Information processing method, information processing device, and program

Abstract

This information processing method performed by a computer involves: acquiring motion information indicating instrument operation and / or behavior of a user; inferring a plurality of characteristics of the user on the basis of the motion information; determining, on the basis of the plurality of characteristics, a service to be provided to the user; and outputting service information indicating the service.

Description

Information processing method, information processing device, and program

[0001] The present disclosure relates to a technique for determining services to be provided to a user.

[0002] Conventionally, there have been known services that estimate a user's intentions and preferences based on the user's search history or browsing history in cyberspace, such as on websites, and provide the user with information such as advertisements that correspond to the user's intentions and preferences. Patent Literature 1 also discloses a technology that estimates which type of personality tendency a user falls into based on the usage history of a device for processing substances.

[0003] However, the above-mentioned conventional techniques do not take into consideration determining the services to be provided to a user based on a plurality of user characteristics estimated from the user's device operations or behavior.

[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 determine the services to be provided to a user based on multiple characteristics of the user that are inferred from the user's device operation or behavior.

[0006] An information processing method according to one aspect of the present disclosure is an information processing method by a computer, which acquires operation information indicating at least one of a user's device operation and behavior, estimates multiple characteristics of the user based on the operation information, determines services to be provided to the user based on the multiple characteristics, and outputs service information indicating the services.

[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. 5 is a diagram illustrating an example of 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 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 characteristic are performed. FIG. 10 is a flowchart illustrating an example of a service information output process. FIG. 11 is a flowchart illustrating an example of a service determination process. FIG. 12 is a diagram illustrating an example of second rule information. FIG. 13 is a diagram illustrating an example of information associating characteristic information with second rule information. FIG. 14 is a diagram illustrating an example of a portion of third rule information. FIG. 15 is a diagram illustrating an example of the remaining portion of the third rule information. FIG. 16 is a diagram illustrating another example of information associating characteristic information with second rules. FIG. 17 is a diagram illustrating an example of fourth rule information. FIG. 18 is a diagram illustrating an example of fifth rule information.

[0008] (Background to the present disclosure) Conventionally, there have been known services that infer a user's intentions and preferences based on the user's search history or browsing history in cyberspace, such as on websites, and provide the user with information, such as advertisements, that correspond to the user's intentions and preferences. However, in this conventional technology, the user's intentions and preferences are inferred 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, in order to adopt this conventional technology, an environment that allows the user to actively input information is required.

[0009] In response to this, Patent Document 1 discloses a technology for estimating which type of personality tendency a user's personality tendency falls into 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 a user's multiple characteristic personality tendencies based on the user's device usage history.

[0010] Therefore, with the above-described conventional technology, it is difficult to determine services to be provided to a user based on multiple user characteristics inferred from the user's device operations or behavior. For example, suppose a user has two characteristics: "being lazy" and "being clumsy." In this case, while the above-described conventional technology can infer one user characteristic, "being lazy," and provide an automatic device control service based on that characteristic, it is difficult to provide an automatic device control service based on the user's other characteristic, "being clumsy."

[0011] Therefore, the inventors have conducted extensive research into technology for determining the services to be provided to a user based on multiple characteristics of the user estimated from the user's device operation or behavior, 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 by a computer, which acquires operation information indicating at least one of a user's device operation and behavior, estimates multiple characteristics of the user based on the operation information, determines services to be provided to the user based on the multiple characteristics, and outputs service information indicating the services.

[0013] According to this configuration, multiple characteristics of a user are estimated based on operation information indicating at least one of the user's device operation and behavior. Then, services to be provided to the user are determined based on the multiple characteristics. Therefore, this configuration can determine services to be provided to the user based on the multiple user characteristics estimated from the user's device operation or behavior.

[0014] (2) In the information processing method described in (1) above, when determining the service, a first element for identifying the service may be identified based on the multiple characteristics, a second element linked to the first element may be identified based on the multiple characteristics, and the service may be determined based on the first element and the second element.

[0015] According to this configuration, a first element and a second element linked to the first element are identified based on a plurality of characteristics estimated based on operation information indicating at least one of a device operation and a behavior of the user. Then, a service to be provided to the user is determined based on the first element and the second element thus identified. Therefore, this configuration can determine a service to be provided to the user based on a plurality of user characteristics estimated from the device operation or behavior of the user.

[0016] (3) The information processing method described in (2) above further includes acquiring information defining a relationship between a plurality of element characteristics, one or more first candidate elements, and one or more second candidate elements; in identifying the first element, for each of the one or more first candidate elements, calculating a first number indicating the number of characteristics among the plurality of characteristics that have content in common with the element characteristic; identifying the first candidate element with the largest first number from the one or more first candidate elements; and identifying the identified first candidate element as the first element; and in identifying the second element, for each of the one or more second candidate elements, calculating a first number indicating the number of characteristics among the plurality of characteristics that have content in common with the element characteristic; Then, a second number indicating the number of characteristics among the plurality of characteristics that have content in common with the element characteristic is calculated, and the second candidate element with the largest second number is identified from the one or more second candidate elements, and the identified second candidate element is identified as the second element.In determining the service, rule information defining the relationship between one or more first elements, one or more second elements, and a plurality of candidate services may be obtained, and candidate services corresponding to the first element and the second element may be identified from the plurality of candidate services, and the identified candidate service may be determined as the service.

[0017] According to this configuration, the candidate service associated with the first candidate element and the second candidate element having the largest number of element characteristics whose content is common to multiple characteristics of the user can be determined as the service to be provided to the user.

[0018] (4) In the information processing method described in (2) above, further, the strength of each of the plurality of characteristics is calculated based on the operation information, and information defining a relationship between the plurality of element characteristics, one or more first candidate elements, and one or more second candidate elements is acquired. In identifying the first element, a first characteristic having the greatest strength among the plurality of characteristics is identified, and from the one or more first candidate elements, a first candidate element corresponding to an element characteristic having a content common to the first characteristic is identified, and the identified first candidate element is identified as the first element. In identifying the second element, The method may identify a characteristic having the second highest strength after the first characteristic as a second characteristic, identify a second candidate element corresponding to an element characteristic having content common to the second characteristic from among the one or more second candidate elements, and identify the identified second candidate element as the second element, and in determining the service, obtain rule information defining the relationship between one or more first elements, one or more second elements, and a plurality of candidate services, identify candidate services corresponding to the first element and the second element from among the plurality of candidate services, and determine the identified candidate service as the service.

[0019] According to this configuration, among the user's multiple characteristics, the candidate services associated with the first characteristic with the greatest intensity and the second characteristic with the second greatest intensity after the first characteristic can be determined as the services to be provided to the user.

[0020] (5) In the information processing method described in (3) or (4) above, the one or more first elements may be any of the service field to which the plurality of candidate services belong, the type of the plurality of candidate services, the execution timing of the plurality of candidate services, and the execution method of the plurality of candidate services, and the one or more second elements may be any of the service field, the type, the execution timing, and the execution method that is different from the one or more first elements.

[0021] According to this configuration, based on multiple characteristics of a user, any two of the service field, type, execution timing, and execution method can be identified as the first element and the second element, and candidate services corresponding to the first element and the second element can be determined as the services to be provided to the user.

[0022] (6) In the information processing method described in (2) above, further, the strength of each of the plurality of characteristics is calculated based on the operation information, and information defining the relationship between one or more first characteristics, one or more automatic controls of devices, one or more second characteristics, and one or more detailed controls included in the automatic control of each device is acquired, and in identifying the first element, a first characteristic having a content common to the plurality of characteristics is identified from the one or more first characteristics, an automatic control of a device corresponding to the identified first characteristic is identified from the one or more automatic controls of devices, and the identified automatic control of the device is The first element may be identified, and in identifying the second element, a second characteristic may be identified from among the one or more second characteristics that corresponds to the automatic control of the device identified as the first element and that has content in common with the multiple characteristics, a detailed control may be identified from among the one or more detailed controls that corresponds to the identified second characteristic, and the identified detailed control may be identified as the second element.In determining the service, an automatic control service that performs the detailed control indicated by the second element and is included in the automatic control of the device indicated by the first element may be determined as the service.

[0023] According to this configuration, an automatic control service that performs detailed control corresponding to a second characteristic whose content is common to multiple characteristics of the user, which is included in the automatic control of an appliance corresponding to a first characteristic whose content is common to multiple characteristics of the user, can be determined as the service to be provided to the user.

[0024] (7) In the information processing method described in (3) above, the users include a first user and a second user, and when the first user and the second user exist in the same environment, the operation information is acquired and the multiple characteristics are estimated for each of the first user and the second user, and a multiset of the multiple characteristics estimated for each of the first user and the second user is used as the multiple characteristics estimated for the user, and the first element and the second element are identified, and the service is determined and the service information is output.

[0025] According to this configuration, it is possible to determine the services to be provided to a first user and a second user who exist in the same environment based on multiple characteristics included in a multiple set of multiple characteristics estimated for each of the first user and the second user who exist in the same environment.

[0026] (8) In the information processing method described in (4) above, the users include a first user and a second user, and when the first user and the second user exist in the same environment, the operation information is acquired, the plurality of characteristics are estimated, the strength of each of the plurality of characteristics is calculated, the first element is identified, the second element is identified, and the service is determined for each of the first user and the second user, and information defining the relationship between one or more competing service groups indicating two or more competing services and a plurality of avoidance methods for avoiding conflict is acquired, the plurality of avoidance methods including a first method for selecting one competing service from the two or more competing services and a second method for merging the two or more competing services, and when the multiset of services determined for each of the first user and the second user includes a service group having content common to the competing service group, the service group is selected from the multiset. and determining whether a target avoidance method, which is an avoidance method corresponding to a competing service group that has content in common with the service group, is the first method or the second method; if the target avoidance method is the first method, acquiring the strength of the first characteristic of a user to whom each of two or more services is provided for each of two or more services included in the service group, selecting one service from the two or more services based on the strength of the first characteristic acquired for each of the two or more services, and outputting information indicating the one service as the service information; if the target avoidance method is the second method, acquiring the strength of the second characteristic of a user to whom each of the two or more services is provided for each of the two or more services, merging the two or more services based on the strength of the second characteristic acquired for each of the two or more services, and outputting information indicating the merged service as the service information.

[0027] In a case where a multiset of services determined as services to be provided to a first user and a second user who are in the same environment includes two or more conflicting services, this configuration makes it possible to output, as service information indicating a service to be provided to the user, information indicating one service that can avoid the conflict between the two or more services.

[0028] Specifically, it is assumed that a target avoidance method corresponding to a group of competing services that share content with the group of services indicating the two or more services is defined in the first method, and in this case, information indicating one service selected from the two or more services based on the strength of the first characteristic of the user to whom each service is provided can be output as the service information.

[0029] On the other hand, if the target avoidance method is set to the second method, the two or more services can be merged based on the strength of the second characteristic of the user to whom each of the two or more services is provided, and information indicating the merged service can be output as the service information.

[0030] (9) In the information processing method described in (8) above, when the target avoidance method is the first method, the one service selected may be the service among the two or more services that has the greatest strength of the first characteristic.

[0031] According to this configuration, when the target avoidance method is set to the first method, information indicating one service among the two or more services for which the greatest strength of the first characteristic has been obtained can be output as information indicating one service that can avoid conflict between the two or more services.

[0032] (10) In the information processing method described in (8) above, when the target avoidance method is the second method, in merging the two or more services, the difference between the intensities of any two of the second characteristics obtained for each of the two or more services is calculated, and if the difference is less than a predetermined value, the parameters that conflict between the two or more services are averaged to obtain the service obtained by merging the two or more services, and if the difference is greater than or equal to the predetermined value, the service among the two or more services for which the greatest intensity of the second characteristic is obtained may be obtained as the merged service.

[0033] According to this configuration, when the target avoidance method is set to the second method, information indicating a merged service corresponding to the difference between any two of the strengths of the second characteristics obtained for each of the two or more services can be output as information indicating a single service that can avoid conflict between the two or more services.

[0034] Specifically, if the difference is less than a predetermined value, the parameters competing between the two or more services may be averaged to determine a service obtained by merging the two or more services as a merged service, and information indicating the merged service may be output as information indicating the one service. On the other hand, if the difference is equal to or greater than the predetermined value, the service among the two or more services for which the greatest strength of the second characteristic is obtained may be determined as a merged service, and information indicating the merged service may be output as information indicating the one service.

[0035] (11) In the information processing method described in any one of (8) to (10) above, when the group of services is extracted, the method further includes obtaining the priority assigned to each of the plurality of candidate services by one or more of the first user and the second user, determining whether or not the priority has been assigned to a candidate service included in the plurality of candidate services that has content in common with each of the two or more services by the user to whom each service is provided, and, when it is determined that the priority has been assigned to one or more of the two or more services, identifying the service assigned the highest priority among the one or more services and outputting the service information indicating the identified service.

[0036] In the above configuration, a group of services that share content with a group of competing services may be extracted from a multiplex set of services determined to be provided to each of a first user and a second user existing in the same environment.

[0037] According to this configuration, in such a case, when one or more of the first and second users have assigned priorities to one or more services included in the service group, the wishes of the one or more users can be given priority, and information indicating the service that has been assigned the highest priority among the one or more services can be output as information indicating a service that can avoid conflict between the two or more services.

[0038] (12) In the information processing method described in (3) or (4) above, further, information defining the relationship between the plurality of element characteristics and one or more environments is acquired, further environmental information indicating the environment in which the user is currently located is acquired, and further, from the plurality of element characteristics, one or more element characteristics corresponding to the environment indicated by the environmental information among the one or more environments are acquired, and in identifying the first element and the second element, one or more characteristics among the plurality of characteristics that have content common to the one or more element characteristics may be used instead of the plurality of characteristics.

[0039] According to this configuration, the element characteristics used to identify the first element and the second element can be limited to one or more element characteristics corresponding to the environment the user is currently in. This makes it possible to limit the services determined based on the first element and the second element to services suited to the one or more element characteristics corresponding to the environment the user is currently in.

[0040] (13) In the information processing method described in (4) above, when the service information is output, together with the service information, request information requesting a return of information indicating whether or not the service indicated by the service information will be used is output to an output device used by the user, and if information indicating that the service will not be used is returned from the output device, the identification of the first element, the identification of the second element, the determination of the service, and the output of the service information are re-executed, and when the second characteristic is identified in the identification of the second element during the re-execution, the characteristic among the multiple characteristics whose strength is second to the second characteristic may be identified as the second characteristic.

[0041] According to this configuration, each time the output device returns information indicating that the service indicated by the service information will not be used, information indicating the service determined by changing the second element can be output to the output device as service information.

[0042] (14) In the information processing method described in (13) above, when outputting the service information, permission / denial request information requesting a return of information indicating whether or not to permit subsequent output of the service information may further be output to the output device, and if information indicating that the service will not be used is returned from the output device until information indicating that subsequent output of the service information is not permitted is returned from the output device, the identification of the first element, the identification of the second element, the determination of the service, and the output of the service information may be re-executed.

[0043] According to this configuration, each time information indicating that the service indicated by the service information will not be used is returned from the output device until information indicating that subsequent output of service information is not permitted is returned from the output device, information indicating the service determined by changing the second element can be output to the output device as service information.

[0044] (15) In the information processing method described in (3) or (4) above, information indicating a plurality of used services that the user has used in the past may be further obtained, and when outputting the service information, the number of target used services among the plurality of used services, which are used services that have content in common with the candidate service associated with the first element identified in the rule information, may be calculated, and if the number of target used services is equal to or greater than a predetermined number, information suggesting that the use of the target used services be stopped may be output together with the service information to an output device used by the user.

[0045] According to this configuration, a user who has previously used a predetermined number or more of target usage services that share content with the candidate services associated with the first element can be suggested to stop using the predetermined number or more of target usage services.

[0046] (16) In the information processing method described in (3) or (4) above, information indicating a plurality of use services used by the user in the past and the frequency of use of each of the plurality of use services may be further acquired, and when outputting the service information, the number of target use services among the plurality of use services, which are use services that have content in common with the candidate service associated with the first element identified in the rule information, may be calculated, and if the number of target use services is equal to or greater than a predetermined number, the service information may be output to an output device used by the user, along with information suggesting that the use of the target use service with the lowest frequency of use among the predetermined number or more of target use services be stopped, and that the service indicated by the service information be used.

[0047] According to this configuration, a user who has previously used a predetermined number or more of target usage services that share content with the candidate services associated with the first element can be suggested to stop using the target usage service that is used least frequently among the predetermined number or more of target usage services, and to use the service indicated by the service information.

[0048] (17) An information processing device according to another aspect of the present disclosure includes an acquisition unit that acquires operation information indicating at least one of a user's device operation and behavior, an estimation unit that estimates multiple characteristics of the user based on the operation information, a determination unit that determines a service to be provided to the user based on the multiple characteristics, and an output unit that outputs service information indicating the service.

[0049] According to this configuration, the same effects as those of the information processing method described above in (1) can be obtained.

[0050] (18) In the information processing device described in (17) above, the determination unit may identify a first element for identifying the service based on the multiple characteristics, identify a second element linked to the first element based on the multiple characteristics, and determine the service based on the first element and the second element.

[0051] According to this configuration, the same effects as those of the information processing method described above in (2) can be obtained.

[0052] (19) A program according to another aspect of the present disclosure is a program that causes a computer to function, causing the computer to function as an acquisition unit that acquires operation information indicating at least one of a user's device operation and behavior, an estimation unit that estimates multiple characteristics of the user based on the operation information, a determination unit that determines services to be provided to the user based on the multiple characteristics, and an output unit that outputs service information indicating the services.

[0053] According to this configuration, the same effects as those of the information processing method described above in (1) can be obtained.

[0054] (20) In the program described in (19) above, the determination unit may identify a first element for identifying the service based on the multiple characteristics, identify a second element linked to the first element based on the multiple characteristics, and determine the service based on the first element and the second element.

[0055] According to this configuration, the same effects as those of the information processing method described above in (2) can be obtained.

[0056] 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.

[0057] 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.

[0058] Embodiments of the present disclosure will be described below 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.

[0059] 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.

[0060] 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.

[0061] 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.

[0062] 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.

[0063] 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.

[0064] 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.

[0065] 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 .

[0066] 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.

[0067] 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.

[0068] 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.

[0069] 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.

[0070] 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.

[0071] 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.

[0072] 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.

[0073] 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.

[0074] 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.

[0075] 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.

[0076] 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.

[0077] 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.

[0078] 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).

[0079] The processor 12 also functions as an acquisition unit 121, an estimation unit 122, a determination unit 123, and an output unit 124. The acquisition unit 121 to the output unit 124 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.

[0080] 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.

[0081] 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.

[0082] 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.

[0083] 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.

[0084] The characteristic information includes the user's characteristics and their strength. The user's characteristics are made up 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.

[0085] 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.

[0086] 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.

[0087] 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 .

[0088] The sensor information storage unit 134 stores the sensor information received by the communication circuit 11 from the sensor 7 via the network 9 .

[0089] The rule information storage unit 135 stores information indicating various rules used in various processes by the processor 12. Details of the information stored in the rule information storage unit 135 will be described later.

[0090] (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.

[0091] First, in step S100, the 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.

[0092] 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.

[0093] 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 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" means that they match within a predetermined tolerance, and this also applies to the following description. The 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 comparison data stored in the user information storage unit 132. The acquisition unit 121 acquires the user ID of the identified user as the user ID included in the operation information.

[0094] Next, in step S200, the processor 12 performs a process (hereinafter, characteristic estimation process) to estimate characteristics of each of the users having one or more user IDs included in the operation information acquired in step S100 (hereinafter, target users) as estimation targets. In the characteristic estimation process, the characteristic information of the target users stored in the user information storage unit 132 is updated. The characteristic estimation process will be described in detail later.

[0095] Next, in step S300, the output unit 124 outputs the characteristic information of each target user. For example, in step S300, the output unit 124 transmits (outputs) the characteristic information of each target user updated in step S200 to a predetermined external device such as the output device 6 ( FIG. 1 ) using the communication circuit 11.

[0096] (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.

[0097] First, in step S201, the acquisition unit 121 acquires operation information (operation information) indicating the operation (equipment operation) of the target user's equipment 3 and facility 5 after the previous characteristic output process has ended, and sensor information (operation information) indicating the target user's behavior.

[0098] Specifically, in step S201, the 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.

[0099] The 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 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.

[0100] Next, in step S202, the estimation unit 122 acquires the current characteristic information of the target user. Specifically, the estimation unit 122 acquires the characteristic information of the target user stored in the user information storage unit 132.

[0101] 6 is a diagram illustrating an example of characteristic information. The characteristic information includes a plurality of characteristics and the strength of each characteristic. The characteristic information illustrated in FIG. 6 indicates that the target user has five element characteristics: "slacker," "saving money," "neat," "sensitive," and "communicative," and that the strengths of these characteristics are "0.1," "0.1," "0.5," "0.1," and "0.2."

[0102] In this embodiment, the larger the strength value, the stronger the element characteristic of the target user. The same applies to the following description. In other words, the characteristic information shown in FIG. 6 indicates that the target user most strongly exhibits the characteristic of "cleanliness."

[0103] Next, in step S203, the estimation unit 122 extracts candidate characteristics that are estimated to be characteristics of the target user based on the operation history information and behavior history information acquired in step S201.

[0104] Specifically, in step S203, the estimation unit 122 acquires, from the rule information storage unit 135, first rule information that defines the relationship between one or more candidate characteristics that may be characteristics of the target user and one or more groups of characteristics that indicate the characteristics of the operation or behavior of the equipment 3 or the facility 5.

[0105] Fig. 7 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. 7, 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.

[0106] For example, in the first rule information shown in Figure 7, the candidate trait "lazy" is associated with a group of traits indicating a lighting operation trait "lights are operated infrequently" and a refrigerator operation trait "refrigerator door is left open for a long time" by a user whose component trait is the candidate trait "lazy."

[0107] 8 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. 8, 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.

[0108] For example, in the first rule information shown in Figure 8, 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.

[0109] 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 one feature of the user's operation or behavior of the device 3 or the facility 5.

[0110] Then, the estimation unit 122 refers to the first rule information and extracts candidate characteristics that are estimated to be characteristics of the target user based on the operation history information and behavior history information acquired in step S201.

[0111] Specifically, the estimation unit 122 refers to the first rule information shown in FIG. 7 and determines whether the operation of the device 3 or facility 5 of the target user indicated by the operation history information includes an operation of the device 3 or facility 5 that indicates one or more groups of features included in the first rule information.

[0112] 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 once. 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 122 makes the above determination by referring to the information.

[0113] When determining that the operation of the device 3 or facility 5 exhibiting one or more feature groups is included, the estimation unit 122 identifies one or more candidate characteristics associated with the one or more feature groups in the first rule information. The estimation unit 122 estimates the identified one or more candidate characteristics as characteristics of the target user and extracts the one or more candidate characteristics.

[0114] For example, suppose that the target user's operations of the appliance 3 or facility 5 indicated by the operation history information include one or more lighting operations that indicate 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. 7. Also suppose that the target user's operations of the appliance 3 or facility 5 indicated by the operation history information include one or more refrigerator operations that indicate the characteristic "refrigerator door is left open for a long time" included in the characteristic group. In this case, the estimation unit 122 estimates that the candidate characteristic "lazy" associated with the characteristic group in the first rule information is the target user's characteristic, and extracts the candidate characteristic "lazy."

[0115] Note that a lighting operation that exhibits the characteristic "low frequency of lighting operation" 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, this is not limited to this, and the operation 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 placed 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 placed may be obtained by referring to the device information stored in the device information storage unit 131 and the behavior history information including the detection date and time that matches the operation date and time included in the operation history information.

[0116] 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).

[0117] Similarly, the estimation unit 122 refers to the first rule information shown in Figure 8 and determines whether the behavior of the target user indicated by the behavior history information includes behavior that indicates one or more groups of characteristics included in the first rule information.

[0118] 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 122 makes the above determination by referring to the information.

[0119] When determining that the behavior indicates one or more feature groups, the estimation unit 122 identifies one or more candidate characteristics associated with the one or more feature groups in the first rule information. The estimation unit 122 estimates the identified one or more candidate characteristics as characteristics of the target user and extracts the one or more candidate characteristics.

[0120] For example, suppose that the target user's behavior indicated by the behavior history information includes one or more actions indicating the characteristic "messy desk" included in the characteristic group associated with the candidate characteristic "lazy" included in the first rule information shown in Figure 8. Also suppose that the target user's behavior indicated by the behavior history information also includes one or more actions indicating the characteristic "low frequency of folding laundry" included in the characteristic group. In this case, the estimation unit 122 estimates that the candidate characteristic "lazy" associated with the characteristic group in the first rule information is the target user's characteristic, and extracts the candidate characteristic "lazy."

[0121] 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.

[0122] In step S203, the estimation unit 122 may omit extracting candidate characteristics based on either the operation history information or the behavior history information acquired in step S201.

[0123] In step S203, if no candidate characteristic is extracted (NO in step S203), the characteristic information acquired in step S202 is not updated, and the characteristic estimation process ends.

[0124] On the other hand, if one or more candidate characteristics estimated to be characteristics of the target user are extracted in step S203 (YES in step S203), in this case, in step S204, the estimation unit 122 updates the characteristic information acquired in step S202 and ends the characteristic estimation process.

[0125] Specifically, in step S204, if the candidate characteristic extracted in step S203 is not included in the characteristic information acquired in step S202, the estimation unit 122 adds the candidate characteristic to the characteristic information. Then, the estimation unit 122 updates (sets) the strength of each characteristic included in the characteristic information, and updates the characteristic information of the target user stored in the user information storage unit 132 with the updated characteristic information.

[0126] Details of step S204 will be described below. Fig. 9 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 characteristic have been performed. Fig. 9 shows an example of the relationship between the characteristic information of the target user shown in Fig. 6 and the number of times that characteristic actions corresponding to each characteristic included in the characteristic information have been performed. The number of times that characteristic actions corresponding to each characteristic have been performed is stored in the user information storage unit 132 in association with the characteristic information.

[0127] The characteristic actions corresponding to each characteristic refer to the operation or behavior of the device 3 or facility 5 that indicates a group of characteristics associated with a candidate characteristic that shares content with each characteristic in the first rule information. For example, the characteristic actions corresponding to the characteristic "lazy" refer to the operation of a light and the operation of a refrigerator that respectively indicate two characteristics, "low frequency of operating lights" and "long time the refrigerator door is open," that are associated with the candidate characteristic "lazy" that shares content with the characteristic "lazy" in the first rule information (FIG. 7). Furthermore, the characteristic actions corresponding to the candidate characteristic "lazy" refer to actions that respectively indicate two characteristics, "messy desk" and "low frequency of folding laundry," that are associated with the candidate characteristic "lazy" in the first rule information (FIG. 8).

[0128] The number of times that the characteristic action corresponding to the characteristic "lazy" included in the characteristic information 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, are performed in the operation of the device 3 or facility 5 of the target user indicated by the operation history information, and the number of times that the above-mentioned actions, which are the characteristic actions, are performed in the behavior of the target user indicated by the behavior history information.

[0129] In other words, the number of times that the characteristic action corresponding to each characteristic is performed is the minimum number of times that the operation and behavior of the device 3 or facility 5 that indicates each characteristic included in the characteristic group corresponding to the candidate characteristic that has content in common with the characteristic. However, without being limited to this, the number of times that the characteristic action corresponding to each characteristic is performed may be the average or maximum number of times that the operation and behavior of the device 3 or facility 5 that indicates each characteristic included in the characteristic group corresponding to the candidate characteristic that has content in common with the characteristic.

[0130] In step S204, the estimation unit 122 refers to the operation history information and the behavior history information, and calculates the number of times that characteristic actions corresponding to the characteristics included in the characteristic information and whose content is common to the candidate characteristics extracted in step S203. The estimation unit 122 adds the currently calculated number of times that the characteristic actions corresponding to the characteristics included in the characteristic information have been executed to the number of times that the characteristic actions corresponding to the characteristics have been executed, which is stored in the user information storage unit 132.

[0131] 10 is a diagram showing an example of the relationship between the updated characteristics of the target user and the number of times the characteristic action corresponding to each characteristic is performed. In step S204, the estimation unit 122 calculates the number of times the characteristic action corresponding to the characteristic "lazy" is performed "1 time," and adds this number of times to the number of times the characteristic action corresponding to the characteristic "lazy" included in the characteristic information shown in FIG. 9 , resulting in "11 times."

[0132] Then, the estimation unit 122 sets the strength of each characteristic included in the characteristic information based on the number of times the characteristic action corresponding to each characteristic included in the characteristic information has been performed.

[0133] Specifically, the estimation unit 122 sets the ratio of the number of times that characteristic actions corresponding to each characteristic included in the characteristic information are executed to the total number of times that characteristic actions corresponding to each characteristic included in the characteristic information are executed as the strength of each characteristic. As a result, the sum of the strengths of each characteristic included in the characteristic information is normalized to 1.

[0134] 10 , the total number of times the five characteristic actions corresponding to the five traits have been performed is 101 (=11+10+50+10+20). Therefore, the estimation unit 122 sets the ratio of the total number of times the characteristic action corresponding to the trait "lazy" has been performed (11) to the total number of times (101), which is 0.109 (=11 / 101), as the strength of the trait "lazy."

[0135] Similarly, the estimation unit 122 sets the ratios of the number of times characteristic actions corresponding to the traits "frugal," "neat," "neurotic," and "communicative" to the total number of times the five characteristic actions corresponding to the five traits have been performed, "10 times," "50 times," "10 times," and "20 times," respectively, of "0.099," "0.495," "0.099," and "0.198," as the intensities of the traits "frugal," "neat," "neurotic," and "communicative."

[0136] The method for setting the strength of each characteristic is not limited to this. For example, the estimation unit 122 may set the number of times (e.g., “11 times”) that a characteristic action corresponding to each characteristic (e.g., “lazy”) is performed as the strength of each element characteristic.

[0137] In addition, in step S204, the estimation unit 122 may not set the strength of each characteristic, so that the strength of each characteristic is not included in the characteristic information.

[0138] (Flow of Service Information Output Processing) The following describes the flow of the service information output processing performed in the information processing device 1. The service information output processing is processing in which, for each user who has been pre-registered as a target of the service information output processing, a service to be provided to each user is determined based on the user's characteristic information output in the characteristic output processing, and information indicating the service is output.

[0139] 11 is a flowchart showing an example of the service information output process. The service information output process is executed at a predetermined timing. The predetermined timing may be, for example, every hour, every half day, every day, every week, or every month. Hereinafter, a user who is the target of the service information output process will be referred to as a target user.

[0140] First, in step S400 , the acquisition unit 121 acquires characteristic information of the target user from the user information storage unit 132 .

[0141] Next, in step S500, the processor 12 executes a process (hereinafter, service determination process) for determining a service to be provided to the target user based on the characteristic information acquired in step S400. The service determination process will be described in detail later.

[0142] Next, in step S600, the output unit 124 outputs information indicating the service to be provided to the target user determined in step S500 (hereinafter, service information). For example, in step S600, the output unit 124 transmits (outputs) the service information indicating the service to be provided to the target user determined in step S500 to the output device 6 used by the target user using the communication circuit 11.

[0143] However, without being limited to this, in step S600, the output unit 124 may store (output) service information indicating the service to be provided to the target user determined in step S500 in the user information storage unit 132 as user information of the target user.

[0144] (Flow of Service Decision Processing) Next, the service decision processing in step S500 will be described in detail. Fig. 12 is a flowchart showing an example of the service decision processing.

[0145] First, in step S501, the determination unit 123 identifies a first element based on the multiple characteristics included in the characteristic information acquired in step S400. The first element is information derived based on the characteristics of the target user and indicates information used to identify a service to be provided to the target user.

[0146] For example, a housekeeping service can be identified as a service belonging to the service category "Lifestyle (Housework)." On the other hand, a target user with the characteristic "Lazy" is presumed to be prone to using services belonging to the service category "Lifestyle (Housework)" because doing housework is a hassle. In this way, the service category "Lifestyle (Housework)" can be derived from the target user's characteristic "Lazy."

[0147] As described above, the information indicating the service field can be derived based on the characteristics of the target user, and the service to be provided to the target user can be identified. Therefore, the information indicating the service field can be used as the first element. Therefore, an example in which the information indicating the service field is used as the first element will be described below.

[0148] Specifically, in step S501, the acquiring unit 121 acquires second rule information indicating rules for identifying the first element and the second element from the rule information storage unit 135. The second element, like the first element, is information derived based on the characteristics of the target user and is information used to identify a service to be provided to the target user, but is indicated as information linked to the first element but different from the first element.

[0149] For example, a food delivery service can be identified as a service of the type "outsourcing" belonging to the service category "meals." On the other hand, a target user with the characteristic "lazy" is presumed to be prone to using services of the type "outsourcing" belonging to the service category "meals" because cooking meals is a hassle. In this way, the service type "outsourcing" can be derived from the target user's characteristic "lazy" and can be linked to the service category "meals."

[0150] As described above, information indicating the type of service can be derived based on the characteristics of the target user, and the service to be provided to the target user can be identified. Furthermore, the information indicating the type of service can be linked to information indicating the service field, which is the first element. Therefore, the information indicating the type of service can be used as the second element. Therefore, hereinafter, an example in which the information indicating the type of service is used as the second element will be described.

[0151] In other words, the second rule information is information that defines the relationship between multiple element characteristics that may be included in the user's characteristics, the service field (first candidate element) to which candidate services (hereinafter, candidate services) to be provided to users with characteristics that share content in common with each element characteristic belong, and the type of candidate service (second candidate element).

[0152] Service fields to which the candidate services belong include, for example, life (general), equipment or facilities, life (healthcare), life (housework), life (EC), life (food), etc. Types to which the candidate services belong include, for example, notification, prediction, suggestion, control, outsourcing, etc.

[0153] 13 is a diagram illustrating an example of second rule information. In the second rule information illustrated in FIG. 13, an element characteristic “characteristic 1” is associated with a service field “lifestyle (general)” and a type “outsourcing.”

[0154] The determination unit 123 identifies a first characteristic having the greatest strength among the multiple characteristics included in the characteristic information acquired in step S400. The determination unit 123 identifies a service field corresponding to an element characteristic having content common to the first characteristic from among the service fields included in the second rule information acquired by the acquisition unit 121. The determination unit 123 identifies the identified service field as a first element.

[0155] 14 is a diagram showing an example of information associating characteristic information with second rule information. For example, FIG. 14 shows an example in which the characteristic information acquired in step S400 includes four characteristics, "Characteristic 1" to "Characteristic 4," and the intensities of these characteristics, "0.5," "0.2," "0.2," and "0.1." FIG. 14 also shows an example in which a portion of the second rule information shown in FIG. 13 is associated with the characteristic information, the portion including four element characteristics, "Characteristic 1" to "Characteristic 4," that share content with the four characteristics, "Characteristic 1" to "Characteristic 4," included in the characteristic information.

[0156] In this example, the determination unit 123 identifies, as the first characteristic, the characteristic "characteristic 1" having the largest strength of "0.5" among the four characteristics included in the characteristic information. As shown in the shaded area in FIG. 14 , the determination unit 123 identifies, from the service fields included in the second rule information, the service field "life (general)" that corresponds to the element characteristic "characteristic 1" that has content in common with the first characteristic. The determination unit 123 identifies the identified service field "life (general)" as the first element.

[0157] Next, in step S502, the determining unit 123 identifies a second element linked to the first element based on the multiple characteristics included in the characteristic information acquired in step S400.

[0158] Specifically, in step S502, the determination unit 123 identifies, as the second characteristic, the characteristic having the second highest strength after the first characteristic among the multiple characteristics included in the characteristic information acquired in step S400. The determination unit 123 identifies a candidate service type corresponding to an element characteristic having content in common with the second characteristic from the types of candidate services included in the second rule information acquired by the acquisition unit 121. The determination unit 123 identifies the identified candidate service type as the second element linked to the first element identified in step S501.

[0159] For example, in the above example, the determination unit 123 identifies, as second characteristics, two characteristics "Characteristic 2" and "Characteristic 3" whose strengths are second to the first characteristic "Characteristic 1" among the four characteristics included in the characteristic information ( FIG. 14 ). As shown in the shaded area in FIG. 14 , the determination unit 123 identifies, from the types of candidate services included in the second rule information, two candidate service types "Outsourcing" and "Notification" that correspond to the two element characteristics "Characteristic 2" and "Characteristic 3" that share content with the second characteristic. The determination unit 123 identifies the two identified service types "Outsourcing" and "Notification" as second elements linked to the service field "Life (general)" identified as the first element in step S501.

[0160] The determination unit 123 may identify, as the second characteristic, a characteristic whose intensity differs from that of the first characteristic among the multiple characteristics included in the characteristic information acquired in step S400. For example, in the above example, the determination unit 123 may identify, as the second characteristic, three characteristics "Characteristic 2," "Characteristic 3," and "Characteristic 4" whose intensity differs from that of the first characteristic "Characteristic 1" among the four characteristics included in the characteristic information ( FIG. 14 ).

[0161] Next, in step S503, the determination unit 123 determines a service to be provided to the target user based on the first element identified in step S501 and the second element identified in step S502.

[0162] Specifically, in step S503, the determination unit 123 acquires third rule information indicating rules for determining a service from the rule information storage unit 135. The third rule information is information that defines the relationship between a service field (one or more first elements), a service type (one or more second elements), and a plurality of candidate services.

[0163] The candidate services include various services that can be executed by the information processing device 1. For example, the candidate services include to-do list notification, past photo notification, today's schedule notification, device or facility alert notification, device or facility maintenance time notification, scheduled delivery date and time notification, consumable supply consumption status notification, current health status notification, health status prediction based on the current health status, consumable supply consumption time prediction, lifestyle tips suggestions, automatic control of device or facility, automatic ordering of consumable supplies, etc.

[0164] The candidate services also include various services that can be executed by the external service server 8. For example, the candidate services include delivery (meals, food, etc.), housekeeping (cleaning, meals, babysitting, etc.), meal reservations (transportation, restaurants, etc.), travel reservations (transportation, accommodations, accommodation plans, etc.), and ticket reservations (movies, events, entertainment facilities, amusement parks, etc.).

[0165] 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 candidate services are associated with the type of each candidate service and the service field to which each candidate service belongs, and further, the execution timing of each candidate service is associated with the execution method of each candidate service.

[0166] The execution timing of the candidate service includes, for example, the start time of the candidate service (e.g., 12:00, anytime, etc.), the time interval at which the candidate service is repeated (e.g., every hour), the number of times the candidate service is repeated (e.g., three times), etc. Note that "anytime" refers to when information necessary for executing the candidate service is obtained.

[0167] The execution method of the candidate service includes, for example, an output destination and output instructions for information output by the execution of the candidate service (hereinafter, the output information of the candidate service). The output information of the candidate service includes, for example, information specific to the target user, such as the user's to-do list, schedule, and vital data, control information for the device 3 or facility 5, and information requesting the execution of a service provided by the service server 8.

[0168] The destinations of the output information of the candidate service include, 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 candidate service, etc. The output instructions for the output information of the candidate service include, for example, an instruction to display the output information of the candidate service, an instruction to output it as audio, an instruction to store it, an instruction to transfer it, an instruction to execute it, etc.

[0169] For example, in the third rule information shown in FIG. 15, the type "notification", the candidate service "to-do list notification", and the service field "life (general)" are associated with each other, and further, the execution timing "once a day at XX o'clock" and the execution method "instruct display on the user's output device" are associated with each other.

[0170] In the third rule information shown in Figure 16, five candidate services are associated with the type of each candidate service and the service field to which each candidate service belongs, and further, the execution timing of each candidate service and the execution method of each candidate service are associated.

[0171] For example, in the third rule information shown in FIG. 16, the type "outsourcing" is associated with the candidate service "delivery (meals, food)" and the service field "daily life (food)", and further, the execution timing "anytime" is associated with the execution method "instruct display on the user's output device".

[0172] The determination unit 123 identifies a candidate service that corresponds to the first element identified in step S501 and the second element identified in step S502 from among the plurality of candidate services included in the third rule information. The determination unit 123 determines the identified candidate service as the service to be provided to the target user.

[0173] For example, as in the above example, it is assumed that the first element identified in step S501 is the service field "life (general)" and the second element identified in step S502 is two service types "outsourcing" and "notification." It is also assumed that the determining unit 123 acquires the third rule information shown in FIGS. 15 and 16.

[0174] In this case, the determination unit 123 determines, as the services to be provided to the target user, two candidate services, “Travel Reservation (Transportation, Accommodation, Accommodation Plans, etc.)” and “Travel Reservation (Transportation, Accommodation, Accommodation Plans, etc.),” which are associated with the service field “Lifestyle (General)” and the service type “Outsourcing” in the third rule information shown in FIG. 16 .

[0175] Furthermore, the determination unit 123 determines, in the third rule information shown in FIG. 15 , the four candidate services “To-do list notification,” “Past photo notification,” “Today’s schedule notification,” and “Scheduled delivery date and time notification,” which are associated with the service field “Life (general)” and the service type “Notification,” as services to be provided to the target user.

[0176] In this case, in step S600 ( FIG. 11 ), the output unit 124 outputs, as the service information, character string information (text) (e.g., “To-do list notification”) indicating the service determined in step S503. However, without being limited to this, the output unit 124 may refer to the third rule information and further include, in the service information, character string information indicating one or more of the type, service field, execution timing, and execution method corresponding to candidate services that share content with the service determined in step S503.

[0177] The configuration of this embodiment can employ the following modifications.

[0178] (1) In the above embodiment, an example has been described in which the first element and the second element are identified based on the intensities of multiple characteristics included in the characteristic information in step S501 ( FIG. 12 ) and step S502 ( FIG. 12 ). However, as will be described below, the first element and the second element may be identified based on multiple characteristics included in the characteristic information.

[0179] Specifically, in step S501 , the acquisition unit 121 acquires second rule information from the rule information storage unit 135 .

[0180] The determining unit 123 calculates, for each of one or more service fields included in the second rule information, the number of characteristics (hereinafter referred to as the first number) that have content in common with the element characteristic corresponding to each service field, among the multiple characteristics included in the characteristic information. The determining unit 123 identifies the service field with the largest first number from the one or more service fields included in the second rule information, and identifies the identified service field as the first element.

[0181] 17 is a diagram showing another example of information associating characteristic information with second rule information. For example, FIG. 17 shows an example in which the characteristic information acquired in step S400 includes four characteristics, "Characteristic 1" to "Characteristic 4." FIG. 17 also shows an example in which a portion of the second rule information shown in FIG. 13 is associated with the characteristic information, the portion including four element characteristics, "Characteristic 1" to "Characteristic 4," that share content with the four characteristics, "Characteristic 1" to "Characteristic 4," included in the characteristic information.

[0182] In this example, the determiner 123 calculates the first number for each of the three service fields "daily life (general)," "daily life (food)," and "daily life (housework)" included in the second rule information. Specifically, the determiner 123 calculates, as the first number for the service field "daily life (general)," the number "2" of the characteristics "characteristic 1" and "characteristic 3" that share content with the element characteristics "characteristic 1" and "characteristic 3" corresponding to the service field "daily life (general)" out of the four characteristics "characteristic 1" to "characteristic 4" included in the characteristic information. Similarly, the determiner 123 calculates the first number "1" for the service field "daily life (food)" and the service field "daily life (housework)."

[0183] Then, the determination unit 123 identifies the service field "Life (general)" which has the largest first number of "2" from the three service fields "Life (general)," "Life (food)," and "Life (housework)" included in the second rule information, and identifies the identified service field "Life (general)" as the first element.

[0184] In step S502, similarly to step S501 described above, the determination unit 123 calculates, for each of the one or more candidate service types included in the second rule information, the number of characteristics (hereinafter referred to as the second number) that share content with element characteristics corresponding to each candidate service type among the multiple characteristics included in the characteristic information. The determination unit 123 identifies the candidate service type with the largest second number from among the one or more candidate service types included in the second rule information, and identifies the identified candidate service type as the second element.

[0185] For example, in the above example, the determination unit 123 calculates the second number for each of the two candidate service types, "outsourcing" and "notification," included in the second rule information. For example, the determination unit 123 calculates, as the second number for the candidate service type "outsourcing," the number "3" of characteristics "Characteristic 1," "Characteristic 2," and "Characteristic 4" that share content with the element characteristics "Characteristic 1," "Characteristic 2," and "Characteristic 4" that correspond to the candidate service type "outsourcing" out of the four characteristics "Characteristic 1" to "Characteristic 4" included in the characteristic information. Similarly, the determination unit 123 calculates the second number "1" for the candidate service type "notification."

[0186] Then, the determination unit 123 identifies the candidate service type "outsourcing", which has the largest second number of "3", from the two candidate service types "outsourcing" and "notification" included in the second rule information, and identifies the identified candidate service type "outsourcing" as the second element.

[0187] (2) In the above embodiment and modified example, in step S501 ( FIG. 12 ) and step S502 ( FIG. 12 ), an example has been described in which the first element and the second element are identified using second rule information ( FIG. 13 ) that defines the relationship between a plurality of element characteristics, the service field to which the candidate service belongs, and the type of the candidate service. However, the second rule information is not limited to this, and may be information that defines the relationship between a plurality of element characteristics and any two of the service field to which the candidate service belongs, the type of the candidate service, the execution timing of the candidate service, and the execution method of the candidate service.

[0188] (3) In the above embodiment and modified example, the first element and the second element are identified using the second rule information in step S501 ( FIG. 12 ) and step S502 ( FIG. 12 ). However, the first element and the second element may be identified using the fourth rule information in step S501 ( FIG. 12 ) and step S502 ( FIG. 12 ), as shown below. Accordingly, step S503 ( FIG. 13 ) may be modified as shown below.

[0189] Specifically, in step S501, the acquiring unit 121 acquires fourth rule information indicating rules for identifying the first element and the second element from the rule information storage unit 135. The fourth rule information is information that defines the relationship between one or more first characteristics that may be included in the user's characteristics and the automatic control of one or more devices 3 or facilities 5, and between one or more second characteristics that may be included in the user's characteristics and one or more detailed controls included in the automatic control of each device 3 or each facility 5.

[0190] Fig. 18 is a diagram showing an example of fourth rule information. In the fourth rule information shown in Fig. 18, the first characteristic "lazy" and the automatic control "adjust the set temperature of the air conditioner" of the device 3 or the facility 5 are associated with the second characteristic "dexterous" and the detailed control "preset menu" included in the automatic control "adjust the set temperature of the air conditioner." Note that the detailed control "preset menu" included in the automatic control "adjust the set temperature of the air conditioner" is a control that automatically adjusts the set temperature of the air conditioner according to the preset menu.

[0191] Furthermore, the first characteristic "lazy" and the automatic control "adjusting the set temperature of the air conditioner" of the device 3 or the facility 5 are associated with the second characteristic "clumsy" and the detailed control "user customized menu" included in the automatic control "adjusting the set temperature of the air conditioner." The detailed control "user customized menu" included in the automatic control "adjusting the set temperature of the air conditioner" is a control that automatically adjusts the set temperature of the air conditioner according to a customized menu that is preset by the user.

[0192] 18 , the first characteristic "sensitive to heat" is also associated with the automatic control "adjust the set temperature of the air conditioner" of the device 3 or the facility 5. Furthermore, the first characteristic "sensitive to heat" and the automatic control "adjust the set temperature of the air conditioner" of the device 3 or the facility 5 are associated with the second characteristic "frugal" and the detailed control "saving mode" included in the automatic control "adjust the set temperature of the air conditioner", and the second characteristic "spendthrifty" and the detailed control "powerful mode" included in the automatic control "adjust the set temperature of the air conditioner".

[0193] The detailed control "saving mode" included in the automatic control "adjusting the set temperature of the air conditioner" is a control that automatically adjusts the set temperature of the air conditioner in saving mode. The detailed control "powerful mode" included in the automatic control "adjusting the set temperature of the air conditioner" is a control that automatically adjusts the set temperature of the air conditioner in powerful mode.

[0194] 18 , the first characteristic "cleanliness freak" is associated with the automatic control "set the cleaning robot's cleaning frequency to high" of the appliance 3 or the facility 5. The first characteristic "cleanliness freak" and the automatic control "set the cleaning robot's cleaning frequency to high" of the appliance 3 or the facility 5 are associated with the second characteristic "meticulous" and the detailed control "detailed log output" included in the automatic control "set the cleaning robot's cleaning frequency to high", and the detailed control "log output OFF" included in the second characteristic "lazy" and the automatic control "set the cleaning robot's cleaning frequency to high".

[0195] The detailed control "detailed log output" included in the automatic control "set cleaning frequency of cleaning robot to high" is a control that sets the cleaning frequency of the cleaning robot to high and sets it to output detailed log information about the cleaning work. The detailed control "log output OFF" included in the automatic control "set cleaning frequency of cleaning robot to high" is a control that sets the cleaning frequency of the cleaning robot to high and sets it to not output log information about the cleaning work.

[0196] The determiner 123 identifies a first characteristic that has content in common with the multiple characteristics included in the characteristic information acquired in step S400 ( FIG. 11 ), from among one or more first characteristics included in the fourth rule information acquired by the acquirer 121. Then, the determiner 123 identifies automatic control of the device 3 or facility 5 that corresponds to the identified first characteristic, from among automatic controls of the one or more devices 3 or facilities 5 included in the fourth rule information. The determiner 123 identifies the identified automatic control of the device 3 or facility 5 as a first element.

[0197] For example, suppose that the characteristic information acquired in step S400 ( FIG. 11 ) includes two characteristics, “lazy” and “dexterous,” and that the acquisition unit 121 acquires the fourth rule information shown in FIG.

[0198] In this case, the determination unit 123 identifies the first characteristic "lazy" from among the three first characteristics "lazy," "sensitive to heat," and "cleanliness" included in the fourth rule information, which has content in common with the two characteristics "lazy" and "dexterous" included in the characteristic information. Then, the determination unit 123 identifies the automatic control "adjust the set temperature of the air conditioner" of the device 3 or facility 5 from among the two automatic controls "adjust the set temperature of the air conditioner" and "set the cleaning frequency of the cleaning robot to a high frequency" of the device 3 or facility 5 included in the fourth rule information, which corresponds to the identified first characteristic "lazy." The determination unit 123 identifies the identified automatic control "adjust the set temperature of the air conditioner" of the device 3 or facility 5 as the first element.

[0199] In step S502 (FIG. 12), the determiner 123 identifies, from one or more second characteristics included in the fourth rule information acquired by the acquirer 121, a second characteristic that corresponds to the automatic control of the device 3 or facility 5 identified as the first element in step S501 and has content in common with the multiple characteristics included in the characteristic information acquired in step S400 (FIG. 11). Then, the determiner 123 identifies a detailed control that corresponds to the identified second characteristic from one or more detailed controls included in the automatic control of each device 3 or each facility 5 included in the fourth rule information. The determiner 123 identifies the identified detailed control as the second element.

[0200] For example, in the above example, the determination unit 123 identifies the second characteristic "Dexterous" from among the six second characteristics "Dexterous," "Clumsy," "Frugal," "Spendthrift," "Meticulous," and "Lazy" included in the fourth rule information ( FIG. 18 ), which corresponds to the automatic control "adjusting the set temperature of the air conditioner" of the appliance 3 or facility 5 identified as the first element in step S501 and has content in common with the two characteristics "Lazy" and "Dexterous" included in the characteristic information acquired in step S400 ( FIG. 11 ). Then, the determination unit 123 identifies the detailed control "preset menu" corresponding to the identified second characteristic "Dexterous" from among the six detailed controls included in the automatic control of each appliance 3 or each facility 5 included in the fourth rule information. The determination unit 123 identifies the identified detailed control "preset menu" as the second element.

[0201] In step S503 (Figure 12), the determination unit 123 determines that the automatic control service that performs the detailed control indicated by the second element identified in step S502 (Figure 12), which is included in the automatic control of the equipment 3 or facility 5 indicated by the first element identified in step S501 (Figure 12), is the service to be provided to the user.

[0202] In the above example, the determination unit 123 determines that the automatic control service to perform the detailed control "preset menu" indicated by the second element, which is included in the automatic control "adjusting the set temperature of the air conditioner" of the device 3 or facility 5 indicated by the first element, is the service to be provided to the user.

[0203] (4) In the configurations of the above embodiment and modified examples, suppose that the characteristic output process ( FIG. 3 ) is performed with each of a first user and a second user who are pre-registered as targets of the service information output process as target users. Thereafter, if the first user and the second user are present in the same space 40, the service information output process may be performed with each of the first user and the second user as target users. In this case, there is a risk that two or more competing services may be included in the multiset of services determined as services to be provided to each target user.

[0204] For example, suppose that the service to be provided to a first user is determined to be the service "automatic control of equipment or facilities" based on the first user's characteristic of "being sensitive to heat." The service "automatic control of equipment or facilities" is a service that automatically controls equipment 3 or facilities 5 present in the space 40 in which the user is present, according to the user's characteristic. Similarly, suppose that the service to be provided to a second user is determined to be the service "automatic control of equipment or facilities" based on the second user's characteristic of "being sensitive to cold."

[0205] In this case, when the service "automatic control of equipment or facilities" provided to the first user is executed, control information is output to the air conditioner in the space 40 where the first user is present to set the set temperature to "25 degrees" in accordance with the first user's characteristic of "sensitive to heat." On the other hand, when the service "automatic control of equipment or facilities" provided to the second user is executed, control information is output to the air conditioner in the space 40 where the second user is present to set the set temperature to "27 degrees" in accordance with the second user's characteristic of "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 the first user and the second user are present, will compete with each other.

[0206] Therefore, as described above, when the first user and the second user exist in the same environment, the service information output process is performed with each of the first user and the second user as a target user, and the service multiset determined in step S503 (FIG. 12) includes two or more conflicting services. In this case, in step S600 (FIG. 11), the output unit 124 may output service information indicating a service that avoids the conflict, as shown below.

[0207] Specifically, in step S600 (FIG. 11), the output unit 124 first determines whether the first user and the second user are present in the same environment.

[0208] In detail, the output unit 124 refers to matching data including the user ID of the first user stored in the user information storage unit 132, and acquires sensor information including detection information related to the space 40 in which the first user is present from the sensor information storage unit 134. The output unit 124 acquires sensor information including the most recent detection date and time from the acquired sensor information as information indicating the behavior of the first user in the space 40 in which the first user currently is present (hereinafter referred to as first behavior information). Similarly, the output unit 124 acquires information indicating the behavior of a second user in the space 40 in which a second user currently is present (hereinafter referred to as second behavior information).

[0209] The output unit 124 refers to the device information stored in the device information storage unit 131 and determines whether the space 40 in which the sensor 7 having the sensor ID included in the first behavior information is placed matches the space 40 in which the sensor 7 having the sensor ID included in the second behavior information is placed. If the output unit 124 determines that there is a match, it determines that the first user and the second user are in the same environment, and if it determines that there is a mismatch, it determines that the first user and the second user are not in the same environment.

[0210] If the output unit 124 determines that the first user and the second user do not exist in the same environment, it executes step S600 (FIG. 11) as described above, with each of the first user and the second user as the target users.

[0211] On the other hand, when the output unit 124 determines that the first user and the second user are not in the same environment, it acquires fifth rule information from the rule information storage unit 135. The fifth rule information is information that defines the relationship between one or more competing service groups indicating two or more competing services and a plurality of avoidance methods for avoiding conflicts caused by the two or more competing services included in each competing service group.

[0212] FIG. 19 is a diagram illustrating an example of fifth rule information. In the fifth rule information illustrated in FIG. 19, two competing service groups are associated with two avoidance methods. For example, in the fifth rule information illustrated in FIG. 19, a competing service group indicating two competing services, "Service A" and "Service B," is associated with an avoidance method, "Select Any One," for avoiding a conflict between the two competing services, "Service A" and "Service B," included in the competing service group. The avoidance method, "Select Any One," indicates that one competing service is selected from two or more competing services included in the competing service group. Hereinafter, the avoidance method, "Select Any One," will be referred to as the first method.

[0213] 19 , a competing service group including two competing services, "Service C1" and "Service C2," is associated with an avoidance method, "Merge," for avoiding a conflict between the two competing services, "Service C1" and "Service C2," included in the competing service group. The avoidance method, "Merge," indicates merging two or more competing services included in the competing service group. Hereinafter, the avoidance method, "Merge," will be referred to as the second method.

[0214] The output unit 124 refers to the fifth rule information and determines whether the multiset of services determined for each of the first user and the second user includes a service group whose content is common to the competitive service group. If the output unit 124 determines that the multiset of services whose content is common to the competitive service group includes the service group, the output unit 124 extracts the service group from the multiset of services.

[0215] For example, suppose that the multiset of services determined for each of the first user and the second user includes four services, "Service A," "Service B," "Service C," and "Service D." Furthermore, suppose that the output unit 124 acquires the fifth rule information shown in Fig. 19 . In this case, the output unit 124 extracts, from the multiset of services, a service group indicating two services, "Service A" and "Service B," whose content is common to the competing service group indicating two competing services, "Service A" and "Service B."

[0216] On the other hand, if the output unit 124 determines that the service group does not include a service group with content common to the competing service group, it executes step S600 (Figure 11) as described above, with the first user and the second user as target users.

[0217] In addition, the multiset of services may include not only a group of services that share content with the group of competing services, but also a group of services that are different from the group of competing services. In this case, the output unit 124 outputs service information indicating each service (in the above example, "service C" and "service D") included in the different group of services to the output device 6 used by the first user or the second user to whom each service is provided, in the same manner as in step S600 (FIG. 11).

[0218] When the output unit 124 extracts a group of services that share content with a group of competing services, it refers to the fifth rule information and determines whether the avoidance method corresponding to the group of competing services that share content with the group of competing services (hereinafter referred to as the target avoidance method) is the first method or the second method.

[0219] In the above example, the fifth rule information ( FIG. 19 ) associates a conflicting service group indicating two conflicting services, “Service A” and “Service B,” which share content with the service group extracted by the output unit 124, with the avoidance method “select one of them” (first method). Therefore, the output unit 124 determines that the target avoidance method is the first method.

[0220] If the output unit 124 determines that the target avoidance method is the first method, it acquires the strength of the first characteristic of the user to whom each service is provided for each of two or more services included in the extracted service group.

[0221] In the above example, the group of services extracted by the output unit 124 includes two services, "Service A" and "Service B." Therefore, the output unit 124 acquires the strength of the first characteristic of the first user or second user to whom the service "Service A" is provided, i.e., the maximum strength of the strengths of the multiple characteristics of the first user or second user. Similarly, the output unit 124 acquires the strength of the first characteristic of the first user or second user to whom the service "Service B" is provided.

[0222] Then, the output unit 124 selects one service from among the two or more services included in the extracted service group, based on the strength of the first characteristic acquired for each of the two or more services.

[0223] Specifically, the output unit 124 selects, as the one service, the service for which the greatest strength of the first characteristic is obtained from two or more services included in the extracted service group, and outputs information indicating the one selected service as service information.

[0224] For example, in the above example, assume that the output unit 124 acquires "0.5" as the strength of the first characteristic for the service "Service A" and "0.3" as the strength of the first characteristic for the service "Service B." In this case, the output unit 124 selects, as the single service, the service "Service A" for which the strength of the first characteristic of "0.5" is the greatest, from among the two services "Service A" and "Service B" included in the extracted service group.

[0225] Furthermore, the output unit 124 may select the one service in another predetermined manner, such as selecting the service with the smallest first characteristic strength among the two or more services included in the extracted service group, without being limited to the service with the largest first characteristic strength obtained.

[0226] Then, the output unit 124 outputs information indicating the selected service as service information, similar to step S600 (FIG. 11) described above.

[0227] On the other hand, if the output unit 124 determines that the target avoidance method is the second method, it acquires the strength of the second characteristic of the user to whom each service is provided for each of two or more services included in the extracted service group.

[0228] For example, suppose that two services, "Service C1" and "Service C2," are included in the service group extracted by the output unit 124. As a result, suppose that the output unit 124 refers to the fifth rule information shown in Fig. 19 and determines that the target avoidance method is the second method (the avoidance method "Merge").

[0229] In this case, the output unit 124 acquires the strength of the second characteristic of the first or second user to whom the service "Service C1" is provided, i.e., the strength that is next to the largest strength among the strengths of the multiple characteristics of the first or second user. Also, the output unit 124 acquires the strength of the second characteristic of the first or second user to whom the service "Service C2" is provided, i.e., the strength that is next to the largest strength among the strengths of the multiple characteristics of the first or second user.

[0230] Then, the output unit 124 merges the two or more services included in the extracted service group based on the strength of the second characteristic acquired for each of the two or more services. Hereinafter, the service obtained by merging the two or more services will be referred to as a merged service.

[0231] Specifically, the output unit 124 calculates the difference between the intensities of any two of the second characteristics obtained for each of the two or more services included in the extracted service group. For example, the output unit 124 calculates the difference between the maximum intensity of the second characteristic and the minimum intensity of the second characteristic among the intensities of the second characteristic obtained for each of the two or more services included in the extracted service group.

[0232] If the calculated difference is less than a predetermined value, the output unit 124 averages the parameters that compete between the two or more services and merges the two or more services. On the other hand, if the calculated difference is equal to or greater than a predetermined value, the output unit 124 determines the service with the greatest strength of the second characteristic among the two or more services as the merged service.

[0233] For example, in the above example, assume that the output unit 124 obtains "0.5" as the strength of the second characteristic for the service "Service C1" and "0.3" as the strength of the second characteristic for the service "Service C2." Also assume that the predetermined value is "0.3."

[0234] In this case, the output unit 124 calculates the difference "0.2" between the strength "0.5" of the second characteristic acquired for the service "Service C1" and the strength "0.3" of the second characteristic acquired for the service "Service C2." Because the calculated difference "0.2" is less than the predetermined value "0.3," the output unit 124 averages the parameters that conflict between the two services "Service C1" and "Service C2" and merges the two or more services.

[0235] For example, suppose that service "Service C1" is a service that automatically sets the set temperature of an air conditioner to "25 degrees," and service "Service C2" is a service that automatically sets the set temperature of an air conditioner to "27 degrees." In this case, the output unit 124 averages the set temperature of the air conditioner, which is a parameter that conflicts between the two services "Service C1" and "Service C2," to "26 degrees (= (25 degrees + 27 degrees) / 2)," and merges the two or more services. In other words, the merged service obtained by merging the two or more services is a service that automatically sets the set temperature of an air conditioner to "26 degrees."

[0236] On the other hand, suppose the predetermined value is 0.2. In this case, since the calculated difference of 0.2 is equal to or greater than the predetermined value 0.2, the output unit 124 determines that the service "Service C1" having the greatest second characteristic strength of 0.5 out of the two services "Service C1" and "Service C2" is the merged service.

[0237] Then, the output unit 124 outputs information indicating the merged service as service information, similar to step S600 (FIG. 11) described above.

[0238] Furthermore, in the configuration of this modified example (4), the priority assigned to each of the multiple candidate services included in the third rule information (Figures 15 and 16) by each of one or more users who have been pre-registered as targets of the service information output process may be stored in memory 13.

[0239] In addition, when the output unit 124 extracts a group of services that share content with a group of competing services, as shown below, the output unit 124 may identify a service that avoids a conflict between two or more services included in the group of services based on the above-described priority order.The output unit 124 may then output information indicating the identified service as service information.

[0240] Specifically, it is assumed that the output unit 124 extracts a group of services that share content with the group of competing services from the multiple sets of services determined for each of the first user and the second user. In this case, the output unit 124 obtains from the memory 13 the priorities that each of the first user and the second user has assigned to each of the multiple candidate services included in the third rule information (FIGS. 15 and 16 ).

[0241] The output unit 124 determines whether or not a priority has been assigned to candidate services that share content with each of the two or more services included in the extracted service group by the user to whom each service is provided.

[0242] For example, assume that a certain service included in the service group extracted by the output unit 124 is the service that has been determined to be provided to the first user. In other words, assume that the user to whom the service is to be provided is the first user.

[0243] In this case, when the output unit 124 has acquired from the memory 13 the priority assigned by the first user to the candidate service that shares content with the service in question, the output unit 124 determines that the user to whom the service is provided has assigned a priority to the candidate service that shares content with the service in question. On the other hand, when the output unit 124 has not acquired from the memory 13 the priority assigned by the first user to the candidate service that shares content with the service in question, the output unit 124 determines that the user to whom the service is provided has not assigned a priority to the candidate service that shares content with the service in question.

[0244] Similarly, when the user to whom a service included in the extracted service group is provided is a second user, the output unit 124 determines whether the user to whom the service is provided has assigned priority to candidate services that have content in common with the service in question.

[0245] Then, suppose that the output unit 124 determines that, for one or more of the two or more services included in the extracted service group, the user to whom each service is provided has assigned a priority to a candidate service that shares content with the service. In this case, the output unit 124 identifies the service to which the highest priority is assigned among the one or more services. Then, similar to step S600 ( FIG. 11 ) described above, the output unit 124 outputs information indicating the identified service as service information.

[0246] On the other hand, suppose that the output unit 124 determines that no priority has been assigned to any of the two or more services included in the extracted service group by the users to whom each service is provided. In this case, as described above, the output unit 124 refers to the fifth rule information ( FIG. 19 ) to determine whether the target avoidance method is the first method or the second method, and outputs service information indicating a service that avoids conflicts between the two or more services in accordance with the result of the determination.

[0247] (5) In the configuration of the above-described modified example (1), suppose that the characteristic output process (FIG. 3) is performed with each of the first user and the second user, who are pre-registered as targets of the service information output process, as the target users. After that, if the first user and the second user are present in the same space 40, the service information output process (FIG. 11) may be performed with each of the first user and the second user as the target users.

[0248] However, instead of this, when a first user and a second user exist in the same space 40, step S400 ( FIG. 11 ) may be performed with each of the first user and the second user as a target user. Whether or not the first user and the second user exist in the same space 40 may be determined in the same manner as in the above-described modified example (4).

[0249] In this case, information indicating a multiplex set of multiple characteristics included in the characteristic information of each of the first user and the second user acquired in step S400 may be used as characteristic information of a single user present in space 40 where the first user and the second user exist. Then, step S500 ( FIG. 11 ) and step S600 ( FIG. 11 ) may be performed with the single user as the target user.

[0250] (6) In the configurations of the above embodiment and modified examples, the rule information storage unit 135 may further store sixth rule information that defines the relationship between a plurality of element characteristics and one or more spaces 40.

[0251] For example, the sixth rule information associates the element characteristic "sensitive to heat" with the space ID of the space 40 where an air conditioner that is frequently used by a user with the characteristic "sensitive to heat" that shares content with the element characteristic is located. Also, the sixth rule information associates the element characteristic "lazy" with the space ID of the space 40 where a user with the characteristic "lazy" that shares content with the element characteristic stays for a long time.

[0252] In addition, as shown below, the sixth rule information may be used to restrict the multiple characteristics of the target user used to identify the first and second elements depending on the space 40 (environment) in which the target user currently exists.

[0253] Specifically, in step S501 ( FIG. 12 ), the acquisition unit 121 acquires not only the second rule information but also the sixth rule information from the rule information storage unit 135. In addition, the acquisition unit 121 acquires information indicating the space 40 in which the target user currently exists (hereinafter, environmental information).

[0254] In detail, the acquisition unit 121 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 output unit 124 acquires, from the acquired sensor information, sensor information including the most recent detection date and time as information indicating the target user's behavior in the space 40 in which the target user currently exists (hereinafter, behavior information). The acquisition unit 121 refers to the device information stored in the device information storage unit 131, and acquires, as environment information, the space ID of the space 40 in which the sensor 7 with the sensor ID included in the behavior information is located.

[0255] The acquisition unit 121 further acquires, from the sixth rule information, one or more element characteristics corresponding to the space 40 indicated by the environmental information.

[0256] Thereafter, in step S501 (FIG. 12), the determination unit 123 identifies the first element based on one or more characteristics among the multiple characteristics included in the characteristic information of the target user acquired in step S400 (FIG. 11) that have content in common with one or more element characteristics acquired by the acquisition unit 121 from the sixth rule information, instead of the multiple characteristics included in the characteristic information of the target user acquired in step S400 (FIG. 11).

[0257] Similarly, in step S502 (FIG. 12), the determination unit 123 identifies the second element based on one or more characteristics among the multiple characteristics included in the characteristic information of the target user acquired in step S400 (FIG. 11) that have content in common with one or more element characteristics acquired by the acquisition unit 121 from the sixth rule information, instead of the multiple characteristics included in the characteristic information of the target user acquired in step S400 (FIG. 11).

[0258] (7) In step S600 ( FIG. 11 ) in the configurations of the above-described embodiment and modified examples, the output unit 124 may output, together with the service information, request information to the output device 6 used by the target user, requesting a reply of information indicating whether or not the service indicated by the service information will be used. If the reply of information indicating that the service will not be used is received from the output device 6, the service determination process ( FIG. 12 ) may be re-executed, and step S600 ( FIG. 11 ) may be re-executed.

[0259] In step S502 (FIG. 12) when the service determination process (FIG. 12) is re-executed, the determination unit 123 may identify, as the second characteristic, a characteristic whose strength is next to the second characteristic identified in the previous service determination process, among the multiple characteristics included in the characteristic information. In this way, the service determined to be provided to the target user in the re-executed service determination process may be as different as possible from the service determined in the previous service determination process.

[0260] (8) In step S600 ( FIG. 11 ) in the configuration of the above-described variation (7), the output unit 124 may further output, to the output device 6 used by the target user, information requesting a reply of information indicating whether or not to permit output of subsequent service information (permission / denial request information). If the output device 6 returns information indicating that the service will not be used until the output device 6 returns information indicating that the output of subsequent service information is not permitted, the service determination process ( FIG. 12 ) may be re-executed, and step S600 ( FIG. 11 ) may be re-executed. In this case, the service information output process may be terminated if the output device 6 returns information indicating that the output of subsequent service information is not permitted.

[0261] (9) In the configurations of the above embodiment and modified examples, information indicating multiple services that the user has used in the past (hereinafter, “used services”) may be further stored in the user information storage unit 132. Then, the output unit 124 may output, to the output device 6 used by the target user, information suggesting that the target user stop using one or more used services that the target user has used in the past, as described below.

[0262] Specifically, in step S600 ( FIG. 11 ), the output unit 124 acquires information indicating a plurality of available services that the target user has used in the past from the user information storage unit 132. The output unit 124 refers to the third rule information ( FIGS. 15 and 16 ) stored in the rule information storage unit 135, and calculates the number of available services (hereinafter, target available services) that have content in common with the candidate services associated with the first element identified in step S501 ( FIG. 12 ) among the plurality of available services.

[0263] If the number of target services to be used is equal to or greater than a predetermined number, the output unit 124 outputs, together with the service information, information suggesting that the target user stop using the target services to the output device 6 used by the target user.

[0264] Alternatively, the user information storage unit 132 may store information indicating a plurality of used services and information indicating the frequency of use of each of the plurality of used services in association with each other.

[0265] In addition, in step S600 (FIG. 11), the output unit 124 may acquire information indicating a plurality of services used by the target user in the past and information indicating the frequency of use of each of the plurality of services from the user information storage unit 132. Then, the output unit 124 may calculate the number of target services in the same manner as described above.

[0266] In this case, when the number of target usage services is equal to or greater than a predetermined number, the output unit 124 may output, together with the service information, information to the output device 6 used by the target user suggesting stopping the usage of the target usage service with the lowest usage frequency among the predetermined number or more of target usage services, and using the service indicated by the service information.

[0267] (10) In step S500 ( FIG. 11 ) in the configurations of the above-described embodiment and modified examples, the determination unit 123 may determine a service to be provided to the target user based on a plurality of characteristics included in the target user's characteristic information acquired in step S400 ( FIG. 11 ) without executing the service determination process shown in FIG. This configuration can be realized, for example, as follows.

[0268] Specifically, seventh rule information associating one or more element characteristic groups each consisting of a plurality of element characteristics with one or more candidate services is stored in the rule information storage unit 135. In step S500 ( FIG. 11 ), the determination unit 123 refers to the seventh rule information and determines, as a service to be provided to the target user, a candidate service associated with an element characteristic group including a plurality of element characteristics whose contents are common to the plurality of characteristics included in the characteristic information of the target user acquired in step S400 ( FIG. 11 ).

[0269] In addition, the present disclosure may be implemented by arbitrarily combining the above-described embodiments and modifications (1) to (10).

[0270] The present disclosure is useful in providing services according to multiple characteristics of a user that are inferred from the user's operation or behavior of a device.

Claims

1. An information processing method by a computer, comprising: acquires operation information indicating at least one of a device operation and a behavior of a user; Estimating a plurality of characteristics of the user based on the motion information; Identifying a first element for identifying a service to provide to the user based on the plurality of characteristics; Identifying a second element associated with the first element based on the plurality of characteristics; determining the service based on the first factor and the second factor; outputting service information indicating the service; Information processing methods.

2. Further, information defining a relationship between a plurality of element characteristics, one or more first candidate elements, and one or more second candidate elements is acquired; In identifying the first element, For each of the one or more first candidate elements, a first number indicating the number of characteristics among the plurality of characteristics that have content in common with the element characteristic is calculated; identifying a first candidate element having the largest first number from the one or more first candidate elements, and identifying the identified first candidate element as the first element; In identifying the second element, For each of the one or more second candidate elements, a second number indicating the number of characteristics among the plurality of characteristics that have content in common with the element characteristic is calculated; identifying a second candidate element having the largest second number from the one or more second candidate elements, and identifying the identified second candidate element as the second element; In determining the service, acquiring rule information that defines a relationship between one or more first elements, one or more second elements, and a plurality of candidate services; identifying a candidate service corresponding to the first element and the second element from among the plurality of candidate services, and determining the identified candidate service as the service; The information processing method according to claim 1 .

3. Furthermore, calculating an intensity of each of the plurality of characteristics based on the operation information; Further, information defining a relationship between a plurality of element characteristics, one or more first candidate elements, and one or more second candidate elements is acquired; In identifying the first element, Identifying a first characteristic having the greatest strength among the plurality of characteristics, identifying a first candidate element corresponding to an element characteristic having content common to the first characteristic from among the one or more first candidate elements, and identifying the identified first candidate element as the first element; In identifying the second element, Identifying a characteristic having the second largest strength after the first characteristic among the plurality of characteristics as a second characteristic, identifying a second candidate element corresponding to an element characteristic having a common content with the second characteristic from the one or more second candidate elements, and identifying the identified second candidate element as the second element; In determining the service, acquiring rule information that defines a relationship between one or more first elements, one or more second elements, and a plurality of candidate services; identifying a candidate service corresponding to the first element and the second element from among the plurality of candidate services, and determining the identified candidate service as the service; The information processing method according to claim 1 .

4. the one or more first elements are any of a service field to which the plurality of candidate services belong, a type of the plurality of candidate services, an execution timing of the plurality of candidate services, and an execution method of the plurality of candidate services; the one or more second elements are any of the service field, the type, the execution timing, and the execution method that are different from the one or more first elements; 4. The information processing method according to claim 2 or 3.

5. Furthermore, calculating an intensity of each of the plurality of characteristics based on the operation information; further acquiring information defining a relationship between one or more first characteristics, one or more automatic controls of the devices, one or more second characteristics, and one or more detailed controls included in the automatic controls of the devices; In identifying the first element, Identifying a first characteristic from the one or more first characteristics that has a common content with the plurality of characteristics; Identifying an automatic control of a device corresponding to the identified first characteristic from among the automatic controls of the one or more devices, and identifying the identified automatic control of the device as the first element; In identifying the second element, Identifying a second characteristic from the one or more second characteristics that corresponds to automatic control of the device identified as the first element and has content in common with the plurality of characteristics; Identifying a detailed control corresponding to the identified second characteristic from among the one or more detailed controls, and identifying the identified detailed control as the second element; In determining the service, determining, as the service, an automatic control service that performs the detailed control indicated by the second element and that is included in the automatic control of the device indicated by the first element; The information processing method according to claim 1 .

6. The users include a first user and a second user; When the first user and the second user are in the same environment, acquiring the motion information and estimating the plurality of characteristics for each of the first user and the second user; Identifying the first element and the second element by using a multiset of the plurality of characteristics estimated for each of the first user and the second user as the plurality of characteristics estimated for the user; determining the service and outputting the service information; The information processing method according to claim 2 .

7. The users include a first user and a second user; When the first user and the second user are in the same environment, acquiring the motion information, estimating the plurality of characteristics, calculating the strength of each of the plurality of characteristics, identifying the first element, identifying the second element, and determining the service for each of the first user and the second user; Furthermore, information is acquired that defines a relationship between one or more conflicting service groups indicating two or more conflicting services and a plurality of avoidance methods for avoiding the conflict; the plurality of avoidance methods include a first method of selecting one competing service from the two or more competing services, and a second method of merging the two or more competing services; extracting a service group having a content common to a competitive service group from the multiset of services determined for each of the first user and the second user; determining whether a target avoidance method, which is an avoidance method corresponding to a conflicting service group having content common to the service group, is the first method or the second method; When the object avoidance method is the first method, For each of two or more services included in the group of services, a strength of the first characteristic of a user to whom each service is provided is acquired; selecting one service from the two or more services based on the strength of the first characteristic acquired for each of the two or more services, and outputting information indicating the one service as the service information; When the object avoidance method is the second method, For each of the two or more services, obtain the strength of the second characteristic of the user who is a destination of each service; merging the two or more services based on the strength of the second characteristic acquired for each of the two or more services, and outputting information indicating the merged service as the service information. The information processing method according to claim 3 .

8. Further, information defining a relationship between the plurality of element characteristics and one or more environments is acquired; Furthermore, environmental information indicating the environment in which the user currently resides is acquired; further acquiring, from the plurality of element characteristics, one or more element characteristics corresponding to an environment indicated by the environmental information among the one or more environments; In identifying the first element and the second element, Instead of the plurality of characteristics, one or more characteristics that have a common content with the one or more element characteristics are used.

4. The information processing method according to claim 2 or 3.

9. In the output of the service information, outputting, together with the service information, request information requesting a reply of information indicating whether or not the service indicated by the service information is to be used, to an output device used by the user; when information indicating that the service will not be used is returned from the output device, re-executing the identification of the first element, the identification of the second element, the determination of the service, and the output of the service information; In identifying the second characteristic in identifying the second element at the time of re-execution, a characteristic having a second largest strength after the second characteristic among the plurality of characteristics is identified as the second characteristic. The information processing method according to claim 3 .

10. Furthermore, information indicating a plurality of services used by the user in the past is acquired; The output of the service information further includes: Calculating the number of target use services that are use services having content common to the candidate service associated with the identified first element in the rule information among the plurality of use services; If the number of the target services to be used is equal to or greater than a predetermined number, information suggesting that the user stop using the target services to be used is output together with the service information to an output device used by the user.

4. The information processing method according to claim 2 or 3.

11. Furthermore, information indicating a plurality of services used by the user in the past and the frequency of use of each of the plurality of services is acquired; The output of the service information further includes: Calculating the number of target use services that are use services having content common to the candidate service associated with the identified first element in the rule information among the plurality of use services; If the number of target use services is equal to or greater than a predetermined number, outputting, together with the service information, information suggesting stopping use of the target use service with the lowest usage frequency among the predetermined number or more target use services, and using the service indicated by the service information to an output device used by the user.

4. The information processing method according to claim 2 or 3.

12. an acquisition unit that acquires operation information indicating at least one of a device operation and a behavior of a user; an estimation unit that estimates a plurality of characteristics of the user based on the motion information; a determination unit that determines a service to be provided to the user based on the plurality of characteristics; an output unit that outputs service information indicating the service; Equipped with The determination unit Identifying a first element for identifying the service based on the plurality of characteristics; Identifying a second element associated with the first element based on the plurality of characteristics; determining the service based on the first factor and the second factor; Information processing device.

13. A program that causes a computer to function, The computer an acquisition unit that acquires operation information indicating at least one of a device operation and a behavior of a user; an estimation unit that estimates a plurality of characteristics of the user based on the motion information; a determination unit that determines a service to be provided to the user based on the plurality of characteristics; an output unit that outputs service information indicating the service; It functions as The determination unit Identifying a first element for identifying the service based on the plurality of characteristics; Identifying a second element associated with the first element based on the plurality of characteristics; determining the service based on the first factor and the second factor; program.