Server device, analysis method, and program

Abstract

To accurately collect information indicating details of excrements excreted by a user of a toilet without the need to conduct a hearing from the user, while considering privacy of the user of the toilet, and cope with a case where an immediate notification to a monitor is required.SOLUTION: A server 40 comprises: a receiving unit that receives detail information indicating details of excretion being a result of analyzing excrements in a toilet bowl from imaging data picked up in the toilet bowl; a storage unit that stores the detail information received by the receiving unit; and an information processing unit. The detail information includes at least information indicating the date and time of excretion, the type of excretion, and shapes of the excrements. The information processing unit aggregates the detail information for each shape of the excrements.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present disclosure relates to an excrement analyzer, an analysis system, a server device, and a program. [Background technology]

[0002] Caregivers who provide excretion assistance in the field of care are expected to maintain the dignity of the person requiring care while reducing incontinence and encouraging independence. Because excretion assistance in the field of care can sometimes damage the dignity of the person requiring care, it places a heavy burden on caregivers, and support is needed to reduce the workload.

[0003] In addition, there are cases where the caregiver needs assistance when the care recipient gets off the toilet seat or when leaving the toilet, and there are also cases where the caregiver must be with the care recipient all the time before and after excretion in order to prevent any unforeseen incidents in the toilet. This is another point where the burden on the caregiver can be said to be large.

[0004] The caregiver's duties include creating a toilet diary for the person requiring care to help with excretion. To this end, the caregiver obtains information to be recorded in the toilet diary by either entering the toilet together with the person requiring care and observing the person's excretion behavior or by interviewing the person requiring care.

[0005] In the former case, it is mainly carried out for those who are unable to hear accurate information due to dementia, etc. In the former case, since being observed while excreting is embarrassing for the care recipient, it can be said that there are likely to be situations that violate the dignity of the care recipient, and observation in such a case is also a burden on the caregiver.

[0006] On the other hand, in the latter case, inaccurate reports may occur due to the embarrassment of the care recipient, so it can be said that the excretion records are personal, and as a result, even if the care recipient performs the same excretion act, the contents of the excretion diary may differ. If such differences exist, it may be difficult for the caregiver to accurately grasp the health damage caused by constipation or urinary disorders, which may delay the response, or even if the care recipient does not suffer from health damage, incorrect reporting may result in unnecessary medication such as laxatives being administered more frequently. Therefore, in order to compensate for such differences, the burden on the caregiver in terms of excretion management and excretion records becomes greater.

[0007] In addition, if the person requiring care has dementia, they may mistake the urinary pad for toilet paper when they are using the toilet, or may flush the urinary pad down the toilet when they are intentionally trying to hide evidence of their failure to use the toilet (feces or urine incontinence) out of embarrassment. In such cases, or periodically, the care facility must not only request a contractor to clean the drain pipes and remove foreign objects, but also to clear the blockages, and the facility related to the drainage cannot operate during the work. In order to solve this problem, the caregiver may check whether the person requiring care has finished using the toilet or if there is any abnormality in the toilet, but even if they later interview the person for the toilet diary, they will still have to wait by the user's side.

[0008] In order to improve these situations, a mechanism has been proposed for managing the excretion of toilet users by installing sensors in the toilet and analyzing data acquired by the sensors. For example, Patent Document 1 describes a method for use with a subject's human waste placed in a toilet bowl. In this method, while the human waste is placed in the toilet bowl, one or more optical sensors are used to receive light from the toilet bowl, and a computer processor is used to analyze the received light to detect one or more spectral components indicative of light absorption by red blood cell components in the received light. In response to the detection, the method determines that blood is present in the human waste, and generates an output of an output device at least in part in response to the determination. Patent Document 1 also describes monitoring the subject's human waste over an extended period of time, comparing the amount of blood detected in the human waste with a threshold amount over a period of time, and generating an alert if the degree of bleeding indicates the presence of cancer and / or polyps.

[0009] Patent Document 2 describes a pet excretion notification system connected to at least a user terminal and a pet toilet. The excretion notification system described in Patent Document 2 acquires individual identification information including at least the name of the individual pet from the user terminal when use is started, and registers the individual identification information in association with the pet's identifier. After use is started, this excretion notification system acquires weight information of the individual pet from the pet toilet and stores the weight information in association with the pet's identifier, and calculates and registers a body weight threshold based on the average weight of the individual pet in a predetermined period. Furthermore, after use is started, this excretion notification system acquires urination information of the individual pet from the pet toilet, calculates the average number of urinations and amount of urination of the individual pet in a predetermined period, and registers them as the urination number threshold and the urination amount threshold, respectively. Then, when the weight information or urination information of the individual pet obtained from the pet toilet deviates from each threshold, this excretion notification system notifies alert information indicating a possible sign of a predetermined pathology. In addition, this excretion notification system is equipped with a camera to determine whether the pet has entered the pet toilet.

[0010] As a technique for finding the daily change tendency of the Na / K ratio in the urine of a subject, Patent Document 3 describes a urine component analyzer for the purpose of accurately determining the Na / K ratio in the urine excreted by the subject. This device stores data representing the correlation between the statistical concentration ratio obtained by performing statistical processing on the Na / K ratio in multiple urine excreted by a person and the Na / K ratio in the total urine of one or more days when all urine excreted by a person on one or more days is collected. In addition, this device obtains the statistical concentration ratio by performing statistical processing on the Na / K ratio in the urine of the subject on multiple times, on the premise that the Na / K ratio in one urine excreted by the subject for all multiple time periods of the day is input. Then, this device converts and obtains the Na / K ratio in the total urine of the subject for one or more days based on this statistical concentration ratio and using the stored correlation. In addition, the device sequentially stores the Na / K ratio in association with the urination date and time, the measurement date and time, and the time period when the urination occurred. By reading out the stored contents, the device allows the user to easily know the daily change tendency of the Na / K ratio in the subject's total urine for one or more days.

[0011] Furthermore, as a technique for estimating the health condition of a living organism, Patent Document 4 describes a data detection device for the purpose of acquiring biometric data non-contact and non-invasively to estimate the health condition of a living organism. This device includes an image capturing unit that captures at least one of the anus and its surroundings, the private parts and its surroundings, or the excrement of the living organism, and a data analysis unit. This data analysis unit acquires biometric data relating to the properties of the anus, private parts, or excrement of the living organism by analyzing the images captured by the image capturing unit, and estimates the health condition of the living organism from the biometric data. Here, the properties of the excrement are at least one of the color, shape, temperature, light reflectance, or light transmittance of the excrement.

[0012] Patent Document 5 describes a bioinformation utilization system that aims to efficiently collect sufficient information to create highly accurate value-added information. In this system, body temperature, urinary protein concentration, urinary glucose concentration, urinary amino acid concentration, and stool viscosity are used as bioinformation. In addition, this system creates value-added information including values ​​obtained by aggregating measured values ​​at a predetermined measurement date and time by residential district number corresponding to the subject identification number. Patent Document 5 also describes that the value aggregated by residential district number is the average body temperature by residential district, and that value-added information containing the average value of collected fevers of subjects aggregated by residential district number is effective for verification. The verification here refers to the verification of the geographical distribution of the prevalence of infectious diseases such as influenza. [Prior art documents] [Patent documents]

[0013] [Patent Document 1] Special Publication No. 2018-510334 [Patent Document 2] JP 2019-071896 A [Patent Document 3] JP 2017-072410 A [Patent Document 4] JP 2007-252805 A [Patent Document 5] JP 2007-323528 A Summary of the Invention [Problem to be solved by the invention]

[0014] The technology described in Patent Document 1 can only determine the presence of blood in the excrement, and cannot monitor for foreign objects or grasp the state of the excrement other than the presence of blood. Therefore, the applicant thought it would be desirable to create an excrement diary based on image data captured by an imaging device. Note that although the system described in Patent Document 2 has a camera, the camera is for monitoring the pet and is not used to capture the excrement.

[0015] However, toilet users, including those who require care, are burdened with the mental burden of having their excretory actions and waste photographed and managed by an imaging device. This mental burden is related to privacy, as the captured image data may be seen by a third party. Therefore, it is desirable to have a way of reducing the mental burden on toilet users by capturing image data of excrement using a toilet sensor but not allowing third parties to see it.

[0016] Furthermore, in order to create an excretion diary, it is necessary to accurately analyze and record the image data of the excretion. However, accurate analysis takes time, and it is often not possible to grasp the health damage to the user from a single excretion, and there are also situations where it is necessary to immediately notify the caregiver.

[0017] For example, it is conceivable to obtain advanced analysis results by performing analysis of the image data using a cloud service, but since the image data must be sent to a server device that provides the service and the analysis results must be waited for, it becomes difficult to immediately notify a monitor such as a caregiver. Examples of situations in which an immediate notification is required include a notification of the presence of a foreign object for removal, a notification of the start of excretion, a notification of the end of excretion, and a notification of other abnormalities. In addition, sending the image data to a server device for analysis places a heavy mental burden on the toilet user in terms of privacy, as described above.

[0018] On the other hand, if one were to try to achieve analysis at the same speed and accuracy as a cloud service using only a device installed in the toilet without using a cloud service, it would be necessary to install a computer with the specifications required for that analysis. The computer here can refer to a CPU (Central Processing Unit) or the like. However, installing such a computer is not realistic due to issues such as space, heat generation, and price. The technologies described in Patent Documents 3 to 5 cannot solve the problems described above.

[0019] An object of the present disclosure is to provide an excrement analysis device, an analysis system, a server device, a program, etc. that solves the above-mentioned problem. The above-mentioned problem is to accurately collect information indicating the contents of excrement excreted into a toilet bowl without having to ask the toilet user, while respecting the privacy of the toilet user, and to make it possible to respond to situations where an immediate notification to a supervisor is required. [Means for solving the problem]

[0020] An excrement analysis device according to a first aspect of the present disclosure comprises an input unit that inputs imaging data captured by an imaging device installed so as to include within its imaging range the excrement excretion area in the toilet bowl, a holding unit that temporarily holds the imaging data input by the input unit, a first analysis unit that analyzes first analysis target data, which is the imaging data input by the input unit, and outputs notification information to a monitor monitoring users of the toilet, and a second analysis unit that analyzes second analysis target data, which is the imaging data input by the input unit and temporarily held in the holding unit, and outputs detailed information indicating the contents of the excretion.

[0021] An analysis system according to a second aspect of the present disclosure comprises the excrement analysis device, a terminal device used by the monitor and connected to the excrement analysis device, and a server device connected to the excrement analysis device and the terminal device, wherein the excrement analysis device outputs the notification information by transmitting it to the terminal device and outputs the detailed information by transmitting it to the server device, the server device stores the detailed information received from the excrement analysis device in a state viewable from the terminal device, and the terminal device comprises a diary generation unit that generates an excretion diary based on the notification information received from the excrement analysis device and the detailed information stored in the server device.

[0022] A server device according to a third aspect of the present disclosure includes a receiving unit that receives the detailed information from the excrement analysis device, a memory unit that stores the detailed information received by the receiving unit, and an information processing unit, wherein the detailed information includes at least information indicating the excretion date and time, the type of excrement, and the shape of the defecation, and the information processing unit compiles the detailed information for each shape of the defecation.

[0023] A program according to a fourth aspect of the present disclosure is a program for causing a control computer provided in an excrement analysis device to execute the following steps: an input step of inputting imaging data captured by an imaging device installed so as to include within its imaging range the excrement excretion area in the toilet bowl; a retention step of temporarily retaining the imaging data input in the input step; a first analysis step of analyzing first analysis target data, which is the imaging data input in the input step, and outputting notification information to a monitor monitoring users of the toilet; and a second analysis step of analyzing second analysis target data, which is the imaging data input in the input step and temporarily retained in the retention step, and outputting detailed information indicating the contents of the excretion. Effect of the Invention

[0024] The present disclosure can provide an excrement analysis device, analysis system, server device, program, etc. that solves the above problems. That is, the present disclosure can accurately collect information indicating the contents of excrement excreted into a toilet bowl without having to ask the toilet user, while respecting the privacy of the toilet user, and can also respond to situations where an immediate notification to a supervisor is required. [Brief description of the drawings]

[0025] [Figure 1] 1 is a block diagram showing an example of the configuration of an excrement analyzer according to a first embodiment. [Diagram 2] FIG. 11 is a diagram showing an example of the configuration of an excrement analyzing system according to a second embodiment. [Diagram 3] 3 is a block diagram showing an example of the configuration of an excrement analyzer in the excrement analysis system of FIG. 2. FIG. [Figure 4] FIG. 3 is a conceptual diagram for explaining an example of processing in the excrement analyzing system of FIG. 2. [Diagram 5] 3 is a diagram for explaining an example of processing in an excrement analyzer in the excrement analyzing system of FIG. 2. FIG. [Figure 6] 3 is a diagram for explaining an example of processing in an excrement analyzer in the excrement analyzing system of FIG. 2. FIG. [Figure 7] 3 is a diagram for explaining an example of processing in an excrement analyzer in the excrement analyzing system of FIG. 2. FIG. [Figure 8] 3 is a flow diagram for explaining an example of processing in an excrement analyzer in the excrement analyzing system of FIG. 2. [Figure 9] 3 is a flow diagram for explaining an example of processing in an excrement analyzer in the excrement analyzing system of FIG. 2. [Figure 10] FIG. 10 is a diagram showing an example of a fecal analysis included in a non-real-time analysis in the processing example of FIG. [Figure 11] FIG. 10 is a diagram showing an example of stool color analysis included in non-real-time analysis in the example processing of FIG. 9. [Figure 12]FIG. 10 is a diagram showing an example of a urine volume analysis included in a non-real-time analysis in the processing example of FIG. [Figure 13] FIG. 11 is a block diagram showing a configuration example of a server device according to a third embodiment. [Figure 14] FIG. 13 is a diagram showing an example of the configuration of an analysis system according to a fourth embodiment. [Figure 15] 15 is a diagram showing an example of transmission information transmitted from an excrement analyzer in the analysis system of FIG. 14. FIG. [Figure 16] 15 is a diagram showing an example of an aggregated information table included in an excretion information database stored in a server device in the analysis system of FIG. 14. FIG. [Figure 17] 15 is a diagram showing an example of a tabulated information table included in an excretion information database stored in a server device in the analysis system of FIG. 14. FIG. [Figure 18] 15 is a diagram showing an example of a tabulated information table included in an excretion information database stored in a server device in the analysis system of FIG. 14. FIG. [Figure 19] 15 is a diagram showing an example of a tabulated information table included in an excretion information database stored in a server device in the analysis system of FIG. 14. FIG. [Figure 20] 15 is a flowchart illustrating an example of processing performed by a server device in the analysis system of FIG. 14. [Figure 21] FIG. 13 is a diagram showing an example of the configuration of an analysis system according to a fifth embodiment. [Figure 22] 22 is a diagram showing an example of an aggregated information table included in an excretion information database stored in a server device in the analysis system of FIG. 21. FIG. [Figure 23] 22 is a diagram showing an example of a tabulated information table included in an excretion information database stored in a server device in the analysis system of FIG. 21. FIG. [Figure 24] 22 is a flowchart illustrating an example of processing performed by a server device in the analysis system of FIG. 21. [Diagram 25] FIG. 2 illustrates an example of a hardware configuration of the apparatus. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0026] Hereinafter, the embodiments will be described with reference to the drawings. In the embodiments, the same or equivalent elements may be given the same reference numerals, and duplicated descriptions will be omitted as appropriate. In addition, the reference numerals and names of elements in the drawings are conveniently given to each element as an example to aid understanding, and they do not limit the contents of the present disclosure in any way. In addition, although some of the drawings described below depict unidirectional and bidirectional arrows, each arrow simply indicates the direction of a certain signal (data) flow, and does not exclude bidirectionality or unidirectionality.

[0027] <Embodiment 1> The excrement analyzer according to the first embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing an example of the configuration of the excrement analyzer according to the first embodiment.

[0028] As shown in FIG. 1, an excrement analyzer 1 according to this embodiment can include an input section 1a, a holding section 1b, a first analysis section 1c, and a second analysis section 1d.

[0029] The input unit 1a inputs imaging data (image data) captured by an imaging device (hereinafter, exemplified as a camera) installed so as to include within its imaging range the excrement excretion area in the toilet bowl. This imaging data is used by the excrement analyzer 1 to analyze the contents of the excrement and obtain information about it.

[0030] Therefore, the excrement analysis device 1 is connected to or includes a camera installed in this manner. However, it can be said that it is preferable for the excrement analysis device 1 to include a camera in terms of integrating the device and preventing the image data from leaking to other devices. The camera is not limited to a visible light camera, but may be an infrared camera or the like, and may also be a video camera as long as it can extract still images. When the camera is connected to the outside of the excrement analysis device 1, it may be connected to the input unit 1a. This image data may include additional information (attached information) such as the image capture date and time, the image capture conditions, etc. The image capture conditions may include, for example, the resolution if the resolution can be set, and the zoom magnification if the camera has a zoom function.

[0031] The excretion range can be an area including the water-filled part of the toilet bowl, and can also be called the expected excretion range. By installing the camera so that such an excretion range is included in the imaging range, the captured imaging data will include excrement and the like as a subject. Of course, the excretion range is preferably an area that does not include the user (a toilet user), and the camera is preferably installed so that the lens of the camera is not visible to the user. In addition, when the excretion analyzer 1 is used in a hospital or a care facility, for example, the user is mainly a patient or other person who requires care. In addition, examples of the caregiver include a caregiver, and in some cases, a doctor, but it is not limited to a caregiver, and it may also be an assistant, or anyone else.

[0032] Hereinafter, information obtained from the excrement analysis device 1 will be referred to as excretion information. The excretion information includes information indicating the content of the excretion, and in a simpler example, it can be information indicating whether the excretion is stool (feces) or urination (urine). The excretion information can also include other information such as information indicating the color of the excretion, and its shape if it is a solid object. In addition, the excretion information can include or be added with additional information such as date and time information indicating the date and time of shooting or acquisition of the imaging data, and shooting conditions.

[0033] The analysis of the contents of excretion is performed by the first analysis unit 1c and the second analysis unit 1d as described below, and a storage unit 1b is provided to temporarily store data to be analyzed by the second analysis unit 1d. In other words, the storage unit 1b temporarily stores the imaging data inputted by the input unit 1a. The storage unit 1b can be a storage device such as a memory.

[0034] The first analysis unit 1c analyzes the first analysis target data, which is the imaging data inputted by the input unit 1a, and outputs notification information to a supervisor who supervises users of the toilet. The notification information is a part of the excretion information, and is information that notifies the contents according to the analysis result by the first analysis unit 1c. Although a specific example of the notification information will be described later, the notification information can be information that notifies the fact that a foreign object has been mixed in when a foreign object is captured in the imaging data. In addition, since the notification information is information that is presented to the supervisor by notifying the supervisor, it can also be called presentation information. In addition, the notification information can include information that the supervisor needs to deal with, and in that case, it can also be called warning information. Since the first analysis unit 1c analyzes the imaging data inputted by the input unit 1a, the analysis performed here corresponds to real-time analysis. Therefore, the first analysis unit 1c can be called a real-time analysis unit.

[0035] Furthermore, the output destination of the notification information by the first analysis unit 1c may be a terminal device used by the monitor, and the direct output destination may be a server device capable of receiving the notification information and transferring the notification to the terminal device. Note that the terminal device used by the monitor is not limited to a terminal device used by an individual monitor such as a caregiver, but may be, for example, a terminal device installed in a monitoring station such as a nurse's station, and this terminal device may function as an alarm device. Furthermore, the output destination of the notification information is not limited to one location.

[0036] Furthermore, the imaging data input by the input unit 1a or the imaging data output by the input unit 1a to the holding unit 1b and the first analysis unit 1b at the downstream stage can be data when, for example, an object is detected as a subject in the excretion area or a change such as a change in the color of the standing water is detected. These detections can be performed, for example, by the camera or the input unit 1a capturing images with the camera all the time or at regular intervals, and using the captured image data obtained therefrom. Alternatively, imaging can be performed based on the user detection results from a separately provided user detection sensor (such as a load sensor provided on the toilet seat or other human presence sensor), and the captured image data at that time can be selected as data to be output by the camera or the input unit 1a to the downstream stage.

[0037] The second analysis unit 1d analyzes the second analysis target data, which is the imaging data input by the input unit 1a and temporarily stored in the storage unit 1b, and outputs detailed information indicating the contents of the excretion. The detailed information is a part of the excretion information, and is information indicating the contents according to the analysis result by the second analysis unit 1d. The detailed information is information that provides more detailed information than the notification information, and examples of which will be described later, and may be information indicating, for example, stool quality, stool volume, stool color, urine volume, urine color, etc. Since the second analysis unit 1d analyzes the imaging data stored in the storage unit 1b, the analysis performed here corresponds to non-real-time analysis. Therefore, the second analysis unit 1d can be called a non-real-time analysis unit.

[0038] The destination of the detailed information by the second analysis unit 1d can be a server device that collects and manages excretion information, and for example, this server device can be a cloud server device. In the case of a facility such as a hospital, the server device can be installed within the facility, and in the case of personal use, it can be installed in a personal home or an apartment building. In addition, the destination of the detailed information is not limited to one location.

[0039] The excrement analyzer 1 may have a communication unit (not shown), and this communication unit may be provided in each of the first analysis unit 1c and the second analysis unit 1d. This communication unit may be configured, for example, with a wired or wireless communication interface.

[0040] The excrement analyzer 1 may have a control unit (not shown) for controlling the entire excrement analyzer 1, and this control unit may include parts of the above-mentioned input unit 1a, storage unit 1b, first analysis unit 1c, and second analysis unit 1d. This control unit may be realized, for example, by a CPU (Central Processing Unit), a working memory, and a non-volatile storage device storing a program. This program may be a program for causing the CPU to execute the processing of each of the units 1a to 1d. The storage unit 1b may use this storage device, or may have a separate storage device. The control unit provided in the excrement analyzer 1 may also be realized, for example, by an integrated circuit.

[0041] As described above, the excrement analysis device 1 is a device that analyzes the contents of excrement excreted in the toilet and outputs excretion information, and can also be called a toilet excretion analysis device or an excretion information acquisition device. The excrement analysis device 1 can be a device that functions as an edge toilet sensor in an excrement analysis system (analysis system) configured on a network including a monitor's terminal device and an external server device.

[0042] As described above, the excrement analysis device 1 separates the analysis of the image data acquired from the camera into a real-time analysis for the purpose of notification and a non-real-time analysis for the purpose of recording. This allows the excrement analysis device 1 to have a built-in control unit such as a CPU that is space-saving and power-saving. This means that the excrement analysis device 1 efficiently uses limited computational resources by separating the analysis processing into functions that require immediacy and other functions. Furthermore, the excrement analysis device 1 does not need to transmit the image data acquired from the camera and other image data to an external device such as a cloud, and can analyze the excrement by itself installed in the toilet. In other words, all images and videos used in the analysis by the excrement analysis device 1 are processed within the excrement analysis device 1, and the images and videos are not transmitted to the outside. Therefore, it can be said that the excrement analysis device 1 is configured to reduce the mental burden on the user regarding privacy.

[0043] As described above, the excrement analyzer 1 can accurately collect information indicating the contents of excrement excreted into the toilet bowl without having to listen to the toilet user while respecting the privacy of the toilet user, and can also respond to situations where an immediate notification to a monitor is required. In other words, while improvements are being made to install sensors in toilets to reduce the burden of excretion management in monitoring such as nursing care, the excrement analyzer 1 can achieve both consideration of the privacy of toilet users and notification and recording. The notification and recording here are notifications of real-time events at the monitoring site such as the nursing site and recording of accurate information. Therefore, the excrement analyzer 1 can reduce the physical and mental burden on monitors and toilet users.

[0044] <Embodiment 2> The second embodiment will be described with a focus on the differences from the first embodiment with reference to Figures 2 to 12, but the various examples described in the first embodiment can be applied. Figure 2 is a diagram showing an example of the configuration of an excrement analysis system according to the second embodiment, and Figure 3 is a block diagram showing an example of the configuration of an excrement analysis device in the excrement analysis system of Figure 2.

[0045] The excrement analysis system according to this embodiment (hereinafter, this system) can include an excrement analysis device 10 attached to a toilet 20, a terminal device 50 used by a caregiver, and a server device (hereinafter, server) 40. The caregiver can be considered an example of a monitor who monitors toilet users.

[0046] The excrement analyzer 10 is an example of the excrement analyzer 1, and is illustrated as a toilet-mounted device, but it may be any device that is installed inside a toilet. The toilet 20 may be provided with a toilet seat 22 equipped with a warm water flushing function for user washing, and a toilet seat cover 23 for covering the toilet seat 22, on its main body 21. The excrement analyzer 10 and the toilet 20 may constitute an analysis-equipped toilet 30 that is equipped with a function for analyzing and outputting the results.

[0047] The shape of the excrement analyzer 10 is not limited to the shape shown in FIG. 2, and may be configured such that all or part of its functions are embedded in the toilet seat 22 or the like. Some of the functions of the excrement analyzer 10 may be provided on the toilet seat 22 side. For example, instead of providing the distance sensor 16a described later in the excrement analyzer 10, a weight sensor may be provided on the toilet seat 22, and the excrement analyzer 10 may receive information from the weight sensor via wireless or wired communication. The weight sensor may be provided in the box-to-box connector 12 described later, or may simply be a pressure sensor that detects pressure above a certain level. Instead of providing the first camera 16b described later in the excrement analyzer 10, a camera may be provided on the toilet seat 22 side, and the excrement analyzer 10 may receive image data from the camera via wireless or wired communication.

[0048] The server device (server) 40 and the terminal device 50 can be wirelessly connected to the excrement analyzing device 10, and the terminal device 50 can be wirelessly connected to the server 40. These connections can be made within one wireless LAN (Local Area Network), for example, but other connection forms such as connection via separate networks can also be adopted. Also, some or all of these connections may be made by wire.

[0049] In this system connected in this manner, the excrement analyzer 10 outputs notification information by transmitting it to the terminal device 50, and outputs detailed information by transmitting it to the server 40. The terminal device 50 is a terminal device held by a caregiver of the toilet user, and can be a portable excrement analyzer, but may also be a stationary device. In the former case, the terminal device 50 can be a mobile phone (including what is called a smartphone), a tablet, a mobile PC, or the like. The server 40 can be a device that collects and manages excrement information including detailed information, and stores the detailed information received from the excrement analyzer 10 in a state that can be viewed from the terminal device 50.

[0050] The server 40 may also include a control unit 41 for controlling the entire server, a storage unit 42 for storing detailed information in, for example, a database (DB) format, and a communication unit (not shown) for making the above-mentioned connection. The control unit 41 controls the storage of detailed information transmitted from the excrement analyzer 10 in the storage unit 42, and controls browsing from the terminal device 50. The control unit 41 may be realized, for example, by a CPU, a working memory, and a non-volatile storage device storing a program. This storage device may also serve as the storage unit 42, and the program may be a program for causing the CPU to realize the functions of the server 40. The control unit 41 may also be realized, for example, by an integrated circuit.

[0051] In addition, the terminal device 50 may include a control unit for controlling the entire device, a storage unit, and a communication unit for making the above-mentioned connection, although these are not shown. This control unit, like the control unit 41, may be realized by, for example, a CPU, a working memory, a non-volatile storage device storing a program, or an integrated circuit. In addition, the program stored in the storage device may be a program for causing the CPU to realize the functions of the terminal device 50.

[0052] Moreover, the terminal device 50 preferably includes a diary generation unit that generates an excretion diary based on the notification information received from the excretion analyzer 10 and the detailed information stored in the server 40. This diary generation unit can be installed, for example, by incorporating a diary creation application program into the terminal device 50. The created excretion diary can be stored in an internal memory unit. The diary creation unit can also be installed as a part of a care record unit that creates a care record. The care record creation unit can also be realized by incorporating an application program into the terminal device 50.

[0053] Next, a detailed example of the excrement analysis device 10 will be described. The excrement analysis device 10 can be composed of two devices, for example, as shown in Fig. 2 and Fig. 3. More specifically, the excrement analysis device 10 can have two boxes, for example, a first external box 13 and a second external box 11, as its housing. The excrement analysis device 10 can also have an inter-box connection part (inter-box connection structure) 12 that connects between the first external box 13 and the second external box 11. The first external box 13 and the second external box 11 can be connected by an interface, a specific example of which is shown in Fig. 3.

[0054] The excrement analysis device 10 in this example can be installed in the main body 21 of the toilet 20, for example, as follows. That is, the excrement analysis device 10 can be installed in the toilet 20 by placing the inter-box connector 12 on the edge of the main body 21 so that the first external box 13 is disposed on the inside of the main body 21 (the side where the excrement is excreted) and the second external box 11 is disposed on the outside of the main body 21.

[0055] For example, a distance sensor 16a and a first camera 16b can be stored in the first external box 13. As will be described later, the distance sensor 16a is an example of a seating sensor that detects when a person sits on the toilet seat 22, and the first camera 16b is a camera that captures an image of excrement.

[0056] The second external box 11 includes a device that performs real-time analysis based on the imaging data (image data) captured by the first camera 16b, and non-real-time analysis based on the image data and the real-time analysis results. The second external box 11 also includes a communication device 14 that, under the control of the device, notifies the caregiver when an event occurs and transmits the analysis results to the server 40.

[0057] For example, the second external box 11 can accommodate a CPU 11a, a connector 11b, USB I / Fs 11c and 11d, a WiFi module 14a, a Bluetooth module 14b, a human sensor 15a, and a second camera 15b. Note that USB is an abbreviation for Universal Serial Bus, and USB, WiFi, and Bluetooth are all registered trademarks (hereinafter the same). The communication device 14 is exemplified by the modules 14a and 14b, and the CPU 11a executes real-time analysis and non-real-time analysis while transmitting and receiving data to and from other parts via the elements 11b, 11c, and 11d as necessary. Note that in this example, the CPU 11a is described as also being equipped with a memory as an example of the holding unit 1b. Also, the second external box 11 can be directly connected to the CPU 11a without being equipped with various I / Fs and connectors. Also, the communication device 14 is not limited to a communication module of the exemplified standard, and may be wireless or wired. Examples of communication modules include a Long Term Evolution (LTE) communication module, a fifth generation mobile communication module, and a Low Power, Wide Area (LPWA) communication module.

[0058] As shown in FIG. 3, the first external box 13 and the second external box 11 are connected by an interface exemplified by a connector 11b and a USB I / F 11c, and the connection wire is provided inside the inter-box connection section 12 to form a single excrement analysis device 10.

[0059] The first external box 13 will now be described. Distance sensor 16a is a sensor that measures the distance to an object (the buttocks of the user of toilet bowl 20) and detects that the user has sat on toilet seat 22, and detects that the object has sat on toilet seat 22 when a certain period of time has elapsed after the threshold value is exceeded. Distance sensor 16a also detects that the user has left the toilet seat 22 when the distance to the object changes after sitting down.

[0060] The distance sensor 16a may be, for example, an infrared sensor, an ultrasonic sensor, an optical sensor, or the like. When the distance sensor 16a is an optical sensor, a transmitting / receiving element may be disposed so as to transmit and receive light (not limited to visible light) through a hole provided in the first external box 13. The transmitting / receiving element may be configured as a transmitting element and a receiving element separately, or may be integrated. The distance sensor 16a is connected to the CPU 11a via the connector 11b, and is capable of transmitting the detection result to the CPU 11a.

[0061] The first camera 16b is an example of a camera that captures the imaging data input to the input unit 1a in Fig. 1, and can be an optical camera with a lens portion disposed in a hole provided in the first external box 13. As described in the first embodiment, the first camera 16b is installed so that the imaging range includes the excrement excretion range in the toilet bowl 20. The first camera 16b is connected to the CPU 11a via the USB I / F 11c, and transmits the imaging data to the CPU 11a.

[0062] The second external box 11 will now be described. The CPU 11a is an example of a main control unit of the excrement analyzer 10, and controls the entire excrement analyzer 10. As described below, real-time analysis and non-real-time analysis are executed by the CPU 11a. The connector 11b connects the human sensor 15a and the distance sensor 16a to the CPU 11a. The USB I / F 11c connects the first camera 16b to the CPU 11a, and the USB I / F 11d connects the second camera 15b to the CPU 11a.

[0063] The human presence sensor 15a is a sensor that detects the presence of a person (entry or exit of a person) in a specific area (a measurement area range of the human presence sensor 15a), and this specific area can be set as an area in which entry and exit to the restroom can be determined. The human presence sensor 15a can adopt any detection method, for example, an infrared sensor, an ultrasonic sensor, an optical sensor, etc. The human presence sensor 15a is connected to the CPU 11a via the connector 11b, and when it detects a person in the specific area, it transmits the detection result to the CPU 11a.

[0064] Based on the detection result, the CPU 11a can control the operation of the distance sensor 16a and the first camera 16b. For example, the CPU 11a can perform processing such as activating the distance sensor 16a when the detection result indicates that a person has entered the room, and activating the first camera 16b when the distance sensor 16a detects that a person is seated.

[0065] The second camera 15b may be an optical camera with a lens portion disposed in a hole provided in the second external box 11, and is an example of a camera that captures a facial image of a user to obtain facial image data in order to identify the user of the toilet. The second camera 15b may be installed on the toilet bowl 20 so that the user's face is included in the imaging range, but may also be installed in the toilet room in which the toilet bowl 20 is installed.

[0066] The Bluetooth module 14b is an example of a receiver that receives identification data for identifying a user from a Bluetooth tag held by the user, and can be replaced with a module based on other short-range communication standards. The Bluetooth tag held by the user can have a different ID for each user and can be embedded in a wristband or the like so that the user can keep it.

[0067] The WiFi module 14a is an example of a communication device that transmits various data including notification information to the terminal device 50 and various data including detailed information to the server 40, and can be replaced with a module that adopts other communication standards. The face image data acquired by the second camera 15b and the identification data acquired by the Bluetooth module 14b can be added to or embedded in the notification information and detailed information and then transmitted to the terminal device 50 and the server 40, respectively. The terminal device 50 and the server 40 that receive the face image data can perform face recognition processing based on the face image data and identify the user. However, the excrement analyzer 10 can be configured not to transmit face image data. In that case, if the face recognition processing is performed by the CPU 11a, user identification by face recognition is possible, and identification data indicating the result can be the subject of transmission.

[0068] The USB I / F 11c, or the CPU 11a and the USB I / F 11c, can be an example of the input unit 1a in FIG. 1, and inputs the image data captured by the first camera 16b. The CPU 11a and the WiFi module 14a can be an example of the first analysis unit 1c in FIG. 1, and the CPU 11a analyzes the image data in real time and transmits notification information to the terminal device 50 via the WiFi module 14a. The notification information can also be transmitted via the Bluetooth module 14b. In this way, the notification information can be output by transmitting it to the terminal device 50 connected to the excrement analyzer 10 via a network or a short-range wireless communication network. Of course, the transmission here may be via the server 40 or another server, as long as it is transferred to the terminal device 50. The transmitted notification information does not include the image data itself, which not only reduces the mental burden on the user regarding privacy, but also reduces the amount of transmitted data. The additional information of the image data (such as the image capture date and time) can be transmitted.

[0069] Although a smartphone is illustrated as an example of the terminal device 50, the notification destination (transmission destination) may be, in addition to or instead of a smartphone, a notification device of a nurse call system, another terminal device owned by a caregiver, an intercom, etc. Examples of the other terminal devices include a PHS (Personal Handy-phone System).

[0070] The CPU 11a includes a storage device such as a memory and can be an example of the storage unit 1b in FIG. 1, and stores the input imaging data and the results of the real-time analysis. The CPU 11a and the WiFi module 14a can be an example of the second analysis unit 1d in FIG. 1, and the CPU 11a performs non-real-time analysis of the stored data and transmits detailed information to the server 40 via the WiFi module 14a. In this way, the detailed information can be output by transmitting it to the server 40 connected to the excrement analyzer 10 via a network. The transmitted detailed information does not include the imaging data itself, which not only reduces the mental burden on the user regarding privacy but also reduces the amount of transmitted data. Note that additional information of the imaging data (such as the imaging date and time) can be transmitted. In this way, the imaging data itself is not output to the outside of the excrement analyzer 10, so that the user's privacy can be protected.

[0071] The real-time analysis and non-real-time analysis will be briefly described with reference to Figures 4 and 5. Figure 4 is a conceptual diagram for explaining an example of processing in this system, and Figure 5 is a diagram for explaining an example of processing in the excrement analyzer 10.

[0072] As shown in FIG. 4, an example will be given in which a user P uses a toilet bowl 30 with an analysis function installed in a toilet, and a caregiver C of the user P monitors the state of the toilet bowl 30. When the user P uses the toilet bowl 30 with an analysis function, the CPU 11a detects that the user has sat on the toilet seat based on the detection result from the distance sensor 16a that functions as a seating sensor. When the CPU 11a detects that the user has sat on the toilet seat, it instructs the first camera 16b to start shooting, and performs real-time analysis 31 based on the captured image data. The CPU 11a can perform foreign object determination as the real-time analysis 31. More specifically, the CPU 11a can perform an analysis of whether or not a foreign object that is an object other than feces and urine is included as a subject other than the toilet bowl and the liquid for cleaning the toilet bowl. The foreign object can also be called a "other object," and may be a liquid or solid other than feces and urine, and may include, for example, one or more of vomit, bloody stool, vomited blood (vomited blood), a urine pad, a diaper, a toilet paper roll, and the like.

[0073] When the result of the real-time analysis 31 indicates that an immediate notification to the caregiver is required, such as detection of a foreign object, the CPU 11a transmits notification information (real-time notification 32) to the terminal device 50 of the caregiver C who is located away from the toilet via the WiFi module 14a. In this way, the CPU 11a can transmit foreign object information indicating whether or not a foreign object is contained (foreign object information indicating the foreign object determination result) to the terminal device 50. This foreign object information is output as at least a part of the notification information.

[0074] This relieves the caregiver C from having to be constantly with the user P during excretion, and enables the caregiver C to rush to the scene in an emergency 51 by receiving the real-time notification 32. Here, the transmitted real-time notification 32 does not include imaging data.

[0075] After completing the real-time analysis 31, the CPU 11a executes a more detailed non-real-time analysis 33, which is a more detailed excrement analysis, based on the stored imaging data and the real-time analysis results. For this purpose, the storage unit in the CPU 11a temporarily stores the real-time analysis results as part of the second analysis target data. The CPU 11a executes transmission 34 of the non-real-time analysis results to the server 40 via the WiFi module 14a.

[0076] Furthermore, the caregiver C of the user P creates 53 a care record (excretion diary) for the user P on the terminal device 50 while appropriately referring 52 to detailed information about the user P stored in the server 40 based on the received notification information. The excretion diary can be created as a part of the care record. In this way, the excretion diary for each user can be recorded on the terminal device 50. The format of the excretion diary is not important.

[0077] In this way, the analysis results of the real-time analysis 31 and the non-real-time analysis 33 are transmitted to the server 40 by executing analysis result transmission 34 using the communication function. The analysis result transmission 34 is transmitted without including the imaging data. The information recorded in the server 40 can be used as a reference 52 by the caregiver C for creating a care record (excretion diary) 53 or for future care support.

[0078] The real-time analysis 31 and non-real-time analysis 33 will be described with reference to Fig. 5 to Fig. 7. Fig. 5 to Fig. 7 are diagrams for explaining an example of processing in the excrement analyzer 10.

[0079] First, an example of input, method, and output of real-time analysis and non-real-time analysis will be described with reference to Fig. 5. Real-time analysis is analysis that requires real-time performance, such as notification to caregiver C. Real-time analysis takes image data (imaging data) captured by the first camera 16b as input, classifies the data into one of the following six types using Deep Learning (DL), for example, and outputs the classification result. The six types are foreign objects (diapers, incontinence pads, etc.), feces, feces + urine, urine, urine drips, and a posterior cleansing device (posterior cleansing machine).

[0080] DL technology can be used to compare an image (background image) before excretion, etc., occurs with an image afterwards (an image during excretion or after excretion is completed). For example, the background image and the image afterwards can be input as input to a learning model, and it can output which of six types it falls into. Alternatively, a difference image of the image afterwards from the background image can be obtained as preprocessing, and this difference image can be input to the learning model, and it can output which of the six types it falls into. If it is classified as a bottom washer, it can be determined that excretion has been completed. These classification types are examples of events that trigger real-time notifications.

[0081] In this way, in the real-time analysis, the notification information can be obtained from the first analysis target data using a trained model that inputs the first analysis target data and outputs the notification information. The notification information can be, for example, information that is predetermined in correspondence with the classification result. In this way, the excrement analyzer 10 can notify the caregiver, etc. of information such as the start and end of excretion, and the presence of foreign matter in the excrement, as the notification information, and the caregiver, etc. can obtain this information in real time. Note that the algorithm (machine learning algorithm) of the trained model and hyperparameters such as the number of layers do not matter, and they may be generated by machine learning. In addition, the machine learning here does not matter whether or not there is teacher data. In addition, a plurality of trained models may be used in the real-time analysis, and for example, a trained model that is different from at least one of the above six types and the other types can be used.

[0082] Non-real-time analysis can be performed, for example, by inputting the image data from the first camera 16b and the real-time analysis result, using two techniques: DL and Image Processing (IP). For example, analysis using DL can output stool characteristics, and analysis using IP can output stool color, stool volume, urine color, and urine volume. Note that here, real-time analysis is treated as pre-processing for non-real-time analysis. In non-real-time analysis, DL and IP are used to compare the analysis results (which may be images) after this pre-processing with the learned data, and output stool characteristics, stool color, etc.

[0083] Here too, DL technology can be used to compare an image (background image) before excretion and the like is performed with an image (image during excretion or after excretion is completed) after excretion. For example, the classification result in real-time analysis, the background image, and the image after excretion can be input as input to the learning model, and fecal matter can be output. Alternatively, a difference image of the image after excretion from the background image can be obtained as preprocessing, and the classification result in real-time analysis and the difference image can be input to the learning model to output fecal matter. Also, only if the classification result in real-time analysis includes feces, analysis by DL in non-real-time analysis may be performed, in which case the above classification result is not necessary for input to the learned model. Also, the processing method in IP does not matter, as long as the desired detailed information can be obtained. For example, a matching process can be performed with a comparison target image stored in advance by extracting the features of the image, and the fecal color, etc. shown by the comparison target image with a high matching rate can be output. In addition, in non-real-time analysis, all outputs may be obtained by either IP or DL.

[0084] In this way, in the non-real-time analysis, at least a part of the detailed information can be obtained from the second analysis target data by using a trained model that inputs the second analysis target data (which may include the real-time analysis result) and outputs the detailed information. The trained model may have any algorithm (machine learning algorithm) or hyperparameters such as the number of layers, and may be generated by machine learning. The machine learning here may or may not have teacher data. A plurality of trained models may be used in the real-time analysis. Furthermore, as described above, in the non-real-time analysis, at least a part of the detailed information can be obtained by image processing of the second analysis target data. As described above, the method of this image processing may be any method as long as the desired detailed information can be obtained.

[0085] A detailed example of real-time analysis will be described with reference to FIG. 6. In real-time analysis, foreign objects, types of excretion, and posterior washer can be judged. First, foreign object detection is performed based on an image (image data) captured by the first camera 16b, which is an optical camera. Foreign object detection can be performed at any time, and when a foreign object is detected, a caregiver is notified. After that, an image captured at the timing of sitting down is used as a background image, and then, based on a preprocessed image (and / or additional information) obtained by preprocessing images captured at a fixed cycle, a judgment is made by DL as to whether the object is feces, feces + urine, urine, or urine dripping. This judgment is made until the time of leaving the seat. The additional information here can also include the additional information exemplified by the shooting date and time, and can be, for example, information indicating a statistical value taking into account the above-mentioned fixed cycle, information indicating an area such as a size, etc. In addition, a posterior washer is also detected by the same method and timing, and the judgment of feces, feces + urine, urine, or urine dripping is completed when the posterior washer is detected.

[0086] In this way, the CPU 11a may transmit at least one of information indicating the usage status of the posterior washer installed on the toilet and information indicating that a person has sat on the toilet as at least a part of the notification information to the terminal device 50 as a result of the real-time analysis. As described above, information indicating the usage status of the posterior washer can be obtained as a result of real-time analysis of the imaging data. This is because the nozzle that discharges the cleaning liquid or the cleaning liquid itself is included as a subject of the imaging data during use. Also, information indicating that a person has sat on the toilet can be obtained by a seating sensor exemplified by the distance sensor 16a. In this way, real-time analysis can also be performed using information other than the imaging data. Note that the usage status of the posterior washer can be known by the CPU 11a not only by analyzing the imaging data, but also by obtaining information from the posterior washer if it is connected to the posterior washer, for example.

[0087] A detailed example of non-real-time analysis will be described with reference to FIG. 7. In non-real-time analysis, analysis can be performed on all images pre-processed in real-time analysis by selecting a background image and an input image. Detailed analysis is performed by selecting a background image and an input image appropriate for each judgment target. To explain an example of combination, first, for feces quality, an image after sitting is selected as the background image, and the last feces image is selected as the input image. In the case of feces only or urine only, similarly, target images are selected for feces color, feces volume, and urine color. However, for urine color, a urine image is used instead of feces. In the case of feces + urine, the last urine image before urination is used as the background image, and the last urine stool image is used as the input image. For urine volume, all images judged as urine dripping are used as input images without using a background image.

[0088] Here, in the non-real-time analysis, the detailed information is outputted as information indicating the amount of urination and the amount of feces, but the detailed information is not limited thereto. In the non-real-time analysis, the detailed information can be outputted as information on at least one of the following: urinary flow rate or amount of urination, the number of defecations or amount of defecation per unit period, and excretion timing, which is the timing of excretion. In particular, in the non-real-time analysis, it is preferable to output, as the detailed information, information indicating at least one of the following: a decrease in urinary flow rate or amount of urination, a decrease in the number of defecations or amount of defecation per unit period, and a prolonged excretion timing, which is the timing of excretion. The decrease in urinary flow rate or amount of urination refers to an increase in the urination interval, in other words. The timing of the excretion can be defined to include at least the date and time of excretion, and the other timings can be defined to include at least the date and time of occurrence of the target event.

[0089] In this way, in the non-real-time analysis, the stool texture, stool color, and urine color can be identified and the stool volume and urine volume can be calculated from the acquired imaging data, and detailed information can be output. In addition, in the non-real-time analysis, for the stool volume and urine volume, threshold processing can be performed and information indicating whether or not a predetermined threshold has been exceeded can be used as detailed information or added to the detailed information. It is desirable that the detailed information output as a result of these threshold processing processes is also sent (notified) to the terminal device 50 directly or via the server 40. Such notifications (which may include warnings) allow the caregiver to understand events that require action.

[0090] Next, an example of the procedure of the real-time analysis process will be described with reference to Fig. 8. Fig. 8 is a flow diagram for explaining an example of the process in the excrement analyzer 10, and is a flow diagram showing an example of the operation content of real-time analysis triggered by a user entering the toilet and sitting on the toilet seat. The operation content described here can be performed mainly by the CPU 11a controlling each part.

[0091] First, the presence or absence of a reaction from the distance sensor 16a functioning as a seating sensor is checked (step S1). If there is no reaction in step S1 (if NO), the system will wait until the seating sensor reacts. If the user sits down, the distance sensor 16a will react, and step S1 will result in YES. If step S1 results in YES, the terminal device 50 is notified of the user's sitting down (step S2), and real-time analysis is started (step S3). Note that if the human sensor 15a detects entry before the user sits down, the terminal device 50 can also be notified of the user's entry, and the same applies to the user's leaving the room.

[0092] In the real-time analysis, the inside of the toilet is photographed by the first camera 16b, and it is first determined whether the image can be normally identified (step S4). If an abnormality is detected (NO in step S4), an abnormality notification is sent to the caregiver's terminal device 50 (step S5). In this way, even if the inside of the toilet cannot be normally photographed, it is preferable that notification information indicating this is sent to the terminal device 50. On the other hand, if the image can be normally identified (YES in step S4), the process proceeds to a detailed analysis, and first pre-processing of the photographed image is performed (step S6).

[0093] After the captured image is pre-processed in step S6, the detected object is classified as a foreign object, excrement, or bidet (step S7). If a foreign object is detected, a foreign object detection notification is sent to the caregiver's terminal device 50 (step S8). If excrement is detected, an excretion notification (notification information indicating that excretion has occurred) is sent to the caregiver's terminal device 50 (step S9), and an excrement analysis is performed (step S10). This excrement analysis classifies the excrement as stool, stool + urine, urine, or urine drips. After the process of step S10, the process returns to step S4.

[0094] If the object detected in step S7 is a posterior washer, it is determined that excretion has been completed, an excretion completion notification (notification information indicating that excretion has been completed) is sent to the caregiver's terminal device 50 (step S11), and real-time analysis ends (step S12). Alternatively, the excretion completion notification may be sent only when there is no reaction from the seating sensor. This is because the posterior washer may be used more than once. Note that the real-time analysis also ends after steps S5 and S8.

[0095] An example of the procedure of non-real-time analysis processing will be described with reference to Figs. 9 to 12. Fig. 9 is a flow diagram for explaining an example of processing in the excrement analyzer 10, and is a flow diagram showing an example of the operation content of non-real-time analysis. The operation content described here can be performed mainly by the CPU 11a controlling each part. Figs. 10, 11, and 12 are diagrams showing an example of stool nature analysis, an example of stool color analysis, and an example of urine volume analysis, respectively, included in the non-real-time analysis in the processing example of Fig. 9.

[0096] The real-time analysis shown in Figure 8 is performed using a space-saving, power-saving CPU, while performing the minimum analysis necessary to provide immediate notification to caregivers. In contrast, non-real-time analysis performs a more detailed analysis of excrement.

[0097] First, it is determined whether the real-time analysis is completed (step S21), and if it is completed (if the result is YES), non-real-time analysis is started (step S22). Alternatively, if a user identification function is provided, it may be determined whether a predetermined number of excretion times has been exceeded (or a predetermined period of time has elapsed) for each user, and if so, non-real-time analysis may be started.

[0098] The inputs for the non-real-time analysis and the respective analysis methods can be as described with reference to FIG. 7, but first, the real-time analysis results are determined (step S23), and different analyses are performed depending on the results.

[0099] If the real-time analysis result in step S23 is stool, stool nature analysis (step S24), stool color analysis (step S25), and stool volume analysis (step S26) are performed. Of course, these orders do not matter. If the real-time analysis result in step S23 is urine or urine dripping, urine color analysis (step S27) and urine volume analysis (step S28) are performed. Of course, these orders do not matter. If the real-time analysis result in step S23 is stool + urine, stool nature analysis (step S24), stool color analysis (step S25), stool volume analysis (step S26), urine color analysis (step S27), and urine volume analysis (step S28) are performed. Of course, these orders do not matter. In addition, each analysis in steps S24 to S28 can be performed using, for example, an individual learning model, but multiple analyses or all analyses can be performed using one learning model.

[0100] Here, in the fecal analysis in step S24, the most reliable image is used to perform an analysis by comparing it with the image already learned by DL. The most reliable image can be the image itself indicated by the imaging data, or an image obtained by preprocessing the imaging data using a preprocessing method suitable for fecal analysis. In addition, in this fecal analysis, the analysis can be performed in a form conforming to the Bristol scale shown in FIG. 10, for example. As a result of the analysis, the fecal matter can be classified into any one of types 1 to 7 as shown in FIG. 10.

[0101] In addition, in the stool color analysis in step S25, for example, pre-processing can be performed as shown in the processing procedure of transitioning between images 61, 62, and 63 in FIG. 11. In the pre-processing exemplified here, a light-colored portion occupying a wide area is removed from the original image 61 to obtain image 62, and then a narrow area of ​​the same color is removed to obtain image 63. In the stool color analysis in step S25, an image such as image 63 from which necessary information has been extracted (and / or added) by pre-processing is used, and a distance calculation is performed between the extracted stool color and the stool reference color, and the color occupying the largest area in the extracted stool image can be determined as the stool color. For example, in image 63, there is a stool form consisting of two colors, and the color of the larger area of ​​the two colors can be determined as the stool color. The information added here can be, for example, information indicating the area.

[0102] In the stool volume analysis in step S26, the stool volume can be calculated (estimated) as an area ratio within a certain size using a stool image (e.g., image 63, or real-time analysis results) extracted in preprocessing for the image at the time of completion of excretion. However, since the stool volume differs depending on the stool type even for the same area, it is advisable to calculate it using the area ratio corresponding to the stool type and a standard value for the stool volume.

[0103] The urine color analysis in step S27 is performed in the same manner as the stool color analysis in step S25, but the target image is a urine image instead of a stool image, and the distance from the reference color is calculated, and the color that occupies the largest area is determined to be the urine color.

[0104] In the urine volume analysis in step S28, the urine volume can be calculated using information such as the duration of urine dripping (urine dripping image information) and coefficients for all urine dripping images classified as "urine dripping" as a real-time analysis result. Here, the coefficients can be, for example, a general or average urination volume of the user. If all the urine dripping images are images acquired at a constant interval, the urination volume can be estimated from the images and the average urination volume, and the urine volume can be classified based on the estimated result. Note that values ​​related to the urination volume, such as the average urination volume, can be obtained as a result of conducting surveys at any time, and in this case, they become variable parameters.

[0105] Moreover, the results of the urination volume can be classified into classes corresponding to the urination volume as shown in Fig. 12. In the example shown in Fig. 12, the class names are very small, small, medium, large, and very large, and are classified as below threshold a, at least threshold a and below threshold b, at least threshold b and below threshold c, at least threshold c and below threshold d, and at least threshold d.

[0106] When each analysis is completed, the analysis results are transmitted to server 40 such as a cloud server (step S29). At this time, the analysis results to be transmitted can be both real-time analysis results and non-real-time analysis results. Also, image data captured by first camera 16b is not transmitted to server 40. When the transmission of the analysis results to server 40 is completed in step S29, the non-real-time analysis is also completed (step S30).

[0107] However, the procedure of classification, etc. is not limited to the example shown in FIG. 8 to FIG. 12. The real-time analysis can be a comparison process with the image learned by DL as described above, but it can be configured to first determine whether it is excrement or a foreign object. This determination is performed at regular intervals, and if it is determined to be a foreign object, a foreign object notification is sent to the caregiver, and the excrement analysis is performed to classify the excrement into five types: "feces," "feces + urine," "urine," "urine drip," and "bottom washer." This excrement analysis is also performed at regular intervals, and excretion completion is determined by detecting "bottom washer." Upon completion of excretion, the excretion analysis device 10 sends an excretion completion notification together with the real-time analysis result to the terminal device 50 of the caregiver, and the process proceeds to non-real-time analysis using the image used in the real-time analysis and the real-time analysis result. All the processes from the detection of sitting to this point are performed by the excretion analysis device 10 installed on the toilet.

[0108] As described above, the excrement analyzer 10 can obtain the start of excretion, detection of foreign body, detection of excretion, and completion of excretion as real-time analysis results, and can obtain stool texture, stool color, urine volume, urine color, and urine volume as non-real-time analysis results. Any of the analysis results can be recorded in the server 40 on the cloud in a state that can be viewed from the terminal device 50, and can also be configured to transmit them to the terminal device 50. Also, the server 40 can be configured to accumulate the received analysis results, perform further analysis from the accumulated data, and notify the terminal device 50 of the analysis results or make them viewable from the terminal device 50.

[0109] In addition, the excrement analyzer 10 or the system including the same can be used in a private home on the assumption that there is only one user, but it is preferable to provide a function for identifying users on the assumption that there are multiple users. This function has been described using face image data acquired by the second camera 15b and identification data obtained by the Bluetooth module 14b. This makes it possible to notify the caregiver of entry notifications, exit notifications, sitting notifications, leaving notifications, excretion start notifications, excretion completion notifications, etc. along with the user name, record detailed information for each user, and create an excretion diary and a care record including the same.

[0110] Here, a supplementary explanation will be given regarding the excretion diary and the care record including the same. Information obtained by real-time analysis or non-real-time analysis can be used when a caregiver creates the user's excretion diary, etc. The program of the terminal device 50 can be executablely incorporated into the terminal device 50 as care software including a presentation function for presenting notification information received from the excretion analyzer 10. This care software can have a function for automatically inputting information transferred from the server 40 or information obtained when accessing the server 40 into the excretion diary or the care record including the excretion diary. Such care software may be provided on the server 40, and in that case, it is sufficient to receive notification information and detailed information from the excretion analyzer 10 and automatically input the information into the excretion diary or the care record.

[0111] It is desirable that the excretion diary is a record of future excretion predictions. For this purpose, the present system is equipped with a prediction function. Prediction can be performed from the results of non-real-time analysis (and real-time analysis), and can be realized, for example, by installing a trained model for making predictions in at least one of the server 40 and the terminal device 50. In the above-mentioned real-time analysis and non-real-time analysis, the excretion date and time, the excretion amount, etc. can be output for each user, so in the present system, the excretion diary can be finally recorded in the server 40 and / or the terminal device 50. The present system can be configured to use this excretion diary, input necessary information therein to the trained model, and output the date and time (excretion timing) and amount of urination or defecation from the next time onwards. This output may be the tendency of urination or defecation (average interval, etc.). Alternatively, the above-mentioned predictions can be included in the non-real-time analysis.

[0112] By incorporating such a prediction function, not only can the burden of daily excretion records and excretion diaries on the caregiver be reduced, but the trends of these data can also be analyzed. As a result, if there is no defecation record for a set number of days, the system can notify the user and the caregiver of constipation alerts and encourage them to take action. For example, the system checks the date and time of excretion and calculates the average interval between excretion for each user, predicts urination time, and notifies the user and the caregiver that it is time to excrete when it is the scheduled time to excrete, thereby reducing the user's incontinence and supporting independence. Furthermore, by grasping the tendency of urinary disorders when the urination interval exceeds a certain threshold, and notifying the user and the caregiver of an alarm from the system, early hospital visits are possible. The system can also be configured to similarly notify an alarm for defecation intervals. In this way, the system can grasp the tendency of urinary disorders and constipation by checking the date and time of excretion and the information on the content of excretion, and judge whether it exceeds the set threshold, and notify the caregiver and user of a warning. These functions reduce the burden on the caregiver and enable thorough support for toilet users.

[0113] Furthermore, in this system, when the excrement analyzer 10 detects a foreign object other than excrement, it is preferable that the system not only notifies the caregiver with an alarm, but also has a function of stopping water purification of the toilet (flushing stop function). For this purpose, the excrement analyzer 10 can be provided with a flushing control unit (not shown) that controls the flushing function of the toilet. This flushing control unit is connected to or can be connected to a device that has a flushing function for the toilet (for example, a warm-water washing toilet seat such as Washlet (registered trademark) that has a function of flushing the toilet). The object to be washed by the warm-water washing toilet seat is the user's buttocks, etc. The system can also include such a device or a toilet with an integrated warm-water washing toilet seat.

[0114] Explaining the configuration example of FIG. 3, the CPU 11a and the interface (not shown) between the toilet seat 22 and the CPU 11a can be an example of this flushing control unit. The flushing function can be controlled by using existing technology to control the amount of water flowing into the toilet bowl 20 (in this example, the toilet seat 22 controls it). When the CPU 11a notifies information including a foreign object as notification information, it outputs a stop instruction to the toilet bowl side (in this example, the toilet seat 22) to stop the flushing function, thereby stopping the flushing function. For example, the excrement analyzer 10 notifies a remotely operable power tap connected to the power cord of the toilet seat 22 to turn off the power, thereby stopping the flushing function of the toilet bowl 20. More specifically, it is possible to supply power to the toilet seat 22 via an IoT (Internet of Things) tap, and output a stop instruction to this IoT tap to turn off the power. In this case, the stop instruction can be issued by the CPU 11a via the Bluetooth module 14b, for example.

[0115] By providing such a flush stop function, even if the user uses the flush function, the flush function is stopped, so the foreign object can be left in without being flushed, and the foreign object can be later tested as a specimen, etc. Also, since the foreign object is not flushed and warning information indicating the detection of the foreign object is output, the caregiver of the user can rush to the toilet, thereby preventing the confusion that the user may feel when the foreign object cannot be flushed.

[0116] As described above, the present system can achieve the effects described in embodiment 1. In particular or in addition to those effects, the present system achieves the following effects, for example.

[0117] The first effect is that the combination of the first camera and machine learning automatically records the contents of excrement identified, eliminating the need for manual tasks such as listening to the excrement, measuring urine volume, checking stool condition, and creating an excretion diary, which were previously required. This reduces the administrative work hours of caregivers.

[0118] The second benefit is that real-time analysis enables caregivers to be notified immediately of events occurring in the toilet (sitting, excretion, foreign object detection, etc.), freeing caregivers from having to constantly monitor the user's excretion.

[0119] The third benefit is that when a foreign object is detected through real-time analysis, a warning (alarm) is sent to the caregiver, preventing accidents related to toilet drainage and reducing the costs of responding to drainage problems.

[0120] The fourth effect is that when analyzing the image captured by the first camera 16a, all analysis processing is performed by the excrement analyzer 10, and only the analysis results can be transmitted to a server 40 such as a cloud server. This prevents third parties from seeing the image data of the excrement, reducing the mental burden on the user regarding privacy.

[0121] The fifth effect is that by dividing the analysis of excrement into real-time analysis and non-real-time analysis, it is possible to reduce the space and power consumption of the CPU 11a built into the excrement analyzer 10, thereby making the excrement analyzer 10 more inexpensive. The inexpensive excrement analyzer 10 reduces the introduction costs of the system, including the server, and the maintenance costs in the event of a breakdown.

[0122] The sixth effect is that by being able to grasp the possibility of constipation or urinary disorders from the excretion records in which the results of the analysis of excrement are recorded in a database format, it becomes unnecessary to administer laxatives even if they are not necessary, as was previously done to be on the safe side, due to the reliability issues of asking whether or not there is stool. This makes it possible to reduce the cost of medicine.

[0123] The seventh effect is that it becomes possible to grasp the urination interval of each individual user from the excretion record that records the analysis results of the excrement in a database format, etc. This allows users to avoid using diapers or urine pads on a regular basis, reducing expenses and allowing caregivers to grasp the condition of each user and easily support each user in becoming independent.

[0124] <Embodiment 3> The third embodiment will be described with reference to Fig. 13, focusing on the differences from the first and second embodiments, but the various examples described in the first and second embodiments can also be applied. Fig. 13 is a block diagram showing an example of the configuration of a server device according to the third embodiment.

[0125] 13, the server device 70 according to this embodiment includes a receiving unit 70a that receives detailed information from the excrement analyzer 1 or the excrement analyzer 10, a storage unit 70b that stores the detailed information received by the receiving unit 70a, and an information processing unit 70c. The server device 70 can be configured as a computer, and the information processing unit 70c can be said to be its control unit.

[0126] In this embodiment, the detailed information includes at least information indicating the date and time of excretion (date and time of occurrence), the type of excrement, and the shape of the defecation. The information processing unit 70c then tally up the detailed information for each shape of defecation. As a simple example, the tallying up can be a process such as counting the number of times for each shape, or calculating the average number of times for a certain period of time.

[0127] Furthermore, the information processing unit 70c can extract information including the excretion date and time, the type of excrement, and the shape of the defecation (information to be tallied) from the detailed information, and can tally the extracted information for each shape of the defecation under various conditions.

[0128] In this way, the server device 70 can tally up accurate detailed information (which can be referred to as excretion information) collected by the excreta analyzer 1 or the excreta analyzer 10. In addition, during the tallying process, it is also possible to extract necessary information from the detailed information and perform the tallying process only on the extracted information.

[0129] The collected results can be stored in a storage device such as the storage unit 70b. The collected results are preferably stored in a state in which they can be provided to an external device such as the terminal device 50 used by the caregiver C or the terminal device used by the toilet user P in response to a request from the external device. In this case, the server device 70 includes a providing unit (not shown) that provides the processing results of the information processing unit 70c to the external device via a network or the like. The collected results are preferably stored in a database format, and are preferably stored in a server device (e.g., a cloud server device) that can be accessed from the external device. The collected results can be provided for various purposes, and the method of use thereof will be described later in the fourth and fifth embodiments.

[0130] The receiving unit 70a has been described on the assumption that it receives detailed information from the excrement analysis device 1 or the excrement analysis device 10. However, the detailed information may be information analyzed by a device other than the excrement analysis device 1 or the excrement analysis device 10, or may be information received from a device other than the excrement analysis device 1 or the excrement analysis device 10. The detailed information is detailed information indicating the contents of the excrement, which is a result of analyzing image data of excrement in a toilet bowl captured at the toilet bowl, and may include at least information indicating the date and time of excrement, the type of excrement, and the shape of the excrement.

[0131] <Embodiment 4> The fourth embodiment will be described with a focus on the differences from the third embodiment with reference to Figs. 14 to 20, but the various examples described in the first to third embodiments can be applied. Fig. 14 is a diagram showing a configuration example of an analysis system according to the fourth embodiment, and Fig. 15 is a diagram showing an example of transmission information transmitted from the excrement analyzer 10 in the analysis system of Fig. 14. Fig. 16 is a diagram showing an example of an aggregated information table included in the excretion information database stored in the server device in the analysis system of Fig. 14, and Figs. 17 to 19 are diagrams showing examples of aggregated information tables included in the excretion information database.

[0132] 14, the analysis system according to this embodiment can be configured by connecting multiple excrement analyzers 10 and terminal devices 80 used by toilet users or managers such as their caregivers to a cloud network N including an excretion information database (DB) 71. The excretion information DB 71 can be stored in the memory unit 70b of the server device 70 in FIG.

[0133] That is, in this analysis system, the information contained in the excretion information DB 71 can be provided to the terminal device 80 on the cloud network N. The terminal device 80 can obtain desired information from the excretion information DB 71 (however, information tailored to the user of the terminal device 80, with consideration given to privacy). In this analysis system, a service that provides such information can be provided to the user of the terminal device 80. Note that constructing a DB on the cloud network N is advantageous in that the DB capacity, processing performance, and number of devices can be flexibly changed depending on the number of excrement analyzers 10, the number of toilet users, and actual usage conditions.

[0134] A specific example of the excretion information DB 71 will be described with reference to FIGS. The excretion information DB 71 can include information (for example, the aggregated information table 71a in FIG. 16) obtained by aggregating transmission information (for example, the transmission information in FIG. 15) transmitted from a plurality of excrement analyzers 10 by the information processing unit 70c, and can also include information obtained by extracting information to be aggregated from the information. The excretion information DB 71 can also include aggregated information (for example, the aggregated information tables 71b, 71c, and 71d in FIGS. 17 to 19) as information to be provided on the cloud network N.

[0135] The excretion analyzer 10 collects excretion information (detailed information described above) and transmits the information (transmission information) to the server device 70 together with user information and installation location information. The collected excretion information can include the following information, as exemplified in FIG. 15. That is, the excretion information can include the excretion date and time (date and time of occurrence), the type of excretion (information indicating either urination, defecation, or foreign body), the amount of urine (information indicating, for example, either a lot, normal, or small amount), and the shape of the defecation (information indicating, for example, either hard, normal, or diarrhea). In addition, the excretion information can include the color of the defecation, and further the number of times (number of urinations and excretions per day).

[0136] As illustrated in FIG. 15, the transmission information can include such excretion information, user information (user information) including the age and sex of the toilet user, and address information (installation location information) indicating the installation location of the toilet or the address of the toilet user. The user information and address information are associated with the excretion information. It is preferable that the address information is information that takes privacy into consideration, such as a postal code only. The installation location of the toilet can indicate the installation location of the excreta analysis device 10. In addition, in an example in which it is necessary to contact the user, which will be described later, the user information can include information such as the user's contact information. The transmission information can be received by the receiving unit 70a of the server device 70 in FIG. 13 and stored in the memory unit 70b as a target for extraction and aggregation by the information processing unit 70c.

[0137] The server device 70 receives such transmission information and registers it in the excretion information DB 71. When this registration is performed, an aggregated information table 71a (in a state where no information is stored) in Fig. 16 is generated for registering the transmission information in the excretion information DB 71 on the cloud network N. The excretion analysis device 10 collects the excretion information, and transmits the excretion information, together with user information and installation location information as shown in Fig. 15, as transmission information to the server device 70 equipped with the excretion information DB 71 on the cloud network N. When the excretion information DB 71 receives the transmission information transmitted from the excretion analysis device 10, it updates the information stored in the aggregated information table 71a with the transmission information.

[0138] Next, data aggregation in the excretion information DB 71 will be described. As described in the third embodiment, the information processing unit 70c can extract information including the excretion date and time, the type of excretion, and the shape of the stool (information to be aggregated) from the transmitted information, and aggregate the extracted information for each shape of the stool under various conditions. Data aggregation can be performed from the aggregated information table 71a on the excretion information DB 71, but is performed in order to generate information to be provided. Examples of recipients of the information include caregivers and toilet users. It is preferable that the information to be provided is information that is easy to view for the recipients of the information to view the contents and changes of the excretion.

[0139] For example, the tally information tables 71b to 71d shown in Fig. 17 to Fig. 19 can be generated in the excretion information DB 71. In order to generate these tables, it is preferable to first generate a view that can obtain such tally results in advance and register information.

[0140] The aggregated information table 71b is a table showing the results of tallying the defecation shapes, and can be generated using information on the occurrence date and time, the type of excrement, and the shape of the defecation from the aggregated information table 71a. For example, information on the type of excrement corresponding to defecation can be extracted from the aggregated information table 71a, the extracted information can be classified by the occurrence date and time (in this example, the month of occurrence) and the information on the shape of the defecation, and the classified information can be aggregated in the aggregated information table 71b. From the aggregated information table 71b, the tendency of the defecation shape by month can be seen, and a person looking at this information can recognize that, for example, in months with a lot of diarrhea, the person is more likely to become sick.

[0141] The aggregated information table 71c is a table showing the aggregated results of defecation shapes by age group, and can be generated using information on the occurrence date and time, type of excrement, defecation shape, and age from the aggregated information table 71a. For example, information on the type of excrement corresponding to defecation can be extracted from the aggregated information table 71a, and the extracted information can be classified by the occurrence date and time (month of occurrence in this example), defecation shape, and age information, and the classified information can be aggregated in the aggregated information table 71c. From the aggregated information table 71c, it is possible to see the tendency of defecation shapes classified by age group for each month.

[0142] The aggregated information table 71d is a table showing the aggregated results of defecation shapes by region, and can be generated by using information on the occurrence date and time, type of excrement, defecation shape, and address (zip code) from the aggregated information table 71a. For example, information on the type of excrement corresponding to defecation can be extracted from the aggregated information table 71a, and the extracted information can be classified by information on the occurrence date and time (month of occurrence in this example), defecation shape, and address (zip code), and the classified information can be aggregated in the aggregated information table 71d. From the aggregated information table 71d, the tendency of defecation shapes classified by region for each month can be seen.

[0143] As shown in the examples where trends can be understood from the aggregate information tables 71b to 71d, it is preferable that the information processing unit 70c analyzes the trend of the change in the shape of stool over time. Any method for analyzing the trend is acceptable. The analysis result may be provided as a sentence such as "Month with the most diarrhea is XX month" for the aggregate information table 71c.

[0144] As illustrated in FIG. 15, the detailed information in the transmission information preferably includes information indicating the color of the stool. In this case, the information processing unit 70c preferably analyzes the trends in the changes in the shape and color of the stool over time. The results of analyzing the trends in the changes in the shape and color of the stool can be used for predicting infectious diseases, which will be described later. For example, in infectious gastroenteritis, the shape and color of the stool change due to infection, so the results of analyzing the trends in the changes in the stool can be used for predicting such infectious diseases. Similarly, the detailed information in the transmission information can also include information indicating the amount of stool.

[0145] In addition, when predicting an infectious disease, it is necessary to take into consideration the region because the outbreak situation of the infectious disease differs from region to region. When taking the region into consideration, as described above, the receiving unit 70a needs to receive address information associated with the detailed information, and receives caution information (including warnings) that calls attention to the epidemic of the infectious disease in order to predict the infectious disease.

[0146] The address information can be received together with the detailed information. The warning information can be received via a route separate from the detailed information. For example, the warning information can be received as input data from an operation unit provided in the server device 70 or by reading it from an external recording medium. Alternatively, the warning information can be received by periodically acquiring the information from a server device for providing warning information connected to the server device 70 (for example, a server device used by a public health center to provide information).

[0147] The information processing unit 70c then analyzes the tendency of time-dependent changes in defecation (shape or shape and color, etc.) for each region indicated by the address information from the address information and detailed information, and predicts the epidemic of the infectious disease for each region based on the analysis results and the warning information (combining the analysis results and the warning information). The address information and detailed information used for the analysis can be information obtained by aggregating transmitted information as exemplified in the aggregated information table 71a, but it is preferable to use aggregated results such as those in the aggregated information table 71d. Furthermore, the region can refer to a city, ward, town, or village area, but can also be a district under the jurisdiction of a health center or a school district, and it is sufficient to receive address information that distinguishes the region to be predicted.

[0148] The prediction method is not limited, but can be performed based on whether the warning information and the stool shape and color that can be caused by the infectious disease are increasing. The receiving unit 70a may receive environmental information including warning information and climate information (weather forecast information), and predict the epidemic of the infectious disease for each region based on the analysis results and the environmental information. Prediction can be performed for multiple infectious diseases, one for each infectious disease.

[0149] The server device 70 preferably includes a provider (not shown) that provides the results predicted for each region by the information processor 70c to a provider associated with each region. This predicted result is based on the results of defecation by toilet users, including infected individuals who have not been diagnosed as infected, and therefore can be said to reflect the actual infection situation better than the warning information. In addition, this predicted result (infectious disease epidemic warning information) can be provided by sending a notification from the server device 70 to a terminal device 80, such as a smartphone, for each region, such as a town area of ​​a city, ward, town, or village or a school district.

[0150] In this way, the analysis system according to this embodiment can be constructed as an infectious disease prediction system that predicts the spread of infectious diseases and provides the prediction results as information for maintaining health.

[0151] In addition, although the stool shape aggregation period is shown as being in months, it may be in days, years, a predetermined number of months, a predetermined number of days, or a predetermined number of years. This allows the tendency of stool shape, such as daily or yearly, to be understood. Furthermore, the results of yearly aggregation can be further aggregated by day or month.

[0152] Next, a process flow of the server device 70 in the infectious disease prediction system according to this embodiment will be described briefly with reference to Fig. 20. Fig. 20 is a flow diagram for explaining a process example of the server device 70.

[0153] First, the receiving unit 70a of the server device 70 receives the transmission information (step S41) and stores it in the memory unit 70b (step S42). The information processing unit 70c counts the transmission information for each defecation shape and stores the counting results in the memory unit 70b (step S43). In an example in which prediction of an infectious disease is also performed, the information processing unit 70c further analyzes the temporal change in defecation shape for each region (step S44). Next, the information processing unit 70c predicts the epidemic of the infectious disease for each region based on the analysis result and the warning information about the infectious disease, and stores the prediction result in the memory unit 70b (step S45).

[0154] Next, the effects on predicting the spread of infectious diseases will be described in particular. First, we will explain the current methods for providing information on infectious diseases and the challenges involved. Currently, when an infectious disease such as infectious gastroenteritis occurs, medical institutions report the number of patients who have visited the institution to the public health center, etc., and if the number of reports exceeds a certain threshold, the public health center issues information about the epidemic (advisory or warning). Therefore, the public health center knows that the infectious disease is epidemic within its jurisdiction, but cannot identify the locations of the towns and schools within the municipalities where the disease is epidemic because it does not know the address information of the infectious disease patients. This creates a contradiction in that the infectious disease is epidemic in the jurisdiction of the public health center, but is not epidemic in the towns and schools within the municipalities or school districts within the jurisdiction. To resolve this contradiction, the public health center needs to issue advisories and warnings to the towns and schools within the municipalities or school districts, but this is not currently possible because it does not know the address information of each infectious disease patient and cannot identify the detailed range of the epidemic.

[0155] Additionally, currently, medical institutions report the number of infectious disease patients for the week to the public health center on the following Monday. The public health center compiles reports from medical institutions within its jurisdiction and issues warnings and alerts when the number of infectious disease patients exceeds a certain number, so there is a time lag between an increase in the number of infectious disease patients and the issuance of warnings and alerts. As such, because medical institutions report the results of their reporting to the public health center on a weekly basis, there is a time lag between an increase in the number of infectious disease patients and the issuance of warnings and alerts.

[0156] In contrast, in this embodiment, the excretion information collected by the excreta analyzer 10 can be tallied, for example, on a daily basis. Therefore, in this embodiment, it is possible to know from the daily tally that the number of people with diarrhea is increasing, and the location of the relevant city, ward, town, village, or school district can be identified from the address information. Then, in this embodiment, by combining this information with infectious disease outbreak information issued by the health center, it is possible to predict the epidemic of infectious diseases in the relevant city, ward, town, village, or school district, and to provide warning information for each area showing the prediction results.

[0157] In this way, the infectious disease prediction system according to the present embodiment collects information such as the shape and color of excrement, analyzes it for each region, and predicts the spread of the infectious disease using warning information about the infectious disease. Therefore, according to this infectious disease prediction system, even if infectious disease spread warning information is issued for the jurisdiction of a public health center, it is possible to provide the warning information for each city, ward, town, village, or school district, etc., taking into account the actual infection situation. In addition, since the infectious disease prediction system can provide warning information taking into account the actual infection situation, it is possible to solve the problem of delays in warning information making it difficult to prevent infectious diseases quickly, and it is expected to be effective in preventing the spread of infectious diseases.

[0158] <Embodiment 5> The fifth embodiment will be described with reference to Figures 21 to 24, focusing on the differences from the fourth embodiment, but the various examples described in the first to fourth embodiments can also be applied. Figure 21 is a diagram showing a configuration example of an analysis system according to the fifth embodiment, and Figures 22 and 23 are diagrams showing an example of an aggregated information table and an example of a tabulated information table, respectively, included in the excretion information database stored in the server device in the analysis system of Figure 21.

[0159] As explained in the fourth embodiment, the detailed information (excretion information) collected by the excreta analyzer 10 can be used to prevent the spread of infectious diseases, but it is desirable to increase the benefits that toilet users themselves and installers of the excreta analyzer 10 can gain from installing it. In doing so, it is also necessary to take into consideration that excretion information is sensitive information and that people are reluctant to provide it.

[0160] Therefore, in this embodiment, the installer of the excrement analyzer 10 provides a service to toilet users who provide defecation and urination information through excretion, such as predicting their health condition from that information and providing health advice appropriate to their health condition. This creates benefits for the installation of the excrement analyzer 10 and the provision of information, and ultimately makes it possible to promote the installation of the excrement analyzer 10.

[0161] Such an embodiment will now be described in detail. In the analysis system according to this embodiment, the server device 70 in Fig. 13 is configured to perform the following process. First, the receiving unit 70a receives user information and address information associated with the detailed information, and also receives environmental information including weather information and infectious disease epidemic information showing the results of an infectious disease epidemic. The storage unit 70b stores the received information.

[0162] 21, the analysis system according to this embodiment can be configured by connecting multiple excrement analyzers 10, a terminal device 80 used by a caregiver or other manager, and a terminal device 90 used by a toilet user to a cloud network N including an excretion information DB 71. Here, as shown in the figure, the terminal device 90 can also be connected to the terminal device 80 via a network N1 different from the cloud network N.

[0163] The information processing unit 70c analyzes the tendency of temporal changes in bowel movements according to the environmental information for each user indicated by the user information from the user information, address information, environmental information, and detailed information. Then, the information processing unit 70c predicts the health condition, including the infection status, for each user indicated by the user information from the analysis result.

[0164] Although the method of analysis and prediction does not matter, information may be first aggregated for each user so that it can be easily used for health prediction for each user. More specifically, information for each user is extracted from the aggregated information table 71a of FIG. 16 stored in the excretion information DB 71, and an individual aggregated information table 71e shown in FIG. 22 is generated. Analysis is performed using information on the occurrence date and time, the type of excrement, the shape of the defecation, and the color of the defecation from this individual aggregated information table 71e. For example, first, information corresponding to the type of excrement corresponding to defecation is extracted from the individual aggregated information table 71e, and the extracted information is classified by the occurrence date and time, the shape of the defecation, and the color of the defecation, and the classified information is aggregated in the aggregated information table 71f of FIG. 23. From the aggregated information table 71f, the tendency of change in the shape and color of the defecation for each month for the user can be seen. Note that, although an example in which the defecation aggregation period is set to a monthly unit has been given, this is not limited thereto.

[0165] As an example in which a trend can be grasped from the aggregate information table 71f has been given, the information processing unit 70c performs an analysis of such a trend. As described above, the analysis method is not limited.

[0166] The information processing unit 70c then predicts the health condition, including the infection state, for each user from the analysis result of the defecation tendency. The prediction can be performed for each of a plurality of infections. As described above, the prediction method is not limited, but it is possible to analyze detailed information for each user that has been accumulated so far, and predict the time when each user is likely to become sick from the detailed information and environmental information, or predict infection with an infection for each user from the outbreak of an infection in a nearby area. The information processing unit 70c can also generate health advice information for each user, such as information on how to avoid becoming sick from such prediction results, or a method of preventing infection with an infection, as health advice information. The health advice information can be provided in a format prepared in advance according to the prediction results.

[0167] The server device 70 may also include a providing unit (not shown) that provides the results predicted for each piece of user information by the information processing unit 70c to a contact point indicated by contact information for the user indicated by each piece of user information. Therefore, the user information may include contact information indicating the contact information of the toilet user.

[0168] For example, the prediction results and health advice information may be configured to be viewable by accessing a web page from terminal device 90 such as a smartphone and specifying a user, or by logging in to an application program installed in terminal device 90. The prediction results and health advice information may be stored in storage unit 70b. It is also desirable to configure the health predictions and health advice information so that similar information can be viewed not only by the toilet user, but also by terminal devices used by family members living with the toilet user or family members living apart from the toilet user.

[0169] Furthermore, this embodiment is not limited to the configuration in which detailed information and the like is acquired by the excrement analyzers 1 and 10 described in the first and second embodiments, but may also employ a configuration in which similar information is acquired by other devices. The above-mentioned similar information refers to detailed information indicating the contents of excrement, which is the result of analyzing image data of excrement in a toilet bowl captured at the toilet bowl, user information and address information associated with the detailed information, and environmental information. The environmental information may include weather information and infectious disease epidemic information indicating the results of an infectious disease epidemic.

[0170] In this way, the analysis system according to this embodiment can be constructed as a health information providing system that uses excretion information to predict and provide an individual's health condition. Next, the flow of processing by the server device 70 in the health information providing system according to this embodiment will be described in outline with reference to Fig. 24. Fig. 24 is a flow diagram for explaining an example of processing by the server device 70.

[0171] First, the receiving unit 70a of the server device 70 receives the transmission information and the environmental information (step S51) and stores them in the storage unit 70b (step S52). The information processing unit 70c analyzes the tendency of temporal changes in bowel movements according to the environmental information for each user indicated by the user information from the user information, address information, environmental information, and detailed information, and stores the analysis result in the storage unit 70b (step S53). Note that prior to step S53, aggregation for each user may be performed as described above. Furthermore, the information processing unit 70c predicts the health condition, including the infection state, for each user indicated by the user information from the analysis result, and stores the prediction result in the storage unit 70b (step S54).

[0172] According to this embodiment, the user's health condition can be predicted from excretion information, and it is possible to provide users of the excreta analyzer with health information that is effective in improving their health, thereby creating benefits to installing an excreta analyzer and can be expected to have the effect of encouraging the installation of excreta analyzers.

[0173] <Other embodiments> [a] In each embodiment, the analysis system and the functions of each device included in the system have been described, but the devices are not limited to the configuration examples shown in the figures, and it is sufficient if each device can realize these functions. For example, the above-mentioned server devices such as the server 40 and the server device 70 can be constructed as a distributed system consisting of multiple server devices with distributed functions.

[0174] [b] Each of the devices according to the first to fifth embodiments may have the following hardware configuration. Fig. 25 is a diagram showing an example of the hardware configuration of the device. The same applies to the other embodiment [a] described above.

[0175] The device 100 shown in FIG. 25 may have a processor 101, a memory 102, and a communication interface (I / F) 103. The processor 101 may be, for example, a microprocessor, a MPU (Micro Processor Unit), or a CPU. The processor 101 may include a plurality of processors. The memory 102 is, for example, configured by a combination of a volatile memory and a non-volatile memory. The functions of each device described in the first to fifth embodiments are realized by the processor 101 reading and executing a program stored in the memory 102. At this time, information can be exchanged with other devices via the communication interface 103 or an input / output interface (not shown). In particular, when the device 100 is an excrement analyzer, information (including image data) of an imaging device built into or externally attached to the device 100 can also be exchanged via the communication interface 103 or an input / output interface (not shown).

[0176] In the above example, the program can be stored and provided to the computer using various types of non-transitory computer readable media. The non-transitory computer readable media includes various types of tangible storage media. Examples of the non-transitory computer readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives) and magneto-optical recording media (e.g., magneto-optical disks). Further, this example includes CD-ROM (Read Only Memory), CD-R, and CD-R / W. Further, this example includes semiconductor memory (e.g., mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (Random Access Memory)). The program may also be provided to the computer by various types of transitory computer readable media. Examples of the transitory computer readable media include electric signals, optical signals, and electromagnetic waves. The transitory computer readable media can provide the program to the computer via a wired communication path such as an electric wire and an optical fiber, or a wireless communication path.

[0177] [c] Furthermore, as the procedure of the excrement analysis method in the excrement analysis system is exemplified in the above-mentioned first and second embodiments, the present disclosure may also take the form of an excrement analysis method (analysis method). This excrement analysis method may include the following input step, holding step, first analysis step, and second analysis step. In the input step, the excrement analysis device inputs imaging data captured by an imaging device installed so as to include the excrement excretion range in the toilet bowl in its imaging range. In the holding step, the excrement analysis device temporarily holds the imaging data input in the input step. In the first analysis step, the excrement analysis device analyzes the first analysis target data, which is the imaging data input in the input step, and outputs notification information to a supervisor monitoring the toilet user. In the second analysis step, the excrement analysis device analyzes the second analysis target data, which is the imaging data input in the input step and temporarily held in the holding step, and outputs detailed information indicating the content of the excretion. Note that other examples are as described in the first and second embodiments. Moreover, the above program can be said to be a program for causing an excrement analyzer (a control computer provided in the excrement analyzer) to execute the above input step, the above retention step, the above first analysis step, and the above second analysis step.

[0178] Also, as the procedure of the analysis method in the analysis system is exemplified in the third and fourth embodiments, the present disclosure may also take the form of other analysis methods. The analysis method here includes the following receiving step, storage step, and information processing step, and preferably includes the following providing step. In the receiving step, the server device receives detailed information (which may also be called excretion information) indicating the contents of excretion, which is a result of analyzing the excretion in the toilet bowl from the image data captured at the toilet bowl. In the storing step, the server device stores the detailed information received in the receiving step. Here, the detailed information includes at least information indicating the excretion date and time, the type of excretion, and the shape of the excretion. In the information processing step, the server device compiles the detailed information for each shape of the excretion. In the providing step, the server device provides the processing result in the information processing step to an external device. Note that other examples are as described in the third to fifth embodiments. In this case, the program can be said to be a program for causing the server device (computer) to execute the receiving step, the storage step, and the information processing step (preferably the providing step in addition to them).

[0179] Also, as the procedure of the analysis method in the analysis system is exemplified in the fifth embodiment, the present disclosure may also take the form of other analysis methods. The analysis method here includes the following receiving step, storing step, and information processing step, and preferably includes the following providing step. In the receiving step, the server device receives detailed information indicating the contents of the excretion, which is a result of analyzing the excretion in the toilet bowl from image data captured at the toilet bowl, and user information, address information, and environmental information associated with the detailed information. Here, the detailed information includes at least information indicating the date and time of excretion, the type of excretion, and the shape of the feces. Furthermore, the user information is information indicating the user of the toilet, and the address information is information indicating the address where the user resides or the address of the location where the toilet is installed. Furthermore, the environmental information is information including weather information and infectious disease epidemic information indicating the result of an infectious disease epidemic. In the storing step, the server device stores the detailed information, user information, address information, and environmental information received in the receiving step. In the information processing step, the server device analyzes the tendency of temporal changes in bowel movements according to the environmental information for each user indicated by the user information from the user information, based on the user information, address information, environmental information, and detailed information. In the information processing step, the server device further predicts the health condition, including the infectious disease status, for each user indicated by the user information from the analysis results. In the providing step, the server device provides the processing results of the information processing step to an external device (user's contact information). Other examples are as described in embodiment 5. In this case, the program can be said to be a program for causing the server device (computer) to execute the receiving step, the storing step, and the information processing step (preferably in addition to these, the providing step).

[0180] The present disclosure is not limited to the above-described embodiment, and may be modified as appropriate without departing from the spirit and scope of the present disclosure. In addition, the present disclosure may be implemented by appropriately combining the respective embodiments.

[0181] A part or all of the above-described embodiments can be described as, but is not limited to, the following supplementary notes. <Additional Notes>

[0182] (Appendix 1) an input unit for inputting image data captured by an imaging device installed so as to include an imaging range of the excrement area in the toilet bowl; a storage unit that temporarily stores the imaging data inputted by the input unit; a first analysis unit that analyzes first analysis target data, which is the imaging data input by the input unit, and outputs notification information to a monitor who monitors users of the toilet; a second analysis unit that analyzes second analysis target data, which is the imaging data input by the input unit and temporarily stored in the storage unit, and outputs detailed information indicating the content of excretion; Equipped with Excrement analyzer.

[0183] (Appendix 2) the first analysis unit performs an analysis to determine whether or not a foreign object, which is an object other than feces and urine, is included in the subject other than the toilet bowl and the flushing liquid for the toilet bowl, and outputs foreign object information indicating whether or not a foreign object is included as at least a part of the notification information. 2. An excrement analysis device as described in appendix 1.

[0184] (Appendix 3) The first analysis unit outputs the notification information by transmitting it to a terminal device used by the monitor. 3. An excrement analyzer according to claim 1 or 2.

[0185] (Appendix 4) The second analysis unit outputs the detailed information by transmitting the detailed information to a server device connected to the excrement analysis device via a network. 4. An excrement analyzer according to any one of claims 1 to 3.

[0186] (Appendix 5) The first analysis unit outputs the notification information by transmitting it to the server device. 5. The excrement analyzer of claim 4.

[0187] (Appendix 6) The storage unit temporarily stores a result of the analysis by the first analysis unit as a part of the second analysis target data. 6. An excrement analyzer according to any one of claims 1 to 5.

[0188] (Appendix 7) The first analysis unit obtains the notification information from the first analysis target data using a trained model that inputs the first analysis target data and outputs the notification information. 7. An excrement analyzer according to any one of claims 1 to 6.

[0189] (Appendix 8) The second analysis unit obtains at least a part of the detailed information from the second analysis target data using a trained model that inputs the second analysis target data and outputs the detailed information. 8. An excrement analyzer according to any one of claims 1 to 7.

[0190] (Appendix 9) The second analysis unit performs image processing on the second analysis target data to obtain at least a part of the detailed information. An excrement analyzer according to any one of claims 1 to 8.

[0191] (Appendix 10) The second analysis unit outputs, as the detailed information, information on at least one of a urinary flow rate or a urination volume, a defecation frequency or a defecation volume per unit time period, and an excretion timing, which is a timing of an excretory act. 10. An excrement analyzer according to any one of claims 1 to 9.

[0192] (Appendix 11) The second analysis unit outputs, as the detailed information, information indicating at least one of a decrease in urinary flow rate or urination volume, a decrease in the number of defecations or the volume of defecation per unit time period, and a prolongation of excretion timing, which is the timing of the excretion act. 11. The excrement analysis device of claim 10.

[0193] (Appendix 12) the first analysis unit outputs at least one of information indicating a usage status of a rear cleansing device installed in the toilet and information indicating that a person has sat on the toilet as at least a part of the notification information; 12. An excrement analyzer according to any one of claims 1 to 11.

[0194] (Appendix 13) The imaging device is further provided. 13. An excrement analyzer according to any one of claims 1 to 12.

[0195] (Appendix 14) A system comprising: an excrement analyzer according to any one of claims 1 to 13; a terminal device used by the monitor and connected to the excrement analyzer; and a server device connected to the excrement analyzer and the terminal device, the excrement analyzer outputs the notification information by transmitting it to the terminal device, and outputs the detailed information by transmitting it to the server device; the server device stores the detailed information received from the excrement analyzer in a state that can be viewed from the terminal device; the terminal device includes a log generating unit that generates an excretion log based on the notification information received from the excretion analyzer and the detailed information stored in the server device; Analysis system.

[0196] (Appendix 15) A receiving unit that receives the detailed information from the excrement analyzer according to any one of claims 1 to 13; a storage unit that stores the detailed information received by the receiving unit; An information processing unit; Equipped with The detailed information includes at least information indicating the date and time of excretion, the type of excretion, and the shape of the excretion, The information processing unit collects the detailed information for each of the defecation shapes. Server device.

[0197] (Appendix 16) a receiving unit for receiving detailed information indicating the content of the excrement in the toilet bowl, the detailed information being a result of analyzing image data captured of the excrement in the toilet bowl; a storage unit that stores the detailed information received by the receiving unit; An information processing unit; Equipped with The detailed information includes at least information indicating the date and time of excretion, the type of excretion, and the shape of the excretion, The information processing unit collects the detailed information for each of the defecation shapes. Server device.

[0198] (Appendix 17) The information processing unit analyzes a trend of a change in the shape of the defecation over time. 17. The server device according to claim 15 or 16.

[0199] (Appendix 18) The detailed information includes information indicating a color of the feces, The information processing unit analyzes the tendency of the change over time in the shape and color of the stool. 17. The server device according to claim 15 or 16.

[0200] (Appendix 19) a providing unit for providing a processing result of the information processing unit to an external device; 19. The server device according to any one of appendixes 15 to 18.

[0201] (Appendix 20) The receiving unit receives address information indicating an address of the toilet user or an address of a location where the toilet is installed, which is associated with the detailed information, and receives warning information warning of an infectious disease outbreak; the information processing unit analyzes a trend of a temporal change in the defecation for each area indicated by the address information from the address information and the detailed information, and predicts an epidemic of the infectious disease for each area based on a result of the analysis and the warning information. 20. The server device according to any one of claims 17 to 19.

[0202] (Appendix 21) a providing unit that provides the results predicted for each region by the information processing unit to a destination associated with each region, 21. The server device according to claim 20.

[0203] (Appendix 22) the receiving unit receives user information indicating a user of the toilet and address information indicating an address where the toilet user resides or an address where the toilet is installed, which are associated with the detailed information, and receives environmental information including weather information and infectious disease epidemic information indicating the results of an infectious disease epidemic; the information processing unit analyzes a tendency of a temporal change in the defecation according to the environmental information for each user indicated by the user information from the user information, the address information, the environmental information, and the detailed information, and predicts a health condition including a state of infection with the infectious disease for each user indicated by the user information from a result of the analysis. 20. The server device according to any one of claims 17 to 19.

[0204] (Appendix 23) a receiving unit that receives detailed information indicating the content of the excrement, which is the result of analyzing image data of excrement in a toilet bowl taken at the toilet bowl, user information indicating a user of the toilet and address information indicating the address where the toilet user resides or the address of the location where the toilet is installed, which are associated with the detailed information, and environmental information including weather information and infectious disease epidemic information indicating the results of an infectious disease epidemic; a storage unit that stores the detailed information, the user information, the address information, and the environmental information received by the receiving unit; An information processing unit; Equipped with The detailed information includes at least information indicating the date and time of excretion, the type of excretion, and the shape of the excretion, the information processing unit analyzes a tendency of a temporal change in the defecation according to the environmental information for each user indicated by the user information from the user information, the address information, the environmental information, and the detailed information, and predicts a health condition including a state of infection with the infectious disease for each user indicated by the user information from a result of the analysis. Server device.

[0205] (Appendix 24) The user information includes contact information indicating contact information of a user of the toilet, A providing unit provides the result predicted for each of the user information by the information processing unit to a contact indicated by the contact information for the user indicated by each of the user information. 24. The server device according to claim 22 or 23.

[0206] (Appendix 25) an input step in which the excrement analysis device inputs imaging data captured by an imaging device installed so as to include an excrement excretion area in the toilet bowl as an imaging range; a storage step in which the excrement analysis device temporarily stores the imaging data input in the input step; a first analysis step in which the excrement analyzer analyzes first analysis target data, which is the imaging data input in the input step, and outputs notification information to a supervisor who monitors users of the toilet; a second analysis step in which the excrement analysis device analyzes second analysis target data, which is the imaging data input in the input step and temporarily stored in the storage step, and outputs detailed information indicating the content of the excrement; Equipped with Analysis method.

[0207] (Appendix 26) A receiving step in which a server device receives the detailed information; a storage step in which the server device stores the detailed information received in the receiving step; An information processing step; A providing step; Equipped with The detailed information includes at least information indicating the date and time of excretion, the type of excretion, and the shape of the excretion, In the information processing step, the server device collects the detailed information for each of the defecation shapes, The providing step includes the server device providing a processing result of the information processing step to an external device. Analytical method described in Appendix 25.

[0208] (Appendix 27) a receiving step in which the server device receives detailed information indicating the content of the excrement, the detailed information being a result of analyzing image data of the excrement in the toilet bowl of the toilet from the image data of the toilet bowl; a storage step in which the server device stores the detailed information received in the receiving step; An information processing step; A providing step; Equipped with The detailed information includes at least information indicating the date and time of excretion, the type of excretion, and the shape of the excretion, In the information processing step, the server device collects the detailed information for each of the defecation shapes, The providing step includes the server device providing a processing result of the information processing step to an external device. Analysis method.

[0209] (Appendix 28) The control computer of the excrement analyzer is An input step of inputting imaging data captured by an imaging device installed so as to include an imaging range of the excrement excretion range in the toilet bowl; a holding step of temporarily holding the imaging data inputted in the input step; a first analysis step of analyzing first analysis target data, which is the imaging data input in the input step, and outputting notification information to a monitor who monitors users of the toilet; a second analysis step of analyzing second analysis target data, which is the imaging data input in the input step and temporarily stored in the storage step, and outputting detailed information indicating the content of excretion; A program for executing.

[0210] (Appendix 29) The computer includes: A receiving step of receiving detailed information including at least information indicating an excretion date and time, a type of excretion, and a shape of the excretion as the detailed information; a storage step of storing the detailed information received in the receiving step; an information processing step of aggregating the detailed information for each of the defecation shapes; a providing step of providing a processing result in the information processing step to an external device; This is a program for executing 29. The program according to claim 28.

[0211] (Appendix 30) On the computer, receiving detailed information indicating the content of the excretion, the detailed information being a result of analyzing image data of the excretion in the toilet bowl of the toilet, the detailed information including at least information indicating the excretion date and time, the type of excretion, and the shape of the excretion; a storage step of storing the detailed information received in the receiving step; an information processing step of aggregating the detailed information for each of the defecation shapes; a providing step of providing a processing result in the information processing step to an external device; A program for executing. [Explanation of symbols]

[0212] 1, 10 Excrement analyzer 1a Input section 1b Holding part 1c 1st Analysis Department 1d 2nd Analysis Department 11 Second external box 11a CPU 11b Connector 11c,11d USB I / F 12 Box-to-box connections 13 First external box 14a WiFi module 14b Bluetooth module 15a Human Sensor 15b Second Camera 16a Distance sensor 16b First Camera 20 Toilet 21 Main unit 22 Toilet seat 23 Toilet seat cover 30 Toilet with excrement analyzer 40 Servers 41 Control section 42 Storage section 50, 80, 90 Terminal Equipment 70 Server equipment 70a Receiving section 70b Storage section 70c Information Processing Section 100 devices 101 Processor 102 Memory 103 Communication Interface

Claims

1. a receiving unit for receiving detailed information indicating the content of the excrement in the toilet bowl, the detailed information being a result of analyzing image data captured of the excrement in the toilet bowl; a storage unit that stores the detailed information received by the receiving unit; An information processing unit; Equipped with The detailed information includes at least information indicating the date and time of excretion, the type of excretion, the color of the excretion, and the shape of the excretion; the information processing unit collects the detailed information for each shape of the defecation and analyzes a trend of a change in the shape and color of the defecation over time. Server device.

2. A receiving unit for receiving detailed information indicating the content of excrement in a toilet bowl, the detailed information being the result of analyzing image data captured of the toilet bowl; a storage unit that stores the detailed information received by the receiving unit; An information processing unit; a providing unit that provides a processing result of the information processing unit to an external device; Equipped with The detailed information includes at least information indicating the date and time of excretion, the type of excretion, and the shape of the excretion, The information processing unit collects the detailed information for each of the defecation shapes. Server device.

3. The receiving unit receives address information indicating an address of the toilet user or an address of a location where the toilet is installed, which is associated with the detailed information, and receives warning information warning of an infectious disease outbreak; the information processing unit analyzes a trend of a temporal change in the defecation for each area indicated by the address information from the address information and the detailed information, and predicts an epidemic of the infectious disease for each area based on a result of the analysis and the warning information.

3. The server device according to claim 1 or 2.

4. a providing unit that provides the results predicted for each region by the information processing unit to a destination associated with each region, The server device according to claim 3.

5. the receiving unit receives user information indicating a user of the toilet and address information indicating an address where the toilet user resides or an address where the toilet is installed, which are associated with the detailed information, and receives environmental information including weather information and infectious disease epidemic information indicating the results of an infectious disease epidemic; the information processing unit analyzes a tendency of a temporal change in the defecation according to the environmental information for each user indicated by the user information from the user information, the address information, the environmental information, and the detailed information, and predicts a health condition including a state of infection with the infectious disease for each user indicated by the user information from a result of the analysis.

3. The server device according to claim 1 or 2.

6. a receiving unit that receives detailed information indicating the content of the excrement, which is the result of analyzing image data of excrement in a toilet bowl taken at the toilet bowl, user information indicating a user of the toilet and address information indicating the address where the toilet user resides or the address of the location where the toilet is installed, which are associated with the detailed information, and environmental information including weather information and infectious disease epidemic information indicating the results of an infectious disease epidemic; a storage unit that stores the detailed information, the user information, the address information, and the environmental information received by the receiving unit; An information processing unit; Equipped with The detailed information includes at least information indicating the date and time of excretion, the type of excretion, and the shape of the excretion, the information processing unit analyzes a tendency of a temporal change in the defecation according to the environmental information for each user indicated by the user information from the user information, the address information, the environmental information, and the detailed information, and predicts a health condition including a state of infection with the infectious disease for each user indicated by the user information from a result of the analysis. Server device.

7. The user information includes contact information indicating contact information of a user of the toilet, A providing unit provides the result predicted for each of the user information by the information processing unit to a contact indicated by the contact information for the user indicated by each of the user information.

7. The server device according to claim 5 or 6.

8. a receiving step in which the server device receives detailed information indicating the content of the excrement, the detailed information being a result of analyzing image data of the excrement in the toilet bowl of the toilet from the image data of the toilet bowl; a storage step in which the server device stores the detailed information received in the receiving step; An information processing step; A providing step; Equipped with The detailed information includes at least information indicating the date and time of excretion, the type of excretion, and the shape of the excretion, In the information processing step, the server device collects the detailed information for each of the defecation shapes, The providing step includes the server device providing a processing result of the information processing step to an external device. Analysis method.

9. On the computer, receiving detailed information indicating the content of the excretion, the detailed information being a result of analyzing image data of the excretion in the toilet bowl of the toilet, the detailed information including at least information indicating the excretion date and time, the type of excretion, and the shape of the excretion; a storage step of storing the detailed information received in the receiving step; an information processing step of aggregating the detailed information for each of the defecation shapes; a providing step of providing a processing result in the information processing step to an external device; A program for executing.

Images