes the functions and actions of information processing described below. For example, the control unit 130 according to the fifth embodiment executes the processes executed by the information processing units such as the dehydration estimation means 15, the evaluation means 16, the notification means 17, and the frequent urination estimation means 18 described above.

[0488] The acquisition unit 131 according to the fifth embodiment acquires various types of information in the same manner as the acquisition unit 131 according to the second embodiment. The acquisition unit 131 receives information (detection information, etc.) detected by each sensor, such as the human body detection sensor 32, the seating detection sensor 33, the optical sensor 34B, and the radio wave sensor 200. The acquisition unit 131 acquires information to be used for processing from the storage unit 120.

[0489] The measurement unit 132 according to the fifth embodiment performs various measurements in the same manner as the measurement unit 132 according to the second embodiment. The measurement unit 132 measures the sensor value detected by the radio wave sensor 200 using the information acquired by the radio wave sensor 200.

[0490] The measuring unit 132 uses the information detected by the radio wave sensor 200 to measure information relating to a change in the state of the seal water on the trap section 82 side. The measuring unit 132 uses the information detected by the radio wave sensor 200 to measure information relating to a change in the state of the seal water based on the overflow from the apex 821 of the trap section 82.

[0491] The determination unit 133 according to the fifth embodiment performs determination processing in the same manner as the determination unit 133 according to the second embodiment. The determination unit 133 determines the cause of the change in the state of the seal water of the toilet 7 based on the detection results by the optical sensor 34B. The determination unit 133 classifies the change in the state of the seal water of the toilet 7 based on the detection results by the optical sensor 34B. The determination unit 133 determines which object caused the change in the state of the seal water of the toilet 7 based on the detection results by the optical sensor 34B.

[0492] Based on the detection results of optical sensor 34B, determination unit 133 determines whether an object has fallen (landed) into the seal water of toilet bowl 7. Based on the detection results of optical sensor 34B, determination unit 133 determines whether an object has landed in the seal water of toilet bowl 7. Based on the detection results of optical sensor 34B, determination unit 133 determines whether the object is excrement of the user.

[0493] For example, the determination unit 133 classifies a plurality of types of changes in the state of the water seal, including a first type of change in the state of the water seal that is a change in the state of the water seal due to feces, a second type of change in the state of the water seal that is a change in the state of the water seal due to urine, and a third type of change in the state of the water seal that is a change in the state of the water seal due to feces and urine. For example, the determination unit 133 classifies the change in the state of the water seal detected by the optical sensor 34B as either a change in the state of the water seal due to feces, a change in the state of the water seal due to urine, or a change in the state of the water seal due to feces and urine.

[0494] The determination unit 133 may determine whether the state of the seal water has changed by any method. For example, the determination unit 133 may determine whether the state of the seal water has changed by exceeding a signal level threshold or by using AI (artificial intelligence). The determination unit 133 may determine whether the state of the seal water has changed by frequency analysis, image processing, machine learning, deep learning, etc.

[0495] For example, the determination unit 133 determines the change in the state of the seal water using AI technology. For example, the determination unit 133 may determine the change in the state of the seal water using a model (also referred to as a "seal water state change determination model") generated by machine learning. In this case, the seal water state change determination model is trained in advance using training data that indicates classification judgments. This training data includes multiple combinations of information (seal water change information), such as images, regarding the change in the state of the seal water, and labels (correct answer information) indicating the type of the change in the state of the seal water corresponding to the seal water change information. The type here indicates the object that caused the change in the state of the seal water, such as feces, urine, or both feces and urine. For example, the training data includes multiple combinations of seal water change information and labels (correct answer information) indicating the object that landed (fell) on the seal water when the change in the state of the seal water corresponding to the seal water change information occurred in the seal water.

[0496] The seal water state change determination model is a model that receives seal water change information as input and outputs information indicating the type of seal water state change corresponding to the input seal water change information. For example, when seal water change information is input, the seal water state change determination model is trained to output information on a label (type of seal water state change) corresponding to the input seal water change information. The seal water state change determination model is trained using various techniques related to so-called supervised learning as appropriate. In this case, the seal water state change determination model is stored in the memory unit 120, and the determination unit 133 may determine a change in the seal water state using the seal water state change determination model stored in the memory unit 120. For example, the control device 100 may perform a learning process to generate the seal water state change determination model. Note that the above is merely an example, and the determination unit 133 may determine a change in the seal water state using various information as appropriate.

[0497] Furthermore, the determination unit 133 may determine whether or not a defecation (faecal discharge) has occurred based on information detected by a stool detection means. The determination unit 133 may determine whether or not the user has defecate using information detected by a stool detection means such as the optical sensor 34B. The determination unit 133 determines whether or not a defecation has occurred based on an image captured by the stool detection means. Note that the above determination of whether or not a defecation has occurred is merely an example, and the determination unit 133 may determine whether or not a defecation has occurred by appropriately using various information when determining whether or not a defecation has occurred.

[0498] The estimation unit 134 according to the fifth embodiment functions as a dehydration estimation means. For example, the estimation unit 134 estimates the dehydration of the toilet user by the same processing as the dehydration estimation means 15 according to the first embodiment.

[0499] The estimation unit 134 estimates the dehydration state of the toilet user based on the urination data stored in the memory unit 120. The estimation unit 134 estimates the dehydration state when the integrated value of the urine volume over a predetermined period of time is less than a predetermined value. The estimation unit 134 estimates the dehydration state when the urination interval is longer than a predetermined interval. The estimation unit 134 estimates the dehydration state when the urine volume over a predetermined period of time is less than a predetermined volume. The estimation unit 134 estimates the dehydration state when the urination interval is longer than the predetermined interval and the urine volume is less than a predetermined volume.

[0500] The estimation unit 134 estimates the dehydration state based on the urination data and at least one of the toilet user's age-specific and season-specific urination characteristics. The estimation unit 134 suspends estimation of the dehydration state when the number of urinations based on the urination data is equal to or less than a predetermined number of times.

[0501] The estimation unit 134 according to the fifth embodiment functions as an evaluation unit. For example, the estimation unit 134 executes a process related to evaluation of dehydration of the toilet user by the same process as the evaluation unit 16 according to the first embodiment.

[0502] The estimation unit 134 functions as a dehydration assessment means that classifies the dehydration state of the toilet user into a plurality of levels based on the urination data. When the amount of urine included in the urination data is less than a predetermined amount, the estimation unit 134 classifies the dehydration state into a plurality of levels based on the urine color included in the urination data of the toilet user.

[0503] The estimation unit 134 according to the fifth embodiment functions as a frequent urination estimation means. For example, the estimation unit 134 estimates the frequent urination of the toilet user by the same processing as the frequent urination estimation means 18 according to the first embodiment.

[0504] The estimation unit 134 estimates the toilet user's frequent urination based on the urination data. The estimation unit 134 estimates frequent urination when the urination interval is shorter than a predetermined period.

[0505] The estimation unit 134 estimates the toilet user's frequency of urination based on the urination data stored in the memory unit 120. The estimation unit 134 estimates nocturia based on the urine volume or urine flow rate per night, or the average urine volume or average urine flow rate during the night, using the nighttime urination information identified from the urination information and other urination information.

[0506] The estimation unit 134 estimates nocturia based on the daytime and nighttime urination data identified by the urination information and other urination information. The estimation unit 134 estimates nocturia based on the daytime urine volume or urine flow rate per urination and the nighttime urine volume or urine flow rate per urination.

[0507] The estimation unit 134 estimates nocturia based on the average daytime urine volume or average urine flow rate and the average nighttime urine volume or average urine flow rate. The estimation unit 134 estimates nocturia using the nighttime urination information identified from the urination information and other urination information when there are multiple urinations at night and the relationship between the urine volume or urine flow rate per urination and the interval between urination times satisfies a predetermined condition.

[0508] The estimation unit 134 according to the fifth embodiment performs various processes such as calculation processes, similar to the estimation unit 134 according to the second embodiment. The estimation unit 134 performs the estimation process. For example, the estimation unit 134 performs the estimation process based on an arbitrary estimation method. For example, the estimation unit 134 performs the estimation process by calculating information through calculation processes based on an arbitrary calculation method. The estimation unit 134 performs the estimation process using various information stored in the storage unit 120. The estimation unit 134 performs the estimation process using various information acquired by the acquisition unit 131. The estimation unit 134 estimates (calculates) information related to excrement, such as urine flow rate (urine volume) or stool volume, based on the determination result by the determination unit 133.

[0509] For example, the estimation unit 134 estimates information about urine or feces related to excrement based on the detection results of the radio wave sensor 200. The estimation unit 134 estimates the urine flow rate or feces volume based on changes in the state of the seal water. The estimation unit 134 estimates the urine flow rate based on information about standing waves output from the radio wave sensor 200.

[0510] For example, the estimation unit 134 estimates information about urine or feces based on the detection results of the radio wave sensor 200 and the optical sensor 34B. For example, the estimation unit 134 estimates information about urine or feces when there is a correlation between the detection results of the radio wave sensor 200 and the optical sensor 34B. When the detection result of the optical sensor 34B indicates that the user's excrement is urine, the estimation unit 134 estimates information about urine based on the detection result of the radio wave sensor 200. When the detection result of the optical sensor 34B indicates that the user's excrement is urine, the estimation unit 134 estimates the amount of urine based on the detection result of the radio wave sensor 200. When the detection result of the optical sensor 34B indicates that the user's excrement is feces (stool), the estimation ...

Claims

1. a data storage means for storing urination data acquired based on urination of a toilet user in the toilet device; a dehydration estimation means for estimating a dehydration state of a toilet user based on the urination data stored by the data storage means; Equipped with The urination data includes urination information regarding the amount of urine or the urine flow rate obtained based on a change in the state of the bowl portion of the toilet device. A dehydration estimation device characterized by:

2. The urination data includes other urination information having at least one of information on urination time, urination frequency, or urination frequency. The dehydration estimation device according to claim 1 .

3. The change in state inside the bowl portion includes a change in state of the internal space of the bowl portion above the seal water formed on the bottom side of the bowl portion, or a change in state of the seal water. The dehydration estimation device according to claim 1 .

4. The urination information includes information obtained based on a change in the state of the water seal on the bowl portion side.

4. The dehydration estimation device according to claim 3.

5. The toilet device has a trap portion that forms a water seal on the bottom side of the bowl portion, The urination information includes information obtained based on a change in the state of the water seal on the trap portion side.

4. The dehydration estimation device according to claim 3.

6. The urination information is information obtained by detecting a change in the state of the water seal on the trap section side using a radio wave sensor, The detection range of the radio wave sensor is set to an area including the apex of the trap portion, and the radio wave sensor detects a change in the state of the seal water based on overflow from the apex of the trap portion.

6. The dehydration estimation device according to claim 5.

7. The urination information includes information obtained by detecting a change in the state of the water seal formed on the bottom side of the bowl portion side using a radio wave sensor or an optical sensor.

4. The dehydration estimation device according to claim 3.

8. The urination information includes information obtained by detection by a sound sensor. The dehydration estimation device according to claim 1 .

9. The change in state inside the bowl portion includes at least one of a change in humidity, a change in temperature, and a change in gas composition that accompanies urination. The dehydration estimation device according to claim 1 .

10. The urination information includes information obtained based on changes in the state of the water seal caused by urination, excluding changes in the state of the water seal caused by defecation. The dehydration estimation device according to claim 1 .

11. The dehydration estimation means estimates that the subject is dehydrated when an integrated value of the amount of urine for a predetermined period of time is less than a predetermined value. The dehydration estimation device according to claim 1 .

12. The dehydration estimation means estimates that the user is dehydrated when the urination interval is longer than a predetermined interval. The dehydration estimation device according to claim 1 .

13. The dehydration estimation means estimates that the subject is in a dehydrated state when the amount of urine in a predetermined period is less than a predetermined amount. The dehydration estimation device according to claim 1 .

14. The dehydration estimation means estimates that the subject is dehydrated when the urination interval is longer than a predetermined interval and the urine volume is less than a predetermined volume. The dehydration estimation device according to claim 1 .

15. The dehydration estimation means estimates the dehydration state based on the urination data and at least one of the urination characteristics by age and season of the toilet user. The dehydration estimation device according to claim 1 .

16. The urination data includes information about urine color, a dehydration state assessment means for classifying the dehydration state of the toilet user into a plurality of levels based on the urination data; Furthermore, The dehydration state assessment means classifies the dehydration state into a plurality of levels based on the urine color included in the urination data of the toilet user when the amount of urine included in the urination data is less than a predetermined amount. The dehydration estimation device according to claim 1 .

17. The dehydration estimation means suspends estimation of the state of dehydration when the number of urinations is equal to or less than a predetermined number of times based on the urination data. The dehydration estimation device according to claim 1 .

18. a notification means for notifying a predetermined destination of highlight information indicating the health status of the toilet user based on the urination data for a predetermined period including the latest urination data; Furthermore, If the number of urinations based on the urination data is equal to or less than a predetermined number of times, the notification means does not notify the specified destination of the highlight information.

18. The dehydration estimation device according to claim 17.

19. the notification means notifies the predetermined destination of recommendation information for improving the health condition of the toilet user based on the urination data for a predetermined period including the latest urination data; If the number of urinations based on the urination data is equal to or less than a predetermined number of times, the notification means does not notify the recommended information to a predetermined destination.

19. The dehydration estimation device according to claim 18.

20. The notification means notifies the predetermined destination of next recommendation information generated based on predetermined input information in response to the recommendation information received by the toilet user.

20. The dehydration estimation device according to claim 19.

21. a frequent urination estimation means for estimating the frequency of urination of the toilet user based on the urination data; Furthermore, The frequent urination inferring means infers frequent urination when the urination interval is shorter than a predetermined period. The dehydration estimation device according to claim 1 .

22. A toilet device; a data storage means for storing urination data acquired based on urination by a toilet user in the toilet device; a dehydration estimation means for estimating a dehydration state of a toilet user based on the urination data stored by the data storage means; Equipped with The urination data includes urination information regarding the amount of urine or the urine flow rate obtained based on a change in the state of the bowl portion of the toilet device. A toilet system characterized by:

23. A control method for a toilet system including a toilet device, a data storage means for storing urination data acquired based on urination by a toilet user in the toilet device, and a dehydration estimation means for estimating a dehydration state of the toilet user based on the urination data stored by the data storage means, a first step of acquiring urination data based on urination of a toilet user on the toilet device; a second step of storing the urination data acquired in the first step in a data storage means; a third step of estimating a dehydration state of the toilet user based on the urination data stored by the data storage means; Including, In the third step, the dehydration state is estimated based on the urination data including urination information related to the amount of urine or the amount of urine flow obtained based on a change in the state of the bowl portion of the toilet device. A method for controlling a toilet system.

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