Device control apparatus, computer-readable recording medium, and device control method

Abstract

An apparatus control device (110) has a character information acquisition section that acquires character information indicating a character of a user, a control method determination section (115) that determines a control method of an apparatus (101) used by the user, i.e., an apparatus control method, based on the character information and a life pattern of the user, and a control section (116) that controls the apparatus (101) in accordance with the apparatus control method.

Description

TECHNICAL FIELD

[0001] The present application relates to an apparatus control device, a computer-readable recording medium, and an apparatus control method. BACKGROUND

[0002] In the past, a user-specific life pattern is extracted from a user's use history of an apparatus, and by using the life pattern, an apparatus control that matches the user's life pattern and situation is performed. For example, in Patent Literature 1, there is disclosed a technique of generating experience data in which contents associated with a specific experience are combined as element data from life data, a technique of analyzing the relationship between the element data included in the experience data, a technique of determining a user-specific life pattern from the relationship between the element data, and a technique of controlling an apparatus using the user's life pattern information.

[0003] PRIOR ART DOCUMENTS

[0004] PATENT LITERATURE

[0005] Patent Literature 1: Japanese Patent No. 3744932 SUMMARY

[0006] PROBLEMS TO BE SOLVED BY THE INVENTION

[0007] However, whether or not a user desires an apparatus control using a life pattern depends on the user's personality. Therefore, when a control content is determined only using a life pattern, a specific user feels that the control content is not desirable. Therefore, there is a problem that the specific user does not continue to use an apparatus control service thereafter, or the satisfaction with the apparatus control service becomes low.

[0008] Therefore, according to one or more embodiments of the present application, it is an object to be able to perform an apparatus control that corresponds to a user's life pattern and the user's personality.

[0009] MEANS FOR SOLVING THE PROBLEMS

[0010] An apparatus control device according to one embodiment of the present application is characterized by including a personality information acquisition section that acquires personality information indicating a user's personality, a control method determination section that determines a control method of an apparatus, i.e., an apparatus control method, used by the user, based on the personality information and a life pattern of the user, and a control section that controls the apparatus in accordance with the apparatus control method.

[0011] The program of one embodiment of the present application is characterized in that the program causes a computer to function as: a character information acquisition unit that acquires character information indicating a character of a user; a control method determination unit that determines a control method of an apparatus, i.e., an apparatus control method, used by the user in accordance with the character information and a life pattern of the user; and a control unit that controls the apparatus in accordance with the apparatus control method.

[0012] The apparatus control method of one embodiment of the present application is characterized by acquiring character information indicating a character of a user, determining a control method of an apparatus, i.e., an apparatus control method, used by the user in accordance with the character information and a life pattern of the user, and controlling the apparatus in accordance with the apparatus control method.

[0013] Effects of Invention

[0014] According to one or more embodiments of the present application, it is possible to perform apparatus control corresponding to a life pattern of a user and a character of the user. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 FIG. 1 is a block diagram schematically illustrating the structure of an apparatus control system including an apparatus control device of Embodiments 1 and 2.

[0016] Figure 2 FIG. 3 is a schematic view illustrating an example of life data.

[0017] Figure 3 FIG. 4 is a graph illustrating an example of a life pattern in Embodiment 1.

[0018] Figure 4 (A) and (B) of FIG. 5 are block diagrams illustrating examples of hardware structures.

[0019] Figure 5 FIG. 6 is a flowchart illustrating an example of the overall operation of the apparatus control device.

[0020] Figure 6 FIG. 7 is a flowchart illustrating the operation of the control method determination unit.

[0021] Figure 7 FIG. 8 is a graph for explaining a first example of determining an apparatus control method.

[0022] Figure 8 FIG. 9 is a graph for explaining a second example of determining an apparatus control method.

[0023] Figure 9 FIG. 10 is a graph for explaining a third example of determining an apparatus control method.

[0024] Figure 10 FIG. 11 is a graph for explaining a fourth example of determining an apparatus control method.

[0025] Figure 11 is a flowchart showing the operation of the control section.

[0026] Figure 12 is a table showing an example of the life pattern in Embodiment 2.

[0027] Figure 13 is a table for explaining a first example of a device control method determined in accordance with the frequency of device linkage.

[0028] Figure 14 is a table for explaining a second example of a device control method determined in accordance with the frequency of device linkage.

[0029] Figure 15 is a table for explaining a third example of a device control method determined in accordance with the frequency of device linkage.

[0030] Figure 16 is a table for explaining a fourth example of a device control method determined in accordance with the frequency of device linkage. DETAILED DESCRIPTION

[0031] Embodiment 1

[0032] Figure 1 is a block diagram schematically showing the structure of a device control system 100 having a device control apparatus 110 of Embodiment 1.

[0033] The device control system 100 has devices 101A, 101B, a sensor 102, a user device 103, and the device control apparatus 110.

[0034] The devices 101A, 101B are objects controlled by the device control apparatus 110. The devices 101A, 101B are, respectively, air conditioners, televisions, refrigerators, induction cookers, microwave ovens, EcoCute, or lighting, and the like.

[0035] Here, the devices 101A, 101B are referred to as devices 101, respectively, without the need to particularly distinguish the devices 101A, 101B, respectively. In the device control system 100, there can be one device 101, or there can be two or more devices 101.

[0036] The sensor 102 is a sensor that detects a predetermined object, such as a human sensor, an opening / closing sensor, a hygrometer, a light meter, a carbon dioxide concentration meter, a pressure sensor, or an acceleration sensor.

[0037] The sensor 102 can also be built into any one of the devices 101. Further, in the device control system 100, there can be one or more sensors 102, or there can be no sensor 102.

[0038] The user device 103 is a device such as a smartphone or a smart speaker that delivers information to a user who utilizes the device 101 that becomes a control target and accepts input from the user.

[0039] In addition, the device 101 such as a television or a refrigerator can also function as the user device 103. In a case where there are a plurality of users who utilize the device 101 that becomes a control target, there can also be a plurality of user devices 103, and each user holds each user device 103.

[0040] The device control apparatus 110 controls the device 101.

[0041] As shown in FIG. 1, the device control apparatus 110 has a communication section 111, a life data storage section 112, a life pattern extraction section 113, a character information acquisition section 114, a control method determination section 115, and a control section 116. Figure 1

[0042] The communication section 111 is an interface that communicates with the device 101, the sensor 102, or the user device 103.

[0043] The life data storage section 112 stores life data.

[0044] The life data indicates at least a history of a plurality of events related to the device 101. A history of a plurality of events related to the sensor 102 can also be included in the life data.

[0045] The history of a plurality of events is, for example, an operation history or an action history of the device 101 or the sensor 102. The operation is, for example, an on operation, an off operation, a setting change operation, a timer setting operation, or the like. The action is, for example, an action start, an action completion, an action change, a detection of the sensor 102, a periodic measurement value acquisition of the sensor 102, or the like.

[0046] Figure 2 is a schematic diagram showing an example of the life data.

[0047] As shown in FIG. 1, the life data 120 is table information having an event date and time column 120a, a category column 120b, and an event content column 120c. Figure 2 The event date and time column 120a stores a date and time at which an event is performed.

[0048] The category column 120b stores a category of the device 101 or the sensor 102 at which an event is performed.

[0049]

[0050] ​​The event content column 120c stores information indicating event content that has occurred. In the event content column 120c, for example, detection of the sensor 102, use (for example, an ON operation) or stop (for example, an OFF operation) of a function that the device 101 has, or the like can be stored. In addition, in a case where the device 101 has only one function, use or stop of the device 101 can also indicate use or stop of the one function.

[0051] In addition, in the life data 120, in addition to this, identification information, that is, an ID, or the like for identifying the device 101 or the sensor 102 can be included.

[0052] Further, in Figure 2 In the example of FIG. 1, a case where the device 101A is an air conditioner, the device 101B is a television, and the sensor 102 is a human sensor is shown, but the device 101 and the sensor 102 that are connected to the device control apparatus 110 and store the history are not limited to these.

[0053] Further, as Figure 2 indicated in FIG. 1, event content related to the device 101 is not limited to ON and OFF. For example, if it is an air conditioner, it can also be event content such as a set temperature change operation or a temperature measured by a thermometer built in the air conditioner exceeding a threshold value that is set in advance.

[0054] Returning to Figure 1 , the life pattern extraction section 113 extracts a life pattern from the life data stored in the life data storage section 112.

[0055] The life pattern in Embodiment 1 is the frequency of use of each function of each device 101 by each time or the like.

[0056] For example, in the life data, as a plurality of events related to the device 101, a plurality of operations with respect to the function of the device 101 are included. Further, the life pattern extraction section 113 extracts the frequency of each of the plurality of operations for each predetermined time period as a life pattern by referring to the life data and calculating the frequency of each of the plurality of operations performed for each predetermined time period.

[0057] Figure 3 is a graph showing an example of the life pattern in Embodiment 1.

[0058] Figure 3 is a graph showing the frequency of use of cooling of the air conditioner by each time.

[0059] The life pattern in Embodiment 1 is the frequency for each predetermined time period, which is the number of times of use of a specific function (here, cooling) in each time period within a specific period divided by the number of days of the specific period.

[0060] Here, the specific period is, for example, a predetermined period (e.g., the past 1 month) from the date on which the extraction of the life pattern is performed. The specific period can also be changed as needed.

[0061] Further, the life pattern extraction section 113 can also divide the specific period into weekdays and holidays, separately calculate the frequency of each time period within each period, and set the life pattern. This enables device control that matches the life pattern of each of the weekdays and holidays, and is therefore preferable.

[0062] Further, with respect to the life pattern, in addition to the frequency calculated for each time period, for example, the frequency of using the function for each value of the room temperature or the like can also be used.

[0063] The time period can be determined in advance in a manner shorter than the above-described specific period, for example, such as 30 minutes or the like.

[0064] Returning to Figure 1 The personality information acquisition section 114 acquires personality information indicating the personality of the user who uses the device 101.

[0065] The personality information is, for example, the Big Five personality traits. The Big Five personality traits, also referred to as the Five-Factor Model, attribute personality (personality) using five parameters of openness, conscientiousness, extraversion, agreeableness, and emotional stability. That is, the personality information can include such parameters in an element. The Big Five personality traits are described in detail in the following document.

[0066] John, Oliver P., Laura P. Naumann, and Christopher J. Soto. "Paradigm shift to the integrative big five trait taxonomy." Handbook of personality: Theory and research 3.2 (2008), pp. 114-158

[0067] Openness indicates the degree of liking new experiences or variety, and can also be referred to as openness to experience.

[0068] Conscientiousness indicates the degree of having an upward tendency and a tendency to achieve goals or a tendency to like planned actions, and can also be referred to as honesty.

[0069] Extraversion indicates the degree of liking interaction or conversation with others.

[0070] Agreeableness indicates the degree of a tendency to cooperate with others, and can also be referred to as harmony or nostalgia.

[0071] Emotional stability indicates the degree of the tendency to be stable in character and not to easily experience unpleasant emotions, and the opposite thereof can also be called the tendency to neurosis.

[0072] Further, the character information can also include, for example, a parameter indicating the strength of self-control as an element. Self-control is described in detail in the following document.

[0073] Tangney, June P., Roy F. Baumeister, and Angie Luzio Boone. "High self-control predicts good adjustment, less pathology, better grades, and interpersonal succes." Journal of personality 72.2 (2004), pp. 271-324

[0074] Self-control refers to the suppression of an action that is not preferred in favor of an action that is preferred when faced with temptation or impulse.

[0075] In addition, in the character information, other parameters for which definitions and measurement methods have been established in the field of psychology can also be included. In addition, in a case where a plurality of users exist who use the device 101, it is preferable that the character information be present in the amount of a plurality of persons of these users.

[0076] Further, the character information acquisition unit 114 can acquire the character information, for example, by conducting a questionnaire survey related to character to the user. The questionnaire survey can be conducted using the user device 103, or can be conducted face-to-face at the time of purchase of the device 101. The character information acquisition unit 114 can acquire a score value of a personality standard that has been measured, via a network or the like, or can be acquired by user input.

[0077] Further, regarding the character information, for example, information estimated from operation history or writing history of "like!" and the like according to SNS (Social Network Service) can also be acquired via a network or the like. The method of such acquisition is described in detail in the following document.

[0078] Youyou, Wu, Michal Kosinski, and David Stillwell. "Computer-based personality judgments are more accurate than those made by humans." Proceedings of the National Academy of Sciences 112.4 (2015), pp. 1036-1040

[0079] Further, regarding the personality information, information estimated from an operation history, a motion history, or a saved content of a user device such as a smartphone, or the like can be acquired via a network or the like. Such an estimation method is described in detail in the following document.

[0080] Stachl, Clemens, et al. "Predicting personality from patterns of behavior collected with smartphones." Proceedings of the National Academy of Sciences 117.30 (2020), pp. 17680-17687

[0081] In addition, the user device used when acquiring the personality information can be the same as the user device 103 shown in Figure 1 , and can be another user device.

[0082] Further, in a case where a plurality of users use the device 101 and the personality information of the plurality of users is acquired, the acquisition method based on the questionnaire or the estimation, or the like is repeated by the number of people, and thus the personality information can be acquired.

[0083] Further, it is preferable that the user using the device 101 be registered for each of the devices 101 that are control targets, and the control of the device 101 corresponding to the personality of the user using the device 101 be performed. At this time, the frequency of use or the time period is set for each user, the accuracy of specifying the user using can be improved, and thus the control of the device 101 corresponding to the personality of the user is performed, and thus it is preferable.

[0084] Further, it is preferable that the user be able to be recognized by a sensor or the like in advance. The sensor for recognizing a person can be the same as the sensor 102 shown in Figure 1 , and can be another sensor. For example, the sensor is a camera built in the device 101, and by pre-registering the face image of the user, the recognition of the person using the device 101 can be performed.

[0085] Furthermore, the sensor is a fingerprint sensor attached to the operation button of device 101, which can also identify the user. In addition, when the user operates device 101 using voice, the user can also be identified based on voice information. Furthermore, when the user operates device 101 via a separately held user device, the user can be identified based on the registration information of the user device used during operation.

[0086] The control method determination unit 115 determines the control method of the device 101, i.e., the device control method, based on the lifestyle pattern extracted by the lifestyle pattern extraction unit 113 and the personality information obtained by the personality information acquisition unit 114.

[0087] For example, the control method determination unit 115 determines a threshold based on personality information, compares the determined threshold with a lifestyle pattern, and thereby determines the control method of the device 101.

[0088] Specifically, the control method determination unit 115 determines the device control method in the following manner: by referring to personality information, a threshold is determined based on the user's personality, and when the frequency represented by the lifestyle pattern exceeds the threshold, control related to the corresponding operation is performed during the corresponding time period.

[0089] In Embodiment 1, the control method determination unit 115 determines a first device control method and a second device control method as device control methods. The first device control method refers to automatically performing a corresponding operation as control when a first threshold (which is a threshold value) is exceeded. The second device control method refers to recommending performing a corresponding operation as control when a second threshold (which is a threshold value lower than the first threshold value) is exceeded. Details of the method for determining the device control method will be described later.

[0090] The control unit 116 controls the equipment 101 according to the equipment control method determined by the control method determination unit 115.

[0091] For example, Figure 4 As shown in (A), some or all of the above-described lifestyle pattern extraction unit 113, personality information acquisition unit 114, control method determination unit 115, and control unit 116 can be constituted by a memory 10 and a processor 11, such as a CPU (Central Processing Unit), that executes the program stored in the memory 10. This program can be provided via a network, or it can be provided by recording on a recording medium. That is, this program can also be provided as a program product, for example. In this case, the device control device 110 can be implemented using a so-called computer.

[0092] In addition, for example, Figure 4As illustrated in (B), a part or all of the life pattern extraction section 113, the personality information acquisition section 114, the control method determination section 115, and the control section 116 can also be constituted by the processing circuit 12 such as a single circuit, a composite circuit, a processor that acts using a program, a parallel processor that acts using a program, an ASIC (Application Specific Integrated Circuit), or an FPGA (Field Programmable Gate Array).

[0093] As described above, the life pattern extraction section 113, the personality information acquisition section 114, the control method determination section 115, and the control section 116 can be realized by a processing circuit network.

[0094] In addition, the life data storage section 112 can be constituted by a memory such as a ROM (Read Only Memory) or a RAM (Random-access Memory), a storage medium such as an HDD (Hard Disc Drive) or an SSD (Solid State Drive), or the like.

[0095] Further, the communication section 111 can be constituted by a communication device such as a NIC (Network Interface Card).

[0096] In addition, the life data storage section 112, the life pattern extraction section 113, the personality information acquisition section 114, the control method determination section 115, or the control section 116 can exist on a cloud server, can be a separate device, and can also be built into either of the device 101 or the sensor 102. Further, these structures can also be divided into a plurality of parts and exist in the above-described forms respectively.

[0097] Next, the operation of the device control device 110 will be described.

[0098] Figure 5 is a flowchart illustrating an example of the overall operation of the device control device 110.

[0099] First, the communication section 111 receives life data from the device 101, the sensor 102, and the like, and causes the life data storage section 112 to store the life data (S10).

[0100] The life pattern extraction section 113 extracts a life pattern from the stored life data (S11).

[0101] The personality information acquisition section 114 acquires personality information of the user via the communication section 111 (S12).

[0102] The control method determination section 115 determines a control method of the device 101, i.e., a device control method, based on the life pattern and the personality information (S13).

[0103] The control section 116 controls the device 101 in accordance with the device control method determined by the control method determination section 115 (S14).

[0104] Next, the device control method determined in step S13 will be described. Figure 5

[0105] In Embodiment 1, as the device control method, automatic control and recommendation are performed.

[0106] The automatic control is a device control method in which an operation that is significantly frequent in the life pattern and that is highly likely to be performed by the user is automatically performed. The device control method in which the automatic control is performed is also referred to as a first device control method.

[0107] The recommendation is a device control method in which, with respect to an operation that is frequent in the life pattern and that is highly likely to be performed by the user, the user is notified in advance of performing the operation, and if the user accepts, the control is performed. The device control method in which the recommendation is performed is also referred to as a second device control method.

[0108] Figure 6 is a flowchart showing the operation of the control method determination section 115.

[0109] The control method determination section 115 decides a threshold value of the automatic control, i.e., an automatic control threshold value, based on the personality information acquired by the personality information acquisition section 114 (S20). The automatic control threshold value is also referred to as a first threshold value.

[0110] The control method determination section 115 decides an object operation and a time at which the automatic control is performed, based on the life pattern extracted by the life pattern extraction section 113 and the automatic control threshold value decided in step S20 (S21). The time here can be any time of the corresponding time period. For example, it can be a time at which the time period starts, i.e., a start time, it can be a time in the middle of the time period, i.e., a middle time, or it can be a time at which the time period ends, i.e., an end time. Further, it can be a time at which an average of events is performed, i.e., an average time, used when the threshold value is calculated.

[0111] Further, the control method determination section 115 decides a threshold value of the recommendation, i.e., a recommendation threshold value, based on the personality information acquired by the personality information acquisition section 114 (S22). The recommendation threshold value is also referred to as a second threshold value.

[0112] ​The control method determination section 115 determines the target operation and the time for which the recommendation is made, based on the life pattern extracted by the life pattern extraction section 113 and the recommendation threshold determined in step S22 (S23). The time here can be any time in the corresponding time period. For example, it can be the time at which the time period starts, i.e., the start time, or the time in the middle of the time period, i.e., the middle time, or the time at which the time period ends, i.e., the end time. Further, it can be the average time at which the event is averaged, which is used when the threshold is calculated.

[0113] Here, the determination of the threshold in steps S20 to S23 and the determination of the target operation and the time for which the control is made will be described in detail. Figure 6

[0114] Figure 7 is a graph for explaining the first example of the determination of the device control method.

[0115] In the example of Figure 7 , the following example is explained: the device 101 is an air conditioner, and the control method is determined based on the frequency at which the cooling is turned on. Here, it is assumed that the character information of the user is average. For example, in the character information, all of the parameters indicating openness, diligence, extroversion, coordination, emotional stability, and self-control are sometimes included in a predetermined numerical range. The numerical range here can be the same for all parameters, or can be different for each parameter.

[0116] In this case, the control method determination section 115, for example, determines the automatic control threshold ATh for turning the cooling of the device 101 from off to on to be 90%, which is the automatic control reference threshold, and determines the recommendation threshold RTh for turning the cooling of the device 101 from off to on to be 50%, which is the recommendation reference threshold.

[0117] Further, the control method determination section 115, in the case where the frequency at which the cooling of the air conditioner as the device 101 is turned on exceeds the automatic control threshold ATh, performs the automatic control for turning on the cooling of the air conditioner, the time for which the automatic control is performed being the time at which the frequency exceeds the automatic control threshold ATh.

[0118] Further, the control method determination section 115, in the case where the frequency at which the cooling of the air conditioner is turned on exceeds the recommendation threshold RTh, performs the recommendation for turning on the cooling of the air conditioner, the time for which the recommendation is performed being the time at which the frequency exceeds the recommendation threshold RTh.

[0119] In the example of Figure 7 , the control method determination section 115 determines the device control method in which the recommendation for turning on the cooling of the air conditioner is performed at 6:00 and the automatic control for turning on the cooling of the air conditioner is performed at 6:21.

[0120] ​Here, the control method determination unit 115 may also apply a rule to the device control method that prevents unnecessary control from being executed when the frequency of function activation of device 101 fluctuates around a threshold. For example, a rule that prevents automatic control related to the same operation from being performed 30 minutes after the time of automatic control or a rule that prevents recommendations related to the same operation from being made 30 minutes after the time of recommendation may also be applied to the device control method.

[0121] Furthermore, the control method determination unit 115 can also control the function of the device 101 to change from on to off based on the frequency of the device 101’s function being turned on.

[0122] For example, the control method determination unit 115 may determine the automatic control threshold in the control that changes the function of the device 101 from on to off as an automatic control reference threshold of 10%, and determine its recommended threshold as a recommended reference threshold of 50%.

[0123] In addition, Figure 7 In the example, the equipment control method is determined based on the frequency of the air conditioner's cooling operation. However, similarly, the equipment control method can also be determined based on the frequency of the function of the equipment 101 other than the air conditioner, the frequency of using specific functions that are not turned on, the frequency of the value measured by the sensor 102 exceeding the threshold, etc.

[0124] Next, the control method determination unit 115 will be described in a way that makes it easier for the device to be controlled by determining a threshold based on the user's personality information.

[0125] Figure 8 This is a graph used to illustrate the second example of determining the equipment control method.

[0126] In cases where device control would improve the effectiveness of services based on device control, such as when a user has high openness, high emotional stability, low diligence, or low self-control, the control method determination unit 115 lowers the control threshold to make device control easier to occur.

[0127] For example, in personality information, openness is sometimes higher than the predetermined value range, emotional stability is sometimes higher than the predetermined value range, diligence is sometimes lower than the predetermined value range, or self-control is sometimes lower than the predetermined value range.

[0128] In this case, the control method determination section 115 determines the automatic control threshold value ATh to be 80% lower than the automatic control reference threshold value and determines the recommendation threshold value RTh to be 40% lower than the recommendation reference threshold value, for example. At this time, the control method determination section 115 determines the device control method of making the recommendation to turn on the cooling of the air conditioner at 5:59 and making the automatic control to turn on the cooling of the air conditioner at 6:11. Thus, compared to the case where the personality information is averaged Figure 7 , the timing of the control is advanced. Further, by lowering the threshold value, the frequency of the device control increases.

[0129] For example, in a case where the openness is high in the personality information of the user, the tendency to like is high in that the automatic control or the recommendation by the device control apparatus 110 is understood as a new experience or variety in life. Further, for example, in a case where the emotional stability is high in the personality information of the user, the possibility that the control by the device control apparatus 110 is not liked is small. Thus, by performing the device control earlier as described above or increasing the frequency, the user is not caused to feel unpleasant, and the service effect based on the device control can be improved.

[0130] Further, for example, in a case where the diligence is low or the self-control is low in the personality information of the user, the user's planned action is assisted by the device control apparatus 110, and thus, there is a large margin in that the user's action becomes a desired action. Thus, by performing the device control earlier as described above or increasing the frequency, the user can be more strongly assisted, and the service effect based on the device control can be improved.

[0131] Next, a case where the control method determination section 115 determines the threshold value according to the personality information of the user so that the device control does not easily occur will be described.

[0132] Figure 9 is a graph for explaining a third example of determining a device control method.

[0133] In a case where the service effect based on the device control is improved when the device control does not easily occur in the personality information of the user, for example, in a case where the openness of the user is low, in a case where the emotional stability is low, in a case where the diligence is high, or in a case where the self-control is high, the control method determination section 115 makes the device control not easily occur by increasing the threshold value of the control.

[0134] For example, in the personality information, the openness is sometimes lower than a predetermined numerical range, the emotional stability is sometimes lower than a predetermined numerical range, the diligence is sometimes higher than a predetermined numerical range, or the self-control is sometimes higher than a predetermined numerical range.

[0135] In this case, the control method determination section 115 determines the automatic control threshold value ATh to be 95% higher than the automatic control reference threshold value and determines the recommendation threshold value RTh to be 60% higher than the recommendation reference threshold value, for example. At this time, the control method determination section 115 determines the device control method of recommending that the cooling of the air conditioner be turned on at 6:02. Thus, compared to the case where the personality information is averaged Figure 7 , the timing of the control is delayed. Further, by increasing the threshold value and not performing automatic control, the frequency of device control is reduced.

[0136] For example, in the case where the openness in the personality information of the user is low, the user does not like new experiences or diversity in life, and thus, there is a tendency to dislike the automatic control or the recommendation itself by the device control apparatus 110. Further, in the case where the content of the device control does not match the intention of the user, the evaluation of the service for the device control is further reduced, and the use of the service using the device control can be discontinued.

[0137] Further, for example, in the case where the emotional stability in the personality information of the user is low, the evaluation of the service for the device control is significantly reduced when the content of the device control does not match the intention of the user, and the use of the service using the device control can be discontinued.

[0138] Further, for example, in the case where the diligence or the self-control in the personality information of the user is high, the user originally takes a planned action, and thus, there is little room for the action of the user to become a desired action. Therefore, in this case, by narrowing the object of the device control to a more reliable object as described above, the possibility of causing the user to feel unpleasant is reduced, and the possibility of continuing to use the service using the device control is increased.

[0139] Next, a case where the control method determination section 115 decides the threshold value based on the personality information of the user so that the recommendation is easily made is described.

[0140] Figure 10 is a graph for explaining a fourth example of determining a device control method.

[0141] In the case where the personality information of the user is such that the recommendation is easily made, the control method determination section 115 makes the recommendation easily by changing the threshold value of the control, for example, in the case where the extroversion of the user is high or in the case where the agreeableness is high.

[0142] For example, in the personality information, the extroversion is sometimes higher than a predetermined numerical range, or the agreeableness is sometimes higher than a predetermined numerical range.

[0143] In this case, the control method determination section 115 determines the automatic control threshold value ATh to be 95% higher than the automatic control reference threshold value, and determines the recommendation threshold value RTh to be 40% lower than the recommendation reference threshold value, for example. At this time, the control method determination section 115 determines the device control method of recommending that the air conditioning be turned on at 5:59. Thus, compared to the case where the personality information is averaged Figure 7 , the frequency of recommendations increases, and the frequency of automatic control decreases.

[0144] For example, in the case where the extroversion is high in the personality information of the user, the tendency to like to communicate or have a conversation with the device control apparatus 110 is high. Also, for example, in the case where the agreeableness is high in the personality information of the user, the tendency to accept recommendations is high when the user's intention is not greatly deviated from. Therefore, by increasing the frequency of recommendations as described above, the user is not caused to feel unpleasant, and the service effect based on device control can be improved. Also, in the case where the extroversion or the agreeableness of the user is low, the control method determination section 115 can decrease the frequency of recommendations.

[0145] Here, a case where a plurality of users utilize the device 101 and the personality information of the plurality of users is acquired will be described when the control method determination section 115 determines the threshold value based on the personality information of the user.

[0146] In the case where only one user or the user who utilizes the control target device 101 can be determined to be one user, the threshold value can be determined based on the personality information of the user.

[0147] In the case where a plurality of users are registered with respect to the control target device 101 and the user who utilizes cannot be determined, for example, the average of parameters indicating the personality information of the users can be taken, and the threshold value can be determined based on the value. Instead of the average of the parameters, a representative value such as the central value of the parameters, the maximum value, or the minimum value can be set in advance.

[0148] Also, in the case where the frequency of utilization or the period of time is set in advance for each user, or the possibility can be quantified with respect to which user is currently utilizing by the individual recognition by the sensor 102, the value can be weighted, the average of parameters indicating the personality information can be taken, and the threshold value can be determined based on the value.

[0149] As described above, the control method determination section 115 determines a negative weight value in a case where the parameter indicating "openness", "diligence", "extraversion", "coordination", "emotional stability", and "strength of self-control" is outside the predetermined numerical range, determines a positive weight value in a case where the parameter is inside the predetermined numerical range, multiplies each parameter of the character information by the weight value and adds them to obtain a weighted sum, adds the reference threshold value to the weighted sum, and thereby determines the threshold value. Here, a function such as a logistic function can be applied to the value of the weighted sum, and then added to the reference threshold value, and thereby the threshold value can be determined. Further, the weight value can be a predetermined fixed value, or can be such that the farther the parameter is from the predetermined numerical range, the greater the value is if the weight value is positive, and the smaller the value is if the weight value is negative.

[0150] Next, the control method performed by the control section 116 in step S14 of the process of Fig. 14 will be described in detail. Figure 5

[0151] Figure 11 is a flowchart showing the operation of the control section 116.

[0152] First, the control section 116 determines whether or not it is time to perform automatic control (S30). Here, even if it is the time to perform automatic control determined by the control method determination section 115, the control section 116 determines that it is not time to perform control in a case where the control has no effect. A case where the control has no effect is, for example, a case where the content of the control is to turn on the cooling of the air conditioner and the user has already turned on the cooling of the air conditioner before that time. In a case where it is time to perform automatic control (S30: YES), the process proceeds to step S31, and in a case where it is not time to perform automatic control (S30: NO), the process proceeds to step S33.

[0153] In step S31, the control section 116 performs the control target operation determined by the control method determination section 115.

[0154] The control section 116 notifies the user device 103 of the content of the control that has been performed via the communication section 111 (S32). Then, the process proceeds to step S33.

[0155] In step S33, the control section 116 determines whether or not it is time to perform recommendation. Here, even if it is the time to perform recommendation determined by the control method determination section 115, the control section 116 determines that it is not time to perform recommendation in a case where the recommendation has no effect. A case where the recommendation has no effect is, for example, a case where the content of the recommendation is to turn on the cooling of the air conditioner and the user has already turned on the cooling of the air conditioner before that time. In a case where it is time to perform recommendation (S33: YES), the process proceeds to step S34, and in a case where it is not time to perform recommendation (S33: NO), the process returns to step S30. ​

[0156] In step S34, the control section 116 recommends to the user the control object operation determined by the control method determination section 115 via the user device 103. For example, the control section 116 transmits a screen image recommending such a control object operation to the user device 103 via the communication section 111, and causes the user device 103 to display such a screen image.

[0157] Then, the control section 116 determines whether or not the user accepts the recommended control object operation (S35). For example, the control section 116 determines that the user accepts the recommended control object operation in a case where a notification indicating acceptance of the control object operation is received from the user via the communication section 111. On the other hand, the control section 116 determines that the user does not accept the recommended control object operation in a case where such a notification is not received from the user via the communication section 111 within a predetermined period, or in a case where a notification indicating rejection of the control object operation is received from the user. In a case where the user accepts the recommended control object operation (S35: YES), the process proceeds to a heating step S36, and in a case where the user does not accept the recommended control object operation (S35: NO), the process returns to step S30.

[0158] In step S36, the control section 116 performs the control object operation determined by the control method determination section 115. Then, the process returns to step S30.

[0159] As described above, according to Embodiment 1, the device is controlled in accordance with the user's life pattern and the user's character, and thus, it is possible to perform the device control desired by the user.

[0160] For example, in a case where the user's character likes the control of the device 101 by the device control apparatus 110, the control method determination section 115 determines the threshold value in such a manner that the frequency of control is increased. On the other hand, in a case where the user's character dislikes the control of the device 101 by the device control apparatus 110, the threshold value is determined in such a manner that the frequency of control is decreased.

[0161] Further, in a case where the user's character strongly regulates the user's action, the control method determination section 115 determines the threshold value in such a manner that the frequency of control is decreased. On the other hand, in a case where the user's character weakly regulates the user's action, the control method determination section 115 determines the threshold value in such a manner that the frequency of control is increased.

[0162] Furthermore, if the user's personality prefers conversation, the control method determination unit 115 determines a second threshold in a way that increases the frequency of recommendations. On the other hand, if the user's personality dislikes conversation, the control method determination unit 115 determines a second threshold in a way that decreases the frequency of recommendations. In this case, to make automatic control less likely, the first threshold could also be increased; however, Embodiment 1 is not limited to this example.

[0163] Generally speaking, increasing the frequency of equipment control can include more control that aligns with the user's intentions, thereby reducing the user's labor and time. However, it can also include control that does not align with the user's intentions, leading to user dissatisfaction. The degree of dissatisfaction with control that does not align with the user's intentions varies depending on the user's personality. Furthermore, the degree of pleasure or dissatisfaction with control that closely aligns with the user's intentions also varies depending on the user's personality. Consequently, the expected level or effectiveness of reducing labor and time also varies depending on the user's personality. According to Implementation Method 1, determining the frequency of equipment control based on personality can improve user satisfaction.

[0164] Furthermore, as a method of equipment control, the following effect can be achieved by setting up stages such as automatic control that does not require user acceptance and recommendation that requires user acceptance.

[0165] For controls with a significantly high probability of being requested by the user, automatic control can be implemented, thereby reducing the effort and time required for the user to accept such controls. Furthermore, for controls with a significantly low probability of being requested, recommendations can be made and the user required to accept them, thereby reducing controls that are inconsistent with the user's intentions and the resulting unpleasantness.

[0166] Furthermore, regarding automatic control and recommendation, the degree of liking depends on the user's personality. Therefore, changing the frequency of these two aspects according to the user's personality can improve user satisfaction.

[0167] Furthermore, according to Embodiment 1, an appropriate frequency of device control is preset based on the user's personality, thereby enabling desired device control from the initial stage in device control-based services. This eliminates the labor and time required for users to trial and error while setting the frequency of individual device controls to match their preferences, and also eliminates the unpleasantness of that process.

[0168] Implementation Method 2

[0169] like Figure 1 As shown, the device control system 200 with the device control device 210 of Embodiment 2 includes a device 101, a sensor 102, a user device 103 and the device control device 210.

[0170] The device 101, the sensor 102, and the user device 103 of the device control system 200 in Embodiment 2 are the same as the device 101, the sensor 102, and the user device 103 of the device control system 100 in Embodiment 1.

[0171] As shown in Figure 1 , the device control apparatus 210 of Embodiment 2 has the communication section 111, the life data storage section 112, the life pattern extraction section 213, the character information acquisition section 114, the control method determination section 215, and the control section 216.

[0172] The communication section 111, the life data storage section 112, and the character information acquisition section 114 of the device control apparatus 210 of Embodiment 2 are the same as the communication section 111, the life data storage section 112, and the character information acquisition section 114 of the device control apparatus 110 of Embodiment 1.

[0173] The life pattern extraction section 213 extracts a life pattern from the life data stored in the life data storage section 112.

[0174] The life pattern in Embodiment 2 is the frequency of event linkage of the device 101 or the sensor 102 per condition.

[0175] For example, the life data contains at least a history of a plurality of events related to the device 101, and the plurality of events contain a plurality of operations for a function of the device 101. Also, the life pattern extraction section 213 extracts, as the life pattern, the frequency of each of a plurality of sequences in which two operations are extracted from the plurality of operations, from the preceding operation to the subsequent operation, within a predetermined period, by referring to the life data and calculating the frequency.

[0176] Further, the life data contains at least a history of a plurality of events related to the device 101 and the sensor 102, and the plurality of events contain a plurality of operations for a function of the device 101 and detection of a predetermined object by the sensor 102. Also, the life pattern extraction section 213 extracts, as the life pattern, the frequency of each of the plurality of operations calculated based on the detection by the sensor 102 within a predetermined period, by referring to the life data.

[0177] Figure 12 is a table showing an example of the life pattern in Embodiment 2.

[0178] In Figure 12 , it is assumed that the device 101A is an air conditioner, the device 101B is a television, and the sensor 102 is a human sensor.

[0179] In Figure 12In the table, the frequency of events such as the start of cooling by the air conditioner, the stop of cooling by the air conditioner, the start of viewing by the television, the stop of viewing by the television, and the detection of a person by the person sensor is shown.

[0180] Specifically, Figure 12 The vertical direction of the table indicates operations or actions that become triggers. Here, the start of cooling by the air conditioner, the stop of cooling by the air conditioner, the start of viewing by the television, the stop of viewing by the television, and the detection of a person by the person sensor are operations or actions that become triggers.

[0181] Also, Figure 12 The horizontal direction of the table indicates operations that are linked to the triggers. Here, the start of cooling by the air conditioner, the stop of cooling by the air conditioner, the start of viewing by the television, and the stop of viewing by the television are operations that are linked to the triggers.

[0182] Figure 12 The values in the table shown in the drawing indicate the frequency of events, i.e., operations, that are caused to be linked to the triggers in a predetermined period of time from when the events, i.e., operations, that become triggers are generated in a certain period of time. Also, "-" in the table indicates that the frequency is not calculated. The certain period of time is also referred to as a first period of time, and the predetermined period of time is also referred to as a second period of time.

[0183] Here, the certain period of time is set to be within 1 month from the date when the living pattern is extracted, from 5:00 to 10:00 in the morning on weekdays, and the predetermined period of time is set to be 5 minutes, but can be changed as needed.

[0184] For example, in Figure 12 In the table, when the cooling by the air conditioner is changed from off to on in the certain period of time, if the viewing by the television is off, the frequency of the viewing by the television being changed to on within the predetermined period of time of 5 minutes is 89%. This frequency is obtained by dividing the number of times of events that are caused to be linked in the predetermined period of time by the number of times of events that can be caused to be linked when the events that become triggers are generated in the certain period of time.

[0185] Here, a specific example of a case where an event can be caused to be linked is described.

[0186] For example, assume that the event that is caused to be linked is "the viewing by the television is changed to on". Also, when the event that becomes a trigger occurs, if the viewing by the television is off, it becomes a case where the event can be caused to be linked. On the other hand, when the event that becomes a trigger occurs, if the viewing by the television is already on, it becomes a case where the event cannot be caused to be linked.

[0187] In addition, it is preferable that the specific period be divided into weekdays and weekends, the frequency of the event linkage be calculated separately for each period, and the life pattern be set, and that the device control be performed in accordance with the life pattern for each of the weekdays and weekends.

[0188] In addition, it is preferable that the specific period be divided into time periods such as morning and evening, the frequency of the event linkage be calculated separately for each period, and the life pattern be set, and that the device control be performed in accordance with the life pattern for each of the time periods.

[0189] The sensor 102 is not the target of the user's operation, and thus, as shown in FIG. 6, the frequency of the event of the sensor that triggers the linkage can also be omitted from the life pattern. Figure 12

[0190] In addition, as shown in FIG. 7, the linkage related to the same operation such as the turning on and off of the same function of the same device 101 can also be omitted from the life pattern. Figure 12

[0191] When the number of data that is the basis of the frequency of the linkage is small, the frequency lacks reliability, and thus, the frequency of the linkage can also be omitted from the life pattern. For example, when the number of times of the event that can cause the linkage when the event that is the trigger is generated in the specific period is less than a predetermined number of times (for example, 5 times), the frequency of the linkage can be omitted. Thus, it is possible to prevent inappropriate control due to a value that lacks reliability.

[0192] The control method determination section 215 determines the control method of the device 101 in accordance with the life pattern extracted by the life pattern extraction section 213 and the personality information acquired by the personality information acquisition section 114.

[0193] For example, the control method determination section 215 determines the threshold value in accordance with the personality information, compares the determined threshold value and the life pattern, and thereby determines the control method of the device 101. In Embodiment 2, the control method determination section 215 determines the event that is the trigger and the event that links with the trigger as the device control method.

[0194] The control method determination section 215 determines the device control method in such a manner that the threshold value is determined in accordance with the personality of the user by referring to the personality information, and in the case where the frequency indicated by the life pattern exceeds the threshold value, the control related to the subsequent operation is performed when the preceding operation is performed in the corresponding sequence.

[0195] ​​Specifically, the control method determination section 215 determines, as the device control method, a first device control method in which, as the control, the subsequent operation is automatically performed when the preceding operation is performed in the corresponding sequence in a case where the frequency represented by the life pattern exceeds a first threshold value as the threshold value, and a second device control method in which, as the control, the subsequent operation is recommended to be performed when the preceding operation is performed in the corresponding sequence in a case where the frequency represented by the life pattern exceeds a second threshold value as the threshold value.

[0196] Further, the control method determination section 215 determines the device control method in such a manner that the threshold value is determined in accordance with the character of the user by referring to the character information, and the control related to the corresponding operation is performed when the detection based on the sensor 102 is performed in a case where the frequency represented by the life pattern exceeds the threshold value.

[0197] Specifically, the control method determination section 2155 determines, as the device control method, a first device control method in which, as the control, the corresponding operation is automatically performed when the detection is performed in a case where the frequency represented by the life pattern exceeds a first threshold value as the threshold value, and a second device control method in which, as the control, the corresponding operation is recommended to be performed when the detection is performed in a case where the frequency represented by the life pattern exceeds a second threshold value as the threshold value which is lower than the first threshold value.

[0198] In addition, the details of the determination method of the control method will be described later.

[0199] The control section 216 controls the device 101 in accordance with the control method determined by the control method determination section 215. In Embodiment 2, the control section 216 executes the control method associated with the event linked to the trigger at the timing at which the event determined by the control method determination section 215 to be the trigger occurs.

[0200] Figure 13 is a table for explaining the first example of the determination of the device control method in accordance with the frequency of the linkage of the device 101.

[0201] In Figure 13 , it is assumed that the device 101 is an air conditioner and a television, and the sensor 102 is a human sensor. Also, the linkage of the cooling of the air conditioner, the viewing and listening of the television, and the detection of the human sensor is explained. Further, the frequency of the linkage is calculated between 5 o'clock in the morning and 10 o'clock in the morning on weekdays.

[0202] Here, it is assumed that the character information of the user is average. For example, in the character information, all the parameters indicating openness, diligence, extroversion, coordination, emotional stability, and self-control are sometimes included in a predetermined numerical range. The numerical range here can be the same with respect to all the parameters, or can be different for each parameter.

[0203] The control method determination section 115 determines, for example, the automatic control threshold value for the device 101 linkage to be the automatic control reference threshold value, that is, 90%, and the recommendation threshold value for the device linkage to be the recommendation reference threshold value, that is, 50%.

[0204] In the case of Figure 13 the operation of turning off the air conditioner cooling in linkage with the television viewing start exceeds the automatic control threshold value.

[0205] In addition, the operation of turning on the television viewing in linkage with the air conditioner cooling on, the operation of turning off the television viewing in linkage with the air conditioner cooling off, the operation of turning off the air conditioner cooling in linkage with the television viewing off, and the operation of turning off the air conditioner cooling in linkage with the human sensor detection exceed the recommendation threshold value.

[0206] The control method determination section 215 determines, in the case where the frequency of the event linkage exceeds the automatic control threshold value, the device control method in which the automatic control of the event of the linkage is performed and the timing of the automatic control is the time when the triggered event occurs.

[0207] In addition, the control method determination section 215 determines, in the case where the frequency of the event linkage exceeds the recommendation threshold value, the device control method in which the recommendation of the event of the linkage is performed and the timing of the recommendation is the time when the triggered event occurs.

[0208] In the case of Figure 13 In the example of the case of the weekdays, the control method determination section 215 determines, in the period from 5 a.m. to 10 a.m., the device control method in which the automatic control of turning on the air conditioner cooling is performed when the television viewing start occurs, the device control method in which the recommendation of turning on the television viewing is performed when the air conditioner cooling on occurs, the device control method in which the recommendation of turning off the air conditioner cooling is performed when the television viewing off occurs, the device control method in which the recommendation of turning on the air conditioner cooling is performed when the human sensor detection occurs, and the device control method in which the recommendation of turning off the television viewing is performed when the air conditioner cooling off occurs. Also, the device control method can be determined based on the frequency calculated in different periods for other combinations of the devices 101 or the sensors 102.

[0209] Next, the case where the control method determination section 215 determines the threshold value based on the user's character information so that the device control is likely to occur will be described.

[0210] Figure 14 is a table for explaining the second example of determining the device control method based on the frequency of the device 101 linkage.

[0211] In a case where the service effect based on the device control is improved when the device control is made to occur easily in the personality information of the user, for example, in a case where the openness of the user is high, a case where the emotional stability is high, a case where the diligence is low, or a case where the self-control is low, the control method determination section 215 makes the device control to occur less easily by lowering the threshold value of the control.

[0212] For example, in the personality information, the openness is sometimes higher than a predetermined numerical range, the emotional stability is sometimes higher than a predetermined numerical range, the diligence is sometimes lower than a predetermined numerical range, or the self-control is sometimes lower than a predetermined numerical range.

[0213] In this case, the control method determination section 215 determines, for example, the automatic control threshold value to be 80% lower than the automatic control reference threshold value, and determines the recommendation threshold value to be 40% lower than the recommendation reference threshold value. In this case, in the device control method determined by the control method determination section 215, the device control method in which the television viewing is made to start when the person sensing sensor detection occurs is added as compared to the case where the personality information is averaged. Figure 13 In addition, the device control method in which the television viewing is made to start when the air conditioner cooling is made to start is changed to the device control method in which the automatic control is performed.

[0214] By thus lowering the threshold value, the frequency of the device control increases. In addition, the recommendation is changed to the automatic control, and the automation is promoted.

[0215] Next, a case where the control method determination section 215 determines the threshold value according to the personality information of the user so that the device control does not occur easily will be described.

[0216] Figure 15 This is a table for explaining a third example in which the device control method is determined according to the frequency of the device 101 linkage.

[0217] In a case where the service effect based on the device control is improved when the device control does not occur easily in the personality information of the user, for example, in a case where the openness of the user is low, a case where the emotional stability is low, a case where the diligence is high, or a case where the self-control is high, the control method determination section 215 makes the device control to occur less easily by raising the threshold value of the control.

[0218] For example, in the personality information, the openness is sometimes lower than a predetermined numerical range, the emotional stability is sometimes lower than a predetermined numerical range, the diligence is sometimes higher than a predetermined numerical range, or the self-control is sometimes higher than a predetermined numerical range.

[0219] In this case, the control method determination section 215 determines the automatic control threshold value to be 95% higher than the automatic control reference threshold value and determines the recommendation threshold value to be 60% higher than the recommendation reference threshold value, for example. In this case, among the device control methods determined by the control method determination section 215, the device control method of making a recommendation to turn the television on for viewing when the human sensor detects is added compared to the case where the personality information is averaged. Figure 13 In addition, the device control method of making an automatic control to turn the air conditioner on for cooling when the television is turned on for viewing is changed to a device control method of making a recommendation.

[0220] By thus increasing the threshold values, the frequency of device control decreases. In addition, the automatic control is changed to a recommendation, and the automation is suppressed.

[0221] Next, a case where the control method determination section 215 decides the threshold values in accordance with the personality information of the user so that a recommendation is likely to occur will be described.

[0222] Figure 16 is a table for explaining a fourth example of determining a device control method in accordance with the frequency of the device 101 linkage.

[0223] In a case where the service effect based on device control is likely to improve when a recommendation is likely to occur in the personality information of the user, for example, in a case where the extroversion of the user is high or in a case where the agreeableness of the user is high, the control method determination section 115 makes a recommendation likely to occur by changing the threshold value of the control.

[0224] For example, in the personality information, the extroversion is sometimes higher than a predetermined numerical range, or the agreeableness is sometimes higher than a predetermined numerical range.

[0225] In this case, the control method determination section 215 determines the automatic control threshold value to be 95% higher than the automatic control reference threshold value and determines the recommendation threshold value to be 40% lower than the recommendation reference threshold value, for example. In this case, among the device control methods determined by the control method determination section 215, the device control method of making a recommendation to turn the television on for viewing when the human sensor detects is added compared to the case where the personality information is averaged. Figure 13 In addition, the device control method of making an automatic control to turn the air conditioner on for cooling when the television is turned on for viewing is changed to a device control method of making a recommendation.

[0226] By thus changing the threshold values, the frequency of recommendations increases.

[0227] In Implementation Method 2, the control method determination unit 215 also determines a negative weight value when the parameters representing "openness," "diligence," "extroversion," "cooperation," "emotional stability," and "strength of self-control" are outside a predetermined numerical range. This is done by lowering the baseline threshold using these parameters and determining a positive weight value when the baseline threshold is raised using these parameters. The weighted sum obtained by multiplying each parameter of the personality information by its weight value and adding them together is then added to the baseline threshold to determine the threshold. Alternatively, a logical function can be applied to the weighted sum, and then added to the baseline threshold to determine the threshold. Furthermore, the weight value can be a predetermined fixed value, or it can be a value that increases as the parameter deviates from the predetermined numerical range, becoming larger for positive weight values ​​and smaller for negative weight values.

[0228] As described above, through implementation method 2, device control is also performed according to the user's lifestyle and personality, thereby enabling the device control as desired by the user.

[0229] Furthermore, the lifestyle pattern in Embodiment 1 described above is based on the frequency of utilizing each function of each device 101 according to conditions such as time, while the lifestyle pattern in Embodiment 2 is based on the frequency of triggering events of device 101 or sensor 102 according to conditions. However, the lifestyle patterns in Embodiment 1 or 2 are not limited to the examples above. For example, experience generation rules can be prepared according to the method disclosed in Patent Document 1, experience data can be generated according to the experience generation rules, a frequent occurrence pattern tree can be generated according to the experience data, and lifestyle patterns can be extracted from the frequent occurrence pattern tree.

[0230] Furthermore, lifestyle patterns are not limited to being extracted solely from users' lifestyle data. For example, lifestyle pattern extraction units 113 and 213 may also pre-store lifestyle patterns that are referenced from general users. Lifestyle pattern extraction units 113 and 213 may also acquire and store lifestyle patterns extracted from the lifestyle data of other users.

[0231] Furthermore, while embodiments 1 and 2 have been described above, the present invention is not limited to these embodiments 1 or 2. When extracting lifestyle patterns using different methods, by determining the determination threshold for the lifestyle pattern to be the target of control execution based on personality information when determining the device control method, the same effect as in embodiments 1 or 2 can also be obtained.

[0232] Label Explanation

[0233] 100, 200: device control system; 101: device; 102: sensor; 103: user device; 110, 210: device control means; 111: communication section; 112: life data storage section; 113, 213: life pattern extraction section; 114: character information acquisition section; 115, 215: control method determination section; 116, 216: control section.

Claims

1. An apparatus control device characterized by comprising: The device control apparatus has: a character information acquisition section that acquires character information indicating a character of a user; a control method determination section that determines a control method for a device used by the user, i.e., a device control method, based on the character information and a life pattern of the user; and a control section that controls the device in accordance with the device control method, The device control apparatus further has: a life data storage section that stores life data indicating at least a history of a plurality of events related to the device; and a life pattern extraction section that extracts the life pattern from the life data, The plurality of events include a plurality of operations on a function of the device, The life pattern extraction section extracts, as the life pattern, a frequency of performing a later operation after a prior operation in a predetermined period, for each of a plurality of sequences in which two operations are extracted from the plurality of operations, by referring to the life data and calculating the frequency for each of the plurality of sequences, The control method determination section determines the device control method in such a manner that a threshold value is determined based on the character of the user by referring to the character information, and control related to the later operation is performed when the prior operation is performed in the corresponding sequence in a case where the frequency exceeds the threshold value.

2. The device control apparatus according to claim 1, wherein The control method determination section determines a first device control method and a second device control method as the device control method, the first device control method being a method in which the corresponding operation is automatically performed as the control in a case where a first threshold value serving as the threshold value is exceeded, and the second device control method being a method in which the corresponding operation is recommended to be performed as the control in a case where a second threshold value lower than the first threshold value serves as the threshold value.

3. An apparatus control device characterized by comprising: The device control apparatus has: a character information acquisition section that acquires character information indicating a character of a user; a control method determination section that determines a control method for a device used by the user, i.e., a device control method, based on the character information and a life pattern of the user; and a control section that controls the device in accordance with the device control method, The device control apparatus further has: a life data storage section that stores life data indicating at least a history of a plurality of events related to the device; and a life pattern extraction section that extracts the life pattern from the life data, The plurality of events include a plurality of operations on a function of the device, The life pattern extraction section extracts, as the life pattern, a frequency of performing a later operation after a prior operation in a predetermined period, for each of a plurality of sequences in which two operations are extracted from the plurality of operations, by referring to the life data and calculating the frequency for each of the plurality of sequences, The control method determination section determines the device control method in such a manner that a threshold value is determined based on the character of the user by referring to the character information, and control related to the later operation is performed when the prior operation is performed in the corresponding sequence in a case where the frequency exceeds the threshold value.

4. The device control apparatus according to claim 3, wherein The control method determination section determines a first device control method and a second device control method as the device control method, the first device control method being a method in which, as the control, the subsequent operation is automatically performed when the preceding operation is performed in the corresponding sequence in a case where a first threshold value as the threshold value is exceeded, and the second device control method being a method in which, as the control, the subsequent operation is recommended to be performed when the preceding operation is performed in the corresponding sequence in a case where a second threshold value as the threshold value is exceeded.

5. An apparatus control device characterized by comprising: The device control apparatus has: a character information acquisition section that acquires character information indicating a character of a user; a control method determination section that determines a control method of a device, i.e., a device control method, used by the user, in accordance with the character information and a life pattern of the user; and a control section that controls the device in accordance with the device control method, The device control apparatus further has: a life data storage section that stores life data indicating at least a history of a plurality of events related to the device and a sensor; and a life pattern extraction section that extracts the life pattern from the life data, the plurality of events including a plurality of operations on a function of the device and detection of a predetermined object by the sensor, the life pattern extraction section extracting, as the life pattern, frequencies at which the plurality of operations are respectively performed within a predetermined period, which are calculated on the basis of the detection by referring to the life data, the control method determination section determining the device control method in such a manner that a threshold value is determined in accordance with the character of the user by referring to the character information, and a control related to a corresponding operation is performed when the detection is performed in a case where the frequency exceeds the threshold value.

6. The device control apparatus according to claim 5, wherein the control method determination section determines a first device control method and a second device control method as the device control method, the first device control method being a method in which, as the control, the corresponding operation is automatically performed when the detection is performed in a case where a first threshold value as the threshold value is exceeded, and the second device control method being a method in which, as the control, the corresponding operation is recommended to be performed when the detection is performed in a case where a second threshold value as the threshold value is exceeded, the second threshold value being lower than the first threshold value.

7. The device control apparatus according to any one of claims 1 to 6, wherein the character information includes an element by which it is determined whether the character likes the control of the device by the device control apparatus, in a case where the character likes the control of the device by the device control apparatus, the control method determination section determines the threshold value in such a manner that a frequency of the control is increased, and in a case where the character does not like the control of the device by the device control apparatus, the control method determination section determines the threshold value in such a manner that the frequency of the control is decreased.

8. The device control apparatus according to any one of claims 1 to 6, wherein the character information includes an element that can determine whether the character governs the user's action to a high degree or a low degree, the control method determination section determines the threshold value in such a manner that the frequency of the control is reduced in a case where the character governs the user's action to a high degree, and determines the threshold value in such a manner that the frequency of the control is increased in a case where the character governs the user's action to a low degree.

9. The device control apparatus according to any one of claims 2, 4, and 6, wherein the character information includes an element that can determine whether the character likes conversation or not, the control method determination section determines the second threshold value in such a manner that the frequency of the recommendation is increased in a case where the character likes conversation, and determines the second threshold value in such a manner that the frequency of the recommendation is reduced in a case where the character does not like conversation. The device control apparatus has: a character information acquisition section that acquires character information that represents a character of a user; a control method determination section that determines a control method of a device, i.e., a device control method, used by the user, in accordance with the character information and a life pattern of the user; a control section that controls the device in accordance with the device control method, 10. An apparatus control device characterized by comprising: The device control apparatus further has: a life data storage section that stores life data that represents at least a history of a plurality of events related to the device and a sensor; and a life pattern extraction section that extracts the life pattern from the life data, the plurality of events include an operation or a motion of the device or the sensor, the life pattern extraction section extracts, as the life pattern, a frequency of the operation or the motion of the device or the sensor by referring to the life data, the control method determination section determines, as the device control method, an event that becomes a trigger and an event that is linked with the trigger in a case where the frequency exceeds a threshold value, in accordance with the character of the user by referring to the character information. when the computer program is executed by a processor, acquire character information that represents a character of a user, extract a life pattern of the user from life data that represents at least a history of a plurality of events related to a device used by the user, determine a control method of the device, i.e., a device control method, in accordance with the character information and the life pattern, 11. A computer-readable recording medium storing a computer program, characterized by comprising: control the device in accordance with the device control method, the plurality of events include a plurality of operations with respect to a function of the device, the extracting of the life pattern of the user from the life data that represents at least the history of the plurality of events related to the device used by the user includes extracting, as the life pattern, a frequency of each of the plurality of operations in each predetermined time period by referring to the life data, ​ ​ ​ ​ The control method of the device according to the character information and the life pattern of the user, includes: determining a threshold value according to the character of the user by referring to the character information, and performing control related to a corresponding operation in a corresponding time period when the frequency exceeds the threshold value.

12. A computer-readable recording medium storing a computer program, characterized by comprising: When the computer program is executed by a processor, character information representing a character of a user is acquired, a life pattern of the user is extracted from life data representing at least a history of a plurality of events related to a device used by the user, a control method of the device, i.e., a device control method, is determined according to the character information and the life pattern, the device is controlled according to the device control method, the plurality of events include a plurality of operations on a function of the device, the life pattern of the user is extracted from life data representing at least a history of a plurality of events related to a device used by the user, by referring to the life data, calculating frequencies of a plurality of sequences in which two operations are extracted from the plurality of operations, the frequencies being frequencies of performing a preceding operation to a subsequent operation in the two operations within a predetermined period, and extracting the frequencies of the respective plurality of sequences as the life pattern, the control method of the device, i.e., the device control method, is determined according to the character information and the life pattern, by referring to the character information, determining a threshold value according to the character of the user, and performing control related to a subsequent operation when a preceding operation is performed in a corresponding sequence when the frequency exceeds the threshold value.

13. A computer-readable recording medium storing a computer program, characterized by comprising: When the computer program is executed by a processor, character information representing a character of a user is acquired, a life pattern of the user is extracted from life data representing at least a history of a plurality of events related to a device and a sensor used by the user, a control method of the device, i.e., a device control method, is determined according to the character information and the life pattern, the device is controlled according to the device control method, the plurality of events include a plurality of operations on a function of the device and detection of a predetermined object by the sensor, the life pattern of the user is extracted from life data representing at least a history of a plurality of events related to a device and a sensor used by the user, by referring to the life data, calculating frequencies of performing the plurality of operations respectively within a predetermined period based on the detection, and extracting the frequencies calculated in the plurality of operations respectively as the life pattern, the control method of the device, i.e., the device control method, is determined according to the character information and the life pattern, by referring to the character information, determining a threshold value according to the character of the user, and performing control related to a corresponding operation when the detection is performed when the frequency exceeds the threshold value.

14. A computer-readable recording medium storing a computer program, characterized by comprising: When the computer program is executed by a processor, character information representing a character of a user is acquired, a life pattern of the user is extracted from life data representing at least a history of a plurality of events related to a device and a sensor used by the user, determining a control method of the device, i.e., a device control method, based on the personality information and the life pattern, controlling the device according to the device control method, the plurality of events include operations or actions of the device or the sensor, the life pattern of the user is extracted from life data indicating at least a history of a plurality of events related to the device and the sensor used by the user, including calculating a frequency of operations or actions of the device or the sensor being linked together by referring to the life data, and extracting the frequency as the life pattern, the determining a control method of the device, i.e., a device control method, based on the personality information and the life pattern, includes determining an event that becomes a trigger and an event that is linked with the trigger as the device control method by referring to the personality information, and determining a threshold value based on the personality of the user, in a case where the frequency exceeds the threshold value.

15. A device control method, characterized by: acquiring personality information indicating a personality of a user, extracting a life pattern of the user from life data indicating at least a history of a plurality of events related to a device used by the user, determining a control method of the device, i.e., a device control method, based on the personality information and the life pattern, controlling the device according to the device control method, the plurality of events include a plurality of operations for a function of the device, the extracting a life pattern of the user from life data indicating at least a history of a plurality of events related to a device used by the user, includes calculating a frequency of each of the plurality of operations being performed in each predetermined time period by referring to the life data, and extracting the frequency of each of the plurality of operations in each predetermined time period as the life pattern, the determining a control method of the device, i.e., a device control method, based on the personality information and the life pattern, includes determining a control related to a corresponding operation in a corresponding time period as the device control method by referring to the personality information, and determining a threshold value based on the personality of the user, in a case where the frequency exceeds the threshold value.

16. A device control method, characterized by: acquiring personality information indicating a personality of a user, extracting a life pattern of the user from life data indicating at least a history of a plurality of events related to a device used by the user, determining a control method of the device, i.e., a device control method, based on the personality information and the life pattern, controlling the device according to the device control method, the plurality of events include a plurality of operations for a function of the device, the extracting a life pattern of the user from life data indicating at least a history of a plurality of events related to a device used by the user, includes calculating a frequency of each of a plurality of sequences of two operations extracted from the plurality of operations, in which a preceding operation is followed by a succeeding operation, being performed in a predetermined period by referring to the life data, and extracting the frequency of each of the plurality of sequences as the life pattern, The control method of the device determined based on the character information and the life pattern includes determining a threshold value based on the character of the user by referring to the character information, and performing control related to a subsequent operation when a preceding operation is performed in the corresponding sequence if the frequency exceeds the threshold value.

17. A device control method, comprising: acquiring character information indicating a character of a user, extracting a life pattern of the user from life data indicating at least a history of a plurality of events related to a device and a sensor used by the user, determining a control method of the device based on the character information and the life pattern, controlling the device according to the control method of the device, the plurality of events include a plurality of operations of a function of the device and detection of a predetermined object by the sensor, the extracting of the life pattern of the user from the life data indicating at least the history of the plurality of events related to the device and the sensor used by the user includes calculating frequencies of the plurality of operations performed respectively within a predetermined period based on the detection by referring to the life data, and extracting the frequencies calculated respectively in the plurality of operations as the life pattern, the determining of the control method of the device based on the character information and the life pattern includes determining a threshold value based on the character of the user by referring to the character information, and determining an event to be triggered and an event associated with the triggering as the control method of the device if the frequency exceeds the threshold value.

18. A device control method, comprising: acquiring character information indicating a character of a user, extracting a life pattern of the user from life data indicating at least a history of a plurality of events related to a device and a sensor used by the user, determining a control method of the device based on the character information and the life pattern, controlling the device according to the control method of the device, the plurality of events include an operation or action of the device or the sensor, the extracting of the life pattern of the user from the life data indicating at least the history of the plurality of events related to the device and the sensor used by the user includes calculating a frequency of an operation or action of the device or the sensor, and extracting the frequency as the life pattern, the determining of the control method of the device based on the character information and the life pattern includes determining a threshold value based on the character of the user by referring to the character information, and determining an event to be triggered and an event associated with the triggering as the control method of the device if the frequency exceeds the threshold value.

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