JP7693303B2 - Moisture advice output device, moisture advice output method, and program - Google Patents

Description

The present invention relates to a fluid advice output device that outputs advice based on the user's fluid intake.

Conventionally, there has been a health management support device that notifies a user's terminal of health advice information based on vital data detected by a vital sensor installed in a wearable device (see, for example, Patent Document 1).

JP 2020-149150 A

However, conventional technology does not allow users to receive appropriate advice based on their water intake.

The fluid advice output device of the first invention is a fluid advice output device that includes an intake acquisition unit that acquires intake information related to the user's fluid intake, an advice acquisition unit that acquires advice information for the user using the intake information, and an advice output unit that outputs the advice information.

This configuration allows the user to receive appropriate advice based on their water intake.

The moisture advice output device of the second invention is a moisture advice output device that further includes a correspondence information storage unit having two or more pieces of correspondence information that correspond between intake conditions related to intake information and advice source information that is the basis of the advice information, and the advice acquisition unit acquires advice information using the advice source information that is paired with the intake conditions that the intake information matches.

This configuration allows the user to receive appropriate advice based on their water intake.

The moisture advice output device of the third invention is a moisture advice output device according to the first or second invention, further comprising a user attribute value acquisition unit that acquires a user attribute value corresponding to the intake amount information, and the advice acquisition unit acquires advice information for the user using the user attribute value and the intake amount information.

This configuration allows users to receive appropriate advice based on their attribute values.

The fluid advice output device of the fourth invention is a fluid advice output device according to any one of the first to third inventions, further comprising a diagnostic information receiving unit that receives diagnostic information related to a user's health check, and the advice acquisition unit acquires advice information for the user using the intake amount information and the diagnostic information.

With this configuration, appropriate advice can be obtained using diagnostic information related to health checkups as well.

The fluid advice output device of the fifth invention is a fluid advice output device according to any one of the first to fourth inventions, further comprising a score acquisition unit that uses intake information to acquire a score related to the suitability of the user's fluid intake, and a score output unit that outputs the score.

This configuration allows the user to be presented with a score regarding the quality of their fluid intake.

The fluid advice output device of the sixth invention is a fluid advice output device according to any one of the first to fifth inventions, further comprising a raw information storage unit that stores raw information that is the basis for estimating the fluid intake amount from answer information to two or more questions including questions other than a question that directly asks about the amount of fluid intake, and an answer receiving unit that receives user answer information having answer information to two or more questions, and the intake amount acquisition unit acquires intake amount information that specifies the amount of fluid intake using the two or more answer information contained in the user answer information accepted by the answer receiving unit and the raw information stored in the raw information storage unit.

With this configuration, appropriate advice can be obtained based on the amount of fluid intake obtained using the answers to the questions.

The seventh invention is a hydration advice output device according to the sixth invention, in which the two or more questions are two or more of the following: beverage-related questions about beverage addictiveness, alcohol-related questions about alcohol addictiveness, diet-related questions about diet-related addictiveness, and all-origin questions about all origins.

With this configuration, appropriate advice can be obtained based on the amount of fluid intake obtained by answering appropriate questions.

The eighth invention is a moisture advice output device according to the sixth or seventh invention, further comprising a questionnaire storage unit in which two or more pieces of questionnaire information each having question information for two or more questions are stored in association with conditions related to user attribute values, a questionnaire acquisition unit that acquires questionnaire information corresponding to the conditions corresponding to the user attribute values of the user from the questionnaire storage unit, and a questionnaire output unit that transmits the questionnaire information acquired by the questionnaire acquisition unit to a user terminal, the raw information storage unit stores two or more pieces of raw information corresponding to the conditions corresponding to the user attribute values, the reception unit receives user answer information corresponding to the user attribute values, and the intake amount acquisition unit acquires intake amount information using the raw information corresponding to the user attribute values corresponding to the user answer information and the two or more pieces of answer information contained in the user answer information.

With this configuration, appropriate advice can be obtained based on the amount of fluid intake obtained by answering questions appropriate to the user's attribute values.

The fluid advice output device of the ninth invention is a fluid advice output device according to any one of the sixth to eighth inventions, in which the two or more questions have two or more types of question sets each consisting of one or more questions, the raw information storage unit stores two or more pieces of raw information corresponding to the types of questions, the intake amount acquisition unit acquires intake amount information for each type using answer information corresponding to each question of each of the two or more types and the raw information corresponding to each type, and acquires intake amount information using the two or more pieces of intake amount information.

With this configuration, the appropriate amount of fluid intake can be obtained based on the answers to the appropriate questionnaire, and appropriate advice can be given according to that amount of fluid intake.

The moisture advice output device of the tenth invention is a moisture advice output device according to any one of the sixth to ninth inventions, in which the original information is a learning device constructed by performing a learning process using a machine learning algorithm using two or more teacher data sets having answer information to two or more questions or answer-related information obtained from the answer information and moisture intake information, and the intake acquisition unit is a moisture advice output device that performs a prediction process using a machine learning algorithm using two or more answer information or answer-related information obtained from two or more answer information contained in the user answer information accepted by the answer acceptance unit and the learning unit stored in the original information storage unit to acquire the intake information.

With this configuration, a machine learning algorithm can be used to obtain an appropriate amount of fluid intake and provide appropriate advice based on that amount.

The moisture advice output device of the eleventh invention is a moisture advice output device according to the tenth invention, in which the machine learning algorithm is a random forest.

With this configuration, the random forest algorithm can be used to obtain an appropriate amount of fluid intake and provide appropriate advice based on that amount of fluid intake.

The fluid advice output device of the present invention can provide appropriate advice to the user based on their fluid intake.

Concept of water intake estimation system A in embodiment 1 Block diagram of the water intake estimation system A Block diagram of the water intake estimation device 2 A flowchart illustrating an example of the operation of the learning device 1. A flowchart illustrating an example of the operation of the water intake estimation device 2. A flowchart for explaining an example of the operation of the user terminal 3 A diagram showing an example of the questionnaire information A diagram showing an example of the questionnaire information FIG. 13 shows the user response information management table. The figure shows the actual measurement value management table. A diagram showing the identity information management table A diagram showing an example of the output A diagram showing an example of the output Conceptual diagram of moisture advice system B in embodiment 2 Block diagram of the moisture advice system B Block diagram of the moisture advice output device 4. A flowchart for explaining an example of the operation of the moisture advice output device 4. A flowchart for explaining an example of the operation of the user terminal 5 FIG. 2 shows the correspondence information management table. A diagram showing an example of the output FIG. 2 shows the correspondence information management table. A diagram showing an example of the output Overview of the computer system according to the above embodiment. Block diagram of the computer system

Below, embodiments of a fluid intake estimation device, a fluid advice output device, and the like will be described with reference to the drawings. Note that components with the same reference numerals in the embodiments perform similar operations, and therefore repeated explanations may be omitted.

(Embodiment 1)
In this embodiment, a water intake estimation system is described that includes a water intake estimation device that acquires and outputs a water intake amount using answer information to two or more questions included in a questionnaire that includes questions other than the question directly asking about the amount of water ingested, and raw information for obtaining the water intake amount using the answer information. Note that the questionnaire has two or more questions from, for example, beverage origin, alcohol origin, food origin, and all origin. In addition, each of the two or more questionnaires is associated with, for example, a user attribute value condition, and a different questionnaire is sent to the user terminal depending on the user attribute value.

In addition, in this embodiment, a water intake estimation system is described that has two or more types of questions and is equipped with a water intake estimation device that obtains the water intake amount using raw information for each type of question.

In addition, in this embodiment, a water intake estimation system including a water intake estimation device that acquires water intake using a machine learning algorithm is described. The machine learning is, for example, a random forest.

Figure 1 is a conceptual diagram of a water intake estimation system A in this embodiment. The water intake estimation system A includes a learning device 1, a water intake estimation device 2, and one or more user terminals 3.

The learning device 1 is a device that acquires raw information (described later) using the actual measured value of the water intake and answer information for each of two or more questions included in the questionnaire. The learning device 1 may be, for example, a personal computer, tablet terminal, smartphone, server, etc., and the type does not matter. The server may be, for example, a cloud server or an ASP server, and the type does not matter. The learning device 1 may be a standalone device or a server that receives instructions from the user terminal 3 and operates accordingly.

The water intake estimation device 2 is, for example, a so-called server. The server may be, for example, a cloud server or an ASP server, and the type does not matter. However, the water intake estimation device 2 may also be a standalone device such as a so-called personal computer, tablet terminal, smartphone, etc.

The user terminal 3 may be a personal computer, tablet terminal, smartphone, etc., and the type is not important.

The learning device 1, the water intake estimation device 2, and the user terminal 3 may be capable of communicating with each other via the Internet, a LAN, etc.

Figure 2 is a block diagram of the water intake estimation system A in this embodiment. Figure 3 is a block diagram of the water intake estimation device 2.

The learning device 1 includes a learning storage unit 11, a learning reception unit 12, a learning processing unit 13, and a learning output unit 14. The learning storage unit 11 includes a response storage unit 111, and an actual value storage unit 112.

The water intake estimation device 2 comprises a storage unit 21, a reception unit 22, a processing unit 23, and an output unit 24. The storage unit 21 comprises a questionnaire storage unit 211, and a raw information storage unit 212. The reception unit 22 comprises a response reception unit 221. The processing unit 23 comprises a questionnaire acquisition unit 231, and an intake acquisition unit 232. The output unit 24 comprises a questionnaire output unit 241, and an intake output unit 242.

The user terminal 3 includes a terminal storage unit 31, a terminal reception unit 32, a terminal processing unit 33, a terminal transmission unit 34, a terminal reception unit 35, and a terminal output unit 36.

The learning storage unit 11 that constitutes the learning device 1 stores various types of information. The various types of information are, for example, answer information, actual measured values, and identification information for each of two or more pieces of original information.

The identification information is information used when acquiring two or more pieces of original information. The identification information is information that specifies the conditions of the answer information used when acquiring the original information. The identification information is information that corresponds to the acquired original information. The identification information is, for example, information that specifies the conditions related to the user attribute value. The identification information is, for example, information that identifies the type of question set. The identification information includes, for example, information that specifies the conditions related to the user attribute value and information that identifies the type of question set. The identification information is, for example, "male, female" which is a condition related to the user attribute value, and "beverage-derived, alcohol-derived, food-derived, all-derived" which is information that identifies the type of question set. The identification information is, for example, (gender = male & type of question set = beverage origin) (gender = male & type of question set = alcohol origin) (gender = male & type of question set = food origin) (gender = male & type of question set = all origins) (gender = female & type of question set = beverage origin) (gender = female & type of question set = alcohol origin) (gender = female & type of question set = food origin) (gender = female & type of question set = all origins).

Fluid intake from beverages is the amount of fluid ingested from beverages. Fluid intake from alcoholic beverages is the amount of fluid ingested from alcoholic beverages. Fluid intake from food is the amount of fluid ingested from food. Fluid intake from total sources is the amount of fluid ingested from beverages, alcoholic beverages, and food.

Two or more pieces of answer information are stored in the answer storage unit 111. The answer information is information that specifies the answer to the question. For example, answer information associated with an identifier is stored in the answer storage unit 111. The answer information is information that specifies the user's answer to each question in the questionnaire. The user is the respondent. The answer information is usually associated with the question identifier of each question in the questionnaire. The question identifier is information that identifies the question, such as a question number or a question ID. The identifier is also a user identifier, or a day identifier, or a user identifier and a day identifier. The user identifier is information that identifies the user, such as an ID, email address, telephone number, or the ID of the terminal used by the user (for example, an IP address, a MAC address, a terminal identifier, etc.).

The answer information corresponds to, for example, the identification information. That is, the answer information may correspond to a user attribute value. The user attribute value is an attribute value of the user, such as gender, age, or occupation. The answer information may also correspond to a type identifier that identifies the type of question. The type is, for example, origin. The type may be, for example, beverage origin, alcohol origin, food origin, or all origin.

The actual measurement value storage unit 112 stores two or more actual measurement values. The actual measurement values are usually associated with answer information. The actual measurement values are usually associated with a set of answer information for each question in the questionnaire. The actual measurement values are associated with, for example, an identifier.

The actual measurement value is, for example, the amount of water intake of a user in a day. The actual measurement value is, for example, the amount of water intake of a single user in a day, and is associated with a user identifier. The actual measurement value is, for example, the amount of water intake of a single user in a day, and is associated with a user identifier and a day identifier.

The actual measurement value is associated with, for example, a type identifier. It is preferable that the actual measurement value storage unit 112 stores the actual measurement value for each origin. If the actual measurement value is the user's daily water intake, the origin may be, for example, two or more of beverage origin, alcohol origin, food origin, and all origin.

There is no restriction on the method of obtaining the actual measurement value. The actual measurement value is, for example, the daily fluid intake obtained from the user's responses to a multiple-choice questionnaire, which is a set of questions that asks the user to select the type and amount of food and drink consumed in a multiple-choice format. The actual measurement value is, for example, the daily fluid intake obtained from the user's responses to a questionnaire based on a descriptive food record method. However, the actual measurement value may be a value entered manually. In other words, it is preferable that the actual measurement value is an accurate fluid intake value, but there may be some error. The actual measurement value may be a value that is considered to be roughly accurate.

The multiple-choice questionnaire above is a set of questions to determine actual fluid intake, and asks participants to select the types and amounts of food and drink they ingested each day.

The descriptive food record method involves giving subjects a record sheet to record what they have eaten and drunk over a certain period of time. The greatest advantage of the food record method is that it provides information about what they actually ate. Using responses based on the food record method, it is possible to obtain the user's actual daily fluid intake.

The learning reception unit 12 receives various instructions, information, etc. The various instructions, information, etc. are, for example, learning instructions. A learning instruction is an instruction to obtain original information. The input means for the various instructions, information, etc. may be anything, such as a touch panel, keyboard, mouse, or menu screen. The learning reception unit 12 may also receive various instructions, information, etc. from the user terminal 3.

The raw information is the information that is the basis for estimating the amount of fluid intake from the answer information to each of the two or more questions. Note that the two or more questions include questions other than those that directly ask about the amount of fluid intake. The amount of fluid intake here is the amount of fluid intake over a specified period of time. The specified period is preferably one day, but may be one week, half a day, etc.

The raw information is, for example, a learning device, which will be described later. The raw information is, for example, a correspondence table, which will be described later. The raw information is, for example, an arithmetic formula, which will be described later. The raw information is acquired by the learning processing unit 13, which will be described later.

The learning processing unit 13 acquires raw information. The process of the learning processing unit 13 is, for example, any one of the following (1) to (3). It is preferable that the learning processing unit 13 acquires a learning device by performing the following process (1).
(1) When the source information is a learning device

The learning processing unit 13 acquires two or more pairs from the learning storage unit 11. A pair is a collection of an actual value and two or more pieces of answer information. The actual value in the pair corresponds to the collection of two or more pieces of answer information in the pair. The actual value and the collection of answer information in the pair correspond to the same identifier, for example.

The learning processing unit 13 performs learning processing using the two or more acquired pairs according to a machine learning algorithm, and acquires a learning device. More specifically, the learning processing unit 13, for example, provides the two or more acquired pairs to a module that performs machine learning learning processing, executes the module, and acquires a learning device. Note that the learning device may be called a classifier or a model. Furthermore, this learning device is provided to a module that performs machine learning prediction processing together with a set of two or more pieces of answer information, and is a learning device for acquiring the amount of water intake.

The learning module of the machine learning may be a random forest, a decision tree, deep learning, SVR, or the like, and the algorithm is not limited. For the machine learning, various machine learning functions such as the TensorFlow library, fastText, tinySVM, and the random forest module of the R language, and various existing libraries can be used.
(2) When the original information is a correspondence table

The learning processing unit 13 acquires two or more sets of answer information from the answer storage unit 111. The learning processing unit 13 also acquires actual measurement values corresponding to the sets of answer information from the actual measurement value storage unit 112.

For example, for each of two or more sets of answer information, the learning processing unit 13 constructs a vector whose elements are each of the answer information contained in each set. The learning processing unit 13 also acquires, for each set, correspondence information that associates the vector with an actual measurement value corresponding to the set of answer information that is the basis of the vector. The learning processing unit 13 then constructs a correspondence table having two or more pieces of correspondence information. Note that the correspondence information may be a set of answer information and an actual measurement value, or may be link information that associates a set of answer information and an actual measurement value, and may be any information that allows a set of answer information to be associated with an actual measurement value.
(3) When the original information is an arithmetic expression

The learning processing unit 13 acquires two or more pairs from the learning storage unit 11. Then, the learning processing unit 13 acquires an arithmetic formula that outputs the actual measurement value of each of the two or more pairs, for example, using each answer information of the set of answer information owned by each of the two or more pairs as a parameter. The learning processing unit 13 acquires the arithmetic formula, for example, by multiple regression analysis. Note that the arithmetic formula is not limited to a linear formula, but may be an equation of quadratic or higher order. Furthermore, the learning processing unit 13 may reduce the number of dimensions of a vector having each answer information as an element, for example, by principal component analysis, and then acquire the arithmetic formula using the vector.

The learning output unit 14 outputs information. For example, the learning output unit 14 outputs raw information acquired by the learning processing unit 13. It is preferable that the learning output unit 14 accumulates the raw information in the raw information storage unit 212 of the water intake estimation device 2.

In this case, output usually means storage on a recording medium, but it may also be a concept that includes display on a display, projection using a projector, printing on a printer, sound output, transmission to an external device, and handing over the processing results to other processing devices or other programs, etc.

Various types of information are stored in the storage unit 21 that constitutes the water intake estimation device 2. The various types of information include, for example, questionnaire information (described below), source information, intake information (described below), and one or more pieces of user information.

User information includes a user identifier and one or more user attribute values. The user attribute value is, for example, gender, but may also include various attribute values such as age, type of work (e.g., manual labor, white-collar, clerical work, construction, etc.), height, weight, etc.

The questionnaire storage unit 211 stores one or more pieces of questionnaire information. It is preferable that the questionnaire storage unit 211 stores two or more pieces of questionnaire information in association with conditions related to user attribute values. The questionnaire information has question information for two or more questions. The questionnaire information may exist for each type identifier that identifies the type of question.

The two or more questions in the questionnaire information include one or more questions other than a question that directly asks about the amount of fluid intake. The condition related to the user attribute value may be a condition using one user attribute value (e.g., "male", "age 20 or younger"), or a condition using two or more user attribute values (e.g., "male and 50 years or older", "male and physical labor", etc.).

The raw information storage unit 212 stores one or more pieces of raw information. The raw information storage unit 212 may store two or more pieces of raw information corresponding to conditions corresponding to user attribute values.

The raw information storage unit 212 may store two or more pieces of raw information corresponding to the type of question. In other words, the raw information may be associated with a type identifier.

The original information is information that serves as the basis for estimating the amount of fluid intake from the answer information to two or more questions, including questions other than those that directly ask about the amount of fluid intake. The original information is, for example, a learning device. The learning device is information acquired by performing a learning process using a machine learning algorithm using two or more teacher data sets that have answer information to two or more questions or answer-related information obtained from the answer information, and fluid intake information. The answer-related information (for example, "1", "2") is information that corresponds to the answer information (for example, "Yes", "No") and may be called answer information. The answer information is information entered by the user, and the answer-related information is information that has a one-to-one relationship with the answer information.

The reception unit 22 receives various instructions, information, and the like. For example, the reception unit 22 receives a questionnaire output instruction. This is an instruction to output questionnaire information. It is preferable that the questionnaire output instruction includes a user identifier or one or more user attribute values. The reception unit 22 receives, for example, one or more pieces of user answer information.

Note that, although reception here usually refers to the reception of information transmitted via a wired or wireless communication line, it may also be a concept that includes the reception of information input from an input device such as a keyboard, mouse, or touch panel, or the reception of information read from a recording medium such as an optical disk, magnetic disk, or semiconductor memory.

The answer receiving unit 221 receives user answer information having answer information for each of two or more questions. The user answer information has two or more pieces of answer information. Such answer information corresponds to a question identifier. The user answer information may have two or more pieces of answer information and a user identifier. The user answer information may have two or more pieces of answer information and one or two or more user attribute values.

The processing unit 23 performs various processes. For example, the processing unit 23 includes the questionnaire acquisition unit 231 and the intake amount acquisition unit 232.

The questionnaire acquisition unit 231 acquires questionnaire information from the questionnaire storage unit 211. For example, the questionnaire acquisition unit 231 acquires questionnaire information from the questionnaire storage unit 211 that corresponds to a condition that matches one or more user attribute values that are paired with a user identifier contained in the accepted questionnaire output instruction. For example, the questionnaire acquisition unit 231 acquires questionnaire information from the questionnaire storage unit 211 that corresponds to a condition that matches one or more user attribute values that are paired with a user identifier contained in the accepted questionnaire output instruction.

The intake amount acquisition unit 232 acquires intake amount information that specifies the amount of water intake, using two or more pieces of answer information contained in the user answer information accepted by the answer acceptance unit 221 and the raw information stored in the raw information storage unit 212.

The intake amount acquisition unit 232 acquires the intake amount information, for example, by using raw information corresponding to the user attribute value corresponding to the user answer information accepted by the answer acceptance unit 221 and two or more pieces of answer information contained in the user answer information.

The intake amount acquisition unit 232 acquires intake amount information for each type, for example, using answer information corresponding to each question of two or more types, which is answer information contained in the user answer information accepted by the answer acceptance unit 221, and raw information corresponding to each type, and acquires intake amount information using two or more pieces of intake amount information. Note that "for each type" means for each type identifier. The intake amount acquisition unit 232 acquires intake amount information, for example, for all origins, beverage origins, alcohol origins, and food origins, using answer information corresponding to the questions corresponding to each origin and raw information corresponding to each origin.

The intake amount acquiring section 232 acquires the intake amount information, for example, by any one of the following methods (1) to (3).
When the source information is a learner

The intake amount acquisition unit 232 performs prediction processing using a machine learning algorithm, using two or more pieces of answer information contained in the user answer information accepted by the answer acceptance unit 221 or answer-related information obtained from each of the two or more pieces of answer information, and a learning device stored in the raw information storage unit 212, to acquire intake amount information. Note that the answer-related information is information acquired from the answer information entered by the user, and may be regarded as the same as the answer information.

The machine learning prediction module, like the learning module, may be a random forest, a decision tree, deep learning, SVR, or the like, and the algorithm is not important. Furthermore, for machine learning, various machine learning functions such as the TensorFlow library, fastText, tinySVM, and the random forest module of the R language, as well as various existing libraries, can be used.

More specifically, the intake acquisition unit 232 acquires two or more pieces of answer information contained in the user answer information accepted by the answer acceptance unit 221, or answer-related information obtained from each of the two or more pieces of answer information.

Next, the intake amount acquisition unit 232 acquires a learning device from the raw information storage unit 212. The intake amount acquisition unit 232 acquires, for example, a learning device corresponding to a user attribute value corresponding to user response information from the raw information storage unit 212. The intake amount acquisition unit 232 also acquires, for example, a learning device corresponding to each of two or more types, for each type, from the raw information storage unit 212. The intake amount acquisition unit 232 also acquires, for example, a learning device corresponding to a user attribute value corresponding to user response information, from the raw information storage unit 212, a learning device corresponding to each of two or more types, for each type.

Next, the intake amount acquiring unit 232 provides two or more pieces of answer information or two or more pieces of answer-related information and the learning device to a module that performs machine learning prediction processing, executes the module, and acquires the intake amount information. The intake amount acquiring unit 232 acquires the intake amount information, for example, by type.
(2) When the original information is a correspondence table (2-1) When using one vector that is most similar to a vector obtained from user response information

The intake acquisition unit 232 constructs a vector whose elements are each piece of information contained in two or more pieces of answer information contained in the user answer information accepted by the answer acceptance unit 221 or answer-related information obtained from each of the two or more pieces of answer information.

Next, the intake amount acquisition unit 232 searches the correspondence table for a vector that is most similar to the vector. The intake amount acquisition unit 232 acquires the actual measurement value that is paired with the most similar vector as intake amount information.

The intake amount acquiring unit 232 acquires intake amount information by the above-mentioned process, for example, using a correspondence table corresponding to user attribute values. The intake amount acquiring unit 232 acquires intake amount information by the above-mentioned process, for each type, for example, using a correspondence table corresponding to each of two or more types. The intake amount acquiring unit 232 acquires intake amount information by the above-mentioned process, for each type, for example, using a correspondence table corresponding to user attribute values and corresponding to each of two or more types.
(2-2) When using two or more vectors that meet the conditions

The intake acquisition unit 232 constructs a vector whose elements are each piece of information contained in two or more pieces of answer information contained in the user answer information accepted by the answer acceptance unit 221 or answer-related information obtained from each of the two or more pieces of answer information.

Next, the intake amount acquisition unit 232 determines two or more vectors that are included in each correspondence information in the correspondence table and that satisfy the approximation condition for the vector constructed by the intake amount acquisition unit 232. Next, the intake amount acquisition unit 232 acquires actual measurement values that are paired with each of the two or more vectors.

Next, the intake amount acquisition unit 232 acquires intake amount information using the two or more acquired actual measured values. Note that the intake amount acquisition unit 232 acquires, for example, a representative value (e.g., average value, median) of the two or more acquired actual measured values as the intake amount information. For example, the intake amount acquisition unit 232 calculates a weighted average of the two or more acquired actual measured values using the actual measured values and the degree of approximation, and acquires this value as the intake amount information. Note that the approximation condition is, for example, that the distance between the two vectors is equal to or less than a threshold value or is less than a threshold value.

The intake amount acquiring unit 232 acquires intake amount information by the above-mentioned process, for example, using a correspondence table corresponding to user attribute values. The intake amount acquiring unit 232 acquires intake amount information by the above-mentioned process, for each type, for example, using a correspondence table corresponding to each of two or more types. The intake amount acquiring unit 232 acquires intake amount information by the above-mentioned process, for each type, for example, using a correspondence table corresponding to user attribute values and corresponding to each of two or more types.
(3) When the original information is an arithmetic expression

The intake acquisition unit 232 constructs a vector whose elements are each piece of information contained in two or more pieces of answer information contained in the user answer information accepted by the answer acceptance unit 221 or answer-related information obtained from each of the two or more pieces of answer information.

The intake amount acquisition unit 232 acquires the calculation formula, which is the raw information, from the raw information storage unit 212. The intake amount acquisition unit 232 provides the constructed vector to the calculation formula, executes the calculation formula, and acquires the intake amount information.

The output unit 24 outputs various types of information. The various types of information include, for example, questionnaire information and intake information.

Here, output usually means transmission to the user terminal 3, but it may also be a concept that includes display on a display, projection using a projector, printing on a printer, sound output, storage on a recording medium, and delivery of the processing results to other processing devices or other programs, etc.

The questionnaire output unit 241 transmits the questionnaire information acquired by the questionnaire acquisition unit 231 to the user terminal 3.

The intake output unit 242 outputs the intake information acquired by the intake acquisition unit 232.

Here, output usually means transmission to the user terminal 3, but it may also be a concept that includes display on a display, projection using a projector, printing on a printer, sound output, storage on a recording medium, and delivery of the processing results to other processing devices or other programs, etc.

The terminal storage unit 31 constituting the user terminal 3 stores various types of information. The various types of information are, for example, a user identifier and one or more user attribute values.

The terminal reception unit 32 receives various instructions and information. The various instructions and information are, for example, answer information, a questionnaire output instruction, and a transmission instruction. The transmission instruction is an instruction to transmit intake amount information. The transmission instruction includes user answer information. The transmission instruction includes, for example, a user identifier. The transmission instruction includes, for example, one or more user attribute values.

The means for inputting various instructions and information can be anything, such as a touch panel, keyboard, mouse, or menu screen.

The device processing unit 33 performs various types of processing. For example, the various types of processing are to convert the instructions, information, etc. accepted by the device accepting unit 32 into a data structure for instructions, information, etc. to be transmitted. For example, the various types of processing are to convert the information received by the device receiving unit 35 into a data structure for output.

The terminal transmission unit 34 transmits various instructions, information, etc. to the water intake estimation device 2. The terminal transmission unit 34 transmits instructions, information, etc. configured by the terminal processing unit 33 to the water intake estimation device 2.

The terminal receiving unit 35 receives various types of information. For example, the terminal receiving unit 35 receives questionnaire information or intake information from the water intake estimation device 2.

The terminal output unit 36 outputs various types of information. For example, the terminal output unit 36 outputs questionnaire information or intake amount information.

The learning storage unit 11, the response storage unit 111, the actual value storage unit 112, the storage unit 21, the questionnaire storage unit 211, the raw information storage unit 212, and the terminal storage unit 31 are preferably non-volatile recording media, but can also be realized using volatile recording media.

The process by which information is stored in the learning storage unit 11, etc. is not important. For example, information may be stored in the learning storage unit 11, etc. via a recording medium, information transmitted via a communication line, etc. may be stored in the learning storage unit 11, etc., or information inputted via an input device may be stored in the learning storage unit 11, etc.

The learning acceptance unit 12 and the terminal acceptance unit 32 may be realized by a device driver for an input means such as a touch panel or a keyboard, or control software for a menu screen. The learning acceptance unit 12 may also be realized by a wireless or wired communication means.

The learning processing unit 13, processing unit 23, questionnaire acquisition unit 231, intake acquisition unit 232, and device processing unit 33 can usually be realized by a processor, memory, etc. The processing procedures of the processing unit 23, etc. are usually realized by software, and the software is recorded in a recording medium such as a ROM. However, they may also be realized by hardware (dedicated circuitry). The processor may be, for example, a CPU, MPU, GPU, etc., and the type is not important.

The learning output unit 14 and the terminal output unit 36 may or may not include output devices such as a display or a speaker. The learning output unit 14 and the like may be realized by driver software for an output device, or driver software for an output device and an output device, etc. The learning output unit 14 may also be realized by wireless or wired communication means.

The reception unit 22, the response reception unit 221, and the terminal reception unit 35 are typically realized by wireless or wired communication means, but may also be realized by means of receiving broadcasts.

The output unit 24, questionnaire output unit 241, intake output unit 242, and terminal transmission unit 34 are typically implemented using wireless or wired communication means, but may also be implemented using broadcasting means.

The terminal reception unit 32 can be realized by a device driver for an input means such as a touch panel or keyboard, or control software for a menu screen, etc.

The terminal output unit 36 may or may not include an output device such as a display or speaker. The terminal output unit 36 may be realized by driver software for an output device, or by a combination of driver software for an output device and an output device, etc.

Next, an example of the operation of the water intake estimation system A will be described. First, an example of the operation of the learning device 1 will be described using the flowchart in FIG. 4.

(Step S401) The learning processing unit 13 assigns 1 to counter i.

(Step S402) The learning processing unit 13 judges whether or not to acquire the i-th raw information. If the i-th raw information is to be acquired, the process proceeds to step S403, and if the i-th raw information is not to be acquired, the process ends.

The learning processing unit 13 determines whether to acquire the i-th original information, for example, depending on whether the i-th identification information exists in the learning storage unit 11. Note that if the identification information in the learning storage unit 11 is, for example, (gender = male & type of question set = beverage origin) (gender = male & type of question set = alcohol origin) (gender = male & type of question set = food origin) (gender = male & type of question set = all origins) (gender = female & type of question set = beverage origin) (gender = female & type of question set = alcohol origin) (gender = female & type of question set = food origin) (gender = female & type of question set = all origins), the counter i can take a value from 1 to 8.

(Step S403) The learning processing unit 13 assigns 1 to counter j.

(Step S404) The learning processing unit 13 determines whether or not the jth set of answer information exists. If the jth set of answer information exists, the process proceeds to step S405; if the jth set of answer information does not exist, the process proceeds to step S410.

The jth set of answer information is associated with an identifier, for example. The identifier is a user identifier, a day identifier, or a user identifier and a day identifier.

(Step S405) The learning processing unit 13 acquires the jth set of answer information. Note that the answer information acquired here may not be the entire jth set of answer information. In other words, if a question corresponds to any of two or more types, the learning processing unit 13 acquires only the answer information corresponding to the question of the type corresponding to the ith original information.

(Step S406) The learning processing unit 13 constructs a vector using the set of answer information acquired in step S405.

(Step S407) The learning processing unit 13 acquires the actual measurement values that are paired with the set of answer information acquired in step S405 from the actual measurement value storage unit 112.

(Step S408) The learning processing unit 13 creates a record having the vector obtained in step S406 and the actual measurement value obtained in step S407, and temporarily stores the record in a buffer (not shown).

(Step S409) The learning processing unit 13 increments the counter j by 1. Return to step S404.

(Step S410) The learning processing unit 13 obtains two or more records from a buffer (not shown) and obtains raw information using the two or more records. The learning processing unit 13 obtains a learning device, for example, by machine learning prediction processing.

(Step S411) The learning processing unit 13 stores the raw information acquired in step S410. When acquiring two or more pieces of raw information, the learning processing unit 13 stores the raw information in association with the identification information. The raw information may be stored in the learning storage unit 11, for example, but is not limited thereto.

(Step S412) The learning processing unit 13 increments the counter i by 1. Return to step S402.

Next, an example of the operation of the water intake estimation device 2 will be described using the flowchart in Figure 5.

(Step S501) The reception unit 22 determines whether or not a questionnaire output instruction has been received. If a questionnaire output instruction has been received, the process proceeds to step S502. If a questionnaire output instruction has not been received, the process proceeds to step S504. Here, the reception unit 22 determines whether or not a questionnaire output instruction has been received from the user terminal 3.

(Step S502) The questionnaire acquisition unit 231 acquires questionnaire information corresponding to the questionnaire output instruction received in step S501 from the questionnaire storage unit 211. The questionnaire acquisition unit 231 acquires, for example, one or more user attribute values corresponding to the user identifier included in the questionnaire output instruction from the storage unit 21, and acquires questionnaire information corresponding to the one or more user attribute values from the questionnaire storage unit 211.

(Step S503) The questionnaire output unit 241 outputs the questionnaire information acquired in step S502. Return to step S501. Note that the questionnaire output unit 241 transmits the questionnaire information to the user terminal 3, for example.

(Step S504) The answer receiving unit 221 judges whether or not user answer information has been received. If user answer information has been received, the process proceeds to step S505, and if user answer information has not been received, the process returns to step S501. Note that here, the receiving unit 22 judges, for example, whether or not user answer information has been received from the user terminal 3.

(Step S505) The intake acquisition unit 232 assigns 1 to counter i.

(Step S506) The intake acquisition unit 232 determines whether the i-th question type exists. If the i-th question type exists, the process proceeds to step S507, and if the i-th question type exists, the process proceeds to step S511.

(Step S507) The intake acquisition unit 232 acquires two or more pieces of answer information corresponding to the type of the i-th question from the user answer information. The intake acquisition unit 232 uses the two or more pieces of acquired answer information to construct a vector.

(Step S508) The intake acquisition unit 232 acquires raw information corresponding to the i-th question type from the raw information storage unit 212.

(Step S509) The intake amount acquisition unit 232 acquires the water intake amount using the vector constructed in step S507 and the raw information acquired in step S508. The intake amount acquisition unit 232, for example, performs a machine learning prediction process using the vector constructed in step S507 and the raw information acquired in step S508 to acquire the water intake amount.

(Step S510) The intake acquisition unit 232 increments the counter i by 1. Return to step S506.

(Step S511) The intake acquisition unit 232 uses one or more water intake amounts acquired in step S509 to construct the intake information to be output.

(Step S512) The intake output unit 242 outputs the intake information acquired in step S511. Return to step S501.

Here, the intake output unit 242 transmits, for example, the intake information acquired in step S511 to the user terminal 3.

In the flowchart in Figure 5, processing ends when the power is turned off or an interrupt occurs to end processing.

Next, an example of the operation of the user terminal 3 will be explained using the flowchart in FIG. 6.

(Step S601) The terminal reception unit 32 determines whether or not a questionnaire output instruction has been received. If a questionnaire output instruction has been received, the process proceeds to step S602; if a questionnaire output instruction has not been received, the process returns to step S601.

(Step S602) The device processing unit 33 configures a questionnaire output instruction to be output. The device transmission unit 34 transmits the configured questionnaire output instruction to the water intake estimation device 2.

The device processing unit 33, for example, reads out the user identifier from the device storage unit 31 and generates an instruction to output a questionnaire having the user identifier.

(Step S603) The terminal receiving unit 35 determines whether or not questionnaire information has been received. If questionnaire information has been received, the process proceeds to step S604; if not, the process returns to step S603.

(Step S604) The device processing unit 33 constructs questionnaire information to be output from the questionnaire information received in step S603. The terminal output unit 36 outputs the questionnaire information.

(Step S605) The terminal reception unit 32 determines whether or not answer information has been received from the user. If answer information has been received, the process proceeds to step S606; if answer information has not been received, the process proceeds to step S607.

(Step S606) The device processing unit 33 associates the answer information received in step S605 with the question identifier and temporarily stores it in a buffer (not shown). Return to step S605.

(Step S607) The terminal reception unit 32 determines whether or not a transmission instruction has been received from the user. If a transmission instruction has been received, the process proceeds to step S608; if a transmission instruction has not been received, the process returns to step S605.

(Step S608) The device processing unit 33 reads two or more pieces of answer information from the buffer and configures user answer information. Note that the user answer information includes, for example, a user identifier.

(Step S609) The terminal transmission unit 34 transmits the user response information constructed in step S608 to the water intake estimation device 2.

(Step S610) The terminal receiving unit 35 determines whether or not intake information has been received from the water intake estimation device 2. If intake information has been received, the process proceeds to step S611, and if intake information has not been received, the process returns to step S610.

(Step S611) The device processing unit 33 uses the intake amount information received in step S610 to construct the intake amount information to be output. The terminal output unit 36 outputs the intake amount information. Return to step S601.

In the flowchart in Figure 6, processing ends when the power is turned off or an interrupt occurs to end processing.

The specific operation of the water intake estimation system A in this embodiment will be described below. A conceptual diagram of the water intake estimation system A is shown in Figure 1.

Now, it is assumed that the learning storage unit 11 of the learning device 1 stores two or more pieces of questionnaire information including the questionnaire information shown in Figures 7 and 8. The questionnaire information in Figure 7 corresponds to information "male" that specifies a condition related to a user attribute value. The questionnaire information in Figure 8 corresponds to information "female" that specifies a condition related to a user attribute value. It is also assumed that each question in the questionnaire information corresponds to a type identifier. Here, it is assumed that the type identifier is one of "beverage-derived," "alcohol-derived," "food-derived," and "all-derived."

In this situation, assume that many users have inputted answer information to the questionnaire information, and as a result, a large number of sets of answer information are stored in the learning storage unit 11 in association with user identifiers. An example of such a large number of sets of answer information is the user answer information management table shown in FIG. 9. The user answer information management table is a table having "user identifier", "user attribute value", "question identifier", and "type identifier". In this case, the "question identifier" ranges from "1" to "40". There are also 10 questions for each type identifier. The first record in FIG. 9 indicates that the user with user identifier "U001" is a "male" and has input answer information "3" ... "5", "3" ... "5", "1" ... "4", "3" ... "3".

Also, assume that the actual measured values of many users are stored in the learning storage unit 11 in association with user identifiers. Note that the actual measured values here are the amount of water intake per day.

As described above, the learning processing unit 13 may obtain actual measurement values for each type identifier, for example, from the user's responses to a multiple-choice questionnaire. The learning processing unit 13 may also obtain actual measurement values for each type identifier from the user's responses to a survey form based on a descriptive food record method. Furthermore, the learning processing unit 13 may obtain actual measurement values that are input by the user and that are associated with the user identifier. In other words, the method of obtaining the actual measurement management table is not important.

As a result of the above processing, the actual measurement storage unit 112 stores the actual measurement management table shown in Fig. 10. The actual measurement management table is a table showing the correspondence between user identifiers, type identifiers, and water intake amounts. The water intake amounts are, for example, _a001 , _a002 , ..., _b001 , ..., _c001 , ..., _d001 , _d002 , ..., and these values are, for example, numerical values in milliliters.

Then, the learning processing unit 13 of the learning device 1 performs a machine learning learning process for each user identifier (male, female) and each type identifier (beverage-derived, alcohol-derived, food-derived, all-derived) using the user response information management table shown in FIG. 9 and the actual measured values in the actual measured value management table shown in FIG. 10, by the process described with reference to FIG. 5, and obtains a learning device. In other words, the learning processing unit 13 performs a machine learning learning process for each user identifier and each type identifier, and obtains eight learning devices. The learning processing unit 13 then associates each of the eight learning devices with identification information having a user identifier and a type identifier, and stores them in the raw information storage unit 212 of the water intake estimation device 2.

Through the above process, the raw information management table shown in FIG. 11 is stored in the raw information storage unit 212 of the water intake estimation device 2. The raw information management table has eight records, each having an "ID", "user identifier", "type identifier", and "raw information". Here, "ID" is information that identifies the record. "Raw information" is an identifier (e.g., file name) of the file of the machine learning (e.g., random forest) learning device. Note that the actual file is assumed to exist in the raw information storage unit 212. Furthermore, the "user identifier" and "type identifier" may be collectively referred to as identification information.

Furthermore, it is assumed that the questionnaire storage unit 211 stores two or more pieces of questionnaire information including the questionnaire information in Figures 7 and 8.

Furthermore, the storage unit 21 stores a user information management table (not shown) that manages two or more pieces of user information each having a user identifier and one or more user attribute values (including gender).

In this situation, it is assumed that the user inputs a questionnaire output instruction to the user terminal 3. Then, by the process described in FIG. 6, the user terminal 3 accepts the questionnaire output instruction and transmits a questionnaire output instruction including the user identifier to the water intake estimation device 2.

Next, the reception unit 22 of the water intake estimation device 2 receives the questionnaire output instruction. The questionnaire acquisition unit 231 then acquires a user attribute value (here, "male") corresponding to the user identifier included in the questionnaire output instruction from the user information management table in the storage unit 21, and acquires questionnaire information corresponding to the user attribute value from the questionnaire storage unit 211. Next, the questionnaire output unit 241 transmits the questionnaire information to the user terminal 3.

Next, the user terminal 3 receives and outputs the questionnaire information. An example of such output is shown in FIG. 12.

Let us assume that the user inputs answer information for each question in the questionnaire information in FIG. 12 and selects the "Send" button 1201. Then, the user terminal 3 transmits user answer information, which includes a user identifier and two or more pieces of answer information, to the water intake estimation device 2.

Next, the response receiving unit 221 of the water intake estimation device 2 receives the user response information from the user terminal 3.

Next, the intake amount acquisition unit 232 acquires the learning device paired with the user attribute value "male" for each type identifier from FIG. 11. Then, for each type identifier, the intake amount acquisition unit 232 acquires two or more pieces of answer information corresponding to each type identifier from the user answer information, and uses the two or more pieces of answer information to construct a vector. Next, the intake amount acquisition unit 232 provides the vector and the learning device corresponding to the type identifier for each type identifier to a machine learning prediction module, executes the prediction module, and acquires intake amount information for each type identifier. Such intake amount information is intake amount information for each of beverages, alcoholic beverages, meals, and total intakes. Next, the intake amount acquisition unit 232 adds up the four pieces of intake amount information to acquire intake amount information "1215 milliliters" indicating the user's daily water intake.

Next, the output unit 24 transmits the intake amount information to the user terminal 3. The output unit 24 may transmit information containing the intake amount information to the user terminal 3. Such information is, for example, a character string, and is a character string in which the acquired intake amount information is substituted for the variable <intake amount information> of a template (here, "Your average daily water intake is <intake amount information>").

Next, the user terminal 3 receives and outputs the intake amount information. An example of such output is shown in FIG. 13.

As described above, according to this embodiment, water intake can be estimated based on responses to a questionnaire that includes questions other than those directly asking about the amount of water ingested.

In addition, in this embodiment, the appropriate amount of fluid intake can be estimated based on answers to a questionnaire that varies depending on the user's attribute values.

In addition, this embodiment can estimate the appropriate amount of water intake for each source.

Furthermore, in this embodiment, the appropriate amount of fluid intake can be estimated using machine learning algorithms such as random forest.

The processing in this embodiment may be realized by software. This software may be distributed by software download or the like. This software may also be recorded on a recording medium such as a CD-ROM and distributed. This also applies to the other embodiments in this specification. The software that realizes the water intake estimation device 2 in this embodiment is a program such as the following. In other words, this program:
The program causes a computer that can access a raw information storage unit in which raw information that is the basis for estimating fluid intake from answer information to two or more questions, including questions other than those that directly ask about the amount of fluid ingested, to function as an answer accepting unit that accepts user answer information having answer information to the two or more questions, an intake amount acquiring unit that acquires intake information that specifies the amount of fluid intake using two or more answer information contained in the user answer information accepted by the answer accepting unit and the raw information stored in the raw information storage unit, and an intake amount output unit that outputs the intake amount information.

(Embodiment 2)
In this embodiment, a moisture advice system will be described that includes a moisture advice output device that acquires a user's moisture intake amount, acquires advice information corresponding to the moisture intake amount, and outputs the advice information.

In addition, in this embodiment, a moisture advice system is described that includes a moisture advice output device that outputs advice information based on the user's moisture intake and appropriate advice information according to the user's attribute values.

In addition, in this embodiment, a moisture advice system is described that includes a moisture advice output device that acquires advice information using information on moisture intake and health checkups, and outputs the advice information.

In this embodiment, a moisture advice system is described that includes a moisture advice output device that receives answers to a questionnaire, obtains a moisture intake amount using the answers, and obtains and outputs advice information according to the moisture intake amount. The questionnaire has two or more types of questions, for example, from among beverage-derived, alcohol-derived, and diet-derived. The questionnaire is associated with user attribute value conditions (for example, gender, age, and type of work), and it is preferable that different questionnaires are used depending on the user attribute value. It is also preferable that there are two or more types of questions, and that the moisture intake amount is obtained for each type of question. It is also preferable that the moisture intake amount is obtained using machine learning such as random forest.

Figure 14 is a conceptual diagram of a moisture advice system B in this embodiment. The moisture advice system B includes a moisture advice output device 4 and one or more user terminals 5. The moisture advice system B may also include the learning device 1 and moisture intake estimation device 2 described above.

The moisture advice output device 4 is, for example, a so-called server. The server may be, for example, a cloud server or an ASP server, and the type does not matter. However, the moisture advice output device 4 may also be a standalone device such as a so-called personal computer, tablet terminal, smartphone, etc.

The user terminal 5 may be a personal computer, tablet terminal, smartphone, etc., and the type is not important.

The moisture advice output device 4 and the user terminal 5 may be capable of communicating with each other via the Internet, LAN, etc.

Figure 15 is a block diagram of the moisture advice system B in this embodiment. Figure 16 is a block diagram of the moisture advice output device 4.

The moisture advice output device 4 includes a storage unit 41, a reception unit 42, a processing unit 43, and an output unit 44. The storage unit 41 includes a questionnaire storage unit 211, a raw information storage unit 212, and a corresponding information storage unit 411. The reception unit 42 includes a response reception unit 221 and a diagnosis information reception unit 421. The processing unit 43 includes a questionnaire acquisition unit 231, an intake amount acquisition unit 232, an advice acquisition unit 431, and a score acquisition unit 432. The output unit 44 includes a questionnaire output unit 241, an intake amount output unit 242, an advice output unit 441, and a score output unit 442.

The user terminal 5 includes a terminal storage unit 51, a terminal reception unit 52, a terminal processing unit 53, a terminal transmission unit 54, a terminal reception unit 55, and a terminal output unit 56.

Various types of information are stored in the storage unit 41 constituting the moisture advice output device 4. The various types of information are, for example, questionnaire information, raw information, correspondence information described below, a score calculation formula, and one or more pieces of user information. The one or more pieces of user information may be referred to as a user information management table.

The score formula is a formula for calculating a score. The score formula is a formula that uses intake information as a parameter. The score formula may correspond to an intake condition. The score is information regarding the goodness of the user's water intake. Information regarding the goodness of water intake can also be said to be information regarding the badness of water intake.

User information includes a user identifier and one or more user attribute values. The user attribute value is, for example, gender, but may also include various attribute values such as age, type of work (e.g., manual labor, white-collar, clerical work, construction, etc.), height, weight, etc.

The correspondence information storage unit 411 stores two or more pieces of correspondence information. The correspondence information is information for establishing a correspondence between intake conditions and advice source information. Two or more pieces of correspondence information may be called a correspondence table. The correspondence information may be information for establishing a correspondence between intake conditions and scores.

The intake amount condition is a condition related to the intake amount information. The intake amount condition may be a condition using the intake amount information and a user attribute value. The intake amount condition may be a condition using the intake amount information and diagnostic information. The intake amount condition may be a condition using the intake amount information, a user attribute value, and diagnostic information.

The intake amount condition is, for example, information indicating the range of the intake amount information (for example, "1000 ml <= 1500 ml", "2000 ml or more"). The intake amount condition may also include a user condition. The user condition is a condition based on one or more user attribute values, a condition based on diagnostic information described below, or a condition based on one or more user attribute values and diagnostic information. For example, the user condition is "gender = male", "gender = female & age >= 40 years old". For example, the user condition is "has diabetes". For example, the user condition is "gender = female & age >= 40 years old" & "has diabetes".

The advice source information is information that is the source of the advice information. The advice source information is information for obtaining the advice information. The advice source information may be the advice information itself. The advice source information is, for example, a template sentence for the advice information. The advice source information is, for example, link information (for example, a file name, a URL) to the advice information (for example, a file). Note that the advice information is information that constitutes the advice. The advice is usually advice regarding fluid intake. The advice is usually advice for maintaining health.

The reception unit 42 receives species instructions and information, etc., such as questionnaire output instructions, user response information, user response information corresponding to user attribute values, diagnostic information (described below), and intake amount information. It is preferable that the intake amount information is associated with a user identifier.

Note that, although reception here usually refers to the reception of information transmitted via a wired or wireless communication line, it may also be a concept that includes the reception of information input from an input device such as a keyboard, mouse, or touch panel, or the reception of information read from a recording medium such as an optical disk, magnetic disk, or semiconductor memory.

The diagnostic information receiving unit 421 receives diagnostic information. The diagnostic information is information relating to the health of the user. It is preferable that the diagnostic information is information relating to the results of the user's health check. However, the diagnostic information may also be information that identifies the user's subjective health condition. Examples of diagnostic information include the presence or absence of diabetes, blood glucose level, and uric acid level. The diagnostic information may be of any target or part, or any content. It is preferable that the diagnostic information is information relating to a target or part for which the required amount of fluid intake changes.

The processing unit 43 performs various processes. For example, the processing unit 43 is the process performed by the questionnaire acquisition unit 231, the intake acquisition unit 232, the advice acquisition unit 431, and the score acquisition unit 432.

It is preferable that the intake amount acquisition unit 232 acquires the intake amount information by the process described in embodiment 1. However, the intake amount acquisition unit 232 may acquire the intake amount information accepted by the acceptance unit 42. The intake amount information accepted by the acceptance unit 42 is usually intake amount information input by the user.

The advice acquisition unit 431 acquires advice information for the user using the intake amount information acquired by the intake amount acquisition unit 232.

The advice acquisition unit 431 acquires advice information, for example, using advice source information that is paired with the intake condition that the intake amount information matches. That is, the advice acquisition unit 431 determines, for example, the intake condition that the intake amount information matches from the correspondence table in the storage unit 41. The advice acquisition unit 431 acquires advice source information that is paired with the determined intake amount condition from the correspondence table. Next, the advice acquisition unit 431 acquires advice information, for example, using the advice source information. For example, the advice acquisition unit 431 constructs advice information by substituting the acquired intake amount information for a variable of the advice source information having a variable for substituting the intake amount information.

It is preferable that the advice acquisition unit 431 acquires advice information for the user using the user attribute value and the intake amount information. For example, the advice acquisition unit 431 may determine an intake amount condition corresponding to the acquired user attribute value and intake amount information, and acquire advice information using advice source information that is paired with the intake amount condition.

It is preferable that the advice acquisition unit 431 acquires advice information for the user using the intake amount information and the diagnosis information. For example, the advice acquisition unit 431 may determine an intake condition corresponding to the acquired intake amount information and diagnosis information, and acquire advice information using advice source information that is paired with the intake amount condition.

It is preferable that the advice acquisition unit 431 acquires advice information for the user using the user attribute value, intake amount information, and diagnosis information. For example, the advice acquisition unit 431 may determine an intake amount condition corresponding to the acquired user attribute value, intake amount information, and diagnosis information, and acquire advice information using advice source information that is paired with the intake amount condition.

The score acquisition unit 432 acquires the score using the intake amount information.

The score acquisition unit 432, for example, acquires a score corresponding to the intake condition that the intake information matches from the correspondence table in the storage unit 41.

The score acquisition unit 432 acquires, for example, a score corresponding to an intake condition where the user attribute value matches the intake information from the correspondence table in the storage unit 41.

The score acquisition unit 432 acquires, for example, a score corresponding to an intake condition where the intake information and the diagnosis information match from the correspondence table in the storage unit 41.

The score acquisition unit 432 acquires, for example, a score corresponding to an intake condition where the user attribute value, the intake information, and the diagnosis information match from the correspondence table in the storage unit 41.

The score acquisition unit 432, for example, substitutes the acquired intake amount information into a score calculation formula that uses the intake amount information as a parameter, executes the score calculation formula, and calculates the score.

The score acquisition unit 432, for example, acquires from the storage unit 41 a score calculation formula that is paired with the intake condition that the intake information matches, substitutes the acquired intake information into the score calculation formula, executes the score calculation formula, and calculates the score.

The score acquisition unit 432, for example, acquires from the storage unit 41 a score calculation formula that is paired with an intake condition where the user attribute value and the intake amount information match, substitutes the acquired intake amount information into the score calculation formula, executes the score calculation formula, and calculates the score.

The score acquisition unit 432, for example, acquires from the storage unit 41 a score calculation formula that is paired with an intake condition where the diagnostic information and the intake information match, substitutes the acquired intake information into the score calculation formula, executes the score calculation formula, and calculates a score.

The score acquisition unit 432, for example, acquires from the storage unit 41 a score calculation formula that pairs with an intake condition where the user attribute value, the diagnosis information, and the intake information match, substitutes the acquired intake information into the score calculation formula, executes the score calculation formula, and calculates a score.

The output unit 44 outputs various types of information, such as questionnaire information, intake amount information, advice information, and scores.

Here, output usually means transmission to the user terminal 5, but it may also be a concept that includes display on a display, projection using a projector, printing on a printer, sound output, storage on a recording medium, and delivery of the processing results to other processing devices or other programs, etc.

The advice output unit 441 outputs the advice information acquired by the advice acquisition unit 431. The advice output unit 441 transmits the advice information to, for example, the user terminal 5.

The score output unit 442 outputs the score acquired by the score acquisition unit 432. The score output unit 442 transmits the score to, for example, the user terminal 5.

The terminal storage unit 51 constituting the user terminal 5 stores various types of information. The various types of information are, for example, a user identifier and one or more user attribute values.

The terminal reception unit 52 receives various instructions and information. Examples of the various instructions and information include answer information, questionnaire output instructions, transmission instructions, intake amount information, and diagnostic information.

The transmission instruction is an instruction to transmit advice information. The transmission instruction includes user response information. The transmission instruction includes, for example, a user identifier. The transmission instruction includes, for example, one or more user attribute values.

The means for inputting various instructions and information can be anything, such as a touch panel, keyboard, mouse, or menu screen.

The device processing unit 53 performs various types of processing. For example, the various types of processing are to convert the instructions, information, etc. accepted by the device accepting unit 52 into a data structure for instructions, information, etc. to be transmitted. For example, the various types of processing are to convert the information received by the device receiving unit 55 into a data structure for output.

The terminal transmission unit 54 transmits various instructions, information, etc. to the moisture advice output device 4. The terminal transmission unit 54 transmits instructions, information, etc. configured by the device processing unit 53 to the moisture advice output device 4. The terminal transmission unit 54 transmits, for example, answer information, questionnaire output instructions, transmission instructions, intake amount information, and diagnostic information to the moisture advice output device 4.

The terminal receiving unit 55 receives various types of information, etc. The terminal receiving unit 35 receives, for example, questionnaire information, intake amount information, advice information, or a score from the fluid advice output device 4.

The terminal output unit 56 outputs various information, etc. The terminal output unit 36 outputs, for example, questionnaire information, intake amount information, advice information, or a score.

Here, output is a concept that includes displaying on a display, projecting using a projector, printing on a printer, outputting sound, sending to an external device, storing on a recording medium, and passing on the processing results to other processing devices or other programs, etc.

The storage unit 41, the correspondence information storage unit 411, and the terminal storage unit 51 are preferably non-volatile recording media, but can also be realized using volatile recording media.

The process by which information is stored in the storage unit 41, etc. is not important. For example, information may be stored in the storage unit 41, etc. via a recording medium, information transmitted via a communication line, etc. may be stored in the storage unit 41, etc., or information inputted via an input device may be stored in the storage unit 41, etc.

The reception unit 42, the diagnostic information reception unit 421, and the terminal reception unit 55 are usually realized by wireless or wired communication means, but may be realized by means for receiving broadcasts. The reception unit 42 and the diagnostic information reception unit 421 may also be realized by a device driver for an input means such as a touch panel or a keyboard, or by control software for a menu screen, etc.

The processing unit 43, advice acquisition unit 431, score acquisition unit 432, and device processing unit 53 can usually be realized by a processor, memory, etc. The processing procedures of the processing unit 43, etc. are usually realized by software, and the software is recorded in a recording medium such as a ROM. However, they may also be realized by hardware (dedicated circuitry). The processor may be, for example, a CPU, MPU, GPU, etc., and the type is not important.

The output unit 44, advice output unit 441, score output unit 442, and terminal transmission unit 54 are usually realized by wireless or wired communication means, but may be realized by broadcasting means. The output unit 44, advice output unit 441, and score output unit 442 may be realized by driver software for an output device such as a display or speaker, or by driver software for an output device and an output device, etc.

The terminal reception unit 52 can be realized by a device driver for an input means such as a touch panel or keyboard, or control software for a menu screen, etc.

The terminal output unit 56 may or may not include an output device such as a display or speaker. The terminal output unit 56 may be realized by driver software for an output device, or by a combination of driver software for an output device and an output device, etc.

Next, an example of the operation of the moisture advice system B will be described. First, an example of the operation of the moisture advice output device 4 will be described using the flowchart in FIG. 17. Note that in the flowchart in FIG. 17, explanations of steps that are the same as those in the flowchart in FIG. 5 will be omitted. It goes without saying that the subject of the flowchart in FIG. 17 is the moisture advice output device 4.

(Step S1701) The intake amount acquisition unit 232 acquires intake amount information using one or more water intake amounts acquired in step S509. For example, the intake amount acquisition unit 232 adds up two or more water intake amounts acquired in step S509 to acquire intake amount information. For example, the intake amount acquisition unit 232 acquires one water intake amount acquired in step S509.

(Step S1702) The score acquisition unit 432 acquires a score using the intake amount information acquired in step S1701. Note that there are various methods for the score acquisition unit 432 to acquire a score, and as these have been described above, detailed explanations will be omitted here.

(Step S1703) The advice acquisition unit 431 acquires advice information using the intake amount information acquired in step S1701. Note that there are various methods for the advice acquisition unit 431 to acquire advice information, and as these have been described above, detailed explanations will be omitted here.

(Step S1704) The processing unit 43 constructs information to be output using one or more of the intake amount information acquired in step S1701, the score acquired in step S1702, and the advice information acquired in step S1703. The information to be output typically includes one or more of the intake amount information, score, and advice information.

(Step S1705) The output unit 44 outputs the information configured in step S1704. Return to step S501. Note that the output unit 44 transmits the information configured in step S1704 to the user terminal 5, for example.

In addition, in step S504 of the flowchart in FIG. 17, diagnostic information may also be accepted. In such a case, it is preferable that the advice acquisition unit 431 acquires advice information using the diagnostic information as well. In such a case, it is preferable that the score acquisition unit 432 acquires a score using the diagnostic information as well. In the flowchart in FIG. 17, it is preferable that the processing unit 43 acquires advice information or a score using one or more user attribute values that are paired with a user identifier corresponding to the user answer information.

Furthermore, in the flowchart of FIG. 17, processing ends when the power is turned off or an interrupt occurs to end processing.

Next, an example of the operation of the user terminal 5 will be described with reference to the flowchart in FIG. 18. Note that in the flowchart in FIG. 18, the description of the same steps as in the flowchart in FIG. 6 will be omitted.

(Step S1801) The terminal receiving unit 55 determines whether or not information to be output has been received from the moisture advice output device 4. If information has been received, the process proceeds to step S1802, and if information has not been received, the process returns to step S1801. Note that the received information is written in, for example, HTML, XML, etc. However, the structure of the received information is not important.

(Step S1802) The device processing unit 53 uses the information received in step S1801 to compose information to be output. The terminal output unit 56 outputs the information. Return to step S601. Note that the information to be output typically includes one or more of the following: intake amount information, score, and advice information.

In the flowchart in Figure 18, processing ends when the power is turned off or an interrupt occurs to end processing.

A specific example of the operation of the moisture advice system B in this embodiment will be described below. A conceptual diagram of the moisture advice system B is shown in FIG. 14.

In this specific example, intake information is acquired through a process similar to that described in the specific example of embodiment 1.

The questionnaire storage unit 211 of the moisture advice output device 4 stores two or more pieces of questionnaire information, including the questionnaire information shown in Figures 7 and 8.

The raw information storage unit 212 stores the raw information management table shown in FIG. 11. Note that the method for acquiring the raw information management table shown in FIG. 11 has been described in the first embodiment, so a detailed description thereof will be omitted here.

In this situation, two specific examples will be described below. Specific example 1 is a case where advice information and a score are obtained using intake amount information and a user identifier. Specific example 2 is a case where advice information and a score are obtained using intake amount information, a user identifier, and diagnosis information.

(Specific Example 1)
It is now assumed that the correspondence information management table shown in FIG. 19 is stored in the correspondence information storage unit 411 of the moisture advice output device 4. The correspondence information management table is a table for managing one or more pieces of correspondence information. The correspondence information here has "ID", "intake amount condition", "advice information", and "score". The "intake amount condition" has a "user attribute value" and "intake amount information (x)". The "user attribute value" is a condition related to one or more user attribute values. The "user attribute value" here is "male" or "female". The "intake amount information (x)" is information specifying the range of daily moisture intake specified by the intake amount information. The "advice information" here is a character string indicating the advice. The "score" here is an integer from 1 to 5, with 5 being the best and 1 being the worst.

In Figure 19, advice information and scores vary depending on user attribute values and intake information.

In this situation, the process described in the specific example of the first embodiment is performed, and the user inputs answer information to the questionnaire information (see FIG. 7, for example) displayed on the user terminal 5. Here, it is also assumed that the user presses a send button (not shown) displayed on the user terminal 5.

Then, the user terminal 5 constructs user answer information having a collection of answer information and a user identifier, and transmits the user answer information to the moisture advice output device 4.

Next, the reception unit 42 of the moisture advice output device 4 receives user answer information having a set of answer information and a user identifier.

As described in the specific example of the first embodiment, it is assumed that the intake amount acquiring unit 232 of the fluid advice output device 4 acquires intake amount information "1215 milliliters" indicating the user's daily fluid intake. Note that "1215 milliliters" satisfies the intake amount information (x) " _a1 < x <= _a2 " in Fig. 19.

Next, the score acquisition unit 432 acquires the user attribute value "male" that is paired with the received user identifier from a user management table (not shown). The score acquisition unit 432 also determines the intake condition " _a1 < x <= _a2 " that is satisfied by the user attribute value "male" and the intake amount information "1215 milliliters" from the correspondence information management table of Fig. 19. The score acquisition unit 432 then acquires the score "2" that is paired with the user attribute value "male" and the intake amount condition " _a1 < x <= _a2 " from the correspondence information management table of Fig. 19.

Next, the advice acquisition unit 431 acquires advice information that pairs the user attribute value "male" with the intake amount condition "a ₁ <x<=a ₂ " from the correspondence information management table of FIG.

Next, the processing unit 43 uses the acquired intake information, the acquired score, and the acquired advice information to construct the information to be output.

Next, the output unit 44 transmits the configured information to the user terminal 5.

Next, the user terminal 5 receives and outputs the information. An example of such output is shown in FIG. 20. In FIG. 20, 2001 is intake amount information, 2002 is score, and 2003 is advice information.

(Specific Example 2)
It is now assumed that the correspondence information management table shown in FIG. 21 is stored in the correspondence information storage unit 411 of the moisture advice output device 4. The correspondence information management table is a table that manages one or more pieces of correspondence information. The correspondence information here has "ID", "intake amount condition", "advice information", and "score calculation formula". The "intake amount condition" has "user condition" and "intake amount information (x)". The "user condition" is a condition related to the user, and here has "user attribute value" and "diagnosis information". The "diagnosis information" is a condition related to the diagnosis information, and here has "diabetes" and "uric acid level 7.0 or higher".

The "user attribute value" is a condition related to one or more user attribute values. The "user attribute value" is, here, "male" or "female". The "diabetes" indicates the presence or absence of diabetes, with "1" indicating diabetes and "0" indicating no diabetes. The "uric acid level 7.0 or more" indicates whether the uric acid level is 7.0 or more. "1" indicates that the uric acid level is 7.0 or more, and "0" indicates that the uric acid level is less than 7.0. The "intake amount information (x)" is information specifying the range of the daily water intake specified by the intake amount information. The "advice information" is, here, a character string indicating advice, or a variable (a part surrounded by "<>") and a template. For example, the variable <g ₂₁ (x)> is an arithmetic expression for calculating the insufficient water intake, and is the arithmetic expression "g ₂₁ (x)" with the intake amount information (x) as a parameter. The arithmetic expression "g ₂₁ (x)" is a decreasing function with x as a parameter. The "score calculation formula" is a calculation formula that uses the intake amount information (x) as a parameter and calculates a score. The score here is, for example, an integer between 0 and 100, with 100 being the best and 0 being the worst. The calculation formulas "f ₁₁ (x)", "f 12 (x)", "f ₁₃ (x)", "f ₁₄ (x)", "f ₂₁ (x)", "f ₂₂ (x)", _{"f 23 (} x)", and "f ₂₄ (x)" are increasing functions with x as a parameter. The calculation formulas "f ₃₁ (x)", "f ₃₂ (x)", "f ₃₃ (x)", "f ₃₄ (x)", "f ₄₁ (x)", "f ₄₂ (x)", "f ₄₃ (x)", and "f ₄₄ (x)" are decreasing functions with x as a parameter.

In FIG. 21, it is preferable that the advice information and score calculation formula differ depending on the user attribute value, diagnosis information, and intake amount information.

Note that in Figure 21, records corresponding to the user attribute value "female" have been omitted, with some exceptions.

In this situation, the process described in the specific example of the first embodiment is performed, and the user inputs answer information to the questionnaire information (see, for example, FIG. 7) displayed on the user terminal 5. The user also inputs the diagnosis information "<Diabetes> Yes, <Uric acid level> 7.5" into the user terminal 5, and presses the send button (not shown).

The user terminal 5 then creates user answer information that includes a collection of answer information, the diagnosis information "<Diabetes> Yes, <Uric acid level> 7.5", and the user identifier, and transmits the user answer information to the fluid advice output device 4.

Next, the reception unit 22 of the fluid advice output device 4 receives user response information including a set of response information, the diagnosis information "<Diabetes> Yes, <Uric acid level> 7.5", and a user identifier.

As described in the specific example of the first embodiment, it is assumed that the intake amount acquiring unit 232 of the fluid advice output device 4 acquires intake amount information "1215 milliliters" indicating the user's daily fluid intake. Note that "1215 milliliters" satisfies the intake amount information (x) " _a11 <x<= _a12 " in Fig. 21.

Next, the score acquisition unit 432 acquires the user attribute value "male" that is paired with the received user identifier from a user management table (not shown). The score acquisition unit 432 also determines that "uric acid level is 7.0 or more" from "<uric acid level>7.5" and acquires the value "1". The score acquisition unit 432 also determines that the intake condition satisfied by the intake amount information "1215 milliliters" is "a ₁₁ <x<=a ₁₂ ". The score acquisition unit 432 then acquires the score calculation formula "S ₂₁ =f 21 (x)" that is paired with the user attribute value "male", the uric acid level of 7.0 or more "1", and the intake amount condition "a ₁ <x<=a ₂ " from the correspondence information management table of FIG. ₂₁ . Next, the score acquisition unit 432 substitutes "1215" for x in the score calculation formula "S ₂₁ =f ₂₁ (x)," executes the score calculation formula, and acquires the score "S ₂₁ =52."

Next, the advice acquisition unit 431 acquires advice information "Drink < _g21 (x)> milliliters of fluid until going to bed" that is paired with the user attribute value "male", the uric acid value "1" of 7.0 or more, and the intake amount condition " _a1 <x<= _a2 " from the correspondence information management table of Fig. 21. Next, the advice acquisition unit 431 substitutes "1215" for x in the arithmetic expression " _g21 (x)", executes the arithmetic expression, and acquires the value "500". Next, the advice acquisition unit 431 substitutes the value "500" for < _g21 (x)>, and acquires the advice information to be output, "Drink 500 milliliters of fluid until going to bed". The arithmetic expressions " _g21 (x)", " _g22 (x)", " _g23 (x)", and " _g24 (x)" are decreasing functions with the intake amount information (x) as a parameter, and are arithmetic expressions for obtaining the amount of water that is deficient.

Next, the processing unit 43 uses the acquired intake information, the acquired score, and the acquired advice information to construct the information to be output.

Next, the output unit 44 transmits the configured information to the user terminal 5.

Next, the user terminal 5 receives and outputs the information. An example of such output is shown in FIG. 22. In FIG. 22, 2201 is intake amount information, 2202 is score, and 2203 is advice information.

As described above, this embodiment allows the user to receive appropriate advice based on their water intake.

In addition, according to this embodiment, appropriate advice can be obtained based on the user's attribute values and water intake.

In addition, according to this embodiment, diagnostic information related to health checkups can also be used to provide appropriate advice.

In addition, this embodiment can present the user with a score regarding the quality of their fluid intake.

Furthermore, according to this embodiment, appropriate advice can be obtained according to the amount of fluid intake obtained using the answers to the questions.
It is possible to obtain appropriate advice according to the amount of fluid intake obtained by using answers to appropriate questions according to the user attribute values.

Furthermore, according to this embodiment, a machine learning algorithm such as random forest can be used to obtain an appropriate amount of fluid intake, and appropriate advice based on that amount of fluid intake can be obtained.

The processing in this embodiment may be realized by software. This software may be distributed by software download or the like. This software may also be recorded on a recording medium such as a CD-ROM and distributed. This also applies to the other embodiments in this specification. The software that realizes the moisture advice output device 4 in this embodiment is a program as described below. In other words, this program causes a computer to function as an intake acquisition unit that acquires intake information regarding the user's moisture intake, an advice acquisition unit that uses the intake information to acquire advice information for the user, and an advice output unit that outputs the advice information.

Figure 23 also shows the appearance of a computer that executes the programs described in this specification to realize the learning device 1 and water intake estimation device 2 of the various embodiments described above. The above-mentioned embodiments can be realized by computer hardware and a computer program executed thereon. Figure 23 is an overview of this computer system 300, and Figure 24 is a block diagram of system 300.

In FIG. 23, computer system 300 includes computer 301, which includes a CD-ROM drive, keyboard 302, mouse 303, and monitor 304.

In FIG. 24, in addition to a CD-ROM drive 3012, the computer 301 includes an MPU 3013, a bus 3014 connected to the CD-ROM drive 3012 etc., a ROM 3015 for storing programs such as a boot-up program, a RAM 3016 connected to the MPU 3013 for temporarily storing instructions for application programs and providing temporary storage space, and a hard disk 3017 for storing application programs, system programs, and data. Although not shown here, the computer 301 may further include a network card that provides a connection to a LAN.

A program that causes the computer system 300 to execute the functions of the water intake estimation device 2 of the above-mentioned embodiment, etc., may be stored on the CD-ROM 3101, inserted into the CD-ROM drive 3012, and then transferred to the hard disk 3017. Alternatively, the program may be sent to the computer 301 via a network (not shown) and stored on the hard disk 3017. The program is loaded into the RAM 3016 when executed. The program may be loaded directly from the CD-ROM 3101 or the network.

The program does not necessarily have to include an operating system (OS) or third-party programs that cause the computer 301 to execute the functions of the water intake estimation device 2 of the above-described embodiment. The program only needs to include instructions that call appropriate functions (modules) in a controlled manner to obtain the desired results. How the computer system 300 operates is well known, and a detailed description will be omitted.

In the above program, the steps of transmitting information and receiving information do not include processing performed by hardware, such as processing performed by a modem or interface card in the transmission step (processing that is performed only by hardware).

The computer that executes the above program may be a single computer or multiple computers. In other words, centralized processing or distributed processing may be performed. In other words, the water intake estimation device 2, etc. may be a standalone device or may be composed of two or more devices.

Furthermore, in each of the above embodiments, it goes without saying that two or more communication means present in one device may be realized physically by one medium.

In addition, in each of the above embodiments, each process may be realized by centralized processing in a single device, or may be realized by distributed processing in multiple devices.

The present invention is not limited to the above-described embodiment, and various modifications are possible, and it goes without saying that these are also included within the scope of the present invention.

As described above, the fluid advice output device of the present invention has the effect of being able to obtain appropriate advice based on the user's fluid intake, and is useful as a server that provides advice regarding fluid intake.

REFERENCE SIGNS LIST 1 Learning device 2 Water intake estimation device 3, 5 User terminal 4 Water advice output device 11 Learning storage unit 12 Learning reception unit 13 Learning processing unit 14 Learning output unit 21, 41 Storage unit 22, 42 Reception unit 23, 43 Processing unit 24, 44 Output unit 31, 51 Terminal storage unit 32, 52 Terminal reception unit 33, 53 Terminal processing unit 34, 54 Terminal transmission unit 35, 55 Terminal reception unit 36, 56 Terminal output unit 111 Answer storage unit 112 Actual measurement value storage unit 211 Questionnaire storage unit 212 Raw information storage unit 221 Answer reception unit 231 Questionnaire acquisition unit 232 Intake amount acquisition unit 241 Questionnaire output unit 242 Intake amount output unit 411 Corresponding information storage unit 421 Diagnosis information reception unit 431 Advice acquisition unit 432 Score acquisition unit 441 Advice output unit 442 Score output unit

Claims (12)

an intake acquisition unit that acquires intake information that is a water intake amount of a user;
a diagnostic information receiving unit that receives diagnostic information related to a health check of the user;
an advice acquisition unit that acquires advice information for the user using the intake amount information;
an advice output unit that outputs the advice information;
a score acquisition unit that acquires a score related to the user's water intake using the intake amount information and the diagnosis information ;
and a score output unit that outputs the score rather than the intake amount information. The score acquisition unit,
Substituting the intake amount information acquired by the intake amount acquisition unit into a score calculation formula, which is a calculation formula having the intake amount information as a parameter, and executing the score calculation formula to acquire the score.
or a score corresponding to the intake condition that matches the intake information acquired by the intake acquisition unit is acquired from a correspondence table having two or more correspondence information having intake conditions and scores related to the intake information. The score acquisition unit,
The moisture advice output device of claim 2, further comprising: a score calculation formula paired with an intake condition in which the diagnostic information and the intake information match, which is obtained from a storage unit in which score calculation formulas corresponding to two or more intake conditions are stored; the intake information is substituted into the score calculation formula; the score calculation formula is executed; and the score is calculated. A user attribute value acquisition unit that acquires a user attribute value corresponding to the intake amount information,
The score acquisition unit,
The moisture advice output device according to claim 1 , wherein the score is obtained by using the user attribute value, the intake amount information, and the diagnosis information . a raw information storage unit for storing raw information that is used to estimate the amount of water intake from answer information to two or more questions including questions other than the question directly asking about the amount of water intake;
and an answer receiving unit that receives user answer information having answer information to each of the two or more questions,
The intake amount acquisition unit is
5. The fluid advice output device according to claim 1, further comprising: a fluid intake information storage unit that stores raw information on a user's fluid intake based on the user's fluid intake amount and a response information of the user's fluid intake amount. The fluid advice output device of claim 5, wherein the two or more questions include two or more of the following: beverage-related questions about beverage addictiveness, alcohol-related questions about alcohol addictiveness, diet-related questions about diet-related addictiveness, and all-related questions about all origins. a questionnaire storage unit in which two or more pieces of questionnaire information each having question information for two or more questions are stored in association with conditions related to user attribute values;
a questionnaire acquisition unit that acquires questionnaire information corresponding to a condition corresponding to a user attribute value of a user from the questionnaire storage unit;
a questionnaire output unit that transmits the questionnaire information acquired by the questionnaire acquisition unit to a user terminal,
The raw information storage unit includes:
Two or more pieces of original information corresponding to conditions corresponding to user attribute values are stored;
The answer receiving unit,
receiving the user answer information corresponding to a user attribute value;
The intake amount acquisition unit is
7. The fluid advice output device according to claim 5, wherein the intake amount information is obtained using the raw information corresponding to a user attribute value corresponding to the user answer information and two or more pieces of answer information contained in the user answer information. The two or more questions include two or more types of question sets each including one or more questions,
The raw information storage unit includes:
Two or more pieces of source information corresponding to the type of question are stored,
The intake amount acquisition unit is
The fluid advice output device according to any one of claims 5 to 7, wherein intake information is obtained for each of the two or more types of questions using answer information corresponding to each of the two or more types and raw information corresponding to each of the types, and the intake information is obtained using the two or more intake information. The raw information is a learning device constructed by performing a learning process using a machine learning algorithm using two or more teacher data including answer information to two or more questions or answer-related information obtained from the answer information and water intake information,
The intake amount acquisition unit is
The fluid advice output device according to any one of claims 5 to 8, further comprising: a learning unit that uses two or more pieces of answer information contained in the user answer information received by the answer receiving unit or answer-related information obtained from each of the two or more pieces of answer information, and a learning device stored in the raw information storage unit, to perform a prediction process using a machine learning algorithm and obtain the intake amount information. The moisture advice output device according to claim 9, wherein the machine learning algorithm is a random forest. A fluid advice output method implemented by an intake acquisition unit, an advice acquisition unit, a diagnosis information reception unit, an advice output unit, a score acquisition unit, and a score output unit, comprising:
an intake acquisition step in which the intake acquisition unit acquires intake information which is a water intake of the user;
a diagnostic information receiving step in which the diagnostic information receiving unit receives diagnostic information related to a health check of the user;
an advice acquisition step in which the advice acquisition unit acquires advice information for the user using the intake amount information;
an advice output step in which the advice output unit outputs the advice information;
a score acquisition step in which the score acquisition unit acquires a score regarding a degree of the user's water intake using the intake amount information and the diagnosis information ;
and a score output step in which the score output unit outputs the score which is not the intake amount information. Computer,
an intake acquisition unit that acquires intake information that is a water intake amount of a user;
a diagnostic information receiving unit that receives diagnostic information related to a health check of the user;
an advice acquisition unit that acquires advice information for the user using the intake amount information;
an advice output unit that outputs the advice information;
a score acquisition unit that acquires a score related to the user's water intake using the intake amount information and the diagnosis information ;
A program for causing the score output unit to function as a score output unit that outputs the score other than the intake amount information.

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