Estimation device

Abstract

To provide an estimation device for easily estimating a temperature environment based on the estimation of a clothing amount regardless of a building.SOLUTION: An estimation device 100 for estimating a temperature environment of an object space includes an acquisition part 101 for acquiring first image information including a person entering the object space and second image information including a person leaving the object space, and obtains first clothing information which is a clothing amount of the person entering the object space on the basis of the first image information. And an estimation unit 104 that obtains an amount of change from the clothing amount of the person entering the target space to the clothing amount of the person leaving the target space on the basis of the first clothing information and the second clothing information and estimates that the temperature environment is hot in a case where the clothing amount decreases and that the temperature environment is cold in a case where the clothing amount increases. 102.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an estimation device. [Background technology]

[0002] As a method for automatically adjusting the settings of an air conditioning device installed in an office, a method for controlling the air conditioning device based on the estimated thermal sensation of occupants is known (see, for example, Patent Document 1). Specifically, a camera installed in the office captures images of the amount of clothing worn by the occupants, and an estimation device can estimate the thermal sensation of the occupants from the amount of clothing worn by the occupants. The air conditioning device can be controlled based on the estimated thermal sensation. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2023-138228 Summary of the Invention [Problem to be solved by the invention]

[0004] To implement the above-mentioned control, cameras are installed inside the office. However, if the office is large, it is necessary to install a huge number of cameras inside the office, which is costly and difficult to implement.

[0005] The present invention has been made to solve the above-mentioned problems, and aims to provide an estimation device that can easily estimate the temperature environment based on an estimation of the amount of clothing worn, regardless of the building. [Means for solving the problem]

[0006] In order to achieve the above object, the present invention provides the following means. An estimation device according to one embodiment of the present invention is an estimation device that estimates the temperature environment of a target space, and is characterized by including: an acquisition unit that acquires first image information including a person entering the target space and second image information including a person leaving the target space; a clothing information unit that calculates first clothing information, which is the amount of clothing worn by the person entering the target space, based on the first image information, and second clothing information, which is the amount of clothing worn by the person leaving the target space, based on the second image information; and an estimation unit that calculates the amount of change from the amount of clothing worn by the person entering the target space to the amount of clothing worn by the person leaving the target space, based on the first clothing information and the second clothing information, and estimates that the temperature environment is hot when the amount of clothing decreases, and that the temperature environment is cold when the amount of clothing increases.

[0007] According to the estimation device of the first aspect of the present invention, first image information is acquired which is image information of a person entering a target space (hereinafter also referred to as an entrant) and second image information is acquired which is image information of a person leaving the target space (hereinafter also referred to as an exiting person). Based on the acquired first image information and second image information, it is possible to calculate a first clothing amount which is the amount of clothing worn by the entering person and a second clothing amount which is the amount of clothing worn by the exiting person.

[0008] If the amount of clothing worn by the person leaving the room is less than the amount of clothing worn by the person entering, the estimation device will estimate that the target space is hot. Specifically, if the person entering the room is wearing long sleeves and the person leaving is wearing short sleeves, the estimation device will estimate that the target space is hot.

[0009] If the person leaving the room is wearing more clothing than the person entering, the estimation device will estimate that the target space is cold. Specifically, if the person entering the room is wearing short sleeves and the person leaving the room is wearing long sleeves, the estimation device will estimate that the target space is cold.

[0010] If the amount of clothing worn by the person leaving the room is not different from the amount of clothing worn by the person entering the room, the estimation device estimates that the temperature of the target space is appropriate for the people present. In the first aspect of the above invention, it is preferable that an identification unit is further provided that determines whether a person entering the target space and a person leaving the target space are the same person, and that the estimation unit estimates the temperature environment based on the amount of change in the amount of clothing worn by the person determined to be the same person.

[0011] In this way, by providing an identification unit, it is possible to determine whether the person entering the room included in the first image information matches the person leaving the room included in the second image information, and by making this determination, it is possible to determine the amount of change in the amount of clothing worn by the same person when they entered the room and when they left.

[0012] In the first aspect of the above invention, it is preferable that the first image information is linked to information on the time when a person enters the target space, and the second image information is linked to information on the time when a person leaves the target space, and a stay unit is further provided that calculates the time that the person determined to be the same stayed in the target space based on the first image information and the second image information, and the estimation unit selects a person based on the time of stay and estimates the temperature environment based on the amount of change in the amount of clothing worn by the selected person.

[0013] In this way, by providing a resident section, the time spent in the target space can be calculated, and the temperature environment can be estimated based on the amount of clothing worn by a person who has been there for a long time. By estimating the temperature environment based on the amount of change in the amount of clothing worn by people who have been staying in the room for a long time, the estimation device can easily estimate a temperature environment that is comfortable for many people in the room. [Effects of the Invention]

[0014] The estimation device of the present invention makes it easy to estimate the temperature environment based on the amount of clothing worn by occupants, regardless of the building. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a block diagram illustrating a configuration of an estimation device according to a first embodiment of the present invention. [Figure 2] FIG. 2 is a schematic diagram illustrating the configuration of a camera. [Figure 3] 3 is a flowchart illustrating processing performed by the estimation device according to the first embodiment of the present invention. [Figure 4] FIG. 4 is a block diagram illustrating the configuration of an estimation device according to a second embodiment of the present invention. [Figure 5] FIG. 10 is a schematic diagram illustrating the processing of an identification unit. [Figure 6] 10 is a flowchart illustrating processing performed by an estimation device according to a second embodiment of the present invention. [Figure 7] FIG. 10 is a block diagram illustrating the configuration of an estimation device according to a third embodiment of the present invention. [Figure 8] 10 is a flowchart illustrating processing performed by an estimation device according to a second embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0016] [First embodiment] Configuration description An estimation device 100 according to a first embodiment of the present invention will be described with reference to Fig. 1 to Fig. 3. The estimation device 100 of this embodiment is a device for estimating an indoor ambient temperature. It is also possible to control an air conditioner 500 based on the estimated ambient temperature.

[0017] The air conditioner 500 is configured to take in indoor air of a building, cool it, and supply the cooled air to the indoors of the building. Specifically, the air is cooled by circulating a refrigerant between the air and an outdoor unit (not shown) to exchange heat between the air and the refrigerant. The outdoor unit is configured so that the refrigerant removes heat from the air and releases it to the outside air.

[0018] The air conditioner 500 is provided with a heat exchanger (not shown) that cools the intake air by heat exchange, and an air conditioner fan (not shown) that sends out the heat-exchanged air. The heat exchanger and the air conditioner fan have known configurations.

[0019] The air conditioner 500 is preferably installed in an office. However, the air conditioner 500 may be installed in buildings other than offices. For example, it may be installed in a house or a school classroom. Furthermore, the air conditioner 500 may be installed in a means of transportation other than a building.

[0020] The air conditioner 500 has a configuration that allows it to be connected so as to be able to communicate with the estimation device 100. Specifically, it is preferable that the air conditioner 500 be controlled based on a signal transmitted from the estimation device 100.

[0021] The estimation device 100 is an information processing device such as a server or computer having a CPU (central processing unit), ROM, RAM, input / output interface, etc. The estimation device 100 is connected to a plurality of air conditioners 500 and cameras 300 so that information can be communicated therewith. The number of air conditioners 500 and cameras 300 connected to the estimation device 100 may be one or more.

[0022] As shown in FIG. 1, the estimation device 100 has a program stored in the ROM or the like that causes the CPU, ROM, RAM, and input / output interface to function in cooperation with each other as at least an acquisition unit 101, a memory unit 102, a clothing information unit 103, an estimation unit 104, a calculation unit 105, and a control unit 106.

[0023] The acquisition unit 101 is connected so as to be able to communicate and acquire image information captured by a camera 300 (described later). The acquisition unit 101 has a function of acquiring image information including at least one of a person entering a room and a person leaving a room, which is captured by the camera 300.

[0024] The image information preferably includes information for estimating at least one of a first clothing amount, which is the amount of clothing worn by the person entering the room, and a second clothing amount, which is the amount of clothing worn by the person leaving the room. The clothing amount is a parameter that indicates the type and number of layers of clothing worn by the person in the building. For example, it indicates the sleeve length and number of jackets worn by the person in the building.

[0025] The storage unit 102 is an information storage medium and has a function of storing information for estimating the indoor ambient temperature. The stored information preferably includes information acquired by the acquisition unit 101. The storage unit 102 may be a flash memory such as an SD memory card, or may be a recording medium of another type.

[0026] The clothing information unit 103 has a function of estimating the amount of clothing worn by at least one of the person entering and the person leaving the room based on the image information acquired by the acquisition unit 101. If the image information includes multiple people entering and leaving the room, it is preferable that the clothing information unit 103 estimates the amount of clothing worn by each of the people entering and leaving the room. Specific processing details of the clothing information unit 103 will be described later.

[0027] The amount of clothing is information that indicates the amount of clothing worn by the person entering or leaving the room. In this embodiment, the amount of clothing is information that indicates the sleeve length of the clothing worn by the person entering or leaving the room. The estimation unit 104 has a function of calculating a PMV value based on the amount of clothing worn by each total number of people calculated by the calculation unit 105. Specifically, the estimation unit 104 estimates a first PMV value and a second PMV value based on the pattern of the most common amount of clothing worn by the entrants.

[0028] The estimation unit 104 is configured to estimate the indoor ambient temperature based on at least one of the first PMV value and the second PMV value. The detailed processing of the estimation unit 104 will be described later.

[0029] The PMV value is a parameter calculated by a comfort equation with six variables: indoor temperature, humidity, radiant temperature, wind speed, clothing amount, and activity level. In this embodiment, the PMV value is a parameter calculated by a comfort equation with variables: indoor temperature, humidity, and radiant temperature included in the information about the indoor environment, wind speed included in the information about the outdoor environment, and clothing amount and activity level included in the information about the occupants.

[0030] The PMV value ranges from -3 (cold) to +3 (hot), and statistically, approximately 95% of people will feel comfortable when the PMV value is 0, and statistically, approximately 90% of people will feel comfortable when the PMV value is +0.5 to -0.5. It is preferable to control the air conditioning so that the PMV value falls within this specified range.

[0031] The first PMV value is a PMV value calculated based on at least the amount of clothing worn by the person entering the room. It differs from the second PMV value described below in that it does not use the amount of clothing worn by the person leaving the room as a parameter.

[0032] The second PMV is a PMV obtained by correcting the first PMV based on at least the amount of clothing worn by the person leaving the room. Note that if the amount of clothing worn by the person entering the room is the same as the amount of clothing worn by the person leaving the room, the first PMV and the second PMV may be the same.

[0033] The calculation unit 105 has the function of calculating the total number of people entering the room wearing short sleeves, the total number of people entering the room wearing long sleeves, the total number of people leaving the room wearing short sleeves, and the total number of people leaving the room wearing long sleeves, based on the amount of clothing worn by people entering the room and the amount of clothing worn by people leaving the room estimated by the clothing information unit 103.

[0034] The clothing pattern refers to the sleeve length pattern of the clothing worn by the person entering or leaving the room. In this embodiment, it is preferable to use four patterns: a pattern in which the person entering the room is wearing long sleeves, a pattern in which the person entering the room is wearing short sleeves, a pattern in which the person leaving the room is wearing long sleeves, and a pattern in which the person leaving the room is wearing short sleeves. However, other patterns may also be used.

[0035] The control unit 106 has a function of calculating the settings of the air conditioner 500 based on the PMV value calculated by the estimation unit 104. The control unit 106 also has a function of transmitting a signal to change the settings of the air conditioner 500. The means for transmitting the signal may use known technology.

[0036] The settings of the air conditioner 500 preferably include the set temperature, operating state, etc. of the air conditioner 500. As shown in Fig. 2, at least one camera 300 is installed in a room so as to capture images of entrances and exits, and is a device that captures images of people entering and leaving the room. Furthermore, camera 300 is configured to be able to transmit captured image information to estimation device 100. In this embodiment, it is preferable that camera 300 be able to capture images of all entrances and exits.

[0037] The camera 300 may be a camera 300 having the functions of an existing camera 300 in a building, may be incorporated into the estimation device 100, or may be configured independently. In this embodiment, a case will be described in which the camera 300 is configured independently of the estimation device 100.

[0038] Furthermore, camera 300 is preferably installed in an upper space so that it can overlook the entrance / exit that is the subject of imaging from above. Specifically, camera 300 is preferably installed on the ceiling near the entrance / exit that is the subject of imaging. However, camera 300 may also be installed somewhere other than the ceiling inside the room that is the subject of imaging.

[0039] Description of action Next, the operation of the estimation device 100 configured as described above will be described. First, the air conditioner 500 will be described, second, the camera 300 will be described, third, the processing of the estimation device 100 will be described, and fourth, the learning method of the learning model will be described.

[0040] First, the air conditioner 500 rotates the air conditioning fan to draw air from the office room into the air conditioner 500. The air that is drawn in includes air that has had heat radiated from people in the building and air that has been exhausted from electronic devices installed in the office.

[0041] The drawn-in air is cooled in a heat exchanger (not shown). Specifically, the temperature of the drawn-in air is lowered as heat is absorbed by the refrigerant circulating between the air and an outdoor unit (not shown). The refrigerant that has absorbed heat then releases the heat to the outside air in the outdoor unit. The refrigerant that has released the heat then absorbs heat from the drawn-in air again in the heat exchanger.

[0042] The air cooled in the heat exchanger is sent into the office room by an air conditioner fan (not shown). The air sent into the office room is conditioned based on the PMV value to ensure comfort for the occupants. The air sent into the office room is then drawn back into the air conditioner 500.

[0043] The air to be cooled is preferably air that brings the ambient temperature in the room to the set temperature estimated by the estimation device 100. Next, the control of camera 300 will be described. When camera 300 is powered on, it continues to capture images of all entrances and exits. When a person entering or leaving the room is captured, camera 300 transmits image information of the person entering or leaving to estimation device 100. In other words, every time at least one of a person entering or leaving the room is captured, camera 300 transmits image information of the person entering or leaving to estimation device 100.

[0044] Next, the control in the estimation device 100 will be described with reference to FIG. When processing in the estimation device 100 starts, the acquisition unit 101 acquires image information from the camera 300 at any timing (S1). The acquired image information is at least either first image information capturing an image of a person entering the room or second image information capturing an image of a person leaving the room. The first image information and the second image information may include one person entering or leaving the room, or may include multiple people entering or leaving the room.

[0045] The image information acquired by the acquisition unit 101 is stored in the storage unit 102. Based on the stored image information, the clothing information unit 103 estimates the amount of clothing worn by the person entering and the person leaving the room (S2). Specifically, the clothing information unit 103 estimates whether the clothing worn by the person entering and the person leaving the room, which is included in the image information, is short-sleeved or long-sleeved.

[0046] Once the amount of clothing is estimated, the calculation unit 105 performs a process of calculating the total number of people entering the room wearing short sleeves, the total number of people entering the room wearing long sleeves, the total number of people leaving the room wearing short sleeves, and the total number of people leaving the room wearing long sleeves (S3).

[0047] After the total number of people for each group is calculated, the estimation unit 104 estimates the first PMV value based on the amount of clothing worn by the people entering the room (S4). Note that the estimation unit 104 may estimate the first PMV value each time first image information is acquired.

[0048] Furthermore, the estimation unit 104 estimates a second PMV value based on the amount of clothing worn by the person leaving the room (S5). Note that the estimation unit 104 may estimate the second PMV value each time second image information is acquired. The processes of S4 and S5 by the estimation unit 104 differ depending on whether the total number of entrants wearing short sleeves is large or the total number of entrants wearing long sleeves is large. Therefore, we will explain the cases where the majority of entrants are wearing short sleeves and the cases where the majority of entrants are wearing long sleeves.

[0049] First, a case where many people wearing short sleeves enter the room will be described. The estimation unit 104 calculates a first PMV value based on the amount of short sleeves they are wearing. Specifically, it is preferable to change the set temperature so that the PMV value one hour later falls within the range of -0.5 to +0.5.

[0050] If the number of people wearing short sleeves exceeds the number of people wearing long sleeves, the room is judged to be at a comfortable temperature, and the first PMV is maintained. In other words, if the clothing patterns of the people entering and leaving the room are the same, the second PMV is set to the same value as the first PMV.

[0051] If the total number of people entering the room wearing short sleeves is less than the total number of people leaving the room wearing long sleeves, the estimation unit 104 determines that the indoor temperature environment is cold, corrects the first PMV value, and calculates the second PMV value. Specifically, it is preferable to change the PMV value after one hour to between -0.3 and +0.5. In other words, if there is a large change in the amount of clothing worn by people entering the room and people leaving the room, the estimation unit 104 determines that the indoor temperature environment is cold and calculates the second PMV value.

[0052] A large change in clothing volume refers to an increase in the number of layers of clothing worn or an increase in sleeve length. A small change in clothing volume refers to a decrease in the number of layers of clothing worn or a decrease in sleeve length.

[0053] Secondly, a case where many of the people entering the room are wearing long sleeves will be described. The estimation unit 104 calculates the first PMV value based on the amount of long sleeves they are wearing. Specifically, it is preferable to change the set temperature so that the PMV value one hour later falls within the range of -0.5 to +0.5.

[0054] If the total number of people wearing long sleeves is greater than the total number of people wearing short sleeves, the estimation unit 104 maintains the first PMV value. In other words, if the clothing pattern of the people entering and leaving the room is the same, the estimation unit 104 sets the second PMV value to the same value as the first PMV value.

[0055] If the total number of people entering the room wearing long sleeves is less than the total number of people leaving the room wearing short sleeves, the estimation unit 104 determines that the indoor temperature environment is hot, corrects the first PMV value, and calculates the second PMV value. Specifically, it is preferable to change the PMV value after one hour to -0.5 to +0.3. In other words, if the amount of change in the amount of clothing worn by people entering the room and people leaving the room becomes small, the estimation unit 104 determines that the indoor temperature environment is hot and calculates the second PMV value.

[0056] When the maintained first or second PMV value is calculated, the control unit 106 estimates the set temperature of the air conditioner 500 based on at least the maintained first or second PMV value (S6).

[0057] When the set temperature is estimated, the control unit 106 performs processing to transmit a signal to change the set temperature of the air conditioner 500 based on the estimated set temperature (S7). Next, we will explain the machine learning of the learning model.

[0058] In this embodiment, an example will be described in which machine learning of a learning model is performed in an information processing device different from the estimation device 100. The learning model that has undergone machine learning is stored in the storage unit 102 before processing by the estimation device 100.

[0059] Furthermore, after control is performed by the estimation device 100, a model that has undergone further machine learning may be stored in the storage unit 102. In this case, the previously stored learning model is replaced with the learning model that has undergone further machine learning.

[0060] Note that machine learning of the learning models may be performed in different information processing devices as described above, or may be performed in the estimation device 100. When machine learning is performed in the estimation device 100, a machine learning unit that performs machine learning is provided in the estimation device 100. Alternatively, machine learning for one of the learning models may be performed in different information processing devices, and machine learning for the other may be performed in the estimation device 100.

[0061] In the machine learning of the learning model, when a person in a building moves, training data is used to determine that the person is the same person before and after the movement. Specifically, training data that determines the person is the same person based on the distance the person moved estimated from previous and next frames of the image may be used, or training data that determines the person is the same person based on similarity may be used.

[0062] Regarding the specific machine learning in the learning model, known supervised learning can be used, and the specific content of the calculation process in supervised learning is not limited. Also, regarding the method of creating the teacher data for the learning model, known creation methods can be used, and the specific creation method is not limited.

[0063] Description of effects The estimation device 100 configured as described above can determine the amount of clothing worn by the person entering the room and the person leaving the room. The temperature environment of the target space can be estimated based on the amount of change in the amount of clothing worn by the person entering and the person leaving the room. Specifically, if the amount of clothing worn by the person leaving the room is less than the amount of clothing worn by the person entering the room, the estimation device 100 estimates that the target space is hot. Specifically, if the person entering the room is wearing long sleeves and the person leaving the room is wearing short sleeves, the estimation device 100 estimates that the target space is hot.

[0064] If the amount of clothing worn by the person leaving the room is greater than the amount of clothing worn by the person entering the room, the estimation device 100 estimates that the target space is cold. Specifically, if the person entering the room is wearing short sleeves and the person leaving the room is wearing long sleeves, the estimation device 100 estimates that the target space is cold.

[0065] In this way, by estimating the temperature environment of the target space based on the amount of clothing worn by the people entering and leaving the room, the estimation device 100 can estimate the temperature environment of the target space that is comfortable for the people entering and leaving the room.

[0066] In this way, by estimating the temperature environment of the target space based on the amount of clothing worn by people entering and leaving the room, it is only necessary to install cameras 300 at entrances and exits, and estimation device 100 can estimate the temperature environment regardless of the structure of the building. In other words, since there is no need to estimate the amount of clothing worn by people in the building, there is no need to install cameras 300 inside the room, and the number of cameras 300 installed can be reduced even in a large room.

[0067] <Second embodiment> Next, a second embodiment of the present invention will be described with reference to Fig. 4 to Fig. 6. The basic configuration of an estimation device 100A of this embodiment is similar to that of the first embodiment, except that an estimation unit 104A is provided instead of the estimation unit 104, and that an identification unit 107A is further provided. In this embodiment, only the configurations that differ from those of the first embodiment will be described, and a description of the same configurations will be omitted.

[0068] As shown in FIG. 4, the estimation device 100A has a program stored in the ROM or the like that causes the CPU, ROM, RAM, and input / output interface to function in cooperation with each other as at least an acquisition unit 101, a memory unit 102, a clothing information unit 103, an estimation unit 104A, a calculation unit 105, an identification unit 107A, and a control unit 106.

[0069] The estimation unit 104A has the function of calculating the first PMV value based on the clothing amount pattern of the larger total number of people between the total number of people wearing short sleeves and the total number of people wearing long sleeves calculated by the calculation unit 105.

[0070] The estimation unit 104A has a function of calculating a second PMV value based on the amount of clothing of a person who is determined by the identification unit 107A (described later) to be the same person as the person entering the room and the person leaving the room (hereinafter also referred to as the same person).

[0071] The identification unit 107A has a function of determining whether the person entering the room and the person leaving the room are the same, as shown in Fig. 5. In this embodiment, the identification unit 107A has a configuration that uses a person database to determine whether the person entering the room and the person leaving the room are the same.

[0072] The person database is a database that stores information about the appearance of people entering and leaving a room. Description of action Next, the processing of the estimation device 100A having the above configuration will be described with reference to Fig. 6. Note that the description of the processing up to the calculation of the first PMV value of the air conditioner 500, the camera 300, and the estimation device 100, which is the same as the operation of the first embodiment, will be omitted.

[0073] After the first PMV value is calculated, the identification unit 107A selects image information including a person entering the room that matches the person leaving the room from all stored image information including people entering the room. In other words, the identification unit 107A estimates the person entering the room that matches the person leaving the room (hereinafter, also referred to as the same person) (S11).

[0074] If the same person is identified, the clothing information unit 103 estimates the amount of clothing worn by the selected person (S12). Specifically, the clothing information unit 103 estimates the amount of change in the amount of clothing worn by the same person included in the image information.

[0075] Once the change in clothing amount is estimated, the calculation unit 105 calculates the total number of people for the same person whose clothing amount has changed a lot, whose clothing amount has changed a little, and whose clothing amount has not changed at all (S13).

[0076] Once the respective total number of people is calculated, the estimation unit 104A calculates the second PMV value (S14). Specifically, if the total number of people for the same item with the largest change in clothing amount is the largest, the estimation unit 104A corrects the first PMV value and calculates the second PMV value based on the clothing amount pattern with the largest change in clothing amount.

[0077] When the total number of people for whom the change in clothing amount has decreased is the largest among the same items, the estimation unit 104A corrects the first PMV value and calculates the second PMV value based on the pattern of clothing amount for which the change in clothing amount has decreased.

[0078] If the total number of people with no change in clothing amount among the same person is the largest, the estimation unit 104A maintains the first PMV value. In other words, if the clothing amount pattern of the same person does not change, the estimation unit 104A sets the second PMV value to the same value as the first PMV value.

[0079] When the maintained first or second PMV value is calculated, the control unit 106 estimates the set temperature of the air conditioner 500 based on at least the maintained first or second PMV value (S15).

[0080] When the set temperature is estimated, the control unit 106 performs processing to transmit a signal to change the set temperature of the air conditioner 500 based on the estimated set temperature (S16). effect The estimation device 100A configured as described above includes the identification unit 107A, which makes it possible to determine whether the person entering the room and the person leaving the room are the same. This determination makes it possible to determine the amount of change in the amount of clothing worn by the same person when they enter the room and when they leave. By determining the amount of change in the amount of clothing worn by the same person, it becomes easier to estimate the comfortable temperature environment in the room with high accuracy.

[0081] Third Embodiment Next, a third embodiment of the present invention will be described with reference to Figures 7 and 8. The basic configuration of an estimation device 100B of this embodiment is similar to that of the first and second embodiments, but differs in that an estimation unit 104B is provided instead of the estimation unit 104 or the estimation unit 104A, and that a residence unit 108B is further provided. In this embodiment, only the configurations that differ from the first and second embodiments will be described, and descriptions of the same configurations will be omitted.

[0082] As shown in FIG. 7, the estimation device 100B has a program stored in the ROM or the like that causes the CPU, ROM, RAM, and input / output interface to function in cooperation with each other as at least an acquisition unit 101, a memory unit 102, a clothing information unit 103, an estimation unit 104B, a calculation unit 105B, an identification unit 107A, a stay unit 108B, and a control unit 106.

[0083] The estimation unit 104B has a function of estimating the indoor environmental temperature based on the amount of change estimated by the clothing information unit 103 and the staying time calculated by the staying time unit 108B. Specifically, when the amount of change of multiple identical people is estimated, the indoor environmental temperature may be estimated based on the amount of change of the matching person who stayed for the longest time.

[0084] The calculation unit 105B has a function of totaling the staying time in addition to the contents described in the first embodiment. Specifically, it is preferable to calculate the total staying time of the total number of people wearing short sleeves when the same person leaves, and the total staying time of the total number of people wearing long sleeves when the same person leaves.

[0085] The staying unit 108B has a configuration to calculate the staying time of all the same persons who are determined by the identification unit 107A to be the same person as the person entering the room and the person leaving the room. The staying time is the time from when the person enters the room to when the person leaves the room.

[0086] Description of action Next, the processing of the estimation device 100B having the above configuration will be described with reference to Fig. 8. Note that the description of the processing up to the calculation of the first PMV value of the air conditioner 500, the camera 300, and the estimation device 100, which is the same as the operations of the first and second embodiments, will be omitted.

[0087] After the first PMV value is calculated, the identification unit 107A selects image information including a person entering the room that matches the person leaving the room from all stored image information including people entering the room. In other words, the identification unit 107A estimates that the person is the same person (S21).

[0088] If the same person is identified, the clothing information unit 103 estimates the amount of clothing worn by the selected person (S22). Specifically, the clothing information unit 103 estimates the amount of change in the amount of clothing worn by the same person included in the image information.

[0089] Once the amount of clothing is estimated, the stay unit 108B calculates the stay time of all the same person (S23). Specifically, the stay unit 108B calculates the difference between the time when the same person entered the room and the time when they left the room.

[0090] Once the stay time is calculated, the calculation unit 105 calculates the total stay time of the same person for each clothing amount pattern (S24). Specifically, the total number of people wearing short sleeves at the time of exit by the same person is calculated. Furthermore, the stay time of the total number of people wearing short sleeves is totaled. Furthermore, the total number of people wearing long sleeves at the time of exit by the same person is calculated. Furthermore, the stay time of the total number of people wearing long sleeves is totaled.

[0091] After the total stay time is calculated, estimation unit 104B calculates a second PMV value based on the clothing amount pattern with the longest total stay time (S25). Specifically, estimation unit 104B calculates the second PMV value based on the clothing amount pattern with the longest total stay time out of the total stay time of the total number of people wearing short sleeves and the total stay time of the total number of people wearing long sleeves calculated in the process of S24.

[0092] Once the second PMV value is calculated, the control unit 106 sets the set temperature of the air conditioner 500 based on at least the second PMV value (S26). Once the set temperature is estimated, the control unit 106 performs processing to transmit a signal to change the set temperature of the air conditioner 500 based on the estimated set temperature (S27).

[0093] Description of effects The estimation device 100B having the above configuration is provided with the stay unit 108B, so that the stay time of the same person can be estimated. By calculating the stay time, when there are multiple people coming and going through the entrance, it is possible to weight the amount of clothing worn by the person who stayed in the room for the longest time. Furthermore, it is possible to estimate the thermal sensation in the room based on the weighted amount of clothing worn by the target person. The estimation device 100B as described above can estimate the indoor temperature environment with high accuracy.

[0094] The technical scope of the present invention is not limited to the above-described embodiments, and various modifications can be made without departing from the spirit of the present invention. For example, the present invention is not limited to applications of the above-described embodiments, and may be applied to embodiments in which these embodiments are appropriately combined, and is not particularly limited. [Explanation of symbols]

[0095] 100, 100A, 100B...estimation device, 101...acquisition unit, 102...memory unit, 103...clothing information unit, 104, 104A, 104B...estimation unit, 105, 105B...calculation unit, ...control unit 106, 107A...identification unit, 108B...stay unit, 300...camera, 500...air conditioning unit.

Claims

1. An estimation device for estimating a temperature environment in a target space, an acquisition unit that acquires first image information including a person entering the target space and second image information including a person leaving the target space; a clothing information unit that calculates first clothing information representing the amount of clothing worn by a person entering the target space based on the first image information, and calculates second clothing information representing the amount of clothing worn by a person leaving the target space based on the second image information; an estimation unit that calculates the amount of change from the amount of clothing worn by a person entering the target space to the amount of clothing worn by a person leaving the target space based on the first clothing information and the second clothing information, and estimates that the temperature environment is hot when the amount of clothing worn decreases, and that the temperature environment is cold when the amount of clothing worn increases.

2. An identification unit is further provided to determine whether a person entering the target space and a person leaving the target space are the same person, The estimation device according to claim 1 , wherein the estimation unit estimates the temperature environment based on the amount of change in the amount of clothing worn by the person determined to be the same person.

3. The first image information is linked to information on the time when a person enters the target space, and the second image information is linked to information on the time when a person leaves the target space, a stay unit that calculates a time during which the person determined to be the same stayed in the target space based on the first image information and the second image information, The estimation device according to claim 2 , wherein the estimation unit selects a person based on the length of time the person stayed, and estimates the temperature environment based on the amount of change in the amount of clothing worn by the selected person.

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