JP2020103496A - Environment control system and environment control method - Google Patents

Abstract

To provide an environment control system capable of effectively awakening a user.SOLUTION: An environment control system 10 includes: a first acquisition unit 110 acquiring input information including information on user's physiological index; a determination unit 120 determining control contents for awakening a user and also of environment control equipment 400 including light output equipment from the input information according to the control content determination rule; a control unit 130 executing control of the environment control equipment 400 on the basis of the determined control contents; a second acquisition unit 150 acquiring evaluation information showing user evaluation to the executed control; and an update unit 180 updating the control content determination rule according to machine learning using a value based on the evaluation information as a reward.SELECTED DRAWING: Figure 1

Description

The present invention relates to an environment control system and an environment control method for determining control contents of an environment control device for awakening a user.

Conventionally, various techniques for awakening a user have been proposed. Patent Document 1 discloses a wake-up device that notifies a sleeping person to wake up based on the sleeping state of the sleeping person.

JP, 2014-023571, A

By the way, it is desired that the environment control system that controls the environment to wake up the user can effectively wake up the user.

Therefore, the present invention provides an environment control system and an environment control method that can effectively awaken a user.

An environment control system according to an aspect of the present invention includes a first acquisition unit that acquires input information including user's physiological index information, and a control content for awakening the user from the input information according to a control content determination rule. The determining unit that determines the control content of the environmental control device including the device that outputs light, the control unit that controls the environmental control device based on the determined control content, and the executed control unit. A second acquisition unit that acquires evaluation information indicating the evaluation of the user with respect to control, and an updating unit that updates the control content determination rule by machine learning using a value based on the evaluation information as a reward.

An environmental control method according to an aspect of the present invention includes a first acquisition step of acquiring input information including user's physiological index information, and a control content for awakening the user from the input information according to a control content determination rule. The determining step of determining the control content of the environmental control device including the device that outputs light, the control step of executing control of the environmental control device based on the determined control content, and the executed The method includes a second acquisition step of acquiring evaluation information indicating an evaluation of the user with respect to control, and an updating step of updating the control content determination rule by machine learning using a value based on the evaluation information as a reward.

Note that these comprehensive or specific aspects may be realized by a recording medium such as a system, a method, an integrated circuit, a computer program, or a computer-readable CD-ROM, and the system, the integrated circuit, the computer program, and the recording. It may be realized by any combination of media.

The environment control system and the environment control method according to an aspect of the present invention can effectively awaken a user.

FIG. 1 is a block diagram showing the functional configuration of the environment control system according to the first embodiment. FIG. 2 is a diagram for explaining the outline of awakening control. FIG. 3 is a diagram showing a plurality of types of lighting equipment. FIG. 4 is a flowchart of the operation of the control device according to the first embodiment during awakening control. FIG. 5 is a diagram showing information that can be used as input information. FIG. 6 is a diagram for explaining control parameters for awakening control. FIG. 7 is a chromaticity diagram for explaining the change of the emission color in the awakening control. FIG. 8 is a flowchart of the reward calculating operation of the control device according to the first embodiment. FIG. 9 is a diagram showing items that can be used to calculate a reward. FIG. 10: is a figure which shows the relationship between the item for determining individual reward, and the physiological index information which can be used for determining the said individual reward. FIG. 11 is a first diagram for explaining control parameters for sleep control. FIG. 12 is a second diagram for explaining control parameters for sleep control. FIG. 13 is a block diagram showing a functional configuration of the environment control system according to the second embodiment.

Hereinafter, embodiments will be described with reference to the drawings. It should be noted that each of the embodiments described below shows a comprehensive or specific example. Numerical values, shapes, materials, constituent elements, arrangement positions of constituent elements, connection forms, steps, order of steps, and the like shown in the following embodiments are examples, and are not intended to limit the present invention. Further, among the constituent elements in the following embodiments, constituent elements not described in independent claims are described as arbitrary constituent elements.

It should be noted that each drawing is a schematic diagram and is not necessarily strictly illustrated. Further, in each drawing, the substantially same configurations are denoted by the same reference numerals, and overlapping description may be omitted or simplified.

Further, in the present specification, numerical values and numerical ranges are expressions that represent not only a strict meaning but also substantially equivalent ranges, for example, including a difference of about several percent.

(Embodiment 1)
[Overview]
Hereinafter, the environment control system according to the first embodiment will be described. FIG. 1 is a block diagram showing the functional configuration of the environment control system according to the first embodiment. The environment control system 10 according to the first embodiment is an awakening support system for awakening the user during sleep. The environment control system 10 performs awakening control to awaken a user by using a device that outputs light, such as a lighting device. FIG. 2 is a diagram for explaining the outline of awakening control.

As shown in FIG. 2, the awakening control is, for example, control for gradually increasing the brightness of light emitted from the lighting device from the start time of the target period to the end time of the target period. Thereby, the environment control system 10 can wake up the user comfortably.

Here, the control content of the awakening control (the length of the target period, the maximum brightness, the amount of change in brightness, the change function of brightness (that is, the following) is defined by the physiological index information indicating the physical and mental state of the user before or during sleep. , The shape of the brightness curve) etc.) is considered to be different. Therefore, if the control content of the awakening control is fixed regardless of the state of mind and body of the user, the effect of awakening the user comfortably may decrease.

Therefore, the environment control system 10 has a learning device 100a that is constructed in advance by machine learning. When the physiological index information is given to the learning device 100a as input information, the learning device 100a outputs the control content of the awakening control considered to be optimum. Thereby, the environment control system 10 can wake up the user effectively (that is, comfortably).

The environment control system 10 shown in FIG. 2 can also perform sleep control for making the user sleep comfortably during the sleep introduction period or the sleep period. The control performed during the sleep induction period is also described as light fluctuation control. As described below, the control content in sleep control is used as input information for causing the learning device 100a to output the control content of awakening control.

Note that the sleep here includes a nap. A nap is a short sleep, for example, a sleep performed by interrupting the work in the middle of a work, and a long sleep (hereinafter referred to as main sleep) taken by a person who is active during the day at night. Also described)) is a lighter sleep. As shown in FIG. 1, the environmental control system 10 specifically includes a control device 100, a sensor 200, an input device 300, and an environmental control device 400. Hereinafter, each of these devices will be described in detail.

[Sensor]
The sensor 200 detects the physical and physical condition of the user and outputs physiological index information indicating the detected physical and physical condition of the user to the control device 100. Such a sensor 200 is, for example, a heart rate monitor, a camera, a thermometer, an electroencephalograph, a saliva sensor, a perspiration sensor, a respiratory sensor, a body movement sensor, a blood flow sensor, or the like. Each of the sensors 200 that outputs such physiological index information to the control device 100 may be a contact sensor that contacts a user or a non-contact sensor.

Further, the sensor 200 may include a sensor that detects a user's action and outputs action index information that directly or indirectly indicates the detected user action to the control device 100. Such a sensor 200 is, for example, a user interface system that detects the user's type speed or the number of mouse clicks of the user, and the user sits down to detect the state of leaving the user (the frequency of leaving and the number of times of leaving). For example, a pressure sensor provided on a chair. The sensor 200 is a voice recognition system that detects the number of conversations or the state of the user, a vital sensor that detects the sleep time of the user, the quality of sleep, or the wake-up time and bedtime (specifically, a sleep meter or an electroencephalograph). ). The user's sleep time, sleep quality, or wake-up time/sleep time may be detected by executing an application of a mobile terminal such as a smartphone, or may be detected by a dedicated wearable terminal.

Further, the sensor 200 may include a sensor that detects environmental information around the user and outputs the detected environmental information to the control device 100. Such a sensor 200 is, for example, a solar radiation sensor, a received light amount sensor, a temperature sensor, an odor sensor, a microphone, a CO ₂ concentration sensor, or the like. The number of sensors 200 included in the environment control system 10 is not particularly limited.

[Input device]
The input device 300 is a user interface device that receives an operation for a user to input information to the control device 100. The input device 300 outputs behavior index information (medicine intake history, eating and drinking history), subjective index information, schedule information, user information, and the like to the control device 100, for example, based on a user operation.

In addition, the input device 300 outputs, to the control device 100, the evaluation information of the user regarding the awakening control during or after the execution, based on the operation of the user. The evaluation information is used to calculate a reward in machine learning.

The input device 300 is, for example, a mobile terminal such as a smartphone or a tablet terminal, but may be a wearable device such as a smart watch. Further, the input device 300 may be a microphone, a mechanical push button, a keyboard, a mouse, or the like. The number of input devices 300 included in the environment control system 10 is not particularly limited.

[Environmental control equipment]
The environment control device 400 is a device for controlling an environment (a light environment, an air environment, a temperature environment, or the like) around the user, and is a device controlled by the control device 100 in the awakening control. The environment control device 400 is, specifically, a device such as a lighting device that outputs light (that is, a device that stimulates a user with light).

The environment control system 10 may include a plurality of types of lighting devices as the environment control device 400. FIG. 3 is a diagram showing a plurality of types of lighting equipment. As shown in FIG. 3, the plurality of types of lighting devices include, for example, lighting devices that perform direct lighting such as downlights, lighting devices that perform indirect lighting such as cove lighting and cornice lighting, and upper awakening lighting and lower lighting. Side awakening lighting is included. In the awakening control, these multiple types of lighting devices may be individually controlled, or may be grouped and controlled in group units.

The environment control device 400 may be a device other than the lighting device and may include another device that controls the environment in order to wake up the user. The environment control device 400 may include, in addition to light, a device that stimulates the user with images, sounds, scents, vibrations, temperature and humidity, airflow, and tactile sensations. Specifically, the environment control device 400 may further include an air conditioner, an air purifier, a ventilation fan, a fan, or floor heating. Further, the environment control device 400 may include an opening/closing device for a light-shielding facility (for example, a blind and a curtain) that covers the window so that the window can be opened/closed. Further, the environment control device 400 may include a video device, an audio device, or an audiovisual device. Further, the environment control device 400 may include an fragrancer. The environment control device 400 may also include a massager.

[Control device]
Next, the control device 100 will be described. The control device 100 acquires the physiological index information as the input information, and determines the control content of the environmental control device 400 in the awakening control based on the acquired input information. Further, the control device 100 outputs a control signal for controlling the environment control device 400 to the environment control device 400 according to the determined control content. The control device 100 is realized by, for example, a microcomputer, but may be realized by a processor or the like.

Specifically, the control device 100 includes a first acquisition unit 110, a determination unit 120, a control unit 130, a second acquisition unit 150, a reward calculation unit 160, a reward condition setting unit 170, and an update unit 180. And a storage unit 190. Among these constituent elements, constituent elements other than the control unit 130 constitute the learning device 100a. The reward calculation unit 160, the reward condition setting unit 170, the update unit 180, and the storage unit 190 configure the learning unit 100b.

The first acquisition unit 110 acquires input information including user's physiological index information.

The determination unit 120 determines the control content for awakening the user from the input information according to the control content determination rule. The determination unit 120 specifically determines the control content of the environment control device 400 controlled in the awakening control for waking up the user. The control content determination rule is stored in the storage unit 190.

The control unit 130 controls the environment control device 400 based on the control content determined by the determination unit 120. Specifically, the control unit 130 outputs a control signal corresponding to the control content to the environment control device 400.

The 2nd acquisition part 150 acquires the evaluation information which shows a user's evaluation with respect to awakening control. The evaluation information includes information indicating an evaluation of the control executed by the control unit 130, and includes, for example, information input by the user via the input device 300 after the awakening control. The second acquisition unit 150 acquires the information output by the input device 300 as the evaluation information, but may acquire the information output by the sensor 200 as the evaluation information.

The reward calculation unit 160 calculates a reward based on the evaluation information acquired by the second acquisition unit 150. Details of the process of calculating the reward will be described later.

The reward condition setting unit 170 sets conditions for calculating the reward in the reward calculating unit 160. As described below, the condition is, for example, a weighting coefficient. The condition may be stored in advance in the storage unit 190, or when the condition is fixed, the reward condition setting unit 170 may not be provided.

The update unit 180 updates the control content determination rule by machine learning using a value based on the evaluation information acquired by the second acquisition unit 150 as a reward.

The storage unit 190 is a storage device that stores control content determination rules, usage history information of the environment control system 10, user schedule information output by the input device 300, and the like. The storage unit 190 is realized by, for example, a semiconductor memory.

[Operation during awakening control]
Next, the operation of the control device 100 during awakening control will be described. FIG. 4 is a flowchart of the operation of the control device 100 during awakening control.

First, the 1st acquisition part 110 acquires input information containing a user's physiological index information (S110). FIG. 5 is a diagram showing physiological index information that can be used as input information. As shown in FIG. 5, the physiological index information includes heartbeat (pulse wave), blink/line of sight, eye movement, pupil change, skin temperature (periphery, nose, forehead), facial expression (emotion), electroencephalogram, saliva, Head movement, sweating (normal sweating, mental sweating), respiration, body movement, blood flow (brain/periphery), etc. are included. The heartbeat used as the physiological index information includes not only the heart rate but also frequency components LF, HF, HF/LF of heartbeat fluctuation. The physiological index information may include information (time information) indicating changes with time of these items.

The 1st acquisition part 110 acquires at least 1 of these physiological index information as input information. The first acquisition unit 110 acquires, for example, the physiological index information from the sensor 200, but may acquire the physiological index information from the input device 300 or the physiological index information stored in the storage unit 190. Good.

Next, according to the control content determination rule stored in the storage unit 190, the determination unit 120 is the control content of the awakening control for awakening the user from the input information, and the environment control device 400 including a device that outputs light. The control content of is determined (S120).

The control content determination rule is represented by, for example, an action value function that determines the value of the control content. The action value function is an example of a value function. The determination unit 120 uses, for example, the action value function to determine the control content for which the reward is estimated to be the highest from the input information (for example, the control content for which the maximum reward for the arousal effect is obtained) as the control content for the input information. To determine that.

The control content with the highest reward may differ for each user. Therefore, when the environment control system 10 is shared by a plurality of users, the determination unit 120 may calculate the reward of the user for the control content according to the control content determination rule different for each user.

The control content of the awakening control includes control parameters as shown in FIG. FIG. 6 is a diagram for explaining control parameters for awakening control. The vertical axis of FIG. 6 represents the brightness of light emitted by the lighting device, and the horizontal axis of FIG. 6 represents time.

The awakening control is a control in which the brightness of the light emitted from the lighting device is gradually increased from the start time of the target period to the end time of the target period and then kept constant. Thereby, the environment control system 10 can wake up the user comfortably. At this time, the control parameters determined by the determining unit 120 include (a) the length of the target period, (b) the maximum brightness, (c) the time required to reach the maximum brightness, and (d) the maximum brightness. Is maintained, and (e) the shape of the curve of the brightness until the maximum brightness is reached is illustrated. The shape of the curve includes a linear shape, an upward convex shape, a downward convex shape, and the like.

In the awakening control, the emission color (chromaticity of light emitted by the lighting device) may be changed instead of or in addition to the brightness. When the emission color is changed, the vertical axis in FIG. 6 is replaced with the emission color. FIG. 7 is a chromaticity diagram for explaining the change of the emission color in the awakening control.

For example, when changing the chromaticity from point b to point a on the chromaticity diagram shown in FIG. 7, the control parameters determined by the determination unit 120 include (a) the length of the target period and (b) a. Chromaticity of point, (c) time required for chromaticity to reach from point b to point a, (d) time to maintain chromaticity of point a, and (e) reach chromaticity of point a The shape of the chromaticity curve up to the above is exemplified. The shape of the curve includes a linear shape, an upward convex shape, and a downward convex shape.

In the awakening control, the air conditioner may be controlled in addition to the lighting device. The awakening control targeting the air conditioner is a control in which the strength of the airflow generated by the air conditioner is gradually increased and then made constant from the start time of the target period to the end time of the target period. That is, the vertical axis in FIG. 6 is replaced with the strength of the airflow.

In this case, (a) the length of the target period, (b) the maximum airflow, (c) the time required to reach the maximum airflow, and (d) the maximum airflow are maintained as the control parameters determined by the determination unit 120. And the shape of the curve of the strength of the airflow until reaching the maximum airflow (e). The shape of the curve includes a linear shape, an upward convex shape, a downward convex shape, and the like.

After step S120, the control unit 130 executes control of the environmental control device 400 (that is, awakening control) based on the determined control content (S130). Specifically, the control unit 130 outputs a control signal corresponding to the control content to the environment control device 400.

Next, the 2nd acquisition part 150 acquires the evaluation information which shows a user's evaluation with respect to the awakening control performed in step S130 (S140). The second acquisition unit 150 acquires the information output by the input device 300 as the evaluation information, but may acquire the information output by the sensor 200 as the evaluation information.

Next, the reward calculation unit 160 calculates a reward based on the evaluation information acquired in step S140 (S150). Details of the reward calculation operation will be described later. The acquisition of the evaluation information in step S150 is performed after the awakening control, but may be performed during the awakening control.

Next, the updating unit 180 updates the control content determination rule by machine learning using the reward calculated by the reward calculating unit 160 (S160). The updating unit 180 learns the determination of the control content adapted to the user (that is, the control content with which the user receives the most reward) by the reinforcement learning based on the reward calculated by the reward calculating unit 160. As described above, in the first embodiment, the updating unit 180 updates the control content determination rule by updating the action value function.

Hereinafter, a method of updating the action value function will be described. Q learning and TD learning are known as typical methods of reinforcement learning. Hereinafter, Q learning will be described as an example. Q-learning is a method of learning the value Q(s, a) of selecting the control content a under the user's state s indicated by the input information, and in a certain state s, the value Q(s, a) The highest control content a is selected as the optimum control content. The learning device 100a (update unit 180) selects various control contents a under a certain state s, and rewards the control contents a at that time. Thereby, the learning device 100a learns better selection of control content, that is, the correct value Q(s,a). Such an updating formula of the value Q(s, a) can be expressed by Formula 1, for example.

Here, it s _t represents a state at time t, a _t represents the control content at time t. The state changes to s _t+1 depending on the control content a _t . r _t+1 represents the reward obtained by changing the state. In addition, the term with max is the value obtained by multiplying γ by the Q value under the state s _t+1 when the control content a _t+1 having the highest Q value known at that time is selected. Here, γ is a parameter of 0<γ≦1 and is called a discount rate. Further, α is a learning coefficient, and is set in a range of 0<α≦1.

The above method is an example of the method of reinforcement learning. For the reinforcement learning, any existing method such as a method using a neural network or a method combining deep learning with the reinforcement learning may be used.

[Reward calculation operation]
Next, details of the reward calculating operation in step S150 will be described. FIG. 8 is a flowchart of the reward calculation operation.

First, the reward calculation unit 160 determines the individual reward Fa for the feeling of comfort (S210). The reward calculation unit 160 determines the individual reward Fa by using, for example, the subjective index information indicating the subjective evaluation result of the user output by the input device 300 as the evaluation information. The individual reward Fa may be determined using the heart rate as the evaluation information. In this case, the higher the feeling of comfort indicated by the subjective index information or the heart rate, the larger the value of the individual reward Fa.

Next, the reward calculation unit 160 determines the individual reward Fb for the refresh feeling (S220). The reward calculation unit 160 determines the individual reward Fb by using the subjective index information of the user output by the input device 300 as the evaluation information, for example. In this case, the higher the comfort level indicated by the subjective index information, the larger the value of the individual reward Fb.

Next, the reward calculation unit 160 determines an individual reward Fc for the user's motivation (S230). The reward calculation unit 160 determines the individual reward Fc by using the subjective index information of the user output by the input device 300 as the evaluation information, for example, but evaluates the type speed of the user detected by the user interface system used as the sensor 200. The individual reward Fc may be determined as the information. In this case, the higher the degree of motivation indicated by the subjective index information, the larger the value of the individual reward Fc, and the faster the type speed, the larger the value of the individual reward Fc.

Next, the reward calculation unit 160 determines the individual reward Fd for the drowsiness level (S240). The reward calculation unit 160 determines the individual reward Fd using, for example, the user's subjective index information output by the input device 300 as evaluation information, but the user's blink in a predetermined period detected by the camera used as the sensor 200. The individual reward Fd may be determined by using the number of times as evaluation information. In this case, the higher the degree of reduction of the drowsiness level indicated by the subjective index information, the larger the value of the individual reward Fd, and the smaller the number of blinks after awakening than the number of blinks before falling asleep, the smaller the individual reward Fd. The value increases.

Next, the reward calculation unit 160 determines an individual reward Fe for improving the concentration level after awakening (S250). The reward calculation unit 160 determines the individual reward Fe, for example, using the subjective index information of the user output by the input device 300 as the evaluation information, but evaluates the type speed of the user detected by the user interface system used as the sensor 200. The individual reward Fe may be determined as the information. In this case, the higher the motivation improvement degree indicated by the subjective index information, the larger the value of the individual reward Fe, and the faster the type speed, the larger the value of the individual reward Fe.

Then, the reward calculation unit 160 determines the reward F for the control content based on the individual rewards Fa to Fe determined in steps S210 to S250 (S260). At this time, the reward calculation unit 160 may calculate the reward F by weighting and adding the individual rewards Fa to Fe. For example, the reward calculation unit 160 may calculate the reward F based on Expression 2.

F=w1×Fa+w2×Fb+w3×Fc+w4×Fd+w5×Fe (Equation 2)

w1 to w5 are weights of the items set by the reward condition setting unit 170, and are examples of reward conditions. That is, the reward condition setting unit 170 sets the weights w1 to w5 when the reward calculation unit 160 performs weighted addition.

Note that the reward condition setting unit 170 may change the condition (for example, weight) according to at least one of weather, season, and time zone when the user awakens. For example, when the weather, season, and time zone are included in the input information acquired by the first acquisition unit 110, the reward condition setting unit 170 acquires information about the weather, season, and time zone from the first acquisition unit 110. can do. In addition, the reward condition setting unit 170 may acquire the information regarding the season and the time zone from a general-purpose timer IC (timer circuit) that measures the current time, which is included in the control device 100, or a real-time clock IC.

Although the reward calculating operation has been described above, such a reward calculating operation is an example. For example, the items for determining individual rewards (comfort, refreshment, motivation, drowsiness level, and concentration level) are examples, and the reward is calculated by determining individual rewards for at least one item. It should be done. Further, in the calculation of the reward, the individual reward may be determined for other items. FIG. 9 is a diagram showing items that can be used to calculate a reward.

In the reward calculation operation, information indicating subjective evaluation results, behavior index information (type speed), or physiological index information (heart rate and blink) is used to determine individual rewards. Was used as. Here, in the operation of calculating the reward, the individual reward may be determined using other physiological index information. FIG. 10: is a figure which shows the relationship between the item for determining individual reward, and the physiological index information which can be used for determining the said individual reward.

As shown in FIG. 10, the items for determining the individual reward include an item indicating the state of the user during awakening control and an item indicating the state of the user after awakening. The items for determining the individual reward include items determined based on changes in physiological index information before falling asleep and after waking up. As described above, the individual reward may be absolutely determined based on the state of the user during or after awakening control, or may be relatively determined based on changes in physiological index information before falling asleep and after awakening. May be.

[Other input information 1]
The input information is not limited to the physiological index information. Hereinafter, other input information will be described with reference to FIG.

The 1st acquisition part 110 may acquire action index information which shows a user's action as input information. The behavior index information includes the type speed at which the user operates the keyboard, sleep time, sleep quality, wake-up time, bedtime, number of mouse clicks, frequency of leaving and leaving, number of conversations/state of conversation, break time, The history of medicine intake and the history of eating and drinking are included. The action index information may include information (time information) indicating changes with time of these items. The action index information is acquired from the sensor 200, for example, but may be acquired from the input device 300.

In addition, the first acquisition unit 110 may acquire subjective index information as input information. Subjective index information includes drowsiness, motivation, physical condition/fatigue, stress, concentration, performance, tension/relaxation degree, frustration/anger/sadness, and the like. The subjective index information may include information (time information) indicating changes with time of these items. The subjective index information is acquired from the input device 300, for example.

The first acquisition unit 110 may also acquire schedule information indicating the user's schedule as input information. The schedule information includes the date of use, the day before use, the activity schedule of the next day (meeting, etc.), the work state (taking in, leaving, having a meeting, etc.), the season to which the day of use belongs, the time period of use, and the like. The schedule information is acquired from the input device 300, for example.

The first acquisition unit 110 may also acquire, as input information, usage history information of the user's environment control system 10 (wakeup control). The usage history information includes usage time/time, day of the week, timing, input information, output information, reward, and the like. The usage history information is acquired from the storage unit 190, for example. That is, the usage history information is stored in the storage unit 190.

In addition, the first acquisition unit 110 may acquire environment information around the user as input information. The environmental information includes weather (amount of solar radiation), amount of received light (that is, light environment information), season/time zone, environmental temperature, humidity, odor, sound environment, CO ₂ concentration, and the like.

The first acquisition unit 110 may also acquire user information as input information. The user information includes sex, age, race, place of origin, occupation, constitution (such as photosensitivity), medical history (including insomnia), and the like. The user information is acquired from the input device 300, for example.

[Other input information 2]
The 1st acquisition part 110 may acquire a control parameter in sleep control as input information. Specifically, the first acquisition unit 110 acquires, as input information, a control parameter in sleep control performed in a sleep induction period (or sleep period) before (for example, immediately before) the wakefulness control to be performed. Good. The control parameters for sleep control will be described below. 11 and 12 are diagrams for explaining control parameters for sleep control. The vertical axis in FIGS. 11 and 12 represents the brightness of light emitted from the lighting device, and the horizontal axes in FIGS. 11 and 12 represent time.

In the following, among the relaxation period, the sleep induction period, and the sleep period, the control content of the sleep induction period (in other words, the control content of the light fluctuation control) will be described.

As shown in FIG. 11, the control parameters for sleep control include the length of the entire sleep induction period, the maximum brightness and the minimum brightness, the rising time required to raise the brightness, the time for which the maximum brightness is maintained, and the brightness. Required time for lowering the brightness, time required to maintain the minimum brightness, cycle, rising curve showing how to change when increasing brightness (for example, slope), and how to change when decreasing brightness (for example, , Slope) is included. The maximum brightness and the minimum brightness mean the maximum value and the minimum value of the brightness when the brightness is changed periodically.

Further, at least one of the maximum brightness, the minimum brightness, various times, and various curves may change with the passage of time. FIG. 12 shows an example in which the maximum brightness changes with the passage of time.

As shown in FIG. 12, the sleep control parameters further include a change start time at which a change in maximum brightness starts, a change end period at which a change in maximum brightness ends, and a method of changing maximum brightness. A change curve shown and a change target value showing the maximum brightness after the change may be included.

Note that in sleep control, the emission color (chromaticity of light emitted by the lighting device) may be changed instead of or in addition to the brightness. When the emission color is changed, the control parameters for sleep control may include a control parameter for the emission color in addition to the control parameter for the brightness. For example, when changing the emission color from point b to point a on the chromaticity diagram shown in FIG. 7, the control parameters for sleep control include chromaticity at point a, chromaticity at point b, and chromaticity at point a. Time, the chromaticity at point a is maintained, the chromaticity at point b is reached, the chromaticity at point b is maintained, the cycle, the chromaticity at point a is reached. The shape of the curve until reaching the point and the shape of the curve until reaching the chromaticity at point b are included.

Also in this case, at least one of the chromaticity at point a, the chromaticity at point b, various periods, and various curves may change over time. For example, when the chromaticity at the point a changes with time, the sleep control parameters include a change start time at which the chromaticity at the point a starts to change, and a change end to end the change in the chromaticity at the point a. A period, a change curve indicating how the chromaticity at the point a changes, and a change target value indicating the chromaticity at the point a after the change may be included.

[Modification 1]
As described above, the second acquisition unit 150 can acquire the evaluation information during the execution of the awakening control. Then, the reward calculation unit 160 can calculate the reward during execution of the awakening control based on the acquired evaluation information, and the update unit 180 calculates the reward based on the calculated reward during the execution of the awakening control. The control content determination rule (action value function) can be updated. As a result, the determination unit 120 can change the control content (that is, redetermine the control content) during the execution of the awakening control.

In this way, if the control content is re-determined during the execution of the awakening control, the environment control system 10 can determine a more appropriate control content for the user's state at that time, and Can wake up effectively.

[Modification 2]
The storage unit 190 may store the control content determined in the past by the determination unit 120. Thereby, the environment control system 10 can substitute and use the control content stored in the storage unit 190 when the input information cannot be acquired and the control content cannot be determined for some reason. The control content stored in the storage unit 190 may be stored as a part of the above-mentioned usage history information or may be stored alone. The storage unit 190 may store the control content in association with the input information used to determine the control content, or may use the control content to determine the control content. It may be stored without being associated with the input information.

[Effects]
As described above, the environment control system 10 uses the first acquisition unit 110 that acquires the input information including the physiological index information of the user and the control content for awakening the user from the input information according to the control content determination rule. Therefore, the determination unit 120 that determines the control content of the environment control device 400 including the device that outputs light, the control unit 130 that controls the environment control device 400 based on the determined control content, and The 2nd acquisition part 150 which acquires the evaluation information which shows a user's evaluation with respect to control is provided, and the update part 180 which updates a control content determination rule by machine learning which uses the value based on evaluation information as a reward.

The environment control system 10 as described above can determine the control content based on the control content determination rule learned in association with the physiological index information and the evaluation information. Therefore, the environment control system 10 can effectively awaken the user.

Further, for example, the control content determination rule includes a value function that determines the value of the control content, and the updating unit 180 updates the value function.

Such an environment control system 10 can determine the control content based on the value function learned in association with the physiological index information and the evaluation information.

In addition, for example, the environment control system 10 further includes a reward calculating unit 160 that calculates a reward based on the evaluation information, and a reward condition setting unit 170 that sets conditions for calculating the reward in the reward calculating unit 160.

Such an environment control system 10 can calculate the reward according to the condition set by the reward condition setting unit 170. For example, if the condition is set according to the user's preference, the control content according to the user's preference can be easily determined.

Further, for example, the environmental control system 10 further includes a storage unit 190 that stores the control content determined by the determination unit 120.

Such an environment control system 10 reads the control content (for example, the previous control content) stored in the storage unit 190, so that even if the input information cannot be acquired and the control content cannot be determined, Can be controlled to awaken.

In addition, for example, the update unit 180 updates the control content determination rule based on the evaluation information acquired by the second acquisition unit 150 while controlling the environment control device 400 with the control content. The determination unit 120 further determines the control content for the input information during control again according to the control content determination rule updated while controlling the environment control device 400.

Such an environment control system 10 can update the control content determination rule and change the control content according to the state of the user under control. That is, the environment control system 10 can determine the more appropriate control content for the user's state at that time by learning during the control, so that the user can be more effectively awakened.

Further, for example, the input information further includes at least one of user action index information, user schedule information, usage history information of the user's environment control system 10, and environment information.

Such an environment control system 10 can determine the control content based on the control content determination rule learned by associating at least one of the action index information, the schedule information, the usage history information, and the environment information with the evaluation information. it can.

Further, for example, the control unit 130 can further execute sleep control for making the user sleep by using the environment control device 400, and the input information further includes a control parameter in sleep control.

Such an environment control system 10 can determine the control content based on the control content determination rule learned by associating the control parameter in sleep control with the evaluation information.

Further, for example, the environment control device 400 includes devices other than the device that outputs light. The determination unit 120 determines the control content of the environment control device 400 including the other devices.

Such an environment control system 10 can perform control for awakening a user by using each of a device that outputs light and a device other than that.

Further, for example, the other device is an air conditioner.

Such an environment control system 10 can perform control for waking the user by using each of the device that outputs light and the air conditioner.

In addition, for example, the control content for waking up the user is (a) the length of the target period in the awakening control for increasing the brightness of the light output by the device that outputs light performed in the target period, (b) ) Maximum brightness, (c) time required to reach maximum brightness, (d) time when maximum brightness is maintained, and (e) shape of curve of brightness until reaching maximum brightness At least one of

Such an environment control system 10 can determine the control parameter in the awakening control as the control content.

In addition, the environment control method executed by the computer such as the environment control system 10 includes the first acquisition step (S110) of acquiring input information including the physiological index information of the user, and the user from the input information according to the control content determination rule. A determination step (S120) of determining the control content of the environment control equipment 400 including the equipment that outputs light, which is the control content for awakening, and the control of the environment control equipment 400 is executed based on the determined control content. The control content determination rule is updated by a control step (S130) for performing, a second acquisition step (S140) for acquiring evaluation information indicating the user's evaluation of the executed control, and machine learning using a value based on the evaluation information as a reward. And an updating step (S160).

The environment control system 10 as described above can determine the control content based on the control content determination rule learned in association with the physiological index information and the evaluation information. Therefore, the environment control system 10 can effectively awaken the user.

(Embodiment 2)
[Constitution]
In the second embodiment, another configuration of the environment control system will be described with reference to FIG. FIG. 13 is a block diagram showing a functional configuration of the environment control system according to the second embodiment.

As shown in FIG. 13, the environment control system 10b according to the second embodiment includes a plurality of individual environment control systems 10c and a server apparatus 500 communicably connected to each of the plurality of individual environment control systems 10c. ..

Each of the plurality of individual environment control systems 10c has, for example, a configuration similar to that of the environment control system 10 of the first embodiment, but in FIG. 13, the configuration other than the first acquisition unit 110 and the storage unit 190 is omitted. ing. The number of the plurality of individual environment control systems 10c included in the environment control system 10b is not particularly limited.

The server apparatus 500 receives the input information acquired by the first acquisition unit 110 from each of the plurality of individual environment control systems 10c and the learning result stored in the storage unit 190 (for example, control content, reward, and updated). At least one of the action value functions) and centrally manage it. The server device 500 stores the acquired information in the storage unit 510. As a result, it is possible to share the learning result of each of the plurality of individual environment control systems 10c.

Note that at least one control device 100 of the plurality of control devices 100 included in each of the plurality of individual environment control systems 10c may function as a server device. That is, the environment control system 10b does not have to include the server device 500 separately from the individual environment control system 10c. In this case, each of the plurality of individual environment control systems 10c is communicably connected to each other and communicates at least one of the input information, the evaluation information, and the learning result with each other. Then, the updating unit 180 updates the action value function based on at least one of the input information acquired from the other individual environment control system 10c and the learning result.

[Effects]
As described above, the environment control system 10b includes a plurality of individual environment control systems 10c including the first acquisition unit 110, the determination unit 120, the control unit 130, the second acquisition unit 150, and the update unit 180. Each of the plurality of individual environment control systems 10c is communicably connected to each other, and communicates at least one of the input information and the learning result with each other. Then, the updating unit 180 updates the control content determination rule based on at least one of the input information and the learning result acquired from the other individual environment control system 10c.

In such an environment control system 10b, the update unit 180 can update the action value function of the own device based on the input information and the like acquired by the other individual environment control system 10c. Therefore, the accuracy of learning in the own device is improved, and a more appropriate action value function can be obtained.

The environment control system 10b includes a plurality of individual environment control systems 10c, and a server device 500 communicably connected to each of the plurality of individual environment control systems 10c.

Such an environment control system 10b can centrally manage at least one of input information, evaluation information, and a learning result. Further, when the server device 500 includes a learning unit, the action value function can be updated by machine learning based on the input information and the evaluation information acquired from each of the plurality of individual environment control systems 10c. .. Therefore, learning accuracy is improved, and a more appropriate action value function can be obtained. In this case, it is preferable that the server device 500 includes a processor or the like that can perform processing faster than the control device 100.

(Other embodiments)
Although the embodiments have been described above, the present invention is not limited to the above embodiments.

For example, in the above embodiment, the environment control system may determine a plurality of patterns of control content as a recommended pattern to the user, and the user may select one of the plurality of patterns of control content using the input device. .. In this case, the environmental control system executes control of the selected control content.

Further, in the above-described embodiment, the example in which the control parameter (that is, the control content) of the sleep control is used as the input information to determine the control content of the environmental control device in the wakeup control has been described. However, conversely, a control parameter (that is, control content) of awakening control may be used as input information to determine the control content of the environment control device in sleep control.

Further, in the above embodiment, the place where the awakening control is performed is not particularly limited. Awakening control is performed, for example, in a nap room of an office, but may be performed in a house, a medical facility, a nursing facility, or the like.

Further, in the above embodiment, the environment control system is realized by a plurality of devices, but may be realized as a single device. When the environment control system is implemented by a plurality of devices, the components described in the above embodiments may be distributed to the plurality of devices in any way. Further, the environment control system may be realized as a client server system.

Further, the communication method between the devices in the above embodiment is not particularly limited. The communication performed between the devices is wireless communication using a communication standard such as specific low power wireless communication, ZigBee (registered trademark), Bluetooth (registered trademark), or Wi-Fi (registered trademark). It may be communication. Further, a relay device (not shown) may intervene in the communication between the devices.

Further, in the above-described embodiment, the processing executed by the specific processing unit may be executed by another processing unit. Further, the order of the plurality of processes may be changed, or the plurality of processes may be executed in parallel.

Further, in the above-described embodiment, each component may be realized by executing a software program suitable for each component. Each component may be realized by a program execution unit such as a CPU or a processor reading and executing a software program recorded in a recording medium such as a hard disk or a semiconductor memory.

Further, each component may be realized by hardware. For example, each component may be a circuit (or integrated circuit). These circuits may constitute one circuit as a whole or may be separate circuits. Further, each of these circuits may be a general-purpose circuit or a dedicated circuit.

Further, the general or specific aspects of the present invention may be realized by a recording medium such as a system, a device, a method, an integrated circuit, a computer program, or a computer-readable CD-ROM. Further, the system, the device, the method, the integrated circuit, the computer program, and the recording medium may be implemented in any combination. For example, the present invention may be realized as the control device according to the above embodiment. Further, the present invention may be realized as a program for causing a computer to execute the environment control method according to the above-described embodiment, or as a computer-readable non-transitory recording medium in which such a program is recorded. May be realized.

In addition, it is realized by making various modifications to those embodiments by those skilled in the art, or by arbitrarily combining the components and functions of the embodiments without departing from the spirit of the present invention. The present invention also includes the forms.

10, 10b Environment control system 10c Individual environment control system 110 First acquisition unit 120 Determination unit 130 Control unit 150 Second acquisition unit 160 Reward calculation unit 170 Reward condition setting unit 180 Update unit 190 Storage unit 400 Environmental control device 500 Server device

Claims (13)

A first acquisition unit for acquiring input information including user's physiological index information;
According to a control content determination rule, from the input information, a determination unit that determines the control content of the environmental control device that is a control content for awakening the user, and that includes a device that outputs light,
A control unit that executes control of the environment control device based on the determined control content;
A second acquisition unit that acquires evaluation information indicating the evaluation of the user for the executed control;
An environment control system comprising: an updating unit that updates the control content determination rule by machine learning using a value based on the evaluation information as a reward. The control content determination rule includes a value function that determines the value of the control content,
The environment control system according to claim 1, wherein the updating unit updates the value function. further,
A reward calculation unit that calculates the reward based on the evaluation information,
The environment control system according to claim 1, further comprising: a reward condition setting unit that sets a condition for calculating the reward in the reward calculating unit. The environment control system according to claim 1, further comprising a storage unit that stores the control content determined by the determination unit. The update unit updates the control content determination rule based on the evaluation information acquired by the second acquisition unit while controlling the environment control device with the control content,
The determination unit further determines the control content for the input information during the control again according to the control content determination rule updated while controlling the environment control device. Environmental control system. The input information further includes at least one of behavior index information of the user, schedule information of the user, usage history information of the environment control system of the user, and environment information. The environment control system according to item 1. The control unit is further capable of executing sleep control for sleeping the user using the environment control device,
The environment control system according to claim 1, wherein the input information further includes a control parameter in the sleep control. The environment control device further includes a device other than the device that outputs the light,
The environment control system according to claim 1, wherein the determination unit determines the control content of the environment control device including the other device. The environment control system according to claim 8, wherein the other device is an air conditioner. The control content for waking up the user is (a) the length of the target period and (b) the maximum in the control for increasing the brightness of the light output by the device that outputs the light performed in the target period. Brightness, (c) time required to reach the maximum brightness, (d) time when the maximum brightness is maintained, and (e) a curve of brightness until the maximum brightness is reached. The environmental control system according to claim 1, comprising at least one of shapes. A plurality of individual environment control systems having the first acquisition unit, the determination unit, the control unit, the second acquisition unit, and the update unit,
Each of the plurality of individual environment control systems are communicably connected to each other, and mutually communicate at least one of the input information and the learning result,
The update unit updates the control content determination rule based on at least one of the input information and the learning result acquired from another individual environment control system. Environmental control system. A plurality of individual environment control systems,
The environment control system according to claim 11, comprising a server device communicatively connected to each of the plurality of individual environment control systems. A first acquisition step of acquiring input information including user's physiological index information;
In accordance with a control content determination rule, a determination step of determining the control content of the environmental control device including the device that outputs light, which is the control content for awakening the user from the input information.
A control step of executing control of the environmental control device based on the determined control content;
A second acquisition step of acquiring evaluation information indicating the evaluation of the user with respect to the executed control;
An updating step of updating the control content determination rule by machine learning using a value based on the evaluation information as a reward.

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