Data Analysis System

Abstract

To provide appropriate support to the local community. [Solution] The data analysis system according to the embodiment is characterized by comprising: data acquisition means for acquiring detection data of plumbing fixtures installed in each of several houses; data storage means for storing the installation location of the plumbing fixtures and the detection data together with date and time information; and data analysis means for analyzing the detection data located within a predetermined area.

Description

Technical Field

[0001] The disclosed embodiments relate to a data analysis system.

Background Art

[0002] Conventionally, there has been known a technique for analyzing an individual's health status in combination with regional health characteristics and a regional social capital index (regional SCI) of a region, and presenting health advice considering regional characteristics to an individual (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the above-described conventional technology, it may not be possible to appropriately provide regional support. For example, in the conventional technology, since the health status of each resident is analyzed based on the results of a health examination, etc., there is a non-negligible time lag from when an impact appears on the health status of a resident until the health status is analyzed after receiving a health examination. That is, it is difficult to grasp the health status of a resident with high immediacy and provide regional support.

[0005] An object of the disclosed embodiments is to provide a data analysis system that can appropriately provide regional support.

Means for Solving the Problems

[0006] A data analysis system according to one embodiment is characterized by comprising: a data acquisition means for acquiring detection data of plumbing fixtures installed in each of several houses; a data storage means for storing the installation location of the plumbing fixtures and the detection data together with date and time information; and a data analysis means for analyzing the detection data located within a predetermined area.

[0007] According to a data analysis system in one embodiment, by analyzing detection data and installation locations of plumbing fixtures installed in each house, regional detection data can be analyzed with high real-time speed. In other words, the data analysis system makes it possible to appropriately provide regional support by utilizing the detection data of plumbing fixtures of residents in the region, which has been analyzed with high real-time speed.

[0008] The data acquisition means of a data analysis system according to one embodiment acquires user information relating to the user of the plumbing equipment with respect to the detection data, along with the detection data; the data storage means stores the user information and the detection data linked together; and the data analysis means analyzes the user's health status or lifestyle based on the detection data and the user information.

[0009] According to one embodiment of the data analysis system, the health status or lifestyle of users is analyzed based on detection data from plumbing equipment and user information. This allows for the real-time analysis of regional detection data and the acquisition of users' health status with high accuracy. In other words, the data analysis system links detection data from plumbing equipment with user information for analysis, enabling the appropriate analysis of individual users' health status or lifestyle and its use in community support.

[0010] In one embodiment of the data analysis system, the data acquisition means acquires product identification information set on the plumbing equipment, and identifies the installation location of the plumbing equipment from information recorded in an external database based on the acquired product identification information.

[0011] According to a data analysis system in one embodiment, the installation location can be identified from the identification number of the plumbing fixture, allowing for the immediate acquisition of region-specific analysis data. In other words, the data analysis system identifies the installation location using an external database to which product identification information unique to each plumbing fixture is associated, thus eliminating the need for manual input of the installation location and simplifying the work.

[0012] A data analysis system according to one embodiment includes output means for outputting analysis results from the data analysis means to an external source, and external data acquisition means for acquiring information request data from an external system that receives the outputted analysis results, wherein the data analysis means changes the mode of analysis to be output to the external system according to the acquired information request data.

[0013] According to one embodiment of the data analysis system, when outputting analysis results to an external system, the analysis results are modified to suit the external system's requirements and provided to the external system in a manner suitable for management by the external system, thereby enabling appropriate support for the local community. For example, the data analysis system adds items indicating changes in the state after the analysis results are provided to the analysis results, allowing the administrator of the external system to measure the effectiveness of using the data and take appropriate action according to the degree of effectiveness. To give a specific example, according to the data analysis system, an external system that manages stores can change the shelf layout of the store based on the analysis results, and take appropriate action such as further changing or reverting the shelf layout in response to changes in the health status of local residents after the change.

[0014] A data analysis system according to one embodiment further comprises a product management means which analyzes the user's health condition based on detection data detected by sensors in the plumbing equipment, and determines the type or quantity of products to be displayed on the shelves of stores located in a predetermined area corresponding to the detection data analyzed by the data analysis means, based on the analysis results of the data analysis means.

[0015] According to a data analysis system in one embodiment, the analyzed health status of users is used to determine the shelf layout of stores within a region. In other words, the data analysis system determines the shelf layout of stores based on the analyzed health status of residents within a predetermined region, thereby enabling the creation of a product assortment that is appropriate for the current situation of the local residents and providing appropriate support to the community.

[0016] A data analysis system according to one embodiment further comprises a delivery route management means that determines a delivery route for goods within a predetermined area corresponding to the detection data analyzed by the data analysis means, based on the analysis results of the data analysis means.

[0017] According to a data analysis system in one embodiment, the system determines delivery routes within a region using the analyzed lifestyle rhythms of users. In other words, the data analysis system determines delivery routes based on the lifestyle rhythms of residents within a predetermined region, enabling the execution of delivery routes that are in line with the living conditions of residents, such as whether they are out or at home, thereby providing appropriate community support.

[0018] A data analysis system according to one embodiment further comprises a shift management means that sets the patrol frequency of monitors or personnel shift information within a predetermined area corresponding to the detection data analyzed by the data analysis means, based on the analysis results of the data analysis means.

[0019] According to a data analysis system in one embodiment, security shifts within a region are determined using the analyzed lifestyle rhythms of users. In other words, the data analysis system determines security shifts based on the analyzed lifestyle rhythms of residents within a predetermined region, enabling optimal patrols and surveillance tailored to the living conditions of residents, such as whether they are out or at home, thereby providing appropriate support to the region.

[0020] A data analysis system according to one aspect of the embodiment further includes output means for outputting information from the data analysis system. The data analysis means analyzes a change in state in the predetermined area from the acquired detection data, and the output means transmits alert information based on the analysis result of the data analysis means.

[0021] According to a data analysis system according to one aspect of the embodiment, alert information corresponding to a change in state such as the analyzed health state of the user is transmitted. That is, according to the data analysis system, it is possible to appropriately provide regional support by transmitting necessary alerts based on the change tendency of the situation of residents in a predetermined area.

[0022] A data analysis system according to one aspect of the embodiment further includes external data acquisition means for acquiring regional information regarding a change in state within the predetermined area, and output means for outputting information from the data analysis system. The data analysis means generates the information according to the acquired regional information.

[0023] According to a data analysis system according to one aspect of the embodiment, an analysis result of detection data corresponding to regional information regarding a change in state within a region acquired from an external system is output. That is, according to the data analysis system, it is possible to provide detection data and analysis results of water-related equipment according to the infection state of a region acquired from a group within the region such as a local government or a medical facility, enabling the group within the region to confirm the change in the situation within the region and appropriately provide regional support.

Effect of the Invention

[0024] According to one aspect of the embodiment, regional support can be appropriately provided.

Brief Description of the Drawings

[0025] [Figure 1] FIG. 1 is a diagram showing a configuration example of a data analysis system according to the first embodiment. [Figure 2]Figure 2 shows an overview of the processing performed by the data analysis system according to the first embodiment. [Figure 3] Figure 3 shows an example of the configuration of the analysis server according to the first embodiment. [Figure 4] Figure 4 shows an example of detection data stored by the storage unit according to the first embodiment. [Figure 5] Figure 5 shows an example of detection data stored by the storage unit according to the first embodiment. [Figure 6] Figure 6 shows an example of the configuration of an external server according to the first embodiment. [Figure 7] Figure 7 is a sequence diagram showing an example of the processing flow performed by the data analysis system according to the first embodiment. [Figure 8] Figure 8 is a sequence diagram showing an example of the processing flow performed by the data analysis system according to the second embodiment. [Figure 9] Figure 9 is a diagram showing an overview of the processing performed by the data analysis system according to the second embodiment. [Figure 10] Figure 10 is a sequence diagram showing an example of the processing flow performed by the data analysis system according to the third embodiment. [Figure 11] Figure 11 is a diagram showing an overview of the processing performed by the data analysis system according to the fourth embodiment. [Figure 12] Figure 12 is a sequence diagram showing an example of the processing flow performed by the data analysis system according to the fourth embodiment. [Modes for carrying out the invention]

[0026] Hereinafter, with reference to the attached drawings, embodiments of a data analysis system, which is an example of the data analysis system disclosed in this application, will be described in detail. In the first embodiment, the process by which the data analysis system 1 analyzes health status etc. based on detection data obtained from plumbing equipment and modifies management data based on the analysis results will be described. In the second embodiment, the process by which the data analysis system 1 obtains analysis results with added data items indicating changes in the state of the region after the management data has been modified will be described. In the third embodiment, the process by which the data analysis system 1 issues alert information based on changes in the state of the region will be described. In the fourth embodiment, the process by which the data analysis system 1 generates and outputs analysis data corresponding to regional information acquired from an external source will be described. However, this invention is not limited to the embodiments shown below.

[0027] <First Embodiment> [Configuration of the data analysis system] First, with reference to Figure 1, an example configuration of the data analysis system according to the first embodiment will be described. Figure 1 is a diagram showing an example configuration of the processing system according to the first embodiment.

[0028] First, before giving a detailed description of the embodiments, an overview of the definitions of terms used in this application will be provided. 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 water-related spaces. For example, water-related equipment includes toilets, urinals, bathrooms, bathtubs, washbasins (vanity units), and various other water-related devices such as kitchens. For example, water-related equipment includes toilet equipment, bathroom equipment, washbasin equipment, kitchen equipment, etc.

[0029] 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 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 of the components (sensors, etc.) that realize 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."

[0030] For example, if a toilet has multiple (two) functions, such as a function to detect the consistency of stool using a stool sensor (image sensor, etc.) (also called a "stool detection function") and a function to detect gas (odor) using a gas sensor, etc. (also called a "gas detection function"), the toilet may be referred to as a plumbing device in relation to the functional equipment that implements the stool detection function and the functional equipment that implements the gas detection function. Furthermore, the functional equipment that implements the stool detection function and the functional equipment that implements the gas detection function that the toilet has may be referred to as plumbing devices if, for example, information is collected for each of those functional equipment. For example, when describing functional equipment as plumbing devices, a toilet with multiple such functional equipment may be referred to as a plumbing device. For example, if detection data is collected by only one of the following: another toilet, urinal, bathroom, bathtub, washbasin, kitchen, etc., then that one becomes a plumbing device, and each of the multiple functional equipment that that plumbing device has becomes a plumbing device.

[0031] In other words, if a toilet has multiple functional components, that toilet may be referred to as a plumbing fixture or plumbing device. Also, if a toilet has multiple functional components, each of those functional components may be referred to as a plumbing fixture or a functional component. In the following explanation, plumbing fixtures such as toilets, urinals, bathrooms, bathtubs, washbasins, kitchens, etc. may be read as plumbing devices, and plumbing fixtures that realize the multiple functions of a plumbing device may be read as functional components.

[0032] For example, detection data includes data (information) acquired from plumbing equipment when a user (also simply called "user") uses plumbing equipment to perform actions (behaviors) such as urination, bathing, washing face, brushing teeth, cooking, etc., in order to maintain the hygiene of the user of the plumbing equipment. For example, detection data includes data (information) detected by sensors regarding the user's actions (behaviors) when they use plumbing equipment, such as urination, bathing, washing face, brushing teeth, cooking, etc., in order to maintain the hygiene of the user.

[0033] For example, detection data may include measurement data taken by plumbing equipment. For example, detection data may include various types of data such as biometric data, excretion data, and log data (also simply called "log data") indicating the use of plumbing equipment. For example, detection data may be data to which at least one of the biometric data, excretion data, and log data is associated with account data corresponding to the user of the data (account identifier, user information, etc.), time data indicating the date and time the data was acquired (date and time information, etc.), and location data indicating the place where the data was acquired (plumbing space, location information, etc.).

[0034] For example, excretion data (also called "excretion information") includes various information (data) about what the user excretes (also called "excrement"). For example, excretion data includes various information (data) about what the user excretes, such as information (data) about the feces (also called "feces" or "defecation") the user excretes, information (data) about the user's excretory gases, etc. Here, excretory gases are not limited to flatulence (farts), which are gases released from the user themselves, but are a concept that includes gases released from objects (feces, urine, etc.) that the user excretes. In other words, excrement here includes various things that are produced in response to the user's excretion, such as defecation, urination, and excretory gases.

[0035] Furthermore, for example, biometric data (also called "biometric information") includes various types of information (data) obtained from the user (biological body). Biometric data includes not only the user's blood flow information (data) shown as an example below, but also various types of information (data) about the user's body, such as heart rate (pulse) information (data), respiration information (data), body temperature information (data), brainwave information (data), and muscle (electromyography) information (data).

[0036] For example, log data indicating the use of plumbing equipment is data (information) indicating the use of plumbing equipment, excluding biometric data and excretion data. For example, log data indicating the use of plumbing equipment includes the number of times the plumbing equipment is used, the frequency of use, and the duration of use. For example, if the plumbing equipment is related to a toilet, the log data includes the number of times the toilet is used, the frequency of use, whether or not the toilet seat is occupied, the duration of sitting on the toilet seat, and the number of times the body is washed per toilet use. Note that the above is merely an example, and log data may include various data (information) indicating the use of plumbing equipment other than biometric data and excretion data. Log data may also be read as log information or history information.

[0037] Thus, detection data includes various data (information) collected from plumbing equipment. For example, detection data includes excretion data such as stool consistency, stool volume, color, urine consistency, urine volume, color, and excretory gas characteristics. For example, detection data includes biological data such as blood flow data and body temperature data.

[0038] Based on the above, an example configuration of data analysis system 1 will be described below. Data analysis system 1 includes plumbing fixtures installed in house 2, an analysis server 100 that analyzes information detected by the plumbing fixtures, and an external server 300 that manages the analysis results and utilizes them for various purposes. Note that the configuration of data analysis system 1 shown in Figure 1 is merely an example, and any device configuration can be adopted as long as data analysis system 1 can perform the desired processing. The following describes each component of data analysis system 1. Note that house 2 is a collective term for house 2-1, house 2-2, and house 2-n, and below, unless distinguished from each other, they will be referred to as house 2.

[0039] (Analysis Server 100) The analysis server 100 is a server device that provides cloud services. The analysis server 100 analyzes detection data acquired from plumbing equipment to analyze the health status of the users of the plumbing equipment, and outputs the analysis results to the external server 300.

[0040] The analysis server 100 can communicate with plumbing equipment and external information processing devices such as the external server 300 via a communication unit implemented by a communication device, communication circuit, etc. For example, the analysis server 100 sends and receives information between the plumbing equipment and the external server 300 via the internet. More specifically, the analysis server 100 acquires detection data from the plumbing equipment via the internet. The analysis server 100 also transmits analysis results and other data to the external server 300 via the internet.

[0041] (Plumbing fixtures) Plumbing fixtures include, for example, plumbing fixtures such as toilets 210, bathrooms 220, and washbasins 230. Each plumbing fixture is installed in a structure such as a house 2. There may be multiple plumbing fixtures. For example, the data analysis system 1 may include multiple toilets 210, such as a toilet 210 installed on the first floor and a toilet 210 installed on the second floor of a predetermined structure (a house, etc.). Furthermore, the data analysis system 1 shown in Figure 1 is merely an example, and for example, the data analysis system 1 may include various components other than those shown in Figure 1. For example, the data analysis system 1 may include a kitchen. For example, the data analysis system 1 may include kitchen appliances and kitchen sensors, etc.

[0042] (toilet) Toilet 210 is a water-related space used by toilet users (users) for the act of defecation, and where detection data including information related to the user's defecation (excretion data), biometric data, and log data is collected. Toilet 210 is equipped with toilet devices 211, toilet sensors 212, etc. For example, toilet 210 transmits detection data of the user related to the toilet from at least one of the devices such as toilet devices 211 and toilet sensors 212 to analysis server 100. Note that toilet 210 may have multiple toilet devices 211 and multiple toilet sensors 212.

[0043] Toilet 210 collects user detection data related to toilet 210 using devices such as toilet equipment 211 and toilet sensors 212. For example, toilet 210 collects various information such as log data including toilet log data, daily detection data of the user, the user's health status derived from the daily detection data, sensing information, and advanced health status.

[0044] The toilet device 211 is a so-called toilet (toilet bowl), remote control device, etc., and is a device used by the toilet user (user) to perform the act of defecation. For example, if the toilet device 211 has a waste detection function, it may be equipped with a toilet sensor 212, which is a waste sensor used for the waste detection function. For example, if the toilet device 211 has a gas detection function, it may be equipped with a toilet sensor 212, which is a gas sensor used for the gas detection function.

[0045] The toilet device 211 can communicate with other devices such as the analysis server 100 via a communication unit implemented by a communication device, communication circuit, etc. The toilet device 211 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 211 may be connected to other devices in a communicative manner via a predetermined wireless communication function such as mobile communication or Wi-Fi (registered trademark). Alternatively, the toilet device 211 may be connected to other devices in a communicative manner via Bluetooth (registered trademark) functions such as BLE (Bluetooth Low Energy), for example, through communication via a gateway (GW).

[0046] The toilet device 211 is a plumbing device (water-related equipment) that is connected to the analysis server 100 via a predetermined network in a way that allows it to communicate with the analysis server 100. For example, the toilet device 211 sends and receives information to and from the analysis server 100 via the predetermined network. For example, the toilet device 211 sends detection data regarding toilet use to the analysis server 100.

[0047] For example, the toilet device 211 transmits detection data such as excretion data, biometric data, and log data to the analysis server 100. The toilet device 211 may also transmit the detection data to the analysis server 100 along with the date and time information on when the detection data was acquired. The toilet device 211 may also transmit detection data corresponding to a request from the analysis server 100 to the analysis server 100 in response to a request from the analysis server 100.

[0048] Furthermore, the toilet device 211 collects detection data for each user of the plumbing equipment who uses the toilet (toilet user). The toilet device 211 may also have a function to authenticate (identify) the user who uses the toilet 210. The toilet device 211 may use an account identifier (user ID, etc.) received from a remote control device or the like that accepts operations related to the toilet by the plumbing equipment user to identify which of the registered users the user is. For example, the toilet device 211 associates the collected detection data with the date and time the detection data was acquired and an account identifier (personal identification data) that identifies the user corresponding to the detection data, and transmits it to the analysis server 100. In this case, if the toilet device 211 receives a user designation from the analysis server 100, it may transmit the detection data corresponding to that user to the analysis server 100.

[0049] The toilet sensor 212 is a sensor device that detects the user's use of the toilet 210. For example, the toilet sensor 212 may be a sensor device mounted on the toilet unit 211. For example, the toilet sensor 212 may be a fecal sensor used for a fecal matter detection function. For example, the toilet sensor 212 may be a gas sensor used for a gas detection function. For example, the toilet sensor 212 may be a radio wave sensor used for a function to detect the amount of feces or urine excreted by the user. For example, the toilet sensor 212 may be a sensor device that detects (receives) operations such as flushing of the toilet unit 211.

[0050] For example, the toilet sensor 212 may be a sensor device such as a sensor that detects the use of the toilet equipment 211. For example, the toilet sensor 212 may be a sensor device such as a sensor that detects the entry and exit of a user into the toilet 210. For example, the toilet sensor 212 may be a sensor device such as a sensor that detects the duration of use of the toilet 210 by a user. For example, the toilet sensor 212 may be a sensor device such as a seating sensor that detects when someone sits on the toilet seat of the toilet equipment 211. The toilet sensor 212 may be a flush button having large and small types that detect the use of either the large or small toilet. Note that the above are merely examples, and the toilet sensor 212 may be a sensor device such as a sensor device provided separately from the toilet equipment 211. For example, the toilet sensor 212 may be a sensor device such as a pyroelectric sensor using infrared signals or a μ (micro) wave sensor (such as a human presence sensor).

[0051] The toilet sensor 212 can communicate with other devices such as the analysis server 100 via a communication unit implemented by a communication device, communication circuit, etc. The toilet sensor 212 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 212 may also be connected to other devices via a predetermined wireless communication function such as Wi-Fi or Bluetooth.

[0052] The toilet sensor 212 is a functional device (water-related equipment) that is connected to the analysis server 100 via a predetermined network in a way that allows it to communicate with the analysis server 100. For example, the toilet sensor 212 sends and receives information to and from the analysis server 100 via the predetermined network. For example, the toilet sensor 212 transmits detection data regarding toilet use to the analysis server 100.

[0053] For example, the toilet sensor 212 transmits detection data such as excretion data, biometric data, and log data to the analysis server 100. The toilet sensor 212 may also transmit the detection data to the analysis server 100 along with the date and time information on when the detection data was acquired. The toilet sensor 212 may also transmit detection data corresponding to a request from the analysis server 100 to the analysis server 100 in response to a request from the analysis server 100.

[0054] Furthermore, the toilet sensor 212 collects detection data for each user of the plumbing equipment. The toilet sensor 212 may have a storage means (such as a memory device) for managing (registering) detection data for each user of the plumbing equipment. The toilet sensor 212 may have a function for authenticating (identifying) the user who uses the toilet 210. The toilet sensor 212 may use an account identifier (such as a user ID) received from a remote control device or the like that accepts operations related to the toilet by the toilet user (user of the plumbing equipment) to identify which of the registered users the user is. For example, the toilet sensor 212 associates the collected detection data with the date and time the detection data was acquired and an account identifier that identifies the user corresponding to the detection data, and transmits it to the analysis server 100. In this case, if the toilet sensor 212 receives a user designation from the analysis server 100, it may transmit the detection data corresponding to that user to the analysis server 100.

[0055] (bathroom) Bathroom 220 is a bathroom space used by a user to perform bathing activities, and is a water-related space where detection data, including biometric data and log data such as bathing time and bathing temperature, is collected. Bathroom 220 is equipped with bathroom devices 221, bathroom sensors 222, etc. For example, bathroom 220 transmits detection data of the user related to the bathroom from at least one of the devices such as bathroom devices 221 and bathroom sensors 222 to the analysis server 100. Note that bathroom 220 may have multiple bathroom devices 221 and multiple bathroom sensors 222.

[0056] Bathroom 220 collects user detection data related to the bathroom 220 using devices such as bathroom equipment 221 and bathroom sensors 222. For example, bathroom 220 collects various information such as bathroom temperature and faucet water temperature.

[0057] Bathroom equipment 221 is a so-called bathtub, shower, etc., and is equipment used by the user of the bathroom to perform the act of bathing. For example, if bathroom equipment 221 has a bathroom temperature detection function, it may be equipped with a bathroom sensor 222, which is a temperature sensor used for the bathroom temperature detection function. For example, if bathroom equipment 221 has a faucet water temperature detection function, it may be equipped with a bathroom sensor 222, which is a temperature sensor used for the faucet water temperature detection function.

[0058] The bathroom device 221 can communicate with other devices such as the analysis server 100 via a communication unit implemented by a communication device, communication circuit, etc. The bathroom device 221 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 221 may also be connected to other devices via a predetermined wireless communication function such as Wi-Fi or Bluetooth.

[0059] The bathroom device 221 is a plumbing device (water-related equipment) that is connected to the analysis server 100 via a predetermined network in a way that allows it to communicate with the analysis server 100. For example, the bathroom device 221 sends and receives information to and from the analysis server 100 via the predetermined network. For example, the bathroom device 221 sends detection data regarding the use of the bathroom to the analysis server 100.

[0060] For example, the bathroom device 221 transmits detection data such as biometric data and log data to the analysis server 100. The bathroom device 221 may transmit the detection data to the analysis server 100 along with the date and time information on when the detection data was acquired. The bathroom device 221 may also transmit detection data corresponding to a request from the analysis server 100 to the analysis server 100 in response to a request from the analysis server 100.

[0061] Furthermore, the bathroom device 221 collects detection data for each user of plumbing fixtures. The bathroom device 221 may also have a function to authenticate (identify) the user using the bathroom 220. The bathroom device 221 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 fixtures) to identify which of the registered users the user is. For example, the bathroom device 221 associates the collected detection data with the date and time the detection data was acquired and an account identifier that identifies the user corresponding to the detection data, and sends it to the analysis server 100. In this case, if the bathroom device 221 receives a user designation from the analysis server 100, it may send the detection data corresponding to that user to the analysis server 100.

[0062] The bathroom sensor 222 is a sensor device that detects the user's use of the bathroom 220. For example, the bathroom sensor 222 may be a sensor device mounted on the bathroom device 221. For example, the bathroom sensor 222 may be a temperature sensor used for a bathroom temperature detection function. For example, the bathroom sensor 222 may be a temperature sensor used for a faucet water temperature detection function.

[0063] For example, the bathroom sensor 222 may be a sensor device such as a sensor that detects the use of the bathroom equipment 221. For example, the bathroom sensor 222 may be a sensor device such as a sensor that detects the user entering and leaving the bathroom 220. For example, the bathroom sensor 222 may be a sensor device such as a sensor that detects the user's usage time of the bathroom 220. For example, the bathroom sensor 222 may be a sensor device such as a motion sensor that detects bathing in the bathroom equipment 221. Note that the above are merely examples, and the bathroom sensor 222 may be a sensor device such as a sensor device provided separately from the bathroom equipment 221. For example, the bathroom sensor 222 may be a sensor device such as a pyroelectric sensor using infrared signals or a μ (microwave) sensor (motion sensor, etc.).

[0064] The bathroom sensor 222 can communicate with other devices such as the analysis server 100 via a communication unit implemented by a communication device, communication circuit, etc. The bathroom sensor 222 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 222 may also be connected to other devices via a predetermined wireless communication function such as Wi-Fi or Bluetooth.

[0065] The bathroom sensor 222 is a functional device (water-related equipment) that is connected to the analysis server 100 via a predetermined network in a communicative manner. For example, the bathroom sensor 222 sends and receives information to and from the analysis server 100 via the predetermined network. For example, the bathroom sensor 222 transmits detection data regarding the use of the bathroom to the analysis server 100.

[0066] For example, the bathroom sensor 222 transmits detection data such as biometric data and log data to the analysis server 100. The bathroom sensor 222 may also transmit the detection data to the analysis server 100 along with the date and time information on when the detection data was acquired. The bathroom sensor 222 may also transmit detection data corresponding to a request from the analysis server 100 to the analysis server 100 in response to a request from the analysis server 100.

[0067] Furthermore, the bathroom sensor 222 collects detection data for each user of plumbing fixtures. The bathroom sensor 222 may have a storage means (such as a memory device) for managing (registering) detection data for each user of plumbing fixtures. The bathroom sensor 222 may also have a function for authenticating (identifying) users who use the bathroom 220. The bathroom sensor 222 may use an account identifier (such as a user ID) received from a remote control device or the like 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. For example, the bathroom sensor 222 associates the collected detection data with the date and time the detection data was acquired and an account identifier that identifies the user corresponding to the detection data, and transmits it to the analysis server 100. In this case, if the bathroom sensor 222 receives a user designation from the analysis server 100, it may transmit the detection data corresponding to that user to the analysis server 100.

[0068] (Washbasin) The washbasin 230 is configured for use by a user of the washbasin, and is a water-related space where detection data, including biometric data and log data such as washbasin usage time, is collected. The washbasin 230 is equipped with a washbasin device 231, a washbasin sensor 232, etc. For example, the washbasin 230 transmits detection data of the user related to the washbasin from at least one of the devices such as the washbasin device 231 and the washbasin sensor 232 to the analysis server 100. Note that the washbasin 230 may have multiple washbasin devices 231 and multiple washbasin sensors 232.

[0069] The washbasin 230 collects user detection data related to the washbasin 230 using devices such as the washbasin unit 231 and the washbasin sensor 232. For example, the washbasin 230 collects various information such as facial expressions and blood circulation in the face.

[0070] The washbasin device 231 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 231 has a function to detect the user's facial expression, it may be equipped with a washbasin sensor 232, which is an image sensor used for the function to detect the user's facial expression. For example, if the washbasin device 231 has a function to detect the blood flow of the user's face, it may be equipped with a washbasin sensor 232, which is a blood flow sensor used for the function to detect the blood flow of the user's face.

[0071] The washbasin unit 231 can communicate with other devices such as the analysis server 100 via a communication unit implemented by a communication device, communication circuit, etc. The washbasin unit 231 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 231 may also be connected to other devices via a predetermined wireless communication function such as Wi-Fi or Bluetooth.

[0072] The washbasin unit 231 is a plumbing device (water-related equipment) that is connected to the analysis server 100 via a predetermined network in a way that allows it to communicate with the analysis server 100. For example, the washbasin unit 231 sends and receives information to and from the analysis server 100 via the predetermined network. For example, the washbasin unit 231 transmits detection data regarding the use of the washbasin to the analysis server 100.

[0073] For example, the washbasin device 231 transmits detection data such as biometric data and log data to the analysis server 100. The washbasin device 231 may transmit the detection data to the analysis server 100 along with the date and time information on when the detection data was acquired. The washbasin device 231 may also transmit detection data corresponding to a request from the analysis server 100 to the analysis server 100 in response to a request from the analysis server 100.

[0074] Furthermore, the washbasin device 231 collects detection data for each user of the plumbing equipment. The washbasin device 231 may also have a function to authenticate (identify) the user using the washbasin 230. The washbasin device 231 may use an account identifier (user ID, etc.) received from a remote control device or the like that accepts operations related to the washbasin by the washbasin user (user of the plumbing equipment) to identify which of the registered users the user is. For example, the washbasin device 231 associates the collected detection data with the date and time the detection data was acquired and an account identifier that identifies the user corresponding to the detection data, and transmits it to the analysis server 100. In this case, if the washbasin device 231 receives a user designation from the analysis server 100, it may transmit the detection data corresponding to that user to the analysis server 100.

[0075] The washbasin sensor 232 is a sensor device that detects the user's use of the washbasin 230. For example, the washbasin sensor 232 may be a sensor device mounted on the washbasin unit 231. For example, the washbasin sensor 232 may be an image sensor used for detecting the user's facial expressions. For example, the washbasin sensor 232 may be a blood flow sensor used for detecting the blood circulation in the user's face.

[0076] For example, the washbasin sensor 232 may be a sensor device such as a sensor that detects the use of the washbasin unit 231. For example, the washbasin sensor 232 may be a sensor device such as a sensor that detects the entry and exit of a user to the washbasin 230. For example, the washbasin sensor 232 may be a sensor device such as a sensor that detects the usage time of the user of the washbasin 230. For example, the washbasin sensor 232 may be a sensor device such as a motion sensor that detects the use of the washbasin to the washbasin unit 231. Note that the above are merely examples, and the washbasin sensor 232 may be a sensor device such as a sensor device provided separately from the washbasin unit 231. For example, the washbasin sensor 232 may be a sensor device such as a pyroelectric sensor using infrared signals or a μ (microwave) sensor (motion sensor, etc.).

[0077] The sink sensor 232 can communicate with other devices such as the analysis server 100 via a communication unit implemented by a communication device, communication circuit, etc. The sink sensor 232 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 232 may also be connected to other devices via a predetermined wireless communication function such as Wi-Fi or Bluetooth.

[0078] The sink sensor 232 is a functional device (water-related equipment) that is connected to the analysis server 100 via a predetermined network in a communicative manner. For example, the sink sensor 232 sends and receives information to and from the analysis server 100 via the predetermined network. For example, the sink sensor 232 transmits detection data regarding the use of the sink to the analysis server 100.

[0079] For example, the sink sensor 232 transmits detection data such as biometric data and log data to the analysis server 100. The sink sensor 232 may also transmit the detection data to the analysis server 100 along with the date and time information on when the detection data was acquired. The sink sensor 232 may also transmit detection data corresponding to a request from the analysis server 100 to the analysis server 100 in response to a request from the analysis server 100.

[0080] Furthermore, the washbasin sensor 232 collects detection data for each user of the plumbing fixtures. The washbasin sensor 232 may have a storage means (such as a storage device) for managing (registering) detection data for each user of the plumbing fixtures. The washbasin sensor 232 may also have a function for authenticating (identifying) the user who uses the washbasin 230. The washbasin sensor 232 may use an account identifier (such as a user ID) received from a remote control device or the like that accepts operations related to the washbasin by the washbasin user (user of the plumbing fixtures) to identify which of the registered users the user is. For example, the washbasin sensor 232 associates the collected detection data with the date and time the detection data was acquired and an account identifier that identifies the user corresponding to the detection data, and transmits it to the analysis server 100. In this case, if the washbasin sensor 232 receives a user designation from the analysis server 100, it may transmit the detection data corresponding to that user to the analysis server 100.

[0081] In the following, when describing water-related spaces such as toilets 210, bathrooms 220, and washbasins 230 without distinction, they may be referred to as water-related spaces 200. Similarly, when describing water-related equipment (water fixtures) such as toilets 211, bathrooms 221, and washbasins 231 without distinction, they may be referred to as water-related equipment 201. Furthermore, when describing functional equipment (water-related equipment) such as toilet sensors 212, bathroom sensors 222, and washbasin sensors 232 without distinction, they may be referred to as functional equipment 202.

[0082] As described above, each water-related space 200 has a water-related device 201 and functional equipment 202, and transmits detection data from the water-related device 201, functional equipment 202, etc. to the analysis server 100. In addition, each water-related space 200 may transmit information (raw sensor data, etc.) detected (acquired) by functional equipment 202 such as sensors as detection data to the analysis server 100, or it may process the information (raw sensor data, etc.) detected (acquired) by functional equipment 202 and transmit the processed data as detection data to the analysis server 100.

[0083] The aforementioned plumbing device 201 or functional device 202 can identify an individual through personal authentication. For example, the plumbing device 201 identifies the user by communicating with a terminal device brought into the plumbing space by the user and performing personal authentication. Personal authentication by the plumbing device 201 or functional device 202 may also be performed by operation by the user. For example, the plumbing device 201 or functional device 202 identifies the user by detecting the pressing of a button provided on the device for identifying each user.

[0084] (External server 300) The external server 300 is a server device that provides cloud services. The external server 300 implements an external system located outside the analysis server 100. The external system is a system that provides various services, such as managing products displayed in stores, managing delivery routes for packages, managing the shifts of security personnel, preventing the spread of infectious diseases, and managing promotions. The external server 300 utilizes the analysis results from the analysis server for various purposes, such as determining shelf allocation for products, determining delivery routes for packages, setting shifts for security personnel, determining infectious disease prevention measures, and determining promotion plans. For example, the external server 300 determines the shelf allocation of products in stores within a specified area based on health status information for a specified area output from the analysis server 100, and transmits the determined shelf allocation information to the stores.

[0085] The external server 300 can communicate with external information processing devices such as the analysis server 100 via a communication unit implemented by a communication device, communication circuit, etc. The external server 300 is connected to a predetermined network such as the Internet by wired or wireless connection and transmits and receives information with the external information processing device. The external server 300 may also be connected to the external information processing device via a predetermined wireless communication function such as Wi-Fi.

[0086] [Overall picture of the data analysis system's processing] Next, with reference to Figure 2, the overall process performed by the data analysis system 1 according to the first embodiment will be described. Figure 2 is a diagram showing the overall process performed by the data analysis system 1 according to the first embodiment. Figure 2 shows the flow from the acquisition of detection data for plumbing equipment to the utilization of the analysis results in services provided to the community.

[0087] First, the data acquisition means obtains detection data, user information, and product identification information from plumbing fixtures installed in each house. It also obtains information from an external database that associates product identification information, user information, and installation location. Next, the data storage means links the detection data of the plumbing fixtures with the user information. Subsequently, the data storage means identifies the installation location of each plumbing fixture by referring to the information that associates product identification information with the installation location. In other words, the data storage means stores the detection data linked to the installation location and date / time information.

[0088] Next, the external data acquisition means acquires information from an external system that requests analysis results. For example, the external data acquisition means acquires information from an external system that requests the health status or lifestyle rhythm of a predetermined region. Subsequently, the data analysis means, upon receiving the request for analysis results, creates region-specific analysis data based on the detection data and user information stored in the data storage means. For example, the data analysis means performs an analysis on the detection data of a predetermined region for which an analysis result request has been received, and obtains the health status and lifestyle rhythm of that region. Subsequently, the output means transmits the analysis results to the management means. The management means then modifies the management data based on the analysis results. For example, the management means changes the types and quantities of goods displayed in stores in a predetermined region according to the health status of that region.

[0089] Through a series of processes, as exemplified above, the data analysis system 1 enables appropriate community support by utilizing detection data of plumbing fixtures within a region, which has been analyzed with high real-time accuracy. In other words, the data analysis system 1 enables appropriate community support by allowing service providers in the region to utilize health status information obtained from the detection data of plumbing fixtures used daily by local residents.

[0090] Furthermore, when various advice was given to individuals in the community to improve their health, it was necessary for each individual to change their behavior, such as receiving the suggested services or engaging in the suggested activities, which placed an excessive economic and mental burden on them. However, according to data analysis system 1, it is possible to realize a system for promoting health by measuring and analyzing health characteristics and social characteristics and then implementing policies and advice based on that.

[0091] [Configuration of the analysis server] Next, with reference to Figure 3, an example of the configuration of the analysis server 100 according to the first embodiment will be described. Figure 3 is a diagram showing an example of the configuration of the analysis server 100 according to the first embodiment. The analysis server 100 shown in Figure 3 has a communication unit 110, a storage unit 120, and a control unit 130. The analysis server 100 may also have an input unit (e.g., a keyboard or mouse) that accepts various operations from the administrator of the analysis server 100, and a display unit (e.g., a liquid crystal display) for displaying various information.

[0092] (Communications Department 110) The communication unit 110 is implemented, for example, by a communication device, a communication circuit, etc. The communication unit 110 is connected to any network such as the Internet by wired or wireless connection and transmits and receives information with an external information processing device. The communication unit 110 may also be connected to an external information processing device in a communicative manner by a predetermined wireless communication function such as Wi-Fi.

[0093] For example, the communication unit 110 transmits and receives information with other devices in the plumbing space 200, such as plumbing equipment 201, functional equipment 202, and an external server 300. For example, the communication unit 110 is connected via the Internet to multiple plumbing devices such as plumbing equipment 201 and functional equipment 202, and to the external server 300, and transmits and receives information. In this way, the communication unit 110 is a connection means that enables multiple plumbing devices to communicate via a predetermined network.

[0094] (Storage unit 120) The storage unit 120 is implemented by, for example, a semiconductor memory element such as RAM (Random Access Memory) or flash memory, or a storage device such as a hard disk or optical disc. For example, the storage unit 120 is a computer-readable recording medium that non-temporarily records data used by an information processing program. The storage unit 120 stores the identification information (user ID, etc.) of the user of the plumbing equipment. The storage unit 120 stores the detection data acquired from the plumbing equipment in association with the identification information (user ID, etc.) of the user of the plumbing equipment.

[0095] The memory unit 120 stores user information relating to users of plumbing equipment, with residents being an example. The user information includes various information about the user associated with an account identifier that identifies the corresponding user. For example, the user information may include information indicating the terminal device used by that user. The user information may also include various personal information such as name, address, gender, and age. In addition, the user information may include information about the resident's lifestyle. Furthermore, the user information may include demographic information such as the user's age and gender, as well as psychographic information. Demographic information such as age and gender, as well as psychographic information, may be used for analysis. The user information is linked to detection data. Note that the user's identification information may be stored anonymized.

[0096] The memory unit 120 stores information about the installation location of the plumbing fixtures. The installation location of the plumbing fixtures is, for example, the address of the house 2 where the plumbing fixtures are installed. The installation location of the plumbing fixtures is stored in association with detection data and date and time information.

[0097] The memory unit 120 stores various information, such as user detection data. The memory unit 120 functions as a storage means for storing detection data acquired from the water-related space 200. The memory unit 120 functions as a storage means for storing detection data received from multiple water-related devices such as the water-related equipment 201 and functional devices 202. For example, the memory unit 120 functions as a storage means for storing detection data acquired from water-related devices such as the toilet equipment 211. For example, the memory unit 120 functions as a storage means for storing detection data acquired from water-related devices such as the bathroom equipment 221.

[0098] The storage unit 120 stores detection data such as biometric data and excretion data, associated with an account identifier (personal identification data such as a user ID) used to identify each user. For example, when a user uses plumbing equipment such as the plumbing device 201, the storage unit 120 stores the user's detection data associated with the account identifier identified by the user's own operation. The storage unit 120 also stores the detection data associated with the date and time information on which the detection data was acquired.

[0099] Here, with reference to Figure 4, an example of detection data stored by the storage unit 120 according to the first embodiment is shown. Figure 4 is a diagram showing an example of detection data stored by the storage unit 120 according to the first embodiment. For example, as shown in Figure 4, the storage unit 120 stores information associated with "product ID, installation location, date and time information, detection data," etc. "Product ID" indicates a number that identifies the plumbing equipment. "Installation location" indicates the place where the plumbing equipment is installed. The installation location is indicated, for example, by region and house. "Date and time information" indicates the date and time when the use of the plumbing equipment was detected. The date and time may also be a period. "Detection data" indicates the type and content of the detection data. Note that in Figure 4, only the type of detection data is shown for explanatory purposes, but the detection data includes data detected by each plumbing equipment.

[0100] Let's explain using product "ID:01" in Figure 4 as an example. The memory unit 120 stores the information that "the plumbing equipment of product ID01 installed in house (1) in area A detected toilet use on 2024 / 10 / 31."

[0101] The memory unit 120 stores the analysis results. The analysis results include information such as the user's health status, the user's lifestyle, the health status of the community, and the lifestyle of the community. The user's health status indicates that the user is in various conditions such as "constipation, diarrhea, frequent nighttime urination, or frailty." The user's lifestyle indicates information such as the user's going out (staying at home) and activity levels. The community's health status provides an overview of the health status of users in the community, such as "many users suffer from constipation." The community's lifestyle also provides an overview of the living conditions of users in the community, such as "people often go out between **:** and **:**." Note that the community's health status and living conditions may be expressed as percentages in addition to expressions such as "many."

[0102] Here, with reference to Figure 5, an example of analysis results stored by the storage unit 120 according to the first embodiment is shown. Figure 5 is a diagram showing an example of analysis results stored by the storage unit 120 according to the first embodiment. For example, as shown in Figure 5, the storage unit 120 stores analysis results associated with "region, analysis items, analysis content," etc. "Region" indicates the identification number of each region. "Analysis items" indicate the items of information obtained by analyzing the detection data. Analysis items include, for example, health status and lifestyle rhythm. "Content" indicates the information obtained by analyzing the detection data. Content includes, for example, information such as whether there are many or few residents in the target region with conditions such as constipation, diarrhea, or nocturia, or whether there is a lot or little going out in the target region.

[0103] Let's explain using Area A in Figure 5 as an example. The memory unit 120 stores the analysis result that "the residents of Area A have a health condition in which they 'often experience constipation, rarely diarrhea, and frequently urinate at night,' and they lead a lifestyle that involves a lot of going out."

[0104] The memory unit 120 stores detection data related to the toilet 210. The memory unit 120 also stores detection data related to the bathroom 220. Furthermore, the memory unit 120 stores detection data related to the washbasin 230. Finally, the memory unit 120 stores detection data related to the kitchen. In this way, the memory unit 120 stores detection data acquired from each plumbing fixture.

[0105] (Control unit 130) The control unit 130 may be, for example, an information processing device (control device) that controls various configurations and processes. The control unit 130 may have, for example, a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit), and may be implemented by executing a program (for example, the information processing program according to this disclosure) stored inside the control unit 130 using RAM or the like as a working area. The control unit 130 may also have, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0106] As shown in Figure 3, the control unit 130 includes a data acquisition unit 131, a data analysis unit 132, an external data acquisition unit 133, and an output unit 134, and realizes or executes the information processing functions and operations described below. Note that the internal configuration of the control unit 130 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.

[0107] (Data acquisition unit 131) The data acquisition unit 131 receives various information from other devices via the communication unit 110, which is a connection means. The data acquisition unit 131 acquires information from plumbing equipment 201, functional equipment 202, etc. in the plumbing space 200. For example, the data acquisition unit 131 acquires detection data from plumbing equipment such as plumbing equipment 201, functional equipment 202, etc. in the plumbing space 200. For example, the data acquisition unit 131 acquires detection data from plumbing equipment installed in each of the multiple houses 2.

[0108] To give a specific example, the data acquisition unit 131 acquires detection data from the toilet sensor 212 indicating that the resident of house 2 is using the toilet equipment 211. The data acquisition unit 131 also acquires detection data from the bathroom sensor 222 indicating that the resident of house 2 is using the bathroom equipment 221. The data acquisition unit 131 also acquires detection data from the washbasin sensor 232 indicating that the resident of house 2 is using the washbasin equipment 231.

[0109] The data acquisition unit 131 acquires user information about the user of the plumbing equipment related to the detection data, along with the detection data. For example, the data acquisition unit 131 acquires user information along with the detection data and stores the detection data and user information in the storage unit 120 in association with each other.

[0110] As an alternative example, the data acquisition unit 131 acquires product identification information set on the plumbing fixture and identifies the installation location of the plumbing fixture from the information recorded in the external database based on the acquired product identification information. Here, the external database is a database that stores information such as product identification information, the owner of the plumbing fixture indicated by the product identification information, the installation location, and the owner's attributes in association with each other. For example, the data acquisition unit 131 refers to the product identification information and installation location stored in the external database to identify the installation location that corresponds to the product identification information set on the plumbing fixture.

[0111] (Data Analysis Department 132) The data analysis unit 132 analyzes detection data within a designated area. Based on the detection data and user information detected by plumbing equipment installed within the designated area, the data analysis unit 132 analyzes the user's health status or lifestyle rhythm.

[0112] Here, the health status analyzed by the data analysis unit 132 includes various conditions that can be estimated using the number of detections and detection dates and times detected by plumbing equipment, such as constipation, diarrhea, nocturia, and frailty. As an example, to explain how to determine whether a user has diarrhea from the detection data, this may be done by performing a threshold determination on the number of times the user used the toilet 210's full flush during a predetermined period. The analysis of health status by the data analysis unit 132 is not limited to the above example, as long as it is a determination method using detection data.

[0113] Furthermore, the lifestyle rhythm analyzed by the data analysis unit 132 includes various user conditions that can be estimated using the number of detection data and detection dates and times detected by plumbing equipment, such as the user's status of going out (or staying at home) and activity time. As an example, to explain how to estimate the user's status of going out from detection data, if the period during which no detection data indicating that the user used plumbing equipment is obtained exceeds a predetermined period, it is determined that the user was out during that period.

[0114] The data analysis unit 132 uses the above method to determine from the detection data whether the user falls under any of the various health conditions or situations, and analyzes the user's health condition or lifestyle rhythm. For example, the data analysis unit 132 analyzes the detection data of users who have used plumbing equipment, which is associated with user information, to obtain information such as the user's health condition "diarrhea, frequent nighttime urination" or lifestyle rhythm "**:**~**:** out and about".

[0115] As an alternative example, the data analysis unit 132 analyzes the health status or lifestyle rhythm of a region. For example, the data analysis unit 132 aggregates information on the health status or lifestyle rhythm of each user within a predetermined region to obtain trends in the health status or lifestyle rhythm of that region. For example, the data analysis unit 132 obtains information indicating "Diarrhea: High" for region A if the number of users in region A with the health status "Diarrhea" is above a predetermined percentage of the total number of users in region A. Similarly, the data analysis unit 132 obtains information indicating "Diarrhea: Low" for region B if the number of users in region B with the health status "Diarrhea" is below a predetermined percentage of the total number of users in region B. Note that expressions indicating proportions or numbers such as "high" and "low" may also be numerical values ​​such as percentages. For example, the data analysis unit 132 analyzes and aggregates the detection data for region A to obtain information indicating "Diarrhea: 38%" for region A.

[0116] Furthermore, the data analysis unit 132 obtains information indicating that the lifestyle rhythm of region A is "frequently out (**:**~**:**)" if the number of users in region A whose lifestyle rhythm is "**:**~**:** out" is at least a predetermined ratio to the total number of users in region A. Note that the lifestyle rhythm of a region is analyzed by time of day, and different results may be obtained depending on the time of day, even within the same region.

[0117] In other words, the data analysis unit 132 aggregates the health status and lifestyle rhythms of users within a predetermined region that has been analyzed, and obtains information on the percentage of users who meet each predetermined condition as the health status and lifestyle rhythms of the predetermined region.

[0118] (External data acquisition unit 133) The external data acquisition unit 133 acquires information request data from an external system that receives the outputted analysis results. For example, the external data acquisition unit 133 acquires data from an external server 300 requesting analysis results obtained by analyzing detection data for a predetermined region. More specifically, the external data acquisition unit 133 acquires data from an external server 300 requesting the health status and lifestyle rhythm of region A.

[0119] (Output section 134) The output unit 134 outputs the analysis results from the data analysis unit 132 to an external source. For example, the output unit 134 outputs the health status and lifestyle rhythm of a predetermined region, which have been analyzed by the data analysis unit 132, to an external source. To give a specific example, the output unit 134 outputs the information obtained by the data analysis unit 132, "Health status of region A: Constipation: frequent, Diarrhea: infrequent, Nocturia: infrequent" and lifestyle rhythm: "Frequent outings," to an external server 300.

[0120] Furthermore, if the analysis server 100 has a management unit 332, which will be described later, the output unit 134 can output management data that has been changed, decided, or set by the management unit 332, in addition to the analysis results from the data analysis unit 132.

[0121] [External Server Configuration] Next, with reference to Figure 6, an example of the configuration of the external server 300 according to the first embodiment will be described. Figure 3 is a diagram showing an example of the configuration of the external server 300 according to the first embodiment. The external server 300 shown in Figure 6 has a communication unit 310, a storage unit 320, and a control unit 330. The external server 300 may also have an input unit that receives various operations from the administrator of its own device, etc., and a display unit for displaying various information.

[0122] (Communications Department 310) The communication unit 310 is implemented, for example, by a communication device, a communication circuit, etc. The communication unit 310 is connected to any network such as the Internet by wired or wireless connection and transmits and receives information with an external information processing device. The communication unit 310 may also be connected to an external information processing device in a communicative manner by a predetermined wireless communication function such as Wi-Fi.

[0123] For example, the communication unit 310 transmits and receives information with other devices such as the analysis server 100. For example, the communication unit 310 is connected to the analysis server 100 via the Internet and transmits and receives information. In this way, the communication unit 310 is a connection means that is connected in a way that enables communication via a predetermined network.

[0124] (Storage unit 320) The storage unit 320 is implemented by, for example, semiconductor memory elements such as RAM and flash memory, or storage devices such as hard disks and optical discs. For example, the storage unit 320 is a computer-readable recording medium that non-temporarily records data used by information processing programs.

[0125] The memory unit 320 stores management data. Management data includes, for example, product management data, delivery management data, security management data, promotion management data, and infectious disease prevention management data. Product management data includes information such as the location of stores selling products, product types, quantities, and display timing. Delivery management data includes information such as delivery locations, delivery times, and delivery routes when vehicles deliver products. Security management data includes information such as the locations guarded by security personnel, patrol frequency, and shift information. Promotion management data includes information such as the regions where advertising is conducted, the target audience of advertising, the media used, and the content of the promotion. Infectious disease prevention management data includes information such as the locations where infectious disease prevention is carried out, the infectious diseases to be prevented, the symptoms to be prevented, the methods of prevention, and the content of prevention.

[0126] (Control unit 330) The control unit 330 may be, for example, an information processing device that controls various configurations and processes. The control unit 330 may have, for example, a CPU or GPU, and may be implemented by executing a program stored inside the control unit 330 using RAM or the like as a working area. Alternatively, the control unit 330 may have, for example, an integrated circuit such as an ASIC or FPGA.

[0127] As shown in Figure 6, the control unit 330 has a request unit 331 and a management unit 332, and realizes or executes the information processing functions and operations described below. Note that the internal configuration of the control unit 330 is not limited to the configuration shown in Figure 6, and other configurations are also acceptable as long as they perform the information processing described later.

[0128] (Request part 331) The request unit 331 requests information from an external system. For example, the request unit 331 requests analysis results from the analysis server 100. More specifically, the request unit 331 requests information on the health status and lifestyle rhythm of a predetermined region from the analysis server 100.

[0129] (Management Department 332) The Management Department modifies management data based on the analysis results of the Data Analysis Department 132. Management data includes product management data, delivery management data, security management data, promotion management data, infectious disease prevention management data, etc. The Management Department 332 functions as a management system, product management system, delivery route management system, shift management system, infectious disease request management system, and promotion management system.

[0130] For example, the management unit 332 determines, based on the analysis results of the data analysis unit 132, the type or quantity of products to be displayed on the shelves of stores located in a predetermined area corresponding to the detection data analyzed by the data analysis unit 132. For example, the management unit 332 determines whether or not to display products that affect a predetermined health condition, as included in the analysis results of the data analysis unit 132, on the shelves of stores located in a predetermined area, and the quantity to display.

[0131] For example, the management unit 332 decides to include products that can improve a predetermined health condition, as included in the analysis results of the data analysis unit 132, on the shelves of stores located in a predetermined area, or to increase the quantity of such products on display. To give a specific example, if the health condition of area B analyzed by the data analysis unit 132 is "diarrhea: frequent," the management unit 332 decides to increase the quantity of lactic acid bacteria beverages displayed on the shelves of convenience stores located in area B.

[0132] Conversely, the management department 332 decides not to display products that may worsen a predetermined health condition, as included in the analysis results of the data analysis department 132, on the shelves of stores located in a predetermined area, or to reduce the quantity of such products displayed. To give a specific example, if the health condition of area B analyzed by the data analysis department 132 is "diarrhea: frequent," the management department 332 decides to reduce the quantity of milk displayed on the shelves of convenience stores located in area B.

[0133] Furthermore, the change in the quantity of products displayed on the shelves of stores located in a designated area by the management unit 332 may be based on the quantity of the same product in a different area. To give a specific example, if the health status of area B, as analyzed by the data analysis unit 132, is "diarrhea: frequent," the management unit 332 decides to increase the quantity of lactic acid bacteria beverages displayed on the shelves of convenience stores located in area B by more than the quantity of lactic acid bacteria beverages displayed on the shelves of convenience stores located in area A.

[0134] As an alternative example, the management unit 332 determines the delivery route for goods within a predetermined area corresponding to the detection data analyzed by the data analysis unit 132, based on the analysis results of the data analysis unit 132. For example, the management unit 332 determines the delivery route for goods within a predetermined area according to the information on the lifestyle rhythms of the predetermined area analyzed by the data analysis unit 132.

[0135] To give a concrete example, based on information about people's lifestyles, such as "people in area A tend to go out between 9:00 and 18:00," the management department 332 decides on a delivery route that does not actively deliver goods to houses in area A during the 9:00-18:00 timeframe. Conversely, based on information about people's lifestyles, such as "people in area B tend to go out less between 9:00 and 18:00," the management department 332 decides on a delivery route that actively delivers goods to houses in area B during the 9:00-18:00 timeframe.

[0136] As an alternative example, the management unit 332 sets the patrol frequency or personnel shift information of monitors within a predetermined area corresponding to the detection data analyzed by the data analysis unit 132, based on the analysis results of the data analysis unit 132. For example, the management unit 332 sets the patrol frequency or personnel shift of monitors according to the lifestyle rhythm information of a predetermined area analyzed by the data analysis unit 132. To give a specific example, based on lifestyle rhythm information that "people in area A are often out between 9:00 and 18:00," the management unit 332 sets a shift that increases the patrol frequency or number of monitors in area A during the 9:00 to 18:00 timeframe.

[0137] Conversely, based on information about the lifestyle rhythm of residents in Area B, such as "less outings between 9:00 and 18:00," Management Department 332 sets a shift that reduces the frequency or number of patrols by surveillance officers in Area A during the 9:00-18:00 timeframe.

[0138] Alternatively, the management unit 332 can also determine whether or not to monitor a predetermined region corresponding to the detection data analyzed by the data analysis unit 132, based on the analysis results of the data analysis unit 132. For example, if the lifestyle rhythm of region A analyzed by the data analysis unit 132 is "frequent going out," the management unit 332 will set region A as a monitoring target.

[0139] As an alternative example, the Management Department 332 determines the content of infectious disease prevention in a predetermined region corresponding to the detection data analyzed by the Data Analysis Department 132, based on the analysis results of the Data Analysis Department 132. Here, the content of infectious disease prevention includes information such as the type of infectious disease to be prevented, symptoms, prevention methods, and necessary items for prevention. For example, the Management Department 332 determines the type of infectious disease to be prevented and the prevention methods according to the health status of a predetermined region analyzed by the Data Analysis Department 132. To give a specific example, if the health status of region A analyzed by the Data Analysis Department 132 is "diarrhea: frequent," the Management Department 332 decides that the methods of preventing infectious gastroenteritis that causes diarrhea in region A are hand washing with disinfectant, gargling, and wearing a mask.

[0140] As an alternative example, the Management Department 332 determines a promotion plan within a predetermined region corresponding to the detection data analyzed by the Data Analysis Department 132, based on the analysis results of the Data Analysis Department 132. For example, the Management Department 332 determines the location, time, and medium for promotion based on the lifestyle rhythm information of the predetermined region analyzed by the Data Analysis Department 132. To give a specific example, based on lifestyle rhythm information that "there is little going out between 9:00 and 18:00 in region A," the Management Department 332 decides to advertise products and services of, for example, hospitals and clinics to residents of region A using geotargeting advertising that delivers advertisements to target individuals in region A between 9:00 and 18:00.

[0141] [Sequence Diagram] Next, with reference to Figure 7, an example of the processing flow performed by the data analysis system 1 according to the first embodiment will be described. Figure 7 is a sequence diagram showing an example of the processing flow performed by the data analysis system 1 according to the first embodiment. Each step in the sequence diagram may be rearranged within a consistent range, and there may be steps that are not performed.

[0142] First, the data acquisition means transmits the acquired data to the data storage means (step S11). The data acquired by the data acquisition means includes, for example, detection data of plumbing equipment, user information of plumbing equipment, product identification information of plumbing equipment, and information relating the product identification information to the installation location. Next, the data storage means stores the acquired information in association (step S12). For example, the data storage means stores the acquired detection data of plumbing equipment, user information, and installation location in association.

[0143] Next, the requesting means requests analysis data (step S13). For example, the requesting means requests information on the health status and lifestyle rhythm of a predetermined area from the external data acquisition means. Subsequently, the external data acquisition means transmits the data request information to the data storage means (step S14).

[0144] Next, the data storage means transmits the detection data corresponding to the data request to the data analysis means. Subsequently, the data analysis means analyzes the detection data transmitted from the data storage means and obtains the requested data (step S15). For example, the data analysis means analyzes information on the health status and lifestyle rhythm of a predetermined area. Subsequently, the output means outputs the analysis results to the management means (step S16).

[0145] Next, the management means modifies the management data based on the outputted analysis results (step S17). For example, the management means determines the shelf arrangement of products in stores in a given region according to the health status of that region. After that, the data analysis system 1 terminates processing.

[0146] <Second Embodiment> In the first embodiment, the process by which the data analysis system 1 modifies management data based on the analysis results of detection data of plumbing equipment was described. In the second embodiment, the process by which the data analysis system 1 obtains analysis results that include data items indicating changes in the state of the region will be described. Furthermore, the contents described in the first embodiment will be omitted as appropriate.

[0147] [Configuration of the analysis server] (Data Analysis Department 132) The data analysis unit 132 changes the analysis method output to the outside according to the acquired information request data. The analysis method includes changes to the data items to be output and changes to the display format. For example, if the acquired information request data is the health status of a predetermined region, including a comparison with a predetermined period prior, the data analysis unit 132 obtains an analysis result that adds an item for changes in health status in addition to the health status of the predetermined region.

[0148] To give a specific example, when the data analysis unit 132 receives requested data from the external data acquisition unit 133, such as information on the health status of region A including a comparison with one week ago, it analyzes the detected data for region A and obtains information such as "Health status of region A: Constipation: Low (compared to last week: increase), Diarrhea: High (compared to last week: decrease), Nocturia: Low (compared to last week: decrease)." Note that the degree of increase or decrease may be expressed as a percentage.

[0149] (External data acquisition unit 133) The external data acquisition unit 133 acquires data from the external server 300 that requests the analysis results of detection data for a predetermined region, including a comparison with data from a predetermined period prior. For example, the external data acquisition unit 133 acquires data from the external server 300 that requests the health status of region A, including a comparison with data from one week prior.

[0150] [External Server Configuration] (Request part 331) The request unit 331 requests information. For example, the request unit 331 requests the analysis server 100 to provide the results of an analysis of detection data for a predetermined region, including a comparison with data from a predetermined period prior. To give a specific example, the request unit 331 requests the analysis server 100 to provide the health status of region A, including a comparison with data from one week prior.

[0151] [Sequence Diagram] Next, with reference to Figure 8, an example of the processing flow performed by the data analysis system 1 according to the second embodiment will be described. Figure 8 is a sequence diagram showing an example of the processing flow performed by the data analysis system 1 according to the second embodiment. Note that the data acquisition and data linking described in the first embodiment will not be described.

[0152] First, the requesting means requests analysis data (step S21). For example, the requesting means requests health status information for region A from the external data acquisition means. Next, the external data acquisition means transmits the acquired request data to the data storage means. Then, the data storage means identifies the relevant data (step S22). For example, the data storage means identifies detection data linked to installation location and date / time information where the installation location is region A.

[0153] Next, the data analysis means performs data analysis on the identified detection data (step S23). For example, the data analysis means analyzes detection data where the installation location is region A and obtains the analysis result that the health status of region A is "constipation: infrequent, diarrhea: frequent, nocturia: infrequent". Subsequently, the output means outputs the analysis results to the management means (step S24).

[0154] Next, the control device modifies the control data based on the outputted analysis results (step S25). For example, the control device modifies the shelf allocation of products in stores in region A to increase the types and quantities of lactic acid bacteria beverages, according to the health status of region A, which is "constipation: infrequent, diarrhea: frequent, nocturia: infrequent".

[0155] Next, the requesting means requests analysis data after the change in management data, including a comparison with a predetermined period prior (step S26). For example, the requesting means requests the data storage means, via the external data acquisition means, a health status report for region A after the shelf arrangement of products in stores in region A has been changed, including a comparison with the past. Subsequently, the data storage means identifies the relevant data again (step S27).

[0156] Next, the data analysis means analyzes the data after the change in management data and compares it with past data, focusing on the identified detection data (step S28). For example, after a change in the product shelf layout of a store in region A, the data analysis means analyzes the detection data where the installation location is in region A, including a comparison with data from a predetermined period prior, and obtains the analysis result that the health status of region A is "constipation: low (compared to the previous time: increase), diarrhea: high (compared to the previous time: decrease), nocturia: low (compared to the previous time: decrease)". Then, the output means outputs the analysis results to the management means (step S29). After that, the data analysis system 1 terminates processing.

[0157] <Third Embodiment> In the first and second embodiments, the process by which the data analysis system 1 modifies management data based on the analysis results was described. In the third embodiment, the process by which the data analysis system 1 issues alert information based on changes in the state of the region will be described. Furthermore, the contents described in the first and second embodiments will be omitted as appropriate.

[0158] Next, with reference to Figure 9, an overview of the processing performed by the data analysis system 1 according to the third embodiment will be described. Figure 9 is a diagram illustrating an overview of the processing performed by the data analysis system 1 according to the third embodiment. Figure 9 shows an example in which an alert is issued based on the analysis results of detection data from plumbing equipment.

[0159] In the example shown in Figure 9, the data analysis means first analyzes the detection data to obtain analysis data of changes in status for each predetermined region. For example, the data analysis means analyzes the detection information of users in region A to obtain information on the health status of region A: "Constipation: Low (increase compared to last week), Diarrhea: High (increase compared to last week), Nocturia: Low (decrease compared to last week)". Then, the output means creates alert information indicating that "diarrhea is on the rise in region A" from the analysis result of "Diarrhea: High (increase compared to last week)" and outputs it to the external server 300.

[0160] [Configuration of the analysis server] (Data Analysis Department 132) The data analysis unit 132 analyzes changes in a given region from the acquired detection data. For example, the data analysis unit 132 analyzes changes in a given region by comparing the health status of the region analyzed from the acquired detection data with the health status of the region from a predetermined period ago. To give a specific example, the data analysis unit 132 compares the latest health status of residents in region A with their health status from one week ago to obtain a health status that includes information on changes in status such as "Health status: Diarrhea (compared to last week: increase)".

[0161] (Output section 134) The output unit 134 outputs information from the data analysis system 1. For example, the output unit 134 sends alert information based on the analysis results of the data analysis unit 132. For example, the output unit 134 sends alert information based on the health status of a predetermined region. The alert information is information that indicates an increasing or decreasing trend in a predetermined symptom or a predetermined disease.

[0162] First, the output unit 134 generates alert information when the health status of a given region meets predetermined conditions. For example, the output unit 134 generates alert information when the percentage of a given health status in a given region exceeds a predetermined threshold and has a predetermined relationship with the percentage of past health statuses. To give a specific example, the output unit 134 generates alert information indicating that diarrhea is on the rise in region A when the percentage of people with the health status "diarrhea" in region A exceeds 30% and is higher than the percentage of people with the health status "diarrhea" in region A one week ago.

[0163] The output unit 134 then transmits the created alert information. For example, the output unit 134 transmits the created alert information, "Diarrhea is on the rise in region A," to an external server 300 managed by a local government, public health center, medical institution, etc. The degree of increase or decrease may be changed depending on the degree of change in the condition. For example, the output unit 134 can transmit alert information indicating the degree of increase or decrease, such as "slowly increasing" if the week-on-week change in a certain health condition is less than a predetermined multiple, or "rapidly increasing" if the week-on-week change is more than a predetermined multiple.

[0164] [Sequence Diagram] Next, with reference to Figure 10, an example of the processing flow performed by the data analysis system 1 according to the third embodiment will be described. Figure 10 is a sequence diagram showing an example of the processing flow performed by the data analysis system 1 according to the third embodiment. Note that the data acquisition and data linking described in the first embodiment will not be described.

[0165] First, the requesting means requests analysis data (step S31). For example, the requesting means requests information on changes in the health status of region A from the external data acquisition means. Next, the external data acquisition means transmits the acquired request data to the data storage means. The data storage means identifies the relevant data (step S32). For example, the data storage means identifies the detection data linked to the installation location and date / time information where the installation location is region A.

[0166] Next, the data analysis means analyzes the data by referring to the data storage means (step S33). Subsequently, the output means issues an alert based on the analysis results (step S34). For example, the output means creates an alert message, "The number of residents with diarrhea is increasing in area A," from the health status of area A, "Diarrhea: High (compared to the previous time: Increase)," and sends it to the management means. After that, the data analysis system 1 terminates its processing.

[0167] <Fourth Embodiment> In the first to third embodiments, we described the process of analyzing and outputting detection data without considering regional information. In the third embodiment, and in the fourth embodiment, we will describe the process of generating and outputting analysis data corresponding to regional information acquired from an external source by the data analysis system 1. Furthermore, we will omit descriptions of the contents explained in the first to third embodiments as appropriate.

[0168] Next, with reference to Figure 11, an overview of the processing performed by the data analysis system 1 according to the fourth embodiment will be described. Figure 11 is a diagram showing an overview of the processing performed by the data analysis system 1 according to the fourth embodiment. Figure 11 shows an example of generating and outputting analysis results according to regional information.

[0169] In the example shown in Figure 11, the external data acquisition means first acquires regional information for a predetermined area. The regional information includes information about changes in the state of the area, such as information about the trend in the number of patients with a predetermined disease in the area. For example, the external data acquisition means acquires regional information about changes in the state of area A. Next, the data analysis means generates information according to the acquired regional information. For example, the data analysis means generates analysis information for area A, which is the target area of ​​the acquired regional information. Then, the output means outputs the generated analysis information to an external system. For example, the output means outputs the generated information on the health status and lifestyle rhythm of area A to an external server 300 managed by a local government, public health center, medical institution, etc.

[0170] [Configuration of the analysis server] (Data Analysis Department 132) The data analysis unit 132 generates information according to the acquired regional information. For example, the data analysis unit 132 generates information about regions related to the acquired regional information. To give a specific example, if the data analysis unit 132 acquires the information that "last week the number of patients per 1 million people with disease X was 11 in region A, 38 in region B, and 19 in region C, and this week the number of patients per 1 million people with disease X is 24 in region A, 15 in region B, and 22 in region C", then it will use regions A to C as regions related to the regional information and generate information about the health status and lifestyle rhythm of each of regions A to C.

[0171] (External data acquisition unit 133) The external data acquisition unit 133 acquires regional information regarding changes in conditions within a predetermined region. For example, the external data acquisition unit 133 acquires information on changes in the number of patients related to a predetermined disease for each predetermined region. To give a specific example, the external data acquisition unit 133 acquires information from the external server 300 that "last week the number of patients per 1 million people for disease X was 11 in region A, 38 in region B, and 19 in region C, and this week the number of patients per 1 million people for disease X is 24 in region A, 15 in region B, and 22 in region C."

[0172] (Output section 134) The output unit 134 outputs the information generated by the data analysis unit 132. For example, the output unit 134 transmits the health status and lifestyle rhythm information for a predetermined region, generated by the data analysis unit 132, to the external server 300. Specifically, the output unit 134 transmits to the external server 300 the following information generated by the data analysis unit 132: "Health status of Region A (Constipation: infrequent, Diarrhea: frequent, Nocturia: infrequent) and lifestyle rhythm (Frequent outings)", "Health status of Region B (***) and lifestyle rhythm (***)", and "Health status of Region C (***) and lifestyle rhythm (***)".

[0173] [Sequence Diagram] Next, with reference to Figure 12, an example of the processing flow performed by the data analysis system 1 according to the fourth embodiment will be described. Figure 12 is a sequence diagram showing an example of the processing flow performed by the data analysis system 1 according to the fourth embodiment. Note that the data acquisition and data linking described in the first embodiment will not be described.

[0174] First, the requesting means transmits regional information regarding changes in the state within a predetermined area (step S41). For example, the requesting means transmits information on changes in the number of patients in areas A to C to the external data acquisition means. Next, the external data acquisition means transmits the regional information to the data storage means. The data storage means identifies the target data (step S42). For example, among the detection data linked to the installation location and date / time information, the data storage means identifies the detection data where the installation location is in area A, the detection data where the installation location is in area B, and the detection data where the installation location is in area C, corresponding to areas A to C which are the target of the regional information.

[0175] Next, the data analysis means performs an analysis of the detection data targeting the identified detection data (step S43). For example, the data analysis means analyzes the detection data targeting regions A to C to obtain information on the health status and lifestyle rhythm of each region. Then, the output means outputs the analysis results to the management means (step S44). After that, the data analysis system 1 terminates its processing.

[0176] 〔others〕 The various types of information, such as detection data, in each of the embodiments and modifications described above may be manually entered by the user. For example, in each of the embodiments and modifications described above, the detection data acquired from each plumbing fixture may be manually entered by the resident or others. For example, after a resident defecates, the resident or a cohabitant may visually or olfactorily confirm the excrement, such as feces, and then operate a terminal to input information about the feces.

[0177] Furthermore, the components of each illustrated device are functionally conceptual and do not necessarily need to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions.

[0178] 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 equivalents.

[0179] The embodiments and modifications described above may also have the following configurations, but are not limited to them. (1) A data acquisition means for acquiring detection data from plumbing fixtures installed in multiple houses, A data storage means that stores the installation location of the plumbing equipment and the detection data together with date and time information, A data analysis means for analyzing the detection data located within a predetermined area, A data analysis system characterized by having the following features. (2) The data acquisition means acquires user information relating to the user of the plumbing equipment with respect to the detection data, along with the detection data. The data storage means stores the user information and the detection data in association, The data analysis means analyzes the user's health status or lifestyle based on the detection data and user information. The data analysis system according to (1), characterized in that (3) The data acquisition means acquires product identification information set on the plumbing equipment and identifies the installation location of the plumbing equipment from the information recorded in the external database based on the acquired product identification information. A data analysis system according to (1) or (2), characterized in that... (4) Output means for outputting the analysis results from the data analysis means to an external source, The system further comprises external data acquisition means for acquiring information request data from an external system that receives the output analysis results, The data analysis means changes the mode of analysis output to the outside in accordance with the acquired information request data. A data analysis system according to any one of (1) to (3), characterized by the above. (5) The data analysis means analyzes the user's health status based on the detection data detected by the sensors of the plumbing equipment. Product management means that determines, based on the analysis results of the data analysis means, the type or quantity of products to be displayed on the shelves of stores located in a predetermined area corresponding to the detection data analyzed by the data analysis means. Furthermore, it is equipped with A data analysis system according to any one of (1) to (4), characterized by the above. (6) The data analysis system according to any one of (1) to (5), further comprising a delivery route management means that determines a delivery route for goods within a predetermined area corresponding to the detection data analyzed by the data analysis means, based on the analysis results of the data analysis means. (7) The data analysis system according to any one of (1) to (6), further comprising a shift management means for setting the patrol frequency of monitors or personnel shift information within a predetermined area corresponding to the detection data analyzed by the data analysis means, based on the analysis results of the data analysis means. (8) The system further comprises an output means for outputting information from the aforementioned data analysis system, The data analysis means analyzes the changes in the state in the predetermined region from the acquired detection data. The data analysis system according to any one of (1) to (7), characterized in that the output means transmits alert information based on the analysis results of the data analysis means. (9) An external data acquisition means for acquiring regional information regarding state changes within the predetermined region, The system further comprises an output means for outputting information from the aforementioned data analysis system, The data analysis system according to any one of (1) to (8), characterized in that the data analysis means generates the information according to the acquired regional information. [Explanation of Symbols]

[0180] 1. Data Analysis System 100 Analysis Servers 110 Communications Department 120 Storage section 130 Control Unit 131 Data Acquisition Unit 132 Data Analysis Department 133 External Data Acquisition Unit 134 Output section 210 Toilets 211 Toilet equipment 212 Toilet Sensor 220 Bathroom 221 Bathroom equipment 222 Bathroom Sensor 230 Washbasin 231 Washbasin equipment 232 Bathroom sink sensor 300 External Servers 310 Communications Department 320 Storage section 330 Control Unit 331 Request part 332 Management Department

Claims

1. A data acquisition means for acquiring detection data from plumbing fixtures installed in multiple houses, A data storage means that stores the installation location of the plumbing equipment and the detection data together with date and time information, A data analysis means for analyzing the detection data located within a predetermined area, A data analysis system characterized by having the following features.

2. The data acquisition means acquires user information relating to the user of the plumbing equipment with respect to the detection data, along with the detection data. The data storage means stores the user information and the detection data in association, The data analysis means analyzes the user's health status or lifestyle based on the detection data and user information. The data analysis system according to feature 1.

3. The data acquisition means acquires product identification information set on the plumbing equipment and identifies the installation location of the plumbing equipment from the information recorded in the external database based on the acquired product identification information. The data analysis system according to feature 1.

4. Output means for outputting the analysis results from the data analysis means to an external source, The system further comprises external data acquisition means for acquiring information request data from an external system that receives the output analysis results, The data analysis means changes the mode of analysis output to the outside in accordance with the acquired information request data. The data analysis system according to feature 1.

5. The data analysis means analyzes the user's health status based on the detection data detected by the sensors of the plumbing equipment. Product management means that determines, based on the analysis results of the data analysis means, the type or quantity of products to be displayed on the shelves of stores located in a predetermined area corresponding to the detection data analyzed by the data analysis means. Furthermore, it is equipped with The data analysis system according to feature 1.

6. The data analysis system according to claim 1, further comprising a delivery route management means for determining a delivery route for goods within a predetermined area corresponding to the detection data analyzed by the data analysis means, based on the analysis results of the data analysis means.

7. The data analysis system according to claim 1, further comprising a shift management means for setting the patrol frequency of monitors or personnel shift information within a predetermined area corresponding to the detection data analyzed by the data analysis means, based on the analysis results of the data analysis means.

8. The system further comprises an output means for outputting information from the aforementioned data analysis system, The data analysis means analyzes the changes in the state in the predetermined region from the acquired detection data. The data analysis system according to claim 1, characterized in that the output means transmits alert information based on the analysis results of the data analysis means.

9. An external data acquisition means for acquiring regional information regarding state changes within the predetermined region, The system further comprises an output means for outputting information from the aforementioned data analysis system, The data analysis system according to claim 1, characterized in that the data analysis means generates the information according to the acquired regional information.

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