Indoor environment control system, indoor environment control method, and program

Abstract

An indoor environment control system (1) according to the present disclosure is provided with: an air-cleaning device (20) for cleaning air inside a building; a radio wave sensor (30) for detecting the gait of a user located in the building; and a control device (10) for estimating the amount of air-quality contaminants in the building from the gait of the user as determined on the basis of the detection result from the radio wave sensor (30), and controlling the air-cleaning device (20) on the basis of the estimated amount of air-quality contaminants generated.

Description

[Technical field]

[0001] The present disclosure relates to an indoor environment control system, an indoor environment control method, and a program. [Background technology]

[0002] Conventionally, there is a technology for detecting a person's gait using a pressure sensor, etc. Patent Document 1 discloses a gait data management system that detects a user's walking state and gait based on the measurement value of a pressure sensor attached to the user's foot, and manages gait data for walking support. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2016 / 038824 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the above-mentioned conventional technology cannot detect the gait of a person who is not wearing a pressure sensor, making it difficult to detect the gait of a user who is not wearing a sensor during their daily activities and reflect this in indoor environmental control.

[0005] Therefore, the present disclosure provides an indoor environment control system etc. that can detect the gait of a user during daily movements of the user who is not wearing a sensor and reflect the detected gait in indoor environmental control. [Means for solving the problem]

[0006] An indoor environment control system according to one embodiment of the present disclosure includes an air purifying device that purifies the air within a building, a radio wave sensor that detects the gait of a user located within the building, and a control device that estimates an amount of air pollutants generated within the building from the gait of the user determined based on the detection results of the radio wave sensor, and controls the air purifying device based on the estimated amount of air pollutants generated.

[0007] In addition, an indoor environment control method according to one aspect of the present disclosure includes a detection step of detecting the gait of a user located within a building using a radio wave sensor, an estimation step of estimating an amount of air pollutants generated within the building from the gait of the user determined based on the detection result of the radio wave sensor, and a control step of controlling an air purifier that purifies the air within the building based on the estimated amount of air pollutants generated.

[0008] Moreover, an indoor environment control system according to one embodiment of the present disclosure includes an air purifier that purifies the air in a building, a radio wave sensor for detecting the gait of a user located in the building, and a control device that controls the air purifier, the control device having one or more processors, the one or more processors inputting gait detection data representing the gait of the user detected by the radio wave sensor into a model generated using gait data representing the gaits of a number of users and dust amount data, estimating the amount of air pollutants generated in the building, and controlling the air purifier based on the estimated amount of air pollutants generated.

[0009] Moreover, an indoor environment control method according to one aspect of the present disclosure includes a detection step of detecting the gait of a user located within a building by a radio wave sensor, an estimation step of inputting the user's gait detection data detected by the radio wave sensor into a model generated using gait data representing the gaits of a large number of users and dust amount data to estimate an amount of air pollutants generated within the building, and a control step of controlling an air purifier that purifies the air within the building based on the amount of air pollutants generated estimated in the estimation step, and the estimation step and the control step are executed by one or more processors.

[0010] In addition, these comprehensive or specific aspects may be realized by an apparatus, a method, an integrated circuit, a computer program, or a recording medium such as a computer-readable CD-ROM, or may be realized by any combination of an apparatus, a method, an integrated circuit, a computer program, and a recording medium. Effect of the Invention

[0011] An indoor environment control system according to one embodiment of the present disclosure can detect the gait of a user during the user's daily movements without wearing a sensor, and reflect this in indoor environmental control. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a block diagram of an indoor environment control system according to an embodiment. [Diagram 2] FIG. 2 is a schematic diagram of an indoor environment control system according to an embodiment. [Diagram 3] FIG. 3 is a diagram showing a radio wave sensor included in the indoor environment control system according to the embodiment. [Figure 4] FIG. 4 is a diagram showing the difference in effect between a conventional indoor environment control system and the indoor environment control system according to the embodiment. [Figure 5A] FIG. 5A is a diagram showing gait parameters. [Figure 5B]FIG. 5B is a diagram showing the relationship between dust generation from the floor and walking. [Figure 5C] FIG. 5C is a diagram showing the relationship between gait parameters and the amount of dust generated. [Figure 5D] FIG. 5D is a diagram showing a method for estimating the amount of dust generated. [Figure 6] FIG. 6 is a diagram showing an example of detection of walking movements by comparing detection data of a radio wave sensor with image dynamics analysis. [Figure 7] FIG. 7 is a flowchart showing the operation of the indoor environment control system in the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Hereinafter, the embodiment will be specifically described with reference to the drawings.

[0014] The embodiments described below are all comprehensive or specific examples. The numerical values, shapes, materials, components, the arrangement and connection of the components, steps, and the order of steps shown in the following embodiments are merely examples and are not intended to limit the scope of the claims. Furthermore, among the components in the following embodiments, components that are not described in the independent claims showing the highest concept are described as optional components. Furthermore, each figure is not necessarily a strict illustration. In each figure, substantially the same configuration is given the same reference numeral, and duplicated explanations are omitted or simplified.

[0015] (Embodiment) [Outline of indoor environmental control system] First, an overview of the indoor environment control system in the embodiment will be described. Fig. 1 is a block diagram of an indoor environment control system 1 in the embodiment.

[0016] The indoor environment control system 1 includes a control device 10, an air purifying device 20, a radio wave sensor 30, an air supply device 40, an exhaust device 50, an air conditioning device 60, a humidity sensor 70, a temperature sensor 80, a server 90, and an alarm device 100. The control device 10 also includes a control unit 11, a communication unit 12, a storage unit 13, and an acquisition unit 14.

[0017] It is noted that the indoor environment control system 1 does not necessarily have to include the air supply device 40, the exhaust device 50, the air conditioner 60, the humidity sensor 70, the temperature sensor 80, the server 90, and the notification device 100.

[0018] The control device 10 is realized by one or more processors and one or more memories. The control unit 11 of the control device 10 estimates the amount of air pollutants generated in the building from the gait of the user determined based on the detection result of the radio wave sensor 30, and controls the air purifying device 20 based on the estimated amount of air pollutants generated. The air pollutants are, for example, pollen or PM (Particulate Matter) 10, and may be referred to as dust in this specification.

[0019] Furthermore, the control unit 11 of the control device 10 controls the air purifying device 20 so that the amount of air pollutants generated in the building becomes a predetermined amount. The control unit 11 of the control device 10 estimates the amount of air pollutants generated in the building based on the user's gait determined based on the detection result of the radio wave sensor and the humidity in the building detected by the humidity sensor 70.

[0020] In addition, the communication unit 12 of the control device 10 transmits the estimated amount of air pollutants generated and environmental information within the building detected by an environmental sensor (e.g., a humidity sensor 70 or a temperature sensor 80) to an external server (server 90).

[0021] The memory unit 13 of the control device 10 stores programs executed by the control unit 11, data detected by the radio wave sensor 30, etc. The memory unit 13 may store programs for control of the air purifying device 20, the air supply device 40, or the exhaust device 50, or data related to the air purifying device 20, the air supply device 40, and the exhaust device 50, etc. The memory unit 13 may also store data detected by an environmental sensor (for example, the humidity sensor 70 or the temperature sensor 80).

[0022] The acquisition unit 14 of the control device 10 acquires environmental information from an environmental sensor (for example, a humidity sensor 70 or a temperature sensor 80). The environmental information is specifically the humidity or temperature inside a building.

[0023] The air purifying device 20 removes air quality pollutants from the air inside a building and purifies the air. The air purifying device 20 includes a filter and collects dust particles and the like in the air. The air purifying device 20 may be of a fan type or an electric dust collecting type.

[0024] The radio wave sensor 30 uses radio waves to measure the distance to a target object. The radio wave sensor 30 transmits pulsed radio waves from a transmitting antenna, and measures the time it takes for the reflected wave to hit the target object and return to the receiving antenna. By providing multiple transmitting antennas and multiple receiving antennas, it is possible to measure the distance to an object in three dimensions. The radio wave sensor 30 can also detect the direction of movement of the target object.

[0025] The air intake device 40 supplies air from outside the building to the inside of the building. The air intake device 40 includes a fan and blows air from outside the building into the inside of the building. The air intake device 40 may further include a filter, etc. The air intake device 40 may be integrated with an exhaust device 50, which will be described later.

[0026] The exhaust device 50 exhausts air from inside the building to the outside of the building. The exhaust device 50 includes a fan and blows the air inside the building toward the outside of the building. The exhaust device 50 may further include a filter or the like. As described above, the exhaust device 50 may be integrated with the air supply device 40.

[0027] The air conditioner 60 includes an air filter, a humidifier, a cooling coil, a heating coil, and a blower. The air conditioner 60 is a device that adjusts the temperature or humidity of the air in the room by transporting heated air, cooled air, humidified air, or dehumidified air using a heat pump or the like.

[0028] The humidity sensor 70 detects the humidity in the room in which the indoor environment control system 1 is installed. The humidity sensor 70 may be a bimetal hygrometer, a psychrometric meter, an electric hygrometer, a dew point meter, or a telescopic hygrometer. The electric hygrometer may be a resistive type or a capacitive type. The electric hygrometer detects humidity by detecting a change in the resistance value of a moisture-sensitive material with an electrode.

[0029] The temperature sensor 80 measures the temperature of an object, converts the temperature into a physical quantity such as a voltage or a resistance value, and outputs the measured temperature. The temperature sensor 80 may be a contact-type temperature sensor using a thermocouple or the like, or a non-contact-type temperature sensor using a radiation thermometer. The temperature sensor 80 may also be a thermal imaging camera that measures the temperature difference by sensing the strength of far-infrared rays.

[0030] Specifically, the temperature sensor 80 detects the temperature in the room in which the indoor environment control system 1 is installed. The temperature sensor 80 is, for example, a thermistor thermometer or an infrared radiation thermometer. A thermistor thermometer measures the resistance by passing a small amount of current through a sensor made of two types of metal with different thermoelectric powers welded together, and converts it into a temperature value. An infrared radiation thermometer detects infrared rays emitted from an object to detect temperature. The temperature sensor 80 may also be a mercury thermometer or a bimetal thermometer.

[0031] The server 90 is realized by a processor and a memory. The server 90 may be a database server or a file server. The server 90 stores the estimated amount of generated air quality pollutants and environmental information in the building detected by an environmental sensor (e.g., the humidity sensor 70 or the temperature sensor 80). The server 90 may also communicate with the control device 10 and transmit the stored data to the control device 10.

[0032] The notification device 100 notifies the health risk information determined based on the amount of air pollutants generated estimated by the control unit 11 and the user's stay time in the building. The user's stay time in the building may be estimated from a typical schedule of the user registered in advance, or may be estimated by detecting the user's location information. The notification device 100 may be a mobile terminal such as a smartphone or tablet terminal, or a display of a PC or the like. The mobile terminal such as a smartphone or tablet terminal, and the display of a PC or the like may notify the health risk information by image or sound under the control of the control unit 11. Alternatively, the notification device 100 may be a speaker or the like that notifies the health risk information by sound under the control of the control unit 11. The notification device 100 may also be a dedicated terminal equipped with a display, speaker, or the like.

[0033] The components of the indoor environment control system 1 are installed in a room of a building. Figure 2 is a schematic diagram of the indoor environment control system according to the embodiment.

[0034] A radio wave sensor 30 installed on a wall surface inside a building detects the gait of a user walking inside the building. The data detected by the radio wave sensor 30 is acquired by the control device 10 through wired or wireless communication. Based on the acquired data detected by the radio wave sensor, the control device 10 controls the air purifying device 20 through wired or wireless communication to purify the air inside the building.

[0035] The control device 10 may also transmit data detected by the radio wave sensor 30 or results calculated by the control device 10 via wired or wireless communication to the notification device 100 installed on a wall inside a building, and notify the user of health risk information. The control device 10 may generate the health risk information, or the notification device 100 may generate the health risk information by a circuit and memory provided in the notification device 100 after acquiring various data.

[0036] Furthermore, the indoor environment control system 1 may include a humidity sensor 70 or a temperature sensor 80 on a wall surface inside the building, and transmit detected data to the control device 10 via wired or wireless communication. The control device 10 may also control the air supply device 40 and the exhaust device 50 to circulate the air inside the building with the air outside the building. The control device 10 may also control an air conditioner 60 installed on a wall surface inside the building to adjust the temperature and humidity inside the building.

[0037] [Radio wave sensor] Next, a description will be given of the radio wave sensor 30. Fig. 3 is a diagram showing the radio wave sensor 30 provided in the indoor environment control system 1 in the embodiment.

[0038] The radio wave sensor 30 includes a frequency analysis unit, an RF IC, an input (RX), and an output (TX). The output (TX) transmits radio waves, and the input (RX) acquires the radio waves reflected from a user or the like. The RF IC is a radio frequency integrated circuit, and receives the radio waves acquired by the input (RX). The frequency analysis unit performs frequency analysis on the radio waves received by the RF IC, and outputs data resulting from the frequency analysis.

[0039] The radio wave sensor 30 detects the user's movements by directing radio waves at the feet of the user, receiving the reflected radio waves, and performing frequency analysis on the received signals.

[0040] [Differences from conventional examples] Next, the difference between the indoor environment control system 1 and the conventional example will be described. Fig. 4 is a diagram showing the difference in effect between the conventional indoor environment control system and the indoor environment control system of the embodiment.

[0041] An example of a conventional indoor environment control system is shown in (a) of Fig. 4. Conventionally, dust sensors are provided on the ceiling and the air purifying device 20, and the dust sensors detect dust after dust such as PM10 fills the room. Therefore, in the conventional indoor environment control system, the air is purified by the air purifying device 20 after the user has already been exposed to dust such as PM10 that has filled the room.

[0042] In contrast, in the indoor environment control system 1 according to the embodiment of the present disclosure shown in Fig. 4(b), a radio wave sensor 30 installed on the ceiling detects the gait of a user, and predicts the amount of dust generation based on the detected gait data. Then, the air purifying device 20 is operated based on the predicted amount of dust generation, so that dust such as PM10 can be removed by the air purifying device 20 before the dust such as PM10 fills the room. Therefore, the indoor environment control system 1 can suppress the user's exposure to PM10.

[0043] [Gait detection and estimation of dust generation volume] Next, a description will be given of gait detection and dust generation amount estimation by the indoor environment control system 1. Fig. 5A is a diagram showing gait parameters. As shown in Fig. 5A, parameters such as the number of steps W1, stride length W2, walking speed W3, and step width W4 are used as gait parameters for gait detection.

[0044] The number of steps W1 is measured by counting the number of steps within a predetermined period of time. The number of steps W1 may be an average value or a median value of the number of steps measured multiple times over a predetermined period of time.

[0045] The stride length W2 is measured as a value obtained by dividing the walking distance by the number of steps or a value estimated from the amount of displacement of each part of the body during walking. This may be the average or median value of multiple measurements of the stride length over a given period of time.

[0046] The walking speed W3 may be a value obtained by dividing a walking distance in a predetermined time by the predetermined time, or may be an average or median of walking speeds measured multiple times.

[0047] The step width W4 may be an average value or a median value of the step widths measured multiple times within a predetermined time period. The step width W4 may also be expressed by the acceleration of the user's stepping motion. Specifically, the step width W4 may be expressed by the acceleration of the user's knee movement. For example, the step width may be the vertical distance from the point where the user raises his / her foot the highest to the ground.

[0048] FIG. 5B is a diagram showing the relationship between dust generation from the floor and walking. As shown in FIG. 5B, the kicking up of dust is determined, for example, in relation to the height of the user's foot step, as with other gait parameters. Among the parameters shown in FIG. 5A, step width W4 is related to the foot step. FIG. 5B shows how step width W4 is related to dust generation. Other gait parameters are also related to dust generation, as is step width W4.

[0049] 5C is a diagram showing the relationship between gait parameters and the amount of dust generated. As shown in FIG 5C, as the value of each gait parameter increases, the amount of dust generated also increases monotonically.

[0050] Next, the relationship between gait detection and estimation of the amount of dust generated will be described in detail below. Fig. 5D is a diagram showing a method of estimating the amount of dust generated.

[0051] First, the radio wave sensor 30 detects gait parameters (S1). The radio wave sensor 30 receives radio waves that are transmitted by the radio wave sensor 30 and reflected by the user. Then, the radio wave sensor 30 performs frequency analysis on the received radio waves to detect the displacement of each part of the user, or the distance and the direction of the user's movement. The radio wave sensor 30 may be of a Doppler type or an FMCW type, and is not limited to any of the above. For example, it is preferable to use a Doppler type for detecting the displacement of each part of the user. The radio wave sensor 30 may include a plurality of receiving antennas, etc., and may grasp the user's movement in a three-dimensional manner. Here, the detected gait parameters are, for example, the number of steps W1, the stride length W2, the walking speed W3, and the step width W4 shown in FIG. 5A.

[0052] Next, the control unit 11 converts the gait parameters (step S2). The control unit 11 converts the detection data detected by the radio wave sensor 30 into values ​​that can be used in a calculation formula for estimating the amount of dust generated. For example, the control unit 11 may normalize the data indicating each gait parameter detected by the radio wave sensor 30. Alternatively, the control unit 11 may weight each gait parameter.

[0053] Next, the control unit 11 multiplies the converted gait parameters W1 to W4 (step S3). Specifically, the control unit 11 calculates a numerical value for determining a gait rank by multiplying the weighted gait parameters W1 to W4. Note that step S3 may be an addition instead of a multiplication.

[0054] Next, the control unit 11 determines a gait rank (step S4). The control unit 11 determines a gait rank that indicates the intensity of a gait based on the calculated numerical value for determining the gait rank. The control unit 11 may determine an absolute value of a numerical value that indicates the intensity of a gait, or may determine a rank that indicates the intensity of a gait divided into a plurality of stages.

[0055] The control unit 11 determines the amount of dust generation taking into account the humidity data and temperature data (step S5). The control unit 11 takes into account the humidity data detected by the humidity sensor 70 or the temperature data detected by the temperature sensor 80.

[0056] The control unit 11 may determine the amount of dust generation using an absolute value of the amount of dust generation determined from the gait / amount generation comparison table, or a value obtained by correcting a rank based on the amount of dust generation divided into multiple stages with humidity data or temperature data. For example, the control unit 11 may perform a correction such that when the humidity is lower than a predetermined humidity, the residence time after dust generation is longer, and therefore the amount of dust generation is greater than when the humidity is higher than the predetermined humidity. Alternatively, the control unit 11 may determine the amount of dust generation based on a data table created based on humidity data or temperature data.

[0057] Then, the control unit 11 determines the amount of dust generation from the gait / generation amount comparison table based on the gait rank (step S6). The control unit 11 may determine the absolute value of the amount of dust generation from the gait / generation amount comparison table, or may determine a rank based on the amount of dust generation divided into multiple stages. The control unit 11 may also hold a relational expression for calculating the amount of dust generation from the gait rank (a numerical value indicating the intensity of the gait) instead of the gait / generation amount comparison table, and may calculate the amount of dust generation from the gait rank (a numerical value indicating the intensity of the gait) using the relational expression.

[0058] The control unit 11 judges the occurrence of pollution based on the amount of dust generated derived from the gait / generation amount comparison table etc. The judgment of the occurrence of pollution may be made based on the absolute value of the amount of dust generated, or may judge the rank of pollution in which the amount of dust generated is divided into multiple stages.

[0059] The control unit 11 controls the air intake device 40, the exhaust device 50, or the air purifying device 20 based on the result of the pollution occurrence determination. For example, if the pollution rank is determined to be equal to or higher than a predetermined value, the control unit 11 may operate the air intake device 40 and the exhaust device 50 more powerfully. Also, if the pollution rank is determined to be equal to or higher than a predetermined value, the control unit 11 may operate the air purifying device 20 more powerfully.

[0060] [Analysis by frequency analysis] 6 is a diagram showing an example of detection of walking motion by comparing detection data of the radio wave sensor 30 with image dynamic analysis. Similarity was observed between the detected foot motion of the user by image dynamic analysis and the detection data of the radio wave sensor 30 in the 40 Hz and 20 Hz data obtained by frequency analysis of the detection data of the radio wave sensor 30. Specifically, between the detected motion by image dynamic analysis and the detection data of the radio wave sensor 30, the 40 Hz frequency data of the user's knee motion and the 20 Hz frequency data of the ankle motion were similar to the results of the image dynamic analysis.

[0061] Therefore, the movement of the user's feet can be detected from the detection data of the radio wave sensor 30 that has been subjected to frequency analysis.

[0062] [Operation] FIG. 7 is a flowchart showing the operation of the indoor environment control system 1 in the embodiment.

[0063] First, the radio wave sensor 30 detects the user's gait (step S10). The radio wave sensor 30 detects the user's foot movement by performing frequency analysis on the received radio waves. In order to detect the user's gait, the radio wave sensor 30 detects the number of steps of the user, the user's stride length, the user's walking speed, the user's step width, etc.

[0064] Next, the control unit 11 estimates the amount of air pollutants generated (step S11). The control unit 11 calculates the intensity of the user's gait based on data (gait detection data) representing the user's gait detected by the radio wave sensor, and estimates the amount of dust generated from the intensity of the user's gait. The control unit 11 may determine a rank of the amount of air pollutants generated, dividing the amount of air pollutants generated into a plurality of stages. Here, the air pollutants are, for example, PM10 or dust.

[0065] Next, the control unit 11 controls the air purifier based on the amount of generated air pollutants (step S12). For example, when it is determined that the amount of generated air pollutants is equal to or greater than a predetermined value, the control unit 11 may operate the air purifier 20 more powerfully. At this time, the control unit 11 may control the air intake device 40, the exhaust device 50, and the air conditioner 60 instead of or together with the air purifier.

[0066] Furthermore, the control unit 11 may use the notification device 100 to notify the user of the amount of generated air pollutants estimated by the control unit 11, or health risk information of the user based on the amount of generated air pollutants estimated by the control unit 11. For example, as the health risk information, the control unit 11 may calculate a spatial pollution index based on the estimated amount of generated air pollutants, generate spatial location information of the user from temporal position information of the user, and calculate an exposure index from the spatial pollution index and the spatial location information.

[0067] The control unit 11 may estimate the air quality and the user's actions that affect the air quality on a communication terminal in the room from signals from a plurality of sensors installed in the room, and calculate a spatial pollution index from the estimated air quality and the user's actions that affect the air quality. The control unit 11 may cause the notification device 100 to notify the user of the exposure index as a health impact degree. The health impact degree may be, for example, the sum of a value obtained by multiplying the exposure index by the user's stay time in the target space.

[0068] The spatial location information may be generated by, for example, estimating the location where the user was based on the user's typical schedule, or by detecting the user with a sensor installed in the room and estimating the location where the user was. The control unit 11 may also calculate the past history and cumulative value, or the average value for one year, of the numerical value estimated in this way, and notify the user of the calculated numerical value, so that the user can recognize the impact of the living environment on his / her health.

[0069] [Models, etc.] Here, a method for estimating the amount of generated air pollutants by the control unit 11 will be described in detail. The control unit 11 may estimate the amount of generated indoor pollutants by a model generated from gait data representing the gaits of many users, temperature and humidity data, and dust amount data, which have been learned in advance. Here, the gait data refers to data representing the gaits of many users used for learning the model. The above model is a model generated by machine learning using teacher data so as to be able to determine whether or not the amount of generated indoor pollutants is relatively high.

[0070] The teacher data may include a time-series data set consisting of gait data including a parameter indicating the intensity of gait acquired by a radio wave sensor, indoor humidity data at that time, and data output from a dust meter or the like that measures the amount of dust generated as an indoor pollutant under that situation. Alternatively, the teacher data may be a combination consisting of average values, representative values, or integrated values ​​of the above data under predetermined conditions.

[0071] In the model, parameters indicating the intensity of gait and temperature and humidity parameters are used as training data because they relate to the amount of dust generated. Here, the parameters indicating the intensity of gait refer to parameters indicating the number of steps of the user, the stride length of the user, the walking speed of the user, the step width of the user, etc. Furthermore, the temperature and humidity parameters may be any of humidity data, temperature data, and both temperature and humidity data.

[0072] The amount of dust generated can be expressed using several parameters that represent the amount of dust generated, such as the change in dust concentration in the room, the rate at which the dust concentration increases, the extent to which the dust has spread into the room, or the degree to which the dust is stirred up in the height direction. Alternatively, the rate at which the dust concentration decays from a dust-generated state can also be used as a parameter that represents the amount of dust generated. Each of the above dust-related data can be obtained from data obtained by a dust meter that measures the amount of dust such as PM10 generated indoors, or a particle counter.

[0073] The measurement position when measuring each of the above dust-related data may be the center point of the room to be measured, or data from a representative point such as a position corresponding to face height, multi-point measurement data obtained by measuring at multiple measurement points in the horizontal or vertical direction, or analytical data indicating the amount of dust generated obtained by further analyzing the same.

[0074] Then, a model is generated by machine learning using multiple instances of training data including the dust-related data obtained by the method described above.

[0075] Furthermore, by inputting gait detection data representing the gait of a user acquired by the radio wave sensor and humidity data acquired by the humidity sensor to this model, the model can estimate the amount of dust generated, which is an indoor pollutant. The gait detection data is an input value for obtaining an output value from the model, and is data representing the gait of one or more users detected indoors when estimating the amount of dust generated.

[0076] In addition, the above model may be a model generated based on a trained model using a generally known neural network for processing multiple time-series signals consisting of images, audio, etc.

[0077] (Effects, etc.) The indoor environment control system 1 of the present disclosure comprises an air purifying device 20 that purifies the air in a building, a radio wave sensor 30 for detecting the gait of a user located in the building, and a control device 10 that estimates the amount of air pollutants generated in the building based on the user's gait determined based on the detection results of the radio wave sensor 30, and controls the air purifying device 20 based on the estimated amount of air pollutants generated.

[0078] This allows the indoor environment control system 1 of the present disclosure to estimate the amount of dust generated by the user's walking at any time without contacting the user, and therefore the indoor environment control system 1 of the present disclosure can control the indoor environment to quickly remove dust.

[0079] Also, for example, in the indoor environment control system 1 of the present disclosure, the control device 10 controls the air purifying device 20 so that the amount of air pollutants generated in the building is a predetermined amount.

[0080] As a result, the indoor environment control system 1 of the present disclosure can suppress the amount of air pollutants generated in the building, and therefore the indoor environment control system 1 of the present disclosure can keep the indoor environment clean.

[0081] For example, the indoor environment control system 1 of the present disclosure further includes an air conditioner 60 that adjusts the temperature and humidity inside the building.

[0082] As a result, the indoor environment control system 1 of the present disclosure can adjust the amount of dust generated by adjusting the temperature and humidity inside the building. Therefore, the indoor environment control system 1 of the present disclosure can control the indoor environment so as to remove dust.

[0083] For example, the indoor environment control system 1 of the present disclosure further includes an exhaust device 50 that exhausts air inside the building outside the building, and an air supply device 40 that supplies air outside the building into the building, and the control device 10 controls the exhaust device 50 or the air supply device 40 so that the amount of air quality pollutants generated inside the building is a predetermined amount.

[0084] In this way, the indoor environment control system 1 of the present disclosure can adjust the amount of dust generated by circulating the air inside the building with the air outside the building. Therefore, the indoor environment control system 1 of the present disclosure can control the indoor environment so as to remove dust.

[0085] Furthermore, for example, the indoor environment control system 1 of the present disclosure further includes a humidity sensor 70 that detects the humidity inside the building, and the control device 10 estimates the amount of air pollutants generated inside the building based on the user's gait determined based on the detection results of the radio wave sensor 30 and the humidity inside the building detected by the humidity sensor 70.

[0086] This allows the indoor environment control system 1 of the present disclosure to appropriately estimate the amount of dust generated by the user's walking according to the indoor environment. Therefore, the indoor environment control system 1 of the present disclosure can control the indoor environment so as to more appropriately remove dust.

[0087] Furthermore, for example, the indoor environment control system 1 of the present disclosure further includes an environmental sensor that detects environmental information within the building, and the control device 10 further transmits the estimated amount of air quality pollutants generated and the environmental information within the building detected by the environmental sensor to an external server.

[0088] As a result, the indoor environment control system 1 of the present disclosure can detect the environment within a building, reflect the detected environment within the building in estimates of the amount of air pollutants generated, and store data regarding the detected environment within the building and the amount of air pollutants generated.

[0089] Moreover, for example, the indoor environment control system 1 of the present disclosure further includes a notification device 100 that notifies the estimated amount of generated air pollutants.

[0090] This allows the indoor environment control system 1 of the present disclosure to notify the user of the estimated amount of generated air pollutants.

[0091] Moreover, for example, the indoor environment control system 1 of the present disclosure further includes a notification device that notifies health risk information determined based on the estimated amount of air pollutants generated and the time the user has stayed in the building.

[0092] This allows the indoor environment control system 1 of the present disclosure to notify the user of the estimated amount of generated air pollutants and health risk information.

[0093] In addition, the indoor environment control method disclosed herein includes a detection step of detecting the gait of a user located within a building by a radio wave sensor 30, an estimation step of estimating the amount of air pollutants generated within the building from the user's gait determined based on the detection results of the radio wave sensor 30, and a control step of controlling an air purifying device 20 that purifies the air within the building based on the estimated amount of air pollutants generated.

[0094] As a result, the indoor environment control method of the present disclosure can achieve the same effects as the indoor environment control system 1 described above.

[0095] Further, a program of the present disclosure is a program for causing a computer to execute the indoor environment control method.

[0096] As a result, the program of the present disclosure can achieve the same effects as the above-mentioned indoor environment control method.

[0097] Moreover, the indoor environment control system 1 of the present disclosure includes an air purifying device 20 that purifies the air in a building, a radio wave sensor 30 for detecting the gait of a user located in the building, and a control device 10 that controls the air purifying device 20, and the control device 10 has one or more processors, which input gait detection data representing the user's gait detected by the radio wave sensor 30 into a model generated using gait data representing the gaits of multiple users and dust amount data, estimate the amount of air pollutants generated in the building, and control the air purifying device 20 based on the estimated amount of air pollutants generated.

[0098] As a result, the indoor environment control system 1 of the present disclosure can estimate the amount of dust generated by the user's walking from the gait detection data using a model based on the gait data and the dust amount data, etc. Therefore, the indoor environment control system 1 of the present disclosure can control the indoor environment so as to quickly remove dust.

[0099] In the indoor environment control system 1 of the present disclosure, a model is generated using gait data, temperature and humidity data, and dust amount data, and one or more processors input the user's gait detection data detected by the radio wave sensor 30 and the temperature and humidity data inside the building to the model.

[0100] This allows the indoor environment control system 1 of the present disclosure to take into account the temperature and humidity inside the building when estimating the amount of dust generation from gait detection data, and therefore the indoor environment control system 1 of the present disclosure can estimate the amount of dust generation more accurately.

[0101] In the indoor environment control system 1 of the present disclosure, the model is a neural network model.

[0102] As a result, the indoor environment control system 1 of the present disclosure can estimate the amount of dust generation from the gait detection data not only by supervised learning but also by unsupervised learning.

[0103] In addition, the indoor environment control method disclosed herein includes a detection step of detecting the gait of a user located within a building by a radio wave sensor 30, an estimation step of inputting the user's gait detection data detected by the radio wave sensor 30 into a model generated using the gait data and the dust amount data to estimate the amount of air pollutants generated within the building, and a control step of controlling the air purifying device 20 that purifies the air within the building based on the amount of air pollutants generated estimated in the estimation step, and the estimation step and control step are executed by one or more processors.

[0104] As a result, the indoor environment control method of the present disclosure can estimate the amount of dust generated by the user's walking from the gait detection data using a model based on the gait data and the dust amount data, and therefore can control the indoor environment to quickly remove dust.

[0105] Further, a program of the present disclosure is a program for causing a computer to execute the indoor environment control method.

[0106] As a result, the program of the present disclosure can achieve the same effects as the above-mentioned indoor environment control method.

[0107] (others) Although the embodiments have been described above, the present disclosure is not limited to the above-described embodiments.

[0108] For example, in the above embodiment, the process executed by a specific processing unit may be executed by another processing unit. Also, the order of multiple processes may be changed, or multiple processes may be executed in parallel.

[0109] In the above 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 on a recording medium such as a hard disk or a semiconductor memory.

[0110] Furthermore, each component may be realized by hardware. For example, each component may be a circuit (or an integrated circuit). These circuits may form a single circuit as a whole, or each may be a separate circuit. Furthermore, each of these circuits may be a general-purpose circuit, or a dedicated circuit.

[0111] In addition, the general or specific aspects of the present disclosure may be realized in a system, an apparatus, a method, an integrated circuit, a computer program, or a computer-readable recording medium such as a CD-ROM. In addition, the general or specific aspects of the present disclosure may be realized in any combination of a system, an apparatus, a method, an integrated circuit, a computer program, and a recording medium.

[0112] For example, the present disclosure may be realized as a program for causing a computer to execute the indoor environment control method according to the above embodiment. The present disclosure may be realized as a computer-readable non-transitory recording medium having such a program recorded thereon.

[0113] In addition, the present disclosure also includes forms obtained by applying various modifications to each embodiment that a person skilled in the art may conceive, or forms realized by arbitrarily combining the components and functions of each embodiment within the scope that does not deviate from the spirit of the present disclosure. [Explanation of symbols]

[0114] 1. Indoor environmental control system 10 Control device 20 Air Purifiers 30 Radio wave sensor 40 Air supply system 50 Exhaust system 60 Air conditioning equipment 70 Humidity Sensor 80 Temperature Sensor 90 Servers 100 Notification device

Claims

1. An air purifier that purifies the air inside the building; a radio wave sensor that detects the gait of a user located inside the building by performing frequency analysis on radio waves reflected by the user; a control device that estimates an amount of generated air pollutants in the building from the gait parameters of the user determined based on the detection results of the radio wave sensor, and controls the air purifier based on the estimated amount of generated air pollutants; The gait parameters include at least one of a step count, a step length, and a step height; The step height indicates the vertical distance from the point where the user raises his / her foot to the ground. Indoor climate control system.

2. The control device controls the air purifying device so that the amount of the air pollutants generated in the building is a predetermined amount.

2. The indoor climate control system of claim 1.

3. The building further includes an air conditioner for adjusting the temperature and humidity inside the building.

3. An indoor environment control system according to claim 1 or 2.

4. Further, an exhaust device that exhausts air inside the building to the outside of the building; an air supply device that supplies air outside the building to the building, The control device controls the exhaust device or the air supply device so that the amount of the air pollutant generated in the building is a predetermined amount. The indoor environment control system according to any one of claims 1 to 3.

5. Further, a humidity sensor is provided to detect humidity inside the building, The control device estimates the amount of generated air pollutants in the building based on the gait of the user determined based on the detection result of the radio wave sensor and the humidity in the building detected by the humidity sensor. The indoor environment control system according to any one of claims 1 to 4.

6. Further, an environmental sensor is provided to detect environmental information within the building, The control device further transmits the estimated amount of generated air pollutants and the environmental information in the building detected by the environmental sensor to an external server. The indoor environment control system according to any one of claims 1 to 5.

7. The air quality control system further includes an alarm device for notifying the estimated amount of generated air pollutants. The indoor environment control system according to any one of claims 1 to 6.

8. The building may further include a notification device that notifies the user of health risk information determined based on the estimated amount of generated air pollutants and the user's stay time in the building. An indoor environment control system according to any one of claims 1 to 7.

9. The gait parameters include the step height. An indoor environment control system according to any one of claims 1 to 8.

10. A detection step of detecting a gait of a user by a radio wave sensor that detects the gait of the user by performing frequency analysis of radio waves reflected by the user located inside a building; an estimation step of estimating an amount of generated air pollutants in the building from gait parameters of the user determined based on a detection result of the radio wave sensor; and a control step of controlling an air purifying device that purifies the air in the building based on the estimated amount of generated air quality pollutants, The gait parameters include at least one of a step count, a step length, and a step height; The step height indicates the vertical distance from the point where the user raises his / her foot to the ground. Indoor climate control methods.

11. A program for causing a computer to execute the indoor environment control method according to claim 10.

12. An air purifier that purifies the air inside the building; a radio wave sensor that detects the gait of a user located inside the building by performing frequency analysis on radio waves reflected by the user; A control device for controlling the air purifier, The control device has one or more processors; the one or more processors input gait detection data representing gait parameters of the user detected by the radio wave sensor into a model generated using gait data representing the gaits of a large number of users and dust amount data, estimate an amount of air pollutants generated in the building, and control the air purifier based on the estimated amount of air pollutants generated; The gait parameters include at least one of a step count, a step length, and a step height; The step height indicates the vertical distance from the point where the user raises his / her foot to the ground. Indoor climate control system.

13. the model is generated using the gait data, the temperature and humidity data, and the dust amount data; The one or more processors input the gait detection data of the user detected by the radio wave sensor and the temperature and humidity data in the building into the model.

13. The indoor climate control system of claim 12.

14. The model is a neural network model.

14. An indoor climate control system according to claim 12 or 13.

15. A detection step of detecting a gait of a user by a radio wave sensor that detects the gait of the user by performing frequency analysis on radio waves reflected by the user located inside a building; an estimation step of inputting gait detection data representing gait parameters of the user detected by the radio wave sensor into a model generated using gait data representing the gaits of a large number of users and dust amount data, and estimating an amount of generated air pollutants in the building; and a control step of controlling an air purifying device that purifies the air in the building based on the amount of generated air quality pollutants estimated in the estimation step, The estimation step and the control step are executed by one or more processors; The gait parameters include at least one of a step count, a step length, and a step height; The step height indicates the vertical distance from the point where the user raises his / her foot to the ground. Indoor climate control methods.

16. A program for causing a computer to execute the indoor environment control method according to claim 15.

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