Information providing apparatus, information providing method, and program

Abstract

This information providing device is provided with: a physical information acquisition means that acquires physical information including a user's attribute, physical condition, and goal for said physical condition; a user information acquisition means that acquires information related to the user, which includes schedule information of the user; a determination means that determines, on the basis of the physical information and the schedule information, content of the advice for the goal and a timing for executing said content of the advice; and an output means that outputs the content of the advice and the timing.

Description

Information providing device, information providing method, and recording medium

[0001] The present disclosure relates to an information providing device, an information providing method, and a recording medium.

[0002] 2. Description of the Related Art In order to encourage users to improve their lifestyle habits, there is a technology that provides advice on daily activities based on the user's activity log.

[0003] For example, Patent Document 1 discloses a technology that generates appropriate advice messages based on the diet and health status of a person who is a health management target. Patent Document 2 discloses an information processing device that transmits advice to bring a user's physical condition closer to an ideal body specified by the user based on the user's lifestyle information and preference information.

[0004] International Publication No. 2017 / 022013 International Publication No. 2019 / 116679

[0005] However, with the techniques described in Patent Documents 1 and 2, depending on the user's schedule, it may not be possible to act as advised. For this reason, it is necessary to provide advice that the user can implement.

[0006] An example of an objective of the present disclosure is to provide an information providing device that can provide advice for improving lifestyle habits that can be implemented by a user.

[0007] An information providing device in one aspect of the present disclosure includes a physical information acquiring means for acquiring physical information including a user's attributes, physical condition, and goals for the physical condition; a user information acquiring means for acquiring information about the user including the user's schedule information; a determining means for determining the content of advice toward the goal and the timing for implementing the content of the advice based on the physical information and the schedule information; and an output means for outputting the content and timing of the advice.

[0008] In one aspect of the present disclosure, an information providing method includes a computer acquiring physical information including a user's attributes, physical condition, and a goal for the physical condition, acquiring information about the user including the user's schedule information, determining the content of advice toward the goal and the timing for implementing the content of the advice based on the physical information and the schedule information, and outputting the content and timing of the advice.

[0009] In one aspect of the present disclosure, a recording medium stores a program that causes a computer to execute a process of acquiring physical information including a user's attributes, physical condition, and goals for the physical condition, acquiring information about the user including the user's schedule information, determining the content of advice toward the goal and the timing for implementing the content of the advice based on the physical information and the schedule information, and outputting the content and timing of the advice.

[0010] According to the present disclosure, advice for improving lifestyle habits that can be implemented by a user can be provided.

[0011] FIG. 1 is a block diagram showing an example of the configuration of an information providing device according to a first embodiment. FIG. 2 is a diagram showing a hardware configuration in which the information providing device according to the first embodiment is realized by a computer device and its peripheral devices. FIG. 3 is a graph showing the frequency of locations where a user stopped in the first embodiment. FIG. 4 is an example of a screen used by a physical information acquisition unit to acquire physical information in the first embodiment. FIG. 5 is an example of a screen used by a user to select advice content in the first embodiment. FIG. 6 is an example of output of a user's schedule information in the first embodiment. FIG. 7 is a diagram for explaining a method of determining advice in the first embodiment. FIG. 8 is a flowchart showing the operation of an information providing device according to the first embodiment and a modified version of the first embodiment. FIG. 9 is a diagram for explaining a method of determining advice content based on behavioral information and lifestyle habit information in another modified version of the first embodiment. FIG. 10 is a diagram for explaining a method of determining advice content based on behavioral information and preference information in another modified version of the first embodiment. FIG. 11 is a diagram for explaining a method of determining advice content based on environmental information in another modified version of the first embodiment. FIG. 12 is a block diagram showing an example of the configuration of an information providing device according to a second embodiment. Fig. 13 is a block diagram showing an example of the configuration of an information providing device according to the third embodiment, and Fig. 14 is a flowchart showing the operation of the information providing device according to the third embodiment.

[0012] Hereinafter, with reference to the drawings, embodiments of an information providing device, an information providing method, and a non-transitory recording medium storing a program according to the present disclosure will be described in detail. The disclosed technology is not limited to these embodiments.

[0013] 1 is a block diagram showing an example of the configuration of an information providing system according to the first embodiment. Referring to FIG. 1, an information providing device 100 includes a physical information acquiring unit 101, a user information acquiring unit 102, a determining unit 103, and an output unit 104.

[0014] The information providing device 100 outputs advice to the user on behavioral change aimed at improving lifestyle habits. For example, the user's attributes, physical condition, and physical condition goals are registered in an application program for health management, and the information providing device 100 outputs advice to the user through the same application program. In this embodiment, the advice refers to actions the user takes to improve health indicators such as the user's weight, height, waist circumference, blood pressure, blood glucose level, and blood lipids. The actions include exercise and dietary details. In this way, the information providing device 100 encourages the user to take care of their own health (self-care), for example.

[0015] 2 is a diagram illustrating an example of a hardware configuration in which the information providing device 100 according to the first embodiment of the present disclosure is realized by a computer device 500 including a processor. As shown in FIG. 2, the information providing device 100 includes a CPU (Central Processing Unit) 501, memories such as a ROM (Read Only Memory) 502 and a RAM (Random Access Memory) 503, a storage device 505 such as a hard disk for storing a program 504, a communication interface 508 for network connection, and an input / output interface 509 for inputting and outputting data. In the first embodiment, the information providing device 100 is connected to each component via a bus 510. The information providing device 100 according to the first embodiment shown in FIG. 1 can also be configured using cloud computing or the like.

[0016] The CPU 501 runs an operating system to control the entire information providing device 100 according to the first embodiment of the present invention. The CPU 501 also reads programs and data into memory from a recording medium 506 attached to, for example, a drive device 507. The CPU 501 also functions as the physical information acquiring unit 101, the user information acquiring unit 102, the determining unit 103, and the output unit 104 according to the first embodiment, or as part of these units, and executes processing or commands in the flowchart shown in FIG. 8, which will be described later, based on the program.

[0017] The recording medium 506 is, for example, an optical disk, a flexible disk, a magneto-optical disk, an external hard disk, or a semiconductor memory. The semiconductor memory or the like that is part of the recording medium is a non-volatile storage device that stores the program. The program may also be downloaded from an external computer (not shown) that is connected to a communication network.

[0018] As described above, the first embodiment shown in Fig. 1 is realized by the computer hardware shown in Fig. 2. However, the means for realizing each unit of the information providing device 100 in Fig. 1 is not limited to the configuration described above. The information providing device 100 may be realized by a single physically coupled device, or may be realized by a system consisting of two or more physically separated devices connected by wire or wirelessly.

[0019] The physical information acquisition unit 101 is a means for acquiring physical information including the user's attributes, physical condition, and goals for the physical condition. The user's attributes include gender and age. The physical condition refers to the most recent measured values ​​of health indicators that indicate the health state, such as weight, height, waist circumference, blood pressure, blood glucose level, and blood lipids. The goal refers to the ideal value for the indicator, and also includes the deadline for achieving the target state. For example, the goal for weight is to lose 0.5 kg in one month. In this embodiment, the goal may be either a final goal (e.g., a 5 kg loss in six months) or a short-term goal (e.g., a weekly goal) that is piecemeal toward the final goal.

[0020] The physical information acquisition unit 101 acquires, for example, attributes, physical conditions, and goals for the physical conditions input into an application program. Furthermore, the physical information acquisition unit 101 may acquire attributes from a terminal owned by the user if the attributes are registered in the terminal. If measuring devices for each health index are connected to a network, the physical information acquisition unit 101 may acquire information indicating the physical condition from each measuring device via the communication interface 508. Furthermore, if an information management server of a medical institution that stores information indicating the physical information is connected to the network, the physical information acquisition unit 101 may acquire information indicating the physical condition from the information management server via the communication interface 508.

[0021] The physical information acquisition unit 101 may input attributes and physical conditions for the goal and acquire a goal for achieving an ideal situation based on a learning model trained by machine learning. This learning model is machine-learned using, as learning data, paired information of a plurality of users, each of which is made up of user attributes and the user's physical condition a predetermined X months ago (for example, 3, 6, or 12 months ago) and the user's current physical information, and represents a prediction model that predicts the user's physical information X months from now when the user's attributes and current physical condition are input.

[0022] The user information acquisition unit 102 is a means for acquiring information about the user, including the user's schedule information. The schedule information includes the user's future plans for work / school, exercise, meals, and home (house), and in particular, the schedule that affects the content of advice for improving lifestyle. The user information acquisition unit 102 acquires, for example, schedule information stored in the user's terminal.

[0023] The user information acquisition unit 102 may acquire life log information of the user and estimate the user's schedule information based on the life log information. The life log information in this embodiment is information about activities such as work, meals, exercise, and sleep, and includes the content of each activity, location information, required time, travel time, travel route, etc.

[0024] The user information acquisition unit 102 may acquire location information where the user has stopped based on life log information in order to estimate the user's schedule information. The location information is information about the locations where the user spends their daily life, such as work / school, exercise, meals, and home. In this embodiment, "stopping" refers to, for example, staying in the same area (e.g., less than 200 meters) for a predetermined period of time (e.g., 20 minutes or more). The user information acquisition unit 102 identifies location information such as longitude and latitude from the GPS location information of the user's device and identifies the name of the location from the correspondence with map information. The user information acquisition unit 102 identifies the location where the user has stopped based on preset location information types (work / school, exercise, meals, home). If there is no location corresponding to the preset location information type, the user information acquisition unit 102 may inquire of the user about the location where the user has stopped and have the user input the location. Furthermore, the user information acquisition unit 102 may add the input information to the location type. Furthermore, the user information acquisition unit 102 may acquire the user's walking and other movements based on information obtained from an acceleration sensor of the user's terminal.

[0025] The user information acquisition unit 102 may also acquire the frequency of locations where the user has stopped. Fig. 3 is a graph showing the frequency of locations where the user has stopped. In the example of Fig. 3, the frequency of locations where the user has stopped during each time period for each day of the week is shown. The user information acquisition unit 102 estimates location information where the user is located during each time period for each day of the week, based on, for example, information about the user's stopping locations and stopping frequency.

[0026] The determination unit 103 is a means for determining the content of advice toward a goal and the timing for implementing the content of the advice based on physical information and schedule information. Specifically, the determination unit 103 first calculates the amount of calories that the user should reduce in order to approach the target physical state based on physical information including the goal for the user's physical state. Next, the determination unit 103 extracts timings, such as days and time periods, when an action can be taken to reduce calories based on the user's schedule information. Next, the determination unit 103 determines to provide advice to take the action at the extracted timings.

[0027] The content of the advice determined by the determination unit 103 may simply be advice to increase the amount of exercise or reduce calorie intake from meals, or may be specific advice on a specific exercise or diet. Furthermore, the determination unit 103 may receive a response from the user to determine the content of the advice and the timing of its implementation. For example, the determination unit 103 may receive a response on whether to increase the amount of exercise or reduce calorie intake from meals. Furthermore, the determination unit 103 may receive the name of the exercise that the user will perform when exercising to reduce calories.

[0028] Here, a method for determining the content of advice to be provided to a user and the timing of implementing the advice will be described with reference to the drawings. FIG. 4 shows an example of a screen used by the physical information acquisition unit 101 to acquire physical information. In the example of FIG. 4, a goal of losing 1.0 kg in four weeks is input as a goal for a physical condition. As shown in FIG. 4, the determination unit 103 may calculate information regarding the target calorie expenditure and basal metabolic calorie, and the output unit 104 may output this information. In the example of FIG. 4, to lose 1.0 kg, the user needs to lose 7000 / 4 kcal = 1750 kcal per week. In other words, the user needs to lose 1750 / 7 = 250 kcal per day. Therefore, the determination unit 103 may advise, for example, three exercises each day to reduce 100 kcal.

[0029] 5 shows an example of a screen that allows the user to select advice content. In the example of FIG. 5, exercise advice is displayed, prompting the user to select from walking, climbing stairs, stretching / muscle training, bath cleaning, or vacuuming for weekdays (Monday through Friday). For weekends (Saturday and Sunday), a display allows the user to select sports such as soccer, golf, or tennis in addition to the weekday options. The example screen of FIG. 5 also prompts the user to check work / school, exercise, meals, and planned locations in the home where exercise can be performed (types of location information) for each type of exercise.

[0030] In the example screen of FIG. 5 , when the user inputs the name of the exercise and the planned location where the exercise can be performed, the user information acquisition unit 102 acquires the user's schedule information. The user information acquisition unit 102 may acquire schedule information estimated based on information about the user's stop locations and stop frequency. FIG. 6 shows an example of output of the user's schedule information in this embodiment. Next, the determination unit 103 identifies a time period (timing) during which the user can perform the exercise based on the exercise selected by the user on the screen of FIG. 5 and the planned location where the exercise can be performed, and the types of location information (work / school, exercise, meal, and home) extracted from the schedule information. Next, the determination unit 103 extracts days of the week that do not include location information types from the user's schedule information. If one or more days of the week are extracted, the exercises for the extracted days are allocated to days other than the extracted days. Specifically, in the example of FIG. 6 , the location information type is not included on Friday. In this case, the decision unit 103 decides not to give advice on the three exercises on Friday, but to give advice on the three exercises for Saturday and the three exercises for Friday on Saturday.

[0031] The determination unit 103 determines the name of the exercise to be advised and the timing of the advice, including the day of the week and the planned time slot, based on, for example, the acquired user's schedule information, the exercise selected by the user in FIG. 5 and the planned location where the exercise can be performed (type of location information: work / school, exercise, meal, home). Also, assume that the user plans to stay at home for three consecutive hours during the daytime. In this case, if "home" is selected as the planned location where the exercise can be performed in the example screen of FIG. 5, the determination unit 103 may determine to advise the user on the content of the exercise that can be performed at home during the time slot where the user will be at home.

[0032] The output unit 104 is a means for outputting the content of the advice and the timing to execute the advice. The output unit 104 outputs the determined content of the advice and the execution timing on, for example, an application program. The output unit 104 may also send a message to the user based on the information determined by the determination unit 103, such as the type of exercise to be advised on which day of the week and during which scheduled time slot. Specifically, if the determination unit 103 determines that the exercise advice for Wednesday in FIG. 6 is "walking for 30 minutes" and that the advice is to be given during the "work / school" time slot, the output unit 104 sends the user a message saying "We recommend walking for 30 minutes" during that time slot. The output unit 104 may also function as an output control means for outputting the advice on a display device or audio output device, which is a user terminal owned by the user. For example, the output unit 104 displays the content of the advice and the execution timing on a display device. In this case, the output unit 104 generates a display signal and supplies the generated display signal to the display device. The output unit 104 may control the sound output of the audio output device so as to output audio guidance or the like to notify the user.

[0033] As described above, in the first embodiment, the information providing device 100 has the determining unit 103 determine the content of advice toward a goal and the timing for implementing the advice based on physical information and schedule information, and the output unit 104 outputs the content of the advice and the implementation timing. In this case, for example, if the user has plans all day and cannot find time to implement actions toward lifestyle improvement, the information providing device 100 can encourage the user to implement the advice of that day on another day. This makes it possible to provide advice for lifestyle improvement that the user can implement. The user can, for example, refer to the advice and implement actions toward lifestyle improvement. In other words, the information providing device 100 can support the user's decision-making by providing advice for lifestyle improvement.

[0034] [Modification of First Embodiment] Next, a modification of the first embodiment of the present disclosure will be described in detail with reference to the drawings. Below, the description of the present embodiment will be omitted to the extent that it does not become unclear.

[0035] In the first embodiment described above, the determination unit 103 determines the content of advice toward the goal and the timing for implementing the advice content, and the output unit 104 outputs these contents. In contrast, in this modified example, the user information acquisition unit 102 further acquires current behavioral information of the user. Then, when the determination unit 103 detects behavior for which advice is possible, the determination unit 103 determines the content of advice using the detected behavior. In this modified example, the advice determined by the determination unit 103 is advice regarding specific exercises and dietary contents that can be implemented within the user's current behavior.

[0036] The user information acquisition unit 102 acquires, as the user's current behavior information, location information of the user based on the user's terminal location using, for example, a Global Positioning System (GPS), a combination of Wi-Fi and GPS, or Bluetooth Low Energy (registered trademark). The user information acquisition unit 102 may also acquire schedule information for the current time from schedule information stored in the user's terminal. However, the behavior information acquired by the user information acquisition unit 102 is not limited to this information as long as it can grasp the user's current behavior. For example, when the user is moving, the user information acquisition unit 102 acquires the user's current behavior information and outputs it to the determination unit 103.

[0037] When the determination unit 103 detects an action for which advice can be given, it determines the content of advice using the detected action. For example, when the determination unit 103 detects that the user is about to get on an elevator based on the user's location information, it determines to advise the user to use the stairs. Furthermore, when the determination unit 103 detects that the user's schedule information at the current time is soccer and that the user has moved to a soccer field, it determines to advise the user to play soccer for a predetermined period of time. Furthermore, when the determination unit 103 detects that the user has moved to a convenience store, it determines to advise the user to purchase food with low calorie intake. Furthermore, the output unit 104 outputs the determined content of advice to the user using an application program or a message as needed.

[0038] FIG. 7 is a diagram illustrating a method for determining advice by the determination unit 103. As shown in FIG. 7, keywords related to location, position, and acceleration sensor information are linked in advance to each piece of exercise advice and diet advice. The determination unit 103 determines whether the behavior corresponds to the keyword based on the location, position, and acceleration sensor information acquired from the user's terminal. If the behavior corresponds to the keyword, the determination unit 103 determines the content of the linked advice. This enables the determination unit 103 to provide advice in a timely manner without querying the user.

[0039] 8 is a flowchart showing an outline of the operation of the information providing device 100 in the first embodiment and the modified example of the first embodiment. The processing according to this flowchart may be executed based on program control by the processor described above. In this flowchart, the processing in steps S101 to S104 corresponds to a part of the first embodiment, and the processing in steps S105 to S108 corresponds to a part of the modified example of the first embodiment.

[0040] 8, the physical information acquisition unit 101 acquires physical information including the user's attributes, physical condition, and goals for the physical condition (step S101). Next, the user information acquisition unit 102 acquires information about the user including schedule information (step S102). Next, the determination unit 103 determines the content of advice toward the goal and the timing to implement the advice content based on the physical information and schedule information (step S103). The output unit 104 outputs the determined content of advice and the timing to implement the advice (step S104). Note that the processes in S101 to S104 are performed, for example, at the timing when a short-term goal is output (for example, every week).

[0041] Next, the user information acquisition unit 102 acquires the user's current behavior information (step S105). If the determination unit 103 detects an advisable behavior of the user (step S106; YES), it determines the content of advice using the detected behavior (step S107). Next, the output unit 104 outputs the determined content of advice (step S108). The processes in S105 to S108 are executed every time the determination unit 103 detects an advisable behavior of the user.

[0042] On the other hand, if the determination unit 103 does not detect any behavior of the user that can be advised within a predetermined period (for example, by the deadline for the short-term goal) (step S106; NO), the information providing device 100 ends the information providing process.

[0043] As described above, in the modification of the first embodiment, when the determination unit 103 detects an advisable behavior of a user, the information providing device 100 determines the content of advice using the detected behavior. Then, the output unit 104 outputs the determined content of advice. In this case, for example, the user can take timely behavior in their daily life to improve their lifestyle.

[0044] [Variation 2 of First Embodiment] Next, another variation of the first embodiment of the present disclosure will be described. Below, descriptions of content that overlaps with the above description will be omitted to the extent that the description of this embodiment is not unclear. In this variation, the determination unit 103 uses, in addition to the user's schedule information, the user's current behavior information, and any one of life log information and environmental information, to determine the content of advice to the user.

[0045] The user information acquisition unit 102 acquires the user's schedule information, current behavior information, and life log information. The method of acquiring each piece of information is the same as in the first embodiment or Modification 1 of the first embodiment. In this modification, for example, the determination unit 103 determines the content of advice based on the behavior information, the life log information, and the user's lifestyle habit information and preference information obtained by analyzing the life log information.

[0046] The lifestyle habit information is information about daily meals and exercise, and is information acquired by analyzing the user's behavioral history, such as travel history, travel time, and commuting route, or information about meals, such as food and drink purchase history, visits to restaurants, orders at restaurants, and images captured while eating and drinking. The user information acquisition unit 102 acquires information about exercise, such as daily exercise content, exercise amount, or calories burned, calculated based on the user's behavioral history. The user information acquisition unit 102 also acquires information about meals, such as daily meal content and calorie intake. The user information acquisition unit 102 may estimate the lifestyle habit information from life log information input into an application program.

[0047] Here, a specific example of estimating lifestyle habit information based on life log information entered into an application program will be described. Examples of lifestyle habit information will be described using (1) favorite places and exercise names, and (2) favorite restaurants and menu items. Regarding (1) favorite places and exercise names, for example, the user is asked to input the places and exercise names where they exercised. Based on the results, combinations of places and exercise names are ranked in order of the total number of times over two weeks, and the top three combinations of places and exercise names are designated as favorite places and exercise names. Similarly, regarding (2) favorite restaurants (eating establishments), for example, if the user eats out at a restaurant, the user is asked to input the restaurant name and menu name. Based on the results, combinations of restaurant names and menu names are ranked in order of the total number of times over two weeks, and the top three combinations of restaurant names and menu names are designated as favorite restaurants and menu names.

[0048] The preference information is, for example, information about the user's taste preferences for tea, coffee, sweets, or other luxury items, or information about the user's hobbies, such as a favorite sport. The preference information is acquired, for example, by analyzing a camera installed in the user's terminal or a purchase history. The user information acquisition unit 102 may also estimate the preference information from life log information entered into an application program. In this case, for example, the user is asked to directly enter the contents of the foods they have eaten into the application program. The results are tallied, and a ranking is created, for example, based on the total number of times over a two-week period, in descending order of frequency. For example, the top three foods are estimated to be the favorite foods.

[0049] FIG. 9 is a diagram illustrating a method for determining advice content based on behavioral information and lifestyle information in this modified example. As shown in FIG. 9 , lifestyle information, detected behavioral information (location), recommended items, and advice content are linked and stored in the storage device 505. In the example of FIG. 9 , the lifestyle information indicates that the user has a habit of eating melon bread when at a convenience store and a habit of playing soccer when at a park. When the determination unit 103 detects a specific behavior, it may determine to provide advice linked to the behavioral information. In the example of FIG. 9 , when the determination unit 103 detects that the user is at a convenience store, it determines to advise the user to switch to anpan, which has a lower calorie intake than melon bread, and the output unit 104 sends a message stating, "By switching to anpan, you can reduce your calorie intake by 100 kcal." Furthermore, when the determination unit 103 detects that the user is at a park, it determines to advise the user to play soccer, and the output unit 104 sends a message stating, for example, "Playing soccer will help you burn 600 kcal in 60 minutes."

[0050] FIG. 10 is a diagram illustrating a method for determining advice content based on behavioral information and preference information in this modified example. As shown in FIG. 10, preference information and a method for determining advice are associated and stored in the storage device 505. The example in FIG. 10 shows that, among Japanese sweets, the user likes anpan (sweet bean bun). When a user who likes anpan records eating anpan in an application program, the determination unit 103 advises the user to switch from anpan to dango (rice dumplings), which have a lower calorie intake. The output unit 104 sends a message such as, "If you change anpan to dango, you can reduce your calorie intake by 100 kcal," for example.

[0051] As another example, when the determination unit 103 detects that the user has moved to a ramen restaurant, the determination unit 103 may determine to advise the user to eat ramen with fewer calories. Assume that the calorie intake of ramen increases in the order of salt, soy sauce, and miso. In this case, the determination unit 103 may determine to give advice such as, for example, "Since the calorie intake increases in the order of salt, soy sauce, and miso, salt is recommended if the user is going to eat ramen." As another example, for example, when advising a user to exercise on Saturdays, the determination unit 103 may determine to advise a user who likes to play soccer to play soccer for a predetermined period of time. Furthermore, when the determination unit 103 detects that a user who likes to play soccer in a park has moved to the park, the determination unit 103 may determine to advise the user to play soccer in the park for a predetermined period of time.

[0052] In this modification, the user information acquisition unit 102 may further acquire environmental information relating to the current environment surrounding the user, and the determination unit 103 may determine the content of the advice based on the environmental information. The environmental information refers to, for example, the weather, temperature, humidity, etc. around the user's location information, and the user information acquisition unit 102 acquires the environmental information based on weather forecast information, etc.

[0053] FIG. 11 is a diagram illustrating a method for determining advice content based on environmental information by the determination unit 103. As shown in FIG. 11 , the storage device 505 stores, in association with the content of alternative advice for changing the content of pre-stored advice when the weather or temperature is specific. In the example of FIG. 11 , when the temperature is hotter than a predetermined temperature (e.g., 30 degrees or higher), the determination unit 103 normally advises a user who often eats ramen at a favorite restaurant or a user whose favorite food is ramen, "If you're eating ramen, we recommend salt because the calorie intake increases in the order of salt, soy sauce, and miso." However, instead, the determination unit 103 advises a user who often eats ramen at a favorite restaurant or whose favorite food is ramen, "We recommend chilled ramen. The calorie intake increases in the order of salt, soy sauce, and miso, so we recommend salt." Furthermore, if it is raining, the determination unit 103 does not advise a user who plays soccer on the same day or who likes soccer to play soccer. Alternatively, instead of the advice to play soccer, the determination unit 103 presents indoor sports or indoor exercise. In this case, it is possible to provide advice content that is more easily implemented by the user.

[0054] [Second Embodiment] Next, a second embodiment of the present disclosure will be described in detail with reference to the drawings. Below, the description of the second embodiment will be omitted to the extent that it does not make the description of the present embodiment unclear.

[0055] Fig. 12 is a block diagram showing an example of the configuration of an information providing device 110 according to the second embodiment. As with the computer device shown in Fig. 2, the functions of the information providing device 110 can be realized not only by hardware but also by a computer device or software based on program control.

[0056] 12 , the information providing device 110 includes a physical information acquiring unit 111, a user information acquiring unit 112, a determining unit 113, a deciding unit 114, and an output unit 115. The information providing device 110 differs from the first embodiment in that it includes at least the determining unit 113. The configurations and functions of the physical information acquiring unit 111 and the user information acquiring unit 112 are similar to those of the information providing device 100.

[0057] In this embodiment, the determination unit 113 is a means for determining an optimal behavioral pattern toward the user's goal using a learning model obtained by machine learning based on life log information. This model is obtained using information including the user's life log information and behavioral patterns as learning data. The determination unit 113 selects the user's optimal behavioral pattern from lifestyle information calculated based on the life log information, including daily calorie intake (IN) from meals and calories burned through basal metabolism and exercise (OUT). For example, to reduce calories by approximately 1,000 kcal per week, the value obtained by subtracting OUT from IN (IN - OUT) should be less than -143 kcal (1,000 / 7 kcal) per day. To achieve this, possible measures include (1) reducing IN, (2) increasing OUT, and (3) reducing IN and increasing OUT.

[0058] The determination unit 113 automatically selects which of the methods (1) to (3) the user would use to most likely reduce the IN-OUT value to a negative value, based on a learning model obtained by machine learning using the daily IN and OUT states of multiple users as learning data. This learning model is a model that, when life log information including the user's dietary details (calories ingested) and exercise details (calories burned) for a predetermined period prior to the determination is input, outputs information on the user's optimal behavioral pattern from among (1) to (3).

[0059] Here, we will explain a means for determining the optimal behavior pattern from among the above-mentioned behavior patterns (1) to (3) using a learning model. This learning model uses a different learning model for each time j to determine the behavior pattern to be executed at that time and to achieve the user's final goal (the goal for achieving the user's ideal situation). In this case, the time may be absolute or relative. If relative, the time may be called a stage. Furthermore, the time may refer to a point on a time axis or a predetermined period on the time axis. In the following, j is a natural number. For example, time j = 1 indicates the first week, time j = 2 indicates the second week, time j = t indicates the tth week, and time j = T (T is a natural number greater than t) may indicate the final time, i.e., the final week at which it is known whether the final goal has been achieved or not.

[0060] For example, the jth learning model D ＊ ｊ is the state X observed by user h at time j. ｊｈ Here, the state includes the weight record at each time, the IN record at each time, the OUT record at each time, the frequency information of each meal name at each time, the frequency information of each exercise content at each time, etc. of the user observed from time 1 to time j. Then, the j-th learning model D ＊ ｊ is the behavior pattern A of user h at time j ｊｈ The determined behavior pattern A ｊｈ is a behavior pattern that maximizes the total effect (the negative value of (IN-OUT)) that user h can obtain from time j to the final time T.

[0061] The behavioral pattern determination by the determination unit 113 is performed prospectively as time j passes. For example, if the current time j is t, the state X of the user h observed at the current time t is ｔｈ The t-th learning model D ＊ ｔ By inputting the following, the behavior pattern A of the user h at the current time t is obtained. ｔｈThen, when time passes and the time reaches t+1, the determination unit 113 obtains the state X （ｔ＋１）ｈ By inputting the above, the behavior A of user h at time t+1 is （ｔ＋１）ｈ In this way, the determination unit 113 determines the behavior pattern to be taken as time passes, and therefore, the behavior plan is dynamically created.

[0062] The determination unit 114 determines the content of advice based on the user's optimal behavioral pattern. In addition to the method of determining the content of advice by the determination unit 103, the determination unit 114 determines the content of advice according to any one of the behavioral patterns (1) to (3). For example, if the user's optimal behavioral pattern is (1), the determination unit 114 determines to provide advice mainly on dietary content. If the user's optimal behavioral pattern is (2), the determination unit 114 determines to provide advice mainly on exercise content. If the user's optimal behavioral pattern is (3), the determination unit 114 determines to provide advice on both dietary content and exercise content. Note that, for the exercise content advice in (1) or (2), the determination unit 114 may determine to advise the user to perform the exercise selected by the user on the screen of FIG. 5. The output unit 115 outputs the advice on dietary content and exercise content determined by the determination unit 114.

[0063] The determination unit 113 may also select the user's optimal behavioral pattern based on the calorie consumption (OUT) of exercise. To achieve this, the behavioral pattern may be determined by determining the calorie consumption per day through exercise, for example, (A) 100 kcal, (B) 200 kcal, or (C) 300 kcal. In this case, the determination unit 113 uses the user's daily OUT information to automatically select which of (A) to (C) the user will use to achieve their goal based on a learning model obtained by machine learning. The goal here is, for example, a goal of losing 2 kg in one month, with the goal being to reduce weight to close to 2 kg (weight loss significantly exceeding 2 kg will not achieve the goal). This learning model is a model that outputs information on the user's optimal behavioral pattern from (A) to (C) when life log information including the user's diet and exercise for a predetermined period prior to the determination is input. Then, the decision unit 114 decides to give advice on dietary and exercise content based on the behavioral patterns (A) to (C).

[0064] As described above, in the second embodiment, the information providing device 110 determines the content of advice based on the optimal behavioral pattern of the user by the determination unit 114. In this case, optimal advice toward the goal can be provided.

[0065] [Third Embodiment] Next, a third embodiment of the present disclosure will be described in detail with reference to the drawings. Below, descriptions of the contents that overlap with the above description will be omitted to the extent that the description of this embodiment is not unclear.

[0066] Fig. 13 is a block diagram showing an example of the configuration of an information providing device 120 according to the third embodiment. As with the computer device shown in Fig. 2, the functions of the information providing device 120 can be realized not only by hardware but also by a computer device or software based on program control.

[0067] 13 , the information providing device 120 includes a physical information acquiring unit 121, a user information acquiring unit 122, a determining unit 123, an output unit 124, and a verifying unit 125. The information providing device 120 differs from the information providing device 100 in that it includes at least the verifying unit 125. In this embodiment, the process up to the output of the advice content determined by the determining unit 123 is the same as in the first embodiment and the first modified example of the first embodiment, and the configurations and functions of the physical information acquiring unit 121 and the user information acquiring unit 122 are also the same as those of the information providing device 100.

[0068] The verification unit 125 is a means for verifying whether the user has implemented the advice content that has been output. After a predetermined period of time (several hours to several days) has passed since the output unit 124 outputted the advice, the verification unit 125 acquires, for example, information on the meal content or exercise content for the day or time period for which the advice content was specified to be implemented, based on the life log information. Next, if there is information on the meal content or exercise content that corresponds to the advice content, the verification unit 125 determines that the user has implemented the advice content. On the other hand, if there is no information on the meal content or exercise content that corresponds to the advice content, the verification unit 125 determines that the user has not implemented the advice content.

[0069] If the user does not follow the advice, the decision unit 123 decides to provide advice different from the advice. In other words, the decision unit 123 decides the content of the second advice based on whether or not the first advice already provided to the user has been followed. The content of the first advice and the content of the second advice are different. If the advice regarding dietary content is not followed, the decision unit 123 decides to provide advice to eat other foods. Furthermore, if the advice regarding exercise content is not followed, the decision unit 123 decides to provide advice encouraging the user to do other exercise. For example, if the decision unit 123 has advised the user to replace melon bread, which has a lower calorie intake, with bean paste buns in order to reduce calorie intake, but the user does not follow the advice, the decision unit 123 decides to provide advice to replace melon bread with dumplings, which have a lower calorie intake.

[0070] The determination unit 123 may determine to provide advice on exercise content if the user does not follow the advice even after continuing to provide advice on diet content. Conversely, the determination unit 123 may determine to provide advice on diet content if the user does not follow the advice even after continuing to provide advice on exercise content. The output unit 124 outputs the determined advice content.

[0071] 14 is a flowchart showing an outline of the operation of the information providing device 120 in the third embodiment. The processing according to this flowchart may be executed based on program control by the processor described above. This flowchart is executed, for example, after the processing of S108 in FIG. 8. The processing according to this flowchart is executed, for example, at the timing when a short-term goal is output (for example, every week).

[0072] As shown in FIG. 14 , first, the output unit 124 outputs the advice content determined by the determination unit 123 (step S121). Next, when a predetermined period of time has elapsed since the advice was output, the verification unit 125 acquires the user's life log information (step S122). Next, the verification unit 125 verifies whether the user has implemented the output advice content (step S123). If the user has not implemented the advice content (S123; NO), the verification unit 125 outputs that information to the determination unit 123, and the determination unit 123 decides to provide advice different from the advice content (step S124). Next, the output unit 124 outputs the determined different advice content (step S125). On the other hand, if the user has implemented the advice content (S123; YES), the verification unit 125 ends the process.

[0073] As described above, in the third embodiment, the information providing device 120 provides advice different from the advice content when the user does not carry out the advice content, by the decision unit 123. In this case, it is possible to increase the possibility that the user will carry out the advice content.

[0074] Although the present disclosure has been described above with reference to various embodiments, the present disclosure is not limited to the above embodiments. The configuration and details of each of the present disclosures may include embodiments to which various modifications that would be apparent to those skilled in the art are applied within the scope of the present disclosure. The present disclosure may also include embodiments in which the details described herein are appropriately combined or substituted as necessary. For example, details described using a particular embodiment may also be applied to other embodiments to the extent that no contradiction occurs. For example, although multiple operations are described in sequence in the form of a flowchart, the order of description does not limit the order in which the multiple operations are performed. Therefore, when implementing each embodiment, the order of the multiple operations may be changed as long as it does not interfere with the content.

[0075] 100, 110, 120 Information providing device 101, 111, 121 Physical information acquisition unit 102, 112, 122 User information acquisition unit 103, 114, 123 Determination unit 104, 115, 124 Output unit 113 Determination unit 125 Verification unit 500 Computer device 501 CPU 502 ROM 503 RAM 504 Program 505 Storage device 506 Recording medium 507 Drive device 508 Communication interface 509 Input / output interface 510 Bus

Claims

1. A body information acquisition means for acquiring body information including the user's attributes, physical condition, and goals for the physical condition; A user information acquisition means for acquiring information about the user, including the user's schedule information; A determination means for determining the content of advice directed to the goal and the timing for executing the content of the advice based on the body information and the schedule information; An information providing apparatus comprising an output means for outputting the content of the advice and the timing.

2. The information providing apparatus according to claim 1, wherein the user information acquisition means acquires the user's life log information and acquires the schedule information based on the life log information.

3. The user information acquisition means further acquires the user's current action information, The information providing apparatus according to claim 1 or claim 2, wherein the determination means determines the content of advice using the detected action when an action for which advice can be given is detected.

4. The user information acquisition means acquires the user's life log information, The information providing apparatus according to claim 3, wherein the determination means determines the content of the advice based on the action information and the life log information.

5. The information providing apparatus according to claim 4, wherein the determination means analyzes the user's lifestyle or preferences based on the life log information, and determines the content of the advice based on the action information and the lifestyle information or preference information obtained as a result of the analysis.

6. The user information acquisition means further acquires environmental information regarding the current environment around the user, The information providing apparatus according to claim 1 or claim 2, wherein the determination means determines the content of the advice based on the environmental information.

7. The user information acquisition means acquires the user's life log information, The information providing apparatus further comprises a determination means for determining an optimal action pattern directed to the goal using a model obtained by machine learning based on the life log information, The information providing apparatus according to claim 1 or claim 2, wherein the determination means determines the content of the advice based on the optimal action pattern of the user.

8. The information providing apparatus further comprises a verification means for verifying whether the user has executed the outputted content of the advice. The information providing apparatus according to claim 1 or claim 2, wherein the determination means determines to provide advice different from the advised content when the user does not execute the advised content.

9. A computer acquires physical information including a user's attributes, physical condition, and a goal for the physical condition, acquires information about the user including the user's schedule information, determines the content of advice directed to the goal and the timing for executing the content of the advice based on the physical information and the schedule information, and outputs the content of the advice and the timing, an information providing method.

10. acquires physical information including a user's attributes, physical condition, and a goal for the physical condition, acquires information about the user including the user's schedule information, determines the content of advice directed to the goal and the timing for executing the content of the advice based on the physical information and the schedule information, and a program that causes a computer to execute a process of outputting the content of the advice and the timing.