JP7563115B2 - Indoor environment management support device and indoor environment management support method - Google Patents

Description

This disclosure relates to an indoor environment management support device and an indoor environment management support method.

As the COVID-19 pandemic spreads, efforts are being made nationwide to reduce the risk of mass infection by avoiding the "three Cs" (closed spaces, crowded places, and close contact). As part of this effort, there has been growing interest in ventilating indoor spaces, with the aim of reducing the risk of viral infection through closed spaces. However, viruses are impossible to detect visually. For this reason, although the Ministry of Health, Labor and Welfare and other organizations have published guidelines for indoor ventilation, even if the guidelines are followed, the actual effectiveness is unclear as it is invisible, and anxiety cannot be completely dispelled.

In July 2020, heavy rains hit various parts of Kyushu, mainly Kumamoto Prefecture. As a result, many residents of the prefecture were forced to live in evacuation shelters amid the COVID-19 pandemic. However, due to the suddenness of the disaster, there was little time to implement ventilation measures in evacuation shelters to combat COVID-19, and local governments were forced to implement them on a trial-and-error basis.

Meanwhile, in May 2020, Nara Medical University and others announced evidence that ozone gas can inactivate the new coronavirus. As a result, interest in using ozone gas to eliminate the new coronavirus has increased. However, because ozone gas cannot be visually detected, many users are concerned about whether ozone gas is filling the entire room, even if they install devices such as ozone generators.

Japanese Patent Application Publication No. 11-142236 Japanese Patent Application Publication No. 11-63622

In order to recognize the diffusion status of ozone gas, there is a method (see Patent Document 1) in which a small portable optical measuring device (ozone concentration measuring device) is used to actually measure the ozone gas concentration indoors. However, in order to use this method to capture the spatial concentration in three dimensions, it is necessary to install multiple measuring devices and perform measurements, making it difficult to respond immediately in an emergency.

In addition, in order to visualize the ventilation status and gas diffusion status within a room, a technology exists that performs thermal fluid analysis using a three-dimensional model of the room to determine the airflow distribution within the room, and then analyzes the dust concentration distribution within the room (see Patent Document 2). Using this technology, it is possible to grasp the ventilation status and gas diffusion status within the room in three dimensions, but there has been a demand for technology that provides users with an easy-to-understand explanation of the grasped status and useful improvement proposals based on this status.

This disclosure has been made in consideration of the above circumstances, and aims to provide an indoor environment management support device and an indoor environment management support method that are capable of providing information indicating indoor airflow conditions and improvement proposals based on these airflow conditions.

The indoor environment management support device according to the present disclosure includes an imaging information acquisition unit that acquires two-dimensional imaging information of the room to be managed, a three-dimensional model information generation unit that generates three-dimensional model information of the room from the two-dimensional imaging information acquired by the imaging information acquisition unit, an analysis unit that analyzes the airflow condition in the room using the three-dimensional model information generated by the three-dimensional model information generation unit, and a diagnosis result information generation unit that generates diagnosis result information including information indicating proposed changes to the indoor condition that are effective in improving the airflow condition and that have been input based on the information analyzed by the analysis unit and that have been diagnosed as needing to improve the indoor airflow condition, and image information and numerical information indicating the predicted improvement in the indoor airflow condition as a result of the changes.

The analysis unit may use the three-dimensional model information to analyze the air exchange condition in the room, and the diagnosis result information generation unit may generate diagnosis result information based on the information analyzed by the analysis unit, the diagnosis result information including information indicating proposed changes to the condition in the room that are effective in improving the air exchange condition and that have been input after diagnosing that the air exchange condition in the room needs to be improved, and image information and numerical information indicating the predicted improvement in the air exchange condition in the room as a result of the changes.

The air exchange state in the room may also indicate the ventilation state in the room, the state in which the air in the room is sucked to the outside by a blower, and the state in which the air in the room is purified by a dust collector.

The analysis unit may also replace information on changes in the temperature field in the room analyzed using the three-dimensional model information with information on changes in the concentration of air present in the room at the start of the analysis, and use this information in the analysis process of the ventilation condition in the room.

The analysis unit may also use the three-dimensional model information to analyze the drug diffusion state within the room, and the diagnosis result information generation unit may generate diagnosis result information based on the information analyzed by the analysis unit, the diagnosis result information including information indicating proposed changes to the state within the room that are effective in improving the drug diffusion state and that have been input after diagnosing that the drug diffusion state within the room needs to be improved, and image information and numerical information indicating the predicted improvement in the drug diffusion state within the room as a result of the changes.

The agent may be ozone or alcohol, and may be in the form of gas, fine bubble water, droplets, or aerosol.

The analysis unit may also use the three-dimensional model information to analyze the state of ozone gas diffusion within the room, taking into account the state of ozone gas adhesion to objects, including walls, within the room.

The indoor environment management support method according to the present disclosure acquires two-dimensional imaging information of the room to be managed, generates three-dimensional model information of the room from the acquired two-dimensional imaging information, analyzes the airflow condition in the room using the generated three-dimensional model information, and generates diagnosis result information based on the analyzed information, including information indicating proposed changes to the indoor condition that are effective in improving the airflow condition and that have been diagnosed as needing improvement in the indoor airflow condition and input, and image information and numerical information indicating the predicted improvement in the indoor airflow condition as a result of the changes.

The indoor environment management support device and indoor environment management support method disclosed herein can provide information indicating the airflow conditions within a room and improvement suggestions based on these airflow conditions.

1 is a block diagram showing a configuration of an indoor environment support system using an indoor environment management support device according to a first embodiment. FIG. 4 is a flowchart showing an operation of the indoor environment management support device according to the first embodiment. 1A is an example of two-dimensional imaging information acquired by the indoor environment management support device according to the first embodiment, and FIG. 1B is an example of three-dimensional model information generated from the two-dimensional imaging information of FIG. 11 is an example of image information showing a simulation result of the ventilation state before and after a change in the room, generated by the indoor environment management support device according to the first embodiment. 13A and 13B are other examples showing the ventilation state of the room before and after a change, generated by the indoor environment management support device according to the first embodiment. 1 is a graph showing the change over time in the indoor air exchange rate before and after a change in the indoor condition, generated by the indoor environment management support device according to the first embodiment. This is information used by the indoor environment management support device of the second embodiment, and is a graph showing the change in the average ozone concentration in the room simulated taking into account the adhesion state of ozone gas on the wall surface, and the change in the average ozone concentration in the room simulated without taking into account the adhesion state of ozone gas on the wall surface. 13A and 13B are examples of image information showing simulation results of the ozone gas diffusion state before and after the change in the indoor environment, generated by the indoor environment management support device according to the second embodiment. 13 is a graph showing the change over time in ozone concentration at each position in the room, both before and after a change in the indoor condition, generated by the indoor environment management support device according to the second embodiment.

Below, an exemplary embodiment of an indoor environment support system using an indoor environment management support device will be described with reference to the drawings.

First Embodiment
Configuration of the indoor environment management support system according to the first embodiment
The indoor environment management support system 1A of this embodiment includes a mobile terminal 10 carried by a user who is in room Y of a building X to be managed, and an indoor environment management support device 30 installed at a location remote from the building X and connected to the mobile terminal 10 via a communication network 20.

The mobile terminal 10 has a camera device 11, a first input unit 12, a terminal communication unit 13, a first display unit 14, and an information processing unit 15. The camera device 11 has a function of taking pictures in response to user operations. The first input unit 12 inputs the contents of operations performed by the user. The terminal communication unit 13 communicates with the indoor environment management support device 30 via the communication network 20. The first display unit 14 displays display information.

The indoor environment management support device 30 has a support device communication unit 31, a CPU 32, a second display unit 33, and a second input unit 34. The support device communication unit 31 communicates with the mobile terminal 10 via the communication network 20. The CPU 32 has an image information acquisition unit 321, a three-dimensional model information generation unit 322, an analysis unit 323, and a diagnosis result information generation unit 324.

The imaging information acquisition unit 321 acquires two-dimensional imaging information of the room Y captured by the user using the camera device 11 and transmitted from the mobile terminal 10. The three-dimensional model information generation unit 322 generates three-dimensional model information of the room Y from the two-dimensional imaging information acquired by the imaging information acquisition unit 321. The analysis unit 323 analyzes the state of ventilation due to the airflow in the room Y using the three-dimensional model information of the room Y captured using the three-dimensional model information. The diagnosis result information generation unit 324 generates diagnosis result information including information input by the administrator indicating proposed changes to the state of the room Y that are effective in improving the airflow state, and image information and numerical information indicating the predicted improvement status of the airflow state in the room as a result of the changes. The diagnosis result information generation unit 324 transmits the generated diagnosis result information to the mobile terminal 10.

The second display unit 33 displays information processed by the CPU 32, such as information analyzed by the analysis unit 323. The second input unit 34 inputs operation information by the manager who manages the environment of the room Y.

<Operation of the indoor environment management support system according to the first embodiment>
As an operation of the indoor environment management support system 1A according to this embodiment, a process of diagnosing the ventilation state as the air exchange state of the room Y with one window open will be described with reference to Figs. 2 to 6.

First, the user photographs the interior Y of the building X from multiple angles using the camera device 11 of the mobile terminal 10. The user operates the first input unit 12 to create a request for diagnosis of the ventilation condition with the photographed two-dimensional image information attached, and sends it to the indoor environment management support device 30 via the communication network 20 using an email function or the like.

The diagnosis request information sent from the mobile terminal 10 is received by the support device communication unit 31 of the indoor environment management support device 30 ("YES" in S1), and the attached two-dimensional image information of the room Y is acquired by the imaging information acquisition unit 321. When the imaging information acquisition unit 321 acquires the diagnosis request information, the three-dimensional model information generation unit 322 generates three-dimensional model information of the room Y from the two-dimensional imaging information attached to the diagnosis request information, for example, using computer-aided design (CAD) (S2).

There are two methods for generating 3D model information from 2D imaging information using CAD. The first method involves converting the number of pixels corresponding to a specific subject in the 2D imaging information into the actual size of the subject to grasp the size of each object in the room Y and generate 3D model information. The second method involves using functions installed in existing tablet terminals or the like to automatically generate 3D model information from 2D imaging information using image recognition technology. Figure 3(a) is an example of 2D imaging information of room Y acquired by the 3D model information generation unit 322, and Figure 3(b) is an example of 3D model information generated from the 2D imaging information of Figure 3(a).

Next, the analysis unit 323 analyzes the state of ventilation by airflow in the room Y using the generated three-dimensional model information of the room Y (S3). Specifically, the analysis unit 323 performs analysis processing by performing a thermal fluid simulation by coupling an equation related to the transport of a predetermined substance concentration with a general thermal fluid analysis method. The analysis unit 323 then generates image information or video information showing the ventilation state of the room Y for each elapsed time from the specified time point, and calculates the air exchange rate of the room Y for each elapsed time from the specified time point.

Applications that perform thermal fluid simulations generally have a function for analyzing the temperature field of air. Using this function, in this embodiment, information on the change in the temperature field in room Y is replaced with information on the concentration change due to the air flow (transport) that existed in room Y at the start of the analysis, and is used in the analysis process of the ventilation state of room Y. This makes it possible to easily obtain the analysis results of the ventilation state of room Y using existing technology. The information obtained by the analysis process is displayed on the second display unit 33 (S4).

When the information acquired by the analysis unit 323 is displayed on the second display unit 33, the manager in charge of managing the environment of room Y visually checks it and diagnoses whether the airflow in room Y meets the specified conditions. Specifically, the manager determines whether the air exchange rate in room Y has reached a specified value or higher within a preset time, for example, whether the air exchange rate in room Y has reached 90% or higher within 5 minutes.

Here, if the airflow in room Y does not meet the predetermined conditions, the manager diagnoses that the airflow in room Y needs to be improved, considers proposals for changing the state of room Y that are effective in improving the ventilation state, and inputs them from the second input unit 34 ("YES" in S5). Examples of proposals for changing the state of room Y include increasing the number of open windows from one to two, placing an electric fan in the room, moving items placed near the windows, etc.

When it is determined that the airflow condition in room Y needs to be improved and a proposed change is input as an improvement plan ("YES" in S5), the process returns to step S3. The analysis unit 323 then analyzes the ventilation condition in room Y after the change, and displays the information obtained by the analysis process on the second display unit 33 (S3, S4). The manager visually checks the information displayed on the second display unit 33 and determines whether the airflow in room Y has reached a state that satisfies the specified conditions. The process of steps S3 to S5 is repeated until the airflow in room Y reaches a state that satisfies the specified conditions.

When the airflow in room Y meets the predetermined conditions and the administrator diagnoses that improvement to the airflow condition in room Y is not necessary ("NO" in S5), the administrator performs an operation from the second input unit 34 to instruct the generation of a judgment result. When the administrator performs this operation, the diagnosis result information generation unit 324 generates diagnosis result information. The diagnosis result information generated here includes information input by the administrator indicating the proposed changes to the condition of room Y that are effective in improving the airflow condition, image information or video information indicating the predicted improvement in the airflow condition in room Y as a result of the changes, and numerical information.

Examples of information contained in the generated diagnosis results are shown in Figs. 4 to 6. Fig. 4 shows display information P that shows the simulation results of the ventilation state of room Y before and after the change proposed by the administrator to the state of room Y, which is to "increase the number of open windows from one to two."

Image information 41 to 43 included in display information P show the ventilation state on a plane at a specified height position when the state of room Y is before the change, that is, when there is one open window. Image information 41 shows the ventilation state of room Y at time t0 when the analysis process starts, image information 42 shows the ventilation state of room Y one minute after time t0, and image information 43 shows the ventilation state of room Y five minutes after time t0. These pieces of image information 41 to 43 show that one minute after the analysis process starts t0, only a narrow area near the window is ventilated with outside air, and five minutes later the area ventilated with outside air expands further, but the air from when the analysis process started t0 still remains.

Image information 44 to 46 show the ventilation state of room Y after the change, that is, the state of ventilation on a plane at a specified height when two windows are open. Image information 44 shows the ventilation state of room Y at time t0 when the analysis process begins, image information 45 shows the ventilation state of room Y one minute after time t0, and image information 46 shows the ventilation state of room Y five minutes after time t0. These images 44 to 46 show that one minute after the analysis process begins t0, a wide area of room Y has already been ventilated with outside air, and that five minutes later, the air that was there at the start of the analysis process t0 has been ventilated to the point where it has almost completely disappeared. These images show that the ventilation state of room Y after the change is improved compared to its state before the change.

In the above example, image information showing the ventilation state on a plane at a predetermined height in room Y is generated as information showing the simulation results of the ventilation state before and after the change in room Y, but this is not limited to the example. As another example, as shown in FIG. 5, image information showing the ventilation state of room Y may be generated by showing the air flow linearly. FIG. 5(a) shows the ventilation state for a predetermined period in the state before the change in room Y, that is, when there is one open window, and FIG. 5(b) shows the ventilation state for a predetermined period in the state after the change, that is, when there are two open windows. As another example, image information showing the ventilation state of the entire space, not just the plane at a predetermined height in room Y, may be generated.

The information showing the improvement status of the airflow condition in the room Y may not only be image information at a specific timing, but also video information that continuously shows the airflow condition in the room Y for a specific period of time.

Figure 6 is a graph showing the change over time in the air exchange rate in room Y before and after the change, generated as an example of numerical information showing the predicted improvement in the airflow state due to a change in the state of room Y. The dotted line L1 in this graph shows the change in the air exchange rate in room Y before the change, and the solid line L2 shows the change in the air exchange rate in room Y after the change. This graph shows that when there is one window open, the air exchange rate in room Y is only about 50% even 10 minutes after the start of processing, whereas when there are two windows open, the air exchange rate in room Y reaches 90% or more about 5 minutes after the start of processing.

The generated diagnostic result information is transmitted from the support device communication unit 31 to the mobile terminal 10 (S6). The transmitted diagnostic result information is received by the mobile terminal 10 and displayed on the first display unit 14 by the information processing unit 15. The user can visually check the information displayed on the first display unit 14 and increase the number of open windows from one to two as suggested, thereby achieving an appropriate ventilation state for room Y.

According to the first embodiment described above, it is possible to provide the user with information indicating the ventilation status of the room and improvements to the indoor conditions based on this ventilation status in an easy-to-understand manner from a location remote from the managed room. This allows the user to take action to ensure that the air in a room where contaminants such as viruses may be dispersed is exchanged and the room becomes a comfortable space.

In the first embodiment described above, the case where the air exchange state of the room Y is diagnosed by analyzing the ventilation state of the room Y has been described. However, this is not limited to this, and the air exchange state of the room Y may be diagnosed by analyzing the state of the airflow when performing a process to more actively remove indoor pollutants, such as the state of sucking the air of the room Y to the outside by a blower, or the state of purifying the air of the room Y by a dust collector. By diagnosing the air exchange state in this way, the convection state and suction state of aerosols, dust, or droplets to which pollutants are attached can be analyzed. In these cases, the air exchange state of the room Y can be diagnosed by analyzing the state of the airflow using three-dimensional model information of the room Y in the same manner as in the process of the first embodiment described above, taking into account the installation position and performance of the blower or dust collector.

Second Embodiment
The configuration of the indoor environment management support system 1B of this embodiment is similar to the configuration of the indoor environment management support system 1A described in the first embodiment, so a detailed description thereof will be omitted.

As an operation of the indoor environment management support system 1B according to this embodiment, a process for diagnosing the diffusion state when a desired drug is diffused into room Z of a movie theater for the purpose of decontaminating viruses and the like that affect the human body will be described with reference to Figs. 2 and 7 to 9. In this embodiment, a process for diagnosing the diffusion state when ozone gas that inactivates the new coronavirus is diffused into room Z by an ozone gas generator installed in room Z will be described.

First, the user photographs the room Z from multiple angles using the camera device 11 of the mobile terminal 10. The user creates diagnosis request information for the ozone gas diffusion state using the mobile terminal 10 and transmits it to the indoor environment management support device 30. The method of creating and transmitting this diagnosis request information is the same as that described in the first embodiment, so a detailed description will be omitted.

When the indoor environment management support device 30 receives the diagnosis request information ("YES" in S1), the three-dimensional model information generation unit 322 generates three-dimensional model information from the attached two-dimensional image information of the room Z in the same manner as described in the first embodiment (S2). Then, the analysis unit 323 uses the generated three-dimensional model information of the room Z to analyze the diffusion state of ozone gas due to airflow when the ozone gas generator D is installed in a predetermined position in the room Z, for example, in front of the front row seats (S3).

When analyzing the diffusion state of ozone gas, the analysis unit 323 performs processing taking into account the state of adhesion of ozone gas to objects such as walls and seats in the room Z. When ozone gas adheres to objects such as walls and seats in the room Z, it becomes inactive, and the ozone concentration in the indoor space decreases. In addition, the degree of adhesion of ozone gas varies depending on the material of the wall or object, and the degree of adhesion is higher on materials with uneven surfaces than on materials with smooth surfaces, resulting in a lower ozone concentration in the room.

The solid line L3 in Figure 7 shows the change in the average indoor ozone concentration, simulated by taking into account the adhesion state of ozone gas on the walls when ozone gas is supplied to the room under specified conditions. The dotted line L4 shows the change in the average indoor ozone concentration, simulated by not taking into account the adhesion state of ozone gas on the walls when ozone gas is supplied under the same conditions.

By taking into account the adhesion state of ozone gas on the wall surfaces, the analysis unit 323 can calculate a value close to the actual ozone concentration in the room Z and perform a highly accurate analysis.

In addition, the diffusion state of the ozone gas supplied to the room Z varies depending on the presence or absence of a gap between the room Z and the external space, the airflow state in the external space, the performance of the ozone gas generator, etc. Therefore, by taking these factors into account, the analysis unit 323 can analyze the diffusion state of the ozone gas in the room Z with even greater accuracy.

The information acquired by the analysis process is displayed on the second display unit 33 (S4). When the analyzed information is displayed on the second display unit 33, the manager in charge of managing the environment of the room Z visually checks it and determines whether the airflow in the room Z satisfies a predetermined condition, for example, whether the ozone concentration at a predetermined location in the room Z is equal to or greater than a predetermined value within a predetermined time.

Here, if the ozone concentration in room Z does not meet the predetermined conditions and the manager diagnoses that the airflow condition in room Z needs to be improved, the manager considers the proposed changes to the condition in room Z that are effective in improving the ozone gas diffusion condition and inputs them from the second input unit 34 ("YES" in S5). Examples of proposed changes to the condition in room Z include increasing the number of ozone gas generators, changing the installation positions of the ozone gas generators, installing electric fans in predetermined positions, etc.

When it is determined that the airflow condition in room Z needs to be improved and the proposed changes are input ("YES" in S5), the process returns to step S3. The analysis unit 323 then analyzes the ozone gas diffusion state in room Z after the changes are made, and displays the information obtained by the analysis process on the second display unit 33 (S3, S4). The manager visually checks the information displayed on the second display unit 33 and diagnoses whether the airflow in room Z has reached a state that satisfies the specified conditions.

When the airflow in room Z meets the predetermined conditions and the administrator diagnoses that improvement of the airflow condition in room Z is not necessary ("NO" in S5), the administrator performs an operation from the second input unit 34 to instruct the generation of a judgment result. When the administrator performs this operation, the diagnosis result information generation unit 324 generates diagnosis result information. The diagnosis result information generated here includes information input by the administrator indicating the proposed changes to the state of room Z that are effective in improving the airflow condition, image information or video information indicating the predicted improvement in the airflow condition in room Z as a result of the changes, and numerical information.

An example of information contained in the generated diagnosis result is shown in Fig. 8 (a) and (b). Fig. 8 (a) and (b) are image information showing the simulation results of the ozone gas diffusion state before and after the change in room Z when the change proposed by the administrator is to "install an electric fan near the ozone gas generator."

Figure 8 (a) shows the state of ozone gas diffusion in room Z before the change, i.e., when no electric fan is installed in room Z, one hour after the ozone gas generator D starts operating. Figure 8 (b) shows the state of ozone gas diffusion in room Z after the change, i.e., when an electric fan E is installed near the ozone gas generator in room Z, one hour after the ozone gas generator D starts operating.

Figures 8(a) and (b) show that one hour after ozone gas generation begins, if no electric fans are installed in room Z, ozone gas does not reach the center row of seats, but if an electric fan is installed and operating, ozone gas will reach the center row.

The information showing the improvement status of the airflow condition in the room Z may not only be image information at a specific timing, but also video information that continuously shows the airflow condition in the room Z for a specific period of time.

Figure 9 is a graph showing the change over time in ozone concentration at each position in room Z before and after the change, as an example of numerical information showing the predicted improvement in airflow conditions due to a change in the state of room Z. The solid line L5 in this graph shows the change over time in ozone concentration at the center of the front row of seats in room Z before the change. The dotted line L6 shows the change over time in ozone concentration at the center of the center row of seats in room Z before the change. The dashed and dotted line L7 shows the change over time in ozone concentration at the center of the last row of seats in room Z before the change. The solid line L8 shows the change over time in ozone concentration at the center of the front row of seats in room Z after the change. The dotted line L9 shows the change over time in ozone concentration at the center of the center row of seats in room Z after the change. The dashed and dotted line L10 shows the change over time in ozone concentration at the center of the last row of seats in room Z after the change.

This graph shows that the diffusion rate of ozone gas is significantly faster when a fan is installed in room Z compared to when it is not.

The generated diagnostic result information is transmitted from the support device communication unit 31 to the mobile terminal 10 (S6). The transmitted diagnostic result information is received by the mobile terminal 10 and displayed on the first display unit 14 by the information processing unit 15. The user can visually confirm the information displayed on the first display unit 14 and install an electric fan in the room Z as suggested, thereby appropriately diffusing the ozone gas.

In addition, because high concentrations of ozone have an adverse effect on the human body, after ozone gas has been diffused into the room Z to perform virus decontamination, it is necessary to ventilate the room to reduce the ozone concentration to a level that does not affect the human body. In this case, too, by diagnosing the ventilation condition while analyzing the airflow condition in the room Z, as in the first embodiment, it is possible to suggest an optimal situation to the user.

According to the second embodiment described above, it is possible to provide the user with information indicating the state of ozone gas diffusion into the room from a location remote from the managed room, and the improvements to the indoor conditions based on this ozone gas diffusion state, in an easy-to-understand manner.

In the second embodiment described above, a case where ozone gas is used to decontaminate a room is described, but this is not limited to this agent and shape, and ozone or other agents, such as alcohol agents, may be diffused in other shapes, such as fine bubble water, droplets, or aerosols.

Although several embodiments have been described, the embodiments can be modified or varied based on the above disclosure. All components of the above embodiments and all features described in the claims may be individually extracted and combined, unless they are mutually inconsistent.

Reference Signs List 1A, 1B Indoor environment management support system 10 Mobile terminal 11 Camera device 12 First input unit 13 Terminal communication unit 14 First display unit 15 Information processing unit 20 Communication network 30 Indoor environment management support device 31 Support device communication unit 32 CPU
33 Second display unit 34 Second input unit 321 Imaging information acquisition unit 322 Three-dimensional model information generation unit 323 Analysis unit 324 Diagnosis result information generation unit

Claims (4)

an image information acquisition unit that acquires two-dimensional image information of the interior of a managed object;
a three-dimensional model information generating unit that generates three-dimensional model information of the room from the two-dimensional imaging information acquired by the imaging information acquiring unit;
an analysis unit that analyzes a state of airflow in the room, including a change in a temperature field in the room , by using the three-dimensional model information generated by the three-dimensional model information generation unit;
a diagnostic result information generating unit that generates diagnostic result information including information indicating proposed changes to the indoor condition that are effective for improving the airflow condition, which are input based on the information analyzed by the analyzing unit after diagnosing that the indoor airflow condition needs to be improved, and image information and numerical information indicating a predicted improvement status of the indoor airflow condition as a result of the changes;
The analysis unit replaces information on changes in the temperature field in the room analyzed using the three-dimensional model information with information on changes in concentration of a specified substance due to the air flow that was present in the room at the start of the analysis, and analyzes the ventilation state of the room as the state of the air flow in the room . an image information acquisition unit that acquires two-dimensional image information of the interior of a managed object;
a three-dimensional model information generating unit that generates three-dimensional model information of the room from the two-dimensional imaging information acquired by the imaging information acquiring unit;
an analysis unit that analyzes an airflow state in the room by using the three-dimensional model information generated by the three-dimensional model information generation unit;
a diagnostic result information generating unit that generates diagnostic result information including information indicating proposed changes to the indoor condition that are effective for improving the airflow condition, which are input based on the information analyzed by the analyzing unit after diagnosing that the indoor airflow condition needs to be improved, and image information and numerical information indicating a predicted improvement status of the indoor airflow condition as a result of the changes;
The analysis unit uses the three-dimensional model information to analyze the state of ozone gas diffusion in the room as the state of airflow in the room when ozone gas is supplied into the room, taking into account the state of ozone gas adhesion to objects including walls in the room . The indoor environment management support device,
Acquire two-dimensional image information of the room to be managed,
generating three-dimensional model information of the room from the acquired two-dimensional imaging information;
Using the generated three-dimensional model information, an airflow state in the room, including a change in a temperature field in the room, is analyzed, and further, the information on the change in the temperature field in the room is replaced with information on a change in concentration of a predetermined substance due to the air flow that existed in the room at the start of the analysis, and the ventilation state of the room is analyzed as the airflow state in the room.
An indoor environment management support method that generates diagnostic result information including information indicating proposed changes to the indoor conditions that are effective in improving the airflow conditions that have been diagnosed as needing improvement based on analyzed information and input, and image information and numerical information indicating the predicted improvement in the indoor airflow conditions as a result of the changes. The indoor environment management support device,
Acquire two-dimensional image information of the room to be managed,
generating three-dimensional model information of the room from the acquired two-dimensional imaging information;
When ozone gas is supplied into the room, the generated three-dimensional model information is used to analyze an ozone gas diffusion state in the room as an airflow state in the room, taking into account an adhesion state of the ozone gas to objects including walls in the room;
An indoor environment management support method that generates diagnostic result information including information indicating proposed changes to the indoor conditions that are effective in improving the airflow conditions that have been diagnosed as needing improvement based on analyzed information and input, and image information and numerical information indicating the predicted improvement in the indoor airflow conditions as a result of the changes .

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