Information processing system

Abstract

To easily provide users with information regarding their health. [Solution] An information processing system according to one embodiment of the system is characterized by comprising: an acquisition means for acquiring sensor information detected by a sensor installed in any one of the water-related spaces such as a toilet, washroom, kitchen, or bathroom; a storage means for storing the sensor information; an estimation means for estimating the biological age of a user of the water-related space by referring to the sensor information stored in the storage means and fitting a model for estimating biological age to the sensor information; and an output means for outputting information indicating the biological age of the user estimated by the estimation means.

Description

[Technical Field]

[0001] The disclosed embodiment relates to an information processing system. [Background Art]

[0002] In recent years, a new health indicator called "biological age" has attracted attention in the healthcare industry. Unlike "chronological age", which represents the length of time elapsed since birth, biological age is an indicator representing biological health level that reflects an individual's physical function and the risk of disease and death. It has attracted attention not only in the medical community but also among health-conscious people around the world, and estimation of biological age through blood DNA analysis has been performed (see, for example, Patent Document 1). [Prior Art Literature] [Patent Literature]

[0003] [Patent Document 1] Japanese Unexamined Patent Application Publication No. 2022-142021 [Summary of the Invention] [Problem to be Solved by the Invention]

[0004] However, the above-mentioned conventional technology has room for improvement. In the above-mentioned conventional technology, since the user's biological information (such as blood) is used to estimate biological age, it is difficult to estimate biological age over time under the user's daily activities.

[0005] In view of the above points, it is a problem to easily provide information related to the user's health.

[0006] An object of the disclosed embodiment is to provide an information processing system that can easily provide information related to the user's health. [Means for Solving the Problem]

[0007] An information processing system according to one embodiment of the system is characterized by comprising: an acquisition means for acquiring sensor information detected by a sensor installed in any one of the water-related spaces such as a toilet, washroom, kitchen, or bathroom; a storage means for storing the sensor information; an estimation means for estimating the biological age of a user of the water-related space by referring to the sensor information stored in the storage means and fitting a model for estimating biological age to the sensor information; and an output means for outputting information indicating the biological age of the user estimated by the estimation means.

[0008] According to one embodiment of the information processing system, the biological age of a user is estimated based on sensor information detected by sensors installed in water-related spaces such as toilets that are used daily, and the estimated biological age is output to a mobile terminal or the like used by the user, making it easy to estimate the user's biological age. As a result, according to one embodiment of the information processing system, users can understand their own biological age simply by going about their daily lives, which can encourage behavioral changes aimed at maintaining the user's health.

[0009] In an information processing system according to one embodiment, the storage means stores the sensor information together with date and time information, and the output means outputs information indicating the change in the user's biological age.

[0010] According to an information processing system in one embodiment, users can be made aware of whether or not they are approaching old age based on changes in their biological age, thereby further encouraging behavioral changes in users.

[0011] In an information processing system according to one embodiment, the storage means stores the sensor information together with date and time information, the estimation means estimates the aging rate at the user's biological age, and the output means outputs information indicating the change in the aging rate at the user's biological age.

[0012] According to an information processing system in one embodiment, it is possible to understand the quality of a user's current lifestyle habits based on their aging rate derived from their biological age, thereby encouraging users to make behavioral changes that will lower their biological age.

[0013] In information processing according to one embodiment, the storage means stores information relating to the user's actual age, and the output means outputs information comparing the user's actual age and biological age.

[0014] According to an information processing system in one embodiment, the system outputs a comparison result between the user's actual age and the estimated biological age, allowing the user to easily understand whether the estimated biological age is good or bad, thereby further encouraging behavioral change. [Effects of the Invention]

[0015] According to one embodiment, information regarding the user's health can be easily provided. [Brief explanation of the drawing]

[0016] [Figure 1] Figure 1 shows an example of the overall configuration of an information processing system according to the embodiment. [Figure 2] Figure 2 shows an example of the processing content of the information processing system according to the first embodiment. [Figure 3] Figure 3 shows an example of the configuration of a cloud server according to the first embodiment. [Figure 4] Figure 4 shows an example of data displayed by the output unit according to the first embodiment. [Figure 5] Figure 5 shows an example of data displayed by the output unit according to the first embodiment. [Figure 6] Figure 6 shows an example of data displayed by the output unit according to the first embodiment. [Figure 7]FIG. 7 is a diagram showing an example of data displayed by the output unit according to the first embodiment. [Figure 8] FIG. 8 is a diagram showing an example of data displayed by the output unit according to the first embodiment. [Figure 9] FIG. 9 is a flowchart showing an example of information processing according to the first embodiment. [Figure 10] FIG. 10 is a flowchart showing an example of information processing according to the first embodiment. [Figure 11] FIG. 11 is a diagram for explaining processing contents of the information processing system according to the second embodiment. [Figure 12] FIG. 12 is a diagram showing an example of processing of an estimation unit according to the second embodiment. [Figure 13] FIG. 13 is a diagram showing an example of processing of an estimation unit according to the second embodiment. [Figure 14] FIG. 14 is a diagram showing an example of data displayed by the output unit according to the second embodiment. [Figure 15] FIG. 15 is a diagram showing an example of data displayed by the output unit according to the second embodiment. [Figure 16] FIG. 16 is a diagram showing an example of data displayed by the output unit according to the second embodiment. [Figure 17] FIG. 17 is a flowchart showing an example of information processing according to the second embodiment. [Figure 18] FIG. 18 is a flowchart showing an example of information processing according to the second embodiment. [Figure 19] FIG. 19 is a diagram for explaining processing contents of the information processing system according to the third embodiment. [Figure 20] FIG. 20 is a diagram showing an example of processing of an estimation unit according to the third embodiment. [Figure 21] FIG. 21 is a diagram showing an example of processing of an estimation unit according to the third embodiment. [Figure 22] FIG. 22 is a diagram showing an example of data displayed by the output unit according to the third embodiment. [Figure 23]Figure 23 shows an example of data displayed by the output unit according to the third embodiment. [Figure 24] Figure 24 shows an example of data displayed by the output unit according to the third embodiment. [Figure 25] Figure 25 is a flowchart showing an example of information processing according to the third embodiment. [Figure 26] Figure 26 is a flowchart showing an example of information processing according to the third embodiment. [Figure 27] Figure 27 is a diagram illustrating the processing content of the information processing system according to the fourth embodiment. [Figure 28] Figure 28 shows an example of the processing of the estimation unit according to the fourth embodiment. [Figure 29] Figure 29 shows an example of the processing of the estimation unit according to the fourth embodiment. [Figure 30] Figure 30 shows an example of data displayed by the output unit according to the fourth embodiment. [Figure 31] Figure 31 shows an example of data displayed by the output unit according to the fourth embodiment. [Figure 32] Figure 32 is a flowchart showing an example of information processing according to the fourth embodiment. [Figure 33] Figure 33 is a flowchart showing an example of information processing according to the fourth embodiment. [Modes for carrying out the invention]

[0017] The embodiments of the information processing system disclosed herein will be described in detail below with reference to the attached drawings. However, the present invention is not limited to the embodiments described below. Furthermore, the embodiments can be combined as appropriate.

[0018] [Introduction] (Example of overall structure) Before providing a detailed description of the processes performed in the information processing systems according to the first to fourth embodiments, we will first describe an example of the overall system configuration common to the information processing systems according to the first to fourth embodiments. Figure 1 is a diagram showing an example of the overall configuration of the information processing system according to the embodiment.

[0019] In the example shown in Figure 1, the information processing system 1 according to this embodiment includes a cloud server 10 that manages the entire system, sensor devices and external terminals that generate input information 20, which is information about users that is input to the cloud server 10, and a user terminal 30. In the information processing system 1, the cloud server 10, the sensor devices and external terminals, and the user terminal 30 are each connected in a way that allows them to communicate with each other.

[0020] Cloud server 10 is an information processing device that estimates a user's biological age using biometric data acquired in their daily life, and is implemented using server devices, cloud systems, etc.

[0021] The cloud server 10 estimates the user's biological age based on input information 20, which is, for example, information measured by sensor devices installed in areas such as bathrooms and kitchens that the user uses in their daily life. The cloud server 10 then generates content related to the estimated biological age and outputs it to the user terminal 30.

[0022] Input information 20 is information about the user that is entered into the cloud server 10 in order to estimate the user's biological age. This includes information measured by sensor devices installed in bathrooms and other areas that the user uses in their daily life, information measured by devices owned by the user such as smartwatches, information on sleep duration and exercise duration manually entered by the user into their device, and blood information measured by external organizations.

[0023] For example, input information 20 is data measured by a sensor device or external terminal that measures data about the user, and is automatically entered into the cloud server 10 at predetermined intervals, such as each time data is measured or once a day. For example, input information 20 is information indicating the results of a health checkup or other diagnostic test that is manually entered by the user into an external terminal, and is entered into the cloud server 10 from the external terminal.

[0024] Here, as shown in Figure 1, the input information 20 includes, for example, water-related space sensor information 21, external terminal sensor information 22, and external terminal input information 23. Each of these pieces of information will be explained in turn below.

[0025] First, let's explain the water-related space sensor information 21. Before giving a detailed explanation of the water-related space sensor information 21, let's briefly explain the definitions of terms used in this application. A water-related space is a space that includes water-related equipment, such as a toilet, bathroom, washroom, or kitchen. For example, water-related equipment is a concept that includes equipment related to water and the functions they have (are installed in). For example, water-related equipment includes various equipment and functions installed in a water-related space. For example, water-related equipment includes toilets, urinals, bathrooms, bathtubs, washbasins (vanity units), and other equipment related to sanitary spaces, as well as various water-related devices such as kitchens. For example, water-related equipment includes toilet equipment, bathroom equipment, washbasin equipment, kitchen equipment, and lighting equipment and ventilation fans placed on the ceiling or walls of a water-related space.

[0026] Furthermore, plumbing fixtures may include functional devices that perform predetermined functions using sensors or the like that detect things related to the plumbing space. For example, plumbing fixtures may include functional devices that realize various functions related to the plumbing space using sensors or the like. In the case of toilets, bathrooms, washbasins, kitchens, etc. that have multiple functions, each component that realizes the multiple functions may be referred to as a "functional device," and the toilets, bathrooms, washbasins, kitchens, etc. may be referred to as "plumbing fixtures."

[0027] For example, the information processing system 1 according to the embodiment shown in Figure 1 has a toilet 211, a bathroom 212, a washbasin 213, and a kitchen 214 as a water-related space. In Figure 1, the toilet 211, bathroom 212, washbasin 213, and kitchen 214 are shown as an example of a water-related space, but other water-related spaces may also be included.

[0028] Toilet 211 is a water-related space used by toilet users for excretion, and is used to collect usage data including information about excretion by users (excretion data), biometric data, and log data. Toilet 211 is equipped with a toilet device 2111 and a toilet sensor 2112. For example, at least one of the toilet device 2111 or the toilet sensor 2112 transmits user usage data related to toilet 211 to the cloud server 10.

[0029] Furthermore, toilet 211 collects user usage data related to toilet 211 through devices such as toilet equipment 2111 and toilet sensor 2112. For example, toilet 211 collects various information such as log data including toilet log data, information on the user's daily use, the user's health status derived from the daily use information, sensing information, and advanced health status.

[0030] The toilet device 2111 is a so-called toilet (futon), remote control device, etc., and is a device used by toilet users to perform the act of defecation. For example, if the toilet device 2111 has a waste detection function, it may be equipped with a waste sensor used for the waste detection function.

[0031] The toilet device 2111 can communicate with other devices such as the cloud server 10 via a communication unit implemented by a communication device, communication circuit, etc. The toilet device 2111 is connected to a predetermined network such as the Internet by wired or wireless connection and transmits and receives information with other devices. The toilet device 2111 may be connected to other devices in a communicative manner by predetermined wireless communication functions such as mobile communication or Wi-Fi (registered trademark). Alternatively, the toilet device 2111 may be connected to other devices in a communicative manner by Bluetooth (registered trademark) functions such as BLE (Bluetooth Low Energy), for example, through communication via a gateway (GW).

[0032] The toilet device 2111 is a plumbing device (water-related equipment) that is connected to the cloud server 10 via a predetermined network in a way that allows it to communicate with the cloud server 10. For example, the toilet device 2111 sends and receives information to and from the cloud server 10 via the predetermined network. For example, the toilet device 2111 sends usage data regarding the use of the toilet 211 to the cloud server 10.

[0033] For example, the toilet device 2111 transmits usage data such as excretion data, biometric data, and log data to the cloud server 10. The toilet device 2111 may also transmit the usage data to the cloud server 10 along with the date and time information on when the usage data was acquired. The toilet device 2111 may also transmit usage data corresponding to a request from the cloud server 10 to the cloud server 10 in response to a request from the cloud server 10.

[0034] Furthermore, the toilet device 2111 collects usage data for each user of the plumbing equipment who uses the toilet. The toilet device 2111 may also have a function to authenticate (identify) the user who uses the toilet 211. The toilet device 2111 may use an account identifier (user ID, etc.) received from a remote control device or the like that accepts toilet operations from the plumbing equipment user to identify which of the registered users the user is. For example, the toilet device 2111 associates the collected usage data with the date and time the usage data was acquired and an account identifier that identifies the user corresponding to the usage data, and sends it to the cloud server 10. In this case, if the toilet device 2111 receives a user designation from the cloud server 10, it may send the usage data corresponding to that user to the cloud server 10.

[0035] The toilet sensor 2112 is a sensor device that detects the use of the toilet 211 by a user. For example, the toilet sensor 2112 may be a sensor device mounted on the toilet unit 2111. For example, the toilet sensor 2112 may be a feces sensor used for a fecal matter detection function. For example, the toilet sensor 2112 may be a sensor device that detects (receives) operations such as flushing of the toilet unit 2111.

[0036] For example, the toilet sensor 2112 may be a sensor device such as a sensor that detects the use of the toilet equipment 2111. For example, the toilet sensor 2112 may be a sensor device such as a sensor that detects when a user enters or leaves the toilet 211. For example, the toilet sensor 2112 may be a sensor device such as a sensor that detects the duration of use of the toilet 211 by a user. For example, the toilet sensor 2112 may be a sensor device such as a seating sensor that detects when someone sits on the toilet seat of the toilet equipment 2111. The toilet sensor 2112 may be a flush button having large and small types that detect the use of either the large or small toilet.

[0037] The above is merely an example, and the toilet sensor 2112 may be a sensor device such as a sensor provided separately from the toilet device 2111. For example, the toilet sensor 2112 may be a sensor device such as a pyroelectric sensor using infrared signals or a μ (microwave) sensor (such as a motion sensor).

[0038] The toilet sensor 2112 can communicate with other devices such as the cloud server 10 via a communication unit implemented by a communication device, communication circuit, etc. The toilet sensor 2112 is connected to a predetermined network such as the Internet by wired or wireless connection and transmits and receives information with other devices. The toilet sensor 2112 may also be connected to other devices via a predetermined wireless communication function such as Wi-Fi or Bluetooth.

[0039] For example, the toilet sensor 2112 sends and receives information to and from the cloud server 10 via a predetermined network. For example, the toilet sensor 2112 sends usage data regarding the use of the toilet 211 to the cloud server 10.

[0040] For example, the toilet sensor 2112 transmits usage data such as excretion data, biometric data, and log data to the cloud server 10. The toilet sensor 2112 may also transmit the usage data to the cloud server 10 along with the date and time information on when the usage data was acquired. The toilet sensor 2112 may also transmit usage data corresponding to a request from the cloud server 10 to the cloud server 10 in response to a request from the cloud server 10.

[0041] Furthermore, the toilet sensor 2112 collects usage data for each user of the plumbing equipment. The toilet sensor 2112 may have a storage means (storage device, etc.) for managing (registering) usage data for each user of the plumbing equipment. The toilet sensor 2112 may have a function for authenticating (identifying) the user who uses the toilet 211. The toilet sensor 2112 may use an account identifier (user ID, etc.) received from a remote control device, etc., that accepts operations related to the toilet by the toilet user (plumbing equipment user) to identify which of the registered users the user is.

[0042] For example, the toilet sensor 2112 associates the collected usage data with the date and time the usage data was acquired and an account identifier that identifies the user corresponding to the usage data, and sends it to the cloud server 10. In this case, if the toilet sensor 2112 receives a user designation from the cloud server 10, it may also send the usage data corresponding to that user to the cloud server 10. Alternatively, instead of measuring the user's weight and identifying the user ID in cooperation with the toilet device 2111, the toilet sensor 2112 may send data determining whether the user is an adult or a child as part of the usage data to the cloud server 10. For example, the toilet sensor 2112 may determine the user is an adult if their weight is above a predetermined weight, and determine the user is a child if their weight is below a predetermined weight.

[0043] Bathroom 212 is configured for use by bathroom users (users of plumbing fixtures) to perform bathing activities, and is a plumbing space where usage data, including biometric data and log data such as bathing time and bathing temperature, is collected. Bathroom 212 is equipped with bathroom devices 2121, bathroom sensors 2122, etc. For example, bathroom 212 transmits user usage data related to bathroom 212 to the cloud server 10 from at least one of the devices such as bathroom devices 2121 and bathroom sensors 2122. Note that bathroom 212 may have multiple bathroom devices 2121 and multiple bathroom sensors 2122.

[0044] Bathroom 212 collects user usage data related to the bathroom 212 using devices such as bathroom equipment 2121 and bathroom sensors 2122. For example, bathroom 212 collects various information such as bathroom temperature, faucet water temperature, user's heart rate, and the user's center of gravity.

[0045] Bathroom equipment 2121 is a so-called bathtub, shower, etc., and is equipment used by bathroom users (users of plumbing equipment) to perform the act of bathing. For example, if bathroom equipment 2121 has a bathroom temperature detection function, it may be equipped with a bathroom sensor 2122, which is a temperature sensor used for the bathroom temperature detection function. For example, if bathroom equipment 2121 has a faucet water temperature detection function, it may be equipped with a bathroom sensor 2122, which is a temperature sensor used for the faucet water temperature detection function.

[0046] The bathroom device 2121 can communicate with other devices such as the cloud server 10 via a communication unit implemented by a communication device, communication circuit, etc. The bathroom device 2121 is connected to a predetermined network such as the Internet by wired or wireless connection and transmits and receives information with other devices. The bathroom device 2121 may also be connected to other devices via a predetermined wireless communication function such as Wi-Fi or Bluetooth.

[0047] The bathroom device 2121 is a plumbing device (water-related equipment) that is connected to the cloud server 10 via a predetermined network in a way that allows it to communicate with the cloud server 10. For example, the bathroom device 2121 sends and receives information to and from the cloud server 10 via the predetermined network. For example, the bathroom device 2121 sends usage data regarding the use of the bathroom 212 to the cloud server 10.

[0048] For example, the bathroom device 2121 transmits usage data such as biometric data and log data to the cloud server 10. The bathroom device 2121 may transmit the usage data to the cloud server 10 along with the date and time information on when the usage data was acquired. The bathroom device 2121 may also transmit usage data corresponding to a request from the cloud server 10 to the cloud server 10 in response to a request from the cloud server 10.

[0049] Furthermore, the bathroom device 2121 collects usage data for each user of the plumbing equipment. The bathroom device 2121 may also have a function to authenticate (identify) the user using the bathroom 212. The bathroom device 2121 may use an account identifier (user ID, etc.) received from a remote control device or the like that accepts operations related to the bathroom by the bathroom user (user of plumbing equipment) to identify which of the registered users the user is. For example, the bathroom device 2121 associates the collected usage data with the date and time the usage data was acquired and an account identifier that identifies the user corresponding to the usage data, and sends it to the cloud server 10. In this case, if the bathroom device 2121 receives a user designation from the cloud server 10, it may send the usage data corresponding to that user to the cloud server 10.

[0050] The bathroom sensor 2122 is a sensor device that detects the user's use of the bathroom 212. For example, the bathroom sensor 2122 may be a sensor device mounted on the bathroom device 2121. For example, the bathroom sensor 2122 may be a temperature sensor used for a bathroom temperature detection function. For example, the bathroom sensor 2122 may be a temperature sensor used for a faucet water temperature detection function. For example, the bathroom sensor 2122 may be an image sensor that detects the position of the user's center of gravity when the user moves within the bathroom.

[0051] For example, the bathroom sensor 2122 may be a sensor device such as a sensor that detects the use of the bathroom equipment 2121. For example, the bathroom sensor 2122 may be a sensor device such as a sensor that detects when a user enters or leaves the bathroom 212. For example, the bathroom sensor 2122 may be a sensor device such as a sensor that detects the duration of use of the bathroom 212 by a user. For example, the bathroom sensor 2122 may be a sensor device such as a motion sensor that detects when someone enters the bathroom equipment 2121.

[0052] The above is merely an example, and the bathroom sensor 2122 may be a sensor device such as a sensor provided separately from the bathroom device 2121. For example, the bathroom sensor 2122 may be a pyroelectric sensor using infrared signals, an image sensor using a camera, a microwave sensor, or other sensor device (such as a motion sensor).

[0053] The bathroom sensor 2122 can communicate with other devices such as the cloud server 10 via a communication unit implemented by a communication device, communication circuit, etc. The bathroom sensor 2122 is connected to a predetermined network such as the Internet by wired or wireless connection and transmits and receives information with other devices. The bathroom sensor 2122 may also be connected to other devices via a predetermined wireless communication function such as Wi-Fi or Bluetooth.

[0054] The bathroom sensor 2122 is a functional device (water-related equipment) that is connected to the cloud server 10 via a predetermined network in a way that allows it to communicate with the cloud server 10. For example, the bathroom sensor 2122 sends and receives information to and from the cloud server 10 via the predetermined network. For example, the bathroom sensor 2122 sends usage data regarding the use of the bathroom 212 to the cloud server 10.

[0055] For example, the bathroom sensor 2122 transmits usage data such as biometric data and log data to the cloud server 10. The bathroom sensor 2122 may also transmit the usage data to the cloud server 10 along with the date and time information on when the usage data was acquired. The bathroom sensor 2122 may also transmit usage data corresponding to a request from the cloud server 10 to that cloud server 10 in response to a request from that server.

[0056] Furthermore, the bathroom sensor 2122 collects usage data for each user of plumbing fixtures. The bathroom sensor 2122 may have a storage means (storage device, etc.) for managing (registering) usage data for each user of plumbing fixtures. The bathroom sensor 2122 may have a function for authenticating (identifying) users who use the bathroom 212. The bathroom sensor 2122 may use an account identifier (user ID, etc.) received from a remote control device, etc., that accepts operations related to the bathroom by the bathroom user (user of plumbing fixtures) to identify which of the registered users the user is.

[0057] For example, the bathroom sensor 2122 associates the collected usage data with the date and time the usage data was acquired and an account identifier that identifies the user corresponding to the usage data, and sends it to the cloud server 10. In this case, if the bathroom sensor 2122 receives a user designation from the cloud server 10, it may also send the usage data corresponding to that user to the cloud server 10.

[0058] Furthermore, the bathroom sensor 2122 may communicate with the bathroom device 2121 using wireless communication and control the water temperature of the bathroom device 2121. Alternatively, instead of measuring the user's weight and identifying the user ID, the bathroom sensor 2122 may send data determining whether the user is an adult or a child as usage data to the cloud server 10. For example, the bathroom sensor 2122 may determine the user is an adult if their weight is above a predetermined weight, and determine the user is a child if their weight is below the predetermined weight. Alternatively, the bathroom sensor 2122 may generate data determining whether the user is an adult or a child using image data of the user.

[0059] The bathroom sensor 2122 controls the water temperature of the bathroom device 2121 based on the mode notified by the cloud server 10. For example, when the bathroom sensor 2122 detects that a user is using the bathroom device 2121, it communicates with the cloud server 10 to obtain whether the mode corresponding to the current time is daytime mode or nighttime mode. Alternatively, the bathroom sensor 2122 may send the user ID to the cloud server 10 to obtain the mode corresponding to the time of day and user ID.

[0060] The bathroom sensor 2122 detects when a user enters the bathroom 212 and, if the current time is within the daytime period, sets the temperature of the hot water supplied (discharged) from the bathroom device 2121 to the first temperature (45 degrees). On the other hand, if the current time is within the nighttime period, the bathroom sensor 2122 sets the temperature of the hot water supplied (discharged) from the bathroom device 2121 to the second temperature (35 degrees).

[0061] This concludes the explanation regarding bathroom 212.

[0062] The washbasin 213 is configured for use by washbasin users and is a water-related space where measurement data, including biometric data and log data such as washbasin usage time, is collected. The washbasin 213 is equipped with a washbasin device (washbasin equipment) 2131, a washbasin sensor 2132, etc. For example, the washbasin 213 transmits measurement data of the user regarding the washbasin from at least one of the devices such as the washbasin device 2131 and the washbasin sensor 2132 to the cloud server 10. Note that the washbasin 213 may have multiple washbasin devices 2131 and multiple washbasin sensors 2132.

[0063] The washbasin 213 collects user measurement data related to the washbasin 213 using devices such as the washbasin device 2131 and the washbasin sensor 2132. For example, the washbasin 213 collects various information such as facial expressions and blood circulation in the face.

[0064] The washbasin device 2131 is a so-called washbasin, smart mirror, etc., and is a device used by the user of the washbasin to perform the act of using the washbasin. For example, if the washbasin device 2131 has a function to detect the user's facial expression, it may be equipped with a washbasin sensor 2132, which is an image sensor used for the function to detect the user's facial expression. For example, if the washbasin device 2131 has a function to detect the blood flow of the user's face, it may be equipped with a washbasin sensor 2132, which is a blood flow sensor used for the function to detect the blood flow of the user's face.

[0065] The washbasin unit 2131 can communicate with other devices such as the cloud server 10 via a communication unit implemented by a communication device, communication circuit, etc. The washbasin unit 2131 is connected to a predetermined network such as the Internet by wired or wireless connection and transmits and receives information with other devices. The washbasin unit 2131 may also be connected to other devices via predetermined wireless communication functions such as Wi-Fi or Bluetooth.

[0066] The washbasin unit 2131 is a plumbing device (water-related equipment) that is connected to the cloud server 10 via a predetermined network in a way that allows it to communicate with the cloud server 10. For example, the washbasin unit 2131 sends and receives information to and from the cloud server 10 via the predetermined network. For example, the washbasin unit 2131 sends measurement data related to the use of the washbasin to the cloud server 10.

[0067] For example, the washbasin device 2131 transmits measurement data such as biometric data and log data to the cloud server 10. The washbasin device 2131 may transmit the measurement data to the cloud server 10 along with the date and time information on when the measurement data was acquired. The washbasin device 2131 may also transmit measurement data corresponding to a request from the cloud server 10 to the cloud server 10 in response to a request from the cloud server 10.

[0068] Furthermore, the washbasin device 2131 collects measurement data for each user of the plumbing equipment. The washbasin device 2131 may also have a function to authenticate (identify, distinguish) the user using the washbasin 213. The washbasin device 2131 may use a personal identification number received from a remote control device or the like that accepts operations related to the washbasin by the washbasin user (plumbing equipment user) to identify which of the registered users that user is.

[0069] For example, the washbasin device 2131 associates the collected measurement data with the date and time the measurement data was acquired and a personal identification number that identifies the user corresponding to the measurement data, and sends it to the cloud server 10. In this case, if the washbasin device 2131 receives a user designation from the cloud server 10, it may also send the measurement data corresponding to that user to the cloud server 10.

[0070] The washbasin sensor 2132 is a sensor device that detects the use of the washbasin 213 by a user. For example, the washbasin sensor 2132 may be a sensor device mounted on the washbasin unit 231. For example, the washbasin sensor 2132 may be an image sensor used for detecting the user's facial expressions. For example, the washbasin sensor 2132 may be a blood flow sensor used for detecting the blood circulation in the user's face.

[0071] For example, the sink sensor 2132 may be a sensor device such as a sensor that detects the use of the sink unit 2131. For example, the sink sensor 2132 may be a sensor device such as a sensor that detects when a user enters or leaves the sink 213. For example, the sink sensor 2132 may be a sensor device such as a sensor that detects the usage time of the sink 213 by a user. For example, the sink sensor 2132 may be a sensor device such as a motion sensor that detects the use of the sink on the sink unit 2131.

[0072] The above is merely an example, and the sink sensor 2132 may be a sensor device other than the sink unit 2131. For example, the sink sensor 2132 may be a sensor device (such as a motion sensor) such as a pyroelectric sensor using infrared signals or a μ (microwave) sensor.

[0073] The sink sensor 2132 can communicate with other devices such as the cloud server 10 via a communication unit implemented by a communication device, communication circuit, etc. The sink sensor 2132 is connected to a predetermined network such as the Internet by wired or wireless connection and transmits and receives information with other devices. The sink sensor 2132 may also be connected to other devices via a predetermined wireless communication function such as Wi-Fi or Bluetooth.

[0074] The sink sensor 2132 is a functional device (bathroom equipment) that is connected to the cloud server 10 via a predetermined network in a way that allows it to communicate with the cloud server 10. For example, the sink sensor 2132 sends and receives information to and from the cloud server 10 via the predetermined network. For example, the sink sensor 2132 sends measurement data regarding the use of the sink to the cloud server 10.

[0075] For example, the sink sensor 2132 transmits measurement data such as biometric data and log data to the cloud server 10. The sink sensor 2132 may also transmit the measurement data to the cloud server 10 along with the date and time information on when the measurement data was acquired. The sink sensor 2132 may also transmit measurement data corresponding to a request from the cloud server 10 to that cloud server 10 in response to a request from that server.

[0076] Furthermore, the washbasin sensor 2132 collects measurement data for each user of the plumbing equipment. The washbasin sensor 2132 may have a storage means (storage device, etc.) for managing (registering) measurement data for each user of the plumbing equipment. The washbasin sensor 2132 may have a function for authenticating (identifying, distinguishing) the user who uses the washbasin 213. The washbasin sensor 2132 may use a personal identification number received from a remote control device, etc., that receives operations related to the washbasin by the washbasin user (plumbing equipment user) to identify which of the registered users the user is.

[0077] For example, the sink sensor 2132 associates the collected measurement data with the date and time the measurement data was acquired and a personal identification number that identifies the user corresponding to the measurement data, and transmits it to the cloud server 10. In this case, if the sink sensor 2132 receives a user designation from the cloud server 10, it may also transmit the measurement data corresponding to that user to the cloud server 10.

[0078] This concludes the explanation regarding the washbasin 213.

[0079] Kitchen 214 is a water-related space configured for use by kitchen users to perform activities such as cooking, and measurement data including biometric data, food ingredient data, and log data such as kitchen usage time are collected. Kitchen 214 is equipped with a counter unit 2141, kitchen sensors 2142, etc. For example, kitchen 214 transmits measurement data of the user regarding kitchen use from at least one of the devices such as the counter unit 2141 and kitchen sensors 2142 to the cloud server 10. Note that kitchen 214 may have multiple counter units 2141 and multiple kitchen sensors 2142.

[0080] Kitchen 214 collects information about the ingredients used by the user in cooking, as well as measurement data of the user, through devices such as the counter unit 2141 and the kitchen sensor 2142. For example, kitchen 214 collects information indicating the ingredients used by the user in cooking and the contents of the dish, as well as various information about the user's facial expressions, blood circulation in their face, etc.

[0081] The counter unit 2141 is a counter used by users for cooking in a kitchen, and is a device used by users to prepare ingredients and meals. For example, the counter unit 2141 may be equipped with a kitchen sensor 2142, which is an image sensor used to detect ingredients placed on the counter unit 2141 by the user as ingredients to be used for cooking. For example, if the counter unit 2141 is to detect the user's health condition, the counter unit 2141 may be equipped with a kitchen sensor 2142, which is a blood flow sensor used for facial blood circulation detection.

[0082] The counter unit 2141 can communicate with other devices such as the cloud server 10 via a communication unit implemented by a communication device, communication circuit, etc. The counter unit 2141 is connected to a predetermined network such as the Internet by wired or wireless connection and transmits and receives information with other devices. The counter unit 2141 may also be connected to other devices via a predetermined wireless communication function such as Wi-Fi or Bluetooth.

[0083] The counter unit 2141 is a plumbing device (water-related equipment) that is connected to the cloud server 10 via a predetermined network. For example, the counter unit 2141 sends and receives information to and from the cloud server 10 via the predetermined network. For example, the counter unit 2141 sends measurement data related to kitchen usage to the cloud server 10.

[0084] For example, the counter unit 2141 transmits measurement data such as food ingredient data, biological data, and log data to the cloud server 10. The counter unit 2141 may also transmit the measurement data to the cloud server 10 along with the date and time information on when the measurement data was acquired. The counter unit 2141 may also transmit the measurement data corresponding to the request to the cloud server 10 in response to a request from the cloud server 10.

[0085] Furthermore, the counter unit 2141 collects measurement data for each user of the plumbing fixtures. The counter unit 2141 may also have a function to authenticate (identify, distinguish) the user using the kitchen 214. The counter unit 2141 may use a personal identification number received from a remote control device or the like that accepts operations related to the kitchen by the kitchen user (user of plumbing fixtures) to identify which of the registered users that user is.

[0086] For example, the counter unit 2141 associates the collected measurement data with the date and time the measurement data was acquired and a personal identification number that identifies the user corresponding to the measurement data, and sends it to the cloud server 10. In this case, if the counter unit 2141 receives a user designation from the cloud server 10, it may also send the measurement data corresponding to that user to the cloud server 10.

[0087] The kitchen sensor 2142 is a sensor device that detects the user's use of the kitchen 214. For example, the kitchen sensor 2142 may be a sensor device mounted on the counter unit 2141. For example, the kitchen sensor 2142 may be an image sensor used to detect ingredients used by the user for cooking. Also, for example, if the kitchen sensor 2142 is used to detect the user's health condition, it may be a blood flow sensor used for detecting blood circulation in the user's face.

[0088] For example, the kitchen sensor 2142 may be a sensor device such as a sensor that detects the use of the counter unit 2141. For example, the kitchen sensor 2142 may be a sensor device such as a sensor that detects when a user enters or leaves the kitchen 214. For example, the kitchen sensor 2142 may be a sensor device such as a sensor that detects the duration of use of the kitchen 214 by a user. For example, the kitchen sensor 2142 may be a sensor device such as a motion sensor that detects kitchen use of the counter unit 2141.

[0089] The above is merely an example, and the kitchen sensor 2142 may be a sensor device such as a sensor device provided separately from the counter unit 2141. For example, the kitchen sensor 2142 may be a sensor device such as a pyroelectric sensor using infrared signals or a μ (microwave) sensor (such as a motion sensor).

[0090] The kitchen sensor 2142 can communicate with other devices such as the cloud server 10 via a communication unit implemented by a communication device, communication circuit, etc. The kitchen sensor 2142 is connected to a predetermined network such as the Internet by wired or wireless connection and transmits and receives information with other devices. The kitchen sensor 2142 may also be connected to other devices via a predetermined wireless communication function such as Wi-Fi or Bluetooth.

[0091] The kitchen sensor 2142 is a functional device (water-related equipment) that is connected to the cloud server 10 via a predetermined network in a communicative manner. For example, the kitchen sensor 2142 sends and receives information to and from the cloud server 10 via the predetermined network. For example, the kitchen sensor 2142 sends measurement data related to kitchen usage to the cloud server 10.

[0092] For example, the kitchen sensor 2142 transmits measurement data such as food ingredient data, biometric data, and log data to the cloud server 10. The kitchen sensor 2142 may also transmit the measurement data to the cloud server 10 along with the date and time information on when the measurement data was acquired. The kitchen sensor 2142 may also transmit measurement data corresponding to a request from the cloud server 10 to the cloud server 10 in response to a request from the cloud server 10.

[0093] Furthermore, the kitchen sensor 2142 collects measurement data for each user of the plumbing equipment. The kitchen sensor 2142 may have a storage means (memory device, etc.) for managing (registering) measurement data for each user of the plumbing equipment. The kitchen sensor 2142 may have a function for authenticating (identifying, distinguishing) users who use the kitchen 214. The kitchen sensor 2142 may use a personal identification number received from a remote control device, etc., that receives operations related to the counter unit 2141 by the kitchen user (plumbing equipment user) to identify which of the registered users the user is.

[0094] For example, the kitchen sensor 2142 associates the collected measurement data with the date and time the measurement data was acquired and a personal identification number that identifies the user corresponding to the measurement data, and sends it to the cloud server 10. In this case, if the kitchen sensor 2142 receives a user designation from the cloud server 10, it may also send the measurement data corresponding to that user to the cloud server 10.

[0095] This concludes the explanation regarding Kitchen 214.

[0096] In the following descriptions of the first to fourth embodiments, when describing water-related spaces such as toilets 211, bathrooms 212, washbasins 213, and kitchens 214 without distinction, they may be referred to as "water-related spaces." Similarly, when describing water-related equipment (water-related fixtures) such as toilets 2111, bathrooms 2121, washbasins 2131, and counter units 2141 without distinction, they may be referred to as "water-related equipment."

[0097] The water-related space sensor information 21 is information such as biometric data and food data measured by water-related sensor devices installed in the water-related spaces that users use in their daily lives, and is constantly input into the cloud server 10 according to the user's lifestyle.

[0098] Next, we will explain the external terminal sensor information 22. The external terminal sensor information 22 is sensor information measured by sensors on external terminals that the user uses in their daily life, such as sensor information acquired by information processing terminals such as smartwatches and smart scales.

[0099] For example, the external terminal sensor information 22 is biometric data such as heart rate, sleep duration, exercise level, and body composition measured by health devices such as smartwatches and smart scales, and is sensor information measured in the user's daily life.

[0100] Next, we will explain the external terminal input information 23. This is information entered into external terminals that the user uses in their daily life, such as computers, tablet devices, smartphones, and other information processing terminals that the user owns.

[0101] For example, the external terminal input information 23 includes information related to general health checkups, such as the user's height, weight, gender, and eating habits, entered into the user's computer, as well as data such as blood information and biological age measured by an external organization, and is related to the user's health. For example, the external terminal input information 23 is information entered into a health-related application installed on the user's smartphone, and includes information that cannot be obtained by sensor devices, such as eating history at restaurants.

[0102] The user terminal 30 is a device owned by the user whose biological age is to be estimated, and can be a smartphone, computer, tablet, etc. For example, the user terminal 30 receives the biological age estimated by the cloud server 10, as well as content related to biological age, from the cloud server 10 and displays it on the screen.

[0103] Regarding the information processing system 1 shown in Figure 1, the external terminals described in the external terminal sensor information 22 and external terminal input information 23 may be the same terminal or different terminals. Also, regarding the information processing system 1 shown in Figure 1, the aforementioned external terminal and user terminal 30 may be the same terminal or different terminals. In other words, in the information processing system 1, if the terminal is a smartwatch or the like, it can process the sensor device that measures the user's biometric data, process the input information from the user, and process the content related to biological age transmitted from the cloud server 10, so the external terminal and user terminal 30 may be realized by a single smartwatch.

[0104] (Problems with conventional technology) Next, I will explain the problems with conventional technology. As mentioned earlier, unlike "chronological age," which represents the length of time since birth, biological age is an indicator that represents a person's biological health status, reflecting their physical function and disease / mortality risk. It is attracting attention not only from the medical community but also from health-conscious people around the world, and biological age is being estimated through blood DNA analysis.

[0105] Here, estimating biological age requires not only DNA information but also an understanding of "what kind of environment" and "how the individual is living," and it is considered desirable to interpret multiple phenotypic data comprehensively and over time.

[0106] However, conventional technologies use the user's blood to estimate biological age, requiring the collection of the user's blood over time in order to estimate biological age over time. Therefore, there is a need for a technology that can estimate biological age easily and with minimal burden on the user.

[0107] (Processing details of Information Processing System 1) Therefore, in view of the aforementioned problems, the information processing system 1 according to this embodiment estimates the user's biological age using data acquired by a sensor device installed in the bathroom or kitchen area that the user uses in their daily life. As a result, the information processing system 1 can easily estimate the user's biological age.

[0108] In the following, we will describe the information processing systems 1 according to this embodiment, from the information processing system 1A according to the first embodiment to the information processing system 1D according to the fourth embodiment, and explain in order the processing content related to biological age performed in each embodiment.

[0109] [First Embodiment] (Summary of the process) An overview of the processing of the information processing system 1A according to the first embodiment will be described. Figure 2 is a diagram showing an example of the processing content of the information processing system according to the first embodiment. The information processing system 1A according to the first embodiment includes an acquisition means for acquiring sensor information detected by a sensor installed in any one of the water-related spaces such as a toilet, washroom, kitchen, or bathroom; a storage means for storing the sensor information; an estimation means for estimating the biological age of a user using the water-related space by referring to the sensor information stored in the storage means and fitting a model for estimating biological age to the sensor information; and an output means for outputting information indicating the biological age of the user estimated by the estimation means.

[0110] For example, as shown in Figure 2, the information processing system 1A acquires information such as the user's biometric data detected by the toilet sensor 2112, bathroom sensor 2122, washbasin sensor 2132, and kitchen sensor 2142, which are installed in the respective water-related spaces of the toilet 211, bathroom 212, washbasin 213, and kitchen 214.

[0111] The information processing system 1A then stores the acquired sensor information in its memory unit, and then adapts the stored information to a machine learning model to obtain the user's biological age. The information processing system 1A then outputs biological age-related content to the user terminal 30, such as a display screen showing a numerical comparison between the estimated biological age and the actual age.

[0112] As a result, the information processing system 1A according to the first embodiment estimates the user's biological age using biometric data acquired in the bathroom and other areas used by the user in their daily life, making it possible to easily estimate the user's biological age.

[0113] (Example configuration for Cloud Server 10A) The following describes the functional configuration of the cloud server 10A according to the first embodiment. Figure 3 is a diagram showing an example of the configuration of the cloud server according to the first embodiment. As shown in Figure 3, the cloud server 10A has a communication unit 110, a control unit 120, and a storage unit 130. The cloud server 10A may also have an input unit (e.g., a keyboard or mouse) that accepts various operations from the administrator of the cloud server 10A, and a display unit (e.g., a liquid crystal display) for displaying various information.

[0114] The communication unit 110 is implemented, for example, by a communication circuit. The communication unit 110 is connected to a predetermined network by wire or wireless and transmits and receives information with an external information processing device. For example, the communication unit 110 is connected to network N by wire or wireless and transmits and receives information with communication equipment such as plumbing fixtures and sensor devices installed in the plumbing space, and with other devices such as a user terminal 30.

[0115] The memory unit 130 is implemented by, for example, semiconductor memory elements such as RAM (Random Access Memory) and flash memory, or by storage devices such as hard disks and optical discs. For example, the memory unit 130 is a computer-readable recording medium that non-temporarily stores data used by various information processing programs such as machine learning models, which will be described later.

[0116] The memory unit 130 stores sensor information. For example, the memory unit 130 stores sensor information such as the user's biometric data obtained from sensor devices installed in the bathroom, linking it to the date and time the data was measured and the user's identification information.

[0117] Furthermore, the memory unit 130 stores information about the user's actual age. For example, the memory unit 130 stores the actual age of a user who is the subject of biological age estimation in advance. The memory unit 130 can also store other information about the user besides their actual age, such as the user's height and weight, and data measured during health checkups.

[0118] Furthermore, the memory unit 130 stores parameter information for the machine learning model used to estimate biological age. For example, the memory unit 130 stores parameter information for a machine learning model that has been trained to output the user's biological data in response to sensor information input acquired by the sensor device. Alternatively, the memory unit 130 may store the trained machine learning model itself.

[0119] Here, a machine learning model that outputs biological age in response to sensor data input is trained to output the correct biological age from sensor data corresponding to a given period, for example, by using biological age estimated from the user's blood data as ground truth data.

[0120] Furthermore, biological age may be estimated for each health-related item, such as the intestines or blood circulation. In this case, for example, the memory unit 130 can store parameters for each item of a machine learning model that has been trained to output the biological age for each item with high accuracy based on the input of sensor information related to each item, such as the intestines or blood circulation.

[0121] Returning to Figure 3, let's continue the explanation. The control unit 120 is implemented, for example, by a CPU (Central Processing Unit) or GPU (Graphics Processing Unit) executing a program stored inside the cloud server 10A using RAM or the like as a working area. Alternatively, the control unit 120 can be implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array).

[0122] As shown in Figure 3, the control unit 120 includes an acquisition unit 121, an estimation unit 122, and an output unit 123, and realizes or executes the information processing functions and operations described below. Note that the internal configuration of the control unit 120 is not limited to the configuration shown in Figure 3, and other configurations are also acceptable as long as they perform the information processing described later.

[0123] The acquisition unit 121 acquires sensor information detected by a sensor device installed in one of the following water-related spaces: the toilet 211, bathroom 212, washbasin 213, or kitchen 214. For example, the acquisition unit 121 acquires the user's biometric data, data on ingredients used by the user for cooking, etc., measured by one or more sensor devices installed in each of the water-related spaces: the toilet sensor 2112, bathroom sensor 2122, washbasin sensor 2132, and kitchen sensor 2142, and stores them in the storage unit 130.

[0124] The estimation unit 122 estimates the biological age of users of the bathroom space by referring to the sensor information stored in the memory unit 130 and fitting a model for estimating biological age to the sensor information. For example, the estimation unit 122 inputs the sensor information acquired when a user uses the bathroom space into a machine learning model that outputs biological age in response to the sensor information input, and obtains the biological age output by the machine learning model.

[0125] Furthermore, the estimation unit 122 estimates the aging rate of the user's biological age. For example, the estimation unit 122 estimates the aging rate of the biological age using the biological age corresponding to the date and time obtained by inputting sensor information along with date and time information into a machine learning model. As an example, the estimation unit 122 estimates the aging rate by calculating the slope of two points targeting the respective biological ages estimated at two specific points in time.

[0126] Furthermore, the estimation unit 122 can also obtain a biological age corresponding to a specific date and time by, for example, inputting only sensor information into a machine learning model and then later associating the corresponding date and time information with the output biological age.

[0127] The output unit 123 outputs information indicating the user's biological age, as estimated by the estimation unit 122. For example, the output unit 123 generates a display screen for content showing the user's biological age based on the output of the machine learning model acquired by the estimation unit 122, and outputs it to the user terminal 30. The following describes the biological age-related content generated by the output unit 123 in order.

[0128] The output unit 123 outputs information indicating the user's biological age changes. For example, the output unit 123 uses the biological age corresponding to each date and time, obtained by the estimation unit 122, to generate and output a display screen showing the progression of the biological age over a certain period.

[0129] The output unit 123 outputs information indicating the change in the user's aging rate. For example, the output unit 123 uses the user's aging rate estimated by the estimation unit 122 to generate and output a display screen showing a comparison between the current aging rate and past aging rates (for example, one month ago or one year ago).

[0130] The output unit 123 outputs information comparing the user's actual age and biological age. For example, the output unit 123 uses the user's actual age information stored in the memory unit 130 to generate and output a display screen showing the comparison result between the estimated biological age and the actual age.

[0131] The output unit 123 outputs information indicating the user's biological age relative to other users of the same age. For example, the output unit 123 uses aggregated information of estimated biological ages of users of various ages and genders to generate and output a display screen showing where the user's biological age is located compared to the biological ages of other users.

[0132] The output unit 123 outputs information indicating the estimated biological age for each predetermined health item. For example, the output unit 123 generates and outputs a display screen showing a list of estimated biological ages for each item, such as the intestines and blood circulation.

[0133] (Example display) Here, we will describe in order an example of content related to biological age that the output unit 123 outputs to the user terminal 30. Figures 4 to 8 show an example of data displayed by the output unit according to the first embodiment.

[0134] Figure 4 shows an example of content that compares the user's actual age with their biological age. As shown in Figure 4, the output unit 123 outputs content that shows a biological age of "48" estimated from sensor information acquired "as of July 22nd". Then, using the user's actual age of "45", the output unit 123 outputs content that shows that a biological age of "48" is "actual age + 3" compared to an actual age of "45".

[0135] Furthermore, as shown in Figure 4, the output unit 123 can also output content that includes information indicating various indicators such as health indicators and stool condition. Here, the various indicators such as health indicators and stool condition include, for example, body water level, fitness level, relaxation level (stress level), metabolic level, heart rate (resting heart rate), bowel movements, internal clock, blood circulation status (lower limb blood circulation status), etc.

[0136] As shown in Figure 4, the output unit 123 outputs content that includes information indicating various indicators such as health indicators and stool condition, based on information estimated using sensor information acquired as of July 22. For example, the output unit 123 outputs content that includes information indicating that the body water level is "90%", which is higher than the evaluation criteria such as past averages. For example, the output unit 123 outputs content that includes information indicating that the heart rate is "55 bpm", which is lower than the evaluation criteria such as past averages.

[0137] Figure 5 shows an example of content that displays the user's biological age change. As shown in Figure 5, the output unit 123 outputs content that shows graph data plotting the monthly average value of the biological age for "20XX" using previously estimated biological ages. For example, the output unit 123 outputs content that shows the biological age in "January 20(XX)" was "52" and the biological age in "December 20(XX)" was "48".

[0138] Figure 6 shows an example of content that illustrates the user's aging rate. As shown in Figure 6, the output unit 123 outputs content in the form of a graph that shows the estimated biological age of "78" in "20 years" based on the user's current aging rate of "1.5 years / year," derived from their biological age of "48" "today." The output unit 123 also generates content that shows the difference of "+13 years" between the estimated biological age of "78" in 20 years and the actual age of "65" in "20 years."

[0139] Furthermore, the output unit 123 can output content that shows a comparison between the current aging rate and previously estimated aging rates, such as the aging rate one year ago or two years ago, by displaying a straight line based on the aging rate one year ago (the dotted line corresponding to one year ago in Figure 6) and a straight line based on the aging rate two years ago (the dotted line corresponding to two years ago in Figure 6) within the graph.

[0140] Furthermore, the output unit 123 can also output content that displays comments explaining the aging rate. As shown in Figure 6, the output unit 123 outputs content that displays comments such as, "Your biological age aging rate is 1.5 years (per year). An aging rate greater than 1 means that aging is progressing faster than your actual age. The aging rate can be reduced by improving your physical health." Here, the output unit 123 can generate comments corresponding to the estimated aging rate using, for example, a large-scale language model or pre-configured template sentences.

[0141] Figure 7 shows an example of content that illustrates a user's relative position in terms of biological age compared to other users of the same age. In the graph shown in Figure 7, the vertical axis represents biological age, and the horizontal axis represents actual age. The graph in Figure 7 also plots the estimated results of other users for whom the biological age was estimated.

[0142] As shown in Figure 7, the output unit 123 outputs content that distinguishes the relevant point from the estimated results of other users (shaded in Figure 7) when, for example, the user's biological age is "20" and their actual age is "30 years old". The output unit 123 then outputs content that indicates the user's biological age of "20" is higher than "13%" of other users who are the same age as the user, "30 years old". In other words, the output unit 123 outputs content that indicates the user's biological age is in the top 13% of other users of the same age.

[0143] Figure 8 shows an example of content that displays the estimated biological age for each predetermined health item. Figure 8 shows the estimated biological age for each health item, specifically "intestinal age," which is estimated based on the user's intestinal input information 20, and "blood circulation age," which is estimated based on the user's blood circulation input information 20. As shown in Figure 8, the output unit 123 outputs content indicating, for example, that for a user with a chronological age of "30 years old," the intestinal age is "45" and the blood circulation age is "20."

[0144] Furthermore, the output unit 123 generates content that also displays the "physical age," which is the estimated biological age of the user's entire body, using the user's input information 20. As shown in Figure 8, for example, the output unit 123 outputs content indicating that a user with a chronological age of "30 years old" has a physical age of "28."

[0145] (Process flow) Next, the processing flow of the cloud server 10A will be described. Figures 9 and 10 are flowcharts showing an example of information processing according to the first embodiment. Note that each step in the flowcharts shown in Figures 9 and 10 can be executed in a different order, and some processes may be omitted.

[0146] First, using Figure 9, we will explain an example of the process for estimating a user's biological age. The cloud server 10A acquires sensor information from within the water-related space (S101). The cloud server 10A then records the acquired information along with date and time information (S102). The cloud server 10A then refers to the recorded information, fits a biological age estimation model, and estimates the user's biological age (S103). Finally, the cloud server 10A outputs content related to the biological age (S104) and terminates the process.

[0147] Next, using Figure 10, an example of the process for estimating the user's aging rate will be explained. The cloud server 10A acquires sensor information from within the water-related area (S201). The cloud server 10A then records the acquired information along with the date and time and the user's actual age (S202). The cloud server 10A then refers to the recorded information, fits a biological age estimation model, and estimates the user's biological age (S203).

[0148] Then, the cloud server 10A refers to the recorded information and estimates the user's aging rate based on the estimated biological age (S204). The cloud server 10A then outputs content related to the biological age (S205) and terminates the process.

[0149] [Second Embodiment] By the way, in the information processing system 1A according to the first embodiment described above, an example was described in which only water-related space sensor information 21 measured by a sensor device installed in the water-related space is used to estimate the biological age, but the system is not limited to this. For example, the information processing system 1B according to the second embodiment can also estimate the user's biological age using external terminal sensor information 22 and external terminal input information 23 in addition to the water-related space sensor information 21.

[0150] Furthermore, while the first embodiment of the information processing system 1A described above explains an example in which the biological age value, the result of comparison with actual age, the rate of aging, etc., are output to the user terminal 30, the system is not limited to this. For example, the second embodiment of the information processing system 1B can also output recommendation information regarding the user's lifestyle habits to the user terminal 30 in accordance with changes in the user's biological age.

[0151] (Summary of the process) An overview of the processing of the information processing system 1B according to the second embodiment will be described. Figure 11 is a diagram illustrating the processing content of the information processing system according to the second embodiment. The information processing system 1B according to the second embodiment includes: acquisition means for acquiring input information which is either information detected by a sensor or information input externally; storage means for storing the input information together with date and time information; estimation means for estimating the change in the user's biological age by referring to the input information stored in the storage means together with the date and time information and fitting a model for estimating biological age to the input information; and output means for outputting recommendation information regarding the user's lifestyle habits based on the change in the user's biological age estimated by the estimation means.

[0152] For example, the information processing system 1B acquires, as input information 20, water-related space sensor information 21, which is measurement data acquired by a toilet sensor 2112 installed in the toilet 211, as well as external terminal sensor information 22 measured by external terminals such as smartwatches and smart scales, and external terminal input information 23, which is information entered into an information processing terminal such as a computer, tablet, or smartphone owned by the user.

[0153] The information processing system 1B then stores the acquired input information 20 along with date and time information in the storage unit 130, and then adapts the stored information to a machine learning model to obtain the user's biological age output. Based on the estimated biological age, the information processing system 1B generates recommendation information regarding lifestyle habits, such as increasing exercise time, increasing sleep time, and reviewing dietary habits, and outputs it to the user terminal 30.

[0154] As a result, the information processing system 1B according to the second embodiment estimates the user's biological age using biometric data acquired in the bathroom and other areas the user uses in their daily life, as well as data acquired from smart devices the user usually wears, making it possible to easily estimate the user's biological age. Furthermore, the information processing system 1B according to the second embodiment displays specific recommendations regarding the user's lifestyle habits in response to changes in the user's biological age, thereby encouraging behavioral changes in the user.

[0155] (Example configuration for Cloud Server 10B) The functional configuration of the cloud server 10B according to the second embodiment will now be described. The cloud server 10B according to the second embodiment has the same functional configuration as the cloud server 10A according to the first embodiment described above (see Figure 3). In the following description, the processing specific to the cloud server 10B according to the second embodiment will be described in order.

[0156] The memory unit 130 stores the input information 20 together with the date and time information. For example, the memory unit 130 stores the input information 20 of the water area sensor information 21, external terminal sensor information 22, and external terminal input information 23, which are acquired by the acquisition unit 121 described later, in association with the date and time information on which each piece of information was measured or input.

[0157] Furthermore, the memory unit 130 stores information regarding the first biological age obtained from the user's blood information, information regarding the second biological age estimated by the estimation unit 122, and user information, along with date and time information. For example, the memory unit 130 stores the first biological age estimated by an external institution based on the user's blood information, the second biological age estimated by the estimation unit 122, and external terminal input information 23 regarding the user, such as the user's age, gender, drinking habits, and smoking habits, in association with the date and time information when the user's blood information was measured.

[0158] For example, when the user's first biological age is obtained, the memory unit 130 identifies the date and time information of when the blood information for the first biological age was measured, and searches for the second biological age and input information 20 associated with the identified date and time information, thereby storing the first biological age, the second biological age, and the input information 20 in association with the date and time information.

[0159] The acquisition unit 121 acquires input information 20 from at least one of the following: information detected by a sensor and information input from an external source. For example, the acquisition unit 121 acquires input information 20 from at least one of the following: information detected by a sensor device, such as water-related space sensor information 21 or external terminal sensor information 22, and external terminal input information 23 input to an external terminal.

[0160] The estimation unit 122 references the input information 20 stored in the memory unit 130 along with the date and time information, and estimates the user's biological age changes by fitting a model for estimating biological age to the input information 20. For example, the estimation unit 122 inputs the aforementioned input information 20 into a machine learning model that outputs biological age in response to the input information 20, and obtains a second biological age output by the machine learning model. Then, the estimation unit 122 estimates the time-series changes in biological age from the estimation result of the second biological age corresponding to the date and time information.

[0161] Furthermore, the estimation unit 122 estimates the time-series changes in the user's biological age based on information regarding either or both of the first and second biological ages. For example, the estimation unit 122 corrects the second biological age estimated from the input information 20 based on the first biological age measured by an external institution from the user's blood information. Then, the estimation unit 122 estimates the changes in the user's biological age by estimating the time-series changes in the corrected second biological age.

[0162] Furthermore, the estimation unit 122's correction process for the second biological age can, for example, weight the first biological age and the second biological age with an arbitrary parameter to correct the second biological age so that it approaches the first biological age. Also, if the estimation unit 122 determines that the second biological age is an abnormal value relative to the first biological age, it can choose not to use the abnormal second biological age in the output unit 123's processing.

[0163] Here, the estimation unit 122 can estimate a more accurate biological age by correcting the second biological age to approach the first biological age, which is considered to have higher accuracy.

[0164] Figures 12 and 13 show examples of the processing of the estimation unit according to the second embodiment. Figure 12 shows an example of the process of estimating the change in biological age using information from both the first biological age and the second biological age. Figure 13 shows an example of the process of estimating the change in biological age by correcting the second biological age with information from the first biological age.

[0165] As shown in Figure 12, the estimation unit 122 estimates the second biological age "43" using, for example, the water-related space sensor information 21, the external terminal sensor information 22, and the external terminal input information 23, which are acquired as input information 20. Here, the external terminal input information 23 includes, for example, information about the user such as age, gender, drinking habits, and smoking habits, as well as blood information such as glucose value, HbA1c value, cholesterol value, AST value, and DHEAS value measured from the user's blood.

[0166] Furthermore, as shown in Figure 12, the estimation unit 122 references the information of the first biological age "50," which is obtained by an external organization based on the user's blood information, from the storage unit 130. The estimation unit 122 then uses the information of both the first biological age "50" and the second biological age "43" to estimate the change in the user's biological age. For example, the estimation unit 122 estimates the change in the user's biological age by comparing the first biological age and the second biological age with similar date and time information, or by comparing the first biological ages with each other.

[0167] As shown in Figure 13, the estimation unit 122 estimates the second biological age "41" using the water-related space sensor information 21, the external terminal sensor information 22, and the external terminal input information 23, which are acquired as input information 20. In the example shown in Figure 13, the external terminal input information 23 includes user information such as age, gender, drinking habits, and smoking habits, but does not include blood information such as glucose values, HbA1c values, cholesterol values, AST values, and DHEAS values ​​measured from the user's blood.

[0168] Furthermore, as shown in Figure 13, the estimation unit 122 references the information of the first biological age "50," which is obtained by an external organization based on the user's blood information, from the storage unit 130. Then, the estimation unit 122 uses the first biological age "50" to correct the value of the second biological age "41" to "47." Finally, the estimation unit 122 estimates the change in the user's biological age by estimating the time-series change of the corrected biological age.

[0169] The output unit 123 outputs recommendation information regarding the user's lifestyle habits based on the changes in the user's biological age estimated by the estimation unit 122. For example, if the estimation unit 122 estimates that the user's biological age is likely to increase, the output unit 123 generates recommendation information regarding lifestyle habits that are effective in lowering the biological age and outputs it to the user terminal 30.

[0170] Here, the lifestyle recommendation information output by the output unit 123 is generated, for example, using points for improvement regarding the user's health estimated from the user's biometric data input as input information 20.

[0171] For example, if the measurement result of sleep time input as external terminal sensor information 22 is shorter than the recommended sleep time, the output unit 123 estimates that the short sleep time of the user is an area for improvement regarding the user's health, and generates recommendation information to go to bed earlier in order to increase sleep time. For example, if the user's diet content input as water area sensor information 21 is nutritionally unbalanced, the output unit 123 estimates that the unbalanced diet of the user is an area for improvement regarding the user's health, and generates recommendation information to try to eat a nutritionally balanced diet.

[0172] (Example display) Here, we will describe in order an example of content related to biological age that the output unit 123 outputs to the user terminal 30. Figures 14 to 16 show an example of data displayed by the output unit according to the second embodiment.

[0173] Figure 14 shows an example of content that displays recommendation and highlight information based on changes in the user's biological age. As shown in Figure 14, the output unit 123 outputs recommendation information regarding lifestyle habits that correspond to changes in biological age, such as, "Your biological age is on the rise. Increase your sleep time."

[0174] Furthermore, as shown in Figure 14, the output unit 123 can also output highlighted information regarding biological age. For example, the output unit 123 may output "average sleep time 6h The system outputs data analysis results that address areas for improvement related to users' health, such as "low," as highlighted information.

[0175] Figure 15 shows an example of content illustrating changes in biological age using the first and second biological ages. As shown in Figure 15, the output unit 123 outputs content that shows graph data plotting the average value of the second biological age for each month for the change in biological age in "20XX". The output unit 123 then outputs content that plots the first biological age, measured by an external organization, "XXX Company," on the graph data.

[0176] Figure 16 shows an example of content that displays the results of blood analysis performed by an external organization that measured the first biological age, along with information on the second biological age. As shown in Figure 16, the output unit 123 outputs content that, for example, when the second biological age is corrected using the first biological age, displays the corrected second biological age "48," along with the blood analysis results performed by "XXX Company" and "YYY Company," respectively, for measuring the first biological age.

[0177] (Process flow) Next, the processing flow of the cloud server 10B will be described. Figures 17 and 18 are flowcharts showing an example of information processing according to the second embodiment. Note that each step in the flowcharts shown in Figures 17 and 18 can be executed in a different order, and some processes may be omitted.

[0178] First, using Figure 17, we will explain an example of a process that outputs recommendations regarding the user's lifestyle habits. The cloud server 10B acquires input information 20 from at least one of sensor detection information and external input information (S301). The cloud server 10B then records the acquired input information 20 along with date and time information (S302). The cloud server 10B then refers to the recorded information, fits a biological age estimation model, and estimates the user's biological age and the change in biological age based on the date and time information (S303). The cloud server 10B then outputs recommendations regarding the user's lifestyle habits based on the change in biological age (S304), and the process ends.

[0179] Next, using Figure 18, an example of a process for estimating changes in biological age using the first biological age will be explained. The cloud server 10B acquires input information 20 from at least one of the sensor detection information and external input information held by the user (S401). The cloud server 10B then records the input information 20 along with the date and time information and actual age (S402).

[0180] The cloud server 10B then obtains input information regarding the first biological age obtained from the user's blood information (S403). The cloud server 10B then refers to the recorded information, fits a biological age estimation model, and estimates the user's second biological age (S404). The cloud server 10B then uses the first biological age and the second biological age to estimate the change in biological age (S405).

[0181] Then, the cloud server 10B refers to the recorded information and estimates the user's aging rate based on the estimated biological age (S406). Then, the cloud server 10B outputs recommendations regarding the user's lifestyle habits based on the changes in biological age and aging rate (S407), and the process ends.

[0182] [Third Embodiment] By the way, while examples have been described for the information processing system 1A according to the first embodiment and the information processing system 1B according to the second embodiment, which output estimated changes in biological age and recommendation information corresponding to changes in biological age, the system is not limited to these examples. For example, the information processing system 1C according to the third embodiment can also output specific recommendation information regarding the user's lifestyle habits to lower their biological age, based on the estimated target value of their biological age.

[0183] (Summary of the process) An overview of the processing of the information processing system 1C according to the third embodiment will be described. Figure 19 is a diagram illustrating the processing content of the information processing system according to the third embodiment. The information processing system 1C according to the third embodiment includes: acquisition means for acquiring input information that is either information detected by a sensor or information input externally; storage means for storing the input information together with date and time information; estimation means for estimating the user's biological age by referring to the input information stored in the storage means together with the date and time information and fitting a model for estimating biological age to the input information; and output means for outputting recommendation information regarding the user's biological age based on the difference between the measured value based on the input information stored in the storage means and the target value for the biological age.

[0184] For example, the information processing system 1C acquires, as input information 20, water-related space sensor information 21, which is measurement data acquired by a toilet sensor 2112 installed in the toilet 211, as well as external terminal sensor information 22 measured by external terminals such as smartwatches and smart scales, and external terminal input information 23, which is information entered into an information processing terminal such as a computer, tablet, or smartphone owned by the user.

[0185] Then, the information processing system 1C stores the acquired input information 20 together with date and time information in the storage unit 130, and then adapts the stored information to a machine learning model to obtain the user's biological age output.

[0186] The information processing system 1C then estimates target biological age parameters, which are biological data such as weight and target values ​​such as exercise time and sleep time, that contribute to improving or maintaining biological age. The information processing system 1C then generates recommendation information regarding the user's lifestyle habits to achieve the estimated target biological age parameters and outputs it to the user terminal 30.

[0187] As a result, the information processing system 1C according to the third embodiment estimates the user's biological age using biometric data acquired in the bathroom and other areas the user uses in their daily life, as well as data acquired from smart devices the user usually wears, making it possible to easily estimate the user's biological age. Furthermore, the information processing system 1C according to the third embodiment estimates parameters related to biological age according to target values ​​and specifically recommends lifestyle habits to the user, thereby encouraging behavioral changes in the user.

[0188] (Example configuration for Cloud Server 10C) The functional configuration of the cloud server 10C according to the third embodiment will now be described. The cloud server 10C according to the third embodiment has the same functional configuration as the cloud server 10A according to the first embodiment and the cloud server 10B according to the second embodiment described above (see Figure 3, etc.). In the following description, the processing specific to the cloud server 10C according to the third embodiment will be described in order.

[0189] The estimation unit 122 estimates target biological age parameters using measured values ​​based on input information 20 and target values ​​related to biological age. For example, the estimation unit 122 estimates target biological age parameters that are the subject of recommendations to the user, according to the target values ​​related to biological age entered by the user.

[0190] Here, the target value for biological age is the upper limit of a health indicator based on input information 20, or a variable value specified by the user. For example, the target value for biological age is the upper limit or variable value of a biological age parameter, such as sleep duration, exercise duration, or calorie intake, which is a health indicator used to estimate biological age and is entered by the user who has confirmed the output of the estimated biological age.

[0191] Furthermore, when the cloud server 10C outputs the estimated user's biological age to the user terminal 30, for example, it can output candidate biological age parameters recommended for improving or maintaining the user's biological age, thereby allowing the user to appropriately input target values ​​for improving or maintaining their biological age.

[0192] For example, the estimation unit 122 uses the user's current sleep time and exercise time acquired as input information 20, and the sleep time and exercise time stored as upper limits for the biological age parameter, to estimate the target biological age parameter, which is the amount of sleep time and exercise time required to improve or maintain the estimated biological age. The estimation unit 122 also estimates the number of days required for the biological age to improve if the estimated target biological age parameter is maintained.

[0193] Furthermore, the estimation unit 122 can estimate target biological age parameters within a range that does not exceed the upper limit of biological age parameters stored in the memory unit 130, for example. The estimation unit 122 can estimate appropriate values ​​as target biological age parameters for the user, for example, based on recommended values ​​for biological age parameters set in advance or the user's past input values ​​for biological age parameters.

[0194] The following describes an example of the process for estimating biological age parameters. Figure 20 shows an example of the processing of the estimation unit according to the third embodiment. Figure 20 shows an example of estimating target biological age parameters based on target values ​​for biological age entered by the user.

[0195] As shown in Figure 20, the acquisition unit 121 acquires, for example, upper limits of biological age parameters related to lifestyle habits that the user can change, such as "sleep time: up to 10 hours / day, exercise amount: up to 1 hour / day, etc." as target values ​​for biological age input as external terminal input information 23, and stores them in the memory unit 130. Then, the estimation unit 122 estimates target biological age parameters for the user's biological age, such as "target sleep time: 8 hours / day, target exercise amount: 0.5 hours / day, etc.", within a range that does not exceed the upper limits of biological age parameters stored in the memory unit 130.

[0196] Furthermore, the target values ​​for biological age are target values ​​for biometric data such as weight and body fat percentage, which are used to estimate biological age, and are entered by the user after they have confirmed the output of the estimated biological age. For example, the target values ​​for biological age are target values ​​for biometric data that the user has specified in order to improve or maintain their biological age, such as the user's target weight.

[0197] Furthermore, when the cloud server 10C outputs the estimated biological age of a user to the user terminal 30, for example, it outputs the relationship between the user's biometric data and the estimated biological age. This allows the cloud server 10C to help users understand how much improvement in their biometric data contributes to improving or maintaining their biological age, thereby enabling them to appropriately input target values ​​related to their biological age.

[0198] Furthermore, the estimation unit 122 estimates the number of days required to reach the target value based on the difference between the measured value and the target value. For example, when target values ​​of the user's biological data, such as weight, are input as target values ​​related to biological age, the estimation unit 122 estimates the number of days required to reach the target values ​​of weight, etc., which are the target values ​​related to biological age, based on the measured values ​​of the user's weight, etc., included in the input information 20, assuming that the user continues to maintain the estimated sleep time, exercise time, and calorie intake as target biological age parameters.

[0199] The following describes an example of the process for estimating biological age parameters and the number of days required. Figure 21 shows an example of the processing of the estimation unit according to the third embodiment. Figure 21 shows an example of estimating target biological age parameters and the number of days required to reach the target values ​​of biological data, based on target values ​​for biological age entered by the user and target values ​​for biological data.

[0200] As shown in Figure 21, the acquisition unit 121 acquires, for example, the biological age parameter "exercise" related to lifestyle habits that can be varied by the user, as a target value for biological age input as external terminal input information 23, and stores it in the storage unit 130. The acquisition unit 121 also acquires, for example, the weight "71 kg" as a target value for biological data input as external terminal input information 23, and stores it in the storage unit 130.

[0201] The estimation unit 122 then estimates a target biological age parameter for the user's biological age, "Target exercise amount: 1h / day," based on the variable biological age parameters stored in the memory unit 130. The estimation unit 122 also estimates the number of days, "10 days," required to improve the current weight of "75kg" to the target value of "71kg" in biological data, assuming that the "Target exercise amount: 1h / day" is maintained.

[0202] The output unit 123 outputs recommendation information regarding the user's biological age based on the difference between the measured values ​​based on the input information 20 stored in the memory unit 130 and the target value for biological age. For example, the output unit 123 uses the measured values ​​of the water area sensor information 21, external terminal sensor information 22, and external terminal input information 23 stored as input information 20 in the memory unit 130, along with the target value for biological age input by the user, to generate recommendation information indicating the target biological age parameter estimated by the estimation unit 122 and output it to the user terminal 30.

[0203] Here, the recommendation information output by the output unit 123 is information that shows, for example, how much the actual values ​​of the user's biological data will improve or be maintained if the target biological age parameters such as sleep time, exercise time, and calorie intake, estimated by the estimation unit 122, are continued, and it is information that shows specific numerical values ​​such as weight and body fat percentage. For example, the output unit 123 can output recommendation information that shows the number of days required to go from the current weight to the target weight by continuing the target biological age parameters, based on the user's past weight trends and measurement data such as calorie intake.

[0204] (Example display) Here, we will describe in order an example of recommendation information regarding biological age that the output unit 123 outputs to the user terminal 30. Figures 22 to 24 show an example of data displayed by the output unit according to the third embodiment.

[0205] Figure 22 shows an example of recommendation information related to the user's biometric data, specifically weight changes. As shown in Figure 22, the output unit 123 outputs recommendation information that includes, for example, a graph showing the user's weight changes over the past week, and the current weight "75 kg" and the target weight "71 kg". The output unit 123 then generates recommendation information indicating that, for example, if the estimated target biological age parameter "exercise target: 1 hour / day" is maintained, the target weight of "71 kg" will be reached "by 10 days (July 25th)".

[0206] Figure 23 shows an example of recommendation information regarding weight change when the user inputs an upper limit for the biological age parameter. As shown in Figure 23, the output unit 123 outputs recommendation information similar to Figure 22, showing a graph of the user's weight change over the past week and the current weight of "75 kg". The output unit 123 then outputs recommendation information indicating that, for example, if the user continues to maintain the target biological age parameter "Target exercise amount: 1 hour / day" estimated under the condition of the biological age target value "Upper limit: Exercise amount up to 1 hour / day", the user will reach a weight of "70 kg" by "15 days (7 / 30)".

[0207] Figure 24 shows an example of recommendation information explaining the relationship between biological age improvement and weight. As shown in Figure 24, the output unit 123 generates recommendation information that explains how weight gain worsens biological age and encourages users to lose weight, such as, "Excessive weight gain can cause an increase in biological age. For the next 10 days, try paying even more attention to the following."

[0208] (Process flow) Next, we will describe the processing flow of the cloud server 10C. Figures 25 and 26 are flowcharts showing an example of information processing according to the third embodiment. Note that each step in the flowcharts shown in Figures 25 and 26 can be executed in a different order, and some processes may be omitted.

[0209] First, using Figure 25, we will explain an example of a process that outputs recommendations regarding the user's lifestyle habits based on target values ​​of health indicators. The cloud server 10C acquires target values ​​of health indicators (S501). Then, the cloud server 10C acquires input information 20 from at least one of sensor detection information and external input information (S502). Then, the cloud server 10C records the acquired input information 20 along with date and time information (S503).

[0210] Then, the cloud server 10C refers to the recorded information, fits a biological age estimation model, and estimates the user's second biological age (S504). Then, the cloud server 10C outputs recommendations regarding lifestyle habits based on the second biological age and the measured values ​​and target values ​​based on the input information 20 (S505), and the process ends.

[0211] Next, using Figure 26, we will explain an example of a process that estimates changes in biological age using the first biological age and outputs recommendations regarding the user's lifestyle based on measured values ​​and target values. The cloud server 10C acquires input information 20 from at least one of the sensor detection information and external input information held by the user (S601). The cloud server 10C then records the input information 20 along with date and time information and actual age (S602).

[0212] The cloud server 10C then obtains input information regarding the first biological age obtained from the user's blood information (S603). The cloud server 10C then refers to the recorded information, fits a biological age estimation model, and estimates the user's second biological age (S604). Based on the input information 20, the cloud server 10C then obtains the upper limit of health indicators that the user can achieve as target values ​​(S605).

[0213] Then, the cloud server 10C estimates the number of days required to achieve the target value from the difference between the measured value based on the input information 20 (S606). Then, the cloud server 10C refers to the recorded information and estimates the user's aging rate based on the estimated biological age (S607). Then, the cloud server 10C outputs recommendations regarding lifestyle habits based on the second biological age, aging rate, measured value based on the input information 20, and target value (S608), and ends the process.

[0214] [Fourth Embodiment] Now, in the information processing systems 1A according to the first embodiment to the information processing system 1C according to the third embodiment described above, examples of outputting estimated changes in biological age, recommendation information corresponding to changes in biological age, and specific recommendation information related to biological age have been explained, but the system is not limited to these. For example, the information processing system 1D according to the fourth embodiment can also output recommendation information related to the user's lifestyle habits based on the difference between a preset target age and the estimated biological age.

[0215] (Summary of the process) An overview of the processing of the information processing system 1D according to the fourth embodiment will be described. Figure 27 is a diagram illustrating the processing content of the information processing system according to the fourth embodiment. The information processing system 1D according to the fourth embodiment includes: acquisition means for acquiring input information which is either information detected by a sensor or information input externally; storage means for storing the input information together with date and time information; estimation means for estimating the user's biological age by referring to the input information stored in the storage means together with the date and time information and fitting a model for estimating biological age to the input information; and output means for outputting recommendation information regarding the user's lifestyle habits based on the difference between the user's biological age estimated by the estimation means and a target set age.

[0216] For example, the information processing system 1D acquires, as input information 20, water-related space sensor information 21, which is measurement data acquired by a toilet sensor 2112 installed in the toilet 211, as well as external terminal sensor information 22 measured by external terminals such as smartwatches and smart scales, and external terminal input information 23, which is information entered into an information processing terminal such as a computer, tablet, or smartphone owned by the user.

[0217] Then, the information processing system 1D stores the acquired input information 20 together with date and time information in the storage unit 130, and then adapts the stored information to a machine learning model to obtain the user's biological age output.

[0218] The information processing system 1D then calculates the difference between the pre-set target age and the estimated biological age. The information processing system 1D then generates recommendation information to encourage the user to improve or maintain their lifestyle habits in order to eliminate the calculated difference and bring their biological age closer to the target age, and outputs this information to the user terminal 30.

[0219] As a result, the information processing system 1D according to the fourth embodiment estimates the user's biological age using biometric data acquired in the bathroom and other areas the user uses in their daily life, as well as data acquired from smart devices the user usually wears, making it possible to easily estimate the user's biological age. Furthermore, the information processing system 1D according to the fourth embodiment recommends lifestyle habits to the user based on the difference between the estimated biological age and the target age, thereby encouraging behavioral changes in the user.

[0220] (Example configuration for Cloud Server 10D) The functional configuration of the cloud server 10D according to the fourth embodiment will now be described. The cloud server 10D according to the fourth embodiment has the same functional configuration as the cloud servers 10A according to the first embodiment to the cloud server 10C according to the third embodiment described above (see Figure 3, etc.). In the following description, the processing specific to the cloud server 10D according to the fourth embodiment will be described in order.

[0221] The estimation unit 122 estimates the number of days required for the user's biological age to reach the target age, based on the difference between the estimated biological age and the target age set by the user, assuming the user continues to follow the parameters set by the user. For example, the estimation unit 122 uses the estimated biological age, the target age (described later), and the target value for biological age entered by the user to estimate the number of days required for the user's biological age to reach the target age, assuming the user continues to follow the target biological age parameters.

[0222] Furthermore, the estimation unit 122 can, for example, output recommendation information indicating the number of days required from the current biological age to the set age, based on input information 20 such as the user's past biological age trends and corresponding biological age parameters, by continuing the target biological age parameters.

[0223] Here, the set age is the biological age estimated by the estimation unit 122 based on the setting parameters set by the user. For example, the set age is the biological age estimated by the estimation unit 122 based on the target value for biological age entered by the user. For example, the estimation unit 122 estimates the target biological age parameter from the target value for biological age entered by the user, and obtains the biological age output when the target biological age parameter is input into the machine learning model as the set age.

[0224] Furthermore, the target values ​​for biological age entered by the user may be upper limits or variable values ​​of health indicators, as described in the third embodiment above, but are not limited to these. For example, the target values ​​for biological age may be the target values ​​of health indicators specified by the user. In other words, the target values ​​for biological age may be upper limits of health indicators such as "sleep time: up to 10 hours / day, exercise: up to 1 hour / day, etc." (see Figure 20), variable values ​​of health indicators such as the user-adjustable lifestyle parameter "exercise" (see Figure 21), or the target values ​​of health indicators themselves, such as "sleep time: 8 hours / day, exercise: 1 hour / day."

[0225] Furthermore, the set age is an arbitrary number set by the user. For example, the set age is either a target age set by the user before the estimated biological age is output, or a target age set by the user after they have confirmed the estimated biological age.

[0226] The set age is the target age used when estimating biological age, and therefore will be set to an age younger than the estimated current biological age.

[0227] The following describes an example of the process for estimating the target age and the number of days required to reach that age. Figure 28 is a diagram showing an example of the processing of the estimation unit according to the fourth embodiment. Figure 28 shows an example of estimating the target age and the number of days required to reach that age based on the target value for biological age entered by the user.

[0228] As shown in Figure 28, the acquisition unit 121 acquires, for example, target values ​​for biological age parameters related to lifestyle habits that can be varied by the user, such as "sleep time: 8h / day, exercise amount: 1h / day, etc." which are input as external terminal input information 23, and stores them in the memory unit 130.

[0229] The estimation unit 122 then uses the target values ​​of the biological age parameters stored in the memory unit 130 to estimate the user's biological age of "40" and sets it as the set age. The estimation unit 122 then estimates the required number of days, "30 days," which is the number of days required to reach the set age of "40" if the target biological age parameters "sleep time: 8 hours / day, exercise amount: 1 hour / day, etc." are maintained, based on the estimated current biological age of "43".

[0230] Furthermore, the estimation unit 122 can also estimate the number of days required according to the target biological age parameters. For example, when the user inputs the upper limit and variable values ​​of health indicators, which are target values ​​related to biological age, along with the target age set by the user, the estimation unit 122 can also estimate multiple target biological age parameters and the corresponding number of days required.

[0231] The following describes an example of the process for estimating multiple biological age parameters. Figure 29 shows an example of the processing of the estimation unit according to the fourth embodiment. Figure 29 shows an example of estimating multiple target biological age parameters and the corresponding number of days required, based on the target value for biological age entered by the user and the set age.

[0232] As shown in Figure 29, the acquisition unit 121 acquires, for example, the upper limit of the user's variable lifestyle biological age parameters, such as "sleep time: up to 10 hours / day, exercise amount: up to 1 hour / day, etc.", as a target value for biological age input as external terminal input information 23, and stores it in the memory unit 130. The acquisition unit 121 also acquires, for example, the target age "41" for biological age input by the user who has confirmed the estimated biological age "43", as a set age input as external terminal input information 23, and stores it in the memory unit 130.

[0233] The estimation unit 122 then estimates several target biological age parameters, such as "target sleep duration: 8 hours / day, target exercise duration: 0.5 hours / day, etc.," "target sleep duration: 10 hours / day, target exercise duration: 1 hour / day, etc.," and "target sleep duration: 6 hours / day, target exercise duration: 0.5 hours / day, etc.," within a range that does not exceed the upper limit of the biological age parameters stored in the memory unit 130.

[0234] The estimation unit 122 then uses each of the estimated target biological age parameters, along with the estimated biological age "43" and the set age "41," to estimate the number of days required to maintain each target biological age parameter. As an example, the estimation unit 122 estimates the number of days required for the target biological age parameters "target sleep duration: 8h / day, target exercise duration: 0.5h / day, etc." as "50 days," for the target biological age parameters "target sleep duration: 10h / day, target exercise duration: 1h / day, etc." as "20 days," and for the target biological age parameters "target sleep duration: 6h / day, target exercise duration: 0.5h / day, etc." as "70 days."

[0235] The output unit 123 outputs recommendation information regarding the user's lifestyle habits based on the difference between the user's biological age estimated by the estimation unit 122 and the target age. For example, the output unit 123 generates recommendation information encouraging the user to continue with the target biological age parameter entered by the user, depending on the magnitude of the difference between the biological age estimated by the estimation unit 122 and the aforementioned target age, and outputs it to the user terminal 30.

[0236] Furthermore, the output unit 123 outputs recommendation information indicating the number of days required if the user continues to maintain the target biological age parameters estimated by the estimation unit 122. For example, the output unit 123 generates recommendation information indicating the number of days required for the user's biological age to reach a set age if the user continues to maintain the target biological age parameters estimated by the estimation unit 122, and outputs it to the user terminal 30.

[0237] Furthermore, the output unit 123 outputs information that accepts target values ​​related to biological age from the user. For example, the output unit 123 generates a screen that accepts target values ​​related to biological age, such as exercise time, sleep time, and calorie intake, and displays it on the user terminal 30.

[0238] (Example display) Here, we will describe in order an example of the information that the output unit 123 outputs to the user terminal 30. Figures 30 and 31 show an example of data displayed by the output unit according to the fourth embodiment.

[0239] Figure 30 shows an example of content that accepts target values ​​for biological age entered by the user, and an example of recommendation information based on the set age determined according to the received information. As shown in Figure 30, the output unit 123 generates a screen that accepts input of target biological age parameters, namely a target value of "6 hours and 50 minutes" for sleep time and a target value of "4 hours and 15 minutes" for exercise time, and outputs it to the user terminal 30.

[0240] Furthermore, the output unit 123 can also display the average value of the biological age parameters over the past X days as a comparison point. In addition, the output unit 123 can enable users to input appropriate target values ​​by displaying the average value of the biological age parameters and the target biological age parameters in comparison to recommended values ​​for health indicators such as "slightly low" or "normal".

[0241] As shown in Figure 30, the output unit 123 can display the target value for sleep duration, "6 hours 10 minutes: low," and the target value for exercise duration, "3 hours 42 minutes: slightly low," as comparison values ​​for the biological age parameters over the past X days. In addition, if the user aims to maintain their current biological age parameters, the output unit 123 can also display a screen that accepts the biological age parameters over the past X days as the target biological age parameters.

[0242] The output unit 123 then displays the estimated biological age of "43" as of "July 22nd" and the set age of "41," and outputs recommendation information indicating the number of days "X days later" needed to reach the set age of "41." The output unit 123 also outputs recommendation information such as, "If you continue the target value you entered for X days, your biological age after X days will be 41 years old (actual age - 2 years)."

[0243] Figure 31 shows an example of information that accepts the user's target age. As shown in Figure 31, the output unit 123 generates a screen that accepts the user's target biological age as the target age and displays it on the user terminal 30. In addition, the output unit 123 can also display the average biological age of "43" over the past X days as a comparison point.

[0244] Here, the output unit 123 can, for example, if it receives input of either the target value of the biological age parameter or the required number of days in addition to the set age, generate recommendation information showing the estimated information for the other and output it to the user terminal 30. The output unit 123 also generates comments explaining the estimated information as recommendation information and outputs them to the user terminal 30.

[0245] For example, if the output unit 123 receives input of a set age of "41" and the required number of days of "20 days," it can generate recommendation information that includes the estimated target biological age parameter "Target sleep duration: 10 hours / day" and a comment such as "To reach the biological age you entered, you need to sleep 10 hours a day for 20 days."

[0246] (Process flow) Next, the processing flow of the cloud server 10D will be described. Figures 32 and 33 are flowcharts showing an example of information processing according to the fourth embodiment. Note that each step in the flowcharts shown in Figures 32 and 33 can be executed in a different order, and some processes may be omitted.

[0247] First, using Figure 32, we will explain an example of a process that outputs recommendations regarding the user's lifestyle habits based on the set age. The cloud server 10D obtains the biological age set in advance by the user (S701). Then, the cloud server 10D obtains input information 20 from at least one of the sensor detection information and external input information (S702). Then, the cloud server 10D records the obtained input information 20 along with the date and time information (S703).

[0248] The cloud server 10D then refers to the recorded information, fits a biological age estimation model, and estimates the user's second biological age (S704). Based on the second biological age and the target age, the cloud server 10D outputs recommendations regarding lifestyle habits (S705) and terminates the process.

[0249] Next, using Figure 33, we will explain an example of a process that estimates changes in biological age using the first biological age and outputs recommendations regarding the user's lifestyle based on the second biological age, the set age, and the aging rate. The cloud server 10D obtains setting parameters regarding the user's lifestyle (S801). Then, the cloud server 10D obtains input information 20 from at least one of the sensor detection information and external input information possessed by the user (S802).

[0250] The cloud server 10D then records the input information 20 along with the date and time information and the actual age (S803). The cloud server 10D then obtains the input information 20 regarding the first biological age obtained from the user's blood information (S804). The cloud server 10D then refers to the recorded information, fits a biological age estimation model, and estimates the user's second biological age (S805). The cloud server 10D then refers to the recorded information and estimates the user's aging rate based on the estimated biological age (S806).

[0251] The cloud server 10D then refers to the setting parameters and recorded information, fits a biological age estimation model, and estimates the user's set age (S807). Based on the second biological age, the set age, and the aging rate, the cloud server 10D outputs recommendations regarding lifestyle habits (S808) and terminates the process.

[0252] [Other examples] The processes described above are merely examples, and information processing systems 1A to 1D may perform a variety of processes not limited to those described above. For example, information processing systems 1A to 1D may perform the processes described in other embodiments, regardless of the descriptions in each of the embodiments described above.

[0253] Further effects and modifications can be readily derived by those skilled in the art. Therefore, broader aspects of the present invention are not limited to the specific details and representative embodiments expressed and described above. Accordingly, various modifications are possible without departing from the spirit or scope of the overall concept of the invention as defined by the appended claims and their equivalents.

[0254] The embodiments and modifications described above may also have the following configurations, but are not limited to them. (1) An acquisition means for acquiring sensor information detected by a sensor installed in one of the following water-related spaces: toilet, washroom, kitchen, or bathroom, storage means for storing said sensor information; estimation means for estimating the biological age of a user who uses the water-related space by referring to said sensor information stored in said storage means and applying a model for estimating biological age to said sensor information; output means for outputting information indicating the biological age of said user estimated by said estimation means; An information processing system comprising: (2) said storage means stores said sensor information together with date and time information, said output means outputs information indicating a change in the biological age of said user, The information processing system according to (1), characterized in that: (3) said storage means stores said sensor information together with date and time information, said estimation means estimates an aging rate in the biological age of said user, said output means outputs information indicating a change in said aging rate of said user, The information processing system according to (1) or (2), characterized in that: (4) said storage means stores information related to the chronological age of said user, said output means outputs information obtained by comparing the chronological age and the biological age of said user, The information processing system according to any one of (1) to (3), characterized in that:

Description of Reference Numerals

[0255] 1, 1A, 1B, 1C, 1D Information processing system 10, 10A, 10B, 10C, 10D Cloud server 20 Input information 30 User terminal 110 Communication unit 120 Control unit 121 Acquisition unit 122 Estimation unit 123 Output unit 130 Storage unit 211 Toilet 212 Bathroom 213 Washbasin 214 Kitchen 2111 Toilet equipment 2112 Toilet Sensor 2121 Bathroom equipment 2122 Bathroom Sensor 2131 Washbasin equipment 2132 Bathroom sink sensor 2141 Counter Unit 2142 Kitchen Sensor

Claims

1. A sensor comprising at least one of the following: a toilet sensor installed in a toilet and collecting excretion data or biometric data of the toilet user; a washbasin sensor installed in a washbasin and collecting biometric data of the washbasin user; a kitchen sensor installed in a kitchen and collecting biometric data of the kitchen user; and a bathroom sensor installed in a bathroom and collecting biometric data of the bathroom user. An acquisition means for acquiring sensor information collected by the aforementioned sensor together with information identifying the user, A storage means for storing the sensor information in association with information identifying the user and the date and time information on which the sensor information was acquired. Estimation means for estimating the biological age of a user of a water-related space by referring to the sensor information stored in the storage means and fitting a model for estimating biological age to the sensor information, wherein estimation means estimates the change in the biological age based on the sensor information corresponding to the user identified using information that identifies the user and the date and time information on which the sensor information was acquired, An output means that outputs information indicating the change in the user's biological age estimated by the estimation means, An information processing system characterized by having the following features.

2. The storage means stores the sensor information together with the date and time information on when the sensor information was acquired. The estimation means estimates the aging rate at the user's biological age based on the sensor information and the date and time information on which the sensor information was acquired. The output means outputs information indicating the change in the user's aging rate. The information processing system according to feature 1.

3. The storage means stores information regarding the user's actual age, The output means outputs information comparing the user's actual age and biological age. The information processing system according to feature 1.

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