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 analysis device, an analysis system, a server device, and a program.

Background Art

[0002] Caregivers who provide excretion assistance at care sites are required to maintain the dignity of care recipients, reduce the incontinence of care recipients, and promote self-care support. Since excretion assistance at care sites may sometimes hurt the dignity of care recipients, caregivers are burdened, and support for reducing the workload of their duties is required.

[0003] In addition, when a caregiver needs assistance when a care recipient gets up from the toilet seat or exits the toilet, or for the purpose of preventing an accident in the toilet, the caregiver may provide constant assistance before and after the excretion act. It can be said that the burden on the caregiver is also great in this regard.

[0004] The duties of caregivers also include creating an excretion log for care recipients during excretion assistance. Therefore, the caregiver obtains the information to be recorded in the excretion log by entering the toilet with the care recipient and observing the care recipient's excretion behavior, or by interviewing the care recipient.

[0005] In the former case, it is mainly performed for care recipients who cannot accurately hear information due to dementia or the like. And in the former case, since being observed during the excretion act is humiliating for the care recipient, it is easy to cause a situation that hurts the dignity of the care recipient, and observing in such a situation is also a burden on the caregiver.

[0006] On the other hand, in the latter case, inaccurate reports may occur due to the care recipient's sense of shame, meaning that excretion records are subjective, and as a result, even if the same excretion act is performed by the care recipient, there will be differences in the contents of the excretion diary. When such differences exist, it is difficult for caregivers to accurately grasp the health problems caused by constipation or urinary dysfunction, which can lead to delays in treatment. Furthermore, even if the care recipient is not suffering from any health problems, incorrect reporting can lead to an over-administration of unnecessary medications such as laxatives. Consequently, in order to compensate for these differences, the burden on caregivers regarding excretion management and record-keeping increases.

[0007] Furthermore, when a care recipient has dementia, they may mistake a urine pad for toilet paper during excretion, or they may intentionally try to conceal evidence of an accident (fecal or urinary incontinence) out of shame, resulting in them flushing the urine pad down the toilet. In such cases, or periodically, care facilities need to hire a contractor to clean the drainpipes and remove foreign objects to clear blockages, and this work will render the drainage-related facilities unusable. To resolve these problems, caregivers could check on the completion of the care recipient's excretion and any abnormalities related to excretion, but even if they conduct interviews later for the purpose of creating an excretion log, they will ultimately have to be constantly by the user's side.

[0008] To improve these situations, a system has been proposed that manages toilet users' excretions by installing sensors in toilets and analyzing the data acquired by the sensors. For example, Patent Document 1 describes a method used for human excrement placed in a toilet bowl. In this method, while the human excrement is 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 in the received light that indicate light absorption by components of red blood cells. In this method, it is determined that blood is present in the human excrement in response to this detection, and an output from an output device is generated in response to this determination, at least partially. Patent Document 1 also describes a method in which the human excrement of a subject is monitored over a long period of time, and the amount of blood detected in the human excrement is compared with a threshold amount over a certain period of time, and a warning is generated 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 pet, from the user terminal when use begins, and registers this individual identification information in association with the pet's identifier. After use begins, this excretion notification system acquires the pet's weight information from the pet toilet, stores this weight information in association with the pet's identifier, and calculates and registers a body weight threshold based on the average weight of the pet over a predetermined period. Furthermore, after use begins, this excretion notification system acquires the pet's urination information from the pet toilet, calculates the average number of urinations and the amount of urine over a predetermined period, and registers these as the urination frequency threshold and urine volume threshold, respectively. Then, if the weight information or urination information of the pet obtained from the pet toilet deviates from the respective threshold, this excretion notification system notifies an alert that there may be a sign of a predetermined pathology. This excretion notification system is also equipped with a camera to determine when a pet enters the pet toilet.

[0010] Furthermore, as a technique for understanding the daily trend of changes in the Na / K ratio in the urine of a subject, Patent Document 3 describes a urine component analyzer aimed at accurately determining the Na / K ratio in the urine excreted by a subject. This device stores data representing the correlation between the statistical concentration ratio obtained by statistically processing the Na / K ratio in multiple urine samples excreted by a person and the Na / K ratio in the total urine for one or more days when all the urine excreted by the person over one or more days is collected as a single sample. In addition, this device assumes that the Na / K ratio in a single urine sample excreted by the subject for all time periods of the day has been input, and then performs statistical processing on the input Na / K ratios in multiple urine samples of the subject to obtain a statistical concentration ratio. Based on this statistical concentration ratio, this device uses the stored correlation to convert and determine the Na / K ratio in the total urine of the subject over one or more days. Furthermore, this device sequentially stores the Na / K ratio, associating it with the date and time of urination, the date and time of measurement, and the time period during which urination occurred. By reading this stored information, the user can easily understand the daily trend of changes in the Na / K ratio in the subject's total urine over one or more days.

[0011] Furthermore, as a technology for estimating the health status of a living organism, Patent Document 4 describes a data detection device aimed at estimating the health status of a living organism by acquiring biological data non-contact and non-invasively. This device comprises an image acquisition unit that captures images of at least one of the following: the anus and its surroundings, the genitals and their surroundings, or the excrement of the living organism, and a data analysis unit. This data analysis unit acquires biological data regarding the characteristics of the anus, genitals, or excrement of a living organism by analyzing images captured by the image acquisition unit, and estimates the health status of the organism from this biological data. Here, the characteristics of excrement refer to at least one of the following: color, shape, temperature, light reflectance, or light transmittance.

[0012] Patent Document 5 describes a biometric information utilization system aimed at efficiently collecting sufficient information to create highly accurate value-added information. This system utilizes body temperature, urinary protein concentration, urinary glucose concentration, urinary amino acid concentration, and fecal viscosity as biometric information. Furthermore, this system creates value-added information that includes values ​​aggregated by residential district number corresponding to the subject identification number, based on measurements taken at predetermined time periods. Patent Document 5 also states that the values ​​aggregated by residential district number are the average body temperature values ​​for each residential district, and that value-added information containing the average value of fever values ​​of collected subjects aggregated by residential district number is effective for verification. 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] Japanese Patent Publication No. 2019-071896 [Patent Document 3] Japanese Patent Publication No. 2017-072410 [Patent Document 4] Japanese Patent Publication No. 2007-252805 [Patent Document 5] Japanese Patent Publication No. 2007-323528 [Overview of the Initiative] [Problems that the invention aims to solve]

[0014] The technology described in Patent Document 1 can only determine the presence of blood in excrement, and cannot monitor for foreign objects or understand the condition of excrement other than the presence of blood. Therefore, the applicant considered it desirable to create an excretion log based on imaging data obtained by photographing excrement with an imaging device. In addition, although the system described in Patent Document 2 has a camera, that camera is for monitoring pets and is not used to image excrement.

[0015] However, for toilet users, including those requiring care, the psychological burden of having their excretory acts and excrement photographed and managed by an imaging device is significant. This psychological burden stems from privacy concerns regarding the possibility of the acquired image data being viewed by third parties. Therefore, while toilet sensors acquire image data of excrement, it is desirable to devise ways to reduce the psychological burden on toilet users by ensuring that this data is not seen by third parties.

[0016] Furthermore, creating an excretion log requires accurately analyzing and recording imaging data of excrement. However, accurate analysis is time-consuming, and it is often impossible to assess the user's health based on a single excretion sample. Despite this, there are situations where immediate notification to caregivers is necessary.

[0017] For example, while it might be possible to obtain advanced analysis results by using cloud services to analyze imaging data, this would involve sending the imaging data to the server device providing the service and waiting for the analysis results, making it difficult to immediately notify caregivers or other monitors. Situations requiring immediate notification include, for example, notification of the presence of a foreign object for removal, notification of the start of excretion, notification of the end of excretion, and notification of other abnormalities. Furthermore, transmitting imaging data to a server device for analysis would increase the psychological burden on toilet users regarding their privacy, as mentioned above.

[0018] On the other hand, if one attempts to achieve analysis with the same speed and accuracy as cloud services using only a device installed in a toilet, without using cloud services, it would be necessary to install a computer with the required specifications for that analysis. Here, "computer" can refer to a CPU (Central Processing Unit), etc. However, installing such a computer is not practical due to issues such as space, heat dissipation, and cost. Furthermore, the technologies described in Patent Documents 3 to 5 do not solve the aforementioned problems.

[0019] The purpose of this disclosure is to provide an excrement analysis device, analysis system, server device, and program, etc., that solve the aforementioned problems. The aforementioned problems are to accurately collect information indicating the contents of excrement defecated in the toilet bowl without having to interview the toilet user, while respecting the privacy of the toilet user, and to enable immediate notification to the monitor in situations where such notification is necessary. [Means for solving the problem]

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

[0021] The analysis system according to the second aspect of the present disclosure includes the excrement analysis device, a terminal device used by the monitor connected to the excrement analysis device, and a server device connected to the excrement analysis device and the terminal device. The excrement analysis device outputs by transmitting the notification information to the terminal device and outputs by transmitting the detailed information 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. The terminal device includes a log generation unit that generates an excretion log based on the notification information received from the excrement analysis device and the detailed information stored in the server device.

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

[0023] The program according to the fourth aspect of the present disclosure causes a control computer provided in an excrement analysis device to execute an input step of inputting imaging data captured by an imaging device installed so as to include the excretion range of excrement in the toilet bowl of the toilet in the imaging range, a holding step of temporarily holding the imaging data input in the input step, a first analysis step of analyzing the first analysis target data which is the imaging data input in the input step and outputting notification information to the monitor who monitors the user of the toilet, and a second analysis step of analyzing the second analysis target data which is the imaging data input in the input step and temporarily held in the holding step and outputting detailed information indicating the content of excretion.

Advantages of the Invention

[0024] This disclosure provides an excrement analysis device, analysis system, server device, and program, etc., that solve the above-mentioned problems. Specifically, this disclosure makes it possible to accurately collect information indicating the contents of excrement defecated in the toilet bowl without having to interview the toilet user, while respecting the privacy of the toilet user, and also to respond to situations where immediate notification to a monitor is necessary. [Brief explanation of the drawing]

[0025] [Figure 1] This is a block diagram showing an example configuration of a waste analysis device according to Embodiment 1. [Figure 2] This figure shows an example configuration of the excrement analysis system according to Embodiment 2. [Figure 3] Figure 2 is a block diagram showing an example configuration of the excrement analyzer in the excrement analysis system. [Figure 4] Figure 2 is a conceptual diagram illustrating an example of processing in the excrement analysis system. [Figure 5] This figure illustrates an example of processing in the excrement analysis device of the excrement analysis system shown in Figure 2. [Figure 6] This figure illustrates an example of processing in the excrement analysis device of the excrement analysis system shown in Figure 2. [Figure 7] This figure illustrates an example of processing in the excrement analysis device of the excrement analysis system shown in Figure 2. [Figure 8] This is a flowchart illustrating an example of processing in the excrement analysis device in the excrement analysis system shown in Figure 2. [Figure 9] This is a flowchart illustrating an example of processing in the excrement analysis device in the excrement analysis system shown in Figure 2. [Figure 10] This figure shows an example of a convenience analysis included in the non-real-time analysis in the processing example shown in Figure 9. [Figure 11] This figure shows an example of stool color analysis included in the non-real-time analysis in the processing example shown in Figure 9. [Figure 12]This figure shows an example of urine volume analysis included in the non-real-time analysis in the processing example shown in Figure 9. [Figure 13] This is a block diagram showing an example configuration of a server device according to Embodiment 3. [Figure 14] This figure shows an example configuration of the analysis system according to Embodiment 4. [Figure 15] Figure 14 shows an example of the transmission information sent from the excrement analyzer in the analysis system. [Figure 16] Figure 14 shows an example of an aggregated information table included in the excretion information database stored in the server device in the analysis system. [Figure 17] Figure 14 shows an example of an aggregate information table included in the excretion information database stored in the server device in the analysis system. [Figure 18] Figure 14 shows an example of an aggregate information table included in the excretion information database stored in the server device in the analysis system. [Figure 19] Figure 14 shows an example of an aggregate information table included in the excretion information database stored in the server device in the analysis system. [Figure 20] Figure 14 is a flowchart illustrating an example of processing by the server device in the analysis system. [Figure 21] This figure shows an example configuration of the analysis system according to Embodiment 5. [Figure 22] Figure 21 shows an example of an aggregated information table included in the excretion information database stored in the server device in the analysis system. [Figure 23] Figure 21 shows an example of an aggregate information table included in the excretion information database stored in the server device in the analysis system. [Figure 24] Figure 21 is a flowchart illustrating an example of processing by the server device in the analysis system. [Figure 25] This figure shows an example of the device's hardware configuration. [Modes for carrying out the invention]

[0026] Embodiments will be described below with reference to the drawings. In the embodiments, the same or equivalent elements may be denoted by the same reference numeral, and redundant explanations will be omitted as appropriate. Furthermore, the reference numerals and element names in the drawings are added for convenience to each element as examples to aid understanding, and they do not limit the content of this disclosure in any way. In addition, some of the drawings described below show unidirectional and bidirectional arrows, but both arrows simply indicate the direction of a signal (data) flow and do not exclude bidirectional or unidirectional flow, respectively.

[0027] <Embodiment 1> The excrement analysis apparatus according to Embodiment 1 will be described with reference to Figure 1. Figure 1 is a block diagram showing an example configuration of the excrement analysis apparatus according to Embodiment 1.

[0028] As shown in Figure 1, the excrement analysis device 1 according to this embodiment may include an input unit 1a, a holding unit 1b, a first analysis unit 1c, and a second analysis unit 1d.

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

[0030] Therefore, the excrement analysis device 1 will have a camera installed in this manner connected to it or will include it. However, it is preferable for the excrement analysis device 1 to be equipped with a camera in order to integrate the device and prevent the leakage of imaging data to other parties. The camera is not limited to a visible light camera, but may also be an infrared light camera, or a video camera if it can extract still images. If the camera is connected to the outside of the excrement analysis device 1, it should be connected to the input unit 1a. This imaging data may include additional information (accessory information) such as the date and time of imaging and imaging conditions. The imaging conditions may include, for example, the resolution if the camera has a set resolution, or the zoom magnification if the camera has a zoom function.

[0031] The excretion area described above can include the area where water remains in the toilet bowl and can also be called the planned excretion area. By setting up the camera so that this excretion area is included in the imaging range, the image data captured will include excrement as a subject. Of course, it is preferable that the excretion area described above is an area in which the user (toilet user, toilet user) is not captured, and it is also preferable that the camera is set up so that the camera lens is not visible to the user. Furthermore, if the excrement analysis device 1 is used in a hospital or nursing home, the user described above will mainly be a patient or other person requiring care. As for caregivers, they may include care workers, and in some cases doctors, but they may also include assistants who are not care workers, or other persons.

[0032] In the following, the information obtained from the excrement analyzer 1 will be referred to as excretion information. Excretion information includes information indicating the content of the excretion, and in a simpler example, it can be information indicating whether the excrement is feces or urine. Excretion information may also include other information, such as information indicating the color of the excrement, and if it is a solid, its shape. In addition, excretion information may include or be added date and time information indicating the date and time of shooting or acquisition of the imaging data, and additional information such as shooting conditions.

[0033] The analysis of the contents of the excretion is performed by the first analysis unit 1c and the second analysis unit 1d, as will be described later. A holding unit 1b is provided to temporarily hold the data to be analyzed by the second analysis unit 1d. In other words, the holding unit 1b temporarily holds the imaging data input by the input unit 1a. The holding 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 input by the input unit 1a, and outputs notification information to the monitor who monitors the toilet user. The notification information is part of the excretion information and is information that notifies the content according to the analysis results by the first analysis unit 1c. Specific examples of the notification information will be described later, but for example, if a foreign object is captured in the imaging data, the notification information may be information that notifies that a foreign object has been found. Also, since the notification information is information presented to the monitor by notifying them, it can also be called presentation information. Furthermore, the notification information may include information that the monitor needs to take action on, in which case it can also be called warning information. Since the first analysis unit 1c analyzes the imaging data input by the input unit 1a, the analysis performed here is 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 any terminal device used by the monitor, and the direct output destination may be a server device capable of receiving notification information and forwarding the notification to that 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 also be a terminal device installed in a monitoring station such as a nurse's station, and this terminal device may also function as an alarm device. In addition, the output destination of the notification information is not limited to one location.

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

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

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

[0039] The excrement analysis device 1 may have a communication unit (not shown), which may be provided in both the first analysis unit 1c and the second analysis unit 1d. This communication unit may be configured, for example, as a wired or wireless communication interface.

[0040] The excrement analyzer 1 may have a control unit (not shown) that controls the entire system, and this control unit may include parts of the input unit 1a, holding unit 1b, first analysis unit 1c, and second analysis unit 1d described above. This control unit can be implemented, for example, by a CPU (Central Processing Unit), working memory, and a non-volatile storage device that stores a program. This program can be a program that causes the CPU to execute the processing of each unit 1a to 1d. The holding unit 1b may also use this storage device, but it may also have a different storage device. Furthermore, the control unit provided in the excrement analyzer 1 may be implemented, for example, by an integrated circuit.

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

[0042] As described above, the excrement analysis device 1 divides the analysis of image data acquired from the camera into real-time analysis for notification purposes and non-real-time analysis for recording purposes. This allows the excrement analysis device 1 to have a space-saving and power-saving control unit, such as the built-in CPU. This means that the excrement analysis device 1 efficiently uses limited computing resources by dividing the analysis process into functions that require immediate processing and other functions. Furthermore, the excrement analysis device 1 does not need to transmit image data acquired from the camera or other image data to an external source such as the cloud, and can perform the analysis of excrement using only the device installed in the toilet. In other words, all images and videos used in the analysis of the excrement analysis device 1 are processed within the excrement analysis device 1, and no images or videos are transmitted externally. Therefore, it can be said that the excrement analysis device 1 is configured in a way that also reduces the user's mental burden regarding privacy.

[0043] In summary, the excrement analysis device 1 accurately collects information about the contents of excrement defecated in the toilet bowl without the need to interview the toilet user, while respecting the user's privacy, and can also respond to situations where immediate notification to the supervisor is necessary. In other words, the excrement analysis device 1 achieves both respect for the user's privacy and notification and recording, while improvements such as installing sensors in toilets are being made to reduce the burden of excretion management in monitoring such as caregiving. The notification and recording here refer to the notification of immediate events and the recording of accurate information in monitoring sites such as caregiving settings. Therefore, the excrement analysis device 1 can reduce the physical and mental burden on supervisors and toilet users.

[0044] <Embodiment 2> Embodiment 2 will be explained, focusing on the differences from Embodiment 1, with reference to Figures 2 to 12, but various examples described in Embodiment 1 can be applied. Figure 2 is a diagram showing one example configuration of the excrement analysis system according to Embodiment 2, and Figure 3 is a block diagram showing one example configuration of the excrement analysis device in the excrement analysis system of Figure 2.

[0045] The excrement analysis system according to this embodiment (hereinafter referred to as "this system") may include an excrement analysis device 10 attached to a toilet bowl 20, a terminal device 50 used by a caregiver, and a server device (hereinafter referred to as "server") 40. The caregiver can be considered an example of a monitor, as they are responsible for monitoring the toilet user.

[0046] The excrement analysis device 10 is an example of an excrement analysis device 1 and is illustrated as a toilet-mounted device, but any device installed in a toilet is acceptable. The toilet 20 can also be equipped with, for example, a toilet seat 22 with a bidet function for user washing and a toilet seat cover 23 to cover the toilet seat 22 on its main body 21. The excrement analysis device 10 and the toilet 20 can be combined to form an analysis-enabled toilet 30 that has the function of analyzing and outputting the results.

[0047] Furthermore, the shape of the excrement analysis device 10 is not limited to the shape shown in Figure 2. For example, it can be configured such that all or part of its functions are embedded in the toilet seat 22. Also, some of the functions of the excrement analysis device 10 can be provided on the toilet seat 22 side. For example, instead of providing the distance sensor 16a described later in the excrement analysis device 10, a weight sensor can be provided on the toilet seat 22, and the excrement analysis device 10 can receive information from the weight sensor via wireless or wired communication. The weight sensor can also be provided in the box connection section 12 described later, or it can simply be a pressure sensor that detects pressure above a certain level. Also, instead of providing the first camera 16b described later in the excrement analysis device 10, a camera can be provided on the toilet seat 22 side, and the excrement analysis device 10 can receive imaging 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 analysis device 10, and the terminal device 50 can be wirelessly connected to the server 40. These connections can be made, for example, within a single wireless LAN (Local Area Network), but other connection methods, such as connecting via separate networks, can also be employed. Furthermore, some or all of these connections may be made via wired connections.

[0049] In this connected system, the excrement analyzer 10 outputs notification information by sending it to the terminal device 50 and outputs detailed information by sending it to the server 40. The terminal device 50 is a terminal device held by the caregiver of the toilet user and can be a portable excrement analyzer, but it may also be a stationary device. In the former case, the terminal device 50 can be a mobile phone (including those called smartphones), a tablet, a mobile PC, etc. 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 by the terminal device 50.

[0050] Furthermore, the server 40 may include a control unit 41 that controls the entire system, a storage unit 42 that stores detailed information, for example, in a database (DB) format, and a communication unit (not shown) for making the aforementioned connections. The control unit 41 controls the storage of detailed information transmitted from the excrement analyzer 10 to the storage unit 42, and controls its viewing from the terminal device 50. The control unit 41 can be implemented, for example, by a CPU, working memory, and a non-volatile storage device that stores a program. This storage device can be used in conjunction with the storage unit 42, and this program can be a program that enables the CPU to implement the functions of the server 40. The control unit 41 can also be implemented, for example, by an integrated circuit.

[0051] Furthermore, although not shown, the terminal device 50 may include a control unit that controls the entire device, a storage unit, and a communication unit for making the above-described connections. This control unit, like the control unit 41, can be implemented by, for example, a CPU, working memory, a non-volatile storage device that stores programs, or by an integrated circuit. The program stored in this storage device can be a program that causes the CPU to implement the functions of the terminal device 50.

[0052] Furthermore, it is preferable that the terminal device 50 includes a log generation unit that generates an excretion log based on notification information received from the excretion analysis device 10 and detailed information stored in the server 40. This log generation unit can be installed, for example, by incorporating a log creation application program into the terminal device 50. The created excretion log can be stored in an internal memory unit. The log generation unit can also be installed as part of a care record unit that creates care records. 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 Figures 2 and 3. More specifically, the excrement analysis device 10 can have two boxes as its housing, for example, a first external box 13 and a second external box 11. The excrement analysis device 10 can also have an inter-box connection section (inter-box connection structure) 12 connecting 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, as shown in Figure 3 for a specific example.

[0054] In this example, the excrement analysis device 10 can be installed on the toilet bowl 20, for example, in the following manner. That is, the excrement analysis device 10 can be installed on the toilet bowl 20 by placing the box-to-box connecting part 12 on the edge of the main body 21 so that the first external box 13 is placed on the inside of the main body 21 (the side where the excrement is excreted) and the second external box 11 is placed on the outside of the main body 21.

[0055] The first external box 13 can house, for example, a distance sensor 16a and a first camera 16b. As will be described later, the distance sensor 16a is an example of a seat sensor that detects when someone sits on the toilet seat 22, and the first camera 16b is a camera that captures images of excrement.

[0056] The second external box 11 is equipped with devices that perform real-time analysis based on 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 is also equipped with communication devices 14 that, in accordance with the control of the devices, notify caregivers and transmit analysis results to the server 40 when an event occurs.

[0057] For example, the second external box 11 can house a CPU 11a, a connector 11b, USB I / F 11c, 11d, a WiFi module 14a, a Bluetooth module 14b, a human presence 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 (the same applies hereinafter). The communication device 14 is exemplified by each module 14a and 14b, and the CPU 11a performs real-time and non-real-time analysis while sending and receiving data with other parts via each element 11b, 11c, and 11d as needed. In this example, the CPU 11a is described as also having memory as an example of a holding unit 1b. Furthermore, the second external box 11 can be connected directly to the CPU 11a without various I / Fs and connectors. Also, the communication device 14 is not limited to the communication module of the exemplified standard, and can be wireless or wired. Examples of communication modules include LTE (Long Term Evolution) communication modules, 5th generation mobile communication modules, and LPWA (Low Power, Wide Area) communication modules, among others.

[0058] As shown in Figure 3, the first external box 13 and the second external box 11 are connected by interfaces exemplified by connector 11b and USB I / F 11c, and by providing the connection wires inside the inter-box connection section 12, a single excrement analysis device 10 is formed.

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

[0060] The distance sensor 16a can be, for example, an infrared sensor, an ultrasonic sensor, or an optical sensor. If an optical sensor is used for the distance sensor 16a, the transmitting and receiving elements should be arranged so that light (not limited to visible light) can be transmitted and received through a hole provided in the first external box 13. The transmitting and receiving elements here may be configured as separate transmitting and receiving elements, or they may be integrated. The distance sensor 16a is connected to the CPU 11a via the connector 11b, and the detection result can be transmitted to the CPU 11a.

[0061] The first camera 16b is an example of a camera that captures imaging data input to the input unit 1a in Figure 1, and can be an optical camera in which the lens portion is positioned in a hole provided in the first external box 13. As described in Embodiment 1, the first camera 16b is installed so as to include the area where excrement is excreted in the toilet bowl 20 in its imaging range. The first camera 16b is connected to the CPU 11a via USB I / F 11c and transmits imaging data to the CPU 11a.

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

[0063] The motion sensor 15a is a sensor that detects the presence of a person in a specific area (the measurement range of the motion sensor 15a) (person entering or leaving a room), and this specific area can be an area that can determine entry into or exit from a toilet. Regardless of its detection method, the motion sensor 15a can employ, for example, an infrared sensor, an ultrasonic sensor, or an optical sensor. The motion 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 this 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 also perform processing such as activating the distance sensor 16a if the detection result indicates entry into the room, and activating the first camera 16b if seating is detected by the distance sensor 16a.

[0065] The second camera 15b can be an optical camera in which the lens portion is positioned in a hole provided in the second external box 11, and is an example of a camera that captures a user's face image to identify the toilet user and obtains face image data. The second camera 15b can be installed on the toilet bowl 20 so as to include the user's face in the imaging range, but it can also be installed in the toilet room where 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 has a different ID for each user and can be kept by the user, for example, by embedding it in a wristband.

[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. It can be replaced with a module that employs other communication standards. Face image data acquired by the second camera 15b and identification data obtained by the Bluetooth module 14b can be added to or embedded in the notification information and detailed information, respectively, and transmitted to the terminal device 50 and the server 40. The terminal device 50 and the server 40, upon receiving the face image data, can perform face recognition processing based on the face image data to identify the user. However, the excrement analysis device 10 can also be configured not to transmit face image data. In that case, if face recognition processing is performed by the CPU 11a, user identification by face recognition becomes possible, and the identification data showing the result can be transmitted.

[0068] The USB I / F 11c, or the CPU 11a and USB I / F 11c, can be an example of the input unit 1a in Figure 1, and inputs the image data captured by the first camera 16b. The CPU 11a and WiFi module 14a can be an example of the first analysis unit 1c in Figure 1, where 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, etc. 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 short-range wireless communication network. Of course, the transmission here can be done via the server 40 or another server, as long as the data is transferred to the terminal device 50. The notification information transmitted will not include the image data itself. This will not only reduce the user's psychological burden regarding privacy but also reduce the amount of data transmitted. However, additional information about the image data (such as the date and time of imaging) may be included in the transmission.

[0069] Although a smartphone is used as an example for terminal device 50 in the illustration, the notification destination (transmission destination) may be other than a smartphone, or in its place, for example, a notification device of a nurse call system, another terminal device held by the caregiver, an intercom, etc. Examples of other terminal devices include PHS (Personal Handy-phone System).

[0070] Furthermore, the CPU 11a is equipped with a storage device such as memory and can be an example of the storage unit 1b in Figure 1, and it stores the input imaging data and the results of real-time analysis. Also, the CPU 11a and the WiFi module 14a can be an example of the second analysis unit 1d in Figure 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, 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, thereby reducing not only the user's mental burden regarding privacy but also the amount of data transmitted. Additional information of the imaging data (such as the date and time of imaging) can be transmitted. In this way, by not outputting the imaging data itself to the outside of the excrement analyzer 10, the user's privacy can be protected.

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

[0072] As shown in Figure 4, an example is given in which user P uses a toilet bowl 30 with an analysis function installed in the toilet, and user P's caregiver C monitors the user's condition. When user P uses the toilet bowl 30 with an analysis function, the CPU 11a detects that the user has sat on the toilet bowl based on the detection result from the distance sensor 16a, which functions as a seating sensor. Upon detecting seating, the CPU 11a 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 detection as part of the real-time analysis 31. More specifically, the CPU 11a can perform an analysis to determine whether or not foreign objects other than feces and urine are included as subjects, excluding the toilet bowl and the toilet bowl cleaning liquid. Foreign objects can also be called other objects, and can be liquids or solids as long as they are not feces and urine, and may include one or more of the following, such as vomit, blood in the stool, vomiting blood (hematemesis), urine pads, diapers, and toilet paper rolls.

[0073] If the CPU 11a detects a foreign object or other object as a result of the real-time analysis 31 and requires immediate notification to the caregiver, it sends notification information (real-time notification 32) via the WiFi module 14a to the terminal device 50 of caregiver C, who is located away from the toilet. In this way, the CPU 11a can send foreign object information (foreign object detection result) indicating whether or not a foreign object is present to the terminal device 50. This foreign object information will be output as at least part of the notification information.

[0074] This frees caregiver C from having to constantly attend to user P during excretion, and the real-time notification 32 allows caregiver C to respond 51, such as rushing to the scene in case of an emergency. However, the real-time notification 32 that is transmitted does not include imaging data.

[0075] After the real-time analysis 31 is completed, the CPU 11a performs a non-real-time analysis 33, which is a more detailed analysis of excrement, based on the retained imaging data and real-time analysis results. For this reason, the retention unit in the CPU 11a temporarily retains the real-time analysis results as part of the second analysis target data. The CPU 11a transmits the non-real-time analysis results 34 to the server 40 via the WiFi module 14a.

[0076] Furthermore, user P's caregiver C, using the terminal device 50, appropriately references user P's detailed information stored on the server 40 52 based on the received notification information, and creates user P's care record (excretion log) 53. The excretion log can be created as part of the care record. In this way, the terminal device 50 can record excretion logs for each user. The format of the excretion log is not restricted.

[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 when the analysis result transmission 34 is executed by the communication function. The analysis result transmission 34 is transmitted without including the imaging data. The information recorded on the server 40 can be used by caregiver C for reference 52 when creating care records (excretion logs) 53 and for future care support.

[0078] The contents of real-time analysis 31 and non-real-time analysis 33 will be explained with reference to Figures 5 to 7. Figures 5 to 7 are diagrams illustrating examples of processing in the excrement analyzer 10.

[0079] First, referring to Figure 5, we will explain an example of the input, method, and output of real-time and non-real-time analysis. Real-time analysis is an analysis that requires real-time processing, such as notifying caregiver C. Real-time analysis takes image data (imaging data) captured by the first camera 16b as input and can classify it into one of the following six types using Deep Learning (DL), and the classification result can be output. The six types are foreign objects (diapers, incontinence pads, etc.), feces, feces + urine, urine, urine drips, and bidet devices (bidet machines).

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

[0081] Thus, in real-time analysis, notification information can be obtained from the first data to be analyzed using a trained model that takes the first data to be analyzed as input and outputs notification information. The notification information can be, for example, predetermined information corresponding to the classification result. As a result, the excrement analysis device 10 can notify caregivers of information such as the start and completion of excretion and the presence of foreign matter in the excrement, and caregivers can obtain this information in real time. Note that the algorithm (machine learning algorithm) and hyperparameters such as the number of layers of the trained model are not relevant, and it is sufficient if it is generated by machine learning. Furthermore, machine learning here does not depend on the availability of training data. Also, multiple pre-trained models may be used in real-time analysis; for example, at least one of the six types mentioned above can be used along with other pre-trained models of a different type.

[0082] Non-real-time analysis can be performed using two methods, DL and Image Processing (IP), with, for example, image data from the first camera 16b and real-time analysis results as input. For example, analysis using DL can output stool properties, while analysis using IP can output stool color, stool volume, urine color, and urine volume. Here, real-time analysis is treated as preprocessing for non-real-time analysis. In non-real-time analysis, DL and IP are used to perform this preprocessing, and the analysis results (which may be images) are compared with the trained data to output stool properties, stool color, etc.

[0083] Here, DL technology can be used to compare images before excretion (background images) with images after excretion (images during or after excretion). For example, the classification result from real-time analysis, the background image, and the subsequent image can be input to a learning model, and the stool characteristics can be output. Alternatively, a difference image from the background image to the subsequent image can be obtained as preprocessing, and the classification result from real-time analysis and that difference image can be input to the learning model, and the stool characteristics can be output. Furthermore, if the classification result from real-time analysis includes stool, DL analysis may be performed in non-real-time analysis, in which case the above classification result is not required as input to the trained model. The processing method in IP is not limited, as long as the desired detailed information can be obtained. For example, by extracting image features and performing matching processing with a pre-saved comparison image, the stool color etc. shown by the comparison image with a high matching rate can be output. In non-real-time analysis, all outputs may be obtained by either IP or DL.

[0084] Thus, in non-real-time analysis, a pre-trained model that takes second data to be analyzed (which may include real-time analysis results) as input and outputs detailed information can be used to obtain at least some of the detailed information from the second data to be analyzed. Note that the algorithm (machine learning algorithm) and hyperparameters such as the number of layers of the pre-trained model are not relevant; it is sufficient if the information is generated by machine learning. Furthermore, the machine learning process here does not require the presence or absence of training data. Furthermore, multiple pre-trained models may be used in real-time analysis. Additionally, as mentioned above, in non-real-time analysis, at least some of the detailed information can be obtained by image processing of the second analysis target data. As stated above, the method of this image processing is not specified; the important thing is that the desired detailed information is obtained.

[0085] A detailed example of real-time analysis is shown with reference to Figure 6. Real-time analysis can detect foreign objects, types of excretion, and bidet devices. First, foreign object detection is performed based on images (imaging data) captured by the first camera 16b, which is an optical camera. Foreign object detection can be performed continuously, and the caregiver is notified when a foreign object is detected. Subsequently, the image captured at the time of sitting is used as the background image, and then pre-processed images (and / or additional information) obtained by pre-processing images captured at regular intervals are used to determine whether it is feces, feces + urine, urine, or urine drips using DL. This determination is performed until the time of leaving the seat. The additional information here can also include additional information such as the date and time of capture, as exemplified above, or information showing statistical values ​​that take into account the regular interval, or information showing area such as width, etc. Also, bidet devices are detected using the same method and timing, and the determination of feces, feces + urine, urine, and urine drips is terminated when a bidet device is detected.

[0086] Thus, the CPU 11a may transmit to the terminal device 50, as part of the notification information, at least one of the following pieces of information as a result of real-time analysis: information indicating the usage status of the bidet installed on the toilet and information indicating that a person has sat on the toilet. As described above, information indicating the usage status of the bidet can be obtained as a result of real-time analysis of the image data. This is because, when in use, the nozzle that dispenses the cleaning fluid or the cleaning fluid itself is included as a subject in the image data. In addition, information indicating that a person has sat on the toilet can be obtained by the seat sensor, as exemplified by the distance sensor 16a. Thus, real-time analysis can also be performed using information other than image data. Furthermore, the CPU 11a can also know the usage status of the bidet not only through analysis of image data, but also, for example, by obtaining information from a connection to the bidet.

[0087] Referring to Figure 7, a detailed example of non-real-time analysis is shown. Non-real-time analysis allows analysis to be performed on images that have been preprocessed entirely in real-time analysis, by selecting background and input images. Detailed analysis is performed by selecting background and input images in combinations appropriate to each target of judgment. To explain the combination examples, first, for fecal matter, the image after sitting is selected as the background image, and the last fecal image is selected as the input image. Similarly, for fecal matter only or urine only, the target images are selected for fecal color, fecal volume, and urine color. However, for urine color, the urine image is used instead of the fecal image. In the case of fecal matter + urine, the background image is the last urine image before urination and defecation, and the input image is the last urine and fecal image. For urine volume, all images that were judged to be urine drips are used as input images, without using a background image.

[0088] Here, we have given an example of outputting information indicating urine volume and stool volume as detailed information in non-real-time analysis, but the detailed information is not limited to these. In non-real-time analysis, information on at least one of the following can be output as detailed information: urine flow rate or urine volume, number of defecations or stool volume per unit period, and elimination timing, which is the timing of the act of defecation. In particular, in non-real-time analysis, it is preferable to output information indicating at least one of the following as detailed information: the decrease in urine flow rate or urine volume, the decrease in the number of defecations or stool volume per unit period, and the prolongation of elimination timing, which is the timing of the act of defecation. A decrease in urine flow rate or urine volume, in other words, refers to an increase in the interval between urinations. The timing of urination can be defined to include at least the date and time of urination, and other timings can also be defined to include at least the date and time of the event in question.

[0089] In this way, non-real-time analysis can identify stool consistency, stool color, and urine color, and calculate stool and urine volume from the acquired imaging data, and output detailed information. Furthermore, in non-real-time analysis, thresholding can be applied to stool and urine volume, and information indicating whether or not a predetermined threshold has been exceeded can be included as detailed information, or added to the detailed information. It is desirable that the detailed information output as a result of this thresholding process is transmitted (notified) to the terminal device 50 directly or via the server 40. Such notifications (which may include warnings) allow caregivers to understand events that require attention.

[0090] Next, an example of the real-time analysis process will be explained with reference to Figure 8. Figure 8 is a flowchart illustrating an example of processing in the excrement analysis device 10, showing an example of the real-time analysis operation triggered when a user enters the toilet and sits on the toilet seat. The operation described here can be performed mainly by the CPU 11a controlling each part.

[0091] First, the presence or absence of a response from the distance sensor 16a, which functions as a seating sensor, is checked (step S1). If there is no response in step S1 (NO), the system waits until the seating sensor responds. When a user sits down, the distance sensor 16a responds, and step S1 becomes YES. If step S1 becomes YES, the terminal device 50 is notified of the seating (step S2), and real-time analysis begins (step S3). In addition, if entry is detected by the motion sensor 15a before the user sits down, the terminal device 50 can also be notified of the entry, and the same applies to exit.

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

[0093] In step S6, after the image preprocessing is performed, the detected object is classified as either a foreign object, excrement, or a 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 (transmission of 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 it as either stool, stool + urine, urine, or urine drips. After the processing in step S10, the process returns to step S4.

[0094] If the object detected in step S7 is a bidet, it is determined that excretion is complete, and an excretion completion notification (transmission of notification information indicating that excretion is complete) is sent to the caregiver's terminal device 50 (step S11), and the real-time analysis ends (step S12). Alternatively, the excretion completion notification may be sent only when the seating sensor stops responding, as bidets may be used more than once. Real-time analysis also ends after step S5 and after step S8.

[0095] An example of a non-real-time analysis process will be explained with reference to Figures 9 to 12. Figure 9 is a flowchart illustrating an example of processing in the excrement analyzer 10, showing an example of the operation of non-real-time analysis. The operation described here is mainly performed by the CPU 11a controlling each part. Figures 10, 11, and 12 show examples of stool composition analysis, stool color analysis, and urine volume analysis included in the non-real-time analysis in the processing example in Figure 9, respectively.

[0096] The real-time analysis illustrated in Figure 8 performs analysis using a space-saving, power-efficient CPU while executing only the minimum necessary analysis to enable immediate notifications 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 complete (step S21), and if it is complete (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 excretions has been exceeded (or a predetermined period has elapsed) for each user, and if so, non-real-time analysis may be started.

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

[0099] If the real-time analysis result in step S23 is stool, stool properties analysis (step S24), stool color analysis (step S25), and stool volume analysis (step S26) are performed. Of course, the order of these is not important. If the real-time analysis result in step S23 is urine or urine drips, urine color analysis (step S27) and urine volume analysis (step S28) are performed. Of course, the order of these is not important. If the real-time analysis result in step S23 is stool + urine, stool properties 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, the order of these is not important. Furthermore, each analysis in steps S24 to S28 can be performed using, for example, individual learning models, but multiple analyses or all analyses can also be performed using a single learning model.

[0100] In step S24, the stool quality analysis is performed by comparing the image with the highest confidence level with the image trained by DL. The image with the highest confidence level can be the image itself represented by the imaging data or an image obtained by preprocessing the imaging data using a preprocessing method suitable for stool quality analysis. Furthermore, this stool quality analysis can be performed in accordance with the Bristol Stool Scale, as shown in Figure 10. As a result of the analysis, the results can be classified into one of types 1 to 7 as shown in Figure 10.

[0101] Furthermore, in the stool color analysis in step S25, preprocessing can be performed, for example, as shown in the processing procedure that transitions sequentially from images 61, 62, and 63 in Figure 11. The preprocessing exemplified here involves removing the lighter colored areas that occupy a large area from the original image 61 to obtain image 62, and then removing the narrow areas of the same color to obtain image 63. Then, in the stool color analysis in step S25, an image from which the necessary information has been extracted (and / or added) through preprocessing, such as image 63, is used to calculate the distance between the extracted stool color and the stool reference color, and the color that occupies the largest area in the extracted stool image can be used as the stool color. For example, in image 63, there are stool-like objects made up of two colors, and the color that occupies the larger area can be used as the stool color. The information added here can also be, for example, information indicating area.

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

[0103] In step S27, the urine color analysis is performed using the same method as in step S25, but the target image is a urine image instead of a stool image. Distance calculation from the reference color and the color occupying the largest area can then be used to determine the urine color.

[0104] In the urine volume analysis in step S28, for all urine drip images classified as "urine drip" as a result of the real-time analysis, calculations can be performed using information such as the duration of urine dripping (urine drip image information) and coefficients. Here, the coefficients can be, for example, the average urine volume of a typical user or the user themselves. If all of the above urine drip images are acquired at regular intervals, the urine volume can be estimated from the images and the average urine volume, and the urine volume can be classified into a value based on the estimation result. Note that values ​​related to urine volume, such as the average urine volume, can be obtained as a result of ongoing surveys, and in this case, they become variable parameters.

[0105] Furthermore, the results of urine output can be classified into classes corresponding to the amount of urine, as illustrated in Figure 12. In the example shown in Figure 12, the class names are very small, small, medium, large, and very large, and these are classified as less than threshold a, between threshold a and threshold b, between threshold b and threshold c, between threshold c and threshold d, and greater than or equal to threshold d, respectively.

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

[0107] However, the classification and other procedures are not limited to those illustrated in Figures 8 to 12. Real-time analysis can be performed by comparing it with images trained by DL as described above, but it can also 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 notification is sent to the caregiver, and the system proceeds to excrement analysis, which classifies the material into five types: "feces," "feces + urine," "urine," "urine drips," and "washlet." This excrement analysis is also performed at regular intervals, and the detection of a "washlet" indicates that excretion is complete. Upon completion of excretion, the excrement analysis device 10 sends an excretion completion notification to the caregiver's terminal device 50 along with the real-time analysis results, and the system proceeds to non-real-time analysis using the images and real-time analysis results used in the real-time analysis. All processing from seating detection up to this point is performed by the excrement analysis device 10 installed on the toilet.

[0108] As described above, the excrement analysis device 10 can obtain real-time analysis results such as the start of excretion, detection of foreign matter, detection of excrement, and completion of excretion, and non-real-time analysis results such as stool properties, stool color, urine volume, urine color, and urine volume. All analysis results can be recorded on the server 40 in 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. Furthermore, the server 40 can store the received analysis results, perform further analysis from the stored data, and notify the terminal device 50 of the analysis results or make them viewable from the terminal device 50.

[0109] Furthermore, while the excrement analysis device 10 or the system including it can be used in a private home on the premise that there is only one user, it is preferable to have a function to identify users on the premise that there are multiple users. This function is explained using facial image data acquired by the second camera 15b and identification data obtained by the Bluetooth module 14b. This makes it possible to notify caregivers of things like the user's name, as well as notifications for entering the room, leaving the room, sitting down, leaving the room, starting excretion, and completing excretion, as well as to record detailed information for each user and create an excretion log and care records including it.

[0110] Here, we will provide supplementary explanation regarding the excretion log and care records including it. Information obtained through real-time and non-real-time analysis can be used by caregivers when creating the user's excretion log, etc. Furthermore, the program of the terminal device 50 can be incorporated into the terminal device 50 in an executable manner as care software that includes a presentation function for displaying notification information received from the excretion analysis device 10. This care software can also have a function to automatically input information transferred from the server 40 or information obtained when accessing the server 40 into the excretion log or care records including it. In addition, such care software may be installed on the server 40, in which case it is sufficient to receive notification information and detailed information from the excretion analysis device 10 and automatically input that information into the excretion log or care records.

[0111] The excretion log should ideally record predictions for future excretions. To achieve this, the system should be equipped with a prediction function. Predictions can be made from the results of non-real-time analysis (and real-time analysis), and can be realized, for example, by installing a trained model for prediction on at least one of the server 40 and the terminal device 50. Since the real-time and non-real-time analyses described above can output the date and time of excretion and the amount of excretion for each user, the system can ultimately record the excretion log on the server 40 and / or the terminal device 50. The system can be configured to use this excretion log and input the necessary information into the trained model to output the date and time (excretion timing) and amount of urination and defecation in the future. This output may also be the trend of urination and defecation (average interval, etc.). Alternatively, the prediction described above can be included in the non-real-time analysis.

[0112] By incorporating such predictive functions, the system not only reduces the burden on caregivers in maintaining daily records and diaries of bowel movements, but also allows for the analysis of trends in this data. This enables the system to alert both the user and caregiver of constipation if there are no records of bowel movements for a set number of days, prompting action. For example, by confirming the date and time of bowel movements and calculating the average interval time for each user, the system can predict urination time and notify the user and caregiver when it is time to urinate, thereby reducing incontinence and supporting independence. Furthermore, by identifying trends in urinary dysfunction when the urination interval exceeds a certain threshold, the system can notify the user and caregiver of an alarm, enabling early hospital visits. The system can also be configured to similarly notify alarms regarding bowel movement intervals. In this way, the system confirms information on the date and time of bowel movements and the content of the excretion, and determines whether a set threshold is exceeded, thereby identifying trends in urinary dysfunction and constipation, and notifying caregivers and users of warnings. These functions reduce the burden on caregivers and enable comprehensive support for toilet users.

[0113] Furthermore, it is preferable that this system not only notifies the caregiver of an alarm when the excrement analyzer 10 detects foreign matter other than excrement, but also has a function to stop the water purification of the toilet (a flush stop function). For this purpose, the excrement analyzer 10 may be equipped with a flush control unit (not shown) that controls the flushing function of the toilet bowl. This flush control unit is connected to or can be connected to a device that has a toilet flushing function (for example, a bidet toilet seat such as Washlet® that has a toilet flushing function). The target of the bidet toilet seat is the user's buttocks, etc. This system may also include such a device, or a toilet bowl with an integrated bidet toilet seat.

[0114] As illustrated in the configuration example in Figure 3, the CPU 11a and the interface (not shown) between the toilet seat 22 and the CPU 11a can be considered an example of this flushing control unit. Regarding the flushing function, existing technology can be used to control the amount of water flushed into the toilet bowl 20 (in this example, the toilet seat 22 controls this). When the CPU 11a receives notification that foreign matter is present, it outputs a stop command to the toilet (in this example, the toilet seat 22) to stop the flushing function. For example, the excrement analysis device 10 notifies a remotely controllable power strip connected to the power cord of the toilet seat 22 of a power cut-off, thereby stopping the flushing function of the toilet bowl 20. More specifically, power can be supplied to the toilet seat 22 via an IoT (Internet of Things) tap, and a stop command can be output to this IoT tap to turn off the power. In this case, the stop command can be issued, for example, by the CPU 11a via the Bluetooth module 14b.

[0115] By incorporating this flush stop function, even if the user uses the flushing function, it is stopped, preventing foreign objects from being flushed down the toilet and allowing them to be later tested as samples. In addition, because it prevents foreign objects from being flushed and outputs a warning message indicating the detection of a foreign object, caregivers or other personnel can rush to the toilet, thereby preventing the user from experiencing the distress that might arise from being unable to flush a foreign object.

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

[0117] The first benefit is that by automatically recording the contents of excrement identified through a combination of the first camera and machine learning, the manual processes of interviewing patients about their excrement, measuring urine volume, checking stool consistency, and creating excretion diaries, which were previously performed manually, become unnecessary. This reduces the administrative work time for caregivers and other care workers.

[0118] The second benefit is that real-time analysis allows caregivers to be notified immediately of events occurring in the toilet (such as sitting, defecation, and detection of foreign objects), freeing them from having to constantly attend to the user's excretion.

[0119] The third benefit is that by notifying caregivers of warnings (alarms) when foreign objects are detected through real-time analysis, accidents related to toilet drainage can be prevented, and the costs associated with dealing with drainage problems can be reduced.

[0120] The fourth benefit is that when analyzing images captured by the first camera 16b, all analysis processing can be performed by the excrement analysis device 10, and only the analysis results can be sent to the server 40, such as a cloud server. As a result, the imaging data of the excrement will not be seen by third parties, and the user's mental burden regarding privacy can be reduced.

[0121] The fifth benefit is that by dividing the analysis of excrement into real-time and non-real-time analyses, the CPU 11a built into the excrement analyzer 10 can be made more space-saving and power-efficient, resulting in a lower cost for the excrement analyzer 10. A lower cost for the excrement analyzer 10 reduces the overall system costs, including servers, and maintenance costs in case of failure.

[0122] The sixth benefit is that by recording the analysis results of excrement in a database format, it becomes possible to identify the possibility of constipation or urinary dysfunction from the excretion records. This eliminates the need to administer laxatives unnecessarily, which was previously done based on the unreliability of asking about the presence or absence of bowel movements. As a result, medication costs can be reduced.

[0123] The seventh benefit is that it becomes possible to understand each user's individual urination interval from excretion records, which are recorded in a database format or similar format based on the analysis results of excrement. As a result, users can avoid the need to constantly use diapers or incontinence pads, thus reducing costs, and caregivers can understand each user's condition and easily provide support for their independence.

[0124] <Embodiment 3> Embodiment 3 will be explained with reference to Figure 13, focusing on the differences from Embodiments 1 and 2, but various examples described in Embodiments 1 and 2 can be applied. Figure 13 is a block diagram showing an example configuration of a server device according to Embodiment 3.

[0125] As shown in Figure 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 also be said to be its control unit.

[0126] In this embodiment, the above detailed information includes at least information indicating the date and time of defecation (date and time of occurrence), the type of excrement, and the shape of the stool. The information processing unit 70c then aggregates the detailed information for each shape of stool. To give a simple example, the aggregation can be performed by counting the number of times each shape occurs, or by calculating the average number of times over a certain period of time.

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

[0128] In this way, the server device 70 can aggregate the accurate detailed information (which can be called excretion information) collected by the excrement analyzer 1 or the excrement analyzer 10. Furthermore, during the aggregation process, it is also possible to extract the necessary information from the detailed information and perform the aggregation process only on the extracted information.

[0129] Furthermore, the aggregated results can be stored in a storage device such as the memory unit 70b. It is preferable to store the aggregated results in a state that allows them to be provided to external devices, such as the terminal device 50 used by caregiver C or the terminal device used by toilet user P, in accordance with requests from external devices. In this case, the server device 70 includes a provisioning unit (not shown) that provides the processing results of the information processing unit 70c to the external device via a network or the like. It is preferable that the aggregated results be stored in a database format and stored in a server device (e.g., a cloud server device) that can be accessed from external devices. The aggregated results can be provided for various purposes, and methods of their use will be described later in Embodiments 4 and 5.

[0130] Furthermore, the receiving unit 70a has been described on the premise 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 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 content of the excretion, which is the result of analyzing the excrement in the toilet bowl from the imaging data captured by the toilet bowl, and should include at least information indicating the date and time of excretion, the type of excrement, and the shape of the stool.

[0131] <Embodiment 4> Embodiment 4 will be explained, focusing on the differences from Embodiment 3, with reference to Figures 14 to 20, but various examples described in Embodiments 1 to 3 can be applied. Figure 14 is a diagram showing an example configuration of the analysis system according to Embodiment 4, and Figure 15 is a diagram showing an example of transmission information sent from the excrement analysis device 10 in the analysis system of Figure 14. Figure 16 is a diagram showing an example of an aggregated information table included in the excrement information database stored in the server device in the analysis system of Figure 14, and Figures 17 to 19 are diagrams showing examples of aggregated information tables included in the excrement information database.

[0132] As shown in Figure 14, the analysis system according to this embodiment can be configured by connecting a plurality of excrement analysis devices 10 and terminal devices 80 used by administrators such as toilet users or their caregivers to a cloud network N that includes an excretion information database (DB) 71. The excretion information DB 71 can be stored in the storage unit 70b of the server device 70 shown in Figure 13.

[0133] In other words, this analysis system is configured to provide information contained in the excretion information DB 71 to the terminal device 80 via the cloud network N. The terminal device 80 can obtain desired information from the excretion information DB 71 (however, with consideration for privacy, the information will be tailored to the user of the terminal device 80). This analysis system can provide a service that provides such information to the user of the terminal device 80. Furthermore, building the DB on the cloud network N is beneficial because the DB capacity, processing performance, and number of devices can be flexibly changed according to the number of excretion analysis devices 10, the number of toilet users, and actual usage conditions.

[0134] A specific example of the excretion information DB71 will be explained with reference to Figures 15 to 19. The excretion information DB71 may include information aggregated by the information processing unit 70c from transmission information sent from multiple excretion analysis devices 10 (for example, the transmission information in Figure 15) (for example, the aggregated information table 71a in Figure 16), and may also include information extracted from that information to be aggregated. Furthermore, the excretion information DB71 can include aggregated information (for example, aggregated information tables 71b, 71c, and 71d in Figures 17 to 19) as information provided by the cloud network N.

[0135] The excrement analyzer 10 collects excretion information (the detailed information described above) and transmits this information (transmission information) to the server device 70, along with user information and installation location information. The collected excretion information may include the following, as illustrated in Figure 15. Specifically, the excretion information may include the date and time of excretion (date and time of occurrence), the type of excrement (information indicating either urination, defecation, or foreign matter), the amount of urine (for example, information indicating either a large, normal, or small amount), and the shape of the stool (for example, information indicating either hard, normal, or diarrhea). In addition, the excretion information may include the color of the stool and the number of times (number of times urination and excretion per day).

[0136] The transmitted information may include, as illustrated in Figure 15, excretion information, user information including the age and gender of the toilet user, and address information indicating the 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 be information that respects privacy, such as only the postal code. The toilet location may refer to the location of the excrement analysis device 10. In cases where it is necessary to contact the user, as described later, the user information may include information such as the user's contact information. The transmitted information is received by the receiving unit 70a of the server device 70 in Figure 13 and can be stored in the storage unit 70b as the target of extraction and aggregation by the information processing unit 70c.

[0137] The server device 70 receives this transmission information and registers it in the excretion information DB 71. During this registration, an aggregate information table 71a (in an empty state) is created in the excretion information DB 71 on the cloud network N, as shown in Figure 16. The excretion analysis device 10 collects excretion information and, as shown in Figure 15, transmits the excretion information, along with user information and installation location information, as transmission information to the server device 70, which is equipped with the excretion information DB 71 on the cloud network N. When the excretion information DB 71 receives the transmission information from the excretion analysis device 10, it updates the information stored in the aggregate information table 71a with that transmission information.

[0138] Next, data aggregation in the excretion information DB 71 will be described. As described in Embodiment 3, the information processing unit 70c extracts information (information to be aggregated) from the transmitted information, including the date and time of excretion, the type of excrement, and the shape of the stool, and can aggregate the extracted information for each shape of stool under various conditions. Data aggregation can be performed from the aggregated information table 71a on the excretion information DB 71, but it is done in order to generate the information to be provided. Recipients of this information include caregivers and toilet users. It is preferable that the information to be provided is in a format that is easy for recipients to view, including the content and changes in excretion.

[0139] For example, the excretion information DB71 can contain the aggregate information tables 71b to 71d shown in Figures 17 to 19. To generate these tables, it is best to first create a view that can obtain such aggregate results and then register the information.

[0140] The summary information table 71b is a table that shows the aggregated results of stool shape, and can be generated using information on the date and time of occurrence, type of excrement, and shape of stool from the aggregate information table 71a. For example, information where the type of excrement is stool can be extracted from the aggregate information table 71a, the extracted information can be classified by the date and time of occurrence (in this example, the month of occurrence) and shape of stool, and the classified information can be aggregated into the summary information table 71b. From the summary information table 71b, trends in stool shape can be seen on a monthly basis, and those who see this information can recognize, for example, that they are more likely to get sick in months when diarrhea is frequent.

[0141] The summary information table 71c is a table that shows the aggregated results of bowel movement patterns by age group, and can be generated using information on the date and time of occurrence, type of excrement, bowel movement pattern, and age from the aggregate information table 71a. For example, information where the type of excrement is bowel movement can be extracted from the aggregate information table 71a, the extracted information can be classified by the date and time of occurrence (in this example, the month of occurrence), bowel movement pattern, and age, and the classified information can be aggregated into the summary information table 71c. From the summary information table 71c, trends in bowel movement patterns classified by age group can be seen on a monthly basis.

[0142] The summary information table 71d is a table that shows the aggregated results of stool shape by region, and can be generated using information such as the date and time of occurrence, type of excrement, shape of stool, and address (postal code) from the aggregate information table 71a. For example, information where the type of excrement is stool can be extracted from the aggregate information table 71a, the extracted information can be classified by the date and time of occurrence (in this example, the month of occurrence), shape of stool, and address (postal code), and the classified information can be aggregated into the summary information table 71d. From the summary information table 71d, it is possible to see the trends in stool shape classified by region on a monthly basis.

[0143] Furthermore, as illustrated by the examples of trends that can be grasped in the summary information tables 71b to 71d, it is preferable for the information processing unit 70c to analyze the trend of changes in the shape of stool over time. The method of analyzing the trend is not limited. In addition, the analysis results may be provided in the form of text, for example, in the summary information table 71c, such as "Month ○ is the month with the most diarrhea."

[0144] Furthermore, as illustrated in Figure 15, it is preferable that the detailed information in the transmitted information includes information indicating the color of the stool. In that case, it is preferable that the information processing unit 70c analyzes the temporal trends in the shape and color of the stool. The results of the analysis of the trends in the shape and color of the stool can be used for predicting infectious diseases, as described later. For example, in infectious gastroenteritis, the shape and color of the stool change due to the illness, so the results of the analysis of trends in changes in the stool can be used to predict such infectious diseases. Similarly, the detailed information in the transmitted information may also include information indicating the amount of stool.

[0145] Furthermore, when predicting infectious diseases, the situation regarding the occurrence of infectious diseases differs from region to region, so the region must also be taken into consideration. When considering the region, as mentioned above, the receiving unit 70a needs to receive address information associated with the detailed information and receive cautionary information (including warnings) to prompt attention to infectious disease outbreaks in order to predict infectious diseases.

[0146] Address information can be received along with detailed information. Warning information can be received through a separate route from detailed information. For example, warning information can be received as input data from the control unit provided on the server device 70 or by reading it from an external recording medium. Alternatively, warning information can be received by periodically acquiring it 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 for providing information).

[0147] The information processing unit 70c then analyzes the temporal trends in stool (shape or shape and color, etc.) for each region indicated by the address information from the address information and detailed information, and predicts the outbreak of the above infectious disease for each region based on the analysis results and warning information (combining the analysis results and warning information). The address information and detailed information used for the analysis can be aggregated information from transmitted information as exemplified in the aggregated information table 71a, but it is preferable to use aggregated results as in the summary information table 71d. In addition, a region can refer to a town or village unit, but it can also refer to a health center jurisdiction unit or a school district unit, etc., as long as address information is received that allows the region to be distinguished from the region to be predicted.

[0148] Furthermore, while the method of prediction is not specified, it can be performed based on warning information and whether the shape and color of stool are increasingly similar to those that can occur with that infectious disease. In addition, the receiving unit 70a may receive warning information and environmental information including climate information (weather forecast information), and based on the results of the analysis and the environmental information, predict the outbreak of infectious diseases for each region. Predictions can also be performed for multiple infectious diseases, with each prediction being performed for each infectious disease.

[0149] Furthermore, it is preferable that the server device 70 includes a provisioning unit (not shown) that provides the results predicted for each region by the information processing unit 70c to the recipients associated with each region. Since these prediction results are based on the defecation results of toilet users, including infected individuals who have not been diagnosed with the disease, it can be said that they reflect the actual infection situation better than warning information. In addition, these predicted results (infectious disease outbreak warning information) can be provided by notifying terminal devices 80 such as smartphones from the server device 70 for each region, such as at the town level of the relevant city or town or school district.

[0150] Thus, the analysis system according to this embodiment can be constructed as an infectious disease prediction system that provides prediction results as information for predicting infectious disease outbreaks and maintaining health.

[0151] Furthermore, while the example given uses a monthly period for aggregating stool consistency, it could also be set to a daily, yearly, predetermined number of months, predetermined number of days, or predetermined number of years period. This would allow for the understanding of trends in stool consistency on a daily or yearly basis. Additionally, results aggregated annually could be further aggregated daily or monthly.

[0152] Next, with reference to Figure 20, the processing flow of the server device 70 in the infectious disease prediction system according to this embodiment will be outlined. Figure 20 is a flowchart illustrating an example of the processing 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 storage unit 70b (step S42). The information processing unit 70c aggregates the transmission information for each stool shape and stores the aggregated results in the storage unit 70b (step S43). In an example that also performs infectious disease prediction, the information processing unit 70c further analyzes the temporal changes in stool shape for each region (step S44). Next, the information processing unit 70c predicts the outbreak of the infectious disease for each region based on the analysis results and cautionary information about the infectious disease, and stores the prediction results in the storage unit 70b (step S45).

[0154] Next, we will explain the effects, particularly regarding the prediction of infectious disease outbreaks. First, I will explain the current methods of providing information on infectious diseases and the challenges involved. Currently, when infectious diseases such as infectious gastroenteritis occur, medical institutions report the number of patients with the disease to public health centers, and if the number of reported cases exceeds a certain threshold, the public health center issues a warning (warning or alert) about the outbreak. As a result, while public health centers know that an infectious disease is spreading within their jurisdiction, they do not have access to the addresses of infected patients, so they cannot pinpoint the specific neighborhoods or school districts within the affected municipalities. This creates a contradiction where an infectious disease is spreading within the public health center's jurisdiction, but not within the specific neighborhoods or school districts of the municipalities within that jurisdiction. To resolve this contradiction, public health centers need to issue warnings and alerts at the neighborhood or school district level within the municipalities, but this is not currently possible because they do not have access to the addresses of individual infected patients and therefore cannot grasp the detailed extent of the outbreak.

[0155] Furthermore, currently, medical institutions report the total number of infectious disease patients for the week to the public health center on the following Monday. The public health center compiles the reports from medical institutions within its jurisdiction and issues a warning or alert if the number of infectious disease patients exceeds a certain number. Therefore, there is a time lag between the increase in infectious disease patients and the issuance of a warning or alert. Thus, because medical institutions report the results to the public health center on a weekly basis, there is a time lag between the increase in infectious disease patients and the issuance of a warning or alert.

[0156] In contrast, in this embodiment, the excretion information collected by the excretion analyzer 10 can be aggregated, for example, on a daily basis. Therefore, in this embodiment, it is possible to understand from the daily aggregate results that the number of people with diarrhea is increasing, and the location of the relevant town area or school district can be identified from the address information. Furthermore, in this embodiment, by combining this information with infectious disease outbreak information issued by the public health center, it is possible to predict the spread of infectious diseases in the relevant town area or school district of the city or town, and to provide regional cautionary information based on the prediction results.

[0157] As described above, the infectious disease prediction system according to this embodiment collects information such as the shape and color of excrement, analyzes it for each region, and uses infectious disease warning information to predict the outbreak of that infectious disease. Therefore, with this infectious disease prediction system, even if infectious disease outbreak warning information is issued for the area under the jurisdiction of a public health center, it becomes possible to provide warning information that takes the actual infection situation into account more accurately for each municipality or school district. Furthermore, because this infectious disease prediction system can provide warning information that takes the actual infection situation into account more accurately, it can solve the problem of not being able to take rapid preventive measures against infectious diseases due to delays in warning information, and is expected to have an effect in preventing the spread of infectious diseases.

[0158] <Embodiment 5> Embodiment 5 will be explained with reference to Figures 21 to 24, focusing on the differences from Embodiment 4, but various examples described in Embodiments 1 to 4 can be applied. Figure 21 is a diagram showing one example configuration of the analysis system according to Embodiment 5, and Figures 22 and 23 are diagrams showing an example of an aggregated information table and an example of a summary information table included in the excretion information database stored in the server device in the analysis system of Figure 21, respectively.

[0159] As described in Embodiment 4, the detailed information (excretion information) collected by the excrement 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 the installers of the excrement analyzer 10 can gain from its installation. In doing so, it is also necessary to consider that excretion information is sensitive information and that there may be resistance to providing it.

[0160] Therefore, in this embodiment, the installer of the excrement analysis device 10 provides a service to toilet users who provide information about defecation and urination through their excretions, such as predicting their health status from that information and providing health advice appropriate to their health status. This creates advantages in the installation of the excrement analysis device 10 and the provision of information, and as a result, it becomes possible to promote the installation of the excrement analysis device 10.

[0161] This embodiment will be described in detail. In the analysis system according to this embodiment, the server device 70 in Figure 13 is configured to perform the following processing. First, the receiving unit 70a receives user information and address information associated with detailed information, and also receives environmental information including climate information and infectious disease outbreak information showing the results of infectious disease outbreaks. The storage unit 70b stores the received information.

[0162] As shown in Figure 21, the analysis system according to this embodiment can be configured by connecting multiple excrement analysis devices 10, terminal devices 80 used by caregivers or other administrators, and terminal devices 90 used by toilet users to a cloud network N which includes an excretion information DB 71. Here, as shown in the figure, terminal devices 90 can also be connected to terminal devices 80 via a different network N1 from the cloud network N.

[0163] The information processing unit 70c analyzes the temporal trends in bowel movements for each user, based on the user information, address information, environmental information, and detailed information, in accordance with the environmental information. Then, based on the analysis results, the information processing unit 70c predicts the health status, including the susceptibility to the above-mentioned infectious diseases, for each user as indicated by the user information.

[0164] While the method of analysis and prediction is not restricted, it is advisable to first aggregate information for each user to facilitate the use of the data for individual health predictions. More specifically, user-specific information is extracted from the aggregated information table 71a shown in Figure 16, which is stored in the excretion information DB 71, to generate the individual aggregated information table 71e shown in Figure 22. Analysis will then be performed using the information from this individual aggregated information table 71e, including the date and time of occurrence, type of excretion, shape of stool, and color of stool. For example, first, information corresponding to stool is extracted from the individual aggregated information table 71e, the extracted information is classified by date and time of occurrence, shape of stool, and color of stool, and the classified information is aggregated into the aggregated information table 71f shown in Figure 23. From the aggregated information table 71f, the monthly trends in the shape and color of stool can be seen for that user. Note that while the example given uses a monthly period for the aggregation of stool data, it is not limited to this.

[0165] Furthermore, as illustrated by the example of how trends can be grasped using the aggregated information table 71f, the information processing unit 70c performs such trend analysis. As mentioned above, the method of analysis is not limited.

[0166] The information processing unit 70c then predicts the health status, including the likelihood of contracting the aforementioned infectious diseases, for each user based on the results of an analysis of their bowel movement patterns. Furthermore, predictions can be performed for multiple infectious diseases, with each prediction being performed separately for each disease. As mentioned above, the prediction method is not limited, but by analyzing the detailed user information accumulated so far and combining that information with environmental information, it is possible to predict when each user is likely to become ill, or to predict each user's risk of contracting an infectious disease based on outbreaks of infectious diseases in the surrounding area. In addition, the information processing unit 70c can generate health advice information for each user based on these prediction results, providing information on how to avoid becoming ill and methods to prevent infection with infectious diseases. The health advice information can be provided in a pre-prepared format according to the prediction results.

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

[0168] For example, the system can be configured so that users can access a web page from a terminal device 90 such as a smartphone and specify a user, or by logging into an application program installed on the terminal device 90, to view prediction results and health advice information. The prediction results and health advice information can be stored in the storage unit 70b. Furthermore, it is desirable that the health prediction and health advice information be made accessible not only to toilet users but also to terminal devices used by family members living with the toilet user or family members living separately.

[0169] Furthermore, this embodiment is not limited to a configuration in which detailed information is obtained using the excrement analysis device 1 and 10 described in Embodiments 1 and 2, but can also employ a configuration in which similar information is obtained using other devices. The same information refers to detailed information indicating the content of the excrement, which is the result of analyzing the excrement in the toilet bowl from the image data captured by the toilet bowl, user information and address information associated with the detailed information, and environmental information. Environmental information may include climate information and infectious disease outbreak information indicating the results of infectious disease outbreaks.

[0170] Thus, the analysis system according to this embodiment can be constructed as a health information provision system that predicts and provides an individual's health status using excretion information. Next, with reference to Figure 24, the processing flow of the server device 70 in the health information provision system according to this embodiment will be described in general terms. Figure 24 is a flowchart illustrating an example of the processing of the server device 70.

[0171] First, the receiving unit 70a of the server device 70 receives the transmission information and environmental information (step S51) and stores them in the storage unit 70b (step S52). The information processing unit 70c analyzes the trend of temporal changes in bowel movements for each user, as indicated by the user information, in accordance with the environmental information, based on the user information, address information, environmental information, and detailed information, and stores the analysis results in the storage unit 70b (step S53). Prior to step S53, the aggregation for each user may be performed as described above. Furthermore, the information processing unit 70c predicts the health status, including the presence of infectious diseases, for each user as indicated by the user information, based on the analysis results, and stores the prediction results in the storage unit 70b (step S54).

[0172] According to this embodiment, it is possible to predict the user's health status from excretion information, and it becomes possible to provide users of the excretion analyzer with health information that is effective in promoting health. Therefore, there are advantages to installing the excretion analyzer, and it is expected that this will encourage the installation of the excretion analyzer.

[0173] <Other Embodiments> [a] In each embodiment, the functions of the analysis system and each device included in the system have been described. However, the devices are not limited to the illustrated configuration examples; any device that can perform these functions is acceptable. For example, the server devices described above, such as server 40 and server device 70, can be configured as a distributed system consisting of multiple server devices with their functions distributed.

[0174] [b] Each of the devices according to Embodiments 1 to 5 may have the following hardware configuration. Figure 25 shows an example of the hardware configuration of the device. The same applies to the other embodiment [a] described above.

[0175] The apparatus 100 shown in Figure 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, an MPU (Micro Processor Unit), or a CPU. The processor 101 may include multiple processors. The memory 102 is composed of, for example, a combination of volatile memory and non-volatile memory. The functions of each apparatus described in Embodiments 1 to 5 are realized by the processor 101 reading and executing a program stored in the memory 102. In this case, information can be sent and received with other devices via the communication interface 103 or an input / output interface (not shown). In particular, if the apparatus 100 is an excrement analyzer, information (including imaging data) from an imaging device built into or attached to the apparatus 100 can also be sent and received via the communication interface 103 or an input / output interface (not shown).

[0176] In the above example, the program can be stored and supplied to the computer using various types of non-transitory computer-readable medium. Non-transitory computer-readable medium includes various types of tangible storage medium. Examples of non-transitory computer-readable medium include magnetic storage media (e.g., flexible disks, magnetic tapes, hard disk drives) and magneto-optical storage media (e.g., magneto-optical disks). Furthermore, this example includes CD-ROM (Read Only Memory), CD-R, and CD-R / W. Furthermore, this example includes semiconductor memory (e.g., mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, and RAM (Random Access Memory)). In addition, the program may be supplied to the computer by various types of transient computer-readable medium. Examples of transient computer-readable medium include electrical signals, optical signals, and electromagnetic waves. Transitory computer-readable medium can be supplied to the computer via wired communication channels such as electric wires and optical fibers, or via wireless communication channels.

[0177] [c] Furthermore, as illustrated in Embodiments 1 and 2 described above, the procedure for the excrement analysis method in the excrement analysis system can also take the form of an excrement analysis method (analysis method). This excrement analysis method may comprise the following input step, retention step, first analysis step, and second analysis step. The input step involves the excrement analysis device inputting imaging data captured by an imaging device installed to include the excrement excretion area in the toilet bowl within its imaging range. The retention step involves the excrement analysis device temporarily retaining the imaging data input in the input step. The first analysis step involves the excrement analysis device analyzing the first analysis target data, which is the imaging data input in the input step, and outputting notification information to a monitor who monitors the toilet user. The second analysis step involves the excrement analysis device analyzing the 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 excrement. Other examples are as described in Embodiments 1 and 2. Furthermore, the above program can be described as a program that causes the excrement analyzer (the control computer provided in the excrement analyzer) to execute the above input step, the above holding step, the above first analysis step, and the above second analysis step.

[0178] Furthermore, as illustrated in Embodiments 3 and 4, the procedure of the analysis method in the analysis system is also illustrated in this disclosure, and the present disclosure may take the form of other analysis methods. The analysis method here comprises the following receiving step, storage step, and information processing step, and preferably the following providing step. In the receiving step, the server device receives detailed information (which can also be called excretion information) indicating the content of excretion, which is the result of analyzing the excrement in the toilet bowl from the imaging data captured by the toilet bowl. In the storage step, the server device stores the detailed information received in the receiving step. Here, the detailed information includes at least information indicating the date and time of excretion, the type of excrement, and the shape of the stool. In the information processing step, the server device aggregates the detailed information for each shape of the stool. In the providing step, the server device provides the processing results from the information processing step to an external device. Other examples are as described in Embodiments 3 to 5. Furthermore, in this case, the above program can be said to be a program that causes the server device (computer) to execute the above receiving step, the above storage step, and the above information processing step (preferably in addition to these, the above providing step).

[0179] Furthermore, as illustrated in Embodiment 5, the procedure of the analysis method in the analysis system is also provided, and this disclosure may take the form of other analysis methods. The analysis method here comprises the following receiving step, storage step, and information processing step, and preferably comprises the following providing step. The receiving step involves the server device receiving detailed information indicating the content of excrement, which is the result of analyzing excrement in a toilet bowl from imaging data captured by the toilet bowl, user information and address information associated with the detailed information, and environmental information. Here, the detailed information includes at least information indicating the date and time of excrement, the type of excrement, and the shape of the stool. 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 where the toilet is installed. The environmental information includes information including climate information and infectious disease outbreak information indicating the result of an infectious disease outbreak. The storage step involves the server device storing the detailed information, user information, address information, and environmental information received in the receiving step. The above information processing step involves the server device analyzing the temporal trends of bowel movements for each user, as indicated by the user information, based on the user information, address information, environmental information, and detailed information. The above information processing step further involves the server device predicting the health status, including the presence of the above infectious disease, for each user as indicated by the user information, based on the analysis results. The above provision step involves the server device providing the processing results from the information processing step to an external device (the user's contact). Further examples are as described in Embodiment 5. In this case, the above program can be said to be a program that causes the server device (computer) to execute the above receiving step, the above storage step, and the above information processing step (preferably in addition to them, the above provision step).

[0180] This disclosure is not limited to the embodiments described above, and may be modified as appropriate without departing from its spirit. Furthermore, this disclosure may be implemented by combining the respective embodiments as appropriate.

[0181] Some or all of the above embodiments may also be described as follows, but are not limited to the following: <Note>

[0182] (Note 1) An input unit that receives imaging data captured by an imaging device installed so as to include the area of ​​excrement in a toilet bowl in the imaging range, A holding unit that temporarily holds the imaging data input by the input unit, The first analysis unit analyzes the first analysis target data, which is the imaging data input by the input unit, and outputs notification information to the monitor who monitors the user of the toilet. A second analysis unit analyzes the second analysis target data, which is imaging data input by the input unit and temporarily held by the holding unit, and outputs detailed information indicating the contents of the excretion. Equipped with, Excrement analyzer.

[0183] (Note 2) The first analysis unit performs an analysis to determine whether or not foreign matter other than feces and urine is included as a subject excluding the toilet bowl and the toilet bowl cleaning liquid, and outputs foreign matter information indicating whether or not foreign matter is included as at least part of the notification information. Excrement analysis device as described in Appendix 1.

[0184] (Note 3) The first analysis unit outputs the notification information by transmitting it to the terminal device used by the monitor. Excrement analyzer as described in Appendix 1 or 2.

[0185] (Note 4) The second analysis unit outputs the detailed information by transmitting it to a server device connected to the excrement analysis device via a network. Excrement analyzer as described in any one of the appendices 1 to 3.

[0186] (Note 5) The first analysis unit outputs the notification information by transmitting it to the server device. Excrement analysis device as described in Appendix 4.

[0187] (Note 6) The holding unit temporarily holds the analysis results from the first analysis unit as part of the second analysis target data. Excrement analyzer as described in any one of the appendices 1 to 5.

[0188] (Note 7) The first analysis unit obtains the notification information from the first analysis target data using a trained model that takes the first analysis target data as input and outputs the notification information. Excrement analyzer as described in any one of the appendices 1 to 6.

[0189] (Note 8) The second analysis unit uses a trained model that takes the second data to be analyzed as input and outputs the detailed information to obtain at least a portion of the detailed information from the second data to be analyzed. Excrement analyzer as described in any one of the appendices 1 to 7.

[0190] (Note 9) The second analysis unit processes the second analysis target data as an image to obtain at least a portion of the detailed information. Excrement analyzer as described in any one of the appendices 1 to 8.

[0191] (Note 10) The second analysis unit outputs information relating to at least one of the following as detailed information: urine flow rate or urination volume, number of defecations or stool volume per unit period, and defecation timing, which is the timing of the act of defecation. Excrement analyzer as described in any one of the appendices 1 to 9.

[0192] (Note 11) The second analysis unit outputs information indicating at least one of the following as detailed information: the decrease in urine flow rate or urination volume, the decrease in the number of bowel movements or stool volume per unit period, and the prolongation of the timing of defecation, which is the timing of the act of defecation. Excrement analysis device as described in Appendix 10.

[0193] (Note 12) The first analysis unit outputs at least one of the following pieces of information as part of the notification information: information indicating the usage status of the bidet installed on the toilet and information indicating that a person has sat on the toilet. Excrement analyzer as described in any one of the appendices 1 to 11.

[0194] (Note 13) The imaging device further comprises the aforementioned, Excrement analyzer as described in any one of the appendices 1 to 12.

[0195] (Note 14) The system comprises an excrement analysis device described in any one of the appendices 1 to 13, a terminal device used by the monitor connected to the excrement analysis device, and a server device connected to the excrement analysis device and the terminal device. 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 format that can be viewed from the terminal device. The terminal device includes a log generation unit that generates an excretion log based on the notification information received from the excretion analysis device and the detailed information stored in the server device. Analysis system.

[0196] (Note 15) A receiving unit that receives the detailed information from the excrement analysis device described in any one of the appendices 1 to 13, A storage unit that stores the detailed information received by the receiving unit, Information processing unit, Equipped with, The aforementioned detailed information includes at least information indicating the date and time of excretion, the type of excrement, and the shape of the stool. The information processing unit aggregates the detailed information for each shape of the stool. Server device.

[0197] (Note 16) A receiving unit that receives detailed information indicating the content of excrement, which is the result of analyzing the excrement in the toilet bowl from the image data captured by the toilet bowl, A storage unit that stores the detailed information received by the receiving unit, Information processing unit, Equipped with, The aforementioned detailed information includes at least information indicating the date and time of excretion, the type of excrement, and the shape of the stool. The information processing unit aggregates the detailed information for each shape of the stool. Server device.

[0198] (Note 17) The information processing unit analyzes the trend of changes in the shape of the stool over time. The server device described in Appendix 15 or 16.

[0199] (Note 18) The aforementioned detailed information includes information indicating the color of the stool, The information processing unit analyzes the trend of changes in the shape and color of the stool over time. The server device described in Appendix 15 or 16.

[0200] (Note 19) The system includes a providing unit that provides the processing results from the information processing unit to an external device. A server device as described in any one of the items 15 to 18 of the appendices.

[0201] (Note 20) The receiving unit receives address information associated with the detailed information, which indicates the address where the toilet user resides or the address of the location where the toilet is installed, and also receives cautionary information that warns of an infectious disease outbreak. The information processing unit analyzes the temporal trends of changes in bowel movements for each region indicated by the address information from the address information and the detailed information, and predicts the outbreak of the infectious disease for each region based on the results of the analysis and the warning information. A server device as described in any one of the items 17 to 19 of the appendix.

[0202] (Note 21) The information processing unit provides a provisioning unit that provides the results predicted for each region to the recipients associated with each region. The server device described in Appendix 20.

[0203] (Note 22) The receiving unit receives user information indicating the 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 also receives environmental information including climate information and infectious disease outbreak information indicating the results of an infectious disease outbreak. The information processing unit analyzes the trend of temporal changes in bowel movements for each user indicated by the user information, in accordance with the environmental information, from the user information, the address information, the environmental information, and the detailed information, and predicts the health status, including the presence of infectious diseases, for each user indicated by the user information based on the results of the analysis. A server device as described in any one of the items 17 to 19 of the appendix.

[0204] (Note 23) A receiving unit that receives detailed information indicating the content of excrement, which is the result of analyzing the excrement in the toilet bowl from imaging data captured by the toilet bowl; user information indicating the user of the toilet and address information indicating the address where the toilet user resides or the address where the toilet is installed, associated with the detailed information; and environmental information including climate information and infectious disease outbreak information indicating the result of an infectious disease outbreak. A storage unit that stores the detailed information, user information, address information, and environmental information received by the receiving unit, Information processing unit, Equipped with, The aforementioned detailed information includes at least information indicating the date and time of excretion, the type of excrement, and the shape of the stool. The information processing unit analyzes the trend of temporal changes in bowel movements for each user indicated by the user information, in accordance with the environmental information, from the user information, the address information, the environmental information, and the detailed information, and predicts the health status, including the presence of infectious diseases, for each user indicated by the user information based on the results of the analysis. Server device.

[0205] (Note 24) The user information includes contact information indicating the contact information of the user of the toilet, The information processing unit provides the results predicted for each user information to the contact information indicated for the user indicated by each user information, and includes a provisioning unit that provides the results predicted for each user information to the contact information indicated for that user, The server device described in Appendix 22 or 23.

[0206] (Note 25) The excrement analysis device inputs imaging data captured by an imaging device installed to include the area of ​​excrement in a toilet bowl within its imaging range, and The excrement analysis device includes a holding step in which it temporarily holds the imaging data input in the input 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 the monitor who monitors the user of the toilet in the first analysis step, The excrement analyzer analyzes the second analysis target data, which is imaging data input in the input step and temporarily held in the holding step, and outputs detailed information indicating the contents of the excrement in the second analysis step. Equipped with, Analysis method.

[0207] (Note 26) The server device receives the detailed information in a receiving step, The server device includes a storage step in which it stores the detailed information received in the receiving step, Information processing steps, The steps to be provided, Equipped with, The aforementioned detailed information includes at least information indicating the date and time of excretion, the type of excrement, and the shape of the stool. The information processing step involves the server device aggregating the detailed information for each shape of the stool, The provision step involves the server device providing the processing results from the information processing step to an external device. The analysis method described in Appendix 25.

[0208] (Note 27) A receiving step in which a server device receives detailed information indicating the content of excrement, which is the result of analyzing the excrement in the toilet bowl from the image data captured by the toilet bowl, The server device includes a storage step in which it stores the detailed information received in the receiving step, Information processing steps, The steps to be provided, Equipped with, The aforementioned detailed information includes at least information indicating the date and time of excretion, the type of excrement, and the shape of the stool. The information processing step involves the server device aggregating the detailed information for each shape of the stool, The provision step involves the server device providing the processing results from the information processing step to an external device. Analysis method.

[0209] (Note 28) The control computer installed in the excrement analysis device, An input step involves inputting imaging data captured by an imaging device installed to include the area of ​​excrement in a toilet bowl within the imaging range, and A holding step for temporarily holding the imaging data input in the input step, A first analysis step that analyzes the first analysis target data, which is the imaging data input in the above input step, and outputs notification information to the monitor who monitors the user of the toilet, A second analysis step analyzes the second analysis target data, which is imaging data input in the input step and temporarily held in the holding step, and outputs detailed information indicating the contents of the excretion. A program to execute.

[0210] (Note 29) To the aforementioned computer, The receiving step includes receiving detailed information which includes at least information indicating the date and time of excretion, the type of excrement, and the shape of the stool, A storage step for storing the detailed information received in the receiving step, An information processing step of aggregating the detailed information for each of the aforementioned defecation shapes, A providing step of providing the processing results from the information processing step to an external device, This is a program to execute, The program described in Appendix 28.

[0211] (Note 30) On the computer, A receiving step of receiving detailed information that indicates the content of excrement, which is the result of analyzing the excrement in the toilet bowl from imaging data captured by the toilet bowl, and which includes at least information indicating the date and time of excrement, the type of excrement, and the shape of the stool, A storage step for storing the detailed information received in the receiving step, An information processing step of aggregating the detailed information for each of the aforementioned defecation shapes, A providing step of providing the processing results from the information processing step to an external device, A program to execute. [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 Inter-box connection section 13. First external box 14a WiFi module 14b Bluetooth module 15a Motion sensor 15b Second Camera 16a Distance sensor 16b Camera 1 20 toilet bowls 21 Main unit 22 toilet seats 23 Toilet seat cover 30 Toilet with excrement analysis device 40 servers 41 Control Unit 42 Storage section 50, 80, 90 terminal devices 70 Server devices 70a Receiver 70b Storage section 70c Information Processing Unit 100 devices 101 Processors 102 memory 103 Communication Interface

Claims

1. A receiving unit that receives detailed information indicating the content of excrement, which is the result of analyzing the excrement in the toilet bowl from the image data captured by the toilet bowl, A storage unit that stores the detailed information received by the receiving unit, Information processing unit, The supply department, Equipped with, The aforementioned detailed information includes at least information indicating the date and time of excretion and the shape of the stool, The receiving unit receives address information associated with the detailed information, which indicates the address where the toilet user resides or the address of the location where the toilet is installed, and also receives cautionary information that warns of an infectious disease outbreak. The information processing unit aggregates the detailed information for each type of stool, analyzes the trend of temporal changes in the stool for each region indicated by the address information from the address information and the detailed information, and predicts the outbreak of the infectious disease for each region based on the results of the analysis and the warning information. The provisioning unit provides the results predicted for each region by the information processing unit to the recipient associated with each region. Server device.

2. The aforementioned detailed information includes information indicating the color of the stool, The information processing unit analyzes the trend of changes in the shape and color of the stool over time. The server device according to claim 1.

3. The providing unit provides the processing results from the information processing unit to an external device. The server device according to claim 1 or 2.

4. A receiving step in which a server device receives detailed information indicating the content of excrement, which is the result of analyzing the excrement in the toilet bowl from the image data captured by the toilet bowl, A storage step for storing the detailed information received in the receiving step, Information processing steps, The steps to be provided, Equipped with, The aforementioned detailed information includes at least information indicating the date and time of excretion and the shape of the stool, The receiving step includes receiving address information associated with the detailed information, which indicates the address where the toilet user resides or the address of the location where the toilet is installed, and receiving cautionary information that warns of an infectious disease outbreak. The information processing step aggregates the detailed information for each shape of the stool, analyzes the trend of temporal changes in the stool for each region indicated by the address information from the address information and the detailed information, and predicts the outbreak of the infectious disease for each region based on the results of the analysis and the warning information. The aforementioned provision step provides the results predicted for each region in the aforementioned information processing step to the recipient associated with each region. Analysis method.

5. On the computer, A receiving function that receives detailed information indicating the content of excrement, which is the result of analyzing the image data captured by the toilet bowl, A storage function that stores the detailed information received by the receiving function, Information processing function, The features provided, A program that makes this a reality. The aforementioned detailed information includes at least information indicating the date and time of excretion and the shape of the stool, The receiving function receives address information associated with the detailed information, which indicates the address where the toilet user resides or the address of the location where the toilet is installed, and also receives cautionary information that warns of an infectious disease outbreak. The information processing function aggregates the detailed information for each type of stool, analyzes the trend of temporal changes in the stool for each region indicated by the address information from the address information and the detailed information, and predicts the outbreak of the infectious disease for each region based on the results of the analysis and the warning information. The aforementioned provisioning function provides the results predicted for each region by the information processing function to the recipients associated with each region. program.

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