Air-conditioning system

Abstract

To provide an air-conditioning system capable of controlling an air conditioner, etc., according to a situation of a target space and biometric information of people, and capable of improving comfort of people in the target space.SOLUTION: An air-conditioning system comprises: air-conditioning means for conditioning air in a target space; biometric information acquisition means for acquiring biometric information of people in the target space; setting means for calculating and setting a reference value from the biometric information; and control means for controlling the air-conditioning means. The control means uses the reference value and the biometric information to determine control content of the air-conditioning means. When a preset update condition is established, the setting means recalculates the reference value from the biometric information, and updates the reference value.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The present disclosure relates to an air conditioning system.

Background Art

[0002] There is known a system in which control of air conditioning equipment or the like arranged in a space is performed based on user vital data, user mental data, weather information, traffic information, etc. (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, even when the situation of the target space changes, for example, the time zone, season, occupancy situation of people in the target space (such as replacement of people in the target space), the vital data (biological information) of the people in the target space also changes. For this reason, in the air conditioning system as shown in Patent Document 1, the estimation accuracy of the comfort of a person based on the biological information of the person in the target space may deteriorate. In particular, when there are a plurality of people in the target space, since the comfort level varies from person to person, the deterioration of the estimation accuracy of comfort may become significant.

[0005] The present disclosure has been made to solve such problems. The object is to provide an air conditioning system capable of controlling an air conditioner or the like according to the biological information of a person in a target space and also according to the time zone, season, occupancy situation of people in the target space, etc., and capable of improving the comfort of the people in the target space.

Means for Solving the Problems

[0006] The air conditioning system according to the present disclosure includes an air conditioning means for conditioning the air in the target space, a biological information acquisition means for acquiring the biological information of a person in the target space, a setting means for calculating and setting a reference value from the biological information, and a control means for controlling the air conditioning means. The control means determines the control content of the air conditioning means using the reference value and the biological information. The setting means recalculates the reference value from the biological information and updates the reference value when a preset update condition is satisfied.

Advantages of the Invention

[0007] According to the air conditioning system of the present disclosure, in controlling an air conditioner or the like according to the biological information of a person in the target space, it is possible to control the air conditioner or the like according to the situation of the target space, and it is possible to improve the comfort of the person in the target space.

Brief Description of the Drawings

[0008]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Modes for Carrying Out the Invention

[0009] A mode for implementing the air conditioning system according to the present disclosure will be described with reference to the accompanying drawings. In each figure, the same or corresponding parts are denoted by the same reference numerals, and overlapping descriptions will be appropriately simplified or omitted. In the following description, for convenience, the positional relationship of each structure may be expressed based on the illustrated state. Note that the present disclosure is not limited to the following embodiments, and within the scope not departing from the gist of the present disclosure, free combinations of each embodiment, modifications of any component of each embodiment, or omissions of any component of each embodiment are possible.

[0010] Embodiment 1. Embodiment 1 of the present disclosure will be described with reference to FIGS. 1 to 8. FIG. 1 is a plan view schematically showing the configuration of the target space of the air conditioning system. FIG. 2 is a perspective view of the air conditioner included in the air conditioning system. FIG. 3 is a perspective view showing an enlarged main part of the air conditioning. FIG. 4 is a block diagram showing the configuration of the air conditioning system. FIG. 5 is a block diagram showing the configuration of a modification example of the air conditioning system. FIG. 6 is a flowchart showing an operation example of the inference device included in the air conditioning system. FIG. 7 is a flowchart showing an operation example of the air conditioning system. FIG. 8 is a diagram showing an example of a configuration for realizing the functions of the control device of the air conditioning system.

[0011] The air conditioning system according to this embodiment performs air conditioning in the target space 1 as shown in FIG. 1. The target space 1 is, for example, the internal space of one room. Specific examples of the target space 1 include the internal spaces such as conference rooms in offices.

[0012] The air conditioning system according to this embodiment includes an air conditioner 301. The air conditioner 301 is a device that controls mainly the thermal environment in the target space 1 by performing air conditioning in the target space 1. The air conditioner 301 is installed on the wall surface or ceiling surface of the room related to the target space 1. In the configuration example described here, the air conditioner 301 is installed on the ceiling surface.

[0013] The air conditioner 301 is an air conditioning means for conditioning the air in the target space 1 by adjusting the temperature, humidity, etc. of the air in the target space 1. The air conditioner 301 is capable of performing an air conditioning operation including one or both of a cooling operation and a heating operation. Further, the air conditioner 301 may be capable of performing any one or more of a dehumidifying operation, a humidifying operation, and a blowing operation.

[0014] The air conditioner 301 of this embodiment is an indoor unit of an air conditioner. The air conditioner 301, which is an indoor unit, is connected to an outdoor unit via a pipe through which a refrigerant flows. The illustration of this pipe and the outdoor unit is omitted in the present disclosure. Also, the illustration of each device constituting the refrigeration cycle necessary for the air conditioner to execute the air conditioning operation and the blowing fan for blowing air into the target space 1 is omitted in the present disclosure. Devices constituting the refrigeration cycle include, for example, a heat exchanger and a compressor.

[0015] As shown in FIG. 2, the air conditioner 301 includes a housing 20. The housing 20 of the air conditioner 301 is formed in a box shape having a substantially rectangular parallelepiped shape. A rectangular or square bottom panel 21 is provided at the lower part of the housing 20 of the air conditioner 301. An intake port 22 is formed in the bottom panel 21. The intake port 22 is an opening for taking air from the outside into the inside of the housing 20. A filter (not shown) is mounted on the intake port 22. In the configuration example shown in FIG. 2, the intake port 22 is disposed at the center of the bottom panel 21.

[0016] Further, an air outlet 23 is formed in the bottom panel 21. The air outlet 23 is an opening for discharging air from the inside of the housing 20 to the outside. In the illustrated configuration example, four air outlets 23 are formed in the bottom panel 21. The four air outlets 23 are disposed around the intake port 22 as shown in FIG. 2. The four air outlets 23 are provided along each side of the bottom panel 21, respectively.

[0017] As shown in FIGS. 2 and 3, the air conditioner 301 includes an upper and lower louver 24 and left and right louvers 25. The upper and lower louver 24 and the left and right louvers 25 are provided at each of the air outlets 23. The upper and lower louver 24 is for adjusting the vertical blowing angle of the air blown out from the air outlet 23. The left and right louvers 25 are for adjusting the horizontal blowing angle of the air blown out from the air outlet 23.

[0018] The upper and lower louver 24 is a member having a rectangular plate shape. One end of the upper and lower louver 24 is rotatably attached to a portion of the edge of the air outlet 23 on the central side of the lower surface panel 21. By rotating the upper and lower louver 24 about this one end, the vertical blowing angle of the air blown out from the air outlet 23 is changed.

[0019] Particularly as shown in FIG. 3, the left and right louvers 25 are composed of a plurality of members having a rectangular plate shape. These plurality of members having a rectangular plate shape are arranged along a direction perpendicular to the longitudinal direction of the air outlet 23. One end of the left and right louvers 25 is rotatably attached to a portion on the back side of the edge of the air outlet 23. By rotating the left and right louvers 25 about this one end, the horizontal blowing angle of the air blown out from the air outlet 23 is changed.

[0020] The upper and lower louver 24 and the left and right louvers 25 configured as described above are an example of a wind direction changing means capable of changing the direction in which air is blown out from the air outlet 23 into the room. The air conditioner 301 in this embodiment can blow air in various directions by changing the combination of the direction of the upper and lower louver 24 and the direction of the left and right louvers 25.

[0021] Also, when the direction of the upper and lower louver 24 is set to the most upward direction, the air outlet 23 is blocked by the upper and lower louver 24. The air conditioner 301 in this embodiment can stop the air blowing from a part of the plurality of air outlets 23 by blocking a part of the air outlets 23 with the upper and lower louvers 24.

[0022] Inside the housing 20, an air passage is formed that leads from the suction port 22 to the blowout port 23. In the air passage leading from the suction port 22 to the blowout port 23, a heat exchanger and a blower fan are installed. The heat exchanger heats or cools the air by heat exchange between the air flowing through the air passage and the refrigerant. Whether the air is heated or cooled by the heat exchanger depends on the type of air-conditioning operation executed by the air conditioner 301. The heat exchanger adjusts the temperature, humidity, etc. of the air by heating or cooling the air, and generates conditioned air. Specifically, during the heating operation, the heat exchanger heats the air. During the cooling operation, the heat exchanger cools the air. Also, during the ventilation operation, the air that has passed through the heat exchanger is generated as conditioned air at room temperature.

[0023] The blower fan is for generating an air flow from the suction port 22 toward the blowout port 23 in the air passage inside the housing 20. When the blower fan operates, air is sucked in from the suction port 22 and blown out from the blowout port 23. The air sucked in from the suction port 22 passes through the air passage inside the housing 20 of the air conditioner 301 in the order of the heat exchanger and the blower fan. The air that has passed through the blower fan, that is, the conditioned air, is blown out from the blowout port 23. During the heating operation, warm air is blown out from the blowout port 23. During the cooling operation, cold air is blown out from the blowout port 23. During the ventilation operation, air at room temperature is blown out from the blowout port 23. At this time, the direction in which the air is blown out from the blowout port 23 is adjusted by the upper and lower louvers 24 and the left and right louvers 25 arranged on the leeward side of the blower fan. The air conditioner 301 can blow air at various temperatures in various directions.

[0024] In the configuration example described here, a surface temperature sensor 11 is provided on the lower surface portion of the housing 20 of the air conditioner 301. The surface temperature sensor 11 is a sensor that non - contact detects the surface temperature of a detected object in the target space 1. The surface temperature sensor 11 periodically detects the surface temperature of the detected object in the target space 1. The surface temperature sensor 11 may have, for example, a configuration including an infrared sensor having a plurality of thermopiles (not shown). The surface temperature sensor 11 may scan the temperature detection range by rotationally driving this infrared sensor and generate thermal image data of the temperature detection range using the output of the infrared sensor. The detected objects within the temperature detection range may include, for example, a human body, a floor surface, and a wall surface, etc. By using the surface temperature sensor 11, it is possible to determine the presence or absence of a person in the target space 1, and when a person exists in the target space 1, it is possible to specify the position of the person and detect the surface temperature of the person's body.

[0025] Instead of the thermopile, the surface temperature sensor 11 may be provided with a non - cooled infrared image sensor of the SOI (Silicon on Insulator) diode type. In the case of the SOI diode type, since a silicon diode is used in the sensor portion, it can be manufactured only with silicon semiconductor lines, and there is an advantage that the production cost is low.

[0026] With such a configuration, the surface temperature sensor 11 scans the aforementioned target range and non - contact acquires the surface temperature distribution within the range. By processing the detection result of the surface temperature sensor 11, that is, the surface temperature distribution data acquired by the surface temperature sensor, with an environment control device 100 etc. described later, for example, from the temperature difference from the background, it is possible to detect the presence or absence and position of a heat source including a person in the room, the surface skin temperature of the human body, the parts of the human body (exposed and non - exposed parts of the skin, head, etc.).

[0027] In addition, based on the detection result of the surface temperature sensor 11, the perceived temperature of a person in the room can also be obtained. In this case, the more the human body exposes its skin, the easier it is to detect the perceived temperature. Further, by processing the surface temperature distribution data acquired by the surface temperature sensor with an environmental control device 100 or the like, the number of people in the target space 1 can also be detected. Further, from the change in the number of people in the target space 1, the entry and exit of people to and from the target space 1 can also be detected.

[0028] Next, with reference to FIG. 4 as well, the description of the configuration of the air conditioning system according to this embodiment will be continued. The air conditioner 301 provided in the target space 1 is an example of the environmental control device 300 included in the air conditioning system. The air conditioning system may include, as the environmental control device 300, for example, a blower 302, a ventilation device 303, a humidity control device 304, and a lighting device 305 as shown in FIG. 4.

[0029] The blower 302 is a device that controls the air environment of the target space 1 by generating an air flow in the target space 1. The ventilation device 303 is a device that controls the air environment of the target space 1 by ventilating the air in the target space 1. The humidity control device 304 is a device that controls the air environment of the target space 1 by adjusting the amount of moisture contained in the air in the target space 1. The humidity control device 304 is, for example, a humidifier or a dehumidifier. The blower 302, the ventilation device 303, and the humidity control device 304 may be included in the air conditioning means described above. The lighting device 305 is a device that irradiates visible light into the target space 1. The lighting device 305 can change, for example, the intensity and color temperature of the irradiated light. The brightness in the target space 1 can be controlled by the lighting device 305.

[0030] The air conditioning system according to this embodiment includes an environmental control device 100. The environmental control device 100 can communicate with each of the air conditioner 301, the blower 302, the ventilation device 303, the humidity control device 304, and the lighting device 305, which are environmental control devices 300. The communication between the environmental control device 100 and each of the environmental control devices 300 may be a wired method or a wireless method. The environmental control device 100 controls the operations of the air conditioner 301, the blower 302, the ventilation device 303, the humidity control device 304, and the lighting device 305, which are environmental control devices 300.

[0031] The environmental control device 100 includes an information acquisition unit 110 and a control unit 120. The information acquisition unit 110 acquires information from an information source. In the illustrated configuration example, there are sensors 10 as information sources. In the configuration example shown in FIG. 4, in addition to the surface temperature sensor 11 described above, the sensors 10 include a biological information sensor 12 and an environmental information sensor 13.

[0032] The biological information sensor 12 may include, for example, the following sensors. · A camera that captures a visible image within the target space 1 · A quasi-millimeter wave / millimeter wave radar application sensor · An electroencephalogram sensor · A heart rate sensor · A body temperature sensor

[0033] The environmental information sensor 13 may include, for example, the following sensors. · A room temperature sensor · An outside air temperature sensor · A humidity sensor · An air quality (carbon dioxide concentration, dust concentration, VOC concentration, etc.) sensor · An illuminance sensor · A color temperature sensor · A sound sensor

[0034] The room temperature sensor is a sensor that detects the temperature of the air in the target space 1. The outside air temperature sensor is a sensor that detects the temperature of the air outside the target space 1, especially outdoors. The humidity sensor is a sensor that detects the humidity of the air in the target space 1. The air quality sensor is a sensor that detects the air quality in the target space 1, such as carbon dioxide concentration, dust concentration, VOC concentration, etc. The illuminance sensor is a sensor that detects the brightness in the target space 1, such as light and darkness. The color temperature sensor is a sensor that detects the color temperature, that is, the color tone of the light in the target space 1. The sound sensor is, for example, a microphone that detects the sound in the target space 1.

[0035] The environmental control device 100 is capable of communicating with each of the sensors 10. The communication between the environmental control device 100 and the sensors 10 may be in a wired manner or a wireless manner.

[0036] The information acquisition unit 110 acquires the detection data of these sensors 10. In particular, the surface temperature sensor 11, the biological information sensor 12, and the information acquisition unit 110 constitute a biological information acquisition means for acquiring the biological information of a person in the target space 1. The biological information acquisition means may acquire biological information from, for example, a person's self-report in addition to the surface temperature sensor 11 and the biological information sensor 12. At this time, for example, it is conceivable to enable the self-report of biological information by operating a remote control of the air conditioner 301, a terminal device such as a smartphone held by a person, etc. In addition, when a plurality of people are present in the target space 1 at the same time, the biological information acquisition means can simultaneously acquire the biological information of each of these plurality of people. Further, the environmental information sensor 13 and the information acquisition unit 110 constitute an environmental information acquisition means for acquiring environmental information of one or both of the inside and outside of the target space 1.

[0037] The control unit 120 controls the operation of the environmental control device 300 based on various information acquired by the information acquisition unit 110. This control unit 120 is an example of a control means for controlling the environmental control device 300 including the air conditioning means described above.

[0038] The control unit 120 includes a storage unit 121, a physiological state value acquisition unit 122, a person position detection unit 123, a reference value setting unit 124, a control content determination unit 125, and a device operation control unit 126. The storage unit 121 stores the detection data of the sensors 10 acquired by the information acquisition unit 110. In particular, the biological information of a person detected by the surface temperature sensor 11 and the biological information sensor 12 is stored in the storage unit 121 as time-series data. When the biological information sensor 12 includes a camera or a radar application sensor, or when the surface temperature sensor 11 is used, biological information can be acquired non-contact with the subject. However, the biological information sensor 12 may be a wearable sensor worn by the subject, or may be provided in a smart watch or the like worn by the subject.

[0039] The physiological state value acquisition unit 122 acquires physiological state values from the biological information of a person stored in the storage unit 121. The physiological state value is a quantification of a person's physiological state. Specific examples of physiological state values include skin temperature, perceived temperature, warm / cold sensation, heart rate, blood flow rate, sleepiness level, arousal level, relaxation level, stress level, and the like.

[0040] As described above, the physiological state value acquisition unit 122 can calculate and acquire skin temperature and perceived temperature by using, for example, the detection result of the surface temperature sensor 11. In addition, the physiological state value acquisition unit 122 can calculate and acquire the warm / cold sensation by using the detection result of the surface temperature sensor 11 and the detection result of the environmental information sensor 13. The warm / cold sensation can be quantified, for example, by setting neutral to 0, positive values for the hot side, and negative values for the cold side.

[0041] In addition, the physiological state value acquisition unit 122 can acquire the heart rate from the detection data of the heart rate sensor of the biological information sensor 12. The physiological state value acquisition unit 122 can estimate and acquire the blood flow rate by performing chromaticity analysis of a person's face using, for example, an image captured by the camera of the biological information sensor 12. The physiological state value acquisition unit 122 can estimate and acquire a person's sleepiness level, arousal level, relaxation level, and stress level from the detection data of the electroencephalogram sensor of the biological information sensor 12.

[0042] When the biological information sensor 12 includes a quasi-millimeter wave / millimeter wave radar application sensor, the biological information sensor 12 can acquire at least one of, for example, human body movement, respiratory rate, heart rate, and blood flow as biological information. Also, when the biological information sensor 12 includes a heart rate sensor, the human heart rate can be acquired as biological information. Based on the heartbeat fluctuations detected in this way, the physiological state value acquisition unit 122 extracts the HF component, which is a high-frequency fluctuation component, and the LF component, which is a low-frequency fluctuation component, and may estimate the state of human tension or relaxation using at least one of the numerical value of the HF component and the numerical value of LF / HF. For example, it may be estimated that the higher the HF component, which is a relaxation index in the autonomic nervous system, the higher the relaxation level of the person. Also, it may be estimated that the lower the value of LF / HF, the higher the relaxation level of the person. Also, it may be estimated that the higher the value of LF / HF, the higher the stress level of the person.

[0043] The biological information sensor 12 may detect at least one of human skin temperature, heart rate, eye movement, eyelid movement, and eyelid opening degree as biological information. Then, the physiological state value acquisition unit 122 may estimate the sleepiness level, wakefulness level, relaxation level, and stress level of the person based on the detected biological information of the person.

[0044] When the biological information sensor 12 includes a camera, the physiological state value acquisition unit 122 performs image recognition processing on the image of the person's face captured by the camera to detect at least one of the person's eye movement, eyelid movement, and eyelid opening degree, and may estimate the sleepiness level based on the detection result. For example, when the sleepiness level is high, the number of blinks per hour decreases. Therefore, the physiological state value acquisition unit 122 may calculate the number of blinks per hour from the eyelid movement of the person acquired by the camera and estimate the sleepiness level of the person based on the number.

[0045] When the sleepiness level is high, the opening degree of the eyelids decreases. Therefore, the physiological state value acquisition unit 122 may estimate the sleepiness level of a person based on the opening degree of the person's eyelids acquired by the camera. Also, when the sleepiness level is high, the temperature difference between the skin temperature of the forehead and the skin temperature of the nose increases. The physiological state value acquisition unit 122 may detect the temperature difference between the skin temperature of the person's forehead and the skin temperature of the nose from the thermal image of the person's face acquired using the surface temperature sensor 11, and estimate the sleepiness level of the person based on the temperature difference.

[0046] The person position detection unit 123 detects the position of a person in the target space 1 using the detection data stored in the storage unit 121, particularly the detection result of the surface temperature sensor 11. The surface temperature sensor 11, the information acquisition unit 110, and the person position detection unit 123 constitute person position detection means for detecting the position of a person in the target space 1. Note that the person position detection means is not limited to using the surface temperature sensor 11. For example, when the biological information sensor 12 includes a camera that captures a visible image in the target space 1, the person position detection unit 123 may detect the position of a person in the target space 1 using the image captured by the camera.

[0047] The reference value setting unit 124 is setting means for calculating and setting a reference value from the biological information acquired by the biological information acquisition means described above. Since the reference value is a numerical value, here, the reference value setting unit 124 calculates the reference value using the physiological state value acquired by the physiological state value acquisition unit 122 from the biological information. The reference value setting unit 124 calculates the reference value using the physiological state value within the most recent preset reference value calculation period. Examples of the calculation of the reference value by the reference value setting unit 124 include the following.

[0048] · Set the average value of the physiological state values within the most recent reference value calculation period as the reference value. · Set the median value of the physiological state values within the most recent reference value calculation period as the reference value. · Set the difference between the maximum value and the minimum value of the physiological state values within the most recent reference value calculation period as the reference value.

[0049] In addition, when there are a plurality of people in the target space 1, the reference value setting unit 124 sets a reference value using the physiological state values of the plurality of people in the target space 1. That is, for example, when the average value of the physiological state values during the reference value calculation period is used as the reference value, the reference value setting unit 124 calculates the average value of the physiological state values of the plurality of people in the target space 1 during the most recent reference value calculation period and uses it as the reference value. The reference value calculated by the reference value setting unit 124 is stored, for example, in the storage unit 121.

[0050] The control content determination unit 125 determines the control content of the environmental control device 300 including the air conditioning means using the reference value set by the reference value setting unit 124 and the latest biological information acquired by the biological information acquisition means described above. Here, similar to the calculation of the reference value, the control content determination unit 125 may use, as the latest biological information, the physiological state value acquired by the physiological state value acquisition unit 122 from the biological information. For example, the control content determination unit 125 may determine the control content of the environmental control device 300 including the air conditioning means according to whether the latest physiological state value is greater than or less than the reference value. More specifically, the control content determination unit 125 may determine the control content of the environmental control device 300 including the air conditioning means so that the difference between the reference value and the latest physiological state value becomes smaller, that is, so that the physiological state value approaches the reference value. In addition, for example, the control content determination unit 125 may determine the control content of the environmental control device 300 including the air conditioning means according to the ratio between the reference value and the latest physiological state value so that the ratio approaches 1. When there are a plurality of people in the target space 1, the control content determination unit 125 may determine the control content of the environmental control device 300 including the air conditioning means using the reference value and the latest physiological state values of the plurality of people in the target space 1.

[0051] The device operation control unit 126 controls the operation of the environmental control device 300 including the air conditioning means according to the control content determined by the control content determination unit 125. In this way, the control unit 120, which is the control means, determines the control content of the air conditioning means using the reference value and the biological information, and controls the air conditioning means.

[0052] When the preset update condition is satisfied, the reference value setting unit 124 updates the reference value. That is, when the update condition is satisfied, the reference value setting unit 124 recalculates the reference value from the most recent biological information acquired by the biological information acquisition means. More specifically, the reference value setting unit 124 recalculates the reference value using the physiological state values within the most recent reference value calculation period. Then, the reference value is updated to the value calculated from the physiological state values within the most recent reference value calculation period in this way. The updated reference value is stored in the storage unit 121, for example.

[0053] According to the air conditioning system configured as described above, in controlling the air conditioner 301 or the like according to the biological information of the person in the target space 1, the value of the biological information serving as a reference when controlling the air conditioner 301 or the like can be updated according to the situation of the target space 1. For this reason, the environmental control device 300 such as the air conditioner 301 can be more appropriately controlled according to the biological information of the person currently in the target space 1. In other words, by updating according to the situation of the target space 1, it is possible to improve the estimation accuracy of whether the comfort of the person in the target space 1 has decreased by comparing the biological information of the person in the target space 1 with the reference value. Therefore, it is possible to improve the comfort, workability, intellectual productivity, etc. of the person. Further, this effect is particularly remarkable when a plurality of people enter and exit the target space 1.

[0054] Next, several examples of the update conditions for the reference value will be described. As a first example, the update condition may include that a preset first time has elapsed since the reference value was last set or updated. In this first example, if the biological information acquisition means acquires the biological information of the person in the target space 1 every time a preset second time elapses, the first time is set to a time longer than the second time. Also, the reference value calculation period is set to, for example, a time equal to or longer than the second time and equal to or shorter than the first time. To give a specific example, the biological information acquisition means acquires biological information every minute. That is, the second time is set to one minute. And the first time is set to 24 hours. That is, the reference value setting unit 124 updates the reference value at a certain fixed time every day. Also, the reference value calculation period is set to 10 minutes. That is, the reference value setting unit 124 calculates a new reference value from the biological information (physiological state value) of the 10 minutes immediately before the above-mentioned fixed time when the reference value is updated.

[0055] Also, the reference value calculation period may be longer than the first time. For example, the first time may be set to one day and the reference value calculation period may be set to one week. By setting the reference value calculation period to a relatively long period of one week, a reference value that excludes the influence of daily fluctuations, fluctuations due to weekdays, etc. can be set. Alternatively, the reference value may be updated multiple times a day. Specifically, for example, the reference value is updated in each of the time zones of morning, afternoon, and night. By doing so, a reference value corresponding to the occupancy status of the target space 1 for each time zone can be set.

[0056] As a second example, the update condition may include a condition related to the environmental information detected by the environmental information sensor 13. For example, using the detection result of the outside air temperature sensor included in the environmental information sensor 13, when the average daytime temperature detected by the outside air temperature sensor becomes equal to or higher than a preset first reference temperature, the reference value may be updated. The first reference temperature is set, for example, according to the average daytime temperature in summer. Also, when the average daytime temperature detected by the outside air temperature sensor becomes equal to or higher than a preset second reference temperature, the reference value may be updated. The second reference temperature is set, for example, according to the average daytime temperature in winter. By doing so, appropriate criteria can be set according to the seasonal variations of the biological information.

[0057] Further, when the state where the temperature during the day detected by the outside air temperature sensor is equal to or higher than a preset reference temperature continues for a preset time or more, the reference value may be updated. Alternatively, when the temperature difference between the morning and afternoon of the day, or the difference between the daily minimum temperature and the daily maximum temperature is equal to or greater than a preset reference difference, the reference value may be updated.

[0058] As a third example, the update condition may include the number of people in the target space 1 or a condition regarding the entry and exit of people to and from the target space 1. As described above, the number of people in the target space 1 and the entry and exit of people to and from the target space 1 can be detected from the detection result of the surface temperature sensor 11. Also, when the biological information sensor 12 is equipped with a camera, the number of people and the entry and exit of people can also be detected from the image captured by the camera. Alternatively, when the target space 1 is a room or the like where entry and exit management is performed for each individual, the number of people in the target space 1 and the entry and exit of people to and from the target space 1 can be detected by using the entry and exit history of each managed individual.

[0059] In this case, for example, when the number of people in the target space 1 becomes equal to or more than a preset reference number of people, the reference value may be updated. As another example, when the number of people entering and exiting the target space 1 becomes equal to or more than a preset reference number of people, the reference value may be updated.

[0060] Furthermore, in this third example, the attribute information of the people in the target space 1 may be included in the update conditions. The attribute information of a person is, for example, the age, gender, physical constitution (heat-intolerant, cold-intolerant), etc. of the person. In this case, for example, the air conditioning system may further include personal identification means for identifying the individuals of the people in the target space 1. The personal identification means is provided, for example, as a personal identification unit in the control unit 120 of the environmental control device 100. As described above, when the target space 1 is a room or the like where entry and exit management is performed for each individual, the individuals of the people in the target space 1 can be identified by using the entry and exit history, etc. of each managed individual. Also, when the target space 1 is an office or the like with free addresses where the seats of each individual are not fixed, the individuals of the people in the target space 1 can be identified by using the check-in (seating and leaving) history, etc. of each seat managed by the seat management system. Furthermore, the individuals can also be identified by using the detection results of the biological information sensor 12. For example, when photographing a person's pupil with a camera or the like, the individual can be identified by using the iris of the pupil. And, for example, by previously storing the attribute information for each individual in the storage unit 121 or the like, the attribute information of the identified individual can be obtained by using the identification result of the individuals of the people in the target space 1.

[0061] Examples of update conditions including the attribute information of the people in the target space 1 are as follows. By setting the update conditions in this way, a reference value corresponding to the attributes of the people in the target space 1 can be set, and the control of the air conditioning means according to the attributes of the people in the target space 1 becomes possible.

[0062] · Set the update conditions using the difference or ratio between the number of men and women in the target space 1. · Set the update conditions using the difference or ratio between the number of heat-intolerant people and cold-intolerant people in the target space 1. · Set the update conditions using the number of elderly people in the target space 1. · Set the update conditions using the number of children in the target space 1.

[0063] As a fourth example, the update condition may include a condition regarding the workability of a person within the target space 1. For example, when the workability of a person within the target space 1 falls below a preset reference workability, the reference value setting unit 124 updates the reference value. When the workability of a person within the target space 1 has decreased to a certain level or below, there is a possibility that the control of the air conditioning means based on the current reference value may not lead to an improvement in workability. Therefore, by updating the reference value when the workability of a person within the target space 1 decreases, there is a possibility that the workability can be improved.

[0064] The work efficiency of an operator varies according to the current physical condition, degree of sleepiness, degree of wakefulness, degree of fatigue, degree of relaxation, degree of stress, etc. of that individual operator. "Workability" corresponds to the ratio of the current efficiency of that individual operator to the maximum efficiency of that individual operator. Workability can also be described as productivity. A high workability of an operator corresponds to the current efficiency of that operator being close to the maximum efficiency of that operator. A low workability of an operator corresponds to the current efficiency of that operator being lower compared to the maximum efficiency of that operator.

[0065] In this case, the air conditioning system further includes workability determination means for determining the workability of a person within the target space 1. The workability determination means is provided, for example, as a workability determination unit in the control unit 120 of the environmental control device 100. For example, first, the workability determination unit estimates the workability of a person (hereinafter also referred to as an operator) within the target space 1 based on the biological information acquired by the aforementioned biological information acquisition means.

[0066] The workability determination unit may calculate a numerical value (hereinafter referred to as the "workability value") that serves as an index of the workability of the operator based on the detection result of the surface temperature sensor 11 and the biological information of the operator obtained using the biological information sensor 12. For example, when the workability value when the workability of an individual operator is at its highest is set to 100, the workability determination unit 41 may calculate a correction coefficient smaller than 1 based on the biological information of the operator obtained using the biological information sensor 12, and calculate the workability value of the operator by multiplying the correction coefficient by 100.

[0067] The workability determination unit may calculate the workability value of the worker based on, for example, the physiological state value of the worker acquired by the physiological state value acquisition unit 122. For example, the workability determination unit may calculate so that the workability value decreases as the drowsiness level increases, or may calculate so that the workability value increases as the arousal level increases. Further, the workability determination unit may calculate so that the workability value increases as the relaxation level increases, or may calculate so that the workability value decreases as the stress level increases.

[0068] The workability determination unit may estimate the workability of the worker based on the operation status of the keyboard of the personal computer operated by the worker. For example, the frequency of input errors may be estimated from the number of keystrokes of the delete keys (backspace key and delete key) of the keyboard per unit time. Also, the workability of the worker may be estimated from the typing speed of the keyboard.

[0069] The update condition does not have to be fixed by one condition, and a plurality of the first to fourth examples listed above may be combined. Also, the update condition may be changed according to the situation. When changing the update condition according to the situation, a model learned using machine learning for the update condition according to the situation may be generated, and the update condition may be inferred using the learned model. Also, even when not changing the update condition according to the situation, the content of the suitable update condition may differ according to the target space 1 in which the air conditioning system is installed. Therefore, even when not changing the update condition according to the situation, the update condition may be inferred using the learned model generated using machine learning.

[0070] In this case, as shown in FIG. 5, the air conditioning system further includes an inference device 500 in addition to the environment control device 100 and the environment control equipment 300. The inference device 500 is the first inference means for inferring the update condition. The inference device 500 includes a data acquisition unit 501, a model update unit 502, and an inference unit 503.

[0071] The learned model storage unit 600 stores a learned model. The learned model stored in the learned model storage unit 600 is for inferring update conditions from input data including at least biological information and environmental information.

[0072] The learned model stored in the learned model storage unit 600 can be generated using, for example, well-known machine learning algorithms. At this time, as the learning algorithm, for example, a known algorithm such as supervised learning using a neural network can be used. That is, learning data consisting of a set of biological information and environmental information and correct answer data of update conditions is prepared, and a learned model can be generated by machine learning using this learning data. Also, as another learning algorithm, for example, deep learning that learns the extraction of features themselves can be used, and machine learning can be executed using other known methods such as genetic programming, functional logic programming, and support vector machines.

[0073] The learned model storage unit 600 is provided, for example, in a server device or the like communicably provided with the inference device 500. Also, the learned model storage unit 600 may be provided in the environment control device 100 or may be provided in the inference device 500.

[0074] The data acquisition unit 501 of the inference device 500 acquires input data to the inference device 500. The input data includes detection data of the sensors 10, that is, detection data of each of the surface temperature sensor 11, the biological information sensor 12, and the environmental information sensor 13.

[0075] The inference unit 503 of the inference device 500 infers an update condition for the reference value setting unit 124 to update the reference value from the input data acquired by the data acquisition unit 501, using the learned model stored in the learned model storage unit 600. The inference unit 503 can output an update condition inferred from the input data by inputting the input data acquired by the data acquisition unit 501 into the learned model. In this way, the inference unit 503 outputs an update condition from the input data acquired by the data acquisition unit 501, using the learned model for inferring the update condition from the input data.

[0076] The update condition output from the inference unit 503 is transmitted to the environment control device 100. When the update condition transmitted from the inference device 500 is satisfied, the reference value setting unit 124 of the environment control device 100 recalculates the reference value from the most recent biological information (physiological state value) and updates the reference value.

[0077] Next, an operation example of the system including the inference device 500 configured as described above will be described with reference to the flowchart of FIG. 6. First, in step S1, the data acquisition unit 501 of the inference device 500 acquires input data. In the subsequent step S2, the inference unit 503 of the inference device 500 inputs the input data acquired in step S1 into the learned model. Further, in the subsequent step S3, the inference unit 503 outputs an update condition, which is an inference result obtained by inputting the input data into the learned model in step S2.

[0078] The data output from the inference unit 503 in step S3 is input to the environment control device 300. After step S3, the environment control device 300 performs the process of step S4. In step S4, the control unit 120 of the environment control device 100 controls the environment control device 300. When the process of step S4 is completed, the series of operations ends.

[0079] In the configuration example shown in FIG. 5, the inference device 500 includes a model update unit 502. The model update unit 502 can update the learned model stored in the learned model storage unit 600. The learned model storage unit 600 stores the learned model updated by the model update unit 502. Then, the inference unit 503 uses the learned model updated by the model update unit 502 to infer the update conditions.

[0080] Based on the result of the operation of the environmental control device 300 based on the reference value updated according to the inferred update conditions, the model update unit 502 updates the learned model according to whether the workability and comfort of the people in the target space 1 have been improved. An example of updating the learned model by the model update unit 502 is that when the workability and comfort of the people in the target space 1 are improved as a result of the operation of the environmental control device 300, and when they are not improved, the model update unit 502 updates the learned model.

[0081] In this example, when the workability and comfort of the people in the target space 1 are improved, the learned model is updated so that the current update conditions are preferentially output, that is, the current output is strengthened. Also, when the workability and comfort of the people in the target space 1 are not improved, the learned model is updated so that something different from the current update conditions is preferentially output.

[0082] As another example of updating the learned model by the model update unit 502, when the workability and comfort of the people in the target space 1 are improved as a result of the operation of the environmental control device 300, the model update unit 502 may update the learned model, and when the workability and comfort of the people in the target space 1 are not improved, the learned model may not be updated.

[0083] Also in this alternative example, when the workability and comfort of the people in the target space 1 are improved, the learned model is updated so that the current update conditions are preferentially output, that is, the current output is strengthened. On the other hand, when the workability and comfort of the people in the target space 1 are not improved, the learned model is not updated.

[0084] Similar to the update condition, the type of biological information used by the reference value setting unit 124 to calculate the reference value may be inferred using machine learning. The type of biological information referred to here also includes the types of physiological state values described above. That is, specifically, for example, the types of biological information may include skin temperature, somatic sensation temperature, warm and cold sensation, heart rate, blood flow rate, sleepiness level, arousal level, relaxation level, stress level, and the like. Further, not only the type of biological information used by the reference value setting unit 124 to calculate the reference value, but also the calculation formula itself of the reference value may be inferred. In this case, for example, a linear combination of various types of physiological state values may be used as the calculation formula of the reference value, and the coefficients applied to various types of physiological state values may be inferred.

[0085] In this case, the air conditioning system further includes second inference means for inferring the type of biological information used by the reference value setting unit 124 to calculate the reference value from input data including at least biological information and environmental information. A specific configuration example of the second inference means is the same as that of the first inference means, that is, the same as the inference device 500 shown in FIG. 4.

[0086] In this case, the learned model stored in the learned model storage unit 600 is for inferring the type of biological information used by the reference value setting unit 124 to calculate the reference value from input data including at least biological information and environmental information.

[0087] Also in this case, the learned model stored in the learned model storage unit 600 can be generated using, for example, well-known machine learning algorithms. At this time, as the learning algorithm, for example, a known algorithm such as supervised learning using a neural network can be used. That is, learning data consisting of a set of biological information and environmental information and correct data of the types of biological information used for calculating the reference value is prepared, and a learned model can be generated by machine learning using this learning data. Further, as another learning algorithm, for example, deep learning that learns the extraction of the feature amount itself can also be used, and machine learning may be executed using other known methods such as genetic programming, functional logic programming, and support vector machines.

[0088] The data acquisition unit 501 of the inference device 500 acquires input data to the inference device 500. The input data includes the detection data of the sensors 10, that is, the detection data of each of the surface temperature sensor 11, the biological information sensor 12, and the environmental information sensor 13.

[0089] The inference unit 503 of the inference device 500 uses the learned model stored in the learned model storage unit 600 to infer the types of biological information used by the reference value setting unit 124 to calculate the reference value from the input data acquired by the data acquisition unit 501. The inference unit 503 can output the types of biological information used by the reference value setting unit 124 to calculate the reference value inferred from the input data by inputting the input data acquired by the data acquisition unit 501 into the learned model. In this way, the inference unit 503 uses the learned model for inferring the types of biological information used by the reference value setting unit 124 to calculate the reference value from the input data acquired by the data acquisition unit 501, and outputs the types of biological information used by the reference value setting unit 124 to calculate the reference value.

[0090] The type of biological information used by the reference value setting unit 124 to calculate the reference value, which is output from the inference unit 503, is transmitted to the environmental control device 100. The reference value setting unit 124 of the environmental control device 100 uses the type of biological information transmitted from the inference device 500 to calculate, for example, the recent average value of the biological information (physiological state value) of the type and calculates the reference value.

[0091] Further, the inference device 500 includes a model update unit 502. The model update unit 502 can update the learned model stored in the learned model storage unit 600. The learned model storage unit 600 stores the learned model updated by the model update unit 502. Then, the inference unit 503 uses the learned model updated by the model update unit 502 to infer the type of biological information used by the reference value setting unit 124 to calculate the reference value.

[0092] Based on the result of the operation of the environmental control device 300 based on the reference value calculated using the inferred type of biological information, the model update unit 502 updates the learned model according to whether the workability and comfort of the person in the target space 1 are improved. The update of this learned model can be performed under the same conditions as the first inference means described above.

[0093] Next, an operation example of the air conditioning system configured as described above will be described with reference to the flowchart of FIG. 7. First, in step S11, the information acquisition unit 110 acquires information related to the detection data of the sensors 10. In the subsequent step S12, the reference value setting unit 124 determines whether the update condition is satisfied. If the update condition is satisfied, the environmental control device 100 performs the process of step S13 next. In step S13, the reference value setting unit 124 updates the reference value using the biological information (physiological state value) within the most recent reference value calculation period. After step S13, the environmental control device 100 performs the process of step S14 next. Also, if the update condition is not satisfied in step S12, the environmental control device 100 skips the process of step S13 and performs the process of step S14.

[0094] In step S14, the control content determination unit 125 acquires the latest biological information (physiological state value). In the subsequent step S15, the control content determination unit 125 compares the latest biological information (physiological state value) with the reference value. Then, in step S16, the control content determination unit 125 determines whether the difference between the latest biological information (physiological state value) and the reference value is within a preset range. If the difference between the latest biological information (physiological state value) and the reference value is not within the range, the environmental control device 100 then performs the process of step S17.

[0095] In step S17, the control content determination unit 125 determines the control content of the environmental control device 100 based on the latest biological information (physiological state value) and the reference value. Then, in the subsequent step S18, the device operation control unit 126 outputs a control signal to the environmental control device 300 including the air conditioner 301 so as to operate with the operation content determined in step S17. The environmental control device 300 including the air conditioner 301 operates according to the control signal from the device operation control unit 126. When the process of step S18 is completed, the series of processes ends.

[0096] On the other hand, when the difference between the latest biological information (physiological state value) and the reference value is within the range in step S16, the environmental control device 100 then performs the process of step S19. In step S19, the control content determination unit 125 determines to continue the current control content. Then, the device operation control unit 126 continues the current control for the environmental control device 300 including the air conditioner 301. When the process of step S19 is completed, the series of processes ends.

[0097] FIG. 8 is a diagram showing an example of a configuration for realizing each function of the environmental control device 100 and the inference device 500 in this embodiment. Each function of the environmental control device 100 and the inference device 500 is realized by, for example, a processing circuit. The processing circuit may include a processor 701 and a memory 702. The processing circuit may be dedicated hardware 703. A part of the processing circuit may be formed as dedicated hardware 703, and the processing circuit may further include a processor 701 and a memory 702. In the example shown in the figure, a part of the processing circuit is formed as dedicated hardware 703. Also, in the example shown in the figure, the processing circuit further includes a processor 701 and a memory 702.

[0098] Examples of the processing circuit in which a part is at least one piece of dedicated hardware 703 include a single circuit, a composite circuit, a programmed processor, a parallel-programmed processor, an ASIC, an FPGA, or a combination thereof. When the processing circuit includes at least one processor 701 and at least one memory 702, the functions of the control device 30 are realized by software, firmware, or a combination of software and firmware.

[0099] Software and firmware are described as programs and stored in the memory 702. The processor 701 realizes the functions of each part by reading and executing the programs stored in the memory 702. The processor 701 is also referred to as a CPU (Central Processing Unit), a central processing unit, a processing unit, an arithmetic unit, a microprocessor, a microcomputer, or a DSP. Examples of the memory 702 include non-volatile or volatile semiconductor memories such as RAM, ROM, flash memory, EPROM, and EEPROM, or magnetic disks, flexible disks, optical disks, compact disks, mini-disks, and DVDs.

[0100] In this way, each processing circuit of the environmental control device 100 and the inference device 500 can implement each function of the control device 30 by hardware, software, firmware, or a combination thereof. When the processing circuit of the control device 30 includes at least a processor 701 and a memory 702, the processor 701 executes a program stored in the memory 702 in the control device 30, and the hardware and software of the control device 30 cooperate with each other, whereby the functions of each part included in each of the environmental control device 100 and the inference device 500 are realized. Note that the environmental control equipment 300 included in the air conditioning system is not limited to a configuration in which the operation is controlled by a single environmental control device 100. The environmental control equipment 300 included in the air conditioning system may be controlled to operate by the cooperation of a plurality of devices.

Explanation of Signs

[0101] 1 Target space 10 Sensors 11 Surface temperature sensor 12 Biometric information sensor 13 Environmental information sensor 20 Housing 21 Bottom panel 22 Suction port 23 Air outlet 24 Up and down louvers 25 Left and right louvers 100 Environmental control device 110 Information acquisition unit 120 Control unit 121 Storage unit 122 Physiological state value acquisition unit 123 Person position detection unit 124 Reference value setting unit 125 Control content determination unit 126 Equipment operation control unit 300 Environmental control equipment 301 Air conditioner 302 Blower 303 Ventilation equipment 304 Humidifying and dehumidifying equipment 305 Lighting equipment 500 Inference device 501 Data Acquisition Unit 502 Model Update Unit 503 Inference Unit 600 Trained Model Memory Unit 701 Processor 702 Memory 703 Dedicated Hardware

Claims

1. Air conditioning means for conditioning the air in the target space, Biometric information acquisition means for acquiring biometric information of a person in the target space, Setting means for calculating and setting a reference value from the biometric information, Control means for controlling the air conditioning means, comprising: The control means determines the control content of the air conditioning means using the reference value and the biometric information, The setting means recalculates the reference value from the biometric information and updates the reference value when a preset update condition is satisfied, an air conditioning system.

2. The update condition is that a preset first time has elapsed since the reference value was last set or updated, The biometric information acquisition means acquires the biometric information of a person in the target space every time a preset second time elapses, The air conditioning system according to claim 1, wherein the first time is longer than the second time.

3. Environment information acquisition means for acquiring environment information of one or both of the inside and outside of the target space, Further comprising first inference means for inferring the update condition from input data including at least the biometric information and the environment information, The air conditioning system according to claim 1 or claim 2, wherein the setting means recalculates the reference value from the biometric information and updates the reference value when the update condition inferred by the first inference means is satisfied.

4. Further comprising second inference means for inferring the type of biometric information used by the setting means to calculate the reference value from input data including at least the biometric information and the environment information, The air conditioning system according to claim 3, wherein the setting means calculates the reference value from the biometric information of the type inferred by the second inference means.

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