Ventilation control system, ventilation control device, and ventilation control program

Abstract

To provide a ventilation control system, a ventilation control device and a ventilation control program for improving convenience of a ventilation device for performing ventilation in a room of a building structure.SOLUTION: A ventilation control system 1 includes an existing ventilation device 2, an existing ventilation device operation part 200, and a ventilation control device 3 that is newly established between the ventilation device 2 and the ventilation device operation part 200. The ventilation control device 3 includes device information identification means for identifying device information corresponding control information acquired from the ventilation device operation part 200 after referring to a first database, setting means for acquiring operation information and control information corresponding to the identified device information from a second database after referring to the second database, and setting the operation information and the control information in the ventilation control device 3, information acquisition means for acquiring indoor sensor information, management setting means for setting a control condition, and determination means for determining a degree of need for control of the ventilation device 2, and the system outputs the control information to the ventilation device 2 on the basis of the degree of need.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a ventilation control system, a ventilation control device, and a ventilation control program for controlling a ventilation device that ventilates the interior of an architectural structure. Background Art

[0002] In recent years, as an operation means for air conditioners installed in architectural structures, control programs for operation via communication devices such as smartphones have been developed. For example, Patent Document 1 discloses a device control system that controls a control target device such as an air conditioner using a control program downloaded by a remote terminal connectable to a communication network. Prior Art Literature Patent Literature

[0003] Patent Document 1 Japanese Unexamined Patent Application Publication No. 2004-289505 Summary of the Invention Problems to be Solved by the Invention

[0004] However, when controlling a ventilation device using the technology disclosed in Patent Document 1, the ventilation device needs to be constantly connected to the communication network in order to receive various requests via the communication network. For this reason, for example, existing ventilation devices installed in buildings that do not support connection with remote terminals cannot be targeted for control. Further, when the corresponding control program differs depending on the type of ventilation device (such as ventilation fans, dampers, and air conditioners), it is necessary to prepare a plurality of control programs, which gives rise to a concern that management becomes complicated.

[0005] Therefore, the present invention was devised in view of the above-mentioned problems, and its objective is to provide a ventilation control system, a ventilation control device, and a ventilation control program that improve the convenience of ventilation devices for ventilating the interior of building structures. [Means for solving the problem]

[0006] According to the ventilation control system of the first invention, the system comprises an existing ventilation device for ventilating a room, an existing ventilation device operation unit that outputs control information for controlling the ventilation device, and a ventilation control device newly installed between the ventilation device and the ventilation device operation unit, wherein the ventilation control device refers to a first database in which reference control information including control information for the ventilation device and reference device information including device information for the ventilation device are pre-linked and stored, and then identifies device information corresponding to the control information obtained from the ventilation device operation unit, and refers to a second database in which reference operation information including operation information indicating the operation content of the ventilation device and reference control information including control information for the ventilation device are pre-linked and stored for each device information of the ventilation device, and then identifies the device information identified by the device information identification means. The ventilation control device comprises: setting means for acquiring operation information and control information corresponding to device information from the second database and setting the acquired operation information and control information to the ventilation control device; information acquisition means for acquiring various information including at least one of the following: indoor information, outdoor information, performance information, indoor sensor information, and outdoor sensor information related to the room or the ventilation device; management setting means for setting control conditions for automatically controlling the ventilation device; and determination means for determining the degree of necessity for controlling the ventilation device based on the various information acquired by the information acquisition means and the control conditions set by the management setting means, and outputting the control information set by the setting means to the ventilation device based on the degree of necessity determined by the determination means.

[0007] According to the ventilation control system of the second invention, in the first invention, the management setting means sets the control conditions based on the various information acquired by the information acquisition means.

[0008] According to the ventilation control system of the third invention, in the first or second invention, the management setting means is characterized in that it uses a judgment model that uses the degree of necessity for the various types of information as training data, and sets the control conditions according to the degree of necessity output from the judgment model when newly acquired various types of information are input.

[0009] According to the ventilation control system of the fourth invention, in the first or second invention, the information acquisition means is characterized by referring to preset calibration conditions and performing calibration on the acquired various types of information.

[0010] According to the ventilation control device of the 5th invention, a ventilation control device newly installed between an existing ventilation device that ventilates a room and an existing ventilation device operation unit that outputs control information for controlling the ventilation device, includes: a device information identification means that identifies device information corresponding to the control information obtained from the ventilation device operation unit after referring to a first database in which reference control information including ventilation device control information and reference device information including ventilation device information are pre-linked and stored; and a second database in which reference operation information including operation information indicating the operation content of the ventilation device and reference control information including ventilation device control information are pre-linked and stored for each device information of the ventilation device, and then the device information identification means identifies operation information and control information corresponding to the device information identified by the device information identification means. The ventilation control device comprises: setting means for obtaining information from the second database and setting the obtained operation information and control information to the ventilation control device; information acquisition means for obtaining various information including at least one of the following: indoor information, external information, performance information, indoor sensor information, and outdoor sensor information related to the indoor or ventilation device; management setting means for setting control conditions for automatically controlling the ventilation device; and determination means for determining the degree of necessity for controlling the ventilation device based on the various information obtained by the information acquisition means and the control conditions set by the management setting means, and outputting the control information set by the setting means to the ventilation device based on the degree of necessity determined by the determination means.

[0011] According to the ventilation control program of the sixth invention, in a ventilation control program for controlling a ventilation control system comprising an existing ventilation device for ventilating a room, an existing ventilation device operation unit that outputs control information for controlling the ventilation device, and a ventilation control device newly installed between the ventilation device and the ventilation device operation unit, the program includes: a device information identification step that identifies device information corresponding to the control information obtained from the ventilation device operation unit after referring to a first database in which reference control information including control information for the ventilation device and reference device information including device information for the ventilation device are pre-linked and stored; and a second database in which reference operation information including operation information indicating the operation content of the ventilation device and reference control information including control information for the ventilation device are pre-linked and stored for each device information of the ventilation device. The above is characterized by causing a computer to execute the following steps: a setting step in which operation information and control information corresponding to the device information identified in the above device information identification step are obtained from the second database and the acquired operation information and control information are set for the ventilation control device; an information acquisition step in which various information including at least one of the following information related to the room or the ventilation device: room information, external information, performance information, room sensor information, and outdoor sensor information; and a determination step in which the computer determines the degree to which control of the ventilation device is necessary based on the various information obtained in the information acquisition step and the pre-set control conditions for automatically controlling the ventilation device, and outputs the control information set in the setting step to the ventilation device based on the determined degree to which control is necessary. [Effects of the Invention]

[0012] According to the first to fourth inventions, the ventilation control system includes a device information identification means for identifying device information corresponding to control information acquired from a ventilation device operation unit, and a setting means for acquiring operation information and control information corresponding to the device information identified by the device information identification means from a second database, and setting the acquired operation information and control information to the ventilation control device. Therefore, the ventilation device can be controlled regardless of the type, manufacturer, model number, etc. This improves the convenience of the ventilation device.

[0013] According to the fifth invention, the ventilation control device includes a device information identification means for identifying device information corresponding to control information acquired from a ventilation device operation unit, and a setting means for acquiring operation information and control information corresponding to the device information identified by the device information identification means from a second database, and setting the acquired operation information and control information for the ventilation control device. Therefore, the ventilation device can be controlled regardless of the type, manufacturer, model number, etc. This improves the convenience of the ventilation device.

[0014] According to the sixth invention, the ventilation control program causes a computer to perform the following steps: an equipment information identification step to identify equipment information corresponding to control information acquired from the ventilation device operation unit; and a setting step to acquire operation information and control information corresponding to the equipment information identified by the equipment information identification means from a second database, and to set the acquired operation information and control information to the ventilation control device. Therefore, the ventilation device can be controlled regardless of the type, manufacturer, model number, etc. This makes it possible to provide a ventilation device with improved convenience. [Brief explanation of the drawing]

[0015] [Figure 1] Figure 1 is a schematic diagram showing an example of a ventilation control system in the first embodiment of the present invention. [Figure 2] Figure 2 is a schematic diagram showing an example of a connection method for a ventilation control system in the first embodiment of the present invention. [Figure 3] Figure 3 is a schematic diagram showing a modified example of the connection method of the ventilation control system in the first embodiment of the present invention. [Figure 4] Figure 4(a) is a schematic diagram showing an example of the configuration of a ventilation control device in the first embodiment of the present invention, and Figure 4(b) is a schematic diagram showing an example of a detailed configuration of a ventilation control device in the first embodiment of the present invention. [Figure 5] Figure 5 is a schematic diagram showing a modified example of the ventilation control system in the first embodiment of the present invention. [Figure 6]FIG. 6 is a flowchart showing an example of the operation of the ventilation control system according to the first embodiment of the present invention. [Figure 7] FIG. 7 is a schematic diagram showing an example of information related to the ventilation control system according to the first embodiment of the present invention. [Figure 8] FIGS. 8(a) to 8(b) are schematic diagrams showing an example of a database related to the ventilation control system according to the first embodiment of the present invention. [Figure 9] FIGS. 9(a) to 9(b) are schematic diagrams showing an example of a first database related to the ventilation control system according to the first embodiment of the present invention. [Figure 10] FIGS. 10(a) to 10(c) are schematic diagrams showing an example of a second database related to the ventilation control system according to the first embodiment of the present invention. [Figure 11] FIGS. 11(a) to 11(b) are schematic diagrams showing an example of details of the second database related to the ventilation control system according to the first embodiment of the present invention. [Figure 12] FIG. 12 is a schematic diagram showing an example of a detailed configuration of the ventilation control device according to the second embodiment of the present invention. [Figure 13] FIG. 13 is a flowchart showing an example of the operation of the ventilation control system according to the second embodiment of the present invention. [Figure 14] FIG. 14 is a schematic diagram showing an example of a learning method for a learning model related to the ventilation control system according to the second embodiment of the present invention. [Figure 15] FIG. 15 is a schematic diagram showing an example of a detailed configuration of the ventilation control device according to the third embodiment of the present invention. [Figure 16] FIG. 16 is a flowchart showing an example of the operation of the ventilation control system according to the third embodiment of the present invention. [Figure 17] FIG. 17 is a schematic diagram showing an example of a learning method for a learning model related to the ventilation control system according to the third embodiment of the present invention. [Figure 18] FIG. 18 is a schematic diagram showing an example of a configuration of the ventilation control system according to the fourth embodiment of the present invention. [Figure 19] Figure 19 is a schematic diagram showing an example of an automatic control method for a ventilation control system in a fourth embodiment of the present invention. [Modes for carrying out the invention]

[0016] The embodiments illustrated below, applying the present invention, will be described with reference to the drawings.

[0017] (First embodiment: Ventilation control system 1) An example of the ventilation control system 1 in this embodiment will be described with reference to Figures 1 to 5. Figure 1 is a schematic diagram showing an example of the ventilation control system 1 in this embodiment. Figure 2 is a schematic diagram showing an example of the connection method of the ventilation control system 1 in this embodiment. Figure 3 is a schematic diagram showing a modified example of the connection method of the ventilation control system 1 in this embodiment. Figure 4(a) is a schematic diagram showing an example of the configuration of the ventilation control device 3 in this embodiment, and Figure 4(b) is a schematic diagram showing an example of a detailed configuration of the ventilation control device 3 in this embodiment. Figure 5 is a schematic diagram showing a modified example of the ventilation control system 1 in this embodiment.

[0018] As shown in Figure 1, the ventilation control system 1 comprises a ventilation device 2, a ventilation device operating unit 200, and a ventilation control device 3.

[0019] <Ventilation device 2> Ventilation device 2 is an existing device that ventilates the room. Ventilation device 2 is installed with a wired connection to the control unit. Examples of ventilation device 2 include a ventilation fan without a temperature control function. Alternatively, an air conditioner with a temperature control function may be used as ventilation device 2. Here, wired connection refers to a connection method for communication using a linear transmission path, and the same meaning is used hereafter. As a means of wired connection, for example, a known circuit connection cable can be used.

[0020] <<Ventilation device control unit 200>> The ventilation system control unit 200 is an existing control unit that outputs control information for controlling the ventilation system 2. The ventilation system control unit 200 is wired to the ventilation system 2. The ventilation system control unit 200 is, for example, an operation panel for operating the ventilation system 2.

[0021] <Ventilation control device 3> The ventilation control device 3 is newly installed between the existing ventilation device 2 and the existing ventilation device control unit 200. Here, "between the existing ventilation device 2 and the existing ventilation device control unit 200" does not refer to the physical arrangement of the ventilation control device 3, the ventilation device 2, and the ventilation device control unit 200, but rather to the fact that the ventilation device 2 and the ventilation device control unit 200 are wired together via the ventilation control device 3. The ventilation control device 3 is wired together with the ventilation device 2 so that it can send and receive various information. The ventilation control device 3 is wired together with the ventilation device control unit 200 so that it can send and receive various information.

[0022] The ventilation control device 3 is wired to the ventilation device 2 by, for example, as shown in Figure 2, by the positive terminal (P) of the ventilation control device 3 being wired to the positive terminal (P) of the ventilation device 2, and by the negative terminal (N) of the ventilation control device 3 being wired to the negative terminal (N) of the ventilation device 2. The ventilation control device 3 is wired to the ventilation device operation unit 200 by, for example, by the positive terminal (P) of the ventilation control device 3 being wired to the positive terminal (P) of the ventilation device operation unit 200, and by the negative terminal (N) of the ventilation control device 3 being wired to the negative terminal (N) of the ventilation device operation unit 200.

[0023] The ventilation control device 3 may be wired to the existing ventilation device 2 and the existing ventilation device control unit 200 by, for example, modifying and using an existing transmission line that wired-connects the existing ventilation device 2 and the existing ventilation device control unit 200. In this case, the ventilation control device 3 can be easily installed without the need for additional wiring work when newly installing it between the existing ventilation device 2 and the existing ventilation device control unit 200.

[0024] The ventilation control device 3 may be wired to a ventilation system 2 having an indoor unit 21 and an outdoor unit 22, as shown in Figure 3, for example. In this case, the positive terminal (P) of the ventilation control device 3 may be wired to a transmission line that wired the positive terminal (P) of the indoor unit 21 and the positive terminal (P) of the outdoor unit 22. The negative terminal (N) of the ventilation control device 3 may also be wired to a transmission line that wired the negative terminal (N) of the indoor unit 21 and the negative terminal (N) of the outdoor unit 22.

[0025] As the ventilation control device 3, a known single-board computer such as Raspberry Pi (registered trademark) is used. The ventilation control device 3 comprises, for example, a chassis 30, a CPU 301, a ROM (Read Only Memory) 302, a RAM (Random Access Memory) 303, a storage unit 304, and I / F 305~307, as shown in Figure 4(a). Each component 301~307 is connected by an internal bus 310.

[0026] The CPU 301 controls the entire ventilation control device 3. The ROM 302 stores the operating code of the CPU 301. The RAM 303 is a work area used when the CPU 301 is operating. The storage unit 304 stores various information such as databases and learning data. As the storage unit 304, a data storage device such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive) can be used. The ventilation control device 3 may also have a GPU (Graphics Processing Unit), for example (not shown).

[0027] The ventilation control device 3 may use an external storage medium, distinct from the ventilation control device 3, instead of the storage unit 304, or in combination with the storage unit 304. Here, the external storage medium may be, for example, a known personal computer, which may be connected to the ventilation control device 3 via a communication network. The communication network may be, for example, the Internet network. The communication network may consist of a so-called optical fiber communication network, and may be implemented using known communication technologies such as a wired communication network or a wireless communication network such as LTE (Long Term Evolution).

[0028] I / F305 is an interface for sending and receiving various information with the ventilation device 2 or the ventilation device control unit 200, etc., as needed. I / F306 is an interface for sending and receiving information with the input unit 308. For example, a keyboard is used as the input unit 308, and the operator inputs control commands and other information via the input unit 308. I / F307 is an interface for sending and receiving various information with the display unit 309. The display unit 309 displays various information stored in the storage unit 304, or evaluation results, etc. A display is used as the display unit 309, and if it is a touch panel type, it is provided together with the input unit 308.

[0029] The ventilation control device 3 may be connected to a terminal 311 via a wireless communication network 4, as shown in Figure 5, and operated via the terminal 311. In this case, the terminal 311 may be used as an input unit 308 and a display unit 309. As the terminal 311, for example, a known tablet terminal or smartphone may be used.

[0030] Next, we will describe the detailed configuration of the ventilation control device 3.

[0031] Figure 4(b) is a schematic diagram showing an example of the detailed configuration of the ventilation control device 3. The ventilation control device 3 includes, for example, a communication means 31, a storage means 32, a device information identification means 33, and a setting means 34. The configurations shown in Figure 4(b) are realized by the CPU 301 executing a program stored in the storage unit 304, etc., using the RAM 303 as a working area.

[0032] <<Communication method 31>> The communication means 31 receives information transmitted from, for example, the ventilation device operation unit 200. The communication means 31 also receives control information for controlling the ventilation device 2 from the ventilation device operation unit 200.

[0033] The communication means 31 transmits information to the ventilation device 2, for example. The communication means 31 transmits control information to the ventilation device 2, for example, to control the ventilation device 2.

[0034] The communication means 31 may, for example, transmit the received, transmitted, or generated information to an external storage medium separate from the ventilation control device 3 in order to store the information in the external storage medium.

[0035] <<Storage means 32>> The storage means 32 stores, for example, information received by the communication means 31 in a database stored in the storage unit 304. The storage means 32 retrieves, for example, various data stored in the database stored in the storage unit 304 as needed. The storage means 32 stores, for example, various data acquired or generated by each of the components 31, 33, and 34 in a database stored in the storage unit 304 as needed.

[0036] <<Device information identification means 33>> The device information identification means 33 identifies device information corresponding to control information for controlling the ventilation device 2. Here, device information includes, for example, information on the type of ventilation device (ventilation fan, air conditioner, etc.), manufacturer information, model number information, etc. The device information identification means 33 identifies device information corresponding to control information for controlling the ventilation device 2 after referring to a database stored in, for example, the storage unit 304. The device information identification means 33 may also identify device information corresponding to control information for controlling the ventilation device 2 after referring to a database stored in, for example, an external storage medium.

[0037] <<Setting means 34>> The setting means 34 acquires operation information and control information corresponding to the device information of the ventilation device 2 identified by the device information identification means 33, and sets them for the ventilation control device 3. Here, operation information is information indicating the operation content of the ventilation device, and includes "start" and "increase the airflow rate by one level". The setting means 34 acquires operation information and control information corresponding to the device information identified by the device information identification means 33 after referring to a database stored in, for example, the storage unit 304. The setting means 34 may also acquire operation information and control information corresponding to the device information identified by the device information identification means 33 after referring to a database stored in, for example, an external storage medium.

[0038] (First embodiment: An example of the operation of the ventilation control system 1) Next, an example of the operation of the ventilation control system 1 in this embodiment will be described with reference to Figures 6 to 11. Figure 6 is a flowchart showing an example of the operation of the ventilation control system 1 in this embodiment. Figure 7 is a schematic diagram showing an example of information related to the ventilation control system 1 in this embodiment. Figures 8(a) to 8(b) are schematic diagrams showing an example of a database related to the ventilation control system 1 in this embodiment. Figures 9(a) to 9(b) are schematic diagrams showing an example of a first database related to the ventilation control system 1 in this embodiment. Figures 10(a) to 10(c) are schematic diagrams showing an example of a second database related to the ventilation control system 1 in this embodiment. Figures 11(a) to 11(b) are schematic diagrams showing an example of details of the second database related to the ventilation control system 1 in this embodiment.

[0039] The ventilation control system 1 is executed, for example, via a ventilation control program installed in the ventilation control device 3. The operation of the ventilation control system 1 includes, for example, a device information identification step S110 and a setting step S120, as shown in Figure 6.

[0040] <Device Information Identification Step S110> In the device information identification step S110, the ventilation control device 3 obtains control information D33' included in control information D33 from the ventilation device operation unit 200. In the device information identification step S110, the device information identification means 33 refers to the first database 61 and then identifies the device information D31 corresponding to the control information D33 obtained by the ventilation control device 3 from the ventilation device operation unit 200. In the device information identification step S110, the ventilation control system 1 may, for example, obtain operation information D32 of the ventilation device 2 along with the device information D31.

[0041] <<Device information D31>> Device information D31 includes information about the ventilation device 2. Device information D31 includes, for example, information about the type of ventilation device 2 (ventilation fan, air conditioner, etc.), manufacturer information, model number information, etc., as shown in Figure 7.

[0042] <<Operation information D32>> Operation information D32 includes information indicating the operation of the ventilation device 2. Operation information D31 includes information indicating the operation of the ventilation device 2, such as "start" or "increase the airflow rate by one level". In this embodiment, the operation information D32 acquired by the various devices is not limited to acquiring all information indicating the operation of the ventilation device 2, but also includes a form in which at least a part of the information indicating the operation of the ventilation device 2 is acquired as needed.

[0043] <<Control Information D33>> Control information D33 includes information for controlling the ventilation device 2. Control information D33 includes, for example, signal information for controlling the ventilation device 2. In this embodiment, among the control information D33, the control information D33 that the ventilation control device 3 acquires from the ventilation device operation unit 200 is described as control information D33'. Control information D33' is included in control information D33 and is the same type of information as control information D33. Furthermore, in this embodiment, the control information D33 acquired by various devices is not limited to a form in which all information for controlling the ventilation device 2 is acquired, but includes a form in which at least a part of the information for controlling the ventilation device 2 is acquired as needed.

[0044] <<First Database 61>> The first database 61 is stored, for example, in the ventilation control device 3. The first database 61 is stored, for example, in the storage unit 304 included in the ventilation control device 3. The first database 61 may also be stored, for example, on an external storage medium.

[0045] The first database 61 stores, for example, reference device information D61-1, which includes device information D31 of ventilation device 2, and reference control information D63-1, which includes control information D33 of ventilation device 2, in a pre-associated manner. The first database 61 includes, for example, as shown in Figure 8(a), a device information table T611 for storing reference device information D61-1 and a control information table T613 for storing reference control information D61-3.

[0046] <<Device Information Table T611>> The device information table T611 stores reference device information D61-1, for example, as shown in Figure 9(a).

[0047] <<Reference device information D61-1>> Reference device information D61-1 is stored, for example, in device information table T611. Reference device information D61-1 includes, for example, device information for ventilation devices. Reference device information D61-1 includes, for example, information on the type of ventilation device (ventilation fan, air conditioner, etc.), manufacturer information, model number information, etc. Reference device information D61-1 includes, for example, device information D31.

[0048] <<Control Information Table T613>> The control information table T613 stores the reference control information D63-1, for example, as shown in Figure 9(b).

[0049] <<Reference control information D63-1>> Reference control information D63-1 is stored, for example, in the control information table T613. Reference control information D63-1 includes, for example, control information for a ventilation system. Reference control information D63-1 includes, for example, signal information for controlling a ventilation system. Reference control information D63-1 includes, for example, control information D33.

[0050] The control information contained in the reference control information D63-1 is linked to, for example, the device information contained in the reference device information D61-1. For example, the model number information "A123" from manufacturer A is linked to the signal information "10XXX" for controlling the model number information "A123". Also, the model number information "B456" from manufacturer B is linked to the signal information "20XXX" for controlling the model number information "B456". In this way, the reference control information D63-1 and the reference device information D61-1 are linked.

[0051] <Setting step S120> In the setting step S120, the setting means 34 refers to the second database 62 and obtains operation information D32 and control information D33 corresponding to the device information D31 identified by the device information identification means 33 in the device information identification step S110, and sets them for the ventilation control device 3. In this case, the ventilation device 2 can be controlled regardless of the type, manufacturer, model number, etc. of the ventilation device 2. This improves the convenience of the ventilation device 2. Here, the control information D33 obtained by the setting means 34 in the setting step S120 is not limited to obtaining all the control information for controlling the ventilation device 2, but may, for example, only a part of the control information for controlling the ventilation device 2 be obtained, and the same applies hereinafter. For example, in the setting step S120, the setting means 34 may acquire only the same control information as the control information D33' acquired by the ventilation control device 3 from the ventilation device operation unit 200 in the device information identification step S110, or it may acquire only a portion of the control information included in the control information D33 that includes the control information D33', or it may acquire only a portion of the control information included in the control information D33 that excludes the control information D33'. Furthermore, the operation information D32 acquired by the setting means 34 in the setting step S120 is the same as the control information D33, and is not limited to acquiring all the information indicating the operation content of the ventilation device 2, but may acquire only a portion of the information indicating the operation content of the ventilation device 2, and the same applies hereinafter.

[0052] <<Second Database 62>> The second database 62 is stored, for example, in the ventilation control device 3. The second database 62 is stored, for example, in the storage unit 304 included in the ventilation control device 3. The second database 62 may be stored, for example, on an external storage medium. The second database 62 may be stored, for example, on the same storage medium as the first database 61, or on a different storage medium.

[0053] The second database 62 stores, for example, reference operation information D62-2, which includes operation information D32 of the ventilation device 2, and reference control information D63-2, which includes control information D33 of the ventilation device 2, pre-associated with each reference device information D61-2, which includes device information D31 of the ventilation device 2.

[0054] The second database 62 includes, for example, a device information table T621 for storing reference device information D61-2, an operation information table T622 for storing reference operation information D62-2, and a control information table T623 for storing reference control information D63-2, as shown in Figure 8(b).

[0055] <<Device Information Table T621>> The device information table T621 stores reference device information D61-2, for example, as shown in Figure 10(a).

[0056] <<Reference device information D61-2>> Reference device information D61-2 is stored, for example, in the device information table T621. Reference device information D61-2 contains, for example, the same information as reference device information D61-1.

[0057] <<Operation Information Table T622>> The operation information table T622 stores reference operation information D62-2, for example, as shown in Figure 10(b).

[0058] <<Reference operation information D62-2>> Reference operation information D62-2 is stored, for example, in the operation information table T622. Reference operation information D62-2 includes, for example, operation information indicating the operation details of a ventilation device. Reference control information D62-2 includes, for example, operation information D32.

[0059] <<Control Information Table T623>> The control information table T623 stores the reference control information D63-2, for example, as shown in Figure 10(c).

[0060] <<Reference control information D63-2>> Reference control information D63-2 is stored, for example, in the control information table T623. Reference control information D63-2 contains, for example, the same information as reference control information D63-1.

[0061] Next, using Figure 11, we will explain the correspondence between the reference device information D61-2 in the second database 62 and the reference operation information D62-2 and reference control information D63-2 that have been pre-associated and stored.

[0062] Reference device information D61-2 includes a library number assigned to each piece of device information, such as type information, manufacturer information, and model number information, as shown in Figure 11(a), for example. Reference device information D61-2 includes, for example, type information "ventilation fan", manufacturer information "Company A", model number information "A123", and library number "1".

[0063] In this case, for example, as shown in Figure 11(b), the library number "1" included in the reference device information D61-2 is linked to the operation information "Start" for the model number information "A123" included in the reference operation information D62-2, and the signal information "10001" included in the reference control information D63-2 is linked to control the model number information "A123" to execute the operation "Start". Also, for example, the library number "1" included in the reference device information D61-2 is linked to the operation information "Increase airflow by one level" for the model number information "A123" included in the reference operation information D62-2, and the signal information "10002" is linked to control the model number information "A123" to execute the operation "Increase airflow by one level".

[0064] In the method described above, the reference operation information D62-2 and the reference control information D63-2 are pre-associated and stored in the second database 62 for each reference device information D61-2. Note that the reference operation information D62-2 and the reference control information D63-2 may be associated with, for example, the model number information "A123" instead of using the library number included in the reference device information D61-2.

[0065] After performing each of the steps described above, the operation of the ventilation control system 1 in this embodiment is completed. Note that the ventilation control system 1 may, for example, repeat each of the steps described above.

[0066] According to this embodiment, the ventilation control system 1 includes a device information identification means 33 that identifies device information D31 corresponding to control information D33' acquired from the ventilation device operation unit 200, and a setting means 34 that acquires operation information D32 and control information D33 corresponding to the device information D31 identified by the device information identification means 33, and sets them for the ventilation control device 3. Therefore, the ventilation device 2 can be controlled regardless of the type, manufacturer, model number, etc. of the ventilation device 2. This improves the convenience of the ventilation device 2.

[0067] According to this embodiment, the ventilation control device 3 includes a device information identification means 33 that identifies device information D31 corresponding to control information D33' acquired from the ventilation device operation unit 200, and a setting means 34 that acquires operation information D32 and control information D33 corresponding to the device information D31 identified by the device information identification means 33, and sets them for the ventilation control device 3. Therefore, the ventilation device 2 can be controlled regardless of the type, manufacturer, model number, etc. of the ventilation device 2. This improves the convenience of the ventilation device 2.

[0068] According to this embodiment, the ventilation control program causes the computer to execute a device information identification step S110 to identify device information D31 corresponding to control information D33' acquired from the ventilation device operation unit 200, and a setting step S120 to acquire operation information D32 and control information D33 corresponding to the device information D31 identified in the device information identification step S110, and to set them for the ventilation control device 3. Therefore, the ventilation device 2 can be controlled regardless of the type, manufacturer, model number, etc. This makes it possible to provide a ventilation device 2 with improved convenience.

[0069] (Second embodiment: Ventilation control system 1) An example of the ventilation control system 1 in this embodiment will be described with reference to Figure 12. Figure 12 is a schematic diagram showing an example of the detailed configuration of the ventilation control device 3 in this embodiment. This embodiment differs from the first embodiment in that the ventilation control device 3 further comprises a learning data acquisition means 35 and a device information model generation means 36, and the device information identification means 33 identifies the device information D31 after referring to the learning model. The same configuration as described above will not be explained.

[0070] <Ventilation control device 3> The ventilation control device 3 further comprises, for example, a learning data acquisition means 35 and a device information model generation means 36, as shown in Figure 12.

[0071] <<Device information identification means 33>> The device information identification means 33 identifies device information corresponding to the control information acquired from the ventilation device operation unit 200, for example, by referring to a learning model pre-stored in the first database 61.

[0072] <<Method 35 for acquiring learning data>> The learning data acquisition means 35, for example, reproduces and generates the acquired control information as reproduced control information, and acquires the control information including the generated reproduced control information, as well as the device information of the ventilation system, as learning data. The reproduced control information will be explained later.

[0073] <<Device Information Model Generation Means 36>> The device information model generation means 36 generates a learning model by machine learning based on the learning data acquired by the learning data acquisition means 35, for example. The device information model generation means 36 generates the device information model described later based on the learning data acquired by the learning data acquisition means 35, for example, which includes reproduction control information and device information.

[0074] (Second embodiment: An example of the operation of the ventilation control system 1) Next, an example of the operation of the ventilation control system 1 in this embodiment will be described with reference to Figures 13 and 14. Figure 13 is a flowchart illustrating an example of the operation of the ventilation control system 1 in this embodiment. Figure 14 is a schematic diagram showing an example of a learning method for the learning model related to the ventilation control system 1 in this embodiment.

[0075] The operation of the ventilation control system 1 further includes, for example, a learning data acquisition step S130 and a device information model generation step S140, as shown in Figure 13.

[0076] <Training data acquisition step S130> In the learning data acquisition step S130, the learning data acquisition means 35 reproduces and generates control information D33' acquired from the ventilation device operation unit 200 and acquires learning data D71 which includes reproduced control information that corresponds to the operation information D32 of the ventilation device 2 and device information D31 of the ventilation device 2 from the reproduced control information output to the ventilation device 2.

[0077] Here, the reproduced control information is newly generated control information that mimics, for example, the signal information contained in the control information D33' of the ventilation device 2. Here, the control information D33' is information for controlling the ventilation device 2 so that the operation indicated by the operation information D32 is performed. However, among the generated reproduced control information, there are cases where the ventilation device 2 cannot be controlled so that the operation indicated by the operation information D32 is performed. For this reason, the learning data acquisition means 35 may output the generated reproduced control information to the ventilation device 2 and acquire only the reproduced control information that can control the ventilation device 2 so that the operation indicated by the operation information D32 is performed as learning data D71. The learning data acquisition means 35 may also acquire only the reproduced control information in which the operation of the ventilation device 2 has confirmed that the ventilation device 2 can be controlled so that the operation indicated by the operation information D32 is performed as learning data D71.

[0078] <<Training Data D71>> The training data D71 is used for machine learning to generate the device information model 81 described later, as shown in Figure 14, for example. The training data D71 is a dataset consisting of, for example, input data D711 and output data D712 as a pair.

[0079] <Input Data D711> Input data D711 is used as part of the training data for machine learning to generate the device information model 81. Input data D711 includes, for example, pre-acquired reference control information D63-1.

[0080] <Output Data D712> The output data D712 is used as part of the training data D71 used for machine learning to generate the device information model 81. The output data D712 includes, for example, previously acquired reference device information D61-1.

[0081] A combination of input data D711 and output data D712 included in the learning data D71 includes, for example, a combination in which reference control information D63-1 included in input data D711 is linked to reference device information D61-1 included in output data D712. An example of a combination in which reference control information D63-1 and reference device information D61-1 are linked is a combination in which control information indicating signal information "10XXX" for controlling the model number "A123" of ventilation device 2 is linked to device information including the model number "A123" of ventilation device 2. In addition to the above, for example, control information indicating signal information "10XXX" for controlling the model number "A123" may be linked to device information including the manufacturer "Company A" of the model number "A123" of ventilation device 2.

[0082] By using the device information model 81 generated using the training data D71, it becomes possible to identify the device information D31 corresponding to the control information D33' acquired from the ventilation device operation unit 200.

[0083] <Device information model generation step S140> In the device information model generation step S140, the device information model generation means 36 generates a device information model 81 by machine learning based on the learning data D71 acquired by the learning data acquisition means 35. That is, it is possible to generate a learning model corresponding to ventilation devices 2 for which learning data D71 cannot be obtained. Therefore, it is possible to identify the device information D31 of various ventilation devices 2. This improves the usability of various ventilation devices 2.

[0084] <<Device Information Model 81>> The device information model 81 is generated, for example, by machine learning using training data D71. The device information model 81 is generated using multiple training data sets D71, where each training data set consists of, for example, input data D711 and output data D712. The device information model 81 is stored, for example, in the first database 61. The device information model 81 is analyzed by regression analysis, for example, with input data D711 as the explanatory variable and output data D712 as the dependent variable, and a regression model is generated based on the analysis results.

[0085] The device information model 81 includes, for example, a device information correlation 810 that has a device information correlation degree between input data D711 and output data D712. The device information correlation 810 may be generated, for example, by machine learning using multiple training data D71. The device information correlation degree indicates the degree of connection between input data D711 and output data D712, and for example, a higher device information correlation degree indicates a stronger connection between the data. The device information correlation degree may be expressed as three or more values ​​(three or more levels), such as a percentage, or as two or more values ​​(two or more levels).

[0086] The device information correlation 810 is constructed, for example, by the degree of connection between many-to-many information (multiple input data D711 pairs with multiple output data D712). The device information correlation 810 is updated as appropriate during the machine learning process and represents, for example, an optimized function (classifier) ​​based on the multiple input data D711 and the multiple output data D712. The device information correlation 810 may have multiple device information correlation degrees, for example, indicating the degree of connection between each data. The device information correlation degree can be associated with weight variables, for example, when the database is constructed using a neural network.

[0087] Therefore, the ventilation device control system 1 selects output data D712 that is suitable for input data D711 using, for example, device information correlation 810 that takes into account all the results determined by the classifier. This makes it possible to quantitatively select output data D712 that is suitable for input data D711, not only when the input data D711 is the same as or similar to output data D712, but also when they are dissimilar.

[0088] The device information correlation 810 may, for example, indicate the degree of connection between multiple input data D711 and multiple output data D712. In this case, by using the device information correlation 810, the degree of relationship between multiple output data D712 (for example, output data A and output data B) can be associated and stored for each of the multiple input data D711 (for example, input data A and input data B). Therefore, for example, multiple input data D711 can be associated with one output data D712 via the device information correlation 810. This enables the selection of output data D712 from multiple perspectives in relation to input data D711.

[0089] The device information correlation 810 has multiple device information correlation degrees, for example, linking each input data D711 to each output data D712. The device information correlation degree is expressed in three or more stages, such as a percentage, a 10-point scale, or a 5-point scale, and is represented by line characteristics (e.g., line thickness). For example, "input data A" contained in input data D711 shows a device information correlation degree AA "73%" between it and "output data A" contained in output data D712, and a device information correlation degree AB "12%" between it and "output data B" contained in output data D712. In other words, the "device information correlation degree" indicates the degree of connection between each data; for example, a higher device information correlation degree indicates a stronger connection between each data.

[0090] Furthermore, the device information correlation 810 may have at least one hidden layer between the input data D711 and the output data D712. The device information correlation degree described above is set in either the input data D711 or the hidden layer data, or both, and this becomes the weighting of each data, and the output is selected based on this. In addition, the output may be selected if this device information correlation degree exceeds a certain threshold.

[0091] The device information model 81 may include a trained model generated by machine learning using, for example, multiple training data D71. The trained model may represent a neural network model such as a CNN (Convolutional Neural Network), or a Support Vector Machine (SVM), etc. Deep learning can also be used as the machine learning method. Input data D711 may also be generated in a pseudo-way by using, for example, a Generative Adversarial Network (GAN) as the machine learning method.

[0092] By using the device information model 81, which includes such device information relationships 810, it becomes possible to identify the device information D31 that corresponds to the control information D33' acquired from the ventilation device operation unit 200.

[0093] <Device Information Identification Step S110> In the device information identification step S110, the device information identification means 33 refers to the device information model 81 generated by the device information model generation means 36 in the device information model generation step S140, and then identifies the device information D31 corresponding to the control information D33' acquired from the ventilation device operation unit 200. This improves the accuracy of identifying the device information D31 of the ventilation device 2. This further improves the convenience of the ventilation device 2.

[0094] According to this embodiment, the device information identification means 33 uses a dataset consisting of input data D711 containing reference control information D63-1 and output data D712 containing reference device information D61-1 as training data D71, and after referring to a device information model 81 generated by machine learning, it identifies the device information D31 corresponding to the control information D33' acquired from the ventilation device operation unit 200. This improves the accuracy of identifying the device information D31 of the ventilation device 2. As a result, the convenience of the ventilation device 2 can be further improved.

[0095] According to this embodiment, the ventilation control system 1 further includes a learning data acquisition means 35 that acquires learning data D71 which includes reconstructed control information D33' acquired from the ventilation device operation unit 200 and output to the ventilation device 2, the reconstructed control information corresponding to the operation information D32 of the ventilation device 2, and the device information D31 of the ventilation device 2; and a device information model generation means 36 that generates a device information model 81 by machine learning based on the learning data D71 acquired by the learning data acquisition means 35. In other words, it is possible to generate a learning model corresponding to a ventilation device 2 for which learning data cannot be obtained. As a result, the device information D31 of various ventilation devices 2 can be identified. This improves the usability of various ventilation devices 2.

[0096] (Third embodiment: Ventilation control system 1) An example of the ventilation control system 1 in this embodiment will be described with reference to Figure 15. Figure 15 is a schematic diagram showing an example of the detailed configuration of the ventilation control device 3 in this embodiment. This embodiment differs from the first embodiment in that the ventilation control device 3 further comprises a learning data acquisition means 35 and a control information model generation means 37, and the setting means 34 acquires operation information D32 and control information D33 corresponding to the operation information D32 after referring to the learning model. Note that the same configuration as described above will not be explained.

[0097] <Ventilation control device 3> The ventilation control device 3 further comprises, for example, a learning data acquisition means 35 and a control information model generation means 37, as shown in Figure 15.

[0098] <Setting means 34> The setting means 34, for example, refers to a learning model pre-stored in the second database 62 and then acquires operation information corresponding to the device information identified by the device information identification means 33, and control information corresponding to that operation information. The setting means 34 then sets the acquired operation information and control information in the ventilation control device 3.

[0099] <Method 35 for acquiring learning data> The learning data acquisition means 35, for example, reproduces and generates the acquired control information as reproduced control information, and acquires the control information including the generated reproduced control information and the operation information of the ventilation device as learning data.

[0100] <Control information model generation means 37> The control information model generation means 37 generates a learning model by machine learning based on the learning data acquired by the learning data acquisition means 35, for example. The control information model generation means 37 generates a control information model, described later, based on the learning data acquired by the learning data acquisition means 35, for example, which includes reproduced control information and operation information.

[0101] (Third embodiment: An example of the operation of the ventilation control system 1) Next, an example of the operation of the ventilation control system 1 in this embodiment will be described with reference to Figures 16 and 17. Figure 16 is a flowchart showing an example of the operation of the ventilation control system 1 in this embodiment. Figure 17 is a schematic diagram showing an example of a learning method for the learning model related to the ventilation control system 1 in this embodiment.

[0102] The operation of the ventilation control system 1 further includes, for example, a learning data acquisition step S130 and a control information model generation step S150, as shown in Figure 16.

[0103] <Training data acquisition step S130> In the learning data acquisition step S130, the learning data acquisition means 35 reproduces and generates the control information D33' acquired from the ventilation device operation unit 200 and acquires learning data D72 which includes the reproduced control information that corresponds to the operation information D32 of the ventilation device 2, and the operation information D32 of the ventilation device 2, from the reproduced control information output to the ventilation device 2.

[0104] <<Training Data D72>> The training data D72 is used for machine learning to generate the control information model 82 described later, as shown in Figure 17, for example. The training data D72 is a dataset consisting of, for example, input data D721 and output data D722 as a pair.

[0105] <Input Data D721> Input data D721 is used as part of the training data for machine learning to generate the control information model 82. Input data D721 includes, for example, pre-acquired reference operation information D62-2.

[0106] <Output Data D722> The output data D722 is used as part of the training data D72 used in machine learning to generate the control information model 82. The output data D722 includes, for example, pre-acquired reference control information D63-2.

[0107] A combination of input data D721 and output data D722 included in the learning data D72 includes, for example, a combination in which reference operation information D62-2 included in input data D721 is linked to reference control information D63-2 included in output data D722. An example of a combination in which reference operation information D62-2 and reference control information D63-2 are linked is an operation information indicating the operation to "activate" ventilation device 2 model number "A123" and a control information indicating signal information "10XXX" for controlling the "activation" of ventilation device 2 model number "A123".

[0108] By using the control information model 82 generated using the training data D72, it becomes possible to obtain operation information D32 corresponding to the device information D31 identified by the device information identification means 33, and control information D33 corresponding to the operation information D32.

[0109] <Control information model generation step S150> In the control information model generation step S150, the control information model generation means 37 generates a control information model 82 by machine learning based on the learning data D72 acquired by the learning data acquisition means 35. In other words, it is possible to generate a learning model that corresponds to a ventilation device 2 for which learning data cannot be obtained. Therefore, even if the control information D33 of the ventilation device 2 is unknown, it is possible to generate new, more accurate control information D33. This makes it possible to improve the usability of a wider variety of ventilation devices 2.

[0110] <<Control Information Model 82>> The control information model 82 is generated, for example, by machine learning using training data D72. The control information model 82 is generated using multiple training data sets D72, for example, with each set consisting of input data D721 and output data D722 as training data D72. The control information model 82 is stored, for example, in a second database 62. The control information model 82 is analyzed by regression analysis, for example, with input data D721 as the explanatory variable and output data D722 as the dependent variable, and a regression model is generated based on the analysis results.

[0111] The control information model 82 includes a control information correlation 820, which has, for example, a degree of control information correlation between input data D721 and output data D722. The control information correlation 820 may be generated, for example, by machine learning using multiple training data D72. The degree of control information correlation indicates the degree of connection between input data D721 and output data D722; for example, a higher degree of control information correlation indicates a stronger connection between the data. The degree of control information correlation may be expressed as a percentage or more (three or more levels), or as a percentage or more (two or more levels).

[0112] The control information correlation 820 is constructed, for example, by the degree of connection between many-to-many information (multiple input data D721 pairs with multiple output data D722). The control information correlation 820 is updated as appropriate during the machine learning process and represents, for example, an optimized function (classifier) ​​based on the multiple input data D721 and the multiple output data D722. The control information correlation 820 may have multiple control information correlation degrees, for example, indicating the degree of connection between each data. The control information correlation degree can be associated with weight variables, for example, when the database is constructed using a neural network.

[0113] Therefore, the ventilation system control system 1 selects output data D722 that is suitable for input data D721 using, for example, a control information correlation 820 that takes into account all the results determined by the classifier. This makes it possible to quantitatively select output data D722 that is suitable for input data D721, not only when the input data D721 is the same as or similar to output data D722, but also when they are dissimilar.

[0114] The control information correlation 820 may, for example, indicate the degree of connection between multiple input data D721 and multiple output data D722. In this case, by using the control information correlation 820, the degree of relationship between multiple output data D722 (for example, output data A and output data B) can be associated and stored for each of the multiple input data D721 (for example, input data A and input data B). Therefore, for example, multiple input data D721 can be associated with one output data D722 via the control information correlation 820. This makes it possible to select output data D722 from multiple perspectives in relation to input data D721.

[0115] The control information correlation 820 has multiple control information correlation degrees, for example, linking each input data D721 to each output data D722. The control information correlation degree is expressed in three or more stages, such as a percentage, a 10-level scale, or a 5-level scale, and is represented by line characteristics (e.g., thickness). For example, "input data A" contained in input data D721 shows a control information correlation degree AA "73%" between it and "output data A" contained in output data D722, and a control information correlation degree AB "12%" between it and "output data B" contained in output data D722. In other words, the "control information correlation degree" indicates the degree of connection between each data; for example, a higher control information correlation degree indicates a stronger connection between each data.

[0116] Furthermore, the control information correlation 820 may have at least one hidden layer between the input data D721 and the output data D722. The control information correlation degree described above is set in either the input data D721 or the hidden layer data, or both, and this becomes the weighting of each data, and the output is selected based on this. In addition, the output may be selected when this control information correlation degree exceeds a certain threshold.

[0117] The control information model 82 may include a trained model generated by machine learning using, for example, multiple training data D72. The trained model may be a neural network model such as a CNN (Convolutional Neural Network), or a Support Vector Machine (SVM), etc. Deep learning can also be used as the machine learning method. Input data D721 may also be generated in a pseudo-way by using, for example, a Generative Adversarial Network (GAN) as the machine learning method.

[0118] By using a control information model 82 that includes such control information relationships 820, it becomes possible to obtain operation information D32 corresponding to the device information D31 identified by the device information identification means 33, and control information D33 corresponding to the operation information D32.

[0119] <Setting step S120> In the setting step S120, the setting means 34, after referring to the control information model 82 generated by the control information model generation means 37 in the control information model generation step S150, obtains operation information D32 corresponding to the device information D31 identified by the device information identification means 33, and control information D33 corresponding to said operation information D32. In this case, even if the control information D33 of the ventilation device 2 is unknown, new control information 2 can be generated. This improves the usability of various ventilation devices 2.

[0120] According to this embodiment, the setting means 34 uses a dataset consisting of input data D721 including reference operation information D62-2 and output data D722 including reference control information D63-2 as training data D72, and after referring to a control information model 82 generated by machine learning, it obtains operation information D32 corresponding to the device information D31 identified by the device information identification means 33, and control information D33 corresponding to said operation information D32. Therefore, even if the control information D33 of the ventilation device 2 is unknown, new control information D33 can be generated. This improves the usability of various ventilation devices 2.

[0121] According to this embodiment, the ventilation control system 1 further includes a learning data acquisition means 35 that acquires learning data D72 including the reproduced control information D33' obtained from the ventilation device operation unit 200 and the reproduced control information output to the ventilation device 2, which corresponds to the operation information D32 of the ventilation device 2, and the operation information D32; and a control information model generation means 37 that generates a control information model 82 by machine learning based on the learning data D72 acquired by the learning data acquisition means 35. In other words, it is possible to generate a learning model corresponding to a ventilation device 2 for which learning data cannot be obtained. Therefore, even if the control information D33 of the ventilation device 2 is unknown, it is possible to generate new, more accurate control information D33. This makes it possible to improve the usability of a wider variety of ventilation devices 2.

[0122] (Fourth embodiment: Ventilation control system 1) An example of the ventilation control system 1 in this embodiment will be described with reference to Figure 18. Figure 18 is a schematic diagram showing an example of the configuration of the ventilation control system 1 in this embodiment. This embodiment differs from the first embodiment in that the ventilation control system 1 further includes an information acquisition means and a determination means. Note that the same configuration as described above will not be explained.

[0123] <Ventilation control system 1> The ventilation control system 1 further comprises information acquisition means for acquiring various types of information and determination means for determining the degree to which control of the ventilation device 2 is necessary. The ventilation control system 1 may further comprise a data server for storing various types of information or control conditions, and management setting means for managing the ventilation control system 1.

[0124] <Information acquisition means> The information acquisition means acquires various types of information. The information acquisition means includes, for example, an indoor information acquisition means for acquiring indoor information, an external information acquisition means for acquiring external information, a performance information acquisition means for acquiring performance information, an indoor sensor information acquisition means for acquiring indoor sensor information, and an outdoor sensor information acquisition means for acquiring outdoor sensor information. Details of the various types of information will be described later. The information acquisition means may be provided separately from the ventilation control device 3, or it may be provided in the ventilation control device 3.

[0125] The information acquisition means may include, for example, a wireless communication control unit for transmitting the acquired information to any communication device. The wireless communication control unit may be connected to the information acquisition means by a wired connection and transmit the acquired information to a communication device connected to the wireless communication network. If the information acquisition means is distinguished from, for example, the ventilation control device 3, it may transmit the acquired information to the ventilation control device 3 via the wireless communication control unit. The information acquisition means may also transmit the acquired information to a data server described later, for example, via the wireless communication control unit.

[0126] <Judgment means> The determination means determines the degree to which control of the ventilation device 2 is necessary. The determination means determines the degree to which control of the ventilation device 2 is necessary based on, for example, one or a combination of various pieces of information acquired by the information acquisition means and the control conditions. Details of the control conditions will be described later. The determination means may be provided separately from, for example, the ventilation control device 3, or it may be provided in the ventilation control device 3. The determination means may be provided in, for example, the information acquisition means, or it may be provided in either the data server or the management setting means described later. The determination means is implemented, for example, by the CPU 301 executing a program stored in the storage unit 304, etc., using the RAM 303 as a working area.

[0127] <Data Server> The data server stores acquired information obtained by various information acquisition means, calibration information obtained as a result of calibrating that acquired information, as well as various regulations and rules such as control conditions and calibration conditions. The data server is connected to the ventilation control device 3 and the wireless communication control unit, for example, via a public communication network. The public communication network may consist of a so-called optical fiber communication network, and may be implemented using known communication technologies such as wired communication networks or wireless communication networks including LTE (Long Term Evolution). The data server may be connected to various communication devices via a wireless access point 5 instead of a public communication network. The ventilation control system 1 may, for example, store the above information in the storage unit 304 of the ventilation control device 3 instead of the data server, or it may store the above information in the storage unit 304 of the ventilation control device 3 in combination with the data server.

[0128] <Management setting means> The management setting means is used by the administrator who actually oversees the control of the ventilation control system 1 to set, change, update, etc., control conditions for the automatic control of the ventilation device 2.

[0129] The management and setting means is connected, for example, via a public communication network to the ventilation control device 3, the data server, and the wireless communication control unit of the information acquisition means. The management and setting means may also be connected to various communication devices via a wireless access point 5 instead of a public communication network. The management and setting means is composed of electronic devices such as a personal computer (PC), but may also be implemented using any other electronic devices such as mobile phones, smartphones, tablet terminals, and wearable devices. This management and setting means displays acquired information and calibration information stored in the actual data server on a user interface for the administrator who actually oversees the control of the ventilation control system 1. The management and setting means also accepts input from this administrator and adjusts or changes the control conditions and calibration conditions stored in the data server.

[0130] <Ventilation control device 3> The ventilation control device 3 may be connected to various communication devices via a wireless communication access point 5, for example, as shown in Figure 18, and may send and receive information. The ventilation control device 3 may be connected to various communication devices via a wireless communication network, for example, and may send and receive information. The ventilation control device 3 may be connected to a data server, for example, and send and receive information. The ventilation control device 3 may be connected to a management setting means, for example, and may send and receive information. The ventilation control device 3 may receive control conditions corresponding to various information acquired by an information acquisition means, for example. The ventilation control device 3 may generate control information D33 based on the control conditions and output it to the ventilation device 2, for example.

[0131] <Wireless communication access point 5> The wireless communication access point 5 is, for example, a gateway base station located indoors or outdoors. The wireless communication access point 5 is configured as a device for wireless communication between, for example, the ventilation control device 3, the data server, and the management and setting means.

[0132] (Fourth embodiment: An example of the operation of the ventilation control system 1) Next, an example of the operation of the ventilation control system 1 in this embodiment will be described with reference to Figure 19. Figure 19 is a schematic diagram showing an example of an automatic control method for the ventilation control system 1 in this embodiment.

[0133] The operation of the ventilation control system 1 further includes an information acquisition step and a determination step.

[0134] <Information Acquisition Steps> In the information acquisition step, the information acquisition means acquires various types of information. These types of information include, for example, indoor information, outdoor information, performance information, indoor sensor information, outdoor sensor information, etc. The information acquisition means acquires indoor information and outdoor information, for example, as shown in Figure 19.

[0135] The various pieces of information acquired in the information acquisition step may be calibrated by referring to calibration conditions. As an example of calibration, if carbon dioxide concentration acquired as indoor sensor information is taken as an example, the lowest value from the past 24 hours is obtained from the acquired data and this value is set as the reference value of 400 ppm. In this calibration, the lowest or average value of the acquired data acquired within one hour may also be used.

[0136] <Interior Information> As indoor information, for example, a recording device for acquired data such as the location and number of ventilation devices 2 installed in the room (including the address of the building structure), the size of the room, the height of the ceiling in the room, the maximum capacity of the room, business hours, and past congestion information of the room can be used. This indoor information acquisition means is for acquiring indoor information and may be input via a user interface such as a keyboard or touch panel, or it may be composed of a database or memory that has already acquired such indoor information.

[0137] <External Information> External information that can be used includes, for example, subsidy information, price information for ventilation system 2, inventory information for ventilation system 2, price information for maintenance and installation of ventilation system 2, availability information for ventilation system 2 installation contractors, information on the current electricity company, contract plan information from various electricity companies, electricity usage information, model number information for the ventilation system 2 being used, start date of use for ventilation system 2, weather forecasts such as sunny, cloudy, rainy, snowy, and haily, perceived temperature index, heat shock forecast, heatstroke information, probability of precipitation, information on pollen, yellow dust, smog, PM2.5, etc., information on volcanic eruptions and the resulting gas buildup and ashfall, ocean wave information, outdoor wind direction and wind speed information, traffic congestion information, radiation information including that caused by nuclear power plant accidents, various news information, beer index, ice index, etc., and recording devices that record data obtained from public communication networks such as the internet. When this information is obtained from a public communication network, if it is obtained as text information, it is subjected to natural language processing, syntactic analysis, and semantic analysis as needed, and then classified into various types of meaningful information. For this reason, the external information acquisition means may have tools implemented for natural language processing of external information composed of text information.

[0138] <Performance Information> The actual usage information is comprised of a database or memory containing pre-acquired historical electricity usage data for the ventilation system 2. This historical electricity usage data may be shown as actual usage data, such as 150 kWh used between 12:00 and 13:00 on Wednesday last week, or 120 kWh used between 13:00 and 15:00 on Tuesday last week. The means for acquiring this actual usage information can include a recording device for acquired data such as past control conditions of the ventilation system 2 and past inputs of the ventilation system 2. This means for acquiring actual usage information is for acquiring actual usage information and may be input via a user interface such as a keyboard or touch panel, or it may be comprised of a database or memory that already contains such indoor information.

[0139] <Indoor sensor information> As indoor sensor information, for example, information acquired by an indoor temperature sensor to acquire indoor temperature, an indoor humidity sensor to acquire indoor humidity, an indoor carbon dioxide concentration sensor to acquire indoor carbon dioxide concentration, a PM sensor, VOC sensor, or pollen sensor to acquire the degree of indoor pollution such as PM2.5 or smog, an indoor odor sensor to acquire the degree of indoor odor, an indoor ozone concentration sensor to acquire indoor ozone concentration, a human detection sensor (human motion sensor, human counter, AI camera, security camera, etc.) to acquire the number of people in the room, a floor temperature sensor, an airflow meter of ventilation device 2, a temperature sensor installed at the outlet of ventilation device 2, a humidity sensor installed at the outlet of ventilation device 2, a power consumption meter of ventilation device 2, and a total operating time meter of ventilation device 2 can be used. In addition, most smartphones that most people currently own have built-in GPS sensors to acquire latitude and longitude of objects, so they can also be used as a substitute for human detection sensors, etc.

[0140] <Outdoor sensor information> Outdoor sensor information can include, for example, information obtained from an outdoor temperature sensor that acquires outdoor temperature, an outdoor humidity sensor that acquires outdoor humidity, a PM sensor, VOC sensor, or pollen sensor that acquires the degree of pollution from PM2.5 or smog outdoors, or an outdoor odor sensor that acquires the degree of odor outdoors.

[0141] <Judgment Step> In the determination step, the determination means determines the degree to which control of the ventilation device 2 is necessary based on the control conditions. In the determination step, the determination means determines the degree to which control of the ventilation device 2 is necessary based on the outdoor comfort level based on external information, the indoor comfort level based on indoor information, and the control conditions, for example, as shown in Figure 19. In the determination step, if the determination means is distinguished from the ventilation control device 3, it transmits the determination result to the ventilation control device 3. In the determination step, the ventilation control device 3 may output control information D33 for controlling the ventilation device 2 based on the determination result.

[0142] In the determination step, the ventilation control device 3 may store the determination result in the storage unit 304 and output a plurality of control information D33 based on the determination result. In the determination step, the determination result stored in the ventilation control device 3 may be updated with a new determination result, or it may be stored together with the new determination result.

[0143] <Control Conditions> The control conditions include the content defined as regulations that link various information acquired by the information acquisition means with the operation information D32 of the ventilation device 2.

[0144] The control conditions are output by referring to an artificial intelligence (AI) learning model that uses control conditions as training data for any one or more combinations of the above types of information, such as a combination of indoor and outdoor information, as shown in Figure 18. This learning model is generated in advance, for example, before the operation of the ventilation control system 1. The control conditions may be determined by a combination of time-series elements or other elements.

[0145] Examples of indoor sensor information include increasing the airflow of ventilation device 2 to high (or rapid) if the CO2 concentration is 1000 ppm or higher, turning off ventilation device 2 if the CO2 concentration is less than 600 ppm, and opening the ventilation valve in ventilation device 2 if the CO2 concentration is 800 ppm or higher.

[0146] Examples of external information include switching ventilation system 2 to energy-saving mode if the number of infected people falls below 10,000, switching ventilation system 2 to infection control mode (a mode that increases ventilation) if the number of infected people is 10,000 or more, switching ventilation system 2 to infection control mode (a mode that increases ventilation) if a disaster occurs nearby, switching ventilation system 2 to disaster countermeasure mode (a mode that enhances ventilation) if the beer index is high or if the temperature and humidity are similar to that of a tropical region, switching ventilation system 2 to a specific mode (ventilation conditions that make beer taste good or give you a tropical feeling), notifying a replacement alert for ventilation system 2 if the service life of ventilation system 2 is exceeded or if it is time to receive a subsidy, and notifying a malfunction alert for ventilation system 2 if the effectiveness of ventilation system 2 has decreased by 30% and it is before the busy period for installation work.

[0147] Examples of outdoor sensor information include: reducing the airflow from ventilation device 2 and switching the heating / cooling system to cooling mode when the outdoor temperature is 25°C or higher; increasing the airflow from ventilation device 2 and switching the heating / cooling system to heating mode when the outdoor temperature is 18°C ​​or lower; increasing the airflow from ventilation device 2 when the indoor comfort level exceeds the outdoor comfort level; and lowering the set temperature of the heating / cooling system and turning off ventilation device 2 when the outdoor humidity is 60% or higher.

[0148] Furthermore, in the case of indoor and outdoor sensor information, indoor temperature, indoor humidity, carbon dioxide concentration, etc., may be acquired in a time series, and the degree of ventilation to be adjusted by the ventilation device 2 may be set based on the frequency or duration of exceeding the standard value within 24 hours, or it may be determined based on whether the average or maximum value of the acquired information over 24 hours exceeds the standard value. In such cases, the one with the highest average value among indoor temperature, indoor humidity, carbon dioxide concentration, etc., may be selected and its average value may be compared with the standard value, or a desired weighting may be applied among these three factors and compared with the standard value.

[0149] For such control conditions, the determination means determines whether the various pieces of information acquired in the information acquisition step conform to them. For example, if the control condition is "turn off ventilation device 2 if the CO2 concentration is less than 600 ppm", it determines whether the detected CO2 concentration is less than 600 ppm. If the result is that the control condition is met, the determination means causes the ventilation control device 3 to output control information D33 so that the operation included in the specific operation information D32 linked to the control condition is executed. On the other hand, if the control condition is not met, no new information is output to the ventilation control device 3.

[0150] The information acquisition means acquires data such as indoor temperature, indoor humidity, and carbon dioxide concentration in a time series and calculates the 24-hour average value every hour. The judgment means determines that there is an abnormality if, for example, any of the average values ​​acquired by the information acquisition means exceeds a threshold. In such cases, based on the control conditions, the judgment means causes the ventilation control device 3 to output control information D33 corresponding to operation information D32 for "activating" the ventilation device 2, or to output control information D33 corresponding to operation information D32 for "increasing the airflow rate of the ventilation device 2 by one level".

[0151] Furthermore, while the automatic control described above is performed via the ventilation control device 3, the wireless communication control unit may also continuously receive information acquired by the information acquisition means. The various types of information to be received by this wireless communication control unit may be uncalibrated raw data, calibrated data, or both raw data and calibrated data.

[0152] The wireless communication control unit transmits the acquired data to the data server. The data server sequentially stores this acquired data. Data is sent to this data server sequentially from wireless communication control units located in various other locations and stored sequentially. As a result, the data server collects acquired data from various information acquisition means via the wireless communication control units.

[0153] This data server can be accessed from the management and configuration means via the public communication network. The management and configuration means statistically organizes and aggregates the acquired information recorded in the data server as needed, and makes it visible on the user interface. This statistical organization and aggregation of acquired information may be performed on an individual wireless communication control unit basis, or it may be aggregated for multiple wireless communication control units together.

[0154] The following example explains how to perform statistical organization and aggregation of acquired information on a per-unit basis for each wireless communication control unit.

[0155] In such cases, the management setting means displays the aggregated results of the acquired data on the user interface. This display screen on the user interface may, for example, display each acquired value in chronological order. If the administrator visually checks the aggregated results of the measurement data and determines that there is an abnormality, they can manually issue a command to change the control conditions. In such cases, the administrator will use their own experience to determine whether to leave the control conditions as they are or to change the control conditions themselves. The result of this determination by the administrator will be reflected in the control conditions. The administrator may decide what control conditions to set based on the result of the determination, or the management setting means may decide this automatically. In such cases, templates linked to control conditions according to the frequency of determinations that the control conditions should be changed may be formed in advance, and the control conditions may be identified based on these templates.

[0156] The changes and updates to these control conditions can, in principle, be performed automatically by the management setting means. As a method for changing the control conditions, for example, a template is prepared that links one or more judgment results such as indoor comfort, energy saving, presence or absence of malfunction, heatstroke risk, infectious disease risk, etc., to one or more acquired data from any one of the following: indoor sensor information, outdoor sensor information, indoor information, performance information, and external information, based on the frequency or duration of exceeding a standard value. Then, the management setting means identifies the frequency or duration of exceeding the standard value for newly acquired data and extracts one or more of the following: indoor comfort, energy saving, presence or absence of malfunction, heatstroke risk, infectious disease risk, etc., linked to that identified frequency or duration. This allows the management setting means to automatically determine one or more of the following from the acquired data each time. Regarding the presence or absence of malfunction, if the value is significantly outside the range of the control conditions, it can be determined that there is a possibility of a malfunction occurring.

[0157] Furthermore, one or more of these factors—indoor comfort, energy efficiency, presence or absence of malfunctions, heatstroke risk, infectious disease risk, etc.—are linked to specific control conditions and prepared in advance as templates. An example of such a template is when indoor comfort is rated second from the top on a 5-point scale, energy efficiency is rated first from the bottom on a 5-point scale, and heatstroke risk is rated third from the top on a 5-point scale, and the control condition is "If the rate of increase in indoor temperature over time is 0.3°C / min and the rate of increase in odor intensity exceeds 30°C / min, immediately turn on ventilation device 2." In this template, changes are made, such as lowering the "rate of increase in indoor temperature over time" from 0.3°C / min to 0.2°C / min.

[0158] Furthermore, it is assumed that a control condition is pre-set to increase ventilation by ventilation device 2 if, for example, the carbon dioxide concentration exceeds 1000 ppm. However, the actual carbon dioxide concentration, even when measured over time, never exceeds 700 ppm in 24 hours, and only exceeds 600 ppm a few times. In such cases, the indoor environment is stable at a low carbon dioxide concentration, and the people inside are accustomed to this environment, so conversely, some may feel uncomfortable if the concentration exceeds 900 ppm. In such cases, the control condition can be changed to increase ventilation by ventilation device 2 if the carbon dioxide concentration exceeds 900 ppm.

[0159] Alternatively, as a method for changing these control conditions, the changes to the control conditions may be directly linked to each acquired data, such as indoor sensor information, outdoor sensor information, indoor information, performance information, and external information. When new acquired information is detected, it can be read and the control conditions to be changed can be directly derived.

[0160] In this manner, the management and configuration means derives the control conditions to be changed and then updates the control conditions recorded in the data server via the public communication network. This update of control conditions may be performed on a per-wireless communication control unit basis, or a common control condition may be updated for multiple wireless communication control units.

[0161] The wireless communication control unit acquires the updated control conditions on this data server via the public communication network and transmits them to the ventilation control device 3. Based on these updated control conditions, the ventilation control device 3 can perform the aforementioned determination.

[0162] Furthermore, the ventilation control system 1 is not limited to cases where the setting, modification, and updating of control conditions are performed by the management setting means based on the method described above. For example, artificial intelligence may be used to automatically determine these conditions as an alternative to the management setting means.

[0163] For example, instead of using a management configuration method, artificial intelligence could be used to automatically determine the settings. In this case, instead of actually using a management configuration method, artificial intelligence would be implemented on the data server. That is, the data stored on this data server would be used to train the artificial intelligence.

[0164] The artificial intelligence of the ventilation control system 1 generates a judgment model using the degree of ventilation necessity as training data for each acquired piece of information (indoor sensor information, outdoor sensor information, indoor information, performance information, external information, etc.). This degree of ventilation necessity may be specifically represented by one or more of the above-mentioned factors such as indoor comfort, energy efficiency, presence or absence of malfunction, risk of heatstroke, and risk of infectious disease. The central neural network takes one or more of the acquired data (indoor sensor information, outdoor sensor information, indoor information, performance information, external information, etc.) as input, and outputs the judgment result, which is the degree of ventilation necessity.

[0165] In particular, the external information acquired by the external information acquisition means, among the information acquisition means, is data information such as weather forecasts and other news that may be directly or related to the control of the ventilation device 2, obtained via public communication networks such as the internet, and is therefore easier to process using artificial intelligence. In such cases, the artificial intelligence, which is an alternative to the management setting means, can identify the external information by performing natural language analysis when it receives text data as input. When the artificial intelligence makes a judgment, it can input the external information and determine the degree of necessity for controlling the ventilation device 2 based on the judgment result as output. External information can be acquired not only from the internet, but also from television, radio, etc. In the case of television, there is software that can convert image information and sound information into text information, and when this text data is input, natural language analysis can be performed to extract keywords and identify the external information. In the case of radio, there is software that can convert sound information into text information, and when this text data is input, natural language analysis can be performed to extract keywords and identify the external information. Furthermore, by pre-quantifying external information for each risk assessment and linking it to the control of the corresponding ventilation device 2, it is also possible to address the issue using a management setting method.

[0166] Specifically, for example, if ventilation device 2 malfunctions or is about to malfunction, external information such as subsidies for ventilation device 2, price information for ventilation device 2, and inventory information for ventilation device 2 can be input to the user's smartphone, etc. The output, which is the judgment result, will determine the degree to which control of ventilation device 2 is necessary. In addition, as an ancillary service, advantageous information such as price information and inventory information for maintenance and replacement, coupon issuance, and conditions for receiving subsidies can be sent, and alerts recommending maintenance or replacement of ventilation device 2 can be sent to the user's smartphone, etc.

[0167] Furthermore, if electricity costs are high, external information such as the user's current electricity provider, their electricity contract plan with the company, and their electricity usage can be entered into the user's smartphone or other device. The output of the judgment will then determine the degree to which control of ventilation device 2 is necessary, and as an additional service, the company can send information on other contract plans and comparisons with other companies.

[0168] Furthermore, by inputting the model number and start date of use of the ventilation device 2 as external information, the system will output a determination of the degree to which control of the ventilation device 2 is necessary. In addition, it can also provide supplementary services such as sending notifications to the user's smartphone if there is any recall information.

[0169] Furthermore, when external information such as weather forecasts (sunny, cloudy, rainy, snowy, haily, etc.), perceived temperature index, heat shock forecast, heatstroke information, probability of precipitation, and information on pollen, yellow dust, smog, PM2.5, is input, the system determines the degree to which control of the ventilation device 2 is necessary in response to these conditions. In addition, it can also provide an ancillary service, such as sending alerts to the user's smartphone.

[0170] Furthermore, if external information such as a volcanic eruption due to a natural disaster is input, including the effects of gas and ashfall, as well as forecasts of outdoor wind direction and speed, this information is combined to produce an output that determines the degree to which control of the ventilation device 2 is necessary. In addition, as an ancillary service, alerts and other notifications can be sent to the user's smartphone, etc.

[0171] Furthermore, in the event of a disaster such as a nuclear power plant accident, if external information such as the distance from the accident site, the effects of radiation, and forecasts of wind direction and speed are input, this information is combined to produce an output that determines the degree to which control of the ventilation device 2 is necessary. In addition, as an ancillary service, alarms and other notifications can be sent to the user's smartphone, etc.

[0172] Furthermore, if external information such as a fire in the neighborhood is input, the output will determine the degree to which control of the ventilation system 2 is necessary, and as an ancillary service, it can also send alarms and other notifications to the user's smartphone. Furthermore, if external information such as being in an area experiencing a spread of coronavirus infection is input, the output will determine the degree to which control of the ventilation system 2 is necessary, and as an ancillary service, it can also send alarms and other notifications to the user's smartphone.

[0173] Furthermore, for example, if the indoor space is a restaurant or similar establishment, and external information such as the temperature and humidity of Dubai, where beer and ice cream are known to be delicious, is input, the output will determine the degree to which control of the ventilation system 2 is necessary.

[0174] Furthermore, the indoor information obtained from the indoor information acquisition means, including the address of the building structure, the installation location and number of ventilation devices 2 inside the room, the size of the room, the ceiling height of the room, and the maximum occupancy, is often conveniently used in combination with other acquired information, particularly external information. Note that indoor information generally does not change, so it may be recorded in advance on a data server or the like. For example, if there is information that the installation location of ventilation devices 2 may be hit by strong winds and rain due to a typhoon, etc., as external information, and the installation location of ventilation devices 2 is also input as indoor information, the degree to which control of the ventilation devices 2 corresponding to these is determined as an output judgment result.

[0175] Furthermore, historical data such as past electricity usage values, past control conditions, and past inputs obtained from the historical data acquisition means are often conveniently used in combination with other acquired information, particularly external information. Since historical data is historical, it may be sent to a data server via a public communication network and recorded in advance. For example, if past abnormal situations such as those described above are input as external information, and how the situation was successfully resolved using control methods is input as historical information, the output, which is the judgment result, will determine the degree to which control of the ventilation device 2 is necessary.

[0176] The above-mentioned judgment model may be trained using previously acquired data and the degree to which the administrator specifically determined the need to control ventilation device 2 as a training dataset.

[0177] By using this artificial intelligence and inputting acquired information, the output, which is a judgment result, determines the degree to which ventilation device 2 is needed. By determining the degree to which control of ventilation device 2 is needed, the ventilation control system 1 can obtain control of the ventilation device 2 that needs to be changed, as described above.

[0178] Furthermore, since people's perceptions of temperature and other factors vary, if there are multiple people in a room, you may want to gather their opinions using their individual smartphones, average these values, and incorporate them into the control conditions.

[0179] As described above, the ventilation control system 1 provides a ventilation control system that takes into account not only the comfort of the interior of a building structure but also high safety and other factors.

[0180] Furthermore, this ventilation control system 1 can provide comfort tailored to each user, and in terms of risk management, for example, if a user does not have hay fever, the control conditions can be set and implemented without incorporating pollen countermeasures as a risk.

[0181] While several embodiments of the present invention have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These novel embodiments can be carried out in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims of the invention and its equivalents. [Explanation of Symbols]

[0182] 1. Ventilation system control system 2. Ventilation system 200 Ventilation system control unit 3. Ventilation control device 30 cabinets 301 CPU 302 ROM 303 RAM 304 Preservation Department 305 I / F 306 I / F 307 I / F 308 Input section 309 Display section 310 Internal bus 31. Means of communication 32 Memory means 33 Device information identification means 34 Setting means 35. Means for acquiring training data 36 Device Information Model Generation Means 37 Control Information Model Generation Means 4 Wireless communication network 61 First Database 62 Second Database 81 Device Information Model 82 Control Information Model S110 Device Information Identification Step S120 Setup Steps S130 Steps to acquire training data S140 Device Information Model Generation Step S150 Control Information Model Generation Step D31 Device information D32 operation information D33 Control Information D61 Reference device information D62 Reference operation information D63 Reference control information D71 Training data (for device information model) D711 Input Data D712 Output Data D72 Training data (for control information model) D721 Input Data D722 Output Data T611 Device Information Table (within the first database) T613 Control Information Table (within the first database) T621 Device Information Table (in the second database) T622 Operation Information Table (in the second database) T623 Control Information Table (in the second database)

Claims

1. The existing ventilation system that ventilates the room, An existing ventilation device operating unit that outputs control information for controlling the above-mentioned ventilation device, The system comprises a ventilation control device newly installed between the ventilation device and the ventilation device operating unit, The above ventilation control device is A device information identification means identifies device information corresponding to the control information obtained from the ventilation device operation unit, after referring to a first database in which reference control information including control information of the ventilation device and reference device information including device information of the ventilation device are pre-linked and stored. A setting means retrieves operation information and control information from the second database corresponding to the device information of a ventilation device, after referring to a second database in which reference operation information including operation information indicating the operation of the ventilation device and reference control information including control information of the ventilation device are pre-linked and stored for each device information of the ventilation device, and sets the retrieved operation information and control information to the ventilation control device. Information acquisition means for acquiring various types of information, including at least one of the following: indoor information, outdoor information, performance information, indoor sensor information, and outdoor sensor information related to the above-mentioned indoor space or ventilation device, A management setting means for setting control conditions for automatically controlling the above ventilation device, The system includes a determination means for determining the degree to which control of the ventilation device is necessary, based on the various information acquired by the information acquisition means and the control conditions set by the management setting means. Based on the degree of necessity determined by the determination means, the control information set by the setting means is output to the ventilation device. A ventilation control system characterized by the following.

2. The above management setting means sets the above control conditions based on the above various information obtained by the above information acquisition means. A ventilation control system according to claim 1, characterized by the following:

3. The above management setting means uses a judgment model that uses the above degree of necessity for the above various information as training data, and sets the above control conditions according to the degree of necessity output from the judgment model when newly acquired above various information is input. A ventilation control system according to claim 1 or 2, characterized by the above.

4. The above information acquisition means refers to pre-set calibration conditions and performs calibration on the acquired various types of information. A ventilation control system according to claim 1 or 2, characterized by the above.

5. In a ventilation control device newly installed between an existing ventilation device that ventilates a room and an existing ventilation device operating unit that outputs control information for controlling the ventilation device, A device information identification means identifies device information corresponding to the control information obtained from the ventilation device operation unit, after referring to a first database in which reference control information including control information of the ventilation device and reference device information including device information of the ventilation device are pre-linked and stored. A setting means retrieves operation information and control information from the second database corresponding to the device information of a ventilation device, after referring to a second database in which reference operation information including operation information indicating the operation of the ventilation device and reference control information including control information of the ventilation device are pre-linked and stored for each device information of the ventilation device, and sets the retrieved operation information and control information to the ventilation control device. Information acquisition means for acquiring various types of information, including at least one of the following: indoor information, outdoor information, performance information, indoor sensor information, and outdoor sensor information related to the above-mentioned indoor space or ventilation device, A management setting means for setting control conditions for automatically controlling the above ventilation device, The system includes a determination means for determining the degree to which control of the ventilation device is necessary, based on the various information acquired by the information acquisition means and the control conditions set by the management setting means. Based on the degree of necessity determined by the determination means, the control information set by the setting means is output to the ventilation device. A ventilation control device characterized by the following.

6. In a ventilation control program for controlling a ventilation control system comprising an existing ventilation device for ventilating a room, an existing ventilation device operating unit that outputs control information for controlling the ventilation device, and a ventilation control device newly installed between the ventilation device and the ventilation device operating unit, A device information identification step involves referring to a first database in which reference control information, including control information for the ventilation system, and reference device information, including device information for the ventilation system, are pre-linked and stored, and then identifying the device information corresponding to the control information obtained from the ventilation system operation unit. A setting step involves referring to a second database in which reference operation information, including operation information indicating the operation of the ventilation device, and reference control information, including control information for the ventilation device, are pre-linked and stored for each device information of the ventilation device, and then obtaining the operation information and control information corresponding to the device information identified in the above device information identification step from the second database, and setting the acquired operation information and control information to the ventilation control device. An information acquisition step in which various types of information are acquired, including at least one of the following: indoor information, outdoor information, performance information, indoor sensor information, and outdoor sensor information related to the above-mentioned indoor space or ventilation device, A determination step which determines the degree to which control of the ventilation device is necessary based on the various information obtained in the above information acquisition step and the pre-set control conditions for automatically controlling the ventilation device, and outputs the control information set in the above setting step to the ventilation device based on the determined degree of necessity, Make the computer do it A ventilation control program characterized by the following.

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