Mold prevention support device, mold prevention support system, mold prevention support method, and mold prevention support program

Abstract

A mold suppression support device (100) supports the suppression of mold growth. A prompt creation unit (110) acquires image data (21) of an image of a surrounding area including a mold-suppressed area, and estimation request information (22) for estimating a mold growth cause (521) and a suppression measure (522) using the image data (21). The prompt creation unit (110) creates a prompt (51) based on the image data (21) and the estimation request information (22). A measure support unit (120) outputs suppression support information (52) including the growth cause (521) and the suppression measure (522) based on the prompt (51).

Description

[Technical Field]

[0001] The present disclosure relates to a mold suppression support device, a mold suppression support system, a mold suppression support method, and a mold suppression support program. [Background technology]

[0002] In hot and humid regions or seasons, mold is likely to grow on the interior and exterior surfaces of buildings such as residences, stores, factories, and warehouses. Examples of the interior and exterior surfaces of buildings include the surfaces or interior surfaces of ceilings, walls, fixtures, furniture, and home appliances. Because mold growth reduces hygiene and design, it is necessary to predict and suppress mold growth.

[0003] Patent Document 1 discloses a mold suppression system that estimates a mold index after a predetermined period of time based on the room temperature and absolute humidity, and determines an operation schedule for a humidity control device according to the progress of the mold index. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 7261103 Summary of the Invention [Problem to be solved by the invention]

[0005] The mold control system in Patent Document 1 supports mold control measures within the feasible scope of the mold control system. However, mold growth is strongly influenced not only by temperature or humidity, but also by the state and circumstances of the surrounding environment. For this reason, there was a problem that mold control would be insufficient unless comprehensive measures including the surrounding environment were supported.

[0006] The purpose of this disclosure is to estimate the causes of mold growth from the state and circumstances of the surrounding environment, and to provide comprehensive support for resolving mold growth. [Means for solving the problem]

[0007] The mold suppression support device according to the present disclosure comprises: a prompt creation unit that acquires image data of a surrounding area including a mold-suppressed area of ​​a target area where mold growth is suppressed, and estimation request information that is information for using the image data to estimate factors that cause mold growth and suppression measures for suppressing the mold growth, and creates a prompt based on the image data and the estimation request information; The system further includes a countermeasure support unit that receives the prompt and outputs suppression support information including the cause of occurrence and the suppression countermeasure based on the prompt. [Effects of the Invention]

[0008] In the mold control support device according to the present disclosure, the prompt creation unit uses image data of the surrounding area including the mold-control area to create a prompt for estimating control support information including mold growth factors and control measures. The countermeasure support unit uses this prompt as input and outputs the mold control support information. Therefore, the mold control support device according to the present disclosure can estimate mold control support information from the surrounding environment of the mold-control area, thereby realizing comprehensive support for resolving mold growth. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a diagram showing an example of the overall configuration of a mold prevention support system according to a first embodiment. [Figure 2] 1 is a diagram showing an example of the configuration of a mold prevention support device according to a first embodiment. [Figure 3] 3 is a flow chart showing an example of the operation of the mold prevention support device according to the first embodiment. [Figure 4] FIG. 2 is a diagram showing an example of input and output of data from the mold prevention support device according to the first embodiment. [Figure 5] FIG. 3 is a diagram showing an example of a prompt according to the first embodiment. [Figure 6] FIG. 10 is a diagram showing a configuration example of a mold prevention support device according to a modified example of the first embodiment. [Figure 7] FIG. 10 is a diagram showing a configuration example of a mold prevention support device according to a second embodiment. [Figure 8] FIG. 10 is a flow chart showing an example of the operation of the mold prevention support device according to the second embodiment. [Figure 9] FIG. 10 is a diagram showing an example of input and output of data from the mold prevention support device according to the second embodiment. [Figure 10] FIG. 10 is a diagram showing an example of an image data portion of a prompt according to the second embodiment. [Figure 11] FIG. 11 is a diagram showing an example of an estimation request information portion of a prompt according to the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] The present embodiment will be described below with reference to the drawings. In each drawing, identical or corresponding parts are designated by the same reference numerals. In the description of the embodiment, the description of identical or corresponding parts will be omitted or simplified as appropriate. Arrows in the drawings mainly indicate the flow of data or the flow of processing. Furthermore, the sized relationships between components in the following drawings may differ from the actual relationships. Furthermore, in the description of the embodiment, directions or positions such as up, down, left, right, front, rear, front, and back may be indicated. These notations are used for convenience of explanation and do not limit the placement, direction, or orientation of objects such as devices, instruments, or parts.

[0011] Embodiment 1 ***Configuration Description*** FIG. 1 is a diagram showing an example of the overall configuration of a mold prevention support system 500 according to this embodiment. FIG. 2 is a diagram showing an example of the configuration of the mold prevention support device 100 according to this embodiment.

[0012] The mold prevention support system 500 according to this embodiment includes a mold prevention support device 100 and an artificial intelligence 200. The mold prevention support device 100 and the artificial intelligence 200 are capable of inputting and outputting data or transmitting and receiving data.

[0013] First, a configuration example of the mold prevention support device 100 will be described. The mold prevention support device 100 is a computer. The mold prevention support device 100 includes a processor 910, as well as other hardware such as a memory 921, an auxiliary storage device 922, an input interface 930, an output interface 940, and a communication device 950. The processor 910 is connected to the other hardware via signal lines and controls the other hardware.

[0014] The mold control support device 100 includes, as functional elements, a prompt creation unit 110, a countermeasure support unit 120, and a storage unit 150. The storage unit 150 stores a prompt 51 and control support information 52.

[0015] The functions of the prompt generation unit 110 and the countermeasure support unit 120 are realized by software. The storage unit 150 is provided in the memory 921. The storage unit 150 may be provided in the auxiliary storage device 922, or may be provided separately in the memory 921 and the auxiliary storage device 922.

[0016] The processor 910 is a device that executes a mold prevention support program. The mold prevention support program is a program that realizes the functions of the prompt generation unit 110 and the countermeasure support unit 120. The processor 910 is an IC that performs arithmetic processing. Specific examples of the processor 910 are a CPU, a DSP, and a GPU. IC is an abbreviation for Integrated Circuit. CPU is an abbreviation for Central Processing Unit. DSP is an abbreviation for Digital Signal Processor. GPU is an abbreviation for Graphics Processing Unit.

[0017] The memory 921 is a storage device that temporarily stores data. Specific examples of the memory 921 are SRAM and DRAM. SRAM is an abbreviation for Static Random Access Memory. DRAM is an abbreviation for Dynamic Random Access Memory. The auxiliary storage device 922 is a storage device that stores data. A specific example of the auxiliary storage device 922 is a HDD. The auxiliary storage device 922 may also be a portable storage medium such as an SD (registered trademark) memory card, CF, NAND flash, a flexible disk, an optical disk, a compact disk, a Blu-ray (registered trademark) disk, or a DVD. Note that HDD is an abbreviation for Hard Disk Drive. SD (registered trademark) is an abbreviation for Secure Digital. CF is an abbreviation for CompactFlash (registered trademark). DVD is an abbreviation for Digital Versatile Disk.

[0018] The input interface 930 is a port connected to an input device such as a mouse, keyboard, or touch panel. Specifically, the input interface 930 is a USB terminal. The input interface 930 may also be a port connected to a LAN. USB is an abbreviation for Universal Serial Bus. LAN is an abbreviation for Local Area Network.

[0019] The output interface 940 is a port to which a cable of an output device such as a display is connected. Specifically, the output interface 940 is a USB terminal or an HDMI (registered trademark) terminal. Specifically, the display is an LCD. The output interface 940 is also called a display interface. HDMI (registered trademark) is an abbreviation for High Definition Multimedia Interface. LCD is an abbreviation for Liquid Crystal Display.

[0020] The communication device 950 has a receiver and a transmitter. The communication device 950 is connected to a communication network such as a LAN, the Internet, a telephone line, or Wi-Fi (registered trademark). Specifically, the communication device 950 is a communication chip or NIC. NIC is an abbreviation for Network Interface Card.

[0021] The mold control support program is executed in the mold control support device 100. The mold control support program is read into the processor 910 and executed by the processor 910. The memory 921 stores not only the mold control support program but also an OS. OS is an abbreviation for Operating System. The processor 910 executes the mold control support program while executing the OS. The mold control support program and the OS may be stored in an auxiliary storage device 922. The mold control support program and the OS stored in the auxiliary storage device 922 are loaded into the memory 921 and executed by the processor 910. Note that part or all of the mold control support program may be incorporated into the OS.

[0022] The mold control support device 100 may include multiple processors that replace the processor 910. These multiple processors share the task of executing the mold control support program. Each processor is a device that executes the mold control support program in the same way as the processor 910.

[0023] Data, information, signal values ​​and variable values ​​used, processed or output by the mold suppression assistance program are stored in memory 921, auxiliary storage device 922, or registers or cache memory within processor 910.

[0024] The "parts" of the prompt creation unit 110 and the countermeasure support unit 120 may be read as "circuits," "processes," "procedures," "processing," or "circuitry." The mold control support program causes a computer to execute a prompt creation process and a countermeasure support process. The "processing" of the prompt creation process and the countermeasure support process may be read as a "program," "program product," "computer-readable storage medium storing a program," or "computer-readable recording medium recording a program." Furthermore, the mold control support method is a method performed by the mold control support device 100 executing the mold control support program. The mold control assistance program may be provided by being stored in a computer-readable recording medium, or may be provided as a program product.

[0025] The artificial intelligence 200 includes an inference unit that performs inference using a trained model. The inference unit receives a prompt 51 from the countermeasure support unit 120 as input, and outputs suppression support information 52 that supports mold suppression corresponding to the prompt 51 based on the trained model. The artificial intelligence 200 may be a generative AI. AI is an abbreviation for Artificial Intelligence. The countermeasure support unit 120 inputs a prompt 51 to the artificial intelligence 200, which is an external component, and instructs it to generate suppression support information 52, causing it to output the suppression support information 52. In this way, various external artificial intelligence services can be utilized to output the suppression support information 52. Note that although the artificial intelligence 200 is an external component of the mold suppression support device 100 in FIG. 1, it may also be an internal component.

[0026] The artificial intelligence 200 may be configured using algorithms such as Transformer, BERT, and GPT. The artificial intelligence 200 may also be configured by combining multiple algorithms including these algorithms. BERT is an abbreviation for Bidirectional Encoder Representations from Transformers. GPT is an abbreviation for Generative Pre-Training.

[0027] ***Explanation of Operation*** Next, the operation of the mold control support device 100 according to this embodiment will be described. The operating procedure of the mold control support device 100 corresponds to a mold control support method. Furthermore, the program that realizes the operation of the mold control support device 100 corresponds to a mold control support program.

[0028] FIG. 3 is a flow chart showing an example of the operation of the mold prevention support device 100 according to this embodiment. FIG. 4 is a diagram showing an example of input and output of data to and from the mold prevention support device 100 according to this embodiment.

[0029] <Prompt creation process> In the prompt creation process, the prompt creation unit 110 acquires the image data 21 and the estimation request information 22 , and creates a prompt 51 based on the image data 21 and the estimation request information 22 . Specifically, it is as follows:

[0030] In step S101, the prompt generator 110 acquires the image data 21 and the estimation request information 22. In step S102, the prompt generator 110 generates a prompt 51 based on the image data 21 and the estimation request information 22. The image data 21 is an image of a surrounding area 61 including a mold-inhibition area 60 of a target area where mold growth is to be inhibited. The estimation request information 22 is information for estimating a mold occurrence factor 521, which is a cause of mold occurrence, and a mold suppression measure 522 for suppressing mold occurrence, using the image data 21. The estimation request information 22 is input by the user using, for example, a fixed phrase.

[0031] FIG. 5 is a diagram showing an example of a prompt 51 according to this embodiment. The mold-inhibition support device 100 acquires, via the input interface 930, image data 21 of an image of a surrounding area 61 including the mold-inhibition area 60. In FIG. 5, the ceiling or wall surface of the room is a mold-inhibition area 60 where mold growth is desired to be inhibited. In the image data 21, the surrounding environment including the ceiling or wall surface that is the mold-inhibition area 60 is photographed as a surrounding area 61. The image data 21 is, for example, data of a photograph taken by a camera. Furthermore, the image data 21 may be one or more.

[0032] The image data 21 preferably includes disturbances that affect mold growth, such as heat sources, moisture sources, or draft sources. For example, the image data 21 preferably includes the surrounding environment, including structures such as windows, doors, and furniture, as the surrounding area 61, in addition to home appliances installed in the room, such as air conditioners, humidifiers, and lighting.

[0033] The estimation request information 22 is information for allowing the artificial intelligence 200 to estimate, using the image data 21, a generation factor 521 that is a factor in mold generation and a suppression measure 522 for suppressing mold generation. The estimation request information 22 in FIG. 5 includes (1) information requesting an analysis of information from an image, (2) information requesting an analysis of the cause, and (3) information requesting consideration of countermeasures.

[0034] The prompt generator 110 generates a prompt 51 including image data 21 and estimation request information 22 . In this embodiment, the prompt 51 is information including the image data 21 and the estimation request information 22, but the estimation request information 22 may also be called the prompt.

[0035] <Countermeasure support processing> In the countermeasure support process, the countermeasure support unit 120 acquires a prompt 51 and outputs, based on the prompt 51, suppression support information 52 including a cause of occurrence 521 and a suppression countermeasure 522. Specifically, it is as follows:

[0036] In step S103, the countermeasure support unit 120 inputs the prompt 51 to the artificial intelligence 200. In step S104, the countermeasure support unit 120 acquires, from the artificial intelligence 200, the control support information 52 including the mold occurrence cause 521 and the control countermeasure 522. In step S105, the countermeasure support unit 120 presents the user with the suppression support information 52. For example, the countermeasure support unit 120 presents the suppression support information 52 to the user by displaying the suppression support information 52 on a display device.

[0037] The suppression support information 52 includes mold growth factors 521 and feasible and comprehensive suppression measures 522 that are suitable for the surrounding environment of the mold-suppressed area 60. The suppression measures 522 include measures to remove the growth factors 521. Examples of mitigation measures 522 include: ·Air conditioner operation schedule creation, · Anti-mold coating construction, ·Air conditioner installation, -Insulate heat-source equipment.

[0038] ***Other Configurations*** <Variation 1> In the present embodiment, the image data 21 has been described as being data of a photograph taken by a camera. In addition to photograph data, the image data 21 may be infrared images taken by an infrared imaging device. Alternatively, the image data 21 may be panoramic images taken by a panoramic imaging device. An infrared image is an image taken with a thermal camera, and shows the temperature distribution or moisture content distribution. A panoramic image is an image taken with a camera that can capture a 360-degree or 180-degree view of the surroundings.

[0039] The prompt creation unit 110 acquires, as image data 21, an infrared image of the mold-inhibited area 60 captured by an infrared imaging device. Alternatively, the prompt creating unit 110 acquires, as image data 21, a panoramic image of the mold-inhibited area 60 captured by a panoramic image capturing device. It is to be noted that the image data 21 may contain a mixture of photographic data, infrared images, and panoramic images. For example, the image data 21 may contain both infrared images and panoramic images.

[0040] By using not only photographic data but also infrared images or panoramic images as the image data 21, more comprehensive and effective prevention measures can be estimated.

[0041] <Variation 2> In this embodiment, the functions of prompt generating unit 110 and countermeasure support unit 120 are realized by software. As a variation, the functions of prompt generating unit 110 and countermeasure support unit 120 may be realized by hardware. Specifically, the mold prevention support device 100 includes an electronic circuit 909 instead of a processor 910 .

[0042] FIG. 6 is a diagram showing an example of the configuration of a mold prevention support device 100 according to a modified example of this embodiment. The electronic circuit 909 is a dedicated electronic circuit that realizes the functions of the prompt generation unit 110 and the countermeasure support unit 120. Specifically, the electronic circuit 909 is a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, a logic IC, a GA, an ASIC, or an FPGA. GA is an abbreviation for Gate Array. ASIC is an abbreviation for Application Specific Integrated Circuit. FPGA is an abbreviation for Field-Programmable Gate Array.

[0043] The functions of the prompt generating unit 110 and the countermeasure supporting unit 120 may be realized by a single electronic circuit, or may be realized by distributing the functions across multiple electronic circuits.

[0044] As another variation, some of the functions of prompt generation unit 110 and countermeasure support unit 120 may be implemented by electronic circuits, with the remaining functions implemented by software. Alternatively, some or all of the functions of prompt generation unit 110 and countermeasure support unit 120 may be implemented by firmware.

[0045] Each of the processor and the electronic circuit is also called processing circuitry. That is, the functions of the prompt generation unit 110 and the countermeasure support unit 120 are realized by the processing circuitry.

[0046] ***Explanation of the effect of this embodiment*** As described above, the mold control support device according to this embodiment can estimate the causes of mold growth and prevention measures based on the surrounding environment of the mold-inhibited area. Specifically, by using image data captured of the surrounding environment as input, the mold control support device according to this embodiment can analyze factors that may affect mold growth, including disturbances that people may not have noticed, and estimate the cause. Therefore, the mold control support device according to this embodiment can input information beyond numerical values, thereby providing comprehensive and effective support for resolving mold growth.

[0047] Embodiment 2 In this embodiment, differences from and additions to the first embodiment will be mainly described. In this embodiment, components having the same functions as those in the first embodiment are given the same reference numerals, and the description thereof will be omitted.

[0048] ***Configuration Description*** FIG. 7 is a diagram showing an example of the configuration of a mold prevention support device 100 according to this embodiment. 2 described in the first embodiment, the present embodiment further includes an image recognition unit 130 and an information receiving unit 140. Furthermore, a storage unit 150 stores a countermeasure database 53.

[0049] ***Explanation of Operation*** FIG. 8 is a flow chart showing an example of the operation of the mold prevention support device 100 according to this embodiment. FIG. 9 is a diagram showing an example of input and output of data to and from the mold prevention support device 100 according to this embodiment. In this embodiment, the processes are described by adding subscripts to the step numbers described in embodiment 1, such as step S101a and step S102a. These processes are basically the same as the processes described in embodiment 1, but indicate that there are some differences from embodiment 1 or some additions to embodiment 1.

[0050] <Prompt creation process> In step S201, the image recognition unit 130 acquires the image data 21. In this embodiment, the image data 21 is assumed to be an infrared image and a panoramic image. As described in Variation 1 of Embodiment 1, the image data 21 may contain a mixture of photographic data, infrared images, and panoramic images. Alternatively, the image data 21 may be any one of photographic data, infrared images, and panoramic images. The image recognition unit 130 outputs the relative position 30 of the surrounding environment in the mold-inhibition area 60 based on the image data 21. Here, the surrounding environment refers to structures, objects, equipment, etc. that exist in the surrounding area 61 that includes the mold-inhibition area 60. For example, the relative position 30 of the surrounding environment is information such as the relative distance from the center of the mold-inhibition area 60 to a specific wall, air conditioner, window, or door. In other words, the relative position 30 of the surrounding environment can be rephrased as the specific relative position of an object or place that exists in the surrounding environment.

[0051] Here, the image recognition unit 130 according to this embodiment may be a machine learning or generative AI. The image recognition unit 130 may use the artificial intelligence 200, as in the countermeasure support unit 120, or may have a generative AI in its internal configuration. For example, the image recognition unit 130 inputs image data 21 to the generation AI and obtains the relative position 30 of the surrounding environment output from the generation AI. Alternatively, the image recognition unit 130 may obtain the relative position 30 of the surrounding environment from the image data 21 using other image recognition techniques.

[0052] In step S202, the prompt generating unit 110 acquires the environmental condition information 23 used to estimate the mold suppression support information 52. The environmental status information 23 includes, for example, the following information: Basic information showing the status of the mold-suppressed area 60 or surrounding area 61, - The operating status and setting status of the equipment in the mold suppression area 60 or the surrounding area 61; the temperature and humidity of the area including the mold-suppressed area 60 or the surrounding area 61; Weather data for the area including the mold suppression area 60 or the surrounding area 61, -Constraints of the mold-inhibited area 60 or the surrounding area 61, Recommended temperature and humidity values. The environmental status information 23 includes any one of the above six pieces of information or a combination of at least two of the above six pieces of information.

[0053] Basic information indicating the status of mold-inhibited area 60 or surrounding area 61 includes the purpose of use of the environment, land characteristics, address, etc. This information may be input by a user, or may be obtained from a sensor or weather database, for example. The operating status and setting status of the equipment in the mold-inhibition area 60 or the surrounding area 61 is, for example, the operating status and setting status of the equipment, such as an air conditioner. This information may be input by a user or may be obtained directly from the equipment. The temperature and humidity of the area including the mold-inhibited area 60 or the surrounding area 61 may be input by the user or obtained from a sensor, a weather database, or the like. Weather data for the area including the mold-inhibited area 60 or the surrounding area 61 may be input by the user or may be obtained from a sensor, a weather database, or the like. The constraints for the mold-inhibited area 60 or the surrounding area 61 may be, for example, temperature or humidity constraints. For example, the temperature or humidity may be recommended depending on the type of use of the store. This information may be input by the user, or may be obtained from preset constraints. The recommended temperature and humidity values ​​are values ​​that avoid temperatures and humidity that are prone to mold growth. This information may be input by the user, or preset recommended values ​​may be acquired, for example.

[0054] 8, the process is performed in the order of step S201 and step S202, but this order is arbitrary. Also, step S201 and step S202 may be performed in parallel.

[0055] Next, in step S101a, the prompt generation unit 110 acquires the image data 21 and the estimation request information 22. Here, the image data 21 is acquired by the image recognition unit 130 in step S201.

[0056] FIG. 10 is a diagram showing an example of the image data 21 portion of the prompt 51 according to this embodiment. FIG. 11 is a diagram showing an example of the estimation request information 22 portion of the prompt 51 according to this embodiment.

[0057] In FIG. 10, the image data 21 is an infrared image and a panoramic image. The estimation request information 22 shown in FIG. 11 will be described. First, the relative position 30 of the surrounding environment obtained from the image recognition process is described. Next, the environmental status information 23 is described. As in the first embodiment, (1) information requesting information analysis from the image, (2) information requesting analysis of the cause, and (3) information requesting consideration of countermeasures are described. Finally, in (4), write, "If there is anything unclear in the above information, or if there is any information that is necessary to further clarify the cause of mold growth, please let us know." This is information to request the presentation of recommended confirmation information 41.

[0058] In this embodiment as well, the estimation request information 22 is input by the user using, for example, a fixed phrase. For example, the estimation request information 22 is input as follows:

[0059] After steps S201 and S202, the prompt creation unit 110 presents the image data 21, the relative position 30 of the surrounding environment, and the environmental situation information 23 to the user. The prompt creation unit 110 also presents a fixed phrase to the user. The user inputs estimation request information 22 using the fixed phrase, the image data 21, the relative position 30 of the surrounding environment, and the environmental situation information 23.

[0060] In step S102a, the prompt creation unit 110 creates a prompt 51 based on the image data 21, the estimation request information 22, the relative position 30 of the surrounding environment, and the environmental situation information 23. If the environmental situation information 23 has not been input, the prompt creation unit 110 may create the prompt 51 based on the image data 21, the estimation request information 22, and the relative position 30 of the surrounding environment. Alternatively, if the relative position 30 of the surrounding environment cannot be acquired, the prompt creation unit 110 may create the prompt 51 based on the image data 21, the estimation request information 22, and the environmental situation information 23. In this embodiment, the prompt 51 is generated based on the image data 21, the estimation request information 22, the relative position 30 of the surrounding environment, and the environmental situation information 23. For example, the prompt 51 as shown in Figs. 10 and 11 is generated.

[0061] As will be described later, when the process returns from step S205, the prompt generator 110 generates a prompt 51 based on the confirmation recommendation information 41. That is, the prompt generator 110 generates the prompt 51 based on the image data 21, the estimation request information 22, the relative position 30 of the surrounding environment, the environmental condition information 23, and the confirmation recommendation information 41. The confirmation recommendation information 41 will be described later.

[0062] Furthermore, as will be described later, when the process returns from step S207, the prompt generator 110 generates a prompt 51 based on the additional information 42. That is, the prompt generator 110 generates the prompt 51 based on the image data 21, the estimation request information 22, the relative position 30 of the surrounding environment, the environmental condition information 23, and the additional information 42. The additional information 42 will be described later.

[0063] Here, prompt creation unit 110 according to the present embodiment may be a generation AI. Prompt creation unit 110 may use artificial intelligence 200, as in countermeasure support unit 120, or may have a generation AI in its internal configuration. For example, the prompt creation unit 110 inputs image data 21, estimation request information 22, relative position of the surrounding environment 30, environmental status information 23, and confirmation recommendation information 41 to the generation AI, and obtains a prompt 51 to be output from the generation AI. Alternatively, the prompt creation unit 110 inputs image data 21, estimation request information 22, relative position of the surrounding environment 30, environmental status information 23, and additional information 42 to the generation AI, and obtains a prompt 51 to be output from the generation AI. In the prompt creation unit 110, the data to be input to the generation AI may be any combination as long as it includes at least image data 21 and estimation request information 22.

[0064] In step S103, the countermeasure support unit 120 inputs the prompt 51 to the artificial intelligence 200. This process is the same as in the first embodiment.

[0065] In step S203, the countermeasure support unit 120 receives the output from the artificial intelligence 200. The countermeasure support unit 120 determines whether the output from the artificial intelligence 200 includes recommended confirmation information 41. The recommended confirmation information 41 is information that the artificial intelligence 200 has determined to be necessary to add in order to output the cause of occurrence 521 and the mitigation measures 522. If the output from the artificial intelligence 200 includes the confirmation recommendation information 41, the process proceeds to step S204. If the output from the artificial intelligence 200 does not include the confirmation recommendation information 41, the process proceeds to step S104.

[0066] As described above, (4) of prompt 51 shown in Fig. 11 states, "If there is anything unclear in the above information or if there is any information necessary to further clarify the cause of mold growth, please let us know." This statement is information for requesting the presentation of confirmation recommendation information 41. If confirmation recommendation information 41 is available, artificial intelligence 200 outputs confirmation recommendation information 41, and if confirmation recommendation information 41 is not available, it outputs suppression support information 52.

[0067] In step S204, the countermeasure support unit 120 presents the confirmation recommendation information 41, which is information necessary to output the suppression support information 52. In step S205, the information receiving unit 140 receives the confirmation recommendation information 41 from the user via the input interface 930 or the communication device 950. Then, the process returns to step S102a and the process of creating the prompt 51 is performed. In step S102a, when the process returns from step S205, the prompt generator 110 generates the prompt 51, further taking into consideration the confirmation recommendation information 41. That is, the prompt generator 110 generates the prompt 51 based on the image data 21, the estimation request information 22, the relative position 30 of the surrounding environment, the environmental condition information 23, and the confirmation recommendation information 41.

[0068] In step S104, the countermeasure support unit 120 acquires, from the artificial intelligence 200, the control support information 52 including the mold occurrence cause 521 and the control countermeasure 522. In step S105, the countermeasure support unit 120 presents the suppression support information 52 to the user. Steps S104 and S105 are the same as those in embodiment 1. However, in this embodiment, the prompt 51 includes more detailed information, and therefore the suppression support information 52 is more comprehensive and effective.

[0069] In step S206, the information receiving unit 140 determines whether or not there is additional information 42, which is feedback from the user in response to the suppression support information 52. If there is additional information 42 from the user, the process proceeds to step S207. If there is no additional information 42 from the user, the process ends.

[0070] In step S207, the information receiving unit 140 receives additional information 42 from the user via the input interface 930 or the communication device 950. The additional information 42 is, for example, information that the user was unable to input when inputting the environmental condition information 23. Alternatively, the additional information 42 is information that the user has determined, after referring to the suppression support information 52, to be additionally input regarding the mold-suppressed area 60 or the surrounding area 61. When the information receiving unit 140 receives the additional information 42, the process returns to step S102a. In step S102a, when the process returns from step S207, the prompt generation unit 110 generates a prompt 51 based on the image data 21, the estimation request information 22, the relative position 30 of the surrounding environment, the environmental situation information 23, and the additional information 42.

[0071] The method by which the information receiving unit 140 receives information from the user may be manual input by the user or voice input by the user. The information receiving unit 140 may also receive the confirmation recommendation information 41 or additional information 42 in a dialogue format or chat format with the user.

[0072] ***Other Configurations*** <Variation 3> The mold prevention support device according to the modified example of this embodiment may include a countermeasure database 53 that stores support products and improvement examples used to estimate the prevention support information 52. The countermeasure database 53 stores information on supporting products and improvement examples necessary for estimating mold suppression measures. Supporting products are suggested products that are suitable for proposing installation when, for example, additional dehumidification is required. Improvement examples are examples that have been proposed in the past for conditions similar to those of the environment in question. The countermeasure database 53 may be stored in an internal storage device or may be stored on an external file server or the like.

[0073] The prompt creation unit 110 includes information for estimating the prevention support information 52 using the countermeasure database 53 in the prompt 51. For example, at the end of the estimation request information 22 in FIG. 11 , (5) states, "Please refer to the countermeasure database to further clarify the measures to prevent mold growth." This statement is information for requesting reference to the countermeasure database 53. In response to such a prompt 51, the artificial intelligence 200 outputs the mold prevention support information 52 referenced in the countermeasure database 53.

[0074] <Variation 4> In the present embodiment, the artificial intelligence 200 has been described as an external component, but it may be an internal component. For example, the countermeasure support unit 120 may be equipped with a generating AI. If the countermeasure support unit 120 is equipped with a generation AI, it is possible to learn in advance the output of the suppression support information 52 using the countermeasure database 53. In this case, the prompt creation unit 110 does not need to include information for estimating the suppression support information 52 using the countermeasure database 53 in the prompt 51.

[0075] ***Explanation of the effect of this embodiment*** As described above, the mold control support device 100 according to this embodiment can create prompts taking into account more detailed information that affects mold growth. Therefore, the mold control support device according to this embodiment can propose more comprehensive and effective mold control measures.

[0076] In the above first and second embodiments, each part of the mold control support device has been described as an independent functional block. However, the configuration of the mold control support device does not have to be the same as that of the above-described embodiments. The functional blocks of the mold control support device may have any configuration as long as they can realize the functions described in the above-described embodiments. Furthermore, the mold control support device may not be a single device, but may be a system composed of multiple devices. Furthermore, it is possible to combine multiple parts of the first and second embodiments. Alternatively, it is possible to implement only one part of these embodiments. In addition, it is possible to implement any combination of these embodiments, either as a whole or in part. That is, in the first and second embodiments, the respective embodiments can be freely combined, or any of the components in the respective embodiments can be modified, or any of the components in the respective embodiments can be omitted.

[0077] The above-described embodiments are essentially preferred examples and are not intended to limit the scope of the present disclosure, the scope of application of the present disclosure, or the scope of use of the present disclosure. The above-described embodiments can be modified in various ways as needed. For example, the procedures described using flow charts or sequence diagrams may be modified as appropriate. [Explanation of symbols]

[0078] 21 image data, 22 estimation request information, 23 environmental condition information, 30 relative position, 41 confirmation recommendation information, 42 additional information, 51 prompt, 52 suppression support information, 521 occurrence cause, 522 suppression measures, 53 countermeasure database, 60 mold suppression area, 61 surrounding area, 100 mold suppression support device, 110 prompt creation unit, 120 countermeasure support unit, 130 image recognition unit, 140 information reception unit, 150 memory unit, 200 artificial intelligence, 500 mold suppression support system, 909 electronic circuit, 910 processor, 921 memory, 922 auxiliary storage device, 930 input interface, 940 output interface, 950 communication device.

Claims

1. A prompt generation unit acquires image data of a surrounding area including a mold suppression area which is a target area for suppressing mold growth, and estimation request information which is information for estimating the factors causing mold growth and suppression measures to suppress mold growth using the image data, and generates a prompt based on the image data and the estimation request information. A countermeasure support unit that obtains the prompt and outputs suppression support information including the cause of occurrence and the suppression countermeasure based on the prompt. A mold suppression support device equipped with [a specific feature].

2. The prompt generation unit, The mold suppression support device according to claim 1, wherein an infrared image of the surrounding area captured by an infrared imaging device is acquired as the image data.

3. The prompt generation unit, The mold suppression support device according to claim 1 or claim 2, wherein the surrounding area is captured by an all-around imaging device and an all-around image is acquired as the image data.

4. The mold suppression support device is The system includes an image recognition unit that acquires the aforementioned image data and outputs the relative position of the surrounding environment in the mold suppression region based on the aforementioned image data. The prompt generation unit, A mold suppression support device according to claim 1 or claim 2, which generates the prompt based on the image data, the estimation request information, and the relative position of the surrounding environment.

5. The prompt generation unit, A mold suppression support device according to claim 1 or 2, which acquires basic information indicating the status of the mold suppression area or the surrounding area, the operating status and settings of equipment in the mold suppression area or the surrounding area, the temperature and humidity of the region including the mold suppression area or the surrounding area, meteorological data of the region including the mold suppression area or the surrounding area, constraints of the mold suppression area or the surrounding area, and at least one of recommended values ​​for temperature and humidity as environmental condition information, and creates the prompt based on the image data, the estimation request information and the environmental condition information.

6. The mold suppression support device is The system includes a database of countermeasures that stores support products and improvement examples used in estimating the aforementioned suppression support information. The prompt generation unit, The mold suppression support device according to claim 1 or claim 2, wherein the prompt includes information for estimating the suppression support information using the countermeasures database.

7. The aforementioned support department for countermeasures, The mold suppression support device according to claim 1 or claim 2, which provides confirmation recommendation information, which is information necessary for outputting the suppression support information.

8. The mold suppression support device is The system includes an information receiving unit that receives the aforementioned confirmation recommendation information, The prompt generation unit, The mold suppression support device according to claim 7, which generates the prompt using the aforementioned confirmation recommendation information.

9. The mold suppression support device is The system includes an information receiving unit that receives additional information which is feedback to the aforementioned suppression support information, The prompt generation unit, The mold suppression support device according to claim 1 or claim 2, which generates the prompt using the additional information.

10. The aforementioned support department for countermeasures, The mold suppression support device according to claim 1 or claim 2, wherein the prompt is input to artificial intelligence and the suppression support information is obtained from the artificial intelligence.

11. The aforementioned support department for countermeasures, The mold suppression support device according to claim 6, which learns the output of the suppression support information in advance using the countermeasures database.

12. A mold suppression support device according to claim 1 or claim 2, Artificial intelligence and A mold suppression support system equipped with [a specific feature].

13. The computer acquires image data of the surrounding area including the mold suppression area, which is the target area for suppressing mold growth, and estimation request information, which is information for estimating the factors causing mold growth and suppression measures to suppress mold growth using the image data, and creates a prompt based on the image data and the estimation request information. A mold suppression support method comprising a computer that obtains the prompt and outputs suppression support information including the cause of occurrence and the suppression measures based on the prompt.

14. A prompt creation process that acquires image data of a surrounding area including a mold suppression area which is a target area for suppressing mold growth, and estimation request information which is information for estimating the factors causing mold growth and suppression measures to suppress mold growth using the image data, and creates a prompt based on the image data and the estimation request information. A countermeasure support process that obtains the prompt and outputs suppression support information including the cause and the suppression countermeasure based on the prompt. A mold suppression support program that instructs a computer to perform certain actions.

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