Information processing method, information processing device, and program

Abstract

A computer: acquires pieces of information indicating an equipment operation and a behavior of a target user and the presence or absence of another user in an environment where the target user is present; extracts, on the basis of the information, first motion information indicating the equipment operation and / or the behavior of the target user in a first environment where no other user is present and second motion information indicating the equipment operation and / or the behavior of the target user in a second environment where another user is present; estimates first characteristics of the target user present in the first environment on the basis of the first motion information; estimates second characteristics of the target user present in the second environment on the basis of the second motion information; and outputs information indicating the first characteristics and / or the second characteristics.

Description

Information processing method, information processing device, and program

[0001] The present disclosure relates to a technique for estimating a user's characteristics.

[0002] Conventionally, there has been known a technique for estimating a user's intentions and preferences based on the user's search history or browsing history in cyberspace such as a website. Patent Document 1 also discloses a technique for estimating a user's personality tendencies with respect to behaviors associated with processing a substance based on the usage history of a device for processing the substance.

[0003] However, the above-mentioned conventional techniques do not take into consideration the estimation of the characteristics of a user individually depending on whether or not other users are present in the same environment as the user.

[0004] Patent No. 6294825

[0005] The present disclosure has been made to solve the above-mentioned problems, and aims to present an information processing method, an information processing device, and a program that can individually estimate the characteristics of a user depending on whether other users are present in the same environment as the user.

[0006] An information processing method according to one aspect of the present disclosure is an information processing method for estimating user characteristics on a computer, the method comprising: acquiring first information indicating device operations and actions of a target user to be estimated; acquiring second information indicating the presence or absence of other users different from the target user in an environment where the target user is present; extracting, based on the first information and the second information, first operation information indicating at least one of device operations and actions of the target user in a first environment where the other users are not present, and second operation information indicating at least one of device operations and actions of the target user in a second environment where the other users are present; estimating, based on the first operation information, a first characteristic that is a characteristic of the target user present in the first environment; estimating, based on the second operation information, a second characteristic that is a characteristic of the target user present in the second environment; and outputting at least one of first characteristic information indicating the first characteristic and second characteristic information indicating the second characteristic.

[0007] 1 is a diagram illustrating an example of an overall configuration of an information processing system according to an embodiment of the present disclosure. FIG. 1 is a block diagram illustrating an example of a configuration of an information processing device. FIG. 2 is a flowchart illustrating an example of a characteristic output process. FIG. 3 is a diagram illustrating an example of operation information. FIG. 4 is a flowchart illustrating an example of a characteristic estimation process. FIG. 4 is a diagram illustrating an example of first characteristic information. FIG. 5 is a diagram illustrating an example of second characteristic information. FIG. 6 is a diagram illustrating an example of first rule information defining a relationship between one or more candidate characteristics and one or more characteristic groups indicating characteristics of operation of a device or facility. FIG. 7 is a diagram illustrating an example of first rule information defining a relationship between one or more candidate characteristics and one or more characteristic groups indicating characteristics of behavior. FIG. 8 is a diagram illustrating an example of a relationship between a target user's characteristics before updating and the number of times characteristic actions corresponding to each element characteristic are performed. FIG. 9 is a diagram illustrating an example of a relationship between a target user's characteristics after updating and the number of times characteristic actions corresponding to each element characteristic are performed. FIG. 10 is a diagram illustrating an example of a change in characteristic information. FIG. 11 is a flowchart illustrating an example of a service provision process. FIG. 12 is a diagram illustrating an example of second rule information. FIG. 13 is a diagram illustrating an example of a portion of third rule information. FIG. 14 is a diagram illustrating an example of a remaining portion of the third rule information.

[0008] (Background to the present disclosure) Conventionally, there has been known a technology for inferring a user's intentions and preferences based on the user's search history or browsing history in cyberspace, such as on websites, and providing the user with services suited to the inferred intentions and preferences. However, this technology infers a user's intentions and preferences based on information that reflects the user's intentions and preferences that the user actively inputs by, for example, entering search keywords or clicking on product images. Therefore, adopting this technology requires an environment in which the user actively inputs information.

[0009] In response to this, Patent Document 1 discloses a technology for estimating a user's personality tendencies based on the user's device usage history in a situation where the user does not actively input information. However, Patent Document 1 does not take into consideration estimating the characteristics of a user individually depending on whether or not other users are present in the same environment as the user.

[0010] Therefore, even if the technology of Patent Document 1 is applied, it is not possible to provide appropriate services to users by taking into account the differences between the characteristics of users when they are alone and when they are with others.

[0011] Therefore, the inventors have conducted extensive research into technology for individually estimating a user's characteristics depending on whether other users are present in the same environment as the user, and have arrived at the following aspects of the present disclosure.

[0012] (1) An information processing method according to one aspect of the present disclosure is an information processing method for estimating user characteristics on a computer, the information processing method comprising: acquiring first information indicating device operations and actions of a target user to be estimated; acquiring second information indicating the presence or absence of other users different from the target user in an environment where the target user is present; extracting, based on the first information and the second information, first operation information indicating at least one of device operations and actions of the target user in a first environment where the other users are not present, and second operation information indicating at least one of device operations and actions of the target user in a second environment where the other users are present; estimating, based on the first operation information, a first characteristic that is a characteristic of the target user present in the first environment; estimating, based on the second operation information, a second characteristic that is a characteristic of the target user present in the second environment; and outputting at least one of first characteristic information indicating the first characteristic and second characteristic information indicating the second characteristic.

[0013] According to this configuration, a first characteristic, which is a characteristic of a target user who is present in a first environment where other users are not present, is estimated based on the first action information. Also, a second characteristic, which is a characteristic of a target user who is present in a second environment where other users are present, is estimated based on the second action information. Therefore, this configuration can individually estimate the characteristic of the target user depending on whether other users are present in the same environment as the target user.

[0014] (2) In the information processing method described in (1) above, in estimating the first characteristic and the second characteristic, first rule information defining a relationship between one or more candidate characteristics and one or more feature groups indicating characteristics of device operations or actions of the target user is acquired, and if the first operation information includes device operations or actions indicating one or more first feature groups included in the one or more feature groups, one or more first candidate characteristics corresponding to the one or more first feature groups are identified from the one or more candidate characteristics, and the identified one or more first candidate characteristics are estimated as the first characteristic, and if the second operation information includes device operations or actions indicating one or more second feature groups included in the one or more feature groups, one or more second candidate characteristics corresponding to the one or more second feature groups are identified from the one or more candidate characteristics, and the identified one or more second candidate characteristics are estimated as the second characteristic.

[0015] In this configuration, one or more first candidate characteristics corresponding to one or more first feature groups indicated by the device operations or actions included in the first operation information are estimated as first characteristics using first rule information. Also, one or more second candidate characteristics corresponding to one or more second feature groups indicated by the device operations or actions included in the second operation information are estimated as second characteristics using the first rule information. Therefore, this configuration can estimate one or more characteristics of the target user both when other users are present and when they are not present in the same environment as the target user.

[0016] (3) In the information processing method described in (2) above, the first characteristic may include one or more first element characteristics, and the second characteristic may include one or more second element characteristics. Further, for each of the one or more first element characteristics, a number of times a first characteristic action is performed is calculated based on the first operation information. The first characteristic action is a device operation or action that exhibits a feature group corresponding to the first element characteristic. The calculated number of times the first characteristic action is performed is set as an intensity of the first element characteristic. Further, for each of the one or more second element characteristics, a number of times a second characteristic action is performed is a device operation or action that exhibits a feature group corresponding to the second element characteristic. The calculated number of times the second characteristic action is performed is set as an intensity of the second element characteristic. The first characteristic information may include an intensity of each first element characteristic, and the second characteristic information may include an intensity of each second element characteristic.

[0017] In this configuration, the strength of each first element characteristic included in the first characteristic is set to the number of times the first characteristic motion is performed calculated based on the first motion information, and is included in the first characteristic information. Also, the strength of each second element characteristic included in the second characteristic is set to the number of times the second characteristic motion is performed calculated based on the second motion information, and is included in the second characteristic information.

[0018] Therefore, the first characteristic information of this configuration makes it possible to grasp not only one or more characteristics of the target user when other users are not present in the same environment as the target user, but also the strength of each of the one or more characteristics.Furthermore, the second characteristic information of this configuration makes it possible to grasp not only one or more characteristics of the target user when other users are present in the same environment as the target user, but also the strength of each of the one or more characteristics.

[0019] (4) In the information processing method described in (3) above, when setting the intensity of each first element characteristic and each second element characteristic, third action information indicating device operations and actions of one or more other users different from the target user may further be acquired, and based on the third action information, a first average value may be calculated as the average number of times the first characteristic action is performed per predetermined time by each of the one or more other users, a first execution count may be calculated as the number of times the first characteristic action is performed per predetermined time by each of the one or more other users, and the result obtained by dividing the first execution count by the first average value may be set as the intensity of each first element characteristic, a second average value may be calculated as the average number of times the second characteristic action is performed per predetermined time by each of the one or more other users, based on the third action information, a second execution count may be calculated as the number of times the second characteristic action is performed per predetermined time by each of the one or more other users, and the result obtained by dividing the second execution count by the second average value may be set as the intensity of each second element characteristic.

[0020] In this configuration, the first execution count, which is the number of times the first characteristic action is performed by the target user per predetermined time, is divided by the first average value, which is the average number of times the first characteristic action is performed per predetermined time by each of one or more other users different from the target user, and the result is set as the strength of each first element characteristic.

[0021] Therefore, this configuration can appropriately set the strength of each first element characteristic based on the first average value. Similarly, this configuration can appropriately set the strength of each second element characteristic based on the second average value, which is the average value of the number of times each of the one or more other users performs the second characteristic action per predetermined time.

[0022] (5) In the information processing method described in (3) above, when estimating the first characteristic and the second characteristic, if at least one of the first operation information and the second operation information includes a shared characteristic action that is a device operation or behavior that exhibits a feature group corresponding to a predetermined shared candidate characteristic from among the one or more candidate characteristics, the shared candidate characteristic is estimated as a shared element characteristic included in both the first characteristic and the second characteristic, and when setting the intensity of each first element characteristic and each second element characteristic, a first execution count that is the number of times the shared characteristic action is executed is calculated based on the first operation information, and a second execution count that is the number of times the shared characteristic action is executed is calculated based on the second operation information, and the sum of the first execution count and the second execution count may be set as the intensity of the shared element characteristic.

[0023] According to this configuration, even if either the first operation information or the second operation information does not contain a shared characteristic action corresponding to the shared candidate characteristic, if at least one of the first operation information or the second operation information contains a shared characteristic action, the shared candidate characteristic can be estimated as a shared element characteristic included in both the first characteristic and the second characteristic.

[0024] Furthermore, the strength of the shared element characteristic can be set to the sum of the number of times the shared characteristic action is performed calculated based on either the first action information or the second action information, rather than the number of times the shared characteristic action is performed calculated based on either the first action information or the second action information.

[0025] (6) In the information processing method described in (3) above, in estimating the first characteristic and the second characteristic, if at least one of the first action information and the second action information includes a shared characteristic action that is a device operation or action that shows a feature group corresponding to a predetermined shared candidate characteristic from the one or more candidate characteristics, the shared candidate characteristic is estimated as a shared element characteristic included in both the first characteristic and the second characteristic, and in setting the intensity of each first element characteristic and each second element characteristic, a first time period that the target user stayed in the first environment is calculated based on the first action information, and a time period that the target user stayed in the second environment is calculated based on the second action information. a second execution count that is the number of times the shared characteristic action is performed based on the first action information; a second execution count that is the number of times the shared characteristic action is performed based on the second action information; a product of the sum of the first execution count and the second execution count and the first time divided by the sum of the first time and the second time, the result being set as the intensity of the shared element characteristic included in the first characteristic; and a product of the sum of the first execution count and the second execution count and the second time divided by the sum of the first time and the second time, the result being set as the intensity of the shared element characteristic included in the second characteristic.

[0026] According to this configuration, even if either the first operation information or the second operation information does not contain a shared characteristic action corresponding to the shared candidate characteristic, if at least one of the first operation information or the second operation information contains a shared characteristic action, the shared candidate characteristic can be estimated as a shared element characteristic included in both the first characteristic and the second characteristic.

[0027] In addition, the sum of the number of times the shared characteristic action is performed calculated based on each of the first action information and the second action information can be proportionally allocated according to the first time period during which the target user stayed in the first environment and the second time period during which the target user stayed in the second environment, and can be appropriately set as the strength of the shared element characteristic included in each of the first characteristic and the second characteristic.

[0028] (7) In the information processing method described in (5) above, if there is an identical element characteristic having similar strength between the first characteristic and the second characteristic, the identical element characteristic may be estimated as the shared element characteristic.

[0029] According to this configuration, when an identical element characteristic having a similar intensity exists between the first characteristic and the second characteristic, the identical element characteristic is estimated as a shared element characteristic. Therefore, the sum of the number of times that device operations or actions exhibiting a feature group corresponding to the identical element characteristic, which is calculated based on each of the first operation information and the second operation information, can be set as the intensity of the identical element characteristic.

[0030] (8) In the information processing method described in (5) above, if the first information further includes a similar characteristic behavior, which is a device operation or behavior that indicates one of the one or more characteristic groups and is performed a similar number of times per unit time in each of the first environment and the second environment, a candidate characteristic corresponding to the characteristic group indicated by the similar characteristic behavior may be estimated as the shared element characteristic.

[0031] According to this configuration, when the similar characteristic motion is included in the first information, a candidate characteristic corresponding to a feature group indicated by the similar characteristic motion is estimated as a shared element characteristic. Therefore, the sum of the number of times the similar characteristic motion is performed, which is calculated based on each of the first motion information and the second motion information, can be set as the strength of the shared element characteristic.

[0032] (9) In the information processing method described in any one of (3) to (8) above, it is further possible to reduce the intensity of each first element characteristic at a first reduction rate when a device operation or behavior showing a group of features corresponding to each first element characteristic has not been performed for a first predetermined time or longer for each of the one or more first element characteristics, and to reduce the intensity of each second element characteristic at a second reduction rate when a device operation or behavior showing a group of features corresponding to each second element characteristic has not been performed for a second predetermined time or longer for each of the one or more second element characteristics.

[0033] According to this configuration, the intensity of a first element characteristic, among one or more first element characteristics included in the first characteristic, for which a device operation or action showing the corresponding feature group has not been performed for a first predetermined time or longer, can be reduced at a first reduction rate. Similarly, according to this configuration, the intensity of a second element characteristic, among one or more second element characteristics included in the second characteristic, for which a device operation or action showing the corresponding feature group has not been performed for a second predetermined time or longer, can be reduced at a second reduction rate.

[0034] (10) In the information processing method described in any one of (3) to (9) above, the method may further include calculating, for each of the one or more first element characteristics, a ratio of the intensity of each first element characteristic to the sum of the intensities of the one or more first element characteristics, and setting the calculated ratio as the intensity of each first element characteristic; and further calculating, for each of the one or more second element characteristics, a ratio of the intensity of each second element characteristic to the sum of the intensities of the one or more second element characteristics, and setting the calculated ratio as the intensity of each second element characteristic.

[0035] According to this configuration, the ratio of the intensity of each first element characteristic to the sum of the intensities of one or more first element characteristics is set as the intensity of each first element characteristic included in the first characteristic. Therefore, the intensity of one or more first element characteristics included in the first characteristic can be normalized. Similarly, according to this configuration, the ratio of the intensity of each second element characteristic to the sum of the intensities of one or more second element characteristics is set as the intensity of each second element characteristic included in the second characteristic. Therefore, the intensity of one or more second element characteristics included in the second characteristic can be normalized.

[0036] (11) In the information processing method described in (2) above, it is further possible to exclude each of the one or more first element characteristics from the first characteristics if a device operation or behavior showing a group of features corresponding to each of the one or more first element characteristics has not been performed for a first predetermined time or more, and to exclude each of the one or more second element characteristics from the second characteristics if a device operation or behavior showing a group of features corresponding to each of the one or more second element characteristics has not been performed for a second predetermined time or more.

[0037] According to this configuration, among one or more first element characteristics included in the first characteristic, a first element characteristic for which a device operation or action showing the corresponding feature group has not been performed for a first predetermined time or more can be excluded from the first characteristic. Similarly, according to this configuration, among one or more second element characteristics included in the second characteristic, a second element characteristic for which a device operation or action showing the corresponding feature group has not been performed for a second predetermined time or more can be excluded from the second characteristic.

[0038] (12) In the information processing method described in (1) above, information indicating one or more attributes of the other users may further be acquired, and for each of the one or more attributes, fourth operation information indicating device operations and actions of the target user in a third environment in which the other users with each attribute are present may be extracted from the second operation information, and based on the fourth operation information, a third characteristic, which is a characteristic of the target user present in the third environment, may be estimated, and third characteristic information regarding the third characteristic may be output.

[0039] According to this configuration, for each of one or more attributes, a third characteristic is estimated, which is a characteristic of a target user who exists in a third environment where other users having each attribute exist. Therefore, this configuration can individually estimate the characteristic of the target user according to the attributes of the other users who exist in the same environment as the target user.

[0040] (13) In the information processing method described in (1) above, when acquiring the first information, information indicating the device operation and behavior of the target user during a first predetermined period may be acquired as the first information, and when acquiring the second information, information indicating a history of the presence or absence of other users in the environment in which the target user is present during the first predetermined period may be acquired as the second information.

[0041] According to this configuration, information indicating device operations and actions of the target user during a first predetermined period is acquired as first information, and information indicating a history of the presence or absence of other users in the environment in which the target user is present during the first predetermined period is acquired as second information. Therefore, the first characteristic and the second characteristic of the target user during the first predetermined period can be appropriately estimated based on the first operation information and the second operation information extracted from the first information based on the second information.

[0042] (14) In the information processing method described in (1) above, third information indicating the behavior of the target user in the environment in which the target user currently exists may be acquired, and based on the third information, it may be determined whether a fourth environment in which the target user currently exists is the first environment or the second environment. If the fourth environment is the first environment, first characteristic information may be acquired, a first service to be provided to the target user may be determined based on the first characteristic information, and the first service may be executed. If the fourth environment is the second environment, second characteristic information may be acquired, a second service to be provided to the target user may be determined based on the second characteristic information, and the second service may be executed.

[0043] According to this configuration, it is determined whether the fourth environment in which the target user currently resides is the first environment or the second environment. If the fourth environment is the first environment, first characteristic information is acquired. If the fourth environment is the second environment, second characteristic information is acquired. Then, if the fourth environment is the first environment, a first service determined based on the first characteristic information is executed. If the fourth environment is the second environment, a second service determined based on the second characteristic information is executed. Therefore, this configuration can execute a service suited to the characteristics of the target user in the environment in which the target user currently resides.

[0044] (15) In the information processing method described in (14) above, the first characteristic may include one or more first element characteristics, and the second characteristic may include one or more second element characteristics. In determining the first service and the second service, second rule information defining a relationship between one or more element characteristic groups indicating the one or more element characteristics and one or more provided services may be acquired. If the first characteristic includes one or more first element characteristic groups included in the one or more element characteristic groups, one or more first provided services corresponding to the one or more first element characteristic groups may be identified, and the identified one or more first provided services may be determined as the first services. If the second characteristic includes one or more second element characteristic groups included in the one or more element characteristic groups, one or more second provided services corresponding to the one or more second element characteristic groups may be identified, and the identified one or more second provided services may be determined as the second services.

[0045] In this configuration, using the second rule information, one or more first provided services corresponding to one or more first element characteristic groups included in the first characteristic are determined as first services to be executed when the fourth environment is the first environment. Also, using the second rule information, one or more second provided services corresponding to one or more second element characteristic groups included in the second characteristic are determined as second services to be executed when the fourth environment is the second environment. Therefore, this configuration can execute one or more provided services suitable for the characteristics of the target user in the environment in which the target user currently exists.

[0046] (16) In the information processing method described in (3) above, third information indicating the behavior of the target user in the environment in which the target user currently exists may be acquired, and based on the third information, it may be determined whether a fourth environment in which the target user currently exists is the first environment or the second environment. If the fourth environment is the first environment, first characteristic information may be acquired, a first service to be provided to the target user may be determined based on the first characteristic information, and the first service may be executed. If the fourth environment is the second environment, second characteristic information may be acquired, a second service to be provided to the target user may be determined based on the second characteristic information, and the second service may be executed.

[0047] According to this configuration, it is determined whether the fourth environment in which the target user currently resides is the first environment or the second environment. If the fourth environment is the first environment, first characteristic information is acquired. If the fourth environment is the second environment, second characteristic information is acquired. Then, if the fourth environment is the first environment, a first service determined based on the first characteristic information is executed. If the fourth environment is the second environment, a second service determined based on the second characteristic information is executed. Therefore, this configuration can execute a service suited to the characteristics of the target user in the environment in which the target user currently resides.

[0048] (17) In the information processing method described in (16) above, in determining the first service and the second service, second rule information defining a relationship between one or more element characteristic groups indicating one or more element characteristics and one or more provided services is acquired, and if the first characteristics include one or more first element characteristic groups included in the one or more element characteristic groups, one or more first provided services corresponding to the one or more first element characteristic groups are identified, and if the second characteristics include one or more second element characteristic groups included in the one or more element characteristic groups, one or more second provided services corresponding to the one or more second element characteristic groups are identified, and third rule information associating the one or more provided services with a coefficient assigned to each provided service and a service field to which each provided service belongs is acquired, and for each of the one or more first provided services, a coefficient is calculated by multiplying the sum of intensities of one or more element characteristics indicated by the element characteristic groups corresponding to each first provided service, which are included in the first characteristics, by the coefficient assigned to each first provided service. The method may calculate a first product, and if a sum of the first products calculated for at least one first provided service belonging to each of the one or more first service fields to which the one or more first provided services belong among the one or more service fields is equal to or greater than a first predetermined value, determine the at least one first provided service as the first service, and calculate a second product, which is a product of a sum of intensities of one or more element characteristics indicated by an element characteristic group corresponding to each second provided service included in the second characteristics and a coefficient assigned to each second provided service, for each of the one or more second provided services to which the one or more second provided services belong among the one or more service fields, is equal to or greater than the first predetermined value, determine the at least one second provided service as the second service.

[0049] In this configuration, if the sum of the first products calculated using the second rule information and the third rule information for each of at least one first provided service belonging to each first service field is greater than or equal to a first predetermined value, the at least one first provided service is determined to be the first service to be executed when the fourth environment is the first environment.

[0050] Therefore, this configuration can determine, for each first service field, whether or not to determine at least one first provided service belonging to each first service field as the first service when the target user is present in the first environment.

[0051] Similarly, this configuration can determine, for each second service field, whether or not to determine at least one second provided service belonging to each second service field as the second service when the target user is present in the second environment.

[0052] (18) In the information processing method described in any one of (14) to (17) above, when multiple users exist in the same environment, the second service is determined for each of the multiple users as the target user, and when the multiple determined second services include multiple services that automatically control devices present in the environment where the user exists in accordance with the characteristics of the user, the multiple services may be executed by averaging parameters used for automatic control of the devices by the multiple services.

[0053] According to this configuration, when a plurality of users exist in the same environment, if the plurality of second services determined include a plurality of services that automatically control devices in the environment in accordance with the characteristics of the users, the parameters used for the automatic control of the devices by the plurality of services are averaged when the plurality of services are executed, thereby making it possible to avoid conflicts between the parameters used for the automatic control of the devices by each service when the plurality of services are executed.

[0054] (19) In the information processing method described in any one of (14) to (17) above, when multiple users exist in the same environment, the second service is determined for each of the multiple users as the target user, and when the multiple determined second services include multiple services that automatically control devices present in the environment where the user exists according to the characteristics of the user, a priority previously assigned to each of the multiple users may be obtained, and when the multiple services are executed, a service determined as the second service to be provided to the user among the multiple users with the highest priority may be executed.

[0055] According to this configuration, when a plurality of users exist in the same environment, if the plurality of determined second services include a plurality of services that automatically control devices in the environment in accordance with the characteristics of the users, the service determined as the second service to be provided to the user with the highest priority among the plurality of users is executed. Thus, this configuration makes it possible to avoid conflicts between the automatic control of devices by each service when the plurality of services are executed.

[0056] (20) In the information processing method described in any one of (14) to (17) above, when multiple users exist in the same environment, the second service is determined for each of the multiple users as the target user, and when the multiple determined second services include multiple services that automatically control devices present in the environment where the user exists according to the characteristics of the user, the execution of the multiple services may include executing the service that is the most numerous among the multiple services.

[0057] According to this configuration, when multiple users exist in the same environment, if the multiple determined second services include multiple services that automatically control devices in the user's environment according to the characteristics of the user, the service with the largest number of the multiple services is executed. Therefore, this configuration can avoid conflicts between the automatic control of devices by each service when the multiple services are executed.

[0058] (21) In the information processing method described in (15) or (17) above, when multiple users exist in the same environment, the second service is determined for each of the multiple users as the target user, and when the multiple determined second services include multiple services that automatically control devices present in the environment where the user exists according to the characteristics of the user, a predetermined priority is obtained for each of the one or more element characteristic groups, and when executing the multiple services, the service corresponding to the element characteristic group with the lowest priority among the multiple services is executed.

[0059] According to this configuration, when a plurality of users exist in the same environment, if the plurality of second services determined include a plurality of services that automatically control devices in the environment in accordance with the characteristics of the users, the service corresponding to the element characteristic group with the lowest priority among the plurality of second services is executed. Therefore, this configuration makes it possible to avoid conflicts between the automatic control of devices by each service when the plurality of services are executed.

[0060] (22) An information processing device according to another aspect of the present disclosure is an information processing device that estimates user characteristics, and includes: a first acquisition unit that acquires first information indicating device operations and actions of a target user to be estimated; a second acquisition unit that acquires second information indicating the presence or absence of other users different from the target user in an environment where the target user is present; an extraction unit that extracts, based on the first information and the second information, first operation information indicating at least one of device operations and actions of the target user in a first environment where the other users are not present, and second operation information indicating at least one of device operations and actions of the target user in a second environment where the other users are present; an estimation unit that estimates a first characteristic that is a characteristic of the target user present in the first environment based on the first operation information, and estimates a second characteristic that is a characteristic of the target user present in the second environment based on the second operation information; and an output unit that outputs at least one of the first characteristic information indicating the first characteristic and the second characteristic information indicating the second characteristic.

[0061] According to this configuration, the same effects as those of the above-described information processing method can be obtained.

[0062] (23) A program according to another aspect of the present disclosure is a program that causes a computer to function to estimate a user's characteristics, and causes the computer to function as a first acquisition unit that acquires first information indicating device operations and actions of a target user to be estimated, a second acquisition unit that acquires second information indicating the presence or absence of other users different from the target user in an environment where the target user is present, an extraction unit that extracts, based on the first information and the second information, first operation information indicating at least one of device operations and actions of the target user in a first environment where the other users are not present, and second operation information indicating at least one of device operations and actions of the target user in a second environment where the other users are present, an estimation unit that estimates a first characteristic that is a characteristic of the target user present in the first environment based on the first operation information and estimates a second characteristic that is a characteristic of the target user present in the second environment based on the second operation information, and an output unit that outputs at least one of the first characteristic information indicating the first characteristic and the second characteristic information indicating the second characteristic.

[0063] According to this configuration, the same effects as those of the above-described information processing method can be obtained.

[0064] The present disclosure can also be realized as a system operated by such a program. Needless to say, such a computer program can be distributed on a non-transitory computer-readable recording medium such as a CD-ROM or via a communication network such as the Internet.

[0065] Note that the embodiments described below each represent a specific example of the present disclosure. The numerical values, shapes, components, steps, and step orders shown in the following embodiments are merely examples and are not intended to limit the present disclosure. Furthermore, among the components in the following embodiments, components that are not described in an independent claim that represents a top-level concept are described as optional components. Furthermore, the contents of each embodiment can be combined.

[0066] First Embodiment Hereinafter, a first embodiment of the present disclosure will be described with reference to the drawings. Fig. 1 is a diagram illustrating an example of the overall configuration of an information processing system 100 according to an embodiment of the present disclosure. The information processing system 100 includes a plurality of devices 3, equipment 5 (devices), and sensors 7 provided in a facility 4 (environment), an output device 6, and an information processing device 1.

[0067] The information processing device 1 and the multiple devices 3, facilities 5, and sensors 7 are communicatively connected to each other via a network 9. The network 9 is, for example, a public communication line such as the Internet. The network 9 may also be a local area network. The multiple devices 3, facilities 5, and sensors 7 may also be communicatively connected to each other via a local network within the facility 4.

[0068] The facility 4 is divided into a plurality of spaces 40 (environments), and a plurality of devices 3, equipment 5, and sensors 7 are arranged in any of the plurality of spaces 40. Fig. 1 shows an example in which the facility 4 is divided into a first space 40a and a second space 40b, and the device 3a, equipment 5a, and sensor 7a are provided in the first space 40a, and the device 3b, equipment 5b, and sensor 7b are provided in the second space 40b.

[0069] The facility 4 is, for example, a residence. The residence may be an apartment building or a single-family home. When the facility 4 is a residence, the space 40 may be, for example, a living room, dining room, kitchen, LDK (living, dining, kitchen), Western-style room, Japanese-style room, hallway, toilet, entrance, and bathroom. An LDK is a space that combines a living room, dining room, and kitchen. The space 40 may also be, for example, the first floor and the second floor. The entire residence may also be considered as one space 40.

[0070] Alternatively, the facility 4 may be an office. When the facility 4 is an office, the space 40 may be, for example, an office, a conference room, a kitchen, a reception room, a lobby, a hallway, a toilet, etc. The space 40 may also be, for example, the first floor and the second floor. The entire office may also be considered as one space 40.

[0071] The devices 3 are electronic devices that can be freely placed within the facility 4, such as rice cookers, washing machines, refrigerators, microwave ovens, and cleaning robots. The devices 3 are operated by switches and remote controls specific to the devices 3. The facilities 5 are electronic devices that are installed at predetermined locations within the facility 4, such as electronic locks, air conditioners, and solar power generation equipment. The devices 5 are operated by switches and remote controls specific to the devices 5.

[0072] It should be noted that the devices 3 and the facilities 5 do not include information processing devices such as personal computers, smartphones, tablet terminals, etc. The operations of the devices 3 and the facilities 5 do not include operations in which the user actively inputs information that reflects his or her own intentions and preferences, such as inputting search keywords and clicking on product images.

[0073] When operated by a user, the device 3 and the facility 5 transmit information relating to the operation (hereinafter, operation information) to the information processing device 1 via the network 9 .

[0074] The operation information includes the date and time when the devices 3 and the facility 5 were operated (hereinafter referred to as operation date and time), identification information of the user who operated the devices 3 and the facility 5 (hereinafter referred to as user ID), identification information of the devices 3 and the facility 5 (hereinafter referred to as device ID), information indicating the content of the operation of the devices 3 and the facility 5 (hereinafter referred to as operation content information), etc. Note that the operation information transmitted by the devices 3 and the facility 5 does not necessarily include the user ID of the user who operated the devices 3 and the facility 5.

[0075] The operation content information includes information indicating the state of the equipment 3 and the facility 5 when operated (hereinafter referred to as state information), information set by operating the equipment 3 and the facility 5 (hereinafter referred to as setting information), information indicating the functions executed by operating the equipment 3 and the facility 5 (hereinafter referred to as function information), etc.

[0076] The sensor 7 periodically detects information relating to the space 40 in which the sensor 7 is installed. The sensor 7 transmits information (hereinafter, sensor information) including the detected information (hereinafter, detection information), the date and time when the detected information was detected (hereinafter, detection date and time), and identification information of the sensor 7 (hereinafter, sensor ID) to the information processing device 1 via the network 9. The sensor 7 includes a camera, a microphone, a radio wave sensor, a human presence sensor, etc.

[0077] The camera captures an image of the space 40 and transmits sensor information including image data representing the captured image as detection information. The microphone collects sounds generated in the space 40 and transmits sensor information including audio data representing the collected sounds as detection information. The radio wave sensor detects the position and shape of a person present in the space 40 based on the strength of radio waves and transmits sensor information including information indicating the position and shape of the detected person as detection information. The human presence sensor is, for example, an infrared sensor or a beacon sensor, and detects whether a person is present in the space 40. When the human presence sensor detects the presence of a person in the space 40, it transmits sensor information including information indicating the position of the person as detection information.

[0078] The output device 6 is connected to the information processing device 1 so as to be able to communicate with each other via a network 9. The output device 6 outputs information instructed by the information processing device 1 via the network 9. The output device 6 includes a display, a speaker, a controller, etc.

[0079] The display is, for example, a display device provided on a television or personal computer placed in the facility 4. The display is not limited to this, and may be provided on a mobile terminal that can be moved outside the facility 4, such as a smartphone or tablet terminal, or may be provided on the device 3 and the equipment 5. The display displays still images or videos instructed by the information processing device 1.

[0080] The speaker is, for example, a smart speaker placed in the facility 4. However, the speaker is not limited to this, and may be provided in a mobile terminal that can be moved outside the facility 4, such as a smartphone or a tablet terminal, or may be provided in the device 3 and the equipment 5. The speaker outputs sound indicating information instructed by the information processing device 1.

[0081] The controller is, for example, a home controller or an edge server located in the facility 4. The controller is not limited to this, and may also be a mobile terminal that can be moved outside the facility 4, such as a smartphone or a tablet terminal. The controller is further connected to the devices 3, the equipment 5, and the sensors 7 via a network 9 or wirelessly without via the network 9. The controller outputs information regarding the control of the devices 3, the equipment 5, and the sensors 7 (hereinafter, control information) that is input by a user operation or instructed by the information processing device 1 to the devices 3, the equipment 5, and the sensors 7. The devices 3, the equipment 5, and the sensors 7 perform various functions according to the control information. In this way, the controller remotely controls the devices 3, the equipment 5, and the sensors 7.

[0082] The information processing device 1 is configured with a cloud server, a personal computer, etc. The information processing device 1 may be an edge server located in a facility 4. The information processing device 1 is connected to an external service server 8 via a network 9 so that they can communicate with each other.

[0083] The service server 8 is composed of a cloud server, a personal computer, etc. The service server 8 executes services requested by the information processing device 1 via the network 9. The services executed by the service server 8 include a service for transmitting information instructed by the information processing device 1 to a database and / or an external service server (not shown), a service for acquiring information instructed by the information processing device 1 from a database and / or an external service server (not shown) and returning the information, etc.

[0084] The following provides a detailed description of the configuration of the information processing device 1. Fig. 2 is a block diagram showing an example of the configuration of the information processing device 1. The information processing device 1 includes a communication circuit 11, a processor 12, and a memory 13.

[0085] The communication circuit 11 is a communication interface circuit compatible with a communication method using a network 9 such as Ethernet (registered trademark). The communication circuit 11 connects the information processing device 1 to the network 9. The communication circuit 11 outputs various pieces of information received via the network 9 to the processor 12. Under the control of the processor 12, the communication circuit 11 also transmits various pieces of information to external devices via the network 9.

[0086] The processor 12 (computer) is configured with, for example, a CPU. The processor 12 stores operation information received by the communication circuit 11 from the devices 3 and the facilities 5 via the network 9 in an operation information storage unit 133 (described later). The processor 12 also stores sensor information received by the communication circuit 11 from the sensors 7 via the network 9 in a sensor information storage unit 134 (described later).

[0087] Furthermore, the processor 12 functions as a first acquisition unit 121, a second acquisition unit 122, an estimation unit 124, an output unit 125, a determination unit 126, and an execution unit 127. The first acquisition unit 121 to the execution unit 127 may be realized by the processor 12 executing a predetermined program stored in the memory 13, or may be configured by a dedicated hardware circuit. In the first embodiment, the processor 12 functions as the first acquisition unit 121, the second acquisition unit 122, the estimation unit 124, and the output unit 125. Details of the first acquisition unit 121 to the output unit 125 will be described later.

[0088] The memory 13 is configured with a storage device such as a hard disk drive or a solid state drive. The memory 13 includes a device information storage unit 131, a user information storage unit 132, an operation information storage unit 133, a sensor information storage unit 134, and a rule information storage unit 135. The device information storage unit 131 to the rule information storage unit 135 are not limited to being included in the memory 13, and may be included in an external storage device that the processor 12 can access via the network 9 using the communication circuit 11.

[0089] The device information storage unit 131 stores information (hereinafter referred to as device information) related to the devices 3, facilities 5, and sensors 7. Specifically, the device information related to the devices 3 and facilities 5 includes identification information of the space 40 in which the devices 3 and facilities 5 are located (hereinafter referred to as space ID), the device IDs of the devices 3 and facilities 5, addresses indicating destinations when control information is sent to the devices 3 and facilities 5, functions possessed by the devices 3 and facilities 5, start times for use of consumables used by the devices 3 and facilities 5, and the status (normal, abnormal) of the devices 3 and facilities 5. The device information related to the sensor 7 includes the space ID of the space 40 in which the sensor 7 is located and the sensor ID of the sensor 7.

[0090] The user information storage unit 132 stores information (hereinafter, user information) about each of multiple users of the information processing system 100. Specifically, the user information includes the user's user ID, information about the user's attributes (hereinafter, attribute information), information indicating the user's characteristics (hereinafter, characteristic information), and the like.

[0091] The attribute information includes, for example, the user's address, age, gender, group to which the user belongs, role in the group, etc. Groups include, for example, family, company departments, etc. Roles include, for example, father, mother, son, daughter, department manager, section chief, etc.

[0092] The characteristic information includes the user's characteristics and their strength. The user's characteristics consist of one or more element characteristics. The element characteristics include, for example, being lazy, meticulous, spendthrifty, thrifty, regular, irregular, neat and tidy, messy, nervous, preferring solitude, and fond of communication. The characteristic information is stored separately as information indicating the user's characteristics when no other users are present in the space 40 in which the user exists, i.e., when the user is alone in the space 40 (hereinafter referred to as first characteristic information), and information indicating the user's characteristics when other users are present in the space 40 in which the user exists (hereinafter referred to as second characteristic information).

[0093] The user information storage unit 132 further stores matching data. The matching data is used to match the detection information included in the sensor information for the purposes of identifying a user present in the space 40 in which the sensor 7 is placed, and identifying a user who operated the devices 3 and facilities 5 placed in the same space 40 as the sensor 7. Specifically, the matching data includes various data indicating the characteristics of the user, such as image data indicating an image of the user's face or whole body, audio data indicating the user's voice, and shape data indicating the user's shape, as well as the user ID of the user.

[0094] In addition, the user information storage unit 132 stores user-specific information such as the user's to-do list, schedule, vital data, current subscription services, favorite external services, identification information of the output device 6 used by the user, and the IP address of the output device 6.

[0095] The operation information storage unit 133 stores operation information that the communication circuit 11 receives from the devices 3 and the facilities 5 via the network 9 .

[0096] The sensor information storage unit 134 stores the sensor information received by the communication circuit 11 from the sensor 7 via the network 9 .

[0097] The rule information storage unit 135 stores information indicating various rules (hereinafter, rule information) used in various processes by the processor 12. Details of the rule information stored in the rule information storage unit 135 will be described later.

[0098] (Characteristic Output Processing Flow) Next, the flow of the characteristic output processing performed in the information processing device 1 will be described. The characteristic output processing is processing for estimating characteristics of a user of the information processing system 100 based on operation information and sensor information, and outputting characteristic information of the user. FIG. 3 is a flowchart showing an example of the characteristic output processing. The characteristic output processing is executed at predetermined intervals, such as once a day, once a week, or once a month. However, without being limited to this, the characteristic output processing may be executed every time operation information is acquired by the processor 12.

[0099] First, in step S100, the first acquisition unit 121 acquires the operation information stored in the operation information storage unit 133 and the sensor information stored in the sensor information storage unit 134 after the previous characteristic output process has ended.

[0100] 4 is a diagram showing an example of operation information. For example, FIG. 4 shows operation information acquired in step S100 of the characteristic output process started at 6:00 on September 1, 2021, after the previous characteristic output process started at 6:00 on August 31, 2021. The operation information indicates, for example, that a user with user ID "User A" performed an operation to turn on device 3 with device ID "Light 1" at 7:05:30 on August 31, 2021.

[0101] As described above, the operation information stored in the operation information storage unit 133 may not include the user ID of the user who operated the device 3 and the facility 5. In this case, the first acquisition unit 121 refers to sensor information including a detection date and time that matches the operation date and time included in the operation information. "Match" refers to matching within a predetermined tolerance, and this also applies to the following description. The first acquisition unit 121 identifies the user who operated the device 3 or the facility 5 in the space 40 indicated by the detection information by comparing the detection information included in the sensor information with the matching data stored in the user information storage unit 132. The first acquisition unit 121 acquires the user ID of the identified user as the user ID included in the operation information.

[0102] Next, in step S200, the processor 12 performs a process (hereinafter, characteristic estimation process) to estimate the characteristics of the target users (hereinafter, target users) by targeting each of the users with one or more user IDs included in the operation information acquired in step S100 as the estimation target.

[0103] In the characteristic estimation process, a characteristic of the target user when he / she is alone in the space 40 is estimated, and first characteristic information indicating the characteristic is updated. In addition, in the characteristic estimation process, a characteristic of the target user when another user (another user) different from the target user is present in the space 40 where the target user is present is estimated, and second characteristic information indicating the characteristic is updated. Details of the characteristic estimation process will be described later.

[0104] Next, in step S300, the output unit 125 outputs at least one of the first characteristic information and the second characteristic information of each target user.

[0105] Specifically, in step S300, the output unit 125 transmits (outputs) at least one of the first characteristic information and the second characteristic information of each target user, which was updated in step S200, to a predetermined external device such as the output device 6 ( FIG. 1 ), using the communication circuitry 11. Without being limited to this, in step S300, the output unit 125 may transmit (output) at least one of the first characteristic information and the second characteristic information of each target user, which is stored in the user information storage unit 132, to a predetermined external device such as the output device 6 ( FIG. 1 ), using the communication circuitry 11, regardless of whether the information was updated in step S200.

[0106] (Flow of characteristic estimation process) Next, details of the characteristic estimation process in step S200 will be described. FIG. 5 is a flowchart showing an example of the characteristic estimation process. For example, assume that the operation information shown in FIG. 4 is acquired in step S100. In this case, the processor 12 performs characteristic estimation process to estimate the characteristics of a user with a user ID "user A" included in the operation information, which is the target user. The processor 12 also performs characteristic estimation process to estimate the characteristics of a user with a user ID "user B" included in the operation information, which is the target user.

[0107] First, in step S201, the first acquisition unit 121 acquires operation information (first information) indicating the operation (equipment operation) of the target user's device 3 and facility 5 after the previous characteristic output process has ended, and sensor information (first information) indicating the target user's behavior.

[0108] Specifically, in step S201, the first acquisition unit 121 acquires operation information including the user ID of the target user from the operation information acquired in step S100. Hereinafter, the operation information indicating the operation of the device 3 or facility 5 by the target user acquired in step S201 will be referred to as operation history information.

[0109] The first acquisition unit 121 refers to the device information stored in the device information storage unit 131 and acquires the sensor ID of the sensor 7 that is located in the same space 40 as the device 3 or facility 5 whose device ID is included in the operation history information. From the sensor information acquired in step S100, the first acquisition unit 121 acquires sensor information that includes the sensor ID and whose detection date and time matches the operation date and time included in the operation history information. Hereinafter, the sensor information indicating the behavior of the target user acquired in step S201 will be referred to as behavior history information.

[0110] Next, in step S202, the second acquisition unit 122 acquires information (second information) indicating the presence or absence of other users in the space 40 where the target user is present after the end of the previous characteristic output process. Hereinafter, the information acquired in step S202 indicating the presence or absence of other users in the space 40 where the target user is present will be referred to as presence history information.

[0111] Specifically, in step S202, the second acquisition unit 122 refers to the device information stored in the device information storage unit 131, and acquires the space ID of the space 40 in which the sensor 7 having the sensor ID included in the behavior history information is located, as the space ID of the space 40 in which the target user exists. The second acquisition unit 122 compares the detection information included in the behavior history information with the comparison data stored in the user information storage unit 132, thereby identifying one or more people present in the space 40 in which the target user exists.

[0112] When the second acquisition unit 122 determines that only one target user exists, it acquires, as presence history information, information that associates the detection date and time included in the behavioral history information, the space ID of the space 40 in which the target user exists, and information indicating that no other users exist (hereinafter, the single flag).

[0113] On the other hand, when the second acquisition unit 122 identifies the existence of the target user and a user whose user ID is different from that of the target user, it acquires, as presence history information, information that associates the detection date and time included in the behavioral history information, the space ID of the space 40 in which the target user exists, the user ID of the different user, and information indicating the existence of other users (hereinafter, multiple flags).

[0114] In addition, when the second acquisition unit 122 determines that the target user and a person who cannot be identified using the matching data exist, it acquires, as presence history information, information that associates the detection date and time included in the behavioral history information, the space ID of the space 40 in which the target user exists, and multiple flags.

[0115] Next, in step S203, the estimation unit 124 acquires current characteristic information of the target user. Specifically, the estimation unit 124 acquires first characteristic information and second characteristic information of the target user stored in the user information storage unit 132.

[0116] FIG. 6 is a diagram illustrating an example of first characteristic information. The first characteristic information is information indicating a characteristic (hereinafter, referred to as the first characteristic) of the target user when the target user is alone in the space 40. The first characteristic information is information that associates one or more element characteristics included in the first characteristic with the intensity of each element characteristic. The first characteristic information illustrated in FIG. 6 indicates five element characteristics, "slacker," "spendthrift," "clean freak," "nervous," and "sensitive to heat," when the target user is alone in the space 40, and indicates that the intensities of these element characteristics are "0.3," "0.2," "0.3," "0.1," and "0.1," respectively.

[0117] In this embodiment, the larger the intensity value, the stronger the element characteristic the target user exhibits. The same applies to the following description. That is, the first characteristic information shown in FIG. 6 indicates that the target user most strongly exhibits the characteristics of “sloth” and “cleanliness” when the target user is alone in the space 40.

[0118] FIG. 7 is a diagram illustrating an example of second characteristic information. As shown in FIG. 7 , the second characteristic information is information indicating a characteristic (hereinafter, the second characteristic) when other users are present in the space 40 where the target user exists. Similar to the first characteristic information, the second characteristic information is information that associates one or more element characteristics included in the second characteristic with the intensity of each element characteristic. The second characteristic information illustrated in FIG. 7 indicates five element characteristics—“slacker,” “frugal,” “cleanliness,” “nervous,” and “communicative”—when other users are present in the space 40 where the target user exists, with the respective intensities of these element characteristics being “0.1,” “0.1,” “0.5,” “0.1,” and “0.2.” In other words, the second characteristic information illustrated in FIG. 7 indicates that the “cleanliness” characteristic is most strongly exhibited when other users are present in the space 40 where the target user exists.

[0119] Next, in step S204, the extraction unit 123 extracts information indicating the operation and behavior of the equipment 3 or facility 5 by the target user in each of the space 40 where no other users are present (hereinafter, the first environment) and the space 40 where other users are present (hereinafter, the second environment) from the operation history information and behavior history information acquired in step S201 based on the presence history information acquired in step S202.

[0120] Specifically, in step S204, the extraction unit 123 refers to the device information stored in the device information storage unit 131, and determines whether the presence history information, which includes the detection date and time that matches the operation date and time included in the operation history information and the space ID of the space 40 in which the device 3 or facility 5 with the device ID included in the operation history information is located, includes a single flag or multiple flags.

[0121] If the extraction unit 123 determines that the operation history information includes a single flag, it extracts the operation history information as information indicating an operation of the device 3 or the facility 5 by the target user in the first environment (hereinafter, referred to as first operation history information). On the other hand, if the extraction unit 123 determines that the operation history information includes multiple flags, it extracts the operation history information as information indicating an operation of the device 3 or the facility 5 by the target user in the second environment (hereinafter, referred to as second operation history information).

[0122] In addition, the extraction unit 123 refers to the device information stored in the device information storage unit 131 and determines whether the presence history information, which includes the detection date and time that matches the detection date and time included in the behavior history information and the space ID of the space 40 in which the sensor 7 with the sensor ID included in the behavior history information is located, includes a single flag or multiple flags.

[0123] When the extraction unit 123 determines that the behavior history information includes a single flag, it extracts the behavior history information as information indicating behavior by the target user in the first environment (hereinafter, first behavior history information). On the other hand, when the extraction unit 123 determines that the behavior history information includes multiple flags, it extracts the behavior history information as information indicating operation of the device 3 or facility 5 by the target user in the second environment (hereinafter, second behavior history information).

[0124] In other words, the first operation history information and first behavior history information extracted in step S204 represent an example of first operation information of the present disclosure, and the second operation history information and second behavior history information represent an example of second operation information of the present disclosure.

[0125] Next, in step S205, the estimation unit 124 extracts candidate characteristics that are estimated to be component characteristics of a first characteristic, which is a characteristic of a target user present in the first environment, and a second characteristic, which is a characteristic of a target user present in the second environment, based on the information extracted in step S204.

[0126] Specifically, in step S205, the estimation unit 124 acquires, from the rule information storage unit 135, first rule information that defines the relationship between one or more candidate characteristics that can become element characteristics and one or more groups of characteristics that indicate the characteristics of the operation or behavior of the equipment 3 or the facility 5.

[0127] Fig. 8 is a diagram showing an example of first rule information that defines the relationship between one or more candidate characteristics and one or more feature groups that indicate characteristics of operation of the device 3 or the facility 5. In the first rule information shown in Fig. 8, eight candidate characteristics are associated with feature groups that indicate two characteristics of operation of the device 3 or the facility 5 by a user, with each candidate characteristic being an element characteristic.

[0128] For example, in the first rule information shown in Figure 8, the candidate trait "lazy" is associated with a group of traits indicating a lighting operation trait "low frequency of lighting operation" and a refrigerator operation trait "leaving the refrigerator door open for a long time" by a user whose component trait is the candidate trait "lazy."

[0129] 9 is a diagram illustrating an example of first rule information that defines a relationship between one or more candidate characteristics and one or more feature groups that indicate characteristics of behavior. In the first rule information illustrated in FIG. 9, eight candidate characteristics are associated with feature groups that indicate two characteristics of a user's behavior, each of which has the candidate characteristic as an element characteristic.

[0130] For example, in the first rule information shown in Figure 9, the candidate trait "lazy" is associated with a group of traits indicating the behavioral traits "messy desk" and "low frequency of folding laundry" of a user who has the candidate trait "lazy" as an element trait.

[0131] The number of features included in the feature group in the first rule information is not limited to two, and may be one, or three or more. However, it is preferable that the number of features included in the feature group in the first rule information is two or more. This is because the user's intentions and preferences are not necessarily clearly reflected in a single feature of the user's operation or behavior of the device 3 or the facility 5.

[0132] Then, the estimation unit 124 refers to the first rule information and extracts candidate characteristics that are estimated to be component characteristics of the first characteristic of the target user based on the first operation history information and the first behavior history information extracted in step S204.

[0133] Specifically, the estimation unit 124 refers to the first rule information shown in FIG. 8 and determines whether the operation of the device 3 or facility 5 by the target user in the first environment indicated by the first operation history information includes an operation of the device 3 or facility 5 that indicates one or more groups of features (first group of features) included in the first rule information.

[0134] The inclusion of an operation of a device 3 or facility 5 exhibiting a feature group means that the number of times that the operation of each of the devices 3 or facilities 5 exhibiting one or more features included in the feature group has been performed is at least one. Information indicating the operation of each device 3 or facility 5 exhibiting each feature is stored in the rule information storage unit 135. The estimation unit 124 makes the above determination by referring to the information.

[0135] When determining that the operation of the device 3 or facility 5 exhibiting one or more feature groups is included, the estimation unit 124 identifies one or more candidate characteristics (first candidate characteristics) associated with the one or more feature groups in the first rule information. The estimation unit 124 estimates the identified one or more candidate characteristics as component characteristics of the first characteristic of the target user, and extracts the one or more candidate characteristics.

[0136] For example, suppose that the target user's operations of the device 3 or facility 5 in the first environment indicated by the first operation history information include one or more lighting operations indicating the characteristic "lighting is operated infrequently" included in the characteristic group associated with the candidate characteristic "lazy" included in the first rule information shown in Fig. 8, and also include one or more refrigerator operations indicating the characteristic "refrigerator door is left open for a long time" included in the characteristic group. In this case, the estimation unit 124 estimates the candidate characteristic "lazy" associated with the characteristic group in the first rule information as an element characteristic of the target user's first characteristic, and extracts the candidate characteristic "lazy."

[0137] Note that a lighting operation that exhibits the characteristic "low lighting operation frequency" refers to, for example, an operation in which the number of times the lighting is turned on or off per day is less than a predetermined number (e.g., twice). However, the operation is not limited to this, and may also be, for example, an operation in which the ratio of the number of times the user turns on or off the lighting to the number of times the user leaves the space 40 in which the lighting is located is less than a predetermined value (e.g., 0.7). The number of times the user leaves the space 40 in which the lighting is located may be obtained by referring to the device information stored in the device information storage unit 131 and the first behavior history information including the detection date and time that matches the operation date and time included in the first operation history information.

[0138] On the other hand, a refrigerator operation exhibiting the characteristic "refrigerator door is left open for a long time" refers to, for example, an operation in which the average time the refrigerator door is left open per day is equal to or longer than a predetermined time. However, the operation is not limited to this, and may also be, for example, an operation in which the ratio of the number of times a warning indicating that the refrigerator door has been left open for a predetermined time or longer after the user has opened it to the number of times the user has opened the refrigerator door is output is equal to or greater than a predetermined value (for example, 0.3).

[0139] Similarly, the estimation unit 124 refers to the first rule information shown in Figure 9 and determines whether the behavior of the target user in the first environment indicated by the first behavior history information includes behavior that indicates one or more groups of features (first group of features) included in the first rule information.

[0140] The inclusion of the number of times of execution of an action indicating a feature group means that the number of times of execution of each of the actions indicating one or more features included in the feature group is at least one. Information indicating the actions indicating each feature is stored in the rule information storage unit 135. The estimation unit 124 makes the above determination by referring to the information.

[0141] When determining that the target user's behavior indicates one or more characteristic groups, the estimation unit 124 identifies one or more candidate characteristics (first candidate characteristics) associated with the one or more characteristic groups in the first rule information. The estimation unit 124 estimates the identified one or more candidate characteristics as component characteristics of the target user's first characteristic, and extracts the one or more candidate characteristics.

[0142] For example, suppose that the behavior of the target user in the first environment indicated by the first behavioral history information includes one or more behaviors indicating the characteristic "messy desk" included in the characteristic group associated with the candidate characteristic "lazy" included in the first rule information shown in Fig. 9, and also includes one or more behaviors indicating the characteristic "infrequently folds laundry" included in the characteristic group. In this case, the estimation unit 124 estimates that the candidate characteristic "lazy" associated with the characteristic group in the first rule information is an element characteristic of the first characteristic of the target user, and extracts the candidate characteristic "lazy."

[0143] The behavior indicating the characteristic "messy desk" refers to, for example, a behavior in which a predetermined number of items or more are left on the desk for a predetermined period of time or more. The behavior indicating the characteristic "low frequency of folding laundry" refers to, for example, a behavior in which the ratio of the number of times unfolded clothes are worn to the number of times clothes are worn is equal to or greater than a predetermined value.

[0144] 8 , the estimation unit 124 determines whether the target user's operations of the device 3 or facility 5 in the second environment indicated by the second operation history information include operations of the device 3 or facility 5 that exhibit one or more feature groups (second feature groups) included in the first rule information. If the estimation unit 124 determines that the operations of the device 3 or facility 5 that exhibit one or more feature groups include the operations of the device 3 or facility 5, the estimation unit 124 identifies one or more candidate characteristics (second candidate characteristics) associated with the one or more feature groups in the first rule information. The estimation unit 124 estimates the identified one or more candidate characteristics as component characteristics of the target user's second characteristic, and extracts the one or more candidate characteristics.

[0145] 9 , and determines whether or not the behavior of the target user in the second environment indicated by the second behavior history information includes behavior that indicates one or more feature groups (second feature groups) included in the first rule information. If the estimation unit 124 determines that the behavior includes behavior that indicates one or more feature groups, the estimation unit 124 estimates that one or more candidate characteristics (second candidate characteristics) associated with the one or more feature groups in the first rule information are component characteristics of the second characteristic of the target user, and extracts the one or more candidate characteristics.

[0146] In step S205, the estimation unit 124 may omit extracting candidate traits based on either the first operation history information or the first behavior history information extracted in step S204. Similarly, the estimation unit 124 may omit extracting candidate traits based on either the second operation history information or the second behavior history information extracted in step S204.

[0147] In step S205, if no candidate characteristic is extracted (NO in step S205), the first characteristic information and the second characteristic information acquired in step S203 are not updated, and the characteristic estimation process ends.

[0148] On the other hand, if one or more candidate characteristics estimated to be component characteristics of the characteristics of the target user present in at least one of the first environment and the second environment are extracted in step S205 (YES in step S205), in this case, in step S206, the estimation unit 124 updates the characteristic information indicating the characteristics of the target user present in at least one of the environments from among the first characteristic information and the second characteristic information acquired in step S203, and ends the characteristic estimation process.

[0149] Specifically, assume that a candidate characteristic estimated as an element characteristic of the first characteristic is extracted in step S205. In this case, in step S206, if the candidate characteristic is not included in the first characteristic indicated by the first characteristic information, the estimation unit 124 adds the candidate characteristic as an element characteristic of the first characteristic. Then, the estimation unit 124 updates (sets) the strength of each element characteristic included in the first characteristic and updates the first characteristic information stored in the user information storage unit 132 with the first characteristic information indicating the updated first characteristic.

[0150] On the other hand, suppose that a candidate characteristic estimated as an element characteristic of the second characteristic is extracted in step S205. In this case, in step S206, if the candidate characteristic is not included in the second characteristic indicated by the second characteristic information, the estimation unit 124 adds the candidate characteristic as an element characteristic of the second characteristic. Then, the estimation unit 124 updates (sets) the strength of each element characteristic included in the second characteristic, and updates the second characteristic information stored in the user information storage unit 132 with the second characteristic information indicating the updated second characteristic.

[0151] Details of step S206 are described below. Note that step S206, which is performed when a candidate characteristic estimated to be an element characteristic of the first characteristic (first element characteristic) is extracted in step S205, and step S206, which is performed when a candidate characteristic estimated to be an element characteristic of the second characteristic (second element characteristic) is extracted in step S205, have similar processing content.

[0152] Therefore, the following will provide a detailed description of step S206, which is performed when the candidate trait "lazy" is extracted in step S205 as a candidate trait that is estimated to be an element trait of the second trait. A detailed description of step S206, which is performed when a candidate trait that is estimated to be an element trait of the first trait is extracted in step S205, will be omitted.

[0153] 10 is a diagram showing an example of the relationship between the characteristics of the target user before updating and the number of times that characteristic actions corresponding to each element characteristic are performed. Fig. 10 shows an example of the relationship between second characteristic information indicating the second characteristic of the target user shown in Fig. 7 and the number of times that characteristic actions corresponding to each element characteristic included in the second characteristic are performed. The number of times that characteristic actions corresponding to each element characteristic included in the second characteristic are stored in the user information storage unit 132 in association with the second characteristic information indicating the second characteristic.

[0154] The characteristic action corresponding to each element characteristic refers to an operation or behavior of the device 3 or facility 5 that indicates a group of characteristics associated with the candidate characteristic indicating each element characteristic in the first rule information. For example, the characteristic action corresponding to the element characteristic "lazy" refers to the operation of a light and the operation of a refrigerator that indicate two characteristics, "low frequency of operating lights" and "long time the refrigerator door is open," that are associated with the candidate characteristic "lazy" in the first rule information ( FIG. 8 ). Furthermore, the characteristic action corresponding to the candidate characteristic "lazy" refers to the behavior that indicates two characteristics, "messy desk" and "low frequency of folding laundry," that are associated with the candidate characteristic "lazy" in the first rule information ( FIG. 9 ).

[0155] The number of times that the characteristic action corresponding to the element characteristic "lazy" included in the second characteristic is performed indicates the minimum value of the number of times that the characteristic actions, namely, the operation of the lighting and the operation of the refrigerator, were performed in the operation of the target user's device 3 or facility 5 in the second environment indicated by the second operation history information, and the number of times that the above-mentioned characteristic actions were performed in the target user's behavior in the second environment indicated by the second behavior history information.

[0156] In other words, the number of times the characteristic action corresponding to each element characteristic is performed is the minimum value of the number of times the operation and behavior of the device 3 or facility 5 is performed, which indicates each feature included in the feature group corresponding to the candidate characteristic indicating each element characteristic. However, without being limited to this, the number of times the characteristic action corresponding to each element characteristic is performed may be the average or maximum value of the number of times the operation and behavior of the device 3 or facility 5 is performed, which indicates each feature included in the feature group corresponding to the candidate characteristic indicating each element characteristic.

[0157] In step S206, the estimation unit 124 refers to the second operation history information and the second behavior history information, and calculates the number of times that a characteristic action (second characteristic action) has been performed that corresponds to an element characteristic that is included in the second characteristic and indicates the candidate characteristic extracted in step S205. The estimation unit 124 adds the number of times that the characteristic action corresponding to the element characteristic that has been calculated this time to the number of times that the characteristic action corresponding to the element characteristic that is included in the second characteristic has been performed, which is stored in the user information storage unit 132.

[0158] 11 is a diagram showing an example of the relationship between the characteristics of the target user after updating and the number of times the characteristic action corresponding to each element characteristic is performed. In step S206, the estimation unit 124 calculates the number of times the characteristic action corresponding to the element characteristic "lazy" is performed "1 time," and adds this number of times to the number of times the characteristic action corresponding to the element characteristic "lazy" included in the second characteristic shown in FIG. 10 is performed, resulting in "11 times."

[0159] Then, the estimation unit 124 sets the strength of each element characteristic included in the second characteristic information based on the number of times the characteristic action corresponding to each element characteristic included in the second characteristic has been performed.

[0160] Specifically, the estimation unit 124 sets the ratio of the number of times characteristic actions corresponding to each element characteristic included in the second characteristic to the total number of times that one or more characteristic actions corresponding to one or more element characteristics included in the second characteristic are executed as the strength of each element characteristic. As a result, the sum of the strengths of the element characteristics included in the second characteristic is normalized to 1.

[0161] 11, the total number of times the five characteristic actions corresponding to the five element traits included in the second trait are executed is 101 (=11+10+50+10+20). Therefore, the estimation unit 124 sets the ratio of the total number of times the characteristic action corresponding to the element trait "lazy" is executed (11 times) to the total number of times (101 times) (0.109 (=11 / 101 times)) as the strength of the element trait "lazy."

[0162] Similarly, the estimation unit 124 sets the ratios of the number of times the characteristic actions corresponding to the element characteristics “frugal,” “neat,” “neurotic,” and “communicative” are executed (10 times), (50 times), (10 times), and (20 times) to the total number of times the five characteristic actions corresponding to the five element characteristics included in the second characteristic are executed (101 times), as “0.099,” “0.495,” “0.099,” and “0.198,” respectively, as the intensities of the element characteristics “frugal,” “neat,” “neurotic,” and “communicative.”

[0163] The method for setting the strength of each element characteristic included in the second characteristic is not limited to this. For example, the estimation unit 124 may set the number of times (e.g., "11 times") that a characteristic action corresponding to each element characteristic included in the second characteristic (e.g., "lazy") is performed as the strength of each element characteristic included in the second characteristic.

[0164] The following modifications can be adopted to the configuration of the first embodiment.

[0165] (1) In the first embodiment, an example was described in which the strength of each element characteristic included in the first characteristic and the second characteristic is set in step S206 using the number of times the characteristic action corresponding to each element characteristic is performed. However, for example, the characteristic actions corresponding to the element characteristic "lazy," such as the operation of the lights and the operation of the refrigerator, are likely to be performed multiple times per day. In contrast, for example, the characteristic actions corresponding to the element characteristic "regular" are the operation of the lights and the operation of the coffee maker that the target user first performs after waking up, which respectively represent two characteristics associated with the candidate characteristic "regular" in the first rule information ( FIG. 8 ), namely, "the lights turn on at a constant time in the morning" and "the coffee maker starts at a constant time." These characteristic actions are performed only once per day.

[0166] In the first embodiment, for example, if the number of times that characteristic actions corresponding to the element characteristics “lazy” and “regular” obtained from the first operation history information for one day are both executed is “once,” the strengths of these element characteristics will be updated with the same weight using the same number of times of execution “one time,” even though the number of times that each characteristic action may be executed per day is different as described above.

[0167] Therefore, the strength of each element characteristic may be updated with the same weight based on the number of times a characteristic action corresponding to each element characteristic is performed per predetermined time by a user other than the target user, as follows.

[0168] Specifically, in step S206, the estimation unit 124 refers to the second operation history information and the second behavior history information to calculate the number of times (second execution count) that a characteristic action is performed per predetermined time period (e.g., one day) that corresponds to an element characteristic that is included in the second characteristic of the target user and indicates the candidate characteristic extracted in step S205. Hereinafter, for convenience of explanation, a characteristic action that is included in the second characteristic of the target user and corresponds to an element characteristic that is included in the second characteristic of the target user and indicates the candidate characteristic extracted in step S205 will be referred to as a target characteristic action.

[0169] The estimation unit 124 acquires, from the operation information storage unit 133, operation information including the user IDs of one or more users (one or more other users) different from the target user, as information indicating operations of the device 3 or facility 5 by the one or more users (hereinafter, referred to as third operation history information). Furthermore, the estimation unit 124 acquires, from the sensor information storage unit 134, sensor information including a detection date and time that matches the operation date and time included in the third operation history information and a space ID of the space 40 in which the device 3 or facility 5 with the device ID included in the third operation history information is located, as information indicating actions by the one or more users (hereinafter, referred to as third behavior history information). In other words, the third operation history information and the third behavior history information represent examples of third behavior information of the present disclosure.

[0170] The estimation unit 124 refers to the third operation history information and the third behavior history information to calculate the number of times the target characteristic action is performed per specified time by each of one or more users other than the target user, and calculates the average value (second average value).

[0171] The estimation unit 124 divides the number of times the target characteristic action is performed per specified time period, calculated by referring to the second operation history information and the second behavior history information, by the average value, and adds the result to the number of times the target characteristic action is performed, which is stored in the user information storage unit 132.

[0172] In a similar manner, the estimation unit 124 updates the number of times that the characteristic actions corresponding to the element characteristics indicating the candidate characteristics extracted in step S205 are performed, which are included in the first characteristic of the target user.

[0173] (2) In the first embodiment, an example has been described in which, in step S100 ( FIG. 3 ), the first acquisition unit 121 acquires the operation information stored in the operation information storage unit 133 and the sensor information stored in the sensor information storage unit 134 after the previous characteristic output process has ended. However, instead of this, in step S100, the first acquisition unit 121 may acquire the operation information stored in the operation information storage unit 133 and the sensor information stored in the sensor information storage unit 134 for a first predetermined period. The first predetermined period is, for example, the most recent one week, one month, three months, or one year.

[0174] Thereby, in step S201, the first acquisition unit 121 may acquire operation information (first information) indicating operations of the device 3 and the facility 5 by the target user and sensor information (first information) indicating the behavior of the target user during the first predetermined period. As a result, in step S202, the second acquisition unit 122 may acquire presence history information (second information) indicating a history of the presence or absence of other users in the space 40 where the target user is present during the first predetermined period.

[0175] (3) In the first embodiment and the above-described modified examples, the characteristic output process is executed to set the intensities of each element characteristic included in the first characteristic and the second characteristic of the target user based on the operation history information and behavior history information acquired in step S201. However, separately from this, each element characteristic included in the first characteristic and the second characteristic set in the characteristic output process and its intensity may be updated based on the operation and behavior of the target user of the device 3 or the facility 5. This configuration can be realized, for example, as follows.

[0176] Specifically, at a predetermined timing, such as once a day, the estimation unit 124 refers to the first characteristic information and the second characteristic information of each user stored in the user information storage unit 132. The estimation unit 124 refers to operation information including the user ID of each user stored in the operation information storage unit 133. The estimation unit 124 also refers to sensor information stored in the sensor information storage unit 134, including a detection date and time that matches the operation date and time included in the operation information and the space ID of the space 40 in which the device 3 or facility 5 with the device ID included in the operation information is located.

[0177] For each element characteristic included in the first characteristic information of each user, if a characteristic action corresponding to the element characteristic has not been performed for a first predetermined time or longer, the estimation unit 124 excludes the element characteristic from the first characteristic or reduces the intensity of the element characteristic by a predetermined first reduction rate. Similarly, for each element characteristic included in the second characteristic information of each user, if a characteristic action corresponding to the element characteristic has not been performed for a second predetermined time or longer, the estimation unit 124 excludes the element characteristic from the second characteristic or reduces the intensity of the element characteristic by a predetermined second reduction rate. This makes it possible to exclude or reduce the intensity of an inappropriate element characteristic included in the first characteristic and second characteristic of each user, thereby relatively improving the intensity of element characteristics other than the inappropriate element characteristic included in the first characteristic and second characteristic.

[0178] The first and second predetermined times are, for example, three days, one week, one month, three months, or one year. The first and second predetermined times may be the same or different. The first and second decrease rates are, for example, 10%. The first and second decrease rates may be the same or different.

[0179] The first and second predetermined times may be determined based on the frequency with which a characteristic action corresponding to each element characteristic is performed. For example, when determining whether a characteristic action corresponding to the element characteristic "lazy" has not been performed for at least the first predetermined time (second predetermined time), the estimation unit 124 may determine that the characteristic action corresponding to the element characteristic "lazy" has not been performed for three days. In this case, the estimation unit 124 may next set the first predetermined time (second predetermined time) used to determine whether to exclude the element characteristic "lazy" or reduce the intensity of the element characteristic "lazy" to three days.

[0180] Furthermore, in this modified example, after the estimation unit 124 excludes each element characteristic from the first characteristic and the second characteristic, or after reducing the intensity of each element characteristic included in the first characteristic and the second characteristic, the intensity of each element characteristic included in the first characteristic and the second characteristic may be normalized.

[0181] Specifically, the estimation unit 124 may calculate a ratio of the intensity of each element characteristic included in the first characteristic to the sum of the intensities of one or more element characteristics included in the first characteristic after the exclusion or reduction process, and reset the ratio as the intensity of each element characteristic included in the first characteristic. Similarly, the estimation unit 124 may calculate a ratio of the intensity of each element characteristic included in the second characteristic to the sum of the intensities of one or more element characteristics included in the second characteristic after the exclusion or reduction process, and reset the ratio as the intensity of each element characteristic included in the second characteristic.

[0182] 12 is a diagram showing an example of a change in characteristic information. For example, FIG. 12 shows an example in which the characteristic output process was performed at time t12. Specifically, based on the first operation history information and the first behavior history information indicating the operations and behaviors of the device 3 or the facility 5 during the period from time t11 to time t12, the characteristic action corresponding to the candidate characteristic "neurotic" was executed "once." Therefore, the element characteristic "neurotic" was added to the first characteristic, and the strength of the element characteristic "neurotic" was calculated to be "1.0."

[0183] 12 shows an example in which the characteristic output process is performed at time t22 after time t12, and the element characteristic "cleanliness" is added to the first characteristic because the characteristic action corresponding to the candidate characteristic "cleanliness" was executed "once" based on the first operation history information and the first behavior history information corresponding to the operations and behaviors of the device 3 or facility 5 during the period from time t21 to time t22. As a result, the strength of the element characteristic "cleanliness" is calculated as "0.5 (= 1 time / (1 time + 1 time))," and the strength of the element characteristic "neurotic" is recalculated as "0.5 (= 1 time / (1 time + 1 time))."

[0184] 12 shows an example in which the characteristic output process is subsequently performed at times t32 and t42, the first characteristic information is updated, and then, at time t5, the element characteristic "neurotic" is removed from the first characteristic information because a characteristic action corresponding to the element characteristic "neurotic" has not been performed for a first predetermined time. Also, FIG. 12 shows an example in which, at time t5, the element characteristic "neurotic" is removed from the first characteristic information, and the intensities of the element characteristics "cleanliness" and "frugal" included in the first characteristic are reset to "0.67 (= 2 times / (2 times + 1 time))" and "0.33 (= 1 time / (2 times + 1 time))."

[0185] Figure 12 shows an example in which the characteristic output process is then performed at time t62, and the characteristic action corresponding to the target user's element characteristic "frugal" has been executed "once," so the intensities of the element characteristics "cleanliness" and "frugal" included in the first characteristic information are reset to "0.50 (= 2 times / (2 times + 2 times))" and "0.5 (= 2 times / (2 times + 2 times))."

[0186] (4) In the first embodiment and the above-described variants, an example was described in which the first characteristic is updated based on the operation and behavior of the target user's device 3 or facility 5 in a first environment where no other users are present, and the second characteristic is updated based on the operation and behavior of the target user's device 3 or facility 5 in a second environment where other users are present.

[0187] However, candidate characteristics (hereinafter, shared candidate characteristics) that can be element characteristics (hereinafter, shared element characteristics) that the target user is likely to have regardless of whether the target user is in the first environment or the second environment may be determined in advance. Then, when a characteristic action (hereinafter, shared characteristic action) corresponding to a shared candidate characteristic is included in the operation or behavior of the device 3 or facility 5 of the target user in at least one of the first environment and the second environment, the shared candidate characteristic may be estimated as a shared element characteristic included in both the first characteristic and the second characteristic, and added to the first characteristic and the second characteristic.

[0188] In this case, the strength of the shared element characteristic included in both the first characteristic and the second characteristic may be set based on the total number of times the shared characteristic action was performed in the operation and behavior of the device 3 or facility 5 of the target user, regardless of whether the target user was in the first environment or the second environment. This configuration can be realized, for example, as follows.

[0189] In step S205 (FIG. 5), the estimation unit 124 determines whether or not a shared characteristic action is included in any of the first operation history information, the first behavior history information, the second operation history information, and the second behavior history information.

[0190] If the estimation unit 124 determines that a shared characteristic action is included, it estimates the shared candidate characteristic as a shared element characteristic included in both the first characteristic and the second characteristic. Then, for any of the first characteristic and the second characteristic that does not include the same element characteristic as the shared candidate characteristic, the estimation unit 124 adds the shared candidate characteristic as a shared element characteristic included in both the first characteristic and the second characteristic.

[0191] In this case, the estimation unit 124 calculates the number of times the shared characteristic action has been performed (hereinafter referred to as the first number of times of performance) based on the first operation history information and the first behavior history information, and calculates the number of times the shared characteristic action has been performed (hereinafter referred to as the second number of times of performance) based on the second operation history information and the second behavior history information. When the number of times the shared characteristic action has been performed is not stored in the user information storage unit 132 in association with the user information of the target user, the estimation unit 124 stores the sum of the first number of times of performance and the second number of times of performance as the number of times the shared characteristic action has been performed in the user information storage unit 132 in association with the user information of the target user. When the number of times the shared characteristic action has been performed is stored in the user information storage unit 132 in association with the user information of the target user, the estimation unit 124 adds the sum of the first number of times of performance and the second number of times of performance to the number of times of performance.

[0192] Then, for the shared element characteristic included in the first characteristic, the estimation unit 124 uses the number of times the shared characteristic action has been executed that is stored in association with the user information of the target user, and for each of the other element characteristics included in the first characteristic, the estimation unit 124 uses the number of times the characteristic action corresponding to each of the other element characteristics that is stored in association with the first characteristic to calculate the strength of the shared element characteristic included in the first characteristic and each element characteristic, as in the first embodiment.

[0193] Similarly, for the shared element characteristic included in the second characteristic, the estimation unit 124 uses the number of times the shared characteristic action has been executed that is stored in association with the user information of the target user, and for each other element characteristic included in the second characteristic, the estimation unit 124 uses the number of times the characteristic action corresponding to each other element characteristic that is stored in association with the second characteristic to calculate the strength of the shared element characteristic and each element characteristic included in the second characteristic.

[0194] (5) In the above variant example (4), an example was described in which the strength of the shared element characteristic included in the first characteristic and the second characteristic is calculated using the sum of the number of times the shared characteristic action is executed (first execution count) calculated based on the first operation history information and the first behavior history information and the number of times the shared characteristic action is executed (second execution count) calculated based on the second operation history information and the second behavior history information.

[0195] In this case, the number of times the shared characteristic motion is executed is calculated based on the operations and actions of the target user of the device 3, etc. during the period in which the target user is present in the first environment and the second environment. In contrast, the number of times the characteristic motions corresponding to each of the other element characteristics included in the first characteristic and the second characteristic are calculated based on the operations and actions of the target user of the device 3, etc. during the period in which the target user is present in each of the first environment and the second environment, which is shorter than the period in which the number of times the shared characteristic motion is executed is calculated. Therefore, in each of the first characteristic and the second characteristic, the strength of the shared element characteristic is likely to be stronger than the strength of each of the other element characteristics.

[0196] Therefore, in the above-described modification (4), the strength of the shared element characteristic included in each of the first characteristic and the second characteristic may be set based on the number of times the shared characteristic action is performed, which is proportionally distributed depending on the period of time that the target user has been in each of the first and second environments. This configuration can be realized, for example, as follows.

[0197] In the configuration of the above-described modified example (4), the estimation unit 124 further calculates the elapsed time from the earliest date and time to the latest date and time among the operation dates and times included in the first operation history information and the first behavior history information as the time that the target user stayed in the first environment (hereinafter referred to as the first time). Similarly, the estimation unit 124 calculates the elapsed time from the earliest date and time to the latest date and time among the operation dates and times included in the second operation history information and the second behavior history information as the time that the target user stayed in the second environment (hereinafter referred to as the second time).

[0198] The estimation unit 124 divides the product of the sum of the first and second execution counts and the second execution count and the first time by the sum of the first and second times, and calculates the result as the number of executions of the shared characteristic action in the first environment. The estimation unit 124 divides the product of the sum of the first and second execution counts and the second time by the sum of the first and second times, and calculates the result as the number of executions of the shared characteristic action in the second environment.

[0199] When the number of times the shared characteristic action has been performed in the first environment (hereinafter referred to as the first shared execution count) is not stored in the user information storage unit 132 in association with the first characteristic information of the target user, the estimation unit 124 stores the calculated number of times the shared characteristic action has been performed in the first environment as the first shared execution count in association with the first characteristic information of the target user in the user information storage unit 132. When the first shared execution count is stored in the user information storage unit 132 in association with the first characteristic information of the target user, the estimation unit 124 adds the calculated number of times the shared characteristic action has been performed in the first environment to the first shared execution count.

[0200] Similarly, when the number of times the shared characteristic action has been performed in the second environment (hereinafter referred to as the second shared execution count) is not stored in the user information storage unit 132 in association with the second characteristic information of the target user, the estimation unit 124 stores the calculated number of times the shared characteristic action has been performed in the second environment as the second shared execution count in association with the second characteristic information of the target user in the user information storage unit 132. When the second shared execution count is stored in the user information storage unit 132 in association with the second characteristic information of the target user, the estimation unit 124 adds the calculated number of times the shared characteristic action has been performed in the second environment to the second shared execution count.

[0201] Then, the estimation unit 124 calculates the strength of the shared element characteristic included in the first characteristic and each element characteristic using the first shared execution count stored in association with the first characteristic information for the shared element characteristic included in the first characteristic, and using the execution count of the characteristic operation corresponding to each of the other candidate characteristics stored in association with the first characteristic information for each of the other element characteristics included in the first characteristic, as in the first embodiment.

[0202] Similarly, the estimation unit 124 calculates the strength of the shared element characteristic included in the second characteristic and each element characteristic by using the second shared execution count stored in association with the second characteristic information for the shared element characteristic included in the second characteristic, and by using the execution count of the characteristic action corresponding to each of the other candidate characteristics stored in association with the second characteristic information for each of the other element characteristics included in the second characteristic.

[0203] (6) In the above variant example (4), an example was described in which, when a shared characteristic action corresponding to a predetermined shared candidate characteristic is performed at least once in the operation and behavior of the device 3, etc. by the target user, the shared candidate characteristic is estimated as a shared element characteristic included in both the first characteristic and the second characteristic.

[0204] Alternatively, however, the estimation unit 124 may refer to the first characteristic information and the second characteristic information of each user stored in the user information storage unit 132 at a predetermined timing, for example, once a day. Then, when the same element characteristic having similar strength exists between the first characteristic and the second characteristic, the estimation unit 124 may estimate the same element characteristic as a shared element characteristic included in both the first characteristic and the second characteristic.

[0205] The same element characteristic with similar intensity refers to an element characteristic with intensity matching within a predetermined range. For example, if the intensity of the element characteristic “lazy” included in the first characteristic matches the intensity of the element characteristic “lazy” included in the second characteristic within a predetermined range (e.g., 0.01), the estimation unit 124 may estimate the element characteristic “lazy” as a shared element characteristic included in both the first characteristic and the second characteristic.

[0206] Furthermore, the operations and actions of the devices 3 or facilities 5 performed by each user may include similar characteristic actions, which are operations or actions (hereinafter, characteristic actions) of the devices 3 or facilities 5 that exhibit one or more characteristic groups included in the first rule information (FIGS. 8 and 9) and are characteristic actions that are similar in the number of times they are performed per unit time in the first environment and the second environment. In this case, the estimation unit 124 may estimate a candidate characteristic corresponding to the characteristic group indicated by the similar characteristic action as a shared element characteristic included in both the first characteristic and the second characteristic of each user. Similarity in the number of times they are performed per unit time means that the number of times they are performed per unit time matches within a predetermined range. Similar characteristic actions can be identified, for example, as follows.

[0207] Specifically, similar to step S201, the estimation unit 124 acquires operation information (hereinafter, past operation information) including the user ID of each user from the operation information storage unit 133, and acquires sensor information (hereinafter, past behavior information) including a detection date and time that matches the operation date and time included in the past operation information from the sensor information storage unit 134.

[0208] The estimation unit 124 compares the detection information included in the past behavior information with the matching data stored in the user information storage unit 132 to identify one or more people present in the space 40 indicated by the detection information.

[0209] When the estimation unit 124 determines that only one user of each type is present in the space 40 indicated by the detection information, it acquires past behavior information including the detection information as information indicating the behavior of each user in the first environment (hereinafter, referred to as first past behavior information). On the other hand, it is assumed that the estimation unit 124 determines that each user and a user with a different user ID from each user are present in the space 40 indicated by the detection information, or that each user and a person who cannot be identified using matching data are present. In these cases, the estimation unit 124 acquires past behavior information including the detection information as information indicating the behavior of each user in the second environment (hereinafter, referred to as second past behavior information).

[0210] The estimation unit 124 refers to the device information stored in the device information storage unit 131, and acquires past operation information that includes the device ID of the device 3 or facility 5 that is located in the same space 40 as the sensor 7 with the sensor ID included in the first past behavior information, and that includes an operation date and time that matches the detection date and time included in the first past behavior information, as information indicating the operation of the device 3 or facility 5 by each user in the first environment (hereinafter, referred to as first past operation information).

[0211] Similarly, the estimation unit 124 refers to the device information stored in the device information storage unit 131, and acquires past operation information that includes the device ID of the device 3 or facility 5 that is located in the same space 40 as the sensor 7 with the sensor ID included in the second past behavior information, and that includes an operation date and time that matches the detection date and time included in the second past behavior information, as information indicating the operation of the device 3 or facility 5 by each user in the second environment (hereinafter, referred to as second past operation information).

[0212] The estimation unit 124 calculates the number of times each characteristic action corresponding to each characteristic group included in the first rule information ( FIGS. 8 and 9 ) is executed per unit time in the operations and actions of each user in the first environment indicated by the first past operation information and the first past behavior information, as the number of times each characteristic action is executed per unit time in the first environment. The estimation unit 124 calculates the number of times each characteristic action corresponding to each characteristic group included in the first rule information ( FIGS. 8 and 9 ) is executed per unit time in the operations and actions of each user in the second environment indicated by the second past operation information and the second past behavior information, as the number of times each characteristic action is executed per unit time in the second environment.

[0213] The estimation unit 124 determines, for each characteristic motion, whether the number of times the characteristic motion is performed per unit time in the first environment and the number of times the characteristic motion is performed per unit time in the second environment match within a predetermined range. The estimation unit 124 identifies, in the determination, a characteristic motion that is determined to match within the predetermined range as a similar characteristic motion.

[0214] (7) In the first embodiment and the above-described modified examples (1) to (6), an example was described in which a second characteristic, which is a characteristic of a target user in a second environment where other users are present, was estimated. However, for example, if the other users are family members of the target user, the target user tends to exhibit the same characteristics as when the target user is alone. However, if the other users are users other than the target user's family, the target user is likely to exhibit characteristics that show consideration for other users. In this way, the characteristics of the target user in the second environment are likely to differ to some extent depending on the attributes of the other users present in the second environment.

[0215] Therefore, the estimation unit 124 may estimate a characteristic (third characteristic) of the target user who exists in an environment (hereinafter, third environment) in which other users with each attribute exist in the second environment, for each of one or more attributes of other users different from the target user, based on the operation and behavior of the device 3 or facility 5 of the target user in the third environment. Then, the output unit 125 may output information indicating the characteristic of the target user who exists in the third environment.

[0216] For example, the characteristics of the target user in a third environment where other users with attribute "A" exist may be estimated based on the operation and behavior of the target user's device 3 or facility 5 in the third environment, and information indicating the characteristics may be output. Also, the characteristics of the target user in the third environment where other users with attribute "B" exist may be estimated based on the operation and behavior of the target user's device 3 or facility 5 in the third environment, and information indicating the characteristics may be output.

[0217] This configuration can be realized, for example, as follows.

[0218] In step S205, the estimation unit 124 further acquires, from the second operation history information, third operation history information corresponding to each attribute for one or more attributes of the other users.

[0219] Specifically, the estimation unit 124 acquires attribute information contained in the user information of other users different from the target user stored in the user information storage unit 132, and extracts, for example, one or more attributes that overlap with a predetermined number or more of other users.

[0220] The estimation unit 124 performs the following process for each of the one or more attributes. The estimation unit 124 references the user information and matching data stored in the user information storage unit 132, and extracts sensor information including detection information indicating information related to the space 40 where other users with each attribute exist, from the second behavior history information. The estimation unit 124 acquires the sensor information as information indicating the behavior of the target user in the second environment where other users with each attribute exist (hereinafter, referred to as third behavior history information corresponding to each attribute).

[0221] Furthermore, the estimation unit 124 refers to the device information stored in the device information storage unit 131, and extracts, from the second operation history information, operation information including an operation date and time that matches a detection date and time included in the third behavior history information corresponding to each attribute, and the device ID of the device 3 or facility 5 that is placed in the space 40 in which the sensor 7 with the sensor ID included in the third behavior history information is placed. The estimation unit 124 acquires the operation information as information indicating operations of the device 3 or facility 5 by the target user in a second environment in which other users with each attribute are present (hereinafter, referred to as third operation history information corresponding to each attribute).

[0222] The estimation unit 124 then estimates candidate traits corresponding to characteristic actions that have been performed one or more times and are included in the third operation history information and the third behavior history information corresponding to each attribute as element traits of the traits of the target user who exists in the third environment where other users with each attribute exist (hereinafter, referred to as the third traits corresponding to each attribute). Similarly to step S206 ( FIG. 5 ) in the first embodiment, the estimation unit 124 calculates the strength of each element trait included in the third trait corresponding to each attribute, and stores information indicating the third trait corresponding to each attribute in the user information storage unit 132 as trait information of the target user.

[0223] In this case, the output unit 125 outputs information indicating the third characteristic corresponding to each attribute, similar to step S300 ( FIG. 3 ). Specifically, the output unit 125 transmits (outputs) the information indicating the third characteristic corresponding to each attribute to a predetermined external device such as the output device 6 using the communication circuit 11.

[0224] (8) In the first embodiment and the above-described modified examples (1) to (7), the examples have been described in which the intensity of each element characteristic included in the first characteristic and the second characteristic is set. However, in step S206 ( FIG. 5 ), the estimation unit 124 may not set the intensity of each element characteristic, so that the intensity of each element characteristic is not included in the first characteristic information and the second characteristic information.

[0225] Second Embodiment A second embodiment of the present disclosure will be described below. In the second embodiment, a service to be provided to each user is determined based on characteristic information that indicates the characteristics of each user according to the environment in which each user exists, and the determined service is executed.

[0226] Specifically, in the second embodiment, the processor 12 further functions as a determination unit 126 and an execution unit 127 ( FIG. 2 ). When a user is in a first environment, the determination unit 126 determines a service to be provided to the user based on first characteristic information of the user. When a user is in a second environment, the determination unit 126 determines a service to be provided to the user based on second characteristic information of the user. The execution unit 127 executes the service determined by the determination unit 126.

[0227] (Flow of service provision processing) The flow of the service provision processing performed in the information processing device 1 of the second embodiment will be described below. The service provision processing is processing in which a user who has been pre-registered as a target of the service provision processing is provided with a service suited to the characteristics of the user in the environment in which the user exists. FIG. 13 is a flowchart showing an example of the service provision processing. The service provision processing is executed at a predetermined timing. The predetermined timing is, for example, every hour, every half day, every day, every week, or every month. Hereinafter, the user who is the target of the service provision processing will be referred to as the target user, as in the first embodiment.

[0228] First, in step S400, the determination unit 126 acquires characteristic information of the target user according to the environment in which the target user currently exists.

[0229] Specifically, the determination unit 126 refers to matching data including the user ID of the target user stored in the user information storage unit 132, and acquires sensor information including detection information related to the space 40 in which the target user exists from the sensor information storage unit 134. The determination unit 126 acquires, from the acquired sensor information, sensor information including the most recent detection date and time as information indicating the behavior of the target user in the space 40 in which the target user currently exists (hereinafter, fourth environment) (hereinafter, current environment information). In other words, the current environment information is an example of third information of the present disclosure.

[0230] The determination unit 126 determines whether the fourth environment is the first environment or the second environment based on the current environment information.

[0231] Specifically, the determination unit 126 identifies one or more people present in the fourth environment by comparing the inspection information included in the current environment information with the matching data stored in the user information storage unit 132.

[0232] If the determination unit 126 determines that only one target user exists in the fourth environment, it determines that the fourth environment is the first environment and obtains the first characteristic information of the target user from the user information storage unit 132.

[0233] On the other hand, if the determination unit 126 determines that the target user and a person who cannot be identified using the matching data exist in the fourth environment, it determines that the fourth environment is the second environment and obtains the second characteristic information of the target user from the user information storage unit 132.

[0234] Furthermore, if the determination unit 126 determines that the target user and a user with a different user ID from the target user exist in the fourth environment, it determines that the fourth environment is the second environment and obtains the second characteristic information of the target user from the user information storage unit 132.

[0235] As shown in the above-described modification example (7), it is assumed that third characteristic information corresponding to each attribute is stored in the user information storage unit 132. In this case, the determination unit 126 may refer to attribute information included in user information of a user whose user ID is different from that of the target user, which is stored in the user information storage unit 132. Then, the determination unit 126 may determine whether third characteristic information corresponding to the attribute indicated by the attribute information is stored in the user information storage unit 132. Then, if the determination unit 126 determines that the third characteristic information is stored, it may determine that the fourth environment is a third environment in which another user with the attribute exists, and may acquire the third characteristic information from the user information storage unit 132.

[0236] Hereinafter, the first characteristic information, the second characteristic information, or the third characteristic information acquired by the determination unit 126 in step S400 will be collectively referred to as target characteristic information. Furthermore, the characteristic of the target user indicated by the target characteristic information will be referred to as target characteristic.

[0237] Next, in step S500, the determination unit 126 determines a service to be provided to the target user based on the target characteristic information acquired in step S400.

[0238] Specifically, in step S500, the determination unit 126 obtains second rule information from the rule information storage unit 135, which defines the relationship between one or more element characteristic groups indicating one or more element characteristics and one or more provided services.

[0239] FIG. 14 is a diagram illustrating an example of second rule information. In the second rule information illustrated in FIG. 14, three element characteristic groups each representing two element characteristics are associated with provided services to be provided to users of target characteristics that include each element characteristic group. For example, in the second rule information illustrated in FIG. 14, an element characteristic group representing two element characteristics, "frugal" and "regular," is associated with a provided service "prediction of when consumables will be consumed." The provided service "prediction of when consumables will be consumed" is a service that predicts when consumables will be consumed (their lifespans) by devices 3 or facilities 5 that a target user has used in the past, and outputs information indicating the prediction results.

[0240] In the second rule information, the number of element characteristics included in the element characteristic group associated with the provided service is not limited to two, but may be one or three or more.

[0241] If the target characteristic includes one or more element characteristic groups included in the second rule information, the determination unit 126 identifies one or more provided services corresponding to the one or more element characteristic groups, and determines the identified one or more provided services as the services to be provided to the target user.

[0242] For example, suppose the target characteristics include three element characteristics: "frugal," "regular," and "tidy." In this case, the determination unit 126 determines, as the service to be provided to the target user, the provided service "prediction of when consumables will be consumed," which is associated with the element characteristic group indicating the two element characteristics, "frugal," and "regular," in the second rule information shown in FIG. 14 .

[0243] Furthermore, the determination unit 126 determines, as the service to be provided to the target user, the provided service "Life Tips Suggestion," which is associated with the element characteristic group indicating two element characteristics, "Frugal" and "Cleanliness," in the second rule information shown in Fig. 14. The provided service "Life Tips Suggestion" is a service that outputs information related to a space 40 in which the target user is present more frequently than a predetermined frequency.

[0244] Note that the method for determining the service in step S500 is not limited to this. For example, the determination unit 126 may further determine the service to be provided to the target user based on the strength of each element characteristic included in the target characteristic information, as shown below.

[0245] Specifically, in step S500, the determination unit 126 identifies one or more provided services (first provided service, second provided service) that are associated with one or more element characteristic groups included in the target characteristic in the second rule information, as described above. The determination unit 126 identifies the identified one or more provided services as candidate services (hereinafter, service candidates) to be provided to the target user.

[0246] The determining unit 126 acquires, from the rule information storage unit 135, third rule information that associates one or more provided services, a coefficient assigned to each provided service, and a service field to which each provided service belongs.

[0247] Fig. 15 is a diagram showing an example of a portion of the third rule information. Fig. 16 is a diagram showing an example of the remaining portion of the third rule information. In the third rule information shown in Fig. 15, 13 provided services are associated with coefficients assigned to each provided service and the service field to which each provided service belongs, and further associated with the type of each provided service.

[0248] 15 , the type of provided service "notification," the provided service "to-do list notification," the coefficient "0.1" assigned to the provided service, and the service category "life (general)" to which the provided service belongs are associated with each other. The provided service "to-do list notification" is a service that outputs a to-do list of a target user stored in the user information storage unit 132.

[0249] In the third rule information shown in FIG. 16, five provided services are associated with a coefficient assigned to each provided service and the service field to which each provided service belongs, and further associated with the type of each provided service.

[0250] For example, in the third rule information shown in Figure 16, the type of provided service "outsourcing", the provided service "delivery (meals, food)", the coefficient "0.1" assigned to the provided service, and the service field "lifestyle (food)" to which the provided service belongs are associated. The provided service "delivery (meals, food)" is a service that outputs information guiding the target user to access a website for using a delivery service that the target user has used in the past.

[0251] The determination unit 126 refers to the third rule information and calculates, for each of the one or more provided services included in the service candidates, the product (first product, second product) of the sum of the intensities of one or more element characteristics included in the target characteristic and indicated by the element characteristic group corresponding to each provided service and the coefficient assigned to each provided service.

[0252] For example, as in the above specific example, suppose the target characteristics include three element characteristics: "frugal," "regular," and "clean." Furthermore, suppose the strengths of these element characteristics are "0.2," "0.3," and "0.5," respectively. Based on this, the determining unit 126 refers to the second rule information and identifies two provision services, "prediction of when consumables will be consumed" and "suggestion of lifestyle tips," as candidate services.

[0253] In this case, for the provided service "Prediction of when consumables will be used up" included in the service candidates, the determination unit 126 calculates the product "0.05 (= 0.1 x 0.5)" of the sum of the intensities of the two element characteristics "frugal" and "regular" indicated by the element characteristic group corresponding to the provided service "Prediction of when consumables will be used up" included in the target characteristics, which is "0.5 (= 0.2 + 0.3)", and the coefficient "0.1" assigned to the provided service "Prediction of when consumables will be used up".

[0254] In addition, for the provided service "Lifestyle Tips Suggestions" included in the service candidates, the determination unit 126 calculates the product "0.07 (= 0.1 x 0.7)" of the sum of the intensities of the two element characteristics "frugal" and "clean freak" indicated by the element characteristic group corresponding to the provided service "Lifestyle Tips Suggestions" included in the target characteristic information, which is "0.7 (= 0.2 + 0.5)", and the coefficient "0.1" assigned to the provided service "Lifestyle Tips Suggestions".

[0255] Then, the determination unit 126 refers to the third rule information, and for each of one or more service fields to which one or more provided services included in the service candidates belong, if the sum of at least one of the products calculated for at least one provided service included in the service candidates that belongs to each service field is equal to or greater than a first predetermined value, determines that at least one provided service as the service to be provided to the target user.

[0256] For example, suppose the candidate services include three provided services: "Device or facility alert notification," "Consumable supply consumption prediction," and "Lifestyle tips suggestion." Also, suppose the products calculated for these provided services are "0.03," "0.05," and "0.07," respectively.

[0257] In this case, for each of the two service categories "Equipment or Equipment" and "Life (Housework)" to which the three provided services included in the service candidates, "Equipment or Facility Alert Notification," "Prediction of When Consumable Items Will Be Used," and "Life Tips Suggestion," belong, if the sum of at least one of the products calculated for at least one provided service included in the service candidates that belongs to each service category is equal to or greater than a first predetermined value, the determination unit 126 determines that at least one provided service will be provided to the target user.

[0258] Specifically, for the service field "equipment or equipment," if the sum of the two products "0.03" and "0.05" calculated for the two provided services included in the service candidates that belong to the service field "equipment or equipment," "alert notification for equipment or equipment" and "prediction of when consumables will be used up," which are "0.08 (=0.03 + 0.05)," is equal to or greater than a first predetermined value, the determination unit 126 determines that the two provided services, "alert notification for equipment or equipment" and "prediction of when consumables will be used up," will be the services to be provided to the target user.

[0259] Furthermore, for the service field "Lifestyle (housework)", if the sum "0.07" of one product "0.07" calculated for one provided service "Lifestyle TIPS Suggestion" included in the service candidates belonging to the service field "Lifestyle (housework)" is equal to or greater than a first predetermined value, the determination unit 126 determines that the one provided service "Lifestyle TIPS Suggestion" is the service to be provided to the target user.

[0260] Next, in step S600, the execution unit 127 executes one or more services determined in step S500 as services to be provided to the target user.

[0261] Specifically, in step S600, the execution unit 127 acquires fourth rule information from the rule information storage unit 135, which associates one or more provided services with the execution timing of each provided service and the execution method of each provided service.

[0262] The execution timing of the provided service includes, for example, the start time of the provided service (e.g., 12:00, immediately, etc.), the time interval at which the provided service is repeated (e.g., every hour), the number of times the provided service is repeated (e.g., three times), etc.

[0263] The execution method of the provided service includes, for example, an output destination and output instructions for information output by the execution of the provided service (hereinafter, referred to as output information of the provided service). The output information of the provided service includes, for example, information specific to the target user, such as the user's to-do list, schedule, vital data, etc., control information for the device 3 or facility 5, information requesting the execution of a service provided by the service server 8, etc.

[0264] The destination of the output information of the provided service includes, for example, the output device 6 used by the target user, the service server 8, the equipment 3 or facility 5 indicated by the output information of the provided service, etc. The output instruction of the output information of the provided service includes, for example, an instruction to display the output information of the provided service, an instruction to output it as audio, an instruction to store it, an instruction to transfer it, an instruction to execute it, etc.

[0265] The execution unit 127 refers to the fourth rule information and executes the execution program for each provided service stored in the memory 13 at the execution timing for each provided service determined in step S500. The execution unit 127 refers to the fourth rule information and outputs the output information for each provided service to the output destination determined by the execution method for each provided service, together with the output instruction determined by the execution method for each provided service. As a result, the output information for each provided service is output to the output destination in accordance with the output instruction.

[0266] The following modifications can be adopted to the configuration of the second embodiment.

[0267] (1) In the configuration of the second embodiment, if there are multiple users who are pre-registered as targets of the service provision process in the same space 40, the service provision process is executed for each of the multiple users as a target user.

[0268] As a result, when the determination unit 126 determines a provided service to be provided to each target user based on the second characteristic information of each target user, the determined multiple provided services (second services) may include multiple provided services "automatic control of devices or facilities." The provided service "automatic control of devices or facilities" is a service that automatically controls devices 3 or facilities 5 present in the space 40 where the user is present, according to the characteristics of the user. In this case, when the execution unit 127 executes the multiple provided services "automatic control of devices or facilities," there is a risk that the content of the automatic control of the devices 3 or facilities 5 will conflict with each other.

[0269] For example, suppose that user A and user B are present in the same space 40, and a service provision process is executed with each of the two users as a target user. In this case, suppose that the determination unit 126 determines the service to be provided to user A to be "automatic control of equipment or facilities" based on the element characteristic "sensitive to heat" included in user A's second characteristic. Similarly, suppose that the determination unit 126 determines the service to be provided to user B to be "automatic control of equipment or facilities" based on the element characteristic "sensitive to cold" included in user B's second characteristic.

[0270] In this case, in the configuration of the second embodiment, the execution unit 127 executes the provided service "automatic control of devices or facilities" to be provided to user A, thereby outputting control information to the air conditioner to set the set temperature of the air conditioner in the space 40 where user A is present to 25 degrees Celsius in accordance with user A's element characteristic "sensitive to heat." Furthermore, the execution unit 127 executes the provided service "automatic control of devices or facilities" to be provided to user B, thereby outputting control information to the air conditioner to set the set temperature of the air conditioner in the space 40 where user B is present to 27 degrees Celsius in accordance with user B's element characteristic "sensitive to cold." As a result, the set temperatures, which are parameters used for the automatic control of the air conditioners in the spaces 40 where users A and B are present, conflict with each other.

[0271] Therefore, as described above, if the multiple provided services determined by the determination unit 126 include multiple provided services of "automatic control of equipment or facilities," the execution unit 127 may average the parameters used for automatic control of equipment 3 or facility 5 by the multiple provided services of "automatic control of equipment or facilities."

[0272] For example, in the above example, the execution unit 127 may average the set temperature, which is a parameter used for automatic control of the air conditioner by the provided service "automatic control of equipment or facilities" provided to user A and user B, to 26 degrees (= (25 degrees + 27 degrees) / 2), and execute the provided service.

[0273] (2) As in the variant example (1) of the second embodiment, when the plurality of provision services determined by the determination unit 126 include a plurality of provision services “automatic control of devices or facilities,” the execution unit 127 may obtain a priority assigned in advance to each of a plurality of users to whom the plurality of provision services “automatic control of devices or facilities” are to be provided.

[0274] Specifically, the user information storage unit 132 may store a priority assigned in advance to each user of the information processing system 100. For example, the priority may be assigned so that the more one or more element characteristics (e.g., lazy, spendthrift) included in the user's second characteristics are less acceptable to users with one or more element characteristics different from the one or more element characteristics (e.g., not lazy, not spendthrift), the higher the priority. However, the method of assigning a priority to each user is not limited to this. The execution unit 127 may acquire, from the user information storage unit 132, a priority assigned in advance to each of multiple users to whom the above-mentioned multiple provided services "automatic control of devices or facilities" are to be provided.

[0275] In this case, the execution unit 127 may execute the service determined as the service to be provided to the user with the highest priority among the plurality of users, from among the plurality of provided services, "automatic control of equipment or facilities."

[0276] (3) As in the variant example (1) of the second embodiment, when the plurality of provision services determined by the determination unit 126 include a plurality of provision services “automatic control of devices or facilities,” the execution unit 127 may execute the service that is most numerous among the plurality of provision services “automatic control of devices or facilities.”

[0277] For example, suppose that the determination unit 126 determines the service to be provided to user A to be "automatic control of equipment or facilities" based on the element characteristic "sensitive to heat" included in the second characteristic of user A, and determines the service to be provided to user B to be "automatic control of equipment or facilities" based on the element characteristic "sensitive to cold" included in the second characteristic of user B. Also, suppose that the determination unit 126 determines the service to be provided to user C to be "automatic control of equipment or facilities" based on the element characteristic "sensitive to heat" included in the second characteristic of user C who exists in the same environment as users A and B.

[0278] In this case, the execution unit 127 may execute the most popular provided service among the three provided services, "automatic control of equipment or facilities," i.e., a service that outputs control information to the air conditioner to set the set temperature of the air conditioner in the space 40 where the user is located to 25 degrees, based on the element characteristic "sensitive to heat."

[0279] (4) A priority may be assigned in advance to each of one or more element characteristic groups included in the second rule information ( FIG. 14 ). For example, the priority may be assigned so that one or more element characteristics (e.g., lazy, spendthrift) indicated by an element characteristic group are less acceptable to users of one or more element characteristics (e.g., not lazy, not spendthrift) indicated by a different element characteristic group.

[0280] Then, as in the variant example (1) of the second embodiment, when the plurality of provision services determined by the determination unit 126 include a plurality of provision services "automatic control of devices or facilities," the execution unit 127 may obtain a priority associated with each of one or more element characteristic groups included in the second rule information (FIG. 14).

[0281] Then, the execution unit 127 may execute the provision service "automatic control of equipment or facilities" that is associated with the element characteristic group with the lowest priority among the above-mentioned multiple provision services "automatic control of equipment or facilities" determined by the determination unit 126.

[0282] For example, in the second rule information of this modified example, a set of element characteristics indicating two element characteristics, "lazy" and "spendthrift," is associated with a provided service, "automatic control of equipment or facilities," and a priority level, "1." Also, a set of element characteristics indicating two element characteristics, "regular" and "frugal," is associated with a provided service, "automatic control of equipment or facilities," and a priority level, "2."

[0283] Here, as in variant example (1) of the second embodiment, the multiple provided services determined by the determination unit 126 include a provided service "automatic control of equipment or facilities" corresponding to a group of element characteristics indicating two element characteristics "lazy" and "spendthrifty," and a provided service "automatic control of equipment or facilities" corresponding to a group of element characteristics indicating two element characteristics "orderly" and "frugal."

[0284] In this case, the executing unit 127 may acquire a priority associated with each of one or more element characteristic groups included in the second rule information. Then, the executing unit 127 may execute the provided service "automatic control of equipment or facilities" associated with the element characteristic group indicating the two element characteristics "lazy" and "spendthrift" that have the lowest priority of "1" among the plurality of provided services "automatic control of equipment or facilities" determined by the determining unit 126.

[0285] In addition, the present disclosure may be implemented by arbitrarily combining the above-described first embodiment, modified examples (1) to (8) of the first embodiment, second embodiment, and modified examples (1) to (4) of the second embodiment.

[0286] The present disclosure is useful in providing services according to the characteristics of a user in both cases where other users are present in the same environment as the user and where they are not.

Claims

1. An information processing method for estimating a user's characteristics in a computer, comprising: acquiring information indicating device operations and actions of the target user during a first predetermined period as first information indicating device operations and actions of the target user to be estimated; acquiring information indicating a history of the presence or absence of other users different from the target user in the environment where the target user is present during the first predetermined period as second information indicating the presence or absence of other users different from the target user in the environment where the target user is present; extracting, based on the first information and the second information, first operation information indicating at least one of a device operation and a behavior of the target user in a first environment in which the other user is not present, and second operation information indicating at least one of a device operation and a behavior of the target user in a second environment in which the other user is present; estimating a first characteristic that is a characteristic of the target user present in the first environment based on the first motion information, and estimating a second characteristic that is a characteristic of the target user present in the second environment based on the second motion information; outputting at least one of first characteristic information indicating the first characteristic and second characteristic information indicating the second characteristic; Information processing methods.

2. In estimating the first characteristic and the second characteristic, acquire first rule information that defines a relationship between one or more candidate characteristics and one or more feature groups that indicate characteristics of device operation or behavior of the target user; When the first operation information includes a device operation or behavior indicating one or more first feature groups included in the one or more feature groups, one or more first candidate features corresponding to the one or more first feature groups are identified from the one or more candidate features, and the identified one or more first candidate features are estimated as the first feature; When the second operation information includes a device operation or behavior indicating one or more second feature groups included in the one or more feature groups, one or more second candidate features corresponding to the one or more second feature groups are identified from the one or more candidate features, and the identified one or more second candidate features are estimated as the second feature. The information processing method according to claim 1 .

3. the first characteristic includes one or more first element characteristics; the second characteristic includes one or more second element characteristics; further, for each of the one or more first element characteristics, based on the first operation information, calculating the number of times a first characteristic action has been performed, the first characteristic action being a device operation or behavior that exhibits a feature group corresponding to each first element characteristic, and setting the calculated number of times the first characteristic action has been performed as a strength of each first element characteristic; further, for each of the one or more second element characteristics, based on the second operation information, calculating the number of times a second characteristic action has been performed, the second characteristic action being a device operation or behavior that exhibits a feature group corresponding to each second element characteristic, and setting the calculated number of times the second characteristic action has been performed as a strength of each second element characteristic; the first characteristic information includes an intensity of each first element characteristic; the second characteristic information includes an intensity of each second element characteristic; The information processing method according to claim 2 .

4. In setting the strength of each first element characteristic and each second element characteristic, Furthermore, third operation information indicating device operations and actions of one or more other users different from the target user is acquired; calculating a first average value, which is an average value of the number of times the first characteristic motion is performed per predetermined time by each of the one or more other users, based on the third motion information; calculating a first execution count, which is the number of times the first characteristic motion is performed per predetermined time, based on the first motion information; and setting a result obtained by dividing the first execution count by the first average value as a strength of each first element characteristic; calculating a second average value, which is an average value of the number of times the second characteristic motion is performed per predetermined time period by each of the one or more other users, based on the third motion information; calculating a second execution count, which is the number of times the second characteristic motion is performed per predetermined time period, based on the second motion information; and setting a result obtained by dividing the second execution count by the second average value as the strength of each second element characteristic. The information processing method according to claim 3 .

5. In estimating the first characteristic and the second characteristic, When at least one of the first operation information and the second operation information includes a shared characteristic operation that is a device operation or behavior that shows a group of characteristics corresponding to a predetermined shared candidate characteristic from among the one or more candidate characteristics, the shared candidate characteristic is estimated as a shared element characteristic included in both the first characteristic and the second characteristic; In setting the strength of each first element characteristic and each second element characteristic, calculating a first execution count, which is the number of times the shared characteristic motion is executed, based on the first motion information; calculating a second execution count, which is the number of times the shared characteristic motion is executed, based on the second motion information; and setting a sum of the first execution count and the second execution count as the strength of the shared element characteristic. The information processing method according to claim 3 .

6. In estimating the first characteristic and the second characteristic, When at least one of the first operation information and the second operation information includes a shared characteristic operation that is a device operation or behavior that shows a group of characteristics corresponding to a predetermined shared candidate characteristic from among the one or more candidate characteristics, the shared candidate characteristic is estimated as a shared element characteristic included in both the first characteristic and the second characteristic; In setting the strength of each first element characteristic and each second element characteristic, calculating a first time period during which the target user stayed in the first environment based on the first motion information, and calculating a second time period during which the target user stayed in the second environment based on the second motion information; calculating a first execution count, which is the number of times the shared characteristic motion is executed, based on the first motion information; and calculating a second execution count, which is the number of times the shared characteristic motion is executed, based on the second motion information; a product of the sum of the first execution count and the second execution count and the first time divided by the sum of the first time and the second time, the result being set as a strength of the shared element characteristic included in the first characteristic; a result obtained by dividing the product of the sum of the first execution count and the second execution count and the second time by the sum of the first time and the second time is set as the strength of the shared element characteristic included in the second characteristic; The information processing method according to claim 3 .

7. Furthermore, if there is an identical element characteristic whose strength is similar between the first characteristic and the second characteristic, the identical element characteristic is estimated as the shared element characteristic. The information processing method according to claim 5 .

8. Furthermore, when the first information includes a similar characteristic action, which is a device operation or behavior that indicates any of the one or more characteristic groups and is performed a similar number of times per unit time in each of the first environment and the second environment, a candidate characteristic corresponding to the characteristic group indicated by the similar characteristic action is estimated as the shared element characteristic. The information processing method according to claim 5 .

9. Furthermore, for each of the one or more first element characteristics, if a device operation or behavior exhibiting a feature group corresponding to each first element characteristic has not been performed for a first predetermined time or longer, the intensity of each first element characteristic is reduced at a first reduction rate; Furthermore, for each of the one or more second element characteristics, if a device operation or behavior exhibiting a feature group corresponding to each second element characteristic has not been performed for a second predetermined time or longer, the intensity of each second element characteristic is reduced at a second reduction rate. The information processing method according to any one of claims 3 to 8.

10. Furthermore, for each of the one or more first element characteristics, a ratio of the intensity of each first element characteristic to a sum of the intensities of the one or more first element characteristics is calculated, and the calculated ratio is set as the intensity of each first element characteristic; further, for each of the one or more second element characteristics, a ratio of the intensity of each second element characteristic to a sum of the intensities of the one or more second element characteristics is calculated, and the calculated ratio is set as the intensity of each second element characteristic; The information processing method according to any one of claims 3 to 8.

11. Furthermore, for each of the one or more first element characteristics, a ratio of the intensity of each first element characteristic to a sum of the intensities of the one or more first element characteristics is calculated, and the calculated ratio is set as the intensity of each first element characteristic; further, for each of the one or more second element characteristics, a ratio of the intensity of each second element characteristic to a sum of the intensities of the one or more second element characteristics is calculated, and the calculated ratio is set as the intensity of each second element characteristic; The information processing method according to claim 9.

12. Furthermore, for each of the one or more first element characteristics, if a device operation or behavior showing a feature group corresponding to each first element characteristic has not been performed for a first predetermined time or more, the first element characteristic is excluded from the first characteristics; Furthermore, when a device operation or behavior exhibiting a feature group corresponding to each of the one or more second element characteristics is not performed for a second predetermined time or longer, each of the second element characteristics is excluded from the second characteristics. The information processing method according to claim 2 .

13. Furthermore, information indicating one or more attributes of the other user is acquired, Further, for each of the one or more attributes, fourth operation information indicating device operations and actions of the target user in a third environment in which the other users having each attribute are present is extracted from the second operation information, a third characteristic that is a characteristic of the target user present in the third environment is estimated based on the fourth operation information, and third characteristic information regarding the third characteristic is output. The information processing method according to claim 1 .

14. An information processing device that estimates a user's characteristics, a first acquisition unit that acquires first information indicating device operations and behaviors of a target user to be estimated over a predetermined period of time; a second acquisition unit that acquires second information indicating whether or not there is a user other than the target user in an environment where the target user exists; an extracting unit that extracts, based on the first information and the second information, first operation information indicating at least one of a device operation and an action of the target user in a first environment where the other user is not present, and second operation information indicating at least one of a device operation and an action of the target user in a second environment where the other user is present; an estimation unit that estimates a first characteristic that is a characteristic of the target user present in the first environment based on the first action information, and estimates a second characteristic that is a characteristic of the target user present in the second environment based on the second action information; an output unit that outputs at least one of first characteristic information indicating the first characteristic and second characteristic information indicating the second characteristic; An information processing device comprising:

15. A program that causes a computer to function to estimate a user's characteristics, The computer a first acquisition unit that acquires first information indicating device operations and behaviors of a target user to be estimated over a predetermined period of time; a second acquisition unit that acquires second information indicating whether or not there is a user other than the target user in an environment where the target user exists; an extracting unit that extracts, based on the first information and the second information, first operation information indicating at least one of a device operation and an action of the target user in a first environment where the other user is not present, and second operation information indicating at least one of a device operation and an action of the target user in a second environment where the other user is present; an estimation unit that estimates a first characteristic that is a characteristic of the target user present in the first environment based on the first action information, and estimates a second characteristic that is a characteristic of the target user present in the second environment based on the second action information; an output unit that outputs at least one of first characteristic information indicating the first characteristic and second characteristic information indicating the second characteristic; A program that functions as a