Microbiological analysis system and microbiological analysis method

Abstract

A microbiological analysis system (1) estimates whether or not a target microbe (212) is present in a target space (SP), or estimates the amount of the target microbe (212) present in the target space (SP). The microbiological analysis system (1) is provided with a first information acquisition unit (20) and a control unit (40). A first information acquisition unit (20) acquires first information (21) relating to a subject space (SP), said first information being information that differs from the presence or absence of a subject microorganism (212) itself and the amount of the subject microorganism (212) present. The control unit (40) estimates, on the basis of the first information (21), the presence or absence of the target microorganism (212) in the target space (SP) or the amount of the target microorganism (212).

Description

Technical Field

[0001] It involves microbial analysis systems and microbial analysis methods. Background Technology

[0002] Previously, genomic materials or DNA were obtained from microorganisms and then amplified to identify specific regions of the genomic materials or DNA, thereby detecting microorganisms (Patent Document 1 (Japanese Patent Publication No. 2020-529869)). Summary of the Invention

[0003] The problem that the invention aims to solve

[0004] However, previous methods for detecting microorganisms required expert operation and specialized equipment, which sometimes involved a lot of effort and time.

[0005] Methods for solving problems

[0006] The first-view microbial analysis system is a system for estimating the existence or quantity of target microorganisms in an object space. It comprises a first information acquisition unit and a control unit. The first information acquisition unit acquires first information about the object space, which differs from information regarding the existence and quantity of the target microorganisms themselves. Based on the first information, the control unit estimates the existence or quantity of the target microorganisms in the object space.

[0007] This microbial analysis system eliminates the need for 100% inspection, thus reducing the time and cost required for testing.

[0008] The second perspective's microbial analysis system is similar to the first perspective's system, where the first piece of information is the environmental information of the object space. This environmental information concerns the quantity of samples collected from the object space that are highly correlated with the presence of the object's microorganisms.

[0009] In this microbial analysis system, by using the amount of samples that are highly correlated with the amount of the target microorganism as environmental information, the presence of the target microorganism can be inferred based on its surrounding environment.

[0010] The third-view microbial analysis system is similar to the first-view system, wherein the first information includes either information about representative microorganisms coexisting with the target microorganism in the object space or information about representative microorganisms that inhibit the presence of the target microorganism. The information about the representative microorganisms includes whether or not the representative microorganisms exist in the object space, or their quantity. Based on the information about the representative microorganisms as the first information, the control unit estimates whether or not the target microorganism exists or its quantity.

[0011] In this microbial analysis system, even for target microorganisms that are difficult to measure, representative microorganisms that are easy to measure can be measured, and the presence of target microorganisms can be inferred based on the relationship between the two.

[0012] The fourth viewpoint's microbial analysis system is similar to the third viewpoint's system, in which the target microorganisms include microorganisms attached to a filter that captures airborne matter in the target space.

[0013] This microbial analysis system can infer the presence of target microorganisms attached to the filter.

[0014] The fifth perspective of microbial analysis systems, such as those of the third or fourth perspectives, also includes an image analysis unit. This unit identifies microorganisms based on their shape. Representative microorganisms are those whose size can be determined through image analysis by the image analysis unit.

[0015] In this microbial analysis system, by using the image resolution unit to identify representative microorganisms of larger size, the presence of target microorganisms can be easily inferred, even if they can only be analyzed by culture methods.

[0016] The sixth viewpoint of microbial analysis system is similar to the third or fourth viewpoint system, wherein the representative microorganism is a microorganism that can be cultured or PCR-reacted more safely than the target microorganism in terms of the safety indicators indicated by the Biosafety Level (BSL), or a microorganism that can be cultured or PCR-reacted more rapidly than the target microorganism.

[0017] In this microbial analysis system, the presence of the target microorganism can be easily inferred by culturing or performing a PCR reaction on a representative microorganism, which is safer and faster than the target microorganism.

[0018] The seventh viewpoint's microbial analysis system, like the systems of any of the third to sixth viewpoints, further includes a correspondence information storage unit. This unit stores correspondence information showing the relationship between the target microorganism and representative microorganisms. The control unit further estimates the presence or quantity of the target microorganism based on this correspondence information.

[0019] In this microbial analysis system, the presence of the target microorganism can be easily predicted by using information about the representative microorganism and the correspondence between the target microorganism and the representative microorganism.

[0020] The microbial analysis system of the eighth perspective is similar to the system of the seventh perspective. In this system, the correspondence information storage unit acquires and stores correspondence information as the learning result of a machine learning machine, which learns the correspondence between target microorganisms and representative microorganisms. Based on the results of the correspondence information, the control unit infers the existence or quantity of the target microorganism, according to the presence or quantity of the representative microorganism.

[0021] In this microbial analysis system, the presence of representative microorganisms can be inferred with high accuracy based on the learning results of the machine learning machine.

[0022] The microbial analysis system of the ninth viewpoint is the same as the system of any of the third to eighth viewpoints, wherein the representative microorganism is one or more selected from the group consisting of fungi, bacteria, pollen and viruses.

[0023] In this microbial analysis system, the presence of the target microorganism can be easily inferred by using a specified representative microorganism.

[0024] The microbial analysis system of the tenth viewpoint is like the system of the seventh or eighth viewpoint, wherein the correspondence information includes at least one of the following correspondences: the object microorganism and the representative microorganism are any one of the first fungus and the second fungus, the first bacterium and the second bacterium, the first pollen and the second pollen, and the first virus and the second virus.

[0025] In this microbial analysis system, the presence of the target microorganism can be inferred even when the target microorganism and the representative microorganism are in the same group of microorganisms.

[0026] The microbial analysis system of the eleventh viewpoint is like the system of the seventh or eighth viewpoint, wherein the correspondence information includes at least one of the following correspondences: when the target microorganism is a fungus, the representative microorganism is any one of bacteria, pollen, and virus; when the target microorganism is a bacterium, the representative microorganism is any one of fungi, pollen, and virus; when the target microorganism is pollen, the representative microorganism is any one of fungi, bacteria, and virus; when the target microorganism is a virus, the representative microorganism is any one of fungi, bacteria, and pollen.

[0027] In this microbial analysis system, the presence of the target microorganism can be inferred even when the target microorganism and the representative microorganism are contained in different groups of microorganisms.

[0028] The microbial analysis system of the twelfth viewpoint is the same as the system of any of the ninth to eleventh viewpoints, wherein the fungi include one or more species selected from the group consisting of: *Aspergillus*, *Nigrospora*, *Cladosporium*, *Fusarium*, *Alternaria*, *Schizophyllum*, *Penicillium*, *Epicoccum*, *Hortaea*, *Eupenidiella*, and *Hymenopterus*. Fungi of the genera *Chaetomium*, *Trametes*, *Pseudopithomyces*, *Toxicocladosporium*, *Peniophora*, *Talaromyces*, *Didymella*, *Pleurotus*, *Wallemia*, *Curvularia*, *Loweporus*, *Periconia*, *Candida*, and *Gibberellinia*. Fungi of the genus Gibberella, fungi of the genus Auricularia, fungi of the genus Malassezia, fungi of the genus Naganishia, fungi of the genus Neurospora, fungi of the genus Ganoderma, fungi of the genus Engyodontium, fungi of the genus Ustilaginoidea, fungi of the genus Peroneutypa, fungi of the genus Flammulina, fungi of the genus Filobasidium, fungi of the genus Cercospora, fungi of the genus Hannaella, and fungi of the genus Pseudomonas. Fungi belonging to the genera *Coprinopsis*, *Irpex*, *Phlebia*, *Pyronema*, *Microascus*, *Sterigmatomyces*, *Trichosporon*, *Spissiomyces*, *Botrytis*, *Rhodotorula*, *Stachybotrys*, *Fibroporia*, and *Bjerkandera*.Fungi belonging to the genera *Phanerochete*, *Emmia*, *Coprinellus*, *Trechispora*, *Acremonium*, *Aureobasidium*, *Lopharia*, *Heterochaete*, *Cutaneotrichosporon*, *Aplosporella*, and *Eutypella*.

[0029] In this microbial analysis system, the presence of the target microorganism can be easily inferred by using a specified fungus as a representative microorganism.

[0030] The microbial analysis system of the thirteenth viewpoint is the same as the system of any of the ninth to eleventh viewpoints, wherein the bacteria include one or more species selected from the group consisting of Streptococcus, Acinetobacter, Alcaligenaceae, Pseudomonas, Paracoccus, Sphingomonas, Corynebacterium, Staphylococcus, Haemophilus, parvum, Clostridium botulinum, and Chlamydia psittaci.

[0031] In this microbial analysis system, the presence of the target microorganism can be easily inferred by using specified bacteria as representative microorganisms.

[0032] The microbial analysis system of the fourteenth viewpoint is the same as that of any of the views from the ninth to the eleventh viewpoints, wherein the pollen includes one or more species selected from the group consisting of the following: Humulus pollen, Boehmeria pollen, Acalypha pollen, Magnolia pollen, Artemisia pollen, Cucumis pollen, Astragalus pollen, Pouzolzia pollen, Osmanthus pollen, Triticum pollen, Citrullus pollen, Podocarpus pollen, Digitaria pollen, Funaria pollen, Solanum pollen, Allium pollen, and Glycine pollen.

[0033] In this microbial analysis system, the presence of the target microorganism can be easily inferred by using specified pollen as a representative microorganism.

[0034] The microbial analysis system of the fifteenth point is the same as the system of any of the ninth to eleventh points, wherein the virus includes one or more of the following groups: influenza virus, monkeypox virus, rabies virus, dengue virus, and Japanese encephalitis virus.

[0035] In this microbial analysis system, the presence of the target microorganism can be easily inferred by using a specified virus as a representative microorganism.

[0036] The microbial analysis system of the sixteenth viewpoint is the same as that of any of the views from the third to the fifteenth viewpoints. In this system, regarding the relationship between the target microorganism and the representative microorganism, the target microorganism, being any of the following fungi—Gibberella, Nigrospora, Fusarium, Cladosporium, Epicoccum, Periconia, Alternaria, Penicillium, Filobasidium, or Pleurotus—is negatively correlated with the representative microorganism of Aspergillus. Conversely, the target microorganism, being a Penicillium or Nigrospora fungus, is positively correlated with the representative microorganism of Boehmeria pollen. The target microorganisms of *Corynebacterium* or *Alternaria* are positively correlated with the representative microorganisms of *Humulus* pollen. The target microorganisms of *Enhydrobacter* are positively correlated with the representative microorganisms of any of the following genera: *Tramaetes*, *Chaetomiun*, or *Boehmeria* pollen. Among the target or representative microorganisms, *Staphylococcus*, *Gibberella*, *Cladosporium*, *Cercospora*, and *Curvularia* fungi are positively correlated with each other. *Streptococcus*, *Haemophilus*, *Solanum* pollen, and *Cucumis* pollen are positively correlated with each other.

[0037] This microbial analysis system can infer the presence of a target microorganism from a combination of multiple target microorganisms and representative microorganisms.

[0038] The microbial analysis system of the seventeenth viewpoint is similar to the system of the seventh viewpoint, in which the control unit uses machine learning to generate corresponding relationship information.

[0039] In this microbial analysis system, the correspondence information can be easily generated by utilizing machine learning.

[0040] The microbial analysis system of the eighteenth viewpoint is similar to the system of the first viewpoint, wherein the first information is the operating status information regarding the operating status of the air conditioning unit installed in the target space. Based on the operating status information as the first information, the control unit estimates whether the target microorganism exists or its quantity.

[0041] In this microbial analysis system, the presence of target microorganisms can be easily inferred using the operating status information of the air conditioning unit.

[0042] The microbial analysis system of the nineteenth viewpoint is similar to the system of the eighteenth viewpoint, wherein the first information is information about the correspondence between the operating status of the air conditioning unit and the types and quantities of representative microorganisms. Based on the information about the correspondence between the operating status of the air conditioning unit and the types and quantities of representative microorganisms as the first information, the control unit estimates whether the target microorganism exists or its quantity.

[0043] In this microbial analysis system, the presence of target microorganisms can be easily inferred by using information on the correspondence between the operating status of the air conditioning unit and the types and quantities of representative microorganisms.

[0044] The microbiological analysis system of the twentieth viewpoint is similar to the system of the eighteenth or nineteenth viewpoint, wherein the operating status of the air conditioning unit includes at least one of the following: operating time of the air conditioning unit, operating mode, air volume, set temperature, set humidity, temperature and humidity of the intake air, and non-cleaning period of the air conditioning unit.

[0045] In this microbial analysis system, the presence of the target microorganism can be easily inferred even when the presence of the target microorganism varies depending on the operating status of the air conditioning unit.

[0046] The microbial analysis system of viewpoint 21 is similar to the system of any of viewpoints 3 through 18, wherein the first information is object space association information. The object space association information includes at least one of the following: climate, weather, geographical features, latitude, longitude, and altitude of the location where the object space exists; characteristics of buildings within the object space; and the family structure of the residents in the object space. The control unit further uses the object space association information as the first information to estimate the presence or quantity of object microorganisms.

[0047] In this microbial analysis system, the presence of object microorganisms in the object space can be easily inferred by further utilizing object space association information.

[0048] The twenty-second viewpoint describes a microbiological analysis method for inferring the existence or quantity of target microorganisms in an object space. This method infers the existence or quantity of target microorganisms based on first information about the object space, which differs from information regarding the actual existence and quantity of the target microorganisms themselves.

[0049] This microbial analysis method does not require 100% inspection, thus reducing the time and cost required for inspection. Attached Figure Description

[0050] Figure 1 This is a diagram of the microbial analysis system.

[0051] Figure 2 This is a diagram illustrating an example of the relationship between fungi, bacteria, and pollen.

[0052] Figure 3 This is a diagram illustrating an example of a fungus that has a negative correlation with Aspergillus.

[0053] Figure 4 This is a flowchart illustrating an example of the processing of a microbial analysis system.

[0054] Figure 5 This is an example of a graph showing the relative proportions of fungal presence in different cities.

[0055] Figure 6 This is a graph showing an example of the relative proportions of the presence of fungi.

[0056] Figure 7 This is an example of a heatmap showing the ratio of fungal presence according to the season.

[0057] Figure 8 This is an example of a heatmap showing the ratio of fungal presence in a city.

[0058] Figure 9 This is an example of a heatmap showing the ratio of fungal presence by region.

[0059] Figure 10 This is a figure illustrating an example of the relationship between bacterial diversity and non-cleaning periods.

[0060] Figure 11 This is a diagram of another microbial analysis system.

[0061] Figure 12 This is a diagram of another microbial analysis system. Detailed Implementation

[0062] (1) Overall composition of the microbial analysis system

[0063] The microbial analysis system 1 of this embodiment is shown in Figure 1 The microbial analysis system 1 uses a sampling device 200 to collect microorganisms 210 attached to the filter 101 of the air conditioning unit 100 as samples, and uses the captured images 301 of the microorganisms 210 captured by the imaging device 300 to analyze the microorganisms 210. The air conditioning unit 100 is installed in the object space (indoor space) SP contained in buildings such as houses, buildings, factories, and public facilities.

[0064] The microbial analysis system 1 is implemented by a computer and includes an image analysis unit 10, a first information acquisition unit 20, a corresponding relationship information storage unit 30, and a control unit 40.

[0065] (2) Detailed composition of the microbial analysis system

[0066] (2-1) Image Resolution Unit

[0067] The image analysis unit 10 acquires the captured image 301 of the microorganism 210 captured by the imaging device 300, and identifies the microorganism 210 based on its shape.

[0068] Microorganism 210 includes representative microorganism 211 and target microorganism 212. Representative microorganism 211 is one or more species selected from the group consisting of fungi, bacteria, pollen, and viruses. Target microorganism 211 is the microorganism whose existence or quantity in the target space SP is to be determined.

[0069] The representative microorganism 211 is defined by its size, which can be determined through image analysis by the image analysis unit 10. The size of the representative microorganism 211 is preferably 0.2 μm or more, and more preferably 2 μm or more. 0.2 μm is the same as the limit value that can be observed with an optical microscope. 2 μm is the same as the size that can be confirmed at a practical magnification (approximately 1000x) of an optical microscope. Fungi are mostly 2 μm or larger in size. It should be noted that bacteria are mostly 1 μm or smaller in size. In particular, fungi and pollen have large particle sizes and can be determined through image analysis, therefore they are preferred as representative microorganisms 211.

[0070] The target microorganisms 212 include microorganisms attached to the filter 101 of the air conditioning unit 100 that captures airborne matter in the target space SP.

[0071] (2-1-1) Fungi

[0072] The fungi include one or more species selected from the group consisting of: *Aspergillus*, *Nigrospora*, *Cladosporium*, *Fusarium*, *Alternaria*, *Schizophyllum*, *Penicillium*, *Epicoccum*, *Hortaea*, *Eupenidiella*, *Chaetomium*, *Trametes*, *Pseudo* Fungi of the genera *Pithomyces*, *Toxicocladosporium*, *Peniophora*, *Talaromyces*, *Didymella*, *Pleurotus*, *Wallemia*, *Curvularia*, *Loweporus*, *Periconia*, *Candida*, *Gibberella*, *Auricularia*, and *Malassezia*. Fungi of the genera *lassezia*, *Naganishia*, *Neurospora*, *Ganoderma*, *Engyodontium*, *Ustilaginoidea*, *Peroneutypa*, *Flammulina*, *Filobasidium*, *Cercospora*, *Hannaella*, *Coprinopsis*, *Irpex*, and *Phlebia*. Fungi, including *Pyronema*, *Microascus*, *Sterigmatomyces*, *Trichosporon*, *Spissiomyces*, *Botrytis*, *Rhodotorula*, *Stachybotrys*, *Fibroporia*, *Bjerkandera*, *Phanerochete*, *Emmia*, and *Coprinellus*.Fungi belonging to the genera *Trechispora*, *Acremonium*, *Aureobasidium*, *Lopharia*, *Heterochaete*, *Cutaneotrichosporon*, *Aplosporella*, and *Eutypella*.

[0073] Fungi may include one or more species selected from the group consisting of the following fungi: Clanostachys, Sordariomycetes, Amphobotrys, Dokmaia, and Bipolaris.

[0074] (2-1-2)Pollen

[0075] Pollen includes one or more species selected from the group consisting of the following: Humulus, Boehmeria, Acalypha, Magnolia, Artemisia, Cucumber, Astragalus, Pouzolzia, Osmanthus, Triticum, Citrullus, Podocarpus, Digitaria, Funaria, Solanum, Allium, and Glycine.

[0076] Pollen may contain one or more species selected from the group consisting of: Astragalus, Ulmus, Brassica, Dinebra, and Streptophyta.

[0077] (2-1-3) Bacteria

[0078] The bacteria include one or more species selected from the group consisting of Streptococcus, Acinetobacter, Alcaligenaceae, Pseudomonas, Paracoccus, Sphingomonas, Corynebacterium, Staphylococcus, Haemophilus, parvum, Clostridium botulinum, and Chlamydia psittaci.

[0079] The bacteria may include one or more species selected from the group consisting of mitochondria, chloroplasts, bacteria of the genera *Brevundimonas*, *Prebotella*, *Micrococcus*, *Roseomonas*, *Craurococcus Caldobatus*, *Allorhizobium*, *Neisseria*, *Skermanella*, *Enhydrobactor*, *Cutibacterium*, and *Lactobacillus*. Additionally, the bacteria may include one or more species selected from the group consisting of *Acinetobacter*, *Craurococcus-Caldovatus* (pathogens), and *Lactocacillus* (probiotics).

[0080] (2-1-4) Virus

[0081] The virus includes one or more of the following groups: influenza virus, monkeypox virus, rabies virus, dengue virus, and Japanese encephalitis virus.

[0082] (2-2) First Information Acquisition Department

[0083] The first information acquisition unit 20 acquires information that differs from the existence and quantity of the object microorganism 212 itself, namely, the first information 21 about the object space SP.

[0084] In this embodiment, the first information acquisition unit 20 acquires first information 21 from the analysis result of the captured image 301 by the image analysis unit 10. The first information 21 includes either information about a representative microorganism 211 that coexists with the target microorganism 212 in the object space SP, or information about a representative microorganism 211 that inhibits the existence of the target microorganism 212. The information about the representative microorganism 211 includes whether or not the representative microorganism 211 exists in the object space SP.

[0085] (2-3) Correspondence information storage unit

[0086] The correspondence information storage unit 30 stores correspondence information 31 that shows the correspondence between the object microorganism 212 and the representative microorganism 211.

[0087] Correspondence information 31 includes information about whether the target microorganism 212 and the representative microorganism 211 are positively or negatively correlated. If the target microorganism 212 and the representative microorganism 211 are positively correlated, then the target microorganism 212 is also present if the representative microorganism 211 is present. If the target microorganism 212 and the representative microorganism 211 are negatively correlated, then the presence of the target microorganism 212 is suppressed if the representative microorganism 211 is present.

[0088] In this embodiment, correspondence information 31 regarding the correspondence between representative microorganism 211 and target microorganism 212 is obtained in advance and stored in the correspondence information storage unit 30.

[0089] Figure 2 This is a diagram illustrating an example of the relationship between fungi, bacteria, and pollen.

[0090] Figure 2The listed fungi (Fungi) are the following 20 species: *Aspergillus*, *Nigrospora*, *Cladosporium*, *Alternaria*, *Schizophyllum*, *Penicillium*, *Chaetomium*, *Trametes*, *Pseudopithomyces*, and *Toxocytozoa*. Fungi belonging to the genera *icocladosporium*, *Curvularia*, *Candida*, *Gibberella*, *Ganoderma*, *Cercospora*, *Clanostachys*, *Sordariomycetes*, *Amphobotrys*, *Dokmaia*, and *Bipolaris*.

[0091] Among them, fungi of the genera *Arpergillus*, *Nigrospora*, *Cladosporium*, *Alternaria*, *Penicillium*, *Curvularia*, *Cercospora*, and *Bipolaris* are potentially harmful fungi.

[0092] in addition, Figure 2The listed bacteria are the following 19 species: Paracoccus, Sphingomonas, Corynebacterium, Staphylococcus, Haemophilus, Streptococcus, Mitochordria, Chloroplasts, and Brevundimonas. Bacteria belonging to the genera *Prebotella*, *Micrococcus*, *Roseomonas*, *Craurococcus Caldobatus*, *Allorhizobium*, *Neisseria*, *Skermanella*, *Enhydrobactor*, *Cutibacterium*, and *Lactobacillus*.

[0093] Among them, bacteria of the genera *Sphingomonas*, *Corynebacterium*, *Staphylococcus*, *Haemophilus*, *Streptococcus*, *Brevundimonas*, *Prebotella*, *Roseomonas*, *Craurococcus Caldobatus*, *Allorhizobium*, *Neisseria*, *Skermanella*, and *Enhydrobactor* are potentially harmful bacteria.

[0094] in addition, Figure 2The listed pollens are the following 20 species: *Humulus* pollen, *Boehmeria* pollen, *Acalypha* pollen, *Magnolia* pollen, *Artemisia* pollen, *Cucumis* pollen, *Astragalus* pollen, *Pouzolzia* pollen, *Osmanthus* pollen, and wheat pollen. Pollen from the genera *Triticum*, *Citrullus*, *Podocarpus*, *Digitaria*, *Funaria*, *Solanum*, *Allium*, *Ulmus*, *Brassica*, *Dinebra*, and *Streptophyta*.

[0095] Among them, pollen from the genera *Humulus*, *Artemisia*, *Solanum*, and *Ulmus* is potentially harmful.

[0096] For example, such as Figure 2 As shown, regarding the relationship between the target microorganism 212 and the representative microorganism 211, the target microorganism 212, which is a fungus of the genus Penicillium or Nigrospora, is positively correlated with the representative microorganism 211, which is a pollen of the genus Boehmeria.

[0097] In addition, the target microorganism 212, which is a bacterium of the genus Corynebacterium or a fungus of the genus Alternaria, is positively correlated with the representative microorganism 211, which is the pollen of Humulus.

[0098] Microorganism 212, which is a bacterium of the genus Enhydrobacter, is positively correlated with microorganism 211, which is a representative of any of the genera Tramaetes, Chaetomiun, or Boehmeria pollen.

[0099] Furthermore, among the target microorganisms 212 or representative microorganisms 211, bacteria of the genus *Staphylococcus*, fungi of the genus *Gibberella*, fungi of the genus *Cladosporium*, fungi of the genus *Cercospora*, and fungi of the genus *Curvularia* showed positive correlations. Additionally, bacteria of the genus *Streptococcus*, bacteria of the genus *Haemophilus*, pollen of the genus *Solanum*, and pollen of the genus *Cucumis* showed positive correlations.

[0100] Figure 3 This is a diagram illustrating an example of a fungus that has a negative correlation with the genus Aspergillus.

[0101] like Figure 3 As shown, for example, regarding the relationship between the target microorganism 212 and the representative microorganism 211, the target microorganism 212, which is any of the fungi of the genera Gibberella, Nigrospora, Fusarium, Cladosporium, Epicoccum, Periconia, Alternaria, Penicillium, Filobasidium, or Pleurotus, has a negative correlation with the representative microorganism 211, which is a fungi of the genera Aspergillus.

[0102] (2-4) Control Unit

[0103] The control unit 40 is implemented by a computer. The control unit 40 includes a control processing unit and a storage device (not shown). The control processing unit can use a processor such as a CPU or a GPU. The control processing unit reads a program stored in the storage device and performs prescribed image processing and calculations according to the program. Furthermore, the control processing unit can write the calculation results to the storage device or read information stored in the storage device according to the program. The storage device can be used as a database.

[0104] Based on the first information 21, the control unit 40 estimates whether the target microorganism 212 exists or its quantity in the target space SP. Based on the information about the representative microorganism 211, which is the first information 21, the control unit 40 estimates whether the target microorganism 212 exists or its quantity. Furthermore, in this embodiment, the control unit 40 further estimates whether the target microorganism 212 exists or its quantity based on the correspondence information 31.

[0105] (3) Overall operation of the microbial analysis system

[0106] use Figure 4 The flowchart illustrates an example of the processing of the microbial analysis system 1.

[0107] In step S101, the image analysis unit 10 acquires the captured image 301 taken by the imaging device 300. In this embodiment, the captured image 301 is an image of microorganisms 210 collected by the sampling device 200 from the filter 101 of the air conditioning unit 100 provided in the object space SP as a sample.

[0108] The sampling device 200 collects samples by immersing a filter 101 cut to a specified size in an elution buffer to elute microorganisms 210 attached to the filter 101. The elution buffer is, for example, phosphate-buffered saline (PBS-T). Alternatively, the sampling device 200 may use, for example, a 10cm piece of... 2 The size and number of filters 101 used in the sampling device 200 are not limited to this.

[0109] The imaging device 300 captures images of microorganisms 210 collected as samples from the filter 101. The imaging device 300 may use, for example, a JIS B7271 (portable microbial observer). The imaging device 300 is not limited to this.

[0110] In step S102, the image analysis unit 10 uses the captured image 301 of the microorganism 210 obtained in step S1 to identify the microorganism 210.

[0111] In this embodiment, the image analysis unit 10 identifies representative microorganisms 211 of a size that can be determined by image analysis from the microorganisms 210 collected as samples from the filter 101 of the air conditioning unit 100 installed in the object space SP. In this embodiment, the representative microorganism 211 is a fungus of the genus *Aspergillus*. The representative microorganism 211 is not limited to fungi of the genus *Aspergillus*, but can be one or more selected from the group consisting of fungi, bacteria, pollen, and viruses.

[0112] In step S103, the first information acquisition unit 20 acquires information about the representative microorganism 211 as first information 21. In this embodiment, the first information acquisition unit 20 acquires the presence or absence of *Aspergillus* fungi as information about the representative microorganism 211. If *Aspergillus* fungi are present in the captured image 301 acquired in step S1, the first information acquisition unit 20 may also acquire the amount of *Aspergillus* fungi present as information about the representative microorganism 211.

[0113] In step S104, the control unit 40 estimates whether the target microorganism 212 exists or its quantity based on the first information 21 obtained in step S3, namely the information about the representative microorganism and the corresponding relationship information stored in the corresponding relationship information storage unit 30.

[0114] In this embodiment, the representative microorganism is a fungus of the genus *Aspergillus*, and the target microorganism is a fungus of the genus *Nigrospora*. The correspondence between *Aspergillus* and *Nigrospora* is negatively correlated. The relationship between the target microorganism 212 and the representative microorganism 211 is not limited to the relationship between *Nigrospora* and *Aspergillus*. Microorganisms with a positive or negative correlation with the representative microorganism 211 are used as the target microorganism 212 to presuppose their presence or quantity. In this embodiment, when the first information acquisition unit 20 acquires information that the presence of *Aspergillus* is detected in step S3, in step S4, the control unit 40 presupposes that the presence of *Nigrospora* is suppressed.

[0115] (4) Characteristics of microorganisms present in the filters of air conditioning units

[0116] The inventors of this application, by collecting filters 101 of air conditioning units 100 in 12 cities in China and investigating the microorganisms 210 present in the filters 101, discovered that there are malignant microorganisms (allergens, etc.) in the filters 101, that the microorganisms present in the filters 101 are related to the usage mode or regionality of the air conditioning unit 100, and that specific combinations of microorganisms have a symbiotic relationship of mutual influence and coexistence.

[0117] (4-1) Overall tendency of attached bacteria

[0118] Figure 5 This is a graph showing an example of the relative proportions of fungi present on the filters 101 of air conditioning units 100 during winter in 12 cities. Figure 6 This is a graph showing the relative proportion of fungi present on the filter 101 of the air conditioning unit 100 during winter, and is an example of the total value for all 12 cities. The 12 cities include northern cities 1-3 (N1-N3) and southern cities 1-9 (S1-S9).

[0119] like Figure 5 As shown, in most of the 12 cities except for the northern city 3 (N3), the relative proportion of fungal presence was greater than that of Aspergillus fungi. Additionally, as... Figure 6As shown, among the relative proportions of fungi detected in 12 cities across China, Aspergillus accounted for 49.44%, a significant difference compared to the second most prevalent genus, Nigrospora (8.82%). On the other hand, among the relative proportions of bacteria detected in the same 12 cities, Paracoccus was the most prevalent (6.12%), showing no significant difference compared to the second most prevalent genus, Acinetobacter (4.85%) (not illustrated).

[0120] Figure 7 This is an example of a heatmap showing the ratio of the amount of fungi detected from the filter 101 of the air conditioning unit 100 according to the season. The ratio of the amount of Aspergillus fungi is particularly high in winter, summer, and autumn.

[0121] (4-2)Regional

[0122] A combination of similar types of fungi and bacteria present in the filter 101 of the air conditioning unit 100.

[0123] Figure 8 This is an example of a heatmap showing the ratio of the amount of fungi detected from the filter 101 of the air conditioning unit 100 according to the city.

[0124] For example, regarding fungi, the types of fungi present in the filter 101 of the air conditioning unit 100 are similar in the combinations of southern city 7 (S7) (not shown) and southern city 4 (S4), southern city 8 (S8) and northern city 2 (N2), southern city 5 (S5) and southern city 9 (S9), and southern city 6 (S6), southern city 3 (S3), southern city (S1) and southern city 2 (S2).

[0125] In addition, regarding bacteria, the types of bacteria present in the filter 101 of the air conditioning unit 100 are similar (not shown) in combinations such as the combination of northern city 3 (N3), southern city 9 (N9) and southern city 7 (S7), the combination of southern city 5 (S5), southern city 2 (S2) and southern city (S6), and the combination of northern city 2 (N2), southern city 1 (S1) and northern city 1 (N1).

[0126] In addition, the proportions of fungi and bacteria present in the filter 101 of the air conditioning unit 100 tend to differ between northern and southern regions.

[0127] Figure 9This is an example of a heatmap showing the ratio of the amount of fungi detected from the filter 101 of the air conditioning unit 100 according to the north-south region.

[0128] The northern region includes northern cities 1 to 3 (N1 to N3). The southern region includes southern cities 1 to 9 (S1 to S9).

[0129] The further south you go, the more prevalent the genus *Arpergillus* becomes among fungi. Additionally, in the south, the genera *Roseomonas* (pathogens) and *Craurococcus-Caldovatus* (pathogens) are more abundant (not shown in the diagram).

[0130] (4-3) Relationship with environmental factors

[0131] The diversity and quantity of bacteria attached to the filter 101 of the air conditioning unit 100 are related to the non-cleaning period of the air conditioning unit 100, the family structure (number of people) of the residents in the object space SP, and the characteristics (number of floors) of the building including the object space SP.

[0132] Figure 10 This is a graph illustrating, as an example, the relationship between the diversity of bacteria attached to the filter 101 of an air conditioning unit 100 and the period of non-cleaning in 12 cities. The vertical axis represents bacterial diversity, and the horizontal axis represents the period of non-cleaning. Figure 10 As shown, when the non-cleaning period of the air conditioning unit 100 is long, the diversity of bacteria decreases.

[0133] Furthermore, the diversity of bacteria attached to the filter 101 of the air conditioning unit 100 tends to increase slightly when the number of family members is large (not shown). Additionally, regarding the amount of microorganisms attached to the filter 101 of the air conditioning unit 100, there is a tendency for the following: the larger the family structure (number of people) of the residents in the target space SP, the more *Candida* fungi (pathogens) and *Roseomonas* bacteria (pathogens); the higher the number of layers, the more *Nigrospora* fungi (pathogens) and *Lactocacillus* (probiotics) (not shown).

[0134] (5) Features

[0135] (5-1)

[0136] The microbial analysis system 1 of this embodiment is a system for estimating the presence or quantity of target microorganisms 212 in a target space SP. It includes a first information acquisition unit 20 and a control unit 40. The first information acquisition unit 20 acquires first information 21 about the target space SP, which is information different from the presence and quantity of the target microorganisms 212 themselves. Based on the first information 21, the control unit 40 estimates the presence or quantity of the target microorganisms 212 in the target space SP.

[0137] In the past, the analysis of microorganisms was laborious and time-consuming. For example, it required cultivation and specialized skills and equipment.

[0138] In this microbial analysis system 1, even without directly measuring the microorganism (target microorganism) 212 that is to be determined to be present, the presence or quantity of the target microorganism 212 that may be attached to the filter 101 of the air conditioning unit 100 can be inferred by knowing the presence or quantity of the symbiotic microorganism (representative microorganism) 211. In this microbial analysis system 1, it is not necessary to check all microorganisms, thus reducing the time and cost required for inspection.

[0139] (5-2)

[0140] In the microbial analysis system 1 of this embodiment, the first information 21 includes either information about a representative microorganism 211 that coexists with the target microorganism 212 in the object space SP, or information about a representative microorganism 211 that inhibits the existence of the target microorganism 212. The information about the representative microorganism 211 includes whether or not the representative microorganism 211 exists in the object space SP.

[0141] In this microbial analysis system 1, information about the presence of representative microorganisms 211 related to the target microorganism 212 can be obtained.

[0142] (5-3)

[0143] In the microbial analysis system 1 of this embodiment, the target microorganism 212 includes microorganisms attached to the filter 101 that captures airborne matter in the target space SP.

[0144] In this microbial analysis system 1, the presence of target microorganisms 212 attached to the filter 101 of the air conditioning unit 100 can be inferred.

[0145] (5-4)

[0146] In the microbial analysis system 1 of this embodiment, an image analysis unit 10 is also included. The image analysis unit 10 identifies microorganisms 210 based on their shape. Microorganisms 211 are defined as those whose size can be identified by image analysis by the image analysis unit 10.

[0147] By selecting a representative microorganism 211 that is large in size, capable of image analysis, and easy to detect, effort, time, cost, and safety risks can be reduced. This microbial analysis system 1 is particularly effective in situations where the target microorganism 212 is a dangerous microorganism, where the target microorganism 212 is difficult to culture, where the target microorganism 212 is too small to be image-analyzed, or where there are microorganisms with similar shapes to the target microorganism 212 that are difficult to image-analyze.

[0148] In this microbial analysis system 1, by using the image analysis unit 10 to identify the larger representative microorganism 211, the presence of the target microorganism 212 can be easily inferred, even if it can only be analyzed by culture method.

[0149] (5-5)

[0150] In the microbial analysis system 1 of this embodiment, a correspondence information storage unit 30 is also provided. The correspondence information storage unit 30 stores correspondence information 31 that shows the correspondence between the target microorganism 212 and the representative microorganism 211. The control unit 40 estimates the existence or quantity of the target microorganism 212 based on the information about the representative microorganism 211 as first information 21 and the correspondence information 31. The correspondence information 31 stored in the correspondence information storage unit 30 may also be known correspondence information.

[0151] In this microbial analysis system 1, the presence of the target microorganism 212 can be easily predicted by using information about the representative microorganism 211 and information about the correspondence between the target microorganism 212 and the representative microorganism 211 that is pre-stored in the correspondence information storage unit 30.

[0152] (5-6)

[0153] In the microbial analysis system 1 of this embodiment, the representative microorganism 211 is selected from one or more species in the group consisting of fungi, bacteria, pollen and viruses, and is a fungus of the genus Aspergillus.

[0154] In this microbial analysis system 1, by using Aspergillus fungi as representative microorganisms 211, the presence or quantity of target microorganisms 212 associated with the presence of Aspergillus fungi can be easily estimated.

[0155] (5-7)

[0156] In the microbial analysis system 1 of this embodiment, the fungi include one or more species selected from the group consisting of: Aspergillus, Nigrospora, Cladosporium, Fusarium, Alternaria, Schizophyllum, and Penicillium. (Fungi of the genus *Penicillium*, *Epicoccum*, *Hortaea*, *Eupenidiella*, *Chaetomium*, *Trametes*, *Pseudopithomyces*, *Toxicocladosporium*, *Peniophora*, *Talaromyces*, *Didymella*, *Pleurotus*, *Wallemia*, and *Curvularia*. Fungi of the genera *Curvularia*, *Loweporus*, *Periconia*, *Candida*, *Gibberella*, *Auricularia*, *Malassezia*, *Naganishia*, *Neurospora*, *Ganoderma*, *Engyodontium*, *Ustilaginoidea*, *Peroneutypa*, and *Flammulina*. Fungi of the genus *Filobasidium*, *Cercospora*, *Hannaella*, *Coprinopsis*, *Irpex*, *Phlebia*, *Pyronema*, *Microascus*, *Sterigmatomyces*, *Trichosporon*, *Spissiomyces*, *Botrytis*, and *Rhodotorula*. Fungi of the genera *Stachybotrys*, *Fibroporia*, *Bjerkandera*, *Phanerochete*, *Emmia*, *Coprinellus*, *Trechispora*, *Acremonium*, *Aureobasidium*, *Lopharia*, *Heterochaete*, and *Cutaneotrichosporon*.Fungi of the genera *Aplosporella* and *Eutypella*.

[0157] The microbial analysis system 1, by using Aspergillus fungi as representative microorganisms 211, can easily infer the presence of target microorganisms 212 that have a positive or negative correlation with Aspergillus fungi.

[0158] (5-8)

[0159] In the microbial analysis system 1 of this embodiment, the bacteria include one or more species selected from the group consisting of Streptococcus, Acinetobacter, Alcaligenaceae, Pseudomonas, Paracoccus, Sphingomonas, Corynebacterium, Staphylococcus, Haemophilus, parvum, Clostridium botulinum, and Chlamydia psittaci.

[0160] In this microbial analysis system 1, by using Aspergillus fungi as representative microorganisms 211, and when the target microorganism 212 is bacteria, the presence of bacteria that have a positive or negative correlation with Aspergillus fungi can be easily inferred.

[0161] (5-9)

[0162] In the microbial analysis system 1 of this embodiment, the pollen includes one or more species selected from the group consisting of: Humulus pollen, Boehmeria pollen, Acalypha pollen, Magnolia pollen, Artemisia pollen, Cucumis pollen, Astragalus pollen, Pouzolzia pollen, Osmanthus pollen, Triticum pollen, Citrullus pollen, Podocarpus pollen, Digitaria pollen, Funaria pollen, Solanum pollen, Allium pollen, and Glycine pollen.

[0163] In this microbial analysis system 1, by using Aspergillus fungi as representative microorganisms 211, and when the target microorganism 212 is pollen, the presence of pollen that has a positive or negative correlation with Aspergillus fungi can be easily inferred.

[0164] (5-10)

[0165] In the microbial analysis system 1 of this embodiment, the virus includes one or more selected from the group consisting of influenza virus, monkeypox virus, rabies virus, dengue virus and Japanese encephalitis virus.

[0166] In this microbial analysis system 1, by using Aspergillus fungi as representative microorganisms 211, when the target microorganism 212 is a virus, the presence of viruses that are positively or negatively correlated with Aspergillus fungi can be easily inferred.

[0167] (5-11)

[0168] In the microbial analysis system 1 of this embodiment, regarding the relationship between the target microorganism 212 and the representative microorganism 211, the target microorganism 212, which is any of the fungi of the genera *Gibberella*, *Nigrospora*, *Fusarium*, *Cladosporium*, *Epicoccum*, *Periconia*, *Alternaria*, *Penicillium*, *Filobasidium*, or *Pleurotus*, has a negative correlation with the representative microorganism 211, which is a fungi of the genus *Aspergillus*. The target microorganism 212, which is a fungi of the genus *Penicillium* or *Nigrospora*, has a positive correlation with the representative microorganism 211, which is a pollen of the genus *Boehmeria*. Microorganism 212, representing either Corynebacterium or Alternaria bacteria, is positively correlated with microorganism 211, representing Humulus pollen. Microorganism 212, representing either Enhydrobacterium bacteria, is positively correlated with microorganism 211, representing either Tramaetes, Chaetomiun, or Boehmeria pollen. Among microorganisms 212 or 211, Staphylococcus bacteria, Gibberella fungi, Cladosporium fungi, Cercospora fungi, and Curvularia fungi are positively correlated with each other. In addition, there is a positive correlation between Streptococcus bacteria, Haemophilus bacteria, Solanum pollen, and Cucumis pollen.

[0169] In this microbial analysis system 1, the presence of target microorganism 212 can be presumed from a combination of multiple target microorganisms 212 and representative microorganisms 211.

[0170] (5-12)

[0171] The microbial analysis method of this embodiment is a method for estimating the existence or quantity of target microorganism 212 in an object space SP. The existence or quantity of target microorganism 212 in the object space SP is estimated based on first information 21 about the object space SP, where the first information 21 is different from information regarding the existence and quantity of the target microorganism 212 itself.

[0172] This microbial analysis method does not require 100% inspection, thus reducing the time and cost required for inspection.

[0173] (6) Variations

[0174] (6-1) Variation 1A

[0175] exist Figure 1 In the microbial analysis system 1 shown, the correspondence information storage unit 30 can also obtain and store the correspondence information 32 as the learning result of the machine learning machine from the machine learning machine (not shown) that represents the correspondence between the learning object microorganism 212 and the representative microorganism 211.

[0176] Furthermore, in the correspondence information 31 and 32, the correspondence between the target microorganism 212 and the representative microorganism 211 is not limited to the correspondence between fungi of the genus *Nigrospora* and fungi of the genus *Arpergillus*. In the correspondence information 31 and 32, the correspondence between the target microorganism 212 and the representative microorganism 211 may include the correspondence between a first fungus and a second fungus, other than *Nigrospora* and *Arpergillus*. Additionally, the correspondence information 31 and 32 may also include at least one of the following correspondences: a first bacterium and a second bacterium, a first pollen and a second pollen, and a first virus and a second virus.

[0177] In addition, the correspondence information 31 and 32 may also include at least one of the following correspondences: when the target microorganism 212 is a fungus, it represents that the microorganism 211 is any one of bacteria, pollen and virus; when the target microorganism 212 is a bacterium, it represents that the microorganism 211 is any one of fungi, pollen and virus; when the target microorganism 212 is pollen, it represents that the microorganism 211 is any one of fungi, bacteria and virus; when the target microorganism 212 is a virus, it represents that the microorganism 211 is any one of fungi, bacteria and pollen.

[0178] In the microbial analysis system of Modification 1A, the presence of a representative microorganism can be inferred with high accuracy based on the correspondence information 32, which is the learning result of a machine learning machine. Furthermore, the presence of the target microorganism 212 can be inferred even when the target microorganism 212 and the representative microorganism 212 are contained in the same group of microorganisms 210. Additionally, the presence of the target microorganism 212 can be inferred even when the target microorganism 212 and the representative microorganism 211 are contained in different groups of microorganisms 210.

[0179] (6-2) Variation 1B

[0180] exist Figure 1 In the microbial analysis system 1 shown, the control unit 40 can also generate correspondence information 31 stored in the correspondence information storage unit 30 through machine learning.

[0181] In the microbial analysis system of variant 1B, the correspondence information 31 can be easily generated by utilizing machine learning.

[0182] (6-3) Variation 1C

[0183] In the microbial analysis system 1a of variant 1C, the first information 21a can also be environmental information of the object space SP. The environmental information is information about the quantity of samples collected from the object space SP that is highly correlated with the quantity of the object microorganism 212.

[0184] The microbial analysis system 1a of variant 1C is shown in Figure 11 .like Figure 11 As shown, the microbial analysis system 1a includes a first information acquisition unit 20a and a control unit 40a.

[0185] The first information acquisition unit 20a acquires environmental information of the object space SP as first information 21a. Environmental information includes, for example, the odor of fungi (mold) and the humidity within the object space SP.

[0186] If the first information 21a is the odor of fungi, the control unit 40a infers the presence of fungi as the target microorganism 212 based on the odor of fungi. Alternatively, if the first information 21a is the humidity in the target space SP, the control unit 40a infers the presence of influenza virus as the target microorganism 212 in the target space SP.

[0187] In the microbial analysis system 1a of variant 1C, the presence of the target microorganism 212 can be inferred from its surrounding environment by using the amount of the sample that is highly correlated with the amount of the target microorganism 212 as environmental information.

[0188] (6-4) Variation 1D

[0189] In the microbial analysis system 1b of Modified Example 1D, the control unit 40b estimates the presence or quantity of the target microorganism based on information about the representative microorganism 211, which serves as first information 21b.

[0190] The microbial analysis system 1b of variant 1D is shown in... Figure 12 .like Figure 12 As shown, the microbial analysis system 1b includes a first information acquisition unit 20b and a control unit 40b.

[0191] In the microbial analysis system 1b, the representative microorganism 211 is a microorganism that can be cultured or PCR-reacted more safely than the target microorganism 212 in terms of the safety indicators indicated by the biosafety level (BSL), or a microorganism that can be cultured or PCR-reacted more rapidly than the target microorganism 212.

[0192] For example, when bacteria or viruses are used as representative microorganisms 211, relatively safe microorganisms with BSL of 1 or 2 and disease classification of 5 or 4 are used as representative microorganisms 211.

[0193] Examples of bacterial BSL and disease classification are shown in Table 1.

[0194] [Table 1]

[0195] Examples of viral BSL and disease classifications are shown in Table 2.

[0196] [Table 2]

[0197] In Modified Example 1D, the sampling device 201 collects microorganisms 210 attached to the filter 101 of the air conditioning unit 100 located in the object space SP as a sample.

[0198] The sampling device 201 collects samples by immersing a filter 101 cut to a specified size in an elution buffer to elute microorganisms 210 attached to the filter 101. The elution buffer is, for example, phosphate-buffered saline (PBS-T). Alternatively, the sampling device 201 may use, for example, a 10cm piece of... 2 The size and number of filters 101 used in the sampling device 201 are not limited to this.

[0199] The eluted microorganisms 210 are cultured to increase their numbers. Alternatively, sampling device 201 extracts DNA from the cultured microorganisms and performs a PCR reaction. Then, sampling device 201 interprets the base sequence of the genes of the PCR-reacted microorganisms 210.

[0200] The first information acquisition unit 20b acquires the gene sequence data of the microorganism 210 from the sampling device 201, and as first information 21b, acquires information about the representative microorganism 211. For example, if the representative microorganism 211 is a Streptococcus bacterium, the first information acquisition unit 20b acquires information about the presence or quantity of Streptococcus bacterium based on the gene sequence data acquired from the sampling device 201, and as first information 21b.

[0201] Based on information 21b obtained by the first information acquisition unit 20b regarding Streptococcus bacteria as representative microorganism 211, the control unit 40b estimates whether or how much of the target microorganism 212 related to the presence of Streptococcus bacteria exists.

[0202] By selecting a representative microorganism 211 that is easy to culture, safe, and easy to detect, effort, time, cost, and safety risks can be reduced. This microbial analysis system 1b is particularly effective, for example, when the target microorganism 212 is a dangerous microorganism or when culturing the target microorganism 212 is difficult. The case of a Streptococcus bacterium as the representative microorganism 211 has been described, but it is not limited to this.

[0203] In the microbial analysis system 1b of Modified Example 1D, even for the target microorganism 212, which is difficult to detect, the presence of the target microorganism 212 can be inferred from the relationship between the two, as the representative microorganism 211, which is easy to detect. Furthermore, in the microbial analysis system 1b, the presence of the target microorganism 212 can be easily inferred by culturing or performing a PCR reaction on the representative microorganism 211, which is safer and faster than the target microorganism 212.

[0204] (6-5) Variation 1E

[0205] exist Figure 1 In the microbial analysis system 1 shown, the first information 21 can also be operation status information about the operation status of the air conditioning unit 100 installed in the target space SP. Based on the operation status information as the first information 21, the control unit 40 estimates whether the target microorganism 212 exists or its quantity.

[0206] In addition, Figure 1In the microbial analysis system 1 shown, information regarding the correspondence between the operating status of the air conditioning unit 100 and the types and quantities of representative microorganisms 211 can also be obtained for the first information 21. Based on the information regarding the correspondence between the operating status of the air conditioning unit 100 and the types and quantities of representative microorganisms 211 as the first information 21, the control unit 40 estimates whether the target microorganism 212 exists or its quantity.

[0207] The operating status of the air conditioning unit 100 includes at least one of the following: operating time, operating mode, air volume, set temperature, set humidity, intake air temperature and humidity, and non-cleaning period of the air conditioning unit 100. For example, the air conditioning unit 100 may send operating status information about its operating status, and the first information acquisition unit 20 may acquire the operating status information from the air conditioning unit 100.

[0208] The balance of microorganisms existing in the target space SP is affected by the operating status of the air conditioning unit 100, such as the non-cleaning period of the air conditioning unit 100, the temperature of the intake air, and the humidity of the intake air. Therefore, the accuracy of the estimation of the presence or quantity of the target microorganisms 212 can be improved by using the operating status information. For example, if the non-cleaning period of the air conditioning unit 100 is short, the diversity of microorganisms (bacteria) is high; if the non-cleaning period of the air conditioning unit 100 is long, the diversity of bacteria is low.

[0209] In the microbial analysis system of Modification 1E, the presence of the target microorganism 212 can be easily estimated using the operating status information of the air conditioning unit 100. Furthermore, the presence of the target microorganism 212 can be easily estimated by using information regarding the correspondence between the operating status of the air conditioning unit 100 and the types and quantities of the representative microorganism 211. Moreover, the presence of the target microorganism 212 can be easily estimated even if the presence changes depending on the operating status of the air conditioning unit 100.

[0210] (6-6) Variation 1F

[0211] exist Figure 1 In the microbial analysis system 1 shown, the first information acquisition unit 20 can also acquire object space association information of object space SP as first information 21.

[0212] The object space association information includes at least one of the following: climate, weather, geographical features, latitude, longitude, and altitude of the location where the object space SP exists; characteristics of the buildings including the object space SP; and the family structure of the residents in the object space SP. For example, the first information acquisition unit 20 may also acquire the object space association information via a network from a user terminal (not shown) owned by a resident of the object space SP equipped with an air conditioning unit 100. The user terminal is, for example, a smartphone owned by a resident of the object space SP.

[0213] The control unit 40 uses the information about the representative microorganism 211 as first information 21 and the object spatial association information to estimate whether the object microorganism 212 exists or its quantity.

[0214] In the microbial analysis system of variant 1F, by further using object space-related information together with information about representative microorganism 211, the presence of object microorganism 212 in object space SP can be easily inferred.

[0215] (6-7) Variation 1G

[0216] In this embodiment, the case where microorganisms 210 attached to the filter 101 of the air conditioning unit 100 installed in the object space SP are collected and analyzed as samples has been described, but this is not the only possibility. Microorganisms 210 can also be collected from the air within the object space SP. In addition, microorganisms 210 can also be collected from the walls, ceiling, floor, etc. of the object space SP.

[0217] (6-8) Variation 1H

[0218] It can also be done in Figure 1 The microbial analysis system 1 shown further includes an air conditioning unit 100, a sampling device 200, and an imaging device 300. Additionally, it is also possible to... Figure 11 The microbial analysis system 1a shown further includes an air conditioning unit 100. Additionally, it is also possible to... Figure 12 The microbial analysis system 1b shown further includes an air conditioning unit 100 and a sampling unit 201.

[0219] (6-9)

[0220] The embodiments of this disclosure have been described above. However, it should be understood that various changes in manner and details can be made without departing from the spirit and scope of this disclosure as set forth in the claims.

[0221] Symbol Explanation

[0222] 1.1a, 1b Microbial Analysis System

[0223] 10 Image Analysis Unit

[0224] 20, 20a, 20b First Information Acquisition Department

[0225] 21, 21a, 21b First Information

[0226] 30 Correspondence Information Storage Department

[0227] Correspondence information between 31 and 32

[0228] 40, 40a, 40b Control Unit

[0229] 100 Air conditioning unit

[0230] 101 Filter

[0231] 200, 201 Sampling devices

[0232] 210 Microorganisms

[0233] 211 represents microorganisms

[0234] 212 Target Microorganisms

[0235] 300 camera device

[0236] 301 captured images

[0237] Existing technical documents

[0238] Patent documents

[0239] Patent Document 1: Japanese Patent Publication No. 2020-529869

Claims

1. A microbial analysis system (1, 1a, 1b) for determining the presence or quantity of a target microorganism (212) in a presumed object space (SP), wherein, The microbial analysis system has the following features: A first information acquisition unit (20, 20a, 20b) acquires first information (21, 21a, 21b) about the object space, wherein the first information (21, 21a, 21b) is information different from the existence and quantity of the object microorganism itself; and Control unit (40, 40a, 40b), Based on the first information, the control unit estimates whether or not object microorganisms exist in the object space or the amount present.

2. The microbial analysis system as described in claim 1, wherein, The first information is the environmental information of the object space. The environmental information is information about the amount of collected material taken from the object space that is highly correlated with the amount of the object microorganisms present.

3. The microbial analysis system as described in claim 1, wherein, The first information includes either information about a representative microorganism (211) that coexists with the object microorganism in the object space or information about a representative microorganism that inhibits the existence of the object microorganism. Information about the representative microorganism includes whether the representative microorganism exists in the object space or the quantity of the representative microorganism. The control unit, based on the information about the representative microorganism as the first information, infers whether the target microorganism exists or its quantity.

4. The microbial analysis system as described in claim 3, wherein, The target microorganisms include microorganisms (210) attached to a filter (101) that traps airborne matter in the target space.

5. The microbial analysis system as described in claim 3 or 4, wherein, The microbial analysis system also includes an image analysis unit (10) that identifies microorganisms based on their shape. The representative microorganism is defined as one whose size can be determined by image analysis of the image analysis unit.

6. The microbial analysis system as described in claim 3 or 4, wherein, The representative microorganism is a microorganism that can be cultured or PCR-reacted more safely than the target microorganism in terms of safety indicators indicated by the Biosafety Level (BSL), or a microorganism that can be cultured or PCR-reacted more rapidly than the target microorganism.

7. The microbial analysis system according to any one of claims 3 to 6, wherein, The microbial analysis system also includes a correspondence information storage unit (30), which stores correspondence information (31) showing the correspondence between the target microorganism and the representative microorganism. The control unit further infers the existence or quantity of the target microorganism based on the correspondence information.

8. The microbial analysis system as described in claim 7, wherein, The correspondence information storage unit obtains and stores the correspondence information (32) as the learning result of the machine learning machine from the machine learning machine that learns the correspondence between the object microorganism and the representative microorganism. Based on the results of the correspondence information, the control unit infers whether the target microorganism exists or its quantity based on the presence or quantity of the representative microorganism.

9. The microbial analysis system according to any one of claims 3 to 8, wherein, The representative microorganism is selected from one or more species in the group consisting of fungi, bacteria, pollen and viruses.

10. The microbial analysis system as described in claim 7 or 8, wherein, The correspondence information includes at least one of the following correspondences: the object microorganism and the representative microorganism are any one of the following: the first fungus and the second fungus, the first bacterium and the second bacterium, the first pollen and the second pollen, and the first virus and the second virus.

11. The microbial analysis system as described in claim 7 or 8, wherein, The correspondence information includes at least one of the following correspondences: In the case where the target microorganism is a fungus, the representative microorganism is any one of bacteria, pollen, and virus. When the target microorganism is bacteria, the representative microorganism is any one of fungi, pollen, and viruses. When the target microorganism is pollen, the representative microorganism is any one of fungi, bacteria, and viruses. In the case where the target microorganism is a virus, the representative microorganism is any one of fungi, bacteria, and pollen.

12. The microbial analysis system according to any one of claims 9 to 11, wherein, The fungus comprises one or more species selected from the group consisting of: *Aspergillus*, *Nigrospora*, *Cladosporium*, *Fusarium*, *Alternaria*, *Schizophyllum*, *Penicillium*, *Epicoccum*, *Hortaea*, *Eupenidiella*, *Chaetomium*, *Trametes*, *Pseudomonas*, etc. Fungi of the genus *dopithomyces*, *Toxicocladosporium*, *Peniophora*, *Talaromyces*, *Didymella*, *Pleurotus*, *Wallemia*, *Curvularia*, *Loweporus*, *Periconia*, *Candida*, *Gibberella*, *Auricularia*, and *Malassezia*. Fungi of the genera *alassezia*, *Naganishia*, *Neurospora*, *Ganoderma*, *Engyodontium*, *Ustilaginoidea*, *Peroneutypa*, *Flammulina*, *Filobasidium*, *Cercospora*, *Hannaella*, *Coprinopsis*, *Irpex*, and *Phlebia*. Fungi, including fungi of the genera *Pyronema*, *Microascus*, *Sterigmatomyces*, *Trichosporon*, *Spissiomyces*, *Botrytis*, *Rhodotorula*, *Stachybotrys*, *Fibroporia*, *Bjerkandera*, *Phanerochete*, *Emmia*, and *Coprinellus*.Fungi belonging to the genera *Trechispora*, *Acremonium*, *Aureobasidium*, *Lopharia*, *Heterochaete*, *Cutaneotrichosporon*, *Aplosporella*, and *Eutypella*.

13. The microbial analysis system according to any one of claims 9 to 11, wherein, The bacteria comprise one or more species selected from the group consisting of Streptococcus, Acinetobacter, Alcaligenaceae, Pseudomonas, Paracoccus, Sphingomonas, Corynebacterium, Staphylococcus, Haemophilus, parvum, Clostridium botulinum, and Chlamydia psittaci.

14. The microbial analysis system according to any one of claims 9 to 11, wherein, The pollen includes one or more species selected from the group consisting of: Humulus, Boehmeria, Acalypha, Magnolia, Artemisia, Cucumber, Astragalus, Pouzolzia, Osmanthus, Triticum, Citrullus, Podocarpus, Digitaria, Funaria, Solanum, Allium, and Glycine.

15. The microbial analysis system according to any one of claims 9 to 11, wherein, The virus comprises one or more of the following: influenza virus, monkeypox virus, rabies virus, dengue virus, and Japanese encephalitis virus.

16. The microbial analysis system according to any one of claims 3 to 15, wherein, Regarding the relationship between the target microorganism and the representative microorganism. The target microorganism, being any one of the fungi of the genera *Gibberella*, *Nigrospora*, *Fusarium*, *Cladosporium*, *Epicoccum*, *Periconia*, *Alternaria*, *Penicillium*, *Filobasidium*, or *Pleurotus*, is negatively correlated with the representative microorganism of the genus *Aspergillus*. The target microorganisms, which are fungi of the genus *Penicillium* or *Nigrospora*, are positively correlated with the representative microorganisms, which are pollen of the genus *Boehmeria*. The target microorganisms, which are bacteria of the genus Corynebacterium or fungi of the genus Alternaria, are positively correlated with the representative microorganisms, which are pollen of Humulus. The target microorganisms, which are bacteria of the genus *Enhydrobacter*, are positively correlated with the representative microorganisms, which are fungi of the genus *Tramaetes*, fungi of the genus *Chaetomiun*, or pollen of the genus *Boehmeria*. Among the target microorganisms or the representative microorganisms There is a positive correlation between bacteria of the genus Staphylococcus, fungi of the genus Gibberella, fungi of the genus Cladosporium, fungi of the genus Cercospora, and fungi of the genus Curvularia. Streptococcus bacteria, Haemophilus bacteria, Solanum pollen, and Cucumis pollen are positively correlated.

17. The microbial analysis system of claim 7, wherein, The control unit generates the correspondence information through machine learning.

18. The microbial analysis system as described in claim 1, wherein, The first information is operational status information regarding the operational status of the air conditioning unit (100) installed in the object space. The control unit infers the presence or quantity of the target microorganism based on the application status information, which serves as the first information.

19. The microbial analysis system of claim 18, wherein, The first piece of information is information about the correspondence between the operating status of the air conditioning device and the types and quantities of the representative microorganisms. Based on the information regarding the correspondence between the operating status of the air conditioning unit and the types and quantities of the representative microorganisms, which serves as the first information, the control unit estimates whether the target microorganism exists or its quantity.

20. The microbial analysis system as described in claim 18 or 19, wherein, The operating status of the air conditioning unit includes at least one of the following: operating time, operating mode, air volume, set temperature, set humidity, temperature and humidity of the intake air, and non-cleaning period of the air conditioning unit.

21. The microbial analysis system according to any one of claims 3 to 18, wherein, The first information is the object space association information of the object space. The object space association information includes at least one of the following: climate, weather, geographical features, latitude, longitude, and altitude of the location where the object space exists; characteristics of the buildings in the object space; and the family composition of the residents in the object space. The control unit further uses the object spatial association information, which serves as the first information, to estimate whether the object microorganism exists or its quantity.

22. A microbiological analysis method for presuming the existence or quantity of target microorganisms in a target space, wherein, The existence or quantity of object microorganisms in the object space is inferred based on first information about the object space, wherein the first information is different from information regarding the existence and quantity of the object microorganisms themselves.

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